JMIR FORMATIVE RESEARCH

Grube et al

Original Paper

Complementary App-Based Yoga Home Exercise Therapy for
Patients With Axial Spondyloarthritis: Usability Study
Lara Grube1,2, MD; Pascal Petit3, PhD; Nicolas Vuillerme3,4,5, PhD; Marlies Nitschke6, MSc; Obioma Bertrand Nwosu6,
MSc; Johannes Knitza3,7, MHBA, MD, PD; Martin Krusche8, MD; Ann-Kristin Seifer6, MSc; Bjoern M Eskofier6,9,
MD; Georg Schett1,2, MD; Harriet Morf1,2, MBA, MD
1

Department of Internal Medicine 3- Rheumatology & Immunology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg,
Erlangen, Germany
2

Deutsches Zentrum Immuntherapie, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

3

AGEIS, Université Grenoble Alpes, Grenoble, France

4

Institut Universitaire de France, Paris, France

5

LabCom Telecom4Health, Orange Labs & Université Grenoble Alpes, CNRS, Inria, Grenoble, France

6

Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen, Germany
7

Institute for Digital Medicine, University Hospital of Giessen and Marburg, Philipps-University Marburg, Marburg, Germany

8III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

9

Translational Digital Health Group, Institute of AI for Health, German Research Center for Environmental Health, Helmholtz Zentrum München,
Neuherberg, Germany

Corresponding Author:
Harriet Morf, MBA, MD
Department of Internal Medicine 3- Rheumatology & Immunology
Universitätsklinikum ErlangenFriedrich-Alexander-Universität Erlangen-Nürnberg
Ulmenweg 18
Erlangen, 91054
Germany
Phone: 49 091318543023
Email: harriet.morf@uk-erlangen.de

Abstract
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 withAS.
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 apositive 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 consideringhttps://formative.jmir.org/2024/1/e57185

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Grube et almobile apps as useful reported higher uMARS (r=0.38, P=.02). The uMARS app quality mean score was correlated with thefrequency 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.
(JMIR Form Res 2024;8:e57185) doi: 10.2196/57185
KEYWORDS
DTx; DHA; usability; Yoga; YogiTherapy; ankylosing spondylitis; axial spondylarthritis; digital health application; eHealth;self-assessment; physical exercise; patient acceptance; therapy; home exercise; exercise; patients; patient; spondyloarthritis;
usability study; app; apps; rheumatic disease; chronic; spine; adjacent joints; joints; joint; correlation analysis; digital therapeutics

