Background
It is widely known that the emotional, social, and cognitive skills that emerge in early childhood are important prerequisites for success in school, employment, and potential income in the later stages of an individual’s life [
11,
12,
29]. The period from birth to 3 years is also the stage when development is most rapid and children at this stage begin reaching basic development milestones. Therefore, early childhood is very sensitive to environmental effects and is also a period suitable for interventions that alleviate effects of external risk factors [
6,
17,
34‐
36].
Early childhood development (henceforth, “ECD”) has been recognized by governments and Non-Governmental Organizations as a window of opportunity to improve the level of individual development and the social and economic well-being of society as a whole [
6]. Under this context, continuous monitoring of ECD outcomes using culturally and developmentally appropriate instruments can provide useful information for developing more effective intervention strategies [
8]. Moreover, population-level measurement of ECD is necessary to improve ECD outcomes and reduce developmental inequality through national, regional, and global policies [
25].
Although there has been significant progress in supporting and monitoring ECD and developing instruments assessing ECD, there are few effective and reliable instruments available to assess children’s early development status at a large scale in different cultural environments [
25]. As Kelly et al. [
16] pointed out, children have different ways and times to acquire motor, cognitive, and language skills in different settings. Differences in preschool children’s cognitive and social emotional skills at the national level were found to be related to the country’s socioeconomic and nutritional status [
24]. The assessment of ECD in different regions of the world helps us understand commonalities and differences in, and factors contributing to ECD, thus providing useful information for developing more effective intervention strategies.
In summary, population-level measurement and evaluation of ECD is a key issue that needs to be solved in the current era. Unlike individual assessment instruments, population-level measurement tools need to be simple and inexpensive to implement and require cross-cultural comparisons [
25]. In this context, a new instrument, the Caregiver Reported Early Development Instruments (CREDI), was developed. The CREDI was designed as a caregiver-reported, cross-culturally comparable, population-level measure of ECD for children under 3 years [
25,
26]. The goal of the CREDI is to provide low-cost, large-scale data to facilitate policy interventions and resource allocation, while tracking global progress in alleviating ECD-related disparities around the world [
27]. The reliability and validity of the CREDI have been studied and its applicability to the evaluation of ECD levels in low- and middle-income countries has been confirmed [
1,
25,
27], but there is still a lack of research about its application in China, and there are still no studies on the application of CREDI in a longer format (henceforth, “long form”). Based on this, this paper introduces and analyzes the application of the CREDI long form in China, with special focus on its reliability and validity, based on survey data from poverty-stricken areas in China.
Results
First, the descriptive characteristics of the sample are displayed in Table
1. As shown in Table
1, 946 toddlers were included in our final analysis. Among these toddlers, only 248 were administered the Bayley-III. The distribution of child and family characteristics between the total sample and Bayley sample were mostly consistent. Generally, there were a slightly higher proportion of female toddlers; slightly over half had siblings; around 5% of the sample were born prematurely; the mother was identified as the primary caregiver for about 70% of the toddlers; the educational attainment of mothers was low overall – around half had junior high school and below. The household wealth status was moderate among all samples, and the wealth status of the Bayley sample was relatively better than the total sample.
Table 1
Descriptive characteristics of the sample
Age group |
5–11 months | 191 | 20.19 | 50 | 20.16 |
12–17 months | 215 | 22.73 | 56 | 22.58 |
18–23 months | 186 | 19.66 | 52 | 20.97 |
24–29 months | 206 | 21.78 | 62 | 25.00 |
30–35 months | 148 | 15.64 | 28 | 11.29 |
Gender |
Female | 487 | 51.48 | 131 | 52.82 |
Male | 459 | 48.52 | 117 | 47.18 |
Sibling |
No | 495 | 52.33 | 125 | 50.40 |
Yes | 451 | 47.67 | 123 | 49.60 |
Premature (gestational age < 37 weeks) |
Yes | 44 | 4.65 | 12 | 4.84 |
No | 902 | 95.35 | 236 | 95.16 |
Primary caregiver |
Mother | 661 | 69.87 | 172 | 69.35 |
Others | 285 | 30.13 | 76 | 30.65 |
Mother’s education |
Junior high school and below | 520 | 54.97 | 120 | 48.39 |
Senior high school and above | 426 | 45.03 | 128 | 51.61 |
Household wealth index, mean (SD) | 946 | 0.01(0.87) | 248 | 0.24(0.78) |
Home stimulation |
Participated in fewer than four of these six activities | 636 | 67.23 | 158 | 63.71 |
Participated in at least four of these six activities | 310 | 32.77 | 90 | 36.29 |
Second, the ECD results are shown in Table
2. The mean scores (SD) from the CREDI indicated that the overall developmental status of our sample was only moderate. In terms of the Bayley-III scores, the Bayley-III has not yet been administered to a healthy reference population in China. As such, we rely on reference populations from other widely accepted research, which reveals that, for a healthy population, the mean score (SD) is expected to be 105 (9.6) for the cognitive scale [
20,
33], 109 (12.3) for the language score [
33], and 107 (14) for the motor score [
7,
20]. According to the above standards, the developmental status of our sample was slightly below average. With respect to the ASQ-3, the mean scores of each domain were a little lower than the referenced mean scores shown in the ASQ-3 user guide. In sum, the results obtained from the three tests were generally consistent with slightly better results from the CREDI.
