Outcomes of transdiagnostic internet-delivered cognitive behavioural therapy tailored to public safety personnel: A longitudinal observational study
Bibliographic record
Abstract
First responders and other public safety personnel (PSP) experience high rates of mental health problems and face barriers to accessing mental healthcare. Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for various mental health concerns. Canadian PSP report favorable attitudes toward ICBT, and preliminary outcomes demonstrate that they benefit from it. Expanding on this research, the current study consisted of a longitudinal observational study of 560 Canadian PSP who participated in ICBT. It was designed to assess the longer term effectiveness of ICBT and moderators of outcomes by gender, linguistic and occupational group, and years of occupational experience. We evaluated symptom change at 8, 26, and 52 weeks post-enrollment, and results among PSP who had elevated clinical scores, showed large reductions (Hedges' g) in symptoms of depression (g = 1.3), anxiety (g =1.48), posttraumatic stress (g =1.24), panic (g =1.19), and anger (g =1.07) and moderate reductions in symptoms of social anxiety (g =.48-.56). Moderator analyses revealed modest differences in pre-treatment symptoms among certain groups but no group differences in symptom change over time. Clients showed good completion of treatment materials and reported high treatment satisfaction. The results suggest further study of ICBT tailored to PSP is warranted, including evaluating ICBT tailored for PSP in other countries.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".