Telehealth Student Experiences and Learning: A Scoping Review
Bibliographic record
Abstract
Telehealth as a service delivery model is increasing in popularity. Knowledge and use of telehealth technology will be a new mandatory learning outcome in occupational therapy curriculums with the implementation of the 2018 Accreditation Council for Occupational Therapy Education standards. However, it is not known how healthcare programs are currently incorporating telehealth into education or which methods of telehealth education are most effective. This study addressed this gap in the literature using Arksey and O’Malley’s five-step methodological process to conduct a scoping review to examine the student experience of delivering healthcare services via telehealth and related learning outcomes. The scoping review encompassed eight databases with inclusion criteria of articles that discussed student learning outcomes, telehealth or telemedicine, and the student experience of delivering telehealth services. The research team screened 955 articles, reviewed 24 full-text articles, and came to a consensus on six articles to include in the review. Findings suggested a high level of student satisfaction related to the experience of delivering healthcare services using telehealth. Results indicated that students have a variety of related learning outcomes including increased knowledge of their professional practice, increased cultural competence, increased knowledge of how to work on interprofessional teams, and increased knowledge and skill in the use of technology. The review revealed a need for objective measures to examine specific student learning outcomes related to utilizing telehealth as a service delivery method. Additionally, the review indicated a need for future research to identify best educational practices for teaching students about telehealth.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 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".