literature review on quality of life pdf

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• v.48(6); 2019 Jun

A review of quality of life (QOL) assessments and indicators: Towards a “QOL-Climate” assessment framework

Ronald c. estoque.

1 Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba City, Ibaraki 305-0053 Japan

Takuya Togawa

2 Fukushima Branch, National Institute for Environmental Studies, 10-2 Fukasaku, Miharu, Tamura District, Fukushima 963-7700 Japan

Makoto Ooba

Shogo nakamura, yasuaki hijioka, yasuko kameyama, associated data.

Quality of life (QOL), although a complex and amorphous concept, is a term that warrants attention, especially in discussions on issues that touch on the impacts of climate change and variability. Based on the principles of RepOrting standards for Systematic Evidence Synthesis, we present a systematic review aimed at gaining insights into the conceptualization and methodological construct of previous studies regarding QOL and QOL-related indexes. We find that (i) QOL assessments vary in terms of conceptual foundations, dimensions, indicators, and units of analysis, (ii) social indicators are consistently used across assessments, (iii) most assessments consider indicators that pertain to the livability of the environment, and (iv) QOL can be based on objective indicators and/or subjective well-being, and on a composite index or unaggregated dimensions and indicators. However, we also find that QOL assessments remain poorly connected with climate-related issues, an important research gap. Our proposed “QOL-Climate” assessment framework, designed to capture the social-ecological impacts of climate change and variability, can potentially help fill this gap.

Electronic supplementary material

The online version of this article (10.1007/s13280-018-1090-3) contains supplementary material, which is available to authorized users.

Introduction

Quality of life (QOL) has been, and continues to be, an important research topic across various disciplines including medicine, health, psychology, economics, sociology, and environmental science. Accordingly, the literature regarding QOL is rich and continuously growing. However, owing to its multidimensionality and nebulousness, the meaning of QOL can vary from person to person across various contexts (Table  1 ). Numerous review articles concerning the various facets of QOL are available, including reviews that focus on its conceptual origin, foundation, and development (e.g., Massam 2002 ; Moons et al. 2006 ; Veenhoven 2007 ; Barcaccia et al. 2013 ). Reviews of various indexes related to QOL are also available (e.g., Hagerty et al. 2001 ; Pantisano et al. 2014 ). In addition, various frameworks and approaches for QOL assessment have been proposed, including those employing medicine and health-related questionnaire survey instruments (see Bakas et al. 2012 ; Theofilou 2013 ) as well as those transcending the scope of medicine and health-related fields (Veenhoven 2000 , 2007 ; Costanza et al. 2007 ; Fahy and Cinnéide 2008 ).

Table 1

Various definitions and descriptions of QOL

In recent years, various global initiatives built on the concept of sustainable development have been framed and propounded, including the Millennium Ecosystem Assessment (MEA 2005 ), the Intergovernmental Panel on Climate Change assessments (IPCC 2014a ), the Future Earth initiative ( www.futureearth.org ), the United Nations Millennium Development Goals (MDGs) (UN 2000 ) and Sustainable Development Goals (SDGs) (UN 2015 ), and the Paris Agreement on climate change (UNFCCC 2015 ). Embedded in these initiatives is the aim of promoting sustainability and improving QOL and human well-being by conserving the natural environment, promoting low carbon development, and adapting to global environmental change, especially climate change and variability.

By definition, climate change refers to “a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties and that persists for an extended period, typically decades or longer” (IPCC 2014a , p. 120). This includes changes in the patterns of essential climate variables such as precipitation and temperature (IPCC 2014a ). Climate variability refers to “variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all spatial and temporal scales beyond that of individual weather events” (IPCC 2014a , p. 121).

Climate change and variability affect QOL and human well-being in many ways, rendering it one of the most pressing and significant challenges of the present day. For instance, climate-related disasters and extreme events (such as droughts, floods, typhoons and landslides) can affect both the social and ecological components of a social-ecological system (Redman et al. 2004 ; Glaser et al. 2008 ; Ostrom 2009 ; Estoque and Murayama 2014a ), a coupled human–environment system (Turner et al. 2003 ), or a coupled human and natural system (Liu et al. 2007a , b ). Changes in precipitation and temperature patterns can also affect the supply and flow of various ecosystem services [provisioning, regulating, supporting, and cultural services (MEA 2005 ; TEEB 2010 )] (MEA 2005 ; IPCC 2014a ; Pecl et al. 2017 ; Runting et al. 2017 ). These ecosystem services are essential to human well-being because they are felt and experienced by people. Indeed, QOL and human well-being are important subjects in discourses on sustainability (Levett 1998 ; Fahy and Cinnéide 2008 ), ecosystem services (MEA 2005 ; Farley 2012 ), and climate impacts (Roberts 1976 ; IPCC 2001 ; Evans 2019 ).

Many scholars have demonstrated that a systematic review (Grant and Booth 2009 ; Haddaway et al. 2018 ) can help capture the state of knowledge and research trends, directions, and gaps in a particular discipline or subject (Englund et al. 2017 ; Jurgilevich et al. 2017 ; Runting et al. 2017 ). Owing to the rapid growth of information across disciplines and continuous improvements in scholars’ access to such information, the number and temporal occurrence of systematic reviews are expected to increase. In order to ensure that systematic reviews including reports are of high quality, attempts have been made to standardize the method used under the banner of RepOrting standards for Systematic Evidence Synthesis (ROSES) (Haddaway et al. 2017a , b , 2018 ; www.roses-reporting.com ). Central to ROSES is a set of detailed, state-of-the-art forms that authors (reviewers) are encouraged to use to ensure that their methods attain the highest possible standards. Although these forms have been specifically designed for environmental topics, they are applicable across disciplines ( www.roses-reporting.com ).

Systematic reviews of QOL assessments in medicine and health-related fields are available (Bakas et al. 2012 ; Ireson et al. 2018 ). In these fields, questionnaire survey instruments such as those by Wilson and Cleary, Ferrans et al., and the World Health Organization (WHO) (see Bakas et al. 2012 ; Theofilou 2013 ) play a key role in assessing QOL. However, there is a glaring absence of a systematic review of QOL assessments that are based on a more general context and that go beyond the use of medicine and health-related questionnaire survey instruments. Therefore, in this review of QOL assessments and indicators, we carried out the necessary to fill the information gap.

Our primary aim was to gain insights regarding the conceptualization and methodological construct of previous studies and assessments of QOL as well as of selected existing and emerging QOL-related indexes. The knowledge gained was used to develop a conceptual framework that may potentially connect QOL with issues of climate change and variability. We achieved this purpose by applying the principles of ROSES for a systematic review.

Materials and methods

The three major steps under the ROSES principles for a systematic review are: (1) searching; (2) screening; and (3) appraisal and synthesis (Haddaway et al. 2017a , b , 2018 ). These steps are described below in the context of this current review (see also Fig.  1 ).

Flowchart of the review. This diagram is based on ROSES (Haddaway et al. 2017a , b , 2018 ; www.roses-reporting.com )

For this review, we used two sub-databases (SCI-EXPANDED and SSCI) within the Web of Science (WoS) Core Collection. WoS is a large database of articles that include those in the social and environmental sciences (Landauer et al. 2015 ; Englund et al. 2017 ; Jurgilevich et al. 2017 ). In a recent scholarly work, it was demonstrated that WoS alone could be used as a source for a major systematic review (Runting et al. 2017 ). The potential limitations of this current review regarding database are discussed in “ Methodology-related discussion ” section.

In this review, we were especially interested in studies focusing on QOL assessment, evaluation, or measurement in the social-ecological context. Hence, we used terms that focus on the assessment, evaluation, and measurement of QOL (see Fig.  1 ). We performed our search on January 4, 2018, and included records published from 2000 to 2017. This period was chosen intentionally to capture recent trends in QOL research. The year 2000 essentially coincides with the Climate Change 2001—IPCC Third Assessment Report, a report that has been instrumental to the advancement of studies on climate impacts, adaptation, and vulnerability, all of which are important factors affecting QOL and human well-being (more details about this are provided in “ Linking QOL with climate change and variability issues ” section). In this review, we focused only on ‘articles’ published in the ‘English’ language.

Our search tracked 3251 articles (Fig.  1 ) that were dominated by medicine and health-related studies as indicated by the authors’ keywords and research areas as per the WoS classification (Fig. S1 ; Table S1 ). We further refined the search by focusing only on research areas that were deemed more relevant under the social-ecological system paradigm (Redman et al. 2004 ; Glaser et al. 2008 ; Ostrom 2009 ; Estoque and Murayama 2014a ): “social sciences other topics,” “sociology,” “science technology other topics,” “environmental sciences ecology,” “engineering,” “anthropology,” “social work,” “social issues,” “agriculture,” “public administration,” “geography,” “operations research management science,” “urban studies,” “physical geography,” and “remote sensing” (Table S1 ).

By narrowing the research areas, the searched articles decreased to 178 articles (Fig.  1 ). Having screened these articles based on title and abstract, 81 articles were identified and subjected to the next level of screening which focused on methods. The articles that were excluded were those that neither explicitly mentioned the method or approach used in QOL assessment, nor proceeded with QOL assessment, evaluation and measurement, as well as those that did not use any method other than medicine and health-related questionnaire survey instruments. On this basis, 19 articles were retained and subjected to a full-text review.

In addition, nine pre-screened existing and emerging QOL-related indexes were included in the review (Fig.  1 ). These included the Human Development Index (HDI) (UNDP 1990 ), Genuine Progress Indicator (GPI) (Cobb et al. 1995 ), Happy Planet Index (HPI) (Marks 2006 ), Cities of Opportunity Quality of Life (COQOL) (PwC 2016 ), Inequality-adjusted HDI (IHDI) (UNDP 2010 ), Better Life Index (BLI) (OECD 2011 ), Human Sustainable Development Index (HSDI) (Togtokh 2011 ), Social Progress Index (SPI) (Porter et al. 2014 ), and Social-Ecological Status Index (SESI) (Estoque and Murayama 2014a , 2017 ). It was important to include these indexes because they are all related to QOL assessment to some extent, and thus provide complementary perspectives through their conceptualization and methodological construct of QOL-related indexes. There might have been some limitations in our selection of these indexes, and these are discussed in “ Methodology-related discussion ” section. Hereafter, these articles and indexes are collectively referred to as “reference(s).”

Appraisal and synthesis

In order to facilitate our analysis of the conceptualization and methodological construct of previous studies and assessments on QOL, as well as of some existing and emerging QOL-related indexes, we developed a questionnaire checklist (Table  2 ) for the systematic retrieval of relevant information from all of the references (Table S2 ). Prior to our analysis of the retrieved information, we examined the QOL publication trends and the network of keywords used in the searched articles (Fig.  1 ).

Table 2

Questionnaire checklist used to retrieve relevant information from the references reviewed

Publication trend and keywords network analysis

We used the two sets of searched articles (i.e., 3251 and 178) in our analysis of the temporal trends in QOL article publications, research areas, and occurrence and network of authors’ keywords. Our analysis of the occurrence and network of authors’ keywords was performed using the VOSviewer version 1.6.6, a software tool for analyzing bibliometric networks, creating maps based on network data, as well as visualizing and exploring these maps (van Eck and Waltman 2010 , 2017 ). The same software has been used in other previous bibliometric analyses (e.g., Gobster 2014 ; Rodrigues et al. 2014 ; Sweileh 2017 ).

