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Record W2063314553 · doi:10.3109/17483107.2010.519096

The experiences of using an anti-collision power wheelchair for three long-term care home residents with mild cognitive impairment

2010· article· en· W2063314553 on OpenAlexaff
Rosalie H. Wang, Pia Kontos, P. J. Holliday, Geoff Fernie

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsPublic Health OntarioUniversity of TorontoToronto Rehabilitation Institute
FundersQueen Mary University of London
KeywordsWheelchairUsabilityThematic analysisAutonomyApplied psychologyPsychologyCognitionLong-term carePopulationIntervention (counseling)MedicineComputer scienceHuman–computer interactionQualitative researchPsychiatrySociology

Abstract

fetched live from OpenAlex

PURPOSE: Presented are three case analyses of long-term care home residents with cognitive impairment who tested an anti-collision power wheelchair. We discuss technology design and research implications for this population. METHOD: Case studies involved 371 h of participant observation and 7 h of open-ended interview with residents (n = 3), family members (n = 3) and clinical staff (n = 11). Thematic analysis generated themes related to technological, psychological and social aspects of residents' inclination and disinclination towards power mobility use. RESULTS: Themes examined the discordance between others' and residents' reports of anti-collision power wheelchair use; a facet of response bias; unanticipated implications for independence and dependence; and implications of device design for self-presentation. CONCLUSIONS: Technology alone is insufficient to help residents to fully benefit from the autonomy that a wheelchair intervention can provide: close attention is required to the social and organisational factors of institutional life. For technology to be acceptable, the design must meet the functional and aesthetic needs of users. Considerations in the design of future power wheelchairs for residents with cognitive impairment include capabilities to drive on uneven surfaces, effort-reducing driving modes, improved user interface usability, and acceptable driving speed, size and appearance.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.008
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.406
Teacher spread0.374 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2010
Admission routes1
Has abstractyes

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