Lifestyle Characteristics of Psychiatric Outpatients
Bibliographic record
Abstract
OBJECTIVE: To describe lifestyle characteristics and associated health issues among psychiatric outpatients in 3 diagnostic categories: schizophrenia, bipolar disorder, and anxiety and (or) depression. METHOD: A series of patients (n=182) attending 3 outpatient mental health clinics in Calgary were administered a set of items and instruments to assess: social support, dietary habits, substance use, exercise, and recreational pursuits. In addition, clinical and laboratory parameters including body mass index (BMI) and lipid and glucose levels were compared when available. RESULTS: Satisfaction with social support was comparable across the 3 diagnostic categories. About two-thirds reported predominantly sedentary routine daily activities. No significant differences in fatty food intake were identified, or for other dietary habits. There were no significant differences between diagnostic groups and total cholesterol, and high-density lipoprotein or low-density lipoprotein levels. According to their BMI, 74% of the entire sample could be described as overweight and 38% as obese; again, differences between the 3 diagnostic categories were not observed. CONCLUSION: Unhealthy lifestyle issues are not restricted to any specific diagnostic group. These data identify a compelling need to develop ameliorative intervention strategies for psychiatric outpatients; however, we could not identify a basis for targeting such interventions specifically in relation to diagnosis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".