MétaCan
Menu
← Back to cohort
Record W3046825606 · doi:10.2196/16928

Perceived Need and Acceptability of an App to Support Activities of Daily Living in People With Cognitive Impairment and Their Carers: Pilot Survey Study

2020· article· en· W3046825606 on OpenAlexvenueno aff
Rhoda Lai, Maria Tensil, Alexander Kurz, Nicola T. Lautenschlager, Janine Diehl‐Schmid

Bibliographic record

VenueJMIR mhealth and uhealth · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersTechnische Universität München
KeywordsActivities of daily livingDementiaCognitionPopulationUsabilityPsychologyCognitive impairmentGerontologyMedicineClinical psychologyPsychiatryDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Modern technologies, including smartphone apps, have the potential to assist people with cognitive impairment with activities of daily living, allowing them to maintain their independence and reduce carer burden. However, such tools have seen a slow rate of uptake in this population, and data on the acceptability of assistive technologies in this population are limited. OBJECTIVE: This pilot study included older adults with cognitive impairment and their carers, and explored the perceived needs for and acceptability of an app that was designed to be a simple assistive tool for activities of daily living. In particular, this study aimed to assess the acceptability of common app functions such as communication, reminder, navigation, and emergency tools in this population, and to compare patients' and carers' responses to them. METHODS: A total of 24 German participants with mild cognitive impairment or dementia and their family carers separately completed two short questionnaires. The first questionnaire asked the participants with cognitive impairment and their carers to self-rate the patients' cognitive impairment levels and affinity to technology. Following a demonstration of the app, participants rated the usability and acceptability of the app and its functions in a second questionnaire. RESULTS: Participants rated themselves as much less cognitively impaired than their carers did (P=.01), and insight into the level of support they received was low. The majority of the participants (19/24, 79%) and their carers (20/24, 83%) had low affinity to technology, and even after the demonstration, 63% (15/24) of the participants had low interest in using the app. A breakdown of acceptability responses by app function revealed that participants were more amenable to the reminder function, the emergency feature, and a wearable form of the app. Features that centered around carers monitoring participants' movements were reported to be less acceptable to participants. CONCLUSIONS: This study highlights the importance of focusing on acceptability and the consumer's perceptions in the development of assistive technology for older adults with cognitive impairment. Participants showed an aversion to functions they perceived as eroding their independence, while functions that more closely aligned with independence and autonomy were perceived as more acceptable.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.387
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJMIR mhealth and uhealth→Same topicDementia and Cognitive Impairment Research→French-language works237,207→