Table 2
The summary statistics of the CREDI, Bayley-III, and ASQ-3
1. CREDI(n = 946) |
Z-score |
Cognitive | 0.058 | 1.095 | −2.981 | 5.887 |
Language | 0.334 | 1.068 | −2.682 | 6.951 |
Motor | −0.012 | 1.020 | −3.311 | 6.069 |
Social-emotional | 0.287 | 1.047 | −3.010 | 5.101 |
2. Bayley-III(n = 248) |
Composite scores |
Cognitive | 102.036 | 13.527 | 65.000 | 145.000 |
Language | 103.423 | 16.911 | 62.000 | 153.000 |
Motor | 105.871 | 16.436 | 61.000 | 151.000 |
3. ASQ-3(n = 955) |
Scores |
Problem Solving | 46.549 | 12.500 | 0.000 | 60.000 |
Communication | 45.327 | 13.604 | 0.000 | 60.000 |
Fine Motor | 47.611 | 13.937 | 0.000 | 60.000 |
Gross Motor | 41.897 | 14.621 | 0.000 | 60.000 |
Personal-Social | 44.904 | 11.644 | 0.000 | 60.000 |
Third, the internal consistency of the CREDI, Bayley-III, and ASQ-3 are shown in Table
3. Both the CREDI and Bayley-III have large Cronbach’s α coefficients, which means the internal consistency of the two scales was high. For the CREDI, the Cronbach’s α coefficients of each subscale ranged from .92 to .97. When the internal consistency was examined by age group, it was found that the Cronbach’s α coefficients of each subscale decreased accordingly, but remained relatively high. For age 6–11 months, the Cronbach’s α coefficients of each subscale ranged from .81 to .87; for age 12–17 months, it ranged from .83 to .91; for age 18–23 months, it ranged from .74 to .93; for age 24–29 months, it ranged from .66 to .91; for age 30–35 months, it ranged from .60 to .89. Overall, the Cronbach’s α coefficients of the cognitive, motor, and social-emotional subscales decreased with age, but increased before 12 months. For the language subscale, the Cronbach’s α coefficients decreased with age, but increased before 24 months. Besides, it should be noted that the CREDI has unacceptably low internal consistency reliability (Cronbach’s α coefficients are below .7) in some places, such as the motor and social-emotional subscale within age 24–35 months.
Table 3
Internal consistency of the CREDI, Bayley-III, and ASQ-3 (Overall and by age groups)
CREDI | Cognitive | 0.9395 | 0.8498 | 0.8632 | 0.8154 | 0.8227 | 0.7634 |
Language | 0.9693 | 0.8720 | 0.9057 | 0.9287 | 0.9121 | 0.8886 |
Motor | 0.9374 | 0.8085 | 0.8258 | 0.7440 | 0.6844 | 0.6606 |
Social-emotional | 0.9178 | 0.8213 | 0.8624 | 0.7977 | 0.6546 | 0.6040 |
Bayley-III | Cognitive | 0.9773 | 0.9701 | 0.9718 | 0.9738 | 0.9454 | 0.8752 |
Expressive communication | 0.9722 | 0.9650 | 0.9708 | 0.9654 | 0.9450 | 0.9027 |
Receptive communication | 0.9720 | 0.9703 | 0.9712 | 0.9638 | 0.9466 | 0.9256 |
Fine motor | 0.9685 | 0.9645 | 0.9767 | 0.9803 | 0.9415 | 0.8641 |
Gross motor | 0.9724 | 0.9648 | 0.9606 | 0.9456 | 0.8989 | 0.7931 |
ASQ-3 | Problem Solving | 0.5450 | 0.5945 | 0.7075 | 0.3741 | 0.4183 | 0.6397 |
Communication | 0.6314 | 0.4898 | 0.4886 | 0.7164 | 0.6684 | 0.5210 |
Fine Motor | 0.6081 | 0.6196 | 0.6512 | 0.4847 | 0.6034 | 0.6635 |
Gross Motor | 0.6963 | 0.5896 | 0.8040 | 0.5078 | 0.5555 | 0.4951 |
Personal-Social | 0.4084 | 0.5134 | 0.5145 | 0.3487 | 0.4786 | 0.4246 |
For the Bayley-III, the Cronbach’s α coefficients of each subscale ranged from .97 to .98. The Cronbach’s α coefficients of each subscale decreased after the sample was divided by age group. Despite this, the internal consistency reliability indicated by the Cronbach coefficients was still very high. For the subscales of cognitive and fine motor skills, the internal consistency reliability increased with age between 6 and 23 months, while the internal consistency reliability decreased with age after 23 months. For the subscales of receptive communication and expressive communication, the internal consistency reliability increased with age between 6 and 17 months, while it decreased with age after 17 months. For the subscale of gross motor, the internal consistency reliability decreased with age across the five age groups.
