Prolonged grief disorder is a debilitating condition, affecting 10% of bereaved people. To date, studies evaluating treatments for prolonged grief have focused on symptom change on a group-level, ignoring individual variability in grief responses.

Personalized prolonged grief treatment may enhance treatment outcomes. An assumption underlying personalized care is that people respond differently to treatment. In part 1 of this project, you will test this assumption by examining distinct trajectories in treatment responses, and correlates thereof, using a novel data-archive. This data-archive consists of existing individual patient data of randomized controlled trials evaluating the effects of cognitive behavioral therapy for prolonged grief disorder (PGD).

Moreover, in order to personalize PGD treatment we need to know to what specific intervention might be helpful for this particular person in what certain moment. A precondition for this personalized treatment approach is that the topic of interest is dynamic and context-dependent. While theoretical and anecdotal work supports that this is the case for PGD, you will be the first to provide an empirical base supporting these claims in part 2 of the project, using experience sampling methodology (ESM). In part 3 of the project, you will create, together with experts and bereaved people, an ESM-based personalized intervention for treatment of PGD using qualitative research methods. In a pilot-study you will evaluate the feasibility, acceptability, and potential effectiveness of this ESM-based personalized PGD intervention.

As a result of this project, you will contribute in three ways to personalized treatment for prolonged grief, by:

• improving the understanding of differences in responses to treatment for prolonged grief;
• gaining novel insights in how grief unfolds in daily life;
• offering dynamic support in daily life to treat prolonged grief.

You will harmonize and then analyze existing data from randomized controlled trials using latent variable modelling (part 1). Together with master-students you will collect ESM-data (part 2), which you will analyze using multi-level modelling. In close collaboration with scientist-practitioners and bereaved people you will co-create and evaluate a smart-phone app to reduce PGD using qualitative and quantitative research methods (part 3). You will report your findings in academic peer-reviewed journals as well as media outlets for non-academic audiences and you will present your work at (inter)national conferences. Collaborations with national and international colleagues are part of this project. You will be a member of existing research groups that focus on grief and ESM that organize regular meetings to exchange experiences/knowledge in an informal setting with peers.