To prevent or mitigate health-related stigma in research, investigators can use common theories, frameworks, models, and measures to help them consider the similarities and differences across stigmatized conditions should guide research. Though there are many existing research tools to examine health-related stigma, the majority focus on a single health condition and on the individual—limiting the impact that the resulting innovations can have on stigma reduction and on health outcomes.
The research tools below highlight cross-cutting approaches to stigma-reduction research and encouraging investigators to examine multiple stigmatized conditions at once as well as the interactions between them. These tools also promote a shift to multi-level analyses so that researchers can comprehensively evaluate the individual, interpersonal, and structural levels and understand how they interact to result in poorer health outcomes.
Frameworks and Models
Stigma and discrimination frameworks and models are critical for understanding, measuring, and intervening to reduce stigma and discrimination and improve outcomes. Clear frameworks and models about how stigma and discrimination may occur are important to develop anti-stigma or anti-discrimination interventions. Multiple factors need to be considered to decide which framework or model is a good fit for a particular research or service project. The frameworks and models listed below may help guide measurement, research, intervention development, and policy efforts.
Health Stigma and Discrimination Framework: A global, crosscutting framework that applies to a range of health conditions. It identifies how other stigmas interact with health-related stigma, highlights the domains and pathways common across health-related stigmas, and suggests key areas for research, intervention, monitoring, and policy.
Related NIMH Webinar: Health Stigma and Discrimination: A Global, Cross-cutting Research Approach
Stigma Mechanisms in Health Disparities Model: A model that describes a multilevel process by which stigma “gets under the skin” and the degree to which concealability (i.e., whether stigma is clearly known or visible – “discredited” – or stigma is unknown and concealable – “discreditable”) moderates these effects. The model calls attention to stigma as a social determinant of health and health disparities. It also brings together individual- and structural-level approaches for a comprehensive understanding of stigma mechanisms and processes within a sociocultural context.
The Framework Integrating Normative Influences on Stigma): A systems science approach that examines the stigma complex and offers a multilevel framework to organize and understand how interrelated, heterogeneous parts (such as key concepts, basic premises, and characteristics of the stigmatization process) work together to inform theory, research, and practice.
Intersectional Stigma: The concept of intersectional stigma leverages and integrates several theoretical traditions, including intersectionality, stigma, minority stress, critical race theory, and feminism. To date, much stigma research has taken a “one stigma, one outcome” approach by focusing on how one category of stigma is associated with one type of health outcome. Yet stigma research conducted through an intersectional lens recognizes that stigma is multidimensional; there are multiple, interlocking stigma processes that give rise to HIV inequities (e.g., racism, sexism, heterosexism).
Evolving Intersectionality Within Public Health: From Analysis to Action: Dr. Lisa Bowleg, Ph.D. (with the Department of Psychological and Brain Sciences, Intersectionality Training Institute, The George Washington University, Washington, DC] provides a historical overview of intersectionality, core tenets, and relevance to public health. on the analysis discusses how traditional research organizations are applying intersectionality, and offers practical applications of how intersectionality could facilitate equitable health policy and practice for marginalized groups.
Mediators Linking Stigma to Health: While not a formal model, this conceptual framework provides a way to understand the individual, interpersonal, and structural pathways through which stigma influences health.
Stigma measurements are typically specific to a health condition (for example, HIV, mental illness, or substance use). Clear models of stigma and discrimination are important to provide common terminology and understanding to identify which types and levels of stigma are most critical to measure. Review articles regarding stigma and discrimination measures help provide guidelines and suggestions when interested in studying and measuring stigma. The following articles discuss several measures of health-specific stigma.
The Health Stigma and Discrimination Framework identifies different points in the stigmatization process where data may be collected.
- Assessment tools have been developed for different conditions and different domains of stigma (for example, internalized stigma or anticipated stigma)
- Reviews of stigma and discrimination measures include:
- Measuring health-related stigma – A literature review
- The Stigma Complex
- Ending discrimination against people with mental and substance use disorders: the evidence for stigma change (National Academies of Sciences Engineering and Medicine)
- Reviews of stigma and discrimination measures include:
- More specific measures of stigma are discussed further in Out of the silos: identifying cross-cutting features of health-related stigma to advance measurement and intervention.
In a webinar series produced by the Office of Disease Prevention at the National Institutes of Health, Dr. Valerie Earnshaw, PhD, presented on “Methods for Understanding and Addressing Stigma To Prevent Common Risk Factors for Disease.”
- In this presentation, Dr. Earnshaw provides a cross-cutting conceptual overview of stigma, identifies targets for stigma measurement, recommends methodological approaches for stigma research, and reviews the intervention toolkit to address stigma. She draws on examples from her own and others’ research, with a focus on two highly stigmatized disease contexts: HIV and substance use. She advocates for theory-based cross-cutting research to improve understanding of stigma and the development of intersectional, multilevel, and longitudinal interventions to enhance efforts to address stigma
Development and psychometric evaluation of the Chronic Illness Anticipated Stigma Scale
Earnshaw and colleagues developed a measure of anticipated stigma (such as expectations of prejudice, stereotyping, and discrimination) among people living with chronic illnesses.
Stangl and colleagues developed a succinct set of measures to capture key domains of stigma for use in HIV prevention and treatment research.
- They created parallel measures of HIV stigma (for people living with HIV, community members and health care workers).
- Stigma domains:
- Fear and judgement
- Perceived stigma (in communities and in health settings)
- Anticipated stigma
- Enacted stigma (in communities and in health settings)
- Internalized stigma
Berger HIV Scale
Other researchers have shortened the original 40-item Berger HIV stigma scale to focus on key components such as negative self-image for internalized stigma and public attitudes for perceived stigma. For example, one team created a 10-item version for youth living with HIV that could be considered in COVID-19 research.
This section provides an overview of anti-stigma and anti-discrimination interventions. Several review articles are included that evaluate the quality of the evidence for the effectiveness of health-related stigma interventions.
The Health Stigma and Discrimination Framework identifies different points in the stigmatization process where interventions to reduce stigma may take place.
- Data on the drivers and facilitators of stigma can inform development of appropriate interventions.
- Information about the manifestations of stigma can be used by researchers and evaluators to determine the effectiveness of stigma interventions, by administrators to identify opportunities to reduce or eliminate stigma from health care and other settings, and by communities or advocates to raise awareness of existing stigma and discrimination and to effect change among the general population and policymakers.
- Data on the outcomes of stigma can inform funding and programming decisions for addressing health-related stigma.
- Related reviews:
- Review of stigma interventions (van Brakel et al. 2019)
- Review of interventions to reduce stigma in health facilities (Nyblade et al. 2019)
- Review of multi-level stigma interventions (Rao et al., 2019)
- Systematic review of implementation studies of health-related stigma reduction interventions in LMICs (Kemp et al., 2019)