Correlation between occupational stress, burnout, and satisfaction, and their impact on the productivity of Physical Therapists working in different work environments: A cross-sectional study
Bibliographic record
Abstract
Background: Satisfaction is a positive and pleasurable emotional state promoted by an appraisal, and putting perfection into work is a topic that received the attention of many researchers in different fields Objective: The correlation between occupational exhaustion, stress, and satisfaction was investigated to find a link between different factors in the workplace that may affect productivity among physical therapists in different working environments.Methodology: Cross-sectional study ruled out work factors that create negativity or positivity at the workplace.A job exit questionnaire was used for data collection.Two hundred physical therapists from various private and government clinical settings were chosen.Using the purposive sampling technique, the total number of respondents interviewed was 200, out of which 100 were from government sectors, and 100 who worked in private sectors.Working experience of physiotherapists was decided >5 years as inclusion criteria to test the potential of professional growth in terms of satisfaction.Results: 97±2% of physical therapists had completed and submitted the questionnaire.57% have 7±1.5 years of working experience.There is a direct relation between Job exhaustion with stress r = 0.56, and stress is inversely related to satisfaction r = -0.42.79% of Physiotherapists in the public sector found their occupation less stressful than physiotherapists working in the private sector.Productivity score was high in govt employees.It was determined that the promotion system based on qualification, skill, and seriousness in work positively affects the work performance.Conclusion: Physiotherapists working in the public sector are more satisfied with their job's nature, working environment, and occupation than those working in the private sector.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".