Two-Step Resilience-Oriented Intervention for Veterans with Traumatic Brain Injury: A Pilot Randomized Controlled Trial.
Bibliographic record
Abstract
OBJECTIVE: The present randomized parallel two-arm pilot study aimed to compare the efficacy of two-step resilience-oriented intervention with treatment as usual in veterans with mild to moderate traumatic brain injury. METHOD: Two-step Resilience-Oriented Intervention (TROI) is a brief psychological intervention that targets cognitive (step 1) and emotional (step 2) factors of resilience and consists of six 1-hour sessions. Overall, 70 Ukrainian veterans serviced in Anti-Terrorist Operation / Joint Forces Operation were randomly assigned to an intervention group (TROI group) or a control group that underwent treatment as usual (TAU group). For pre- (T1) and post-treatment (T2) assessment the Connor-Davidson Resilience Scale (CD-RISC), Hospital Anxiety and Depression Scale (HADS), Montreal Cognitive Assessment Scale (MoCA), Neurobehavioral Symptom Inventory (NSI), Posttraumatic Stress Disorder Checklist 5 (PCL-5), Chaban Quality of Life Scale (CQLS), Positive and Negative Affect Scale (PANAS) were used. RESULTS: Multivariable linear regression with the treatment group, gender, baseline cognitive performance level and TBI severity as the independent variables revealed statistically significant improvements in the TROI group in resilience (CD-RISC), cognitive performance (MoCA), postconcussive symptoms (NSI), posttraumatic symptoms (PCL-5), positive affect (PANAS) and quality of life (CQLS) comparing to such in TAU group. We found no statistically significant differences between groups in depression, anxiety (HADS) and negative affect (PANAS) outcomes. Additionally, Wilcoxon signed-rank test revealed that participants who completed two-step resilience-oriented intervention had significantly improved scores for all outcomes compared to the baseline (p < 0.05). CONCLUSIONS: In summary, we can tentatively conclude that adding TROI to the standard treatment measures may improve the resilience and sustainable symptoms in veterans with TBI when compared with standard treatment. Targeting cognitive and emotional factors like problem-solving, decision-making, positive thinking can promote resilience in veterans with TBI and be useful in facilitating recovery from injury. Results of this pilot study are promising, but the intervention needs to be studied in a larger trial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".