Emotional Dysregulation in Emerging Adult ADHD: A Key Consideration in Explaining and Classifying Impairment and Co-Occurring Internalizing Problems.

Objective: The current study sought to clarify and harness the incremental validity of emotional dysregulation and unawareness (EDU) in emerging adulthood, beyond ADHD symptoms and with respect to concurrent classification of impairment and co-occurring problems, using machine learning techniques.

Method: Participants were 1,539 college students ( = 19.5, 69% female) with self-reported ADHD diagnoses from a multisite study who completed questionnaires assessing ADHD symptoms, EDU, and co-occurring problems.

Application and expansion of an algorithm predicting attention-deficit/hyperactivity disorder and impairment in a predominantly White sample.

Current assessment protocols for attention-deficit/hyperactivity disorder (ADHD) focus heavily on a set of highly overlapping symptoms, with well-validated factors like cognitive disengagement syndrome (CDS), executive function (EF), age, sex, and race and ethnicity generally being ignored. Using machine learning techniques, the current study aimed to validate recent findings proposing a subset of ADHD symptoms that, together, predict ADHD diagnosis, severity, and impairment level better than the full symptom list, while also testing whether the inclusion of the factors listed above could further increase accuracy. Parents of 1,922 children (50.

Impulsivity as key bridge symptoms in cross-sectional and longitudinal networks of ADHD and ODD.

Background: Impulsivity is viewed as key to attention-deficit/hyperactivity disorder (ADHD) and disruptive behavior disorders (DBD). Yet, to date, no work has provided an item-level analysis in longitudinal samples across the critical developmental period from childhood into adolescence, despite prior work suggesting items exhibit differential relevance with respect to various types of impairment. The current study conducted a novel longitudinal network analysis of ADHD and oppositional defiant disorder (ODD) symptoms between childhood and adolescence, with the important applied prediction of social skills in adolescence.

A Network Analysis of Executive Functions in Children and Adolescents With and Without Attention-Deficit/Hyperactivity Disorder.

This study applied network analysis to executive function test performances to examine differences in network parameters between demographically matched children and adolescents with and without attention-deficit/hyperactivity disorder (ADHD) (n = 141 per group; M = 12.7 ± 2.9 years-old; 72.

Aging and Pubertal Development Differentially Predict Symptoms of ADHD, Depression, and Impairment in Children and Adolescents: An Eight-Year Longitudinal Study.

Activational effects of the reproductive neuroendocrine system may explain why some youths with ADHD are at greater risk for exacerbated ADHD symptoms (hyperactivity, inattention, impulsivity) during adolescence. For youths diagnosed with ADHD, first signs of ADHD symptoms become noticeable by multiple reporters (e.g.

Data-Driven Methods for Predicting ADHD Diagnosis and Related Impairment: The Potential of a Machine Learning Approach.

Current diagnostic criteria for ADHD include several symptoms that highly overlap in conceptual meaning and interpretation. Additionally, inadequate sensitivity and specificity of current screening tools have hampered clinicians' ability to identify those at risk for related outcomes. Using machine learning techniques, the current study aimed to propose a novel algorithm incorporating key ADHD symptoms to predict concurrent and future (i.

Evidence-Based Assessment for Attention-Deficit/Hyperactivity Disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects individuals from all life stages, genders, and races/ethnicities. Accurate assessment of ADHD across different populations is essential as undiagnosed ADHD is associated with numerous costly negative public health outcomes and is complicated by high comorbidity and developmental change in symptoms over time. Predictive analysis suggests that best-practice evidence-based assessment of ADHD should include both ADHD-specific and broadband rating scales from multiple informants with consideration of IQ, academic achievement, and executive function when there are concerns about learning.

The unity and diversity of executive functions: A network approach to life span development.

As a novel approach to conceptualizing executive functions, this study applied network analysis to a common battery of executive function tests administered to a sample covering the life span. Participants (N = 3,944; age: M = 20.8 years, SD = 19.

Longitudinal network model of the co-development of temperament, executive functioning, and psychopathology symptoms in youth with and without ADHD.

