Development and initial validation of self-report measures of general health, preoperative anxiety, and postoperative pain in young children using computer-administered animation.

BACKGROUND: For young children, existing measures of children's health-related quality of life must be parent-reported or interviewer-administered for those who cannot read or complete measures independently. Parents' and childrens' reports about the child's health have been shown to disagree. AIMS: (a) To test the reliability and validity of an animated, computer-administered Child Health Rating Inventories (CHRIS2.0) among children aged 4-12 undergoing surgery; and (b) to develop and test two CHRIS measures of preoperative anxiety and postoperative pain management. METHODS: We conducted a longitudinal cohort study of a diverse group of 542 children aged 4-12 undergoing surgery. We compared the CHRIS measures to Pediatric Quality of Life Inventory (PedsQL), the Functional Disabilities Inventory (FDI), State-Trait Anxiety Inventory for children (STAI-CH), and the Parent Postoperative Pain Measure (PPPM). RESULTS: Factor analyses supported the construct validity of the 12-item general physical health and the 8-item mental health CHRIS scales, as well as a composite 20-item scale, and the CHRIS preoperative anxiety and postoperative pain scales. Internal consistency reliability for all CHRIS scales exceeded the standard for group comparisons (Cronbach's α ≥0.70). The CHRIS general health composite was significantly correlated with composite PedsQL and FDI (r = 0.28, P < .001 and r = 0.43, P < .001, respectively). The CHRIS peri-operative anxiety measure was significantly correlated with the STAI-CH (r = 0.44, P < .001), as was the CHRIS postoperative pain scale with the PPPM (r = 0.52, P < .001). CONCLUSIONS: The CHRIS measures were reliable and valid in this diverse sample of young children (4-12). Because CHRIS measures are self-administered, scored in real time, and run on multiple different platforms, this approach provides a feasible method for the collection of health-related quality of life in young children and those with limited literacy. Our data indicate that this approach is psychometrically sound and has the potential for adding the child's voice to pediatric outcomes.

Unpredictable maternal behavior is associated with a blunted infant cortisol response.

BACKGROUND: Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is associated with poor physical and mental health. Early-life adversity may dysregulate cortisol response to subsequent stress. This study examines the association between patterns of maternal behavior and infant stress response to a challenge. Specifically, we test whether infant exposure to unpredictable maternal sensory signals is related to the cortisol response to a painful stressor. METHOD: Participants were 102 mothers and their children enrolled in a longitudinal study. Patterns of maternal sensory signals were evaluated at 6 and 12 months during a 10-min mother-infant play episode. Entropy rate was calculated as a quantitative measure of the degree of unpredictability of maternal sensory signals (visual, auditory, and tactile) exhibited during the play episode. Infant saliva samples were collected for cortisol analysis before and after inoculation at 12 months. RESULTS: Unpredictable patterns of maternal sensory signals were associated with a blunted infant cortisol response to a painful stressor. This relation persisted after evaluation of covariates including maternal sensitivity and maternal psychological distress. CONCLUSIONS: This study provides evidence that unpredictable patterns of maternal sensory signals are one process through which caregiving affects the function of infant stress response systems.

Why Temporal Persistence of Biometric Features, as Assessed by the Intraclass Correlation Coefficient, Is So Valuable for Classification Performance.

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer this question. In a recent report, we introduced the intraclass correlation coefficient (ICC) as an index of temporal persistence for such features. Here, we present a novel approach using synthetic features to study which aspects of a biometric identification study are influenced by the temporal persistence of features. What we show is that using more temporally persistent features produces effects on the similarity score distributions that explain why this quality is so key to biometric performance. The results identified with the synthetic data are largely reinforced by an analysis of two datasets, one based on eye-movements and one based on gait. There was one difference between the synthetic and real data, related to the intercorrelation of features in real data. Removing these intercorrelations for real datasets with a decorrelation step produced results which were very similar to that obtained with synthetic features.

The Function Biomedical Informatics Research Network Data Repository.

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

A Test by Any Other Name: P Values, Bayes Factors, and Statistical Inference.

