Health Stigma and Discrimination: A Global, Cross-cutting Research Approach
>> VALERIE EARNSHAW: Good morning, and welcome to everyone joining us here in person, as well as online, for the first of the National Institute of Mental Health, Center for Global Mental Health Research's 2019 webinar series. Today's webinar introduces a collection of articles, sponsored by the Fogarty International Center, which was recently published in BMC Medicine that proposes a global, cross-cutting research approach to health stigma and discrimination. My name is Valerie Earnshaw, I'm a member of the team of guest co-editors for this special issue, along with Gretchen Birbeck, Virginia Bond and Musah Lumumba El-Nasoor. I'm here today on their behalf to introduce the webinar and to moderate our discussion.
I would just like to let you know at this time that we are recording.
There are many determinants of health. There are social determinants, but also economic, environmental, and genetic, or biological. In the midst of all of these determinants, all of these things that we may seek to change, and understand, why should we focus on stigma?
[whispering] Okay. We are just trying to change the slide deck. Bear with us for one moment. Okay, it looks like we are in business. Thanks again for hanging with us through those technical difficulties. Hopefully we should be smooth sailing for the rest of the morning.
But I was just in the middle of making an argument to you for why we should focus on stigma in the midst of many other determinants of health.
We might focus on stigma because it is harmful, but it is also malleable. It is global, and also cross-cutting. So, in short, stigma is a big problem, but it is also a solvable one.
If we focus on stigma as harmful, we have a wealth of evidence that stigma undermines both mental and physical health. Consider this quote from a relatively young girl with bipolar spectrum disorder regarding her experiences with stigma. She was quoted in this article as saying crazy, psycho, nuts, because that's what I heard from everyone else. My mom would be like, you're psycho, you're crazy, my brother would be like, you're freaking psychotic, you're a nut case. So, I just, you know, those were the words for what I had. Believing oneself to be crazy, psycho, or nuts, or internalizing stigma is harmful to health. It may make people feel badly about themselves, maybe leading to or exacerbating depression, anxiety or other mental health issues. Moreover, having a mother who thinks her daughter is crazy or psycho is also harmful to health. It may make this mother less likely to seek out or support treatment for her daughter. In addition to excellent qualitative work such as this, we are now at a phase where we have a great deal of quantitative evidence that stigma is bad for health. This evidence has been summarized in serval meta-analyses and review papers that not only establish the magnitude of some of the associations between stigma and health, but also examines some of the mediating and moderating factors linking stigma with health. Yet stigma is also malleable. Stigma waxes and wanes with time. For example in the United States and globally, we’ve seen changes in HIV stigma over time. Using nationally representative data, Gregory Herrick has documented decreasing HIV stigma in the United States throughout the '90s. And similarly Brian Chan and Alex Tsai document a decreasing desire for social distance, an indicator of stigma, towards people living with HIV in 31 African countries between 2003 and 2013. In this graph representing their findings, we see evidence both that stigma can change, because we see a downward slope within these lines, representing a negative association, and that we have more work to do to eliminate it. And we know that because, at the end of the lines, we are still seeing a 20 to 60 percent prevalence and endorsement of social distance from people living with HIV. Stigma is also global. It may differ in degree or target, but stigma is the pollution that hangs over our largest cities and smallest villages throughout the world. Dr. Bernice Pescosolido and her colleagues have used nationally representative data from 16 countries to examine stigma toward people with depression and schizophrenia, she found that a core of five prejudice items are consistently highly endorsed. Even in countries with low overall stigma scores. In these countries, respondents were unwilling to allow people with these mental illness to care for their children or have them with in-laws. And they thought that they’d be less likely… oh sorry, that they would be likely to be violent towards themselves, that they were unpredictable and that they shouldn’t teach children.
So we will hear more from Dr. Pescosolido later during our webinar.
Stigma is also cross cutting. Stigma plays a fundamental role in generating and perpetuating health inequities across a range of disease contexts, these include HIV, tuberculosis, epilepsy, obesity, and many mental illnesses. To date, much of the research on and interventions to address health related stigma have occurred within these disease silos. Yet theorists have highlighted that there is significant similarities in the drivers, manifestations, and outcomes of stigma across diseases.
And they have indicated that there may be shared mechanisms and pathways through which stigma impacts health, such as through social support and coping. Researchers have also suggested that there may be common approaches to measure and intervene in stigma across these silos. To make meaningful strides in understanding and addressing health related stigma, researchers may need, may need to deconstruct existing disease silos and utilize cross-cutting approaches to stigma research and intervention.
Our special issue essentially presents a road map for researchers, health care providers, policy makers, community members, and other key stakeholders, to address stigma through the use of cross-cutting approaches.
How did we get here? Well, NIH has a history of supporting health related stigma research, which sets the stage for this special collection. Here, I’ll mention just a few highlights. In 2001, Fogarty and his NIH partners hosted an international research conference to discuss the etiology of stigma across conditions, how it impacts the health of citizens globally, and what methods and interventions could be harnessed to measure and address it. This conference informed the creation of Fogarty’s stigma and global health research program which was launched in 2002. With respect to HIV in particular, the Division of AIDS Research at the NIMH and it’s community and federal partners published a series of papers in 2013, examining the state of the science, and identifying key gaps in measurement methods and intervention research.
We are very lucky to have one of the co-editors of that uh series joining us today and she will be speaking next, Dr. Anne Stangl. In 2016, the White House meeting on HIV Stigma was convened by the NIH Office of AIDS Research, NIMH and the Office National AIDS Policies. One emergent theme from this meeting was the intersection of HIV stigma with other forms of stigma and discrimination, such as those related to sexual orientation, gender identify, mental illness, substance use, socio-economic status, and or race and ethnicity. And this has been a priority, um, at the NIMH's Division of AIDS Research ever since.
In 2017, Fogarty and his NIH partners hosted a three-day workshop on the science of stigma reduction, during which multi-disciplinary experts further refined the agenda for cross-cutting stigma research and global health. The workshop conversations helped to inform the launch of Fogarty's new grant program in 2018, reducing stigma to improve HIV AIDS prevention, treatment and care in LIMCs (low and middle income countries). The special collection published this year reflects the research challenges, priorities, and opportunities addressed during this workshop, to catalyze research approaches and collaborations and move this critical field forward.
There are many people [beep/inaudible] roles in the 2017 meeting, 2018 grant program, and 2019 special issue. These include Nalini Anand, and Arianne Malekzadeh from Fogarty, Gregory Greenwood, from the NIMH as well as representatives from 10 other partner institutes, centers, and offices; The BMC Medicine collection guest editors, as well as the authors of the individual articles.
As a co-editor of the series, I'm probably, or likely biased. But I think that this issue contains a treasure-trove of information for people who are doing this work. So it starts with an overview article, providing some historical background on the progression of stigma theory, and summarizes the collections contribution, it then includes articles that focus in on a series of topic.
Uh, Van Brackle and colleagues argued, for example, that a generic approach to stigma research offers important opportunities for cross cutting and synergistic research.
Cane and colleagues review the effects of health related stigma within five high burden diseases and low and middle income countries, these include mental illness, HIV, tuberculosis, epilepsy and substance abuse research.
Kemp and colleagues reported on 35 published studies of evaluations of stigma reduction interventions in low and middle income countries that offer at least one implementation outcome.
Sprague and colleagues argue for the importance of participatory praxis with an emphasis on the need for a shared starting point from the strengths and assets of the community.
And Millum and colleagues’ weight ethical considerations in global health related research with helpful examples and case studies along the way.
This morning’s webinar will highlight four of the articles from this collection. We will hear from Dr. Anne Stangl, who presented a global, cross-cutting theoretical framework to guide research intervention, development and policy. Following Dr. Anne Stangl, we’ll hear about intersectionality. Dr. Turan and colleagues address the convergence of multiple stigmatized identities. Dr. Pescasolito joins us this morning to present on this paper.
Afterwards Dr. Laura Nyblade and Melissa Stockton will tell us about stigma within health care facilities. And finally, Dr. Deepa Rao, [beep/inaudible] from a review of 24 multi-level stigma interventions.
So, this is our agenda for this morning, we will hear from our four presenters, with two breaks for questions and answers, and we will also be concluding with thoughts from Gregory Greenwood, from the NIMH. If you are joining us online, please do log your questions within our webinar system. Arianne Malekzadeh and I will be reading them and will be happy to pose them to our presenters.
I will wrap up this introduction by noting that a cross-cutting approach to stigma research emphasizes connection across disease silos, disciplines of research, and community research representatives.
Imagine a researcher just beginning to try to understand and address stigma associated with a new, or relatively under studied health condition. Perhaps it is the next HIV, or Ebola, or opioid epidemic. At one point this researcher may have felt unconnected, siloed within their field of research, where it might be difficult for them to see how what they are doing relates to mental illness, tuberculosis, or HIV. But today that researcher can pick up this special issue and connect with a theoretical framework to guide research, options for measurement, solutions for interventions, and reflections on partnering with communities.
Imagine how much faster this researcher will be able to get to solutions. To actually doing something about stigma, than if they didn't have this collection of tools readily available to them. The ultimate promise of a cross-cutting approach of this collection includes more rapid and efficacious solutions to health related stigma, in both existing and well-established areas of stigma research, like mental illness, HIV, and epilepsy, as well as new and emerging areas.
I would now like to turn this over to Dr. Anne Stangl, from the International Center for Research on Women. Dr. Stangl is a senior behavioral scientist. She has 17 years of international public health experience in Africa, Asia, and the Caribbean. With a focus on stigma, qualitative and quantitative research methods, research design, statistical analysis, systematic reviews, and monitoring and evaluation. Her research centers on human rights and stigma. Particularly as they relate to HIV prevention, care, and treatment, healthy transitions to adulthood for adolescents, and equitable access to healthcare. She is also actively engaged in utilizing research findings to inform global policy and action. Dr. Stangle holds a PhD in public health from Tulane University.
>> ANNE STANGL: Good morning, everyone. It is a pleasure to be with you today, and welcome to all those online as well, and there's a number of people in the room. Hopefully we will get through this part without any more technical glitches.
So just wanted to begin today, [silence] uh, begin today by just going quickly over the format of the presentation. So first, I am just going to give you some context, and then next I'm going to go over some key stigma definitions, just to make sure that we are all on the same page, and then I am going to give you an overview of the new framework, followed by practical applications of the framework.
Okay. So firstly, before we begin, I think it is really important to remind ourselves why stigma is so important in the broader context of health and development.
First and foremost, the experience of stigma is an infringement on our human right to live a life free from discrimination, as enshrined in the universal declaration of human rights. Article 2 states that everyone can claim their rights, regardless of sex, race, language, religion, social standing, birth, or status. Stigma often interferes with people's ability to access health care and other social services, particularly marginalized populations, so it can really impede health and development globally.
