A5055177602- Mental Health Research Topics
- Digital Mental Health Interventions
- Mental Health via Writing
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Sleep and related disorders
- Mental Health Treatment and Access
- Child and Adolescent Psychosocial and Emotional Development
- Sleep and Wakefulness Research
- Health Policy Implementation Science
- Machine Learning in Healthcare
- Youth Substance Use and School Attendance
- Impact of Technology on Adolescents
- Health, psychology, and well-being
- Neurotransmitter Receptor Influence on Behavior
- Education, Healthcare and Sociology Research
- Social and Educational Sciences
- Early Childhood Education and Development
- Circadian rhythm and melatonin
- Data Analysis with R
- Grit, Self-Efficacy, and Motivation
- Brain Tumor Detection and Classification
- Alcohol Consumption and Health Effects
- Big Data and Business Intelligence
- Resilience and Mental Health
- Functional Brain Connectivity Studies
Karolinska Institutet
2019-2025
Stockholm Health Care Services
2019-2025
KTH Royal Institute of Technology
2023
RISE Research Institutes of Sweden
2023
Stockholm County Council
2019
Linköping University
2018
Abstract O bjective Investigating unique and shared aspects of measures emotion regulation (ER) advances our understanding ER as a multidimensional construct. This study aimed to investigate psychometric properties three ER‐measures: Difficulties in Emotion Regulation Scale (DERS‐36), the abbreviated version DERS‐16, Questionnaire (ERQ). Methods In community sample ( N = 843; 56% females) we investigated their internal consistency, factor structure, convergence, association with symptoms...
To develop a very brief scale with selected items from the Insomnia Severity Index (ISI), and to investigate psychometric properties of proposed in psychiatric sample. Patient data seven Cognitive Behavioral Therapy (CBT) for insomnia trials regular care were used analyses (N = 280-15 653). The samples included patients screening 6936) or receiving treatment 1725) other conditions. Six criteria relating component structure, sensitivity change clinical representativeness select items....
This study applied supervised machine learning with multi-modal data to predict remission of major depressive disorder (MDD) after psychotherapy. Genotyped adult patients (n = 894, 65.5% women, age 18-75 years) diagnosed mild-to-moderate MDD and treated guided Internet-based Cognitive Behaviour Therapy (ICBT) at the Internet Psychiatry Clinic in Stockholm were included (2008-2016). Predictor types demographic, clinical, process (e.g., time complete online questionnaires), genetic (polygenic...
Insomnia is a common and chronic disorder, cognitive behavioral therapy (CBT) the recommended treatment. Very long-term follow-ups of CBT are very rare, this study aimed to investigate if improvements were stable one ten years after for insomnia (CBT-i). Based on three-armed randomized controlled trial bibliotherapeutic CBT-i, participants received an insomnia-specific self-help book therapist guidance, no or waitlist receiving unguided treatment delay. Six weeks was given 133 diagnosed with...
Objective This study proposes a way of increasing dataset sizes for machine learning tasks in Internet-based Cognitive Behavioral Therapy through pooling interventions. To this end, it (1) examines similarities user behavior and symptom data among online interventions patients with depression, social anxiety, panic disorder (2) explores whether these suffice to allow the together, resulting more training when prediction intervention dropout. Methods A total 6418 routine care from Internet...
Individuals with social anxiety disorder (SAD) experience overall emotion regulation difficulties, but less is known about the long-term role of such difficulties in cognitive behavior therapy (CBT) for SAD. Forty-six patients SAD receiving internet-delivered CBT, and matched healthy controls (HCs;
Objective: Early identification of failing psychological treatments could be high clinical value, but therapists themselves have been found to bad at predicting who will benefit or not. Previous research has some methodological limitations, and therapists' predictive accuracy never examined in internet-delivered treatments. Method: Therapists providing cognitive behavior therapy for depression, social anxiety disorder, panic disorder routine psychiatric care made outcome predictions 897...
Therapist guided Internet-Delivered Cognitive Behavior Therapy (ICBT) is effective, but as in traditional CBT, not all patients improve, and clinicians generally fail to identify them early enough. We predict treatment failure 12-week regular care ICBT for Depression, Panic disorder Social anxiety disorder, using only patients' weekly symptom ratings when the accuracy of predictions exceed 2 benchmarks: (a) chance, (b) empirically derived clinician preferences actionable...