Procedures used for statistical inference are receiving increased scrutiny as the scientific community studies the factors associated with insuring reproducible research. This note addresses recent negative attention directed at p values, the relationship of confidence intervals and tests, and the role of Bayesian inference and Bayes factors, with an eye toward better understanding these different strategies for statistical inference. We argue that researchers and data analysts too often resort to binary decisions (e.g., whether to reject or accept the null hypothesis) in settings where this may not be required.

Reliability of ordinal outcomes in forensic black-box studies.

Forensic science disciplines such as latent print examination, bullet and cartridge case comparisons, and shoeprint analysis, involve subjective decisions by forensic experts throughout the examination process. Most of the decisions involve ordinal categories. Examples include a three-category outcome for latent print comparisons (exclusion, inconclusive, identification) and a seven-category outcome for footwear comparisons (exclusion, indications of non-association, inconclusive, limited association of class characteristics, association of class characteristics, high degree of association, identification). As the results of the forensic examinations of evidence can heavily influence the outcomes of court proceedings, it is important to assess the reliability and accuracy of the underlying decisions. "Black box" studies are the most common approach for assessing the reliability and accuracy of subjective decisions. In these studies, researchers produce evidence samples consisting of a sample of questioned source and a sample of known source where the ground truth (same source or different source) is known. Examiners provide assessments for selected samples using the same approach they would use in actual casework. These studies often have two phases; the first phase comprises of decisions on samples of varying complexities by different examiners, and the second phase involves repeated decisions by the same examiner on a (usually) small subset of samples that were encountered by examiners in the first phase. We provide a statistical method to analyze ordinal decisions from black-box trials with the objective of obtaining inferences for the reliability of these decisions and quantifying the variation in decisions attributable to the examiners, the samples, and statistical interaction effects between examiners and samples. We present simulation studies to judge the performance of the model on data with known parameter values and apply the model to data from a handwritten signature complexity study, a latent fingerprint examination black-box study, and a handwriting comparisons black-box study.

Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome.

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges. Hoping to mitigate these challenges we examined the relation of several ELA dimensions to DNA methylation changes and outcome using a within-subject longitudinal design and a high methylation-change threshold. DNA methylation was analyzed in buccal swab/saliva samples collected twice (neonatally and at 12 months) in 110 infants. We identified CpGs differentially methylated across time for each child and determined whether they associated with ELA indicators and executive function at age 5. We assessed sex differences and derived a sex-dependent 'impact score' based on sites that most contributed to methylation changes. Changes in methylation between two samples of an individual child reflected age-related trends and correlated with executive function years later. Among tested ELA dimensions and life factors including income to needs ratios, maternal sensitivity, body mass index and infant sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, high early-life unpredictability interacted with methylation changes to presage executive function. Thus, longitudinal, within-subject changes in methylation profiles may provide a signature of ELA and a potential predictive marker of individual outcome.

Infant hedonic/anhedonic processing index (HAPI-Infant): Assessing infant anhedonia and its prospective association with adolescent depressive symptoms.

BACKGROUND: Anhedonia, an impairment in the motivation for or experience of pleasure, is a well-established transdiagnostic harbinger and core symptom of mental illness. Given increasing recognition of early life origins of mental illness, we posit that anhedonia should, and could, be recognized earlier if appropriate tools were available. However, reliable diagnostic instruments prior to childhood do not currently exist. METHODS: We developed an assessment instrument for anhedonia/reward processing in infancy, the Infant Hedonic/Anhedonic Processing Index (HAPI-Infant). Exploratory factor and psychometric analyses were conducted using data from 6- and 12-month-old infants from two cohorts (N = 188, N = 212). Then, associations were assessed between infant anhedonia and adolescent self-report of depressive symptoms. RESULTS: The HAPI-Infant (47-items), exhibited excellent psychometric properties. Higher anhedonia scores at 6 (r = 0.23, p < .01) and 12 months (r = 0.19, p < .05) predicted elevated adolescent depressive symptoms, and these associations were stronger than for established infant risk indicators such as negative affectivity. Subsequent analyses supported the validity of short (27-item) and very short (12-item) versions of this measure. LIMITATIONS: The primary limitations of this study are that the HAPI-Infant awaits additional tests of generalizability and of its ability to predict clinical diagnosis of depression. CONCLUSIONS: The HAPI-Infant is a novel, psychometrically strong diagnostic tool suitable for recognizing anhedonia during the first year of life with strong predictive value for later depressive symptoms. In view of the emerging recognition of increasing prevalence of affective disorders in children and adolescents, the importance of the HAPI-Infant in diagnosing anhedonia is encouraging. Early recognition of anhedonia could target high-risk individuals for intervention and perhaps prevention of mental health disorders.

