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Objective: The Wechsler Preschool and Primary Scale of Intelligence -- Fourth Edition Australian and New Zealand Standardised Edition (WPPSI-IV[superscript A&NZ]) is one of the most widely used intelligence assessments for children aged 2 years 6 months to 7 years 7 months. Given the impact of clinical and placement decisions that are supported by WPPSI-IV[superscript A&NZ] results, it is important to provide evidence of criterion-related validity. Criterion-related validity refers to the degree to which test scores are associated with an external criterion (e.g., pre-existing diagnosis or classification). Method: Two studies of children with intellectual giftedness (n = 19) and intellectual disability (n = 15) were conducted to determine if the constructs measured by the WPPSI-IVA&NZ perform as expected in criterion groups with known characteristics. Results: Independent sample t-tests revealed mean composite scores for intellectually gifted children were significantly higher than matched controls, with the exception of the Processing Speed Index and Cognitive Proficiency Index. Children with intellectual disability on average obtained significantly lower mean scores on all composites relative to matched controls. Conclusion: Results indicated that the WPPSI-IV[superscript A&NZ] can provide valid estimates of intellectual ability for children with intellectual giftedness and intellectual disability that align with their previous diagnosis or classification.

Objectives: This study examined the factorial invariance of the factor structure of the Wechsler Intelligence Scale for Children, Fifth Edition (WISC‐V) across the UK, US and Australia & New Zealand (A&NZ). The factorial equivalence of cognitive assessments should be demonstrated before assuming cross‐culture generalizability and interpretations of score comparisons. Methods: Data were obtained from the UK, US and A&NZ normative standardizations of the WISC‐V. The samples consisted of 415 UK, 2200 US and 528 A&NZ children, aged 6–16. Confirmatory factor analysis was applied separately in each sample to establish the baseline model. Next, tests of factorial invariance were undertaken using the recommended hierarchical approach, firstly across the UK and A&NZ samples and then across the UK and US samples. Results: The five‐factor first‐order scoring model was found to be excellent fit across all three samples independently. Strict factorial invariance of the WISC‐V was demonstrated firstly across the UK and A&NZ and secondly the UK and US nationally representative standardization samples. Comparison of latent means found small but significant differences in female children across the UK and A&NZ samples. Conclusions: Consistent with previous research, these results demonstrate the generality of the WISC‐V factor structure across the UK, US and A&NZ. Furthermore, as the WISC‐V factor structure aligns with the Cattell–Horn–Carroll (CHC) model of cognitive abilities, the results add further support to the cross‐cultural generalizability of the CHC model. Small but significant differences in latent factor scores found across samples support the development and use of local normative data. [ABSTRACT FROM AUTHOR]

Measurement invariance underlies construct validity generalization in psychology and must be demonstrated prior to any cross-population comparison of means and validity correlations. The purpose of this study was to evaluate the measurement invariance of the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V) across Australia and New Zealand (A&NZ) versus the U.S. normative samples. The WISC-V is the most widely used assessment of intelligence in children. Participants were census matched, nationally representative samples from A&NZ (n = 528) and the United States (n = 2,200) who completed the WISC-V standardization version. Baseline model estimation was conducted to ensure the same model showed acceptable fit in both samples separately. Measurement invariance was then examined across A&NZ and United States. The five-factor scoring model described in the test manual showed excellent fit in both samples. Results showed that the WISC-V demonstrated strict metric measurement invariance across the A&NZ and U.S. samples. Further, the results were consistent with the Cattell–Horn–Carroll (CHC) framework of cognitive abilities, indicating the generalizability of cognitive abilities across cultures. Small but significant differences in visual spatial latent means were found across females, highlighting the importance of local normative data. These findings suggest that the WISC-V scores can be meaningfully compared across A&NZ and United States and that the constructs, which align with CHC theory, and associated construct validity research, generalize across countries. Public Significance Statement: This study examined the generalizability of the WISC-V, the most widely used intelligence test for children, across nationally representative samples from A&NZ and the United States. The results suggest that WISC-V scores can be meaningfully compared across A&NZ and U.S. children and that the psychological constructs measured by the WISC-V generalize across countries. However, small mean score differences highlight the importance of local normative data. [ABSTRACT FROM AUTHOR]