Secondly, stigma influences population health outcomes by worsening or impeding a number of processes that exacerbate poor health, including social relationships, the availability of resources, stress, and psychological and behavioral responses, and lastly, recent research documented the negative impact of internalized and experienced stigma on various health outcomes across a range of diseases. So first…so with this background in mind, I just wanted to spend a few minutes making sure that we are all on the same page about some basic definitions.
So what is stigma? I find it very helpful to start with the very first conceptualization of stigma by sociologist Irving Goffman, he defines stigma as an attribute that is deeply discrediting and reduces the bearer from a whole and usual person to a tainted and discounted one. This then leads to disqualification from full social acceptance. He goes on to highlight the insidious nature of stigma. By definition, of course, we believe the person with the stigma is not quite human. On this assumption, we exercise varieties of discrimination, through which we effectively, if [beep/inaudible], reduce his life chances. It is important to note here that Goffman was really focused on the individual and his conceptualization of stigma. But stigma actually emerges through a dynamic social process, beginning when a difference is labelled, followed by stereotyping because of that difference, and then a separation of us from them occurs, followed by status loss and discrimination.
The stigmatization process is enabled by underlying social, political, and economic powers. Oops, hold on, the slides are doing something funny. Okay.
The stigmatization process is enabled, by underlying social, political, and economic powers that seek to devalue some groups to create superiority in others, by turning difference into inequity based on a number of things such as gender, age, and sexual orientation. This leads to exclusion of groups, and this piece is really critical for our thinking around structural interventions to reduce stigma and discrimination.
Okay. So lastly, I just want to note that stigma and discrimination are often combined together as if they are one in the same. But they are actually distinct concepts that need to be distinguished in order to respond to reduce them. In recent years, the definition of discrimination has changed to clarify how it is distinct from stigma. We now define discrimination as the experience of stigmatizing behaviors that fall within the purview of the law, so basically actions that are illegal in a given context, this may include things like losing housing or a job due to your health status, being physically assaulted because of your status and so on. Previous definitions of discrimination have been much broader, for example, UNAIDS defines discrimination as unfair or unjust treatment of an individual based on the real or perceived status or attribute, such as a medical condition, or being perceived to belong to a particular group. So we will come back to this distinction between stigma and discrimination later in the presentation when I walk you through the framework.
So, as Valerie mentioned a little bit earlier, researchers studying health-related stigma have tended to focus quite narrowly on specific disease or health conditions.
Uh, let me see if my little button… Okay, there we go.
So this approach has led to theoretical silos, despite the fact that the stigmatization process is fairly similar across health conditions and contexts. So for example, we identified seven obesity frameworks, seven HIV frameworks, and five mental health stigma frameworks when preparing this paper. Health stigma frameworks are typically specific to one mental health condition, as I just mentioned, and they tend to concentrate on psychological pathways among individuals. Very few explore the social and structural pathways leading to stigma.
And, as a result, current health stigma frameworks really limit Researchers’ ability to inform the multi-level interventions required to meaningfully influence the stigmatization process. This siloed approach really impedes comparisons across stigmatized conditions, it also impedes research on innovations to reduce health related stigma and ultimately to improve health outcomes.
So we developed a new framework called the health, stigma, and discrimination framework. The framework builds from existing conceptualizations of health related stigma and the from practical experience of the co-authors in designing stigma reduction interventions for a range of health-related stigmas.
I just want to take a moment here to acknowledge my co-authors who you see pictured here. It was really such an honor to work with some of the world's greatest thinkers on this topic. Collectively, we brought experience from stigma research on mental health, HIV, leprosy, cancer, tuberculosis, and obesity. And I think the resulting framework really benefits from this diversity of expertise. So our intent was really to provide a broad orienting framework, similar to Perlin’s stress process model, to give conceptual organization to diverse lines of research that are underway across disciplines.
So now I’m gonna spend several minutes on this slide. This slide shows the framework that is presented in the paper. I want to walk you through the process and define some key terminology.
So the [beep/inaudible] framework articulates the stigmatization process as it unfolds across the socio-ecological spectrum in the context of health, which can vary across economic contexts in low, middle, and higher income countries. The process can be broken down into a series of constituent domains including drivers and facilitators, stigma marking, and stigma manifestations, which influence a range of outcome among affected populations, as well as organizations and institutions that ultimately impact health and society.
So, the first domain refers to factors that drive, or facilitate, health-related stigma. Drivers really vary by health condition, but they are conceptualized as inherently negative. They can range from fear of infection, through casual contact for communicable diseases, to concerns about productivity due to poor health for chronic conditions, to social judgment and blame. Facilitators however may be positive or negative influences. For example, the presence or absence of occupational safety standards and protective supplies in health facilities can minimize or exacerbate stigmatizing avoidance behaviors towards populations with infectious diseases by health care workers.
Drivers and facilitators determine whether stigma marking occurs, in which a stigma is applied to people or groups related to either a specific health condition, or a perceived difference, such as race, class, gender, sexual orientation, or occupation. Intersecting stigma occurs when people are marked with multiple stigmas. Once a stigma is applied, it manifests in a range of stigma experiences and practices.
Stigma experiences can include experience discrimination, which refers to stigmatizing behaviors that fall within the purview of the law in some places. I mentioned earlier things like refusal of housing, and experience stigma, or stigmatizing behaviors that fall outside the purview of the law, such as verbal abuse or gossip.
Another stigma experience is internalized or self-stigma, this is defined as a stigmatized group member's own adoption of negative societal beliefs and feelings, [beep/inaudible] and social devaluation associated with his or her stigmatized status. Perceived stigma, which refers to perceptions about how he or she is treated in a given context, and anticipated stigma, which refers to expectations of bias being perpetrated by others, if their health condition becomes known, are also classified as stigma experiences in our framework.
Lastly, secondary or associative stigma, which refers to the experience of stigma by family or friends by members of stigmatized groups, or among health care providers who provide care to members of stigmatized groups is included under stigma experiences. Stigma practices can include stereotypes, prejudice, stigmatizing behavior, and discriminatory attitudes. In the framework, we consider stereotypes and prejudices as [beep/inaudible] manifestations, as they both fuel and are reinforced by the stigmatization process.
We postulate that stigma manifestations go on to influence a number of outcomes for affected populations including access to justice, access to and acceptability of health care services, uptake of testing, adherence to treatment, resilience, or the power to challenge stigma, and advocacy. They also influence outcomes for organizations and institutions, including laws and policies, the availability of quality health services, law enforcement practices, and social protections.
While the framework is specific to health-related stigma, it recognizes that health-related stigma often co-occurs with other intersecting stigmas, such as those related to sexual orientation, race, and poverty. So incorporating intersecting stigmas into the framework was really necessary, as stigma manifestations and health outcomes may be influenced by a range of stigmatizing circumstances that must be considered to understand the full impact of stigma. And you will be hearing a bit more about intersecting stigma in the next presentation.
So, what is different about the new framework? The health stigma and discrimination framework differs from many other models in that it does not distinguish the stigmatized from the stigmatizer. The absence of this dichotomy is really intentional as we seek to challenge the us versus them distinction that enables people to set others apart as different from the norm, which is a key component of the stigmatization process.
We are seeking here to move psychological models that see stigma as a thing that individuals impose on others, and instead emphasize the broader, social, cultural, political, and economic forces that structure stigma. Removing the us versus them dichotomy also makes the framework more palatable to change agents, such as community leaders, advocates and policy makers, as it highlights that all persons can act as change agents and underscores the need for self reflection and awareness of biases.
Another difference from previous frameworks is the separation of manifestations into experiences and practices. This distinction clarifies the pathways to various outcomes following the stigma marking the phase of the process. Those who experience, internalize, perceive or anticipate health related stigma face a range of possible outcomes, such as delayed treatment, poor adherence to treatment, or intensification of risk behavior that may diminish their health and wellbeing. Stigma practices, on the other hand, highlight how the stigmatization process can generate or reinforce stereotypes and prejudice towards people or groups, living with or at risk for various health conditions, and foster discriminatory attitudes that fuel social inequality.
We also differentiated [beep/inaudible] outcomes for affected populations, for example, the stigmatized person or group, as well as their family, friends, or health care providers, from outcomes for organizations or institutions. Our framework seeks to demonstrate that stigma experiences and practices influence both affected populations and organizations and institutions which then together affect the health and social impacts of stigma.
So, by articulating these outcomes, the framework highlights the need for multi-level interventions to respond to health related stigma. It also focuses attention on the far-reaching influence of health related stigma on societies, as well as individuals.
So, how do we use the framework? One way is to guide the development of interventions. In terms of where to intervene, ideally we want to stop stigma marking from occurring. So interventions often focus on the drivers and facilitators of stigma. So, for example, mass communication efforts may be used to help populations better understand the health condition and dispel myths about how a disease and isn't transmitted, and who is at risk.
Similarly, new policies could be developed and implemented in health care facilities, to ensure that patients with specific health conditions like HIV are not identified in any way, for example, through specific colored file folders. So while we’d like to prevent stigma from being applied, and we also need to be prepared to deal with the manifestations of stigma. This could include psycho-social support for people living with a specific health condition or legal aid to cope with discrimination.
It could also include training for health care providers and police to overcome stereotypes and discriminatory attitudes, or development of new laws or policies to protect against discrimination.
So, in addition, it is our hope that the framework will enable stigma researchers across disciplines to standardize measures, compare outcomes, and build more effective, cross-cutting interventions.
In addition, we hope that researchers can also use the framework to generate research foci, to explore multiple health issues, and consider the interaction between multiple identities, social inequalities, and health issues. The framework can also point to areas where clinicians, program implementers and policy makers can focus greater attention to better meet the needs of and improve health outcomes among their clients, communities and societies more broadly.
Implementation science approaches can advance how we tailor and apply the framework to guide stigma reduction, interventions, and policies. For example, in defining who is the target audience, who the target audience is for change, what specific drivers and facilitators of stigma should be addressed, what intervention or policy components are appropriate to address them, and how to measure change and specific outcomes over time.
So to demonstrate the cross-cutting nature of the health stigma and discrimination framework, we examined how it applies to both communicable and non-communicable health conditions. I am going to share two of these examples with you now.
So, for some reason, I am seeing the slides on the laptop, but now they are sort of frozen on my screen here. But I am going to keep going, so those the webinar can see this. It is just a table that basically depicts exactly what I am going to walk you through at the moment. So, we are going to start with leprosy, perhaps the oldest stigmatized health condition.
Drivers of leprosy stigma include fear of contagion, social exclusion and disfigurement, as well as beliefs that the person with leprosy has sinned or broken taboos. In terms of facilitators, social inequalities really come into play here. So for example, people affected by leprosy often have diminished economic status, low or no education, and low or no awareness of human rights, which really heightens their risk of discrimination.
