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Record W2788346547 · doi:10.2196/rehab.9247

Physiotherapy Questionnaires App to Deliver Main Musculoskeletal Assessment Questionnaires: Development and Validation Study

2018· article· en· W2788346547 on OpenAlexvenueno aff
Nestor Cavalcante Teixeira Neto, Yuri Lopes Lima, Gabriel Peixoto Leão Almeida, Márcio Almeida Bezerra, Pedro Olavo de Paula Lima, Rodrigo Ribeiro de Oliveira

Bibliographic record

VenueJMIR Rehabilitation and Assistive Technologies · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical therapyMobile appsMedicinePsychologyApplied psychologyPhysical medicine and rehabilitationComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Patient-reported outcomes (PROs) translate subjective outcomes into objective data that can be quantified and analyzed. Nevertheless, the use of PROs in their traditional paper format is not practical for clinical practice due to limitations associated with the analysis and management of the data. To address the need for a viable way to group and utilize the main functioning assessment tools in the field of musculoskeletal disorders, the Physiotherapy Questionnaires app was developed. OBJECTIVE: This study aims to explain the development of the app, to validate it using two questionnaires, and to analyze whether participants prefer to use the app or the paper version of the questionnaires. METHODS: In the first stage, the app for an Android operational system was developed. In the second stage, the aim was to select questionnaires that were most often used in musculoskeletal clinical practice and research. The Foot and Ankle Outcome Score (FAOS) and American Orthopaedic Foot and Ankle Society (AOFAS) questionnaire were selected to validate the app. In total, 50 participants completed the paper and app versions of the AOFAS and 50 completed the FAOS. The study's outcomes were the correlation of the data between the paper and app versions as well as the preference of the participants between the two versions. RESULTS: The app was approved by experts after the adaptations of the layout for mobile phones and a total of 18 questionnaires were included in the app. Moreover, the app allows the generation of PDF and Excel files with the patients' data. In regards to validity, the mean of the total scores of the FAOS were 91.54% (SD 8.86%) for the paper version and 91.74% (SD 9.20%) for the app. There was no statistically significant differences in the means of the total scores or the subscales (P=.11-.94). The mean total scores for the AOFAS were 93.94 (SD 8.47) for the paper version and 93.96 (SD 8.48) for the app. No statistically significant differences were found for the total scores for the AOFAS or the subscales (P>.99). The app showed excellent agreement with the paper version of the FAOS, with an ICC value of 0.98 for the total score (95% CI 0.98-0.99), which was also found for the AOFAS with the ICC for the total score of 0.99 (95% CI 0.98-0.99). For compliance, 72% (36/50) of the participants in the FAOS group and 94% (47/50) in the AOFAS group preferred the app version. CONCLUSIONS: The Physiotherapy Questionnaires app showed validity and high levels of compliance for the FAOS and AOFAS, which indicates it is not inferior to the paper version of these two questionnaires and confirms its viability and feasibility for use in clinical practice.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.023
GPT teacher head0.445
Teacher spread0.421 · 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".

Quick stats

Citations19
Published2018
Admission routes1
Has abstractyes

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