Introduction
Axial spondyloarthritis (AS) is an inflammatory rheumatic
disease causing spine inflammation and chronic back pain [1,2].
This leads to stiffness and limited mobility due to deformity
and ossification [3]. AS usually begins before age 45, impacting
quality of life, daily activities, social participation, andemployment [4-6]. Treatment combines pharmacological andnonpharmacological approaches [7,8] with physical therapy
recommended by AS guidelines [9]. Intensive training cancounteract spinal ankylosis and modulate inflammation
positively [10]. The EULAR (European Alliance of Associations
for Rheumatology) recommendation lists strength training andstretching as key activities for patients with arthritis [11].
General physical activity is crucial for long-term patientadherence and requires further research [12].
Digital Therapeutics (DTx), digital health applications (DHA),
and telemedicine have gained traction [13], promoting active
patient participation and adherence to therapy [14,15]. Interest
in digitalization in rheumatology has grown, reinforced by the
COVID-19 pandemic [16,17]. A survey identified DTx’s
benefits as saving time (64%, 208/325), enabling healthmonitoring (48.9%, 159/325), and providing accurate
information (40.9%, 133/325) [18]. High-quality apps for AS
are limited worldwide. In an evaluation of 1253 English apps,
only 2 were of high quality [19-21]. However, there is a demandfor AS-specific apps, with high acceptance to use and pay forthem [15,16,22].
In German-speaking countries, 5 fitness apps stand out:
Assessment of SpondyloArthritis International Society (ASAS;
Stichting Assessment of Spondyloarthritis International Society),
Gymondo (Gymondo GmbH), Kaia Health (Kaia Health
Software GmbH), Rheuma Auszeit (Deutsche Rheuma-Liga
Bundesverband eV) and Axia (Applimeda). ASAS calculatesdisease activity scores and provides disease information [23].
Gymondo and Kaia Health offer fitness and pain management
exercises but are not AS-specific [24,25]. Rheuma Auszeit
includes mental and physical exercises but lacks diseaseprogression tracking [26]. The Axia app, approved as a medical
device, offers personalized training for patients with AS bytracking sports and physiotherapy sessions [27].
YogiTherapy (MaD Lab) is a complementary treatment forpatients with rheumatism, combining yoga exercises andself-monitoring of disease progression [2]. It includes electronic
patient-reported outcomes like The Bath Ankylosing Spondylitis
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Metrology Index (BASMI), The Bath Ankylosing Spondylitis
Functional Index (BASFI), The Bath Ankylosing Spondylitis
Disease Activity Index (BASDAI), and Ankylosing Spondylitis
Quality of Life (ASQoL) [28], which can be shared with thephysician. Yoga combines muscle strengthening and stretching,
improving sleep, pain perception, mental health, and overall
functionality [29-31]. Its adaptability makes it suitable forvarious fitness levels, including older adults or those withlimited mobility [32]. Mind-body practices such as yoga,
recognized by the WHO, are increasingly used for managing
chronic rheumatic diseases, with evidence suggesting they
improve patient-reported outcomes [33].
As Nitschke et al [34] and Truong et al [2] have already reported
in detail on YogiTherapy, placing the app in the context ofdigitalization in rheumatology, we are adding our further resultson the acceptance and usability of the app in a larger patient
population here. Larger surveys are needed to ensure the app’s
efficiency and security. We would like to take this opportunity
to point out that further background information on YogiTherapy
can be found in the previously published papers mentioned
above. This study used the revised YogiTherapy app prototype.
The objective is to assess the usability and acceptance of the
YogiTherapy app in patients with AS, aiming for targeted
adjustments to promote long-term use and optimize
self-management.

Methods
Study Design
The study was carried out at the outpatient clinic of the
Department of Rheumatology and Immunology at the University
Hospital Erlangen in Germany. The participating patients weremainly recruited from May 2022 to June 2023. Subsequently,
the data was analyzed. The expected publication was plannedfor 2024. Inclusion criteria were a diagnosis of AS according
to the classification criteria of the ASAS [35] or axial
involvement in the context of psoriatic arthritis [36]. All patientswere invited to complete questionnaires on acceptance, usability,and disease-specific questions created with the SoSci Survey
platform (SoSci Survey GmbH). Additional information on thepatients’ demographic data, app affinity, physical activity, andlaboratory data, such as C-reactive protein (CRP) anderythrocyte sedimentation rate (ESR), was collected.

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Application Description
The prototype of the YogiTherapy app was developed byengineering students from the Laboratory for Machine Learningand Data Analysis at Friedrich-Alexander-Universität
Erlangen-Nürnberg (FAU) and doctors from Erlangen University
Hospital. The app offers a training section with guided yoga
videos. In the test section, patients can carry out disease-specifictests, the results of which are displayed graphically on atimeline. The app also provides information on the disease anddietary recommendations for rheumatic diseases.

Grube et al
In an initial survey [2], problems with design and app function
were mentioned and revised [34].
The functional requirements were retained, including a home
page for language selection and registration (welcome page in
Figure 1), a training area with yoga videos, with search, filter,and favorites options (training section, yoga videos, and“selected yoga video in Figure 1), an assessment area forcompleting disease-specific tests and tracking diseaseprogression (assessment section and test section in Figure 1).

Figure 1. User interface and dashboard of the current version of the app YogiTherapy used in this study. Insight into the training area with exercise
videos and into the test area to check progress on the reduction of axial spondyloarthritis–specific symptoms.