Across ages and places: Unpredictability of maternal sensory signals and child internalizing behaviors.

BACKGROUND: Patterns of sensory inputs early in life play an integral role in shaping the maturation of neural circuits, including those implicated in emotion and cognition. In both experimental animal models and observational human research, unpredictable sensory signals have been linked to aberrant developmental outcomes, including poor memory and effortful control. These findings suggest that sensitivity to unpredictable sensory signals is conserved across species and sculpts the developing brain. The current study provides a novel investigation of unpredictable maternal sensory signals in early life and child internalizing behaviors. We tested these associations in three independent cohorts to probe the generalizability of associations across continents and cultures. METHOD: The three prospective longitudinal cohorts were based in Orange, USA (n = 163, 47.2 % female, Mage = 1 year); Turku, Finland (n = 239, 44.8 % female, Mage = 5 years); and Irvine, USA (n = 129, 43.4 % female, Mage = 9.6 years). Unpredictability of maternal sensory signals was quantified during free-play interactions. Child internalizing behaviors were measured via parent report (Orange & Turku) and child self-report (Irvine). RESULTS: Early life exposure to unpredictable maternal sensory signals was associated with greater child fearfulness/anxiety in all three cohorts, above and beyond maternal sensitivity and sociodemographic factors. The association between unpredictable maternal sensory signals and child sadness/depression was relatively weaker and did not reach traditional thresholds for statistical significance. LIMITATIONS: The correlational design limits our ability to make causal inferences. CONCLUSIONS: Findings across the three diverse cohorts suggest that unpredictable maternal signals early in life shape the development of internalizing behaviors, particularly fearfulness and anxiety.

Sex-Specific Effects of Early Life Unpredictability on Hippocampal and Amygdala Responses to Novelty in Adolescents.

Background: Unpredictable childhood experiences are an understudied form of early life adversity that impacts neurodevelopment in a sex-specific manner. The neurobiological processes by which exposure to early-life unpredictability impacts development and vulnerability to psychopathology remain poorly understood. The present study investigates the sex-specific consequences of early-life unpredictability on the limbic network, focusing on the hippocampus and the amygdala. Methods: Participants included 150 youth (54% female). Early life unpredictability was assessed using the Questionnaire of Unpredictability in Childhood (QUIC). Participants engaged in a task-fMRI scan between the ages of 8 and 17 (223 total observations) measuring BOLD responses to novel and familiar scenes. Results: Exposure to early-life unpredictability associated with BOLD contrast (novel vs. familiar) in a sex-specific manner. For males, but not females, higher QUIC scores were associated with lower BOLD activation in response to novel vs. familiar stimuli in the hippocampal head and amygdala. Secondary psychophysiological interaction (PPI) analyses revealed complementary sex-specific associations between QUIC and condition-specific functional connectivity between the right and left amygdala, as well as between the right amygdala and hippocampus bilaterally. Conclusion: Exposure to unpredictability in early life has persistent implications for the functional operations of limbic circuits. Importantly, consistent with emerging experimental animal and human studies, the consequences of early life unpredictability differ for males and females. Further, impacts of early-life unpredictability were independent of other risk factors including lower household income and negative life events, indicating distinct consequences of early-life unpredictability over and above more commonly studied types of early life adversity.

Experiences of COVID-19-Related Racism and Impact on Depression Trajectories Among Racially/Ethnically Minoritized Adolescents.

