Time of Day Influences Nonattendance at Urgent Short-Term Mental Health Unit in Victoria, British Columbia
Bibliographic record
Abstract
OBJECTIVES: To identify the patient profile of first-time no-shows (FTNS) and to examine which process variables predict FTNS. METHOD: We developed a questionnaire exploring vriables that might impact attendance. Of 779 referrals over 9 months, all FTNS (n = 60) and a sample of randomly selected control subjects (n = 60) completed the questionnaire. RESULTS: The FTNS rate was 7.7%. A set of 10 variables predicted FTNS at 80% accuracy. Most significant was our finding that "time of day of first appointment" showed a novel and practical difference between FTNS and control subjects. Patients were 3.6 times more likely to show for first appointments scheduled in the afternoon. CONCLUSIONS: Simply making first appointments in the afternoon could significantly decrease FTNS incidence.
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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 | 0.002 | 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 | 0.001 |
| 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 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".