limitation of social work research

Social Work Research Methods That Drive the Practice

Social workers advocate for the well-being of individuals, families and communities. But how do social workers know what interventions are needed to help an individual? How do they assess whether a treatment plan is working? What do social workers use to write evidence-based policy?

Social work involves research-informed practice and practice-informed research. At every level, social workers need to know objective facts about the populations they serve, the efficacy of their interventions and the likelihood that their policies will improve lives. A variety of social work research methods make that possible.

Data-Driven Work

Data is a collection of facts used for reference and analysis. In a field as broad as social work, data comes in many forms.

Quantitative vs. Qualitative

As with any research, social work research involves both quantitative and qualitative studies.

Quantitative Research

Answers to questions like these can help social workers know about the populations they serve — or hope to serve in the future.

• How many students currently receive reduced-price school lunches in the local school district?
• How many hours per week does a specific individual consume digital media?
• How frequently did community members access a specific medical service last year?

Quantitative data — facts that can be measured and expressed numerically — are crucial for social work.

Quantitative research has advantages for social scientists. Such research can be more generalizable to large populations, as it uses specific sampling methods and lends itself to large datasets. It can provide important descriptive statistics about a specific population. Furthermore, by operationalizing variables, it can help social workers easily compare similar datasets with one another.

Qualitative Research

Qualitative data — facts that cannot be measured or expressed in terms of mere numbers or counts — offer rich insights into individuals, groups and societies. It can be collected via interviews and observations.

• What attitudes do students have toward the reduced-price school lunch program?
• What strategies do individuals use to moderate their weekly digital media consumption?
• What factors made community members more or less likely to access a specific medical service last year?

Qualitative research can thereby provide a textured view of social contexts and systems that may not have been possible with quantitative methods. Plus, it may even suggest new lines of inquiry for social work research.

Mixed Methods Research

Combining quantitative and qualitative methods into a single study is known as mixed methods research. This form of research has gained popularity in the study of social sciences, according to a 2019 report in the academic journal Theory and Society. Since quantitative and qualitative methods answer different questions, merging them into a single study can balance the limitations of each and potentially produce more in-depth findings.

However, mixed methods research is not without its drawbacks. Combining research methods increases the complexity of a study and generally requires a higher level of expertise to collect, analyze and interpret the data. It also requires a greater level of effort, time and often money.

The Importance of Research Design

Data-driven practice plays an essential role in social work. Unlike philanthropists and altruistic volunteers, social workers are obligated to operate from a scientific knowledge base.

To know whether their programs are effective, social workers must conduct research to determine results, aggregate those results into comprehensible data, analyze and interpret their findings, and use evidence to justify next steps.

Employing the proper design ensures that any evidence obtained during research enables social workers to reliably answer their research questions.

Research Methods in Social Work

The various social work research methods have specific benefits and limitations determined by context. Common research methods include surveys, program evaluations, needs assessments, randomized controlled trials, descriptive studies and single-system designs.

Surveys involve a hypothesis and a series of questions in order to test that hypothesis. Social work researchers will send out a survey, receive responses, aggregate the results, analyze the data, and form conclusions based on trends.

Surveys are one of the most common research methods social workers use — and for good reason. They tend to be relatively simple and are usually affordable. However, surveys generally require large participant groups, and self-reports from survey respondents are not always reliable.

Program Evaluations

Social workers ally with all sorts of programs: after-school programs, government initiatives, nonprofit projects and private programs, for example.

Crucially, social workers must evaluate a program’s effectiveness in order to determine whether the program is meeting its goals and what improvements can be made to better serve the program’s target population.

Evidence-based programming helps everyone save money and time, and comparing programs with one another can help social workers make decisions about how to structure new initiatives. Evaluating programs becomes complicated, however, when programs have multiple goal metrics, some of which may be vague or difficult to assess (e.g., “we aim to promote the well-being of our community”).

Needs Assessments

Social workers use needs assessments to identify services and necessities that a population lacks access to.

Common social work populations that researchers may perform needs assessments on include:

• People in a specific income group
• Everyone in a specific geographic region
• A specific ethnic group
• People in a specific age group

In the field, a social worker may use a combination of methods (e.g., surveys and descriptive studies) to learn more about a specific population or program. Social workers look for gaps between the actual context and a population’s or individual’s “wants” or desires.

For example, a social worker could conduct a needs assessment with an individual with cancer trying to navigate the complex medical-industrial system. The social worker may ask the client questions about the number of hours they spend scheduling doctor’s appointments, commuting and managing their many medications. After learning more about the specific client needs, the social worker can identify opportunities for improvements in an updated care plan.

In policy and program development, social workers conduct needs assessments to determine where and how to effect change on a much larger scale. Integral to social work at all levels, needs assessments reveal crucial information about a population’s needs to researchers, policymakers and other stakeholders. Needs assessments may fall short, however, in revealing the root causes of those needs (e.g., structural racism).

Randomized Controlled Trials

Randomized controlled trials are studies in which a randomly selected group is subjected to a variable (e.g., a specific stimulus or treatment) and a control group is not. Social workers then measure and compare the results of the randomized group with the control group in order to glean insights about the effectiveness of a particular intervention or treatment.

Randomized controlled trials are easily reproducible and highly measurable. They’re useful when results are easily quantifiable. However, this method is less helpful when results are not easily quantifiable (i.e., when rich data such as narratives and on-the-ground observations are needed).

Descriptive Studies

Descriptive studies immerse the researcher in another context or culture to study specific participant practices or ways of living. Descriptive studies, including descriptive ethnographic studies, may overlap with and include other research methods:

• Informant interviews
• Census data
• Observation

By using descriptive studies, researchers may glean a richer, deeper understanding of a nuanced culture or group on-site. The main limitations of this research method are that it tends to be time-consuming and expensive.

Single-System Designs

Unlike most medical studies, which involve testing a drug or treatment on two groups — an experimental group that receives the drug/treatment and a control group that does not — single-system designs allow researchers to study just one group (e.g., an individual or family).

Single-system designs typically entail studying a single group over a long period of time and may involve assessing the group’s response to multiple variables.

For example, consider a study on how media consumption affects a person’s mood. One way to test a hypothesis that consuming media correlates with low mood would be to observe two groups: a control group (no media) and an experimental group (two hours of media per day). When employing a single-system design, however, researchers would observe a single participant as they watch two hours of media per day for one week and then four hours per day of media the next week.

These designs allow researchers to test multiple variables over a longer period of time. However, similar to descriptive studies, single-system designs can be fairly time-consuming and costly.

Learn More About Social Work Research Methods

Social workers have the opportunity to improve the social environment by advocating for the vulnerable — including children, older adults and people with disabilities — and facilitating and developing resources and programs.

Learn more about how you can earn your  Master of Social Work online at Virginia Commonwealth University . The highest-ranking school of social work in Virginia, VCU has a wide range of courses online. That means students can earn their degrees with the flexibility of learning at home. Learn more about how you can take your career in social work further with VCU.

From M.S.W. to LCSW: Understanding Your Career Path as a Social Worker

How Palliative Care Social Workers Support Patients With Terminal Illnesses

How to Become a Social Worker in Health Care

Gov.uk, Mixed Methods Study

MVS Open Press, Foundations of Social Work Research

Open Social Work Education, Scientific Inquiry in Social Work

Open Social Work, Graduate Research Methods in Social Work: A Project-Based Approach

Routledge, Research for Social Workers: An Introduction to Methods

SAGE Publications, Research Methods for Social Work: A Problem-Based Approach

Theory and Society, Mixed Methods Research: What It Is and What It Could Be

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Evidence-Based Practice in Social Work: Challenges and Opportunities for Clinicians and Organizations

• Original Paper
• Published: 19 April 2014
• Volume 42 , pages 161–170, ( 2014 )

Cite this article

• Traci L. Wike 1 ,
• Sarah E. Bledsoe 2 ,
• Jennifer I. Manuel 1 ,
• Mathieu Despard 2 ,
• Lydia V. Johnson 2 ,
• Jennifer L. Bellamy 3 &
• Candace Killian-Farrell 2  

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Evidence-based practice (EBP) is increasingly emphasized in social work, yet effective approaches for translating research evidence into social work practice remain elusive. Despite a growing body of evidence describing effective interventions with a variety of populations, social workers continue to encounter substantial challenges with incorporating knowledge gained from these intervention studies into their routine practice with clients. This paper presents the current research outlining the known barriers and promoters to using EBP in social work clinical practice. Because social workers practice within the context of organizations, we consider the barriers that exist at both the individual and organizational levels that affect clinical social work practice. In addition to addressing the various challenges to incorporating research evidence into practice, we will also discuss a variety of emergent opportunities accompanying the move toward EBP that can be leveraged by clinicians in their social work practice with clients.

