First-hand accounts of structural stigma toward people who use opioids on Reddit.

People who use opioids face multilevel stigma that negatively affects their health and well-being and drives opioid-related overdose. Little research has focused on lived experience of the structural levels of stigma toward opioid use. This study identified and qualitatively analyzed Reddit content about structural stigma toward opioid use. Iterative, human-in-the-loop natural language processing methods were used to identify relevant posts and comments from an opioid-related subforum. Ultimately, 273 posts and comments were qualitatively analyzed via directed content analysis guided by a prominent conceptualization of stigma. Redditors described how structures-including governmental programs and policies, the pharmaceutical industry, and healthcare systems-stigmatize people who use opioids. Structures were reported to stigmatize through labeling (i.e., particularly in medical settings), perpetuating negative stereotypes, separating people who use opioids into those who use opioids "legitimately" versus "illegitimately," and engendering status loss and discrimination (e.g., denial of healthcare, loss of employment). Redditors also posted robust formulations of structural stigma, mostly describing how it manifests in the criminalization of substance use, is often driven by profit motive, and leads to the pervasiveness of fentanyl in the drug supply and the current state of the overdose crisis. Some posts and comments highlighted interpersonal and structural resources (e.g., other people who use opioids, harm reduction programs, telemedicine) leveraged to navigate structural stigma and its effects. These findings reveal key ways by which structural stigma can pervade the lives of people who use opioids and show the value of social media data for investigating complex social processes. Particularly, this study's findings related to structural separation may help encourage efforts to promote solidarity among people who use opioids. Attending to first-hand accounts of structural stigma can help interventions aiming to reduce opioid-related stigma be more responsive to these stigmatizing structural forces and their felt effects.

Evaluation of Two Videos that Apply Evidence-Based Strategies to Increase Self-Efficacy and Reduce Opioid-Related Stigma Among Medical Students.

OBJECTIVE: This study evaluated the video-based application of evidence-based stigma reduction strategies to increase medical students' screening-diagnostic self-efficacy for opioid use disorder (OUD) and reduce stigma toward opioid use. METHODS: Formative qualitative research informed development of two videos for medical students. One uses an education strategy by including education regarding non-stigmatizing language use and OUD screening and diagnosis (Video A); the other uses an interpersonal contact strategy by presenting narratives regarding opioid use from three people who have a history of opioid use and three physicians (Video B). Both videos were administered to all respondents, with video order randomized. Effects on outcomes were evaluated using a pre-/post-test design with a 1-month follow-up. Participants also provided feedback on video content and design. RESULTS: Medical students (N = 103) watched the videos and completed the pre-/post-test, with 99% (N = 102) completing follow-up 1 month after viewing both videos. Self-efficacy increased directly following viewing Video A, and this increase was sustained at 1-month follow-up. Stigma toward opioid use decreased directly following viewing Video B, and this decrease was sustained at 1-month follow-up for participants who watched Video B first. Statistically significant improvements were observed in most secondary outcomes (e.g., harm reduction acceptability) directly following watching each video and most were sustained at 1-month follow-up. Feedback about the videos suggested the delivery of evidence-based strategies in each video was appropriate. CONCLUSIONS: Video-based applications of these evidence-based strategies were found acceptable by medical students and have potential to elicit sustained improvement in their screening-diagnostic self-efficacy and opioid-related stigma.

A pilot pragmatic trial of a "what matters most"-based intervention targeting intersectional stigma related to being pregnant and living with HIV in Botswana.

We conducted a pilot trial of an intervention targeting intersectional stigma related to being pregnant and living with HIV while promoting capabilities for achieving 'respected motherhood' ('what matters most') in Botswana. A pragmatic design allocated participants to the intervention (N = 44) group and the treatment-as-usual (N = 15) group. An intent-to-treat, difference-in-difference analysis found the intervention group had significant decreases in HIV stigma (d = - 1.20; 95% CI - 1.99, - 0.39) and depressive symptoms (d = - 1.96; 95% CI - 2.89, - 1.02) from baseline to 4-months postpartum. Some, albeit less pronounced, changes in intersectional stigma were observed, suggesting the importance of structural-level intervention components to reduce intersectional stigma.

Systematic Review of Cultural Aspects of Stigma and Mental Illness among Racial and Ethnic Minority Groups in the United States: Implications for Interventions.

