The Development of Cognitive Functioning Indices in Early Childhood - - PowerPoint PPT Presentation

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The Development of Cognitive Functioning Indices in Early Childhood - - PowerPoint PPT Presentation

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T HE D EVELOPMENT OF C OGNITIVE F UNCTIONING I NDICES IN EARLY C HILDHOOD : F INDINGS FROM G ROWING UP IN N EW Z EALAND COMPASS Seminars 2019 Denise Neumann PhD Candidate Supervisors: A/P Karen Waldie, Dr Elizabeth Peterson School of

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THE DEVELOPMENT OF COGNITIVE FUNCTIONING INDICES IN EARLY CHILDHOOD: FINDINGS FROM GROWING UP IN NEW ZEALAND

COMPASS Seminars 2019

Denise Neumann

PhD Candidate Supervisors: A/P Karen Waldie, Dr Elizabeth Peterson

School of Psychology The University of Auckland - Te Whare Wānanga o Tāmaki Makaurau

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  • 1. Background
  • 2. The Growing up in New Zealand study (GUiNZ)
  • 3. Methods
  • 4. Results
  • 5. Conclusion

Outline

The Development of Cognitive Functioning Indices in Early Childhood

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  • 1. Background
  • Early childhood years: Rapid changes in

development of cognitive abilities  brain development, environmental input

  • Brain development prolonged process, important

changes taking place during the preschool years

(Mungas et al., 2013)

  • Early cognitive disadvantages associated with

poorer behavioural, socio-emotional and academic

  • utcomes later in life (Beitchman et al., 1996)
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  • 1. Background
  • Limitations of previous studies: Focus on narrow age ranges;

few attempts to observe developmental trajectories of cognitive functioning; cross-sectional

  • Challenges of longitudinal assessment of the development of

cognitive constructs, i.e.

– Tasks that are developmentally appropriate for one age are not necessarily appropriate for another – Great variability in child performance during early periods in development (Best & Miller, 2010) – Lack of established measures that are suitable across the entire age range (Mungas et al. 2013) – Funding and time restrictions in large population-based longitudinal studies

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  • 1. Background
  • Developing cognitive composite indices (CCIs) at 9

months, 2 years and 4.5 years  Using data from an up-to-date longitudinal population- based New Zealand birth cohort: Growing Up in New Zealand study

  • Investigation of trajectories of cognitive functioning in

early childhood

  • Identification of predictors promoting or hindering

cognitive abilities Aims and objectives

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  • A longitudinal study following a group of New

Zealand children, in the context of their families, from pre-birth to early adulthood – 6846 babies (52% male) – born in 2009/2010 – interviews in homes antenatally, at 9 months, and 2 years, 4.5 years, 8 years

  • 2. The Growing up in New Zealand Study (GUiNZ)
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What were the GUiNZ recruitment areas?

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Research domains and themes for GUiNZ

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Why create a Cognitive Composite Index (CCI)?

  • Global picture  global level of delay
  • Different cognitive measures/cognitive abilities at each data

collection wave

  • Longitudinal study: Examine cognitive trajectories over time
  • Avoids problem of multiple testing
  • Accounting for interrelations between

cognitive outcomes

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Measures: Cognitive Outcomes

  • 9 months: Pre-linguistic communication (Mac Arthur

CDI: Words and Gestures); Verbal communication (CSBS); Motor milestones (parent-report)

  • 2 years: Expressive verbal communication (Mac

Arthur CDI-II); Inhibitory control, Attention, Motor abilities (Stack & Topple interaction task)

  • 4.5 years: Receptive language (PPVT); Phonological

awareness (DIBELS); Executive control (Luria Clapping Task); Writing, Numeracy and Symbols (Who am I? Name and Numbers task, Count up, Count down task)

  • 3. Methods
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Measures: Cognitive Outcomes

  • 9 months: Pre-linguistic communication (Mac Arthur

CDI: Words and Gestures); Verbal communication (CSBS); Motor milestones (parent-report)

  • 2 years: Expressive verbal communication (Mac

Arthur CDI-II); Inhibitory control, Attention, Motor abilities (Stack & Topple interaction task)

  • 4.5 years: Receptive language (PPVT);

Phonological awareness (DIBELS); Executive control (Luria Clapping Task); Writing, Numeracy and Symbols (Who am I? Name and Numbers task, Count up, Count down task)

  • 3. Methods
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Measures: Cognitive Outcomes

  • 9 months: Pre-linguistic communication (Mac Arthur

CDI: Words and Gestures); Verbal communication (CSBS); Motor milestones (parent-report)

  • 2 years: Expressive verbal communication (Mac

Arthur CDI-II); Inhibitory control, Attention, Motor abilities (Stack & Topple interaction task)

  • 4.5 years: Receptive language (PPVT); Phonological

awareness (DIBELS); Executive control (Luria Clapping Task); Writing, Numeracy and Symbols (Who am I? Name and Numbers task, Count up, Count down task)

  • 3. Methods
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Measures: Cognitive Outcomes

  • 9 months: Pre-linguistic communication (Mac Arthur

CDI: Words and Gestures); Verbal communication (CSBS); Motor milestones (parent-report)

  • 2 years: Expressive verbal communication (Mac

Arthur CDI-II); Inhibitory control, Attention, Motor abilities (Stack & Topple interaction task)

  • 4.5 years: Receptive language (PPVT); Phonological

awareness (DIBELS); Executive control (Luria Clapping Task); Writing, Numeracy and Symbols (Who am I? Name and Numbers task, Count up, Count down task)

