Clinical and Educational Telepsychiatry Applications: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Telepsychiatry in the form of videoconferencing brings enormous opportunities for clinical care, education, research, and administration. Focusing on videoconferencing, we reviewed the telepsychiatry literature and compared telepsychiatry with services delivered in person or through other technologies. METHODS: We conducted a comprehensive review of telepsychiatry literature from January 1, 1965, to July 31, 2003, using the terms telepsychiatry, telemedicine, videoconferencing, effectiveness, efficacy, access, outcomes, satisfaction, quality of care, education, empowerment, and costs. We selected studies for review if they discussed videoconferencing for clinical and educational applications. RESULTS: Telepsychiatry is successfully used for various clinical services and educational initiatives. Telepsychiatry is feasible, increases access to care, enables specialty consultation, yields positive outcomes, allows reliable evaluation, has few negative aspects in terms of communication, generally satisfies patients and providers, facilitates education, and empowers parties using it. Data are limited with regard to clinical outcomes and cost-effectiveness. CONCLUSIONS: Telepsychiatry is effective. More short- and long-term quantitative and qualitative research is warranted on clinical outcomes, predictors of satisfaction, costs, and educational outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it