Using an Electronic Tablet to Assess Patients’ Home Environment by Videoconferencing Prior to Hospital Discharge: Protocol for a Mixed-Methods Feasibility and Comparative Study
Bibliographic record
Abstract
BACKGROUND: Occupational therapists working in hospitals are usually involved in discharge planning to assess patients' safety and autonomy upon returning home. However, their assessment is usually done at the hospital due to organizational and financial constraints. The lack of visual data about the patients' home may thus reduce the appropriateness and applicability of the support recommended upon discharge. Although various technological tools such as mobile devices (mobile health) are promising methods for home-based distance assessment, their application in hospital settings may raise several feasibility issues. To our knowledge, their usefulness and added value compared to standard procedure have not been addressed yet in previous studies. Moreover, several feasibility issues need to be explored. OBJECTIVE: This paper aims to (1) document the clinical feasibility of using an electronic tablet to assess the patient's home environment by mobile videoconferencing and (2) explore the added value of using mobile videoconferencing, compared to the standard procedure. METHODS: A feasibility and comparative study using a mixed-methods (convergent) design is currently undergoing. Six occupational therapists will assess the home environment of their patients in the hospital setting: they will first perform a semistructured interview (a) and then use mobile videoconferencing (b) to compare "a versus a+b." Interviews with occupational therapists and patients and their caregivers will further explore the advantages and disadvantages of mobile videoconferencing. Two valid tools are used (the Canadian Measure of Occupational Performance and the telehealth responsivity questionnaire). Direct and indirect time is also collected. RESULTS: The project was funded in the spring of 2016 and authorized by the ethics committee in February 2017. Enrollment started in April 2017. Five triads (n=4 occupational therapists, n=5 clients, n=5 caregivers) have been recruited until now. The experiment is expected to be completed by April 2019 and analysis of the results by June 2019. CONCLUSIONS: Mobile videoconferencing may be a familiar and easy solution for visualizing environmental barriers in the home by caregivers and clinicians, thus providing a promising and inexpensive option to promote a safe return home upon hospital discharge, but clinical feasibility and obstacles to the use of mobile videoconferencing must be understood. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11674.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".