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ObjectiveThe COVID-19 pandemic has dramatically impacted mental health, increasing rates of substance misuse. Resilience is a positive adaptation to stress that may act as a buffer against adverse mental health outcomes. Based on prior knowledge, we hypothesized that PLWH would display higher resilience than HIV-uninfected peers, and that high resilience would be associated with lower risk of substance misuse.MethodsThis analysis of the Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO) included data from six USA cohorts that administered a COVID-19-related survey with a 3-month follow-up during May 2020 and March 2021. All data was self-reported. The Brief Resilience Scale and General Anxiety Disorder-7 were utilized. Primary analyses consisted of multivariate generalized linear mixed models with random intercepts using binary logistic regression.ResultsA total of 1430 participants completed both surveys, of whom 670 (46.9%) were PLWH. PLWH had lower odds of anxiety (OR=0.67, 95% CI: 0.51-0.89) and higher odds of high resilience (OR=1.21, 95% CI: 1.02-1.44) than HIV-uninfected participants, adjusted for covariates. The presence of anxiety was associated with higher risk of misuse of all substances. High resilience was associated with lower risk of anxiety and misuse of substances, adjusted for covariates.ConclusionsPsychological resilience was associated with lower risk of anxiety and substance misuse, potentially serving as a buffer against poor mental and behavioral health during the COVID-19 pandemic. Further research is needed to identify pathways of resilience in the context of substance misuse and comprehensive resilience-focused interventions.

BackgroundIn Kenya, the prevalence of alcohol use disorder (AUD) is close to 6%, but a notable treatment gap persists. AUD is especially pronounced among men, leading to negative consequences at both individual and family levels. This study examines the experiences of problem-drinking fathers in Kenya regarding previous treatment-seeking related to alcohol use. Experiences and dynamics of the family are also explored as they pertain to treatment-seeking experiences.MethodsIn Eldoret, Kenya, semi-structured qualitative interviews were conducted with 11 families with a male exhibiting problem drinking, his spouse, and one child. Thematic content analysis was used to examine themes related to barriers and facilitators to treatment.ResultsParticipants only reported informal help received from family and community members; they exhibited little awareness of available formal treatments. Families were both deeply affected by alcohol use and actively involved in help-seeking. Indeed, fathers' experiences are described as help-accepting rather than help-seeking. Three overarching themes emerged from the results: poverty, people, and practices. Poverty could be a motivator to accept help to support one's family financially, but stress from lack of work also drove drinking behaviours. People were also crucial as both barriers and facilitators of help-accepting. Negative help strategies or peer influence deterred fathers from accepting help to quit. Positive motivation, social support, and stigma against drinking were motivators. Practices that were culturally salient, such as religiosity and gender roles, facilitated help acceptance. Overall, most help efforts were short-term and only lead to very short-term behaviour change.ConclusionFamilies and communities are active in help provision for problem-drinking men in Kenya, though results confirm remaining need for effective interventions. Future interventions could benefit from recognizing the role of family to aid in treatment-engagement and attending to the importance of poverty, people, and practices in designing treatment strategies.

This letter considers the use of machine learning algorithms for predicting cocaine use based on magnetic resonance imaging (MRI) connectomic data. The study used functional MRI (fMRI) and diffusion MRI (dMRI) data collected from 275 individuals, which was then parcellated into 246 regions of interest (ROIs) using the Brainnetome atlas. After data preprocessing, the data sets were transformed into tensor form. We developed a tensor-based unsupervised machine learning algorithm to reduce the size of the data tensor from 275 (individuals) × 2 (fMRI and dMRI) × 246 (ROIs) × 246 (ROIs) to 275 (individuals) × 2 (fMRI and dMRI) × 6 (clusters) × 6 (clusters). This was achieved by applying the high-order Lloyd algorithm to group the ROI data into six clusters. Features were extracted from the reduced tensor and combined with demographic features (age, gender, race, and HIV status). The resulting data set was used to train a Catboost model using subsampling and nested cross-validation techniques, which achieved a prediction accuracy of 0.857 for identifying cocaine users. The model was also compared with other models, and the feature importance of the model was presented. Overall, this study highlights the potential for using tensor-based machine learning algorithms to predict cocaine use based on MRI connectomic data and presents a promising approach for identifying individuals at risk of substance abuse. [ABSTRACT FROM AUTHOR]

Objective: To examine whether (a) Living in the Face of Trauma (LIFT), a group intervention to address coping with HIV and childhood sexual abuse (CSA), significantly reduced traumatic stress over a 1-year follow-up period more than an attention-matched support group comparison intervention; and (b) reductions in avoidant coping over time mediated reductions in traumatic stress. Method: In a randomized controlled trial, 247 participants completed measures of traumatic stress and avoidant coping at pre- and post intervention, and at 4-, 8-, and 12-month follow-ups. Latent growth curve modeling examined changes over the 5 time points; standardized path coefficients provide estimates of effects. Results: As compared with the support intervention, the coping intervention led to a reduction in traumatic stress over time (b = -0.20, p less than 0.02). Participants in the coping intervention also reduced their use of avoidant coping strategies more than did participants in the support intervention (b = -0.22, p less than 0.05). Mediation analyses showed reductions in avoidant coping related to reductions in traumatic stress (b = 1.45, p less than 0.001), and the direct effect of the intervention on traumatic stress was no longer significant (b = 0.04, ns), suggesting that changes in avoidant coping completely mediated intervention effects on traumatic stress. Conclusions: The LIFT intervention significantly reduced traumatic stress over time, and changes in avoidant coping strategies mediated this effect, suggesting a focus on current stressors and coping skills improvement are important components in addressing traumatic stress for adults living with HIV and CSA. (Contains 2 figures and 1 table.)

Urban teens face many traumas, with implications for potential growth and distress. This study examined traumatic events, posttraumatic growth, and emotional distress over 18 months among urban adolescent girls (N = 328). Objectives were to (a) describe types of traumatic events, (b) determine how type and timing of events relate to profiles of posttraumatic growth, and (c) prospectively examine effects of event type and posttraumatic growth on short- and long-term emotional distress with controls for pre-event distress. Results indicate that type of event was related to profiles of posttraumatic growth, but not with subsequent emotional distress. When baseline emotional distress was controlled, posttraumatic growth was associated with subsequent reductions in short- and long-term emotional distress. Implications for future research and clinical practice with adolescents are addressed.