A Mixed-Methods Approach to Testing Stigma's Impact on Stress Processes in Substance Use Recovery

Date
2025-08
Language
American English
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Ph.D.
Degree Year
2025
Department
Psychology
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Indiana University
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Abstract

Although individuals with substance use disorder (SUD) often cite stigma as one of the biggest barriers to treatment, it is unclear how the effects of stigma extend to those in recovery. The aims of this study were to 1a) examine the longitudinal relationship between substance-use related stigma and functional markers of recovery, 1b) test stress, measured via anxiety symptoms, as a mediating mechanism of this relationship, and perceived social support and post-traumatic stress disorder (PTSD) symptoms as moderators on the indirect effects of stigma, and 2) identify qualitative themes surrounding perceptions of substance use-related stigma, social support, and trauma on recovery processes. The first aim included a longitudinal sample of 370 community adults (51.1% male, Mage=41.6 years, ±11.0 SD) in recovery from SUD, while the second aim included a sample of 44 adults (52.3% male, Mage=40.6 years, ±12.2 SD) in recovery from SUD. Structural equation modeling was used to test the longitudinal moderated-mediation model, using baseline, 6-month, and 12-month timepoints. Qualitative analyses were conducted on focus group transcripts using grounded theory approach to identify emergent themes surrounding the roles of stigma, perceived social support and trauma on recovery processes. Quantitative results did not support the direct relationship or moderated mediation model tested (p’s>.05). However, qualitative results identified higher-order categories of how social support and trauma helped, hurt, and had no effect on recovery, while stigma codes were categorized into impact on recovery treatment, and perceptions of self and others. Integration of findings suggest that mixed effects identified in qualitative themes were likely masked in quantitative analyses due to broad assessments of constructs. Recommendations are made for future work, such as improving measurement specificity, content validity, and domains assessed, as well as using existing theoretical models to inform viable alternative pathways and mediators.

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