Attention Deficit Hyperactivity Disorder (ADHD) is a common, chronic, and impairing disorder, yet presentations of ADHD and clinical course are highly heterogeneous. Despite substantial research efforts, both (a) the secondary co-occurrence of ADHD and complicating additional clinical problems and (b) the developmental pathways leading toward or away from recovery through adolescence remain poorly understood. Resolving these requires accounting for transactional influences of a large number of features across development.

Longitudinal Temperament Pathways to ADHD Between Childhood and Adolescence.

The current investigation extended prior cross-sectional mapping of etiological factors, transdiagnostic effortful and affective traits, and ADHD symptoms to longitudinal pathways extending from two etiological domains: polygenic and prenatal risk. Hypotheses were (1) genetic risk for ADHD would be related to inattentive ADHD symptoms in adolescence and mediated by childhood effortful control; (2) prenatal smoking would be related to hyperactive-impulsive ADHD symptoms during childhood and mediated by childhood surgency; and (3) there would be age-related variation, such that mediation of genetic risk would be larger for older than younger ages, whereas mediation of prenatal risk would be larger in earlier childhood than at later ages. Participants were 849 children drawn from the Oregon ADHD-1000 Cohort, which used a case control sample and an accelerated longitudinal design to track development from childhood (at year 1 ages 7-13) through adolescence (at year 6 ages 13-19).

Networks of ADHD and SCT Symptoms in Emerging Adulthood.

Objective: Emerging adulthood (18-25 years) is a transitional and understudied developmental period. Yet, little is known about how specific symptoms of ADHD, as well as those from the related SCT domain, may differentially relate to one another during this period, if there are differences based on biological sex, or how closely results will align with adulthood.

Methods: We used network analysis techniques to explore the structure of ADHD and SCT symptoms within emerging adulthood, with additional comparisons between sexes as well as between emerging adulthood and adulthood.

Utility of the Limited Prosocial Emotions Specifier in Preschoolers With Conduct Problems.

This study examined the clinical utility of the "Limited Prosocial Emotions" (LPE) specifier (i.e., prevalence rates, group differences, and predictive utility) in a high-risk preschool sample ( = 109, age = 4.

Clarifying Relations Between ADHD and Functional Impairment in Adulthood: Utilization of Network and Machine Learning Approaches.

Using network analysis and random forest regression, this study identified attention-deficit/hyperactivity disorder (ADHD) symptoms most important for indicating impairment in various functional domains. Participants comprised a nationally representative sample of 1249 adults in the United States. Bridge symptoms were identified as those demonstrating unique relations with impairment domains that, in total, were stronger than those involving other symptoms.

Longitudinal attention-deficit/hyperactivity disorder symptom networks in childhood and adolescence: Key symptoms, stability, and predictive validity.

The current study visualized attention-deficit/hyperactivity disorder (ADHD) symptom networks in a longitudinal sample of participants across childhood and adolescence with exploratory examination of age and gender effects. Eight hundred thirty-six children ages 7-13 years were followed annually for 8 years in total. Across parent and teacher report, results suggested "is easily distracted" and "difficulties sustaining attention" as central symptoms across three testing points (i.

Etiological Networks of Attention-Deficit/Hyperactivity Disorder during Childhood and Adolescence.

Objective: The purpose of the current study was to use network analysis techniques to parse relations between attention-deficit/hyperactivity disorder (ADHD) symptom domains, domains of executive function, and temperament traits.

Methods: Participants were 420 children aged 6-17 years (55% boys). The majority of the participants were Caucasian (72.

Identifying the Inter-Domain Relations Among ODD, CD, and CU Traits in Preschool Children Using Network Analysis.

Oppositional defiant disorder (ODD) and conduct disorder (CD) are two of the most common forms of disruptive behavior disorders during childhood. Callous-unemotional (CU) traits are an important factor in understanding the presentation of these externalizing forms of psychopathology. ODD, CD, and CU traits are highly related constructs, yet little work has examined how these externalizing forms of psychopathology are related at the domain level.

Multiple informant average integration of ADHD symptom ratings predictive of concurrent and longitudinal impairment.

