Depression and Anxiety in Palestine: Piloting a Digital Application Based on the Friendship Bench (Preprint)
Bibliographic record
Abstract
Background: The burden of mental disorders is high in conflict-affected populations. In Palestine, we piloted Inuka Coaching, a digital intervention adapted from the Friendship Bench delivered by trained and supervised lay coaches. This paper documents the implementation of the intervention in this highly volatile context after October 7, 2023. Objective: This study aimed to describe the implementation of Inuka Coaching, a digital mental health tool based on task shifting, in Palestine and examine contextual challenges, fidelity to the coaching model, and lessons learned regarding recruitment, retention, and delivery during escalating ethnic cleansing. Methods: Two Palestinian mental health professionals were trained and certified in the Inuka method as head coaches, and subsequently trained 5 lay coaches. Palestinian adults in Gaza and the West Bank were recruited primarily through social media and received up to 4 structured, text-based coaching sessions typically delivered over 4 weeks depending on participant availability and preference. Standardized mental health screening questionnaires (Self-Reporting Questionnaire-20 [SRQ-20] and Posttraumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [PCL-5]) were collected at baseline, immediately after the first coaching session, and 3 months after the final session. Session transcripts were reviewed to assess coaches' fidelity to the Inuka method, and a focus group discussion explored coaches' experiences with training, delivery, and contextual challenges. Results: Between August 2023 and February 2024, a total of 70 participants were enrolled. Baseline assessments indicated high levels of psychological distress: 95.7% (67/70) scored above the PCL-5 threshold of 31, suggesting likely posttraumatic stress disorder, and 69.4% (43/62) scored in the "at risk" range on the SRQ-20. The effectiveness of the method could not be determined as retention was low, with only 7.1% (5/70) completing the program. Coach fidelity was high, with 94.6% (35/37) of transcripts adhering to all 5 steps of the intervention. Coaches reported positive experiences with the method but identified challenges related to recruitment, session continuity, platform usability, and the need for flexibility during acute crises. Key implementation learnings included the importance of early in-person collaboration and training, culturally sensitive framing, flexible delivery and session structures, and robust support for lay coaches. Conclusions: While digital, task-shifted mental health interventions can be delivered with fidelity in conflict settings, sustaining engagement during escalating violence remains challenging. Future implementations require flexible design, context-sensitive recruitment and retention strategies, adaptive delivery models, and strong support for lay coaches.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".