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Sarah E. Bledsoe, Mathieu Despard, Lydia V. Johnson & Candace Killian-Farrell

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Wike, T.L., Bledsoe, S.E., Manuel, J.I. et al. Evidence-Based Practice in Social Work: Challenges and Opportunities for Clinicians and Organizations. Clin Soc Work J 42 , 161–170 (2014). https://doi.org/10.1007/s10615-014-0492-3

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Published : 19 April 2014

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DOI : https://doi.org/10.1007/s10615-014-0492-3

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The Pursuit of Quality for Social Work Practice: Three Generations and Counting

Enola proctor.

Shanti K. Khinduka Distinguished Professor and director of the Center for Mental Health Services Research at Washington University in St. Louis

Social work addresses some of the most complex and intractable human and social problems: poverty, mental illness, addiction, homelessness, and child abuse. Our field may be distinct among professions for its efforts to ameliorate the toughest societal problems, experienced by society’s most vulnerable, while working from under-resourced institutions and settings. Members of our profession are underpaid, and most of our agencies lack the data infrastructure required for rigorous assessment and evaluation.

Moreover, social work confronts these challenges as it is ethically bound to deliver high-quality services. Policy and regulatory requirements increasingly demand that social work deliver and document the effectiveness of highest quality interventions and restrict reimbursement to those services that are documented as evidence based. Social work’s future, its very survival, depends on our ability to deliver services with a solid base of evidence and to document their effectiveness. In the words of the American Academy of Social Work and Social Welfare (AASWSW; n.d.) , social work seeks to “champion social progress powered by science.” The research community needs to support practice through innovative and rigorous science that advances the evidence for interventions to address social work’s grand challenges.

My work seeks to improve the quality of social work practice by pursuing answers to three questions:

• What interventions and services are most effective and thus should be delivered in social work practice?
• How do we measure the impact of those interventions and services? (That is, what outcomes do our interventions achieve?)
• How do we implement the highest quality interventions?

This paper describes this work, demonstrates the substantive and methodological progression across the three questions, assesses what we have learned, and forecasts a research agenda for what we still need to learn. Given Aaron Rosen’s role as my PhD mentor and our many years of collaboration, the paper also addresses the role of research mentoring in advancing our profession’s knowledge base.

What Interventions and Services Are Most Effective?

Answering the question “What services are effective?” requires rigorous testing of clearly specified interventions. The first paper I coauthored with Aaron Rosen—“Specifying the Treatment Process: The Basis for Effectiveness Research” ( Rosen & Proctor, 1978 )—provided a framework for evaluating intervention effectiveness. At that time, process and outcomes were jumbled and intertwined concepts. Social work interventions were rarely specified beyond theoretical orientation or level of focus: casework (or direct practice); group work; and macro practice, which included community, agency-level, and policy-focused practice. Moreover, interventions were not named, nor were their components clearly identified. We recognized that gross descriptions of interventions obstruct professional training, preclude fidelity assessment, and prevent accurate tests of effectiveness. Thus, in a series of papers, Rosen and I advocated that social work interventions be specified, clearly labeled, and operationally defined, measured, and tested.

Specifying Interventions

Such specification of interventions is essential to two professional responsibilities: professional education and demonstrating the effectiveness of the field’s interventions. Without specification, interventions cannot be taught. Social work education is all about equipping students with skills to deliver interventions, programs, services, administrative practices, and policies. Teaching interventions requires an ability to name, define, see them in action, measure their presence (or absence), assess the fidelity with which they are delivered, and give feedback to students on how to increase or refine the associated skills.

To advance testing the effectiveness of social work interventions, we drew distinctions between interventions and outcomes and proposed these two constructs as the foci for effectiveness research. We defined interventions as practitioner behaviors that can be volitionally manipulated by practitioners (used or not, varied in intensity and timing), that are defined in detail, can be reliably measured, and can be linked to specific identified outcomes ( Rosen & Proctor, 1978 ; Rosen & Proctor, 1981 ). This definition foreshadowed the development of treatment manuals, lists of specific evidence-based practices, and calls for monitoring intervention fidelity. Recognizing the variety of intervention types, and to advance their more precise definition and measurement, we proposed that interventions be distinguished in terms of their complexity. Interventive responses comprise discrete or single responses, such as affirmation, expression of empathy, or positive reinforcement. Interventive strategies comprise several different actions that are, together, linked to a designated outcome, such as motivational interviewing. Most complex are interventive programs , which are a variety of intervention actions organized and integrated as a total treatment package; collaborative care for depression or community assertive treatment are examples. To strengthen the professional knowledge base, we also called for social work effectiveness research to begin testing the optimal dose and sequencing of intervention components in relation to attainment of desired outcomes.

Advancing Intervention Effectiveness Research

Our “specifying paper” also was motivated by the paucity of literature at that time on actual social work interventions. Our literature review of 13 major social work journals over 5 years of published research revealed that only 15% of published social work research addressed interventions. About a third of studies described social problems, and about half explored factors associated with the problem ( Rosen, Proctor, & Staudt, 2003 ). Most troubling was our finding that only 3% of articles described the intervention or its components in sufficient detail for replication in either research or practice. Later, Fraser (2004) found intervention research to comprise only about one fourth of empirical studies in social work. Fortunately, our situation has improved. Intervention research is more frequent in social work publications, thanks largely to the publication policies of the Journal of the Society for Social Work and Research and Research on Social Work Practice .

Research Priorities

Social work faces important and formidable challenges as it advances research on intervention effectiveness. The practitioner who searches the literature or various intervention lists can find more than 500 practices that are named or that are shown to have evidence from rigorous trials that passes a bar to qualify as evidence-based practices. However, our profession still lacks any organized compendium or taxonomy of interventions that are employed in or found to be effective for social work practice. Existing lists of evidence-based practices, although necessary, are insufficient for social work for several reasons. First, as a 2015 National Academies Institute of Medicine (IOM) report—“Psychosocial Interventions for Mental and Substance Use Disorders: A Framework for Establishing Evidence-Based Standards” ( IOM, 2015 )—concluded, too few evidence-based practices have been found to be appropriate for low-resource settings or acceptable to minority groups. Second, existing interventions do not adequately reflect the breadth of social work practice. We have too few evidence-based interventions that can inform effective community organization, case management, referral practice, resource development, administrative practice, or policy. Noting that there is far less literature on evidence-based practices relevant to organizational, community, and policy practice, a social work task force responding to the 2015 IOM report recommended that this gap be a target of our educational and research efforts ( National Task Force on Evidence-Based Practice in Social Work, 2016 ). And finally, our field—along with other professions that deliver psychosocial interventions—lacks the kinds of procedure codes that can identify the specific interventions we deliver. Documenting social work activities in agency records is increasingly essential for quality assurance and third-party reimbursement.

Future Directions: Research to Advance Evidence on Interventions

Social work has critically important research needs. Our field needs to advance the evidence base on what interventions work for social work populations, practices, and settings. Responding to the 2015 IOM report, the National Task Force on Evidence-Based Practice in Social Work (2016) identified as a social work priority the development and testing of evidence-based practices relevant to organizational, community, and policy practice. As we advance our intervention effectiveness research, we must respond to the challenge of determining the key mechanisms of change ( National Institute of Mental Health, 2016 ) and identify key modifiable components of packaged interventions ( Rosen & Proctor, 1978 ). We need to explore the optimal dosage, ordering, or adapted bundling of intervention elements and advance robust, feasible ways to measure and increase fidelity ( Jaccard, 2016 ). We also need to conduct research on which interventions are most appropriate, acceptable, and effective with various client groups ( Zayas, 2003 ; Videka, 2003 ).

