This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
Traditional secondary prevention programs often fail to produce sustainable behavioral changes in everyday life. Peer-modeling interventions and integration of peer experiences in health education are a promising way to improve long-term effects in behavior modification. However, effects of peer support modeling on behavioral change have not been evaluated yet. Therefore, we implemented and evaluated a website featuring patient narratives about successful lifestyle changes.
Our aim is to examine the effects of using Web-based patient narratives about successful lifestyle change on improvements in physical activity and eating behavior for patients with coronary heart disease and chronic back pain 3 months after participation in a rehabilitation program.
The lebensstil-aendern (“lifestyle-change”) website is a nonrestricted, no-cost, German language website that provides more than 1000 video, audio, and text clips from interviews with people with coronary heart disease and chronic back pain. To test efficacy, we conducted a sequential controlled trial and recruited patients with coronary heart disease and chronic back pain from 7 inpatient rehabilitation centers in Germany. The intervention group attended a presentation on the website; the control group did not. Physical activity and eating behavior were assessed by questionnaire during the rehabilitation program and 12 weeks later. Analyses were conducted based on an intention-to-treat and an as-treated protocol.
A total of 699 patients were enrolled and 571 cases were included in the analyses (control: n=313, intervention: n=258; female: 51.1%, 292/571; age: mean 53.2, SD 8.6 years; chronic back pain: 62.5%, 357/571). Website usage in the intervention group was 46.1% (119/258). In total, 141 trial participants used the website. Independent
Usage of the lebensstil-aendern website corresponds to more positive lifestyle changes. However, as-treated analyses do not allow for differentiating between causal effects and selection bias. Despite these limitations, the trial indicates that more than occasional website usage is necessary to reach dose-response efficacy. Therefore, future studies should concentrate on strategies to improve adherence to Web-based interventions and to encourage more frequent usage of these programs.
Noncommunicable and chronic diseases, such as coronary heart disease or chronic back pain, create a substantial personal and public burden globally. Diseases of the circulatory system account for 35% of deaths in Europe [
Peer-modeling interventions and integration of peer support and peer experiences in health education are a promising way to improve long-term effects in disease management [
Patient narratives about illness experiences can be found on various Web forums, such as video and social networking websites (eg, YouTube and Facebook), and on publicly funded websites such as the healthtalkonline website (formerly DIPEx) [
The website lebensstil-aendern (“lifestyle-change”) is a nonrestricted, no-cost, German language website that provides more than 1000 video, audio, and text clips from interviews with patients living with coronary heart disease and chronic back pain. The website has been online since November 2011 and is certified with the Health on the Net Foundation Code of Conduct (HONcode), a certificate addressing reliability and trustworthiness of medical information on the Internet [
We interviewed 39 people with coronary heart disease and 27 with chronic back pain who reported that they had successfully modified their behavior in at least 1 lifestyle domain for more than 6 months. These problem-centered interviews [
The interviews lasted between 1 to 3 hours. We extracted short clips addressing different aspects of lifestyle modification. All clips are provided with text and may also contain a video or audio clip depending on the interviewees’ preferences. Before publication, patients were contacted again to decide which clips should be published, whether statements should be removed, and if they wanted to use a pseudonym or their real name. For quality assessment and to avoid potentially harmful suggestions, experienced cardiologists and orthopedists reviewed all patient statements before publication.
The website is structured using a horizontal menu with links to the home page, a news page, the patient narratives, a forum, background information, and a contact form (see
The news page is updated several times a month by the project team and provides news about recent research results and announcements of new patient narratives, recipes, and project-related updates. The patient narratives are divided into 2 indication-specific modules and structured using a vertical menu with the following categories: overcoming your “weaker self”, getting active, eating healthier, reducing stress, getting support, dealing with the disease, quitting smoking (only in the coronary heart disease module), and keeping the spine in mind (only in the chronic back pain module). In addition to the menu, suitable clips can be found via a filter for age and sex, a tag cloud, searching for keywords, or through overview pages for each patient. Users can comment on single clips and evaluate them (see
The forum contains the same categories as the patient narratives. Posts are accessible for everyone, but users must be registered and logged in to post to the forum.
Screenshot of the lebensstil-aendern home page.
