stereotype research paper

Gender stereotypes change outcomes: a systematic literature review

Journal of Humanities and Applied Social Sciences

ISSN : 2632-279X

Article publication date: 15 December 2021

Issue publication date: 19 October 2023

Even though researchers have discussed gender stereotype change, only a few studies have specifically projected outcomes or consequences. Hence, the main purpose of this study is to examine the impact of gender stereotype change concerning the different outcomes.

Design/methodology/approach

In achieving the purpose, the authors searched and reviewed current empirical knowledge on the outcomes of gender stereotype change in the Scopus and EBSCOhost databases from 1970 to 2020. The entire process was conducted through a systematic literature review methodology. The article selection criteria were executed using the PRISMA article selection flowchart steps, and 15 articles were included for the review.

The findings reveal that the outcomes from gender stereotype change research can be categorized mainly under the themes of “family and children,” “marriage” and “equality and women's employment.”

Research limitations/implications

The co-occurrence network visualization map reveals gaps in the existing literature. There may be more possible outcomes relating to the current realities, and more cross-cultural research is needed.

Practical implications

These outcomes provide some implications for policymakers.

Originality/value

Even though researchers have discussed gender stereotype change on its various outcomes or consequences, research is less. Hence, this study provides a synthesis of consequences and addresses the gaps in the area.

• Gender stereotypes change
• Systematic literature review

Priyashantha, K.G. , De Alwis, A.C. and Welmilla, I. (2023), "Gender stereotypes change outcomes: a systematic literature review", Journal of Humanities and Applied Social Sciences , Vol. 5 No. 5, pp. 450-466. https://doi.org/10.1108/JHASS-07-2021-0131

Emerald Publishing Limited

Copyright © 2021, K.G. Priyashantha, A. Chamaru De Alwis and Indumathi Welmilla

Published in Journal of Humanities and Applied Social Sciences . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

A society's beliefs about the appropriate roles for men and women are gender role attitudes, gender ideology ( Davis and Greenstein, 2009 ) or gender stereotypes ( Attanapola, 2004 ; Berridge et al. , 2009 ; Bosak et al. , 2018 ; Charlesworth and Banaji, 2021 ; De Silva and Priyashantha, 2014 ; Eagly et al. , 2020 ; Lopez-Zafra and Garcia-Retamero, 2021 ). Such beliefs are formed from the peoples' observations of the behavior of men and women in different social roles ( Priyashantha et al. , 2021b ). Particularly, when women or men demonstrate certain behavior more typical to different social roles more often than the opposite sex, such behaviors are believed to be the common traits relevant to men or women ( Eagly et al. , 2020 ; Eagly and Karau, 2002 ). Hence, men are believed to be assertive, independent, rational and decisive, while women are believed to be showing concern for others, warmth, helpfulness and nurturance ( Hoyt et al. , 2009 ). These attributes concerning men and women are referred to as agentic (masculine) and communal (feminine), respectively ( Abele, 2003 ). This agency and communion are then perceived as the fundamental motivators in men's and women's behaviors ( Bakan, 1966 ). However, researchers argue that these perceptions have changed in the contemporary world of work, which has been promoted by females' income-generating activities ( Eagly et al. , 2020 ). Social and economic developments took place, and United Nations initiatives (e.g. human rights, gender equality, nondiscrimination against women, women in development programs) ( Benería et al. , 2015 ) have backed this females' income generation in the mid-20th century in most countries ( Attanapola, 2004 ; Boehnke, 2011 ; Zosuls et al. , 2011 ). These female income generation activities have, in turn, resulted in changes in social role distribution where both men and women are now in multiple roles as parents, employees, employers, volunteers, friends, spouses, siblings, etc. ( Najeema, 2010 ; Perrigino et al. , 2021 ). Thus, peoples' various roles include women's work in men's roles and vice versa ( Blau and Kahn, 2006 ; Mergaert, 2012 ) while playing their traditional roles ( Eagly et al. , 2020 ). This trend has evolved the traditional gender role stereotypes into changing gender stereotypes during the last 50 years ( Blau and Kahn, 2006 ; Mergaert, 2012 ; Priyashantha et al. , 2021b ).

Even though it has been almost 50 years for research into changing gender stereotypes, there are scholarly arguments for the prevalence of traditional gender stereotypes ( Haines et al. , 2016 ; Rudman et al. , 2012 ; Rudman and Glick, 2001 ). Some theoretical bases and the prevalence of some cultures that value gender stereotyping further support these scholarly arguments. Meanwhile, there is an opinion that gender stereotyping violates human rights ( Tabassum and Nayak, 2021 ). Such an opinion is justified by the fact that gender stereotyping limits the capacity of women and men to develop their attributes or professional skills and make decisions about their lives and plans ( Office of the High Commissioner for Human Rights, 2014 ). Therefore, researchers have been highly interested in finding whether gender stereotypes have changed or not in societies ( Bosak et al. , 2018 ; Eagly et al. , 2020 ; Haines et al. , 2016 ; Lopez-Zafra and Garcia-Retamero, 2012 , 2021 ; Twenge, 1997a , b ; Ugwu, 2021 ). Instead, it is reported that there are more gender gaps in employment participation in some countries. If the gender stereotypes have changed, theoretically, there should be no such gender gap. Researching this question, the researchers have also been interested in how gender stereotypes change cross-culturally ( Boehnke, 2011 ; Constantin and Voicu, 2015 ; Diekman et al. , 2005 ; Diekman and Eagly, 2000 ; Lopez-Zafra and Garcia-Retamero, 2011 ). Accordingly, they have found that gender stereotypes have changed in Europe ( Berkery et al. , 2013 ; Boehnke, 2011 ; Garcia-Retamero et al. , 2011 ; Lopez-Zafra and Garcia-Retamero, 2012 ) and America ( Alfieri et al. , 1996 ; Beere et al. , 1984 ; Bem, 1974 ; Broverman et al. , 1970 ; Deaux and Lewis, 1984 ; Gill et al. , 1987 ; Lueptow et al. , 1995 ; Parelius, 1975 ; Spence and Hahn, 2016 ; Twenge, 1997a ; Twenge et al. , 2012 ; Zosuls et al. , 2011 ). In addition to that, researchers have found that the gender stereotype change has taken place in East Asia ( Boehnke, 2011 ), Africa ( Bosak et al. , 2018 ) and the Arab World ( Sikdar and Mitra, 2012 ) as well. Some global level studies also confirm that gender stereotype change has occurred in most countries with minor exceptions ( Brown, 1991 ; Charlesworth and Banaji, 2021 ; Constantin and Voicu, 2015 ; Williams and Best, 1990 ). We know that if something happened, this could have various outcomes related to the incident. Accordingly, as the gender stereotype change has also taken place, there could be multiple outcomes associated with it. However, to the best of our knowledge, there is minimal research on this subject matter ( Priyashantha et al. , 2021c ).

Therefore, with the expectation of finding the outcomes of gender stereotype change, we positioned the central question of the current study as, what is the impact of gender stereotype change? Thus, the present study systematically and quantitatively analyzes selected literature in the last 50 years to identify the outcomes of gender stereotypes and gaps in the prevailing knowledge.

Methodology

This article is positioned as Systematic Literature Review (SLR). The SLRs require a prior protocol to be developed to document the inclusion and exclusion of studies and analysis methods ( Pahlevan-Sharif et al. , 2019 ). We did a comprehensive literature search for this study, and a protocol was designed before the article search. There is a standard way of reporting the SLR known as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA- Liberati et al. , 2009 ), which is highly recommended in Medicine. However, as there is no such framework in social sciences, authors who intend to conduct the SLR tend to use the narrative and arbitrary guidelines ( Pahlevan-Sharif et al. , 2019 ; Petticrew and Roberts, 2006 ). Instead, in this study, for the article selection process to be objective and systematic, we followed the PRISMA article selection flow chart steps to select the articles.

The PRISMA article selection flow diagram has four steps: identification, screening, eligibility and included, and we followed them in the article selection. The identifications stage includes database, search terms and search criteria. The databases were Scopus and Ebscohost for searching the articles. The search terms were “gender stereotype change” and “outcomes.” The search criteria or algorithm was developed by combining the terms with AND operative, and each search term was given similar words combined with OR operative. Accordingly, we retrieved 56 articles from Scopus and 68 Articles from EBSCOhost databases. Subsequently, the retrieved list containing the title, abstract, keywords, authors' names and affiliations, journal name, cited numbers and year, etc., was exported to a Microsoft Excel sheet. The duplicates were then searched and removed.

The screening stage includes eliminating the articles when their titles and abstracts do not meet the inclusion criteria ( Meline, 2006 ). The inclusion criteria for the current study were the “empirical studies” published in “academic journals” in “English” on “gender stereotype change” during the “1970–2020” period. Thus, the reason for selecting 1970 as the entry point was that gender stereotype change started in 1970, and it was extended to 2020 to include more studies for the review. Each author of the current research independently went through each title and abstract and eliminated the studies that did not meet the inclusion criteria. Notably, if there was any disagreement about elimination was resolved through discussion and consensus. Hence, we excluded 73 articles that were based on “review,” “qualitative,” “books,” “book chapters,” “magazines,” “conference papers,” “non-English” and “non-relevance to the current study's scope.” Then, the remaining 50 articles' full-text versions were retrieved for assessing their eligibility, which is the next step of the PRISMA flow diagram.

Since the articles have already been screened out up to this stage, evaluating their methodological reporting for eligibility checking is much better ( Meline, 2006 ). It is justifiable as we had taken an inclusion criterion as “empirical studies.” Thus, the evaluation areas may be the population, methodology, methods, design, context, etc., and can find the reasons for excluding the articles as “ambiguous methods” and “required original information from the author,” etc. ( Meline, 2006 ). Accordingly, we independently evaluated each article on such grounds. We identified some studies based on qualitative reviews, perspectives, ambiguous methods and some sought original information about the methodology from the authors. They all were excluded through our discussion and consensus. In total, we identified 35 papers as irrelevant at this stage, and finally, we selected 15 articles for the review. They are shown in Table 1 , and the process we followed for article selection is shown in Figure 1 .

The Microsoft Excel sheet was then modified, and the data in it were fed into the VOSviewer Software to run the keyword co-occurrence and term co-occurrence network visualization maps. That was to identify the core themes in the selected studies scientifically. Notably, the keyword co-occurrence is to identify the main areas touched from the keywords of the studies as the keywords of a research article denote its primary content on a particular field of investigation. Moreover, the term co-occurrence analysis is to identify more about studies than the keywords co-occurrence as it searches key terms reflected in the titles and abstracts of each article.

Results and analysis

This section is mainly organized to present the results of the SLR and analyze them. It primarily consists of two sections: descriptive analysis and literature classification.

Descriptive analysis

The year-wise article distribution is shown in Figure 2 . Even the 50 years considered for the review, the empirical studies reported on outcomes of gender stereotype change since 1998. Figure 2 shows that at least one empirical study has been conducted for each year during the 1998–2020 period. Moreover, there is a high frequency of studies in 2005, 2017 and 2018 years. Table 2 shows the methodological reporting of the studies. It reveals that studies have been conducted based on large samples drawn on panel surveys. The information ensures the validity of the selected studies for the review, as we had an inclusion criterion for selecting papers as “empirical studies.” Concerning the context under which studies were conducted ( Figure 3 ), the USA takes the led by having seven empirical studies published (1970–2020). Canada is in the second position having two studies during the period. Australia, China, the Netherlands, Norway, Spain and United Kingdom have conducted one study each.

Literature classification

The classification of results is critical in finding out actual work done on the objective set for the research ( Jabeen et al. , 2020 ; Priyashantha et al. , 2021a ). Since the main research objective of the current study was to identify the outcomes of the gender stereotype change, this section mainly classifies the results relating to that. As the keyword co-occurrence network analysis is suitable for identifying the critical areas on a particular investigation, we used it for our study to answer the study's central question. Figure 4 shows the output of it.

The size of the node denotes the number of occurrences in a keyword co-occurrences visualization map. Hence, the higher the number of occurrences, the larger the node's size. Thus, our analysis of the keyword co-occurrences found that “gender,” “employment” and “longitudinal research” denoted in larger nodes in the map ( Figure 4 ). It reveals that they are the keywords that have frequently occurred in studies. We know that “gender” is highly associated with gender stereotypes. It may be a justifiable reason why it happens so often in studies. “Employment” opportunities are also justifiable since it has been proven that employment opportunities have been a significant cause for gender stereotypes changes ( Eagly et al. , 2020 ). Moreover, as almost all the studies in the sample have adopted the “longitudinal research” design, the keyword “longitudinal research” has also fallen to the frequently occurring category. It demonstrates the methods used by the selected articles and their suitability to the current study.

Additionally, Figure 4 shows four main clusters denoted in different colors containing different keywords in each cluster. More specifically, Table 3 shows the number of terms in each cluster, indicating that changing gender stereotype outcomes varied by different areas of investigations. Grouping the keywords into one cluster is regarded as the keywords' likelihood to reflect similar topics. Hence, clusters one and two (as stated in Table 3 ) have the highest number of keywords and suggest that the topics highlighted in those are the centralized fields in gender stereotype change and outcome research. Thus, the central areas highlighted are “attitudes,” “cohabitation,” “fertility,” “life course,” “living arrangements,” “marriage,” “couples,” “employment,” “family economics,” “gender roles,” “longitudinal research” and “marital quality.”

Moreover, the term co-occurrence network visualization map created by the VOSviewer software ( Figure 5 ) is treated as more detailed than the keyword co-occurrence analysis. It provides an analysis that goes beyond the keywords as it further investigates the areas focused on in the title and abstracts of the studies. Hence, creating this type of map further identified the areas frequently investigated on gender stereotypes change outcomes. Accordingly, Figure 5 categorized the terms into three clusters in Blue, Red and Green. In the Blue cluster, there are two terms as “family” and “child.” A common theme can be formed for them as family and child-related outcomes. As we did a detailed search for the outcomes in each article, we could summarize them in Table 4 . Hence, we could extract different family and children-related outcomes from Table 4 . They are; “Family Role Overload and Stress” ( Duxbury et al. , 2018 ), “Subsequent School Enrollment” ( Cunningham et al. , 2005 ), “Fewer Children” ( Barber and Axinn, 1998 ), “Delay in Marital Parenthood” ( Cunningham et al. , 2005 ) and “Children's Convergence of Egalitarian Attitudes” ( Dawson et al. , 2016 ).

Concerning the family and children-related outcomes, Duxbury et al. (2018) have found that the “family role overload” of both husbands and wives was consequent in changing gender stereotype contexts. The sense of family role overload then becomes a strong predictor of couples' “perceived stress” ( Duxbury et al. , 2018 ). The perceived stress can undermine the health and well-being of people. The literature confirms that “psychological strains” and “disorders” ( Hébert et al. , 2017 ), “adverse impacts on the immune system” ( Barry et al. , 2020 ; Cohen et al. , 1999 ), “low quality of life,” “insomnia,” “burnout” ( Ribeiro et al. , 2018 ) and “family distress” ( Aryee et al. , 1999 ) resultant from the stress. When the stress becomes to distress level, there is a high possibility of causing chronic diseases and mortality ( Barry et al. , 2020 ). Therefore, these findings provide more implications for the policymakers to emphasize reducing those negative outcomes.

Apart from this, young adults' biases toward changing gender role attitudes can cause “subsequent school enrolments” ( Ciabattari, 2001 ; Cunningham et al. , 2005 ). It is severe, particularly among women, as they need to acquire knowledge to upgrade their employment status ( Cunningham et al. , 2005 ) and be independent ( Goldscheider and Goldscheider, 1993 ). However, later school enrollment may hinder performing family roles of adults as intensive time is devoted to education ( Marini, 1978 ). Moreover, women with changing attitudes toward gender roles are “less likely to have children” ( Barber and Axinn, 1998 ) and “delay in marital parenthood” ( Cunningham et al. , 2005 ). As a result, the future society could go into a severe crisis regarding population growth ( Barber and Axinn, 1998 ). It could be challenging to find people for growth prospects in economies. Therefore, the policymakers need to consider this seriously and try to overcome that. In the meantime, scholars need to focus on further research on this outcome to confirm this viewpoint further.

The last outcome of the family and children-related category is the “children's convergence of egalitarian attitudes” ( Dawson et al. , 2016 ). It indicates that gender stereotype changes could evolve over the generations and possibly consequent the different outcomes of gender stereotype change. It implies that more research on this area is required to find more associated outcomes.

The cluster in Red ( Figure 5 ) has categorized the terms as; “Role Attitude,” “Attitudes,” “Cohabitation,” “Marriage” and “Consequences.” Out of them, the “role attitudes,” “attitudes” and “consequences” are the general search terms related to the concept of gender stereotype change outcomes, and hence, we ignored them for review. However, the remaining two terms, “marriage” and “cohabitation,” were considered for the review. Since these terms are related to marriage, we themed them as “marriage-related.” Hence, marriage-related outcomes we found were “Increased Cohabitation, Low Marriage Rate” ( Barber and Axinn, 1998 ), “Delay in Marriage” ( Cunningham et al. , 2005 ), “Low Satisfaction,” “Low Relationship Quality,” “Low Stability in Marital Relationships” ( Blom and Hewitt, 2020 ) and “Attitude Convergence in Marriage” ( Kalmijn, 2005 ).

The “increased cohabitation,” “low marriage rate” ( Barber and Axinn, 1998 ) and “delay in marriage” ( Cunningham et al. , 2005 ) can subsequently impact the population growth negatively ( Barber and Axinn, 1998 ). If such outcomes exist over time, it could be a barrier to the progression of societies. However, another finding reveals that gender stereotype change increases childbirth to single parents in recent decades ( Cunningham et al. , 2005 ). Therefore, it is difficult to directly conclude that such outcomes negatively affect population growth or societal progression. More research is needed to find the associated outcomes of these consequences so that reasonable judgments can be made whether such outcomes generate more negative or positive effects on the population, society or any other.

Moreover, in marital relationships, Australian-related research has found that “low satisfaction,” “low relationship quality” and “low stability” ( Blom and Hewitt, 2020 ) were consequent from the gender stereotype changes. All of which resemble negative outcomes by their surface nature. However, another finding reveals that “attitude convergence in marriage” ( Kalmijn, 2005 ) occurred due to gender stereotype changes. It is contrary to the previous finding, which is a positive outcome by its surface nature.

Most importantly, for these types of outcomes, positivity or negativity is dependent on cultural values. The negative outcomes as “low satisfaction,” “low relationship quality” and “low stability” may be very accurate for the cultures which value male breadwinner family structures ( Blom and Hewitt, 2020 ). However, more opposing consequences, like “attitude convergence in marriage” ( Kalmijn, 2005 ), can be found in cultures with more egalitarian values like Nordic countries ( Vitali and Arpino, 2016 ). Hence, in total, the positivity or negativity of outcomes is a matter of societal and cultural values. Therefore, generalizing interpretations about the positivity or negativity of each outcome is suitable with more cross-cultural research. Similarly, further research is needed regarding the associated outcomes of each of these outcomes.

Finally, the Green cluster has the terms as; “Outcomes,” “Gender Differences,” “Gender Egalitarianism,” “Work” and “Women.” As in other clusters, we had a common search term, “outcome,” in this cluster, and we ignored it. Except that, the terms “gender difference” and “gender egalitarianism” seem to represent a common theme of “equality.” The remaining terms “work” and “women” are merged, and a theme can be given as “women's employment.” Thus, this cluster is then characterized by the theme of “equality and women employments.” Specifically, under this cluster, we found the outcomes of “Reduction of Gender Role Stereotyping” ( Dawson et al. , 2016 ), “Egalitarian Essentialism” ( Cotter et al. , 2011 ), “Non-Difference in Men or Women for Work-Life” ( Lyness and Judiesch, 2014 ) and “Gender Differences in Personality Cross-Culturally” ( Schmitt et al. , 2017 ), and they can be related to the equality. Similarly, the “Women's Full-Time Employment,” “Women's Independent Living” ( Cunningham et al. , 2005 ), “More Working Hours” and “More Income for Women” ( Corrigall and Konrad, 2007 ) and “Increased Entrepreneurial Intention of Women” ( Perez-Quintana et al. , 2017 ) were found, and they can be categorized under the theme of women's employment. Moreover, the outcomes of the “Reduction of the Women's Disadvantage in Entering Male-Dominated Occupations” ( He and Zhou, 2018 ) and “Economic Rationality of Females” ( Onozaka and Hafzi, 2019 ) are also categorized to the theme of “women's employment.”

Thus, the “equality” related outcomes in the “equality and women's employment,” the “reduction of traditional gender role stereotyping” ( Dawson et al. , 2016 ), “egalitarian essentialism” ( Cotter et al. , 2011 ) and “non-difference in men or women for work-life” ( Lyness and Judiesch, 2014 ) may change in different cultural contexts. As we have various cultural contexts that value either traditional gender norms or gender stereotype change, more cross-cultural research is needed to interpret such outcomes. Moreover, one cross-cultural study found that a “gender difference in personality” is consequenced even though people's gender stereotype attitudes have already changed ( Schmitt et al. , 2017 ). Therefore, this finding confirms the overall behavioral diversity of people, including diversity in gender role behaviors, although the equality of gender roles is emphasized.

Concerning women's employment-related outcomes, such as increases in “women's full-time employment opportunities” ( Cunningham et al. , 2005 ), “reduction of women's disadvantage in entering male-dominated occupations” ( He and Zhou, 2018 ), “more working hours and more income for women” ( Corrigall and Konrad, 2007 ) and “their increased entrepreneurial intention” ( Perez-Quintana et al. , 2017 ), women's “economic rationality” ( Onozaka and Hafzi, 2019 ) reveals the women's improved economic status. Moreover, the findings like increased “women's independent living” ( Cunningham et al. , 2005 ) represent their independent decision-making. The positive side of these is that they reduce the gender gap in employment participation and the ultimate contribution to economic growth. However, since we have different cultures worldwide, more cross-cultural research is needed to generalize this. As discussed under “family and children” related outcomes, the negative side of women's employment-related outcomes is the missing family responsibilities or adverse health effects and low reproductivity. Therefore, this provides an implication for policymakers to avoid those harmful effects. In the meantime, as the socialization forces are diverse over time ( Brown and Stone, 2016 ), researchers can further test whether these types of outcomes exist over time.

In the network visualization map in Figure 5 , the circles' size denotes the number of occurrences. It suggests that the higher the number of occurrences, the larger the circle's size. Accordingly, the term “women” is then considered to be the frequently used term. It implies that the women-related outcomes should have been investigated repeatedly. However, even the term “women” has been found to be co-occurred many times in this study, our detailed analysis of each article found that the different women-related outcomes have been investigated only once. Instead, the other outcomes related to terms represented by the nodes in Figure 5 have not been co-occurred or tested frequently in the studies. Hence, overall, more research is needed to be a well-established knowledge on each outcome of stereotype change found in this study.

