Effects of 12 Weeks of At-Home, Application-Based Exercise on Health Care Workers’ Depressive Symptoms, Burnout, and Absenteeism
Bibliographic record
Abstract
Importance: During the COVID-19 pandemic, health care workers (HCWs) reported a significant decline in their mental health. One potential health behavior intervention that has been shown to be effective for improving mental health is exercise, which may be facilitated by taking advantage of mobile application (app) technologies. Objective: To determine the extent to which a 12-week app-based exercise intervention can reduce depressive symptoms, burnout, and absenteeism in HCWs, compared with a wait list control condition. Design, Setting, and Participants: A 2-group randomized clinical trial was conducted, with participants screened from April 6 to July 4, 2022. Participants were recruited from an urban health care organization in British Columbia, Canada. Participants completed measures before randomization and every 2 weeks thereafter. Interventions: Exercise condition participants were asked to complete four 20-minute sessions per week using a suite of body weight interval training, yoga, barre, and running apps. Wait-listed control participants received the apps at the end of the trial. Main Outcomes and Measures: The primary outcome consisted of the between-group difference in depressive symptoms measured with the 10-item Center for Epidemiological Studies Depression Scale. The secondary outcomes corresponded to 3 subfacets of burnout (cynicism, emotional exhaustion, and professional efficacy) and absenteeism. Intention-to-treat analyses were completed with multilevel structural equation modeling, and Feingold effect sizes (ES) were estimated every 2 weeks. Results: A total of 288 participants (mean [SD] age, 41.0 [10.8] years; 246 [85.4%] women) were randomized to either exercise (n = 142) or wait list control (n = 146) conditions. Results revealed that ESs for depressive symptoms were in the small to medium range by trial's end (week 12, -0.41 [95% CI, -0.69 to -0.13]). Significant and consistent treatment effects were revealed for 2 facets of burnout, namely cynicism (week 12 ES, -0.33 [95% CI, -0.53 to -0.13]) and emotional exhaustion (week 12 ES, -0.39 [95% CI, -0.64 to -0.14]), as well as absenteeism (r = 0.15 [95% CI, 0.03-0.26]). Adherence to the 80 minutes per week of exercise decreased from 78 (54.9%) to 33 (23.2%) participants between weeks 2 and 12. Conclusions and Relevance: Although exercise was able to reduce depressive symptoms among HCWs, adherence was low toward the end of the trial. Optimizing adherence to exercise programming represents an important challenge to help maintain improvements in mental health among HCWs. Trial Registration: ClinicalTrials.gov Identifier: NCT05271006.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".