BACKGROUND: Physiological signals such as heart rate and electrodermal activity can provide insight into an individual's mental state, which are invaluable information for mental health care. Using recordings of physiological signals from wearable devices in the wild can facilitate objective monitoring of symptom severity and evaluation of treatment progress. OBJECTIVE: We designed a study to evaluate the feasibility of predicting obsessive-compulsive disorder (OCD) events from physiological signals recorded using wrist-worn devices in the wild. Here, we present an analysis plan for the study to document our a priori hypotheses and increase the robustness of the findings of our planned study. METHODS: In total, 18 children and adolescents aged between 8 and 16 years were included in this study. Nine outpatients with an OCD diagnosis were recruited from a child and adolescent mental health center. Nine youths without a psychiatric diagnosis were recruited from the catchment area. Patients completed a clinical interview to assess OCD severity, types of OCD, and number of OCD symptoms in the clinic. Participants wore a biosensor on their wrist for up to 8 weeks in their everyday lives. Patients were asked to press an event tag button on the biosensor when they were stressed by OCD symptoms. Participants without a psychiatric diagnosis were asked to press this button whenever they felt really scared. Before and after the 8-week observation period, participants wore the biosensor under controlled conditions of rest and stress in the clinic. Features are extracted from 4 different physiological signals within sliding windows to predict the distress event logged by participants during data collection. We will test the prediction models within participants across time and multiple participants. Model selection and estimation using 2-layer cross-validation are outlined for both scenarios. RESULTS: Participants were included between December 2021 and December 2022. Participants included 10 female and 8 male participants with an even sex distribution between groups. Patients were aged between 10 and 16 years, and adolescents without a psychiatric diagnosis were between the ages of 8 and 16 years. Most patients had moderate to moderate to severe OCD, except for 1 patient with mild OCD. CONCLUSIONS: The strength of the planned study is the investigation of predictions of OCD events in the wild. Major challenges of the study are the inherent noise of in-the-wild data and the lack of contextual knowledge associated with the recorded signals. This preregistered analysis plan discusses in detail how we plan to address these challenges and may help reduce interpretation bias of the upcoming results. If the obtained results from this study are promising, we will be closer to automated detection of OCD events outside of clinical experiments. This is an important tool for the assessment and treatment of OCD in youth. TRIAL REGISTRATION: ClinicalTrials.gov NCT05064527; https://clinicaltrials.gov/study/NCT05064527. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48571.
Atypical neurocognitive functioning has been found in adult patients with obsessive-compulsive disorder (OCD). However, little work has been done in children and adolescents with OCD. In this study, we investigated neurocognitive functioning in a large and representative sample of newly diagnosed children and adolescents with OCD compared to non-psychiatric controls. Children and adolescents with OCD (n = 119) and non-psychiatric controls (n = 90) underwent psychopathological assessment, intelligence testing, and a neurocognitive test battery spanning cognitive flexibility, planning and decision-making, working memory, fluency, and processing speed. The MANOVA main effect revealed that children and adolescents with OCD performed significantly worse than the control group (p < .001, [Formula: see text] = 0.256). Atypical patient performance was particularly found for indices of cognitive flexibility, decision-making, working memory, and processing speed. We found no evidence of differences in planning or fluency. Moreover, we found no significant associations between neurocognitive performance and OCD symptom severity or comorbidity status. Our results indicate that children and adolescents with OCD show selective atypical neurocognitive functioning. These difficulties do not appear to drive their OCD symptoms. However, they may contribute to lifespan difficulties and interfere with treatment efficacy, an objective of our research currently.