Gender stereotype change has been given scholarly attention since the 1970s. Traditional gender stereotypes have evolved into gender stereotype change or egalitarian gender stereotypes with females' participation in employment ( Brandth et al. , 2017 ; Mergaert et al. , 2013 ). This gender stereotype change has created various outcomes in various areas. This SLR studied the outcomes of gender stereotype change in the literature during the 1970–2020 period. The literature search was conducted using the Scopus and EBSCOhost databases. Empirical studies were mainly focused on selecting the articles. Initially, we extracted 124 articles for screening. After assessing their eligibility, we finally selected 15 articles for the review. They were subjected to the keyword and term co-occurrence analysis for finding the themes of gender stereotypes change outcomes.

The findings reveal that outcomes of gender stereotypes change are under the main themes of “family and children,” “marriage” and “equality and women's employment.” There are very few studies found relating to the “family and children” related outcomes. They are “Family Role Overload and Stress” ( Duxbury et al. , 2018 ), “Fewer Children” ( Barber and Axinn, 1998 ), “Later School Enrollment” ( Cunningham et al. , 2005 ) and “Children's Convergence of Egalitarian Attitudes” ( Dawson et al. , 2016 ). Of these results, it was found that all other results, except for the convergence of children's egalitarian attitudes ( Dawson et al. , 2016 ), had some adverse effects, such as neglect of family responsibilities and negative effects on health and female fertility. They provide implications to policymakers to ovoid those harmful effects. Moreover, more research is needed to test whether these outcomes exist over time since the socialization forces are diverse ( Brown and Stone, 2016 ).

Compared to the “family and children” related outcomes, more outcomes have found “marriage” associated outcomes. They are “Increase Cohabitation,” “Low Marriage Rate” ( Barber and Axinn, 1998 ), “Delay in Marriage” ( Cunningham et al. , 2005 ), “Attitude Convergence in Marriage” ( Kalmijn, 2005 ), “Low Satisfaction,” “Lower Relationship Quality” and “Low Stability in Marital Relationships” ( Blom and Hewitt, 2020 ). “The Increase in Cohabitation,” “Low Marriage Rate” ( Barber and Axinn, 1998 ) and “Delay in Marriage” ( Cunningham et al. , 2005 ) can further negatively impact the population growth ( Barber and Axinn, 1998 ). However, more research is needed regarding these outcomes and their associated outcomes to generalize whether they generate more positive or negative consequences. Moreover, concerning all the marriage-related outcomes, their positivity or negativity cannot be determined from their surface interpretation. More research is needed to be done on the associated outcomes of each of these outcomes. Moreover, as the marriage-related outcomes are subjected to cultural perspectives on gender roles, we cannot determine the positivity or negativity of such outcomes without doing more cross-cultural studies. Therefore, more cross-cultural research is needed.

Compared to the family and children and marriage-related outcomes, more outcomes were found relating to equality and women's employment-related category. For the analysis purposes, we further categorized them into two sub-themes as equality and women's employment-related. The “equality”-related outcomes found were; “Reduction of Traditional Gender Role Stereotyping” ( Dawson et al. , 2016 ), “Egalitarian Essentialism” ( Cotter et al. , 2011 ), “Non-Difference in Men or Women for Work-Life” ( Lyness and Judiesch, 2014 ), “Gender Difference in Personality” ( Schmitt et al. , 2017 ). We believe that these outcomes may change in different cultural contexts. Hence, more cross-cultural research is needed to make generalizations. Similarly, the women's employment-related outcomes found were: increases in “Women's Full-Time Employment Opportunities” ( Cunningham et al. , 2005 ), “Reduction of Women's Disadvantage in Entering Male-Dominated Occupations” ( He and Zhou, 2018 ), “More Working Hours and More Income for Women” ( Corrigall and Konrad, 2007 ), “Women's Increased Entrepreneurial Intention” ( Perez-Quintana et al. , 2017 ), “Women's Independent Living” ( Cunningham et al. , 2005 ) and their “Economic Rationality” ( Onozaka and Hafzi, 2019 ). These outcomes reveal the improved economic status and independent living of females. These can help reduce the employment gender gap that ultimately contributes to economic growth. For this also, more cross-cultural research is needed to make more generalizations. It is proven in this study that family responsibilities are missed and have adverse effects on health and reproductivity when females are involved in employment opportunities. Therefore, the outcomes provide an implication for the policymakers to ovoid those harmful effects. Moreover, more research is needed to test whether these outcomes exist over time since the socialization forces are diverse ( Brown and Stone, 2016 ).

Practicality and research implications

There are implications for future researchers from the findings of the current research. Although the 50 years considered for reviewing the literature on gender stereotype outcomes, we were able to find very few outcomes from only 15 studies conducted on an empirical basis. Therefore, more research is needed on this area. More specifically, gender stereotyping is coupled with cultural values on gender norms. Mainly, we have cultures on gender role stereotyping and gender role egalitarianism. Therefore, future researches need to focus more research on a cross-cultural basis. Moreover, since the socialization forces are diverse, complex and continuously evolving, more research is essential to have a well-established knowledge of gender stereotype change outcomes.

Additionally, the outcome of “Family Role Overload and Stress” ( Duxbury et al. , 2018 ) has a high possibility to create more health risks to the employees whose gender role attitude changed. Moreover, “Fewer Children” ( Barber and Axinn, 1998 ), “Later School Enrollment” ( Cunningham et al. , 2005 ), “Increase in Cohabitation,” “Low Marriage Rate” ( Barber and Axinn, 1998 ) and “Delay in Marriage” ( Cunningham et al. , 2005 ), and all the outcomes of women employment-related category can negatively impact on population growth. Therefore, they provide implications to policymakers to ovoid those harmful effects.

PRISMA article selection flow diagram

Year-wise research article distribution

Country-wise article publication

Keywords co-occurrence network visualization map

Term co-occurrence network visualization map

Included articles for the review

Source(s): Authors created (2021)

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Barry , V. , Stout , M.E. , Lynch , M.E. , Mattis , S. , Tran , D.Q. , Antun , A. , Ribeiro , M.J. , Stein , S.F. and Kempton , C.L. ( 2020 ), “ The effect of psychological distress on health outcomes: a systematic review and meta-analysis of prospective studies ”, Journal of Health Psychology , Vol. 25 No. 2 , pp. 227 - 239 , doi: 10.1177/1359105319842931 .

Beere , C.A. , King , D.W. , Beere , D.B. and King , L.A. ( 1984 ), “ The Sex-Role Egalitarianism Scale: a measure of attitudes toward equality between the sexes ”, Sex Roles , Vol. 10 Nos 7-8 , pp. 563 - 576 .

Bem , S.L. ( 1974 ), “ The measurement of psychological androgyny ”, Journal of Consulting and Clinical Psychology , Vol. 42 No. 2 , pp. 155 - 162 , doi: 10.1037/h0036215 .

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Acknowledgements

Funding : No funding was available for this research

Authors Contributions : All authors contributed to the study conception, design, material preparation, data collection and analysis. All versions of drafts of the manuscript were written by Author 1, and other authors commented and revised. All authors read and approved the final manuscript.

Availability: Data collected during the current study are not publicly available. However, they can be available from the corresponding author upon reasonable request.

Conflicts of Interest : On behalf of all authors, the corresponding author states that there is no conflict of interest.

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• Published: 01 September 2017

Implicit stereotypes and the predictive brain: cognition and culture in “biased” person perception

• Perry Hinton 1  

Palgrave Communications volume  3 , Article number:  17086 ( 2017 ) Cite this article

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Over the last 30 years there has been growing research into the concept of implicit stereotypes. Particularly using the Implicit Associations Test, it has been demonstrated that experimental participants show a response bias in support of a stereotypical association, such as “young” and “good” (and “old” and “bad”) indicating evidence of an implicit age stereotype. This has been found even for people who consciously reject the use of such stereotypes, and seek to be fair in their judgement of other people. This finding has been interpreted as a “cognitive bias”, implying an implicit prejudice within the individual. This article challenges that view: it is argued that implicit stereotypical associations (like any other implicit associations) have developed through the ordinary working of “the predictive brain”. The predictive brain is assumed to operate through Bayesian principles, developing associations through experience of their prevalence in the social world of the perceiver. If the predictive brain were to sample randomly or comprehensively then stereotypical associations would not be picked up if they did not represent the state of the world. However, people are born into culture, and communicate within social networks. Thus, the implicit stereotypical associations picked up by an individual do not reflect a cognitive bias but the associations prevalent within their culture—evidence of “culture in mind”. Therefore to understand implicit stereotypes, research should examine more closely the way associations are communicated within social networks rather than focusing exclusively on an implied cognitive bias of the individual.

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Traditionally a stereotype has been defined as overgeneralized attributes associated with the members of a social group (such as the reserved English or the geeky engineer), with the implication that it applies to all group members ( Hinton, 2000 ). A large body of research, particularly in the United States of America (USA), has focused on the (negative) stereotypes of women and African Americans, which are linked to prejudice and discrimination in society ( Nelson, 2009 , Steele, 2010 ). Psychological researchers have sought to identify why certain people employed stereotypes and, in much of the twentieth century, they were viewed as due to a mental fallacy or misconception of a social group, an individual’s “biased” cognition, resulting from proposed factors such as “simplicity” of thought ( Koenig and King, 1964 ) and arising from upbringing and social motivation (particularly “authoritarianism”, Adorno et al., 1950 ). A considerable amount of effort has been made subsequently to persuade people to avoid stereotype use, by highlighting its inaccuracy and unfairness (for example, Brown, 1965 ). However, since the 1960s, cognitive researchers, such as Tajfel (1969) , have argued that stereotyping is a general feature of human social categorization. Despite this, it has been argued that individuals can consciously seek to avoid using negative stereotypes and maintain a non-prejudiced view of others ( Devine, 1989 ; Schneider, 2004 ). Indeed, Fiske and Taylor (2013) claim that now only ten percent of the population (in Western democracies) employ overt stereotypes. Unfortunately, recent work, specifically using techniques such as the Implicit Associations Test ( Greenwald et al., 1998 ), has shown that stereotypical associations can implicitly influence social judgement, even for people who consciously seek to avoid their use ( Lai et al., 2016 ). These implicit stereotypes have provoked questions of both the control of, and an individual’s responsibility for, the implicit effects of stereotypes that they consciously reject ( Krieger and Fiske, 2006 ). This article explores the nature of implicit stereotypes by examining what is meant by “bias” in the psychological literature on stereotyping, and proposes an explanation of how culture influences implicit cognition through the concept of the “predictive brain” ( Clark, 2013 ). The present work argues that, rather than viewing implicit stereotypes as a problem of the cognitive bias of the individual (for example, Fiske and Taylor, 2013 ), they should be viewed as “culture in mind” influencing the cognition of cultural group members. It is also proposed that combining the research on implicit cognition with an understanding of the complex dynamics of culture and communication, will lead to greater insight into the nature of implicit stereotypes.

Implicit stereotypes

The view of a stereotype as a fixed set of attributes associated with a social group comes from the seminal experimental psychology research by Katz and Braly (1933) . One hundred students of Princeton University were asked to select the attributes that they associated with ten specific nationalities, ethnic and religious groups from a list of 84 characteristics. The researchers then compiled the attributes most commonly associated with each group. Katz and Braly (1933 : 289) referred to these associations as “a group fallacy attitude”, implying a mistaken belief (or attitude) on behalf of the participants. The study was repeated in Princeton by Gilbert (1951) and Karlins et al. (1969) , and similar attributes tended to emerge as the most frequent for the groups. The endurance of these associations, such as the English as tradition-loving and conservative, over 35 years has often been narrowly interpreted as evidence for the fixed nature of stereotypes. Yet, a closer look at the data shows counter-evidence. Rarely was an attribute selected by more than half the participants: for the English only “sportsmanlike” in 1933, and “conservative” in 1969 reached this figure. Also both the percentages and the chosen attributes changed over time. By 1969, “sportsmanlike” for the English had dropped to 22%. A number of attributes in the initial top five for some of the groups dropped to below 10% by 1969. Also the stereotypes generally tended to become more positive over time. However, what the studies did establish was a methodological approach to stereotypes as the experimental investigation of “character” attributes associated with social groups in the mind of an individual.

The notion of implicit stereotypes is built on two key theoretical concepts: associative networks in semantic (knowledge) memory and automatic activation. Concepts in semantic memory are assumed to be linked together in terms of an associative network, with associated concepts having stronger links, or are closer together, than unrelated concepts ( Collins and Loftus, 1975 ). Thus “doctor” has a stronger link to “nurse” (or viewed as closer in the network) than to unrelated concepts, such as “ship” or “tree”. Related concepts cluster together, such as hospital, doctor, nurse, patient, ward, orderly, operating theatre, and so forth, in a local network ( Payne and Cameron, 2013 ) that is sometimes referred to as a schema ( Ghosh and Gilboa, 2014 ; see Hinton, 2016 ). Activation of one concept (such as reading the word “doctor”) spreads to associated concepts in the network (such as “nurse”) making them more easily accessible during the activation period. Evidence for the associative network model comes from response times in a number of research paradigms, such as word recognition, lexical decision and priming tasks: for example, Neely (1977) showed that the word “nurse” was recognized quicker in a reaction time task following the word “doctor” than when preceded by a neutral prime (such as a row of X’s) or an unrelated prime word (such as “table”). Considerable amount of research has been undertaken on the nature of semantic association, which reflects subjective experience as well as linguistic similarity, although people appear to organize their semantic knowledge in similar ways to others. Weakly associated concepts may be activated by spreading activation based on thematic association, and the complexity of the structure of associations develops over time and experience ( De Deyne et al., 2016 ).

The spreading activation of one concept to another was viewed as occurring unconsciously or automatically. In the mid-1970s a distinction was made between two forms of mental processing: conscious (or controlled) processing and automatic processing ( Shiffrin and Schneider, 1977 ). Conscious processing involves attentional resources and can be employed flexibly and deal with novelty. However, it requires motivation and takes time to operate, which can lead to relatively slow serial processing of information. Automatic processing operates outside of attention, occurs rapidly and involves parallel processing. However, it tends to be inflexible and (to a high degree) uncontrollable. Kahneman (2011) refers to these as System 2 and System 1, respectively. Shiffrin and Schneider (1977) found that detecting a letter among numbers could be undertaken rapidly and effortlessly, implying the automatic detection of the categorical differences of letters and numbers. Detecting items from a group of target letters among a second group of background letters took time and concentration, requiring (conscious) attentional processing. However, novel associations (of certain letters as targets and other letters as background) could be learnt by extensive practice as long as the associations were consistent (targets were never used as background letters). After many thousands of trials, detection times reduced significantly, with the participants reporting the targets “popping out” from the background letters, implying that practice had led to automatic activation of the target letters (based on the new target-background letter categories). Thus, consistency of experience (practice) can lead to new automatically activated learnt associations. However, when Shiffrin and Schneider (1977) switched the targets and background letters after thousands of consistent trials, performance dropped to well below the initial levels—detection times were extremely slow requiring conscious attention as participants struggled with the automatic activation of the old-but-now-incorrect targets. Slowly, and with additional practice of thousands of trials, performance gradually improved with the new configuration of target and background letters. Thus, highly practiced semantic associations—consistent in a person’s experience—can become automatically activated on category detection—but once learnt are extremely difficult to unlearn.

Employing these theoretical ideas, a stereotypical association (such as “Black” and “aggressiveness”) might be stored in semantic memory and automatically activated, producing an implicit stereotype effect. This was demonstrated by Devine (1989) . White participants were asked to generate the features of the Black stereotype, and also to complete a prejudice questionnaire. Devine found that both the low- and high-prejudiced individuals knew the characteristics of the Black stereotype. In the next phase of the study the participants rated the hostility of a person only referred to as Donald, described in a 12-sentence paragraph as performing ambiguously hostile behaviours such as demanding his money back on something he had just bought in a store. Before the description, words related to the Black stereotype were rapidly displayed on the screen but too briefly to be consciously recognized. This automatic activation of the stereotype was shown to affect the judgement of Donald’s hostility by both the low- and high-prejudiced participants. Finally, the participants were asked to anonymously list their own views of Black people. Low-prejudice individuals gave more positive statements and more beliefs (such as “all people are equal”) than traits, whereas high-prejudice participants listed more negative statements and more traits (such as “aggressive”).

Devine explained these results by arguing that, during socialization, members of a culture learn the beliefs existing in that culture concerning different social groups. Owing to their frequency of occurrence, stereotypical associations about people from the stereotyped group become firmly-established in memory. Owing to their widespread existence in society, more-or-less everyone in the culture, even the non-prejudiced individual, has the implicit stereotypical associations available in semantic memory. Consequently, the stereotype is automatically activated in the presence of a member of the stereotyped group, and has the potential to influence the perceiver’s thought and behaviour. However, people whose personal beliefs reject prejudice and discrimination may seek to consciously inhibit the effect of the stereotype in their thoughts and behaviour. Unfortunately, as described above, conscious processing requires the allocation of attentional resources and so the influence of an automatically activated stereotype may only be inhibited if the person is both aware of its potential bias on activation and is motivated to allocate the time and effort to suppress it and replace it in their decision-making with an intentional non-stereotypical judgement. Devine (1989 : 15) viewed the process of asserting conscious control as “the breaking of a bad habit”.

It has been argued that conscious attentional resources are only employed when necessary, with the perceiver acting as a “cognitive miser” ( Fiske and Taylor, 1991 ): as a result, Macrae et al. (1994) argued that stereotypes could be viewed as efficient processing “tools”, avoiding the need to “expend” valuable conscious processing resources. Yet, Devine and Monteith (1999) argued that they can be consciously suppressed when a non-prejudiced perception is sought. Also an implicit stereotype is only automatically activated when the group member is perceived in terms of a particular social meaning ( Macrae et al., 1997 ) so automatic activation is not guaranteed on presentation of a group member ( Devine and Sharp, 2009 ). Devine and Sharp (2009) argued that conscious and automatic activation are not mutually exclusive but in social perception there is an interplay between the two processes. Social context can also influence automatic activation so that, in the context of “prisoners” there is a Black stereotype bias (compared with White) but not in the context of “lawyers” ( Wittenbrink et al., 2001 ). Indeed, Devine and Sharp (2009) argued that a range of situational factors and individual differences can affect automatic stereotype activation, and conscious control can suppress their effects on social perception. However, Bargh (1999) was less optimistic than Devine in the ability of individual conscious control to suppress automatically activated stereotypes, and proposed that the only way to stop implicit stereotype influence was “through the eradication of the cultural stereotype itself” ( Bargh (1999 : 378). Rather than the cognitive miser model of cognitive processing, Bargh proposed the “cognitive monster”, arguing that we do not have the degree of conscious control, which Devine proposes, to mitigate the influence of implicit stereotypes ( Bargh and Williams, 2006 ; Bargh, 2011 ).

Greenwald and Banaji (1995) called for the greater use of indirect measures of implicit cognition to demonstrate the effect of activation outside of the conscious control of the perceiver. They were particularly concerned about implicit stereotypes, arguing that the “automatic operation of stereotypes provides the basis for implicit stereotyping”, citing research such as that of Gaertner and McLaughlin (1983) . In this latter study, despite participants scoring low on a direct self-report measure of prejudice, they still reliably reacted quicker to an association between “White” and positive attributes, such as “smart”, compared with the pairing of “Black” with the same positive attributes. Thus, they concluded that the indirect reaction time measure was identifying an implicit stereotype effect. Consequently, Greenwald et al. (1998) developed the Implicit Association Test (or IAT). This word-association reaction time test presents pairs of words in a sequence of trials over five stages, with each stage examining the reaction time to different combinations of word pairings. From the results at the different stages, the reaction time to various word associations can be examined. For example, the poles of the age concept, “young” and “old”, can be sequentially paired with “good” and “bad” to see if the reaction times to the young-good and/or the old-bad pairing are reliably faster than alternative pairings indicating evidence of the implicit stereotype of age. As a technique the IAT can be applied to any word pair combination and as a result can be used to examine a range of implicit stereotypes, such as “White” and “Black” for ethnic stereotyping, or “men” and “women” for gender stereotyping, paired with any words associated with stereotypical attributes, such as aggression or dependence. The results have been quite dramatic. The subsequent use of the IAT has consistently demonstrated implicit stereotyping for a range of different social categories, particularly gender and ethnicity ( Greenwald et al., 2015 ). Implicit stereotyping is now viewed as one aspect of implicit social cognition that is involved in a range of social judgements ( Payne and Gawronski, 2010 ).

Criticisms of the findings of the IAT have questioned whether it is actually identifying a specific unconscious prejudice, unrelated to conscious judgement ( Oswald et al., 2013 ) or, as Devine (1989) suggested, simply knowledge of a cultural association that may be controllable and inhibited in decision-making ( Payne and Gawronski, 2010 ). In support of the IAT, Greenwald et al.’s (2009) meta-analysis of 184 IAT studies showed that there was predictive validity of the implicit associations to behavioural outcomes across a range of subject-areas, and Greenwald et al. (2015) claim this can have significant societal effects. As a consequence, if implicit stereotyping indicates a potentially-uncontrollable cognitive bias, the question then arises as to how to deal with the outcomes of it in decision-making, particularly for a person genuinely striving for a non-prejudiced judgement. Overt prejudice has been tackled by a range of socio-political measures from anti-discrimination laws to employment interviewer training, but interventions essentially seek to persuade or compel individuals to consciously act in a non-prejudiced way. Lai et al. (2016) examined a range of intervention techniques to reduce implicit racial prejudice, such as exposure to counter-stereotypical exemplars or priming multiculturalism, but the conclusions were somewhat pessimistic. Different interventions had different effects on the implicit stereotype (as measured by the IAT). For example, a vivid counter-stereotypical example (which the participants read)—imagining walking alone at night and being violently assaulted by a White man and rescued by a Black man—was quite effective. However, of the nine interventions examined by Lai et al. (2016) , all were effective to some extent but subsequent testing showed that the beneficial effect disappeared within a day or so. The authors concluded that, while implicit associations were malleable in the short term, these (brief) interventions had no long term effect. This could indicate that implicit stereotypes are firmly established and may only be responsive to intensive and long-term interventions ( Devine et al., 2012 ). Lai et al. (2016) also suggest that children may be more susceptible to implicit stereotype change than adults.

The problem is that if people are not consciously able to change their implicit “bias”, to what extent are they responsible for actions based on these implicit stereotypes? Law Professor Krieger (1995) argued that lawmakers and lawyers should take account of psychological explanations of implicit bias in their judgements. For example, in a study by Cameron et al. (2010) participants rated the responsibility of a White employer who sometimes discriminated against African Americans, despite a conscious desire to be fair. When this discrimination was presented as resulting from an unconscious bias, that the employer was unaware of, then the personal responsibility for the discrimination was viewed as lower by the participants. However, being told that the implicit bias was an automatic “gut feeling” that the employer was aware of, but found difficult to control, did not produce the same reduction in moral responsibility. This also has potential legal significance ( Krieger and Fiske, 2006 ), as the law has traditionally assumed that a discriminatory act is the responsibility of the individual undertaking that act, with the assumption of an underlying discriminatory motivation (an intention). The effect of an implicit stereotype bias may be a discriminatory action that the individual neither intended nor was conscious of.

