Nature, predictors, and outcomes of Nurses' trajectories of harmonious and obsessive passion
Bibliographic record
Abstract
Abstract This study sought to achieve a dynamic person‐centered understanding of the various harmonious and obsessive work passion trajectories observed among a sample of nurses, as well as the connections between these two types of work passion trajectories. Moreover, it sought to document the predictive role of workload, unfairness, harassment, and supervisor support in relation to these harmonious and obsessive passion trajectories, as well as the implications of these trajectories for a variety of outcomes related to attitude (i.e., turnover intention), psychological health (i.e., perceived psychological health and work fatigue), and behaviors (i.e., work performance, presenteeism, and absenteeism). A sample of 622 nurses was surveyed six times over a period of five months. Our results revealed that harmonious and obsessive passion trajectories matched five primary profiles, similar across the two types of work passion. Workload, unfairness, harassment, and supervisor support were associated with these trajectories in a way that mainly supported our expectations. Trajectories characterized by higher levels of harmonious passion and lower levels of obsessive passion were associated with higher levels of perceived psychological health and work performance, and with lower levels of work fatigue, turnover intention, presenteeism, and absenteeism. Conversely, trajectories characterized by lower levels of harmonious passion and higher levels of obsessive passion were associated with the most negative outcomes.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".