Development of a Web-Based Monitoring System for Power Tilt-in-Space Wheelchairs: Formative Evaluation (Preprint)
Bibliographic record
Abstract
BACKGROUND A power tilt-in-space wheelchair meets many clinical purposes, including pressure management, increased postural control, and pain management. However, there is a significant gap between the use of tilt as recommended by clinicians and its actual usage. A Web-based electronic health (eHealth) intervention, including a goal setting, monitoring, reminder, and feedback system of the use of power tilt-in-space wheelchairs was developed. The intervention incorporates behavior change principles to promote optimal use of tilt and to improve clinical postprocurement follow-up. OBJECTIVE This study aimed to conduct a formative evaluation of the intervention prototype to pinpoint the functionalities needed by end users, namely, power wheelchair users and clinicians. METHODS On the basis of an evaluation framework for Web-based eHealth interventions, semistructured interviews were conducted with power wheelchair users and clinicians. A content analysis was performed with a mix of emerging and a priori concepts. RESULTS A total of 5 users of power tilt-in-space wheelchairs and 5 clinicians who had experience in the field of mobility aids aged 23 to 55 years were recruited. Participants found the Web interface and the physical components easy to use. They also appreciated the reminder feature that encourages the use of the tilt-in-space and the customization of performance goals. Participants requested improvements to the visual design and learnability of the Web interface, the customization of reminders, feedback about specific tilt parameters, and the bidirectionality of the interaction between the user and the clinician. They thought the current version of the intervention prototype could promote optimal use of the tilt and improve clinical postprocurement follow-up. CONCLUSIONS On the basis of the needs identified by power wheelchair users and clinicians regarding the prototype of a power tilt-in-space wheelchair monitoring system, 3 main directions were defined for future development of the intervention. Further research with new wheelchair users, manual tilt-in-space wheelchairs, various age groups, and family caregivers is recommended to continue the formative evaluation of the prototype.
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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 | 0.036 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".