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Record W4283311936 · doi:10.1080/17483107.2022.2089739

Usability of a navigation application for travel in Quebec City with wheeled mobility device and, further validation of the Evaluation of satisfaction with geospatial assistive technology

2022· article· en· W4283311936 on OpenAlexaffabout
Claude Vincent, Sophie Levac, Frédéric Dumont, Philippe S. Archambault, François Routhier, Mir Abolfazl Mostafavi

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre for Interdisciplinary Research in RehabilitationUniversité LavalMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
Fundersnot available
KeywordsUsabilityGeomaticsGeospatial analysisConstruct validityPopulationComputer scienceConstruct (python library)Applied psychologyPsychologyPatient satisfactionHuman–computer interactionMedicineGeographyCartographyNursing

Abstract

fetched live from OpenAlex

Purpose Knowledge of route accessibility is indispensable for “wheeled mobility device” users to travel safely and efficiently; however, current navigation technologies hardly provide adapted information for this population. Aims of the study were to collect data on the usability of a navigation application and to propose a version 1.0 of the Evaluation of satisfaction with geospatial assistive technology (ESGAT), by addressing the criterion, construct and cross-cultural validities.Method A filmed field trial and a methodological study were conducted in parallel. Thirty wheeled mobility device users were filmed planning and making a 10-minute known journey using the HERE WeGo app. The ESGAT, ÉSTGA (French version) and the Computer System Usability Questionnaire were administered. A video observation grid addressed the effectiveness and efficiency during the journey. Descriptive, correlation and multiple match analyses were performed.Results Fourteen men and 16 women averaging 45.9 years old tried out HERE WeGo; 14 were powered wheelchair users. Usability of the app was moderate (good effectiveness, moderate efficiency and quite satisfied). The criterion validity of the ÉSTGA was good (r = 0.598; p < 0.001). The construct validity was average considering the results for factor 1 (α = 0.789, acceptable), factor 2 (α = 0,586, low) and factor 3 (α = 0.409, unacceptable). The cross-cultural validity (French vs English) was moderate (r = 0.861; p < 0.001).Conclusion ESGAT and ÉSTGA 1.0 questionnaires are now available in English and French with a total mean score (11 items), an informatics subscore (mean of 5 items) and a geomatic subscore (mean of 6 items). Their validation should be pursued with new navigation applications. IMPLICATIONS FOR REHABILITATIONClinicians should ask their clients using a wheeled mobility device to test navigation applications to ensure their safety and complete the Evaluation of satisfaction with geospatial assistive technology (ESGAT 1.0), also available in French.Clinicians should inquire about satisfaction for items addressing informatics (Ease of access, Learnability, Hands-free function, Ease of use, Transportability and Appearance) and items addressing geomatic (Content, Geographic information, Effectiveness, Efficiency, Real-time navigation assistance, Aspect of security).Rehabilitation clinicians should inquire about the efficiency of the navigation app, considering avoiding or announcing potential obstacles such as: travelling on the street for a long portion of the trip and not on the sidewalk; verbal indication too soon or too late; incorrect indication; damaged, and congested sidewalk.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.380
Teacher spread0.347 · 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.

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".

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Citations2
Published2022
Admission routes2
Has abstractyes

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