Examination of the Structure and Measurement of Inattentive, Hyperactive, and Impulsive Behaviors from Preschool to Grade 4

Allan, Darcey M.; Lonigan, Christopher J.

doi:10.1007/s10802-018-0491-x

Cited by 15 publications

(19 citation statements)

References 40 publications

(49 reference statements)

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“…In keeping with much prior research (e.g., [18][19][20][21][22][23][24][25][26]), the traditional goodness of fit indices showed that the bifactor models provided a better fit than the correlated models in both samples. Recently, some concerns have been raised about relying on or overemphasizing traditional goodness of fit indices as these indices may favor the less constrained model possessing more parameters such as the bifactor model and due to the potential tendency to overfit data ascribed to the bifactor models [37][38][39].…”

Section: Bifactor Vs Correlated Modelssupporting

confidence: 75%

“…In these models, each symptom loads on the general factor and on one of the specific factors, and the correlations between all specified factors are restricted to zero (i.e., orthogonality) [14,16]. Studies have quite consistently supported bifactor models of ADHD over traditional correlated models across diverse ages, informants, measures, and samples (e.g., [18][19][20][21][22][23][24][25][26]).…”

Section: Introductionmentioning

confidence: 99%

“…Uncertainty remains as to whether hyperactivity and impulsivity are better represented as one or two (specific) factors (e.g., [22]). Most studies support a bifactor model with two specific factors [16], although quite a few studies failed to compare this model with a bifactor model with three specific factors [9,22,[27][28][29][30][31]. Of those that have, some studies have found the bifactor model with three specific factors to have a better fit in young children [21,32] and adults [24,25,33].…”

Section: Introductionmentioning

confidence: 99%

“…Another issue yet to be resolved is where the item "talks excessively" should be placed. Some studies have included it as an indicator of hyperactivity (e.g., [6,21,22,34,35]), others of impulsivity (e.g., [24,25,32,33,36]), reflecting differences between DSM-IV/DSM-5 and ICD-10, respectively. Crucially, the placement of this item may explain the mixed findings in the literature regarding the structure of impulsiveness and hyperactivity and the overall factor solution favored.…”

Section: Introductionmentioning

confidence: 99%

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The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

Arildskov

Virring

Lambek

et al. 2020

Preprint

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This study investigated the factor structure of attention-deficit/hyperactivity disorder (ADHD) by comparing the fit of a single-factor model, a correlated model with two or three factors, and a bifactor model with one general and two or three specific factors. Different three-factor solutions that varied with regard to the specification of the item "talks excessively" as impulsivity or hyperactivity were also tested. Parent ratings on the ADHD-Rating Scale (ADHD-RS-IV) were collected in a sample of 2044 schoolchildren (1st to 3rd grade) from the general population and in a clinical sample of 165 children and adolescents with ADHD referred to a public regional child and adolescent psychiatric hospital. Confirmatory factor analyses found a satisfactory fit for most models in both samples. However, a correlated three-factor model where "talks excessively" was included as an indicator of impulsivity and especially the bifactor version of this model with one general and three specific factors fit the data slightly better in the general population. In the clinical sample, a number of models performed equally well (the same version of the correlated three-factor model and all the bifactor models). Overall, the factor structure of ADHD seems to be better characterized by a bifactor model with a strong general factor and two or three weaker specific factors. Due to the strong general factor, we suggest emphasizing the ADHD-RS-IV total score rather than the subscale scores in clinical practice.

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Section: Bifactor Vs Correlated Modelssupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

Arildskov

Virring

Lambek

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Although both are expressed through lack of control, impulsivity could be better understood as a lack of cognitive inhibition and hyperactivity as a lack of motor inhibition. To verify this, some authors have evaluated the levels of hyperactivity and impulsivity in a sample of more than 10,000 healthy children, concluding emphatically that the measures of hyperactivity and impulsivity address different constructs [52]. In this regard, it is not complicated to imagine a person of any age who can be very energetic, in terms of activity, and yet be extremely reflective in terms of decision making.…”

Section: Hyperactivity and Impulsivity: Different Concepts Same Diagmentioning

confidence: 99%

Traditional Scales Diagnosis and Endophenotypes in Attentional Deficits Disorders: Are We on the Right Track?

Jiménez-Soto¹,

Vargas²,

Díaz³

et al. 2021

ADHD - From Etiology to Comorbidity

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The concept of ADHD has changed widely through the history of mental health classification manuals. In the past three decades, the number of ADHD diagnoses has hugely increased worldwide. One of the reasons to explain this fact could be the lack of precision, differentiation and adjust of the criteria and indicators of this disease. Research has detected as well, some subjectivity bias in the traditional assessment (based in questionnaires and behavioral scales), which is affecting to the precision in the diagnose and to the further adjustment to the treatment. In this regard, these diagnoses are based in symptoms but not in etiology of the disorder. Therefore, different disorders will share the same treatment, regardless etiology. A different approach is based on the study of vulnerable traits associated with impulsivity and attentional deficit. In a quantitative fashion; these traits could be used to define a specific endophenotype. This view would allow us a more precise medical/psychological assessment focus on patient along the life spam, avoiding a diagnostic based on the number of symptoms. Here, we discuss about the differences between traditional diagnosis scales and the possibilities to find endophenotypes in order to address a specific treatment.

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Data-driven profiles of attention-deficit/hyperactivity disorder using objective and ecological measures of attention, distractibility, and hyperactivity

Fernández-Martín

Rodríguez-Herrera

Cánovas³

et al. 2023

Eur Child Adolesc Psychiatry

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In the past two decades, the traditional nosology of attention-deficit/hyperactivity disorder (ADHD) has been criticized for having insufficient discriminant validity. In line with current trends, in the present study, we combined a data-driven approach with the advantages of virtual reality aiming to identify novel behavioral profiles of ADHD based on ecological and performance-based measures of inattention, impulsivity, and hyperactivity. One hundred and ten Spanish-speaking participants (6–16 years) with ADHD (medication-naïve, n = 57) and typically developing participants (n = 53) completed AULA, a continuous performance test embedded in virtual reality. We performed hybrid hierarchical k-means clustering methods over the whole sample on the normalized t-scores of AULA main indices. A five-cluster structure was the most optimal solution. We did not replicate ADHD subtypes. Instead, we identified two clusters sharing clinical scores on attention indices, susceptibility to distraction, and head motor activity, but with opposing scores on mean reaction time and commission errors; two clusters with good performance; and one cluster with average scores but increased response variability and slow RT. DSM-5 subtypes cut across cluster profiles. Our results suggest that latency of response and response inhibition could serve to distinguish among ADHD subpopulations and guide neuropsychological interventions. Motor activity, in contrast, seems to be a common feature among ADHD subgroups. This study highlights the poor feasibility of categorical systems to parse ADHD heterogeneity and the added value of data-driven approaches and VR-based assessments to obtain an accurate characterization of cognitive functioning in individuals with and without ADHD.

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Examination of the Structure and Measurement of Inattentive, Hyperactive, and Impulsive Behaviors from Preschool to Grade 4

Cited by 15 publications

References 40 publications

The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

Traditional Scales Diagnosis and Endophenotypes in Attentional Deficits Disorders: Are We on the Right Track?

Data-driven profiles of attention-deficit/hyperactivity disorder using objective and ecological measures of attention, distractibility, and hyperactivity

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