Working in value‐discrepant environments inhibits clinicians’ ability to provide compassion and reduces well‐being: A cross‐sectional study
Bibliographic record
Abstract
Abstract Background The practice of compassion in healthcare leads to better patient and clinician outcomes. However, compassion in healthcare is increasingly lacking, and the rates of professional burnout are high. Most research to date has focused on individual‐level predictors of compassion and burnout. Little is known regarding how organizational factors might impact clinicians’ ability to express compassion and well‐being. The main study objective was to describe the association between personal and organizational value discrepancies and compassion ability, burnout, job satisfaction, absenteeism and consideration of early retirement among healthcare professionals. Methods More than 1000 practising healthcare professionals (doctors, nurses and allied health professionals) were recruited in Aotearoa/New Zealand. The study was conducted via an online cross‐sectional survey and was preregistered on AsPredicted (75407). The main outcome measures were compassionate ability and competence, burnout, job satisfaction and measures of absenteeism and consideration of early retirement. Results Perceived discrepancies between personal and organizational values predicted lower compassion ability (B = −0.006, 95% CI [−0.01, −0.00], p < 0.001 and f 2 = 0.05) but not competence (p = 0.24), lower job satisfaction (B = –0.20, 95% CI [–0.23, –0.17], p < 0.001 and f 2 = 0.14), higher burnout (B = 0.02, 95% CI [0.01, 0.03], p < 0.001 and f 2 = 0.06), absenteeism (B = 0.004, 95% CI [0.00, 0.01], p = 0.01 and f 2 = 0.01) and greater consideration of early retirement (B = 0.02, 95% CI [0.00, 0.03], p = 0.04 and f 2 = 0.004). Conclusions Working in value‐discrepant environments predicts a range of poorer outcomes among healthcare professionals, including hindering the ability to be compassionate. Scalable organizational and systems‐level interventions that address operational processes and practices that lead to the experience of value discrepancies are recommended to improve clinician performance and well‐being outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.001 |
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".