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Procedures
A medical doctor explained the functions of the app in person
or over the phone. Patients were then able to briefly explore theapp before completing the questionnaires. Participants rated theusability of the app using the German version of the User
Version of the Mobile Application Rating Scale (uMARS) [37],a user-friendly version of the Mobile App Rating Scale [38]with 20 questions on engagement, functionality, aesthetics,
information, and subjective quality on 5-point scales. Subjective
quality is based on the willingness to recommend, the expected
frequency of use, the willingness to pay, and the overall rating.
The mean values of the subcategories result in the score, whichranges from 0 to 5 points.
The acceptance of YogiTherapy was measured using the net
promoter score (NPS) [39]. Patients were asked on an 11-point
Likert scale: “How likely is it that you would recommend thistreatment to others?” Scores of 9 or 10 mean promoter, scoresof 7 or 8 mean indifferent, and scores of 0 to 6 mean
nonpromoter. This categorization predicts user behavior [39].
The patient survey also collected sociodemographic information,
physical activity, and affinity for apps. Questions such as “Howoften do you use apps on a smartphone?” “Do you think the useof DTx is useful?” “Do you feel able to use DTx?” and “Do
you use DTx?” were answered on a 5-point scale. Similar
questions were used by Lambrecht et al [26] to investigate
attitudes toward mHealth (mobile health). Physical activity wasassessed using the BSA questionnaire, which records thefrequency, duration, and type of activity over 4 weeks, inminutes per week [40]. In addition, BASDAI (0- to 10-point
scale, where 0=low disease activity and 10=high diseaseactivity), BASMI (0-10 point scale, where 0 is no limited and
10 is high limited mobility), and BASFI (0-10 point scale, where
0 means no limited and 10 means very limited function) scores
were included in the analysis to define physical function, diseaseactivity and mobility in patients with AS [28].

Ethical Considerations
The study was approved by the institutional review board of
the Medical Faculty of the University of Erlangen-Nuremberg,
Germany (8_21_B, 26.02.2021). Participation in the survey was
voluntary. All patients gave their written informed consent
before study inclusion. All patients were coded with aconsecutive number in a pseudonymization procedure. The datacollected was stored and analyzed in a password-protected
database. Only authorized persons had access to this data.
Patients had the option of withdrawing their participation in the
study at any time, whereby all personal data was irrevocably
deleted. There was no financial compensation for participatingin the study. The study was conducted in accordance with the
ethical guidelines of the Declaration of Helsinki.

Statistical Analysis
Descriptive analysis was performed. Correlation analysis was
conducted, with Pearson correlation calculated for continuous

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Grube et alvariables, while polyserial correlation was determined for
categorical variables. Differences in the median (for continuous
variables) or the proportion (for categorical variables) between
both sexes and 2 age categories were examined. The Wilcoxon
Mann-Whitney rank sum test was used to test whether there
were differences between the 2 groups regarding the median ofeach continuous variable. Due to skewed, nonnormal, or
multimodal distributions, the outcomes were evaluated with
nonparametric methods [41]. The Vargha and Delaney A (VDA)
was used. VDA [42] suggested an effect size (ES) of 0.45-0.55
as a negligible effect, 0.56-0.63 (or 0.35-0.44) as a small effect,0.64-0.70 (or 0.30-0.34) as a medium effect, and >0.70 (or<0.30) as a large effect. The chi-square test for count data wasused to test whether there were proportion differences between
the 2 groups for each categorical variable present in the data
set. To measure the strength of the association between 2
categorical variables, Cramer V was computed, with a value of
1 corresponding to complete association and of 0 corresponding
to no association between the variables. The type I error rate
was set at α=.05. All statistical analyses were performed using
R software (version 4.3.1, R Foundation for StatisticalComputing) for Windows 10. The VDA and Cramer V were
calculated using the effect size package [43]. Polyserial
correlations were calculated using the psych package [44].

