Cognitive Factors Research Articles

Depression severity and verbal comprehension in children and adolescents with a major depressive episode.

Severe depression is a prevalent psychiatric illness in children and adolescents associated with high levels of morbidity, disability, and a high risk of suicidal behavior. Cognitive factors associated with depression severity in juveniles have been poorly reported. We investigated the relationship between depression severity and intelligence quotient (IQ)with its subscales in 65 juveniles (aged 10-17 years) with a current major depressive episode evaluated at the Mood Disorder Program of Bambino Gesù Children's Hospital in Rome. Pearson's correlation analyses were followed by a Benjamini-Hochberg correction and linear multivariable regression model. Depression severity measured with the total score of the Children's Depression Rating Scale-Revised (CDRS-R) was positively associated with the Verbal Comprehension Index (VCI; Pearson's r = 0.309 [0.042-0.534]; p = 0.024). The CDRS-R subscales positively associated with VCI by Pearson's correlation were depressed feelings, suicidal ideation, excessive weeping, and reduced facial expressions. Suicidal ideation was the only factor independently and significantly associated with higher VCI in the multivariable linear regression model. Suicidal ideation was significantly and independently associated with higher verbal comprehension, indicating that depressed juveniles with better verbal ability may be at a greater risk of showing suicidal ideation.

Drinking motives and alcohol sensitivity mediate multi-dimensional genetic influences on alcohol use behaviors.

Genetic influences account for a substantial proportion of individual differences in alcohol use behaviors (AUBs). However, multiple distinct sets of genes are linked to different AUBs, which may explain their dramatic variability in risk factors and manifestations. In this study, we explore whether intermediate neurobiological traits and alcohol-related cognitions mediate the relationship between polygenic scores (PGS) and multiple AUBs, with the aim to better understand processes captured by different genetic profiles. Using results from prior genome-wide association studies, we derived PGS for 6 AUBs in participants from Spit for Science, a longitudinal study of college students in the U.S. (n=4,549). Self-report measures included personality traits, alcohol expectancies, drinking motivations, and alcohol sensitivity measures as well as drinking frequency, drinking quantity, alcohol use disorder (AUD) symptoms, and maximum drinks in 24 hours. Using linear regression and multiple mediation models, we investigated the direct and indirect effects of PGS on AUBs. In univariable regression results, PGSs indexing broad AUB dimensions such as drinks per week (DPW) and AUD predicted higher levels of sensation-seeking and multiple drinking motives, while BeerPref PGSs (indexing a variable pattern of alcohol problems associated with a preference for beer) predicted higher negative urgency and lower alcohol sensitivity. Mediational models indicated strong direct and indirect effects of DPW PGSs on multiple AUBs via social/enhancement drinking motives and alcohol sensitivity, indirect effects of AUD PGSs on AUD symptoms via coping motives, and indirect effects of BeerPref PGS on all AUBs via the joint effect of mediators including alcohol sensitivity. These findings provide initial evidence that the genetic influences on different AUBs are associated with and partially mediated by intermediate neurobiological and cognitive factors, which may be more amenable to intervention. Greater focus on drinking motives and alcohol sensitivity is warranted in genetic research, as well as attention to the heterogeneous pathways linking genes to alcohol use outcomes.

‘Flashforward’ mental imagery in adolescents: exploring developmental differences and associations with mental health

Abstract Background: Future events can spring to mind unbidden in the form of involuntary mental images also known as ‘flashforwards’, which are deemed important for understanding and treating emotional distress. However, there has been little exploration of this form of imagery in youth, and even less so in those with high psychopathology vulnerabilities (e.g. due to developmental differences associated with neurodiversity or maltreatment). Aims: We aimed to test whether flashforwards are heightened (e.g. more frequent and emotional) in autistic and maltreatment-exposed adolescents relative to typically developing adolescents. We also explored their associations with anxiety/depression symptoms. Method: A survey including measures of flashforward imagery and mental health was completed by a group of adolescents (n=87) aged 10–16 (and one of their caregivers) who met one of the following criteria: (i) had a diagnosis of autism spectrum disorder; (ii) a history of maltreatment; or (ii) no autism/maltreatment. Results: Flashforwards (i) were often of positive events and related to career, education and/or learning; with phenomenological properties (e.g. frequency and emotionality) that were (ii) not significantly different between groups; but nevertheless (iii) associated with symptoms of anxiety across groups (particularly for imagery emotionality), even after accounting for general trait (non-future) imagery vividness. Conclusions: As a modifiable cognitive risk factor, flashforward imagery warrants further consideration for understanding and improving mental health in young people. This implication may extend to range of developmental backgrounds, including autism and maltreatment.

