A Mobile Phone–Based Intervention to Reduce Mental Health Problems in Health Care Workers During the COVID-19 Pandemic (PsyCovidApp): Randomized Controlled Trial
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The global health emergency generated by the COVID-19 pandemic is posing an unprecedented challenge to health care workers, who are facing heavy workloads under psychologically difficult situations. Mental mobile Health (mHealth) interventions are now being widely deployed due to their attractive implementation features, despite the lack of evidence about their efficacy in this specific population and context. OBJECTIVE: The aim of this trial is to evaluate the effectiveness of a psychoeducational, mindfulness-based mHealth intervention to reduce mental health problems in health care workers during the COVID-19 pandemic. METHODS: We conducted a blinded, parallel-group, controlled trial in Spain. Health care workers providing face-to-face health care to patients with COVID-19 were randomly assigned (1:1) to receive the PsyCovidApp intervention (an app targeting emotional skills, healthy lifestyle behavior, burnout, and social support) or a control app (general recommendations about mental health care) for 2 weeks. The participants were blinded to their group allocation. Data were collected telephonically at baseline and after 2 weeks by trained health psychologists. The primary outcome was a composite of depression, anxiety, and stress (overall score on the Depression Anxiety Stress Scale-21 [DASS-21]). Secondary outcomes were insomnia (Insomnia Severity Index), burnout (Maslach Burnout Inventory Human Services Survey), posttraumatic stress (Davidson Trauma Scale), self-efficacy (General Self-Efficacy Scale), and DASS-21 individual scale scores. Differences between groups were analyzed using general linear modeling according to an intention-to-treat protocol. Additionally, we measured the usability of the PsyCovidApp (System Usability Scale). The outcome data collectors and trial statisticians were unaware of the treatment allocation. RESULTS: Between May 14 and July 25, 2020, 482 health care workers were recruited and randomly assigned to PsyCovidApp (n=248) or the control app (n=234). At 2 weeks, complete outcome data were available for 436/482 participants (90.5%). No significant differences were observed between the groups at 2 weeks in the primary outcome (standardized mean difference -0.04; 95% CI -0.11 to 0.04; P=.15) or in the other outcomes. In our prespecified subgroup analyses, we observed significant improvements among health care workers consuming psychotropic medications (n=79) in the primary outcome (-0.29; 95% CI -0.48 to -0.09; P=.004), and in posttraumatic stress, insomnia, anxiety, and stress. Similarly, among health care workers receiving psychotherapy (n=43), we observed improvements in the primary outcome (-0.25; 95% CI -0.49 to -0.02; P=.02), and in insomnia, anxiety, and stress. The mean usability score of PsyCovidApp was high (87.21/100, SD 12.65). After the trial, 208/221 participants in the intervention group (94.1%) asked to regain access to PsyCovidApp, indicating high acceptability. CONCLUSIONS: In health care workers assisting patients with COVID-19 in Spain, PsyCovidApp, compared with a control app, reduced mental health problems at 2 weeks only among health care workers receiving psychotherapy or psychotropic medications. TRIAL REGISTRATION: ClinicalTrials.gov NCT04393818; https://clinicaltrials.gov/ct2/show/NCT04393818.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it