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dc.contributor.advisorPfuhl, Gerit
dc.contributor.authorLüdtke, Thies
dc.date.accessioned2021-05-17T11:34:07Z
dc.date.available2021-05-17T11:34:07Z
dc.date.embargoEndDate2026-06-10
dc.date.issued2021-06-10
dc.description.abstractThe present thesis aims at using insights from ESM studies (i.e., frequent ecologically valid self-reports for approximately one week) to improve the treatment and the prediction psychotic symptoms. ESM indicates that warning signs, such as negative affect, worrying, sleep problems, or aberrant salience precede rapidly fluctuating psychotic symptoms throughout the day. Assuming underlying causal associations, we developed an Internet intervention called EviBaS that targets ESM-derived warning signs to improve psychotic symptoms (studies 1-3). Further, we examined said warning signs as candidate predictors of psychotic relapses (study 4). EviBaS improved positive symptoms compared to a waitlist condition (p = .047, d = -0.37) in a randomized controlled trial (study 1, n = 101). Mixed model analyses (study 2; n = 124) indicated that this effect did not rely on improving ESM-based predictors, as their course did not differ between groups. However, worrying (p = .030) and quality of sleep (p = .003) predicted subsequent psychotic symptoms during the intervention, indicating that they would have been worthwhile treatment targets. Whereas worrying and sleep were unrelated to EviBaS’ efficacy, mindfulness emerged as a possible mechanism of change. In voice hearers (n = 55), completing the EviBaS-mindfulness module improved hallucinations (p = 0.001, ηp2 = 0.214), mediated by mindfulness. Study 4 incorporated a one-week ESM phase followed by bi-weekly assessments over one year (n = 30). Negative affect (p = .003) and aberrant salience (p < .001) predicted short-term paranoia but only aberrant salience remained a predictor of bi-weekly paranoia (p < .001). No variable predicted relapse. In sum, this thesis shows that ESM findings offer promising starting points to improve the treatment and the prediction of psychotic symptoms. It seems worthwhile to improve EviBaS to target a wider range of outcomes. Further, we should examine aberrant salience in sufficiently powered relapse-prediction studies.en_US
dc.description.doctoraltypeph.d.en_US
dc.description.popularabstractThe intensity of paranoia or hallucinations changes over time – even within the same day. Before symptoms get worse, people with psychosis often report warning signs, such as sadness, sleep problems, or worrying. Theoretical models suggest that sadness, sleep, or worrying not only precede but cause subsequent symptoms, so my colleagues and I developed an online program called EviBaS that aims at treating these warning signs to indirectly improve hallucinations and paranoia. The program improved hallucinations and mindfulness, but sleep and worrying remained unchanged. The second goal of this thesis was to use within-day warning signs to improve the prediction of relapse. Whereas attempts to predict severe relapses were unsuccessful, we could find that warning signs predicted more subtle symptoms two weeks in advance. In sum, this thesis shows that findings from patients’ everyday lives offer promising starting points to improve the treatment and the prediction of psychotic symptoms.en_US
dc.description.sponsorshipThe EviBaS Project, which was at the core of this thesis, was funded by the Swiss National Science Foundation (project number: #159384) and the German Research Foundation (project number: DFG Mo 969/17-1)en_US
dc.identifier.urihttps://hdl.handle.net/10037/21190
dc.language.isoengen_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.relation.haspart<p>Paper 1: Westermann, S., Rüegg, N., Lüdtke, T., Moritz, S. & Berger, T. (2020). Internet-based self-help for psychosis: Findings from a randomized controlled trial. <i>Journal of Consulting and Clinical Psychology, 88</i>(10), 937–950. Published version not available in Munin due to publisher’s restrictions. Published version available at <a href=https://doi.org/10.1037/ccp0000602> https://doi.org/10.1037/ccp0000602</a>. <p>Paper 2: Lüdtke, T., Pfuhl, G., Moritz, S., Rüegg, N. L., Berger, T. & Westermann, S. (2021). Sleep problems and worrying precede psychotic symptoms during an online intervention for psychosis. British Journal of Clinical Psychology, 60, 48–67. Also available in Munin at <a href=https://hdl.handle.net/10037/20210>https://hdl.handle.net/10037/20210</a>. <p>Paper 3: Lüdtke, T., Platow-Kohlschein, H., Rüegg, N., Berger, T., Moritz, S. & Westermann, S. (2020). Mindfulness Mediates the Effect of a Psychological Online Intervention for Psychosis on Self-Reported Hallucinations: A Secondary Analysis of Voice Hearers From the EviBaS Trial. <i>Frontiers in Psychiatry, 11</i>, 228. Also available in Munin at <a href=https://hdl.handle.net/10037/20198>https://hdl.handle.net/10037/20198</a>. <p>Paper 4: Lüdtke, T., Moritz, S., Westermann, S. & Pfuhl, G. Aberrant Salience Predicts Fluctuations of Paranoia but not Relapse During a 1-Year Experience Sampling Study in People With Psychosis. (Manuscript).en_US
dc.rights.accessRightsembargoedAccessen_US
dc.rights.holderCopyright 2021 The Author(s)
dc.subject.courseIDDOKTOR-003
dc.subjectVDP::Social science: 200::Psychology: 260en_US
dc.subjectVDP::Samfunnsvitenskap: 200::Psykologi: 260en_US
dc.titleIdentifying and treating predictors of psychotic symptoms - How findings from Experience Sampling research can help to improve the treatment of psychosis and the prediction of relapseen_US
dc.typeDoctoral thesisen_US
dc.typeDoktorgradsavhandlingen_US


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