Documenting the Impact of Interventions: Specifying and Measuring Outcomes

Outcomes are key to documenting the impact of social work interventions. My 1978 “specifying” paper with Rosen emphasized that the effectiveness of social work practice could not be adequately evaluated without clear specification and measurement of various types of outcomes. In that paper, we argued that the profession cannot rely only on an assertion of effectiveness. The field must also calibrate, calculate, and communicate its impact.

The nursing profession’s highly successful campaign, based on outcomes research, positioned that field to claim that “nurses save lives.” Nurse staffing ratios were associated with in-hospital and 30-day mortality, independent of patient characteristics, hospital characteristics, or medical treatment ( Person et al., 2004 ). In contrast, social work has often described—sometimes advertised—itself as the low-cost profession. The claim of “cheapest service” may have some strategic advantage in turf competition with other professions. But social work can do better. Our research base can and should demonstrate the value of our work by naming and quantifying the outcomes—the added value of social work interventions.

As a start to this work—a beginning step in compiling evidence about the impact of social work interventions—our team set out to identify the outcomes associated with social work practice. We felt that identifying and naming outcomes is essential for conveying what social work is about. Moreover, outcomes should serve as the focus for evaluating the effectiveness of social work interventions.

We produced two taxonomies of outcomes reflected in published evaluations of social work interventions ( Proctor, Rosen, & Rhee, 2002 ; Rosen, Proctor, & Staudt, 2003 ). They included such outcomes as change in clients’ social functioning, resource procurement, problem or symptom reduction, and safety. They exemplify the importance of naming and measuring what our profession can contribute to society. Although social work’s growing body of effectiveness research typically reports outcomes of the interventions being tested, the literature has not, in the intervening 20 years, addressed the collective set of outcomes for our field.

Fortunately, the Grand Challenges for Social Work (AASWSW, n.d.) now provide a framework for communicating social work’s goals. They reflect social work’s added value: improving individual and family well-being, strengthening social fabric, and helping to create a more just society. The Grand Challenges for Social Work include ensuring healthy development for all youth, closing the health gap, stopping family violence, advancing long and productive lives, eradicating social isolation, ending homelessness, creating social responses to a changing environment, harnessing technology for social good, promoting smart decarceration, reducing extreme economic inequality, building financial capability for all, and achieving equal opportunity and justice ( AASWSW, n.d. ).

These important goals appropriately reflect much of what we are all about in social work, and our entire field has been galvanized—energized by the power of these grand challenges. However, the grand challenges require setting specific benchmarks—targets that reflect how far our professional actions can expect to take us, or in some areas, how far we have come in meeting the challenge.

For the past decade, care delivery systems and payment reforms have required measures for tracking performance. Quality measures have become critical tools for all service providers and organizations ( IOM, 2015 ). The IOM defines quality of care as “the degree to which … services for individuals and populations increase the likelihood of desired … outcomes and are consistent with current professional knowledge” ( Lohr, 1990 , p. 21). Quality measures are important at multiple levels of service delivery: at the client level, at the practitioner level, at the organization level, and at the policy level. The National Quality Forum has established five criteria for quality measures: They should address (a) the most important, (b) the most scientifically valid, (c) the most feasible or least burdensome, (d) the most usable, and (e) the most harmonious set of measures ( IOM, 2015 .) Quality measures have been advanced by accrediting groups (e.g., the Joint Commission of the National Committee for Quality Assurance), professional societies, and federal agencies, including the U.S. Department of Health and Human Services. However, quality measures are lacking for key areas of social work practice, including mental health and substance-use treatment. And of the 55 nationally endorsed measures related to mental health and substance use, only two address a psychosocial intervention. Measures used for accreditation and certification purposes often reflect structural capabilities of organizations and their resource use, not the infrastructure required to deliver high-quality services ( IOM, 2015 ). I am not aware of any quality measure developed by our own professional societies or agreed upon across our field.

Future Directions: Research on Quality Monitoring and Measure Development

Although social work as a field lacks a strong tradition of measuring and assessing quality ( Megivern et al., 2007 ; McMillen et al., 2005 ; Proctor, Powell, & McMillen, 2012 ), social work’s role in the quality workforce is becoming better understood ( McMillen & Raffol, 2016 ). The small number of established and endorsed quality measures reflects both limitations in the evidence for effective interventions and challenges in obtaining the detailed information necessary to support quality measurement ( IOM, 2015 ). According to the National Task Force on Evidence-Based Practice in Social Work (2016) , developing quality measures to capture use of evidence-based interventions is essential for the survival of social work practice in many settings. The task force recommends that social work organizations develop relevant and viable quality measures and that social workers actively influence the implementation of quality measures in their practice settings.

How to Implement Evidence-Based Care

A third and more recent focus of my work addresses this question: How do we implement evidence-based care in agencies and communities? Despite our progress in developing proven interventions, most clients—whether served by social workers or other providers—do not receive evidence-based care. A growing number of studies are assessing the extent to which clients—in specific settings or communities—receive evidence-based interventions. Kohl, Schurer, and Bellamy (2009) examined quality in a core area of social work: training for parents at risk for child maltreatment. The team examined the parent services and their level of empirical support in community agencies, staffed largely by master’s-level social workers. Of 35 identified treatment programs offered to families, only 11% were “well-established empirically supported interventions,” with another 20% containing some hallmarks of empirically supported interventions ( Kohl et al., 2009 ). This study reveals a sizable implementation gap, with most of the programs delivered lacking scientific validation.

Similar quality gaps are apparent in other settings where social workers deliver services. Studies show that only 19.3% of school mental health professionals and 36.8% of community mental health professionals working in Virginia’s schools and community mental health centers report using any evidence-based substance-abuse prevention programs ( Evans, Koch, Brady, Meszaros, & Sadler, 2013 ). In mental health, where social workers have long delivered the bulk of services, only 40% to 50% of people with mental disorders receive any treatment ( Kessler, Chiu, Demler, Merikangas, & Walters, 2005 ; Merikangas et al., 2011 ), and of those receiving treatment, a fraction receive what could be considered “quality” treatment ( Wang, Demler, & Kessler, 2002 ; Wang et al., 2005 ). These and other studies indicate that, despite progress in developing proven interventions, most clients do not receive evidence-based care. In light of the growth of evidence-based practice, this fact is troubling evidence that testing interventions and publishing the findings is not sufficient to improve quality.

So, how do we get these interventions in place? What is needed to enable social workers to deliver, and clients to receive, high-quality care? In addition to developing and testing evidence-based interventions, what else is needed to improve the quality of social work practice? My work has focused on advancing quality of services through two paths.

Making Effective Interventions Accessible to Providers: Intervention Reviews and Taxonomies

First, we have advocated that research evidence be synthesized and made available to front-line practitioners. In a research-active field where new knowledge is constantly produced, practitioners should not be expected to rely on journal publications alone for information about effective approaches to achieve desired outcomes. Mastering a rapidly expanding professional evidence base has been characterized as a nearly unachievable challenge for practitioners ( Greenfield, 2017 ). Reviews should critique and clarify the intervention’s effectiveness as tested in specific settings, populations, and contexts, answering the question, “What works where, and with whom?” Even more valuable are studies of comparative effectiveness—those that answer, “Which intervention approach works better, where, and when?”

Taxonomies of clearly and consistently labeled interventions will enhance their accessibility and the usefulness of research reports and systematic reviews. A pre-requisite is the consistent naming of interventions. A persistent challenge is the wide variation in names or labels for interventive procedures and programs. Our professional activities are the basis for our societal sanction, and they must be capable of being accurately labeled and documented if we are to describe what our profession “does” to advance social welfare. Increasingly, and in short order, that documentation will be in electronic records that are scrutinized by third parties for purposes of reimbursement and assessment of value toward outcome attainment.