In southeast Asia, a low-caste background can add an additional intersecting layer of stigma as is the case for women in many endemic countries. The stigma attached to leprosy typically manifests as a spoiled identity in the affected person. Affecting status and reputation of the individual as well as family members. Social participation may be severely restricted, including problems in finding or keeping a job, reduced access to education, or reduced opportunities in finding a marital partner.
Many people would seek to conceal their condition, this concealment causes stress and anxiety, but it may also cause people to delay presenting for diagnosis and treatment. When treatment is delayed, this may increase the severity and disability. Some people may opt to discontinue treatment, rather than risk being found out. At the personal level these outcomes of stigma lead to a number of negative impacts for people living with leprosy, such as reduced quality of life and mental well-being, including things…increased risk of anxiety and depression.
At the organizational level, leprosy related stigma outcomes may include poor quality of health services and increased staff turn over. And at the societal level, the combined impact of these outcomes may be prolonged transmission of the bacilli in the community.
So the next example I'm going to share with you is mental health.
So mental health-related stigma is often grounded in stereotypes that people living with a mental health issue…[inaudible] Okay, there we go… are dangerous, or they are responsible for their mental health issue. That it cannot be controlled, or they cannot recover, and that they should be ashamed. People living with mental health issues are often viewed as incompetent or unable to live independently. Negative attitudes, opinions and intentions persist and are reported across diverse global contexts, regarding having a person with mental health issues, provide child care, teach children, [beep/inaudible] family or hold authority positions. Race and gender appear to intersect with mental health-related stigma influencing its severity. Certain mental health conditions…concerns are perceived as masculine, such as addiction, or anti-social personality disorders, and others as feminine, such as eating disorders. The public stigma towards perceived masculine issues appears to be higher than perceived feminine issues. There are also gender issues in perceived stigma where men may experience elevated stress regarding disclosing mental health issues in comparison with women.
Common manifestations of mental health stigma are anticipated and perceived stigma, which contribute to fear of acknowledging ones mental health issue and can lead to shame and avoidance regarding seeking mental health care. Mental health related stigma also has a profound influence on life opportunities, and persons realizing their goals and potential. It is associated with lower self efficacy and self esteem, and compromised engagement in employment and independent living. Public policy responses in some countries have gone a long way towards reducing the harmful effects of mental health-related stigma at the organizational and institutional level. So for example in the United States, the Americans with Disability Act, which was enacted in 1990, called for preventing discrimination on the basis of mental health, and social inclusion and participation of people living with mental health issues in society.
I just wanted to note that the examples of drivers, facilitators, intersecting stigmas and manifestations reviewed for leprosy and mental health are really intended to be illustrative. Researchers, clinicians, program implementers and policy makers would need to ascertain the most relevant aspects of each of these domains in their contexts, or with the specific population they are working with, to form [beep/inaudible] in support of stigma discrimination research and reduction efforts.
So, in conclusion, we are really at a critical moment when cross disciplinary and cross disease research and collaboration are needed to tackle health-related stigma and its harmful consequences. Our hope is that the health stigma and discrimination framework will facilitate such collaboration. We believe that research and interventions inspired by the common framework will enable the field to identify commonalities and differences in stigma processes across diseases and amplify our collective ability to respond effectively and at scale to this major driver of poor health outcomes globally. So I am just going to end by sharing a few acknowledgements, which are here on the slide, which people in the room can’t see, which are basically just to thank the Fogarty Center, for all your support, Nalini and Arianne, very much appreciated. The William and Flora Hewlett Foundation which supported some of my time to work on the paper, and also of course my co-authors. Thanks very much and I will look forward to your questions after the next presentation. So, thank you.
>> VALERIE EARNSHAW: Okay, a warm thank you to Dr. Stangl. We are having some internet connectivity issues here at NIH. So for the folks in the room, it is TBD whether we are going to see Dr. Pescasolito's slides. But we hope that for those of you that are joining us online, we hope that you will see her slides and you will still be able to hear from her.
So I am going to go ahead and introduce her now. She’s our next speaker. Bernice Pescasolito is the distinguished and Chancellor’s professor of sociology at Indiana University, and founding director of the Indiana Consortium for Mental Health Services Research, and the Indiana University Network Science Institute. Her research focuses on four areas: stigma, health care use, suicide, and social networks. Primarily looking at mental illness, substance abuse, and the role that social and organizational [beep/inaudible] and people’s responses to problems. Trained as a medical sociologist at Yale, her research has been published in sociology, anthropology, public health, [beep/inaudible] journals and has been supported by the NIH, Fogarty, and others. She has served as the vice president of the American Sociological Association, and has received several career, teaching and mentoring awards in sociology and public health. In 2016, she was elected to the National Academy of Medicine.
>> BERNICE PESCASOLITO: Valerie, thank you for the kind introduction, and Anne, thank you for setting the general stage so well. My job today is really to provide a conceptual, methodological and analytic overview or orientation to the idea of intersectionality. So all that Anne talked about, I am going to focus in on this one idea, which is fairly recent in public health.
And it is important -- I am not able to change my slides.
>> OPERATOR: If you’ll say “next slide,” I will advance.
>> BERNICE PESCASOLITO: Okay, all right.
So this is -- the idea of going across silos that Anne mentioned is very important, because the silos here are many. They include disease states, socio demographic categories, disciplines, and countries. So we have a lot of thinking to do in terms of understanding how multiple characteristics OF people, and places matter in terms of how they experience different stigmatized conditions.
And really, the idea underlying intersectionality is the recognition of complexity, or holism of the individual. But too often, they are studied separately. So we talk about statuses in the paper, which include race, ethnicity, or sexual orientation as examples, or conditions, which we think of in the -- with the National Institute of Mental Health as disease states. The idea really goes back to Crenshaw, a classic paper by Crenshaw in 1989, which is a piece in Black feminism in which she asked the question, what does it mean to be both a woman and African-American in the United States, where both of those receive less attention, resources, etc. than the more dominant conditions.
So we want to talk about this, and intersectionality, you can talk about these factors interacting in a way that produces greater risk to the individual, but it can also be -- some of these can be protective factors.
So, for example, in talking about intersectionality’s that aggravate conditions, we can talk about HIV and sexual orientation. We know in the United States that this delayed policy and treatment responses. Or it can mediate the effect, and here, having resources, being in higher social class statuses, or having access to wealth can mediate the effect of the effect of the stigma of certain disease conditions. Now when you look at the literature in this, you have to think about varied terms that have been used. Intersectionality is the term that we chose to use across this series of papers, but you might also see it as layered stigma, multiple stigma, overlapping stigma, double stigma, triple stigma, or even multi-level stigma. So let's do a deeper dive into what this looks like.
Okay. So there are two ways to think about, and again, Anne talked about these differences between public stigma and self stigma, or the perspective of stigmatized individuals. When we talk about public stigma, we’re talking about how others respond to the person, and their prejudicial and discriminatory responses. So for example, when we talk about intersectionality, in a general population study, individuals who responded to a vignette of a pregnant woman with opioid addiction endorsed a lower stigma when the vignette depicted successful treatment. But, this is only true for the women who were described as also being of high socio-economic status.
In another example that shows that we need more research in this area, because things are not always producing the same results. Walkup did a study in which he documented that the inclusion of HIV-positive status in descriptions of individuals did not substantially increase the stigmatization related to mental health issues. When we talk about self-stigma, this is stigma that is internalized by the individuals. It affects their own perceptions and their behaviors. It may not be the condition itself, but behaviors that are included.
So a couple of examples, I think here in terms of the existing research literature; That more severe symptoms of depression have been seen among HIV-positive men who reported increased stigma, due to having sex with men in studies in India. Similarly, among black American women with HIV in Chicago, they found that the awareness of systematic oppression and a desire to join others to enact social change, or what they call "critical consciousness," was associated with a higher likelihood of a CD4 ground greater than 350, and a lower likelihood of actual detectable HIV viral load. But this was only the case when those women perceived racial discrimination was high. So, you can see how complex some of the intersectionality issues become.
So what do we know about intersectional stigma?
[cuts out] ...thank you.
Well, I have tried to give you some examples of some of the research that is out there. But we have -- while the research is still relatively new or sparse, but there have been studies that have documented the effects of not only stigma, but intersectionality on health behaviors, such as disclosure, on health outcomes, such as quality of life and successful treatment, and on healthcare access, and particularly the willingness to go to treatment.
We also see it affecting the kind of coping strategies that individuals use, including whether or not they are willing to disclose and/or whether or not they have a feeling of solidarity with other individuals.
So the concept itself is flexible, but it is ambiguous at this point. But it requires -- the one thing it does have, is it requires the ability to characterize complexity.
And I think we know that this is an increasingly important issue at the forefront of science. And so we have to think about different kinds of categories when we think about intersectional stigma, you know, in terms of the different kinds of stigmas that may be embedded in the public's response, or an individual self stigma. For example, with mental illness, both unpredictability and danger are two that Anne mentioned. In thinking about inter-categorical, we need to, sort of, drill down and do an in-depth exploration into one set of identities. But we also need to do a comparison between different identities. For example: The issue of intersectional stigma has been raised many times and early on in the statistics that show that African-American men are diagnosed with schizophrenia four times more than other groups.
Now, fortunately, I think in this area, we are beyond the notion of one right way to do the research. In fact, we know that some of the strengths of this research to date has come from thinking about it as a multi-method area. We -- there is quantitative data on this, in which, you know, there are scales that have been used. The simplest way to think about it, and some -- I think there has been some movement past this, is to think about intersectionality as additive. And what I mean by that is that, if you find statistically significant effects for mental illness, for example, that somebody says, yes, this person they labelled the situation as a mental illness, and they also give a higher -- they also report higher levels of prejudice for individuals who are African-American, then you have two significant factors. And if you simply add them together, you get a sense of it.
But I think that we will go through a number of analytic strategies in the quantitative frame that will show you how to move past this to more sophisticated ones. With regard to qualitative methods, we have found that this has been very important in understanding some of the drivers and mechanisms underlying stigma.
For example: Individuals with HIV and tuberculosis tend to report greater HIV-related stigma than individuals with only HIV.
now, it turns out that qualitative research has shown that this has little to do with tuberculosis itself. The qualitative data study show that tuberculosis-like symptoms have been interpreted by the public as a marker for a previously concealed HIV diagnosis. So that we need not only the overall nature of the relationships between different concepts in intersectionality, but we need to drill down to understand exactly how this is working.
Okay. So there are a number of ways to think about this. So if you had a number of statuses, or conditions, that you were thinking about, you could -- for each one of those, you could use parallel measures. For example: Social distance scales, developed by Bogartis in 1965 for race issues has been used quite effectively across the different disease states and adapted for those. So you would ask the same questions for each of the stigmatized statuses that is in your intersectional comparison.
