Combining developmental and sleep health measures for autism spectrum disorder screening: an ECHO study.

BACKGROUND: Sleep problems are reported for up to 80% of autistic individuals. We examined whether parsimonious sets of items derived from the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Brief Infant Sleep Questionnaire (BISQ) are superior to the standard M-CHAT-R in predicting subsequent autism spectrum disorder (ASD) diagnoses. METHODS: Participants from 11 Environmental influences on Child Health Outcomes (ECHO) cohorts were included. We performed logistic LASSO regression models with 10-fold cross-validation to identify whether a combination of items derived from the M-CHAT-R and BISQ are superior to the standard M-CHAT-R in predicting ASD diagnoses. RESULTS: The final sample comprised 1552 children. The standard M-CHAT-R had a sensitivity of 44% (95% CI: 34, 55), specificity of 92% (95% CI: 91, 94), and AUROC of 0.726 (95% CI: 0.663, 0.790). A higher proportion of children with ASD had difficulty falling asleep or resisted bedtime during infancy/toddlerhood. However, LASSO models revealed parental reports of sleep problems did not improve the accuracy of the M-CHAT-R in predicting ASD diagnosis. CONCLUSION: While children with ASD had higher rates of sleep problems during infancy/toddlerhood, there was no improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. IMPACT: Parental-reported sleep problems are common in autism spectrum disorder (ASD). We investigated whether the inclusion of parental-reports of infant/toddler sleep patterns enhanced the effectiveness of developmental screening for autism. We reported higher rates of difficulty falling asleep and resisting bedtime during infancy and toddlerhood among children later diagnosed with ASD; however, we did not find an improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. In our sample, the standard M-CHAT-R had a sensitivity of 39% among children of mothers with government insurance compared with a sensitivity of 53% among children of mothers with employer-based insurance.

Patients and family attitudes about clinical and research sharing of electronic clinical data.

PURPOSE: To access the attitudes of service users about the sharing of health records for research and to foster collaboration between municipal health services and the specialist health services in Norway. METHODS: Members (n ≈ 2000) of the Norwegian mental health service users' organizations (SUO's), ADHD Norway, the Autism Association and the Tourette Association, representing Central Norway, participated in the study, (N = 108, 5.4% response rate). Descriptive statistics were used to evaluate distributions of responses to the questionnaire. RESULTS: Service users reported being aware that municipal health services collaborate with the specialist health service (62%), with mental health care in the specialist health service (57%), and child and adolescent psychiatric services (61%). A large proportion of individuals were aware of the benefits of sharing their health records (93%), have trust in the use of data by health authorities (81%), and were willing to share records to benefit fellow patients (84%). Personal experience (69%) and impressions from mainstream media (55%) had the most influential impact on users' views of the Health Platform, an electronic health communication system. A majority of users had a negative perception of the Health Platform, even though some expect it to become a valuable tool in the future (50%). CONCLUSIONS: Service users are aware of and positive about benefiting others by sharing health records. They trust the health authorities, however, have negative attitudes about the Health Platform, apparently based on personal experiences and media influence. However, service users can see the potential usefulness of the Health Platform in the future.

Economic evidence of clinical decision support systems in mental health: A systematic literature review.

Mental health conditions are among the highest disease burden on society, affecting approximately 20% of children and adolescents at any point in time, with depression and anxiety being the leading causes of disability globally. To improve treatment outcomes, healthcare organizations turned to clinical decision support systems (CDSSs) that offer patient-specific diagnoses and recommendations. However, the economic impact of CDSS is limited, especially in child and adolescent mental health. This systematic literature review examined the economic impacts of CDSS implemented in mental health services. We planned to follow PRISMA reporting guidelines and found only one paper to describe health and economic outcomes. A randomized, controlled trial of 336 participants found that 60% of the intervention group and 32% of the control group achieved symptom reduction, i.e. a 50% decrease as per the Symptom Checklist-90-Revised (SCL-90-R), a method to evaluate psychological problems and identify symptoms. Analysis of the incremental cost-effectiveness ratio found that for every 1% of patients with a successful treatment result, it added €57 per year. There are not enough studies to draw conclusions about the cost-effectiveness in a mental health context. More studies on economic evaluations of the viability of CDSS within mental healthcare have the potential to contribute to patients and the larger society.

