The Impact of an Online Mindfulness-Based Practice Program on the Mental Health of Brazilian Nurses during the COVID-19 Pandemic
Bibliographic record
Abstract
This quantitative, before-after study was developed to evaluate the usefulness of an online mindfulness practices program to help nursing professionals deal with stress in the challenging context of the COVID-19 pandemic through the assessment of perceived stress, anxiety and depression, levels of mindfulness, and participants' satisfaction with the program. Eligible participants were assessed at baseline to receive the online mindfulness training program for eight weeks and were appraised again at the end of the program. Standardized measures of perceived stress, depression, anxiety, and one-dimensional and multidimensional mindfulness were performed. Participant satisfaction was also studied. Adherence to treatment was 70.12%. The perceived stress, depression, and anxiety scores were significantly lower after the intervention. The mindfulness measure increased significantly, as well as the sense of well-being and satisfaction with life, study, and/or work. The participants showed high satisfaction with the program and would recommend it to other professionals. Our results indicate that mindfulness-based interventions represent an effective strategy for nurses in the face of the need for self-care with mental health and mechanisms that guarantee the sustainability of their capacities to continue exercising health care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".