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Record W2107330430 · doi:10.4017/gt.2011.10.3.005.00

The design of intelligent in-home assistive technologies: Assessing the needs of older adults with dementia and their caregivers

2011· article· en· W2107330430 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGerontechnology · 2011
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementiaAssistive technologyAging in placeGerontologyPsychologyComputer scienceMedicineHuman–computer interaction

Abstract

fetched live from OpenAlex

Objective: To determine the needs of older adults with dementia and their family caregivers during Activities of Daily Living (ADL), and the role of intelligent assistive technology (AT) in supporting these needs. Methods An 85 item questionnaire was administered to family caregivers of older adults with dementia exploring: (i) challenging ADL for an older adult with dementia to complete independently, (ii) difficult ADL for a caregiver to assist, (iii) the role of AT supporting ADL completion, and (iv) the features and functions of in-home AT designed to support ADL. Results Respondents (n=106) indicated the person they care for has partial ability to complete ADL, that private tasks (e.g., showering) are difficult to assist, and that AT designed to support ADL must be autonomous, familiar, simple and unobtrusive. Respondents also showed little knowledge of existing AT that support ADL. Conclusions Designers of AT should focus on supporting caregivers and older adults with dementia in the completion of private and personal ADL.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.277
Teacher spread0.250 · 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