Citations

ABSTRACT Consumer‐grade wearables, including smartwatches, fitness trackers, and smart rings, are accessible tools for studying pharmacologic responses in real‐time, monitoring participant health in decentralized clinical trials, optimizing outcome measures, and delivering digital interventions that promote behavior change. However, incorporating consumer wearables into clinical studies is not as straightforward as simply purchasing devices and providing them to participants. It requires engaging with a complex engineering ecosystem with multiple investigator decisions on device selection, associated data management practices, and patient/participant engagement and technical support. This tutorial, based on experience running large clinical trials using consumer wearables, outlines the wearables market landscape across varying form factors and manufacturers as well as the data management software products supporting wearable use. It delineates the major decision processes involved in designing studies that incorporate wearables and presents a structured framework to guide the selection of devices and supporting data tools according to study objectives.

Background: Cardiac biomarkers are recognized as potential indicators for brain function, emotion regulation, and psychiatric risk. While research in adults has suggested associations between cardiac variables of autonomic function and neural changes, little is known about these relationships in children and young adults with psychiatric conditions. This systematic review aimed to examine the evidence linking cardiac biomarkers with structural, functional, and connectivity-based brain changes in this population. Methods: A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Multiple databases were searched for studies examining associations between any cardiac biomarker and neuroimaging findings in individuals under 21 years old with psychiatric diagnoses. After screening and full-text review, 11 eligible studies were included. Results: The included studies investigating a range of psychiatric conditions and cardiac biomarkers were associated with brain changes across three domains: structure, connectivity, and neural responses. Associations were most consistent between higher vagal tone and structural and functional integrity of emotion-regulating regions such as the prefrontal cortex, amygdala, and insula. However, findings were heterogeneous and potentially moderated by symptom severity or environmental stressors. Conclusions: This review supports the potential of cardiac biomarkers, particularly high-frequency heart rate variability and root mean square of the successive differences, as proxies of brain changes in youth with psychiatric disorders. While promising, current evidence is too limited and variable for clinical applications. Future research should prioritize large-scale, longitudinal studies using harmonized protocols and wearable technologies to validate these indices as translational tools in child and adolescent psychiatry.

Objective: This study aimed to examine whether parent–child interaction therapy (PCIT), compared with other therapy modalities, was associated with differences in substance use and psychiatric outcomes in a cohort of children with attention-deficit/hyperactivity disorder (ADHD). Methods: This retrospective cohort study was conducted using medical record data from the Rochester Epidemiology Project (REP). The sample included 643 children aged ≤7 years who were diagnosed with ADHD and received either stimulant or nonstimulant medication, along with psychosocial therapy. Participants were categorized into two groups: those who documented exposure to PCIT versus other therapy modalities such as behavioral management, play therapy, cognitive behavioral therapy, parent management training, occupational therapy, speech therapy, parenting class, applied behavior analysis, and social skills training. Conditional logistic regression models were used to examine differences in baseline characteristics and outcomes between the two treatment groups. Results: Individuals in the PCIT group were more likely to have private insurance (66% vs. 57%; p = 0.016) and to fall into higher socioeconomic status quartiles ( p = 0.024) at baseline. PCIT recipients also had a higher prevalence of emotional and behavioral disturbances at baseline (40% vs. 25%; p < 0.001). The median age of the participants at follow-up was 19.6 years, indicating a median follow-up period of approximately 13 years from the initiation of treatment. At follow-up, the PCIT group demonstrated higher rates of problematic alcohol (24% vs. 17%; HR = 1.50, 95% CI: [1.02, 2.20]; p = 0.038) and cannabis use (25% vs. 18%; HR = 1.48, 95% CI: [1.03, 2.15]; p = 0.037). However, after controlling for covariates in the adjusted model, no statistically significant differences emerged between the groups across any substance use outcome. No significant differences were observed in other psychiatric diagnoses or mental health service utilization. Conclusions: Findings indicate that individuals who documented exposure to PCIT demonstrated elevated rates of alcohol and cannabis use in young adulthood, but had no other differences in psychiatric outcomes. While this aligns with prior literature reporting increased substance use risk in ADHD populations, our study cannot confirm this association relative to non-ADHD controls because such a comparison was not included. These associations likely reflect underlying differences in clinical severity and clinical comorbidities at baseline, rather than a direct effect of PCIT. Further investigation is warranted to determine the treatment effects based on baseline risk factors.

