Health Stigma and Discrimination: A Global, Cross-cutting Research Approach

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. [whispering]>>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. [clears throat] 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. [Applause] [Whispering/inaudible]>>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. [silence]>>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 intersectionalities
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. Next slide. 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. Next slide. 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. Next slide. 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. Next slide. 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. Next slide. 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. Next slide. 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. Next slide. 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. Next slide. Okay. 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. Next slide. 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. Next slide. 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. Thank you.>>VALERIE EARNSHAW: Okay, thank you so much
to Dr. Pescasolito. [audience applause 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. [silence] 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. [Applause].>>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. [Applause]

Comments

(0 Comments)

Your email address will not be published. Required fields are marked *