Assessment of service provider competency for child and adolescent psychological treatments and psychosocial services in global mental health: evaluation of feasibility and reliability of the WeACT tool in Gaza, Palestine
Bibliographic record
Abstract
Abstract Background There is a scarcity of evaluated tools to assess whether non-specialist providers achieve minimum levels of competency to effectively and safely deliver psychological interventions in low- and middle-income countries. The objective of this study was to evaluate the reliability and utility of the newly developed Working with children – Assessment of Competencies Tool (WeACT) to assess service providers’ competencies in Gaza, Palestine. Methods The study evaluated; (1) psychometric properties of the WeACT based on observed role-plays by trainers/supervisors ( N = 8); (2) sensitivity to change among service provider competencies ( N = 25) using pre-and-post training WeACT scores on standardized role-plays; (3) in-service competencies among experienced service providers ( N = 64) using standardized role-plays. Results We demonstrated moderate interrater reliability [intraclass correlation coefficient, single measures, ICC = 0.68 (95% CI 0.48–0.86)] after practice, with high internal consistency ( α = 0.94). WeACT assessments provided clinically relevant information on achieved levels of competencies (55% of the competencies were scored as adequate pre-training; 71% post-training; 62% in-service). Pre-post training assessment saw significant improvement in competencies ( W = −3.64; p < 0.001). Conclusion This study demonstrated positive results on the reliability and utility of the WeACT, with sufficient inter-rater agreement, excellent internal consistency, sensitivity to assess change, and providing insight needs for remedial training. The WeACT holds promise as a tool for monitoring quality of care when implementing evidence-based care at scale.
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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 | 0.002 | 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".