The Transition of Academic Mental Health Clinics to Telehealth During the COVID-19 Pandemic
Bibliographic record
Abstract
OBJECTIVE: A consortium of 8 academic child and adolescent psychiatry programs in the United States and Canada examined their pivot from in-person, clinic-based services to home-based telehealth during the COVID-19 pandemic. The aims were to document the transition across diverse sites and to present recommendations for future telehealth service planning. METHOD: Consortium sites completed a Qualtrics survey assessing site characteristics, telehealth practices, service use, and barriers to and facilitators of telehealth service delivery prior to (pre) and during the early stages of (post) the COVID-19 pandemic. The design is descriptive. RESULTS: All sites pivoted from in-person services to home-based telehealth within 2 weeks. Some sites experienced delays in conducting new intakes, and most experienced delays establishing tele-group therapy. No-show rates and use of telephony versus videoconferencing varied by site. Changes in telehealth practices (eg, documentation requirements, safety protocols) and perceived barriers to telehealth service delivery (eg, regulatory limitations, inability to bill) occurred pre-/post-COVID-19. CONCLUSION: A rapid pivot from in-person services to home-based telehealth occurred at 8 diverse academic programs in the context of a global health crisis. To promote ongoing use of home-based telehealth during future crises and usual care, academic programs should continue documenting the successes and barriers to telehealth practice to promote equitable and sustainable telehealth service delivery in the future.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".