Acceptability of an e-Learning Program to Help Nursing Assistants Manage Relationship Conflict in Nursing Homes
Bibliographic record
Abstract
BACKGROUND: Management of nursing assistants' (NAs) emotional stress from relationship conflicts with residents, families, and coworkers is rarely the focus of educational programs. Our objective was to gather feedback from NAs and their nursing supervisors (NSs) about the utility of our e-learning program for managing relationship stress. METHODS: A total of 147 NAs and their NSs from 17 long-term care homes viewed the educational modules (DVD slides with voice-over), either individually or in small groups, and provided feedback using conference call focus groups. RESULTS: Qualitative analysis of NA feedback showed that workplace relationship conflict stress was associated with workload and the absence of a forum for discussing relationship conflicts that was not acknowledged by NSs. CONCLUSION: This accessible e-learning program provides NAs with strategies for managing stressful emotions arising from workplace relationship conflict situations and underscores the importance of supervisory support and team collaboration in coping with emotionally evoked workplace stress.
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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 | 0.005 | 0.018 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".