Psychoeducational Burnout Intervention for Nurses: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Nurses face high levels of stress and emotional exhaustion due to heavy workloads and demanding work environments. Prolonged exposure to these stressors predisposes nurses to burnout, which can adversely affect patient care. Addressing burnout among nurses requires a multifaceted approach, involving both personal and organizational strategies. While organizational strategies target systemic workplace issues, personal interventions are often favored for their ease of implementation, immediate benefits, and empowerment of health care workers through stress management and resilience-building. Prioritizing evidence-based interventions to mitigate burnout among nurses is crucial for managing occupational stress and promoting well-being. Person-directed psychoeducation is an effective personal intervention strategy used to equip nurses with the appropriate knowledge and skills to handle stressors, thereby safeguarding their mental health and ensuring high-quality patient care. OBJECTIVE: This protocol proposes a systematic review that aims to identify and assess the effectiveness of person-directed psychoeducational interventions for nurses. The review aims to pinpoint effective interventions that can be implemented to manage burnout and support the mental health of nurses. METHODS: This systematic review will follow the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. In total of 5 electronic databases (PubMed-MEDLINE, EBSCOhost, Ovid MEDLINE, Scopus, and ScienceDirect) will be searched for studies published between January 1, 2014, and December 31, 2023. The search will encompass 3 main keywords: "nurses," "burnout intervention," and "burnout." Predefined eligibility criteria will guide the screening process. Data will be extracted to address the objectives of the review. The risk of bias for each study will be assessed using Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Preliminary searches have been initiated since February 2024, with the review expected to be completed by June 2024. The expected results will include a comprehensive list of psychoeducational interventions and their effectiveness in reducing burnout among nurses. The review will highlight interventions that demonstrate significant impact in published studies from various countries. CONCLUSIONS: Given the rising prevalence of burnout among nurses and its detrimental effects on individuals and health care organizations, the findings from this systematic review are expected to inform health care policy and practice. By evaluating different interventions, it will provide insights into the most effective strategies, contributing to evidence-based practices that support nurses' mental health and well-being. The findings can support stakeholders in developing and implementing targeted strategies to combat nurse burnout, ultimately enhancing the quality of patient care and health care delivery. In addition, the findings will also offer valuable information for researchers, guiding future practice and research in this area. TRIAL REGISTRATION: PROSPERO CRD42024505762; https://tinyurl.com/4p84dk3d. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58692.
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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 | 0.058 | 0.064 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.018 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.083 | 0.011 |
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".