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 in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org, as well as this copyright and license information must be included.
The development of mobile interventions for noncommunicable diseases has increased in recent years. However, there is a dearth of apps for patients with peripheral arterial disease (PAD), who frequently have an impaired ability to walk.
Using a patient-centered approach for the development of mobile interventions, we aim to describe the needs and requirements of patients with PAD regarding the overall care situation and the use of mobile interventions to perform supervised exercise therapy (SET).
A questionnaire survey was conducted in addition to a clinical examination at the vascular outpatient clinic of the West-German Heart and Vascular Center of the University Clinic Essen in Germany. Patients with diagnosed PAD were asked to answer questions on sociodemographic characteristics, PAD-related need for support, satisfaction with their health care situation, smartphone and app use, and requirements for the design of mobile interventions to support SET.
Overall, a need for better support of patients with diagnosed PAD was identified. In total, 59.2% (n=180) expressed their desire for more support for their disease. Patients (n=304) had a mean age of 67 years and half of them (n=157, 51.6%) were smartphone users. We noted an interest in smartphone-supported SET, even for people who did not currently use a smartphone. “Information,” “feedback,” “choosing goals,” and “interaction with physicians and therapists” were rated the most relevant components of a potential app.
A need for the support of patients with PAD was determined. This was particularly evident with regard to disease literacy and the performance of SET. Based on a detailed description of patient characteristics, proposals for the design of mobile interventions adapted to the needs and requirements of patients can be derived.
Circulatory disorders of peripheral arteries due to atherosclerotic lesions are the third most frequent manifestation of atherosclerotic disease after its manifestation in coronary and cerebrovascular arteries [
One recommendation of the current guidelines is supervised exercise therapy (SET) or a supervised exercise program (SEP) [
Recent studies have shown that patient empowerment helps to increase therapy adherence. This is mainly achieved through gaining greater control in health decisions [
Mobile health (mHealth) technologies provide digital solutions to close gaps in care [
As a first step in a patient-centered approach to develop PAD-specific mobile interventions, we describe the needs and requirements from a patient perspective.
The aim of the study was to determine the needs and requirements of patients with PAD. This included their overall care situation and the potential use of mobile interventions.
In addition to the clinical examination, we answer the following research questions:
What is the current perception of medical care in patients with PAD? Can a need for medical support be determined among the study participants?
Do patients with PAD currently use smartphones and apps? What are the characteristics of smartphone users and nonusers?
What are the requirements for the design of mobile interventions to support patients with PAD in performing supervised exercise therapy?
In addition to the clinical examination, we conducted a questionnaire-based survey at the vascular outpatient clinic of the West-German Heart and Vascular Center Essen of the University Clinic Essen, Germany. This clinic treats more than 1500 patients with PAD annually. Patients were recruited between September and December 2018.
Consecutively, patients with diagnosed PAD were asked to participate in this study. The inclusion criteria were male or female patients aged 18 or older with PAD. PAD had to be diagnosed at least 3 months prior to the study.
Furthermore, patients were excluded if they were unable to complete the questionnaire themselves (eg, severe dementia or cognitive dysfunction). We also excluded individuals who did not have sufficient knowledge of the German language.
In total, we surveyed 304 patients with PAD. Two-thirds of the patients were men (n=203, 66.8%;
Sociodemographic characteristics of patients with peripheral arterial disease (PAD) divided into all patients, smartphone users, and non–smartphone users.