In contrast, the ASQ-3 had a relatively lower scale internal consistency reliability. The Cronbach’s α coefficients of each subscale ranged from .41 to .70. Among the five subscales, the internal consistency reliability of the gross motor subscale was the highest and its Cronbach coefficient was .70; the internal consistency reliability of the personal-social subscale was the lowest and its Cronbach coefficient was .41. When the sample was divided by age group, the Cronbach’s α coefficients varied irregularly within different age groups.
Subsequently, the correlations between the CREDI and Bayley-III scores, the ASQ-3 and Bayley-III scores, and the CREDI and the ASQ-3 scores for each of their domains by age group were calculated respectively.
P-values of the correlations were calculated by bootstrapping methods, with 1000 replications. As shown in Table
4, the results indicated that the concurrent validity of the CREDI with the Bayley-III scale was high in general. That is, CREDI cognitive, language, and motor subscales had strong correlations with the corresponding Bayley-III subscales. The correlation coefficients ranged from .84 to .90, among which the correlation between the CREDI motor subscale and the Bayley-III gross motor subscale was the largest. In contrast, although the correlation coefficients between the ASQ-3 communication subscale and the Bayley-III expressive communication and receptive communication subscales, and the ASQ-3 gross motor subscale and the Bayley-III gross motor subscale were significant at moderate levels, the concurrent validity of the ASQ-3 with the Bayley-III scale was relatively lower in general. With respect to the concurrent validity of the ASQ-3 with the CREDI, the results showed that only the correlation coefficients between the ASQ-3 communication subscale and the CREDI language subscale, as well as the ASQ-3 gross motor subscale and the CREDI motor subscale were significant at moderate levels, and the correlations in other domains were extremely weak.
Table 4
Correlations among CREDI, Bayley-III, and the ASQ-3
| Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI | | | | |
Cognitive | 0.835*** | 0.791*** | 0.814*** | 0.828*** | 0.864*** | | | | |
Language | 0.889*** | 0.855*** | 0.897*** | 0.870*** | 0.852*** | | | | |
Motor | 0.879*** | 0.813*** | 0.839*** | 0.872*** | 0.901*** | | | | |
Social-emotional | 0.868*** | 0.803*** | 0.831*** | 0.856*** | 0.896*** | CREDI (n = 946) | |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.100+ | − 0.017 | − 0.053 | −0.069 | − 0.117* | 0.116*** | 0.060+ | 0.059+ | 0.059+ |
Communication | 0.319*** | 0.404*** | 0.426*** | 0.322*** | 0.249*** | 0.388*** | 0.472*** | 0.348*** | 0.362*** |
Fine Motor | −0.181** | −0.134* | − 0.145* | − 0.167** | − 0.171** | 0.060+ | − 0.016 | 0.009 | − 0.002 |
Gross Motor | 0.429*** | 0.373*** | 0.391*** | 0.426*** | 0.549*** | 0.491*** | 0.442*** | 0.533*** | 0.484*** |
Personal-Social | −0.036 | 0.047 | 0.031 | −0.011 | 0.016 | 0.196*** | 0.133*** | 0.153*** | 0.149*** |
The heterogeneous analysis of the CREDI was also conducted, as shown in Tables
5,
6 and
7. The correlations were calculated among the Bayley-III, the CREDI, and the ASQ-3 by age group, primary caregiver, and wealth status. Table
5 shows that the correlations between the CREDI and Bayley-III varied with different age groups. In general, the correlation between the CREDI and the Bayley-III was strong before 18 months but was relatively weak at 18 to 23 months, and was moderate after 24 months. When the correlations between the ASQ-3 and Bayley-III by age group were examined, it was found that, generally, the correlation in the domain of communication between ASQ-3 and Bayley-III was better within 12–29 months than other age periods. With respect to the correlations between the CREDI and the ASQ-3 by age group, it was found that within 5–11 months, only the correlation between the CREDI language subscale and the ASQ-3 communication was significant and at a moderate level. After 12 months, the correlations between each domain of the CREDI and the ASQ-3 were significant and moderate.