You can also look at variation in a single stigma measure by membership in other sub-groups. And so, you have one marked devalued condition, and you would ask, but what if the person was, in this country, or that country, or was a male or a female, or a member of an in-group, or an out-group? You can also do a specific -- have specific measures for each stigma under study. Because it is pretty clear, from the research literature to date, that there are different kinds of underlying, discredited statuses associated with different kinds of stigmatized conditions.
The other thing that you could do is you could use a measure of the specific intersection. So you could look at -- you could explore or construct different kinds of statuses and conditions.
So -- I'm going to walk through a number of analytic strategies that can be used. And one of the ones that is depicted here on the left-hand side of the screen is doing a moderation, and the question here is: Whether or not a second characteristic that is involved in the intersectionality theory that you are looking at moderates or changes the direct effect between stigma and whatever you are interested in, in terms of an outcome variable. Now, to do a moderation completely, one must do a series of analyses, including looking at, in this case, whether or not HIV affects injection drug use, whether or not injection drug use affects the viral load, whether HIV infects the viral load and then a final specification where HIV, whether that, whether that is affected by viral load and injection.
But there's also the possibility of doing mediation, and in this case, the model specification would look at whether or not viral suppression is a function of HIV stigma, plus stigma associated with injection drug use, and whether or not -- and in multiplicative factor that look at HIV times injection drug use. Now this is an important way and a very straightforward way to look at it, but it does come with some limitations. And we know from research that the main effects tend to explain a large proportion of the variance. But more difficultly, work by Christopher Winship on issues of interaction effects -- large, that they are very difficult to interpret, and many people -- or the traps that people fall into, is really misinterpreting them. The other thing is as your intersectionality conceptualization becomes more sophisticated or diverse, it can be -- it can require larger and larger sample sizes. So, if you have a two-way interaction, which would be something like HIV stigma times injection drug use, that will be important. But, as you go to higher order interactions, where you might have three, you’re going to -- you’re going to introduce issues of multi-colinearity, stem cells, and that will question or lead you to consider how robust and how stable your effects are.
One of the things that is one of the more, I think you need to go back one. Thank you. Okay.
One of the most interesting news strategies out there is doing multi-level modeling. And it really is a very sophisticated strategy for answering the question: What works for whom under what conditions?
And so, for example, in the graphic that you see here, the question of what works, having certain state and national policy, may work under certain conditions, which would be local contexts, how normative is it -- how normative is it, or whether or not the overall prevalence of injection drug use is higher or lower. And then, for whom, looking at the different categories of disease statuses and identities.
These may all come together to -- in a complicated way, re-integrate -- effect reintegration into the community. So in this case, you would have nested data. And the strengths of this, is that you can look at how structural influences, or contextual influences, change the effect of different individual-level variables.
But the key reason why we use special models for this is that, having nested data affects the standard deviations of estimates that can change whether or not you are correctly computing the statistical significance of your effects.
And having the ability to talk about something like whether or not state or national policies work, really involved in having an adequate end of what is called -- an adequate end at level two, which is the higher level of state and national policies. So people talk about being able to do this in a substantively meaningful way. With 10 or more cases there are cases in which people have analyzed data in China, using a different – using 100 different communities, that is a really wonderful case. But those data are difficult to collect. But it does provide a really good understanding of how context affects what is going on.
And the other thing you have to think about with these models is whether or not you are assuming fixed effects, which is the effects are the same, for example, of race or ethnicity across countries, or whether or not you want to say that effect differs across countries, and you want to use a random multi-level model.
Latent class analysis is very complicated one in which both the questions of measurement of how you put together your scales, or individual groupings, is combined with understanding the effects of those groupings.
So it considers making the construction of measures and detecting the association among concepts one step. Now, it has -- you also have the problem here of needing large samples, it can be difficult to explain, in other words, one of the things one does in a latent class analysis is, you have to assign error terms, which some people have questions about that. And it may not be right for every question. But, let me -- let me give you an example of how, how useful this can be when you have large sample size, and the question of interest is how the nature of stigma may vary, based on the presence of different combinations of stigmatized behaviors or identities.
So Garnet and colleagues use this approach to identify four patterns of discrimination. That's the part where the model uses the data to come up with the different patterns for scales. And bullying among adolescents based on race, immigration status, weight, and sexual orientation. One subgroup identified was an intersectional class, characterized by high probabilities of bullying, and both weight and race-related discrimination. So you can see that very complicated questions can be asked with latent class analysis, but they also require very complicated specifications and data.
So, thinking about -- thinking about recommendations: One of the things that the paper that my colleagues have done in this paper is to re-think the measures and the research. So thinking about how you use -- as a basis -- what is the basis that you are interested in for anti-stigma efforts?
Second recommendation is: Do you need to tailor? So that, when you do intersectional analyses, you see whether or not the approach that is needed for, say, African-American communities is different than for Asian communities -- or Asian-American communities. Or whether or not men have to be approached differently than women for this. And then the third consideration has to do with the drivers and mechanisms that Anne talked about, some aspects and effects that are similar or different across stigma.
Because -- the reason that we want to consider these things very carefully is because there are many options in terms of anti-stigma reduction programs. They can be one, as in the first box, that are very unique. In the second, there may be common strategies that can affect multiple stigmas. And in the third, there can be special sub-groups that have to be addressed in particular ways.
And the implications of this are important for what policy makers do in terms of thinking about the larger issues of structural stigma.
Whether or not they -- you know -- whether or not funders prioritize intersectional approaches, whether policy makers prioritize strategies that deal with single or multiple stigmas, and whether or not researchers work to break down silos in interdisciplinary teams.
So you can see, from this brief overview, which is dealt with in much more sophisticated detail in the paper, that there are -- the issue of intersectionality really brings into focus not a characteristic of a person, but a person as a whole, and is really part of the forefront of the need for more research in this area.
>> VALERIE EARNSHAW: Okay, thank you so much to Dr. Pescasolito.
So now we have a break for Q&A. We are going to field questions for 10 minutes, according to the agenda, up until 10:50, or maybe a little less, in case we have some more technical difficulties.
So let me open it up. Does anyone have questions.
>> AUDIENCE QUESTION: [inaudible]
>> VALERIE EARNSHAW: So I'm going to repeat that so everyone online can hear us.
So we have a great question from someone online. It is a two-parter: The first is, “do we have a sense of the percentage of a population that doesn't hold stigmatizing views and/or doesn't enact those, that doesn't engage in discriminatory or mistreatment of people living with stigmatized characteristics? And the second part of this question is: Can we learn from these people? What can we learn from these people about stigma reduction?”
>> BERNICE PESCASOLITO: Do you want me to take that?
>> VALERIE EARNSHAW: Sure.
>> BERNICE PESCASOLITO: Okay, I can say a few things about the United States, and also cross-nationally that, in looking at something as simple as social distance, which is the unwillingness to engage with a person across -- a person with a stigmatized condition across a number of venues and a number of different disorders. In the United States, about 50 percent of Americans express some prejudice, or discriminatory potential. We do not have data to show -- on a representative sample of the American population, about whether or not they follow through on that. But there is some classic and contemporary work that shows that people are more willing to express stigma or, as I say, say stupid things, than they are to discriminate, which is to do stupid things. So we think of the cross-national population-based, representative of the country, study, as providing a litmus test for -- you know, the level of stigma in a country. And it varies tremendously across countries, from very low countries with stigmatizing potential, like Iceland, and Germany, to areas where there are very high levels of stigma, and they -- in our study, it was the Philippines, South Korea, and Bangladesh had the highest levels.
So I hope that answers some of your first question.
And I think what that tells us is that we grow up in societies that internalize various feelings of prejudice towards different groups. And it needs to be addressed not only toward people who have mental health problems, for example, or HIV, but there has to be change in the larger culture as well.
>> VALERIE EARNSHAW: Great. I think we had one of the best people in the country to speak about levels of stigma world-wide. So thank you very much, Dr. Pescasolito.
Okay. You want to read it -- [inaudible]
>> UNKNOWN SPEAKER: Hello, there's a second question from Kim. And the question is: “Is there any information on whether there are tipping points that are necessary to reduce stigmatization –a certain percentage in a community not holding stigmatization views or conducting stigmatization?”
>> BERNICE PESCASOLIDO: Well, that's a very interesting question in terms of stigma, and I can't answer that with regard to stigma per se, but I will say, in our research on suicide, that we know that there are -- which is also a stigmatized condition, we know that, if you have a risk factor for suicide, say, divorce, that if you live in a community that had about a 20 percent or higher divorce rate, that your risk actually goes down, because you are surrounded by like others, is what we’re arguing.
So I don't know if there's a tipping point, but I have seen some work out there, new work out there, that suggests that there has to be a tipping point, but the tipping point is about the number of people who self-disclose. And once that gets to a certain point, and I would hypothesize 20 percent, given our suicide data—but that's a hypothesis to be tested—that then other people jump on the bandwagon, because they don't want to be on the wrong side of history.
So I don't know, if Anne has any research that thinks about a national or local tipping point. But if I were to hypothesize 20 percent disclosure rate, and then maybe followed by this, you know, coming on board thing. So it is hard to know.
>> ANNE STANGL: Yes, and this is Anne, I think that's a great question, Kim. I would say, from the global data, if you look at the demographic and health survey data on HIV stigma, and Valerie referenced some of the papers by Alex Tsai in the beginning of her presentation, those will sort of show you, sort of, how reductions in certain types of stigma, like HIV stigma, can happen over time. Now frankly, those are -- we know that these are not great measures of stigma that are in the DHS, but at least they give us a good sense of trends. And you can see now that, with some of those measures that have been asked over the last decade or so, it is getting down to others about some of the very few people, like maybe only 20 percent of people might hold a discriminatory attitude towards a teacher living with HIV in many countries. And so you can kind of track that -- though I will say there is no hard data or studies that I have seen that kind of point to a tipping point, so I think Barbara's guess is probably a good one, and clearly more research is needed there. But you can look -- there's a lot of interesting policy studies that have been done to look, as stigma shifts, and reduces over time. You know we can kind of compare that with what's happening on the ground. How are people living with HIV, for example, experiencing stigma, are they welcomed in their communities, and those sorts of things. And if you look at the HIV epidemic, specifically, you can see that, you know, that 20 years ago, it was much more stigmatizing and the effects of the stigmatizing outcomes were much worse in many ways, much more obvious, and they are becoming less so.
So it is a little tricky, you have to be careful when you are looking at these big sort of indicators, and say it looks like we’re getting to a fairly low proportion of people who are holding these discriminatory attitudes, but stigma can become much more nuanced, so people may not experience it overtly, but they may experience it in other ways, especially in health care facilities and others, where maybe they are asked to be -- so they cannot have children, or maybe they are told that they have to be on birth control in order to get their antiviral medications, there are those kinds of things that you have to be careful because when you are looking at the general trends, it is not always really showing you what is happening on the ground with the stigmatized individuals who are experiencing it. So I would just sort of caution against that sort of thinking, or just approach that type of research carefully.
