Youth social networks and substance use prevention in Ghana: Exploring approaches to designing school-based preventive interventions
Bibliographic record
Abstract
Background: Globally, harmful substance use among young people is a public health problem with gender-specific impact. According to a Global Disease Burden study, substance use prevalence increased by 76% between 1990 and 2019 among young people in Africa, including Ghana. Despite the increasing burden of substance use, school-based interventions for prevention are lacking. Given the influence of peer relations on young people’s behaviours, interventions that leverage their social networks may be effective. Goal: The goal of my doctoral research was to explore approaches for the development of school-based substance use prevention interventions in Ghana, with examination of gender and social networks. I conducted a multi-method research study comprised of three phases. Phase one was a scoping review of school-based substance use prevention programs in Low-Middle-Income-Countries (LMICs) to identify the underlying theories, models, or frameworks (TMF) and core components of school-based substance use prevention interventions among young people in LMICs. Findings indicate that while a range of TMFs are used in designing interventions, the most widely used TMF was social learning theory followed by theory of planned behaviour. Six core intervention components were identified: education, school environment, school policy, parental involvement, peer engagement and counselling. Phase two was a mixed-methods social networks study to describe the social network features and substance use prevalence of senior high school students in Ghana, with a focus on levels of homophily (with respect to gender and substance use), and possible mechanisms through which friendship networks influence young people’s substance use behaviour. The results indicate that gender identity is a strong predictor of friend selection. In terms of substance use, a key finding was that only a few young people indicated a preference for friends with same substance use behaviour. Taken together, quantitative and qualitative results identified the existence and importance of a “friendship network and gender norms” in determining substance use behaviour within friendship networks.In phase three, a deliberative dialogue with interest holders was organized to garner feedback on study findings, and recommendations regarding key considerations in designing school-based interventions for substance use prevention. I used findings from this phase, together with further review of the literature, to develop the School-based Substance Use Prevention (SSUP) framework. The SSUP framework has five main priorities: (i) the guiding principles of SSUP prevention interventions; (ii) the core components to consider when designing an SSUP intervention; (iii) delivery groups to prioritize in an SSUP intervention; (iv) SSUP intervention stakeholder engagement process; and (v) the application of TMFs in an SSUP intervention. While this project focuses on Ghana, its findings and the resulting SSUP framework may be applicable to other African settings experiencing a similar substance use burden among young people
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".