Long-Term Effects of a Video-Based Smartphone App ("VIDEA Bewegt") to Increase the Physical Activity of German Adults: A Single-Armed Observational Follow-Up Study

Can mobile-health applications contribute to long-term increase in physical activity after medical rehabilitation?-A pilot-study

Due to the positive effects of rehabilitation declining over time, the aim of this study was to investigate the long-term physical activity level (PAL) following inpatient rehabilitation in relation to the use of a smartphone-based after-care program. 202 patients (mean Body Mass Index (BMI): 30,8 kg/m2; 61% female) with chronic diseases (e.g., diabetes mellitus, obesity, chronic low back pain, depression) were recruited between 08/2020 and 08/2021 in this single-arm observational study. All patients underwent a 3-week inpatient rehabilitation program. PAL (in total activity minutes/week) was measured with a validated (online) questionnaire (Freiburger Questionnaire on PA) after 3, 6, 9, and 12 months. App usage (online time, completion of a course) was recorded automatically and used to evaluate the app user behavior (adherence). A variety of socio-economic factors (age, sex, education level, income etc.) were collected to identify possible barriers of app use. Except for sex, no significant difference was observed for socio-economic factors regarding app usage behavior. Median PAL significantly increased after rehabilitation in the total cohort from 360 min/week (before rehabilitation) to 460 min/week 6 months after rehabilitation, then declined to 420 min/week 9 months after rehabilitation before falling below baseline level after 12 months. There was no significant difference in PAL between app users (45%, 91/202) and non-users (55%, 111/202), although app users tended to retain higher activity levels after 3 and 6 months, respectively. Overall, our study emphasizes the effectiveness of a 3-week rehabilitation program on PAL and the acceptance and usability of a smartphone-based after-care program in this patient group. The adherence to this 3-months after-care app program was acceptable (30%), with modest evidence supporting the effectiveness of app use to sustain PAL in the short term.

A Digital Lifestyle Coach (E-Supporter 1.0) to Support People With Type 2 Diabetes: Participatory Development Study

BACKGROUND

A healthy lifestyle, including regular physical activity and a healthy diet, is becoming increasingly important in the treatment of chronic diseases. eHealth interventions that incorporate behavior change techniques (BCTs) and dynamic tailoring strategies could effectively support a healthy lifestyle. E-Supporter 1.0 is an eCoach designed to support physical activity and a healthy diet in people with type 2 diabetes (T2D).

OBJECTIVE

This paper aimed to describe the systematic development of E-Supporter 1.0.

METHODS

Our systematic design process consisted of 3 phases. The definition phase included the selection of the target group and formulation of intervention objectives, and the identification of behavioral determinants based on which BCTs were selected to apply in the intervention. In the development phase, intervention content was developed by specifying tailoring variables, intervention options, and decision rules. In the last phase, E-Supporter 1.0 integrated in the Diameter app was evaluated using a usability test in 9 people with T2D to assess intervention usage and acceptability.

RESULTS

The main intervention objectives were to stimulate light to moderate-vigorous physical activities or adherence to the Dutch dietary guidelines in people with T2D. The selection of behavioral determinants was informed by the health action process approach and theories explaining behavior maintenance. BCTs were included to address relevant behavioral determinants (eg, action control, self-efficacy, and coping planning). Development of the intervention resulted in 3 types of intervention options, consisting of motivational messages, behavioral feedback, and tailor-made supportive exercises. On the basis of IF-THEN rules, intervention options could be tailored to, among others, type of behavioral goal and (barriers to) goal achievement. Data on these variables could be collected using app data, activity tracker data, and daily ecological momentary assessments. Usability testing revealed that user experiences were predominantly positive, despite some problems in the fixed delivery of content.

CONCLUSIONS

The systematic development approach resulted in a theory-based and dynamically tailored eCoach. Future work should focus on expanding intervention content to other chronic diseases and lifestyle behaviors, enhancing the degree of tailoring and evaluating intervention effects on acceptability, use, and cost-effectiveness.