Synthesis of the conceptualization and methodological construct for QOL assessment

Based on our pre-defined set of questions (Table  2 ), we summarized the following information in a table: year of publication or first release; purpose and scope; theoretical or conceptual foundation; dimensions and indicators; weighting and aggregation methods; value range and unit of final index; unit of analysis; and type of data used.

In our synthesis, we evaluated the references in relation to the triple bottom line. The triple bottom line has been, and continues to be, an important framework for sustainability assessment. It comprises three dimensions that are central to people’s quality of life and well-being: economic (profit), social (people), and environmental (planet) (Elkington 1994 , 1997 ). We classified the references based on the presence or absence of indicators (i.e., for an objective assessment) that fall under each of the three dimensions of the triple bottom line. To this end, the reference that included at least one indicator that falls within the scope of the dimension under consideration was marked by placing its number inside a circle. Otherwise, the reference was marked with a circle only, without its number. The references were also evaluated for whether subjective well-being (satisfaction, happiness, fulfillment, welfare, etc.) was considered in their respective assessments. Here, an objective assessment is defined as a type of evaluation or measurement that uses indicators that are based on statistics (e.g., census data) and other type of data (e.g., remote sensing and GIS data) independent of perceptions, while a subjective assessment is a type of evaluation or measurement that captures individual perceptions, preferences and evaluations (e.g., subjective well-being).

As part of our synthesis, we also evaluated and classified the references based on the four qualities of life plotted in four quadrants (Veenhoven 2000 , 2007 ). The four quadrants (Q1, Q2, Q3, and Q4) are the results of the intersections of two dichotomies, namely the outer and inner qualities of life, and the life chances and life results: (Q1) outer quality-life chances (livability of the environment); (Q2) inner qualities-life chances (life-ability of a person); (Q3) outer qualities-life results (utility of life); and (Q4) inner qualities-life results (enjoyment of life). According to Veenhoven ( 2000 , 2007 ), “outer quality” and “inner quality” are found in the environment and within the individual, respectively. Life chances refer to opportunities for a good life, while life results refer to outcomes. Livability of environment refers to the habitability of the environment, while the life-ability of a person refers to the capacity of individuals to cope with pressures or perturbations. Utility of life includes the external effects of life or the individual’s contributions to society and the environment, while enjoyment of life refers to the subjective appreciation of life, subjective well-being, life satisfaction, or happiness, including life expectancy (Veenhoven 2000 , 2007 ). Based on their respective indicators (i.e., either based on statistics, questionnaire surveys, or other types of data), we determined whether each of the references could have fulfilled each quadrant.

Synthesis of the linkage between QOL and climate change and variability issues

After the results of the bibliometric analysis and full-text review were summarized, we determined whether the issues of climate change and variability were considered in the references reviewed. Our finding (“ Methodological construct for QOL assessment ” and “ QOL and climate change and variability issues: their connections ” sections) revealed that QOL assessments were not [yet] well-connected with the issues of climate change and variability. To help advance this subfield of QOL research, we developed a conceptual framework that could potentially link QOL with issues relating to climate change and variability (“ Linking QOL with climate change and variability issues ” section).

Publication trends and keywords network

Of the total 3251 articles that resulted from our search, 38% were published during the first half of the analysis period (2000–2008), while 62% were published during the latter period (2009–2017) (Fig.  2 a). This means that the average number of articles published per year was higher during the 2009–2017 period (223) than during the 2000–2008 period (138). From 2000 to 2017, the average annual number of articles published was 181. Based on the 178 articles, i.e., those articles that were derived from the bibliometric search on the selected research areas (Fig.  1 , Table S1 ), a similar trend was observed; 31% and 69% of the articles were published during the earlier and latter periods, respectively (Fig.  2 b). The results also revealed some fluctuations in the annual publication of QOL research articles during the analysis period. Nevertheless, the results showed an overall significant increase in article publication of QOL assessments over the past 18 years for both sets of articles (Fig.  2 a, b).

Temporal trends in article publications regarding QOL (2000–2017). a Based on the 3521 articles resulting from all research areas; and b Based on the 178 articles resulting from the selected research areas. Table S1 lists all the research areas and those selected

Table S1 provides the complete list of research areas that the 3251 searched QOL articles fell into as per the WoS classification. With a few exceptions, most of the research areas are directly related to the medicine and health-related fields. Among these research areas, “health care sciences services,” “public environmental occupational health,” “oncology,” “surgery,” and “neurosciences neurology” topped the list. Those areas that are not directly related to the medicine and health-related fields include “sociology,” “environmental sciences ecology,” “engineering,” “agriculture,” “geography,” and “urban studies.”

Figure  3 presents the occurrence and network of authors’ keywords based on the 178 articles obtained after further screening, while the network map of the 3251 articles is presented in Fig. S1 . In both figures, the size of the circles indicates occurrences, while the thickness of the lines indicates link strength between keywords. The color and position of the circles indicate the clustering pattern. For the 178 articles (Fig.  3 ), the keyword “quality of life” had the highest occurrence (86) and total link strength (48). This was followed by the keyword “well-being” with an occurrence of 9 and a total link strength of 8. The keyword “well-being” also had the strongest connection with “quality of life,” followed by “assessment,” and “life satisfaction.”

Total occurrence and network of authors’ keywords based on the 178 articles (2000–2017). Fractional counting was used, which means that the weight of a link was fractionalized. For example, if a keyword co-occurs with five other keywords, each of the five keywords has a weight of 0.2 (1/5). For these 178 articles, a threshold of 2 was applied (i.e., the minimum number of occurrences for each keyword), resulting in a total of 50 keywords. The result for the 3251 articles is presented in Fig. S1

Conceptualization of QOL

The articles reviewed were structured on more specific concepts or variants of QOL, including quality of life as a function of objective socioeconomic and environmental variables, urban quality of life, transport quality of life, tourism-related community quality of life, and sustainable tourism development (Table S2 ). On the other hand, the QOL-related indexes reviewed were designed based on general concepts, including human development, sustainability or sustainable development, better life, social progress, and social-ecological status.

A wide range of QOL dimensions was identified from the references reviewed, and each of these dimensions included at least one indicator (Table S2 ). Selection of these dimensions and indicators was largely based on the references’ conceptualization of QOL as mentioned above, as well as on their respective purposes (see Table S2 ). For indicators, we found that 71% of the references considered indicators that could fulfill all the three dimensions of the the triple bottom line (economic, social and environmental) and 39% explicitly considered subjective well-being in their respective assessments (Fig.  4 ; see also Table S3 ). All of the references considered indicators that were related to the social dimension. However, some of the references did not consider indicators that directly fall under the economic (18%) and environmental (14%) dimensions (Fig.  4 ).

Classification of the references reviewed (19 articles [1–19] and 9 indexes [20–28]) based on their respective indicators plotted according to the triple bottom line (fulfillers of human needs). The figure also shows the articles and indexes that explicitly considered subjective well-being (satisfaction, happiness, fulfillment, welfare, etc.) in their respective frameworks and assessments. The numbers correspond to the numbers under the column heading “No.” in Tables  3 , S2 and S3 , and those in Fig. ​ Fig.5 5

Figure  5 presents the categorization of the references reviewed in terms of their respective indicators in relation to the four qualities of life. Q1 (livability of the environment) included any indicator that is related to the quality of the social and physical environment, such as housing conditions, as well as the quantity and quality of urban facilities, water, air, and green spaces. Q2 (life-ability of a person) was associated with human and personal attributes, such as those related to health and education. Q3 (utility of life) included any indicator that is related to one’s (or the community’s) contribution to society and the environment, such as civic involvement, ecological footprint, sustainability-related programs, and efforts toward environmental conservation and art and culture preservation. Q4 (enjoyment of life) comprised indicators or dimensions such as subjective well-being, life satisfaction, happiness, and life expectancy. Of the total references reviewed, 39% were present in all four quadrants, which means that these references included at least one indicator under each of the four qualities of life. Among the four quadrants, Q3 had the highest percentage of references that lacked any indicator with 36%, followed by Q2 and Q4 with 25% each. In Q1, all but one of the references had at least one indicator.

Classification of the references reviewed (19 articles [1–19] and 9 indexes [20–28]), plotted across the four quadrants of QOL based on their respective indicators. The numbers correspond to the numbers in Fig.  4 and to the numbers under the column heading “No.” in Tables  3 , S2 and S3

Methodological construct for QOL assessment

Unit of analysis.

The results revealed that QOL assessments varied greatly in terms of context or unit of analysis. With the exception of González et al. ( 2011a ), the studies (articles) reviewed were conducted at the level of either census tract or neighborhood (C T /N), municipality or city (M/C), district or province (D/P), region or state (R/S), or country (C) (Table  3 ). In González et al. ( 2011a ), QOL assessment was conducted at three different administrative levels: M/C, D/P, and R/S. Of the nine indexes reviewed, eight were designed for country-level assessments, of which some could also be applied to sub-national level assessments (e.g., GPI and SESI; see also description in Table ​ Table3). 3 ). Of all the indexes, GPI appeared to be the most flexible as it could also be applied at the M/C, D/P, and R/S levels, in addition to the country level. Of the studies (articles) reviewed, 47% assessed QOL in an urban area or city, two of which focused on transport systems (Table S2 ; see also description in Table ​ Table3). 3 ). Eight of the nine indexes were designed for general assessment without targeting any particular sector, like urban areas or cities. COQOL is designed for QOL assessment in cities.

Table 3

Summary table highlighting some of the salient features of the references reviewed (articles [1–19] and indexes [20–28]). The table also indicates whether a particular reference used unequal weights (UW) during aggregation (dimension level) and whether it derived an overall composite index (OCI). The column called “No.,” which stands for number, corresponds to the column called “No.” in Tables S2 and S3 , and to the numbers in Figs.  4 and ​ and5. 5 . C T /N—census tract/neighborhood; M/C—municipality or city; D/P—district or province; R/S—region or state; and C—country. Indexes: HDI (UNDP 1990 , 2010 , 2013 ); GPI (Cobb et al. 1995 ; Talberth and Weisdorf 2017 ); HPI (Marks 2006 ; NEF 2016 ); COQOL (PwC 2016 ); IHDI (UNDP 2010 , 2013 ); BLI (OECD 2011 , 2017 ); HSDI (Togtokh 2011 ); SPI (Porter et al. 2014 ; Stern et al. 2017 ); and SESI (Estoque and Murayama 2014a , 2017 )

a This reference presents a rule-based expert system for evaluating QOL. The intended unit of analysis was not explicitly mentioned. The testing of its prototype was performed in two universities. b HDI and IHDI are mainly used at the country level, though they are also used at the province or state level in some countries. c The BLI has no final index, but its web application allows users to assign weights to its dimensions. d The SESI can be applied across the units of analysis mentioned provided the required data are available. In this table, Reference Nos. (articles) 2–4, 8–9, 12, and 15–17 assessed QOL in an urban area or city, two of which focused on the transport system (4 and 8). Except for Reference Nos. 19 (article) and 23 (index), which respectively focused on tourism and urban/city, the rest of the references (articles and indexes) were designed for general assessments. More details can be found in Table S2

Methodological framework

The methodological framework employed by the references reviewed generally follows the principles of hierarchical aggregation (Fig.  6 ). This means that indicators are aggregated first, followed by the aggregation of the dimensions to produce a composite index. Of the references reviewed, 86% derived an overall composite index (OCI) (Table  3 ). The other 14% either did not aggregate at all (e.g., Carse 2011 ), or had their aggregation stopped at the dimension level (e.g., COQOL, PwC 2016 ). Of those that derived an OCI, 58% used unequal weights (UW) for their dimensions (Table  3 ), while the rest either explicitly used equal weights, simply derived the arithmetic or geometric mean, or had their own models for aggregation (Table S2 ). The BLI (OECD 2011 , 2017 ) does not have an OCI, but its web application allows users to assign weights to its dimensions.