PURPOSE: In 2020, racially/ethnically minoritized (REMD) youth faced the "dual pandemics" of COVID-19 and racism, both significant stressors with potential for adverse mental health effects. The current study tested whether short- and long-term trajectories of depressive symptoms from before to during the COVID-19 pandemic differed between REMD adolescents who did and did not endorse exposure to COVID-19-era-related racism (i.e., racism stemming from conditions created or exacerbated by the COVID-19 pandemic). METHODS: A community sample of 100 REMD adolescents enrolled in an ongoing longitudinal study of mental health was assessed before and during the COVID-19 pandemic. Participants were 51% girls, mean age = 16, standard deviation = 2.7, and identified as Latinx/Hispanic (48%), Multiethnic (34%), Asian American (12%), and Black (6%). RESULTS: REMD adolescents' depressive symptoms were elevated during the COVID-19 pandemic compared to pre-pandemic levels, and increases were more pronounced over time for those who endorsed exposure to COVID-19-era-related racism. In general, Asian American participants endorsed racism experiences at the highest rates compared to others, including being called names (42%), people acting suspicious around them (33%), and being verbally threatened (17%). Additionally, more than half of Black and Asian American participants reported worry about experiencing racism related to the COVID-19 pandemic, even if they had not experienced it to date. DISCUSSION: REMD adolescents are at increased risk for depressive symptoms related to converging stressors stemming from the COVID-19 pandemic and pandemic-related racism, which has the potential to widen racial/ethnic mental health disparities faced by the REMD youth.

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome.

Background: Adverse early-life experiences (ELA), including poverty, trauma and neglect, affect a majority of the world's children. Whereas the impact of ELA on cognitive and emotional health throughout the lifespan is well-established, it is not clear how distinct types of ELA influence child development, and there are no tools to predict for an individual child their vulnerability or resilience to the consequences of ELAs. Epigenetic markers including DNA-methylation profiles of peripheral cells may encode ELA and provide a predictive outcome marker. However, the rapid dynamic changes in DNA methylation in childhood and the inter-individual variance of the human genome pose barriers to identifying profiles predicting outcomes of ELA exposure. Here, we examined the relation of several dimensions of ELA to changes of DNA methylation, using a longitudinal within-subject design and a high threshold for methylation changes in the hope of mitigating the above challenges. Methods: We analyzed DNA methylation in buccal swab samples collected twice for each of 110 infants: neonatally and at 12 months. We identified CpGs differentially methylated across time, calculated methylation changes for each child, and determined whether several indicators of ELA associated with changes of DNA methylation for individual infants. We then correlated select dimensions of ELA with methylation changes as well as with measures of executive function at age 5 years. We examined for sex differences, and derived a sex-dependent 'impact score' based on sites that most contributed to the methylation changes. Findings: Setting a high threshold for methylation changes, we discovered that changes in methylation between two samples of an individual child reflected age-related trends towards augmented methylation, and also correlated with executive function years later. Among the tested factors and ELA dimensions, including income to needs ratios, maternal sensitivity, body mass index and sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, an interaction was observed between a measure of high early-life unpredictability and methylation changes, in presaging executive function. Interpretation: These findings establish longitudinal, within-subject changes in methylation profiles as a signature of some types of ELA in an individual child. Notably, such changes are detectable beyond the age-associated DNA methylation dynamics. Future studies are required to determine if the methylation profile changes identified here provide a predictive marker of vulnerabilities to poorer cognitive and emotional outcomes.

Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies.

This report provides practical recommendations for the design and execution of multicenter functional MRI (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The study was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multisite aspects include: (i) establishing and verifying scan parameters including scanner types and magnetic fields, (ii) establishing and monitoring of a scanner quality program, (iii) developing task paradigms and scan session documentation, (iv) establishing clinical and scanner training to ensure consistency over time, (v) developing means for uploading, storing, and monitoring of imaging and other data, (vi) the use of a traveling fMRI expert, and (vii) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery.

Genetic variations in the dopamine system and facial expression recognition in healthy chinese college students.

