Satisfaction and Motivation of General Physicians toward Their Career
Bibliographic record
Abstract
BACKGROUND: Human resource in health system especially in developing countries has main role in health promotion. Therefore their satisfaction and motivation are the key points in developing health system. OBJECTIVE: To determine the motivation and satisfaction of general physicians (GP) towards their career. METHODS: Using random sampling, 150 physicians were selected from comprehension commercial database list. Data were collected using a self-administered questionnaire that consisted of three sections; first demographic data, second work satisfaction and third questions toward biologic, dependent and growth motivation. Data were analyzed by SPSS version 16 with P<0.05. RESULTS: From participants 64.7% of physicians were in age between 30-40 years and 27.3% were men. Only 5.3% of physicians who were employed for over 10 years were satisfied from their career. Satisfaction of career among female and male physicians was 8% and 24% respectively. The item of job safety sensation in biologic motivation had maximum scale (4.1±0.89). In dependent and growth motivations, value success sensation in job (4+-0.88) and make new skills and knowledge (4+-0.67) had maximum scale of mean. Relation of growth motivators with age (P<0.01), postgraduate duration (P<0.005) was significant. Dependent motivators had significant relation with age (P<0.04), postgraduate duration (P<0.01) and employment duration (P<0.002). Biological motivators had significant relation with sex (P<0.4) and satisfaction of work hours (P<0.007). Correlation of biological (r=0.44, P<0.001) and growth (r=0.7, P<0.001) motivators was significant. CONCLUSION: Growth motivators score had higher ranking than other motivators. However, biological motivators especially job security and finance were also important and must be noticed from decision makers.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".