Attitudes to antipsychotics: a multi-site survey of Canadian psychiatry residents
Bibliographic record
Abstract
Purpose The purpose of this paper is to identify the training needs of the next generation of psychiatrists, and barriers in prescribing first-generation antipsychotics (FGAs), long-acting injectable (LAIs) antipsychotics and clozapine. Design/methodology/approach An electronic survey was sent to psychiatry residents ( N = 75/288, 26 percent) at four Canadian residency programs in late December 2017. The survey was based on an instrument originally developed at the University of Cambridge and consisted of 31 questions in 10 content domains. Findings Nearly 80 percent of residents were aware that FGAs and second-generation antipsychotics (SGAs) have similar efficacy. However, extra-pyramidal symptoms and lack of training experience were the leading concerns associated with the prescribing of FGAs. Although over 90 percent of residents felt confident about initiating an oral SGA as a regular medication, only 40 percent did so with FGAs. Confidence with initiating LAIs and clozapine was 60 and 61 percent, respectively. Practical implications The survey highlights the need for better training in the use of FGAs, clozapine and LAIs. These medications can be effectively used in providing patients with the most appropriate evidence-based treatment options to improve treatment outcomes, while ensuring that these resources are not lost to the future generations of psychiatrists. Originality/value The survey may be the first of its kind to assess antipsychotic prescribing attitudes in Canadian psychiatry residents in multiple sites.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".