Understanding and Treating Nightmares: A Comprehensive Review of Psychosocial Strategies for Adults and Children.

Nightmares are distressing dreams that evoke strong negative emotions, such as fear or anxiety, often leading to waking from sleep and subsequent sleep disruption. They are prevalent across various age groups, with significant psychological and physiological health implications. This review explores the nature of nightmares, distinguishing them from other sleep disturbances like night terrors and sleep paralysis. It examines the prevalence of nightmares in children and adults, highlighting their impact on mental health and daily functioning. The review also emphasizes the importance of addressing nightmares through effective treatment strategies. While pharmacological options are available, psychosocial interventions offer promising non-pharmacological solutions. Cognitive behavioral therapy (CBT), imagery rehearsal therapy (IRT), and mindfulness-based therapies are discussed as key approaches for managing nightmares. These strategies focus on altering maladaptive thought patterns and emotional responses, reducing nightmares' frequency and intensity, and improving overall sleep quality. Psychosocial interventions provide a comprehensive approach to treating nightmares by addressing the underlying cognitive and emotional factors, benefitting individuals across different age groups. This review aims to highlight the efficacy of these strategies and their role in enhancing the quality of life for those affected by persistent nightmares.

Towards a taxonomy of team workflow structures

AbstractTeam workflow represents interactions between individuals and specific actions or tasks. Individuals’ interactions have important effects on fellow teammates’ actions by expanding or constraining actions available to them. For example, teammates may avoid performing the same action to avoid duplication of effort or they may perform their actions sequentially if one task’s completion is a prerequisite for another task. Complex dependencies embedded in these interactions suggest the need to understand team workflows from a relational perspective. As workflow structures are shaped by elements of organizational design, cognitive factors, and features of the task environment, no single workflow structure is optimal for all teams, and team workflows may manifest in countless distinct configurations. Through a systematic, network-based representation of team workflows, this paper uses a sample of 139,500 teams on GitHub to identify common patterns of team workflows. Each team is represented as a two-mode network where individuals form ties to up to fifteen distinct actions capturing productivity, discussion, and team management. Several node-level and graph-level centrality indices highlight patterns of differentiation across team workflows, and a k-means clustering algorithm detects three distinct clusters of team workflow structures: small teams of highly active generalists, small teams with a moderately active mix of focused and generalist members, and large, segmented teams of focused individuals collectively engaging in a few extremely popular actions. These results demonstrate how a structural representation of team workflows provides unique insight into team behavior and highlights distinctions that may otherwise be lost when examining team activity in aggregate.

Increased reliance on heuristic thinking in mild cognitive impairment

ABSTRACT Reasoning can be fast, automatic, and intuitive or slow, deliberate, and analytical. Use of one cognitive reasoning style over the other has broad implications for beliefs, but differences in cognitive style have not previously been reported in those with mild cognitive impairment (MCI). Here, the cognitive reflection test is used to measure cognitive style in healthy older adults and those with MCI. Those with MCI performed worse than cognitively healthy older adults, indicating they are more likely to engage in intuitive thinking than age-matched adults. This association is reliable after controlling for additional cognitive, self-report, and demographic factors. Across all measures, subjective cognitive decline was the best predictor of cognitive status. A difference in cognitive style represents a novel behavioral marker of MCI, and future work should explore whether this explains a broader pattern of reasoning errors in those with MCI, such as susceptibility to scams or impaired financial reasoning.

A spectrum of altered non-rapid eye movement sleep in schizophrenia.

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations, are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, ageing, cognitive profiles and medication regimens. Using newly collected high-density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported group-level differences between patients and controls (original N=130) during N2 stage. Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability. We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (AUC=0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics. Although multiple clinical and cognitive factors were associated with NREM metrics, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater contributor to variability. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on the sleep EEG; further, among patients, certain medications exacerbated these effects, in particular olanzapine. Collectively, our results point to a spectrum of N2 sleep deficits among SCZ patients that can be measured objectively and at scale, with relevance to both the etiological heterogeneity of SCZ as well as potential iatrogenic effects of antipsychotic medication.

