Novel Web-Based Drop-In Mindfulness Sessions (Pause-4-Providers) to Enhance Well-Being Among Health Care Workers During the COVID-19 Pandemic: Descriptive and Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic exerted extraordinary pressure on health care workers (HCWs), imperiling their well-being and mental health. In response to the urgent demand to provide barrier-free support for the health care workforce, Pause-4-Providers implemented 30-minute live web-based drop-in mindfulness sessions for HCWs. OBJECTIVE: This study aims to evaluate the use, feasibility, satisfaction, and acceptability of a novel mindfulness program aimed at enhancing the well-being of HCWs during the COVID-19 pandemic. METHODS: Accrual for the study continued throughout the first 3 pandemic waves, and attendees of ≥1 session were invited to participate. The evaluation framework included descriptive characteristics, including participant demographics, resilience at work, and single-item burnout scores; feedback questionnaires on reasons attended, benefits, and satisfaction; qualitative interviews to further understand participant experience, satisfaction, benefits, enablers, and barriers; and the number of participants in each session summarized according to the pandemic wave. RESULTS: We collected descriptive statistics from 50 consenting HCWs. Approximately half of the participants (24/50, 48%) attended >1 session. The study participants were predominantly female individuals (40/50, 80%) and comprised physicians (17/50, 34%), nurses (9/50, 18%), and other HCWs (24/50, 48%), who were largely from Ontario (41/50, 82%). Of 50 attendees, 26 (52%) endorsed feeling burned out. The highest attendance was in May 2020 and January 2021, corresponding to the first and second pandemic waves. The participants endorsed high levels of satisfaction (43/47, 92%). The most cited reasons for attending the program were to relax (38/48, 79%), manage stress or anxiety (36/48, 75%), wish for loving kindness or self-compassion (30/48, 64%), learn mindfulness (30/48, 64%), and seek help with emotional reactivity (25/48, 53%). Qualitative interviews with 15 out of 50 (30%) participants identified positive personal and professional impacts. Personal impacts revealed that participation helped HCWs to relax, manage stress, care for themselves, sleep better, reduce isolation, and feel recognized. Professional impacts included having a toolbox of mindfulness techniques, using mindfulness moments, and being calmer at work. Some participants noted that they shared techniques with their colleagues. The reported barriers included participants' needing time to prioritize themselves, fatigue, forgetting to apply skills on the job, and finding a private place to participate. CONCLUSIONS: The Pause-4-Providers participants reported that the web-based groups were accessible; appreciated the format, content, and faculty; and had high levels of satisfaction with the program. Both novel format (eg, drop-in, live, web-based, anonymous, brief, and shared activity with other HCWs) and content (eg, themed mindfulness practices including micropractices, with workplace applications) were enablers to participation. This study of HCW support sessions was limited by the low number of consenting participants and the rolling enrollment project design; however, the findings suggest that a drop-in web-based mindfulness program has the potential to support the well-being of HCWs.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".