This study was formally reviewed and approved by the research ethic committee of XXXX Hospital (City, Country). Informed written and verbal consent was obtained from parents prior to participation at each time point.
Participants
Families of children aged under 71 months who received an AS diagnosis at the specialized assessment clinic at XXXX Hospital between January 2014 and February 2020 were invited to participate in this study. Exclusion criteria for this group included having an identified associated genetic disorder or having an important motor delay (equivalent age < 18 months) susceptible to interfere with tests administration. AS diagnosis was based on gold standard instruments and expert clinician judgment. Of the 41 autistic children, 34 were assessed using Toddler Module or Module 1 of the ADOS-2 (64) or ADOS-G (65). Two children were assessed using Module 2 of ADOS-2 and used phrased speech at time of their diagnosis. Five children received an AS diagnosis based on clinical judgment.
NT participants were recruited in daycare centers of the same geographic area. Children in the NT group did not have any diagnosed developmental or neurological condition and did not have any sibling with an AS diagnosis. Participants’ characteristics are presented in Table 1.
Measures
Full-scale IQ (FSIQ). The Wechsler Preschool and Primary Scales of Intelligence – Fourth edition (WPPSI-IV: 66) was used to assess FSIQ. It is normed for children aged 2 years 7 months to 7 years 7 months, with a version designed for children under 4 and one for children of 4 years and older. These two versions include respectively 5 (Receptive Vocabulary, Information, Block Design, Object Assembly, Picture Memory) and 6 (Information, Similarities, Block Design, Matrix Reasoning, Picture Memory, Bug Search) core subtests allowing the computation of a FSIQ score in percentiles.
Non-verbal IQ (NVIQ). The board form of the Raven’s Colored Progressive Matrices (RCPM: 67) was used to measure NVIQ. Raven’s Matrices are among the most commonly used cognitive assessments in research studies (68) as this test uses non-verbal material and is relatively independent of culture. The RCPM includes three sets of 12 items (A, Ab, B) of increasing difficulty and complexity within and across sets. Each item presents a pattern or a 2 x 2 matrix that the child must complete by choosing which of the six movable pieces best completes the matrix. The Netherlands norms, from 3 years and 9 months to 10 years and 2 months, were used to derive percentiles from raw scores obtained by participants.
Table 1
Children and Families Sociodemographic Characteristics (N = 98: 38 girls, 60 boys)
Characteristics
|
n
|
%
|
Diagnostic group
|
|
|
Autistic
|
41
|
42
|
NT
|
57
|
58
|
Annual Income ($)
|
|
|
0 – 29,999
|
17
|
17
|
30,000 – 49,999
|
14
|
14
|
50,000 – 69,999
|
10
|
10
|
70,000 – 89,999
|
13
|
13
|
90,000 – 119,999
|
8
|
8
|
120,000+
|
23
|
24
|
Missing
|
13
|
13
|
|
Mothers
|
Fathers
|
|
n
|
%
|
n
|
%
|
Parental level of education
|
|
|
|
|
High school not completed
|
4
|
4
|
2
|
2
|
High school
|
11
|
11
|
13
|
13
|
Collegea
|
17
|
17
|
18
|
18
|
Undergraduate studies
|
28
|
29
|
32
|
33
|
Graduate studies
|
19
|
17
|
13
|
13
|
Postdoctoral fellowship
|
3
|
3
|
2
|
2
|
Missing
|
16
|
16
|
18
|
18
|
Parental ethnicity
|
|
|
|
|
Asian
|
1
|
1
|
1
|
1
|
Black
|
11
|
12
|
11
|
12
|
Latina
|
4
|
4
|
3
|
3
|
Middle Eastern countries
|
18
|
18
|
18
|
18
|
White
|
51
|
52
|
50
|
51
|
Missing
|
9
|
9
|
11
|
11
|
a Colleges are general and vocational educational institutions that grant two- or three-year postsecondary degrees preparing students for university-level education. NT = Neurotypicals
Perceptual abilities. Perceptual abilities were assessed using two different tests requiring selective visual attention: the Visual Search (VS) Task and the Children Embedded Figures Test (CEFT).
