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There is mixed evidence on whether experiences of HIV-related stigma are mitigated with lived experience. We sought to examine whether people living with HIV (PLWH) with longer living experience reported varying levels of HIV-related stigma. Between January 2016-September 2018, we used purposive sampling to enrol PLWH aged ≥19 across British Columbia, Canada, where participants completed the 10-item Berger HIV Stigma Scale. We conducted bivariate analyzes examining key sociodemographic characteristics and HIV-related stigma scores. Multivariable linear regression modelled the association between year of HIV diagnosis by treatment era and HIV-related stigma scores. We enrolled 644 participants; median age at enrolment was 50 years (Q1–Q3: 42–56), with 37.4% (n = 241) diagnosed before the year 2000. The median HIV-stigma scores of all participants (19.0, Q1–Q3: 13–25, range 0–40) stratified by treatment era were: 17.0 (pre-1996), 20.0 (1996–1999), 20.0 (2000–2009), 19.0 (2010–2018) (p = 0.03). While there was a significant association at the univariate level, year of HIV diagnosis by treatment era was not associated with stigma scores after controlling for age, gender, HIV key populations, ethnicity, relationship status, social support, and ever having a mental health disorder diagnosis. This suggests that PLWH still experience HIV-related stigma today, compared to those diagnosed in earlier time periods. [ABSTRACT FROM AUTHOR]

Depressive symptoms among people living with HIV (PLWH) are associated with poorer overall health outcomes. We characterized depressive symptoms and improvements in symptomology among PLWH (≥ 19 years old) in British Columbia (BC), Canada. We also examined associations between depressive symptomology and antiretroviral therapy (ART) treatment interruptions. Depressive symptoms were measured using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10), within a longitudinal cohort study with three surveys administered 18-months apart. We used multivariable logistic regression to model factors associated with improvements in depressive symptoms (CES-D-10 scores from ≥ 10 to < 10). Of the 566 participants eligible for analysis 273 (48.2%) had CES-D scores indicating significant depressive symptoms (score ≥ 10) at enrollment. Improvements in symptoms at first follow-up were associated with greater HIV self-care on the Continuity of Care Scale (adjusted odds ratio: 1.17; 95% CI 1.03–1.32), and not having a previously reported mental health disorder diagnosis (aOR 2.86; 95% CI 1.01–8.13). Those reporting current cocaine use (aOR 0.33; 95% CI 0.12–0.91) and having a high school education, vs. less than, (aOR 0.25; 95% CI 0.08–0.82) had lower odds of improvement in depressive symptomatology. CES-D scores ≥ 10 were not significantly associated with ART treatment interruptions during follow-up (aOR: 1.08; 95% CI:0.65–1.8). Supporting greater self-care and consideration of mental health management strategies in relation to HIV may be useful in promoting the wellbeing of PLWH who experience depressive symptoms. [ABSTRACT FROM AUTHOR]

Community-based participatory research (CBPR) has a long history within HIV research, yet little work has focused on facilitating team-based data analysis within CBPR. Our team adapted Thorne's interpretive description (ID) for CBPR analysis, using a color-coded "sticky notes" system to conduct data fragmentation and synthesis. Sticky notes were used to record, visualize, and communicate emerging insights over the course of 11 in-person participatory sessions. Data fragmentation strategies were employed in an iterative four-step process that was reached by consensus. During synthesis, the team created and recreated mind maps of the 969 sticky notes, from which we developed categories and themes through discussion. Flexibility, trust, and discussion were key components that facilitated the evolution of the final process. An interactive, team-based approach was central to data co-creation and capacity building, whereas the "sticky notes" system provided a framework for identifying and sorting data. [ABSTRACT FROM AUTHOR]