Results
Patient Characteristics
A total of 65 (100%) patients with AS participated in the study
from May 2022 to June 2023, of whom 51% (33/65) werefemales. The mean age was 43.5 (SD 14.6) years. The mean
CRP value was 1.63 (SD 3.69) mg/L, and the mean ESR value
was 10.6 (SD 13.0) mm/hour. There were 48% (31/65) patientswith a positive human leukocyte antigen B27 (HLA-B27)
antigen test status. The BASDAI showed a mean average of
3.33 (SD 2.21) points. The BASFI was 2.12 (SD 1.87) points.
The BASMI demonstrated 0.64 (SD 1.22) points.
In total, 52% (34/65) of patients reported using apps several
times a day, and 57% (37/65) would be willing to use DTx
regularly. When asked if they thought DTx was useful, 29%(19/65) answered “applies completely,” 45% (29/65) answered“applies,” and no participant rated the usefulness of DTx as“does not apply” or “does not apply at all.” The data is shownin Table S1 in Multimedia Appendix 1.

YogiTherapy uMARS Rating
The usability of YogiTherapy was measured using the uMARS,
as shown in Tables 1 and 2. The overall uMARS app quality
mean score was 3.35 (SD 0.47; 0-5-point scale). Information
received the highest score (mean 3.88, SD 0.63), followed byfunctionality (mean 3.84, SD 0.87), graphical design (mean3.56, SD 1.26), and engagement (mean 3.40, SD 0.64). The
uMARS app quality mean score was correlated with thefrequency of using applications (r=–0.21, P<.001) and being afemale (P=.03).

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Grube et al

Table 1. User Version of the Mobile Application Rating Scale (uMARS) sections and mean scores by sex in a cross-sectional study of 65 patients withaxial spondyloarthritis (51% female, 49% male) in Erlangen, Germany, from May 2022 to June 2023.
uMARS dimensionsauMARS mean score

P value

Both sexes (n=65), mean (SD)

Female (n=33), mean (SD)Male (n=32), mean (SD)

Mean score3.35 (0.47)

3.47 (0.48)

3.23 (0.45).04aEngagement

3.40 (0.64)

3.55 (0.66)

3.26 (0.59).07

Functionality

3.84 (0.87)

3.93 (0.94)

3.76 (0.81).43Graphic design

3.56 (1.26)

3.59 (1.31)

3.52 (1.23).84

Information

3.88 (0.63)

4.02 (0.54)

3.75 (0.71).09

Subjective quality

3.15 (0.66)

3.28 (0.65)

3.02 (0.66).11

App specific quality

3.26 (0.89)

3.43 (0.89)

3.08 (0.86).11Significant at P<.05.

Table 2. User Version of the Mobile Application Rating Scale (uMARS) sections and mean scores by age in a cross-sectional study of 65 patients withaxial spondyloarthritis (average age 43.3, SD 13.6 years) in Erlangen, Germany, from May 2022 to June 2023.
uMARS dimensionsauMARS mean score

P value

Both age categories (n=65),
mean (SD)<41 years (n=31), mean (SD)≥41 years (n=34), mean (SD)

Mean score3.35 (0.47)

3.39 (0.40)

3.32 (0.54).15

Engagement

3.40 (0.64)

3.41 (0.60)

3.39 (0.68).38

Functionality

3.84 (0.87)

4.17 (0.55)

3.54 (1.00)<.001aGraphic design

3.56 (1.26)

3.72 (1.34)

3.41 (1.18).20

Information

3.88 (0.63)

3.93 (0.61)

3.84 (0.67).09

Subjective quality

3.15 (0.66)

3.15 (0.56)

3.16 (0.75).93

App specific quality

3.26 (0.89)

3.07 (0.89)

3.42 (0.86).40

Significant at P<.05.

