Exploratory Graph Analysis of the Strengths and Difficulties Questionnaire in the Longitudinal Study of Australian Children

Abstract

In Australia, the Strengths and Difficulties Questionnaire (SDQ) has been implemented in several national studies, including the Longitudinal Study of Australian Children (LSAC). However, three previous state-level validations indicated problems with instrument dimensionality, warranting further research. To address this gap, the current study employed exploratory graph analysis to investigate dimensionality of the caregiver-completed SDQ version 4 to 10 years in a nationally representative sample of Australian children. Data were from a dual cohort cross-sequential study (LSAC) that included more than 20,000 responses. Gaussian graphical models were estimated in each study wave and exploratory graph analysis applied. Structural consistency, item stability and network loadings were evaluated. The findings provided mixed support for the original SDQ five-factor structure. The Peer Problem scale displayed low structural consistency since items clustered with the Emotional Symptoms and Prosocial behavior, generating four-dimensional structures. Implications for future use of the SDQ version 4 to 10 years in Australia are provided.

Is it time to revise the SDQ? The psychometric evaluation of the Strengths and Difficulties Questionnaire.

“…Our results revealed that the emotional problems and prosocial behavior scales fulfilled the fit criteria for one-dimensionality. The result corresponds with earlier studies (Koskelainen et al, 2001; Ribeiro Santiago et al, 2022; Richter et al, 2011). The conduct problems scale was deemed one-dimensional, although part of the indices indicated a poor fit especially among mid-adolescent girls.…”

Exploratory Graph Analysis of the Strengths and Difficulties Questionnaire for Aboriginal and/or Torres Strait Islander Children

“…Considering that responses to the caregiver-informant SDQ for children aged 4-10 years have already been collected for Aboriginal and/or Torres Strait Islander children in national surveys (Department of Families, 2009) and longitudinal cohorts in Australia (Jamieson et al, 2021), one main implication of the network structure of the caregiver-informant SDQ in Aboriginal and/or Torres Strait Islander children is that, instead of summing items into subscale scores, the SDQ items should be considered individually. For example, the item bullied ("picked on or bullied by other children") can be used to inform Aboriginal and/or Torres Strait Islander children's experience of victimization without needing to be summed with the other peer problem items to create a subscale score (Ribeiro Santiago et al, 2021a). Thus, based on our findings from more than 4,000 caregiver-informant SDQ responses, we do not recommend the summation of items into subscale scores (e.g., "hyperactivity, " "emotional symptoms, " "conduct problems, " "Peer Problems, " and "prosocial behavior" subscales) for Aboriginal and/or Torres Strait Islander children.…”

“…The network analysis provided new insights into the SDQ functioning, such as how the Peer Problems items were scattered across the network clustering with other dimensions and how a network structure should be preferred than a factorial structure for Aboriginal and/or Torres Strait Islander children. While (Ribeiro Santiago et al, 2021a) recently compared factorial structures identified from EGA with traditional SDQ factorial structures in Australian children, to the best of our knowledge, this is the first study to directly compare network structures with traditional SDQ factorial structures across any population. While network models have been recently shown to be superior to factor models when evaluating intelligence (Schmank et al, 2021) and even the concentration and empathy of children , to the best of our knowledge, this is also the first study to compare network and factor models to evaluate the SEWB of children.…”

Understanding Connections and Boundaries Between Positive Symptoms, Negative Symptoms, and Role Functioning Among Individuals With Schizophrenia

“…The walktrap algorithm measures similarities between vertices based on random walks. We also examined item stability, defined as the proportion of times specific items clustered with their community across the replicated bootstrapped samples …”