A single case series using visuospatial task interference to reduce the number of visual intrusive memories of trauma with refugees
Bibliographic record
Abstract
The current worldwide so-called "refugee crisis" has led to an unprecedented increase in migration globally. Because of stigma and language barriers, mental health care for refugees is limited. There is a need for novel, scalable psychological interventions. We investigated whether a brief behavioural intervention involving a memory reminder cue and Tetris gameplay on a smartphone reduces intrusive memories in refugees using a single case (N = 4) ABAB withdrawal design. The baseline phase (A) included a no-intervention week; the intervention phase (B) included an in-person session with the researchers, comprised of the behavioural intervention followed by self-guided use in daily life the following week. All participants reported a decrease in intrusive memories after the intervention, as well as functional improvements (e.g., in concentration). Importantly, participants rated the intervention as feasible and acceptable. As one in-person session was effective in persistent intrusion reduction, ABAB proved not to be the optimal design as intrusions did not rebound in the withdrawal phase. Findings are promising and highlight the need for further evaluation of novel interventions for mental health problems in refugees.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".