Implicit stereotype bias provides a challenge to the individual as the sole source and cause of their thoughts and actions. In a huge study of over two hundred thousand participants, all citizens of the USA, Axt et al. (2014) employed the MC-IAT, a variant of the IAT, to examine implicit bias in the judgement of ethnic, religious and age groups. Whilst participants showed in-group favouritism, consistent hierarchies of the social groups emerged in their response times. For ethnicity, in terms of positivity of evaluation, Whites were highest, followed by Asians, Blacks and Hispanics, with the same order obtained from participants from each of the ethnic groups. For religion, a consistent order of Christianity, Judaism, Hinduism and Islam was produced. For the age study, positive evaluations were associated with youth, with a consistent order of children, young adults, middle-aged adults, and old adults, across participants of all ages, from their teens to their sixties. Axt et al. argued that the consistent implicit evaluations reflect cultural hierarchies of social power (and social structures) “pervasively embedded in social minds” ( Axt et al., 2014 : 1812). They also suggest that these implicit biases might “not be endorsed and may even be contrary to conscious beliefs and values” ( Axt et al., 2014 : 1812). The focus on cognitive bias, with its implication of an individual’s biased judgement has tended to ignore the importance of culture in cognition. It is this issue that is now considered here.

Implicit cognitive “bias”

Implicit stereotypes are referred to in the literature, and taught to psychology students, as a cognitive bias ( Fiske and Taylor, 2013 ). When, in the past, only a specific group of people were assumed to stereotype (such as authoritarians or the cognitively simple) then they could be viewed as biased in terms of the liberal views of the rest of the population. However, as Fiske and Taylor (2013) claim that now only 10% of the population use overt stereotypes in liberal Western democracies, the major issue is the implicit stereotypes that could affect us all. Indeed, some psychologists (who the reader rightly infers to be supporters of egalitarian values) are willing to reveal examples of their inadvertent use of implicit stereotypes in their own lives—to their chagrin (for example, Stainton Rogers, 2003 : 301). Now the assumption is that implicit stereotypes can affect everyone. This makes the use of the term cognitive “bias” problematic when it is universally applied, particularly as it contains the implication of an unconscious cognitive “failing” of the individual (a “cognitive monster” within them), especially given the unsuccessful attempts to correct it, noted above. There also arises the question of how an unbiased judgement can be defined. This idea of an implicit stereotype as a cognitive bias is challenged here.

A wheel is said to be biased if it wobbles on an axle (when others do not). Adjusting it or correcting the imperfections makes it “true” and it is able to run smoothly and straight on the axle. Indeed, the word bias derives from the word “oblique” (for a diagonal thread in weaving) or deviating from the perpendicular. In human social terms, the idiomatic “straight (or strait) and narrow” view might be based on “self-evident truths” (to quote the Declaration of Independence of the USA) rooted in religious or philosophical beliefs, which essentially provide a position from which all other views are biased. Yet, unlike “true” wheels and “fair” coins, there is not an absolute moral standard that is universally accepted, with a long philosophical debate ranging from Plato and Kant to Hume about the issue. Different cultures—as nation states—have different belief systems that are conventionalised into different national legal systems, with dynamically changing laws. Despite the United States Constitution, there are many differences between the views of the Republican and Democratic Parties and their conservative and liberal supporters, and there is a constant political interplay between them about what, in terms of another idiom, is “good and proper” thinking. Recently, the psychologist Haidt (2012) has examined the difference between liberals and conservatives in the USA in terms of their moral foundations. Conventional wisdom is also about both power and politics and in modern times has also been challenged (and changed) by social movements, such as civil rights and women’s liberation. Thus, in human terms a “biased” view is often one that differs from the agreed position of a powerful group in a society, with power relations often considered in the sociology of stereotyping (for example, Pickering, 2001 ), but much less so in the cognitive research. In many cases throughout history, dissenters (such as heretics or dissidents) have been severely punished, imprisoned and put into “psychiatric” institutions, for their unconventional “biased” views.

Furthermore, not all implicit stereotypes have the same cultural value. Consider the associations of “artists” with “creativity” and “women” with “dependence”. Both associations are overgeneralisations and can be labelled as stereotypes. In this sense they are both cognitive “biases”. Yet there is no large body of psychological research challenging the stereotype of the creative artist. This is because the two associations differ significantly in their socio-cultural and political meaning. The latter presents a representation of women (common in the past) which is no longer acceptable in a modern liberal democracy where generations of women have politically fought hard to overcome discrimination and achieve equality. Not surprisingly, the majority of the research into stereotyping in the psychological literature has focused on very specific topics: ethnicity or race, gender, sexuality, disability and age. These are all critical issues in the political debates during the last century in Western societies, particularly the USA. Conventional views about these social groups have also undertaken radical change in line with the greater concerns about reducing discrimination and promoting equality. As a result the common views (and associated descriptive terminology) of only a past generation or two are now socially unacceptable and often illegal. It is not unusual to hear modern egalitarian adults discuss with horror the racist or homophobic views they heard at the feet of their grandparents’ generation. These topics continue to be of significance in an ongoing political discussion about anti-discrimination and equality in modern Western democracies.

Finally, human cognitive abilities have evolved for a purpose, and implicit associations guiding rapid decision-making have a survival benefit. Fox (1992) argued that this form of pre-judgement (rather than culturally based intergroup prejudices) has evolutionary value. Learning an association of large animals with danger might be “biased” against harmless large animals (who we run away from needlessly) but that is a very small cost to pay compared to a life-saving rapid decision to get out of the way of a dangerous beast. Indeed, Todd et al. (2012) argued that it is our ability to make “fast and frugal” strategic (heuristic) judgements that make humans smart. Making decisions using simple associations, based on factors such as recognition or familiarity, may not always result in a logically “correct” answer but can be highly successful heuristics, as research in topics such as economics and investment decision-making, emergency medicine and consumer behaviour have all shown ( Gigerenzer and Gaissmaier, 2011 ). The model of the person emerging from the implicit stereotyping research appears to characterise the fair-minded individual as wrestling with an implicitly biased cognitive monster within them. However, it is argued here that this is a false image. We learn the cultural mores of our society through socialisation and daily communication with other members of the culture. We may not approve of all aspects of our culture (and indeed might strongly object to some) but cultural knowledge—just like other knowledge—is crucial to our pragmatic functioning in society. The wide range of semantic associations we learn in our culture can successfully guide our judgements from what to wear at a job interview, which side of the road to drive on, and how to talk to the boss. In order to change the specific set of implicit associations which we find consciously objectionable, it may be better to explore ways of changing the culture to undermine these specific associations, rather than focusing on the inferred “bias” of human cognition: as is argued from the “predictive brain” model below, human cognition is functionally driven to pick up regularities and develop implicit associations from the world around us.

The predictive brain

It has been proposed that human brains are “prediction machines” ( Clark, 2013 : 181), in that experience develops expectations. Perception operates by employing prior probabilities that are efficiently deployed to reduce the processing requirements of treating each new experience as completely new. While explored mostly with basic object perception, Clark (2013) argued that it is applicable to social perception, and Otten et al. (2017) have applied it to social knowledge. For Clark (2014) perceiving is predicting. For example, we are able to quickly and efficiently recognize a friend we have arranged to meet outside a restaurant, even from quite a distance. Through repeated experience of the friend we have developed a sophisticated prediction based on a range of cues from their gait to their favourite coat. Usually, this prediction is correct and it is the person we expected. The dynamic of the predictive brain is to minimise the error of the prediction, that is, the difference between the prediction and the experienced event. Every now and again we are “surprised”—we mistake a stranger for the friend—and this instance of “surprisal” (an engineering term for the error) will also have an incremental effect on the probabilities (and we might be a little more careful when we next meet the friend). The brain seeks to minimise “surprisal” by a constant process of updating probabilities with each experience. However, an occasional error—as only one instance—will normally only have a small effect on the prior probabilities that have been developed over multiple successful perceptions. In this model of the brain, cognitive bias is not an inaccurate deviation from a “true” position, but an expectation or prediction based on the prior probabilities that have developed through experience. Prediction is not about being correct every time—but is about minimising error and maximising predictive accuracy. This process follows Bayes’ Theorem, which expresses a probability of one event (A) given that another event (B) has occurred (such as it being the friend, given the familiarity of the coat and hairstyle observed). This is referred as “likelihood”. Human perception operating according to Bayesian decision-making has been studied in both psychology and economics, so the predictive brain model is also referred to as the “Bayesian brain” ( El-Gamal and Grether, 1995 ; Bubic et al., 2010 ). The implicit semantic associations of “bread” and “butter” or “table” and “chair” ( Neely, 1977 ) have developed through their repeated co-occurrence during our experience of the world. Clearly in ancient Japan (without bread and butter or Western-style tables and chairs) these specific implicit associations did not develop. In social perception we can ask: what is the probability of this man being a basketball player given that he is a tall, Black professional sportsman? This likelihood is based on prior probabilities—which come from experience or knowledge of the culture—so the likelihood could be judged differently by a person from the USA compared with a person from Kenya.

Allport (1979 : 191) proposed that stereotypes were “exaggerated beliefs” associated with a social group, citing “all lawyers are crooked” as an example. The idea that stereotypes involve a belief that all members of the category share an attribute has persisted in the cognitive research ( Hinton, 2000 ). However, Allport (1979 : 189) also stated that a stereotype is “a generalized judgement based on a certain probability that an object of a class will possess a given attribute”. This is not the same. The assumption that stereotypes involve “all” judgements presents them as rigid and fixed, yet the probabilistic association of a stereotyped group member and a specific attribute does not. The presence of an honest lawyer demonstrably proves the former “all” statement to be an incorrect generalization. In the latter case, which follows from the predictive brain model, the experience of an honest lawyer will only adjust the probabilities according to Bayes’ theorem, making it slightly less likely that the next (unknown) lawyer will be predicted to be crooked.

In a well-known study Kahneman and Tversky (1973 : 241) gave participants a description of Jack that matched the stereotype of an engineer:

Jack is a 45-year-old man. He is married and has four children. He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies which include home carpentry, sailing and mathematical puzzles.

They were then asked to predict the probability of Jack actually being an engineer in a room of 30 engineers and 70 lawyers. Participants tended to ignore the base-rate probabilities (0.3 for engineer and 0.7 for lawyer) but made their judgements on the stereotypicality of the description. Kahneman and Tversky argued that the participants were making their judgements on the similarity of the description to the engineer stereotype, which they called “the representativeness heuristic”, and not on the base-rate probabilities. They argued that this strategy was not as good as using the base-rate probabilities as the description may not be valid and furthermore it could match more of the lawyer group as there are simply more of them. However, they admitted that a Bayesian prediction could produce the likelihood of Jack being an engineer if the description was accurate and diagnostic. This highlights a key problem of arguing that people’s judgements are “biased” compared to an “accurate” measurement. Outside the psychological laboratory people almost never know the base-rate probabilities ( Todd et al., 2012 ) and learnt associations are often all they have to go on. In an attempt to find accurate demographic information about engineers, I discovered that 80% of engineering students in the USA are men ( Crawford, 2012 )—which is not diagnostic in this case—but could find no data on the overall proportion of engineers who are uninterested in politics or enjoy mathematical puzzles. In many cases like this, accurate demographic data is unavailable, either because it is not there or because we do not have the time and motivation to find it—we can only rely on our general knowledge of engineers. The Bayesian brain develops its statistical probabilities from experience of engineers—such as the engineers encountered in life and learnt about through the media. The likelihood that an engineer is a man who is uninterested in politics and likes mathematical puzzles does not mean that all engineers must have these attributes, simply that these are frequently encountered in engineers in the social world, such as the engineer Howard Wolowitz in the popular US sitcom The Big Bang Theory , 2007. Thus, the predictive brain, operating through past experience and subtly adapting to each new experience, is a pragmatically functional system rather than being “biased” by an all-or-none overgeneralization.

Consider the following example where I could find some demographic information Footnote 1 . There are 70 professional golfers and 30 professional basketball players in a room (all men and from the USA). The only available information is that Tom is 193 cm tall (6′4″). What is the probability that he is a basketball player? From Kahneman and Tversky (1973) , we can infer that a participant will respond, using the representativeness heuristic, that Tom is probably a basketball player on the learnt association that “basketball players are tall”. Using only the base-rate probabilities Tom should be predicted to be a golfer. However, a Bayesian analysis of the demographic data agrees with the representativeness heuristic that it is very likely that Tom is a basketball player. Rather than assuming that human cognition is statistically naive, an alternative explanation is that people are unconsciously Bayesian and they normally assume that a description identifying learnt implicit associations is accurate and diagnostic (unless they consciously decide otherwise). Kahneman (2011 : 151) acknowledges the link between height and basketball players as an example of where representativeness can lead to a more accurate than chance guess of an athlete’s sport. Outside of the psychological laboratory it may be that a limited description is all the information people have to go on. Indeed, Jussim (2012) argues that when a perceiver has almost no information about a person except, say, a social category (“This person is an engineer”) then they may employ stereotypical associations, based on social knowledge, to make predictions about them (“Engineers are not interested in politics”), which may well be accurate. However, in an encounter with the specific person, they will learn new information to adjust this view if the prediction is not supported.

Jussim (2012 : 159) argued, in agreement with Kelly (1955) , that people operate as naïve scientists, seeking to make accurate predictions of people and events based on expectation and, in the research focus on bias, the evidence that social perception is generally accurate has been ignored, with various independent factors often conflated in the discussion of stereotype accuracy. For example, if a perceiver Ben predicts, on the stereotypical association of a social group and underachievement, that Joe (a member of the group) will not get into the top university he has applied for, and Joe is rejected by the university, then Ben’s social perception is accurate. However, this does not relate to Ben’s belief about why Joe wasn’t admitted or the actual reason why Joe was not admitted. Ben could be prejudiced against the social group (believing the stereotype) but, alternatively, he might be a fair-minded person who believes that the university is prejudiced against the group in its procedures. Also the university might have rejected Ben either as it is prejudiced in its selection or, alternatively, has a fair-assessment system and Ben is rejected for reasons unrelated to his group membership. These additional factors do not mitigate the evidence that Ben’s social judgement was correct. Jussim (2012 : 155) challenged the researchers who criticize the “permissibility” of relying on stereotypes in judgement social judgement—arguing for a moral imperative that stereotypes should not be employed in social judgements—in their rejection of the accuracy data.

A key point to note here is that the predictive brain operates on the state of the world as it is experienced and not on the state of the world as we believe it should be . Working towards gender equality and encouraging more women into engineering is a key aim in many Western societies, but that admirable social and political goal should not lead us to misunderstand the unconscious working of the predictive brain. Indeed, according to Crawford’s (2012) figures, the probabilistic association of “engineer” and “man” is an accurate reflection of the “true” state of the USA in 2012 where 80% of the recruits to the profession are men. A second important point is that the Bayesian brain seeks predictive validity through the picking up of regularities (to form associations) on the basis of experience. Diversity, or counter-stereotypical examples (such as encountering a woman engineer) will reduce the probability of an association (between “engineer” and “man”), but only to the degree that they are experienced. Whereas the presence of even a single female engineer disproves the assertion that “all engineers are men”—and demonstrates that gender is not a relevant factor in engineering ability—the presence of only one female engineer (where all the rest are men) will only have a small effect on the predictive probability of an engineer being a man. The implication from the predictive brain model is that when there are more women engineers, who then become more visible in everyday life (and in the media) then the implicit stereotypical association of “engineer” and “man” will change ( Weber and Crocker, 1983 ).

The predictive brain, as a perceptual mechanism, is directed solely by the minimization of surprisal. It does not make a moral judgement or provide an explanation for the state of the world. It simply seeks to make accurate predictions. In a study on language learning, Perfors and Navarro (2014) argued that the Bayesian brain learns through a process of iterative learning (from other members of the community). Whereas previous researchers have argued that it is solely the structure of language that structures the meanings acquired, Perfors and Navarro (2014) argued that the structure of the external world (and the meanings within it) will also influence the process. We don’t simply learn that an engineer, by definition, designs and builds systems but also that, in the external world, they are mostly men. Thus, semantic knowledge acquired will be shaped by the meaning structure communicated. As long as the things people talk about reflect the relationships of those things in the external world then the semantic relationships learnt will reflect the meanings present in the external world. Thus, knowledge of the relationship between concepts will be acquired from the meanings communicated by others. Furthermore, the proposal of a Bayesian brain does not require that it operates in an optimal (or rational) manner—simply that a Bayesian model best represents its behaviour ( Tauber et al., 2017 ). Learning for the Bayesian brain involves testing predictions (hypotheses) by using the data obtained from the world and applying Bayes’ theorem to develop probabilities ( Perfors, 2016 ). For the predictive brain, the degree to which implicit stereotypes are learnt and employed depends on the probabilities with which the implicit associations between the social category and an attribute are expected and experienced in communication. It is this world of the social perceiver that is considered now.

Implicit stereotypes and “culture in mind”

Implicit stereotypes, like other implicit associations can be viewed as cultural knowledge or folk wisdom that the person acquires through their experience in a culture ( Bruner, 1990 ). The idea that stereotypical associations are cultural in origin was proposed in the early work on stereotypes, but has tended to be ignored in the focus on the fallacy or bias of individual cognition. Journalist and political commentator Walter Lippmann is usually seen as stimulating the academic study of stereotyping with his 1922 book Public Opinion ( Hinton, 2000 ). While Lippmann used the term “stereotype” familiar to him from newspaper printing, he saw it as a cultural phenomenon: “we tend to perceive that which has been picked out in the form s tereotyped for us by our culture .” ( Lippmann, 1922 : 81; my italics) In Lippmann’s view it is the culture that is creating the stereotype, not the individual ( Hinton, 2016 ). As Allport (1979 : 189) pointed out: stereotypes “manifestly come from somewhere ”. To illustrate this, we can examine the origin of the associations identified in the Princeton studies, discussed at the beginning of this article, by considering the example of the English. As Hinton (2016) has argued, the selected attributes reflect the notion of the English gentleman, a common representation of the Englishman in the American media of the first half of the twentieth century, and hence familiar to the exclusively male, upper-class Princeton student participants who, if they had encountered English people it is likely that they would be from the same class demographic as themselves. It is also likely that these participants did not consider (nor were they asked to do so) a range of categories of English people, such as women or the working classes, so, not surprisingly, tended to focus on the specific and familiar representation of the English defined for them by their culture (to paraphrase Lippmann). By 1969, the image of the English gentleman had become rather archaic and even a figure of fun in both the British and American media ( Hinton, 2016 ) and the selected English attributes had changed. Also, a crucial point to note is that the student participants were only asked “to select those [attributes] which seem to you to be typical” of the group ( Katz and Braly, 1933 : 282). Even so, some students refused to do the task in 1951 and 1969 ( Brown et al., 1987 ), which indicates that, even for the students who had agreed to take part in the study, there was no evidence that the selected attributes represented their own personal attitudes, thus the responses did not reflect a fallacy or a cognitive bias of the participants. To perform the task with no information except the category name, the students may have simply drawn on attributes they knew to be commonly circulating about the English in their culture. The most popular attribute in 1933 for the English was “sportsmanlike”, and this might even have shown up in the IAT if it had been available at the time. Yet this does not mean that the students viewed all English people as sportsmanlike. However, the sportsmanlike English gentleman was a familiar trope in American popular culture at the time, typified by actor Ronald Colman in Hollywood movies such as The Dark Angel , 1925, and Bulldog Drummond , 1929. By 1969, “sportsmanlike” had dropped out of the Princeton top five attributes for the English ( Karlins et al., 1969 ). We can take Allport’s example of the “crooked lawyer” stereotype as a second example. A person with no personal antipathy to lawyers, and well-aware that they are a highly regulated profession of mostly honest people, might make the prediction that when a lawyer character appears in a popular crime drama that they will (probably) be crooked from the experience of lawyers in famous movies such as The Godfather series, 1972–1990, and television programs such as Breaking Bad , 2008–2013, (along with the spin-off series about a crooked lawyer, Better Call Saul , 2015).

As Devine (1989) has argued, well-learnt associations picked up during socialization form implicit stereotypes even for the individual seeking non-prejudiced views. It is argued here that the predictive brain model provides the mechanism for this. The process of picking up associations probabilistically is happening unconsciously through Bayesian principles throughout a person’s life within a culture. Yet culture is neither monolithic nor fixed and unchanging. People are active in the construction both of their social world and their media environment ( Livingstone, 2013 ; Burr, 2015 ). As Smith (2008 : 51) points out “In reality, people’s social environments are probably best characterized as social networks . People have links of acquaintanceship, friendship, etc. to particular other people, which interconnect them in a complex web”. Within any society, there will be different social networks of this kind communicating different social representations about social groups. According to Moscovici (1998) , it is these shared representations that define a culture or subcultural group. Different cultural groups will differ ideologically through their position in society and the representations that circulate in the communication within their social network. While one cultural group may be actively promoting one representation (such as “immigrants” are “a great economic benefit to our society and add to the diversity of our culture”) through a range of communications, such as television, newspaper and social media, another group may be promoting an alternative representation (such as “immigrants” are “a burden on society, taking jobs and undermining our culture”). In the communication within any social network there will be regular and consistent associations between social groups and attributes, which will be picked up by it members, through the working of the predictive brain. The extent to which individuals share implicit associations will depend on the hegemonic social representations within the society across cultural groups ( Gillespie, 2008 ), such as a positive belief in democracy and a negative view of communism, which are prevalent in the wider social institutions within a nation, and examined in the sociological study of stereotypes (for example, Pickering, 2001 ).

The role of stereotypes in communication within a social network was demonstrated by Kashima and colleagues ( Kashima and Yeung, 2010 ; Kashima et al., 2013 ) in their research on the serial retelling of stories. The results showed that stereotype-consistent information was emphasized. Even though stereotype-inconsistent information attracted attention it was not necessarily passed on. Thus, the story became more stereotypical and consistent in the serial retelling. They argued that “stereotypes can be thought of a significant cultural resources that help us to transmit cultural information” ( Kashima and Yeung, 2010 ). Within a social network common understandings are developed via the use of stereotypes. Members of the culture assume a knowledge of the stereotype in other group members, which facilitates social interaction, but potentially also helps to maintain the stereotype, even in the face of inconsistent information. From this research, it can be argued that the analysis of implicit stereotypes should focus on the communication of meaning within a social network, rather than considering them as a “bias”. The complex dynamics of the individual within a social network (for example, Christakis and Fowler, 2009 ) needs to be considered in investigating the formation, transmission and maintenance of implicit stereotypes.