Stigma is integral to understanding mental health disparities among racial and ethnic minority groups in the United States. We conducted a systematic review to identify empirical studies on cultural aspects of mental illness stigma (public, structural, affiliative, self) among three racial and ethnic minority groups (Asian Americans, Black Americans, Latinx Americans) from 1990 to 2019, yielding 97 articles. In comparison studies (N = 25), racial and ethnic minority groups often expressed greater public and/or self-stigma than White American groups. In within-group studies (N = 65; Asian American, n = 21; Black American, n = 18; Latinx American; n = 26), which were primarily qualitative (73%), four major cultural themes emerged: 1) service barriers including access and quality (structural stigma); 2) family experiences including concealment for family's sake, fear of being a burden, and stigma extending to family (affiliative stigma); 3) lack of knowledge about mental illness and specific cultural beliefs (public stigma); and 4) negative emotional responses and coping (self-stigma). These findings confirmed stigma has both similar and unique cultural aspects across groups. Despite this, few studies tested stigma reduction interventions (N = 7). These cultural insights can inform contextual change at the health systems and community levels to reduce stigma, and empowerment at the interpersonal and individual levels to resist stigma.

A brief anti-stigma intervention for Chinese immigrant caregivers of individuals with psychosis: adaptation and initial findings.

Mental illness stigma has adverse effects on both the caregivers' psychological well-being and the effectiveness of care that consumers receive. While anti-stigma interventions for family caregivers from Western settings have recently shown efficacy, these interventions may not be equally applicable across culturally diverse groups. Specifically, Chinese immigrant caregivers experience heightened internalized stigma, which predisposes the adoption of harmful coping strategies and reduced quality of social networks. We present an anti-stigma intervention based on a peer-family group format, co-led by a clinician and a trained family caregiver, to counter stigma among Chinese immigrants. Data are presented from a brief intervention administered to a pilot sample of 11 Chinese immigrant caregivers that provides: psychoeducation, strategies to counter experienced discrimination, and techniques to resist internalized stigma. Case vignettes illustrate implementation of this intervention, and how the peer-family format via interactive contact counteracts internalized stereotypes, encourages adaptive coping strategies, and reinvigorates social networks. Quantitative results further suggest preliminary efficacy in reducing internalized stigma for caregivers who evidenced at least some prior internalized stigma. This study constitutes an initial but important step towards reducing mental illness stigma among Asian Americans, for whom stigma has played a powerful role in the delay and underuse of treatment.

Mental illness-related disparities in length of stay: algorithm choice influences results.

Methodological challenges arise when one uses various Veterans Health Administration (VHA) data sources, each created for distinct purposes, to characterize length of stay (LOS). To illustrate this issue, we examined how algorithm choice affects conclusions about mental health condition (MHC)-related differences in LOS for VHA patients with diabetes nationally (n = 784,321). We assembled a record-level database of all fiscal year (FY) 2003 inpatient care. In 10 steps, we sequentially added instances of inpatient care from various VHA sources. We processed databases in three stages, truncating stays at the beginning and end of FY03 and consolidating overlapping stays. For patients with MHCs versus those without MHCs, mean LOS was 17.7 versus 13.6 days, respectively (p < 0.001), for the crudest algorithm and 37.2 versus 21.7 days, respectively (p < 0.001), for the most refined algorithm. Researchers can improve the quality of data applied to VHA systems redesign by applying methodological considerations raised by this study to inform LOS algorithm choice.

Using administrative data to identify mental illness: what approach is best?

The authors estimated the validity of algorithms for identification of mental health conditions (MHCs) in administrative data for the 133 068 diabetic patients who used Veterans Health Administration (VHA) nationally in 1998 and responded to the 1999 Large Health Survey of Veteran Enrollees. They compared various algorithms for identification of MHCs from International Classification of Diseases, 9th Revision (ICD-9) codes with self-reported depression, posttraumatic stress disorder, or schizophrenia from the survey. Positive predictive value (PPV) and negative predictive value (NPV) for identification of MHC varied by algorithm (0.65-0.86, 0.68-0.77, respectively). PPV was optimized by requiring > or =2 instances of MHC ICD-9 codes or by only accepting codes from mental health visits. NPV was optimized by supplementing VHA data with Medicare data. Findings inform efforts to identify MHC in quality improvement programs that assess health care disparities. When using administrative data in mental health studies, researchers should consider the nature of their research question in choosing algorithms for MHC identification.