Screenshot of a video subpage from the coronary heart disease module. On the left side is the vertical menu with the tag cloud beneath. Below the video player are buttons for evaluation and short information text about the patient’s health condition.
We recruited patients in 7 inpatient rehabilitation centers from September 2012 to August 2013. Patients had to be diagnosed with coronary heart disease (International Statistical Classification of Diseases and Related Health Problems, ICD-10 I20-25) or chronic back pain (ICD-10 M50-54), have sufficient German language skills, and have no disabling cognitive deficits. All patients meeting the inclusion criteria were enrolled and sequentially assigned to the control group and intervention group, respectively (see
Flowchart of study participants.
Patients in the intervention group were invited to join a presentation about the website. During the 1-hour presentation, the project team introduced the aims and scopes of the project and provided information on how to find suitable content on the website. They also discussed how to register and post on the forum, and addressed issues of data protection, including anonymity. To give the participants an idea of the website content, 1 to 3 patient narrative videos were shown. To further reduce barriers to using the website, the intervention group received a detailed printed manual and was encouraged to contact the project team in case of problems or questions. Those participants who provided an email address received an email reminder with the link to the website 4 weeks after the presentation. Patients in the control group received no intervention.
Both the intervention and control groups completed a questionnaire at some point during participation in a rehabilitation program. Questions addressed sociodemographic characteristics (eg, age, sex, education, and income), diagnosis, body mass index (BMI), and baseline behavior for physical activity and eating routine. The latter 2 were measured on a numerical scale of 0 to 10 asking about the frequency of exercise and the attention paid to a healthy diet. The follow-up questionnaire also included 2 questions about exercise frequency and attention paid to healthy diet. Additionally, patients were asked to rate, on a 5-point Likert scale ranging from slightly deteriorated (–1) to improved substantially (3), their improvements in physical activity (frequency, regularity, integration in daily routine) and eating behavior (eating more healthy foods, avoiding unhealthy foods, eating smaller portions, using less fat for cooking). Lastly, usage of and satisfaction with the website were assessed.
Statistical analysis was conducted using SPSS Statistics version 21 (IBM Corp, Armonk, NY, USA). Uncertainties during data entry (eg, the participants’ handwriting was difficult to decipher or more than 1 box marked as an answer) were discussed by the team and resolved by consensus. Seven participants were excluded for not matching the ICD-10 diagnoses I20-25 or M50-54 and all 118 dropout cases and 3 other cases were excluded for having more than 30% missing data. Missing data in the remaining sample were estimated using multiple imputations under a fully conditional specification and 10 iterations. Because 41.3% (236/571) cases had missing values in any of the variables to be imputed, we imputed 60 datasets [
For estimating improvements in exercise frequency and attention paid to a healthy diet, we calculated mean differences (Δ) between the 2 measure points and compared these mean differences in independent
A total of 699 participants filled out the first questionnaire during rehabilitation. During follow-up, 118 patients (16.8%) dropped out. Dropout was higher among patients with coronary heart disease (21.5% vs 14.1%, χ2
1=6.3,
In total, 24 of 313 control group participants (7.7%) and 164 of 258 intervention group participants (63.6%) claimed to know the website. Nevertheless, approximately one-quarter of these patients (46/188, 24.5%) never visited the website. Overall, 119 of 258 in the intervention group (46.1%) and 22 of 313 in the control group (7.0%) visited the website; 1 participant (0.7%) stated he used the website 3 to 4 times a week, 6 participants (4.3%) stated they used it once or twice a week, 60 (42.6%) used it once or twice a month, and 74 (52.5%) accessed the website at least once.
Participants had a mean age of 53.2 years (SD 8.6), 51.1% (292/571) were women, and 62.5% (357/571) had been diagnosed with chronic back pain (
There were no significant differences in outcome variables between the groups (see
Baseline characteristics—intention-to-treat analysis.
