Behavioural Change Support Systems
In the topic line of
Behavioural Change Support Systems
we offer topics for analysis, design, implementation, and evaluation in the following areas for a bachelor's, master's, diploma, or seminar thesis:
- HBCSS interfaces (Conversational Agents and Virtual Coaches)
- The transition of complex behavioral changes into small habits that can be better integrated into patients' daily lives
Implementation of Habits
| Behavioral changes through implementation and strengthening of habits | |
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| Health problems such as obesity, diabetes, and depression often require complex behavioral changes in the areas of exercise (10,000 steps a day), diet (sugar-free), and relaxation. Since such extensive behavioral changes are often not well integrated into everyday life and usually do not refer to specific actions, they are often not tackled in the first place or not sustained for long. Introducing small habits can help translate extensive habits into small, practicable units that can be maintained in the long term. The Digital Health research group is particularly interested in how the introduction and strengthening of habits can be supported digitally. Theses in this area can be of a technical nature (implementation of digital strategies in prototypes) or conceptual (reviews, literature analyses, development of habit repositories, etc.). | |
| Building specific sports habits | |
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| Regular physical activity, such as running, swimming, or strength training, is a key part of a healthy lifestyle. However, it is often difficult for beginners to establish a long-term exercise routine. Sports apps promise to provide support through individual coaching, motivation, and progress tracking. The aim of this paper is to analyze sports apps on a discipline-specific basis to determine the extent to which they exploit their full digital potential to support habit formation, as described by Stark et al. (2023). For example, work in the areas of weight training, running, and swimming is conceivable. Furthermore, the additional mechanisms used to promote habit formation in various sports, such as running, strength training, or yoga, will be investigated. Findings from these specific sports will be transferred to general habit formation in order to identify overarching approaches to establishing healthy routines. A more in-depth analysis could include an evaluation of selected apps to assess their contribution to establishing long-term sports habits in specific disciplines and to learn from these sports to general habits. | |
| “One last time, then I'll definitely stop” - breaking negative habits | |
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| Every year, we set ourselves the goal of giving up one of our less attractive habits. Some of us want to give up smoking, others want to eat less meat, and others want to cut down on coffee consumption. But giving up unhealthy habits is a challenge. At this point, specific apps such as “Smoke-Free” or “Sugar-Free Challenge” promise to offer support in overcoming these habits. The aim of this thesis is to analyze these apps for a specific use case (e.g., quitting smoking). The aim is to investigate whether they exploit the full potential of digital mechanisms to support habit formation and how the reduction of unhealthy habits differs from the development of healthy habits. | |
| Updating and analyzing habit-tracking apps | |
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Digital habit-tracking apps support users in establishing new habits and maintaining them in the long term. In a previous analysis, various lifestyle and habit apps were already examined in terms of their functions and supported habits. The aim of this work is to update this existing database, identify new relevant apps and record current technological developments in the field of habit tracking. In particular, new features such as AI-supported recommendations, gamification elements or context-adaptive reminders will be considered. The work offers a structured and easy-to-follow methodology with clear instructions that enable error-free implementation. It also offers the opportunity to examine the current state of the art in habit-tracking apps and critically reflect on their developments. |
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| Context-Sensitive Support for Behavioural Change: Developing a Data-Driven Recommendation System Using Ontologies and NLP | |
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The integration of healthy habits into daily life requires a deep understanding of the relationships between habits and their contexts, such as location, time, and prior behavior. Behavioural Change Support Systems (BCSS) play a pivotal role by actively supporting users in identifying meaningful contexts where habits can be seamlessly integrated. The aim of this work is to design a BCSS that leverages ontologies, semantic networks, and Natural Language Processing (NLP) techniques to analyze, cluster, and systematically categorize contexts. Semantic analysis will uncover relevant relationships between various contextual variables, such as behavior, environment, and temporal patterns, to develop personalized recommendations. This study includes the conceptualization and prototypical implementation of a tool that processes real-world data, identifies context-sensitive patterns, and applies them to optimize Health Recommender Systems. Through automated clustering and categorization, the system establishes a data-driven foundation, enabling more effective and individually tailored recommendations that sustainably support behavioral change. |
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Investigation of Behaviour Change Theories and Measures
| Systematic Review of Scales and Survey Items for Behavioral Change Variables in Health Recommender Systems |
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Health Recommender Systems (HRS) play a crucial role in promoting healthy behaviors through personalized recommendations. Context-specific variables, such as psychological factors or habits, are essential for tailoring recommendations to the individual user. This thesis will conduct a systematic literature review to identify appropriate scales and specific survey items that can be used to measure behavioral change variables. The focus will be on gathering relevant dimensions, such as demographic data, psychological factors, or behavioral patterns, that are utilized in HRS to support healthy behaviors. The aim of this thesis is to provide a comprehensive overview of the scales and measurement instruments for key behavioral variables used in research on Health Recommender Systems. The results may contribute to the further development of context-sensitive HRS by enhancing personalization capabilities. |
| Adoption behavior of digital artifacts under consideration of adopter types |
| The adoption of digital artifacts is significantly influenced by different types of adopters, each of which requires different conditions in order to accept and effectively use digital solutions. According to diffusion theory, adopters can be divided into groups such as innovators, early adopters, early majority, late majority, and laggards. Each of these groups has specific requirements for digital transformation, such as technological support, trust in digital systems, usability, or adaptation to existing work processes. The thesis could investigate what conditions are required for the different types of adopters to accept digital artifacts and integrate them into their work in the long term. Another exciting question is which types of adopters are more likely to be present in which medical domains and what mix constitutes an optimal digitalization culture. |
| Gamification |
| The integration of gamification into digital health applications (DiGA) promises to improve user engagement and therapy outcomes. Different gamification models offer different approaches to motivate and activate users. The aim of this scientific paper is to analyze different gamification models and investigate their application potential in digital health applications. Subsequently, one of the models is applied to a practical example in order to derive concrete recommendations for action for the app. |
HBCSS-Interfaces (Conversational Agents and Virtual Coaches)
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Virtual Coaching |
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| Software products are increasingly being recognized in modern medicine as a means of medical and, above all, behavioral intervention. Humanized digital avatars, implemented in the form of virtual coaches, are intended to help actively train and educate patients in health behavior, training measures, and skills. Research and development potential lies in the adaptation of avatar behavior based on contextual information, the technological design of such coaches, and research into the perception of such coaches on the part of service providers and all those involved. Another aspect of research is investigating the use of VC in specific healthcare domains. One example would be the use of virtual coaches in a clinical setting. As patient companions, they could support the PROM/PRE assessment or provide useful information on upcoming treatment. Numerous design issues still need to be clarified. | |
| Use of virtual coaching in an inpatient setting |
| AI-based virtual coaches have already proven themselves in studies as digital patient companions in everyday life but are not yet widely used in inpatient hospital settings. These technologies could help patients through individualized support during their inpatient stay by providing information on treatment, promoting the recovery process, and facilitating communication with medical staff. This study examines the potential of using such systems in the inpatient setting, the barriers to implementation in hospitals, and the expected impact on patient care and experience |
If you are interested, please e-mail a brief presentation of your ideas or subject interests, including your CV, to .