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Many psychiatric patients are not sufficiently improved by current interventions. Functional magnetic imaging brain imaging (fMRI) has proven to be a promising method for predicting treatment outcomes in psychiatric treatment. Individuals moment-to-moment variability have not yet been evaluated as a predictor of treatment of three common forms of mental illness: depression, insomnia and health anxiety. The goal is to investigate whether objective measurements of brain function contribute to a better prediction of a patient's success in treatment than experiences and self-reports, e.g., treatment credibility and patients expectations about the treatment. The prediction model will be tested on internet-delivered CBT (iCBT) for depression, insomnia and social anxiety. Patients in each diagnostic group are asked for participation before treatment. The total number of participants in this study will amount to 225 participants. The goal is that 35% consists of healthy controls and that the remaining part is equally distributed between the three diagnostic patient groups.
Being able to better predict how well a psychiatric treatment will work for an individual has great value from both an economic and a treatment perspective. The findings from this study may contribute to increased knowledge about neurobiological complications in mental illness. In the longer term, it can lead to improved routines and help in clinical decision-making when patients should be recommended treatment.
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Background: There is extensive evidence that cognitive behavioral therapy (CBT) is an effective method of treating common psychiatric disorders such as depression, social anxiety and insomnia. However, access to CBT is very limited. Furthermore, evidence suggest that internet-delivered CBT (iCBT) is as effective as traditional CBT. However, many psychiatric patients are not sufficiently improved by current interventions. Functional brain imaging has proven to be a promising method for predicting treatment outcomes in psychiatric treatment. Calculations on brain signal variability based on the blood-oxygen-level-dependent, BOLD signal (BOLD-fMRI) is a relatively new technique, shown to accurately predict chronological age and cognitive performance. Preliminary data from the investigators' lab suggest that pre-treatment BOLD-fMRI variability is predictive of CBT outcome in patients with social anxiety disorder.
Objectives: The objective of the study is to investigate whether objective measurements of brain function, in comparison with subjective experiences and self-reports (e.g., rating on treatment credibility and patients expectations about the treatment), contribute to better prediction of treatment outcome. The prediction model will be tested on iCBT for three common forms of mental disorders (depression, insomnia and social anxiety). Furthermore, participants will be compared with healthy controls to better understand neurobiological factors that may contribute to mental illness. Preliminary data from the investigators' lab suggest that BOLD-fMRI variability differs between social anxiety disorder participants and healthy individuals.
Method: A sample of outpatients scheduled for iCBT treatment for depression, insomnia or social anxiety at the Internet Psychiatry Unit at Karolinska University Hospital in Huddinge, Stockholm, will be invited to participate in the study. In addition to clinical participants, a healthy control group will be recruited via advertisement in social media. The length of the iCBT intervention is 12 weeks, during which participants engage in web-based treatment modules in a sequential manner, guided though a digital messaging system by a licensed psychologist who provides support and feedback on progress and assignments.
Measuring instruments: Brain imaging is performed before the patients initiate psychiatric treatment. The brain will be examined with structural and functional magnetic resonance imaging (MRI) using an EPI sequence to capture the BOLD signal (Philips 3-Tesla, 32 channel head-coil).
During the online self-referral process and during clinical intake interview, data on a number of potential predictor variables are collected:
Measurements only administered at screening/pre-treatment:
Behavioural measurements before/while undergoing MRI (all participants):
Predictors of treatment outcome
Behavioral predictor(s) of treatment outcome:
Brain-signal variability predictor(s), as derived from the following BOLD-fMRI experiments (all participants):
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150 participants in 3 patient groups
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Viktor Kaldo, PhD; Kristoffer Kristoffer, PhD
Data sourced from clinicaltrials.gov
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