About

Booil Jo is a Professor of Psychiatry and Behavioral Sciences at Stanford University, specializing in Interdisciplinary Brain Science Research. His research focuses on latent variable modeling, causal inference, longitudinal data analysis, missing data analysis, mixture and growth mixture modeling, and prevention science methodology. He has contributed to understanding heterogeneity among unobserved subpopulations in mental health research and has been involved in various courses related to research methodology in behavioral sciences. His academic background includes a Ph.D. in Applied Statistics from UCLA, obtained in 1998. Dr. Jo has been actively engaged in research that explores complex statistical methods to improve mental health and behavioral science studies. His work has been recognized through awards such as the R01 grant from NIMH for studying heterogeneity in mental health populations. He also serves as a doctoral dissertation reader and faculty sponsor for postdoctoral researchers, contributing to the development of future scholars in his field.

Research topics

• Medicine
• Psychiatry
• Internal medicine
• Psychology
• Neuroscience
• Pediatrics
• Physical medicine and rehabilitation
• Endocrinology
• Audiology

Selected publications

• Family vs Individual Treatment for Children With Avoidant/Restrictive Food Intake Disorder: A Randomized Clinical Trial

  Journal of the American Academy of Child & Adolescent Psychiatry · 2026-04-01

  articleOpen access

  OBJECTIVE: To examine the comparative efficacy of Family-based Treatment for Avoidant/Restrictive Food Intake Disorder (FBT-ARFID) to individual Psychoeducational Motivational Therapy (PMT) for underweight children with ARFID between the ages of 6 and 12 years of age. The main outcome evaluated was the difference between groups on change in percent estimated body weight (%EBW) from baseline (BL) to end of treatment (EOT). METHOD: Ninety-eight children with ARFID were randomized to 14 sessions over 4 months of telehealth FBT-ARFID or PMT. Assessments of weight/height, eating-related cognitions, and behaviors associated with ARFID were collected online at BL, 1 month, 2 months, and EOT by assessors masked to treatment condition. RESULTS: FBT-ARFID was superior to PMT at the EOT in promoting increased %EBW. There were no differences between groups on improvements in overall severity of ARFID symptoms or other related ARFID symptoms; however, BL severity of ARFID symptoms moderated the effect, with children who were most symptomatic improving significantly more in FBT-ARFID than in PMT (exploratory analyses). CONCLUSION: FBT-ARFID is superior to PMT for promoting weight gain in low-weight children with ARFID, especially for those children with greater severity of ARFID symptoms.

  PublisherDOI

• 0953 Multifaceted Effect of Sleep Problems on Emotion Dysregulation in Individuals with ASD

  SLEEP · 2026-05-01

  article

  Abstract Introduction Sleep disturbances are known to be closely linked to emotion dysregulation (ED) across various psychiatric disorders. In individuals with autism spectrum disorder (ASD), the complex interaction of diverse symptoms is assumed to underlie difficulties in emotion regulation, whereas the presence of ED may, in turn, exacerbate other symptoms. However, despite the high prevalence of sleep problems among children with autism, their impact on ED has not been well recognized. The present study aimed to examine how, and to what extent, sleep problems in children with autism influence the association between ED and ASD behaviors. Methods Ninety-five individuals with ASD (25 females; age: 10.56 ± 3.67 years; range: 4-17) participated in the study. The Children's Sleep Habits Questionnaire and Child Behavior Checklist Dysregulation Profile were used to assess subjective sleep problems and ED, respectively. Other ASD behaviors were assessed using the Social Responsiveness Scale, 2nd Edition, the Repetitive Behavior Scale–Revised, and the Sensory Profile, 2nd Edition. Pearson correlation and regression analyses examined associations among ASD behaviors, ED, and sleep problems. To test the mediating effect of sleep problems on the relationship between ASD behaviors and ED as the outcome, Hayes’ PROCESS macro was used. Results 1) More severe parent-reported sleep problems were shown to be associated with greater ED severity. 2) Social communication, restricted and repetitive behaviors, and sensory sensitivity in children with autism were all significantly related to ED. 3) The mediation analyses revealed a significant indirect effect of social communication, restricted and repetitive behaviors, and sensory sensitivity on ED through sleep problems (β=0.37, 95%CI = [0.17 0.58], β=0.39, 95%CI = [0.19 0.62], and β=0.41, 95%CI = [0.20 0.66], respectively). Conclusion Our preliminary findings with cross-sectional data indicate that sleep problems are not merely co-occurring features of ASD but serve as a mediating factor through which core autistic behaviors and sensory experiences contribute to ED. This suggests that sleep disturbances exert multifaceted influences on the diverse symptom domains of autism, potentially serving as an aggravating factor. These results underscore the importance of targeting sleep problems as a potential therapeutic intervention for improving ED in individuals with autism. Support (if any)