Table 5
Correlations among CREDI, Bayley-III, and the ASQ-3 by Age Group
CREDI |
Cognitive | 0.386** | 0.374** | 0.515*** | 0.600*** | 0.566*** | | | | |
Language | 0.449*** | 0.447** | 0.508*** | 0.559*** | 0.515*** | | | | |
Motor | 0.472*** | 0.424** | 0.585*** | 0.634*** | 0.617*** | | | | |
Social-emotional | 0.450*** | 0.413** | 0.544*** | 0.606*** | 0.602*** | CREDI, 5–11 months(n = 191) | |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.007 | −0.182 | − 0.079 | − 0.105 | −0.100 | 0.078 | 0.029 | 0.104+ | 0.032 |
Communication | 0.117 | 0.255+ | 0.179 | 0.162 | 0.104 | 0.322*** | 0.422*** | 0.253*** | 0.339*** |
Fine Motor | 0.038 | −0.122 | −0.021 | − 0.069 | − 0.131 | 0.032 | 0.046 | 0.012 | 0.009 |
Gross Motor | −0.062 | 0.004 | −0.056 | −0.121 | 0.017 | 0.047 | 0.004 | 0.047 | 0.028 |
Personal-Social | 0.121 | 0.100 | 0.052 | −0.027 | 0.067 | 0.159* | 0.126+ | 0.123+ | 0.130+ |
| Bayley III, 12–17 months(n = 56) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI |
Cognitive | 0.460*** | 0.516*** | 0.512*** | 0.505*** | 0.624*** | | | | |
Language | 0.399** | 0.559*** | 0.644 *** | 0.528*** | 0.514*** | | | | |
Motor | 0.442*** | 0.529*** | 0.527*** | 0.532*** | 0.736*** | | | | |
Social-emotional | 0.480*** | 0.488*** | 0.508*** | 0.497*** | 0.631*** | CREDI, 12–17 months(n = 215) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | 0.073 | 0.319** | 0.286** | 0.422** | 0.095 | 0.429*** | 0.381*** | 0.354*** | 0.427*** |
Communication | 0.128 | 0.403*** | 0.440*** | 0.409** | 0.082 | 0.241*** | 0.348*** | 0.126+ | 0.228** |
Fine Motor | 0.082 | 0.208+ | 0.224* | 0.207 | 0.070 | 0.430*** | 0.346*** | 0.400*** | 0.415*** |
Gross Motor | 0.335** | 0.188 | 0.170 | 0.304* | 0.695*** | 0.400*** | 0.293*** | 0.570*** | 0.437*** |
Personal-Social | 0.352* | 0.328** | 0.327** | 0.427*** | 0.348** | 0.496*** | 0.410*** | 0.399*** | 0.513*** |
| Bayley III, 18–23 months(n = 52) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI |
Cognitive | 0.450*** | 0.254* | 0.329*** | −0.021 | 0.201 | | | | |
Language | 0.539*** | 0.381*** | 0.546*** | 0.134 | 0.245+ | | | | |
Motor | 0.498*** | 0.262* | 0.275** | 0.003 | 0.181 | | | | |
Social-emotional | 0.379*** | 0.260* | 0.294** | 0.007 | 0.200 | CREDI, 18–23 months(n = 186) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | 0.023 | −0.030 | 0.063 | 0.089 | −0.094 | 0.341*** | 0.298*** | 0.389*** | 0.302*** |
Communication | 0.428*** | 0.395*** | 0.551*** | 0.105 | 0.243+ | 0.583*** | 0.758*** | 0.572*** | 0.568*** |
Fine Motor | 0.062 | −0.041 | −0.024 | − 0.080 | − 0.139 | 0.408*** | 0.276*** | 0.415*** | 0.338*** |
Gross Motor | 0.044 | 0.014 | 0.112 | 0.070 | 0.157 | 0.178* | 0.149* | 0.337*** | 0.127 |
Personal-Social | −0.086 | 0.083 | 0.211+ | −0.027 | − 0.118 | 0.256** | 0.197* | 0.306*** | 0.227** |
| Bayley III, 24–29 months(n = 62) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI |
Cognitive | 0.228+ | 0.463*** | 0.419*** | 0.343** | 0.284* | | | | |
Language | 0.369** | 0.534*** | 0.612*** | 0.386*** | 0.194 | | | | |