>> VALERIE EARNSHAW: Thank you for these terrific questions.
Okay, we are going to take one more question before we transition to the next.
>> UNKNOWN SPEAKER: So we have a question from Dan. He says, “I'm curious to hear, if any of the speakers talk about their understanding of intersectional HIV and incarceration stigma, and how it has been or can be addressed?”
>> ARIANNE MALEKZADEH: I will speak a little bit to this, if I may, as our moderator. We are currently doing work in prisons, in Indonesia, where we are looking at, for example, the disclosure concerns of mostly men who have been incarcerated and who are living with HIV. And so when I'm thinking about intersectionality for this particular group, what I'm often thinking about is what are their unique concerns that are shaped by both living with HIV, and by being someone who is incarcerated? And then we can actually add more. We can add these are people who have a history of injection drug use, and people who are struggling with different resource insecurities.
And so when I'm thinking of all of these things together, some really unique experiences that this population is having might be, for example, a lot of worry about HIV is disclosed to their friends and family members, or their relationship partners and that once they leave prison, that they won't be able [beep/inaudible] to these people to help them be re-integrated, and give them a place to live. If, if their HIV status becomes known, they may not have access to resources. In Indonesian prisons, it is up to the family a lot of the time to be bringing in food, medication, and other things. So all of these concerns that folks are having are heightened. So people are still worried about disclosure when they are incarcerated in the same way they may be worried about disclosure if they weren’t incarcerated, but we have this sort of extra -- extra shaping or additional concerns that are then in the mix, because that they are incarcerated.
So I think about how do these different things shape their experiences and make those unique from someone who may not be incarcerated.
>> VALERIE EARNSHAW: Okay, so thank you so much for those terrific questions, and we are now going to transition to our next presenter.
We are very lucky to hear from Dr. Laura Nyblade and Melissa Stockton. Dr. Nyblade is a fellow and senior technical advisor on stigma and discrimination in the Division for Global Health at RTI International. For the past two decades she has built and led a portfolio of research and programmatic work on HIV stigma with a focus on data utilization to support evidence-based programmatic practice and policy at local, national and global levels. Working in close collaboration with civil society and governments across sub-Saharan Africa, south and southeast Asia and the Caribbean, Dr. Nyblade has led the design, roll out and evaluation of evidence-based HIV-stigma reduction programs, the development of programmatic tools to engage multiple audiences, and the development and validation of stigma measures. Currently she is leading work focused on reducing stigma in health facilities and working to apply lessons learned from HIV stigma to other conditions. in particular opioid use disorder and cancer. Dr. Nyblade is joined this morning by Melissa Stockton, a doctoral candidate in the Department of Epidemiology at the University of North Carolina at Chapel Hill. Her doctoral research evaluates a program integrating depression screening and management into HIV care in Malawi. Prior to enrolling at UNC, she worked for RTI International where she supported various studies on stigma and discrimination, sexual and reproductive health, and vulnerable populations in Sub Saharan Africa, southeast Asia, and the Caribbean.
LAURA NYBLADE: Thank you, thank you and good morning, good afternoon, to everybody. I hope or I imagine that we have some people who are in the afternoon or evening already somewhere in the world. It is an honor to be here today, and I would like to add my thanks to Fogarty for all of their work and support around this, and also to Greg, who has been a big part of this sort of advancing this work on stigma.
I will be presenting with Melissa, who is co-first author on this paper and, as you will see, we have quite a cast of characters as co-authors. And we bring to the table this group of authors, a lot of practical experience on reducing stigma in health facilities around the globe. And so we are shifting gears a little bit here from the work that we’ve just heard presented which are these great frameworks and thinking around intersectionality, to really getting down to the nitty gritty about how do you actually reduce stigma in a specific setting?
And our focus is on health facilities, not to the exclusion of other areas, because we know, as we saw from Anne's framework, that stigma occurs in multiple spheres of our lives. But, because health facilities -- could I have the next slide, please? I understand it is being advanced online by someone. No? Okay. I will try. Here we go.
The focus on health facilities, because if you think about it, when you are at your most vulnerable, when you need care and you go into a health facility, and you experience stigma or discrimination at that point, that is pretty egregious. And it is our entry point into care and health going forward. So health facilities, along with other spheres of our life, are really important. But I think it is a really good starting point. I work a lot with governments, ministries of health, programs and often times, when you start talking about how, how do you reduce stigma, eyes glaze over, because there is a sense that it is really too large and too complicated to actually be able to do anything concrete. And we know from our research over the past 20 years that that's not the case. We can actually do this. And I think as our introduction today said, it is malleable. It is something that we can address. And health facilities are a really good place to start and to move forward. So, what we do know already globally is that it is something that is pervasive. We have a lot of studies across the globe that show how it is manifesting in facilities, in very different contexts, including here in the U.S., from denial of care, to verbal abuse and, for example, unauthorized disclosure of someone’s status to someone who has no right to know. We know that it is perpetrated by both clinical and non-clinical health facilities staff. And I just want to dwell a moment on that and you’ll see this come back. But in the interventions, as we are learning over the -- we have been learning, is it is really important to work with and address stigma from all staff in health facilities who come into contact with clients, not just those who are presenting -- delivering clinical services.
And as we know, it undermines certain health outcomes which we’ve heard about already. I think what really drives this whole collection, but also our specific work when we are sort of drilling down now into health care facilities, is really the potential for thinking about interventions that might be able to simultaneously reduce stigma related to more than one health condition. As we have heard already this morning, we have been working in silos for a long time. We also know, at least I do from sitting in the programmatic world, I straddled the programmatic/research world, is that there's not a lot of funding around for reducing stigma, whether it’s in HIV or any other area. So as a collective community that is working on this, we need to get smart about how to work and how we can think about potential efficiencies for stigma reduction across these conditions in others that are stigmatized. And we think this is possible because we see, and I will show a slide shortly, that there are common drivers, manifestations, and consequences. So you see that from the framework that Anne presented. You know this is, there are a lot of common things across different disease conditions. We also know that there's a lot of co-morbidity of stigmatized diseases. So this would speak to the fact that we should be able to have responses that work on those stigmatized diseases together. And as we’ve heard, they are often intersectional. So there's a need for this kind of combined response. Despite all of this, stigma reduction in health facilities is rarely a routine part of how services are delivered, or training of health workers. So we have all of this kind of impetus, but yet we’re not actually doing that much about it. So we really wanted to sort of drill down and look at what exactly are we doing in health facilities, and how do we do it? So, I often hear from people when I'm working in countries, well, we don't actually know how to do stigma reduction. We don’t – can’t grasp it. So this was really an effort to look at, what do we know, is it common across different conditions, etc.
Next slide, please. [cuts off] I can do it? Okay. There we go. Okay, So, I can do my own slides.
So this is just sort of drilling down and simplifying a bit, a piece perhaps of the framework that you have already seen. But, as we are thinking about what we are doing in health facilities, specifically, we are working to improve health outcomes, and we know that we do that through multiple pathways: Prevention, testing -- which could be part of testing and diagnosis -- linkage to care, adherence, helping people maintain healthier lives. We also know that stigma undermines each of those pieces. And where I would like to focus you on, and this is a graphic that, on the very left-hand side, has something called immediately actionable drivers. And we use this term specifically in the programmatic world because what we understand, or what we see when we work, particularly with ministries of health and people who are trying to scale up programs, is that there's a sense that it is too big. And so we need to find things that can be grasped now, that we can -- the levers we can push now, that we can, as individuals in health facilities, or ministries of health, can see that we can move, while we are working towards that larger social change that we all want, right, those human rights that we talked about.
And so where we focus on in programmatic work, at least in the world that I work in is [beep/inaudible] and there's a lot of research that has shown that these are things that drive and already have these in the framework. And one is fear of transmission, and this could be the transmission of the condition, it could be fear of the person, or the behaviors, or the assumed behaviors of the person. So it is really important to understand those and address them with health workers. Awareness of stigma, we all stigmatize, it is often times simply because we aren’t aware we are doing it. So something as simple as making concrete and helping people understand, when I say this, when I do that, I'm stigmatizing. Our attitudes, we talked a lot about measurement of attitudes. We often get a little bit of push back on this, well, I deliver [beep/inaudible] it won't influence how I deliver services. But it is a process of sort of discussing, is that really true? We all often have unconscious bias and moving that forward.
And then lastly, that health facility environment. So if you think back to the framework, this is taken down to a much, sort of more granular level. But what is going on in the way the facility is governed, what are the policies, are they implemented, do staff have the supplies they need to actually protect themselves from infection in the workplace? So thinking about this as a sort of lower level framework or more granular framework to thinking about how we actually intervene.
So, with that as a background, and wanting to really understand well, how are, how are we actually addressing stigma in health facilities across multiple conditions? So we embarked on a systematic review, following the PRISMA Guidelines, I won’t go through that. We’ve focused on seven health conditions: HIV, tuberculosis, mental illness, substance abuse, diabetes, leprosy, and cancer. And why these particular ones that we sort of looked at was because they all have common drivers. So this is a very busy slide, but all I wanted you to focus on is the fact that there's a lot of Xs across a lot of these things.
So, a lot of these conditions have very similar drivers of the stigma that is surrounding them, particularly and including in health care facilities. So this is why we focused on these seven for the systematic review.
The inclusion criteria, where we were looking for a clear description of the stigma reduction intervention and how it is implemented. So we wanted to understand what were they actually doing, and you will be surprised how many articles out there that report on studies that don't tell you how they actually did it.
So, that would be one of my recommendations, is that we really focus on actually sharing from our research how we actually achieved those outcomes. Because often times, we are focused on the results and not actually on the process. And when you work in the programmatic world, it is very frustrating when you can’t actually understand what someone did to arrive at that outcome and how you could replicate it.
We looked at an evaluation, whether they had an evaluation of that intervention. It was kind of a mini-review, so we restricted to the past five years, in English. We excluded reviews, or articles, that only describe the intervention development, because we were trying to see what was going on. So we examined again what health conditions stigma was addressed, so we can see if it is one of the 7, what target populations they were looking at. So for example, did they include both clinical and non-clinical staff? The approaches and methods they used -- we will talk a bit more about that -- what kind of stigma drivers were targeted, and then the evaluation methods and the quality of the study. And from that, we really assessed, you know, what is common across conditions, reducing stigma for certain conditions, the gaps we were finding in the literature, and then thinking about the potential synergies for responding to multiple stigmas in facilities. So with that, I'm going to hand over to Melissa. Melissa, I don't know if you can advance slides or not.