  PublisherDOI

• A Stratified Precision Medicine Trial Targeting Selective Mechanisms of Alpha 2A Agonism as a Treatment for the Cognitive Biotype of Depression: The BIomarker Guided (BIG) Study for Depression

  Research Square · 2025-02-27 · 2 citations

  preprintOpen access
  PublisherOA PDFDOI

• Differences in White Matter Microstructure in Children With Type 1 Diabetes Persist During Longitudinal Follow-up: Relation to Dysglycemia

  Diabetes · 2025-06-02 · 6 citations

  articleOpen access

  Type 1 diabetes has detrimental effects in white matter microstructure. In a longitudinal study, we investigated whether these reported findings change as children grow and enter puberty. At study entry, there were 143 children with type 1 diabetes and 71 control participants without diabetes, 4-9 years old. Brain MRI using diffusion tensor imaging, neurocognitive, and glycemic assessments were performed four times across 6-8 years of follow-up. Longitudinal mixed-effects modeling was used to examine changes in fractional anisotropy (FA), axial diffusivity (AD) (measures of myelination and fiber integrity), radial diffusivity (RD) (axonal leakage), and mean diffusivity (MD) (average diffusion). Associations with glycemic and cognitive measures were assessed. We observed in 182 children (121 type 1 diabetes vs. 61 control participants) who had testing at time 4 that FA increased, and RD, AD, and MD decreased significantly in both groups, with no differences between groups for FA, RD and MD over time. However, children with diabetes had lower AD than control participants at 6-10 years. Differences were not detected at 12 years (age imputed from data), when in puberty. Higher blood glucose levels are associated with lower FA and higher RD and MD. Higher glucose percentage time-in-range was associated with higher FA, reflecting better fiber integrity and myelination and higher cognitive metrics. Within the diabetes group, AD and MD showed no association with neurocognitive outcomes. In summary, white matter AD was decreased in children with diabetes, less so during puberty, and FA was reciprocally related to hyperglycemia. These data suggest continued negative impact of chronic hyperglycemia in the developing brain. ARTICLE HIGHLIGHTS: Type 1 diabetes has detrimental effects in white matter in young children. We performed a longitudinal study using brain MRI (diffusion tensor imaging) and cognitive assessments in 4- to 9-year-old children, control participants without diabetes (n = 71) and with type 1 diabetes (n = 143), plus continuous glucose monitoring, to assess changes at four time points as children grow over 6-8 years. White matter myelination and fiber integrity were assessed using axial diffusivity, which was decreased in the diabetes versus control group, less so during puberty, and fractional anisotropy was reciprocally related to hyperglycemia. Data suggest continued negative impact of chronic hyperglycemia in the developing brain.

  PublisherOA PDFDOI

• A data-driven latent variable approach to validating the research domain criteria framework

  Nature Communications · 2025-01-18 · 11 citations

  articleOpen access

  Despite the widespread use of the Research Domain Criteria (RDoC) framework in psychiatry and neuroscience, recent studies suggest that the RDoC is insufficiently specific or excessively broad relative to the underlying brain circuitry it seeks to elucidate. To address these concerns, we employ a latent variable approach using bifactor analysis. We examine 84 whole-brain task-based fMRI (tfMRI) activation maps from 19 studies with 6192 participants. A curated subset of 37 maps with a balanced representation of RDoC domains constitute the training set, and the remaining held-out maps form the internal validation set. External validation is conducted using 36 peak coordinate activation maps from Neurosynth, using terms of RDoC constructs as seeds for topic meta-analysis. Here, we show that a bifactor model incorporating a task-general domain and splitting the cognitive systems domain better fits the examined corpus of tfMRI data than the current RDoC framework. We also identify the domain of arousal and regulatory systems as underrepresented. Our data-driven validation supports revising the RDoC framework to reflect underlying brain circuitry more accurately.

