Effect of a mindfulness intervention on patients admitted after multisystem trauma
Bibliographic record
Abstract
Background The incidence of depression, anxiety, and post-traumatic stress disorders is reported to be as high as 50% in trauma patients. The perpetual negative emotions and state of mind in these disorders predisposes patients to negative mental health outcomes. Mindfulness, on the other hand, helps people to process their experience and emotions in a non-judgmental manner, and recently, there has been increased utilization of mindfulness-based therapies for the treatment of mental health conditions. This proof-of-concept study evaluates the use of a mindfulness-based online application in patients admitted to the trauma service at a Level 1 Trauma Centre. Methods Trauma patients who were English speaking, over the age of 18, and without brain injury or pre-existing neurocognitive disorder were included. Participants completed the Depression Anxiety Stress Scale (DASS)-21 to assess level of depression, anxiety, and stress, and the Connor-Davidson Resilience Scale (CD-RISC) to assess level of resiliency. Then, after 28 consecutive days of practicing mindfulness using the app ‘Stop, Breathe, and Think,’ the questionnaires were repeated and an exit survey conducted. Results For this study, 13 participants were enrolled, 2 withdrew, and 5 were lost to follow-up. The mean DASS-21 score at time enrollment was 16.4 and was 11.2 at follow-up ( p = 0.10). There were no differences between the level of depression and stress from enrollment to follow-up, but there was significant decrease in anxiety symptoms from 7.2 to 3.0 (<0.05). CD-RISC scores at enrollment and follow-up were 77.8 and 81 ( p = 0.23), respectively. At the time of exit interview, 67% of patients continued to use the application three to four times a week and 67% responded they plan to continue using the application. In addition, 83% of patients always or often felt better after practicing mindfulness and stated they would recommend the application to others. Conclusions Mindfulness shows promising potential to decrease psychological distress in trauma patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".