Cognitive defusion as a mediator in the autobiographical memory and metacognitive awareness pathway to problem-solving in borderline personality disorder

BackgroundProblem-solving ability is influenced by numerous cognitive factors. However, a significant research gap exists regarding the mediating role of cognitive defusion in the relationship between autobiographical memory (AM) and metacognitive awareness with problem-solving. Given the critical role of problem-solving, this study aimed to model the relationship between AM and metacognitive awareness with problem-solving, considering the mediating role of cognitive defusion in individuals with borderline personality disorder (BPD). MethodThe study population comprised all individuals with BPD referred to counseling centers and psychiatric clinics in Kurdistan province. A sample of 300 individuals diagnosed with BPD according to the DSM-V and willing to participate was selected. All data were collected using self-report questionnaires. ResultsPath analysis results indicated that AM and metacognitive awareness had a significant positive direct effect on both problem-solving and cognitive defusion. Additionally, cognitive defusion significantly mediated the relationships between AM and metacognitive awareness with problem-solving. ConclusionsThese findings provide evidence for the significant roles of AM and metacognitive awareness in problem-solving, with cognitive defusion acting as a crucial mediating factor in individuals with BPD. these results offer valuable insights for both theoretical understanding and clinical interventions, which could enhance problem-solving skills in individuals with BPD by strengthening cognitive defusion.

Exploring mathematical wellbeing across cultures: insights from diverse students

AbstractAcross many countries, including New Zealand, diverse groups including indigenous, migrant, and marginalised communities, are under-represented in mathematics, as evidenced by achievement disparities and disengagement from higher-level mathematics. Both research and policy have focused on developing equitable education outcomes for all students. A key aspect of this is wellbeing, including within mathematics classrooms, which includes identifying classroom environments that enable wellbeing. This study examines mathematical wellbeing (MWB) across different ethnicities and genders, with a case study focus on students from Pacific heritages. Analysing qualitative responses from over 12,000 diverse students revealed that positive relationships in the mathematics classroom were most commonly associated with students’ MWB. Accomplishment and cognitive factors, including mathematical accuracy, learning new things, and understanding, were also identified as important. Minor gender differences emerged, with female students emphasising mathematical understanding, accuracy, and relationships more than male students. The Pacific student case study highlighted the importance of both cognitive aspects (learning new things and understanding) and relationships (peer and teacher support), uncovering an alignment between cultural values and MWB. This study empirically confirms seven universal values supporting student MWB, previously identified in Australian and Chinese contexts, suggesting that teachers internationally may align pedagogical practices with these values to support most students’ MWB. However, the instrumental values serving these universal values appear culturally unique. This research contributes novel insights to the field by examining wellbeing with a subject-specific focus through student-generated responses, offering implications for developing more equitable and culturally inclusive mathematics classrooms.

Exploring attitudes and behavioral patterns in residential energy consumption: Data-driven by a machine learning approach

The present study focuses on two main objectives: firstly, to clarify the mechanisms by which attitudes impact behavioral changes related to household energy consumption, and secondly, to offer valuable insights to enhance the understanding of residential energy usage through a novel technique called Support Vector Regression (SVR). This method employs several feature space transformations to convert nNar relationships into linear ones. The results highlight the crucial role of psychological factors in determining energy consumption behaviors, demonstrating that cognitive factors significantly influence attitudes and behavioral patterns. The findings show that psychological variables have a major role in determining how people consume energy, with cognitive variables having a particularly large impact on attitudes and behavior patterns. Our findings demonstrate the superior performance of Support Vector Regression (SVR) with radial basis function kernels over traditional predictive models, with a prediction accuracy of 93.7 % for changes in behavior patterns (CHP) and 94.4 % for changes in attitudes (CHA). These results highlight the value of applying cutting-edge machine-learning approaches to create precise models for comprehending and directing energy-saving actions. The policy implications suggest that reducing cognitive barriers can significantly encourage energy-saving behaviors and contribute to a comprehensive approach for energy-efficiency initiatives

The Relationship Between Executive Functioning and Narrative Language Abilities in Aphasia.