>> MELISSA STOCKTON: Thanks, Laura. I think I can keep it going.
>> LAURA NYBLADE: Okay.
>> MELISSA STOCKTON: I'm getting a bit of feedback, if you can mute -- All right. So to go into a bit of the meaty details of what we actually found. Basically here, we started with a total of 728 peer-reviewed abstracts and 43 grey literature records, and we managed to whittle that down into 47 manuscripts, detailing 42 distinct interventions that were included in our literature review.
Some of the key findings, of these 42 distinct interventions that met the inclusion criteria all focused on either HIV, mental illness, or substance abuse. No articles were found that looked at stigma reduction in health facilities for TB, diabetes, cancer or leprosy. The only interventions we found that addressed stigma related to more than one medical condition were those that focused on both on mental illness and substance abuse. As Laura mentioned, we looked at the quality of the interventions, using the Black and Downs checklist, and Spencer’s framework, using a similar scoring system to the one that was used in Anne's Stangl’s review of HIV stigma reduction interventions several years ago. And of the interventions we included, they targeted health care providers, health care students, clients, and patients and then one looked at all level of health care facility worker.
This next slide shows a map of the globe that details where these interventions were implemented. Interventions were implemented across the entire globe, with at least one intervention in every WHO region. The largest number were implemented in the Americas, eight in the U.S., and one in Puerto Rico, and eight in Canada, but none were implemented in South or Central America. Only one was implemented in the eastern Mediterranean region, and most interventions were implemented in high income countries, and of those, nearly all focused on mental illness.
The following six stigma reduction approaches were used, including provision of information, skill building activities, participatory learning approaches, contact strategies, empowerment of clients, and structural or policy changes, and here we have some definitions for those various approaches. So for example, like a contact strategy would involve members of the stigmatized group in the delivery of the intervention to develop empathy, reduce resistance and break down stereotypes.
And here we have a table which shows which approaches were used by health conditions. Nearly every intervention took multiple approaches to reduce stigma, except for two purely structural integration interventions. The most frequently used approach was contact with the stigmatized group, but this was closely followed by provision of information and participatory learning. We tried to look at whether there were patterns across geographic region or by low or high income countries, or how these interventions were combined. But we really didn’t find any discernable pattern.
In line with the programmatic aims of this literature review, we wanted to show how the specific methods -- which specific methods were used to actually implement these various approaches.
For example, in information-based approach might provide educational materials, or lectures, performances, testimonials, learning activities, or clinic rotations to teach or provide information to facility staff about a specific health condition or the stigma associated with it. As interventions often used multiple approaches, they also often used multiple methods to implement these approaches. While we really didn't identify any discernable patterns, again, seemingly when interventions used more passive activities, such as watching a performance or lecture, they paired this with a more participatory activity, such as engaging in a discussion.
Let’s go back a slide there.
So a few articles explicitly identified the driver that their intervention targeted, and in the cases where the stigma drivers were not explicitly described, we tried to infer that from the description of the intervention and found that drivers targeted included attitudes, knowledge of stigma, knowledge of the condition, fear, ability to clinically manage the condition, coping mechanisms for clients, and institutional policies.
And nearly 30 interventions targeted more than one driver; the most commonly targeted was knowledge about the condition.
Finally, we identified a handful of gaps in the literature, including an absence of interventions for TB, diabetes, leprosy, or cancer. Addressing more than one health condition stigma, and targeting all levels of clinical or non-clinical health facility staff, interventions that addressed multiple socio-ecological levels simultaneously, those that worked to structurally change physical or policy aspects of the facility environment, a few that engaged health facility staff and clients in a collaborative effort, a few that used technology for interactive learning, and a few that recognized and addressed stigma experienced by health care workers themselves. These gaps will need to be prioritized in moving the field of stigma reduction in health facilities forward. But luckily there are some ongoing interventions that address some of these gaps that Laura is going to talk about now.
>> LAURA NYBLADE: Thanks, Melissa. So, we thought we should just share two examples of some of the ongoing work that we were able to identify, and -- and when we identified these gaps, we were curious what’s out there that is going on that maybe is not yet published or is current that might be addressing some of these gaps. So I thought, I just picked two, we have several in the paper itself, but I picked two to share with you because they cover several of these gaps, but also -- they also address several of the things that seem to be important in having successful stigma reduction. So we will start by talking about -- and again there is more detail around this and there are also papers that are coming out fairly shortly on some of these interventions.
So this is an intervention that is being carried out in Canada and Peru, and it addresses two stigmas: mental health and substance use. And what I wanted to highlight around this particular intervention is that it is addressing all levels of health facility staff who interact with clients, so it is not just clinical. It brings together clients and health workers together in terms of developing and implementing -- the intervention, and it is also working at multiple levels, it works at the individual level and it is also looking at the structural level within the health facility. So sort of just to give you an example of how an intervention can kind of bring some of these pieces together but is also responding to some of the gaps we identified in the review.
And the second one I want to highlight comes from Thailand, and there's a couple reasons I want to highlight this one. They call it their 3 by 4 approach to HIV stigma-free facilities. And what they are doing is they are targeting -- their three is the three levels that they are targeting within, which is the individual health worker, the systems, so looking at what is going on institutionally in their policies, and then that linkage with the community. So they have these three levels that they are very focused on and within that they are targeting those four actionable drivers I talked about. So really thinking about what is it that we can get a handle on and really move at this point. And, what is really interesting about this is how Thailand, as a country -- so this is work being done by the ministry of health -- has taken global measurement tools and global intervention tools, adopted them to the Thai context quite easily and are actually working to scale this it up. So this is not a research study, this is not donor-funded something, this is actually something that the government, the ministry of health has recognized that addressing stigma is critical to their HIV response. And so they’ve piloted it, they’ve adapted they’ve piloted it and now they are actually scaling up. And, again, they are sort of pushing some of these levers, or these gaps we’ve talked about. They are working with all levels of health facility staff. They are using data very strategically, so what we’re finding in a lot of the work is that having data on stigma and health facilities is a critical piece, a beginning, to actually catalyze action. Because it is very easy to say there is no health, there is no stigma in my health facility, it is the one down the road. And we’re finding that having that data and being able to bring it back to health facilities, and have health facilities themselves analyze that data, then helps develops context-specific interventions that also that are very responsive to the needs.
So just to -- I wanted to highlight that, so this is what we found in terms of the how, the practicalities, that it is being done. There are some clear gaps that then point to where we might need to think about for research going forward. But then also to focus on the, we can do something about this, and there are good examples out there. So just to end, in addition to those gaps that we already identified, to say that the opportunities and sort of where we recommend future priorities, is really in keen, as you saw, we had very few studies identified, or programs identified, that worked on more than one condition -- one stigma. And so that's a really big gap, and I think sort of resonates with what we have been talking about through this collection. So really thinking about how do we do joint stigma reduction across conditions. And how do we create those economies of scale. As we said earlier, I sit in the programmatic world, I'm a bit of an advocate, and we struggle with resources to actually scale up in stigma reduction, not just in health facilities, but elsewhere, and so how can we get smart about how we respond to stigma in health facilities and elsewhere. We know there are common drivers, manifestations and consequences. We have a lot of comorbidities in intersectionality, and now we see, at least in health facilities, there's a lot of common approaches and methods, so how could we meld those and tweak those to be able to respond to more than one at a time.
We think -- as we saw, we saw that there was good quality, but we also saw that a lot of the -- that we need more evaluation to really understand what is going on. Part of the challenge sort of looking at things was we don't have standardized measures to facilitate comparisons so thinking about that between approaches and methods. The other point, again, as we -- particularly as we look for several of the conditions, for example, like HIV and TB, we have global targets for elimination. What do we need to do to scale up and routinize stigma reduction in health facilities or elsewhere. If we don’t make it part of how we do business, how we deliver services, I wager that we probably will never hit our targets.
And the last thing that we noticed is, we didn’t actually, we should have put that as a gap, is we have very little on costs. So a lot of the questions I get from ministries of health, for example, is what is this going to cost, or from donors. And we also, because we don't have costs, we also have no cost effectiveness data. So if we are thinking about where we move forward, I would make a plea for interventions to also do costing and be able to share that alongside.
So, with that, I will end. [applause].
>> VALERIE EARNSHAW: Terrific, thank you for a great presentation. Our next and final [beep/inaudible] is Dr. Deepa Rao, who is a clinical psychologist and associate professor, jointly appointed in the Department of Global Health and Department of Psychiatry and Behavioral Sciences at the University of Washington-Seattle. She has worked primarily in the U.S., India, and east and southern Africa, examining psycho-social distress in integrated care models that would fit diverse contexts. Domestically, Dr. Rao is the PI of an RO1 study of a stigma reduction intervention geared towards improving engagement to care for African-American women living with HIV. She also recently completed work to e pilot test a depression and stigma reduction intervention for African immigrants living with HIV in Seattle. Outside of the U.S., she is the PI of a project that aims to scale up an integrated care model of mental health to help engage people with HIV in care in South Africa. Dr. Rao currently serves as the Associate Director at the University of Washington Center for AIDS Research Behavioral Science core.
>> DEEPA RAO: Okay. Thank you for that introduction. And, can you hear me?
>> VALERIE EARNSHAW: Yes, we can hear you.
>> DEEPA RAO: Okay. And I will go ahead and start. I heard something about technical difficulties, so hopefully that won’t be the case here.
Hello from the west coast. A little early here, and thank you very much for inviting me to be here and talk about such a unique study that we conducted, which was a systematic review of multi-level stigma reduction interventions. The work I'm about to discuss would not have been possible without the close collaboration, time and lots of effort of a few people: Ahmed Elshafei, Minh Nguyen, Mark Hatzenbuehler, Sarah Frey, and Vivian Go. I thank them so much for such an interesting process of conducting this review, and I also thank the Fogarty International Center for making this all possible. So, thank you very much.
So I will start by just kind of talking a little bit about multi-level interventions and the concept of something being multi-level. Researchers have long recognized that stigma has inherently – it’s a multi-level phenomenon. We theorized that because it’s a multi-level phenomenon, working on various levels I will go through in a minute, stigma reduction interventions that are operating on multiple levels can be farther reaching, more synergistic, and more holistic than just simple, single-level interventions.
Okay. What do we mean by multi-levels, when we embarked upon this review? We found two papers that outlined multiple levels that stigma operated on. First there was Heijinders and Van Der Meij in 2006, who reviewed and laid out five levels where stigma operates. The intra-personal level, where the focus of an intervention is on characteristics within individuals living with a stigmatized condition. Then they outlined an interpersonal level, where interventions are focused on the enhancement of care and support in the stigmatized person's local environment, like improving family relations, for example. And they also put forward a community level, and we've heard a little bit about this and some of the prior talks, where the focus is on reducing stigmatizing attitudes and behaviors of non-stigmatized community groups. And then there is the organizational and institutional level, where interventions focus on reducing stigma in an organization or institution.