Motor | 0.095 | 0.183 | 0.190 | 0.253* | 0.370** | | | | |
Social-emotional | 0.187 | 0.360** | 0.317* | 0.315** | 0.281* | CREDI, 24–29 months(n = 206) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | 0.126 | 0.208+ | 0.092 | 0.080 | 0.200 | 0.491*** | 0.399*** | 0.370*** | 0.444*** |
Communication | 0.202+ | 0.410*** | 0.455*** | 0.290* | 0.343* | 0.467*** | 0.604*** | 0.404*** | 0.410*** |
Fine Motor | −0.010 | 0.116 | 0.128 | 0.097 | 0.238+ | 0.451*** | 0.329*** | 0.401*** | 0.366*** |
Gross Motor | −0.216* | −0.153+ | − 0.198* | −0.095 | 0.091 | 0.271*** | 0.154* | 0.351*** | 0.191** |
Personal-Social | −0.031 | 0.129 | 0.213+ | 0.110 | 0.347** | 0.520*** | 0.515*** | 0.528*** | 0.475*** |
| Bayley III, 30–35 months(n = 28) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI |
Cognitive | 0.230 | 0.228 | 0.205 | 0.259 | 0.157 | | | | |
Language | 0.554*** | 0.550*** | 0.560** | 0.575*** | 0.309* | | | | |
Motor | 0.250 | 0.267+ | 0.263 | 0.426*** | 0.242 | | | | |
Social-emotional | 0.246 | 0.162 | 0.181 | 0.196 | 0.033 | CREDI, 30–35 months(n = 148) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | 0.121 | 0.219 | 0.012 | 0.019 | −0.025 | 0.455*** | 0.453*** | 0.411*** | 0.371*** |
Communication | 0.388* | 0.399** | 0.288 | 0.138 | 0.210 | 0.475*** | 0.480*** | 0.356*** | 0.431*** |
Fine Motor | 0.306+ | 0.240 | 0.140 | 0.243 | 0.235 | 0.452*** | 0.340*** | 0.451*** | 0.401*** |
Gross Motor | 0.476** | 0.258 | 0.470* | 0.401* | 0.248 | 0.377*** | 0.379*** | 0.466*** | 0.243*** |
Personal-Social | 0.073 | 0.359** | 0.015 | 0.132 | 0.040 | 0.484*** | 0.394*** | 0.543*** | 0.443*** |
Table 6
Correlations among CREDI, Bayley-III, and the ASQ-3 by caregiver
CREDI | | | | |
Cognitive | 0.850*** | 0.811*** | 0.839*** | 0.841*** | 0.885*** | | | | |
Language | 0.900*** | 0.875*** | 0.910*** | 0.889*** | 0.874*** | | | | |
Motor | 0.879*** | 0.813*** | 0.833*** | 0.873*** | 0.902*** | | | | |
Social-emotional | 0.880*** | 0.821*** | 0.849*** | 0.868*** | 0.915*** | CREDI(n = 661) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.088 | 0.001 | −0.026 | −0.042 | − 0.092 | 0.117** | 0.073+ | 0.069+ | 0.069+ |
Communication | 0.287*** | 0.404*** | 0.425*** | 0.295*** | 0.251*** | 0.379*** | 0.458*** | 0.346*** | 0.349*** |
Fine Motor | −0.243** | −0.197** | − 0.197** | − 0.196** | − 0.184** | 0.020 | − 0.056 | −0.022 | − 0.032 |
Gross Motor | 0.408*** | 0.357*** | 0.368*** | 0.386*** | 0.528*** | 0.528*** | 0.488*** | 0.563*** | 0.526*** |
Personal-Social | −0.089 | −0.002 | −0.013 | − 0.069 | −0.020 | 0.153*** | 0.095* | 0.109** | 0.106** |
| Bayley III, Grandmother is the primary caregiver (n = 66) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI | | | | |
Cognitive | 0.800*** | 0.752*** | 0.744*** | 0.813*** | 0.822*** | | | | |
Language | 0.869*** | 0.822*** | 0.869*** | 0.840*** | 0.807*** | | | | |
Motor | 0.874*** | 0.812*** | 0.848*** | 0.868*** | 0.895*** | | | | |
Social-emotional | 0.830*** | 0.763*** | 0.779*** | 0.836*** | 0.851*** | CREDI(n = 251) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.127 | − 0.054 | − 0.109 | − 0.120 | −0.175+ | 0.169* | 0.072 | 0.086 | 0.090 |