How should intervention research and reviews be organized? Currently, several websites provide lists of evidence-based practices, some with links, citations, or information about dissemination and implementation organizations that provide training and facilitation to adopters. Practitioners and administrators find such lists helpful but often note the challenge in determining which are most appropriate for their needs. In the words of one agency leader, “The drug companies are great at presenting [intervention information] in a very easy form to use. We don’t have people coming and saying, ‘Ah, let me tell you about the best evidence-based practice for cognitive behavioral therapy for depression,’” ( Proctor et al., 2007 , p. 483). We have called for the field to devise decision aids for practitioners to enhance access to the best available empirical knowledge about interventions ( Proctor et al., 2002 ; Proctor & Rosen, 2008 ; Rosen et al., 2003 ). We proposed that intervention taxonomies be organized around outcomes pursued in social work practice, and we developed such a taxonomy based on eight domains of outcomes—those most frequently tested in social work journals. Given the field’s progress in identifying its grand challenges, its associated outcomes could well serve as the organizing focus, with research-tested interventions listed for each challenge. Compiling the interventions, programs, and services that are shown—through research—to help achieve one of the challenges would surely advance our field.

We further urged profession-wide efforts to develop social work practice guidelines from intervention taxonomies ( Rosen et al., 2003 ). Practice guidelines are systematically compiled, critiqued, and organized statements about the effectiveness of interventions that are organized in a way to help practitioners select and use the most effective and appropriate approaches for addressing client problems and pursuing desired outcomes.

At that time, we proposed that our published taxonomy of social work interventions could provide a beginning architecture for social work guidelines ( Rosen et al., 2003 ). In 2000, we organized a conference for thought leaders in social work practice. This talented group wrestled with and formulated recommendations for tackling the professional, research, and training requisites to developing social work practice guidelines to enable researchers to access and apply the best available knowledge about interventions ( Rosen et al., 2003 ). Fifteen years later, however, the need remains for social work to synthesize its intervention research. Psychology and psychiatry, along with most fields of medical practice, have developed practice guidelines. Although their acceptance and adherence is fraught with challenges, guidelines make evidence more accessible and enable quality monitoring. Yet, guidelines still do not exist for social work.

The 2015 IOM report, “Psychosocial Interventions for Mental and Substance Use Disorders: A Framework for Establishing Evidence-Based Standards,” includes a conclusion that information on the effectiveness of psychosocial interventions is not routinely available to service consumers, providers, and payers, nor is it synthesized. That 2015 IOM report called for systematic reviews to inform clinical guidelines for psychosocial interventions. This report defined psychosocial interventions broadly, encompassing “interpersonal or informational activities, techniques, or strategies that target biological, behavioral, cognitive, emotional, interpersonal, social, or environmental factors with the aim of reducing symptoms and improving functioning or well-being” ( IOM, 2015 , p. 5). These interventions are social work’s domain; they are delivered in the very settings where social workers dominate (behavioral health, schools, criminal justice, child welfare, and immigrant services); and they encompass populations across the entire lifespan within all sociodemographic groups and vulnerable populations. Accordingly, the National Task Force on Evidence Based Practice in Social Work (2016) has recommended the conduct of more systematic reviews of the evidence supporting social work interventions.

If systematic reviews are to lead to guidelines for evidence-based psychosocial interventions, social work needs to be at the table, and social work research must provide the foundation. Whether social work develops its own guidelines or helps lead the development of profession-independent guidelines as recommended by the IOM committee, guidelines need to be detailed enough to guide practice. That is, they need to be accompanied by treatment manuals and informed by research that details the effect of moderator variables and contextual factors reflecting diverse clientele, social determinants of health, and setting resource challenges. The IOM report “Clinical Practice Guidelines We Can Trust” sets criteria for guideline development processes ( IOM, 2011 ). Moreover, social work systematic reviews of research and any associated evidence-based guidelines need to be organized around meaningful taxonomies.

Advancing the Science of Implementation

As a second path to ensuring the delivery of high-quality care, my research has focused on advancing the science of implementation. Implementation research seeks to inform how to deliver evidence-based interventions, programs, and policies into real-world settings so their benefits can be realized and sustained. The ultimate aim of implementation research is building a base of evidence about the most effective processes and strategies for improving service delivery. Implementation research builds upon effectiveness research then seeks to discover how to use specific implementation strategies and move those interventions into specific settings, extending their availability, reach, and benefits to clients and communities. Accordingly, implementation strategies must address the challenges of the service system (e.g., specialty mental health, schools, criminal justice system, health settings) and practice settings (e.g., community agency, national employee assistance programs, office-based practice), and the human capital challenge of staff training and support.

In an approach that echoes themes in an early paper, “Specifying the Treatment Process—The Basis for Effectiveness Research” ( Rosen & Proctor, 1978 ), my work once again tackled the challenge of specifying a heretofore vague process—this time, not the intervention process, but the implementation process. As a first step, our team developed a taxonomy of implementation outcomes ( Proctor et al., 2011 ), which enable a direct test of whether or not a given intervention is adopted and delivered. Although it is overlooked in other types of research, implementation science focuses on this distinct type of outcome. Explicit examination of implementation outcomes is key to an important research distinction. Often, evaluations yield disappointing results about an intervention, showing that the expected and desired outcomes are not attained. This might mean that the intervention was not effective. However, just as likely, it could mean that the intervention was not actually delivered, or it was not delivered with fidelity. Implementation outcomes help identify the roadblocks on the way to intervention adoption and delivery.

Our 2011 taxonomy of implementation outcomes ( Proctor et al., 2011 ), became the framework for two national repositories of measures for implementation research: the Seattle Implementation Research Collaborative ( Lewis et al., 2015 ) and the National Institutes of Health GEM measures database ( Rabin et al., 2012 ). These repositories of implementation outcomes seek to harmonize and increase the rigor of measurement in implementation science.

We also have developed taxonomies of implementation strategies ( Powell et al., 2012 ; Powell et al., 2015 ; Waltz et al., 2014 , 2015) . Implementation strategies are interventions for system change—how organizations, communities, and providers can learn to deliver new and more effective practices ( Powell et al., 2012 ).

A conversation with a key practice leader stimulated my interest in implementation strategies. Shortly after our school endorsed an MSW curriculum emphasizing evidence-based practices, a pioneering CEO of a major social service agency in St. Louis met with me and asked,

Enola Proctor, I get the importance of delivering evidence based practices. My organization delivers over 20 programs and interventions, and I believe only a handful of them are really evidence based. I want to decrease our provision of ineffective care, and increase our delivery of evidence-based practices. But how? What are the evidence-based ways I, as an agency director, can transform my agency so that we can deliver evidence-based practices?

That agency director was asking a question of how . He was asking for evidence-based implementation strategies. Moving effective programs and practices into routine care settings requires the skillful use of implementation strategies, defined as systematic “methods or techniques used to enhance the adoption, implementation, and sustainability of a clinical program or practice into routine service” ( Proctor et al., 2013 , p. 2).

This question has shaped my work for the past 15 years, as well as the research priorities of several funding agencies, including the National Institutes of Health, the Agency for Healthcare Research and Quality, the Patient-Centered Outcomes Research Institute, and the World Health Organization. Indeed, a National Institutes of Health program announcement—Dissemination and Implementation Research in Health ( National Institutes of Health, 2016 )—identified the discovery of effective implementation strategies as a primary purpose of implementation science. To date, the implementation science literature cannot yet answer that important question, but we are making progress.

To identify implementation strategies, our teams first turned to the literature—a literature that we found to be scattered across a wide range of journals and disciplines. Most articles were not empirical, and most articles used widely differing terms to characterize implementation strategies. We conducted a structured literature review to generate common nomenclature and a taxonomy of implementation strategies. That review yielded 63 distinct implementation strategies, which fell into six groupings: planning, educating, financing, restructuring, managing quality, and attending to policy context ( Powell et al., 2012 ).

Our team refined that compilation, using Delphi techniques and concept mapping to develop conceptually distinct categories of implementation strategies ( Powell et al., 2015 ; Waltz et al., 2014 ). The refined compilation of 73 discrete implementation strategies was then further organized into nine clusters:

• changing agency infrastructure,
• using financial strategies,
• supporting clinicians,
• providing interactive assistance,
• training and educating stakeholders,
• adapting and tailoring interventions to context,
• developing stakeholder relationships,
• using evaluative and iterative strategies, and
• engaging consumers.

These taxonomies of implementation strategies position the field for more robust research on implementation processes. The language used to describe implementation strategies has not yet “gelled” and has been described as a “Tower of Babel” ( McKibbon et al., 2010 ). Therefore, we also developed guidelines for reporting the components of strategies ( Proctor et al., 2013 ) so researchers and implementers would have more behaviorally specific information about what a strategy is, who does it, when, and for how long. The value of such reporting guidelines is illustrated in the work of Gold and colleagues (2016) .