Introduction: Obsessive-compulsive disorders (OCD) are marked by distress, negative emotions, mental processes and behaviors that are reflected in physiological signals such as heart rate, electrodermal activity, and skin temperature. Continuous monitoring of physiological signals associated with OCD symptoms may make measures of OCD more objective and facilitate close monitoring of prodromal symptoms, treatment progress and risk of relapse. Thus, we explored the feasibility of capturing OCD events in the real world using an unobtrusive wrist worn biosensor and machine learning models. Methods: Nine adolescents (ages 10-17 years) with mild to moderate-severe OCD were recruited from child and adolescent mental health services. Participants were asked to wear the biosensor in the lab during conditions of rest and exposure to OCD symptom-triggering stimuli and for up to 8 weeks in their everyday lives and register OCD events. We explored the relationships among physiological data, registered OCD events, age, OCD symptom severity and symptom types. In the machine learning models, we considered detection of OCD events as a binary classification problem. A nested cross-validation strategy with either random 10-folds, leave-one-subject-out, or leave-week(s)-out in both layers was used. We compared the performance of four models: logistic regression, random forest (RF), feedforward neural networks, and mixed-effect random forest (MERF). To explore the ability of the models to detect OCD events in new patients, we assessed the performance of participant-based generalized models. To explore the ability of models to detect OCD events in future, unseen data from the same patients, we compared the performance of temporal generalized models trained on multiple patients with personalized models trained on single patients. Results: Eight of the nine participants collected biosensor signals totaling 2, 405 h and registered 1, 639 OCD events. Better performance was obtained when generalizing across time compared to across patients. Generalized temporal models trained on multiple patients were found to perform better than personalized models trained on single patients. RF and MERF models outperformed the other models in terms of accuracy in all cross-validation strategies, reaching 70% accuracy in random and participant cross-validation. Conclusion: Our pilot results suggest that it is possible to detect OCD episodes in the everyday lives of adolescents using physiological signals captured with a wearable biosensor. Large scale studies are needed to train and test models capable of detecting and predicting episodes. Clinical trial registration: ClinicalTrials.gov: NCT05064527, registered October 1, 2021.
BACKGROUND: Obsessive compulsive disorder (OCD) in youth is characterized by behaviors, emotions, physiological reactions, and family interaction patterns. An essential component of therapy involves increasing awareness of the links among thoughts, emotions, behaviors, bodily sensations, and family interactions. An automatic assessment tool using physiological signals from a wearable biosensor may enable continuous symptom monitoring inside and outside of the clinic and support cognitive behavioral therapy for OCD. OBJECTIVE: The primary aim of this study is to evaluate the feasibility and acceptability of using a wearable biosensor to monitor OCD symptoms. The secondary aim is to explore the feasibility of developing clinical and research tools that can detect and predict OCD-relevant internal states and interpersonal processes with the use of speech and behavioral signals. METHODS: Eligibility criteria for the study include children and adolescents between 8 and 17 years of age diagnosed with OCD, controls with no psychiatric diagnoses, and one parent of the participating youths. Youths and parents wear biosensors on their wrists that measure pulse, electrodermal activity, skin temperature, and acceleration. Patients and their parents mark OCD episodes, while control youths and their parents mark youth fear episodes. Continuous, in-the-wild data collection will last for 8 weeks. Controlled experiments designed to link physiological, speech, behavioral, and biochemical signals to mental states are performed at baseline and after 8 weeks. Interpersonal interactions in the experiments are filmed and coded for behavior. The films are also processed with computer vision and for speech signals. Participants complete clinical interviews and questionnaires at baseline, and at weeks 4, 7, and 8. Feasibility criteria were set for recruitment, retention, biosensor functionality and acceptability, adherence to wearing the biosensor, and safety related to the biosensor. As a first step in learning the associations between signals and OCD-related parameters, we will use paired t tests and mixed effects models with repeated measures to assess associations between oxytocin, individual biosignal features, and outcomes such as stress-rest and case-control comparisons. RESULTS: The first participant was enrolled on December 3, 2021, and recruitment closed on December 31, 2022. Nine patient dyads and nine control dyads were recruited. Sixteen participating dyads completed follow-up assessments. CONCLUSIONS: The results of this study will provide preliminary evidence for the extent to which a wearable biosensor that collects physiological signals can be used to monitor OCD severity and events in youths. If we find the study to be feasible, further studies will be conducted to integrate biosensor signals output into machine learning algorithms that can provide patients, parents, and therapists with actionable insights into OCD symptoms and treatment progress. Future definitive studies will be tasked with testing the accuracy of machine learning models to detect and predict OCD episodes and classify clinical severity. TRIAL REGISTRATION: ClinicalTrials.gov NCT05064527; https://clinicaltrials.gov/ct2/show/NCT05064527. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45123.