NPS Rating
When analyzing the NPS, the participants were divided into
43% (26/65 nonpromoters, 42% (25/65) indifferent, and 15%(9/65) promoters, as shown in Figure 2. The mean score was
6.23 (SD 2.64). There were more females in the promoters (25%,
8/9). There was a positive correlation with the app quality meanscore (r=0.64; P<.001), the uMARS subjective quality score(r=0.75; P<.001), uMARS engagement score (r=0.53; P<.001),
uMARS information score (r=0.43; P<.001) and the uMARS
functionality score (r=0.31; P<.001).
Patients who used DTx definitely demonstrated higher NPS
ratings (r=0.39; P=.02). Compared with males, more females
chose “applies completely” for both the usage of DTx (Cramer
V=0.36; P=.01) and DTx making sense questions (Cramer
V=0.38; P=.01).

There were several differences between the 2 age categories,
with younger participants (<41 years) that had a lower ESR(mean 6.16, SD 4.84 mm/h; P<.001), lower CRP (mean 0.77,
SD 2.27 mg/L; P=.12), lower BASMI (0.21, SD 0.42; P=.03),
and higher uMARS functionality scores (mean 4.17, SD 0.55;
P<.001) than participants 41 years or older (ESR: mean 15.9,
SD 17.2 mm/h; CRP: mean 2.60, SD 4.67 mg/L; BASMI: mean
1.12, SD 1.62; uMARS functionality score: mean 3.54, SD1.00).
The uMARS functionality score (r=–0.35, P<.001) and theuMARS graphic design score (r=0.13, P<.001) were all
correlated with the frequency of DTx use, as was the uMARS
app quality mean score (r=–0.21, P<.001). The uMARS
functionality score also positively correlated with the frequent
usage of DTx several times a day (r=0.48, P<.001).

When applying the NPS formula, as a subtraction of thepercentage of nonpromoters from the percentage of promoters,
the result is –26%.

Patients who applied completely to the question of DTx making
sense were positively correlated with the total uMARS (r=0.38,
P=.02). The question about the use of DTx was positively related
to the uMARS subjective quality (r=0.34, P=.03).

When examining sex differences, it was noticeable that females
had a higher ESR (mean 12.5, SD 12 mm/h vs mean 8.31, SD
14 mm/h; P≤.001) and a higher uMARS app quality mean scorethan males (3.47, SD 0.48 vs 3.23, SD 0.45; P=.03).

The evaluation of the participants’ sports activity reported in
the BSA questionnaire showed that the younger the patients
were, the higher the level of sports activity reported (r=–0.37,
P=.55).

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Figure 2. Bar chart of net promoter score (NPS) analysis showing the percentage of participants classified as promoter, indifferent, or nonpromoter of
YogiTherapy by age and sex. This cross-sectional study included 65 patients with axial spondyloarthritis (51% female, 49% male) in Erlangen, Germany,from May 2022 to June 2023.