Although individuals with aphasia commonly exhibit challenges in executive functioning (EF) and spoken discourse, there is limited research exploring connections between these abilities within this specific population. Therefore, this study investigated the relationship between verbal and nonverbal EF and narrative productions in aphasia using a multilevel linguistic approach. Participants included 22 persons with aphasia (PWA) and 24 age- and education-matched, neurologically healthy controls (NHC). All participants completed assessments for EF and a story retelling task. Narrative samples were analyzed for microlinguistic (productivity, lexical and syntactic features, semantic content, word and sentence errors) and macrolinguistic (coherence, informational content, organization, and language use) characteristics. Correlational analyses were employed to explore the relationships among narrative variables. EF factors, extracted from principal component analysis, were used as predictive variables in hierarchical stepwise regression analyses to evaluate their role in predicting narrative performances of PWA and NHC. Relative to NHC, PWA exhibited impaired narrative performance affecting both microlinguistic and macrolinguistic levels. Breakdowns at the structural level (i.e., reduced productivity, syntax, lexical retrieval, and diversity) correlated with impaired story completeness, organization, and connectedness; this relationship was more prominent for PWA. Three EF factors representing (1) verbal EF, (2) verbal and nonverbal fluency, and (3) nonverbal EF were extracted. Factors 1 and 2 largely predicted narrative performance, whereas Factor 3 (i.e., nonverbal EF) contributed prominently to predicting macrolinguistic discourse performance in both groups although accounting for less variance in the data. Overall, lower EF scores, particularly verbal EF variables, predicted poor narrative performance in both groups. Our results indicate that both linguistic and extralinguistic cognitive abilities play a role in story retelling performances among PWA. Notably, both verbal and nonverbal EF skills were found to be correlated with narrative abilities. However, the extent of their contributions varied depending on the discourse levels assessed. These findings provide a significant contribution to our understanding of the cognitive factors associated with breakdowns in discourse among PWA and highlight the importance of comprehensive assessment of EF and discourse within this population. https://doi.org/10.23641/asha.26485627.

The S in STEM: gender differences in science anxiety and its relations with science test performance-related variables

BackgroundSTEM education has experienced significant growth due to its pivotal role in innovation and economic development. While cognitive factors like prior knowledge are known predictors of STEM success, non-cognitive factors, including attitudes and demographics, also play vital roles. However, there is a notable scarcity of research focusing on the "S" in STEM—science—compared to extensive studies in fields like mathematics. This study aims to address this gap by exploring gender differences in science test performance and related attitudes, providing insights into this under-researched aspect of STEM education.ResultsThe effective sample comprised 1839 Estonian 12th-grade students who took a computer-assisted science test. The test consisted of tasks combining chemistry, physics, biology, and geography, and a post-test survey was also administered. Across the total sample, the results showed that test performance positively correlated with test-taking duration, effort, and test importance. Test performance was negatively correlated with perceived test difficulty. Interestingly, while general science anxiety was not associated with test performance, subject-specific anxiety, especially chemistry anxiety had a negative association with test performance. While there were no gender differences in test performance, female students scored consistently higher on all science anxiety measures, compared to male students. Furthermore, female students assessed the science test to be more difficult, and they also took more time to complete the test. The correlations in gender subsamples mirrored those observed in the total sample.ConclusionsThe association between science test performance and test-related variables is nuanced: students might not necessarily have a “general” STEM anxiety but it may be associated with a specific subject. Moreover, the findings imply that although there are no gender differences in test performance, girls have a greater anxiety when it comes to natural sciences subjects. These findings indicate the need for investigating the origin of such anxieties, which do not seem to stem from aptitude.

Domains of baseless belief and the characteristics of believers

AbstractObjectiveAn extensive literature examines the prevalence of conspiracy theories and the factors that determine why some people believe them. Conspiracy theories are only one example of baseless beliefs, which we define as beliefs that are not epistemically warranted by the available evidence. The goals of this research were to determine if there are discrete domains of baseless beliefs and to identify the psychological and cognitive factors most closely associated with each type.MethodsWe surveyed 435 U.S. adults about their baseless beliefs and measured an extensive set of cognitive, epistemological, and personal characteristics.ResultsFour distinct domains of baseless belief were discovered, which we label conservative controversies, classic coverups, magical thoughts, and pseudoscience. The data suggest the confidence people have in these beliefs differs across domains and reveal clear differences in the cognitive, epistemological, and personality factors predicting belief in each domain.ConclusionBaseless beliefs encompass a number of distinct domains, and the psychological dynamics underlying belief acquisition vary across these domains. This finding suggests caution in generalizing from studies examining only one domain. The prominent role of conservatism documented in the literature on conspiracy theories, for example, is weaker or not present at all in other domains.

Enabling diagnostic excellence in the real world: Managing complexity, uncertainty and clinical responsibility.

