Sex and intelligence quotient differences in age of diagnosis among youth with attention-deficit hyperactivity disorder.

OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental condition and is characterized by inattention, hyperactivity, and impulsivity. Research suggests that some populations, such as females and individuals with high intelligence quotients may be a risk for late ADHD diagnosis and subsequent treatment. Our goal is to advance our understanding of ADHD diagnosis, by examining (1) how child sex and cognitive abilities together are related to the age of diagnosis and (2) whether symptom presentation, current internalizing and externalizing symptoms, and demographic factors are related to age of diagnosis. METHODS: Our analyses contained children who completed the required tests (N = 568) from a pre-existing dataset of 1380 children with ADHD from the Province of Ontario Neurodevelopmental Disorders (POND) Network (pond-network.ca). First, we conducted a moderation analysis with sex as the predictor, cognitive abilities as the moderator, and age of diagnosis as the outcome. Second, we conducted correlation analyses examining how symptom presentation, current internalizing and externalizing symptoms, and demographic factors are related to age of diagnosis. RESULTS: Higher IQ was related to a later age of diagnosis. Higher hyperactive-impulsive symptoms and externalizing symptoms were related to an earlier age of diagnosis. Internalizing symptoms were trend associated with a later age of diagnosis in girls. Higher socioeconomic status and non-White maternal ethnicity were related to later age of diagnosis. CONCLUSIONS: IQ, sex, ADHD symptomology, internalizing symptoms, externalizing symptoms, and socio-demographic factors affect the age of diagnosis.

Using network science to provide insights into the structure of event knowledge.

The structure of event knowledge plays a critical role in prediction, reconstruction of memory for personal events, construction of possible future events, action, language usage, and social interactions. Despite numerous theoretical proposals such as scripts, schemas, and stories, the highly variable and rich nature of events and event knowledge have been formidable barriers to characterizing the structure of event knowledge in memory. We used network science to provide insights into the temporal structure of common events. Based on participants' production and ordering of the activities that make up events, we established empirical profiles for 80 common events to characterize the temporal structure of activities. We used the event networks to investigate multiple issues regarding the variability in the richness and complexity of people's knowledge of common events, including: the temporal structure of events; event prototypes that might emerge from learning across many experiential instances and be expressed by people; the degree to which scenes (communities) are present in various events; the degree to which people believe certain activities are central to an event; how centrality might be distributed across an event's activities; and similarities among events in terms of their content and their temporal structure. Thus, we provide novel insights into human event knowledge, and describe 18 predictions for future human studies.