  • Mixture of continuous and categorical variables
  •  age-adjustment if correlation with age
  • 3. Methods
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Missing data pattern:

  • Of 6074 cases, 1667 (27%) complete cases
  • Cases >50% missing data (n=491) deleted beforehand
  • 1.5% - 42.2% missing data per variable

Multiple Imputation

13% missingness

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Missing data pattern:

  • Little’s MCAR test: p<.001  data not missing

completely at random

  • Missing at random: Variety of variables associated with

variables with missing data, differences between complete cases and cases with missing data

  • Auxiliary variables (sociodemographic and behavioural

data, low to moderate correlations)

  • Categorical and continuous variables, partially skewed

Multiple Imputation

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Multivariate Imputation by Chained Equations (MICE)

  • Software imputing incomplete multivariate data by fully

conditional specification approach (Van Buuren, 2007)

  • R package (mice) in RStudio
  • Bodner’s rule of thumb: number of imputations in

accordance to percentage of incomplete cases (White et al.,

2011)  73 imputations with 10 iterations

Multiple Imputation

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Problem

  • Combining multiple imputation and factor analysis due to

the issue of combining the results from different imputed data sets  merely averaging not appropriate Solution

  • Nassiri et al. (2018): first estimate the covariance matrix

from imputed data sets using Rubin’s rules (Rubin, 2004)

Multiple Imputation

Factor analysis

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Problem

  • Combining multiple imputation and factor analysis due to

the issue of combining the results from different imputed data sets  merely averaging not appropriate Solution

  • Nassiri et al. (2018): first estimate the covariance matrix

from imputed data sets using Rubin’s rules (Rubin, 2004)

  • Performing factor analysis on a single combined matrix

working on the parameter level

  • Implemented R package mifa to estimate the covariance

matrix for each imputed dataset

  •  mifa function adjusted for estimated mixed correlation

matrix used for analysis

Multiple Imputation

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Creating a cognitive composite index at 9 months

CCI

Non-verbal communication Motor abilities CSBS Emotion CSBS Expression CSBS Comprehension

Principal axis factoring with promax rotation

CSBS Communication

  • 4. Results
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Creating a cognitive composite index at 9 months

CCI

Non-verbal communication Motor abilities CSBS Emotion CSBS Expression CSBS Comprehension

One-factor solution (ω = .76)

CSBS Communication .71 .58 .72 .62 .51

  • 4. Results
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Creating a cognitive composite index at 2 years

CCI

Verbal communication Attention

  • rienting

Joint attention coop Inhibitory control coop Sustained attention

Principal axis factoring with promax rotation

Joint attention dem Inhibitory control dem Motor ability

  • 4. Results
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Creating a cognitive composite index at 2 years

CCI 1

Verbal communication

Attention

  • rienting

Joint attention coop Inhibitory control coop

Sustained attention

Two-factor solution (ω1 = .81; ω2 = .65)

Joint attention dem Inhibitory control dem Motor ability

.66 .82 .82 .72 .48

CCI 2

  • 4. Results
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Creating a cognitive composite index at 4.5 years

CCI

Receptive language Phonological awareness Count Up task Name Task Executive control

Principal axis factoring with promax rotation

Count Down task Name Task

  • 4. Results
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Creating a cognitive composite index at 4.5 years

CCI

Receptive language Phonological awareness Count Up task Name Task Executive control

One-factor solution (ω = .74)

Count Down task Numbers Task .53 .72 .69 .49 .55 .41

  • 4. Results
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Creating a cognitive composite index at 2 years

CCI

Verbal communication Attention

  • rienting

Joint attention coop Inhibitory control coop Sustained attention

One-factor solution (ω = .74)

Joint attention dem Inhibitory control dem Motor ability

.87 .87

  • 4. Results: Complete Cases
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Correlation with:

  • Pragmatic language/early literacy: mother-report at 4.5 years
  • School readiness: mother-report at 6 years

Validity of CCIs

Table 3. Correlation of CCIs with literacy and school readiness

  • Note. Correlation for complete cases in brackets.
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Conclusion

  • Identification of valid CCIs at 9 months and 4.5 years
  • At age 2 years, only the language component related to

later literacy and school readiness  may partially reflect the measures used

  • Results of complete cases analysis vary at 2 years 

largest amount of missing data

  • CCIs provides the opportunity to potentially examine

early cognitive trajectories along with factors that promote or hinder cognitive functioning in early childhood

  • Results of imputed data with high rates of missingness

have to be interpreted with caution

  • 5. Conclusion
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9 months 2 years 4.5 years

CCI CCI CCI

Use of CCIs for further analysis

Outlook

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9 months 2 years 4.5 years

Average

Outlook

Below average Average Average Below average Below average

Trajectories/Movement:

  • Stable
  • Increase
  • Decline
  • 1. Categorical indices
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CCI

Receptive language Phonological awareness Count Up task Name Task Executive control Name Task

  • 2. CCIs as latent constructs in SEM/path modelling

Outlook

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9 months 2 years 4.5 years

CCI CCI CCI Proximal factors Proximal factors Proximal factors Distal factors Distal factors Distal factors

Ante-/ perinatal factors; SES; Ethnicity

Outlook

CCI NIH Toolbox Cognition Attention Memory Executive functioning Language

8 years

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THE DEVELOPMENT OF COGNITIVE FUNCTIONING INDICES IN EARLY CHILDHOOD

COMPASS Seminars 2019

Denise Neumann

PhD Candidate Supervisors: A/P Karen Waldie, Dr Elizabeth Peterson

School of Psychology The University of Auckland - Te Whare Wānanga o Tāmaki Makaurau

Thank you!