Background Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. Methods We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. Results Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. Conclusions Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.
a highly significant difference (t = 5.46, d j = 8, p < .OOl) in favor of the latter score. I n accordance with the interpretation of A-State(g), these two results indicate that Ss reported significantly greater feelings of tension, nervousness, worry, or apprehension during the 10-hour marathon experience than either immediately before or after the session. Furthermore, these findings give empirical support for the heightened intensity of feelings that have been described as characteristic of the marathon interaction(loP ll). It remains for further marathon therapy research to explore the extent of the relationship between a shift in anxiety levels and concomitant changes on other personality measures. SUMMARYThis study investigated the impact of marathon group therapy on state and trait anxiety. Nine university students responded to measures of state and trait anxiety immediately before and after participation in a 10-hour marathon group. The hypothesis that A-State would decline from pre-to posttherapy while A-Trait
The personality differences between 75 reporters of frequent dream recall and 111 low reporters were compared by the MMPI. Although there were no significant personality differences between the two groups, the trends were toward dream recallers tending to be more restless and nervous, more withdrawing, and more inclined to engage in manic activity.
The goal of the study is to investigate the relationship between the HEXACO personality model and Disintegration – representing a broad spectrum of psychotic-like experiences and behavioral tendencies that are reconceptualized as a personality trait. In this pre-registered study, we predicted that the Disintegration factor would separate from HEXACO.The replicability of the factorial structures of HEXACO and Disintegration subcomponents are investigated across the three national samples (X, Y, and Z), matched on key socio-demographic variables. Exploratory Structure Equation Modeling (ESEM) is used to study the invariance of the hypothesized seven-factor structure. Support for the metric invariance of the seven-factor structure based on HEXACO and Disintegration subcomponents/facets across the three nations was found. The disintegration factor lied clearly outside the HEXACO personality space with each of its nine subcomponents. The disintegration factor appeared to be the most robust among the seven across the samples and units of measurement (facets and items). A broad spectrum of psychotic-like experiences/behavioral tendencies relevant in understanding and explaining many aspects of everyday and long-term (mal)adaptations – as expected - is not captured by the HEXACO model.
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