Studies Involving People With Dementia and Touchscreen Technology: A Literature Review
Bibliographic record
Abstract
BACKGROUND: Devices using touchscreen interfaces such as tablets and smartphones have been highlighted as potentially suitable for people with dementia due to their intuitive and simple control method. This population experience a lack of meaningful, engaging activities, yet the potential use of the touchscreen format to address this issue has not been fully realized. OBJECTIVE: To identify and synthesize the existing body of literature involving the use of touchscreen technology and people with dementia in order to guide future research in this area. METHODS: A systematized review of studies in the English language was conducted, where a touchscreen interface was used with human participants with dementia. RESULTS: A total of 45 articles met the inclusion criteria. Four questions were addressed concerning (1) the context of use, (2) reasons behind the selection of the technology, (3) details of the hardware and software, and (4) whether independent use by people with dementia was evidenced. CONCLUSIONS: This review presents an emerging body of evidence demonstrating that people with dementia are able to independently use touchscreen technology. The intuitive control method and adaptability of modern devices has driven the selection of this technology in studies. However, its primary use to date has been as a method to deliver assessments and screening tests or to provide an assistive function or cognitive rehabilitation. Building on the finding that people with dementia are able to use touchscreen technology and which design features facilitate this, more use could be made to deliver independent activities for meaningful occupation, entertainment, and fun.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".