Variable | Control group |
Intervention group |
Total |
|
χ2 1 |
|
|
Age (years), mean (SD) | 52.7 (8.1) | 53.8 (9.2) | 53.2 (8.6) | –1.52 |
|
.13 | |
|
|
|
|
|
|
|
|
|
Female | 170 (54.3) | 122 (47.3) | 292 (51.1) |
|
|
|
|
Male | 143 (45.7) | 136 (52.7) | 279 (48.9) |
|
0.2 | .69 |
|
|
|
|
|
|
|
|
|
Coronary heart disease | 115 (36.7) | 99 (38.4) | 214 (37.5) |
|
|
|
|
Chronic back pain | 198 (63.3) | 159 (61.6) | 357 (62.5) |
|
2.8 | .10 |
|
|
|
|
|
|
|
|
|
≤10 years of school | 236 (75.5) | 172 (66.8) | 408 (71.5) |
|
|
|
|
>10 years of school | 77 (24.5) | 86 (33.2) | 163 (28.5) |
|
4.9 | .03 |
Net equivalent income per month (€), mean (SD) | 1679 (621) | 1713 (633) | 1695 (627) | –0.62 |
|
.56 | |
BMI (kg/m2), mean (SD) | 28.3 (5.3) | 27.9 (5.2) | 28.1 (5.2) | 0.82 |
|
.41 | |
Exercise frequency (scale 0-10), mean (SD) | 3.89 (2.88) | 4.27 (2.81) | 4.06 (2.85) | –1.61 |
|
.11 | |
Attention paid to a healthy diet (scale 0-10), mean (SD) | 5.61 (2.37) | 5.59 (2.60) | 5.60 (2.47) | 0.10 |
|
.92 |
Independent
Dependent variable | Control group |
Intervention group |
Mean difference |
|
95% CI | Cohen’s |
|
|
|
|
|
|
|
|
|
|
Frequency of doing exercise, Δ (t2–t1) | 0.77 | 0.51 | –0.26 | 3.17 | –0.79, 0.27 | –0.08 |
|
Improvements in physical activity frequency, mean | 1.26 | 1.33 | 0.07 | 0.92 | –0.09, 0.23 | 0.08 |
|
Improvements in physical activity regularity, mean | 1.19 | 1.33 | 0.14 | 0.98 | –0.03, 0.30 | 0.14 |
|
Improvements in physical activity in daily routine, mean | 1.23 | 1.31 | 0.08 | 0.97 | –0.08, 0.24 | 0.08 |
|
|
|
|
|
|
|
|
|
Attention paid to a healthy diet, Δ (t2–t1) | 1.10 | 1.20 | 0.11 | 2.34 | –0.29, 0.51 | 0.04 |
|
Improvements in eating more healthy foods , mean | 1.31 | 1.32 | 0.01 | 0.88 | –0.14, 0.17 | 0.01 |
|
Improvements in eating less unhealthy foods, mean | 1.32 | 1.39 | 0.08 | 0.95 | –0.09, 0.24 | 0.08 |
|
Improvements in eating smaller portions, mean | 1.08 | 1.10 | 0.03 | 0.89 | –0.13, 0.18 | 0.03 |
|
Improvements in using less fat for cooking, mean | 1.17 | 1.30 | 0.13 | 0.88 | –0.03, 0.30 | 0.14 |
Multivariate linear regression—intention-to-treat analysis. Each line starting with a dependent variable contains information from one regression analysis (N=571) and provides model fit (
Dependent variable |
|
Group | Further independent predictors | ||||
|
|
B (95% CI) | β | Variable | B (95% CI) | β | |
|
|
|
|
|
|
|
|
|
Frequency of doing exercise, Δ (t2–t1) | .42 | 0.01 (–0.40, 0.42) | .001 | Indication | 0.63 (0.12, 1.13) | .10 |
|
|
|
|
|
Age | –0.40 (–0.65, –0.14) | –.11 |
|
|
|
|
|
Baseline behavior | –0.70 (–0.78, –0.63) | –.63 |
|
Improvements in physical activity frequency | .06 | 0.10 (–0.06, 0.26) | .05 |
|
|
|
|