Background: Knowledge on adverse events in psychotherapy for youth with OCD is sparse. No official guidelines exist for defining or monitoring adverse events in psychotherapy. Recent recommendations call for more qualitative and quantitative assessment of adverse events in psychotherapy trials. This mixed methods study aims to expand knowledge on adverse events in psychotherapy for youth with OCD. Methods: This is an analysis plan for a convergent mixed methods study within a randomized clinical trial (the TECTO trial). We include at least 128 youth aged 8-17 years with obsessive-compulsive disorder (OCD). Participants are randomized to either family-based cognitive behavioral therapy (FCBT) or family-based psychoeducation and relaxation training (FPRT). Adverse events are monitored quantitatively with the Negative Effects Questionnaire. Furthermore, we assess psychiatric symptoms, global functioning, quality of life, and family factors to investigate predictors for adverse events. We conduct semi-structured qualitative interviews with all youths and their parents on their experience of adverse events in FCBT or FPRT. For the mixed methods analysis, we will merge 1) a qualitative content analysis with descriptive statistics comparing the types, frequencies, and severity of adverse events; 2) a qualitative content analysis of the perceived causes for adverse events with prediction models for adverse events; and 3) a thematic analysis of the participants' treatment evaluation with a correlational analysis of adverse events and OCD severity. Discussion: The in-depth mixed methods analysis can inform 1) safer and more effective psychotherapy for OCD; 2) instruments and guidelines for monitoring adverse events; and 3) patient information on potential adverse events. The main limitation is risk of missing data. Trial registration: ClinicalTrials.gov identifier: NCT03595098. Registered on July 23, 2018.
BACKGROUND: Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder which affects up to 3% of children and adolescents. OCD in children and adolescents is generally treated with cognitive behavioural therapy (CBT), which, in more severely affected patients, can be combined with antidepressant medication. The TECTO trial aims to compare the benefits and harms of family-based CBT (FCBT) versus family-based psychoeducation/relaxation training (FPRT) in children and adolescents aged 8 to 17 years. This statistical analysis plan outlines the planned statistical analyses for the TECTO trial. METHODS: The TECTO trial is an investigator-initiated, independently funded, single-centre, parallel-group, superiority randomised clinical trial. Both groups undergo 14 sessions of 75 min each during a period of 16 weeks with either FCBT or FPRT depending on the allocation. Participants are randomised stratified by age and baseline Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS) score. The primary outcome is the CY-BOCS score. Secondary outcomes are health-related quality of life assessed using KIDSCREEN-10 and adverse events assessed by the Negative Effects Questionnaire (NEQ). Primary and secondary outcomes are assessed at the end of the intervention. Continuous outcomes will be analysed using linear regression adjusted for the stratification variables and baseline value of the continuous outcome. Dichotomous outcomes will be analysed using logistic regression adjusted for the stratification variables. The statistical analyses will be carried out by two independent blinded statisticians. DISCUSSION: This statistical analysis plan includes a detailed predefined description of how data will be analysed and presented in the main publication before unblinding of study data. Statistical analysis plans limit selective reporting bias. This statistical analysis plan will increase the validity of the final trial results. TRIAL REGISTRATION: ClinicalTrials.gov NCT03595098. July 23, 2018.
Cognitive Behavioral Therapy , Obsessive-Compulsive Disorder , Adolescent , Child , Cognitive Behavioral Therapy/methods , Family Therapy , Humans , Obsessive-Compulsive Disorder/diagnosis , Obsessive-Compulsive Disorder/psychology , Obsessive-Compulsive Disorder/therapy , Quality of Life , Relaxation Therapy , Treatment Outcome
BACKGROUND: Artificial intelligence tools have the potential to objectively identify youth in need of mental health care. Speech signals have shown promise as a source for predicting various psychiatric conditions and transdiagnostic symptoms. OBJECTIVE: We designed a study testing the association between obsessive-compulsive disorder (OCD) diagnosis and symptom severity on vocal features in children and adolescents. Here, we present an analysis plan and statistical report for the study to document our a priori hypotheses and increase the robustness of the findings of our planned study. METHODS: Audio recordings of clinical interviews of 47 children and adolescents with OCD and 17 children and adolescents without a psychiatric diagnosis will be analyzed. Youths were between 8 and 17 years old. We will test the effect of OCD diagnosis on computationally derived scores of vocal activation using ANOVA. To test the effect of OCD severity classifications on the same computationally derived vocal scores, we will perform a logistic regression. Finally, we will attempt to create an improved indicator of OCD severity by refining the model with more relevant labels. Models will be adjusted for age and gender. Model validation strategies are outlined. RESULTS: Simulated results are presented. The actual results using real data will be presented in future publications. CONCLUSIONS: A major strength of this study is that we will include age and gender in our models to increase classification accuracy. A major challenge is the suboptimal quality of the audio recordings, which are representative of in-the-wild data and a large body of recordings collected during other clinical trials. This preregistered analysis plan and statistical report will increase the validity of the interpretations of the upcoming results. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39613.