  PublisherOA PDFDOI

• Randomized Feasibility Trial of Teleyoga versus In-Person Yoga for Treating Chronic Musculoskeletal Pain in Veterans

  Research Square · 2025-06-23

  preprintOpen access
  PublisherOA PDFDOI

• Are observation codes underused for emergency psychiatric patients with an extended length of stay? A retrospective commercial claims analysis from 2016 to 2022

  General Hospital Psychiatry · 2025-10-27

  articleOpen access
  PublisherOA PDFDOI

• Treatable Traits in Long COVID: Inhaled corticosteroids and long-acting bronchodilators for small airway dysfunction among symptomatic Long COVID patients without known Asthma

  Research Square · 2025-10-21

  preprintOpen access
  PublisherOA PDFDOI

• Effects of app delivered self hypnosis on stress management

  npj Digital Medicine · 2025-12-18

  articleOpen access

  Stress and stress-related chronic illness are increasing worldwide while mental health care access remains limited. Recent neurophysiological advances support the effectiveness and safety of hypnosis for stress management. In this retrospective observational study, we studied app-delivered hypnosis in 84,395 users across 282,893 stress reduction sessions. Users rated pre- and post-session stress on a 10-point Likert Scale. Data analysis utilized Linear Mixed Effects (LME) models to accommodate repeated measures and missing data. Effects of session type, user hypnotizability, age, sex, and membership were assessed. Pre-to-post stress reduction occurred consistently in each of the first 10 sessions (Cohen's d values ranging from -0.71 to -0.78), demonstrating significant improvement in stress management. Across the first 10 sessions, greater stress reduction was observed with interactive and regular-length sessions, higher hypnotizability, older age groups, and paying members. Findings provide evidence that disseminable digital formulations of hypnosis contribute meaningfully to stress reduction.

  PublisherOA PDFDOI

• Developing a text mining-based process for comparative analysis of trends in periodic trade shows: Focusing on CES

  Journal of MICE & Tourism Research · 2025-02-28

  article1st authorCorresponding

  This study aims to analyze the key characteristics and trends of international exhibitions by examining news article text data from the Consumer Electronics Show between 2022 and 2024. While domestic companies across various industries recognize international exhibitions as significant strategic opportunities for global market expansion, the fragmented and inconsistent nature of exhibition-related information across multiple platforms poses a challenge in selecting the most suitable exhibitions and making informed strategic decisions. To address this issue, this study employs Latent Dirichlet Allocation topic modeling and sentiment analysis, two key techniques in natural language processing, to establish a standardized process for analyzing exhibition trends. The findings provide actionable insights that enable domestic companies to make data-driven strategic decisions, select exhibitions aligned with their goals, and develop effective global marketing strategies.

  PublisherDOI

Recent grants

• NIH Grant R01DA031698

  NIH · $652k · 2017

• NIH Grant R01MH066319

  NIH · $620k · 2008

Frequent coauthors

• Amit Etkin

  112 shared

• Gregory A. Fonzo

  Multidisciplinary Association for Psychedelic Studies

  110 shared

• Sanno Zack

  Stanford University

  109 shared

• Meredith Harvey

  109 shared

• Kathy Peng

  Stanford University

  109 shared

• Steven E. Lindley

  Stanford University

  108 shared

• Madeleine S. Goodkind

  University of New Mexico

  107 shared

• Bruce A. Arnow

  107 shared

Labs

• Booil Jo LabPI

Education

• Ph.D., Applied Statistics

  UCLA

  1998

Awards & honors

• R01: Heterogeneity among unobserved (underlying) subpopulati…