|
|
|
|
Age | –0.18 (–0.28, –0.09) | –.17 |
|
|
|
|
|
Income | 0.04 (0.01, 0.07) | .13 |
|
|
|
|
|
Baseline behavior | –0.03 (–0.06, 0.00) | –.09 |
|
Improvements in physical activity regularity | .06 | 0.18 (0.02, 0.34) | .09 | Indication | 0.21 (0.01, 0.42) | .11 |
|
|
|
|
|
Age | –0.18 (–0.28, –0.08) | –.16 |
|
|
|
|
|
Baseline behavior | –0.03 (–0.06, 0.00) | –.10 |
|
Improvements in physical activity in daily routine | .06 | 0.11 (–0.05, 0.27) | .08 | Age | –0.13 (–0.23, –0.03) | –.12 |
|
|
|
|
|
Education | –0.28 (–0.46, –0.09) | –.13 |
|
|
|
|
|
|
|
|
|
Attention paid to a healthy diet, Δ (t2–t1) | .44 | 0.12 (–0.19, 0.42) | .02 | Baseline behavior | –0.63 (–0.70, –0.57) | –.65 |
|
Improvements in eating more healthy foods | .08 | 0.03 (–0.12, 0.18} | .02 | BMI | 0.04 (0.02, 0.05) | .20 |
|
Improvements in eating less unhealthy foods | .09 | 0.08 (–0.08, 0.23) | .04 | Indication | 0.29 (0.09, 0.48) | .15 |
|
|
|
|
|
BMI | 0.03 (0.02, 0.05) | .18 |
|
Improvements in eating smaller portions | .09 | 0.05 (–0.10, 0.20) | .03 | BMI | 0.05 (0.04, 0.07) | .29 |
|
Improvements in using less fat for cooking | .07 | 0.16 (0.01, 0.31) | .09 | Indication | 0.20 (0.01, 0.39) | 0.11 |
|
|
|
|
|
Education | –0.22 (–0.40, –0.05) | –.11 |
|
|
|
|
|
BMI | 0.03 (0.02, 0.04) | .19 |
Users had higher levels of education than nonusers. We did not find any significant differences in baseline variables between nonusers and users in the as-treated analysis (see
Baseline characteristics—as-treated analysis.
Variable | Nonusers |
Users |
|
χ2 1 |
|
|
Age (years), mean (SD) | 53.5 (8.6) | 52.2 (8.4) | –1.56 |
|
.12 | |
|
|
|
|
|
|
|
|
Female | 217 (50.5) | 75 (53.2) |
|
|
|
|
Male | 213 (49.5) | 66 (46.8) |
|
0.3 | .57 |
|
|
|
|
|
|
|
|
Coronary heart disease | 165 (38.4) | 49 (34.8) |
|
|
|
|
Chronic back pain | 265 (61.6) | 92 (65.2) |
|
0.6 | .44 |
|
|
|
|
|
|
|
|
≤10 years of school | 317 (73.7) | 92 (65.2) |
|
|
|
|
>10 years of school | 113 (26.3) | 49 (34.8) |
|
3.9 | .049 |
Net equivalent income per month (€), mean (SD) | 1667 (626) | 1780 (622) | –1.81 |
|
.07 | |
BMI (kg/m2), mean (SD) | 27.9 (5.1) | 28.8 (5.5) | 1.72 |
|
.09 | |
Frequency of doing exercise, (scale 0-10), mean (SD) | 4.09 (2.89) | 3.98 (2.74) | –0.38 |
|
.71 | |
Attention paid to a healthy diet (scale 0-10), mean (SD) | 5.59 (2.45) | 5.62 (2.54) | 0.14 |
|
.89 |
Website use was associated with larger increases in physical activity: users were more successful in integrating physical activity into their daily routine and in improving their physical activity regularity. We did not find a significantly higher mean difference in the frequency of doing exercise between baseline and follow-up 12 weeks later.