In the modern world of the twenty-first century, the options available for people to construct their social environments have radically increased ( Giddens, 1991 ). The media has rapidly expanded through multiple television channels, a proliferation of media outlets, and the development of social media via the internet. While this offers the potential for people to engage with a diversity of representation and counter-stereotypical information, it also allows people to remain in an ideological subculture, communicating with like-minded people where specific representations of cultural others are constantly being circulated unchallenged within the social network. In terms of the predictive brain, implicit associations will develop from the consistent messages people receive in their everyday lives. If certain implicit stereotypes are deemed unacceptable then it will only be when people experience consistent counter-stereotypical information over a long period of time that these associations will be probabilistically undermined. For this to be achieved, everyday experience has to involve necessarily (but not sufficiently) exposure to alternative representations and counter-evidence to these specific implicit stereotypes, rather than people only experiencing the consistent representations about social groups circulating within a particular culture, social network or social media “bubble”.

Over the last 30 years stereotype research has focused on implicit stereotypes, particularly using the IAT, which have been interpreted as revealing an implicit or unconscious cognitive bias, even for the consciously fair-minded person. Despite research questioning the predictive validity of the IAT as a method of revealing unconscious prejudice (for example, Oswald et al., 2013 ), the focus of implicit stereotypes has dominated the psychology of stereotyping in the twenty-first century ( Fiske and Taylor, 2013 ). However, it is argued here that implicit stereotypes, as attributes associated with social groups, do not indicate an unconscious cognitive “bias” (a “cognitive monster”) within the fair-minded person but are learnt associations arising from the normal working of the predictive brain in everyday life. These associations are based on information circulating within the person’s culture, and the associations are probabilistically detected by the predictive brain: as such they can be characterised as “culture in mind” rather than an individual bias. According to the predictive brain model, when the culture changes then the implicit stereotypes of its members will change (albeit slowly for some associations). Therefore, to properly understand the nature of implicit stereotypes, the cognitive research needs to be combined with the study of the dynamics of culture, to understand the specific associations prevalent in the communication within a culture and their implicit influence on the members of that culture.

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How to cite this article : Hinton P (2017) Implicit stereotypes and the predictive brain: cognition and culture in ‘biased’ person perception. Palgrave Communications . 3:17086 doi: 10.1057/palcomms.2017.86.

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ORIGINAL RESEARCH article

The impact of gender stereotypes on the self-concept of female students in stem subjects with an under-representation of females.

• 1 Department for Education, Universität der Bundeswehr München, Neubiberg, Germany
• 2 Federal Centre for Professionalization in Education Research, University of Teacher Education Styria, Graz, Austria
• 3 Educational Psychology Unit, Department of Psychology, University of Graz, Graz, Austria

It's possible to assume that women who study STEM topics with a low proportion of females have successfully overcome barriers in school and the family, making them less prone to stereotypic views, and influences. The present study focuses on these kinds of factors and analyzes to which degree family factors, school-related factors, and individual stereotypes may influence a woman's academic self-concept. The following study presents a latent regression model which is based on a survey of 296 women from different German universities, all of whom are part of STEM programs of study that have <30% females. It was investigated to which degree individual stereotypes, support in school, and family support contribute to the self-concept in STEM. Gender stereotypes were negatively related to students' STEM-specific self-concept in the selected sample. This study also reveals negative family-related influences that lower a woman's self-concept. Positive predictors on the other hand included school aspects that are found in the students' favorite subjects at school. The results of the study provide important aspects for STEM education. Even though the students participating in the study presumably had good grades in STEM, stereotypes still corrupted their self-concept. One of the reasons for this might lie in stereotypes that attribute girls' achievements to diligence instead of talent. The results also point out that direct support, particularly by parents, can have a negative impact on female students' self-concept. Activities that are meant to support pupils directly may actually backfire and transport stereotypes instead. This stresses the need for indirect support during socialization, e.g., by providing opportunities for children to have positive experiences or by giving them the chance to meet role models that are enthusiastic about their STEM professions. These kinds of measures have the potential to spur students' interest in STEM subjects—something that in the present study proved to be especially beneficial for women's positive self-concept when studying STEM topics.

Introduction

In most European countries, the proportion of females pursuing a career in STEM (Science, Technology, Engineering, Mathematics) is still alarmingly low. This holds especially true for occupations in technology and engineering ( Blickenstaff, 2005 ; Ihsen, 2009 ; European Commission, 2015 ). The past decades have seen the proportion of females in these fields remain constant at approximately 25% in the EU, and even lower in Germany with approximately 18% [ CEWS (Center of Excellence Women Science)., 2014 ]. One of the reasons females avoid STEM subjects lies in the negative and stereotyped perception(s) of these subjects (see Engeser et al., 2008 ; Schuster and Martiny, 2017 ). Stereotypical assessments here include expectations e.g., about a particular gender, as well as the attributions of abilities in specific domains. Such assessments are embedded in a broader cultural context of the individual (see Good et al., 2008 ). According to Bronfenbrenner's (1977) ecological systems theory, a major source of stereotypes lies within an individual's macro system, i.e., the cultural and social context of a person's societal group. The macro system refers to the overall values and customs that characterize a given social group which provide a framework for the interactions between the individual and its social context, e.g., the teachers at school or the family. Depending on the macro system and its values, stereotypes about professions, or subjects may vary among nations or cultures (see Nosek et al., 2009 ; Else-Quest et al., 2010 ). Many females in the Western world still believe the stereotype that professions and subjects in STEM are “male” domains ( Nosek et al., 2009 ) and they often apply these kinds of stereotypes to the assessment of their own abilities in STEM (see e.g., Dresel et al., 2007 ).

Stereotypical classifications of professions and subjects have strong implications for females. They impair learning and prevent females from fulfilling their full potential. Stereotypes lower one's self-assessment and sense of competence, i.e., a person's self-concept ( Marsh and Scalas, 2011 ). They even have an impact on career choices (e.g., Engeser et al., 2008 ; Schuster and Martiny, 2017 ).

Against this background, the present study investigates how stereotypes may explain female university students' self-concept in STEM. In this context, it is important to have a closer look into the different STEM subjects. Even if the term is used internationally, there are particularly differences about the definition of the science part. The German equivalent to STEM focuses only on “natural” sciences like physics, chemistry, biology etc., (see Ihsen, 2009 ). The English-speaking community also includes life sciences like medicine (e.g., European Commission, 2015 ; Eccles and Wang, 2016 ), while some authors, primarily from the US context also include social sciences in this definition (e.g., Su and Rounds, 2015 ). It is important to acknowledge this fuzziness when interpreting results with respect to STEM, because all these definitions, comprise subjects with a very low proportion of females, e.g., engineering as well as with a superior proportion of females like e.g., life sciences (see e.g., European Commission, 2015 ; Su and Rounds, 2015 )—even if the proportions of females vary between the countries. This study focusses on a special group of female STEM students for reducing ambiguity: those who study a subject with an especially low proportion of females. We will label these STEM subjects having an under-representation of females as STEM-LPF (STEM subjects with a l ow p roportion of f emales). Studies with an especially low proportion of females have less than 30% ( Buchmann et al., 2002 ). This means that for every female, more than two males study this subject. This group of female STEM-LPF students was selected because it could be expected that they are less prone to stereotypes after they have chosen what can be seen as a less-than-typical career path.

Academic Self-Concept

An academic self-concept comprises a person's self-assessments in academic domains. It is formed through experience and interpretations of one's environment as it regards feelings of self-confidence, competence, and ability. It's influenced by evaluations of significant others, reinforcements, and attributions of one's own behavior ( Marsh and Scalas, 2011 ). Such self-assessments may belong to two frames of reference ( Rost et al., 2005 ): The external frame of reference is guided by a social comparison of one's own achievements with those of peers. The internal frame of reference is guided by a comparison within the individual, for example a comparison of abilities in various subjects. Students compare their achievement in one subject (e.g., mathematics) with their achievement in another (e.g., English).

The academic self-concept in a specific domain does not necessarily accurately reflect achievements. In a study by Ludwig (2010) , female middle school students were much more critical of their abilities in STEM than male students even if they had the same grades. Similar results were found in the PISA studies ( OECD, 2015 ). The academic self-concept of females who perform on the same level as their male counterparts in the PISA science scores was about one quarter standard deviation lower ( OECD, 2015 , p. 75). In most participating countries, females had a more critical academic self-concept in STEM than males. These kinds of differences can be downright vicious because research postulates reciprocal effects between the academic self-concept and achievements (see Marsh and Scalas, 2011 ). In their reciprocal effects model , pathways were found between students' achievements and their academic self-concept and vice versa. This means that, considering students on the same level of achievements, the students with the higher academic self-concept will advance in their achievements over the course of time while the others will lag. This effect may be explained by expectancy-value theory in how students with a higher academic self-concept in a domain have higher expectations regarding their chances for successful outcomes and as a result have a higher motivation to invest time and effort into learning activities in this domain (see Eccles et al., 1983 ; Eccles and Wang, 2016 ).

Attributions for causes of achievement also essentially contribute to the development of an individual's self-concept (see Möller and Köller, 1996 ). Successful achievements may be attributed to ability and thus enhance a positive self-concept, or they may be attributed to luck and have detrimental effects on the self-concept as a result (see Heider, 1958 ). Attributions are also related to learning motivation: Attributing academic failure to a lack of effort may increase effort for the next examination, while attributing failure to the lack of ability may cause resignation. Thus, the academic self-concept influences to which degree a student makes full use of her/his academic potential (see Jahnke-Klein, 2006 ). Studies show that female and male students differ in their attribution patterns in STEM fields ( Beermann et al., 1992 ; Jurik et al., 2013 ). In comparison to males, although females seldom attribute success in STEM fields to ability, they do in fact attribute failure mostly to the lack thereof ( Dickhäuser and Meyer, 2006 ). These kinds of dysfunctional attribution patterns interfere with the development of a positive self-concept and impair learning motivation (see also Ziegler, 2002 ; Dresel et al., 2007 ). All in all, a too-critical self-concept is an important reason why females believe they have inferior skills in STEM fields (see Wang et al., 2015 ; Eccles and Wang, 2016 ); why they are less motivated; and why they seldom consider a career in a STEM field at all ( OECD, 2015 ).

School and family are two distinct environments that support the development of a student's academic self-concept. Different characteristics of classroom teaching show substantial effects on students' academic self-concept and their interest in a subject ( Lazarides and Ittel, 2012 ). Comparisons in the classroom set an external frame of reference for the self-assessment and attribution of achievements (see Rost et al., 2005 ). Teachers' support in the attribution of achievements ( Heller and Ziegler, 1996 ) can help students overcome gender-specific attribution patterns ( Dresel et al., 2007 ). So teacher behavior can support students' interest and their development of a positive academic self-concept and encourage students to perhaps even experience STEM as their favorite field, all while keeping in mind that opposite effects are possible as well.

Within the family context, there is no in-class comparison. Here, parents' attributional beliefs serve as a frame of reference for a student's self-assessment ( Viljaranta et al., 2015 ). Parents' beliefs about their child's ability have strong impacts on his/her self-assessment of ability ( Tiedemann, 2000 ) and academic self-concept as a result. This makes parent support an important aspect in the context of STEM ( Adya and Kaiser, 2005 ). However, if parents consider their child as being less capable, they may provide intrusive support with detrimental effects on the child's self-assessment ( Pomerantz and Eaton, 2001 ). In other words: parents' influence on their children's academic self-concept can be ambiguous depending on their specific behavior, making it important that students experience support for their self-assessments at both school and at home ( Adya and Kaiser, 2005 ). Of note here is that the effects of this support are subject to the particular support behavior. In the context of the STEM subjects, gender stereotypes can be seen as one reason why support measures may achieve the opposite effect.

Stereotypes and their Impact in STEM

The development of the academic self-concept begins in infancy and unfolds its most significant impact(s) after primary school ( Senler and Sungur, 2009 ). Parents' and teachers' expectations and attributions of abilities and achievements essentially shape a child's self-concept ( Dresel et al., 2007 ; Ludwig, 2010 ). They do not necessarily rely on objective assessments; often, parents underlie stereotypical evaluations which do not correspond to their children's actual achievements. For example, parents tend to regard daughters as being less talented in mathematics and science and reinforce dysfunctional attribution patterns as a result ( Dresel et al., 2007 ).

Explicit Stereotypes as a Threat to Performance

Several studies on stereotypes have coined the term “stereotype threat” ( Martignon, 2010 , p. 221; Shapiro and Williams, 2012 ). In these studies, participants usually were confronted with a stereotype about a target group, e.g., females or members of a specific ethnic group. In the context of STEM, stereotypes would include males being more talented and successful in math and science. After confrontation with the stereotype, study participants worked on a task that is associated with the stereotype ( Martignon, 2010 , p. 221), and performance was compared to another group working on the same task that was not confronted with the stereotype. In nearly all studies on stereotype threat, females achieved worse results with mathematical tasks, and their interest decreased when they were confronted with the stereotype that women are less talented in mathematics ( Shapiro and Williams, 2012 ).

Owens and Massey (2011) describe two mechanisms that explain why stereotype threat occurs. The first mechanism works via internalized stereotypes; this means the person has internalized the stereotype and identifies him/herself with the target group. Consequently, he/she invests less effort in the task and the stereotype threat becomes a self-fulfilling prophecy. The internalization of the stereotype also has a negative effect on the academic self-concept ( Heckhausen, 1989 ) and is accompanied by a reduction in motivation and effort ( Möller and Köller, 1996 ). The second mechanism works via external stereotypes ( Owens and Massey, 2011 ). In this case, the person does not necessarily identify him/herself with the stereotype, nor does he/she need to believe the stereotype. Confrontation with the stereotype, however, affects the perception of task difficulty, increasing strain and tension. Rumination about the stereotype uses up resources that are otherwise needed for task completion, impairing performance as a result (see Macher et al., 2015 ). This research shows that even females who believe themselves to be competent and pursue a career in STEM still can be impaired by stereotype threat.

Influence of Stereotypes Communicated by Significant Others

Stereotypes are also communicated by significant others such as parents or teachers ( Gunderson et al., 2012 ). Tiedemann (2000) showed in his study on pupils in primary school that mothers as well as teachers based their feedback on children's competence in mathematics not only regarding previous grades but the respective child's gender as well. Mothers were even more prone toward gender stereotypes than teachers. Stereotypes were especially strong in feedback on achievements and had a significant impact on the children's self-concept ( Tiedemann, 2000 ). In a study by Kiefer and Shih (2006) , students were especially receptive to teacher feedback that was associated with gender stereotypes. According to Dickhäuser and Meyer (2006) , girls mainly rely on perceived teacher evaluations of their ability when making math ability assessments and thus are very susceptible to incorporating significant others' stereotyped evaluations into their own self-concept (see also Xu, 2016 ).

Parents' and teachers' gender stereotypes manifest themselves not only in communication, but in dysfunctional support for their children or students as well. When parents endorse specific gender stereotypes (e.g., boys are better in STEM, girls are better in languages), they are more likely to uninvitedly intrude on homework, undermining children's confidence in these areas, and weakening their self-concept ( Bhanot and Jovanovic, 2005 ). These kinds of long-term influences by parents and teachers may have a significant influence over the years not only on motivation and achievement but regarding career choices as well ( Bleeker and Jacobs, 2004 ).

Research Question

The academic self-concept is a key variable in explaining learning and motivation in specific academic domains. It is also of interest in explaining career choices and perseverance in a specific profession. However, it does not always rely on “objective” data such as actual achievements, but is instead subject to distorting influences such as internalized stereotypes as well as external stereotypical attributions by others.

The present article looks more closely into the academic self-concept of a special group of females: university students in a STEM-LPF subject with a notable underrepresentation of women (equal to or less than 30% females). It can be expected that these females would tend to be confident regarding their academic self-assessments in STEM fields, and less prone to stereotypical attributions concerning females' lack of abilities here. Therefore, the research question will investigate:

To what degree do STEM-LPF students' own stereotypes in comparison to school- and family- related factors contribute to their academic self-concept in STEM?

Regarding this research question, we would still expect a negative effect of stereotypes. However, due to a lack of research in the field, we cannot provide hypotheses about its strength within the context of the ambiguous effects of school and family factors.

The focus of this paper is primarily on a quantitative study with 296 female STEM-LPF students. For strengthening these results, we will also provide evidence from a qualitative study with STEM students that took part in an earlier stage of the project. Students of the qualitative study were also invited to participate in the quantitative one but as this was an anonymous survey there was no control of participation.

Quantitative Study

The sample employed in the quantitative study is part of a larger sample that was gathered in the EU research project SESTEM in six European countries. Five hundred and sixty seven female university students in STEM fields participated in Germany. Ertl et al. (2014) analyze the entire German sample (including students in STEM areas without female underrepresentation) with a focus on motivation and the academic self-concept.

Participants

The present study focuses on a sub-sample of 296 female STEM-LPF students: females who studied one of these STEM subjects that have a proportion of equal to or lower than 30% females. This sample includes 296 students in subjects including mechanical engineering ( n = 97), computer sciences ( n = 48), physics ( n = 39), metal engineering ( n = 36), civil engineering ( n = 34), electrical engineering ( n = 32), and other STEM subjects ( n = 10).

A specific questionnaire was developed for the study. Items were deducted from theory and adapted for the field of the study. During this process, all six partners of the SESTEM project consortium brought in aspects within their field of expertise. Seeking and including expert judgment on the content of a questionnaire, on item formats, item contents, and scoring systems enhance content validity of a measurement instrument. Then, the consortium negotiated about the inclusion of the different scales weighting between satisfying the needs of the different partners, adopting existing scales, and keeping the questionnaire as short as possible for maintaining students' motivation for answering the questions. This resulted in a final questionnaire in an English language version, which was translated into further five national languages including German. These six language versions were implemented as a LimeSurvey multi language questionnaire. The students reported in this paper answered the German language version. They were asked about:

1. Their majors or the subject combination they had chosen for their degree. Based on the data from the German Federal Statistical Office [ Destatis (Statistisches Bundesamt), 2013 ], majors were classified with respect to the proportion of females.

2. Their parents' professions . These were classified according to whether they were from the field of STEM (coded as STEM/not STEM).

3. Their academic self-concept in STEM on a five-point Likert scale (4 items, see Table 1 ). Higher values indicate a more positive self-concept.

4. Their internalization of gender stereotypes was measured by three scales: interests (7 items), abilities (5 items), and conformance (2 items). Each of these scales was based on a five-point Likert scale (see Table 1 ). Higher values indicate stronger stereotypes.

5. School factors . Here the following variables/scales were measured: First, a score was derived from students' STEM favorites (derived from students' three most favorite subjects at school. Subjects from the field of STEM that are known for association as a “male domain” were summed up to a score. This means that the score includes subjects such as mathematics, physics, or computer sciences, but not subjects like biology). Higher values indicate more favorite STEM subjects. Second, STEM support in school was operationalized by teachers' and school activities that facilitated the interest in STEM (e.g., “Were there activities in secondary school that encouraged your interest in STEM?” These answers were also summed up and mapped onto a range between 0 and 5) with higher values indicating more support. Third, a five-point Likert scale regarding students' perception of teachers' stereotyped behavior (4 items, see Table 1 ).

6. Family factors with respect to family support. This was surveyed by different areas in which students may have received support and the persons that supported the students (e.g., “Who supported you in mathematics: father/mother?”) Answers were distinguished with respect to the supporting person and the supported field and summarized into a score for support by parents generally, as well as for support in specific areas (mathematics/science). These scores were mapped regarding their theoretical maxima and minima on a range between 0 and 1. Altogether three variables were derived: Parents' support in math, parents' support in STEM, and parents' general support. Higher values indicate stronger support.

Table 1. Overview on the scales used for the study with the number of items, an exemplary item, and the internal consistency .

Table 1 gives an overview of the different Likert scales including the number of items, an exemplary item, and the internal consistency of the scale. The reported consistency measures relate to the whole sample of 567 students. Missing items of single scales were imputed; missing scales were treated as missing. Table 2 provides an overview of all scales including their value range, their means, and their standard deviations.

Table 2. Ranges, means, and standard deviations for the reported scales .

Qualitative Study

The quantitative study was complemented by a qualitative study. It comprised interviews based on a semi-structured interview protocol (for the complete set-up of the qualitative studies see Mok and Ertl, 2011 ). Interviewees were contacted by personal contact, email, and via STEM-related distribution lists. A sample of 11 female students of STEM subjects like mathematics, physics, engineering, and STEM-related teacher training from three different universities participated in the qualitative study; five students studied a LPF subject (civil engineering n = 2, physics n = 3).

In the following, we will first report results of the quantitative study. The results section will first provide insights into the descriptive outcomes. Then it will describe the results of the confirmatory factor analysis for the factors of stereotypes, school, and family. It will finally present a structural equation model that provides insights into the impacts of each of the factors onto the students' academic self-concept in STEM and illustrate these afterwards by the interviews with these five students of the qualitative study.

Descriptive Statistics

Of the 296 students, nearly the half of the students (139) had a father working in a STEM profession, while more than 10% (31) had a mother in STEM.

Most students showed a very positive self-concept ( M = 4.58; the means described in the following relate to a scale of 1–5, with 1 as the lowest and 5 as the highest value). We could find distinctive occurrences with respect to the internalization of stereotypes between the students. The students agreed mostly that girls and boys have different interests ( M = 3.14). They agreed less about stereotypes regarding a stereotype distribution of abilities ( M = 2.20), and least of all about the need for conformance ( M = 1.64; see Table 2 ).

With respect to school factors, 26 students had three favorite subjects from STEM at school, 129 students two, 121 just one, while 20 had favorite non-STEM subjects ( M = 1.54). They received a moderate amount of STEM support in school ( M = 2.55 of a maximum of 5), and also perceived a moderate amount of stereotyped teacher behavior ( M = 2.51 of a maximum of 5).

Considering family factors, the amount of parents' support in math ( M = 0.15 of a maximum of 1) and STEM ( M = 0.14) was low. General support by the parents was low to medium ( M = 0.36).

To analyse the distribution of the data, we used the values of the skewness and kurtosis. West et al. (1995) set the criteria for indicators used in structural equation models at a value >2 for skewness and >7 for kurtosis for deviation from normal distribution. All scales meet the requirement of normal distribution.

Latent Regression Analysis

Latent regression analysis was used to test relationships between the variables in a multivariate, multiple regression context. Structural relationships between multiple dependent variables and multiple independent variables can be analyzed simultaneously. Regression analyses are specified at the latent level and are corrected for measurement error at the level of the independent and dependent variables. Latent regression analysis has the advantage that the relationship between variables in the regression model can be estimated more accurately. At least two manifest variables (or indicators) are required for each latent variable (factors) in a latent regression model ( Geiser, 2013 ). The data were analyzed with Mplus 6 using a maximum likelihood estimator. The goodness of fit of the data to the hypothesized model was assessed using the following indices: χ 2 /df, comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR).

The model fit indices suggest a good fit of the latent regression analysis model (χ 2 /df = 1.422; CFI = 0.979; RMSEA = 0.038; SRMR = 0.049). Generally, values of χ 2 /df <2, CFI > 0.95, RMSEA < 0.05, and SRMR < 0.05 are considered as indicators of good model fit ( Papousek et al., 2012 ).

