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Record W4308250795 · doi:10.4017/gt.2022.21.s.566.opp1

Building personalized virtual networks of care with the ADel electronic home assistant for older adults

2022· article· en· W4308250795 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGerontechnology · 2022
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsUniversité de MontréalMinistère de l'Agriculture, des Pêcheries et de l'AlimentationMinistry of Education, Recreation and Sports
Fundersnot available
KeywordsGerontologyMedicineComputer sciencePsychology

Abstract

fetched live from OpenAlex

Purpose Technologies to age in place must be personalized to meet the changing reality of aging and to respond to individual needs. A variety of technology applications can be used to help those with chronic conditions to remain at home, provide support to family caregivers at work or at a distant location, check on the status or activities of their loved ones, and enhance access to information and community resources including formal and informal support services ADel (Assistante Domestique lectronique) is an Electronic Domestic Assistant developed in Quebec (Canada) by SoftBiomed to help older adults build personalized virtual networks of care including their family caregivers and healthcare professionals. ADel is an application provided in an electronic tablet with a locked mode (kiosk mode) to family caregivers and clinicians (Figure With ADel, it is possible to customize contacts to make video calls, personalize medication and appointment reminders, and services (e.g., meal delivery and community services). With a panic button and a fall detector integrated into a watch, it provides peace of mind to older adults and their family caregivers. The objective of this pilot study is to explore the feasibility, usability, and user satisfaction of ADel from the perspectives of older adults returning home after a hospitalization, family caregivers, and clinicians being part of a personalized network of care. Methods Participants include 10 older adults without neurocognitive impairment returning home after a hospitalization, 10 family caregivers, and two clinicians. Data on feasibility (semi-structured interview), usability (System Usability Scale), and users' satisfaction (Visual Analog Scale) are collected at one and two months of use of the technology at home. A steering committee with different stakeholders informs the project from the beginning to anticipate any technical, human, cultural, logistical barriers, and facilitators. Results and Discussion The pilot study will allow sharing of expertise between different stakeholders to inform the improvement of this technology across the continuum of care. ADel has the potential to be implemented in individuals with minor and major neurocognitive disorders, older adults living with chronic health conditions, and palliative care. The results will help to improve and adapt this technology according to the older adult's cognitive and physical health status, provide a technological solution to support home care, and prevent social isolation during the current pandemic As the degree of usefulness of these technologies impacts positively elderly people's intention to accept their usage

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.507

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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