Promises in psychological contract drive commitment for clinicians
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – Job satisfaction, mental health and organisational commitment are important for clinician retention. Psychological contracts, organisational justice and negative affectivity (NA) have been linked with these outcomes but there is limited research examining these concepts in combination, particularly for clinicians. The aim of this paper is to examine the relationships between psychological contract breach, organisational justice and NA, on the outcomes of organisational commitment, psychological distress and job satisfaction, in a medical context. Design/methodology/approach – Surveys were distributed to Australian hospital clinicians through their internal mail and 81 completed surveys were returned (response rate=24 per cent). Findings – Multiple regression analyses revealed that organisational commitment was related to NA, psychological contract obligation and the interaction between psychological contract breach and distributive justice. Psychological distress was related to NA and procedural justice. Job satisfaction was related to the interaction between psychological contract breach and informational justice, however, the overall model for job satisfaction was not significant. Practical implications – By implementing innovative social exchange processes, healthcare organisations can ensure distributive justice is maintained in the culture in event of contract breach, and by so doing build safety mechanisms into sustaining commitment from clinicians. Originality/value – This paper contributes to the literature on clinical governance in managing the psychological contract to sustain commitment from clinical staff. The findings provide new insights into the factors effecting employee outcomes for clinicians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.005 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it