Network analysis of narrative discourse and attention-deficit hyperactivity symptoms in adults

Abstract

Previous research investigating language in attention-deficit hyperactivity disorder (ADHD) has demonstrated several deficits in many aspects. However, no previous study employed quantitative methodology providing objective measures that could be compared among different studies with diverse samples. To fill this gap, we used network analysis to investigate how ADHD symptomatology impacts narrative discourse, a complex linguistic task considered to be an ecological measure of language. Fifty-eight adults (34 females and 24 males) with a mean age of 26 years old and a mean of 17 years of educational level were administered the Adult Self-Rating Scale for ADHD symptomatology. They also completed the State-Trait Anxiety Inventory, the Beck Depression Inventory and the Urgency, Premeditation, Perseverance, Sensation Seeking Behavior Scale. Intelligence quotient was calculated. Individuals were asked to tell a story based on a wordless picture book. Speech was recorded and transcribed as an input to SpeechGraphs software. Parameters were total number of words (TNW), number of loops of one node (L1), repeated edges (RE), largest strongly connected component (LSC) and average shortest path (ASP). Verbosity was controlled. Statistical analysis was corrected for multiples comparisons and partial correlations were performed for confounding variables. After controlling for anxiety, depression, IQ, and impulsiveness ADHD symptomatology was positively correlated with L1 and negatively correlated with LSC. TNW was positively correlated with ADHD symptoms. In a subdomain analysis, both inattention and hyperactivity-impulsivity were negatively correlated with LSC. Only hyperactivity-impulsivity positively correlated with TNW and L1. Results indicated a correlation between ADHD symptoms and lower connectedness in narrative discourse (as indicated by higher L1 and lower LSC), as well as higher total number of words (TNW). Our results suggest that the higher the number of ADHD symptoms, the less connectivity among words, and a higher number of words in narrative discourse.

Exploring the relationship between frequent cannabis use, vocal changes and language use

“…The reduced vowel space can be connected to psychomotor retardation influencing articulation and motor control and has been observed in the speech of patients with depression or post-traumatic stress disorder (Albuquerque et al, 2021;Sherer et al, 2016). A higher number of words per sentences might connect impulsivity and hyperactivity (Coelho et al, 2021) without the presence of thought disorder or cognitive problems as measures that have been previously connected to these symptoms such as coherence, on topic, tangentiality, Largest Strongly connected component, Largest Connected Component (Coelho et al, 2021) were not lower in the frequent cannabis user group.…”

“…In mental health research, speech changes are analysed in terms of language use and vocal parameters, usually after sampling a few minutes of speech elicited with standardized prompts and applying computerized, automated techniques to extract different features of speech. Vocal or paralinguistic analysis evaluates the physical aspects of spoken language after representing sound as waveforms and extract temporal, prosodic or frequency features regarding formants, pitch, frequency, duration, pauses and volume (Agurto et al, Jul 2020b;Albuquerque et al, 2021;Coelho et al, 2021;Cohen et al, 2022;Olah et al, 2023). The modern analysis of language use leverages Natural Language Processing, applied on speech transcripts.…”

Language as a Window Into the Altered State of Consciousness Elicited by Psychedelic Drugs

“…Along this line, the method of speech graphs transforms texts into graphs or networks, where nodes correspond to words (before or after lemmatization) and the directed links indicate that one word follows another in the text. The topological properties of the resulting graphs contain information useful to characterize drug-induced language alterations, as well as abnormalities specific to certain neuropsychiatric disorders ( Mota et al, 2012 ; Bertola et al, 2014 ; Mota et al, 2014 ; Mota et al, 2017 ; Coelho et al, 2021 ). Some examples of these topological properties include the number of cycles of different length, the average shortest path in the graph, the maximum distance across all pairs of nodes (diameter), among others ( Bullmore and Sporns, 2009 ).…”

Natural Language as a Window into the Subjective Effects and Neurochemistry of Psychedelic Drugs

“…The topological properties of the resulting graphs contain information useful to characterize druginduced language alterations, as well as abnormalities specific to certain neuropsychiatric disorders (Mota et al, 2012;Mota et al, 2014;Bertola et al, 2014;Mota et al, 2017;Coelho et al, 2021).…”