Perceived Stress Among Resident Doctors in Jordanian Teaching Hospitals: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Medical residents in Jordanian hospitals are involved in many clinical and nonclinical tasks that expose them to various stress factors. High stress and burnout have the potential to negatively impact work performance and patient care, including medication errors, suboptimal care, clinical errors, and patient dissatisfaction. OBJECTIVE: This study aimed to determine the perceived stress among medical residents in Jordanian hospitals and its associated risk factors. METHODS: A cross-sectional study was conducted among residents in Jordanian hospitals. A cluster sample of 5 hospitals with residency programs was selected from different health sectors. All residents who were working in the selected hospitals were invited to participate in this study, during the period from April to July 2017. A total of 555 residents agreed to participate in this study, giving a response rate of 84%. The perceived stress scale (PSS) was used for assessment. RESULTS: A total of 398 male and 157 female residents were included in this study. The mean PSS score in this study was 21.6; 73% (405/555) of the residents had moderate level of stress, and 18% (100/555) had high level of stress. About 6.7% (37/555) of the residents had hypertension, 2.7% (15/555) had diabetes, 3.2% (18/555) had heart disease, and 8.5% (47/555) were anemic. 233 (42%) respondents complained of back pain, and 161 (29%) of the respondents complained of insomnia. Stress was associated with higher workload, sleep deprivation, and dissatisfaction in the relationship with colleagues, with income, and with the program. In multivariate analysis, the following factors were significantly associated with stress: female gender, dissatisfaction with working environment, and facing work-related, academic, and family stressors. CONCLUSIONS: The majority of medical residents in Jordanian hospitals felt nervous and stressed. Conducting stress management programs during residency and improving the work environment are strongly recommended.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".