Diagnostic error is a significant category within preventable patient harm, and it takes many years of effort to develop proficiency in diagnostic reasoning. One of the key challenges medical schools must address is preparing students for the complexity, uncertainty and clinical responsibility in going from student to doctor. Recognising the importance of both cognitive and systems-related factors in diagnostic accuracy, we designed the QUID Prompt (Questions to Use for Improving Diagnosis) for students to refer to at the bedside. This set of questions prompts careful consideration, analysis, and signposting of decision-making processes, to assist students in transitioning from medical school to the real-world of work and achieving diagnostic excellence in clinical settings.

Metacognitive strategies, writing self-efficacy and writing anxiety in different learning modes: A two-wave longitudinal model

Writing difficulties stemming from cognitive and emotional factors contribute to heightened levels of writing anxiety. Studies have highlighted the pivotal roles of metacognitive strategies and writing self-efficacy in predicting writing anxiety, particularly in cross-sectional analyses. However, how these constructs interact with writing anxiety in longitudinal studies remains relatively understudied. Therefore, it is essential to develop a comprehensive understanding of metacognitive strategies and self-efficacy to effectively mitigate writing anxiety for English as a foreign language (EFL) learners. We administered three questionnaires on metacognitive strategies use, writing self-efficacy, and writing anxiety to 301 participants across online and offline learning modes. We employed a two-wave longitudinal model to explore the possible temporal correlations. The findings indicated negative reciprocal correlations between the metacognitive strategies use in writing context and writing anxiety. Writing self-efficacy positively predicted metacognitive strategies use and negatively predicted writing anxiety. Writing self-efficacy did not act as a moderator in the relationship between metacognitive strategies use and writing anxiety, implying that the impact of metacognitive strategies use on anxiety levels remains consistent regardless of learners' self-efficacy. The current study offers valuable insights to EFL educators on integrating metacognitive strategies and self-efficacy to mitigate learners' writing anxiety.

Theories of foreign and second language acquisiton

Theories of foreign and second language acquisition examine how learners acquire languages beyond their native tongue. These theories offer insights into the cognitive, social, and environmental factors that influence language learning. While some theories emphasize innate abilities, others focus on the importance of interaction, cognitive development, or the role of external input and social contexts. This article presents observations on how language learners from diverse backgrounds learn English in different ways.

Research on Assessment Method for Cognitive Influence Factors of Nuclear Power Plant Operators Based on Fuzzy Analytic Hierarchy Process and Deep Learning of Electroencephalogram Signals

This study explores the factors influencing the cognitive processes of operators in digital nuclear power plants, with a focus on the correlation between these factors and electroencephalogram (EEG) features. Initially, based on expert consultations, seven factors were considered: stress, time, fatigue, procedural complexity, user interface experience, procedural clarity, and efficiency. From these, four were identified as the most crucial for each stage of the cognitive process, highlighting their significant roles in influencing cognitive performance and potentially correlating with distinct EEG characteristics. These were assessed using the fuzzy analytic hierarchy process (FAHP) to determine the weightings of influences across the cognitive stages of monitoring, decision making, and execution. Employing a simulated scenario of a steam generator tube rupture, subjective questionnaires were utilized to gauge participant perceptions of influencer impacts at each stage, calculating human factors fuzzy synthetic values. Concurrently, EEG signals were segmented by operational steps, extracting around 114 features across the time, frequency, and time-frequency domains, which were then dimensionally reduced to 17 principal components via adaptive principal components analysis (APCA). A correlation analysis was performed between the human factors fuzzy synthetic values and the APCA-reduced EEG features of participants. Subsequently, the EEG feature columns of the eight selected participants were used as inputs to construct a transformer-based self-attention network model to evaluate the participants’ human factors fuzzy comprehensive values. The findings confirm the transformer model’s efficacy in assessing these values, evidencing a significant correlation between the EEG features and human factors fuzzy synthetic values. Integrating FAHP with machine learning methodologies, this model proficiently estimated operators’ cognitive states during various cognitive processes, significantly enhancing human-machine interface design and the operational safety and efficiency at nuclear power plants.

