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Record W2947473836 · doi:10.1177/0008417419837764

Everyday technologies and public space participation among people with and without dementia

2019· article· en· W2947473836 on OpenAlexvenueno aff
Sophie Nadia Gaber, Louise Nygård, Anna Brorsson, Anders Kottorp, Camilla Malinowsky

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaPublic spaceSpace (punctuation)Everyday lifeRelevance (law)PsychologyGerontologyPublic participationOccupational therapyCognitive impairmentApplied psychologyCognitionPublic relationsSociologyMedicinePolitical scienceComputer sciencePsychiatryEngineering

Abstract

fetched live from OpenAlex

BACKGROUND.: Occupational therapists support everyday technology use; however, it is necessary to consider the challenges that people with dementia encounter with everyday technologies when participating in various places within public space. PURPOSE.: The purpose of the study was to explore stability and change in participation in places visited within public space in relation to the relevance of everyday technologies used within public space. METHOD.: = 34) were interviewed using the Participation in Activities and Places Outside Home Questionnaire and the Everyday Technology Use Questionnaire. Data analysis used modern and classical test theory. FINDINGS.: Both samples participated in places within public space; however, participation and relevance of everyday technologies were significantly lower for the dementia group. IMPLICATIONS.: To enable participation, occupational therapists need to be aware of challenges that technologies and places within public space present to people with dementia.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.983

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 science0.0000.000
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 head0.132
GPT teacher head0.428
Teacher spread0.296 · 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

Citations30
Published2019
Admission routes1
Has abstractyes

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