Social determinants of health and depression in adults presenting to the emergency department
Bibliographic record
Abstract
OBJECTIVE: To estimate the extent to which social determinants of health (SDH) predict levels of depression in adults presenting to the emergency department (ED) with an acute mental health crisis. DESIGN: Secondary data analysis. SETTING: St Paul's Hospital, an urban tertiary care hospital in Vancouver, BC. PARTICIPANTS: Patients 19 years and older presenting to the ED with an acute mental health crisis. MAIN OUTCOME MEASURES: tests. The extent to which SDH variables predicted depression scores, as measured by the Patient Health Questionnaire-9 (PHQ-9), was determined using linear regression. RESULTS: The primary study had 202 participants. Data for the 156 (77%) participants who completed the PHQ-9 were assessed in this secondary analysis. In this sample, 60% of participants identified as men, 37% as women, and 4% as other. The mean (SD) age was 39.1 (13.8) years, with most participants identifying as white (65%) or Indigenous (18%). Thirty-seven percent had a high school diploma or less education, and 72% reported being unemployed. Identifying as a woman, lack of access to clean drinking water, poor food security, feeling unsafe, little structured use of time, lack of a sense of community, and dissatisfaction with housing significantly predicted higher depression scores. Overall, 59% of respondents met the criteria for moderately severe or severe depression (PHQ-9 score ≥ 15), with 37% of those reporting thoughts of suicide nearly every day for the past 2 weeks. CONCLUSION: This study demonstrates the importance of screening for both depression and SDH in the ED. Because the ED often does not have the capacity to address appropriate levels of follow-up for this population, this study has important implications for primary care. Developing a clear pathway of follow-up support for people with depression and SDH risk factors will be critical to optimize patient outcomes, promote patient safety, enhance patient satisfaction, and optimize the use of resources between the ED and primary care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".