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Record W3089429723 · doi:10.1177/1539449220961340

Canadian Occupational Therapists’ Use of Technology With Older Adults: A Nationwide Survey

2020· article· en· W3089429723 on OpenAlexaffabout
Aline Aboujaoudé, Nathalie Bier, Maxime Lussier, Christine Ménard, Mélanie Couture, Louise Demers, Claudine Auger, Hélène Pigot, Martin Caouette, Dany Lussier‐Desrochers, Patrícia Belchior

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2020
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationMcGill UniversityUniversité de SherbrookeUniversité de MontréalUniversité du Québec à Trois-RivièresCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsInformation and Communications TechnologyOccupational therapyLogistic regressionMedicineCross-sectional studyRehabilitationGateway (web page)Family medicinePsychologyPhysical therapy

Abstract

fetched live from OpenAlex

As rehabilitation specialists, occupational therapy practitioners play a gateway role regarding recommendation of various technologies for homecare. However, no study has investigated current occupational therapy practices concerning information and communication technology (ICT) for older adults in Canada. The objective of this study was to identify Canadian occupational therapists’ (OTs) knowledge and practices of ICT with older adults as well as factors associated with its recommendation. A Canada-wide, cross-sectional, online survey was conducted. Of 387 OTs, only 12.4% reported recommending ICT in practice. ICTs supporting communication and cognition were the main types recommended. The reported barriers to use in practice differed between ICT familiar users and nonusers. Multivariate logistic regression analyses showed that clinicians with more years of clinical experience were more likely to recommend ICT. Clinicians’ services, work environments, and client diagnosis were also factors associated with ICT recommendation. Additional research is needed to understand how to overcome barriers to ICT recommendation in OT practice.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.019
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.198
GPT teacher head0.459
Teacher spread0.261 · 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

Citations17
Published2020
Admission routes2
Has abstractyes

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