Navigating Uncharted Waters: Considerations for Training Clinics in the Rapid Transition to Telepsychology and Telesupervision During COVID-19
Bibliographic record
Abstract
The COVID-19 pandemic offers both challenges and opportunities for those who provide and receive psychological services. For training clinics tasked with educating the next generation of health service psychologists, providing vital mental health care to the community, and conducting clinical research, the pandemic offers an opportunity to consider how best to fulfill these crucial missions during a time of global uncertainty. The present paper reviews the recent, rapid move to telepsychology among North American university training clinics in response to the COVID-19 pandemic and offers relevant suggestions for mental health service providers rapidly transitioning to telepsychology moving forward. Data summarizing the response of university training clinics in health service psychology in the United States and Canada to physical distancing guidelines are presented, and considerations regarding best practices in service delivery and supervision via telepsychology are provided. While the present data focus on North American training clinics, the suggestions offered are relevant to any clinic tasked with providing high quality services and training mental health providers via telepsychology, particularly during the COVID-19 pandemic. Given the growing emphasis within health service psychology on increasing access to mental health services via telepsychology prior to the pandemic, as well as the benefits to psychology trainees in gaining competence in this valuable form of service delivery, this paper aims to provide timely guidance around the benefits, risks, and practical considerations regarding the maintenance of effective clinical care in training settings when rapidly implementing telepsychology.
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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 | 0.000 | 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 | 0.000 |
| 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".