A generalized and simplified flowchart for deriving an overall composite index based on hierarchical aggregation. Of the references reviewed, 86% derived an overall composite index, and 58% of these used unequal weights in the aggregation of their dimensions (see Tables ​ Tables3 3 and S2 ). The dotted line between the dimension boxes and the overall composite index box indicates that not all of the references reviewed derived an overall composite index. Here, dimensions also refer to domains, components or their equivalent. In some cases, sub-indicators, called variables in the figure, were also used (e.g., Royuela et al. 2003 )

QOL and climate change and variability issues: their connections

The results revealed that climate-related keywords such as climate change, vulnerability, adaptive capacity, sensitivity, exposure, hazard, and risk were not [yet] popular among QOL scholars (Figs.  3 , S1). Nevertheless, we recognize that some of the references reviewed included some essential climate variables like temperature and rainfall (Royuela et al. 2003 ; Li and Weng 2007 ; Rao et al. 2012 ; Morais and Camanho 2011 ), as well as indicators like exposure and sensitivity to climate hazards (Estoque and Murayama 2014a , 2017 ), and thermal comfort and natural disaster exposure and preparedness (PwC 2016 ) (see also Table S2 ).

Research trend and potential gaps in QOL research

The bibliometric analysis revealed an overall significant increase in article publications concerning QOL assessment over the past 18 years, indicating that this field of study is receiving attention from the research and academic communities. In general, bibliometric analysis supports the evaluation of research trends in a particular field of study (Englund et al. 2017 ; Jurgilevich et al. 2017 ; Runting et al. 2017 ; Sweileh 2017 ). Besides providing guidance, it can encourage and challenge researchers to conduct further studies. In addition to the temporal data from article publications, the resulting research topics or keywords from this review (including their occurrences and networks) can be used to identify research trends and potential gaps in QOL research. We acknowledge that our approach for refining the research areas to be included in the second stage of the bibliometric analysis of QOL assessments that are more general in context was rather subjective. Nonetheless, the approach proved to be useful as it resulted in a more diverse set of keywords, favorable to the purpose of this review.

For instance, in our bibliometric analysis, the inclusion of keywords that go beyond the realms of medicine and health-related fields (e.g., “urban quality of life,” “environment,” “informal settlement,” “social indicators,” “municipalities,” “poverty,” and “remote sensing”) (Fig.  3 ) indicates that QOL assessments based on a more general perspective are becoming increasingly common. However, we observed that the aforementioned keywords still had low occurrences and weak connections with QOL (Fig.  3 ), indicating a need for further studies in their respective contexts. For example, although the keyword “environment” has been used by some scholars in their respective QOL assessments, its occurrence and connection with the keywords “quality of life” or “well-being” remained low and weak (Fig.  3 ). This could be due to the focus of the assessment, which might not be directly related to the environment, and/or the decision of the authors regarding their choice of keywords. Another plausible reason is that “environment” might have been perceived as having little importance in the context of the QOL assessment being performed, or not related to QOL at all. In fact, four of the references reviewed did not include any indicator of environment in their respective assessments or index development (UNDP 1990 , 2010 , 2013 ; Rinner 2007 ; Narayana 2009 ) (Fig.  4 ; Table S2 ). Furthermore, the observed low occurrence of the keyword “environment” and its weak connection with QOL could also signify a research gap, indicating that more studies are required to reveal the importance of natural capital to people’s QOL and well-being, as well as the human impact on the environment.

The results additionally revealed that some of the key environment-related concepts today were not popular among QOL authors in their choice of keywords, such as sustainable development (or sustainability), natural capital, and ecosystem services (Figs.  3 , S1). In fact, the relationship between QOL and sustainable development has continued to constitute an important topic among scholars (e.g., Boersema 1995 ; Mackay and Probert 1995 ; Levett 1998 ; Porio 2015 ; Gazzola and Querci 2017 ). We noted that within the references reviewed, some authors either mentioned or related their QOL assessments to the concept of sustainable development (Doi et al. 2008 ; Carse 2011 ; Atanasova and Karashtranova 2016 ; Yu et al. 2016 ). However, given that the sustainable development (or sustainability) concept was not captured in the analysis (Fig.  3 ), this indicates that more studies are needed to shed light on its connection with QOL and its importance in the actual assessment of human well-being in general. This is especially pertinent because sustainability is not a well-defined concept (Beckerman 1994 ; Wu 2013 ).

It is possible that one way of illustrating the connection between QOL and the concept of sustainable development is through the use of bridging concepts, such as the natural capital and ecosystem services concepts. Natural capital includes environments that generate and provide valuable ecosystem services to people (Costanza and Daly 1992 ; MEA 2005 ). The fresh air we breathe, the clean water we drink, the wood and medicinal plants we harvest, the coastal protective role that mangroves play, and the shade that trees provide (to name a few) are all considered ecosystem services. These services impact the quality of living and well-being of the populace because they are felt and experienced directly by people, and not “sustainable development” per se. However, in order to ensure the sustainability of these services, the concept of sustainable development must be observed and put into practice. The quantity and quality of these services today and in the future are contingent on human actions, i.e., what was done in the past and what is being done today. The United Nations recognizes that sustainable development is crucial to the QOL (UN 2015 ) and hence, the sustainability concept has been incorporated in most of the indexes reviewed (Fig. ​ (Fig.4 4 and Table S2 ).

Conceptualization and methodological construct for QOL assessment

Among the studies (articles) reviewed, differences in the interpretation and operationalization of the QOL concept were observed. These studies have addressed and used the QOL concept in the context of their respective assessments. For instance, in their attempt to develop an integrated evaluation method for accessibility, quality of life, and social interaction, Doi et al. ( 2008 ) anchored their interpretation of the QOL concept on the livability of the environment, both physical and social. In their assessment of general QOL, González et al. ( 2011a , b ) interpreted and operationalized the QOL concept based on social welfare. Rao et al. ( 2012 ) viewed the QOL concept as a function of objective socioeconomic and environmental variables, while other scholars have considered more specific variants of QOL, such as urban quality of life (Li and Weng 2007 ; Rinner 2007 ; Morais and Camanho 2011 ; Brambilla et al. 2013 ), transport quality of life (Carse 2011 ), and tourism-related community quality of life (Yu et al. 2016 ) (see Table S2 ).

Conversely, the indexes reviewed are built on more general concepts and are designed for much broader types of QOL-related assessments. Among these conceptual foundations are sustainable development (or sustainability), human development, social progress, better life, global cities, resilience, and the social-ecological system paradigm. In general, these varied conceptual foundations are indicative of the multidimensionality and flexibility, but also the amorphous nature, of the QOL concept. In line with the references reviewed, we contend that there is a constant need to be explicit and specific, theoretically and conceptually, when attempting to perform a QOL assessment. In fact, in previous reviews, a theoretical/conceptual foundation has been deemed among the most important criteria for evaluating QOL indicators and assessments (Hagerty et al. 2001 ; Pantisano et al. 2014 ). Clarification at the outset of an assessment can help elucidate the overall context, and facilitate the identification and selection of the relevant dimensions and indicators to be included.

Thus, given that the references reviewed have their own conceptualization of QOL or QOL-related indexes according to their respective purposes, their respective sets of dimensions and indicators also varied (Table S2 ). Nevertheless, all of the indicators used can be related to the triple bottom line of sustainability (Fig.  4 ). While we found that HDI and IHDI did not include indicators related to the environment (UNDP 2013 ), two of the articles reviewed also did not include any indicator that could generally be classified under the environmental dimension (Rinner 2007 ; Narayana 2009 ) (Fig.  4 ). In terms of the social dimension, all the references considered at least one indicator, but in terms of the economic dimension, three of the articles (Narayana 2009 ; Brambilla et al. 2013 ; Kapuria 2014 ) and two of the indexes, viz. HPI (Marks 2006 ; NEF 2016 ) and SPI (Porter et al. 2014 ; Stern et al. 2017 ), did not consider any economic indicator. SPI is designed to measure social progress directly based on social and environmental outcomes, independent of economic development (Porter et al. 2014 ; Stern et al. 2017 ). On the other hand, HPI is designed to be a measure of sustainable well-being based on how efficiently residents in different countries use natural resources to achieve long lives and high levels of well-being (Marks 2006 ; NEF 2016 ).

The results also revealed that many of the references considered subjective well-being in their respective assessments (Fig.  4 ; Table S3 ). Overall, while the results (i.e., varying conceptual foundations, dimensions, indicators, and units of analysis) were somewhat expected due to the nature of the QOL concept, they were indicative of the diversity of dimensions and indicators that could be linked to the QOL concept. The extensive list of research areas identified in this review (Table S1 ) is another indication of the wide-ranging scope of the QOL concept. QOL assessments can also be performed across multiple spatial scales or administrative levels, although we recognize that most of the indexes reviewed are designed for country-level assessments (Table  3 ).

The four quadrants in Fig.  5 depict the four qualities of life according to Veenhoven ( 2000 , 2007 ). The results revealed that only 39% of the references reviewed considered at least one indicator under each QOL. Six of the nine indexes (67%) and five of the 19 articles (26%) reviewed considered at least one indicator under each QOL. This indicates that the indexes reviewed are, to some extent, relatively more holistic in their respective approaches to QOL-related assessments, i.e., as per the four qualities of life (Veenhoven 2000 , 2007 ). The four quadrants in Fig.  5 essentially capture the general dimensions of the triple bottom line and people’s subjective well-being (Fig.  4 ). In fact, by considering one’s contribution to society and the environment (Veenhoven 2000 , 2007 ), Q3 is also explicit in taking “leakage effects” into account, or the external environmental impact of development (Estoque and Murayama 2014b ).

In the methodological construct of QOL assessment and QOL-related index development, we need to consider important factors such as the purpose of the assessment or index, the multidimensionality of the QOL concept, the time and unit of analysis, and data availability in the selection of dimensions, indicators, and their corresponding variables (Rinner 2007 ; Grasso and Canova 2008 ; Narayana 2009 ; González et al. 2011a , b ; Morais and Camanho 2011 ; Li and Wang 2013 ; Kapuria 2014 ; Soleimani et al. 2014 ). Data availability is also critical to the testing and further development of various QOL-related indexes, e.g., BLI (OECD 2011 , 2017 ), COQOL (PwC 2016 ), GPI (Talberth and Weisdorf 2017 ), HPI (NEF 2016 ), SESI (Estoque and Murayama 2014a , 2017 ), and SPI (Porter et al. 2014 ; Stern et al. 2017 ). Data can be based on surveys (respondents’ perceptions) and/or census statistics and other sources such as geospatial (remote sensing and GIS) datasets.