Introduction Psychiatric disorders have their genesis in early life. Standard screening approaches during well child visits for pathological infant distress, maternal depression, and dysfunctional parenting behaviors are likely inadequate. Microbiome measures and infant vocalizations have promise as scalable psychiatric biomarkers for infants. The purpose of this study was to examine associations among infant gut colonization based on microbiome measurements with maternal distress and maternal depressive symptoms in a sample of infants. Methods This study sought to examine infant microbiome correlates of infant distress, parent-infant interactions, maternal distress, and maternal depressive symptoms. We collected ( N = 31) microbiome samples, infant vocalizations during vaccination, and behavioral measures during a 4 month well child visit (WCV) and did a battery of clinical assessments to assess for maternal depression, parent-child interactions, family characteristics and family stress. Whole-genome SHOTGUN sequencing was utilized to identify three types of associations: alpha-diversity using Shannon and Inverse-Simpson indexes, beta-diversity using Bray-Curtis and Jaccard distances, and differential abundance using LinDA. Spectral measures of infant cries were also modeled to assess potential relationships with clinical assessments and the microbiome. Results There were 19 phyla, 417 genera, and 1246 species identified with taxonomic classification. Maternal distress as measured by PHQ-9 scores obtained when infants were 2 months old were associated with 4 bacterial species ( Actinomyces johnsonii, Bilophila wadsworthia, Clostridium dakarense and Ruminococcus flavefaciens ; FDR < 0.1) and beta-diversity ( p = 0.006-BC; p = 0.005-Jaccard). Infant cries with greater high frequency band power ( p < 0.03) and a greater high-to-mid frequency ratio–metrics ( p < 0.05) were associated with altered α-diversity of the microbiome. No correlations were present between maternal PHQ-9 at 4 months, PSI-IV and microbiome diversity. Conclusion The present findings suggest that an infant stress (assessed by quality of crying) is associated with lower microbiome diversity. Decreased diversity reflects an unhealthy microbiome. Parental depressive symptoms may also influence infant microbiome. Future interventional studies focused on the quality of the infant-caregiver relationship should examine related changes in intestinal microbiota.

Importance Youth mental health crises have been increasing over the last decade, and there is an urgent need for clinicians to be more knowledgeable about patients with high emergency department (ED) utilization. Several disparities in ED utilization and outcomes have already been identified; however, little data exist on disparities affecting youths with histories of out-of-home placement (OOHP). Objective To explore whether history of OOHP is associated with increased length of stay among child and adolescent patients who present to the emergency department with psychiatric symptoms. Design, Setting, and Participants This retrospective, electronic health record (EHR)–based, cross-sectional study included patients aged 17 years or younger with a child and adolescent psychiatric consultation placed in the Mayo Clinic Rochester ED between January 1, 2021, and June 30, 2024. The Mayo Clinic Rochester is a tertiary referral center that serves as a regional hub for both primary and specialized psychiatric care. Main Outcomes and Measures The primary outcome was the length of stay in the ED. Secondary outcomes were use of physical and pharmacological restraint. Associations between OOHP and length of stay were examined via linear mixed-effects regression models with length of stay log transformed. Results Of the 1572 care encounters (median [IQR] age, 14,9 [13.3-16.3] years) among 1119 unique patients, there were 1244 with no history of OOHP and 328 with history of OOHP. Among the OOHP group, 158 (48%) were male and 170 (52%) female; 11 (4%) American Indian or Alaska Native, 7 (2%) Asian, 49 (16%) Black, 43 (14%) Hispanic, and 222 (71%) White. Among the 1244 encounters without OOHP, 820 (66%) were among female patients and 423 (34%) male; 21 (2%) American Indian or Alaska Native, 47 (4%) Asian, 121 (10%) Black, 125 (10%) Hispanic, and 971 (80%) White. Children and adolescents with history of OOHP were observed to spend 24% (95% CI, 12%-36%) more time in the ED even when adjusting for age at admission, sex, insurance, number of prior diagnoses, presenting concerns, and reasons for prolonged boarding ( P = .004). Children and adolescents with history of OOHP had 2.05 (95% CI, 1.69-2.48) higher odds of being physically restrained ( P &amp;lt; .001) and 2.15 (95% CI, 1.79-2.58) higher odds of receiving pharmacologic restraints ( P &amp;lt; .001) while in the ED. Conclusions and Relevance In this cross-sectional study of 1572 care encounters among 1119 patients, history of OOHP was associated with longer lengths of stay in the emergency department for children and adolescents who presented for mental health concerns. The findings highlight the need for further research on ways to mitigate the risk of extended emergency department stays for children with OOHP.