Table 3 displays the standardized solutions for the latent regression analysis with three the factors of stereotypes, school, and family. Each factor comprises different variables that describe stereotypes rooted in the culture or encountered in school or the family.

Table 3. Standardized coefficients for the latent regression analysis .

The model shows that the three indicators of stereotypes about interests (β = 0.274), stereotypes about ability (β = 0.590), and stereotypes about conformance (β = 0.379) are positively related to the factor stereotypes. Three indicators are related to the factor school: STEM favorites in school (β = 0.614), school support (β = −0.326), and stereotyped teacher behavior (β = −0.274). The three indicators support in mathematics (β = 0.784), support in STEM (β = 0.806), and support by parents (β = 0.787) are high positively related to the latent factor family.

The regression coefficients between the three factors stereotypes, school, and family and self-concept in STEM of students show the following result: Students with higher levels of experienced stereotypes (e.g., females have fewer skills or interest in STEM subjects, females in STEM have to be like men) report lower self-concepts in STEM domains (β = −0.405). The model shows a moderate relationship between the latent factor school and students' self-concept (β = 0.279). Students who reported a higher number of favorite STEM subjects in school have a higher self-concept whereas higher levels of school support and teachers' stereotypes indicate a lower and less positive self-concept in STEM. There was a weak relationship between the latent factor family and the self-concept of students (β = −0.149, p = 0.053). A higher level of support (math, STEM, parents) indicates a lower self-concept. The total variance of self-concept that can be explained by the factors is R 2 = 0.304. Figure 1 gives an overview of indicators and factors of the latent regression analysis model.

Figure 1. Latent regression analysis self-concept .

Correlations between the three latent factors were allowed in the model specification. We found low to moderate, but non-significant correlations between the three latent factors.

Evidence from the Qualitative Study

The analysis of the qualitative study aims to illustrate the latent variables of the quantitative one. Students' statements can give evidence for the latent factors of the quantitative study with respect to the impact of stereotypes and family. School factors were just mentioned in a few words, e.g., that students had taken advanced courses in mathematics (I57) or physics (I30, I57) or that they had enjoyed mathematics in school (I54). We will present the English translation of the statements; the German original version can be found in the project report ( Mok and Ertl, 2011 ).

Impact of Stereotypes

With respect to the impact of stereotypes, students mentioned that they were taking an untypical career path and that their social environment was surprised by this kind of career choice. A civil engineering student mentioned that surprise with respect to her friends: “ They were quite surprised,” I54, L.99. She further elaborated this untypical career with respect to the lack of acceptance of women in the construction area: “ The problems are bigger for women [in STEM] e.g., to be accepted in particular in the construction domain. There you need particularly technical knowledge and you have to know how to behave,” I54, L.124ff. This aspect was also emphasized by I1: “ As a woman you'll be seen different in a technical profession,” I1, L.16f. These untypical career choices also result in a perceived lack of role models and contact persons, e.g., female professors (“ There are few female professors,” I30, L.69). Thus, also the interview data highlights that students are aware that they are studying an untypical subject and name surprise of their friends about their study choice, obstacles for working in the untypical field, as well as missing role models.

Family impact . With respect to family impact, all students mentioned either that their father (I1, I54, I57) and/or mother (I1, I54) is in a STEM profession (“Both of my parents are teachers but my father has also studied physics and got a diploma […],” I57, L.47f.)—or that their parents supported their specific interest in STEM, e.g., by books (I35) or electronic construction toys (“ That my parents had already impacts on me because I also had got electronics experiments kits as a child,” I30, L.19f.). Most parents, particularly those in a STEM field, encouraged their daughters' pursuing a STEM career: “ The parents enhance the STEM-career because they are working in this field themselves” (I1, L.41). Some students further elaborated their parents' pleasure at their daughters' career wish “ My father was happy for me and my mother too.” (I57, L.59).

Parents also supported their children in case of difficulties, e.g., with homework (“[…] I had the opportunity to ask my father of course if I had e.g., pretty problems in mathematics or physics and he was able to help me,” I54, L.28ff.) or by providing stimulating tasks (“My father had written a computer program that provided us arithmetic problems when we attended primary school,” I57, L.36f.).

Yet, some students also described that their parents were doubtful about their ability for pursuing a STEM career (“My dad told me afterwards that he hadn't thought that this is the right thing for me […] because I have an already an understanding for logical relations but I have not an all-embracing one,” I54, L.105ff.) or that they questioned their decision (“my father appreciated my decision but my mother mentioned—although she was also working in the STEM field herself—that I should really think about my decision.” I35, L.56f.).

The results of the interviews stress the ambiguity of the family factor: Firstly, all parents had a STEM-affine background. They could provide content-specific support and foster their daughters' cognitive development in STEM. However, such support may also evoke an attribution of lower abilities in STEM. For example, one participant first mentioned that her father was very helpful when dealing with problems in STEM—but later she described how her father didn't trust her the ability for pursuing a STEM career. Thus, parents' support may be connected to implicit assumptions about their daughters' ability and these assumptions may influence their daughters' academic self-concept in STEM.

The results of the quantitative study were able to show that the model presented is appropriate for explaining students' self-concept. This is indicated by the good model fit indices, as well as by the amount of explained variance: The model explains 30.4% of the total variance of students' self-concept, which is nearly a third of the variance. Results of the qualitative study could furthermore give insights how to interpret the effects of the latent variables. In the following, we will discuss the relationships between stereotypes, school, and family factors, the self-concept, as well as the limitations of the study.

Relationships Between Stereotypes, School, and Family Factors, and the Self-Concept

All three facets of stereotypes (stereotypes about females' abilities, interests, and need for conformance) contributed negatively to the academic self-concept. Remarkably, stereotypes regarding females' abilities in STEM subjects were most strongly related to their self-concept. This is particularly important because the females of this study were already studying a so-called “male” STEM-LPF subject. The descriptive data showed that even these students share stereotypes, indicating that stereotypes even affect students who are already enrolled in a very gender-untypical course of study. Stereotypes about a need for conformance in the work environment and the different interests of females and males also contributed to the factor stereotypes. Also, result from the qualitative study indicate that there is a special need to behave in the domain. This result is of particular interest because it means that the STEM-LPF students acknowledge different interests of females and males, while they at the same time see the context of the “male” work environment and the need for showing conformance. They appear to use conformance to the work environment as a part of their identity construction (see Kessels and Hannover, 2004 , p. 400). This may also be an aspect of identity bifurcation (see Pronin et al., 2004 ) in how females in these subjects disavow some of their own characteristics that are, stereotypically, negatively associated with success in STEM careers.

In contrast, the three indicators of the latent factor school differ in their contribution. Students' favorite subjects in school, which could be seen as an indicator of their interest in STEM, or beneficial role modeling by teachers, were positively related to the self-concept. This stresses the importance of school factors for career choice. These may relate to interesting and gender-sensitive classes ( Faulstich-Wieland et al., 2008 ; Ertl and Helling, 2011 ), role modeling ( Kessels and Hannover, 2008 ), and providing appropriate attribution patterns ( Dresel et al., 2007 ). However, specific support at school and teachers' stereotypes had a negative relationship with the factors of school and self-concept. Teacher stereotypes, e.g., teachers encouraging boys to choose STEM subjects more strongly than girls, can be seen as a specific occurrence of the stereotype threat with the respective consequences (e.g., Good et al., 2008 ; Owens and Massey, 2011 ). It's fairly obvious that these kinds of actions provide a counterpart to students' interests in STEM. In contrast, teachers supporting their female students have the intention that they make further progress in STEM subjects. Nevertheless, these activities may in fact run counter to their interests in STEM, which may be the result of different reasons: The first aspect relates to the development of the self-concept in STEM. If students receive special support in STEM, they may interpret this action as a compensation for their lacking ability and therefore reduce their self-concept ( Pomerantz and Eaton, 2001 ). This is certainly the case when students receive intrusive support (see Bhanot and Jovanovic, 2005 ). From this line of argumentation, it is essential to investigate methods and implementations of support that are not detrimental to a students' self-concept. This result might also be explained by the “doing gender” approach: When giving specific support to females in STEM, their gender will be overemphasized, evoking a stronger identification with the stereotyped group of females in STEM (see Faulstich-Wieland et al., 2008 ). What this means is that supporting activities may in fact unfold their detrimental effects via two different mechanisms: one by giving supported students the message that their individual ability is not sufficient enough to succeed without support; and the other by overemphasizing their affiliation to a stereotyped target group.

Family factors were negatively related to the students' self-concepts, i.e., they impair a positive self-concept. This factor consisted of support by the parents and support in mathematics and STEM. Notably, all three aspects showed rather dysfunctional effects. With respect to family factors, the qualitative study could provide a several hints for interpretation. All students mentioned that their parents were very helpful and supportive. However, one student explicitly mentioned her father attributing her as not gifted enough for a STEM career while giving her support. This is in line with research about intrusive support patterns that are detrimental to a student's self-concept (see Bhanot and Jovanovic, 2005 ). Furthermore, one student reported her mother encouraging her to re-think her career decision for STEM which stresses the impact of significant others in career decisions (see also Xu, 2016 ).

The results generally suggest that the school environment provides more positive impacts than the family. This may relate to the different attribution patterns of teachers and parents ( Dresel et al., 2007 ). Teachers can provide much better attribution patterns in the context of the reference frame of a class's performance than parents who are primarily focused on their child with their beliefs as the key frame of reference. This stresses the need to focus on both school as well as on home environments as essential factors in facilitating students' self-concept (see also Eccles and Wang, 2016 ).

Limitations

A strength of this study lies in the more ecological approach as foreseen in the Bronfenbrenner (1977) model. This approach provided more insights into stereotypes as well as interactions at school and at home. It at the same time included a major challenge for research that relates to the issue of how the study variables were self-reported by the students, with some of the variables even being reported retrospectively. It would have been desirable to research these issues in a longitudinal design in an effort to achieve greater insight into causal relations and the development process of stereotypes, interests, achievements, and the individuals' self-concepts. However, such a design would raise the issue of the necessary sample size at the primary school level to gain the respective number of students at the university level. A further aspect relates to the implementation of the Bronfenbrenner (1977) model in the latent regression analysis. Here, it would have been desirable to provide more interactions between the different levels this model proposes, even though such an approach would also require a longitudinal study design. In contrast, our research can provide insights into different dimensions influencing a STEM-LPF student's self-concept.

Implications

The results of the study provide important aspects for science education. Even though the students participating in the study almost certainly had good grades in STEM, stereotypes still corrupted their self-concept. One of the reasons for this might lie in stereotypes that attribute achievements of girls to diligence instead of talent (see Kessels, 2015 ). STEM subjects, particularly these with a low proportion of females, are stereotyped as requiring an extremely high level of talent to succeed. Good grades, although they are seen as a prerequisite for a STEM-LPF course of study (see Ihsen, 2009 ), are not sufficient to support a self-concept necessary for females to choose STEM-LPF subjects. This means that even students with good grades need support in developing efficient attributes for success ( Ziegler, 2002 ; Dresel et al., 2007 ). This may be implemented e.g., via support for a student's decision about what to study (see Ertl et al., 2014 ). This kind of support provides the implicit attribution pattern that a female student is “gifted enough” to study a male-associated STEM subject (see Dresel et al., 2007 ) and could thereby be seen as a specific method for strengthening an individual's self-concept. It can also be seen from a systemic point of view as an example of appropriate role modeling when it opens perspectives for identification with a subject or with a professional within a subject (see Hannover and Kessels, 2004 ).

A further aspect relates to interests at school. These may positively influence students' self-concepts and career choices if they have the chance to recognize a STEM subject as their favorite. This stresses the need for gender-sensitive teaching and a careful attention to gender-specific group processes in the classroom (see Ertl, 2010 ). Didactic measures that incite interest are, for example, hands-on activities that are oriented toward the students (see Paechter et al., 2006 ), or research clubs that allow students to obtain actual experiences about STEM-LPF professions (see Prenzel et al., 2009 ). The results of the last PISA studies confirm these results and assumptions while pointing out the necessity to overcome gender gaps and support females' interest in STEM subjects ( OECD, 2016 ).

Direct support, particularly by parents, had a negative impact in the present study. This result suggests that activities that are meant to support students directly may achieve the opposite effect and transport stereotypes instead (see e.g., Tiedemann, 2000 ). This stresses the need for indirect support during socialization, e.g., by providing opportunities for children to have positive experiences ( Sonnert, 2009 ) or by giving them the chance to meet role models who are enthusiastic about their STEM professions (see e.g., Mok and Ertl, 2011 ). One particular aspect of this may lie in the provision of mentoring programs (see Stein, 2013 ) that allow students to accompany their mentors over a longer period of time.

Ethics Statement

The study was performed in accordance with the 1964 Declaration of Helsinki and the American Psychological Association's Ethics Code. Review and approval was not required for this study in accordance with the national and institutional requirements. Participants gave consent to participate in the study at the beginning of the qualitative interviews and by submitting the online questionnaire for the quantitative study.

Author Contributions

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

Parts of this paper were funded by the EU (LLP-Program, Project SESTEM 505437-llp-2009-GR-KA1-KA1SCR).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Particular acknowledgments to Ms. Sog Yee Mok for her support in implementing this study.

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Keywords: female STEM students, impacts, self-concept, stereotypes, support

Citation: Ertl B, Luttenberger S and Paechter M (2017) The Impact of Gender Stereotypes on the Self-Concept of Female Students in STEM Subjects with an Under-Representation of Females. Front. Psychol . 8:703. doi: 10.3389/fpsyg.2017.00703

Received: 11 January 2017; Accepted: 21 April 2017; Published: 17 May 2017.

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Copyright © 2017 Ertl, Luttenberger and Paechter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Bernhard Ertl, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Research Article

Twenty Years of Stereotype Threat Research: A Review of Psychological Mediators

* E-mail: [email protected]

Affiliation Department of Psychology, Edge Hill University, Ormskirk, Lancashire, England, United Kingdom

• Charlotte R. Pennington, 
• Derek Heim, 
• Andrew R. Levy, 
• Derek T. Larkin

• Published: January 11, 2016
• https://doi.org/10.1371/journal.pone.0146487
• Reader Comments

This systematic literature review appraises critically the mediating variables of stereotype threat. A bibliographic search was conducted across electronic databases between 1995 and 2015. The search identified 45 experiments from 38 articles and 17 unique proposed mediators that were categorized into affective/subjective ( n = 6), cognitive ( n = 7) and motivational mechanisms ( n = 4). Empirical support was accrued for mediators such as anxiety, negative thinking, and mind-wandering, which are suggested to co-opt working memory resources under stereotype threat. Other research points to the assertion that stereotype threatened individuals may be motivated to disconfirm negative stereotypes, which can have a paradoxical effect of hampering performance. However, stereotype threat appears to affect diverse social groups in different ways, with no one mediator providing unequivocal empirical support. Underpinned by the multi-threat framework, the discussion postulates that different forms of stereotype threat may be mediated by distinct mechanisms.

Citation: Pennington CR, Heim D, Levy AR, Larkin DT (2016) Twenty Years of Stereotype Threat Research: A Review of Psychological Mediators. PLoS ONE 11(1): e0146487. https://doi.org/10.1371/journal.pone.0146487

Editor: Marina A. Pavlova, University of Tuebingen Medical School, GERMANY

Received: June 23, 2015; Accepted: December 17, 2015; Published: January 11, 2016

Copyright: © 2016 Pennington et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors acknowledge support toward open access publishing by the Graduate School and the Department of Psychology at Edge Hill University. The funders had no role in the systematic review, data collection or analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The present review examines the mediators of stereotype threat that have been proposed over the past two decades. It appraises critically the underlying mechanisms of stereotype threat as a function of the type of threat primed, the population studied, and the measures utilized to examine mediation and performance outcomes. Here, we propose that one reason that has precluded studies from finding firm evidence of mediation is the appreciation of distinct forms of stereotype threat.

Stereotype Threat: An Overview

Over the past two decades, stereotype threat has become one of the most widely researched topics in social psychology [ 1 , 2 ]. Reaching its 20 th anniversary, Steele and Aronson’s [ 3 ] original article has gathered approximately 5,000 citations and has been referred to as a 'modern classic' [ 4 , 5 , 6 ]. In stark contrast to theories of genetic intelligence [ 7 , 8 ] (and see [ 9 ] for debate), the theory of stereotype threat posits that stigmatized group members may underperform on diagnostic tests of ability through concerns about confirming a negative societal stereotype as self-characteristic [ 3 ]. Steele and Aronson [ 3 ] demonstrated that African American participants underperformed on a verbal reasoning test when it was presented as a diagnostic indicator of intellectual ability. Conversely, when the same test was presented as non-diagnostic of ability, they performed equivalently to their Caucasian peers. This seminal research indicates that the mere salience of negative societal stereotypes, which may magnify over time, can impede performance. The theory of stereotype threat therefore offers a situational explanation for the ongoing and intractable debate regarding the source of group differences in academic aptitude [ 1 ].

Stereotype threat has been used primarily to explain gaps in intellectual and quantitative test scores between African and European Americans [ 3 , 10 ] and women and men respectively [ 11 ]. However, it is important to acknowledge that many factors shape academic performance, and stereotype threat is unlikely to be the sole explanation for academic achievement gaps [ 12 ]. This is supported by research which has shown “pure” stereotype threat effects on a task in which a gender-achievement gap has not been previously documented [ 13 ], thus suggesting that performance decrements can be elicited simply by reference to a negative stereotype. Furthermore, stereotype threat effects may not be limited to social groups who routinely face stigmatizing attitudes. Rather, it can befall anyone who is a member of a group to which a negative stereotype applies [ 3 ]. For example, research indicates that Caucasian men, a group that have a relatively positive social status, underperform when they believe that their mathematical performance will be compared to that of Asian men [ 14 ]. White men also appear to perform worse than black men when motor tasks are related to 'natural athletic ability' [ 15 , 16 ]. From a theoretical standpoint, stereotype threat exposes how group stereotypes may shape the behavior of individuals in a way that endangers their performance and further reinforces the stereotype [ 10 ].

Over 300 experiments have illustrated the deleterious and extensive effects that stereotype threat can inflict on many different populations [ 17 ]. The possibility of confirming a negative stereotype about one’s group is found to contribute to underperformance on a range of diverse tasks including intelligence [ 3 , 13 ], memory [ 18 , 19 ], mental rotation [ 20 – 23 ], and math tests [ 11 , 24 , 25 ], golf putting [ 26 ], driving [ 27 , 28 ] and childcare skills [ 29 ]. Given the generality of these findings, researchers have turned their efforts to elucidating the underlying mechanisms of this situational phenomenon.

Susceptibility to Stereotype Threat

Research has identified numerous moderators that make tasks more likely to elicit stereotype threat, and individuals more prone to experience it [ 30 , 31 ]. From a methodological perspective, stereotype threat effects tend to emerge on tasks of high difficulty and demand [ 32 , 33 ], however, the extent to which a task is perceived as demanding may be moderated by individual differences in working memory [ 34 ]. Additionally, stereotype threat may be more likely to occur when individuals are conscious of the stigma ascribed to their social group [ 32 , 35 ], believe the stereotypes about their group to be true [ 36 , 37 ], for those with low self-esteem [ 38 ], and an internal locus of control [ 39 ]. Research also indicates that individuals are more susceptible to stereotype threat when they identify strongly with their social group [ 40 , 41 , 42 ] and value the domain [ 10 , 13 , 15 , 33 , 43 ]. However, other research suggests that domain identification is not a prerequisite of stereotype threat effects [ 44 ] and may act as a strategy to overcome harmful academic consequences [ 45 , 46 ].

Mediators of Stereotype Threat

There has also been an exPLOSion of research into the psychological mediators of stereotype threat (c.f. [ 2 , 47 ] for reviews). In their comprehensive review, Schmader et al. [ 2 ] proposed an integrated process model, suggesting that stereotype threat heightens physiological stress responses and influences monitoring and suppression processes to deplete working memory efficiency. This provides an important contribution to the literature, signaling that multiple affective, cognitive and motivational processes may underpin the effects of stereotype threat on performance. However, the extent to which each of these variables has garnered empirical support remains unclear. Furthermore, prior research has overlooked the existence of distinct stereotype threats in the elucidation of mediating variables. Through the lens of the multi-threat framework [ 31 ], the current review distinguishes between different stereotype threat primes, which target either the self or the social group to assess the evidence base with regards to the existence of multiple stereotype threats that may be accounted for by distinct mechanisms.

A Multi-threat Approach to Mediation

Stereotype threat is typically viewed as a form of social identity threat: A situational predicament occurring when individuals perceive their social group to be devalued by others [ 48 , 49 , 50 ]. However, this notion overlooks how individuals may self-stigmatize and evaluate themselves [ 51 , 52 , 53 ] and the conflict people may experience between their personal and social identities [ 54 ]. More recently, researchers have distinguished between the role of the self and the social group in performance-evaluative situations [ 31 ]. The multi-threat framework [ 31 ] identifies six qualitatively distinct stereotype threats that manifest through the intersection of two dimensions: The target of the threat (i.e., is the stereotype applicable to one’s personal or social identity?) and the source of threat (i.e., who will judge performance; the in-group or the out-group?). Focusing on the target of the stereotype, individuals who experience a group-as-target threat may perceive that underperformance will confirm a negative societal stereotype regarding the abilities of their social group. Conversely, individuals who experience a self-as-target threat may perceive that stereotype-consistent performance will be viewed as self-characteristic [ 31 , 55 ]. Individuals may therefore experience either a self or group-based threat dependent on situational cues in the environment that heighten the contingency of a stereotyped identity [ 2 ].

Researchers also theorize that members of diverse stigmatized groups may experience different forms of stereotype threat [ 31 , 56 ], and that these distinct experiences may be mediated by somewhat different processes [ 31 , 57 ]. Indeed, there is some indirect empirical evidence to suggest that this may be the case. For example, Pavlova and colleagues [ 13 ] found that an implicit stereotype threat prime hampered women’s performance on a social cognition task. Conversely, men’s performance suffered when they were primed with an explicit gender-related stereotype. Moreover, Stone and McWhinnie [ 58 ] suggest that subtle stereotype threat cues (i.e., the gender of the experimenter) may evoke a tendency to actively monitor performance and avoid mistakes, whereas blatant stereotype threat cues (i.e., stereotype prime) create distractions that deplete working memory resources. Whilst different stereotype threat cues may simultaneously exert negative effects on performance, it is plausible that they are induced by independent mechanisms [ 58 ]. Nonetheless, insufficient evidence has prevented the multi-threat framework [ 31 ] to be evaluated empirically to date. It therefore remains to be assessed whether the same mechanisms are responsible for the effects of distinct stereotype threats on different populations and performance measures.

