Usability, Usefulness, and Acceptance of a Novel, Portable Rehabilitation System (mRehab) Using Smartphone and 3D Printing Technology: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Smart technology use in rehabilitation is growing and can be used remotely to assist clients in self-monitoring their performance. With written home exercise programs being the commonly prescribed form of rehabilitation after discharge, mobile health technology coupled with task-oriented programs can enhance self-management of upper extremity training. In the current study, a rehabilitation system, namely mRehab, was designed that included a smartphone app and 3D-printed household items such as mug, bowl, key, and doorknob embedded with a smartphone. The app interface allowed the user to select rehabilitation activities and receive feedback on the number of activity repetitions completed, time to complete each activity, and quality of movement. OBJECTIVE: This study aimed to assess the usability, perceived usefulness, and acceptance of the mRehab system by individuals with stroke and identify the challenges experienced by them when using the system remotely in a home-based setting. METHODS: A mixed-methods approach was used with 11 individuals with chronic stroke. Following training, individuals with stroke used the mRehab system for 6 weeks at home. Each participant completed surveys and engaged in a semistructured interview. Participants' qualitative reports regarding the usability of mRehab were integrated with their survey reports and quantitative performance data. RESULTS: Of the 11 participants, 10 rated the mRehab system between the 67.5th and 97.5th percentile on the System Usability Scale, indicating their satisfaction with the usability of the system. Participants also provided high ratings of perceived usefulness (mean 5.8, SD 0.9) and perceived ease of use (mean 5.3, SD 1.5) on a 7-point scale based on the Technology Acceptance Model. Common themes reported by participants showed a positive response to mRehab with some suggestions for improvements. Participants reported an interest in activities they perceived to be adequately challenging. Some participants indicated a need for customizing the feedback to be more interpretable. Overall, most participants indicated that they would like to continue using the mRehab system at home. CONCLUSIONS: Assessing usability in the lived environment over a prolonged duration of time is essential to identify the match between the system and users' needs and preferences. While mRehab was well accepted, further customization is desired for a better fit with the end users. TRIAL REGISTRATION: ClinicalTrials.gov NCT04363944; https://clinicaltrials.gov/ct2/show/NCT04363944.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".