Mindfulness as an intervention after multisystem trauma
Bibliographic record
Abstract
Background There is a known significant risk of negative mental health consequences following traumatic injury, yet no standard approach to prevent psychiatric illness in trauma patients currently exists. Mindfulness-based psychotherapies have been shown to reduce symptoms of post-traumatic stress disorder, depression and anxiety and improve resiliency, however it is unknown whether a mindfulness intervention immediately following traumatic injury would lead to diminished mental health consequences. Methods Multi-system trauma patients at the University of Alberta Hospital (N = 63) and the Foothills Hospital (N = 60) were assigned to the experimental and control groups respectively. Patients in the experimental group were asked to use the guided mindfulness application “Stop, Breathe & Think” for 28 consecutive days. All patients completed the Depression Anxiety Stress Scale (DASS-21) and Connor-Davidson Resilience Scale (CD-RISC) 48 hours and 28 days following admission. An exit interview was conducted for patients in the experimental group. Results There was no significant difference in mean enrollment DASS-21 scores, mean enrollment CD-RISC scores, mean follow-up DASS-21 scores and mean follow-up CD-RISC scores between experimental and control groups. Paired t-tests of mean admission and mean follow-up DASS-21 and CD-RISC scores were not significantly different in the experimental group. Paired t-tests of mean admission and follow-up CD-RISC scores were not significantly different in the control group whereas mean followup DASS-21 scores were decreased in the control group relative to enrolment DASS-21 scores (p = 0.014). Patients reported improved mood after use of mindfulness, and most planned to continue using the therapy and would recommend it to others. Conclusion Our study did not demonstrate an objective benefit of mindfulness intervention immediately following traumatic injury. Exit interview data suggests that a web-based mindfulness intervention may be beneficial for certain trauma patients however further research is required to identify those most likely to realize substantial gains.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".