In generating an overall composite index, weighting and aggregation methods also varied across studies and indexes (Table S2 ). While this indicates that a common approach to this purpose is unavailable, it is also indicative of the richness of the potential approaches that can be applied, explored, and further developed. In fact, it has been noted that the strengths and weaknesses of composite indicators largely depend on the stages of index development, including the weighting and aggregation methods used (OECD 2008 ). Some scholars prefer to use equal weights based on the literature (Royuela et al. 2003 ; Narayana 2009 ) or owing to the absence of empirical evidence or scientific basis (Estoque and Murayama 2014a , 2017 ). The subject of weighting is discussed in detail in other publications (Hagerty and Land 2007 ; OECD 2008 ; Hsieh 2014 ; Hsieh and Kenagy 2014 ).

Some scholars also prefer not to aggregate (Carse 2011 ; Lin 2013 ; PwC 2016 ; Yu et al. 2016 ). There are two sides to the argument regarding aggregation. On the one hand, composite indicators have the ability to reveal the results of an integrated analytical framework, capture the bigger picture, and provide summary statistics that can communicate system status and trends to a wide range of audiences (Baptista 2014 ; Estoque and Murayama 2017 ). They are also “suitable tools whenever the primary information of an object is too complex to be handled without aggregations” (Müller et al. 2000 , p. 13). Conversely, “composite indicators are also criticized for their tendencies to [lose information (Carse 2011 )], ignore or omit important dimensions that are difficult to measure, disguise weaknesses in some components, overlook the interconnectedness of indicators, and misrepresent the observed condition or process due to oversimplification…, [thus] have the potential to misguide policy and practice” (Estoque and Murayama 2017 , p. 613). Furthermore, there is always doubt whether the aggregation of QOL dimensions or indicators can actually reflect the quality of people’s lives (Schneider 1976 ; Lin 2013 ). Therefore, it is necessary for one to pay attention to these issues when using a composite index. Estoque and Murayama ( 2017 , p. 613) have argued that “specific indicators should be given more attention at the planning and policy levels, rather than focusing only on the summary statistic provided by the composite indicator.” Here, the hierarchical structure of a QOL assessment (Fig.  6 ) serves as a diagnostic tool to reveal which of the dimensions and indicators (or their variables, if available) are most responsible for high or low overall composite index values.

Linking QOL with climate change and variability issues

It is indisputable that the IPCC’s assessment reports (AR1–AR5) have helped raise people’s awareness (at least those in the environmental science field) of the social-ecological impacts of climate change and variability, as well as possible mitigation and adaptation measures. In fact, ‘quality of life’ has been explicitly mentioned in these reports (e.g., AR3, IPCC 2001 ). However, the results of this review provide very little evidence regarding the relationship between QOL and issues of climate change and variability as far as the references reviewed are concerned (Figs.  3 , S1 ; Table S2 ). Hence, overall, we believe that there remains a need to expand the scope of QOL research to include climate-related issues more explicitly.

We recognize that this attempt to explicitly connect QOL with climate-related issues is not new. For instance, in the mid-1970s, Hoch and Drake ( 1974 ) examined the relationship between wage rates and climatic variables (precipitation, temperature, and wind velocity) hypothesizing that higher wages compensated for lower quality of life. In their study, they found evidence in support of this hypothesis, the applications of which included estimating changes in real income given specified climate changes. Furthermore, Roberts ( 1976 ) highlighted the impacts of climate change and variability on the quality and character of life for millions of the Earth’s people. In particular, he emphasized impending world food shortages due to population growth, the demands of the affluent on available food supplies, and climate variability.

In a more recent case study, also in the context of QOL, Albouy et al. ( 2014 ) developed a hedonic framework to estimate US households’ preferences regarding local climates. They found that Americans would pay more on the margin to avoid excess heat than cold. In their review, Adger et al. ( 2013 ) highlighted the importance and role of cultural factors or services in climate change adaptation. They postulated that while place attachment contributes to QOL, this cultural value might be lost if people were forced to relocate as part of the strategy to adapt to climate change. Moreover, in a recent review of the behavioral impacts of global climate change, Evans ( 2019 , p. 6.1) posited that “droughts, floods, and severe storms diminish quality of life, elevate stress, produce psychological distress, and may elevate interpersonal and intergroup conflict… [and that] recreational opportunities are compromised by extreme weather, and children may suffer delayed cognitive development.”

In summary, these publications have considered wage rates (Hoch and Drake 1974 ), food (Roberts 1976 ), place attachment (Adger et al. 2013 ), the impacts of exposure to climate on comfort, activity, and health, including time use and mortality risk (Albouy et al. 2014 ), and behavioral impacts (Evans 2019 ) as indicators to bridge QOL and issues of climate change and variability. However, overall, QOL assessments in the context of climate-related issues remain limited. We believe that in order to help advance the “QOL-Climate” subfield of QOL research, a framework identifying and establishing the connection between QOL and climate-related issues is needed. Thus, drawing on the above insights regarding (i) the impacts of climate change and variability, (ii) QOL-Climate connection, and (iii) the results of this review on general QOL assessment, we present a general framework that could potentially link QOL and issues of climate change and variability.

On the right-hand side of Fig.  7 is a general structure for QOL assessment built upon the dimensions of the triple bottom line (economic, social, environmental) and subjective well-being (satisfaction, happiness, fulfillment, welfare, etc.) as summarized from the references reviewed. While the integrative definition of QOL suggests that it is the extent to which objective human needs are fulfilled in relation to personal or group perceptions of subjective well-being that defines QOL (Costanza et al. 2007 ; Table  1 ), this review finds that QOL can be based on objective indicators and/or subjective well-being (Fig. ​ (Fig.4). 4 ). However, it should be noted that although this is a generalized structure (Fig.  7 —right side), some studies did not have a well-defined set of dimensions (Li and Weng 2007 ; Narayana 2009 ; Rao et al. 2012 ) (Table S2 ) and did not generate an overall composite index (Carse 2011 ; PwC 2016 ; Yu et al. 2016 ) (Table  3 ). As discussed above, some of the references also did not include subjective well-being in their respective assessments (Fig.  4 ).

The “QOL-Climate” assessment framework: a general framework for assessing quality of life, considering the social-ecological impacts of climate change and variability. Key references used in the development of this framework include IPCC’s AR5 on climate-related issues, Ostrom ( 2009 ) on the social-ecological system paradigm, Costanza et al. ( 2007 ) on the integrative definition of QOL, Elkington ( 1994 , 1997 ) on the triple bottom line, www.forumforthefuture.org on the five capitals, and www.pik-potsdam.de on impact chain analysis. Also included are references reviewed for some examples of indicators, and the syntheses in this review for the overall structure of the diagram

On the left-hand side of the diagram (Fig.  7 ) is a structure that illustrates the connection between climate change and variability and the components of a social-ecological system (i.e., essentially the ecosystems and sectors of society that produce the five capitals). Here, climate-related impacts across ecosystems and sectors of society are clarified through a climate impact chain analysis (in short: impact chain). An impact chain is “a general representation of how a given climate stimulus propagates through a system of interest via the direct and indirect impacts it entails” ( www.pik-potsdam.de ). For instance, a climate stimulus such as sea level rise can result in land loss, which then can trigger havoc to agricultural production and rural and urban areas, as well as necessitate migration ( www.pik-potsdam.de ). This analysis is important because it can help reveal the impacts of climate change and variability on the five capitals (human, social, natural, financial, and manufactured; www.forumforthefuture.org ) that provide goods and services to people.

In the center of the diagram are indicators (Fig.  7 ), their status being dependent on the condition of the capitals that produce them. The hypothesis is that the resulting QOL, through these indicators, depends on the status of the five capitals, which is also contingent on the extent of climate-related impacts at a given point in time. A feedback loop is drawn from the QOL and its dimensions to the social-ecological system components, indicating that the resulting level of QOL can be used as a driving force for policy intervention and adaptive planning (Fig.  7 ).

Such planning and policy interventions should be able to limit the exposure of the social-ecological system components and their sub-components to climate hazards and reduce their vulnerability to climate change and variability. The latter might be achieved by improving their adaptive capacities and reducing their sensitivities or susceptibilities to harm (IPCC 2014a , b ). In the context of adaptive planning and policy intervention, the hierarchical structure of a QOL assessment (Figs.  6 , ​ ,7—right 7 —right side) can help diagnose which of the outcome indicators (or their variables, if available) need to be prioritized. This cyclic process of the framework is similar to those of other frameworks used in health, development, and environment-related monitoring and evaluation, such as the pressure-state-response (PSR) framework (OECD 1993 ) and the driving force-pressure-state-effect-action (DPSEA) framework (Kjellström and Corvalán 1995 ).

However, the lack of data regarding direct experience with climate change and variability (Evans 2019 ) can represent a major challenge in the operationalization of this proposed “QOL-Climate” assessment framework. We also recognize that all of these insights may not be easy to put into actual practice because every ecosystem and every sector of society may need its own set of interventions. Such interventions are among the hot issues today in the context of climate change adaptation, not only among scholars but also among planners and policy-makers. In a broader context, nature-based solutions or NbS is currently being considered as a potential approach to addressing global societal challenges, including those related to water security, food security, human health, disaster risk reduction, and climate change and variability (Cohen-Shacham et al. 2016 ). Among the ecosystem-based approaches within the NbS family are ecosystem restoration approaches (e.g., ecological restoration, ecological engineering, and forest landscape restoration), issue-specific ecosystem-related approaches (e.g., ecosystem-based approaches, ecosystem-based mitigation, climate adaptation services, and ecosystem-based disaster risk reduction), and green infrastructure and natural infrastructure approaches (for details, see Cohen-Shacham et al. 2016 ).

Methodology-related discussion

We recognize that the findings presented above are limited by the methods applied, and they should be interpreted with those caveats in mind. This is especially true of the search terms used, which focused on quality of life assessment, evaluation, or measurement, without the inclusion of other QOL-related terms like happiness, subjective well-being, and life satisfaction, or climate-related terms such as climate change, climate impacts, vulnerability, and adaptation. Nevertheless, we believe that the search terms used have provided equal opportunity for all research articles in the database to be selected, regardless of their focus (happiness, climate impacts, etc.) for as long as the terms (Fig.  1 ) were explicitly mentioned in their respective titles.

The selection of the scientific database(s) to be used is a very important consideration at the initial stage of any systematic review that adopts the ROSES principles and protocols. The selection of database(s) and the rationale behind their use often depend on their accessibility to users (reviewers), who are themselves reliant on their personal or their institutions’ subscriptions. Our case is no different. Had we included additional scientific databases, more research articles might have been captured. Nevertheless, as we mentioned in “ Searching ” section, it has been shown that WoS (the database we used) can be used on its own as a source for a major systematic review work (Runting et al. 2017 ). That being said, we support any future attempt to replicate this review involving a greater number of scientific databases.

Our selection of the nine QOL-related indexes was also rather subjective. Our intention was to include some relatively old indexes that are still in use (e.g., HDI, GPI), and others that are emerging (e.g., SPI, BLI), as well as peer-reviewed (e.g., SESI and GPI) indexes. As we mentioned in “ Introduction ” section, there exists a number of reviews that can be consulted for a more extensive list and a focused review of QOL-related indexes (e.g., Hagerty et al. 2001 ; Pantisano et al. 2014 ).

