A survey of postdoctoral training in rehabilitation psychology in the United States and Canada: 2019.
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: Survey psychology postdoctoral training programs involving patients with disability receiving rehabilitation services, and compare with similar data from 2007. RESEARCH METHOD/DESIGN: = 92). RESULTS: Programs reported having a primary rehabilitation involvement (42%), a secondary involvement (26%), or an optional involvement (23%). Programs were based in university settings (27%), VA/DoD settings (35%), or private/public health care settings (38%). A total of 433 faculty and 308 residents were involved in these programs. Fifty percent (50%) of programs had faculty with American Board of Rehabilitation Psychology (ABRP) certification, while 62% of programs had faculty with American Board of Clinical Neuropsychology (ABCN) certification. On average, programs formally taught 58% of the ABRP competencies. CONCLUSIONS: Compared to 2007, there has been a 200% increase in the number of training programs with rehabilitation involvement. However, there has been an overall decrease in the variety of populations with which residents work, and an overall decrease in the number of ABRP competencies that are formally taught, so that training has become more focused on specific populations and specific competencies to the exclusion of others. Many rehabilitation patients and teams receive services from psychologists whose professional concentration is not primarily in rehabilitation psychology, and many psychology residents involved with rehabilitation populations do not receive comprehensive training in rehabilitation psychology. There is an opportunity for rehabilitation psychologists to collaborate with these programs to enhance competent services to persons with disability. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".