Implementation of a tablet-based care prevention programme—information and communication technology-integrated occupational therapy for older adults with cognitive decline
Bibliographic record
Abstract
OBJECTIVE: This case report examines the implementation of a tablet-based care prevention program for an older adult with cognitive decline, aiming to enhance Instrumental Activities of Daily Living (IADL) and social participation through Information and Communication Technology (ICT)-integrated occupational therapy. CASE PRESENTATION: The participant was an 80-year-old male diagnosed with mild cognitive impairment (MCI), with a history of glaucoma and hypertension. Despite prior exposure to tablets, he lacked confidence in their use. He enrolled in a community-based ICT support program to improve daily activity engagement. Intervention: A four-month intervention, consisting of two sessions per month, was conducted. Initial assessments included the Mini-Mental State Examination (MMSE), the Mobile Device Proficiency Questionnaire-Japanese (MDPQ-J), and the Canadian Occupational Performance Measure (COPM) and the World Health Organization Quality of Life-BREF (WHOQOL-BREF). The intervention involved guided tablet use, environmental modifications (tablet stand and stylus adaptation), and training in digital mapping and drawing applications. OUTCOMES: After the intervention, the MDPQ-J score improved from 9.58/40 to 13.96/40, and COPM satisfaction scores increased for both digital mapping (4/10 to 6/10) and drawing (5/10 to 7/10). The WHOQOL-BREF score increased from 66 to 70. The participant demonstrated improved ICT confidence and expanded daily activity engagement. CONCLUSION: This case highlights the potential of ICT-integrated occupational therapy in enhancing IADL among community-dwelling older adults with cognitive decline. Future research should focus on both testing and developing structured ICT-based interventions to further support social participation and daily independence.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".