To use or not to use: Clinicians' perceptions of telemental health.
Bibliographic record
Abstract
Equal access to mental health services is necessary for healthy individuals and communities. However, due to geographical distances and other barriers, some clients cannot easily access mental health professionals. Technologies such as videoconferencing for clinical purposes (i.e., telemental health) may help to bridge these gaps to connect clients and clinicians at geographically diverse locations. However, despite its potential utility, telemental health has not been widely adopted in Canada. This study is an exploratory investigation into mental health professionals’ attitudes toward telemental health, factors that affect the frequency with which they use this technology, and their perceptions of individual characteristics which make clients more or less suitable candidates for telemental health. This study has a particular focus on remote and rural and Operational Stress Injury (OSI) contexts. One hundred and sixty mental health workers across Canada participated in an online survey, and twenty-five mental health workers from Operational Stress Injury clinics across Canada participated in in-person interviews. The data were examined using qualitative and quantitative analysis methods. Findings suggest that mental health workers have overall positive attitudes toward the use of telemental health – particularly for clients in remote and rural locations. Additionally, receiving training in telemental health, being in the mental health field for longer, and perceiving the technology as easy to use are associated with more frequent use of telemental health. Finally, clinicians reported specific client characteristics which they perceive to make some clients unsuitable candidates for telemental health. Implications of these findings and directions for future research are discussed.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".