Communication | 0.379*** | 0.400*** | 0.437*** | 0.397*** | 0.252* | 0.436*** | 0.543*** | 0.379*** | 0.427*** |
Fine Motor | −0.004 | 0.031 | 0.003 | −0.060 | − 0.099 | 0.213** | 0.132+ | 0.154* | 0.134* |
Gross Motor | 0.445*** | 0.382*** | 0.404*** | 0.486*** | 0.577*** | 0.365*** | 0.286*** | 0.418*** | 0.332*** |
Personal-Social | 0.021 | 0.104 | 0.072 | 0.067 | 0.043 | 0.296*** | 0.205** | 0.255*** | 0.249*** |
Table 7
Correlations among CREDI, Bayley-III, and the ASQ-3 by wealth status
CREDI | | | | |
Cognitive | 0.792*** | 0.722*** | 0.717*** | 0.781*** | 0.823*** | | | | |
Language | 0.902*** | 0.821*** | 0.867*** | 0.869*** | 0.848*** | | | | |
Motor | 0.846*** | 0.764*** | 0.781*** | 0.869*** | 0.878*** | | | | |
Social-emotional | 0.841*** | 0.768*** | 0.779*** | 0.829*** | 0.869*** | CREDI(n = 235) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.094 | − 0.084 | − 0.162 | 0.089 | − 0.072 | 0.157* | 0.091 | 0.112 | 0.112 |
Communication | 0.357** | 0.389** | 0.306* | 0.298* | 0.329* | 0.409*** | 0.491*** | 0.367*** | 0.398*** |
Fine Motor | −0.317* | − 0.318* | − 0.337* | − 0.207 | −0.154 | − 0.019 | −0.087 | − 0.046 | −0.076 |
Gross Motor | 0.389* | 0.338* | 0.336+ | 0.488*** | 0.594*** | 0.442*** | 0.359*** | 0.475*** | 0.420*** |
Personal-Social | −0.009 | 0.103 | 0.050 | 0.115 | 0.040 | 0.220** | 0.140* | 0.167* | 0.183* |
| Bayley III, 25% richest (n = 79) | | | | |
Cognitive | RC | EC | Fine Motor | Gross Motor | | | | |
CREDI | | | | |
Cognitive | 0.802*** | 0.833*** | 0.841*** | 0.800*** | 0.851*** | | | | |
Language | 0.873*** | 0.905*** | 0.921*** | 0.869*** | 0.835*** | | | | |
Motor | 0.883*** | 0.866*** | 0.882*** | 0.865*** | 0.910*** | | | | |
Social-emotional | 0.845*** | 0.847*** | 0.858*** | 0.833*** | 0.884*** | CREDI(n = 235) |
ASQ-3 | Cognitive | Language | Motor | Social-emotional |
Problem Solving | −0.023 | 0.091 | 0.093 | 0.004 | −0.044 | 0.105* | 0.055 | 0.048 | 0.046 |
Communication | 0.337*** | 0.455*** | 0.521*** | 0.437*** | 0.274** | 0.352*** | 0.470*** | 0.345*** | 0.322*** |
Fine Motor | −0.182 | −0.091 | − 0.056 | − 0.155 | −0.098 | 0.056 | −0.014 | − 0.014 | −0.004 |
Gross Motor | 0.400*** | 0.371*** | 0.412*** | 0.414*** | 0.580*** | 0.430*** | 0.385*** | 0.505*** | 0.435*** |
Personal-Social | −0.067 | 0.033 | 0.065 | 0.002 | 0.070 | 0.110+ | 0.050 | 0.071 | 0.064 |
When the correlations among the three tests were examined by caregiver type and household wealth status, it was found that, in general, regardless of whether the primary caregiver was the mother or the grandmother, or whether the household wealth status was poor or rich, the correlations between the CREDI and Bayley-III were large and statistically significant. The correlations between ASQ-3 and Bayley III were only significant and moderate in the domains of communication and gross motor, and the correlations between the CREDI and ASQ-3 were significant but relatively small. This is shown in Tables
6 and
7.
