A randomized controlled trial testing couple HOPES: An online, self-help couples’ intervention for posttraumatic stress disorder.
Bibliographic record
Abstract
OBJECTIVE: This article presents a randomized waitlist-controlled trial testing Couple HOPES, a coach-guided, online intervention for couples wherein one member had posttraumatic stress disorder (PTSD) symptoms. Aims involved examining whether Couple HOPES resulted in greater improvements in PTSD symptoms, relationship satisfaction, and secondary outcomes compared to a waitlist, whether outcomes were maintained over a 3-month follow-up, and whether outcomes differed if PTSD was COVID-19-related. METHOD: Sixty-seven couples were recruited, where one partner met criteria for likely PTSD and was either a military member, veteran, first responder, health care worker, and/or whose PTSD symptoms were related to COVID. Couples were randomized to receive Couple HOPES immediately or after 8 weeks. Outcomes were measured at the beginning, middle, and end of Couple HOPES/the waiting period, and 1- and 3-months after Couple HOPES. Measures of PTSD and relationship satisfaction were also completed during each of seven modules. RESULTS: Intent-to-treat analyses showed greater improvements in self- and informant-reported PTSD in those receiving Couple HOPES relative to waiting, with large- and medium-effect sizes, respectively. Partners without PTSD symptoms reported greater improvements in relationship satisfaction in Couple HOPES compared to the waitlist with a small effect size, but people with PTSD symptoms did not. Uncontrolled follow-up showed reversion of gains in some outcomes. Whether PTSD was COVID-19-related did not significantly moderate outcomes. CONCLUSIONS: Findings support the efficacy of this low-cost, scalable intervention for improving PTSD, regardless of the means through which it was acquired (COVID-19-related or not). Further testing with larger sample sizes is needed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.012 | 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".