So, for example, interventions that target standard operating procedures. Then, lastly, there was the governmental or structural level, where interventions focus on establishing and enforcing legal, policy, or rights-based structures.
So their paper, Heijinders and Van Der Meij, outlined certain strategies to reduce stigma on these levels, but the strategies were specific to each level. So for example, policy interventions could only work on the government or structural level.
And in the second paper that we leaned on for definitions of multiple levels was Cook and colleagues, who in 2014 laid out three levels where stigma operates. However, they were more flexible about noting that strategies for stigma reduction on these levels could operate on multiple levels at the same time. So for example, an educational intervention can target an intrapersonal and an interpersonal level at once. So we ultimately structured our review to examine five levels, outlined by Heijinders and Van Der Meij, and then having the flexibility of Cook and colleagues, where strategies to address stigma at each level could operate on multiple levels. So for example, if one target of an intervention was to reduce stigma or improve an attitude within a person, where by stigmatized or non-stigmatized -- whether they were stigmatized or non-stigmatized, we categorize this as intrapersonal level interventions.
If an interventions target was to improve interactions between people with stigmatized conditions, or other stakeholders, like caregivers, healthcare workers, etc., we characterize this as operating on the interpersonal level.
And if a non-stigmatized public was targeted, we identify the community level as the focus of the intervention. If an organization was targeted, we identified this as an organizational institutional level. And if a policy or administrative structure was targeted, we identified this intervention as operating on a governmental or structural level.
So what type of review did we do? Similar to the study that Laura and Melissa just presented, we also conducted a PRISMA review and followed PRISMA guidelines. Our review was systematic, and we followed -- and we used their checklist to guide our process.
So we used search terms outlined here, we used the term “stigma” and paired it with one of the following terms: intervention, programs—spelled both the American and British ways, and we used the term policies, or we used the term policies to pair with stigma in our search of the literature. We also used covidence to organize our information—the Covidence database program, that is.
So for our inclusion criteria, we required the articles to be peer-reviewed, use original research, and were published prior to the initiation of our search in November of 2017. So we have been working on this for a bit of time. We evaluated interventions that were operating on more than one level, as I mentioned and defined before. There's a bit of a typo in the slide. It should say operating on more than one level. So those levels were the five that I presented, and we used that hybrid manner, joining the two definitive studies that I described before. And we also examined stigma, only papers that have stigma as an outcome.
And then for exclusion criteria, we excluded all protocol papers, all papers that were not in English language, abstracts that didn’t have full text availability, non peer-reviewed articles, and solely qualitative articles. So we did look at the few mixed method studies that were available. In terms of our data extraction, after removing duplicates, we ended up with a list of 10,621 articles. So it was a quite a feat to kind of dig through all of these articles. And we have two investigators who independently conducted a screening process based on inclusion and exclusion criteria. They first, in the first step, screened based on title and abstract. And then, in a second stage, performed a full text screening. And after these first two stages were conducted, they -- we calculated that they had 99 percent agreement in the articles that they chose to include. We had a third stage of two long meetings where discrepancies were resolved between these two investigators, with two additional investigators. And from these discussion, we retained 138 articles that went through further screening and discussion. Ultimately, we ended up with 24 articles after this full text screening. And the 24 articles all described intervention studies that targeted at least two levels, defined earlier.
So after this, we independently conducted a content analysis. Two investigators coded each of the 24 articles for the following themes. We looked at country where the study was conducted, the condition or population studied, for example, HIV, mental health, substance use, leprosy, diabetes, epilepsy, or orphaned and vulnerable children. So those were the main categories that -- where we found population studies. We also coded for intervention targets. So, who were the populations that were targeted? People living with a certain condition, health care workers, caregivers, or family members, community members. We looked at stigma reduction strategy. So, thank you, Laura, for outlining some of these strategies. But we looked at strategies, like education, context, social marketing, counseling space and problem-solving. And then we coded for the level evaluated, using the definitions I presented just now. We looked at the stigma measures that were used, and also effectiveness of the intervention, Which we simply coded by terms of statistical significance, or non-significance. And we -- you know, since these interventions were operating on multiple levels, we wanted to make sure that if we coded for statistical significance, it was statistical significance on at least one level that was targeted.
So in the actual paper, we actually had listed in table one the 24 articles that we coded, and all of the information from these different codes are presented there. But it was too much information, too busy a slide, for me to present here. But I would refer you to take a look at the table, it is very interesting to see how large some of the studies were, and how small some of the studies were, that we analyzed.
What we found, overall, was that equal numbers of studies, originating from low-and middle-income countries and high income country settings, were within those 24, were 13 studies were conducted in high-income countries, and 11 in low- or middle-income countries settings. So five of the studies were based within the United States, three in the U.K., two in Canada, and two in Indonesia and two in South Africa. We had one study that we analyzed that actually covered five African countries, Lesuto, Malawi, South Africa, Swaziland and Tanzania. We had another study that was conducted in each of the following countries, so one study from Kenya, one from Zambia, China, India, Vietnam, Israel, Haiti, Australia, and Japan.
So the majority of the studies that we reviewed and identified were published after 2010, which to us demonstrating an increasing urgency and movement in the research community towards stigma reduction intervention. In terms of randomization, relatively few studies used randomized control trial design, only six of the 24, and most of the studies were pilot trials of interventions. In terms of the conditions that were studies, as we’ve been mentioning, even with the multi-level studies that we reviewed, the articles that originated for high or low-income countries tended to focus on either mental illness related stigma or HIV related stigma.
Interestingly, in the high income countries, those tended to examine mental illness related stigma, but in the low and middle income countries, those studies tended to focus on HIV-related stigma. And this may be due to the availability of funds, as global health spending in low and middle income countries has decreased over time, with the exception of HIV-related work.
In terms of intervention targets, 18 of the studies examined stigmatized participants -- so people living with stigmatized conditions, 12 focused on community members, six on healthcare workers, 8 of the studies examined caregiver attitudes, and two youths at risk for HIV.
In terms of the strategies used, this was the interesting part, for us at least. The most common stigma reduction strategy studied was education, with 16 studies using this strategy. And then 10 of the studies examined contact, five counseling or coping skills acquisition, three focused on social support, three others, drama, and two of the studies listed problem-solving skills. So as seen on the previous slide, and I am just going to go back to that for a second, the intra and interpersonal levels were most often targeted by the multi-level stigma reductions that we studied. Whether the studies were conducted in a high or low middle income country. So notably, approximately half of the studies reviewed examined community stigma reduction with intrapersonal or interpersonal levels included as the multiple level. So we theorized that this might have been because of convenience of samples where one can target communities, or people living with certain conditions.
And also, the fact that more measures are validated for these populations, whereas it is more difficult to find measures of stigma reduction at organization and governmental levels.
So -- and then -- you know -- speaking of the measures, let me just advance this slide, most investigators that -- of the studies that we reviewed used validated measures. Or when working in a non-western setting, adapted measures of stigma for their studies.
However, they provided little information on how well the measures performed in diverse settings. So in terms of effectiveness, this is where we get the drum roll, it is very interesting information, 17 of the studies reported that their intervention reduced stigma.
And we looked at key values and also confidence intervals to determine this, and at least seven of the studies reported non-significant results.
So the interesting thing was that there were so few of the studies, only two, that provided information to calculate confidence intervals, and only 11 out of the 24 studies provided information where we could calculate effect sizes or provided effect sizes themselves. So this for us was a call for investigators to include more information to help us calculate effect sizes for systematic reviews. So overall, we noted, as I mentioned, an increasing urgency for researchers to study stigma reduction interventions, and we saw and noted a reduction in non-HIV global stigma reduction research. We also noted that more research was needed at the community, organizational and structural levels and results show that more research is needed across a wider range of strategies, beyond educational interventions. So as Corrigan and Collins wrote back as far, in 2002, over years of researching mental illness related stigma, standalone educational programs can lead to stereotype suppression. So this is where members of the public suppress rather than reject stereotype beliefs upon learning when such beliefs are undesirable.
So, in addition, more research is needed with people living with conditions beyond mental illness, because strategies across these conditions may differ and need to be evaluated.
We also have noted that more RCTs are needed that test rigorous methods and measurement approaches, that move beyond the pilot stages of intervention work. And multi-level intervention and equal engagement, and key areas of intervention science for example implementation science. And we note that there is a paper in the series, examining research in the context of implementation science.
And then finally, we left the research community with a few key questions for future research to examine multi-level interventions. For example, we wondered how do multi-level stigma reduction interventions compare in efficacy to single-level interventions? What are the mechanisms of change across all levels? How effective are multi-level interventions translated or disseminated? What interpersonal community and structural factors promote or undermine their dissemination?
So ultimately, our review led to more questions perhaps than more answers. But it was a very interesting body of work to embark upon. So, thank you for giving us this opportunity.
>> VALERIE EARNSHAW: Thank you, Dr. Rao. And what a nice transition slide into the final Q&A of the morning. So I will remind the folks who are listening that you can type in questions, and we are keeping an eye on those and we will read them aloud. We do have one question to kick things off, which is that, “Stigma research has predominantly focused on mental health and HIV AIDS, what are some under-researched areas especially in the global scale and what can we do to bring attention to these areas? “
>> UNKNOWN SPEAKER: Well, I can kick off. I'm sure Deepa has some comments as well. I think, as Valerie mentioned, cancer is one, and I have been doing some work on cancer in India, and was very struck by how many of the drivers were very similar, including fear that cancer is transmissible in ways that it is not, which we see very commonly around HIV. So I think cancer is a big area. We know that there's a growing burden of NCDs globally, but also particularly in low- and middle-income countries. So I think cancer, we will be watching what happens with obesity and in diabetes in these countries. I think in the cancer realm, lung cancer, because of the link to smoking is an area where that there is some work, but not a lot. We didn't find anything very example, around in health facilities around that.
And obviously, at least in the U.S., opioid use disorder and substance abuse. There has been some work on substance abuse in the health facilities, and that was the one sort of area where we saw some overlap with mental health, mental illness, and substance use.
So I think those are areas -- there are also potentially emerging areas. I had someone tell me yesterday that, in Italy, Lyme's disease is stigmatized, which had me very surprised. And I asked why, and he said, well because if you have Lyme's disease, you’ve had a tick on you and you are dirty. And so I was like, I was a little startled by that. So I think there’s, there’s some emerging, the people don’t want that diagnosis, and they don't go for treatment, he said. So, I think there’s areas like that. In terms of drawing attention, I think we all need to be speaking out.
I think this, this collection is very important for kicking off that platform as an advocate for the past 20 years, for stigma reduction, I think we all often sit in our research silos, but we don’t advocate enough for the actual importance of doing this kind of work. So, sorry, I'm getting on my soap box again.