<title>Abstract</title> Introduction Therapist-supported internet-based Cognitive Behavioural Therapy (ICBT) has strong scientific support, but all patients are not helped and further improvements needed. Personalized medicine could enhance ICBT. One promising approach uses a Machine learning (ML) based predictive decision support tool (DST) to help therapists identify at risk of treatment failure adjust their treatments. ICBT is suitable clinical context for developing testing such DST:s,...
While psychological treatments are effective, a substantial portion of patients do not benefit enough. Early identification those may allow for adaptive treatment strategies and improved outcomes. We aimed to evaluate the clinical usefulness machine-learning (ML) models predicting outcomes in Internet-based Cognitive Behavioural Therapy, compare ML-related methodological choices, guide future use these.
Evangelia Gogoulou, Magnus Boman, Fehmi Ben Abdesslem, Nils Hentati Isacsson, Viktor Kaldo, Sahlgren. Proceedings of the 16th Conference European Chapter Association for Computational Linguistics: Main Volume. 2021.
A learning machine, in the form of a gating network that governs finite number different machine methods, is described at conceptual level with examples concrete prediction subtasks. historical data set from over 5000 patients Internet-based psychological treatment will be used to equip healthcare staff decision support for questions pertaining ongoing and future cases clinical care depression, social anxiety, panic disorder. The organizational knowledge graph inform weight adjustment...
To minimize the burden in detecting and monitoring Panic Disorder Agoraphobia by developing a very brief scale with selected items from Severity Scale-Self Report (PDSS-SR), to investigate proposed scale's psychometric properties comorbid sample.A sample of 5103 patients Internet Psychiatry Clinic Sweden, diagnosed treated Internet-based cognitive behavioral therapy for panic disorder (n = 1390), social anxiety 1313) or depression 2400), responded PDSS-SR. Six criteria related factor...
Purpose Depression and anxiety afflict millions worldwide causing considerable disability. MULTI-PSYCH is a longitudinal cohort of genotyped phenotyped individuals with depression or disorders who have undergone highly structured internet-based cognitive-behaviour therapy (ICBT). The overarching purpose to improve risk stratification, outcome prediction secondary preventive interventions. precision medicine initiative that combines clinical, genetic nationwide register data. Participants...
Whereas striatal dopamine D2 receptor (D2R) availability has shown to be altered in individuals with alcohol use disorder (AUD) and healthy a family history of AUD, the role D2R development AUD is unknown. In this positron emission tomography (PET) study, we measured whether associated subsequent alcohol-related factors, at follow-up 8 16 years post-PET scan, social drinkers.Longitudinal study investigating association between PET data later self-report measures individuals.Academic research...
<title>Abstract</title> <bold>Objective</bold> While psychological treatments are effective, a significant portion of patients do not benefit enough. Early identification those may allow for adaptive treatment strategies and improved outcomes. We aimed to evaluate the clinical usefulness machine-learning (ML) models predicting outcome in Internet-based Cognitive Behavioural Therapy, compare ML-related methodological choices, guide future use these.<bold>Methods</bold> Eighty main were...
Introduction: Adaptive Treatment Strategies warns therapists of patients at risk treatment failure to prompt an adaption the intervention. Internet-delivered Cognitive Behavioural Therapy (ICBT) collects a wide range data before and during can quickly be adapted by adjusting level therapist support. Objectives: To evaluate how accurate machine learning algorithms predict single patient’s final outcome opportunities for using them within Strategy. Methods: Over 6000 Internet Psychiatry Clinic...
Summary The objectives were to investigate the potential for sleep‐related behaviours, acceptance and cognitions predict outcome (insomnia severity) of cognitive behavioural therapy insomnia (CBT‐I). Baseline data from four randomised controlled trials ( n = 276) used. Predictors Dysfunctional Beliefs Attitudes about Sleep‐10 (DBAS‐10), Sleep‐Related Behaviours Questionnaire (SRBQ), Sleep Problems Acceptance (SPAQ), empirically derived factors a factor analysis combining all items at...
ABSTRACT BACKGROUND Whether a patient benefits from psychotherapy or not is arguably complex process and heterogeneous information extracted process, genetic, demographic, clinical data could contribute to the prediction of remission status after psychotherapy. This study applied supervised machine learning with such multi-modal baseline predict in patients major depressive disorder (MDD) completed METHODS Eight-hundred ninety-four genotyped adult (65.5% women, age range 18-75 years)...