Visual Search Task. The VS was the same as the one in Courchesne et al.’s (50). Children were asked to find a target letter among sets of 5, 15, 25, 50 or 75 distracters. There were two conditions: (a) the feature condition, in which the target letter differed from distracters in shape (e.g., a red T hidden among red Xs and green Ss), and (b) the conjunction condition in which the target had either the color or the shape in common with the distracters, and thus, only the conjunction of attributes defined the target (e.g., a red X hidden among red Ts and green Xs). Each combination of number of distracters (5) and condition (2) was presented six times for a total of 60 trials. Each stimulus (i.e., target among distracters) was printed out on 28 x 21.5 cm plasticized card. Three different target letters were used in the task, and each was printed on thick plasticized cardboard (3 x 2.4 cm), so the children could manipulate it and answer by placing it over the corresponding target letter on the stimulus. The time (in seconds) required to find the target was used as a measure of performance. The number of correct answers was not used as there was an expected ceiling effect on this test.
Children Embedded Figures Test. The CEFT (69) involves finding a target shape camouflaged within a larger design with semantic meaning. The CEFT is made up of 14 practice trials and 25 test trials. To minimize verbal instructions, as it was done in previous studies (Courchesne et al. 2015; 2019), we removed the instruction not to rotate the target shape, which is normally part of the test instructions. We used the number of correct answers on the test, but not response time as it was only recorded for successful items.
Perceptual repetitive behaviors and interests. Perceptual repetitive behaviors and interests were measured using the Montreal Stimulating Play Situation – revised version (70). This standardized play situation is videotaped and lasts approximately 30 minutes. About 40 toys specifically chosen for their perceptual properties (e.g., toys with lights, musical toys, rotating toys) were displayed in a playroom or presented to the child by an experimenter. Undergraduate students were trained over multiple sessions to code repetitive behaviors (e.g., lining up objects) using Observer XT 11 (Noldus Information Technology Inc.) until they reached a percentage of agreement of 90%. Each repetitive behavior was defined in a repertoire, so that each instance could be easily coded. In the context of this study, only the perceptual explorations described below were considered in the analysis.
Perceptual explorations. Perceptual explorations were defined as repetitive behaviors that were atypical by their nature (e.g., lateral glances at objects) or by their intensity (e.g., lining up objects) and had a perceptual component. A perceptual exploration score was calculated for each participant by doing the sum of the frequency of the following repetitive behaviors: grouping objects based on their perceptual characteristics, lining up objects, writing, close gaze at objects, lateral glances at objects, and obstructed gaze at object. Scores were then divided by the total duration of the Montreal Stimulating Play Situation and multiplied by 3600 seconds. The resulting score therefore represented the number of times the child did perceptual explorations per hour.
Covariates. In addition to the child’s age at T1, sex and group, family socio-economic status (SES) was computed. Standardized scores (Z-scores) of maternal and paternal years of education, and family income were averaged to create a family SES index.
Procedure
This longitudinal study included three time points. The first time point was at the age of diagnosis during preschool (T1; M = 53.38 months, SD = 9.53, Range = 26.67 – 70.00). The second and third time points took place approximately 1 year, (T2; M = 67.86 months, SD = 10.72, Range = 41.00 – 98.00) and 2 years later (T3; M = 79.60, SD = 10.28, Range = 57.50 – 107.00). During the first time point, participants were exposed to the Montreal Stimulating Play Situation designed to elicit restricted and repetitive behaviors in preschool children. Across all time points, children also had to complete a variety of tasks measuring FSIQ and NVIQ levels as well as perceptual skills.