OBJECTIVE: This study investigated the relation between genetic variations in the dopamine system and facial expression recognition. METHODS: A sample of Chinese college students (n = 478) was given a facial expression recognition task. Subjects were genotyped for 98 loci [96 single-nucleotide polymorphisms (SNPs) and 2 variable number tandem repeats] in 16 genes involved in the dopamine neurotransmitter system, including its 4 subsystems: synthesis (TH, DDC, and DBH), degradation/transport (COMT,MAOA,MAOB, and SLC6A3), receptors (DRD1,DRD2,DRD3,DRD4, and DRD5), and modulation (NTS,NTSR1,NTSR2, and NLN). To quantify the total contributions of the dopamine system to emotion recognition, we used a series of multiple regression models. Permutation analyses were performed to assess the posterior probabilities of obtaining such results. RESULTS: Among the 78 loci that were included in the final analyses (after excluding 12 SNPs that were in high linkage disequilibrium and 8 that were not in Hardy-Weinberg equilibrium), 1 (for fear), 3 (for sadness), 5 (for anger), 13 (for surprise), and 15 (for disgust) loci exhibited main effects on the recognition of facial expressions. Genetic variations in the dopamine system accounted for 3% for fear, 6% for sadness, 7% for anger, 10% for surprise, and 18% for disgust, with the latter surviving a stringent permutation test. CONCLUSIONS: Genetic variations in the dopamine system (especially the dopamine synthesis and modulation subsystems) made significant contributions to individual differences in the recognition of disgust faces.

Towards a likelihood ratio approach for bloodstain pattern analysis.

In this work, we explore the application of likelihood ratio as a forensic evidence assessment tool to evaluate the causal mechanism of a bloodstain pattern. It is assumed that there are two competing hypotheses regarding the cause of a bloodstain pattern. The bloodstain patterns are represented as a collection of ellipses with each ellipse characterized by its location, size and orientation. Quantitative measures and features are derived to summarize key aspects of the patterns. A bivariate Gaussian model is chosen to estimate the distribution of features under a given hypothesis and thus approximate the likelihood of a pattern. Published data with 59 impact patterns and 55 gunshot patterns is used to train and evaluate the model. Results demonstrate the feasibility of the likelihood ratio approach for bloodstain pattern analysis. The results also hint at some of the challenges that need to be addressed for future use of the likelihood ratio approach for bloodstain pattern analysis.

A cross-species assay demonstrates that reward responsiveness is enduringly impacted by adverse, unpredictable early-life experiences.

Exposure to early-life adversity (ELA) is associated with several neuropsychiatric conditions, including major depressive disorder, yet causality is difficult to establish in humans. Recent work in rodents has implicated impaired reward circuit signaling in anhedonic-like behavior after ELA exposure. Anhedonia, the lack of reactivity to previously rewarding stimuli, is a transdiagnostic construct common to mental illnesses associated with ELA. Here, we employed an assay of reward responsiveness validated across species, the Probabilistic Reward Task (PRT). In the PRT, healthy participants reliably develop a response bias toward the more richly rewarded stimulus, whereas participants with anhedonia exhibit a blunted response bias that correlates with current and future anhedonia. In a well-established model of ELA that generates a stressful, chaotic, and unpredictable early-life environment, ELA led to blunted response biases in the PRT in two separate cohorts, recapitulating findings in humans with anhedonia. The same ELA rats had blunted sucrose preference, further supporting their anhedonic-like phenotypes. Probing the aspects of ELA that might provoke these deficits, we quantified the unpredictability of dam/pup interactions using entropy measures and found that the unpredictability of maternal care was significantly higher in the ELA groups in which PRT and sucrose preference reward deficits were present later in life. Taken together, these data position the PRT, established in clinical patient populations, as a potent instrument to assess the impact of ELA on the reward circuit across species. These findings also implicate the unpredictability of maternal signals during early life as an important driver of reward sensitivity deficits.

Exposure to unpredictability and mental health: Validation of the brief version of the Questionnaire of Unpredictability in Childhood (QUIC-5) in English and Spanish.