The current article offers the first systematic literature review aiming to: 1), identify and examine critically the proposed mediators of stereotype threat; 2), explore whether the effects of self-as-target or group-as-target stereotype threat on performance are the result of qualitatively distinct mediating mechanisms; and 3), evaluate whether different mediators govern different stereotyped populations.

Literature Search

A bibliographic search of electronic databases, such as PsycINFO, PsycARTICLES, Web of Knowledge, PubMed, Science Direct and Google Scholar was conducted between the cut-off dates of 1995 (the publication year of Steele & Aronson’s seminal article) and December 2015. A search string was developed by specifying the main terms of the phenomenon under investigation. Here, the combined key words of stereotype and threat were utilized as overarching search parameters and directly paired with either one of the following terms; mediator , mediating , mediate(s) , predictor , predicts , relationship or mechanism(s) . Additional references were retrieved by reviewing the reference lists of relevant journal articles. To control for potential publication bias [ 59 , 60 , 61 ], the lead author also enquired about any ‘in press’ articles by sending out a call for papers through the European Association for Social Psychology. The second author conducted a comparable search using the same criteria to ensure that no studies were overlooked in the original search. Identification of relevant articles and data extraction were conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement (PRISMA; See S1 Table ) [ 62 ]. A literature search was conducted separately in each database and the records were exported to citation software, after which duplicates were removed. Relevant articles were screened by examining the title and abstract in line with the eligibility criteria. The remaining articles were assessed for eligibility by performing a full text review [ 63 , 64 ].

Eligibility Criteria.

Studies were selected based on the following criteria: 1), researchers utilized a stereotype threat manipulation; 2), a direct mediation analysis was conducted between stereotype threat and performance; 3), researchers found evidence of moderated-mediation, and 4), the full text was available in English. Articles were excluded on the following basis: 1), performance was not the dependent variable, 2), investigations of “stereotype lift”; 3), doctorate, dissertation and review articles (to avoid duplication of included articles); and 4), moderating variables. Articles that did not find any significant results in relation to stereotype threat effects were also excluded in order to capture reliable evidence of mediation [ 65 ]. See Table 1 for details of excluded articles.

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https://doi.org/10.1371/journal.pone.0146487.t001

Distinguishing Different Stereotype Threats.

The current review distinguished between different experiences of stereotype threat by examining each stereotype threat manipulation. Self-as-target threats were categorized on the basis that participants focused on the test as a measure of personal ability whereas group-as-target threats were classified on the basis that participants perceived performance to be diagnostic of their group’s ability [ 31 ].

A total of 45 studies in 38 articles were qualitatively synthesized, uncovering a total of 17 distinct proposed mediators. See Fig 1 for process of article inclusion (full details of article exclusion can be viewed in S1 Supporting Information ). These mediators were categorized into affective/subjective ( n = 6), cognitive ( n = 7) or motivational mechanisms ( n = 4). Effect sizes for mediational findings are described typically through informal descriptors, such as complete , perfect , or partial [ 66 ]. With this in mind, the current findings are reported in terms of complete or partial mediation. Complete mediation indicates that the relationship between stereotype threat ( X ) and performance ( Y ) completely disappears when a mediator ( M ) is added as a predictor variable [ 66 ]. Partial mediation refers to instances in which a significant direct effect remains between stereotype threat and performance when controlling for the mediator, suggesting that additional variables may further explain this relationship [ 67 ]. Instances of moderated mediation are also reported, which occurs when the strength of mediation is contingent on the level of a moderating variable [ 68 ]. The majority of included research utilized a group-as-target prime ( n = 36, 80%) compared to a self-as-target prime ( n = 6; 13.33%). Three studies (6.66%) were uncategorized as they employed subtle stereotype threat primes, for example, manipulating the group composition of the testing environment.

https://doi.org/10.1371/journal.pone.0146487.g001

Affective/Subjective Mechanisms

Researchers have conceptualized stereotype threat frequently as a fear, apprehension or anxiety of confirming a negative stereotype about one’s group [ 3 , 69 , 70 ]. Accordingly, many affective and subjective variables such as anxiety, individuation tendencies, evaluation apprehension, performance expectations, explicit stereotype endorsement and self-efficacy have been proposed to account for the stereotype threat-performance relationship.

Steele and Aronson’s [ 3 ] original study did not find self-reported anxiety to be a significant mediator of the effects of a self-relevant stereotype on African American’s intellectual performance. Extending this work, Spencer et al. (Experiment 3, [ 11 ]) found that anxiety was not predictive of the effects that a negative group stereotype had on women’s mathematical achievement, with further research confirming this [ 14 , 44 , 71 ]. Additional studies have indicated that self-reported anxiety does not influence the impact of self-as-target stereotype elicitation on African American’s cognitive ability [ 72 ], white students’ athletic skills [ 15 ], and group-as-target stereotype threat on older adults’ memory recall [ 18 , 32 ].

Research also suggests that anxiety may account for one of multiple mediators in the stereotype threat-performance relationship. In a field study, Chung and colleagues [ 73 ] found that self-reported state anxiety and specific self-efficacy sequentially mediated the influence of stereotype threat on African American’s promotional exam performance. This finding is supported by Mrazek et al. [ 74 ] who found that anxiety and mind-wandering sequentially mediated the effects of stereotype threat on women’s mathematical ability. Laurin [ 75 ] also found that self-reported somatic anxiety partially mediated the effects of group-as-target stereotype threat on women’s motor performance. Nevertheless, it is viable to question whether this finding is comparable to other studies as stereotype threat had a facilitating effect on performance.

The mixed results regarding anxiety as a potential mediator of performance outcomes may be indicative of various boundary conditions that enhance stereotype threat susceptibility. Consistent with this claim, Gerstenberg, Imhoff and Schmitt (Experiment 3 [ 76 ]) found that women who reported a fragile math self-concept solved fewer math problems under group-as-target stereotype threat and this susceptibility was mediated by increased anxiety. This moderated-mediation suggests that women with a low academic self-concept may be more vulnerable to stereotype threat, with anxiety underpinning its effect on mathematical performance.

Given that anxiety may be relatively difficult to detect via self-report measures [ 3 , 29 ], researchers have utilized indirect measures. For instance, Bosson et al. [ 29 ] found that physiological anxiety mediated the effects of stereotype threat on homosexual males’ performance on an interpersonal task. Nevertheless, this effect has not been replicated for the effects of group-as-target stereotype threat on older adults’ memory recall [ 32 ] and self-as-target threat on children’s writing ability [ 77 ].

Individuation tendencies.

Steele and Aronson [ 3 ] proposed that stereotype threat might occur when individuals perceive a negative societal stereotype to be a true representation of personal ability. Based on this, Keller and Sekaquaptewa [ 78 ] examined whether gender-related threats (i.e., group-as-target threat) influenced women to individuate their personal identity (the self) from their social identity (female). Results revealed that participants underperformed on a spatial ability test when they perceived that they were a single in-group representative (female) in a group of males. Moreover, stereotype threat was partially mediated by ‘individuation tendencies’ in that gender-based threats influenced women to disassociate their self from the group to lessen the applicability of the stereotype. The authors suggest that this increased level of self-focused attention under solo status conditions is likely related to increased levels of anxiety.

Evaluation apprehension.

Steele and Aronson [ 3 ] also suggested that individuals might apprehend that they will confirm a negative stereotype in the eyes of out-group members. Despite this, Mayer and Hanges [ 72 ] found that evaluation apprehension did not mediate the effects of a self-as-target stereotype threat on African American’s cognitive ability. Additional studies also indicate that evaluation apprehension does not mediate the effects of group-as-target stereotype threat on women’s mathematical performance [ 11 , 79 ].

Performance expectations.

Under stereotype threat, individuals may evaluate the subjective likelihood of success depending on their personal resources. As these personal resources are typically anchored to group-level expectations, in-group threatening information (i.e., women are poor at math) may reduce personal expectancies to achieve and diminish performance [ 80 ]. Testing this prediction, Cadinu et al. (Experiment 1 [ 80 ]) found that women solved fewer math problems when they were primed with a negative group-based stereotype relative to those who received a positive or no stereotype. Furthermore, performance expectancies partially mediated the effect of group-as-target threat on math performance, revealing that negative information was associated with lower expectancies. A second experiment indicated further that performance expectancies partially mediated the effects of group-as-target threat on Black participants’ verbal ability. Research by Rosenthal, Crisp and Mein-Woei (Experiment 2 [ 81 ]) also found that performance expectancies partially mediated the effects of self-based stereotypes on women’s mathematical performance. However, rather than decreasing performance expectancies, women under stereotype threat reported higher predictions for performance relative to a control condition.

Research has extended this work to examine the role of performance expectancies in diverse stigmatized populations. For example, Hess et al. [ 32 ] found evidence of moderated-mediation for the effects of a group-as-target stereotype threat on older adults’ memory recall. Here, the degree to which performance expectancies mediated stereotype threat effects was moderated by participants’ education. That is, elderly individuals with higher levels of education showed greater susceptibility to stereotype threat. These findings add weight to the assertion that lowered performance expectations may account for the effects of stereotype threat on performance, especially among individuals who identify strongly with the ability domain. Conversely, Appel et al. [ 43 ] found that performance expectancies do not mediate the effects of group-based stereotype threat among highly identified women in the domains of science, technology, engineering and mathematics.

Further research suggests that stereotype threat can be activated through subtle cues in the environment rather than explicit stereotype activation [ 58 , 82 ]. It is therefore plausible that expectancies regarding performance may be further undermined when stigmatized in-group members are required to perform a stereotype-relevant task in front of out-group members. Advancing this suggestion, Sekaquaptewa and Thompson [ 82 ] examined the interactive effects of solo status and stereotype threat on women’s mathematical performance. Results revealed that women underperformed when they completed a quantitative examination in the presence of men (solo status) and under stereotype threat. However, whilst performance expectancies partially mediated the relationship between group composition and mathematical ability, they did not mediate the effects of stereotype threat on performance.

Explicit stereotype endorsement.

Research has examined whether targeted individuals’ personal endorsement of negative stereotypes is associated with underperformance. For example, Leyens and colleagues [ 83 ] found that men underperformed on an affective task when they were told that they were not as apt as women in processing affective information. Against predictions, however, stereotype endorsement was not found to be a significant intermediary between stereotype threat and performance. Other studies also indicate that stereotype endorsement is not an underlying mechanism of the effects of self-as-target [ 3 ] and group-as-target stereotype threat on women’s mathematical aptitude [ 11 , 84 ].

Self-efficacy.

Research suggests that self-efficacy can have a significant impact on an individual’s motivation and performance [ 85 , 86 , 87 ], and may be influenced by environmental cues [ 88 ]. Accordingly, it has been proposed that the situational salience of a negative stereotype may reduce an individual’s self-efficacy. As mentioned, Chung et al. [ 73 ] found that state anxiety and specific self-efficacy accounted for deficits in African American’s performance on a job promotion exam. However, additional studies indicate that self-efficacy does not mediate the effects of self-as-target threat on African American’s cognitive ability [ 72 ] and group-as-target threat on women’s mathematical performance [ 11 ].

Cognitive Mechanisms

Much research has proposed that affective and subjective variables underpin the harmful effects that stereotype threat exerts on performance [ 89 ]. However, other research posits that stereotype threat may influence performance detriments through its demands on cognitive processes [ 2 , 89 , 90 ]. Specifically, researchers have examined whether stereotype threat is mediated by; working memory, cognitive load, thought suppression, mind-wandering, negative thinking, cognitive appraisals and implicit stereotype endorsement.

Working memory.

Schmader and Johns [ 89 ] proposed that performance-evaluative situations might reduce working memory capacity as stereotype-related thoughts consume cognitive resources. In three studies, they examined whether working memory accounted for the influence of a group-as-target threat on women’s and Latino American’s mathematical ability. Findings indicated that both female and Latino American participants solved fewer mathematical problems compared to participants in a non-threat control condition. Furthermore, reduced working memory capacity, measured via an operation span task [ 91 ], mediated the deleterious effects of stereotype threat on math performance. Supporting this, Rydell et al. (Experiment 3 [ 92 ]) found that working memory mediated the effects of a group-relevant stereotype on women’s mathematical performance when they perceived their performance to be evaluated in line with their gender identity. Here results also showed that these performance decrements were eliminated when women were concurrently primed with a positive and negative social identity (Experiment 2).

Further research has also examined how stereotype threat may simultaneously operate through cognitive and emotional processes. Across four experiments, Johns et al. [ 90 ] found that stereotype threat was accountable for deficits in women’s verbal, intellectual and mathematical ability. Moreover, emotion regulation − characterized as response-focused coping − mediated the effects of group-as-target stereotype threat on performance by depleting executive resources.

Nonetheless, executive functioning is made up of more cognitive processes than the construct of working memory [ 93 ]. Acknowledging this, Rydell et al. [ 93 ] predicted that updating (i.e., the ability to maintain and update information in the face of interference) would mediate stereotype threat effects. They further hypothesized that inhibition (i.e., the ability to inhibit a dominant response) and shifting (i.e., people’s ability to switch between tasks) should not underpin this effect. Results indicated that women who experienced an explicit group-as-target threat displayed reduced mathematical performance compared to a control condition. Consistent with predictions, only updating mediated the stereotype threat-performance relationship. These results suggest that the verbal ruminations associated with a negative stereotype may interfere with women’s ability to maintain and update the calculations needed to solve difficult math problems.

The extent to which updating accounts for stereotype threat effects in diverse populations, however, is less straightforward. For example, Hess et al. [ 32 ] found that working memory, measured by a computational span task, did not predict the relationship between group-based stereotype threat and older participants’ memory performance.

Cognitive load.

There is ample evidence to suggest that stereotype threat depletes performance by placing higher demands on mental resources [ 89 , 93 ]. These demands may exert additional peripheral activity (i.e., emotional regulation) that can further interfere with task performance [ 90 ]. In order to provide additional support for this notion, Croizet et al. [ 94 ] examined whether increased mental load, measured by participants’ heart rate, mediated the effects of stereotype threat on Psychology majors’ cognitive ability. Here, Psychology majors were primed that they had lower intelligence compared to Science majors. Results indicated that this group-as-target stereotype threat undermined Psychology majors’ cognitive ability by triggering a psychophysiological mental load. Moreover, this increased mental load mediated the effects of stereotype threat on cognitive performance.

Thought suppression.

Research suggests that individuals who experience stereotype threat may be aware that their performance will be evaluated in terms of a negative stereotype and, resultantly, engage in efforts to disprove it [ 3 , 94 , 95 ]. This combination of awareness and avoidance may lead to attempts to suppress negative thoughts that consequently tax the cognitive resources needed to perform effectively. In four experiments, Logel et al. (Experiment 2 [ 95 ]) examined whether stereotype threat influences stereotypical thought suppression by counterbalancing whether participants completed a stereotype-relevant lexical decision task before or after a mathematical test. Results indicated that women underperformed on the test in comparison to men. Interestingly, women tended to suppress stereotypical words when the lexical decision task was administered before the math test, but showed post-suppression rebound of stereotype-relevant words when this task was completed afterwards. Mediational analyses revealed that only pre-test thought suppression partially mediated the effects of stereotype threat on performance.

Mind-wandering.

Previous research suggests that the anticipation of a stereotype-laden test may produce a greater proportion of task-related thoughts and worries [ 93 , 95 ]. Less research has examined the role of thoughts unrelated to the task in hand as a potential mediator of stereotype threat effects. Directly testing this notion, Mrazek et al. (Experiment 2 [ 74 ]) found that a group-as-target stereotype threat hampered women’s mathematical performance in comparison to a control condition. Furthermore, although self-report measures of mind-wandering resulted in null findings, indirect measures revealed that women under stereotype threat showed a marked decrease in attention. Mediation analyses indicated further that stereotype threat heightened anxiety which, in turn, increased mind-wandering and contributed to the observed impairments in math performance. Despite these findings, other studies have found no indication that task irrelevant thoughts mediate the effects of group-as-target stereotype threat on women’s mathematical performance [ 24 ] and African American participants’ cognitive ability [ 72 ].

Negative thinking.

Schmader and Johns’ [ 89 ] research suggests that the performance deficits observed under stereotype threat may be influenced by intrusive thoughts. Further research [ 74 ] has included post-experimental measures of cognitive interference to assess the activation of distracting thoughts under stereotype threat. However, the content of these measures are predetermined by the experimenter and do not allow participants to report spontaneously on their experiences under stereotype threat. Overcoming these issues, Cadinu and colleagues [ 96 ] asked women to list their current thoughts whilst taking a difficult math test under conditions of stereotype threat. Results revealed that female participants underperformed when they perceived a mathematical test to be diagnostic of gender differences. Moreover, participants in the stereotype threat condition listed more negative thoughts relative to those in the control condition, with intrusive thoughts mediating the relationship between stereotype threat and poor math performance. It seems therefore that negative performance-related thoughts may consume working memory resources to impede performance.

Cognitive appraisal.

Other research suggests that individuals may engage in coping strategies to offset the performance implications of a negative stereotype. One indicator of coping is cognitive appraisal, whereby individuals evaluate the significance of a situation as well as their ability to control it [ 97 ]. Here, individuals may exert more effort on a task when the situational presents as a challenge, but may disengage from the task if they evaluate the situation as a threat [ 98 , 99 ]. Taking this into consideration, Berjot, Roland-Levy and Girault-Lidvan [ 100 ] proposed that targeted members might be more likely to perceive a negative stereotype as a threat to their group identity rather than as a challenge to disprove it. They found that North African secondary school students underperformed on a visuospatial task when they perceived French students to possess superior perceptual-motor skills. Contrary to predictions, threat appraisal did not mediate the relation between stereotype threat and performance. Rather, perceiving the situation as a challenge significantly mediated the stereotype threat-performance relationship. Specifically, participants who appraised stereotype threat as a challenge performed better than those who did not. These results therefore suggest that individuals may strive to confront, rather than avoid, intellectual challenges and modify the stereotype held by members of a relevant out-group in a favorable direction [ 101 ].

Implicit stereotype endorsement.

Situational cues that present as a threat may increase the activation of automatic associations between a stereotyped concept (i.e., female), negative attributes (i.e., bad), and the performance domain (i.e., math; [ 102 ]). Implicit measures may be able to detect recently formed automatic associations between concepts and stereotypical attributes that are not yet available to explicitly self-report [ 103 ]. In a study of 240 six-year old children, Galdi et al. [ 103 ] examined whether implicit stereotype threat endorsement accounted for the effects of stereotype threat on girls’ mathematical performance. Consistent with the notion that automatic associations can precede conscious beliefs, results indicated that girls acquire implicit math-gender stereotypes before they emerge at an explicit level. Specifically, girls showed stereotype-consistent automatic associations between the terms ‘boy-mathematics’ and ‘girl-language’, which mediated stereotype threat effects.

Motivational Mechanisms

Most of the initial work on the underlying mechanisms of stereotype threat has focused on affective and cognitive processes. More recently, research has begun to examine whether individuals may be motivated to disconfirm a negative stereotype, with this having a paradoxical effect of harming performance [ 104 , 105 , 106 ]. To this end, research has elucidated the potential role of effort, self-handicapping, dejection, vigilance, and achievement goals.

Effort/motivation.

Underpinned by the “mere effort model” [ 104 ], Jamieson and Harkins [ 105 ] examined whether motivation plays a proximal role in the effect of stereotype threat on women’s math performance. Here they predicted that stereotype threat would lead participants to use a conventional problem solving approach (i.e., use known equations to compute an answer), which would facilitate performance on ‘solve’ problems, but hamper performance on ‘comparison’ problems. Results supported this hypothesis, indicating that stereotype threat debilitated performance on comparison problems as participants employed the dominant, but incorrect, solution approach. Furthermore, this incorrect solving approach mediated the effect of stereotype threat on comparison problem performance. This suggests that stereotype threat motivates participants to perform well, which increases activation of a dominant response to the task. However, as this dominant approach does not always guarantee success, the work indicates that different problem solving strategies may determine whether a person underperforms on a given task [ 105 , 107 ].

Stereotype threat may have differential effects on effort dependent on the prime utilized [ 27 ]. For example, Skorich et al. [ 27 ] examined whether effort mediated the effects of implicit and explicit stereotypes on provisional drivers’ performance on a hazard perception test. Participants in the implicit prime condition ticked their driving status (provisional, licensed) on a questionnaire, whereas participants in the explicit prime condition were provided with stereotypes relating to the driving ability of provisional licensees. Results revealed that participants detected more hazards when they were primed with an explicit stereotype relative to an implicit stereotype. Mediational analyses showed that whilst increased effort mediated the effects of an implicit stereotype on performance, decreased effort mediated the effects of an explicit stereotype prime. Research also indicates that reduced effort mediates the effects of an explicit stereotype on older adults’ memory recall [ 18 ]. Taken together, these results suggest that implicit stereotype primes may lead to increased effort as participants aim to disprove the stereotype, whereas explicit stereotype threat primes may lead to decreased effort as participants self-handicap [ 27 ]. Nevertheless, other studies utilizing self-reported measures of effort have resulted in non-significant findings (Experiment 1 & 2 [ 14 ]; Experiment 4 [ 44 ]; Experiment 2 [ 77 ]; Experiment 2, 4 & 5, [ 108 ]).

Self-handicapping.

Individuals may engage in self-handicapping strategies to proactively reduce the applicability of a negative stereotype to their performance. Here, people attempt to influence attributions for performance by erecting barriers to their success. Investigating this notion, Stone [ 15 ] examined whether self-handicapping mediated the effects of stereotype threat on white athletes’ sporting performance. Self-handicapping was measured by the total amount of stereotype-relevant words completed on a word-fragment task. Results indicated that white athletes practiced less when they perceived their ability on a golf-putting task to be diagnostic of personal ability, thereby confirming a negative stereotype relating to ‘poor white athleticism’. Moreover, these athletes were more likely to complete the term ‘awkward’ on a word fragment completion test compared to the control condition. Mediation analyses revealed that the greater accessibility of the term ‘awkward’ partially mediated the effects of stereotype threat on psychological disengagement and performance. The authors suggest that stereotype threat increased the accessibility of thoughts related to poor athleticism to inhibit athletes' practice efforts. However, a limitation of this research is that analyses were based on single-item measures (i.e., the completion of the word ‘awkward’) rather than total of completed words on the word-fragment test.

Keller [ 109 ] also tested the hypothesis that the salience of a negative stereotype is related to self-handicapping tendencies. Results showed that women who were primed with a group-as-target stereotype underperformed on a mathematical test relative to their control group counterparts. Furthermore, they expressed stronger tendencies to search for external explanations for their weak performance with this mediating the effects of stereotype threat on performance. Despite these preliminary findings, Keller and Dauenheimer [ 44 ] were unable to provide support for the notion that self-reported self-handicapping is a significant intermediary between stereotype threat and women’s mathematical underperformance.

