Guiding older mourners from online self-help to offline support using algorithmic mental health monitoring

Lena Brandl

Research output: ThesisPhD Thesis - Research UT, graduation UT

8 Downloads (Pure)

Abstract

The loss of a loved one is a common experience, especially in later life. Despite its prevalence, bereaved individuals often struggle to articulate their needs and supporting them can be challenging for their loved ones. Grieving is highly personal, and maladaptive coping can lead to significant mental health issues, as recognized by the American Psychological Association by including persistent complex bereavement disorder in the Diagnostic and Statistical Manual of Psychological Disorders (DSM-5). Online self-guided psychological interventions can play a vital role in preventing the exacerbation of maladaptive grief coping. This dissertation focuses on developing a mental health monitoring system to identify when professional intervention may be necessary in the context of an online self-help grief service for older adults who cope with the loss of their spouse.

The research encompasses five key steps: (1) identifying reliable indicators of mental health among (older) users of an online grief service; (2) designing a measurement protocol for data collection and decision-making; (3) developing an automatic decision-making component using fuzzy cognitive mapping (FCM) to recommend seeking (professional) offline support if necessary; (4) investigating strategies to communicate monitoring results to users and professionals; and (5) evaluating the system’s user acceptance, decision-making accuracy, and clinical relevance.

This dissertation explores topics such as personalization strategies for adapting online mental health services to user needs, the application of FCM for decision-making in digital mental health services, and the integration of feedback from grief professionals and older users into the design and development process of mental health monitoring systems. The final evaluation assesses the effectiveness of the developed monitoring system during a 10-week intervention, highlighting its accuracy, usability, and impact on professional guidance.

This dissertation contributes to the fields of stepped care models, where the intensity of delivered mental health care is adjusted to the needs of clients in the context of digital mental health services. It further contributes a blueprint for developing mental health monitoring systems to the field of algorithmic decision-making in healthcare, based on the insights gained about monitoring the mental health and supporting bereaved individuals through digital mental health services.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • Heylen, Dirk K.J., Supervisor
  • Jansen-Kosterink, Stephanie M., Co-Supervisor
Award date30 Jan 2025
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-6435-9
Electronic ISBNs978-90-365-6436-6
DOIs
Publication statusPublished - Jan 2025

Fingerprint

Dive into the research topics of 'Guiding older mourners from online self-help to offline support using algorithmic mental health monitoring'. Together they form a unique fingerprint.

Cite this