Website use was not associated with higher mean differences in the attention paid to a healthy diet, but it was with more success in dietary behaviors (ie, using less fat for cooking) (
Independent
Dependent variable | Nonusers |
Users |
Mean difference |
|
95% CI | Cohen’s |
|
|
|
|
|
|
|
|
|
|
Frequency of doing exercise, Δ (t2–t1) | 0.60 | 0.81 | 0.21 | 0.67 | –0.40, 0.82 | 0.07 |
|
Improvements in physical activity frequency, mean | 1.26 | 1.40 | 0.14 | 1.56 | –0.04, 0.32 | 0.15 |
|
Improvements in physical activity regularity, mean | 1.20 | 1.42 | 0.22 | 2.33 | 0.04, 0.41 | 0.23 |
|
Improvements in physical activity in daily routine, mean | 1.21 | 1.43 | 0.21 | 2.24 | 0.03, 0.40 | 0.22 |
|
|
|
|
|
|
|
|
|
Attention paid to a healthy diet, Δ (t2–t1) | 1.09 | 1.32 | 0.23 | 0.99 | –0.23, 0.69 | 0.10 |
|
Improvements in eating more healthy foods, mean | 1.28 | 1.43 | 0.15 | 1.64 | –0.03, 0.33 | 0.16 |
|
Improvements in eating less unhealthy foods, mean | 1.31 | 1.47 | 0.16 | 1.65 | –0.03, 0.34 | 0.16 |
|
Improvements in eating smaller portions, mean | 1.04 | 1.22 | 0.17 | 1.91 | –0.05, 0.35 | 0.19 |
|
Improvements in using less fat for cooking, mean | 1.18 | 1.38 | 0.20 | 2.17 | 0.02, 0.38 | 0.21 |
In the multivariate regression analyses (
Multivariate linear regression—as-treated analysis. Each line starting with a dependent variable contains information from one regression analysis (N=571) and provides model fit (
Dependent variable |
|
Occasional website usage | Frequent website usage | Further independent predictors | |||||
|
|
B (95% CI) | β | B (95% CI) | β | Variable | B (95% CI) | β | |
|
|
|
|
|
|
|
|
|
|
|
Frequency of doing exercise, Δ (t2–t1) | .42 | –0.13 (–0.74, 0.49) | –.01 | 0.28 (–0.36, 0.92) | .03 | Indication | 0.63 (0.13, 1.14) | .10 |
|
|
|
|
|
|
|
Age | –0.41 (–0.66, –0.15) | –.11 |
|
|
|
|
|
|
|
Baseline behavior | –0.70 (–0.77, –0.62) | –.63 |
|
Improvements in physical activity frequency | .06 | –0.005 (–0.23, 0.22) | –.002 | 0.21 (–0.03, 0.45) | .07 | Age | –0.18 (0.28, 0.09) | –.17 |
|
|
|
|
|
|
|
Income | 0.04 (0.01, 0.07) | .13 |
|
Improvements in physical activity regularity | .06 | 0.12 (–0.12, 0.36) | .04 | 0.27 (0.02, 0.51) | .09 | Indication | 0.21 (0.01, 0.41) | .11 |
|
|
|
|
|
|
|
Age | –0.18 (–0.28, –0.08) | –.16 |
|
|
|
|
|
|
|
Baseline behavior | –0.03 (–0.06, 0.00) | –.09 |
|
Improvements in physical activity in daily routine | .07 | 0.06 (–0.17, 0.30) | .02 | 0.39 (0.14, 0.63) | .13 | Age | –0.13 (–0.23, –0.03) | –.12 |
|
|
|
|
|
|
|
Education | –0.27 (–0.46, –0.09) | –.13 |
|
|
|
|
|
|
|
|
|
|
|
Attention paid, a healthy diet, Δ (t2–t1) | .43 | –0.14 (–0.59, 0.31) | –.02 | 0.73 (0.26, 1.21) | .10 | Baseline behavior | –0.64 (–0.71, –0.58) | –.66 |
|
Improvements in eating more healthy foods | .09 | –0.06 (–0.28, 0.17) | –.02 | 0.36 (0.12, 0.59) | .12 | BMI | 0.03 (0.02, 0.05) | .19 |
|
|
|
|
|
|
|
Baseline behavior | –0.04 (–0.07, 0.00) | –.10 |
|
Improvements in eating less unhealthy foods | .10 | 0.04 (–0.20, 0.27) | .01 | 0.32 (0.08, 0.56) | .11 | Indication | 0.29 (0.10, 0.48) | .15 |
|
|
|
|
|
|
|
BMI | 0.03 (0.02, 0.05) | .17 |
|
Improvements in eating smaller portions | .10 | 0.03 (–0.20, 0.25) | .01 | 0.28 (0.05, 0.51) | .10 | BMI | 0.05 (0.03, 0.06) | .28 |
|
Improvements in using less fat for cooking | .08 | 0.02 (–0.21, 0.25) | .01 | 0.40 (0.17, 0.64) | .14 | Indication | 0.20 (0.01, 0.39) | .11 |
|
|
|
|
|
|
|
Education | –0.21 (–0.39, –0.03) | –.10 |
|
|
|
|
|
|
|
BMI | 0.03 (0.02, 0.05) | .18 |
The aim of this study was to examine the effects of a Web-based intervention featuring patient narratives about successful lifestyle changes on physical activity and eating behavior for chronically ill coronary heart disease and back pain patients. We conducted a sequential controlled trial in which the intervention group participated in a presentation about the website during rehabilitation.
