Sensorimotor and Cognitive Abilities Associated With Touchscreen Tablet App Performance to Support Self-Management of Type 2 Diabetes
Bibliographic record
Abstract
IMPORTANCE: Self-management programs (facilitated by mobile devices) may improve health and prevent secondary complications for older adults with diabetes. However, older adults may have difficulties using mobile devices because of neuropathy or cognitive dysfunction. OBJECTIVE: To identify sensorimotor and cognitive abilities associated with touchscreen tablet app performance to support self-management of diabetes in older adults. DESIGN: Cross-sectional study. SETTING: Outpatient Center for Successful Aging With Diabetes. PARTICIPANTS: Forty-five older adults with Type 2 diabetes. OUTCOMES AND MEASURES: Dexterity (Purdue Pegboard Test), touch sensation (Semmes-Weinstein monofilaments), pinch strength (pinch gauge), cognition (Montreal Cognitive Assessment), and executive functioning (Trail Making Test) were assessed. Two apps were then used: Dexteria and SuCare. Demographic data, prior mobile device use, and diabetes severity (hemoglobin A1C [HbA1C]) were collected. RESULTS: Age and HbA1C accounted for 29.8% and 9.7%, respectively, of the total variance of Dexteria performance time (dominant hand). Dexterity (dominant hand) accounted for an additional 5.4% of the total variance of 45.1%, F(4, 40) = 10.021, p < .001. Prior mobile device use, age, and diabetes severity accounted for 6.4%, 11.8%, and 26.4%, respectively, of the total variance of SuCare performance time. Executive functioning and dominant-hand dexterity accounted for an additional 9.5% and 9.4%, respectively, of the total variance of 61.0%, F(5, 39) = 14.75, p < .001. CONCLUSIONS AND RELEVANCE: Beyond age and diabetes severity, executive functioning and dominant-hand dexterity contributed to app performance, highlighting the importance of diabetes self-management. These findings may help determine suitable candidates for tablet use for self-management. WHAT THIS ARTICLE ADDS: App performance is explained by the executive functioning and dexterity of older adults with Type 2 diabetes. These factors, in addition to age and diabetes severity, should be taken into consideration by occupational therapy practitioners in future mobile self-management programs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".