Sociodemographic characteristics | All patients, n (%) | Smartphone users, n (%) | Non–smartphone users, n (%) | ||||||
|
n=304 | n=157 | n=147 |
|
|||||
|
Male | 203 (66.8)a | 106 (52.2)b | 97 (47.8)b | .73 (0.121) | ||||
|
n=301 | n=155 | n=146 |
|
|||||
|
40-49 | 18 (6.0) | 11 (61.1) | 7 (38.9) | .74 (0.113) |
||||
|
50-59 | 58 (19.3) | 34 (58.6) | 24 (41.4) | .46 (0.556) | ||||
|
60-69 | 102 (33.9) | 64 (62.7) | 38 (37.3) | .09 (2.870) | ||||
|
70-79 | 85 (28.2) | 35 (41.2) | 50 (58.8) | .32 (1.002) | ||||
|
≥80 | 37 (12.3) | 11 (29.7) | 26 (70.3) | .12 (2.382) | ||||
|
n=286 | n=151 | n=135 |
|
|||||
|
<10 | 40 (14.0) | 19 (12.6) | 21 (15.6) | .91 (0.012) | ||||
|
10 |
22 (7.7) | 13 (8.6) | 9 (6.7) | .76 (0.091) | ||||
|
12 |
133 (46.5) | 67 (44.4) | 66 (48.9) | .09 (0.001) | ||||
|
14 |
66 (23.1) | 35 (23.2) | 31 (23.0) | .32 (0.030) | ||||
|
>17 | 25 (8.7) | 17 (11.3) | 8 (5.9) | .12 (1.013) | ||||
|
n=304 | n=157 | n=147 |
|
|||||
|
Currently employed | 77 (25.3) | 43 (55.8) | 34 (44.2) | .57 (0.319) |
||||
|
Retired | 140 (46.1) | 86 (42.9) | 94 (57.1) | .75 (0.100) | ||||
|
Retired due to illness |
40 (13.2) | 26 (65.0) | 14 (35.0) | .26 (0.258) | ||||
|
n=304 | n=157 | n=147 |
|
|||||
|
Not at all | 21 (6.9) | 7 (33.3) | 14 (66.7) | .43 (0.612) |
||||
|
A little | 49 (16.1) | 23 (46.9) | 26 (53.1) | .92 (0.102) |
||||
|
Average | 74 (24.3) | 36 (48.6) | 38 (51.4) | .97 (0.002) |
||||
|
Fair | 98 (32.2) | 57 (58.2) | 41 (41.8) | .32 (1.007) | ||||
|
Great | 62 (20.4) | 34 (54.8) | 28 (45.2) | .72 (0.129) |
||||
Burden of disease | 1.36 (0.76) | 1.45 (0.73) | 1.25 (0.76) | .02 (2.33) | |||||
Burden of environmental conditions | 0.90 (0.63) | 1.02 (0.58) | 0.77 (0.64) | <.001 (3.377) |
aThe percentage is based on the number of all responses for the associated sociodemographic characteristic (sex, age, educational attainment, employment status, and burden of PAD).
bThe percentage is based on the total number of observations within the associated sociodemographic characteristic group.
The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the local ethics committee at the Faculty of Medicine of the University Duisburg-Essen. Patient records were deidentified and analyzed anonymously. Written consent was obtained from each patient included in the study.
The questionnaire was prepared specifically for this study and was pretested on 5 PAD patients not included in the study sample. The pretest did not reveal the need for any changes.
The 10-page questionnaire encompasses a total of 31 questions on sociodemographic characteristics; subjective burden of disease and PAD-related care situations; subjective burden of environmental conditions; implementation and feasibility of SET; mobile or app usage; interests and knowledge regarding SET and medication; and the need for support and satisfaction with the health care situation. In the questionnaire, we used the term supervised walking training instead of the technical term supervised exercise therapy (SET) because the German word “Gehtraining” is more established in clinical practice.
The questionnaire included dichotomous and 5-point assessments similar to the Likert scale, adapted response scales, and open-ended questions. The questionnaire (English translation) is provided in
The thematic structure of the questionnaire included the following topics:
Need for support
Satisfaction with health care situation
Sociodemographic characteristics
Burden of environmental conditions
Burden of PAD and other diseases
Pain-free walking distance
Clinical characteristics
Preferences regarding offers to support patients with PAD
Smartphone usage, knowledge about health apps, and health app usage
Design categories in health apps to support patients with PAD
The detailed classification of the topics is shown in
We performed descriptive data analysis using SPSS (Version 23; IBM Corp). Variables are presented as frequencies and percentages or as means and standard deviations. Variables were compared using an unpaired
Overall, the need for more medical support in patients with PAD was identified (
Current perceptions of central aspects of medical care and need for support in patients with peripheral arterial disease.
