MétaCan
Menu
← Back to cohort
Record W4400305493 · doi:10.2196/57185

Complementary App-based Yoga Home Exercise Therapy for patients with axial Spondyloarthritis: A Usability Study (Preprint)

2024· article· en· W4400305493 on OpenAlexvenueno aff
Lara Grube, Pascal Petit, Nicolas Vuillerme, Marlies Nitschke, Obioma Bertrand Nwosu, Johannes Knitza, Martin Krusche, Ann-Kristin Seifer, Bjoern M. Eskofier, Georg Schett, Harriet Morf

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersAgence Nationale de la RechercheDeutsche Forschungsgemeinschaft
KeywordsMedicinePreprintPhysical therapyUsabilityWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Axial spondyloarthritis (AS) is a chronic inflammatory rheumatic disease characterized by potentially disabling inflammation of the spine and adjacent joints. Regular exercise is a cornerstone of treatment. However, patients with AS currently have little support. YogiTherapy (MaD Lab) is an app developed to support patients with AS by providing instructions for yoga-based home exercise therapy. OBJECTIVE: This study aimed to evaluate the usability and acceptance of the newly designed YogiTherapy app for patients with AS. METHODS: Patients completed the User Version of the Mobile Application Rating Scale (uMARS) and net promoter score (NPS) questionnaires after the app introduction. Wilcoxon Mann-Whitney rank sum test, chi-square test for count data, and correlation analysis were conducted to examine the usability of the app, acceptance, and patient characteristics. RESULTS: A total of 65 patients with AS (33, 51% female; age: mean 43.3, SD 13.6 years) were included in the study from May 2022 to June 2023. Subsequently, the data were analyzed. Usability was rated moderate, with a mean uMARS of 3.35 (SD 0.47) points on a scale from 0 to 5. The highest-rated uMARS dimension was information (mean 3.88, SD 0.63), followed by functionality (mean 3.84, SD 0.87). Females reported a significantly higher uMARS total score than males (mean 3.47, SD 0.48 vs mean 3.23, SD 0.45; P=.03, Vargha and Delaney A [VDA] 0.66, 95% CI 0.53-0.77). The mean average of the NPS was 6.23 (SD 2.64) points (on a scale from 0 to 10), based on 43% (26/65 nonpromoters, 42% (25/65) indifferent, and 15% (9/65) promoters. A total of 7% (5/65) of those surveyed did not answer the question. When applying the NPS formula, the result is -26%. The NPS showed a positive correlation with the usage of mobile apps (r=0.39; P=.02). uMARS functionality was significantly higher rated by patients younger than 41 years (mean 4.17, SD 0.55 vs mean 3.54, SD 1; P<.001; VDA 0.69, 95% CI 0.56-0.80). Patients considering mobile apps as useful reported higher uMARS (r=0.38, P=.02). The uMARS app quality mean score was correlated with the frequency of using apps (r=-0.21, P<.001). CONCLUSIONS: The results revealed moderate acceptance and usability ratings, prompting further app improvement. Significant differences were observed between age and gender. Our results emphasize the need for further improvements in YogiTherapy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.389
Teacher spread0.345 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Formative Research→Same topicSpondyloarthritis Studies and Treatments→French-language works237,207→