A review of information sources and analysis methods for data driven decision aids in child and adolescent mental health services.

OBJECTIVE: Clinical data analysis relies on effective methods and appropriate data. Recognizing distinctive clinical services and service functions may lead to improved decision-making. Our first objective is to categorize analytical methods, data sources, and algorithms used in current research on information analysis and decision support in child and adolescent mental health services (CAMHS). Our secondary objective is to identify the potential for data analysis in different clinical services and functions in which data-driven decision aids can be useful. MATERIALS AND METHODS: We searched related studies in Science Direct and PubMed from 2018 to 2023(Jun), and also in ACM (Association for Computing Machinery) Digital Library, DBLP (Database systems and Logic Programming), and Google Scholar from 2018 to 2021. We have reviewed 39 studies and extracted types of analytical methods, information content, and information sources for decision-making. RESULTS: In order to compare studies, we developed a framework for characterizing health services, functions, and data features. Most data sets in reviewed studies were small, with a median of 1,176 patients and 46,503 record entries. Structured data was used for all studies except two that used textual clinical notes. Most studies used supervised classification and regression. Service and situation-specific data analysis dominated among the studies, only two studies used temporal, or process features from the patient data. This paper presents and summarizes the utility, but not quality, of the studies according to the care situations and care providers to identify service functions where data-driven decision aids may be relevant. CONCLUSIONS: Frameworks identifying services, functions, and care processes are necessary for characterizing and comparing electronic health record (EHR) data analysis studies. The majority of studies use features related to diagnosis and assessment and correspondingly have utility for intervention planning and follow-up. Profiling the disease severity of referred patients is also an important application area.

Challenges in Interpreting Norwegian Child and Adolescent Mental Health Records.

The Electronic Health Record system BUPdata served Norwegian Child and Adolescent Mental Health Services (CAMHS) for over 35 years and is still an important source of information for understanding clinical practice. Secondary usage of clinical data enables learning and service quality improvement. We present some insights from explorative data analysis for interpreting the records of patients referred for hyperkinetic disorders. The major challenges were data preparation, pre-analysis, imputation, and validation. We summarize the main characteristics, spot anomalies, and detect errors. The results include observations about the patient referral diversity based on 12 different variables. We modeled the activities in an individual episode of care, described our clinical observations among data, and discussed the challenges of data analysis.

Measurement bias in caregiver-report of early childhood behavior problems across demographic factors in an ECHO-wide diverse sample.

Background: Research and clinical practice rely heavily on caregiver-report measures, such as the Child Behavior Checklist 1.5-5 (CBCL/1.5-5), to gather information about early childhood behavior problems and to screen for child psychopathology. While studies have shown that demographic variables influence caregiver ratings of behavior problems, the extent to which the CBCL/1.5-5 functions equivalently at the item level across diverse samples is unknown. Methods: Item-level data of CBCL/1.5-5 from a large sample of young children (N = 9087) were drawn from 26 cohorts in the Environmental influences on Child Health Outcomes program. Factor analyses and the alignment method were applied to examine measurement invariance (MI) and differential item functioning (DIF) across child (age, sex, bilingual status, and neurodevelopmental disorders), and caregiver (sex, education level, household income level, depression, and language version administered) characteristics. Child race was examined in sensitivity analyses. Results: Items with the most impactful DIF across child and caregiver groupings were identified for Internalizing, Externalizing, and Total Problems. The robust item sets, excluding the high DIF items, showed good reliability and high correlation with the original Internalizing and Total Problems scales, with lower reliability for Externalizing. Language version of CBCL administration, education level and sex of the caregiver respondent showed the most significant impact on MI, followed by child age. Sensitivity analyses revealed that child race has a unique impact on DIF over and above socioeconomic status. Conclusions: The CBCL/1.5-5, a caregiver-report measure of early childhood behavior problems, showed bias across demographic groups. Robust item sets with less DIF can measure Internalizing and Total Problems equally as well as the full item sets, with slightly lower reliability for Externalizing, and can be crosswalked to the metric of the full item set, enabling calculation of normed T scores based on more robust item sets.

