Digitale Zelfmonitoring in de Geestelijke Gezondheidszorg - Het Gebruikersperspectief Begrijpen

Despite growing interest in digital self-monitoring tools for mental health and care, the field continues to struggle with translating technological potential into meaningful and sustainable clinical implementation. A central reason for this is the limited understanding of how these tools should be designed and implemented to provide genuine value for people with mental health problems and their care providers. This PhD thesis aims to contribute to the facilitation of person-centered mental health care by promoting end-user involvement in the design and implementation of Experience Sampling Methods (ESM) for digital self-monitoring. To this end, the thesis combines qualitative and quantitative methods to capture real-world practices, perspectives and lived experiences of mental health service users and providers. The first two chapters outline the current challenges of implementing digital mental health tools such as ESM and describe the objectives of the thesis. In chapter 2 the thesis seeks to improve our understanding of the goals and needs of people experiencing serious mental health problems in relation to digital self-monitoring. Qualitative findings from focus groups with nine individuals with lived experience of psychosis indicate that digital self-monitoring is primarily valued for its potential to support relapse prevention, enhance self-awareness, and strengthen autonomy. Participants expressed strong interest in monitoring personally meaningful symptoms and psychotic experiences, while emphasizing the need for flexible and personalized assessment tools. At the same time, concerns were raised regarding burden, reliability, and feasibility of use. Following this, in chapter 3, the thesis examines existing patterns in self-monitoring practices and digital technology use among individuals seeking mental health care. A cross-national survey among 435 mental health service users demonstrated substantial interest in and experience with self-monitoring. A latent class analysis identified four distinct user profiles differing in tracking experience and interest. These findings highlight heterogeneity among intended users and underscore the necessity of stratified implementation approaches that also account for differences in age, education, and attitudes toward technology. In chapter 4, the thesis evaluates a prototype ESM tool in clinical practice and provides insight into eleven service users' and seven clinicians' prior expectations, situated use, and future interest in digital self-monitoring. In both user groups, interest in continued use of the tool was strongly influenced by the perceived balance between required effort and added value. High assessment frequency and limited support were identified as key barriers to sustained engagement. Negative emotional reactivity, such as notification stress, also reduced interest in future use among service users, whereas perceived clinical relevance and alignment with therapeutic goals facilitated acceptance among both service users and clinicians. Finally, in chapter 5, the thesis examines mechanisms through which digital self-monitoring tools may promote patient activation in mental health care. Two central mechanisms were identified: repeated self-assessment in daily life, which fosters reflection and emotional awareness, and the collaborative interpretation of self-monitoring data within therapeutic encounters. The latter emerged as particularly important, as the support of clinicians enabled service users to better contextualize their data, develop shared understanding, and translate insights into actionable strategies for mental health management. Altogether, the thesis findings suggest that limited uptake of digital self-monitoring tools is not driven by lack of interest or insufficient digital literacy, but by shortcomings in perceived relevance, compatibility, and support. Both service users and providers express a need for increased tool flexibility, usability and support that can enable meaningful personalization, and provide comprehensible and actionable feedback. Collaborative data interpretation can play an important role in achieving this. Moreover, the thesis highlights the importance of designing tools that are valid, reliable, non-harmful, and trustworthy, drawing attention to risks related to burden, emotional reactivity, digital stress, and potential data exploitation. Overall, this PhD concludes that digital self-monitoring tools can support person-centered mental health care especially when developed through participatory approaches, integrated into clinical practice with adequate support, and critically evaluated for both benefits and unintended consequences. The findings contribute to a more nuanced understanding of how digital self-monitoring can be designed and implemented to meaningfully support mental health management.