Summary and concluding remarks

Based on the principles of ROSES, we have presented a systematic review aimed at gaining insights regarding the conceptualization and methodological construct of previous studies and assessments of QOL and of selected existing and emerging QOL-related indexes. The knowledge gained was used to develop a framework that might link QOL with climate-related issues. Our review revealed that (i) QOL assessments varied in terms of conceptual foundations, dimensions, indicators, and units of analysis, (ii) compared with economic and environmental indicators, social indicators were consistently used across assessments; (iii) most assessments considered indicators that were related to the life-ability of a person, enjoyment of life, utility of life, and especially the livability of the environment, and (iv) QOL could be based on objective indicators and/or subjective well-being, and on a composite index or unaggregated dimensions and indicators. Our review also revealed that QOL assessments remain poorly connected with climate-related issues. We consider this as an important gap in QOL research, which needs to be filled by expanding the scope of such research. Our proposed “QOL-Climate” assessment framework, which is designed to capture the social-ecological impacts of climate change and variability, can potentially help in this regard.

Just like many key concepts such as sustainability, freedom, justice, and democracy (Daly 1995 ; Wu 2013 ) that have emerged in this contemporary geological epoch, the Anthropocene (the age of man) (Crutzen 2002 ), QOL represents a complex and dialectically vague concept (Massam 2002 ; Moons et al. 2006 ; Barcaccia et al. 2013 ). However, although all of these concepts possess elements of ambiguity, they convey fundamental principles that guide our actions and shape our visions for the future (see also Wu 2013 ). Consequently, we argue that, like the aforementioned concepts, QOL is considered a term of great importance to humankind. We are today faced with various pressing issues, including the social-ecological impacts of climate change and variability. Scholars from various fields are encouraged to work together so that this subfield of QOL research, which we have labeled “QOL-Climate,” will advance for the benefit of all.

Below is the link to the electronic supplementary material.

Acknowledgements

This work was supported by the Ministry of Environment, Japan, through Research Grants S2-1708 and S15. The conclusions and recommendations presented in this article are of the authors and do not, in any way, represent the views of the funder.

Biographies

is a Research Associate at the National Institute for Environmental Studies, Japan. His research interests include quality of life assessment, sustainability assessment, climate change vulnerability, impact and adaptation assessment, and the applications of geospatial technologies (remote sensing and geographic information systems) for social-ecological studies, including the monitoring and assessment of land-use/land-cover changes and ecosystem services.

is a Researcher at the National Institute for Environmental Studies, Japan. His research interests include quality of life indicators, sustainability indicators, applied mathematical optimization, and regional and urban environment design theory.

is a Section Head at the National Institute for Environmental Studies, Japan. His research interests include quality of life assessment, ecosystem services assessment, climate change vulnerability, impact and adaptation assessment, environmental ethics, and information science.

is a Senior Researcher at the National Institute for Environmental Studies, Japan. His research interests include integrated modeling, regional sciences, demography, and climate change mitigation and adaptation scenarios.

is a Researcher at the National Institute for Environmental Studies, Japan. His research interests include rural planning, social capital, sustainability, rural resource management, and community environmental management.

is a Section Head at the National Institute for Environmental Studies, Japan. His research interests include the analysis of environmental issues related to climate change, and the development of an integrated assessment model to assess climate change impacts and adaptation measures, as well as policy options for stabilizing global climate.

is a Deputy Director at the National Institute for Environmental Studies, Japan. Her research interests include international and institutional negotiations concerning climate change based on theories and methodologies of international relations, and policies towards a sustainable society, including its assessment.

Contributor Information

Ronald C. Estoque, Email: [email protected] , Email: ku.oc.oohay@k2snor .

Takuya Togawa, Email: [email protected] .

Makoto Ooba, Email: [email protected] .

Kei Gomi, Email: [email protected] .

Shogo Nakamura, Email: [email protected] .

Yasuaki Hijioka, Email: pj.og.sein@akoijih .

Yasuko Kameyama, Email: pj.og.sein@emaky .

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A Complete World Literature Review of Quality of Life (QOL) in Patients with Kidney Stone Disease (KSD)

Affiliations.

• 1 Department of Urology, University Hospital Southampton NHS Trust, Southampton, SO16 6YD, UK.
• 2 Department of Urology, University Hospital Southampton NHS Trust, Southampton, SO16 6YD, UK. [email protected].
• PMID: 27771854
• PMCID: PMC5075340
• DOI: 10.1007/s11934-016-0647-6

Purpose of review: The purpose of this study was to review the current evidence for quality of life (QOL) in patients with kidney stone disease (KSD).

Recent findings: A review of literature from inception to May 2016 for all prospective English language articles on QOL in patients with KSD was done. QOL studies post urological procedures or ureteric stents were excluded. Nine studies (1570 patients) were included of which most (n = 6) used the SF-36 QOL tool. Overall, seven of the nine studies demonstrated a lower QOL in patients with KSD. Bodily pain and general health were significantly lower in patients with KSD compared to their control groups. Patients with KSD have an overall lower QOL with most impact on bodily pain and general health domains. Compared to the scale of patients suffering from KSD, more work needs to be done in measuring QOL both in terms of 'Stone specific' QOL measuring tools and the quality/number of studies in this field.

Keywords: KSD; Kidney stone disease; QOL; Quality of life.

Publication types

• Health Status*
• Kidney Calculi / complications
• Kidney Calculi / psychology*
• Pain / etiology
• Pain / psychology*
• Quality of Life / psychology*

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A LITERATURE REVIEW ON TRAINING & DEVELOPMENT AND QUALITY OF WORK LIFE

In this competitive world, training plays an important role in the competent and challenging format of business. Training is the nerve that suffices the need of fluent and smooth functioning of work which helps in enhancing the quality of work life of employees and organizational development too. Development is a process that leads to qualitative as well as quantitative advancements in the organization, especially at the managerial level, it is less considered with physical skills and is more concerned with knowledge, values, attitudes and behaviour in addition to specific skills. Hence, development can be said as a continuous process whereas training has specific areas and objectives. So, every organization needs to study the role, importance and advantages of training and its positive impact on development for the growth of the organization. Quality of work life is a process in which the organization recognizes their responsibility for excellence of organizational performance as well as employee skills. Training implies constructive development in such organizational motives for optimum enhancement of quality of work life of the employees. These types of training and development programs help in improving the employee behaviour and attitude towards the job and also uplift their morale. Thus, employee training and development programs are important aspects which are needed to be studied and focused on. This paper focuses and analyses the literature findings on importance of training and development and its relation with the employees' quality of work life.

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Quality of Work Life (QWL) of employees in any organization plays a very vital role in shaping of both the employees and the organization. The objective of this research is to highlight the prominence of training and development programmes adopted in manufacturing industries encompassing the private and public sectors and the impact that it exerts on the quality of work life of employees in these sectors. It is assumed that employees who undergo T & D programme either in private or public sectors enjoy better QWL. Here a comparative study among the employees of private and public manufacturing industries is carried out to measure the QWL of employees in these respective sectors. Hence the research concludes that the QWL enjoyed by the employees of private industries is superior to the QWL of employees of public industries.

Noble Academic Publisher

josiah emmanuel

International Journal of Latest Technology in Engineering, Management & Applied Science -IJLTEMAS (www.ijltemas.in)

In this era where competition is increasing day by day in the corporate world training and development has become one of the important key to achieve success. Training is an important subsystem of Human Resource Development. It is a specialized function and is one of the fundamental operative functions for known resource management. Development is a long-term educational process utilizing a systematic and organized procedure by which managerial personnel get conceptual and theoretical knowledge. Basically, it is an attempt to improve the current or future employee performance of the employee by increasing his or her ability to perform through learning, usually by changing the employee’s attitude or increasing his or her skills and knowledge. These types of training and development programs help in improving the employee behavior and attitude towards the job and also uplift their morale. Thus, employee training and development programs are important aspects which are needed to be studied and focused on. This paper focusses on the advantages of the training and development for the employee’s.

International Journal of Scientific Research in Science and Technology IJSRST

The purpose of this paper is to present a conceptual study established on the employee training and development program and its benefits. This paper will inspect the structure and elements of employee training and development program and later the study present what are the positive outcomes for employees and organizations. Training and development play an important role in the effectiveness of organizations and to the experiences of people in work. Training has implications for productivity, health and safety at work and personal development. Modern organizations therefore use their resources (money, time, energy, information, etc.) for permanent training and advancement of their employees. Training and development is an instrument that aid human capital in exploring their dexterity. Therefore training and development is vital to the productivity of organization " s workforce. The study described here is a vigilant assessment of literature on fundamental of employee development program and its benefits to organizations and employees.

Dr Yashpal D Netragaonkar

“ To Study the Effectiveness of Employees Training & Development Program ”. The prime objective of research is to study the changes in skill , attitude, knowledge, behavior of Employees after Training program. It also studies the effectiveness of Training on both Individual and Organizational levels. Due to this research we are able to absorb current trends related to whole academic knowledge a nd its practical use. Such research is exposed us to set familiar with professional environment, working culture, behavior, oral communication & manners. Since the training is a result oriented process and a lot of time and expenditure, it is necessary tha t the training program should be designed with a great care. For evaluating effectiveness if training a questionnaire has to be carefully prepared for participants in order to receive feedback.

Venkata Sandeep

Tolulope J Ogunleye

Overtime, study had shown that to be relevant in any field of work there is need for continuous learning through training and development. The study is aimed at finding out the need for employees training and development in an organization. The need for improvement to change the phenomenon of low productivity and poor service delivery attributed to the employee’s in-adequate experience, calls for investigation on how effective training and development of employee can facilitate improved corporate performance using the banking industry as a field of discuss.. The study concluded that training and development brings about career growth for the employees and bankers thus the study recommended that all organization must do induction training at entry point into the banking sector.

International Journal of Research Publication (IJRP)

IAEME PUBLICATION

Training and development enables to develop skills and competencies necessary to enhance bottom-line results for their organization. It is a key ingredient for organizational performance improvement. It ensures that randomness is reduced and learning or behavioural change takes place in structured format. Training and Development helps in increasing the job knowledge and skills of employees at each level and helps to expand the horizons of human intellect and an overall personality of the employees. This paper analyses the link between various Training and Development programs organized in Larsen &Toubro Group of Companies and their impacts on employee satisfaction and performance. Data for the paper have been collected through primary source that are from questionnaire, surveys. There were two variables: Training and Development (independent) and Employees satisfaction and performance (dependent). The goal was to see whether Training and development has an impact on employee’s satisfaction and performance

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Understanding the influence of different proxy perspectives in explaining the difference between self-rated and proxy-rated quality of life in people living with dementia: a systematic literature review and meta-analysis

• Open access
• Published: 24 April 2024

Cite this article

You have full access to this open access article

• Lidia Engel   ORCID: orcid.org/0000-0002-7959-3149 1 ,
• Valeriia Sokolova 1 ,
• Ekaterina Bogatyreva 2 &
• Anna Leuenberger 2  

Proxy assessment can be elicited via the proxy-patient perspective (i.e., asking proxies to assess the patient’s quality of life (QoL) as they think the patient would respond) or proxy-proxy perspective (i.e., asking proxies to provide their own perspective on the patient’s QoL). This review aimed to identify the role of the proxy perspective in explaining the differences between self-rated and proxy-rated QoL in people living with dementia.

A systematic literate review was conducted by sourcing articles from a previously published review, supplemented by an update of the review in four bibliographic databases. Peer-reviewed studies that reported both self-reported and proxy-reported mean QoL estimates using the same standardized QoL instrument, published in English, and focused on the QoL of people with dementia were included. A meta-analysis was conducted to synthesize the mean differences between self- and proxy-report across different proxy perspectives.

