Unexpected effects of expressive writing on post-disaster distress in the Hurricane Harvey Study: a randomized controlled trial in perinatal women
Bibliographic record
Abstract
BACKGROUND: Expressive writing requires journaling stressor-related thoughts and feelings over four daily sessions of 15 min. Thirty years of research have popularized expressive writing as a brief intervention for fostering trauma-related resilience; however, its ability to surpass placebo remains unclear. This study aimed to determine the efficacy of expressive writing for improving post-traumatic stress symptoms in perinatal women who were living in the Houston area during major flooding caused by Hurricane Harvey. METHODS: A total of 1090 women were randomly allocated (1:1:1) to expressive writing, neutral writing or no writing. Interventions were internet-based. Online questionnaires were completed before randomization and at 2 months post-intervention. The primary outcome was post-traumatic stress symptoms, measured with the Impact of Event Scale-Revised; secondary outcomes were affective symptoms, measured with the 40-item Inventory of Depression and Anxiety Scales. Feelings throughout the intervention were reported daily using tailored questionnaires. RESULTS: In intention-to-treat analyses, no post-treatment between-group differences were found on the primary and secondary outcomes. Per-protocol analyses yielded similar results. A number of putative moderators were tested, but none interacted with expressive writing. Expressive writing produced greater feelings of anxiety and sadness during the intervention compared to neutral writing; further, overall experiences from the intervention mediated associations between expressive writing and greater post-traumatic stress at 2 months post-intervention. CONCLUSIONS: Among disaster-stricken perinatal women, expressive writing was ineffective in reducing levels of post-traumatic stress, and may have exacerbated these symptoms in some.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".