Registered Nurses’ Characteristics and Their Levels of Compassion Competence and Satisfaction: A Cross-Sectional Survey
Bibliographic record
Abstract
Introduction Although registered nurses are expected to treat patients with care and compassion, a variety of characteristics may influence their ability to express compassion. Objectives (1) To assess registered nurses’ level of compassion competence and compassion satisfaction, and; (2) to explore how individual-level, employment-related, and organization-level characteristics are associated with their level of compassion competence and compassion satisfaction. Methods Registered nurses working in any practice setting in Ontario, Canada, completed a cross-sectional electronic survey of valid and reliable measures. Descriptive statistics and multiple linear regression analyses were used to address study objectives. Results One hundred eighty-one registered nurses participated. Most identified as female ( n = 157; 96.3%), Caucasian ( n = 144; 88.3%), and completed baccalaureate training as their highest level of education ( n = 80; 50.6%). Participants’ average compassion competence score was higher than average (4.18 on a 5-point scale), and most participants ( n = 171, 98.3%) reported moderate to high levels of compassion satisfaction. Compassion satisfaction was the only significant predictor of compassion competence, which indicated a positive relationship ( β = 0.344, p < .001). Compassion competence was among a variety of significantly positive predictors of compassion satisfaction ( β = 0.652, p < .001). The other positive significant predictors of compassion satisfaction were higher than baccalaureate education ( β = 0.363, p < .001), full-time work status ( β = 0.253, p = .012), working in organizations with greater compassion practices ( β = 0.114, p = .005), and organizations with higher climate for change ( β = 0.292, p < .001). Conclusions Study findings illuminate varying degrees of significance for individual-level, employment-related, and organization-level characteristics and how these predict registered nurses’ levels of compassion. These distinctions have important implications for intervention development and future research in understanding compassionate care among nurses.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".