Unpredictability is increasingly recognized as a primary dimension of early life adversity affecting lifespan mental health trajectories; screening for these experiences is therefore vital. The Questionnaire of Unpredictability in Childhood (QUIC) is a 38-item tool that measures unpredictability in childhood in social, emotional and physical domains. The available evidence indicates that exposure to unpredictable experiences measured with the QUIC predicts internalizing symptoms including depression and anxiety. The purpose of the present study was to validate English and Spanish brief versions (QUIC-5) suitable for administration in time-limited settings (e.g., clinical care settings, large-scale epidemiological studies). Five representative items were identified from the QUIC and their psychometric properties examined. The predictive validity of the QUIC-5 was then compared to the QUIC by examining mental health in four cohorts: (1) English-speaking adult women assessed at 6-months postpartum (N = 116), (2) English-speaking male veterans (N = 95), (3) English-speaking male and female adolescents (N = 155), and (4) Spanish-speaking male and female adults (N = 285). The QUIC-5 demonstrated substantial variance in distributions in each of the cohorts and is correlated on average 0.84 (r's = 0.81-0.87) with the full 38-item version. Furthermore, the QUIC-5 predicted internalizing symptoms (anxiety and depression) in all cohorts with similar effect sizes (r's = 0.16-0.39; all p's < 0.05) to the full versions (r's = 0.19-0.42; all p's < 0.05). In sum, the QUIC-5 exhibits good psychometric properties and is a valid alternative to the full QUIC. These findings support the future use of the QUIC-5 in clinical and research settings as a concise way to measure unpredictability, identify risk of psychopathology, and intervene accordingly.

Early life exposure to unpredictable parental sensory signals shapes cognitive development across three species.

Exposure to early life adversity has long term consequences on cognitive function. Most research has focused on understanding components of early life adversities that contribute to later risk, including poverty, trauma, maltreatment, and neglect. Whereas these factors, in the aggregate, explain a significant proportion of emotional and cognitive problems, there are serious gaps in our ability to identify potential mechanisms by which early life adversities might promote vulnerability or resilience. Here we discuss early life exposure to unpredictable signals from the caretaker as an understudied type of adversity that is amenable to prevention and intervention. We employ a translational approach to discover underlying neurobiological mechanisms by which early life exposure to unpredictable signals sculpts the developing brain. First, we review evidence that exposure to unpredictable signals from the parent during sensitive periods impacts development of neural circuits. Second, we describe a method for characterizing early life patterns of sensory signals across species. Third, we present published and original data illustrating that patterns of maternal care predict memory function in humans, non-human primates, and rodents. Finally, implications are discussed for identifying individuals at risk so that early preventive-intervention can be provided.

Prenatal maternal mood entropy is associated with child neurodevelopment.

Emerging evidence indicates that the predictability of signals early in life may influence the developing brain. This study examines links between a novel indicator of maternal mood dysregulation, mood entropy, and child neurodevelopmental outcomes. Associations between prenatal maternal mood entropy and child neurodevelopment were assessed in 2 longitudinal cohorts. Maternal mood was measured several times over pregnancy beginning as early as 15 weeks' gestation. Shannon's mood entropy was applied to distributions of mothers' responses on mood questionnaires. Child cognitive and language development were evaluated at 2 and 6-9 years of age. Higher prenatal maternal mood entropy was associated with lower cognitive development scores at 2 years of age and lower expressive language scores at 6-9 years of age. These associations persisted after adjusting for maternal pre and postnatal mood levels and for other relevant sociodemographic factors. Our findings identify maternal mood entropy as a novel predictor of child neurodevelopment. Characterizing components of maternal mood in addition to level of severity or valence may further our understanding of specific processes by which maternal mood shapes child development. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Optimally Balanced Gaussian Process Propensity Scores for Estimating Treatment Effects.

Propensity scores are commonly employed in observational study settings where the goal is to estimate average treatment effects. This paper introduces a flexible propensity score modeling approach, where the probability of treatment is modeled through a Gaussian process framework. To evaluate the effectiveness of the estimated propensity score, a metric of covariate imbalance is developed that quantifies the discrepancy between the distributions of covariates in the treated and control groups. It is demonstrated that this metric is ultimately a function of the hyperparameters of the covariance matrix of the Gaussian process and therefore it is possible to select the hyperparameters to optimize the metric and minimize overall covariate imbalance. The effectiveness of the GP method is compared in a simulation against other methods of estimating the propensity score and the method is applied to data from Dehejia and Wahba (1999) to demonstrate benchmark performance within a relevant policy application.