Faculty Bibliography

There is a growing literature exploring the placebo response within specific mental disorders, but no overarching quantitative synthesis of this research has analyzed evidence across mental disorders. We carried out an umbrella review of meta-analyses of randomized controlled trials (RCTs) of biological treatments (pharmacotherapy or neurostimulation) for mental disorders. We explored whether placebo effect size differs across distinct disorders, and the correlates of increased placebo effects. Based on a pre-registered protocol, we searched Medline, PsycInfo, EMBASE, and Web of Knowledge up to 23.10.2022 for systematic reviews and/or meta-analyses reporting placebo effect sizes in psychopharmacological or neurostimulation RCTs. Twenty meta-analyses, summarising 1,691 RCTs involving 261,730 patients, were included. Placebo effect size varied, and was large in alcohol use disorder (g = 0.90, 95% CI [0.70, 1.09]), depression (g = 1.10, 95% CI [1.06, 1.15]), restless legs syndrome (g = 1.41, 95% CI [1.25, 1.56]), and generalized anxiety disorder (d = 1.85, 95% CI [1.61, 2.09]). Placebo effect size was small-to-medium in obsessive-compulsive disorder (d = 0.32, 95% CI [0.22, 0.41]), primary insomnia (g = 0.35, 95% CI [0.28, 0.42]), and schizophrenia spectrum disorders (standardized mean change = 0.33, 95% CI [0.22, 0.44]). Correlates of larger placebo response in multiple mental disorders included later publication year (opposite finding for ADHD), younger age, more trial sites, larger sample size, increased baseline severity, and larger active treatment effect size. Most (18 of 20) meta-analyses were judged 'low' quality as per AMSTAR-2. Placebo effect sizes varied substantially across mental disorders. Future research should explore the sources of this variation. We identified important gaps in the literature, with no eligible systematic reviews/meta-analyses of placebo response in stress-related disorders, eating disorders, behavioural addictions, or bipolar mania.

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The longitudinal collection of biological samples from over 7000 birthing parents and their children within the HBCD study enables research on pre- and postnatal exposures (e.g., substance use, toxicants, nutrition), and biological processes (e.g., genetics, epigenetic signatures, proteins, metabolites) on neurobehavioral developmental outcomes. The following biosamples are collected from the birthing parent: 1) blood (i.e., whole blood, serum, plasma, buffy coat, and dried blood spots) during pregnancy, 2) nail clippings during pregnancy and one month postpartum, 3) urine during pregnancy, and 4) saliva during pregnancy and at in-person postnatal assessments. The following samples are collected from the child at in-person study assessments: 1) saliva, 2) stool, and 3) urine. Additionally, placenta tissue, cord blood, and cord tissue are collected by a subset of HBCD sites. Here, we describe the rationale for the collection of these biospecimens, their current and potential future uses, the collection protocol, and collection success rates during piloting. This information will assist research teams in the planning of future studies utilizing this collection of biological samples.

Family functioning plays a critical role in childhood disruptive behavior disorders (The Family Journal, 2003, 11(1), 33-41; Research in Nursing and Health, 2016, 39(4), 229-243). Yet, there is limited research on the impact of evidence-based family strengthening interventions on improving family cohesion as a protective factor among children experiencing behavioral challenges. To address this gap, we analyzed data (N = 636) from the SMART Africa-Uganda study (2016-2022), a cluster randomized clinical trial testing an evidence-based family-strengthening intervention called Amaka Amasanyufu (translated as "Happy Families" in the local language). Children aged 8-13 and their caregivers were recruited from 26 public primary schools that were randomized to: (1) control condition receiving generalized psychosocial literature (10 schools), (2) intervention delivered via parent peers (eight schools), and (3) intervention delivered via community healthcare workers (eight schools). Children completed the family cohesion questionnaire at baseline, 8 weeks, 16 weeks, and 6 months post-intervention completion. The intervention effectiveness was evaluated via a three-level logistic mixed effects model with pairwise comparisons across study conditions within each time point. Participants in the parent-peer intervention group had greater odds of being in the higher family cohesion group than participants in the control group at 8 weeks (OR = 3.24), 16 weeks (OR = 1.88) and 6 months (OR = 2.07). At 8 weeks, 16 weeks, and 6 months, participants in the community health worker group had 3.98, 2.08, and 1.79 times greater odds of being in the higher family cohesion group than participants in the control group, respectively. Our findings strengthen the evidence base for Amaka Amansayufu as an effective intervention that can be utilized in SSA to improve family cohesion in families with children experiencing behavioral challenges.

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (β = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

Behavioral and mental health concerns are common, with depressive episodes reported by 1 in 5 adolescents and anxiety reported by 1 in 10 adolescents. In 2021, given the growing mental health crisis worsened by the COVID-19 pandemic, a state of emergency was declared in children's mental health and a national suicide prevention crisis hotline number, 988 was established. Despite the elevated rates of mental health concerns, the ability to access treatment is low and critical shortages in the U.S. Child and Adolescent Psychiatry workforce contribute to the lack of access to trained pediatric mental health professionals. Pediatric primary care is a natural setting for evidence-based and innovative primary, secondary, and tertiary prevention models due to universal access to patients. Pediatricians can integrate behavioral health care into their primary care practice though providing patients with care for common mental health issues either alone or collaborating with mental health specialists. However, the majority of pediatric trainees report that they do not feel competent to assess and treat pediatric patients with common B/MH concerns even though they feel that competency in these areas is important. Regulatory changes in pediatric training programs are necessary but change takes time. Integrated Behavioral Health (IBH) is a term used to describe a variety of models of care that can be implemented by teams of primary care and B/MH providers working together. These models use a systematic approach that emphasizes collaboration and communication to provide patient-centered care and improve patient health outcomes through increased access to and delivery of quality behavioral health care. The integration of behavioral health care into pediatric primary care has the potential to reduce disparities by increasing access to needed mental health care in a familiar and destigmatized environment, decrease wait time for services and improve the quality of B/MH care provided in the primary care setting.

