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The Mapping Individual Routes of Risk and Resilience (Mirorr) study


- candidate number26457
- NTR NumberNTR6324
- ISRCTNISRCTN no longer applicable
- Date ISRCTN created
- date ISRCTN requested
- Date Registered NTR10-jan-2017
- Secondary IDsNL52974 / 2015/159  ABR / METc
- Public TitleThe Mapping Individual Routes of Risk and Resilience (Mirorr) study
- Scientific TitleThe Mapping Individual Routes of Risk and Resilience (Mirorr) study
- ACRONYMMirorr
- hypothesisIn the Mirorr study, we aim to investigate the hypothesis of dynamic symptom networks as the basis of psychopatholgy in general and psychosis in particular and as the driving force of progression of illness through successive clinical stages. Taking a broader, multidimensional and developmental approach, we will examine how symptoms from multiple domains influence each other over time and across diagnostic boundaries, in interaction with environmental factors. We hypothesize that characteristics of these networks can predict illness course and outcome within a clinical staging model.
- Healt Condition(s) or Problem(s) studiedPsychosis
- Inclusion criteriaIn order to be eligible to participate in the study, subjects must meet all of the following criteria: 1) age between 18 and 35 years, 2) read and speak Dutch fluently, 3) capable of following the research procedures, 4) provide Informed Consent. In addition, participants of subsample 1 should not be in clinical care for mental health at the moment of screening. In contrast, participants of subsample 2-4 should currently be in clinical care for mental health. In addition, participants of subsample 2 should have mild, non-psychotic psychopathology, as evidenced by a score below 6 on the Prodromal Questionnaire (PQ), participants of subsample 3 should have mild psychopathology including subclinical psychotic symptoms, as evidenced by a score of or above 6 on the PQ, but are not at ultra-high risk (UHR) for psychosis, as indexed by the Comprehensive Assessment of At Risk Mental State (CAARMS). Finally, participants of subsample 4 should be at UHR for psychosis, as indexed by the CAARMS.
- Exclusion criteriaExclusions criteria are: 1) a history of or current psychotic episode, according to the Diagnostic and Statistical manual of Mental Disorders-IV (DSM-IV) criteria; 2) significant hearing or visual problems impairments; 3) pregnancy, as stated on a general health questionnaire.
- mec approval receivedyes
- multicenter trialno
- randomisedno
- group[default]
- Type[default]
- Studytypeobservational
- planned startdate 1-aug-2015
- planned closingdate1-aug-2019
- Target number of participants175
- Interventions-
- Primary outcomeNetwork parameters will be compared to individual differences in clinical stage, functioning and need for care. They will also be linked wihtin-individual changes in clinical stage.
- Secondary outcome-
- TimepointsAt baseline and 1-year follow-up, participants will report their day-to-day symptoms, affective states and experiences for three consecutive months. Symptomatology, functioning and need for care will be every year by means of questionnaires and interviews
- Trial web site
- statusopen: patient inclusion
- CONTACT FOR PUBLIC QUERIES J.T.W. Wigman
- CONTACT for SCIENTIFIC QUERIES J.T.W. Wigman
- Sponsor/Initiator University Medical Center Groningen (UMCG)
- Funding
(Source(s) of Monetary or Material Support)
NWO, Veni nr. 016.156.019
- Publications-
- Brief summaryBackground: Psychotic disorders are among the most severe mental disorders in terms of individual and societal impact. Our current ability to predict the course and outcome of early psychotic symptoms is limited, hampering timely intervention and treatment. To improve our understanding of the development of psychosis, we propose to re-conceptualize psychopathology as a dynamic system of fluctuating symptoms that impact each other over time and across diagnostic boundaries, forming symptom networks. Adopting this dynamic network approach, the Mapping Individual Routes of Risk and Resilience (Mirorr) study aims to determine whether characteristics of symptom networks can predict illness course and outcome of early psychotic symptoms.

Methods: The sample consists of N=100 participants in the age range of 18-35 years old, divided into four subgroups (N=4x25) with increasing levels of psychopathological severity, representing successive stages of clinical progression. Individuals representing the lowest stage are from the general population and have a psychometric risk of psychotic experiences, whereas individuals representing the highest stage are help-seeking and at ultra-high risk[SB1] for psychosis. [SB2] At baseline and 1-year follow-up, participants will report their day-to-day symptoms, affective states and experiences for three consecutive months in short, daily questionnaires on their smartphone. In addition, symptomatology, functioning, psychopathological severity and need for care will be assessed at three annual assessments by means of questionnaires and diagnostic interviews. The diary questionnaires will be used to map individual networks of symptoms, experiences and emotions. Network parameters, including the strength and directionality of symptom connections and centrality indices will be estimated. Subsequently, they will be linked to individual differences in and within-individual progression through clinical stage.

Discussion: This study will empirically investigate the value of a dynamic network approach to predict illness course and outcome of early psychotic symptoms in the context of a clinical staging model. The results will assist in improving and fine-tuning dynamic models of psychopathology, stimulating both clinical (in terms of both diagnostics and intervention) and scientific progress.
- Main changes (audit trail)
- RECORD10-jan-2017 - 28-mei-2017


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