Kumulative Dissertation, Otto-Friedrich-Universität Bamberg, 2025

Von der genannten Lizenzangabe ausgenommen sind folgende Bestandteile dieser Dissertation:

Study 1 “Bi-directional Associations of Core Affect and Physical Activity in Adults with Higher Body Weights: An Ecological Momentary Assessment Study" (S. 26-44),
Study 2 "A Tailored Gender-Sensitive mHealth Weight Loss Intervention (I-GENDO): Development and Process Evaluation" (S. 46-68) und Study 3 "Differential Effects of the Individualized Gender-Sensitive mHealth Intervention I-GENDO on Eating Styles in Individuals with Overweight and Obesity - a Randomized Controlled Trial" (S. 70-86) stehen unter der CC-Lizenz CC BY.

Lizenzvertrag: Creative Commons Attribution 4.0
https://creativecommons.org/licenses/by/4.0/

Overweight and obesity are associated with a wide range of physical and psychological consequences. The associated loss of quality of life and high levels of psychosocial burden can motivate individuals with overweight and obesity to engage in weight loss activities. Research shows that participating in a behavioral weight loss program successfully changes diet and physical activity behavior and leads to weight loss. However, the behavior change is often not sustained leading to unfavorable emotional experiences and weight gain. Furthermore, despite the increasing prevalence of overweight and obesity worldwide, there is a lack of adequate and sustainable treatment options. This gap in care can be addressed by providing novel digital assessment and intervention approaches that consider the complexity of overweight and obesity. Mobile health (mHealth) interventions delivered through smartphone apps are particularly well suited because they can improve health behaviors in everyday life, offer lowthreshold access, and can be widely disseminated. However, even digital behavioral interventions have shown only short-term effectiveness. For the treatment of overweight and obesity, intervention approaches are needed that enable sustainable behavior change.
This dissertation aims to 1) provide an overview of the current evidence and effectiveness of (digital) behavioral weight loss interventions, and 2) introduce two promising approaches that could increase the long-term impact of intervention effects. First, the integration of underlying emotional and cognitive factors in assessment and intervention studies, and second, the consideration of sex/gender as an individualization approach in mHealth treatment. The body of this thesis consists of four original studies, each of which contributes to these two objectives.
Study 1 examined the bi-directional association between affective determinants (i.e., core affect) and daily physical activity within a 7-day ecological momentary assessment (EMA) study. Core affect is an understudied key facet for behavior change in individuals with overweight and obesity, and EMA studies examining this affect-physical activity association in the context of overweight and obesity are lacking. For this study, data from 157 adults (Body Mass Index, BMI: 32.99±3.87 kg/m2) were included in a multilevel model analysis. Participants wore an accelerometer and completed EMA surveys for seven consecutive days. Results showed a significant bi-directional association between physical activity and energetic arousal and calmness, but not valence. This suggests that the affect-enhancing response to physical activity differs from the experience of individuals with a BMI below 25. When designing mHealth interventions, consideration should be given to setting realistic expectations about the impact of daily physical activity and modifying these affective determinants.
Study 2 presented the development process, usability, and acceptability of the individualized gender-sensitive mHealth intervention I-GENDO. This self-guided multicomponent intervention was designed to change cognitive and emotional aspects related to weight and weight-related behaviors by offering cognitive-behavioral treatment strategies that were offered in two gender-sensitive variants. Analysis of the usage patterns of 116 participants (BMI: 33.07 kg/m2) who used the I-GENDO intervention for 12 weeks showed that the app was used for an average of 625 minutes by female participants and 347 minutes by male participants, and that overall usage time decreased during the intervention period. Significant sex/gender differences were found in engagement with the app, but not in ratings of acceptability, usability, and satisfaction. The gender-sensitive custom treatment options were successfully implemented, but further research is needed to understand the motivation of female and male users to choose a particular treatment variant.
Study 3 examined whether the use of the 12-week gender-sensitive mHealth intervention I-GENDO changes weight-related behaviors (i.e., eating behavior, physical activity) and weight (i.e., BMI) in women and men. We conducted a randomized controlled trial (RCT) that included 116 participants in the intervention group and 97 women and men in the control group (BMI: 33.58 kg/m2). By addressing the underlying cognitive and emotional aspects of overweight and obesity through the I-GENDO intervention, improvements in eating behavior and small reductions in BMI were achieved. However, the effects were mixed in terms of sustainability and differed by sex/gender. The results confirm that cognitive-based health behaviors in particular can be modified by the self-guided mHealth intervention. However, the robustness of the effectiveness of the intervention remains limited, mainly because the chosen design of the study prevents concrete statements about the effectiveness of the novel gender-sensitive approach and individualization features.
In Study 4, guidelines for digital technology researchers and practitioners on how to develop, evaluate, and implement mHealth assessments and interventions in healthcare are proposed. The findings of the I-GENDO evaluation and intervention studies informed the development of these guidelines as well as current literature. The guidelines were developed using an adapted Delphi process among 25 authors with expertise in digital mental health, and cover topics such as intervention content development, user-centered design, participatory approaches, privacy, artificial intelligence, sensors and wearables, evaluation of effectiveness, and transfer to clinical practice. The need for feasible interventions and long-term follow-up measurements is emphasized.
In summary, the findings of this dissertation highlight the importance of assessing cognitive and emotional processes, and health behaviors in everyday life, which can inform the timing and development of individualized mHealth interventions. The results of the presented studies provide important novel insights into how to implement cognitive and emotional mechanisms that influence health behavior in a gender-sensitive treatment approach for digital obesity treatment. At the same time, this work also highlights current limitations and discusses future directions for the development and evaluation of individualized psychological interventions, such as low user engagement and adherence.