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Record W2940798001 · doi:10.2196/12276

Mobile Support for Older Adults and Their Caregivers: Dyad Usability Study

2019· article· en· W2940798001 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Aging · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersMaryland Technology Enterprise InstituteA. James Clark School of EngineeringMaryland Industrial Partnerships
KeywordsUsabilityDyadSystem usability scaleDigital healthPsychologyGerontologyMedicineWeb usabilityHealth careComputer scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Evaluation of digital health applications to support older adults' independence and family caregiving is needed. Digital health is increasingly providing opportunities for older adults and their family caregivers to educate, engage, and share health information across digital platforms. Few apps have documented evidence of usability by older adults and their caregivers. OBJECTIVE: The objective of this study was to determine the usability of a mobile app in a community-based older adult population aged ≥65 years. The app was designed to improve engagement of the patient-informal caregiver team. METHODS: This observational usability study was conducted in participants' homes and independent living facilities in Baltimore, Maryland. Community-dwelling older adults aged ≥65 years and their caregivers enrolled as a dyad (n=24, 12 dyads). The usability evaluation was a mobile and Web-based app that allowed older adult users to record social and health information and share this information with their caregivers. The older adult-caregiver dyad downloaded the app to a smart phone or accessed the Web version, participated in training and onboarding, and used the app for a 1-month period. Participants responded to weekly surveys sent by app push notifications and to the usability and satisfaction surveys at the end of the study. Participant satisfaction and usability were assessed using the Modified Mobile Application Rating Scale (M-MARS) and the System Usability Scale (SUS). RESULTS: The final sample comprised 16 people (8 dyads). Responses to the M-MARS were comparable between older adults and caregiver respondents in terms of engagement and functionality. Caregivers rated aesthetics slightly higher (mean 3.7) than older adult participants did (mean 3.3). Although most responses to the SUS were around the mean (2.3-3.4), older adults and their caregivers differed with regard to integration of app features (mean 3.7 vs 2.8) and the need to learn more before using the app (mean 2.3 vs 3.1). CONCLUSIONS: Technology ownership and use among older adults and caregivers was high. Usability and engagement of the mobile app was average. Additional training is recommended for older adults and their caregivers, including that on targeted behaviors for digital health record keeping.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.011
GPT teacher head0.301
Teacher spread0.289 · 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