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Record W4412749602 · doi:10.1177/20556683251359194

Assessing patient use and satisfaction with ankle foot orthoses and service: A cross-sectional study in a tertiary care hospital

2025· article· en· W4412749602 on OpenAlexaboutno aff
Lall Sanya Prarthana, Chauhan Neema Godiyal Pooja, Bansal Avijit, Gita Handa

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsCross-sectional studyTertiary carePatient satisfactionFoot careFoot (prosody)MedicineService (business)AnklePhysical therapyFamily medicineNursingSurgery

Abstract

fetched live from OpenAlex

The Study was done to examine the use, non-use, the quality of clinical advice, challenges in acquiring AFOs (Ankle Foot Orthosis), and user satisfaction, using a WHO based Rapid Assistive Technology Assessment (rATA) and Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) questionnaire. The cohort (n = 100) consisted mainly of males (71%) and residents of city (82%). It was found that 98 subjects were under advice from healthcare providers to use an AFO but only 59 subjects were using AFO at present. Common complaints were pain, fitting related and social stigma among users. The majority of the subjects (87%) paid for their AFOs. It was found that the majority of the subjects were "more or less satisfied" with the device however 59% strongly agree that they dislike the appearance of their AFO and 37% were completely dissatisfied with the accessibility of their home and surroundings while using the AFO. It is evident that we should work on improving the design and fit of the orthosis so that the acceptance and satisfaction improves. This study also explores the possibility of usage of rATA for the specific assistive Technology (like AFO in this context) assessment. It was observed that patients often have high expectations regarding a cure with the use of an AFO. Therefore, it is essential for service providers to explain that the AFO is intended to improve function rather than provider a cure. This mismatch of understanding may contribute to dissatisfaction by patients using AFOs, hence user education is essential along with technology provision.

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)0.001
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 score0.030
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.007
GPT teacher head0.279
Teacher spread0.272 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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