To complete the analysis, the OLS regression results were reviewed to check whether the three instruments have consistent predictors. All the scores received from the Bayley-III, CREDI, and ASQ-3 were internally standardized before OLS regression.
As shown in
Appendix Table, children from homes with higher stimulation obtained higher Bayley cognitive scores; the older the children, the higher the Bayley cognitive scores. When the same factors were used to predict children’s CREDI cognitive scores, some consistencies with the Bayley-III results were evident. That is, the higher the home stimulation, the higher the CREDI cognitive scores; and the CREDI cognitive scores increased with the child’s age. However, different from the Bayley cognitive, household wealth status was positively related to the CREDI cognitive with a very small effect (indicated by the small coefficient). The child’s gender was negatively related to the CREDI cognitive, that is, girls had higher CREDI scores than boys. Additionally, when the same factors were used to predict children’s ASQ-3 scores, in a similar way to the CREDI and Bayley III, home stimulation was positively related to ASQ-3 “Problem Solving”. Consistent with the CREDI while inconsistent with the Bayley-III, household wealth status was positively related to the ASQ-3. Different from the other two tests, type of primary caregiver was significantly related to the ASQ-3. When the primary caregiver was the mother, the ASQ-3 “Problem Solving” score was higher.
When the same factors were used to predict children’s language scores, it was found that children with higher home stimulation obtained higher Bayley “Receptive Communication” and “Expressive Communication” scores; the older the children, the higher the Bayley scores; girls’ Bayley scores were higher than boys’ s. When the same factors were used to predict children’s CREDI language scores, the results were consistent with the Bayley-III. However, different from the Bayley-III, household wealth status was positively related to CREDI language scores, while the correlation between household wealth status and Bayley III “Receptive communication” and “Expressive communication” was insignificant. When the same factors were used to predict children’s ASQ-3 communication scores, the results were a little different. Just as with the CREDI and Bayley-III, home stimulation was positively related to ASQ-3 “Communication”, and girls obtained higher scores than boys. Consistent with the CREDI while inconsistent with the Bayley III, household wealth status was positively related to ASQ-3. Different from the other two tests, the relationship between age and the ASQ-3 communication score varied with age group. Compared to age 5–11 months, only children aged 18 months and above were higher in ASQ-3 “Communication”.
When the same factors were used to predict children’s motor scores, the results were both consistent as well as inconsistent among the three instruments. Specifically, motor development measured by the three instruments was positively related to children’s age. With respect to the predictor “home stimulation”, the correlation between home stimulation and Bayley motor was insignificant, but home stimulation was positively related to CREDI motor and ASQ motor. The child’s gender was significantly related to CREDI motor rather than Bayley motor and ASQ-3 motor. Whether the child was premature or not was significantly related to the Bayley fine motor results, rather than the CREDI motor and ASQ-3 motor.
In terms of predicting the development of children’s social emotional data, only the ASQ-3 “Personal-Social” and CREDI “Social-Emotional” were assessed because of the lack of a Bayley-III “Social-Emotional” category in our study. The results showed that both the ASQ-3 and CREDI scores were positively related to home stimulation, and girls obtained higher social-emotional scores than boys.
Above all, there was high consistency in predicting ECD status among the three tests in some key predictors, such as home stimulation. That is, higher Bayley scores (except Bayley motor scores), CREDI scores, and ASQ-3 scores were positively related to home stimulation. There were also some consistent results in some individual and family characteristics. For example, the results showed the scores of the three tests indicating language and social emotional development level were higher for girls than boys. Nevertheless, there were inconsistent results in predicting ECD status in some individual and family characteristics. For example, children’s gender was not significantly related to Bayley-III cognitive and motor scores, but was closely related to CREDI scores. Household wealth status was not significantly related to Bayley-III scores, but was positively related to CREDI and ASQ-3 scores indicating cognitive and language development level. With respect to caregiver type, the results of Bayley-III and CREDI scores suggested there was no significant association. However, the results for ASQ-3 scores indicated the caregiver type was connected to the ASQ-3 “Problem- Solving” scores.
In general, the results showed relatively consistent predictors of scores about the level of ECD through different measurements. It can be concluded that as a caregiver-reported, population-level measurement for children’s development, the CREDI is highly consistent with previous widely used instruments in some key predictors (such as home stimulation) concerning the ECD level. Moreover, the CREDI is highly consistent with indirect assessment, namely the ASQ-3, in some individual and family characteristics (such as the children’s gender and household wealth status).