What have we learned, through our own program of research on implementation strategies—the “how to” of improving practice? First, we have been able to identify from practice-based evidence the implementation strategies used most often. Using novel activity logs to track implementation strategies, Bunger and colleagues (2017) found that strategies such as quality improvement tools, using data experts, providing supervision, and sending clinical reminders were frequently used to facilitate delivery of behavioral health interventions within a child-welfare setting and were perceived by agency leadership as contributing to project success.

Second, reflecting the complexity of quality improvement processes, we have learned that there is no magic bullet ( Powell, Proctor, & Glass, 2013 ). Our study of U.S. Department of Veterans Affairs clinics working to implement evidence-based HIV treatment found that implementers used an average of 25 (plus or minus 14) different implementation strategies ( Rogal, et al., 2017 ). Moreover, the number of implementation strategies used was positively associated with the number of new treatment starts. These findings suggest that implementing new interventions requires considerable effort and resources.

To advance our understanding of the effectiveness of implementation strategies, our teams have conducted a systematic review ( Powell et al., 2013 ), tested specific strategies, and captured practice-based evidence from on-the-ground implementers. Testing the effectiveness of implementation strategies has been identified as a top research priority by the IOM (2009) . In work with Charles Glisson in St. Louis, our 15-agency-based randomized clinical trial found that an organizational-focused intervention—the attachment, regulatory, and competency model—improved agency culture and climate, stimulated more clinicians to enroll in evidence-based-practice training, and boosted clinical effect sizes of various evidence-based practices ( Glisson, Williams, Hemmelgarn, Proctor, & Green, 2016a , 2016b ). And in a hospital critical care unit, the implementation strategies of developing a team, selecting and using champions, provider education sessions, and audit and feedback helped increase team adherence to phlebotomy guidelines ( Steffen et al., in press ).

We are also learning about the value of different strategies. Experts in implementation science and implementation practice identified as most important the strategies of “use evaluate and iterative approaches” and “train and educate stakeholders.” Reported as less helpful were such strategies as “access new funding streams” and “remind clinicians of practices to use” ( Waltz et al., 2015 ). Successful implementers in Veterans Affairs clinics relied more heavily on such strategies as “change physical structures and equipment” and “facilitate relay of clinical data to providers” than did less successful implementers ( Rogal et al., 2017 ).

Many strategies have yet to be investigated empirically, as has the role of dissemination and implementation organizations—organizations that function to promote, provide information about, provide training in, and scale up specific treatments. Most evidence-based practices used in behavioral health, including most listed on the Substance Abuse and Mental Health Services Administration National Registry of Promising and Effective Practices, are disseminated and distributed by dissemination and implementation organizations. Unlike drugs and devices, psychosocial interventions have no Federal Drug Administration-like delivery system. Kreuter and Casey (2012) urge better understanding and use of the intervention “delivery system,” or mechanisms to bring treatment discoveries to the attention of practitioners and into use in practice settings.

Implementation strategies have been shown to boost clinical effectiveness ( Glisson et al., 2010 ), reduce staff turnover ( Aarons, Sommerfield, Hect, Silvosky, & Chaffin, 2009 ) and help reduce disparities in care ( Balicer et al., 2015 ).

Future directions: Research on implementation strategies

My work in implementation science has helped build intellectual capital for the rapidly growing field of dissemination and implementation science, leading teams to distinguish, clearly define, develop taxonomies, and stimulate more systematic work to advance the conceptual, linguistic, and methodological clarity in the field. Yet, we continue to lack understanding of many issues. What strategies are used in usual implementation practice, by whom, for which empirically supported interventions? What strategies are effective in which organizational and policy contexts? Which strategies are effective in attaining which specific implementation outcomes? For example, are the strategies that are effective for initial adoption also effective for scale up, spread, and sustained use of interventions? Social workers have the skill set for roles as implementation facilitators, and refining packages of implementation strategies that are effective in social service and behavioral health settings could boost the visibility, scale, and impact of our work.

The Third Generation and Counting

Social work faces grand, often daunting challenges. We need to develop a more robust base of evidence about the effectiveness of interventions and make that evidence more relevant, accessible, and applicable to social work practitioners, whether they work in communities, agencies, policy arenas, or a host of novel settings. We need to advance measurement-based care so our value as a field is recognized. We need to know how to bring proven interventions to scale for population-level impact. We need to discover ways to build capacity of social service agencies and the communities in which they reside. And we need to learn how to sustain advances in care once we achieve them ( Proctor et al., 2015 ). Our challenges are indeed grand, far outstripping our resources.

So how dare we speak of a quality quest? Does it not seem audacious to seek the highest standards in caring for the most vulnerable, especially in an era when we face a new political climate that threatens vulnerable groups and promises to strip resources from health and social services? Members of our profession are underpaid, and most of our agencies lack the data infrastructure required for assessment and evaluation. Quality may be an audacious goal, but as social workers we can pursue no less. By virtue of our code of ethics, our commitment to equity, and our skills in intervening on multiple levels of systems and communities, social workers are ideally suited for advancing quality.

Who will conduct the needed research? Who will pioneer its translation to improving practice? Social work practice can be only as strong as its research base; the responsibility for developing that base, and hence improve practice, is lodged within social work research.

If my greatest challenge is pursuing this quest, my greatest joy is in mentoring the next generation for this work. My research mentoring has always been guided by the view that the ultimate purpose of research in the helping professions is the production and systemization of knowledge for use by practitioners ( Rosen & Proctor, 1978 ). For 27 years, the National Institute of Mental Health has supported training in mental health services research based in the Center for Mental Health Services Research ( Hasche, Perron, & Proctor, 2009 ; Proctor & McMillen, 2008 ). And, with colleague John Landsverk, we are launching my sixth year leading the Implementation Research Institute, a training program for implementation science supported by the National Institute of Mental Health ( Proctor et al., 2013 ). We have trained more than 50 social work, psychology, anthropology, and physician researchers in implementation science for mental health. With three more cohorts to go, we are working to assess what works in research training for implementation science. Using bibliometric analysis, we have learned that intensive training and mentoring increases research productivity in the form of published papers and grants that address how to implement evidence-based care in mental health and addictions. And, through use of social network analysis, we have learned that every “dose” of mentoring increases scholarly collaboration when measured two years later ( Luke, Baumann, Carothers, Landsverk, & Proctor, 2016 ).

As his student, I was privileged to learn lessons in mentoring from Aaron Rosen. He treated his students as colleagues, he invited them in to work on the most challenging of questions, and he pursued his work with joy. When he treated me as a colleague, I felt empowered. When he invited me to work with him on the field’s most vexing challenges, I felt inspired. And as he worked with joy, I learned that work pursued with joy doesn’t feel like work at all. And now the third, fourth, and fifth generations of social work researchers are pursuing tough challenges and the quality quest for social work practice. May seasoned and junior researchers work collegially and with joy, tackling the profession’s toughest research challenges, including the quest for high-quality social work services.

Acknowledgments

Preparation of this paper was supported by IRI (5R25MH0809160), Washington University ICTS (2UL1 TR000448-08), Center for Mental Health Services Research, Washington University in St. Louis, and the Center for Dissemination and Implementation, Institute for Public Health, Washington University in St. Louis.

This invited article is based on the 2017 Aaron Rosen Lecture presented by Enola Proctor at the Society for Social Work and Research 21st Annual Conference—“Ensure Healthy Development for All Youth”—held January 11–15, 2017, in New Orleans, LA. The annual Aaron Rosen Lecture features distinguished scholars who have accumulated a body of significant and innovative scholarship relevant to practice, the research base for practice, or effective utilization of research in practice.

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Social Work Research: Concept, Scope

Last Updated on December 30, 2022 by Team TSW

An effort to create new knowledge or to upgrade existing knowledge either through observation, available facts, evidences or any other method, is research. We often make our mind or take decision, based on our observation about certain objects or phenomena. During whole process we remain unaware of our biases, we do not question them and we attribute our observations entirely to the object being observed. Though it is still possible to arrive at right decision on the basis of wrong reasons or vice versa. This whole thing questions the process of observation. Was the observation error-free? While observing are we aware of our limitations? Every method of observation has certain limitations. Important thing here is to take biases, the errors and limitations into consideration. Social work research is the application of research methods in the field of social work.

