Dialectical behaviour therapy skills training: A feasibility study with active duty military
Bibliographic record
Abstract
LAY SUMMARY This study looked at the use of dialectical behaviour therapy (DBT) skills group training with military personnel. DBT skills group training teaches coping skills to manage emotions; it has been well researched and used effectively with civilians and Veterans, but less is known about its use with military personnel. The General Mental Health (GMH) clinic receives a large volume of referrals for military personnel who have difficulty with coping skills and managing emotions. On the basis of previous research, a modified DBT skills group therapy program was developed for the clinic to offer an efficient, effective treatment program for these clients in this busy clinic. Military personnel may be a particularly good fit for this type of group-based treatment because they are familiar with working in small group settings. This treatment can also allow for a timelier return to work, minimizing interruptions to military deployments and operations. Study results showed that program participants had lower levels of depression and a greater ability to manage emotions and cope more effectively after the program. Treatment gains were largely maintained at six-month follow-up. This research suggests that DBT skills group training may be an effective treatment for military personnel.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 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) | 0.006 | 0.002 |
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".