The impact of family systems and social networks on substance use initiation and recovery among women with substance use disorders.

OBJECTIVE: While social networks influence individuals with substance use disorders (SUDs), the mechanisms for such influence are under-explored among women who use drugs. This study triangulates the perspectives of criminal justice professionals, SUD treatment professionals, and women with past and current experiences with substance use to explore these dynamics. METHOD: We conducted semistructured interviews (N = 42) in 2022 with women with current or past opioid use disorder (n = 20), SUD treatment professionals (n = 12), and criminal justice professionals (n = 10) who work with women with opioid use disorder. Interviews centered around participants' backgrounds, perceived barriers and facilitators to medications for opioid use disorder (MOUD) treatment, and gender-specific issues in MOUD treatment. All interviews were audio-recorded, transcribed, and deidentified. We used a four-step qualitative data analysis process to code transcripts. RESULTS: Across these participants' accounts, we identified mechanisms by which women's social networks influenced their opioid use trajectories: intergenerational substance use, family support and strain, intimate partner influence, and peer support and pressure. Overall, the emergent themes in the present study reflect the embedded nature of support within social systems. Women who had access to and engaged with various forms of social support tended to be those who use/used MOUD and self-identified as in recovery. CONCLUSIONS: Combining MOUD treatment with psychosocial interventions allows women to heal from trauma, learn effective coping skills, and receive valuable resources to support recovery. Interventions focusing on family resilience and peer recovery support can disrupt the cycle of addiction and promote MOUD treatment success. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The role of polysubstance use on criminal justice involvement in the United States.

PURPOSE OF REVIEW: Polysubstance use, broadly defined as using more than one type of substance, disproportionately impacts those involved in the criminal justice system (CJS). This review synthesizes recent findings on polysubstance use among those involved in the CJS and highlights areas of particular concern and interventions. RECENT FINDINGS: We use 18 recent articles to identify the prevalence and types of criminal justice involvement and correlates of polysubstance use and criminal justice involvement. We highlight latent patterns of polysubstance use among various criminal justice populations (adults, pregnant women, and youth) and differential associations with adverse substance use and criminal justice outcomes. Lastly, we discuss substance use treatment in the justice system, the role of polysubstance use in treatment access and outcomes, and substance use-related services for previously incarcerated individuals reentering society. SUMMARY: Current research provides further evidence of the syndemic nature of polysubstance use, criminal justice involvement, and adverse outcomes, which are complicated by significant barriers to accessing evidence-based treatment in justice settings. Yet, current research is limited due to methodological inconsistency and limited focus on the social determinants of health, racial/ethnic disparities, and interventions to increase treatment and reentry services.

Individual and Social Risk and Protective Factors as Predictors of Trajectories of Post-traumatic Stress Symptoms in Adolescents.

The present study elucidates heterogeneity in post-traumatic stress symptoms (PTSS) across adolescence in a sample of youth who have experienced myriad types and combinations of potentially traumatic events (PTEs), including substantiated physical abuse, sexual abuse, neglect and/or at least one other self-reported PTE. A machine learning technique was used to assess a multivariate set of variables (e.g., PTEs, individual risk and protective factors, social risk and protective factors, and racial and ethnic minority status) as predictors of PTSS trajectory group membership. The sample included 498 maltreated (n = 275) and comparison (n = 223) 14-19-year-old female adolescents (M = 15.27, SD = 1.06 at Time 1) assessed annually until age 19. 45.7% of participants were White, 45.3% Black, 0.4% Native American, 0.8% Hispanic, and 7.7% other. Growth mixture modeling identified three distinct trajectories of PTSS: (1) recovery (56%); (2) moderate, chronic (25%); and (3) high, chronic (19%). An elastic net model was used to test predictors of membership in the recovery versus the high, chronic PTSS trajectory groups. Results demonstrated that the recovery trajectory was characterized by the absence of sexual abuse, physical abuse, and other traumas, higher self-esteem, less affective dysregulation, less risky peers, lower levels of parent depression, and being of racial/ethnic minority status. Findings help to characterize individual variation in trajectories of PTSS following PTEs by underscoring the unique trauma responses of racial and ethnic minority youth and offering possible targets of interventions to promote recovery from PTSS.

Understanding posttraumatic stress trajectories in adolescent females: A strength-based machine learning approach examining risk and protective factors including online behaviors.

Heterogeneity in the course of posttraumatic stress symptoms (PTSS) following a major life trauma such as childhood sexual abuse (CSA) can be attributed to numerous contextual factors, psychosocial risk, and family/peer support. The present study investigates a comprehensive set of baseline psychosocial risk and protective factors including online behaviors predicting empirically derived PTSS trajectories over time. Females aged 12-16 years (N = 440); 156 with substantiated CSA; 284 matched comparisons with various self-reported potentially traumatic events (PTEs) were assessed at baseline and then annually for 2 subsequent years. Latent growth mixture modeling (LGMM) was used to derive PTSS trajectories, and least absolute shrinkage and selection operator (LASSO) logistic regression was used to investigate psychosocial predictors including online behaviors of trajectories. LGMM revealed four PTSS trajectories: resilient (52.1%), emerging (9.3%), recovering (19.3%), and chronic (19.4%). Of the 23 predictors considered, nine were retained in the LASSO model discriminating resilient versus chronic trajectories including the absence of CSA and other PTEs, low incidences of exposure to sexual content online, minority ethnicity status, and the presence of additional psychosocial protective factors. Results provide insights into possible intervention targets to promote resilience in adolescence following PTEs.