Changes in the Clinical Practice of Mental Health Service Providers Throughout the COVID-19 Pandemic: Longitudinal Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic impacted the practices of most mental health providers and resulted in a rapid transition to providing telemental health services, changes that were likely related to stay-at-home policies as well as increased need for services. OBJECTIVE: The aim of this study was to examine whether these changes to practice have been sustained over time throughout the course of the COVID-19 pandemic and whether there are differences among mental health provider type and setting. We hypothesized that there would be an increase in the number of patients seen in person after the initial surge of the pandemic in spring 2020 and subsequent discontinuation of stay-at-home policies, though with continued implementation of telemental health services across settings. METHODS: This study surveyed 235 of the 903 mental health providers who responded to a survey in spring 2020 (Time point 1) and at a 1-year follow-up in spring 2021 (Time point 2). Differences in practice adjustments, factors related to telemental health, and number of patients seen were examined across provider type (social worker, psychologist, neuropsychologist) and setting (academic medical center [AMC], community mental health, private practice, and Veterans Affairs hospital). RESULTS: From Time point 1 to Time point 2, there was a small but significant increase in the overall number of providers who were implementing telehealth (191/235, 81% to 204/235, 87%, P=.01) and there was a significant decline in canceled or rescheduled appointments (25%-50% in 2020 to 3%-7% in 2021, P<.001). Psychologists and providers working at AMCs reported decreased difficulty with telehealth implementation (P<.001), and providers working at AMCs and in private practice settings indicated they were more likely to continue telehealth services beyond spring 2021 (P<.001). The percent of time working remotely decreased overall (78% to 59%, P<.001), which was most notable among neuropsychologists and providers working at an AMC. There was an overall increase in the average number of patients seen in person per week compared with earlier in the pandemic (mean 4.3 to 8.7, P<.001), with no change in the number of patients seen via telehealth (mean 9.7 to 9.9, P=.66). CONCLUSIONS: These results show that the rapid transition to telemental health at the onset of the COVID-19 pandemic in spring 2020 was sustained over the next year, despite an overall increase in the number of patients seen in person. Although more providers reported returning to working on-site, over 50% of providers continued to use a hybrid model, and many providers reported they would be more likely to continue telemental health beyond spring 2021. This suggests the continued importance and reliance on telemental health services beyond the acute pandemic phase and has implications for future policies regulating the availability of telemental health services to patients.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".