Items | Total responses, |
40-49 years, |
50-59 years, |
60-69 years, |
70-79 years, |
>80 years, |
|
|
N=304 | n=18 | n=58 | n=102 | n=85 | n=38 | |
|
|||||||
|
Yes | 180 (59.2)a | 8 (44.5)b | 31 (53.4)b | 60 (58.8)b | 49 (57.6)b | 29 (76.3) |
|
|||||||
|
Completely dissatisfied | 50 (16.4) | 2 (11.1) | 16 (27.6) | 12 (11.8) | 10 (11.8) | 9 (23.7) |
|
Rather dissatisfied | 112 (36.8) | 8 (44.4) | 20 (34.5) | 37 (36.3) | 36 (42.4) | 11 (28.9) |
|
Neither dissatisfied nor satisfied | 63 (20.7) | 2 (11.1) | 12 (20.7) | 24 (23.5) | 20 (23.5) | 5 (13.2) |
|
Rather satisfied | 46 (15.1) | 2 (11.1) | 7 (12.1) | 18 (17.6) | 12 (14.1) | 6 (15.8) |
|
Very satisfied | 33 (10.9) |
4 (22.2) | 3 (5.2) | 11 (10.8) | 7 (8.2) | 7 (18.4) |
|
|||||||
|
Yes | 77 (25.3) | 8 (44.4) | 14 (24.1) | 24 (23.5) | 22 (25.9) | 8 (21.1) |
|
|||||||
|
Yes | 40 (13.2) | 3 (16.7) | 8 (13.8) | 9 (8.8) | 14 (16.5) | 6 (15.8) |
|
|||||||
|
Yes |
13 (4.3) |
0 (0) | 3 (5.2) | 4 (3.9% | 3 (3.5) | 3 (7.9) |
|
|||||||
|
Yes |
36 (11.8) |
2 (11.1) | 5 (8.6) | 15 (14.7) | 9 (10.6) | 5 (13.2) |
|
|||||||
|
Yes | 79 (26.0) | 3 (16.7) | 16 (27.6) | 32 (31.4) | 21 (24.7) | 7 (18.4) |
aThe percentage is based on the total number of responses for the associated item.
bThe percentage is based on the total number of people in the age group.
cIn the questionnaire, we used the term supervised walking training instead of the technical term supervised exercise therapy (SET) because the German word “Gehtraining” is more established in clinical practice.
Half of the patients (n=157, 51.6%) were smartphone users. Health apps were used by only a minority of patients (n=17, 5.7%). However, almost half (n=146, 48%) of all participants said they had already heard about health apps for smartphones that are designed to support health improvement.
The proportion of men and women who used a smartphone was comparable (n=159, 52.2% versus n=154, 50.5%,
Among those who had a low to upper-medium educational attainment (≤17 years of education), we did not see notable differences between users of smartphones and nonusers (
Overall, patients tended to feel “quite burdened” (n=98, 32.2%) to “very burdened” (n=62, 20.4%) by their PAD. In addition to PAD, patients were mainly affected by diseases of the musculoskeletal system (mean 2.32, SD 1.63), diseases of the cardiovascular system (mean 2.14, SD 1.50) and respiratory diseases (mean 1.54, SD 1.43).
The burden of environmental conditions was indicated by a mean of 0.90 (SD 0.63), which corresponds to a low burden of environmental conditions. Patients were mainly affected by environmental conditions such as “financial worries” (mean 1.32, SD 1.28), followed by “constant responsibility for their family” (mean 1.23, SD 1.22) and “household” (mean 1.23, SD 5.85), but the standard deviation for the “household” item was conspicuously large. The group of patients without a smartphone felt somewhat less burdened, both in terms of burden of disease and burden of environmental conditions (
In
Health status and risk factors of patients with peripheral arterial disease divided into all patients, smartphone users, and non–smartphone users.
Health status or risk factor | All patients | Smartphone users | Non–smartphone users | ||
|
n=304 | n=157 | n=147 |
|
|
|
<200 m | 101 (33.2)a | 53 (52.5)b | 48 (47.5)b | .83 (0.045) |
|
200-1000 m | 85 (28.0) | 47 (55.3) | 38 (44.7) | .59 (0.289) |
|
>1000 m | 88 (28.9) | 43 (48.9) | 45 (51.1) | .97 (0.001) |
|
I do not know | 30 (9.9) | 14 (46.7) | 16 (53.3) | .95 (0.004) |
|
n=299 | n=155 | n=144 |
|
|
|
Stage I | 125 (41.8) | 66 (52.8) | 59 (47.2) | .75 (0.100) |
|
Stage IIa | 44 (14.7) | 28 (63.6) | 16 (36.4) | .28 (1.158) |
|
Stage IIb | 103 (34.4) | 52 (50.5) | 51 (49.5) | .97 (0.001) |
|
Stage III | 7 (2.3) | 5 (71.4) | 2 (28.6) | .78 (0.075) |
|
Stage IV | 20 (6.7) | 4 (20.0) | 16 (80.0) | .10 (2.747) |
|
n=176 | n=90 | n=86 |
|
|
|
Underweight ( |
7 (4.0) | 2 (2.2) | 5 (5.8) | .78 (0.075) |
|
Normal (18.5 |
55 (31.2) | 27 (30.0) | 28 (32.6) | .96 (0.002) |
|
Overweight (25.0 |
69 (39.2) | 36 (52.2) | 33 (38.4) | .93 (0.007) |
|
Obese ( |
45 (25.6) | 25 (27.8) | 20 (23.3) | .75 (0.100) |
|
n=275 | n=142 | n=133 |
|
|
|
Yes | 86 (31.3) | 47 (33.1) | 39 (29.3) | .65 (0.210) |
|
Not anymore | 39 (14.2) | 19 (13.4) | 20 (15.0) | .96 (0.003) |
aPercentage is based on the number of responses for the associated health status or risk factor (pain-free walking distance, disease severity, BMI, smoking).