The review included 96 articles from which 635 observations were extracted. Most observations extracted used the proxy-proxy perspective (79%) compared with the proxy-patient perspective (10%); with 11% of the studies not stating the perspective. The QOL-AD was the most commonly used measure, followed by the EQ-5D and DEMQOL. The standardized mean difference (SMD) between the self- and proxy-report was lower for the proxy-patient perspective (SMD: 0.250; 95% CI 0.116; 0.384) compared to the proxy-proxy perspective (SMD: 0.532; 95% CI 0.456; 0.609).

Different proxy perspectives affect the ratings of QoL, whereby adopting a proxy-proxy QoL perspective has a higher inter-rater gap in comparison with the proxy-patient perspective.

Avoid common mistakes on your manuscript.

Quality of life (QoL) has become an important outcome for research and practice but obtaining reliable and valid estimates remains a challenge in people living with dementia [ 1 ]. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria [ 2 ], dementia, termed as Major Neurocognitive Disorder (MND), involves a significant decline in at least one cognitive domain (executive function, complex attention, language, learning, memory, perceptual-motor, or social cognition), where the decline represents a change from a patient's prior level of cognitive ability, is persistent and progressive over time, is not associated exclusively with an episode of delirium, and reduces a person’s ability to perform everyday activities. Since dementia is one of the most pressing challenges for healthcare systems nowadays [ 3 ], it is critical to study its impact on QoL. The World Health Organization defines the concept of QoL as “individuals' perceptions of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns” [ 4 ]. It is a broad ranging concept incorporating in a complex way the persons' physical health, psychological state, level of independence, social relationships, personal beliefs, and their relationships to salient features of the environment.

Although there is evidence that people with mild to moderate dementia can reliably rate their own QoL [ 5 ], as the disease progresses, there is typically a decline in memory, attention, judgment, insight, and communication that may compromise self-reporting of QoL [ 6 ]. Additionally, behavioral symptoms, such as agitation, and affective symptoms, such as depression, may present another challenge in obtaining self-reported QoL ratings due to emotional shifts and unwillingness to complete the assessment [ 7 ]. Although QoL is subjective and should ideally be assessed from an individual’s own perspective [ 8 ], the decline in cognitive function emphasizes the need for proxy-reporting by family members, health professionals, or care staff who are asked to report on behalf of the person with dementia. However, proxy-reports are not substitutable for self-reports from people with dementia, as they offer supplementary insights, reflecting the perceptions and viewpoints of people surrounding the person with dementia [ 9 ].

Previous research has consistently highlighted a disagreement between self-rated and proxy-rated QoL in people living with dementia, with proxies generally providing lower ratings (indicating poorer QoL) compared with person’s own ratings [ 8 , 10 , 11 , 12 ]. Impairment in cognition associated with greater dementia severity has been found to be associated with larger difference between self-rating and proxy-rating obtained from family caregivers, as it becomes increasingly difficult for severely cognitively impaired individuals to respond to questions that require contemplation, introspection, and sustained attention [ 13 , 14 ]. Moreover, non-cognitive factors, such as awareness of disease and depressive symptoms play an important role when comparing QoL ratings between individuals with dementia and their proxies [ 15 ]. Qualitative evidence has also shown that people with dementia tend to compare themselves with their peers, whereas carers make comparisons with how the person used to be in the past [ 9 ]. The disagreement between self-reported QoL and carer proxy-rated QoL could be modulated by some personal, cognitive or relational factors, for example, the type of relationship or the frequency of contact maintained, person’s cognitive status, carer’s own feeling about dementia, carer’s mood, and perceived burden of caregiving [ 14 , 16 ]. Disagreement may also arise from the person with dementia’s problems to communicate symptoms, and proxies’ inability to recognize certain symptoms, like pain [ 17 ], or be impacted by the amount of time spent with the person with dementia [ 18 ]. This may also prevent proxies to rate accurately certain domains of QoL, with previous evidence showing higher level of agreement for observable domains, such as mobility, compared with less observable domains like emotional wellbeing [ 8 ]. Finally, agreement also depends on the type of proxy (i.e., informal/family carers or professional staff) and the nature of their relationship, for instance, proxy QoL scores provided by formal carers tend to be higher (reflecting better QoL) compared to the scores supplied by family members [ 19 , 20 ]. Staff members might associate residents’ QoL with the quality of care delivered or the stage of their cognitive impairment, whereas relatives often focus on comparison with the person’s QoL when they were younger, lived in their own home and did not have dementia [ 20 ].

What has been not been fully examined to date is the role of different proxy perspectives employed in QoL questionnaires in explaining disagreement between self-rated and proxy-rated scores in people with dementia. Pickard et al. (2005) have proposed a conceptual framework for proxy assessments that distinguish between the proxy-patient perspective (i.e., asking proxies to assess the patient’s QoL as they think the patient would respond) or proxy-proxy perspective (i.e., asking proxies to provide their own perspective on the patient’s QoL) [ 21 ]. In this context, the intra-proxy gap describes the differences between proxy-patient and proxy-proxy perspective, whereas the inter-rater gap is the difference between self-report and proxy-report [ 21 ].

Existing generic and dementia-specific QoL instruments specify the perspective explicitly in their instructions or imply the perspective indirectly in their wording. For example, the instructions of the Dementia Quality of Life Measure (DEMQOL) asks proxies to give the answer they think their relative would give (i.e., proxy-patient perspective) [ 22 ], whereas the family version of the Quality of Life in Alzheimer’s Disease (QOL-AD) instructs the proxies to rate their relative’s current situation as they (the proxy) see it (i.e., proxy-proxy perspective) [ 7 ]. Some instruments, like the EQ-5D measures, have two proxy versions for each respective perspective [ 23 , 24 ]. The Adult Social Care Outcome Toolkit (ASCOT) proxy version, on the other hand, asks proxies to complete the questions from both perspectives, from their own opinion and how they think the person would answer [ 25 ].

QoL scores generated using different perspectives are expected to differ, with qualitative evidence showing that carers rate the person with dementia’s QoL lower (worse) when instructed to comment from their own perspective than from the perspective of the person with dementia [ 26 ]. However, to our knowledge, no previous review has fully synthesized existing evidence in this area. Therefore, we aimed to undertake a systematic literature review to examine the role of different proxy-assessment perspectives in explaining differences between self-rated and proxy-rated QoL in people living with dementia. The review was conducted under the hypothesis that the difference in QoL estimates will be larger when adopting the proxy-proxy perspective compared with proxy-patient perspective.

The review was registered with the International Prospective Register of Systematic Reviews (CRD42022333542) and followed the Preferred Reporting Items System for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (see Appendix 1 ) [ 27 ].

Search strategy

This review used two approaches to obtain literature. First, primary articles from an existing review by Roydhouse et al. were retrieved [ 28 ]. The review included studies published from inception to February 2018 that compared self- and proxy-reports. Studies that focused explicitly on Alzheimer’s Disease or dementia were retrieved for the current review. Two reviewers conducted a full-text review to assess whether the eligibility criteria listed below for the respective study were met. An update of the Roydhouse et al. review was undertaken to capture more recent studies. The search strategy by Roydhouse et al. was amended and covered studies published after January 1, 2018, and was limited to studies within the context of dementia. The original search was undertaken over a three-week period (17/11/2021–9/12/2021) and then updated on July 3, 2023. Peer-reviewed literature was sourced from MEDLINE, CINAHL, and PsycINFO databases via EBSCOHost as well as EMBASE. Four main search term categories were used: (1) proxy terms (i.e., care*-report*), (2) QoL/ outcome terms (i.e., ‘quality of life’), (3) disease terms (i.e., ‘dementia’), and (4) pediatric terms (i.e., ‘pediatric*’) (for exclusion). Keywords were limited to appear in titles and abstracts only, and MeSH terms were included for all databases. A list of search strategy can be found in Appendix 2 . The first three search term categories were searched with AND, and the NOT function was used to exclude pediatric terms. A limiter was applied in all database searches to only include studies with human participants and articles published in English.

Selection criteria

Studies from all geographical locations were included in the review if they (1) were published in English in a peer-reviewed journal (conference abstracts, dissertations, a gray literature were excluded); (2) were primary studies (reviews were excluded); (3) clearly defined the disease of participants, which were limited to Alzheimer’s disease or dementia; (4) reported separate QoL scores for people with dementia (studies that included mixed populations had to report a separate QoL score for people with dementia to be considered); (5) were using a standardized and existing QoL instrument for assessment; and (6) provided a mean self-reported and proxy-reported QoL score for the same dyads sample (studies that reported means for non-matched samples were excluded) using the same QoL instrument.

Four reviewers (LE, VS, KB, AL) were grouped into two groups who independently screened the 179 full texts from the Roydhouse et. al (2022) study that included Alzheimer’s disease or dementia patients. If a discrepancy within the inclusion selection occurred, articles were discussed among all the reviewers until a consensus was reached. Studies identified from the database search were imported into EndNote [ 29 ]. Duplicates were removed through EndNote and then uploaded to Rayyan [ 30 ]. Each abstract was reviewed by two independent reviewers (any two from four reviewers). Disagreements regarding study inclusions were discussed between all reviewers until a consensus was reached. Full-text screening of each eligible article was completed by two independent reviewers (any two from four reviewers). Again, a discussion between all reviewers was used in case of disagreements.

Data extraction

A data extraction template was created in Microsoft Excel. The following information were extracted if available: country, study design, study sample, study setting, dementia type, disease severity, Mini-Mental Health State Exam (MMSE) score details, proxy type, perspective, living arrangements, QoL assessment measure/instrument, self-reported scores (mean, SD), proxy-reported scores (mean, SD), and agreement statistics. If a study reported the mean (SD) for the total score as well as for specific QoL domains of the measure, we extracted both. If studies reported multiple scores across different time points or subgroups, we extracted all scores. For interventional studies, scores from both the intervention group and the control group were recorded. In determining the proxy perspective, we relied on authors’ description in the article. If the perspective was not explicitly stated, we adopted the perspective of the instrument developers; where more perspectives were possible (e.g., in the case of the EQ-5D measures) and the perspective was not explicitly stated, it was categorized as ‘undefined.’ For agreement, we extracted the Intraclass Correlation Coefficient (ICC), a reliability index that reflects both degree of correlation and agreement between measurements of continuous variables. While there are different forms of ICC based on the model (1-way random effects, 2-wy random effects, or 2-way fixed effects), the type (single rater/measurement or the mean k raters/measurements), and definition of relationship [ 31 ], this level of information was not extracted due to insufficient information provided in the original studies. Values for ICC range between 0 and 1, with values interpreted as poor (less than 0.5), moderate (0.5–0.75), good (0.75–0.9), and excellent (greater than 0.9) reliability between raters [ 31 ].

Data synthesis and analysis

Characteristics of studies were summarized descriptively. Self-reported and proxy-reported means and SD were extracted from the full texts and the mean difference was calculated (or extracted if available) for each pair. Studies that reported median values instead of mean values were converted using the approach outlined by Wan et al. (2014) [ 32 ]. Missing SDs (5 studies, 20 observations) were obtained from standard errors or confidence intervals reported following the Cochrane guidelines [ 33 ]. Missing SDs (6 studies, 29 observations) in studies that only presented the mean value without any additional summary statistics were imputed using the prognostic method [ 34 ]. Thereby, we predicted the missing SDs by calculating the average SDs of observed studies with full information by the respective measure and source (self-report versus proxy-report).