Table of Contents

Purpose of social work research is to produce new knowledge or to increase already available knowledge in the field of social work. Social work research gives new dimensions to social work techniques and methods and provides new ways to deal with problems. Social work research attempts to highlight insights about what intervention or treatment is actually helpful in practice and bring the best result. It also throw light on what hinder the attainment of desired goal. It also look for answers to problems faced by practitioners.

Relevance of Research in Social Work

Social work research tries to find answers to questions faced by practitioners and to make existing intervention more effective. The problems are not only professional but personal too. Overall aim is to make existing social work methods and techniques better and more effective.

In social work research, we study the problems from the point of view of professional social work. The designing of research problems, data collection and its interpretation will have to be attempted in a manner as would be useful to professional social work. The process should add new knowledge to social work theory and practice and also to enhance the outcome of professional social workers.

Limitation of Scientific Research Method in Social Work

Social work primarily deals with human behaviour, which is by and large complex and dynamic in nature. This means that different humans tend to behave differently under the same circumstances. One person can be happy in given circumstances and the second may be sad and at the same time others may remain indifferent. So it can easily be deduced that data collected for humans is subjective in nature and means very little for scientific research. Therefore one can not investigate human behaviour under guided conditions as in natural science. This creates many problems for researchers. 

Social work will never realize the objective of research as completely as natural science does, but still social work does not completely diminish the importance of scientific research methods.

Social Work is a diverse profession and work almost at all level of social system. Possible broad research areas could be:-

• Community health.
• Community mental health.
• Child welfare.
• Women welfare.
• Youth welfare.
• Juvenile delinquency. 
• Crime and correction.
• Aged welfare.
• Poverty alleviation.
• Management of Social Welfare Department and Organization.
• Disaster Management.
• Industrial Social Work. 

These are the areas which are very frequently studied by Social workers. Researchers might focus on individuals, families, groups, community or broad social systems.

Facts, events, and evidence help acquire reliable knowledge about various aspects of human behaviour. To get that knowledge, the method of science is still the most commonly used method. Objectivity, replication, prediction and verifiability are the characteristics of scientific approach, which keeps the researchers at bay from their personal biases, beliefs, perceptions, values, attitudes and emotions. With all the limitations and characteristics, scientific research is the best method to arrive at generalization in the field of social work.

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4.1 Types of research

Learning objectives.

• Differentiate between exploratory, descriptive, and explanatory research

A recent news story about college students’ addictions to electronic gadgets (Lisk, 2011) describes findings from some research by Professor Susan Moeller and colleagues from the University of Maryland . The story raises a number of interesting questions. Just what sorts of gadgets are students addicted to? How do these addictions work? Why do they exist, and who is most likely to experience them?

Social science research is great for answering just these sorts of questions. But in order to answer our questions well, we must take care in designing our research projects. In this chapter, we’ll consider what aspects of a research project should be considered at the beginning, including specifying the goals of the research, the components that are common across most research projects, and a few other considerations.

One of the first things to think about when designing a research project is what you hope to accomplish, in very general terms, by conducting the research. What do you hope to be able to say about your topic? Do you hope to gain a deep understanding of whatever phenomenon it is that you’re studying, or would you rather have a broad, but perhaps less deep, understanding? Do you want your research to be used by policymakers or others to shape social life, or is this project more about exploring your curiosities? Your answers to each of these questions will shape your research design.

Exploration, description, and explanation

You’ll need to decide in the beginning phases whether your research will be exploratory, descriptive, or explanatory. Each has a different purpose, so how you design your research project will be determined in part by this decision.

Researchers conducting exploratory research are typically at the early stages of examining their topics. These sorts of projects are usually conducted when a researcher wants to test the feasibility of conducting a more extensive study and to figure out the “lay of the land” with respect to the particular topic. Perhaps very little prior research has been conducted on this subject. If this is the case, a researcher may wish to do some exploratory work to learn what method to use in collecting data, how best to approach research subjects, or even what sorts of questions are reasonable to ask. A researcher wanting to simply satisfy her own curiosity about a topic could also conduct exploratory research. In the case of the study of college students’ addictions to their electronic gadgets, a researcher conducting exploratory research on this topic may simply wish to learn more about students’ use of these gadgets. Because these addictions seemed to be a relatively new phenomenon, an exploratory study of the topic made sense as an initial first step toward understanding it.

It is important to note that exploratory designs do not make sense for topic areas with a lot of existing research. For example, the question “What are common interventions for parents who neglect their children?” would not make much sense as a research question. One could simply look at journal articles and textbooks to see what interventions are commonly used with this population. Exploratory questions are best suited to topics that have not been studied. Students may sometimes say there is not much literature on their chosen topic, when there is in fact a large body of literature on that topic. However, that said, there are a few students each semester who pick a topic for which there is little existing research. Perhaps, if you were looking at child neglect interventions for parents who identify as transgender or parents who are refugees from the Syrian civil war, less would be known about child neglect for those specific populations. In that case, an exploratory design would make sense as there is less literature to guide your study.

Descriptive research is used to describe or define a particular phenomenon. For example, a social work researcher may want to understand what it means to be a first-generation college student or a resident in a psychiatric group home. In this case, descriptive research would be an appropriate strategy. A descriptive study of college students’ addictions to their electronic gadgets, for example, might aim to describe patterns in how many hours students use gadgets or which sorts of gadgets students tend to use most regularly.

Researchers at the Princeton Review conduct descriptive research each year when they set out to provide students and their parents with information about colleges and universities around the United States. They describe the social life at a school, the cost of admission, and student-to-faculty ratios (to name just a few of the categories reported). Although students and parents may be able to obtain much of this information on their own, having access to the data gathered by a team of researchers is much more convenient and less time consuming.

Social workers often rely on descriptive research to tell them about their service area. Keeping track of the number of children receiving foster care services, their demographic makeup (e.g., race, gender), and length of time in care are excellent examples of descriptive research. On a more macro-level, the Centers for Disease Control provides a remarkable amount of descriptive research on mental and physical health conditions. In fact, descriptive research has many useful applications, and you probably rely on findings from descriptive research without even being aware that that is what you are doing.

Finally, social work researchers often aim to explain why particular phenomena work in the way that they do. Research that answers “why” questions is referred to as explanatory research. In this case, the researcher is trying to identify the causes and effects of whatever phenomenon she is studying. An explanatory study of college students’ addictions to their electronic gadgets might aim to understand why students become addicted. Does it have anything to do with their family histories? With their other extracurricular hobbies and activities? With whom they spend their time? An explanatory study could answer these kinds of questions.

There are numerous examples of explanatory social scientific investigations. For example, in one study, Dominique Simons and Sandy Wurtele (2010) sought to discover whether receiving corporal punishment from parents led children to turn to violence in solving their interpersonal conflicts with other children. In their study of 102 families with children between the ages of 3 and 7, the researchers found that experiencing frequent spanking did, in fact, result in children being more likely to accept aggressive problem-solving techniques. Another example of explanatory research can be seen in Robert Faris and Diane Felmlee’s (2011) research on the connections between popularity and bullying. From their study of 8th, 9th, and 10th graders in 19 North Carolina schools, they found that aggression increased as adolescents’ popularity increased. (This pattern was found until adolescents reached the top 2% in the popularity ranks. After that, aggression declines).

The choice between descriptive, exploratory, and explanatory research should be made with your research question in mind. What does your question ask? Are you trying to learn the basics about a new area, establish a clear “why” relationship, or define or describe an activity or concept? In the next section, we will explore how each type of research is associated with different methods, paradigms, and forms of logic.

Key Takeaways

• Exploratory research is usually conducted when a researcher has just begun an investigation and wishes to understand the topic generally.
• Descriptive research is research that aims to describe or define the topic at hand.
• Explanatory research is research that aims to explain why particular phenomena work in the way that they do.
• Descriptive research- research that describes or define a particular phenomenon
• Explanatory research- explains why particular phenomena work in the way that they do, answers “why” questions
• Exploratory research- conducted during the early stages of a project, usually when a researcher wants to test the feasibility of conducting a more extensive study

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The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external validity or the result of unanticipated challenges that emerged during the study.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Theofanidis, Dimitrios and Antigoni Fountouki. "Limitations and Delimitations in the Research Process." Perioperative Nursing 7 (September-December 2018): 155-163. .