Discussion
Principal Findings
The aim of this study was to assess the usability and acceptanceof the YogiTherapy app to provide complementary exercise
therapy for patients with AS. Overall, the quality of the app wasgood, with the functionality section rated particularly highly,
whereby the acceptance was rather average.
The quality of the app YogiTherapy was rated as “mediocre,”as indicated by a score in the middle range of the uMARS. The
information section of the uMARS received the best rating,followed by the functionality section with the second-highest
value (mean 3.84, SD 0.87). This is consistent with the findingsof a systematic review of 18 pain-related mobile apps also using
the MARS score, where the best ratings were related to technicalaspects of the app itself, such as “functionality” [45].
Furthermore, the information aspect was low here, which was
explained by the fact that most apps are commercial, and a few
are developed by scientific institutions. Thus, YogiTherapy has
an advantage as a DTx developed by a university hospital [2,34].
The widest range of uMARS scores was found in the subjective
quality of the app, engagement, and aesthetics, which is why
these aspects should be improved [45].
With an overall mean score of 3.35 (SD 0.47) on a scale of 5
points in uMARS, the quality rating is slightly lower than therating of 9 other mobile apps for patients with rheumatic
diseases, which ranged from 3.44 to 4.19 [46]. “Rheuma
Auszeit” achieved the highest uMARS score. “Rheuma Auszeit”
was the only 1 of the 9 apps to offer instructions for mental andphysical exercises. However, “Rheuma Auszeit” did not havea feature to track the disease progression. In comparison, theAxia app would be a possible alternative to exercise therapy forpatients with AS, as initial studies have already indicated.
An interesting concept from the developers is the possibility of
combining exercises from the app with everyday tasks. Thisshould probably strengthen adherence in the long term andimprove movement competence, an advantage that Azhar andDhillon [47] also identified in their review. In their systematic
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review to identify factors influencing the effective use ofmHealth apps for self-care, the most commonly identified factors
were perceived usefulness, perceived ease of use, behavioral
intention to use, social influence, and self-efficacy [47]. The
app Axia offers users over 250 exercise videos for personalized
therapy, special programs for acute pain and intensive training,a knowledge library with 56 interactive articles on AS
management, symptom tracking, a progress dashboard,
relaxation exercises, and medication monitoring [48]. As theapproach to supporting patients is similar to that of
YogiTherapy, we could imagine that our app would beparticularly useful for patients who would like to practice yoga
in addition to a physiotherapy approach. Even though
YogiTherapy scored lower than Axia or Rheuma Auszeit in the
uMARS, YogiTherapy provides holistic support to users [34].
In a recent survey on the need for an app in AS, the willingness
to use an app appears to be greatest in patients <60 years of age,patients undergoing biologic therapy, and patients with frequent
back pain [49]. We divided our age categories into patients <41
years and ≥41 years based on the median age. The younger age
category achieved a slightly higher value in the uMARS app
quality mean score (3.39, SD 0.40) than the older age category(3.32, SD 0.54; P=.78). In the case of functionality, younger
patients scored the app significantly higher than older patients(4.17, SD 0.55 vs 3.54, SD 1; P<.001). However, the patients≥41 years achieved a higher mean score in the section of app
specific quality (3.07, SD 0.89 vs 3.42, SD 0.86; P=.08). In a
recent study on online physiotherapy in patients with AS, Paulet al [19] also showed a positive effect of the online programon disease parameters such as BASDAI, BASMI, and AsQoL.
The statement that patients with higher disease activity indicateda greater need for an app was only partially reflected in our data.
There was just 1 significant correlation between uMARS
functionality and higher CRP (r=0.02; P=.03). As females inparticular rated the app well, it was also noticed here that ESR
was significantly higher than in male patients (12.5, SD 12 vs
8.31, SD 14; P<.001). In our study, older patients showed valuesof a greater inflammatory process and poorer functionality; yet,the app was rated slightly lower in quality. This result could befalsified by the different age categories selected. Interestingly,
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however, there were no differences in perceived disease activity
depending on sex and age.
Age-related differences were noted, but these could not berecorded more precisely as experience using the app was notassessed [34].
The uMARS app quality mean score was correlated with thefrequency of using DTx (r=–0.21; P<.001). Looking at thecorrelations between the individual uMARS sections and thestated frequency of DTx use, the app affinity, it is noticeable
that the correlation r is only positive (as a higher point value inthe frequency question represents a rarer frequency) in theGraphic Design section (r=0.13; P<.001). This could indicatethat YogiTherapy is particularly suitable for newcomers to app
use. Patients who used DTx demonstrated higher NPS ratings(r=0.39; P=.02). Females rated the usefulness of DTx
significantly higher, 46.9% (15/19) than men, 12.1% (4/19).
This observation was also evident in the overall uMARS score(3.47, SD 0.48 vs 3.23, SD 0.45; P=.03) and in the NPS, where
the number of promoters among females was 8 (8/9, 25%) and1 (1/9, 3%) among males. It is known that patients who areaware of their self-efficacy in relation to the treatment of theirchronic disease show better compliance with physical exercise[50]. In addition, a positive correlation between medication
self-efficacy and adherence to treatment was found in asystematic study of the relationship between self-efficacy, healthcontrol beliefs, and adherence to treatment [51]. Unfortunately,
we do not have information about patients’ medication. Patientsare looking for alternative treatments to improve their symptoms.
These patients may be more open to exploring different
treatment options and innovative tools such as DTx, which canhelp to improve care and support. This was also observed in astudy of “the AxSpA Live app” [52]. The app offers a diaryfunction in which various disease variables can be documented.
Their results showed that older patients with more diseaseactivity used the app more often.
The NPS showed a less positive result with a mean value of
6.23 (SD 2.64, range 0-10) and a result of –26% in the NPS
formula. This could indicate that patients would probably not
actively recommend the app to others. The discrepancy between
the NPS and the overall satisfaction rating was also reported by
Seppen et al [53]. These authors cited possible culturaldifferences in the type of rating as the reason for this; European
people would tend to give fewer extreme ratings compared with
Americans, and the NPS originated in the United States [54].
This rather poor result in the NPS score gives us the motivation
to continue to improve YogiTherapy in terms of usability andacceptance.
Our evaluation of YogiTherapy focused on the impact on users’
health behaviors, which were assessed in the “App-specificquality” section of the uMARS. Patients rated statements suchas “The app increases awareness of the importance of addressing
health behaviors” and “The app encourages intention andmotivation to improve health behaviors” on a 5-point scale. The
mean score in this category was 3.26 (SD 0.89), with women(mean 3.43, SD 0.89) and participants aged 41 years and older(mean 3.42, SD 0.86) scoring higher than men (mean 3.08, SD0.86) and those aged 41 years and younger (mean 3.07, SD
https://formative.jmir.org/2024/1/e57185