BACKGROUND: Cognitive behavioural therapy (CBT) is the recommended first-line treatment for children and adolescents with obsessive-compulsive disorder (OCD), but evidence concerning treatment-specific benefits and harms compared with other interventions is limited. Furthermore, high risk-of-bias in most trials prevent firm conclusions regarding the efficacy of CBT. We investigate the benefits and harms of family-based CBT (FCBT) versus family-based psychoeducation and relaxation training (FPRT) in youth with OCD in a trial designed to reduce risk-of-bias. METHODS: This is an investigator-initiated, independently funded, single-centre, parallel group superiority randomised clinical trial (RCT). Outcome assessors, data managers, statisticians, and conclusion drawers are blinded. From child and adolescent mental health services we include patients aged 8-17 years with a primary OCD diagnosis and an entry score of ≥16 on the Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS). We exclude patients with comorbid illness contraindicating trial participation; intelligence quotient < 70; or treatment with CBT, PRT, antidepressant or antipsychotic medication within the last 6 months prior to trial entry. Participants are randomised 1:1 to the experimental intervention (FCBT) versus the control intervention (FPRT) each consisting of 14 75-min sessions. All therapists deliver both interventions. Follow-up assessments occur in week 4, 8 and 16 (end-of-treatment). The primary outcome is OCD symptom severity assessed with CY-BOCS at end-of-trial. Secondary outcomes are quality-of-life and adverse events. Based on sample size estimation, a minimum of 128 participants (64 in each intervention group) are included. DISCUSSION: In our trial design we aim to reduce risk-of-bias, enhance generalisability, and broaden the outcome measures by: 1) conducting an investigator-initiated, independently funded RCT; 2) blinding investigators; 3) investigating a representative sample of OCD patients; 3) using an active control intervention (FPRT) to tease apart general and specific therapy effects; 4) using equal dosing of interventions and therapist supervision in both intervention groups; 5) having therapists perform both interventions decided by randomisation; 6) rating fidelity of both interventions; 7) assessing a broad range of benefits and harms with repeated measures. The primary study limitations are the risk of missing data and the inability to blind participants and therapists to the intervention. TRIAL REGISTRATION: ClinicalTrials.gov : NCT03595098, registered July 23, 2018.
Cognitive Behavioral Therapy , Obsessive-Compulsive Disorder , Adolescent , Child , Cognitive Behavioral Therapy/methods , Family Therapy , Humans , Obsessive-Compulsive Disorder/psychology , Outcome Assessment, Health Care , Randomized Controlled Trials as Topic , Relaxation Therapy , Treatment Outcome
In a recent letter to the editor, a group of clinician-researchers posit that the conclusions in our published systematic review1 on cognitive-behavioral therapy (CBT) for pediatric obsessive-compulsive disorder (OCD) are based on inappropriate methodology. In this reply, we address the concerns expressed by Storch et al.2.