Importance of...

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and have your grade lowered because you appeared to have ignored them or didn't realize they existed.

Keep in mind that acknowledgment of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgment of a study's limitations also provides you with opportunities to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and discuss how they possibly impacted your results. Note that descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is generally less relevant in qualitative research if explained in the context of the research problem.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but provide cogent reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe a need for future research based on designing a different method for gathering data.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian! In cases when a librarian has confirmed that there is little or no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design ]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to the accuracy of what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency, but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, data, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this needs to be described. Also, include an explanation why being denied or limited access did not prevent you from following through on your study.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, event, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. NOTE :   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias. For example, if a previous study only used boys to examine how music education supports effective math skills, describe how your research expands the study to include girls.
• Fluency in a language -- if your research focuses , for example, on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic or to speak with these students in their primary language. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods. Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings!

After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitations of your study. Inflating the importance of your study's findings could be perceived by your readers as an attempt hide its flaws or encourage a biased interpretation of the results. A small measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated. Or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may very well be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Lewis, George H. and Jonathan F. Lewis. “The Dog in the Night-Time: Negative Evidence in Social Research.” The British Journal of Sociology 31 (December 1980): 544-558.

Yet Another Writing Tip

Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgment about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Boddy, Clive Roland. "Sample Size for Qualitative Research." Qualitative Market Research: An International Journal 19 (2016): 426-432; Huberman, A. Michael and Matthew B. Miles. "Data Management and Analysis Methods." In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444; Blaikie, Norman. "Confounding Issues Related to Determining Sample Size in Qualitative Research." International Journal of Social Research Methodology 21 (2018): 635-641; Oppong, Steward Harrison. "The Problem of Sampling in qualitative Research." Asian Journal of Management Sciences and Education 2 (2013): 202-210.

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10 Limitations and Prospects of Developmental Social Work

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This chapter draws the previous material together, recognizing that there are limitations to the developmental approach in social work but also that this approach has much future promise particularly in the context of economic challenges and resource constraints. It argues that social workers can use investment strategies in professional practice to promote the participation of social work’s clients in normal community life and in the productive economy, and in this way, contribute positively their long term well-being. The developmental approach is highly compatible with social work’s historical values and commitment to achieving social justice and human rights.

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• Understanding linguistic inequities in healthcare: moving from the technical to the social
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• Christina Reppas-Rindlisbacher 1 , 2 ,
• http://orcid.org/0000-0002-8466-1193 Shail Rawal 1 , 2
• 1 Department of Medicine , Temerty Faculty of Medicine, University of Toronto , Toronto , Ontario , Canada
• 2 Division of General Internal Medicine and Geriatrics , University Health Network and Sinai Health System , Toronto , Ontario , Canada
• Correspondence to Dr Shail Rawal, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; shail.rawal{at}uhn.ca

https://doi.org/10.1136/bmjqs-2023-016873

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When patients and clinicians do not speak the same language, the quality and safety concerns that can arise seem evident. However, the literature on the association between language and a host of health outcomes is vast and varied. In this issue of BMJQS , Chu et al share the results of their well-conducted systematic review and meta-analysis of the relationship between a patient’s spoken language and hospital readmissions and emergency department (ED) revisits. 1 They report that adult inpatients who prefer a non-dominant language are more likely to experience an unplanned hospital readmission or ED revisit after discharge. Moreover, they found that children whose parents spoke a non-dominant language had more ED revisits. The authors’ work is a thoughtful synthesis of a somewhat disparate literature and offers a starting point to consider key challenges in the broader area of research on linguistic inequities in healthcare.

Language as a variable

There are several challenges that arise when language is used as a quantitative variable in research. The first challenge is one of definition. Chu et al describe the heterogeneous approach to the measurement of language in the studies they reviewed as a limitation of their results. Some studies used dominant language proficiency, while others used preferred language, and yet others used primary language. Each measure assesses a different construct. And so, it becomes difficult to aggregate outcomes across studies when fundamentally different concepts are measured and compared.

Importantly, spoken language typically involves both speakers and listeners. However, the current literature almost exclusively examines patients’ language use and rarely reports or assesses that of clinicians. This makes the patient the focus of study rather than the clinician. 2 Future research must consider how to measure the languages used by clinicians and their concordance with a patient’s preferred language, especially given the ample evidence that language concordant care is associated with improved patient outcomes. 3–6

The role of dominant language speakers and institutions

Interactions between patients and clinicians occur within institutions that are embedded in a wider healthcare system and social context. A focus on the patient’s language use as the primary subject of study obscures the role of dominant language speakers, institutions and the health system in shaping linguistic equity. For example, do institutions offer meaningful access to interpretation services? Do they have policies that govern the use of interpretation? Do their hiring practices reflect the linguistic diversity of the communities they serve? What is the institutional culture as it relates to health equity? Understanding linguistic inequities requires that we move beyond measuring the patient’s language to assessing the degree to which institutions provide multilingual care.

Measuring the impact of interpretation services

Chu et al’s work underscores the challenges of understanding how interpretation services influence health outcomes such as readmission rates. In a stratified analysis by ‘access to or use of interpretation services’, the authors found higher odds of readmission from studies that did not describe interpretation services and no difference in readmission rates from studies that did describe interpretation services. Thus, the authors conclude that ‘interpretation access’ could be a mitigating factor in the association between language discordance and hospital readmissions. This finding should be interpreted with some caution due to the small sample size of the two studies analysed and the imprecise definition of interpretation access and use. One of the two studies verified patient-level interpretation and described the clinician who used the service but not the form of interpretation used (in-person, video, telephone). 7 While the other study described the form of interpretation used (telephone) but was unable to match an interpreted encounter to a specific patient or describe the clinical context of the interaction. 8

Thus, although the benefits of interpretation services are well established, 9 a significant barrier to better characterising the relationship between interpretation and health system outcomes, such as hospital readmission, remains the absence of patient-level data on whether interpretation was received by a patient, what form it took (telephone, in-person, video), and what type of communication it was used for (medication reconciliation, discharge counselling, etc). Institutions must create policies to collect such data at the level of the individual patient while also taking steps to protect personal health information. This would allow for a more nuanced understanding of the causative factors underlying the association between interpretation and health outcomes of interest. It would also allow institutions to identify areas for quality improvement and move from simply providing access to interpretation services to setting benchmarks for interpretation use.

The need for theory to inform the claims we make

Chu et al’s work offers an opportunity to reconsider how we account for the relationship between a patient’s spoken language and a given health outcome. Typically, poor communication between language-discordant patients and clinicians is theorised to be the primary mediator of poor patient outcomes. Professional interpretation is known to improve clinical care. 9 Thus, increasing the use of interpretation services is seen as the principal method for improving outcomes and remedying inequities for patients who speak non-dominant languages. However, the outcomes experienced by patients from language minority communities are likely shaped by more than poor communication alone, requiring an understanding of language as a social process.

Chu et al note that an important challenge in the analysis of research on linguistic inequities is the ‘complex relationship between language, race/ethnicity, migration status and socioeconomic status’. Language intersects with these characteristics in ways that are not well examined in conventional healthcare research. For example, it is unclear what proportion of the studies reviewed by the authors collected sociodemographic data from participants. Other studies that have explored these factors have found that patients who do not speak English in English-dominant countries are more likely to be racialised and live in poverty. 10 11 Thus, when considering Chu et al’s findings, non-dominant language speakers may have less access to home care and other social services that support a transition from hospital to home. Using a sociolinguistic lens, we might also consider how perceptions of a person’s language use are linked to racism or xenophobia. For example, a white French speaker in an English-dominant institution may be cared for in a different manner from a French speaker who is not white. 2 Similarly, language hierarchies position European languages above others, 12 and discourses related to migration, assimilation, and visible markers of cultural or religious difference may also shape the care of speakers who are deemed to be inadequately proficient in the dominant language.