A meta-analysis was performed in Stata (17.1 Stata Corp LLC, College Station, TX) to synthesize mean differences between self- and proxy-reported scores across different proxy perspectives. First, the pooled raw mean differences were calculated for each QoL measure separately, given differences in scales between measures. Secondly, we calculated the pooled standardized mean difference (SMD) for all studies stratified by proxy type (family carer, formal carers, mixed), dementia severity (mild, moderate, severe), and living arrangement (residential/institutional care, mixed). SMD accounts for the use of different measurement scales, where effect sizes were estimated using Cohen’s d. Random-effects models were used to allow for unexplained between-study variability based on the restricted maximum-likelihood (REML) estimator. The percentage of variability attributed to heterogeneity between the studies was assessed using the I 2 statistic; an I 2 of 0%-40% represents possibly unimportant heterogeneity, 30–60% moderate heterogeneity, 50–90% substantial heterogeneity, and 75%-100% considerable heterogeneity [ 35 ]. Chi-squared statistics (χ 2 ) provided evidence of heterogeneity, where a p -value of 0.1 was used as significance level. For studies that reported agreement statistics, based on ICC, we also ran a forest plot stratified by the study perspective. We also calculated Q statistic (Cochran’s test of homogeneity), which assesses whether observed differences in results are compatible with chance alone.

Risk of bias and quality assessment

The quality of studies was assessed using the using a checklist for assessing the quality of quantitative studies developed by Kmet et al. (2004) [ 36 ]. The checklist consists of 14 items and items are scored as ‘2’ (yes, item sufficiently addressed), ‘1’ (item partially addressed), ‘0’ (no, not addressed), or ‘not applicable.’ A summary score was calculated for each study by summing the total score obtained across relevant items and dividing by the total possible score. Scores were adjusted by excluding items that were not applicable from the total score. Quality assessment was undertaken by one reviewer, with 25% of the papers assessed independently by a second reviewer.

The PRISMA diagram in Fig.  1 shows that after the abstract and full-text screening, 38 studies from the database search and 58 studies from the Roydhouse et al. (2022) review were included in this review—a total of 96 studies. A list of all studies included and their characteristics can be found in Appendix 3.

PRISMA 2020 flow diagram

General study characteristics

The 96 articles included in the review were published between 1999 and 2023 from across the globe; most studies (36%) were conducted in Europe. People with dementia in these studies were living in the community (67%), residential/institutional care (15%), as well as mixed dwelling settings (18%). Most proxy-reports were provided by family carers (85%) and only 8 studies (8%) included formal carers. The mean MMSE score for dementia and Alzheimer’s participants was 18.77 (SD = 4.34; N  = 85 studies), which corresponds to moderate cognitive impairment [ 37 ]. Further characteristics of studies included are provided in Table  1 . The quality of studies included (see Appendix 4) was generally very good, scoring on average 91% (SD: 9.1) with scores ranging from 50 to 100%.

Quality of life measure and proxy perspective used

A total of 635 observations were recorded from the 96 studies. The majority of studies and observations extracted assumed the proxy-proxy perspective (77 studies, 501 observations), followed by the proxy-patient perspective (18 studies, 62 observations), with 18 studies (72 observations) not clearly defining the perspective. Table 2 provides a detailed overview of number of studies and observations across the respective QoL measures and proxy perspectives. Two studies (14 observations) adopted both perspectives within the same study design: one using the QOL-AD measure [ 5 ] and the second study exploring the EQ-5D-3L and EQ VAS [ 38 ]. Overall, the QOL-AD was the most often used QoL measure, followed by the EQ-5D and DEMQOL. Mean scores for specific QoL domains were accessible for the DEMQOL and QOL-AD. However, only the QOL-AD provided domain-specific mean scores from both proxy perspectives.

Mean scores and mean differences by proxy perspective and QoL measure

The raw mean scores for self-reported and proxy-reported QoL scores are provided in the Supplementary file 2. The pooled raw mean difference by proxy perspective and measure is shown in Table  3 . Regardless of the perspective adopted and the QoL instrument used, self-reported scores were higher (indicating better QoL) compared with proxy-reported scores, except for the DEMQOL, where proxies reported better QoL than people with dementia themselves. Most instruments were explored from one perspective, except for the EQ-5D-3L, EQ VAS, and QOL-AD, for which mean differences were available for both perspectives. For these three measures, mean differences were smaller when adopting the proxy-patient perspective compared with proxy-proxy perspective, although mean scores for the QOL-AD were slightly lower from the proxy-proxy perspective. I 2 statistics indicate considerable heterogeneity (I 2  > 75%) between studies. Mean differences by specific QoL domains are provided in Appendix 5, but only for the QOL-AD measure that was explored from both perspectives. Generally, mean differences appeared to be smaller for the proxy-proxy perspective than the proxy-patient perspective across all domains, except for ‘physical health’ and ‘doing chores around the house.’ However, results need to be interpreted carefully as proxy-patient perspective scores were derived from only one study.

Standardized mean differences by proxy perspective, stratified by proxy type, dementia severity, and living arrangement

Table 4 provides the SMD by proxy perspective, which adjusts for the different QoL measurement scales. Findings suggest that adopting the proxy-patient perspective results in lower SMDs (SMD: 0.250; 95% CI 0.116; 0.384) compared with the proxy-proxy perspective (SMD: 0.532; 95% CI 0.456; 0.609). The largest SMD was recorded for studies that did not define the study perspective (SMD: 0.594; 95% CI 0.469; 0.718). A comparison by different proxy types (formal carers, family carers, and mixed proxies) revealed some mixed results. When adopting the proxy-proxy perspective, the largest SMD was found for family carers (SMD: 0.556; 95% CI 0.465; 0.646) compared with formal carers (SMD: 0.446; 95% CI 0.305; 0.586) or mixed proxies (SMD: 0.335; 95% CI 0.211; 0.459). However, the opposite relationship was found when the proxy-patient perspective was used, where the smallest SMD was found for family carers compared with formal carers and mixed proxies. The SMD increased with greater level of dementia severity, suggesting a greater disagreement. However, compared with the proxy-proxy perspective, where self-reported scores were greater (i.e., better QoL) than proxy-reported scores across all dementia severity levels, the opposite was found when adopting the proxy-patient perspective, where proxies reported better QoL than people with dementia themselves, except for the severe subgroup. No clear trend was observed for different living settings, although the SMD appeared to be smaller for people with dementia living in residential care compared with those living in the community.

Direct proxy perspectives comparison studies

Two studies assessed both proxy perspectives within the same study design. Bosboom et al. (2012) found that compared with self-reported scores (mean: 34.7; SD: 5.3) using the QOL-AD, proxy scores using the proxy-patient perspective were closer to the self-reported scores (mean: 32.1; SD: 6.1) compared with the proxy-proxy perspective (mean: 29.5; SD: 5.4) [ 5 ]. Similar findings were reported by Leontjevas et al. (2016) using the EQ-5D-3L, including the EQ VAS, showing that the inter-proxy gap between self-report (EQ-5D-3L: 0.609; EQ VAS: 65.37) and proxy-report was smaller when adopting the proxy-patient perspective (EQ-5D-3L: 0.555; EQ VAS: 65.15) compared with the proxy-proxy perspective (EQ-5D-3L: 0.492; EQ VAS: 64.42) [ 38 ].

Inter-rater agreement (ICC) statistics

Six studies reported agreement statistics based on ICC, from which we extracted 17 observations that were included in the meta-analysis. Figure  2 shows the study-specific and overall estimates of ICC by the respective study perspective. The heterogeneity between studies was high ( I 2  = 88.20%), with a Q test score of 135.49 ( p  < 0.001). While the overall ICC for the 17 observations was 0.3 (95% CI 0.22; 0.38), indicating low agreement, the level of agreement was slightly better when adopting a proxy-patient perspective (ICC: 0.36, 95% CI 0.23; 0.49) than a proxy-proxy perspective (ICC: 0.26, 95% CI 0.17; 0.35).

Forest plot depicting study-specific and overall ICC estimates by study perspective

While previous studies highlighted a disagreement between self-rated and proxy-rated QoL in people living with dementia, this review, for the first time, assessed the role of different proxy perspectives in explaining the inter-rater gap. Our findings align with the baseline hypothesis and indicate that QoL scores reported from the proxy-patient perspective are closer to self-reported QoL scores than the proxy-proxy perspective, suggesting that the proxy perspective does impact the inter-rater gap and should not be ignored. This finding was observed across different analyses conducted in this review (i.e., pooled raw mean difference, SMD, ICC analysis), which also confirms the results of two previous primary studies that adopted both proxy perspectives within the same study design [ 5 , 38 ]. Our findings emphasize the need for transparency in reporting the proxy perspective used in future studies, as it can impact results and interpretation. This was also noted by the recent ISPOR Proxy Task Force that developed a checklist of considerations when using proxy-reporting [ 39 ]. While consistency in proxy-reports is desirable, it is crucial to acknowledge that each proxy perspective holds significance in future research, depending on study objectives. It is evident that both proxy perspectives offer distinct insights—one encapsulating the perspectives of people with dementia, and the other reflecting the viewpoints of proxies. Therefore, in situations where self-report is unattainable due to advanced disease severity and the person’s perspective on their own QoL assessment is sought, it is recommended to use the proxy-patient perspective. Conversely, if the objective of future research is to encompass the viewpoints of proxies, opting for the proxy-proxy perspective is advisable. However, it is important to note that proxies may deviate from instructed perspectives, requiring future qualitative research to examine the adherence to proxy perspectives. Additionally, others have argued that proxy-reports should not substitute self-reports, and only serve as supplementary sources alongside patient self-reports whenever possible [ 9 ].

This review considered various QoL instruments, but most instruments adopted one specific proxy perspective, limiting detailed analyses. QoL instruments differ in their scope (generic versus disease-specific) as well as coverage of QoL domains. The QOL-AD, an Alzheimer's Disease-specific measure, was commonly used. Surprisingly, for this measure, the mean differences between self-reported and proxy-reported scores were smaller using the proxy-proxy perspective, contrary to the patterns observed with all other instruments. This may be due to the lack of studies reporting QOL-AD proxy scores from the proxy-patient perspective, as the study by Bosboom et al. (2012) found the opposite [ 5 ]. Previous research has also suggested that the inter-rater gap is dependent on the QoL domains and that the risk of bias is greater for more ‘subjective’ (less observable) domains such as emotions, feelings, and moods in comparison with observable, objective areas such as physical domains [ 8 , 40 ]. However, this review lacks sufficient observations for definitive results on QoL dimensions and their impact on self-proxy differences, emphasizing the need for future research in this area.

With regard to proxy type, there is an observable trend suggesting a wider inter-rater gap when family proxies are employed using the proxy-proxy perspective, in contrast to formal proxies. This variance might be attributed to the use of distinct anchoring points; family proxies tend to assess the individual's QoL in relation to their past self before having dementia, while formal caregivers may draw comparisons with other individuals with dementia under their care [ 41 ]. However, the opposite was found when the proxy-patient perspective was used, where family proxies scores seemed to align more closely with self-reported scores, resulting in lower SMD scores. This suggests that family proxies might possess a better ability to empathize with the perspective of the person with dementia compared to formal proxies. Nonetheless, it is important to interpret these findings cautiously, given the relatively small number of observations for formal caregiver reports. Additionally, other factors such as emotional connection, caregiver burden, and caregiver QoL may also impact proxy-reports by family proxies [ 14 , 16 ] that have not been explored in this review.