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Grube et al0.89). This suggests that female and older users may better
recognize the value of health apps. Women may especially bemore open to using DTx as they are more mindful of their healthor already have experience using health services [55]. Younger
users may have different priorities, as our data show a negative
correlation between age and physical activity (r=–0.37; P=.55),
suggesting that younger patients lead a more active lifestyle. In
addition, younger patients had lower ESR values (mean 9.33,
SD 5.69 vs mean 19.0, SD 18.9; P=.002) and better physicalactivity levels (mean 0.50, SD 0.71 vs mean 2.50, SD 1.87;
P=.03) and disease-specific physical function (mean 1.85, SD
1.53 vs mean 2.81, SD 2.28; P=.05) than older patients. This
statement is also supported by the fact that in our collected data,
younger patients had better values for range of motion (mean0.50, SD 0.71 vs mean 2.50, SD 1.87; P=.03) than older patients.
The influence of DTx on health behavior has already been
investigated. The chances of behavioral change were low tomoderate on average (App Behavior Change Scale [ABACUS]
score: mean 8.07, SD 2.30) in a sample of 60 apps [56].
ABACUS is a validated and objective tool that uses 21 items
categorized into knowledge and information, goals and planning,
feedback and monitoring, and actions. The reachable score lies
between 0 and 21. The higher the score, the higher the potential
for promoting behavior change [57]. It was found that apps forpatients with multimorbidity tended to have a higher overall
ABACUS score. The most common features in these apps that
supported behavior change were self-monitoring ofphysiological parameters such as blood pressure (38/60, 63%apps), weight and diet (25/60, 42% apps), physical activity(22/60, 37% apps), and stress management (22/60 apps, 37%)[56]. YogiTherapy, therefore, has the potential to support
behavioral change through its functions.
As many study participants were given information about theapp over the phone, contacting them became more impersonal,
which could have had a negative impact on their evaluation of
the app. Therefore, potential users should be introduced bytrained staff members in one-to-one contact. Practicing andtraining with an app is not suitable for every patient, and a doctor
consultation should take place beforehand. Older patients (≥41
years) expressed concern in verbal feedback that yoga was too
demanding for their previous yoga experience and their physicalfitness. The “RheumaAuszeit” app, which contains relaxation
exercises, received a higher uMARS score [26,46]. Thesefindings allow consideration of offering relaxation exercises in
the YogiTherapy app as well. Although the app already provides
precise instructions on alternative exercises and postures, it
seems sensible to offer an analog introduction to the sport bytrained staff members, especially for newcomers to yoga
practice.
In addition, we analyzed the responses of 45 other patients who
watched and performed the freely available yoga videos usedin the YogiTherapy app. At the end of each video, a survey
appeared asking about the difficulty level of the yoga exercises
and whether they would recommend the videos to a friend. The
second question matched the NPS question and was therefore
also asked of the 65 patients who took part in our survey. As
expected, we found a higher score (mean 8.69, SD 1.97) forrecommending the videos to friends among the study
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JMIR FORMATIVE RESEARCH
participants who, unlike the other patients, had already engaged
with the videos over a longer period of time. There may be abias here, as the 45 patients were not part of the study.
Our study has limitations, starting with the study design, which
aimed to evaluate the app based on first impressions. However,in order to evaluate the true benefit of the YogiTherapy app on
patients with AS, further data over a longer period of timecompared with standard physiotherapy needs to be collected.

