A FASTER Approach to Developing and Evaluating a Smart Insole Technology for Persons Living with Early‐Stage Dementia to Sustain Out‐Of‐Home Participation
Bibliographic record
Abstract
BACKGROUND: Persons living with dementia or cognitive impairment (PLWD/CI) often experience barriers to out-of-home participation (i.e., places outside home or in public) due to cognitive inaccessibility, risks or anxieties related to wandering, and care partners' safety concerns - which can impede health and quality of life. Technology offers the potential to support PLWD/CI in sustaining out-of-home participation, but real-world evaluations within complex, dynamic care ecosystems are necessary to ensure safety and effectiveness. The "Framework for Accelerated and Systematic Technology-based intervention development and Evaluation Research" (FASTER) was created to support the development and evaluation of interventions from conception to real-world use. The aim is to illustrate how FASTER was applied to a novel intervention encompassing a smart shoe insole technology designed to support out-of-home participation for PLWD/CI by enabling tracking, safety alerts, and care collaboration with care partners. METHOD: The FASTER approach includes the following phases: (1) Development, (2) Progressive Usability and Feasibility Evaluation, and (3) Phased Evaluation and Implementation. FASTER was applied to developing and evaluating the smart insole technology for PLWD/CI in real-world use contexts. RESULT: Phase 1 collaborated with the commercial partner to conceptualize the intervention design vis à vis technology design features and use cases, and model theoretically- and evidence-driven processes and outcomes. Six researchers conducted mixed-method pilot usability testing by completing structured use cases in real-world settings. Technical and design issues were identified and evaluation methods were refined to optimize usability, reliability, and mitigate safety risks, for subsequent evaluation with PLWD/CI and care partners. Phase 2 employed a small-scale, mixed-method multiple case study design to evaluate technology usability and feasibility, and primary outcomes (i.e., PLWD/CI's out-of-home participation, dyadic care collaboration) with 3 care ecosystems. Future research will adapt and scale the evaluation methodology for Phase 3, involving implementation and evaluation in a larger cross-Canadian study in Quebec, Ontario, and British Columbia. CONCLUSION: FASTER is a systematic, iterative, and participatory approach to developing, evaluating, refining, and integrating technology-based interventions. This presentation highlights the application of FASTER using a real-world example, showcasing its value for both technological and health/social outcomes, including out-of-home participation and collaborative caring for PLWD/CI.
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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 | 0.054 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".