Research on performance expectations suggests that stereotype threat effects may be mediated by goals set by the participants. Extending this work, Keller and Dauenheimer [ 44 ] hypothesized that female participants may make more errors on a mathematical test due to an overly motivated approach strategy. Results indicated that women underperformed when a math test was framed as diagnostic of gender differences (a group-as-target threat). Furthermore, their experiences of dejection were found to mediate the relation between stereotype threat and performance. The authors suggest that individuals may be motivated to disconfirm the negative stereotype and thus engage in a promotion focus of self-regulation. However, feelings of failure may elicit an emotional response that resultantly determines underperformance.

In contrast to Keller and Dauenheimer [ 44 ], Seibt and Förster (Experiment 5; [ 108 ]) proposed that under stereotype threat, targeted individuals engage in avoidance and vigilance strategies. They predicted that positive stereotypes should induce a promotion focus, leading to explorative and creative processing, whereas negative stereotypes should induce a prevention focus state of vigilance, with participants avoiding errors. Across five experiments, male and female participants were primed with a group-as-target stereotype suggesting that women have better verbal abilities than men. However, rather than showing a stereotype threat effect, results indicated a speed-accuracy trade off with male participants completing an analytical task slower but more accurately than their counterparts in a non-threat control condition. Furthermore, this prevention focus of vigilance was found to partially mediate the effects of stereotype threat on men’s analytical abilities (Experiment 5). The authors conclude that the salience of a negative group stereotype elicits a vigilant, risk-averse processing style that diminishes creativity and speed while bolstering analytic thinking and accuracy.

Achievement goals.

Achievement goals theory [ 110 ] posits that participants will evaluate their role in a particular achievement context and endorse either performance-focused or performance-avoidance goals. In situations where the chances of success are low, individuals engage in performance-avoidance goals, corresponding to a desire to avoid confirming a negative stereotype. Accordingly, Chalabaev et al. [ 111 ] examined whether performance avoidance goals mediated the effects of stereotype threat on women’s sporting performance. Here, the impact of two self-as-target stereotypes (i.e., poor athletic and soccer ability) on performance were assessed relative to a control condition. Results indicated that women in the athletic ability condition performed more poorly on a dribbling task, but not in the soccer ability condition. Furthermore, although these participants endorsed a performance-avoidance goal, this did not mediate the relationship between stereotype threat and soccer performance.

Highlighting the possible interplay between affective, cognitive and motivation mechanisms, Brodish and Devine [ 112 ] proffered a multi-mediator model, proposing that anxiety and performance-avoidance goals may mediate the effects of group-as-target stereotype threat on women’s mathematical performance. Achievement goals were measured by whether participants endorsed performance-avoidant (the desire to avoid performing poorly) or approach goals (trying to outperform others). Results indicated that women under stereotype threat solved fewer mathematical problems relative to those in a control condition. Mediation analyses revealed that performance avoidance goals and anxiety sequentially mediated women’s mathematical performance. That is, stereotype threatened women were motivated to avoid failure, which in turn heightened anxiety and influenced underperformance. Table 2 summarizes the articles reviewed and details their key findings and respective methodologies. See S2 Table for overview of significant mediational findings.

https://doi.org/10.1371/journal.pone.0146487.t002

The current review evaluated empirical support for the mediators of stereotype threat. Capitalizing on the multi-threat framework [ 31 ], we distinguished between self-relevant and group-relevant stereotype threats to examine the extent to which these are mediated by qualitatively distinct mechanisms and imperil diverse stigmatized populations. On the whole, the results of the current review indicate that experiences of stereotype threat may increase individuals’ feelings of anxiety, negative thinking and mind-wandering which deplete the working memory resources required for successful task execution. Research documents further that individuals may be motivated to disconfirm the negative stereotype and engage in efforts to suppress stereotypical thoughts that are inconsistent with task goals. However, many of the mediators tested have resulted in varying degrees of empirical support. Below we suggest that stereotype threat may operate in distinct ways dependent on the population under study, the primes utilized, and the instruments used to measure mediation and performance.

Previous research has largely conceptualized stereotype threat as a singular construct, experienced similarly by individuals and groups across situations [ 31 , 55 ]. Consequently, research has overlooked the possibility of multiple forms of stereotype threats that may be implicated through concerns to an individual’s personal or social identity [ 31 ]. This is highlighted in the present review, as the majority of stereotype threat studies employed a group-as-target prime. Here stereotype threat is typically instantiated to highlight that stereotype-consistent performance may confirm, or reinforce, a negative societal stereotype as being a true representation of one’s social group [ 48 ]. This has led to a relative neglect of situations in which individuals may anticipate that their performance may be indicative of personal ability [ 31 , 55 ].

Similar processes such as arousal, deficits in working memory, and motivation may be triggered by self-as-target and group-as-target stereotype threats. However, it is important to note that the experiences of these stereotype threats may be fundamentally distinct [ 31 ]. That is, deficits in working memory under self-as-target stereotype threat may be evoked by negative thoughts relating to the self (i.e., ruining one’s opportunities, letting oneself down). Conversely, group-based intrusive thoughts may mediate the effects of group-as-target threat on performance as individuals view their performance in line with their social group (i.e., confirming a societal stereotype, letting the group down) [ 31 ]. Moreover, research suggests that when a group-based stereotype threat is primed, individuals dissociate their sense of self from the negatively stereotyped domain [ 78 ]. Yet, this may be more unlikely when an individual experiences self-as-target stereotype threat as their personal ability is explicitly tied to a negative stereotype that governs their ingroup. As such, the activation of a group-based stereotype may set in motion mechanisms that reflect a protective orientation of self-regulation, whereas self-relevant knowledge may heighten self-consciousness. To date, however, research has not explicitly distinguished between self-as-target and group-as-target stereotype threat in the elucidation of mediating variables. Future research would therefore benefit from a systematic investigation of how different stereotype threats may hamper performance in qualitatively distinguishable ways. One way to investigate the hypotheses set out here would be to allow participants to spontaneously report their experiences under self-as-target and group-as-target stereotype threat, and to examine differences in the content of participants’ thoughts as a function of these different primes.

In a similar vein, different mechanisms may mediate the effects of blatant and subtle stereotype threat effects on performance [ 27 , 58 , 111 ]. Blatant threat manipulations explicitly inform participants of a negative stereotype related to performance (e.g., [ 3 , 11 ]), whereas placing stigmatized group members in a situation in which they have minority status may evoke more subtle stereotype threat [ 78 , 82 ]. Providing evidence consistent with this notion, Sekaquaptewa and Thompson [ 82 ] found that performance expectancies partially mediated the effects of solo status, but not stereotype threat on performance. These results suggest that women may make comparative judgments about their expected performance when they are required to undertake an exam in the presence of out-group members, yet may not consciously recognize how a negative stereotype can directly impair performance. Further research suggests that working memory may mediate the effects of subtle stereotype threat cues on performance as individuals attend to situational cues that heighten the salience of a discredited identity [ 88 , 94 ]. Alternatively, motivation may mediate the effects of blatant stereotype threat as individuals strive to disprove the negative stereotype [ 27 , 44 , 58 , 108 ]. Although stereotype threat effects appear to be robust [ 30 ], it is plausible that these distinct manipulations diverge in the nature, the focus, and the intensity of threat they produce and may therefore be mediated by different mechanisms [ 31 ].

It is also conceivable that different groups are more susceptible to certain types of stereotype threat [ 13 , 31 , 56 ]. For example, research indicates that women’s performance on a social cognition task was influenced to a greater extent by implicit gender-related stereotypes, whereas men were more vulnerable to explicit stereotype threat [ 13 ]. Further research suggests that populations who tend to have low group identification (e.g., those with a mental illness or obesity) are more susceptible to self-as-target threats. Conversely, populations with high group identification, such as individuals of a certain ethnicity, gender or religion are more likely to experience group-as-target threats [ 56 ]. Whilst this highlights the role of moderating variables that heighten individuals’ susceptibility to stereotype threat, it also suggests that individuals may experience stereotype threat in different ways, dependent on their stigmatized identity. This may explain why some variables (e.g., anxiety, self-handicapping) that have been found to mediate the effects of stereotype threat on some groups have not emerged in other populations.

Finally, it is conceivable that diverse mediators account for the effects of stereotype threat on different performance outcomes. For example, although working memory is implicated in tasks that typically require controlled processing, it is not required for tasks that rely more on automatic processes [ 24 , 58 , 93 ]. In line with this notion, Beilock et al. [ 24 ] found that experts’ golf putting skills were harmed under stereotype threat when attention was allocated to automatic processes that operate usually outside of working memory. This suggests that well-learned skills may be hampered by attempts to bring performance back under step-by-step control. Conversely, skills such as difficult math problem solving appear to involve heavy processing demands and may be harmed when working memory is consumed by a negative stereotype. As such, distinct mechanisms may underpin different threat-related performance outcomes.

Limitations of Stereotype Threat Research

We now outline methodological issues in current stereotype threat literature with a view to inform the design of future research. First, researchers have predominantly utilized self-report measures in their efforts to uncover the mediating variables of stereotype threat. However, it has long been argued that individuals have limited access to higher order mental processes [ 113 , 114 ], such as those involved in the evaluation and initiation of behavior [ 115 , 116 ]. Resultantly, participants under stereotype threat may be unable to observe and explicitly report the operations of their own mind [ 29 , 114 , 117 , 118 , 119 ]. Consistent with this assertion, Bosson et al. [ 29 ] found that although stereotype threat heightened individuals’ physiological anxiety, the same individuals did not report an awareness of increased anxiety on self-report measures. Participants may thus be mindful of the impression they make on others and engage in self-presentational behaviors in an effort to appear invulnerable to negative stereotypes [ 29 ]. This is supported by research suggesting that stereotype threatened participants tend not to explicitly endorse stereotypes [ 29 , 37 , 83 , 84 ] and are more likely to claim impediments to justify poor performance [ 3 , 14 , 109 ]. Moreover, it is possible that stereotype threat processes are non-conscious [ 119 ] with research indicating that implicit–but not explicit–stereotype endorsement mediates stereotype threat effects [ 103 ]. This suggests that non-conscious processing of stereotype-relevant information may influence the decrements observed in individuals’ performance under stereotype threat. Furthermore, this research underscores the greater sensitivity of indirect measures for examining the mediators of stereotype threat. From this perspective, future research may benefit from the use of physiological measures, such as heart rate, cortisol and skin conductance to examine anxiety (c.f., [ 94 , 120 , 121 ]), the IAT to measure implicit stereotype endorsement [ 103 ] and the sustained response to attention task to measure mind-wandering [ 74 ].

In the investigation of stereotype threat, self-report measures may be particularly susceptible to order effects. For example, Brodish and Devine [ 112 ] found that women reported higher levels of anxiety when they completed a questionnaire before a mathematical test compared to afterwards. This suggests that pre-test anxiety ratings may have reflected participants’ uneasiness towards the upcoming evaluative test, with this apprehension diminishing once the test was completed. Research by Logel and colleagues [ 95 ] provides support for this notion, indicating that women who completed a lexical decision task after a math test were quicker to respond to stereotype-relevant words compared to women who subsequently completed the task. These results exhibit the variability in individuals’ emotions under stereotype threat and suggest that they may be unable to retrospectively report on their feelings once the threat has passed. This emphasizes the importance of counterbalancing test instruments in the investigation of stereotype threat, purporting that the order in which test materials are administered may influence mediational findings.

This review highlights that, in some studies, individuals assigned to a control condition may have also experienced stereotype threat, thus potentially preventing reliable evidence of mediation. For instance, Chalabaev et al. [ 111 ] primed stereotype threat by presenting a soccer ability test as a diagnostic indicator of personal factors related to athletic ability. Nevertheless, participants in the control condition received information that the aim of the test was to examine psychological factors in athletic ability. Consequently, these participants may have also been apprehensive about their performance being evaluated, and this may have precluded evidence that achievement goals mediate the stereotype threat-performance relationship. Furthermore, research has manipulated the salience of stereotype threat by stating that gender differences in math performance are equal [ 82 ]. However, other research has utilized this prime within control conditions (e.g., [ 94 , 105 , 119 ]), underpinned by the rationale that describing a test as ‘fair’ or non-diagnostic of ability eliminates stereotype threat [ 122 ]. It is therefore possible that, in some instances, researchers have inadvertently induced stereotype threat. This outlines the importance of employing a control condition in which individuals are not made aware of any negative stereotypes, and are told that the test is non-diagnostic of ability, in order to detect possible mediators.

Two decades of research have demonstrated the harmful effects that stereotype threat can exert on a wide range of populations in a broad array of performance domains. However, findings with regards to the mediators that underpin these effects are equivocal. This may be a consequence of the heterogeneity of primes used to instantiate stereotype threat and the methods used to measure mediation and performance. To this end, future work is likely to benefit from the following directions: First, account for the existence of multiple stereotype threats; Second, recognize that the experiences of stereotype threat may differ between stigmatized groups, and that no one mediator may provide generalized empirical support across diverse populations; Third, utilize indirect measures, in addition to self-report measures, to examine reliably mediating variables and to examine further the convergence of these two methods; Fourth, counterbalance test instruments to control for order effects; and finally, ensure that participants in a control condition do not inadvertently encounter stereotype threat by stating explicitly that the task is non-diagnostic of ability.

Supporting Information

S1 supporting information. list of excluded studies and rationale for exclusion..

https://doi.org/10.1371/journal.pone.0146487.s001

S1 Table. PRISMA Checklist.

https://doi.org/10.1371/journal.pone.0146487.s002

S2 Table. Summary of affective, cognitive and motivational mechanisms that have been found to mediate stereotype threat effects.

https://doi.org/10.1371/journal.pone.0146487.s003

Author Contributions

Analyzed the data: CRP DH. Contributed reagents/materials/analysis tools: CRP DH ARL DTL. Wrote the paper: CRP. Developed the review design and protocol: CRP DH AL DL. Reviewed the manuscript: DH AL DL. Cross-checked articles in systematic review: CRP DH.

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Gender and Media Representations: A Review of the Literature on Gender Stereotypes, Objectification and Sexualization

Media representations play an important role in producing sociocultural pressures. Despite social and legal progress in civil rights, restrictive gender-based representations appear to be still very pervasive in some contexts. The article explores scientific research on the relationship between media representations and gender stereotypes, objectification and sexualization, focusing on their presence in the cultural context. Results show how stereotyping, objectifying and sexualizing representations appear to be still very common across a number of contexts. Exposure to stereotyping representations appears to strengthen beliefs in gender stereotypes and endorsement of gender role norms, as well as fostering sexism, harassment and violence in men and stifling career-related ambitions in women. Exposure to objectifying and sexualizing representations appears to be associated with the internalization of cultural ideals of appearance, endorsement of sexist attitudes and tolerance of abuse and body shame. In turn, factors associated with exposure to these representations have been linked to detrimental effects on physical and psychological well-being, such as eating disorder symptomatology, increased body surveillance and poorer body image quality of life. However, specificities in the pathways from exposure to detrimental effects on well-being are involved for certain populations that warrant further research.

1. Introduction

As a social category, gender is one of the earliest and most prominent ways people may learn to identify themselves and their peers, the use of gender-based labels becoming apparent in infants as early as 17 months into their life [ 1 ]. Similarly, the development of gender-based heuristics, inferences and rudimentary stereotypes becomes apparent as early as age three [ 2 , 3 ]. Approximately at this age, the development of a person’s gender identity begins [ 4 ]—that is, the process through which a person tends to identify as a man, as a woman or as a vast spectrum of other possibilities (i.e., gender non-conforming, agender, genderfluid, etc.). These processes continue steadily throughout individuals’ lives as they receive and elaborate information about women and men and what it means to belong to either category, drawing from direct and indirect observations, social contact, personal elaborations and cultural representations [ 5 , 6 ]. As a result, social and mental representations of gender are extremely widespread, especially as a strictly binary construct, and can be argued to be ubiquitous in individual and social contexts.

Among the many sources of influence on gender representations, media occupies an important space and its relevance can be assessed across many different phenomena [ 7 , 8 , 9 , 10 , 11 ]. The ubiquity of media, the chronicity of individuals’ exposure to it and its role in shaping beliefs, attitudes and expectations have made it the subject of scientific attention. In fact, several theories have attempted to explore the mechanisms and psychological processes in which media plays a role, including identity development [ 12 , 13 , 14 ], scripts and schemas [ 15 ], cultivation processes [ 16 , 17 , 18 ] and socialization processes [ 5 , 6 ].

The public interest in the topic of gender has seen a surge in the last 10 years, in part due to social and political movements pushing for gender equality across a number of aspects, including how gender is portrayed in media representations. In the academic field as well, publications mentioning gender in their title, abstract or keywords have more than doubled from 2012 to 2022 [ 19 ], while publications mentioning gender in media representations have registered an even more dramatic increase, tripling in number [ 20 ]. Additionally, the media landscape has had a significant shift in the last decade, with the surge in popularity and subsequent addition of social media websites and apps to most people’s mediatic engagement [ 21 ].

The importance of media use in gender-related aspects, such as beliefs, attitudes, or roles, has been extensively documented. As reported in a recent review of the literature [ 22 ], several meta-analyses [ 17 , 23 , 24 ] showed support for the effects of media use on gender beliefs, finding small but consistent effect sizes. These effects appear to have remained present over the decades [ 25 ].

Particular attention has been given to stereotypical, objectifying and sexualizing representations, as portrayals that paint a restrictive picture of the complexity of human psychology, also producing sociocultural pressures to conform to gender roles and body types.

Gender stereotypes can be defined as an extremely simplified concept of attitudes and behaviors considered normal and appropriate for men and women in a specific culture [ 26 ]. They usually span several different areas of people’s characteristics, such as physical appearance, personality traits, behaviors, social roles and occupations. Stereotypical beliefs about gender may be divided into descriptive (how one perceives a person of a certain gender to be; [ 27 ]), prescriptive (how one perceives a person of a certain gender should be and behave; [ 28 , 29 ]) or proscriptive (how one perceives a person of a certain gender should not be and behave; [ 28 , 29 ]). Their content varies on the individual’s culture of reference [ 30 ], but recurring themes have been observed in western culture, such as stereotypes revolving around communion, agency and competence [ 31 ]. Women have stereotypically been associated with traits revolving around communion (e.g., supportiveness, compassion, expression, warmth), while men have been more stereotypically associated with agency (e.g., ambition, assertiveness, competitiveness, action) or competence (e.g., skill, intelligence). Both men and women may experience social and economic penalties (backlash) if they appear to violate these stereotypes [ 29 , 32 , 33 ].

Objectification can be defined as the viewing or treatment of people as objects. Discussing ways in which people may be objectified, Nussbaum first explored seven dimensions: instrumentality (a tool to be employed for one’s purposes); denial of autonomy (lacking self-determination, or autonomy); inertness (lacking in agency or activity); fungibility (interchangeable with others of the same type); violability (with boundaries lacking integrity and permissible to break into); ownership (possible to own or trade); denial of subjectivity (the person’s feelings or experiences are seen as something that does not need to be considered) [ 34 ].

In its initial definition by Fredrickson and Roberts [ 35 ], objectification theory had been offered as a framework to understand how the pervasive sexual objectification of women’s bodies in the sociocultural context influenced their experiences and posed risks to their mental health—a phenomenon that was believed to have uniquely female connotations. In their model, the authors theorized that a cultural climate of sexual objectification would lead to the internalization of objectification (viewing oneself as a sexual and subordinate object), which would in turn lead to psychological consequences (e.g., body shame, anxiety) and mental health risks (e.g., eating disorders, depression). Due to the pervasiveness of the cultural climate, objectification may be difficult to detect or avoid, and objectification experiences may be perceived as normative.

Sexual objectification, in which a person is reduced to a sexual instrument, can be construed to be a subtype of objectification and, in turn, is often defined as one of the types of sexualization [ 36 ]. As previously discussed by Ward [ 37 ], it should be made clear that the mere presence of sexual content, which may be represented in a positive and healthy way, should not be conflated with sexualized or objectifying representations.

The American Psychological Association’s 2007 report defines sexualization as a series of conditions that stand apart from healthy sexuality, such as when a person’s value is perceived to come mainly from sexual appeal or behavior, when physical attractiveness is equated to sexual attractiveness, when a person is sexually objectified or when sexuality is inappropriately imposed on a person [ 36 ]. Sexualization may involve several different contexts, such as personal, interpersonal, and cultural. Self-sexualization involves treating oneself as a sexual object [ 35 ]. Interpersonal contributions involve being treated as sexual objects by others, such as family or peers [ 38 , 39 ]. Finally, contributions by cultural norms, expectations and values play a part as well, including those spread by media representations [ 36 ]. After this initial definition, sexualization as a term has also been used by some authors (e.g., Zurbriggen & Roberts [ 40 ]) to refer to sexual objectification specifically, while others (e.g., Bigler and colleagues [ 41 ]) stand by the APA report’s broader meaning. In this section, we will explore scientific literature adopting the latter.

These portrayals have been hypothesized to lead to negative effects on people’s well-being on a mental and physical level, as well as bearing partial responsibility for several social issues, such as sexism, gender discrimination and harassment. However, the pathways that lead from an individual’s relationship with media to these detrimental effects can be complex. Furthermore, they seem to involve specificities for men and women, as well as for different sexual orientations. A wealth of publications has been produced on these themes and, to the authors’ knowledge, no recent review has attempted to synthesize their findings.

The present article aims to summarize the state of the art of research on stereotyping, sexualization and objectification in gender and media representations. A focus will be placed on the definitions of these concepts, the media where they occur, and verifying whether any changes over time are detectable or any specificities are present. The possible effects of these representations on people’s well-being will be explored as well.

A search of the literature was conducted on scientific search engines (APA PsycArticles, CINAHL Complete, Education Source, Family Studies Abstracts, Gender Studies Database, MEDLINE, Mental Measurements Yearbook, Sociology Source Ultimate, Violence & Abuse Abstracts, PUBMED, Scopus, Web of Science) to locate the most relevant contributions on the topic of media and gender representation, with a particular focus on stereotypes, objectification and sexualization, their presence in the media and their effects on well-being. Keywords were used to search for literature on the intersection of the main topics: media representation (e.g., media OR representation* OR portrayal*), gender (e.g., gender OR sex OR wom* OR m*n) and stereotypes, objectification and sexualization (e.g., stereotyp*, objectif*, sexualiz*). In some cases, additional keywords were used for the screening of studies on specific media (e.g., television, news, social media). When appropriate, further restrictions were used to screen for studies on effects or consequences (e.g., effect* OR impact* OR consequence* OR influence* OR outcome*). Inclusion criteria were the following: (a) academic articles (b) pertaining to the field of media representations (c) pertaining to gender stereotypes, objectification or sexualization. A dataset of 195 selected relevant papers was created. Thematic analysis was conducted following the guidelines developed by Braun and Clarke [ 42 ], in order to outline patterns of meaning across the reviewed studies. The process was organized into six phases: (1) familiarization with the data; (2) coding; (3) searching for themes; (4) reviewing themes; (5) defining and naming themes; and (6) writing up. After removing duplicates and excluding papers that did not meet the inclusion criteria, a total of 87 articles were included in the results of this review. The findings were discussed among researchers (LR, FS, MNP and TT) until unanimous consensus was reached.