bPercentage is based on the total number of observations within the associated group of health outcomes or risk factors, regardless of smartphone use.
Based on the severity of the disease, 42% (n=128) were in Fontaine Stage I (corresponding to mild PAD), 15% (n=46) were in Stage IIa, 34% (n=103) were in Stage IIb, 2% (n=6) were in Stage III, and 7% (n=21) were in Stage IV (corresponding to very severe PAD). On average, patients in the smartphone group (mean 2.05, SD 1.06) and patients in the non–smartphone group (mean 2.30, SD 1.31) had mild PAD. However, in the non–smartphone group, there were more cases of severe PAD (Stage IV, 20% [n=61] versus 80% [n=243],
In total, more than one-third (n=119, 39.2%) of the participants were overweight, and an additional 26% (n=79) were obese. Normal weight was documented in 31% (n=94) of the participants, and 4% (n=12) of the participants were underweight.
Almost half of the participants (n=140, 46%) had smoked at one stage of their life, and of these participants, 31% (n=94) were current smokers and 14% (n=43) had already quit smoking. With regard to smoking behavior, the smartphone users and nonusers did not show substantial differences (
When asked how likely it was that they would use the listed services, participants indicated that they were most likely to use a “training app” on their smartphone (mean 3.18, SD 1.28), followed by “informational material” (mean 2.83, SD 1.48) and “training groups with instructions” (mean 2.53, SD 1.45). “Online platforms” (mean 1.73, SD 1.10) and “support groups” (mean 1.87, SD 1.87) were the response options that participants indicated they were least likely to use. The probability of making use of the listed options for patients with PAD is summarized in
Descriptive analysis of user preferences in terms of offered app components for patients with peripheral arterial disease (refers to Question 15 of the questionnaire). Note that multiple choices were possible.
Descriptive analysis of user-reported relevance in terms of health app components that would assist patients with peripheral arterial disease performing supervised walking training. The analysis refers to question 15 of the questionnaire. Note that multiple choices were possible. In the questionnaire, we used the term "supervised walking training" instead of the technical term "supervised exercise therapy" (SET) because the German word “Gehtraining” is more established in clinical practice.
Age was only found to have an effect on the answer to “reminder to perform walking training (SET).” The older the participants were, the more they preferred a reminder function of a health app (
The ranking of the individual components differed slightly depending on the severity of the disease. For participants in Stage IIa, the ranking was as follows: (1) interaction with physicians and therapists, (2) information about SET, (3) feedback about SET, (4) choosing goals, (5) suggestions for goal setting, (6) reminders, and (7) interaction with other patients. Interaction with physicians and therapists was less important for patients in Stages I, IIb, and IV.
