Relationship Between Depression and Stress Coping Ability Among Residents in Japan: A Two-Year Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Depression among medical residents is a critical issue. The early detection of depression and provision of appropriate care is necessary for fostering healthy conditions during clinical training. To investigate whether Sense of Coherence (SOC), an indicator of stress coping ability, could be a predictor of depression 2 years after the start of clinical training, we conducted a national longitudinal study. METHODS: We distributed self-administered questionnaires to residents in 251 postgraduate educational hospitals just before the start of their clinical training. The questionnaire contained the Center for Epidemiologic Studies Depression (CES-D) scale (a screening tool for depression), the SOC scale, and demographic factors. After 2 years, we distributed questionnaires to residents who responded to the first survey. The second questionnaire contained the CES-D scale and questions about working conditions. We categorized respondents into three groups according to their SOC score and analyzed the relationship between SOC groups (low, middle, high) and depressive symptoms on the follow-up survey. RESULTS: In total, 1,738 of 2,935 residents (59.2%) responded to the first survey. Of these, 1,169 residents (67.3%) also responded to the follow-up survey. A total of 169 residents were excluded because they screened positive for depressive symptoms at the time of the first survey. On the follow-up survey, 187 residents (19.5%) had new-onset depressive symptoms: 33.3% in the low SOC group, 18.2% in the middle SOC group, and 11.4% in the high SOC group (P < 0.01). Compared with the high SOC group, the odds ratio for new-onset depressive symptoms in the low SOC group was 2.04 (95% confidence interval, 1.02 - 4.05) after adjusting for demographic factors, baseline CES-D score, and mean working time. CONCLUSIONS: SOC score is significantly associated with future depressive symptoms among residents after 2 years. Residents in the low SOC group had a 2-fold higher risk of future depressive symptoms than those in the high SOC group. The SOC scale might be a useful predictor of future depression and allow for the provision of appropriate support to residents during clinical training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".