Our review found that the SMD between proxy and self-report increased with greater level of dementia severity, contrasting a previous study, which showed that cognitive impairment was not the primary factor that accounted for the differences in the QoL assessments between family proxies and the person with dementia [ 15 ]. However, it is noteworthy that different interpretations and classifications were used across studies to define mild, moderate, and severe dementia, which needs to be considered. Most studies used MMSE to define dementia severity levels. Given the MMSE’s role as a standard measure of cognitive function, the study findings are considered generalizable and clinically relevant for people with dementia across different dementia severity levels. When examining the role of the proxy perspective by level of severity, we found that compared with the proxy-proxy perspective, where self-reported scores were greater than proxy-reported scores across all dementia severity levels, the proxy-patient perspective yielded the opposite results, and proxies reported better QoL than people with dementia themselves, except for the severe subgroup. It is possible that in the early stages of dementia, the person with dementia has a greater awareness of increasing deficits, coupled with denial and lack of acceptance, leading to a more critical view of their own QoL than how proxies think they would rate their QoL. However, future studies are warranted, given the small number of observations adopting the proxy-patient perspective in our review.

The heterogeneity observed in the studies included was high, supporting the use of random-effects meta-analysis. This is not surprising given the diverse nature of studies included (i.e., RCTs, cross-sectional studies), differences in the population (i.e., people living in residential care versus community-dwelling people), mixed levels of dementia severity, and differences between instruments. While similar heterogeneity was observed in another review on a similar topic [ 42 ], our presentation of findings stratified by proxy type, dementia severity, and living arrangement attempted to account for such differences across studies.

Limitations and recommendations for future studies

Our review has some limitations. Firstly, proxy perspectives were categorized based on the authors' descriptions, but many papers did not explicitly state the perspective, which led to the use of assumptions based on instrument developers. Some studies may have modified the perspective's wording without reporting it. Due to lack of resources, we did not contact the authors of the original studies directly to seek clarification around the proxy perspective adopted. Regarding studies using the EQ-5D, which has two proxy perspectives, some studies did not specify which proxy version was used, suggesting the potential use of self-reported versions for proxies. In such cases, the proxy perspective was categorized as undefined. Despite accounting for factors like QoL measure, proxy type, setting, and dementia severity, we could not assess the impact of proxy characteristics (e.g., carer burden) or dementia type due to limited information provided in the studies. We also faced limitations in exploring the proxy perspective by QoL domains due to limited information. Further, not all studies outlined the data collection process in full detail. For example, it is possible that the proxy also assisted the person with dementia with their self-report, which could have resulted in biased estimates and the need for future studies applying blinding. Although we assessed the risk of bias of included studies, the checklist was not directly reflecting the purpose of our study that looked into inter-rater agreement. No checklist for this purpose currently exists. Finally, quality appraisal by a second reviewer was only conducted for the first 25% of the studies due to resource constraints and a low rate of disagreement between the two assessors. However, an agreement index between reviewers regarding the concordance in selecting full texts for inclusion and conducting risk of bias assessments was not calculated.

This review demonstrates that the choice of proxy perspective impacts the inter-rater gap. QoL scores from the proxy-patient perspective align more closely with self-reported scores than the proxy-proxy perspective. These findings contribute to the broader literature investigating factors influencing differences in QoL scores between proxies and individuals with dementia. While self-reported QoL is the gold standard, proxy-reports should be viewed as complements rather than substitutes. Both proxy perspectives offer unique insights, yet QoL assessments in people with dementia are complex. The difference in self- and proxy-reports can be influenced by various factors, necessitating further research before presenting definitive results that inform care provision and policy.

Data availability

All data associated with the systematic literature review are available in the supplementary file.

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LE contributed to the study conception and design. The original database search was performed by AL and later updated by VS. All authors were involved in the screening process, data extraction, and data analyses. Quality assessment was conducted by VS and LE. The first draft of the manuscript was written by LE and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Engel, L., Sokolova, V., Bogatyreva, E. et al. Understanding the influence of different proxy perspectives in explaining the difference between self-rated and proxy-rated quality of life in people living with dementia: a systematic literature review and meta-analysis. Qual Life Res (2024). https://doi.org/10.1007/s11136-024-03660-w

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• http://orcid.org/0000-0002-2723-4259 Kei Ouchi 1 , 2 , 3 ,
• Adrian Haimovich 2 , 4 ,
• Jason Bowman 1 , 2 , 3
• 1 Department of Emergency Medicine , Brigham and Women's Hospital , Boston , Massachusetts , USA
• 2 Department of Emergency Medicine , Harvard Medical School , Boston , Massachusetts , USA
• 3 Department of Psychosocial Oncology and Palliative Care , Dana-Farber Cancer Institute , Boston , Massachusetts , USA
• 4 Department of Emergency Medicine , Beth Israel Deaconess Medical Center , Boston , Massachusetts , USA
• Correspondence to Dr Kei Ouchi, Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA; kouchi{at}bwh.harvard.edu

https://doi.org/10.1136/emermed-2024-214007

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• Palliative Care

Three-quarters of older adults visit an ED in the last 6 months of life. 1 For older patients with serious, life-limiting illnesses, those who have good awareness of their illness severity have better outcomes. Prognostic awareness is associated with better-informed decisions about patient care, 2 improved ability to cope with illnesses 3 and increased acceptance of illnesses, 4 yielding more patient-centred care at the end of life.

In their EMJ systematic review, Mols et al present the results of a systematic review of patients’ self-assessment of patient outcomes (eg, prognosis) in acute care settings compared with established prognostication tools, perceptions of clinicians or perceptions of caregivers/family. 5 Four outcomes were assessed: (1) Need for hospitalisation and length of stay; (2) Severity of illness; (3) Postdischarge quality of life; and 4) Life expectancy. The review demonstrated that patients could predict the need for admission with 64% accuracy, only slightly better than a coin-flip. This finding is likely confounded because patients’ perceptions and preferences may be driving physicians’ decisions to admit them. Furthermore, 68% of patients overestimated the severity of their illnesses, and only 37% predicted their survival accurately. From this review, we conclude that the literature is limited around patient prognostic understanding in the ED—and these findings have limited implications for the practice of emergency medicine.

Most patients desire honest and realistic prognoses to be communicated. Yet, patients’ prognostic awareness is generally low. Most patient with incurable cancers (>69%) believed that their illnesses are curable, regardless of their educational level or functional status. 6 Since poor prognostic awareness is associated with lower utilisation of supportive end-of-life resources like hospice, 7 improving patients’ prognostic awareness is of vital importance to delivering patient-centred care.

What does this mean for the field of emergency medicine? Established, well-recognised framework exists to support patient-centred, shared decision-making for end-of-life care. 8 The components of this decision-making include eliciting patients’ understanding of illness, sharing serious news about their illnesses, responding to expected negative emotions, seeking to understand patients’ values and goals, aligning available care components to patients’ values and goals, and then making a recommendation about the best care possible for patients based on their values and goals combined with clinician expertise. Patients’ prognostic awareness is a vital component to successfully execute this decision-making process. Though the current study demonstrated that patients in acute care settings can predict the probability of hospitalisation slightly better than a coin-flip, they could not predict illness severity or prognosis. In acute care settings, patients with serious illnesses often lack prognostic awareness. Unfortunately, when decision-making around potential end-of-life care needs to take place in the ED, emergency physicians will have a difficult time navigating this shared decision-making.

To mitigate these anticipated problems, we suggest emergency physicians focus on several tasks most relevant to the acute settings:

Expect that patients with serious illnesses are likely unaware of their prognosis during the ED visit.

Emergency physicians should approach clinical interactions anticipating poor prognostic awareness and be prepared to support patients as they confront new, potentially difficult, prognostic data.

Familiarise themselves with existing tools to estimate long-term prognosis in the ED settings. 9

For example, emergency physicians should be aware that a third of older adults intubated in the ED die in the hospital and only 24% are discharged to home. 10 If they survive the hospitalisation, they have about one-third chance to be alive 1 year after discharge.

Leverage the ED visit to improve patients’ prognostic awareness by conveying clinician ‘worries’.

Recognising that ED visits may be inflection points in patients’ clinical trajectories, it is vitally important that emergency physicians communicate their ‘worries’ in cases of anticipated poor prognosis. For example, emergency physicians could consider language such as, ‘I hope that you will recover from this illness, and I also worry that you may not survive this hospitalisation and even if you do that you will be much less healthy than you were before’.’ ‘I hope… and also I worry’ allows emergency physicians to articulate the potential for poor prognosis while appropriately appreciating prognostic uncertainty during the acute care settings. This empathetic prognostic disclosure can have a lasting impact on a patient’s prognostic awareness after leaving the ED.

Help patients prepare for future medical encounters.

Emergency physicians can also support patient exploration of their values, goals and preferences for future care. Following the ‘Worry’ statement with a specific task for the patient can be empowering. For example, ‘I see you do not have a healthcare proxy. Now is a good time to make sure you have identified someone who would help make medical decisions for you if you were not able to do so for yourself’.

This systematic review demonstrates the critical need for emergency medicine research around shared prognostic awareness between patients and physicians, which is essential to effectively conducting shared decision-making for end-of-life care. Knowledge gaps exist where emergency medicine researchers are well-positioned to address. Chief among these is a more comprehensive understanding of patient prognostic awareness, specifically emphasising functional outcomes important to patients like new nursing home discharges and mortality. Beyond this, outside of screening instruments like the surprise question, 9 we have little knowledge of emergency physician prognostic accuracy.

Emergency physicians often play a crucial role in steering treatment trajectories for seriously ill patients who present to the ED with acute health decompensation. As a specialty, we need to appreciate the clinical significance of patients’ long-term prognosis beyond ED and in-hospital mortality. By engaging in opportunities to improve patients’ prognostic awareness when they come to the ED, we can help them to understand their illnesses better and make decisions around their anticipated quality of life, ultimately leading to more patient-centred end-of-life care in the ED and beyond.

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• McCarthy E ,
• Weber E , et al
• Applebaum AJ ,
• Jacobsen JC , et al
• Choi JY , et al
• Holland M , et al
• Catalano PJ ,
• Cronin A , et al
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Handling editor Mary Dawood

Contributors All authors contributed equally and substantially to the conceptualisation, writing, editing and analysis of this manuscript.

Funding The study was funded by the National Institute on Aging (K76AG064434) and National Center for Advancing Translational Sciences (UM1TR004408).

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

Linked Articles

• Systematic review Can acutely ill patients predict their outcomes? A scoping review Elisabeth Margaretha Mols Harm Haak Mark Holland Bo Schouten Stine Ibsen Hanneke Merten Erika Frischknecht Christensen Prabath W B Nanayakkara Christian Hans Nickel Immo Weichert John Kellett Christian Peter Subbe Marjolein N T Kremers Safer@Home Research Consortium J Alsma M Brabrand T Cooksley Erika F Christensen Harm R Haak Mark Holland Stine Ibsen John Kellett Marjolein N T Kremers Hanneke Merten Elisabeth M Mols Prabath W B Nanayakkara Christian H Nickel Bo Schouten Chris P Subbe Immo Weichtert Emergency Medicine Journal 2024; - Published Online First: 18 Jan 2024. doi: 10.1136/emermed-2022-213000

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