Among our sample of 98 children, 89 completed the FSIQ assessment at Time 1 (T1), 64 at Time 2 (T2), and 41 at Time 3 (T3). Also, 78 children completed the NVIQ assessment at T1, 65 at T2, and 45 at T3. In all, the 98 children of our sample had available data on at least one of the FSIQ or NVIQ assessment points (i.e., T1, T2 or T3; see Table S1 for information on missing data).
Preliminary Analyses
Attrition analyses suggested that the number of missing data was not associated with family SES, group (i.e., NT or autistic) or performance on perceptual predictors (VS time, CEFT score and perceptual explorations), all ps > .05. However, child’s age at T1 was significantly associated with the number of missing data, r = .23, p = .02, such that children who were older at T1 had more missing data. Missing data are considered missing at random when other observed variables are associated with the probability of missingness (71), as it is the case in our study. Consequently, missing data were handled using the robust full-information maximum likelihood (MLR) estimator, as per current best practices, which allows the estimation of model parameters using all available data and increases statistical power (72, 73).
Analytic Strategy
To describe intraindividual trajectories of children’s FSIQ and NVIQ levels over time, multilevel growth curves analyses were conducted using Mplus (74). As opposed to structural equation modeling framework, multilevel modeling (MLM) framework can easily handle partially missing data, unequally spaced time points, and data collected across a range of ages within a particular measure point (72, 75, 76). Using MLM also allows for the exploration of intraindividual change over time (level-1; within-subject) as well as inter-individual differences in intercept and slopes (level-2; between-subjects : 77). Furthermore, it allows examining the links between variables of interests and between-subjects’ differences in both intercept and slope. Using MLM, adequate statistical power is achieved with as few as 30-50 level-2 units (i.e., 30-50 children : 75). All these attributes make MLM particularly well suited to the methodological design of our study.
Modeling change in FSIQ and NVIQ over time. Intraindividual trajectories in FSIQ and NVIQ level over time were first modeled at level-1 (within-person change over time) and differences between children were then examined at level-2 (between-person change over time). Two unconditional models were specified to ascertain the best-fitting trajectory models in FSIQ and NVIQ levels. The Model A (i.e., fixed linear model) included the fixed effect of children exact age in years, coded such that the intercept represented average FSIQ level or NVIQ level at 5 years (representing school entry in XXXX country) and the slope represented the average yearly change in FSIQ or NVIQ level. The Model B (random linear model) included the random effect of time (i.e., between-subjects variability in individual intercepts and slopes). Using children’s exact age enabled us to flexibly handle individually varying time scores and to estimate change in child FSIQ and NVIQ levels from 2 to 8 years.
The log-likelihood (an indicator of deviance) and the Akaike information criterion were used to assess goodness of fit. Lower values indicated better representation of the data by the model (78). The random effects were retained if the model’s log likelihood (LL) was significantly lower or remained the same with the addition of the random terms, based on an adjusted chi-square difference test (i.e., adapted to the MLR estimator), or if the model’s Akaike information criterion was lowered with the addition of the random terms.
Finally, all continuous predictors were centered at the grand mean so that the intercept represents the estimated initial status (baseline level) for individuals with an average value on each predictor.
Predicting change in FSIQ and NVIQ levels over time. After modeling both FSIQ and NVIQ trajectories, a preliminary condition model was tested, including the effects of the potential covariates (i.e., child’s age at T1, family SES, sex) on FSIQ and NVIQ trajectories. Only the covariates significantly associated with the slope, the intercept or with missing data were deemed relevant for our analyses and retained in the final models. Child’s age at T1 was included in all final models as it was associated with missing data, as mentioned above. Only these final models were retained to increase parsimony, maximize statistical power, and to reduce the noise that may be caused by the high number of covariates included in the preliminary models (79).
Determining whether the predictors of change in FSIQ and NVIQ levels are the same in both groups. Group was included in the final models because our second objective was to examine whether the same variables predict the slope and intercept in autistic and NT children.
Final predictive models. Final predictive models, including the retained covariates, were estimated for each main predictor (i.e., VS time, CEFT score and perceptual explorations).