Cognitive Behavioral Therapy , Obsessive-Compulsive Disorder , Adolescent , Child , Cognition , Humans , Obsessive-Compulsive Disorder/therapy
BACKGROUND: Concerns have been raised that synthetic oxytocin, a widely used obstetric tool for labor induction and augmentation, may have deleterious effects on the neuropsychological development of children. Few studies have examined the relationship between oxytocin-stimulated labor and emotional disorders. METHODS: We conducted a nationwide register-based cohort study including 677,629 singletons born in Denmark in the years 2000 to 2012 and followed through 2016 (median ageâ¯=â¯10.6 years). Data on oxytocin-stimulation were obtained from the Danish Medical Birth Register. Cases of emotional disorders - anxiety, obsessive-compulsive disorder, mood or traumatic stress disorders or a redeemed prescription for a selective serotonin reuptake inhibitor - were identified using Danish patient and prescription registries. RESULTS: Oxytocin was used to stimulate 31% of births, and oxytocin-stimulated labor was not associated with childhood emotional disorders (HRâ¯=â¯1.05, 95% CI 0.99, 1.11) after adjustment for maternal history of psychopathology, antidepressants during pregnancy, cohabitation status, highest educational attainment, smoking status during pregnancy, birth year, and indications for labor stimulation. The crude cox model was also small and close to unity (HRâ¯=â¯1.09, 95% CI 1.03, 1.15). LIMITATIONS: About 50% of our population had reached the age of 10 years, but the outcome included disorders with later average debut ages. Oxytocin dosage levels are not recorded in the registers. CONCLUSIONS: Our small effect size estimates suggest that perinatal synthetic oxytocin does not contribute to the development of emotional disorders. Current evidence does not warrant revision of guidelines for the use of oxytocin in obstetrics.
Oxytocin , Child , Cohort Studies , Denmark/epidemiology , Female , Humans , Pregnancy , Proportional Hazards Models , Registries
OBJECTIVE: To assess benefits and harms of cognitive-behavioral therapy (CBT) versus no intervention or versus other interventions for pediatric obsessive-compulsive disorder (OCD). METHOD: We searched for randomized clinical trials of CBT for pediatric OCD. Primary outcomes were OCD severity, serious adverse events, and level of functioning. Secondary outcomes were quality of life and adverse events. Remission from OCD was included as an exploratory outcome. We assessed risk of bias and evaluated the certainty of the evidence with the Grading of Recommendations Assessment, Development and Evaluation (GRADE). RESULTS: Nine trials (N = 645) were included comparing CBT with no intervention and 3 trials (N = 146) comparing CBT with selective serotonin reuptake inhibitors (SSRIs). Compared with no intervention, CBT decreased OCD severity (mean difference [MD] = -8.51, 95% CI = -10.84 to -6.18, p < .00001, low certainty), improved level of functioning (patient-rated: standardized MD [SMD] = -0.90, 95% CI = -1.19 to -0.62, p < .00001, very low certainty; parent-rated: SMD = -0.68, 95% CI = -1.12 to -0.23, p = .003, very low certainty), had similar proportions of participants with adverse events (risk ratio = 1.06, 95% CI = 0.93-1.22, p = .39, GRADE: low certainty), and was associated with reduced risk of still having OCD (risk ratio = 0.50, 95% CI = 0.37-0.67, p < .00001, very low certainty). We had insufficient data to assess the effect of CBT versus no intervention on serious adverse events and quality of life. Compared with SSRIs, CBT led to similar decreases in OCD severity (MD = -0.75, 95% CI = -3.79 to 2.29, p = .63, GRADE: very low certainty), and was associated with similar risk of still having OCD (risk ratio = 0.85, 95% CI = 0.66-1.09, p = .20, very low certainty). We had insufficient data to assess the effect of CBT versus SSRIs on serious adverse events, level of functioning, quality of life, and adverse events. CONCLUSION: CBT may be more effective than no intervention and comparable to SSRIs for pediatric OCD, but we are very uncertain about the effect estimates.
Cognitive Behavioral Therapy , Obsessive-Compulsive Disorder/psychology , Obsessive-Compulsive Disorder/therapy , Adolescent , Child , Humans , Quality of Life
Research has shown that anxiety may be transmitted through verbal information pathways, for example, when parents share their anxious cognitions with their child. Less is known about the influence of parental metacognitions, that is, beliefs regarding thoughts, on child anxiety. We explored the relations between metacognitions in mothers and their children and anxiety in the children. Our study included 111 non-clinical children aged 8 to 12 years and their mothers. Children rated their metacognitions, worry and anxiety, and mothers rated their metacognitions. Results indicated agreement between maternal and child metacognitions. Maternal metacognitions were positively associated with children's anxiety symptoms and worry, and this relation was mediated by the children's metacognitions. Our results warrant further examination of the role of parental metacognitions in child anxiety.
Anxiety , Metacognition , Mother-Child Relations , Mothers/psychology , Child , Female , Humans , Male