To date, there remains no consensus about the best evidence-based method for integrating multiple informant data in the diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD). Several approaches exist, including the psychometrically sound approach of averaging scores, as well as the use of "OR" and "AND" algorithms, which are still commonly used in research. The current study tested these major integration methods in their concurrent and longitudinal prediction of clinician-rated impairment, teacher-rated academic, and parent- and self-rated social skill ratings in children overrecruited for ADHD across a 6-year span from childhood to adolescence.

Binaural Modelling and Spatial Auditory Cue Analysis of 3D-Printed Ears.

In this work, a binaural model resembling the human auditory system was built using a pair of three-dimensional (3D)-printed ears to localize a sound source in both vertical and horizontal directions. An analysis on the proposed model was firstly conducted to study the correlations between the spatial auditory cues and the 3D polar coordinate of the source. Apart from the estimation techniques via interaural and spectral cues, the property from the combined direct and reverberant energy decay curve is also introduced as part of the localization strategy.

Commentary: Extending longitudinal network approaches - a reflection on Funkhouser et al. (2020).

The network approach facilitates an exploration of direct and potentially causal relations among symptoms of psychological disorders, yet most prior research utilizing this approach has done so using cross-sectional data. This commentary highlights the importance of longitudinal network approaches, as depicted in the study conducted by Funkhouser et al. (Journal of Child Psychology and Psychiatry, 2020), and describes two possible key extensions of this approach: (a) accounting for risk markers, etiological mechanisms, and other nonsymptoms within longitudinal network models, and (b) continued exploration of longitudinal within-person networks with attention to personalized treatment applications.

Subgroups of Childhood ADHD Based on Temperament Traits and Cognition: Concurrent and Predictive Validity.

Efforts to parse ADHD's heterogeneity in the DSM system has generally relied on subtypes, or presentations, based on different symptom combinations. Promising recent work has suggested that biologically-relevant and clinically predictive subgroups may be identified via an alternative feature set based on either a) temperament traits or b) executive function measures. Yet, the potential additive ability of these domains for specifying ADHD sub-phenotypes remains unknown.

Conceptualizing the UPPS-P model of impulsive personality through network analysis: Key dimensions and general robustness across young adulthood.

Objective: Within the UPPS-P model of impulsive personality, negative urgency, positive urgency, lack of premeditation, lack of perseverance, and sensation seeking dimensions have been linked to unique etiological mechanisms and outcomes. Yet, additional research is needed exploring direct relations among dimensions to determine how these relations may contribute to the nature of impulsive personality and its correlates. The current study used network analysis to clarify relations among UPPS-P dimensions and assess global robustness of these relations across young adulthood.

Clarifying ADHD and Sluggish Cognitive Tempo Item Relations with Impairment: A Network Analysis.

Despite the pervasive nature of various forms of impairment associated with attention-deficit/hyperactivity disorder (ADHD), the precise nature of their associations with ADHD and related sluggish cognitive tempo (SCT), particularly at the heterogeneous item level, remains ambiguous. Using innovative network analysis techniques, we sought to identify and examine the concurrent validity of ADHD and SCT bridge items (i.e.

Conceptualizing Callous-Unemotional Traits in Preschool through Confirmatory Factor and Network Analysis.

Callous - unemotional (CU) traits are a key factor in understanding the persistence and severity of conduct problems. Most research has used confirmatory factor analysis (CFA) to examine the structure of CU traits; however, most CFA models have yielded marginally acceptable fit, and little research has examined the structure of CU traits in preschool. This gap highlights the need for a more nuanced approach in understanding the structure of CU traits during preschool via statistical examination of inter - item relationships (i.

Self-Adaptive Filtering Approach for Improved Indoor Localization of a Mobile Node with Zigbee-Based RSSI and Odometry.

This study presents a new technique to improve the indoor localization of a mobile node by utilizing a Zigbee-based received-signal-strength indicator (RSSI) and odometry. As both methods suffer from their own limitations, this work contributes to a novel methodological framework in which coordinates of the mobile node can more accurately be predicted by improving the path-loss propagation model and optimizing the weighting parameter for each localization technique via a convex search. A self-adaptive filtering approach is also proposed which autonomously optimizes the weighting parameter during the target node's translational and rotational motions, thus resulting in an efficient localization scheme with less computational effort.