Scoping Review: Digital Mental Health Interventions for Children and Adolescents Affected by War.

OBJECTIVE: More than 200 million children and adolescents live in countries affected by violent conflict, are likely to have complex mental health needs, and struggle to access traditional mental health services. Digital mental health interventions have the potential to overcome some of the barriers in accessing mental health support. We performed a scoping review to map existing digital mental health interventions relevant for children and adolescents affected by war, to examine the strength of the evidence base, and to inform the development of future interventions. METHOD: Based on a pre-registered strategy, we systematically searched MEDLINE, Embase, Global Health, APA PsychInfo, and Google Scholar from the creation of each database to September 30, 2022, identifying k = 6,843 studies. Our systematic search was complemented by extensive consultation with experts from the GROW Network. RESULTS: The systematic search identified 6 relevant studies: 1 study evaluating digital mental health interventions for children and adolescents affected by war, and 5 studies for those affected by disasters. Experts identified 35 interventions of possible relevance. The interventions spanned from universal prevention to specialist-guided treatment. Most interventions directly targeted young people and parents or carers/caregivers and were self-guided. A quarter of the interventions were tested through randomized controlled trials. Because most interventions were not culturally or linguistically adapted to relevant contexts, their implementation potential was unclear. CONCLUSION: There is very limited evidence for the use of digital mental health interventions for children and adolescents affected by war at present. The review provides a framework to inform the development of new interventions. DIVERSITY & INCLUSION STATEMENT: We actively worked to promote sex and gender balance in our author group. STUDY PREREGISTRATION INFORMATION: Digital mental health interventions for children and young people affected by war: a scoping review; https://osf.io/; hrny9.

Neurodevelopmental profiles of 4-year-olds in the Navajo Birth Cohort Study.

Objective: Native American children disproportionally face many risk factors for poor developmental outcomes; these factors include poverty, environmental toxicant exposure, and limited medical, and intervention services. To understand these risks, comprehensive documentation of developmental and behavioral phenotypes are needed. In the current descriptive study, we assessed the neurodevelopment of young Diné (Navajo) children using standardized assessment instruments in combination with expert clinician judgment. Methods: As part of an ongoing, population-based, prospective birth cohort study, we conducted comprehensive neurodevelopmental assessments of 138, 3-5-year-old, Diné children residing on or near the Navajo Nation. We report results from standardized parent reports, psychiatric examinations, and direct assessments of children's language, cognitive, adaptive, and social-emotional development, as well as best estimate clinical diagnoses. Results: Forty-nine percent of our sample met DSM-5 criteria for a neurodevelopmental disorder (NDD) diagnosis. Language and speech sound disorders were most common, although autism spectrum disorder (ASD) was also elevated compared to the general population. Though language performance was depressed amongst all groups of children with, and without, NDDs, those meeting criteria for certain NDDs performed significantly lower on all language measures, when compared to those without. Social-emotional, behavioral, and nonverbal cognitive ability were in the average range overall. Conclusions: Diné children in our study were found to have a high percentage of clinically significant developmental delays. Overall, children presented with a pervasive pattern of depressed language performance across measures, irrespective of diagnosis (or no diagnosis), while other domains of functioning were similar to normative samples. Findings support the need to identify appropriate intervention and educational efforts for affected youth, while also exploring the causes of the specific developmental delays. However, longitudinal studies are necessary to establish best practices for identifying delays and delineating resilience factors to optimize development of Diné children.