>> UNKNOWN SPEAKER: Oh, I was just going to add to that. You know, my team here has done a little bit of work in cancer-related stigma, particularly women's cancers in Uganda. We have a paper of a qualitative exploratory study that we did among breast cancer survivors that was published in Psycho-oncology a few years ago, and ultimately what kept us from going the next step is actually funding. I mean, and, and that’s at least that’s what our theory was at the end of our paper was that what’s driving research in certain areas is funding. So if you’re funded, you know by PEPFAR it’s relatively easy to implement a stigma measure and evaluate whether or not you know any intervention is having impact on stigma but to kind of move into different areas other than those that have been traditionally funded is, is tough. So I guess I would, I would push for, you know availability of more funds to study stigma associated with other conditions because there is so little that we know about interventions in these areas.
>> UNKNOWN SPEAKER: I just want to add another under-researched area but a very important, critical one in lots of conditions is adolescents who are seeking sexual and reproductive health services. There’s a lot of, a lot of stigma around adolescents both from communities and particularly in the healthcare facilities when they are seeking these types of services. So that’s an important area and I think in terms of, of the point that Deepa made, and how do we, I think that just sort of calls again for thinking about how can we address multiple stigmas when we want to make the best use of our resources. And so we are seeing in a lot of the work we are doing that if we’re able to address HIV alongside sexual and reproductive health stigma around adolescents as well as stigma towards key populations, collectively within one intervention.
>> VALERIE EARNSHAW: Thank you. Okay, so our next question is in terms of interventions for healthcare workers in clinical settings, what are the strategies to motivate and empower the healthcare workers in engaging in the efforts of stigma reduction?
>> LAURA NYBLADE: Melissa, do you want to answer that or do you want me to do that? I don’t want to take all the…
So what we are finding, with respect to health workers, at least in the work that we’ve been doing in Ghana, Tanzania, and Thailand, is the importance of empowerment of health care workers at all levels, ensuring that the ownership of the response is coming from the health facilities staff themselves, and particularly getting management on board. And so in terms of motivation, that piece of, and we found that it starts by the data collection and actually having staff and management themselves to analyze the data, and think about what are the responses that they can bring to bear within often the very resource constrained settings, things that are functional or practical, and you would be surprised to see what people come up with. It is very heartening to see what health facilities staff themselves come up with in terms of what they can do within their constraints and within these systems that already exist within health facilities, which I think is key. A big piece of what we are finding, too, is ensuring that staff actually have the understanding and knowledge they need. It has been surprising, I guess, maybe surprising, not surprising to us, around, particularly around HIV how much fear of HIV transmission in the workplace still exists, and misconceptions and myths around how HIV is transmitted and not transmitted. Which drive very often [beep/inaudible] behaviors in health facilities like [beep/inaudible] actual, you know the chart, the marking of charts that Anne mentioned and so often what we see with health workers is not that they intend to stigmatize it’s simply that they are not aware that they are doing it. And so creating the safe space for staff to understand what stigma is and to think through some solutions themselves and what we’re finding is the fact that they think about what can I do as an individual health worker but also what do we need to do collectively. And what we have seen in these three countries is that there is actually a set of health workers within these facilities that emerge kind of spontaneously as champions, once they have the knowledge [beep/inaudible], and in working with management being able to empower them to actually take things forward. And they really do influence the rest of their staff. Now, so I think -- I think that is --
>> DEEPA RAO: I had a, actually this is Deepa. Go ahead.
>> MELISSA STOCKTON: Nope, go ahead, go ahead.
>> DEEPA RAO: No, no, you go ahead, Melissa. I can just wait.
>> MELISSA STOCKTON: I guess the only thing I would add to what Laura is saying, like, outside of the realm of HIV is that I think, what came through especially in our literature review, is that there's a want to better understand how to clinically manage the disease as well, and I think like that is an important aspect of intervention as well, that maybe is kind of overlooked. But otherwise I think Laura hit all the points that I would have said.
>> Go ahead, Deepa.
>> Oh, sorry, I sort of figured that you were about to say something. But I was just going to speak to some emerging work that is out there that is actually quite interesting. It probably wasn't captured in any of our reviews, because the protocol paper was, is out, but not the kind of follow-up of this work. But we’ve also encountered in our work in Kenya, in particular, that, you know, when we use capture interventions or capture approaches to address common mental illnesses in primary care settings and things like that, there are a lot of health care workers that don't want to take on tasks of counseling for mental health issues, because of stigma. And it is interesting because Brandon Court and his team in Nepal is actually engaging in their intervention called re-shape.
And they’re, they’re pairing photo voice integration with integrated care models, particularly through the prime consortium. So work ongoing in Nepal and Ethiopia, where they are taking a health care worker who ultimately may be applying counseling techniques to their work, or even just assessing mental illness, with a person with severe mental illness. And they work together on building a photo voice collage of the person with mental illness’ life, their life story. So the person with mental illness is trained, you know given a camera and takes photographs of their life, and then you know in working on this story with the health care worker, you know, in that context that is involved, stigma is reduced. And this is, this is an intervention that is an adjunct to a whole model of integrated mental health care, in primary care settings. And it’s fascinating that they presented some preliminary results of the NIMH Gold Mental Health Conference last month.
And I think we are about to see some really interesting work emerge from that body. So I just wanted to put a plug in that there are really interesting kind of emerging approaches to reducing, you know, mental illness-related stigma at the healthcare worker level as well.
>> UNKNOWN SPEAKER: And just one more thing to add on how do you motivate health care workers. One of the issues is really sort of a lot of health care workers, we don't recognize that they themselves are experiencing stigma, or are fearful of stigma. And a lot of our interventions, as you will see from the review, don't actually measure or look at what's happening around the health workers themselves. And what we find in our interventions is, is that, you know, when we approach this, it is not just about improving things for clients, but also improving things for staff.
And one of the things that we've done in our interventions is actually -- in our participatory training, is mixed levels of staff, because there is also stigma within hierarchies in health facilities. And so starting to break down those kinds of stigmas within staff can also be very motivating for staff themselves. And we found through these interventions, for example in Tanzania, we actually had a doctor disclose that he is living with HIV in his facility for the first time. So staff were starting to see that if you reduce stigma overall, you’re also improving things for staff themselves.
>> VALERIE EARNSHAW: Well, thank you for these excellent questions, and very thoughtful answers. We are now going to transition over to Gregory Greenwood, who is going to offer up some concluding thoughts.
>> GREGORY GREENWOOD: Alright, thanks so very much, Valerie. And if -- if the slides are available from the organizer, that would be great, but if not, no worries.
So I guess I wanted to start off and thank Fogarty so much. Nalini and Ariane—you guys are incredible. And then, I really would like to give a shout-out to Gretchen Birbeck, Virginia Bond, Valerie Earnshaw, Musah Lumumba El-Nasoor, who were the guest editors and did a fantastic job on this collection. I think a lot of us in the field across conditions are very excited about this collection. I think it will have a great life for many years to come and will spur really excellent work. I think the focus on stigma is timely. There are a lot of efforts currently underway around really understanding the social determinants of health, and stigma is one of those most important ones. So when I was thinking about today's presentations, I came up with -- I'm stuck on alliterations right now so I was thinking models, measures, mechanisms, medical-based, and multi-level interventions. And so in terms of the, you know, the first two talks by Laura and Melissa, excuse me, by Anne and Bernice did a fantastic job laying out a really important framework I think for anyone who is doing stigma related work to consider, to seriously consider. I think that the health stigma discrimination framework is amazing. I really applaud the hard work that you did to combine these different frameworks into a single one that lots of research groups could use. I think that it offers a common language, common terms. It helps to differentiate what is meant by this type of stigma, or that. It helps with the operationalization of the measures, and it is really an incredible benefit to the field, the framework.
With its important emphasis on intersectionality, I think Bernice said something very important. She said, you know it offers some convergence around how we understand intersectionality, but there's flexibility, there’s different ways to measure and analyze this thorny concept of intersectionality and really appreciate the efforts by her and Sarah Murray on intersectionality.
In terms of the interventions, I think both Laura, or Laura, Melissa, and Deepa nicely kept referring back to the framework, the framework really offers an important guide for research. It helps to identify where are the points of modification, what measures are needed, what types of stigma could be useful, or is most relevant, what outcomes are linked with these stigmas, and how could we intervene. There’s a paper that was mentioned early on, and I think I would like to call attention to it and that was the imperative, or the participatory praxis, led by Laurel Spraig and others. And this is really the kind of research that you want your communities at the table with you when you are thinking about the research, as you’re thinking about the questions, as you’re thinking about program. And those the individuals who are stigmatized or experiencing these multiple discriminating forces can help researchers understand where to and how to focus and how to make sense of this, so, excellent paper by Laurel and her colleagues. And so then, the interventions talked a lot about the how, how could we do this, trying to provide more transparency, trying to provide more rigor. Really great examples, I appreciated the examples from the Tylan group, and the Peru Canada group, really helped us grab on to what Laura and Melissa were talking about. And then Deepa's examples of how we can add some transparency around the multi-level interventions. I did want to call out, that with the multi-level and some of these difficult approaches, there are different research designs we can use to kind of disentangle which components are may be most used, like the most designed, for example.
So, and then finally, I think that, you know, with all of this, there was the mention of implementation science, a great implementation science paper, led by Chris Kemp and others, that I think is very important, with an emphasis on cost and cost-savings, cost effectiveness, and comparative analysis, I think was mentioned, of trying to understand the different approaches and the outcomes.
So I know we’re nearing the 12:00 hour here on eastern time, so I think I will close with just a few final thank yous’ and remarks. So the Center for Global Mental Health Research, at NIMH, is the sponsor of this webinar series. This is the kickoff to their webinar series for 2019, and we very much appreciate the global mental health, the Center for Global Mental Health for allowing us to launch their webinar series with this important collection by Fogarty. And I would like to really thank our IT support, here in the room and online. We very much appreciate your hard work to continue. Some of you may know there was an IT outage across NIH during our webinar, and so we, we persevered. And Valerie did an amazing job of just keeping her cool, [laughter], and making it all work. And a shout-out to Anthony and Ashley as well here in the room.
I think that one of the frames was more research, more research, and there's lots of ways for the folks in the room, and folks online, to think about how this work could inform your research.
There, we, at NIMH, in the Division of AIDS Research, we have taken this to heart. We have sponsored a special initiative around the intersectionality specifically in HIV prevention, and that is one of our efforts to try to really build from this great work that you folks have done. And so, in conclusion, thank you Nalini, Ariane, Beverly Pringle from the Center for Global Mental Health, and for everyone online today wherever you are. We appreciate your time and attention and we hope you have a good day. So, that will conclude our webinar today, thank you.