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Record W2772414402 · doi:10.2196/humanfactors.8387

Deciding How to Stay Independent at Home in Later Years: Development and Acceptability Testing of an Informative Web-Based Module

2017· article· en· W2772414402 on OpenAlexaffvenueabout
Mirjam M. Garvelink, C Allyson Jones, Patrick Archambault, Noémie Roy, Louisa Blair, France Légaré

Bibliographic record

VenueJMIR Human Factors · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre hospitalier universitaire de QuébecUniversity of AlbertaCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleUniversité Laval
Fundersnot available
KeywordsAutonomyWeb applicationFace (sociological concept)PsychologyInternet privacyMedicineComputer scienceWorld Wide WebSociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Seniors with loss of autonomy may face decisions about whether they should stay at home or move elsewhere. Most seniors would prefer to stay home and be independent for as long as possible, but most are unaware of options that would make this possible. OBJECTIVE: The study aimed to develop and test the acceptability of an interactive website for seniors, their caregivers, and health professionals with short interlinked videos presenting information about options for staying independent at home. METHODS: The approach for design and data collection varied, involving a multipronged, user-centered design of the development process, qualitative interviews, and end-user feedback to determine content (ie, needs assessment) in phase I; module development (in English and French) in phase II; and survey to test usability and acceptability with end users in phase III. Phase I participants were a convenience sample of end users, that is, seniors, caregivers, and professionals with expertise in modifiable factors (eg, day centers, home redesign, equipment, community activities, and finances), enabling seniors to stay independent at home for longer in Quebec and Alberta, Canada. Phase II participants were bilingual actors; phase III participants included phase I participants and new participants recruited through snowballing. Qualitative interviews were thematically analyzed in phase II to determine relevant topics for the video-scripts, which were user-checked by interview participants. In phase III, the results of a usability questionnaire were analyzed using descriptive statistics. RESULTS: In phase I, interviews with 29 stakeholders, including 4 seniors, 3 caregivers, and 22 professionals, showed a need for a one-stop information resource about options for staying independent at home. They raised issues relating to 6 categories: cognitive autonomy, psychological or mental well-being, functional autonomy, social autonomy, financial autonomy, and people involved. A script was developed and evaluated by participants. In phase II, after 4 days in a studio with 15 bilingual actors, 30 videos were made of various experts (eg, family doctor, home care nurse, and social worker) presenting options and guidance for the decision-making process. These were integrated into an interactive website, which included a comments tool for visitors to add information. In phase III (n=21), 8 seniors (7 women, mean age 75 years), 7 caregivers, and 6 professionals evaluated the acceptability of the module and suggested improvements. Clarity of the videos scored 3.6 out of 4, length was considered right by 17 (separate videos) and 13 participants (all videos together), and 18 participants considered the module acceptable. They suggested that information should be tailored more, and that seniors may need someone to help navigate it. CONCLUSIONS: Our interactive website with interlinked videos presenting information about options for staying independent at home was deemed acceptable and potentially helpful by a diverse group of stakeholders.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.991

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.326
Teacher spread0.277 · 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

Citations11
Published2017
Admission routes3
Has abstractyes

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