Discussion
From the above information, it can be concluded that the administration time, difficulty, and cost of the CREDI is more advantageous than the Bayley-III, and the internal consistency reliability and validity of the CREDI is also more advantageous than another indirect measurement, that is, the ASQ-3.
First, according to the results shown above, the Bayley scales have very good internal consistency, whereas the ASQ-3 has unacceptably poor internal consistency reliability. In contrast, the Cronbach’s α coefficients of each CREDI subscale were large, despite declining when the sample was divided by age group, which indicates the internal consistency reliability of the CREDI was still good in general. However, it should be noted the CREDI has unacceptably low internal consistency reliability in the motor and social-emotional subscale within age 24–35 months. Second, concurrent validity analysis conducted using the Bayley-III as the criterion indicated generally high concurrent validity of the CREDI. In contrast, the concurrent validity of the ASQ-3 with the Bayley-III scale was low, and the concurrent validity of the two indirect assessments, the CREDI and the ASQ-3, was also low. Third, heterogeneous analysis generally showed that the correlation between the CREDI and the Bayley-III was strong before 18 months but relatively weak at 18–23 months, and was moderate after 24 months. In contrast, the correlation in the domain of communication between ASQ-3 and Bayley-III was better within 12–29 months than other age periods. In terms of the correlation between the CREDI and ASQ-3 by age group, within 5–11 months, only the correlation between the CREDI language subscale and ASQ-3 communication was significant and at a moderate level. After 12 months, the correlations between each domain of the CREDI and the ASQ-3 were significant and moderate. In addition, the heterogeneous analysis showed that there are no big differences in the correlations between the CREDI and Bayley-III by caregiver types and household wealth statuses. Finally, OLS analysis showed that, the CREDI was highly consistent with previous widely-used instruments in some key predictors (such as home stimulation) of ECD level. Furthermore, the CREDI was also highly consistent with the indirect assessment, namely the ASQ-3, in some individual and family characteristics (such as the children’s gender and household wealth status).
Compared with previous studies, the current study examined the reliability and validity of the CREDI long form in China, which hasn’t been assessed before. Moreover, the coverage under 3 years of age is extensive and each age group are included except for 0–5 months. Consistent with previous research, the results in the current study suggested that the CREDI can be used as a useful tool to monitor ECD status in impoverished regions of China at large scale. Multivariate regression results are consistent with previous study that emphasizes the importance of home stimulation activities and family economic status. At present, the development of childcare services under 3 years old in China is lagging behind. Systematic and effective childcare policies and services have not yet been formed, and the absence of supportive systems and the shortage of social services are prominent [
47]. Especially after the implementation of the universal two-child policy, the establishment of the childcare policy system has attracted unprecedented attention. The information about the ECD status at the population level is the basis for the Chinese government in the implementation of childcare policies and services and the development of more effective intervention strategies. The current study makes implications for the use of the CREDI long form to monitor the ECD outcomes in impoverished regions of China. Besides, this study also indicates that the public services and support provided by the society cannot completely replace the function of the family, and the improvement of family members’ parenting practices (reflected by the home stimulation activities) is conducive to effectively improving the early development of children in poor rural areas. Despite its merits, the current study has several limitations. First, there are some limitations on using the motor and social-emotional subscale with children aged 24–35 months. The possible reason needs to be explored further. Second, there was an issue with collection of concurrent gold-standard measures of child development with which to determine the CREDI’s concurrent validity. Concurrent validity with direct observation, that is, using the Bayley-III, was tested only for just over two hundred children. Because of the small sample, which lacked corresponding representation, the conclusion of the current study cannot be generalized to the whole Shaanxi Province or China. The focus on a single geographic context for the sample also limits the generalizability of these results. Besides, the measure invariance is not assessed at this stage. Future studies should include samples from geographically, linguistically, developmentally, and culturally diverse contexts of China. Third, there was a lack of inter-rater reliability for the study coordinators who administered the CREDI. Although the two local study coordinators who administered the items of the screening tool by verbal interview were fluent in Mandarin, possible communication issues or varying levels of comprehension should be considered, particularly given the wide range in education backgrounds of the caregivers. Lacking of the test-retest reliability was also a limitation of the study, which should be done in our future studies. At last, our lack of a “gold standard” metric against which to compare our social-emotional items limits our understanding of their concurrent validity in the current study. Children aged 0–5 months old were not included in the study, which makes it impossible to verify and analyze the reliability and validity of the scale for children aged 0–5 months.