Feasibility, acceptability, and effectiveness of a package of interventions to improve the performance of health workers in the Democratic Republic of Congo to deliver adolescent and youth sexual and reproductive health services
Bibliographic record
Abstract
BACKGROUND: Adolescents and youth (AY) in the Democratic Republic of Congo (DRC) face significant sexual and reproductive health (SRH) challenges and require access to quality health services. OBJECTIVE: This study assesses the feasibility, acceptability, and effectiveness of a package of interventions to improve the performance of health workers (HWs) providing SRH services to AY in the DRC. METHODS: This mixed-methods process and outcome evaluation was conducted between January and July 2021 in 30 health facilities in Mbuji-Mayi and Kinshasa. Data were collected through interviews with 25 health facility managers, surveys of 54 HWs, focus groups with 29 HWs, and interviews with 16 AY mystery clients and 18 female AY (10-24 years) health facility service users. Qualitative and quantitative data were analyzed using thematic content analysis and descriptive statistics respectively. RESULTS: Health facility managers reported that the package of interventions was feasible to implement, with concerns about resource shortcomings which were outside the scope of the implementation. From both quantitative and qualitative findings, health facility managers and HWs perceived the package of interventions as acceptable and effective in improving HW competencies, building positive attitudes towards providing SRH services to AY, building HW motivation, and fostering an enabling work environment as illustrated by improved communication, mentorship and constructive feedback between managers and HWs, and motivation, confidence and collaboration among HWs. AY clients reported overall satisfaction with the services they received, but some reported experiencing inappropriate comments and judgmental attitudes. CONCLUSIONS: The package of interventions was perceived as feasible and acceptable by health facility managers and HWs, and effective in improving HW knowledge, skills, attitudes and motivation, and ultimately in providing SRH services to AY. Future efforts are needed to validate the findings in different contexts and with other professionals, e.g. teachers, and to strengthen and amplify the package of interventions.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".