Importance The potential utility of real-time digital therapeutics that identify impending behavioral outbursts to proactively apply evidence-based interventions for managing children with disruptive behavior disorder has not been tested. Objectives To evaluate feasibility and adherence of a digitally augmented, real-time, proactive behavioral intervention (smartwatch) for children with disruptive behaviors. Design, Setting, and Participants This randomized clinical trial was conducted between March 1, 2022, and December 31, 2023, at Mayo Clinic in Rochester, Minnesota. The study enrolled children aged 3 to 7 years with externalizing behavior problems rated above the clinically significant range (I score ≥120; T score ≥60) on the Eyberg Child Behavior Inventory (ECBI). Interventions Twelve weekly sessions of parent-child interaction therapy (PCIT) (treatment as usual [TAU] arm) vs artificial intelligence (AI)–enhanced PCIT augmented with real-time behavioral outburst alerts (PCIT-AI arm). Main Outcomes and Measures The primary outcome was achieving the a priori feasibility benchmark set at greater than 70% for both completion of PCIT sessions and daily smartwatch wear. Parental reaction time to behavior prompts was measured in seconds. Secondary outcomes were percentage changes in ECBI and Pediatric Sleep Questionnaire scores. Behavioral outburst duration was examined based on parental logs of start and end times of observed tantrums using a smartphone application. Result This study enrolled 50 children (median [IQR] age, 5.0 [4.0-6.0] years; 34 [68%] male and 16 [32%] female; 28 randomized to the PCIT-AI arm and 22 to the PCIT-TAU arm). Of these children, 37 (74%; 21 in the PCIT-AI arm and 16 in the PCIT-TAU arm) completed PCIT, with children wearing the watch a median (IQR) 75.7% (67.8%-82.9%) of the time, thus achieving the feasibility benchmark (primary outcome). Median (IQR) response time to behavior prompts in the PCIT-AI arm was 3.65 (2.07-7.08) seconds. Assessing between-group differences, there was no statistically significantly greater numerical improvement in ECBI-intensity percentage change (13.86%; 95% CI, −1.41% to 29.14%), ECBI-problem percentage change subscale scores (38.59%; 95% CI, −1.22% to 78.40%), or absolute change in Pediatric Sleep Questionnaire scores (−0.16; 95% CI, −1.85 to 1.53) with the PCIT-AI arm than with the PCIT-TAU arm. Children in the PCIT-AI arm had significantly shorter mean (SD) tantrum durations (10.4 [20.8] minutes vs 22.1 [30.0] minutes; P &amp;lt; .001) and lower odds of tantrums lasting for 15 minutes or more (odds ratio, 3.66; 95% CI, 2.72-4.95). Conclusions and Relevance In this randomized clinical trial, both recruitment and technology feasibility benchmarks were achieved. The findings inform the design of fully powered efficacy study of wearable, digitally augmented PCIT for children with disruptive behaviors. Trial Registration ClinicalTrials.gov Identifier: NCT05077722

Introduction/Objectives: We aimed to investigate the effect of family structure on depression program outcomes for adolescents enrolled in a depression-focused, primary care-based collaborative care program. Methods: This was a retrospective study of primary care patients ages 12 to 18 years seen at a Midwestern academic center with data obtained by medical record review. We used logistic regression models to assess the effect of family structure on program graduation and achievement of a single Patient Health Questionnaire 9–Modified for Adolescents (PHQ-9M) score <5 at any time while enrolled. Results: Adolescents were divided into 2 groups, Both Parents in Household (n = 179) and Parents Not Together (n = 161). The Both Parents in Household group had higher rates of graduation (38.0% vs 23.6%, P = .005) and achieving single PHQ-9M scores <5 (64.1% vs 46.2%, P = .002) than the Parents Not Together group. Discussion: Youth residing with both parents had higher rates of successful outcomes in a depression-focused collaborative care program.

Objective: Parents frequently purchase and inquire about smartwatch devices to monitor child behaviors and functioning. This pilot study examined the feasibility and accuracy of using smartwatch monitoring for the prediction of disruptive behaviors. Methods: The study enrolled children ( N = 10) aged 7–10 years hospitalized for the treatment of disruptive behaviors. The study team completed continuous behavioral phenotyping during study participation. The machine learning protocol examined severe behavioral outbursts (operationalized as episodes that preceded physical restraint) for preparing the training data. Supervised machine learning methods were trained with cross-validation to predict three behavior states—calm, playful, and disruptive. Results: The participants had a 90% adherence rate for per protocol smartwatch use. Decision trees derived conditional dependencies of heart rate, sleep, and motor activity to predict behavior. A cross-validation demonstrated 80.89% accuracy of predicting the child's behavior state using these conditional dependencies. Conclusion: This study demonstrated the feasibility of 7-day continuous smartwatch monitoring for children with severe disruptive behaviors. A machine learning approach characterized predictive biomarkers of impending disruptive behaviors. Future validation studies will examine smartwatch physiological biomarkers to enhance behavioral interventions, increase parental engagement in treatment, and demonstrate target engagement in clinical trials of pharmacological agents for young children.