An international survey examining the impact of the COVID-19 pandemic on telehealth use among mental health professionals
Bibliographic record
Abstract
BACKGROUND: COVID-19 has profoundly affected the work of mental health professionals with many transitioning to telehealth to comply with public health measures. This large international study examined the impact of the pandemic on mental health clinicians' telehealth use. METHODS: This survey study was conducted with mental health professionals, primarily psychiatrists and psychologists, registered with WHO's Global Clinical Practice Network (GCPN). 1206 clinicians from 100 countries completed the telehealth section of the online survey in one of six languages between June 4 and July 7, 2020. Participants were asked about their use, training (i.e., aspects of telehealth addressed), perceptions, and concerns. OUTCOMES: Since the pandemic onset, 1092 (90.5%) clinicians reported to have started or increased their telehealth services. Telephone and videoconferencing were the most common modalities. 592 (49.1%) participants indicated that they had not received any training. Clinicians with no training or training that only addressed a single aspect of telehealth practice were more likely to perceive their services as somewhat ineffective than those with training that addressed two or more aspects. Most clinicians indicated positive perceptions of effectiveness and patient satisfaction. Quality of care compared to in-person services and technical issues were the most common concerns. Findings varied by WHO region, country income level, and profession. INTERPRETATION: Findings suggest a global practice change with providers perceiving telehealth as a viable option for mental health care. Increasing local training opportunities and efforts to address clinical and technological concerns is important for meeting ongoing demands.
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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 | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".