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Record W4415710454 · doi:10.2196/78229

Examining Technology Perspectives of Older Adults With Mild Cognitive Impairment: Scoping Review

2025· review· en· W4415710454 on OpenAlexvenueno aff
Stephen Isbel, Blooma John, Ramanathan Subramanian, Nathan M. D’Cunha

Bibliographic record

VenueJMIR Aging · 2025
Typereview
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsFeelingUsabilityAffect (linguistics)CognitionAging in placeWork (physics)

Abstract

fetched live from OpenAlex

Background: Mild cognitive impairment (MCI) affects up to 20% of people older than the age of 65 years. The global incidence of MCI is increasing, and technology is being explored for early intervention. Theories of technology adoption predict that useful and easy-to-use solutions will have higher rates of adoption; however, these models do not specifically consider older adults with cognitive impairments or the unique human-computer interaction challenges posed by MCI. There are gaps in understanding the combined impacts of aging and cognitive impairment on factors affecting technology adoption for older adults with MCI, and it is not clear how MCI impacts human-computer interaction and device and interaction modality preferences in this population. Objective: This study aimed to collate perspectives from older adults with MCI about technology solutions proposed for them, to understand whether solutions are perceived as useful, easy to use, and what changes are suggested. It also identifies which devices and interaction modalities are preferred, and other factors that may affect usage and adoption. Methods: This scoping review was completed according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. A consistent search was performed across 9 electronic databases (ACM Digital Library, EBSCOhost CINAHL Plus with Full Text, EBSCOhost Computers and Applied Sciences Complete, Google Scholar, JMIR Publications, IEEE Xplore, EBSCOhost MEDLINE, Scopus, and Web of Science Core Collection) for studies published between January 1, 2014, and May 1, 2024. Extracted data were analyzed using inductive thematic analysis. Results: We identified 4271 studies, and after the removal of duplicates and screening, 83 studies were included for data extraction. Inductive thematic analysis of feedback from older adults with MCI about technology solutions proposed for them identified five themes: (1) purpose and need, (2) solution design and ease of use, (3) self-impression, (4) lifestyle, and (5) interaction modality. Solutions were perceived as useful, even though gaps in functional support exist; however, they were not perceived as entirely easy to use due to issues related to usability and user experience. Devices that are lightweight, portable, familiar, and have large screens are preferred, as is multimodal interaction-particularly speech, visual or text, and touch. Conclusions: Using technology can create feelings that positively or negatively affect a user's comfort, confidence, and overall well-being. Older adults with MCI value independence and autonomy, and solution designs should support these. Usefulness, ease of use, security, privacy, cost, physical comfort, and convenience are important considerations for technology use. Reliable technology creates trust, confidence, and feelings of empowerment. This review recommends future work to (1) improve usability and user experience, (2) enhance personalization, (3) better understand interaction preferences and effectiveness, (4) enable options for multimodal interaction, and (5) more seamlessly integrate solutions into users' lifestyles.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.372
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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