B - 7 Factor Structure of the Beck Depression Inventory-II in Epilepsy

Abstract Objective This study aimed to explore the factor structure of the Beck Depression Inventory, Second Edition (BDI-II) in persons with epilepsy (PWE) and assess its correspondence with validated BDI-II cognitive and somatic-affective factors associated with depression in other populations. Method Retrospective data from 69 PWE (ages 18–72) who completed the BDI-II at a National Association of Epilepsy Centers level 4 epilepsy center were analyzed. Patients with diagnoses of bipolar disorder and schizophrenia spectrum disorders were excluded. An Exploratory Factor Analysis (EFA) using the psych package in R Studio was conducted, allowing factors to correlate with oblique factor rotation. The number of factors was determined using eigenvalues >1 and scree plots. Results Statistical support is strongest for a one-factor solution with eigenvalue 7.91; however, a two-factor solution (Factor two eigenvalue = 1.16) also met criteria. These factors accounted for 30% and 10% of the variance, respectively. Due to the low eigenvalue, few item loadings (3), and low variance explained by the second factor, item-level considerations were implemented to determine whether a two-factor solution added clinically relevant information. Conclusion Although a one-factor solution was best supported by the data, a second factor including sadness, feeling of punishment, and suicidal thoughts may be clinically relevant given elevated suicide risk and qualitative research reporting punishment feelings among PWE.

A - 5 Longitudinal Analysis of Protective Factors on Cognition Following Total Knee Arthroplasty

Abstract Objective To examine cognitive and brain resilience factors on older adult cognition following total knee arthroplasty (TKA). Methods Participants were recruited through orthopedic clinics and screened for eligibility (i.e., age > 60 years, English as first language, diagnosis of knee osteoarthritis, intact activities of daily living). Data were collected before surgery, three weeks, three months, and one-year post-TKA (N = 67; mean(SD) age = 69.49(7.09) years; mean(SD) education = 15.62(2.83) years; 51% female; 90% non-Hispanic White (NHW), 10% non-Hispanic Black. Participants received baseline magnetic resonance imaging (3 T Siemens Verio). Magnetization-prepared rapid gradient-echo images were preprocessed. Machine learning predicted brain age (DeepBrainNet) was calculated for each participant. Linear mixed effects models examined longitudinal effects of word reading (Wide Range Achievement Test-III (WRAT-III)), brain age gap (predicted brain age minus chronological age), sex, ethnicity/race, pain interference (Brief Pain Inventory), and depression (Beck Depression Inventory-II) on cognitive composites (i.e., memory, working memory/inhibition, reasoning, processing speed, language). Results Memory, working memory/inhibition, reasoning, and processing speed had curvilinear trajectories (p’s < 0.05), declining post-TKA and subsequently returning to baseline. Word reading positively associated with memory (β = 0.065, SE = 0.016, p < 0.001), working memory/inhibition (β = 0.069, SE = 0.016, p < 0.001), reasoning (β = 0.099, SE = 0.021, p < 0.001), and processing speed (β = 0.050, SE = 0.015, p < 0.01). Language negatively associated with BAG (β = −0.041, SE = 0.017, p < 0.05). Women had higher processing speed (β = −0.285, SE = 0.135, p < 0.05), and NHW participants had higher memory (β = 0.479, SE = 0.224, p < 0.05). When pain interference was higher, processing speed (β = −0.003, SE = 0.002, p < 0.05) and language (β = −0.007, SE = 0.002, p < 0.01) were lower. Conclusions Cognitive and brain resilience measures may identify individuals protected against cognitive dysfunction post-surgically. Future research increasing representation in underrepresented groups is warranted.

Characteristics of Speech Auditory Brainstem Response in Preschool Children With Attention-Deficit/Hyperactivity Disorder.

This study aimed to investigate the characteristics of auditory processing (AP) in preschool children with attention-deficit/hyperactivity disorder (ADHD) using the speech auditory brainstem response (speech-ABR), which provides insights into the AP of speech signals in the central auditory nervous system (CANS). A total of 84 preschool children diagnosed with ADHD, aged 4-6 years, were matched with 84 typically developing (TD) children based on gender and age. All children underwent speech-ABR testing, cognitive assessment using the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition or the Wechsler Intelligence Scale for Children-Fourth Edition, and a continuous performance test. Children with ADHD exhibited significantly longer latencies of speech-ABR waveforms V, A, and D compared to TD children. Multiple linear regression analysis showed that the latencies of speech-ABR waves V, A, and D were affected by the presence of ADHD, but not by the full-scale intelligence quotient. This study revealed that preschool children with ADHD exhibited abnormal AP of speech signals in their CANS. The findings suggest that speech-ABR can be utilized as a reliable measure to evaluate AP ability in this population, as it remains unaffected by cognitive or attentional factors. The transient response (V, A) of speech-ABR was found to be a significant predictor of ADHD in a clinical setting. Early assessment of AP abnormalities via speech-ABR is recommended in preschool-age children to develop targeted interventions for ADHD. https://doi.org/10.23641/asha.26376502.