Improving access to psychological intervention in low-middle income settings: Results from a waitlist-controlled, proof-of-concept trial of the MemFlex intervention for trauma-exposed Afghan youth
Bibliographic record
Abstract
Low-intensity interventions targeting a range of mental health issues offer a scalable approach for young trauma survivors in low-middle income countries. Here, we present results from a proof-of-concept, randomised, waitlist-controlled trial evaluating MemFlex, an autobiographical memory-based intervention, for trauma-exposed Afghan youth residing in Iran. MemFlex seeks to reduce the negative and overgeneral memory biases which maintain and predict poor mental health. Young people aged 12-18 years (N=40) with parents who had experienced forced migration from Afghanistan were recruited from high schools in Karaj City in Iran. All had experienced a traumatic event in the last month. Participants were randomized to receive four weeks of a group-based delivery of MemFlex, or Waitlist. Our primary cognitive outcome was autobiographical memory flexibility, that is, the ability to deliberately retrieve any memory type on demand. Primary clinical outcome was emotional distress, measured on the Farsi version of the Hopkins Symptom Checklist. Results indicated that MemFlex participants demonstrated large effect sizes for pre-to-post improvement in memory flexibility (d=2.04) and emotional distress (d=1.23). These improvements were significantly larger than Waitlist (ds<0.49), and were maintained at three-month follow-up. Further evaluation of MemFlex in this context may offer a low-cost, and low-resource intervention to improve access to psychological intervention for young migrants in low-middle income countries.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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".