Access to and Waiting Time for Psychiatrist Services in a Canadian Urban Area: A Study in Real Time
Bibliographic record
Abstract
OBJECTIVE: To obtain improved quality information regarding psychiatrist waiting times by use of a novel methodological approach in which accessibility and wait times are determined by a real-time patient referral procedure. METHOD: An adult male patient with depression was referred for psychiatric assessment by a family physician. Consecutive calls were made to all registered psychiatrists (n = 297) in Vancouver. A semistructured call procedure was used to collect information about the psychiatrists' availability for receipt of this and similar referrals, identify factors that affect psychiatrist accessibility, and determine the availability of cognitive-behavioural therapy (CBT). RESULTS: Efforts were made to contact 297 psychiatrists and 230 (77%) were reached successfully. Among the 230 psychiatrists contacted, 160 (70%) indicated that they were unable to accept the referral. Although 70 (30%) indicated that they might be able to consider accepting a referral, 64 (91% of those who would consider accepting the referral) indicated that they would need to review detailed, written referral information and could not provide estimates of the length of wait times if the patient was to be accepted. Only 6 (3% of the 230 psychiatrists contacted) offered immediate appointment times and their wait times ranged from 4 to 55 days. When asked whether they could provide CBT, most (56%) psychiatrists in clinical practice answered maybe. CONCLUSIONS: Substantial barriers exist for family physicians attempting to refer patients for psychiatric referral. Consolidated efforts to improve access to psychiatric assessment are needed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".