Grube et al

Conclusion
In conclusion, our study assessed the usability and acceptanceof the YogiTherapy app in patients with AS. The present
findings highlighted potential age and gender-related variations.
Our results emphasize the need for further improvements in
DTx for rheumatology care.

Acknowledgments
The authors thank all participating patients and the whole team of Medizinische Klinik 3 and of the Machine Learning and Data
Analytics Lab at Universität Erlangen-Nürnberg (FAU) for their support of this project. This study was performed in fulfillmentof the requirements for obtaining the degree of Dr Med for the first author, LG. NV and PP are supported by the French National
Research Agency (ANR) in the framework of the Investissements d’avenir program (ANR-10-AIRT-05 and ANR-15-IDEX-02),
and by MIAI Grenoble Alpes (ANR-19-P3IA-0003). The collaboration was initiated within the framework of the collaborative
research center EmpkinS (DFG CRC 1483).

Data Availability
The data sets generated and analyzed during this study are available from the corresponding author upon reasonable request. The
majority of the data is included in this published article.

Authors' Contributions
LG, JK, PP, NV, MN, and HM wrote the draft manuscript. PP and NV performed the statistical analysis. All authors reviewed
the draft, provided comments for changes, and approved the final manuscript.

Conflicts of Interest
None declared.

Multimedia Appendix 1
Patients' demographic characteristics (n=65).
[DOCX File , 16 KB-Multimedia Appendix 1]

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Abbreviations
ABACUS: App Behavior Change Scale
ANR: French National Research Agency
AS: axial spondyloarthritis
ASAS: Assessment of SpondyloArthritis International Society
ASQoL: Ankylosing Spondylitis Quality of Life
BASDAI: Bath Ankylosing Spondylitis Disease Activity Index
BASFI: Bath Ankylosing Spondylitis Functional Index
BASMI: Bath Ankylosing Spondylitis Metrology Index
CRP: C-reactive protein
DHA: digital health application
DTx: digital therapeutics
ES: effect size
ESR: erythrocyte sedimentation rate
EULAR: European Alliance of Associations for Rheumatology
FAU: Friedrich-Alexander-University
HLA-B27: human leukocyte antigen B27
mHealth: mobile health
NPS: net promoter scale
uMARS: User Version of the Mobile Application Rating Scale
VDA: Vargha and Delaney A

Edited by A Mavragani; submitted 07.02.24; peer-reviewed by P-P Strunz, A Hassan; comments to author 01.05.24; revised version
received 21.05.24; accepted 03.07.24; published 19.09.24
Please cite as:
Grube L, Petit P, Vuillerme N, Nitschke M, Nwosu OB, Knitza J, Krusche M, Seifer A-K, Eskofier BM, Schett G, Morf H
Complementary App-Based Yoga Home Exercise Therapy for Patients With Axial Spondyloarthritis: Usability StudyJMIR Form Res 2024;8:e57185
URL: https://formative.jmir.org/2024/1/e57185
doi: 10.2196/57185
PMID:©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. This is an open-access article distributed under the terms of the Creative Commons
Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction
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