Increasing screen time in childhood has raised concerns about potential effects on academic achievement, with speculation that this is due in part to an overall decrease in sleep. However, research does not often distinguish between different types of screen time, such as that dedicated to home or other educational pursuits. Further, family factors such as socioeconomic status are known to predict academic performance but are rarely examined in concert. The current study aimed to examine the association between screen time and academic achievement and to extend the current research by exploring whether the association was moderated by the type of screen time and family socioeconomic status. Participants were 651 children from Australia and New Zealand (Mage = 10.09, SD = 3.64). Participants completed an academic achievement test, and parents reported screen time activities. Homework, but not sleep, was associated with better academic achievement. Educational television viewing (TV), but not entertainment TV, was associated with lower academic achievement. Socioeconomic status moderated the association between educational TV and academic achievement (B = −.29, p =.007). The results suggest that while screen time type does appear to be implicated in academic achievement, the mechanism appears to be specific to higher socioeconomic status families. [ABSTRACT FROM AUTHOR]

This study set out to examine the associations of certain information communication technology (ICT) factors in the home environment with academic performance. We employed existing data sets collated by Pearson Clinical Assessment in 2016 which included the WIAT-III A&NZ (Wechsler Individual Achievement Test - Australian and New Zealand Standardised, Third Edition) completed by 714 students aged between 4 and 18 years old, and the home environment questionnaire (HEQ) completed by the parents of those children. Sequential multiple regression models were used to analyze the complex interactions between home ICT factors and measures of student reading, writing, mathematical, and oral ability. The findings of this study indicate that after accounting for the known powerful predictors of household income and parental education: (a) a student's access to an ICT rich home environment, (b) their aptitude in using home ICT, and (c) their recreational use of home ICT, are largely unrelated to academic performance. We observed some small positive correlations between academic performance and child ICT affinity, but also comparably sized negative associations with use of social media and educational TV viewing. Encouragingly, we propose that these findings suggest that increasing levels of ICT use and access in the home are unlikely to be detrimental to academic progress. These results provide important information for parents and educators given the impact of the Coronavirus global pandemic and the near world-wide adoption of ICT for home-schooling. [ABSTRACT FROM AUTHOR]

Background: DriveSafe measures awareness of the driving environment. It is one subtest of DriveSafe DriveAware, a cognitive fitness‐to‐drive screening instrument. We converted DriveSafe to a touchscreen format for ease of administration; this necessitated the development of an automatic data collection and scoring system to reflect the decision that would otherwise have been made by an expert rater. We applied a structured process to determine what constituted 'correct' scores. We then examined the resulting scoring parameters to determine if these discriminated at‐risk drivers from a comparison sample. Methods: Thirty at‐risk older drivers and 30 younger drivers took touchscreen DriveSafe. Following presentation of images containing between one and four objects/hazards for 4 seconds, participants indicated their recall of object/hazard characteristics (type, location and direction of movement) by touching the screen. We analysed responses via descriptive statistics to compare spread, accuracy and consistency; and via a Fisher's exact test to determine whether the set scoring parameters could discriminate between at‐risk and comparison drivers. Results: Fisher's exact test results indicated 24 of 28 location zones and 18 of 28 direction ranges discriminated at‐risk drivers from the comparison group (P < 0.05). Frequency of missed or incorrectly identified hazards was much higher for the at‐risk group for all variables. At‐risk drivers missed or misidentified significantly (P < 0.00) more object types (34%), directions (47%), and locations (36%) than the comparison group (≤4% for each variable). At‐risk drivers entered 31 additional responses for objects/hazards not displayed; the comparison group entered no additional responses. Conclusion: The automatic variable data collection and scoring system reflected decisions that would have been made by an expert rater. This systematic process provided automated scoring decisions that enabled us to discriminate at‐risk drivers from a comparison group. Psychometric evaluation of data gathered with touchscreen DriveSafe is required prior to use in clinical practice. [ABSTRACT FROM AUTHOR]