Profiles of quality of life among patients using emergency departments for mental health reasons
Bibliographic record
Abstract
Abstract Background This study identified profiles associated with quality of life (QoL) and sociodemographic and clinical characteristics of patients using emergency departments (ED) for mental health reasons and associated these profiles with patient service use. Methods Recruited in four Quebec (Canada) ED networks, 299 patients with mental disorders (MD) were surveyed from March 1st, 2021, to May 13th, 2022. Data from medical records were collected and merged with survey data. Cluster analysis was conducted to identify QoL profiles, and comparison analyses used to assess differences between them. Results Four QoL profiles were identified: (1) Unemployed or retired men with low QoL, education and household income, mostly having substance-related disorders and bad perceived mental/physical health conditions; (2) Men who are employed or students, have good QoL, high education and household income, the least personality disorders, and fair perceived mental/physical health conditions; (3) Women with low QoL, multiple mental health problems, and very bad perceived mental/physical health conditions; (4) Mostly women with very good QoL, serious MD, and very good perceived mental/physical health conditions. Conclusion The profiles with the highest QoL (4 and 2) had better overall social characteristics and perceived their health conditions as superior. Profile 4 reported the highest level of satisfaction with services used. To improve QoL programs like permanent supportive housing, individual placement and support might be better implemented, and satisfaction with care more routinely assessed in response to patient needs – especially for Profiles 1 and 3, that show complex health and social conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.112 | 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".