A qualitative evaluation of stakeholder perspectives on sustainable financing strategies for ‘priority’ adolescent sexual and reproductive health interventions in Ghana
Bibliographic record
Abstract
Abstract Background Adolescent sexual and reproductive health (ASRH) interventions are underfunded in Ghana. We explored stakeholder perspectives on innovative and sustainable financing strategies for priority ASRH interventions in Ghana. Methods Using qualitative design, we interviewed 36 key informants to evaluate sustainable financing sources for ASRH interventions in Ghana. Thematic content analysis of primary data was performed. Study reporting followed the consolidated criteria for reporting qualitative research. Results Proposed conventional financing strategies included tax-based, need-based, policy-based, and implementation-based approaches. Unconventional financing strategies recommended involved getting religious groups to support ASRH interventions as done to mobilize resources for the Ghana COVID-19 Trust Fund during the global pandemic. Other recommendations included leveraging existing opportunities like fundraising through annual adolescent and youth sporting activities to support ASRH interventions. Nonetheless, some participants believed financial, material, and non-material resources must complement each other to sustain funding for priority ASRH interventions. Conclusion There are various sustainable financing strategies to close the funding gap for ASRH interventions in Ghana, but judicious management of financial, material, and non-material resources is needed to sustain priority ASRH interventions in Ghana.
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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 | 0.036 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".