2.1. Stereotypical Portrayals

Gender stereotypes appear to be flexible and responsive to changes in the social environment: consensual beliefs about men’s and women’s attributes have evolved throughout the decades, reflecting changes in women’s participation in the labor force and higher education [ 31 , 43 ]. Perceptions of gender equality in competence and intelligence have sharply risen, and stereotypical perceptions of women show significant changes: perceptions of women’s competence and intelligence have surpassed those relative to men, while the communion aspect appears to have shifted toward being even more polarized on being typical of women. Other aspects, such as perceptions of agency being more typical of men, have remained stable [ 31 ].

Despite these changes, gender representation in the media appears to be frequently skewed toward men’s representation and prominently features gender stereotypes. On a global scale, news coverage appears to mostly feature men, especially when considering representation as expert voices, where women are still underrepresented (24%) despite a rise in coverage in the last 5 years [ 44 ]. Underrepresentation has also been reported in many regional and national contexts, but exact proportions vary significantly in the local context. Male representation has been reported to be greater in several studies, with male characters significantly outnumbering female characters [ 45 ], doing so in male-led and mixed-led shows but not in female-led shows [ 46 ] in children’s television programming—a key source of influence on gender representations. Similar results have been found regarding sports news, whose coverage overwhelmingly focuses on men athletes [ 47 , 48 ] and where women are seldom represented.

Several analyses of television programs have also shown how representations of men and women are very often consistent with gender stereotypes. Girls were often portrayed as focusing more on their appearance [ 45 ], as well as being judged for their appearance [ 49 ]. The same focus on aesthetics was found in sports news coverage, which was starkly different across genders, and tended to focus on women athletes’ appearance, featuring overly simplified descriptions (vs. technical language on coverage of men athletes) [ 48 ]. In addition, coverage of women athletes was more likely in sports perceived to be more feminine or gender-appropriate [ 47 , 48 , 50 ]. Similarly, women in videogames appear to be both underrepresented and less likely to be featured as playable characters, as well as being frequently stereotyped, appearing in the role of someone in need of rescuing, as love interests, or cute and innocent characters [ 51 ]. In advertising as well, gender stereotypes have often been used as a staple technique for creating relatability, but their use may lead to negative cross-gender effects in product marketing [ 52 ] while also possibly furthering social issues. Hust and colleagues found that in alcohol advertisements, belief in gender stereotypes was the most consistent predictor of intentions to sexually coerce, showing significant interaction effects with exposure to highly objectifying portrayals [ 53 ]. Representation in advertising prominently features gender stereotypes, such as depicting men in professional roles more often, while depicting women in non-working, recreational roles, especially in countries that show high gender inequality [ 54 ]. A recent analysis of print ads [ 55 ] confirmed that some stereotypes are still prominent and, in some cases, have shown a resurgence, such as portraying a woman as the queen of the home; the study also found representations of women in positions of empowerment are, however, showing a relative increase in frequency. Public support, combined with market logic, appears to be successfully pushing more progressive portrayals in this field [ 56 ].

Both skewed representation and the presence of stereotypes have been found to lead to several negative effects. Gender-unequal representation has been found to stifle political [ 57 ] and career [ 58 ] ambition, as well as foster organizational discrimination [ 59 ]. Heavy media use may further the belief in gender stereotypes and has been found to be linked to a stronger endorsement of traditional gender roles and norms [ 60 ], which in turn may be linked to a vast number of detrimental health effects. In women, adherence and internalization of traditional gender roles have been linked to greater symptoms of depression and anxiety, a higher likelihood of developing eating disorders, and lower self-esteem and self-efficacy [ 36 , 61 , 62 , 63 ]. In men as well, adherence to traditional masculine norms has been linked to negative mental health outcomes such as depression, psychological distress and substance abuse [ 64 ], while also increasing the perpetration of risky behaviors [ 65 , 66 ] and intimate partner violence [ 65 , 67 ].

2.2. Objectifying Portrayals

Non-sexual objectifying representations appear to have been studied relatively little. They have been found to be common in advertising, where women are often depicted as purely aesthetic models, motionless and decorative [ 68 ]. They may also include using a woman’s body as a supporting object for the advertised product, as a decorative object, as an ornament to draw attention to the ad, or as a prize to be won and associated with the consumption of the advertised product [ 55 ].

The vast majority of the literature has focused on the sexual objectification of women. This type of representation has been reported to be very common in a number of contexts and across different media [ 69 ], and several studies (see Calogero and colleagues’ or Roberts and colleagues’ review [ 69 , 70 ]) have found support for the original model’s pathway [ 35 ]. Following experimental models expanded on the original (e.g., Frederick and colleagues or Roberts and colleagues [ 69 , 71 ]), highlighting the role of factors such as the internalization of lean or muscular ideals of appearance, finding evidence for negative effects on well-being and mental health through the increase in self-objectification and the internalization of cultural ideals of appearance [ 71 , 72 ].

Sexual objectification also appears to be consistently linked to sexism. For both women and men, the perpetration of sexual objectification was significantly associated with hostile and benevolent sexism, as well as the enjoyment of sexualization [ 73 ]. Enjoyment of sexualization, in turn, has been found to be positively associated with hostile sexism in both men and women, positively associated with benevolent sexism in women and negatively in men [ 74 ].

Exposure to objectifying media in men has been found to increase the tendency to engage in sexual coercion and harassment, as well as increasing conformity to gender role norms [ 75 ]. Consistently with the finding that perpetration of objectification may be associated with a greater men’s proclivity for rape and sexual aggression [ 76 ], a study conducted by Hust and colleagues found that exposure to objectifying portrayals of women in alcohol advertising was also a moderator in the relationship between belief in gender stereotypes and intentions to sexually coerce. Specifically, participants who had a stronger belief in gender stereotypes reported stronger intentions to sexually coerce when exposed to slightly objectifying images of women. Highly objectifying images did not yield the same increase—a result interpreted by the authors to mean that highly objectified women were perceived as sexually available and as such less likely to need coercion, while slightly objectified women could be perceived as more likely to need coercion [ 53 ].

Research on objectification has primarily focused on women, in part due to numerous studies suggesting that women are more subject to sexual objectification [ 73 , 77 , 78 , 79 , 80 ], as well as suffering the consequences of sexual objectification more often [ 81 ]. However, sexually objectifying portrayals seem to have a role in producing negative effects on men as well, although with partially different pathways. In men, findings about media appearance pressures on body image appear to be mixed. Previous meta-analyses found either a small average effect [ 82 ] or no significant effect [ 72 ]. A recent study found them to be significantly associated with higher body surveillance, poorer body image quality of life and lower satisfaction with appearance [ 71 ]. Another study, however, found differing relationships regarding sexual objectification: an association was found between experiences of sexual objectification and internalization of cultural standards of appearance, body shame and drive for muscularity, but was not found between experiences of sexual objectification and self-objectification or body surveillance [ 83 ]: in the same study, gender role conflict [ 84 ] was positively associated to the internalization of sociocultural standards of appearance, self-objectification, body shame and drive for muscularity, suggesting the possibility that different pathways may be involved in producing negative effects on men. Men with body-image concerns experiencing gender role conflict may also be less likely to engage in help-seeking behaviors [ 85 , 86 ]. This is possibly due to restrictive emotionality associated with the male gender role leading to more negative attitudes toward help-seeking, as found in a recent study by Nagai, [ 87 ], although this study finds no association with help-seeking behavior, conflicting with previous ones, and more research is needed.

Finally, specificities related to sexual orientation regarding media and objectification appear to be present. A set of recent studies by Frederick and colleagues found that gay men, lesbian women and bisexual people share with heterosexual people many of the pathways that lead from sociocultural pressures to internalization of thin/muscular ideals, higher body surveillance and a lower body image quality of life [ 71 , 88 ], leading the authors to conclude that these factors’ influence applies regardless of sexual orientation. However, their relationship with media and objectification may vary. Gay and bisexual men may face objectification in social media and dating apps rather than in mainstream media and may experience more objectification than heterosexual men [ 89 ]. In Frederick and colleagues’ studies, gay men reported greater media pressures, body surveillance, thin-ideal internalization, and self-objectification compared to heterosexual men; moreover, bisexual men appeared to be more susceptible to ideal internalization, displaying stronger paths from media appearance pressures to muscular-ideal internalization compared to heterosexual men; lesbian women, instead, demonstrated weaker relationships between media pressures and body image outcomes [ 71 , 88 ]. Consistently with previous studies suggesting a heightened susceptibility to social pressures [ 90 ], bisexual women appeared to be more susceptible to media pressures relative to other groups [ 88 ]. Another recent study of lesbian and bisexual women supported previous evidence for the pathway from the internalization of cultural appearance standards to body surveillance, body shame and eating disorder symptoms; however, it found no significant connection between experiences of objectification and eating disorder symptoms [ 91 ].

2.3. Sexualized Portrayals

Several studies have found sexualizing media representations to be commonplace across a number of different media contents and across different target demographics (i.e., children, adolescents or adults) and genres. Reports of common sexualized representations of women are found in contexts such as television programs [ 92 ], movies [ 93 , 94 , 95 , 96 ], music videos [ 97 , 98 ], advertising [ 54 , 55 ], videogames [ 51 , 99 , 100 ], or magazines [ 101 ].

Exposure to sexualized media has been theorized to be an exogenous risk factor in the internalization of sexualized beliefs about women [ 41 ], as well as one of the pathways to the internalization of cultural appearance ideals [ 102 ]. Daily exposition to sexualized media content has been consistently linked to a number of negative effects. Specifically, it has been found to lead to higher levels of body dissatisfaction and distorted attitudes about eating through the internalization of cultural body ideals (e.g., lean or muscular) in both men and women [ 71 ]. It has also been associated with a higher chance of supporting sexist beliefs in boys [ 103 ], and of tolerance toward sexual violence in men [ 104 ]. Furthermore, exposure to sexualized images has been linked to a higher tolerance of sexual harassment and rape myth acceptance [ 76 ]. Exposure to reality TV programs consistently predicted self-sexualization for both women and men, while music videos did so for men only [ 103 ]. Internalized sexualization, in turn, has been linked to a stronger endorsement of sexist attitudes and acceptance of rape myths [ 105 ], while also being linked to higher levels of body surveillance and body shame in girls [ 106 ]. Internalization of media standards of appearance has been linked to body surveillance in both men and women, as well as body surveillance of the partner in men [ 107 ].

As a medium, videogames have been studied relatively little and have produced less definite results. This medium can offer the unique dynamic of embodiment in a virtual avatar, which has been hypothesized to be able to lead to a shift in self-perception (the “Proteus effect”, as formulated by Yee & Bailenson, [ 108 ]). While some studies have partially confirmed this effect, showing that exposure to sexualized videogame representations can increase self-objectification [ 109 , 110 , 111 ], others [ 112 ] have not found the same relationship. Furthermore, while a study has found an association between sexualized representations in videogames, tolerance of sexual abuse of women and rape myth acceptance [ 113 ], and in another, it was linked to a decreased real-life belief in women’s competence [ 114 ], a recent meta-analysis [ 115 ] found no effect of the presence of sexualized content on well-being, sexism or misogyny.

Research on social media has also shown some specificities. Social media offers the unique dynamic of being able to post and disseminate one’s own content and almost always includes built-in mechanisms for user-generated feedback (e.g., likes), as well as often being populated by one’s peers, friends and family rather than strangers. Sites focusing on image- or video-based content (e.g., Instagram, TikTok) may be more prone to eliciting social comparison and fostering the internalization of cultural appearance ideals, resulting in more associations to negative body image when compared to others that have the same capabilities but offer text-based content as well (e.g., Facebook) [ 116 ]. Social media appears to foster social comparison, which may increase appearance-based concerns [ 117 ]. Consistently with previous research, exposure to sexualized beauty ideals on social media appeared to be associated with lower body satisfaction; exposure to more diverse standards of appearance, instead, was associated with increased body satisfaction and positive mood, regardless of image sexualization [ 116 , 118 ].

3. Discussion

3.1. critical discussion of evidence.

The reviewed evidence (summarized in Table 1 ) points to the wide-ranging harmful effects of stereotyping, objectifying and sexualizing media portrayals, which are reported to be still both common and pervasive. The links to possible harms have also been well documented, with a few exceptions.

Summary of findings.

These representations, especially but not exclusively pertaining to women, have been under social scrutiny following women’s rights movements and activism [ 119 ] and can be perceived to be politically incorrect and undesirable, bringing an aspect of social desirability into the frame. Positive attitudes toward gender equality also appear to be at an all-time high across the western world [ 120 , 121 ], a change that has doubtlessly contributed to socio-cultural pressure to reduce harmful representations. Some media contexts (e.g., advertising and television) seem to have begun reflecting this change regarding stereotypes, attempting to either avoid harmful representations or push more progressive portrayals. However, these significant changes in stereotypes (e.g., regarding competence) have not necessarily been reflected in women’s lives, such as their participation in the labor force, leadership or decision-making [ 31 , 122 , 123 ]. Objectifying or sexualizing representations do not seem to be drastically reduced in prevalence. Certainly, many influences other than media representations are in play in this regard, but their effect on well-being has been found to be pervasive and consistent. Despite widespread positive attitudes toward gender equality, the persistence of stereotypical, objectifying and sexualizing representations may hint at the continued existence of an entrenched sexist culture which can translate into biases, discrimination and harm.

Despite some conflicting findings, the literature also hints at the existence of differences in how media pressures appear to affect men and women, as well as gay, lesbian and bisexual people. These may point to the possibility of some factors (e.g., objectification) playing a different role across different people in the examined pathways, an aspect that warrants caution when considering possible interventions and clinical implications. In some cases, the same relationship between exposure to media and well-being may exist, but it may follow different pathways from distal risk factors to proximal risk factors, as in the case of gender role conflict for men or body shame for lesbian and bisexual women. However, more research is needed to explore these recent findings.

Different media also appear to feature specificities for which more research is needed, such as videogames and social media. The more interactive experiences offered by these media may play an important role in determining their effects, and the type of social media needs to be taken into consideration as well (image- or video-based vs. text-based). Moreover, the experiences of exposure may not necessarily be homogenous, due to the presence of algorithms that determine what content is being shown in the case of social media, and due to the possibility of player interaction and avatar embodiment in the case of videogames.

Past findings [ 37 , 69 ] about links with other social issues such as sexism, harassment and violence appear to still be relevant [ 67 , 73 , 103 , 105 ]. The increases in both tolerance and prevalence of sexist and abusive attitudes resulting from exposure to problematic media representations impact the cultural climate in which these phenomena take place. Consequently, victims of discrimination and abuse living in a cultural climate more tolerant of sexist and abusive attitudes may experience lower social support, have a decreased chance of help-seeking and adopt restrictive definitions for what counts as discrimination and abuse, indirectly furthering gender inequalities.

Exploring ways of reducing risks to health, several authors [ 22 , 41 , 75 ] have discussed media literacy interventions—that is, interventions focused on teaching critical engagement with media—as a possible way of reducing the negative effects of problematic media portrayals. As reported in McLean and colleagues’ systematic review [ 124 ], these interventions have been previously shown to be effective at increasing media literacy, while also improving body-related outcomes such as body satisfaction in boys [ 125 ], internalization of the thinness ideal in girls [ 125 ], body size acceptance in girls [ 126 ] and drive for thinness in girls and boys [ 127 ]. More recently, they were also shown to be effective at reducing stereotypical gender role attitudes [ 128 ], as well as fostering unfavorable attitudes toward stereotypical portrayals and lack of realism [ 129 ]. Development and promotion of these interventions should be considered when attempting to reduce negative media-related influences on body image. It should be noted, however, that McLean and colleagues’ review found no effect of media literacy interventions on eating disorder symptomatology [ 124 ], which warrants more careful interventions.

Furthermore, both internal (e.g., new entrants’ attitudes in interpersonal or organizational contexts) and external (e.g., pressure from public opinion) sociocultural pressures appear to have a strong influence in reducing harmful representations [ 55 , 56 ]. Critically examining these representations when they appear, as well as voicing concerns toward examples of possibly harmful representations, may promote more healthy representations in media. As documented by some studies, the promotion of diverse body representations in media may also be effective in reducing negative effects [ 70 , 118 ].

3.2. Limitations

The current review synthesizes the latest evidence on stereotyping, objectifying and sexualizing media representations. However, limitations in its methodology are present and should be taken into consideration. It is not a systematic review and may not be construed to be a complete investigation of all the available evidence. Only articles written in the English language have been considered, which may have excluded potentially interesting findings written in other languages. Furthermore, it is not a meta-analysis, and as such cannot be used to draw statistical conclusions about the surveyed phenomena.

3.3. Future Directions

While this perception is limited by the non-systematic approach of the review, to what we know, very few studies appear to be available on the relationship between media representation and non-sexual objectification, which may provide interesting directions to explore in relation to autonomy, violability or subjectivity, as was attempted in the context of work and organizations [ 130 ].

More cross-cultural studies (e.g., Tartaglia & Rollero [ 54 ]) would also prove useful in exploring differences between cultural contexts, as well as the weight of different sociocultural factors in the relationship between media representation and gender.

More studies focusing on relatively new media (e.g., social media, videogames) would possibly help clear up some of the identified discrepancies and explore new directions for the field that take advantage of their interactivity. This is particularly true for niche but growing media such as virtual reality, in which the perception of embodiment in an avatar with different physical features than one’s own could prove to be important in sexualization and objectification. Only preliminary evidence [ 131 ] has been produced on the topic.

Studies to further explore the relationship between media representations, gender and sexual orientation would also be beneficial. As already highlighted by Frederick and colleagues [ 132 ], gay, lesbian and bisexual people may deal with a significantly different set of appearance norms and expectations [ 133 ], and face minority-related stresses [ 134 ] that can increase susceptibility to poorer body image and disordered eating [ 135 , 136 ]. Additionally, none of the reviewed studies had a particular focus on trans people, who may have different experiences relating to media and body image, as suggested by the differences in pathways found in a recent study [ 137 ]. Sexual orientation and gender identity should be kept into consideration when investigating these relationships, as their specificities may shed light on the different ways societal expectations influence the well-being of sexual minorities.

The examined literature on the topic also appears to feature specificities that need to be taken into account. As previously reported by Ward [ 37 ], the vast majority of the studies continue to be conducted in the United States, often on undergraduates, which limits the generalizability of the results to the global population. Given the abundance and complexity of the constructs, more studies examining the pathways from media exposure to well-being using methodologies such as path analysis and structural equation modeling may help clarify some of the discrepancies found in the literature about the same relationships.

Finally, as previously reported by many authors [ 37 , 69 , 138 ], sexualization, self-sexualization, objectification and self-objectification are sometimes either treated as synonymous or used with different definitions and criteria, which may add a layer of misdirection to studies on the subject. Given the divergences in the use of terminology, clearly stating one’s working definition of sexualization or objectification would possibly benefit academic clarity on the subject.

4. Conclusions

Consistent empirical evidence highlights the importance of media representations as a key part of sociocultural influences that may have consequences on well-being. Despite some notable progress, harmful representations with well-researched links to detrimental effects are still common across a number of different media. Exposure to stereotyping, objectifying and sexualized representations appears to consistently be linked to negative consequences on physical and mental health, as well as fostering sexism, violence and gender inequity. On a clinical level, interventions dealing with body image and body satisfaction should keep their influence into account. The promotion of institutional and organizational interventions, as well as policies aimed at reducing their influence, could also prove to be a protective factor against physical and mental health risks.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, F.S. and L.R.; methodology, T.T. and M.N.P.; writing—original draft preparation, F.S.; writing—review and editing, T.T. and M.N.P.; supervision, L.R. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Word Through The Times

The History of ‘Stereotype,’ Written on Metal Plates

Stereotype printing is pressed into the story of The New York Times.

By Sarah Diamond

In Word Through The Times, we trace how one word or phrase has changed throughout the history of the newspaper.

The word “stereotype” first appeared in The New York Times in 1858. A young man, The Times reported, had been arrested “on a charge of stealing $300 worth of stereotype plates.”

The invention of stereotype printing — a method in which metal plates are used to transfer text and images to a page — is often attributed to William Ged and dated to 1725, though it may have emerged earlier. According to the historian George A. Kubler, the word was not coined until later, at the end of the 18th century, by the French typesetter Firmin Didot.

“‘Stereo’ is the ancient Greek word for ‘solid,’ and ‘type’ is ‘symbol,’” Adam Aleksic, the linguist behind the Instagram account @etymologynerd, said in an interview. These “solid symbols,” he added, increased printing efficiency.

Thanks to its speed, stereotype printing became popular with newspapers, including The Times, which relied on the method to update later editions of the paper. In 1959, a fire in The Times’s “stereotype room” temporarily interrupted production of the first edition of the next day’s newspaper. The Times managed to report this in the same day’s paper. The fire had started in the “stereotype foundry, where metal page plates for printing presses are cast.” (It was extinguished immediately.)

Stereotype printing made it easy to produce the same page over and over again. So, throughout the 1800s, “stereotype” gained a figurative meaning: “something continued or constantly repeated,” according to the Oxford English Dictionary . That gave way to another definition, per the dictionary, which arrived in the early 1920s: “a preconceived and oversimplified idea of the characteristics which typify a person, situation, etc.”

“Stereotype,” in this figurative sense, first appeared in The Times in a 1925 film review : “The director has kept the picture from being a stereotype,” the author wrote. “He has used brains and imagination.”

Over the last century, the meaning of the word has remained, but its connotation has changed. “Stereotype” underwent pejoration, in which a word gradually adopts a negative meaning, Mr. Aleksic said. “When someone generalizes too much about another group of people, that can often be racist or discriminatory,” he added.

In recent years, The Times has written about “ confronting ,” “ breaking ” and “ fighting ” stereotypes, including those related to race, religion and gender. (Even “‘positive’ stereotypes can become dangerous,” an article from 1998 pointed out.)

Today, the more “oblique sense” of the word, the etymologist Jess Zafarris said, is more common than the literal meaning. “Now, when you say the word ‘stereotype,’” she said, “you don’t think of printing.”

That’s perhaps true — if you don’t work at a printing plant. Mike Connors, the managing director of the production department at The Times’s printing plant in Queens, said in an interview that when he started in 1976, The Times still used stereotype plates. “Now it’s archaic,” he said. “Then, it was chic.”

The Times currently uses a process Mr. Connors called “computer to plate”; instead of a heavy, lead-based plate, a laser burns digital images onto aluminum plates, each one representing a page of the newspaper. These plates are attached to the press, and ink begins to flow.

An earlier version of this article misspelled in one instance the surname of the managing director of the production department at The Times’s printing plant in Queens. He is Mike Connors, not Conners.

How we handle corrections

Sarah Diamond manages production for narrated articles. She previously worked at National Geographic Studios. More about Sarah Diamond

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

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• Silent Generation

Kim Parker is director of social trends research at Pew Research Center

How Teens and Parents Approach Screen Time

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