Moving forward

At a time when global migration is reshaping population demographics, Chu et al’s study provides an opportunity to reflect on the status of research on linguistic inequities in healthcare. First, it brings to light the need for a standardised approach to defining language use in order to better synthesise findings across studies. This requires greater coordination among researchers and the development of a consensus view on how best to report the complex dimensions of language. Health systems must also be mandated to collect such data. Self-reported language preference is a useful starting point, 13 but we must develop the theory and methods needed to move beyond a binary understanding of language to one that considers the reality that patients and clinicians may speak multiple languages with varying proficiency and preference.

Second, the study reminds us to characterise the context in which communication occurs, so that the role of both speakers and listeners are examined. This requires that data on clinician language be included in health and administrative records so that language concordant care can be studied. It also underwscores the need for sociodemographic data be collected so that the scope of analysis can be expanded to include consideration of the effects of racism, xenophobia, religious discrimination and classism on health outcomes in non-dominant language speakers. Finally, the study highlights the need to develop measures and quality standards to assess how well institutions provide multilingual care. Such efforts must be grounded in the views of patients who speak non-dominant languages, and begin with collecting patient-level interpretation data.

Remedying linguistic inequities requires us to move from understanding language as a technical problem of poor communication, 14 to one that accounts for social context. It requires us to enrich our view of language and its intersections with race, migration status, religion and socioeconomic position, and to recognise that interventions to address linguistic inequities should occur in concert with broader efforts to improve health equity. Only then can we better understand the associations between the variables we seek to describe and move towards substantive action to address the inequities experienced by language minority communities.

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• Bardach NS , et al
• Diamond L ,
• Izquierdo K ,
• Canfield D , et al
• Ngo-Metzger Q ,
• Sorkin DH ,
• Phillips RS , et al
• Batista R , et al
• Parker MM ,
• Fernández A ,
• Moffet HH , et al
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• Pérez-Stable EJ ,
• Gregorich SE
• Jacobs EA ,
• Chen AH , et al
• Fischer A ,
• Conigliaro J ,
• Allicock S , et al
• Institute of Medicine (US) Subcommittee on Standardized Collection of Race/Ethnicity Data for Healthcare Quality Improvement
• McElhinny B

Contributors CR-R and SR contributed to the conception, drafting and critical review of this article.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests CR-R reported receiving the Vanier Canada Graduate Scholarship Award, the Eliot Phillipson Clinician-Scientist Training Program Award and the PSI Foundation Resident Research Grant outside the present manuscript. SR is supported by an award from the Mak Pak Chiu and Mak-Soo Lai Hing Chair in General Internal Medicine, University of Toronto.

Provenance and peer review Commissioned; internally peer reviewed.

Linked Articles

• Systematic review Association between language discordance and unplanned hospital readmissions or emergency department revisits: a systematic review and meta-analysis Janet N Chu Jeanette Wong Naomi S Bardach Isabel Elaine Allen Jill Barr-Walker Maribel Sierra Urmimala Sarkar Elaine C Khoong BMJ Quality & Safety 2023; - Published Online First: 30 Dec 2023. doi: 10.1136/bmjqs-2023-016295

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How to Make a “Good” Presentation “Great”

• Guy Kawasaki

Remember: Less is more.

A strong presentation is so much more than information pasted onto a series of slides with fancy backgrounds. Whether you’re pitching an idea, reporting market research, or sharing something else, a great presentation can give you a competitive advantage, and be a powerful tool when aiming to persuade, educate, or inspire others. Here are some unique elements that make a presentation stand out.

• Fonts: Sans Serif fonts such as Helvetica or Arial are preferred for their clean lines, which make them easy to digest at various sizes and distances. Limit the number of font styles to two: one for headings and another for body text, to avoid visual confusion or distractions.
• Colors: Colors can evoke emotions and highlight critical points, but their overuse can lead to a cluttered and confusing presentation. A limited palette of two to three main colors, complemented by a simple background, can help you draw attention to key elements without overwhelming the audience.
• Pictures: Pictures can communicate complex ideas quickly and memorably but choosing the right images is key. Images or pictures should be big (perhaps 20-25% of the page), bold, and have a clear purpose that complements the slide’s text.
• Layout: Don’t overcrowd your slides with too much information. When in doubt, adhere to the principle of simplicity, and aim for a clean and uncluttered layout with plenty of white space around text and images. Think phrases and bullets, not sentences.

As an intern or early career professional, chances are that you’ll be tasked with making or giving a presentation in the near future. Whether you’re pitching an idea, reporting market research, or sharing something else, a great presentation can give you a competitive advantage, and be a powerful tool when aiming to persuade, educate, or inspire others.

• Guy Kawasaki is the chief evangelist at Canva and was the former chief evangelist at Apple. Guy is the author of 16 books including Think Remarkable : 9 Paths to Transform Your Life and Make a Difference.

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University of Utah announces major funding for new addiction treatment research

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Patricia Brandt Manager, Public Relations and Communications, Huntsman Mental Health Institute University of Utah Health Email: Patricia.Brandt @hsc.utah.edu

Salt Lake City (April 10, 2024) - Worldwide, someone dies from drug or alcohol addiction every four minutes. Now, researchers at Huntsman Mental Health Institute at the University of Utah have been selected by Wellcome Leap to research a new treatment for substance use disorder as part of a $50 million commitment to develop innovative treatments.

Brian J. Mickey, MD, PhD, professor of psychiatry at Huntsman Mental Health Institute (pictured top left), will lead the team of investigators with expertise in psychiatry, biomedical engineering, neuroscience, radiology, and social work to research a new, noninvasive treatment for addiction. Co-principal investigators include Jan Kubanek, PhD , (pictured top center), and Taylor Webb, PhD (pictured top right); co-investigators include (from left to right) Eric Garland, PhD, LCSW ; Rana Jawish, MD ; Vincent Koppelmans, PhD ; and Tom Riis, PhD.

The research will be funded by the Untangling Addiction program, which is a $50 million program founded by Wellcome Leap , to develop scalable measures to assess addiction susceptibility, quantify the risks stemming from addiction, and develop innovative treatments.  

“Substance use disorder is a significant global health problem, and yet the treatment options are limited,” Mickey said.  “We’re developing a non-invasive intervention for preventing and treating addiction, chronic pain, and depression. This funding will help us validate and generate the data to support the next critical step: an efficacy trial to determine the effectiveness of the intervention.”

Mickey’s team will use a novel ultrasound-based device to modulate deep brain regions and behaviors associated with opioid addiction. The goal will be to ultimately develop this approach into an individually targeted therapeutic intervention for a range of addictions. “Addictions are brain illnesses that have enormous negative impact on individuals, families, and society,” Mickey said. “A major reason that addictions have been difficult to prevent—and treat—is that they are driven by dysfunction of deep brain regions that are challenging to access. Many psychiatric problems such as depression, anxiety, and addiction are caused by malfunction of brain circuits. This project is an example of our mission to understand how these neural circuits are dysregulated and to develop novel, circuit-targeted interventions that return the brain to a healthy state.”

"We are proud to bring Wellcome Leap's innovative problem-solving and funding approach to our research enterprise at the University of Utah," said Taylor Randall, President , University of Utah. "To have our mental health researchers contributing to pioneering work on addiction treatment reaffirms our commitment to improving lives through discovery."

“What makes research like this so impactful is that it brings together a variety of disciplines to help solve complex problems in mental health,” said Mark Hyman Rapaport, MD , CEO of Huntsman Mental Health Institute. “This is particularly timely news given the groundbreaking of a new translational research building on campus focused on mental health and the brain. Our nation is in a mental health crisis, but there is hope if we can think differently and work together to change this trajectory.”

About Huntsman Mental Health Institute

Huntsman Mental Health Institute at University of Utah Health brings together 75 years of patient care, research, and education into one of the nation's leading academic medical centers focused on mental health. Nestled in the campus of University of Utah, Huntsman Mental Health Institute serves the community with 1,600 faculty and staff in 20 locations providing inpatient and outpatient services for youth, teens, and adults as well as a comprehensive crisis care model which includes the nationally recognized SafeUT app and the 988 Crisis hotline for Utah. Our mission is to advance mental health knowledge, hope, and healing for all. Learn more at:  HMHI.utah.edu  and join the conversation on  Instagram ,  Facebook ,  TikTok ,  X  and  LinkedIn .

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