Fetal inflammation, typically measured indirectly through prenatal maternal cytokine markers, has been shown to impact early childhood executive functions (EFs), which are central to later cognitive and life outcomes. Here, we assessed the impact of prenatal inflammation on EF developmental trajectories using direct placenta histopathology measures in 131 mothers who predominantly self-identified as Black (90.8% Black; 0.8% Asian American, 1.5% biracial, 0.8% Latinx, 3.1% White, 3.1% Missing). We found that placental measures of inflammation were associated with limited gain in EF development from 3 to 5 years old. In follow up analyses, we addressed whether screening questionnaires in infancy might aid in classification of infants as higher risk for subsequent EF problems. We found that parent responses to the Ages & Stages Questionnaire and the Infant/Toddler Sensory Profile at 12 months predict the development of EF abilities in children exposed to chronic inflammation. These findings open promising opportunities for early screening of children at risk for poor executive functioning in children exposed to prenatal inflammation.

OBJECTIVE:We conducted an umbrella review of systematic reviews (SRs), with or without meta-analysis (MA), of randomized controlled trials (RCTs) assessing nonpharmacological sleep interventions for children and adolescents across various clinical populations. METHOD/METHODS:We searched multiple electronic databases up to January 24, 2024. Meta-analyzable data from RCTs in the retrieved SRs/MAs were pooled using Metaumbrella. Primary outcomes were subjective/objective child sleep parameters. Additional outcomes included child health/functioning and parental sleep/health. The quality of the MAs/SRs was assessed with Assessment of Multiple Systematic Reviews (AMSTAR-2), and the certainty of evidence using Grading of Recommendations, Assessment, Development and Evaluations (GRADE). RESULTS:We included 93 SRs/MAs covering 393 RCTs, with 25 (17%, 39%, and 30%: high, moderate, and low quality) providing data for quantitative synthesis. Behavioral interventions, usually multicomponent including parent training, psychoeducation, and/or specific sleep therapy/strategies, showed beneficial effects on night waking, sleep duration, overall sleep disturbance, mood/depression, and maternal sleep quality (standardized mean difference [SMD] = 0.10-0.80) in participants with sleep problems without a formal sleep disorder diagnosis. For those with a formal diagnosis (mainly insomnia), benefits were found for night waking, sleep efficiency (subjective/actigraphically measured), and sleep onset latency (mean SMD = 0.49-0.97). Those with attention-deficit/hyperactivity disorder (ADHD) improved in bedtime resistance, night waking, parasomnias, sleep anxiety, ADHD symptoms, sleep disturbance, and quality of life (mean SMD = 0.18-0.49). For those with autism, sleep disturbance improved (mean SMD = 0.70). However, all findings were of low to very low certainty of evidence. CONCLUSION/CONCLUSIONS:Among nonpharmacological interventions for sleep difficulties in youth, only behavioral interventions are supported by meta-analytic evidence, yet with small-to-moderate effect sizes and limited certainty of evidence. STUDY PREREGISTRATION INFORMATION/UNASSIGNED:The efficacy and tolerability of nonpharmacological interventions for sleep problems in children and adolescents: protocol for an umbrella review of systematic reviews and meta-analyses of randomised controlled trials. https://osf.io; j9qna/.

BACKGROUND:Placebo and nocebo effects are widely reported across psychiatric conditions, yet have seldom been examined in the context of gambling disorder. Through meta-analysis, we examined placebo effects, their moderating factors, and nocebo effects, from available randomised, controlled pharmacological clinical trials in gambling disorder. METHODS:We searched, up to 19 February 2024, a broad range of databases, for double-blind randomised controlled trials (RCTs) of medications for gambling disorder. Outcomes were gambling symptom severity and quality of life (for efficacy), and drop outs due to medication side effects in the placebo arms. RESULTS:= 833) in the meta-analysis. The overall effect size for gambling severity reduction in the placebo arms was 1.18 (95%CI 0.91-1.46) and for quality of life improvement was 0.63 (0.42-0.83). Medication class, study sponsorship, trial duration, baseline severity of gambling and publication year significantly moderated effect sizes for at least some of these outcome measures. Author conflict of interest, placebo run-in, gender split, severity scale choice, age of participants or unbalanced randomisation did not moderate effect sizes. Nocebo effects leading to drop out from the trial were observed in 6% of participants in trials involving antipsychotics, while this was less for other medication types. CONCLUSION/CONCLUSIONS:Placebo effects in trials of pharmacological treatment of gambling disorder are large, and there are several moderators of this effect. Nocebo effects were measureable and may be influenced by medication class being studied. Practical implications of these new findings for the field are discussed, along with recommendations for future clinical trials.