Complementary App-Based Yoga Home Exercise Therapy for Patients With Axial Spondyloarthritis: Usability Study.

DHA DTx Yoga YogiTherapy adjacent joints ankylosing spondylitis app apps axial spondylarthritis chronic correlation analysis digital health application digital therapeutics eHealth exercise home exercise joint joints patient patient acceptance patients physical exercise rheumatic disease self-assessment spine spondyloarthritis therapy usability usability study

Journal

JMIR formative research
ISSN: 2561-326X
Titre abrégé: JMIR Form Res
Pays: Canada
ID NLM: 101726394

Informations de publication

Date de publication:
19 Sep 2024
Historique:
received: 07 02 2024
accepted: 03 07 2024
revised: 21 05 2024
medline: 19 9 2024
pubmed: 19 9 2024
entrez: 19 9 2024
Statut: epublish

Résumé

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. This study aimed to evaluate the usability and acceptance of the newly designed YogiTherapy app for patients with AS. 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. 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). 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.

Sections du résumé

BACKGROUND 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 OBJECTIVE
This study aimed to evaluate the usability and acceptance of the newly designed YogiTherapy app for patients with AS.
METHODS 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 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 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.

Identifiants

pubmed: 39298754
pii: v8i1e57185
doi: 10.2196/57185
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e57185

Informations de copyright

©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. Originally published in JMIR Formative Research (https://formative.jmir.org), 19.09.2024.

Auteurs

Lara Grube (L)

Department of Internal Medicine 3- Rheumatology & Immunology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Deutsches Zentrum Immuntherapie, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Pascal Petit (P)

AGEIS, Université Grenoble Alpes, Grenoble, France.

Nicolas Vuillerme (N)

AGEIS, Université Grenoble Alpes, Grenoble, France.
Institut Universitaire de France, Paris, France.
LabCom Telecom4Health, Orange Labs & Université Grenoble Alpes, CNRS, Inria, Grenoble, France.

Marlies Nitschke (M)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Obioma Bertrand Nwosu (OB)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Johannes Knitza (J)

AGEIS, Université Grenoble Alpes, Grenoble, France.
Institute for Digital Medicine, University Hospital of Giessen and Marburg, Philipps-University Marburg, Marburg, Germany.

Martin Krusche (M)

III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Ann-Kristin Seifer (AK)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Bjoern M Eskofier (BM)

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Translational Digital Health Group, Institute of AI for Health, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.

Georg Schett (G)

Department of Internal Medicine 3- Rheumatology & Immunology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Deutsches Zentrum Immuntherapie, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Harriet Morf (H)

Department of Internal Medicine 3- Rheumatology & Immunology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Deutsches Zentrum Immuntherapie, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

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Classifications MeSH