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Record W4412826478 · doi:10.1097/pxr.0000000000000471

Understanding barriers and facilitators to accessibility in the built and natural environment for people with lower limb loss: A qualitative study

2025· article· en· W4412826478 on OpenAlexafffund
Stephanie R. Cimino, Kristin Nugent, Michael W. Payne, Ricardo Viana, Sander L. Hitzig, Crystal MacKay, Amanda L. Mayo, Steven Dilkas, William C. Miller, Susan Hunter

Bibliographic record

VenueProsthetics and Orthotics International · 2025
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversity of British ColumbiaWest Park Healthcare CentreParkwood InstituteUniversity of TorontoToronto Rehabilitation InstituteLawson Health Research InstituteSunnybrook Health Science CentreWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPhotovoiceThematic analysisQualitative researchPsychologyPerspective (graphical)Applied psychologyMedical educationMedicineNursingSociologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: To explore the facilitators and barriers to community accessibility from the perspective of persons with lower limb amputation (LLA). METHODS: A qualitative study using an adapted version of the Photovoice methods described by Wang and Burris was undertaken. Analysis of the interviews and photos was conducted following thematic content analysis. RESULTS: Seven adults with LLA who were ambulating with a prosthesis at the time of the interview participated in the Photovoice interviews. From the interviews with the participants, 3 main themes were developed: (1) current state of accessibility, (2) impact of community inaccessibility, and (3) hope for the future. Participants described what accessibility currently involved in their community (eg, the positive and negative structures) as well as the impact of inaccessibility on their physical and emotional health. Participants also spoke about what improvements they would like to see in the future regarding community accessibility. CONCLUSIONS: By using the Photovoice methods, participants were able to provide tangible examples of what influences their community accessibility. This study highlights the broad range of changes that could provide accessibility opportunities for individuals with LLA from simple changes (eg, adding handrails to arenas) to more complex changes (eg, improvements in parking lot accessibility).

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)0.000
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 score0.241
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.295
Teacher spread0.275 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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