Information regarding SET and feedback about SET were moderately to fairly important for patients regardless of disease stage. Interactions with other patients were considered least important by participants in Stages I to III. For Stage IV participants, interactions with other participants were considered more important than choosing goals, reminders, and suggestions for goal setting. The core results of the study are summarized in
Relevance of components of health apps to support patients with peripheral arterial disease by disease severity according to Fontaine stages [
Components of health apps to support patients | Stage I | Stage IIa | Stage IIb | Stage III | Stage IV | |||||
|
Patients, n | Mean (SD) | Patients, n | Mean (SD) | Patients, n | Mean (SD) | Patients, n | Mean (SD) | Patients, n | Mean (SD) |
Information about walking traininga | 113 | 3.32 (1.30) | 42 | 3.66 (1.26) | 97 | 3.28 (1.37) | 6 | 2.66 (1.21) | 20 | 2.80 (1.15) |
Feedback about walking training | 111 | 3.36 (1.36) | 42 | 3.59 (1.30) | 99 | 3.12 (1.40) | 7 |
2.57 (1.27) | 19 | 3.36 (1.38) |
Choosing walking training goals on my own | 110 | 3.14 (1.36) | 40 | 3.35 (1.16) | 95 | 3.03 (1.30) | 6 | 2.16 (1.47) | 20 | 2.70 (1.26) |
Interaction with physicians and therapists | 107 | 3.10 (1.42) | 39 | 3.71 (1.21) | 95 | 2.91 (1.38) | 7 | 2.42 (1.27) | 20 | 2.75 (1.25) |
Reminder to perform walking training | 112 | 3.08 (1.32) | 41 | 3.17 (1.30) | 100 | 2.99 (1.26) | 7 | 2.57 (1.27) | 19 | 2.42 (1.12) |
Getting suggestions for walking training goals | 110 | 2.90 (1.41) | 40 | 3.32 (1.36) | 98 | 2.69 (1.40) | 7 | 2.00 (1.15) | 19 | 2.31 (1.00) |
Interaction with other patients | 111 | 2.39 (1.28) | 39 | 3.00 (1.31) | 97 | 2.30 (1.27) | 7 | 1.71 (1.11) | 19 | 2.73 (1.19) |
aIn the questionnaire, we used the term “supervised walking training” instead of the technical term “supervised exercise therapy” because the German word “Gehtraining” is more established in clinical practice.
Summary of core results.
Research question | Summary of core results |
1 | A need for support was determined. Receiving more educational health information, increased support in the form of prescribed medication, and help in terms of implementing supervised exercise therapy (SET) are the most desired actions for improving the care of patients with PAD. |
2 |
Half of the participants use smartphones. For them, mobile interventions to support SET and medication can be a relevant treatment component. Patients aged >70 years are less likely to use smartphones than younger patients. With regard to characteristics such as sex, education, profession, BMI, smoking behavior, exposure to illness or the environment, or the current state of illness, the data did not reveal any significant differences between smartphone users and nonusers within the patient population. |
3 |
Interest in smartphone-supported training is present, even for people who do not currently use a smartphone. Health app components such as “information,” “monitoring,” and “feedback” were the most relevant for patients with PAD. Other components such as “choosing goals,” “interaction with physicians and therapists,” “interaction with other patients,” and “reminders and suggestions for goal setting” were less relevant for the patients and should be selectable on demand according to patient preference. |
More than half (53.2%) of the participants were less than satisfied or completely unsatisfied with their health care situation. Patients do not feel well-informed enough in terms of SET and their prescribed medication. Since both are cornerstones in the treatment of PAD, this finding is alarming in terms of secondary prevention and long-term outcomes. The lack of educational background is expected to be associated with poor medication and exercise compliance, impeding the successful empowerment of patients. Previous research found that mHealth interventions improve adherence to prescribed medication in patients with cardiovascular disease [
Our results show an evident need for action to support patients with PAD in secondary prevention. A major goal should include patient empowerment. The demand for more support was found in all subgroups, independent of age or severity of disease. Institutional barriers in particular (eg, a lack of training groups and primary health care providers providing care to patients with PAD) limit the likelihood of an adequate health care offer for affected patients. Previous studies already reported the undersupply of primary health care for patients with PAD in general as well as those from various sociodemographic backgrounds [
Personal barriers are primarily linked to poor knowledge about the disease and low empowerment. Mobile interventions might play an ever-increasing role, since they are widely accessible and have a low threshold for access. Time resources for consultations between patients and doctors are limited. In clinical practice, lifestyle recommendations are made within a few minutes. To increase the probability of patients’ adherence and their empowerment to take responsibility for their own health, personalized approaches are promising [
The use of patient-centered methods to develop persuasive strategies for mHealth interventions [
The idea of using a training app was of strong interest, even to participants who currently do not use smartphones. Based on this preference for digital support, the need to design and implement motivating tools that provide educational information was identified. In this setting, the analysis of assessed data regarding usage and user preferences might also be helpful in the feedback process. The current study also demonstrated patients’ priorities regarding important features, such as the opportunity to set individual goals or to get in touch with professionals, including physicians or therapists. Conspicuously, the offered support of interactions with other patients tended to perform poorly, both as a proposed digital chat component in an app and as a component of an analog intervention in the sense of a support group. A previous study showed a high acceptance of electronic health information and disease-related community forums in patients with PAD [
Depending on the severity of their disease, the participants’ ranking of useful components within a digital intervention app differed slightly. Although “information,” “monitoring,” and “feedback” should be fixed components within apps that support patients with PAD, other components, such as “goal selection,” “interaction with physicians or therapists,” “interaction with other patients,” “reminders for structured walking training,” and “suggestions for individual goals” can be offered additionally, as a voluntary, selectable feature according to patients’ preferences.
