Prevalence and Determinants of Unintended Pregnancy : Systematic Review
Bibliographic record
Abstract
Introduction: The aim of this study was to determine the prevalence of burnout, and of asso-ciated factors, amongst family doctors (FDs) in the Middle East.Methodology: A cross-sectional survey of FDs was conducted using a custom-designed and validated questionnaire which incorporated the Maslach Burnout Inventory Human Services Survey (MBI-HSS) as well as questions about demographic factors, working experience, health, lifestyle and job satisfaction.MBI-HSS scores were analysed in the three dimensions of emotional exhaustion (EE), depersonalization (DP) and personal accomplishment (PA).Results: Seven hundred questionnaires were distributed in 5 Midlde Eastern countries, and 500 were returned to give a response rate of 71%.As far as burnout, 44% of respondents scored high for EE burnout, 30% for DP and 28% for PA, with 15% scoring high burnout in each of the three measurements.A little more than 33% of doctors did not score high for burnout in any dimesnion.High burnout was observed to be emphatically connected with a few of the variables under concentrate, particularly those relative to respondents' nation of home, occupation fulfillment, expectation to change work, sick leave usage, the misuse of liquor, tobacco and psychotropic medication, more youthful age and male sex.Conclusions: Burnout is by all accounts a typical issue in FDs over the Midlde East and is connected with individual and workload pointers, and particularly work fulfillment, aim to change work and the abuse of liquor, tobacco and medicine.The study survey has all the earmarks of being a substantial instrument to quantify burnout in FDs.Proposals for changes of employment conditions and future research are needed for further exploring the issue.
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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 | 0.009 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".