Job satisfaction in sport science and sports medicine, an international cross-sectional survey
Bibliographic record
Abstract
Background/Aim: Job satisfaction (JS) and professional burnout among health professionals have been shown to affect several factors: healthcare quality, patient safety, patient satisfaction, turnover/reduction of work effort, healthcare costs and other personal consequences. In general, factors that impact JS for health professionals include professional autonomy, workplace conditions, rewards/recognition, compensation and work-life balance. However, less is known about JS of professions working in sport science and sports medicine (SSSM) especially from an international perspective. This paper addresses JS among SSSM professionals in an international context. Methods: In a cross-sectional study design, the Interprofessional Collaboration (IPC) in SSSM survey, an online survey which included the Warr-Cook-Wall JS questionnaire for international respondents working in fields associated with SSSM, was distributed globally to persons working in SSSM. Data from 320 respondents with complete data sets from USA (n=83), Canada (n=179) and Europe (n=58) were collected. Results: High values were detected in the overall JS of the total sample with some differences in variables relevant for JS internationally and a relationship between positive perceptions of IPC and overall JS. The most important determinant for overall JS in professionals working in SSSM is the opportunity to use abilities. Conclusion: JS has an important influence on the work and services provided by SSSM professionals and experience with IPC can have a positive effect on JS which, in turn, can improve quality of life for clients, patients and professionals. Employers should regard most impactful determinants of overall JS when designing working conditions for their employees.
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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 | 0.024 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 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".