Trauma, time and mental health: a study of temporal reintegration and Depressive Disorder among Southeast Asian refugees
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Prior research suggested that time splitting--suppressing the past and dissociating it from present and future--protected refugee mental health in the aftermath of catastrophe. The current study investigates temporal reintegration, defined as cognitive recapture of the past and reconnecting it with present and future, the mental health effects of temporal reintegration, and factors moderating the associated risk for Depressive Disorder. METHOD: A community sample of 608 Southeast Asian refugees, resettled in Vancouver British Columbia between 1979 and 1981, were interviewed on three separate occasions over a 10-year period. Participants performed a temporal orientation task and responded to questions about employment, social relations and mental health. Depressive Disorder, measured by a typology derived from Grade of Membership analysis of symptoms, constituted the dependent variable. Latent Growth Curve Analysis was used to examine both levels and rates of change in the probability of Depressive Disorder as predicted by changes in temporal reintegration, as well as the contribution of putative social and psychological moderators to explaining variations in growth parameters. RESULTS: Time relatedness increased over the duration of the study. Temporal reintegration jeopardized mental health. Employment and relational stability each moderated the mental health effects of temporal reintegration. CONCLUSIONS: Although time splitting may be effective in coping with adversity over the short-term, eventual temporal reintegration is probably ineluctable. Stability in love and work are protective factors, mitigating the mental health vicissitudes of temporal reintegration. Implications for optimal timing of clinical interventions are discussed.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it