In addition to tools for the implementation of SET, supplementary components that support medication use, healthier nutrition, or cessation of smoking appear useful. Considering the BMI of our study population compared to the German population in 2017 (overweight: 35.9%; obese: 18.1%), the sample was above the national average [
The efficacy of digital interventions is significantly influenced by an individual’s engagement with, for example, a specific app [
Another consideration is the age of the target group, which often includes older patients with noncommunicable diseases. The mean age of participants in this study was 67 years. More than half of the patients aged 70 years or older were not reachable by mobile interventions. This finding has to be taken into consideration when designing digital interventions. Similar results regarding the use of digital interventions in older patients were previously observed [
This analysis merely serves as an empirically sound description of the addressed problem and identifies approaches to improve the care of patients with PAD. This study included only a small sample; thus, the results cannot be generalized.
The study focused on a selection of personal characteristics to avoid time-consuming interviews before starting the actual clinical examination. Other characteristics of patients with PAD that may affect the need for and responsiveness to interventions supporting SET in daily living (eg, self-efficacy, motivation to change, race/ethnicity, income, social capital) were not examined. Based on the present study findings, we developed an app to support SET for patients with PAD [
This study also did not address environmental factors. This is a potential point of criticism. With regard to health, in addition to personal characteristics, environmental characteristics play an important role in the implementation of health-promoting and therapy-compliant behaviors [
Additionally, we offered only an abridged list of design components for an app, rather than all components that are conceivable in principle. The additional demonstration of mock-ups and prototypes to determine the preferences and desires of the participants might be useful in future surveys. Although user-centered methods for app design that combine different methods (eg, design thinking research) are time-consuming, they may improve the effectiveness of behavior-change support systems [
The description of the sociodemographic characteristics of our participants, grouped into smartphone users and non–smartphone users, showed that participants younger than the age of 70 years used smartphones much more often than older participants. Hence, the latter group of patients is hard to reach with mobile interventions. To improve the success of therapy for non–smartphone users, analog interventions (supporting medication use and the implementation of SET for older patients) should also be offered. Except for age, we found no noticeable differences between smartphone and non–smartphone users. The analysis of patient characteristics (ie, sex, education, burden, and health status) with respect to smartphone use, did not reveal any other significant differences between smartphone users and nonusers.
This survey of patients with PAD indicates the necessity of improving the care situation of these patients. A need for support can be determined and identified with regard to educational and general support deficiencies. This need includes a better understanding of the prescribed medication and the necessary implementation of SET as a central pillar of the guideline-oriented care of patients with PAD.
There also exists a great interest in mobile support services. To improve the care situation of these patients, mobile interventions are promising. The large reach and wide availability of these interventions are major advantages.
Questionnaire.
Classification of topics.
mobile Health
peripheral arterial disease
supervised exercise program
supervised exercise therapy
JL contributed to study design, data collection, data analysis, data interpretation, manuscript writing, and final approval. JS contributed to the literature search, figures, data collection, manuscript writing, and final approval. TK contributed to the literature search, figures, tables, and final approval. IKA contributed to study design, manuscript writing, and final approval. GU contributed to the literature search, figures, data collection, and final approval. MS contributed to the data collection, data analysis, manuscript writing, and final approval. CR contributed to the data collection, data analysis, manuscript writing, and final approval. RAJ contributed to the literature search, data analysis, manuscript writing, and final approval. SM contributed administrative support, data analysis, data interpretation, manuscript writing, and final approval. TR contributed administrative support, data interpretation, manuscript writing, and final approval. KP contributed to study design, data collection, data analysis, data interpretation, manuscript writing, and final approval.
None declared.