Adapting and Piloting a Combined Gender, Livelihoods, and HIV Prevention Intervention with Street-connected Young People in Eldoret, Kenya
Bibliographic record
Abstract
Despite being highly vulnerable to acquiring human immunodeficiency virus (HIV), no effective evidence-based interventions exist for street-connected young people in low- and middle-income countries (LMICs). In Kenya, street-connected young people have a heightened HIV prevalence, engage in sexual practices that elevate their exposure to HIV, and experience structural drivers of HIV acquisition, such as gender inequities and economic marginalization. Therefore, the overall objective of this doctoral thesis was to adapt and pilot a combined gender, livelihoods, and HIV prevention with street-connected young people in Eldoret, Kenya using a multi-stage mixed methods study design. In the first stage, the Stepping Stones and Creating Futures interventions and a matched-savings programme were adapted using a modified ADAPT-ITT model. During adaptation, we used community-based research methods informed by a rights-based approach, with four Peer Facilitators and 24 street-connected young people aged 16 to 24 years. Numerous adaptations came forth to the programme content and delivery. This adaptation process resulted in producing a comprehensive intervention entitled ‘Stepping Stones ya Mshefa na Kujijenga Kimaisha’. In the second stage, we piloted the adapted intervention with 80 street-connected young people using a pre- and post-intervention convergent mixed methods design. The primary outcomes of interest were HIV knowledge and gender equitable attitudes. Secondary outcomes included condom-use self-efficacy, sexual practices, economic resources, and livelihoods. Participants had significant increases in HIV knowledge and gender equitable attitudes from pre- to post-intervention. Attendance level at the intervention was a significant predictor of HIV knowledge and gender equitable attitudes change scores. Intervention participants reported encouraging changes in condom use knowledge, condom use self-efficacy, health-seeking practices, daily earnings, housing, livelihood activities, and street-involvement. Overall, this research demonstrated that it was feasible to adapt an evidence-based intervention with street-connected young people and provides a model for other researchers and organizations in LMICs to use, which may assist in addressing the knowledge gap in effective interventions for street-connected young people. The pilot findings support the potential for further testing with a rigorous study design to investigate how best to tailor the intervention, particularly accounting for gender differences, and increase the overall effectiveness of the programme.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".