In the intention-to-treat analysis, there were no significant effects of the intervention in the bivariate analyses and only small interventional effects on physical activity regularity and on using less fat for cooking in the multivariate analyses. However, all but 1 (frequency of doing exercise) of the measured outcome variables showed positive tendencies in the expected direction. Comparing website users to nonusers in the as-treated analysis, we found an association between website usage and improvements in most physical activity and dietary behavior outcome variables. Multivariate regression analyses revealed that this association persists only in conjunction with frequent website usage (defined as having visited the website at least 3 times) not with occasional website usage.
A larger sample size, associated with a sufficiently large power, may have ensured the detection of even small intervention effects. In any case, effect sizes were consistently small and demand a closer look at possible reasons. First, the small intervention effects in the intention-to-treat analysis can be explained in part by the low usage of the website because less than half of the intervention group visited the website. The problem of low usage rates is well known and an often cited problem in trials on Web-based interventions [
In addition to the low utilization rates, the intervention dose was probably too low to result in behavioral modifications for most participants. The results of the as-treated analysis indicate that more than occasional website usage is necessary to reach dose-response efficacy. This finding is consistent with results from other studies [
Finally, although the integration of peer experiences is seen as promising in health education and disease management and meets the interest of patients with a chronic condition, the additional inclusion of further behavior modification strategies (eg, individual tailoring or providing feedback) may be required in a peer-modeling approach to show satisfactorily large effects on lifestyle behavior [
Future studies should concentrate on strategies to improve adherence to Web-based interventions and especially to induce more frequent usage of these programs. Individually tailored interventions may be a promising approach because these interventions, besides being more efficacious, have also been shown to stimulate more frequent use of Web-based interventions and to increase adherence [
We were able to assess behavioral change through self-reported nonvalidated measures only, which are subject to response bias. One important aim of rehabilitation programs is to increase awareness for unhealthy lifestyle behavior. Thus, recruiting the participants at this point of time might have led to an overestimation of the 2 baseline variables, which then would have a flattening effect on the mean difference between t2 and t1. Due to time restrictions in the research project, we could only observe the effects of the intervention 3 months after participation in the rehabilitation program. The long-term effects of the intervention remain unclear. Furthermore, we did not control for Internet literacy or Internet usage patterns, which might explain differences in website usage rates and website efficacy.
The as-treated analysis implicates positive results, but does not allow for a causal interpretation because nonmeasured variables associated with more frequent use of the website could account for the improved health behavior or successful patients might tend to more actively seek support and information and use a website such as the lebensstil-aendern website.
For the multivariate regression analyses, model fit was very low. This could either be due to variables accounting for behavioral change but not being included in the model or, considering that all outcome variables were single item variables, unreliable measurements contributing to the large error variances.
To our knowledge, our study is the first trial to test the efficacy of Web-based patient narratives on behavioral outcomes in coronary heart disease and chronic back pain patients. In our study, patients that use the website more frequently report more favorable health-related behavior and more marked improvements in physical activity and diet. Even if more motivated patients seek support and information more actively, for this patient group in particular, a website such as the lebensstil-aendern website appears to be a helpful tool.
Body mass index
International Statistical Classification of Diseases and Related Health Problems
The project “lebensstil-aendern.de—Videogestützte Internetplattform zur Unterstützung einer nachhaltigen Lebensstilmodifikation im Alltag” was funded by the German Pension Fund (Deutsche Rentenversicherung Bund) from September 2010 to March 2014 (funding code: 0422/00-40-65-50-22).
Rebecca Schweier wrote the manuscript. Cynthia Richter and Rebecca Schweier implemented the website and planned and conducted the trial together. Matthias Romppel helped in planning the trial and performed the statistical analysis with Rebecca Schweier. Eike Hoberg, Harry Hahmann, Inge Scherwinski, Gregor Kosmützky, and their teams did the screening in the rehabilitation centers, recruited the control group, and helped in conducting the trial. Gesine Grande managed the research project and supervised during each of its respective stages.
None declared.