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Record W4376224459 · doi:10.1177/20556683231172671

Potential assistive technology preferences of informal caregivers of people with disability

2023· article· en· W4376224459 on OpenAlexafffundabout
Oladele Ademola Atoyebi, Maude Beaudoin, François Routhier, Claudine Auger, Louise Demers, Andrew Wister, Michelle Plante, W. Ben Mortenson

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsSimon Fraser UniversityInstitut Universitaire de Gériatrie de MontréalUniversité de MontréalUniversité LavalCentre for Interdisciplinary Research in RehabilitationGF Strong Rehabilitation CentreCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversity of British Columbia
FundersAGE-WELL
KeywordsNeurocognitivePreferencePsychologyAssistive technologyApplied psychologyGerontologyMedicineCognitionPsychiatryComputer science

Abstract

fetched live from OpenAlex

Background: Preferences of informal caregivers of people with neurocognitive disorders for technological solutions are important in user- centered design approaches. It is crucial to take into consideration the needs and preferences of users when developing new technology to facilitate their uptake. Objectives: The objective of this study was to determine caregiver preferences for potential technological solutions to help address their needs and compare technology preferences of caregivers who provide care to those with and without neurocognitive disorders (NCD). Methods: This was a quantitative descriptive study. We surveyed informal caregivers of older adults with disability in Canada. Participants were asked to answer questions about their preferences for 10 potential technological solutions that could be developed to make caregiving easier. Results: Data from 125 respondents (72 caregivers of people with NCD and 53 caregivers of people with non-NCD-related disabilities) were analyzed. Generally, caregivers preferred web-based solutions as these were among the first five choices for both groups combined. However, there were some differences in the order of preference of potential solutions in both groups. Conclusion: Informal caregivers of people with NCD preferred web-based solutions to help address their needs.

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)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.322
Teacher spread0.305 · 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.

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

Citations2
Published2023
Admission routes3
Has abstractyes

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Same venueJournal of Rehabilitation and Assistive Technologies EngineeringSame topicAssistive Technology in Communication and MobilityFrench-language works237,207