Public safety personnel feedback from a remote trial of Goal Management Training for post-traumatic stress during Covid-19
Bibliographic record
Abstract
Purpose: This paper explores participants’ perspectives on the acceptability, utility, and perceived therapeutic effects of a virtual group cognitive remediation program, Goal Management Training (GMT)™, during the COVID-19 pandemic. The advantages and drawbacks of these groups are considered as part of an online research study protocol exploring cognitive remediation among first responders (police, firefighters, paramedics, emergency dispatchers, corrections and parole officers, and nurses) who have been impacted by trauma. Methods: We qualitatively examined the results of an anonymous participant feedback survey collected from 20 first responders who took part in the first round of our online therapy groups. A thematic analysis approach was taken to highlight key themes and recommendations. Results: Survey results indicated that participants found our online protocol effective in terms of group facilitation, the utility of online platforms, and perceived therapeutic effects. Further, some participants preferred participating online versus attending in-person groups. Conclusion: This early data suggests that providing virtual options for research and treatment among trauma-impacted public safety personnel may increase accessibility and overall participation among this population.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".