MétaCan
Menu
Back to cohort
Record W4402851361 · doi:10.4017/gt.2024.23.s.936.opp

Understanding digital technology usability in home-based neurorehabilitation: A realist review

2024· review· en· W4402851361 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGerontechnology · 2024
Typereview
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsNOSM University
FundersUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
KeywordsNeurorehabilitationUsabilityAssistive technologyHuman–computer interactionPsychologyComputer scienceRehabilitationNeuroscience

Abstract

fetched live from OpenAlex

PurposeIn the realm of gerontechnology, the integration of digital technology into the management of neurological disorders holds promise, especially for the aging population requiring intensive rehabilitative care in both clinical and home settings.While prior research has informed the advantages of digital rehabilitation platforms for specific populations such as stroke survivors and children with disabilities, the current underutilization of these technologies at home indicates barriers related to their usability in terms of effectiveness, efficiency, and satisfaction (ISO 9241-11, 2018).Our study aims to understand the usability of digital technologies for home-based rehabilitation in older adults with neurological conditions, thus determining essential factors that could influence their implementation.Method We conducted a realist review complemented by expert consultations, adhering to realist review principles (Pawson & al., 2005) and the RAMESES I publication standards (Wong & al., 2013).An initial program theory (figure 1) was developed based on multiple frameworks and established theories to explain the extent of which certain technologies are usable for home neurorehabilitation for older adults.This program theory was reviewed and refined through focus group discussions with five research experts in gerontechnology or realist review methodologies.Their insights were crucial for validating the framework and recommending enhancements.We are currently examining literature from 2015 to 2023 across various databases and grey literature, using the Context-Mechanism-Outcome configuration analysis (CMOC) (Pawson et al., 2005) to further test this program theory.We focus on understanding how the home setting activates mechanisms that influence technology's usability for older adults with neurological conditions.Each CMOC extracted could reinforce or challenge aspects of our program theory, thereby testing and adjusting it to better reflect the reality of technology usability.A second consultation with users, clinicians, and researchers is planned to validate the updated theory based on their experiences.This process aims to lead to a middle-range theory that is specific enough to guide the usability of certain technologies at home and general enough to apply across different situations, such as various technologies or neurological conditions.Results and Discussion An initial program theory explaining the usability of digital technologies for home neurorehabilitation of older adults was developed and validated by field experts.A screening of 4,708 references led to 137 key articles selected for extraction.The resulting middle-range theory details mechanisms triggered by the home setting, offering actionable guidelines for practical implementation of new digital technologies for rehabilitation at home.The findings underscore the critical role of technology in improving quality of life for older adults by facilitating effective, efficient, and satisfying home-based rehabilitation solutions.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.004
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0000.001

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 head0.367
GPT teacher head0.501
Teacher spread0.134 · 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