An Estimated Prevalence of Cognitive Behavioral Therapy for Psychosis (CBTp) Providers in the United States and Canada
Bibliographic record
Abstract
Introduction: Cognitive Behavioral Therapy for psychosis (CBTp) is an evidence-based treatment for psychotic disorders. Despite its evidence base, CBTp is estimated to be widely unavailable in the U.S. and Canada. Previous research suggests that there is variation in CBTp training for mental health professionals. Methods: We designed a questionnaire to assess the prevalence of CBTp trained providers in the U.S. and Canada and to assess the characteristics of trainers and their training methods to better understand the state of the field with regard to CBTp training. Providers who train others in CBTp were sampled from professional networks, and a further snowball sample was collected from these trainers. Data Analysis: Descriptive statistics were used to analyze responses, and the frequency and percent of the sample were calculated for each answer option. Means, standard deviations, and ranges were calculated for numerical responses. The prevalence of CBTp trained mental health providers was calculated using the total number of trainees as provided by respondents added with the number of respondents currently practicing CBTp, and U.S. and Canadian employment statistics for mental health provider occupations. An accessibility estimate was calculated using our CBTp trained provider total, prevalence of psychotic disorders in the U.S. and Canada from other studies, and population data for each country. Results: Based on questionnaire results, we estimate that a combined 0.54% of mental health providers in the U.S. and Canada are trained in CBTp. We estimate there are 10.8 – 21.4 CBTp trained providers for every 10,000 people with a psychotic disorder in the U.S. and Canada. Survey results showed several differences in training approaches, settings, funding sources, and geographic location. Discussion: This prevalence suggests that there is very little penetration of CBTp into the mental health provider community in the U.S. and Canada. Accessibility is low among individuals with psychotic disorders, and trainings are largely dependent on location, suggesting that CBTp accessibility is limited in rural areas. Conclusion: This estimate is higher than previous estimates of prevalence of CBTp trained providers but still suggests very little penetration of CBTp in the mental health workforce. Future studies should focus on country and regional differences in trainings and employ more rigorous sampling methods to provide a more robust prevalence estimate.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".