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Measuring Being 'Developmentally on Track': Comparing Direct Assessment and Caregiver Report of Early Childhood Development in Bangladesh, China, India and Myanmar

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Title: Measuring Being 'Developmentally on Track': Comparing Direct Assessment and Caregiver Report of Early Childhood Development in Bangladesh, China, India and Myanmar
Language: English
Authors: Rao, Nirmala (ORCID 0000-0002-5695-3156), Chan, Stephanie W. Y. (ORCID 0000-0001-8779-1164), Su, Yufen (ORCID 0000-0002-9423-5753), Richards, Ben (ORCID 0000-0002-8809-9097), Cappa, Claudia (ORCID 0000-0003-4636-7652), De Castro, E. Filipa, Petrowski, Nicole
Source: Early Education and Development. 2022 33(6):1013-1035.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 23
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Foreign Countries, Child Development, Preschool Children, Age Differences, Mothers, Parent Background, Educational Attainment, Socioeconomic Status, Sustainable Development, Caregiver Attitudes, Evaluation Methods, Parent Attitudes, Scores, Correlation, Cultural Differences
Geographic Terms: Bangladesh, China, India, Burma
DOI: 10.1080/10409289.2021.1928446
ISSN: 1040-9289
1556-6935
Abstract: Assessment of progress toward UN Sustainable Development Goal 4 requires measurement of the proportion of children aged 24 to 59 months developmentally on track in health, learning, and psychosocial well-being (Indicator 4.2.1). UNICEF's methodological work culminated with the development of the Early Childhood Development Index 2030 (ECDI2030) to measure on track status. To compare direct assessment and caregiver report of early child development, a measure aligned to ECDI2030 -- the Early Childhood Development Assessment Scale-Direct Assessment (ECDAS-DA) -- was developed and administered to 510 preschoolers aged 36- to 59-months from Bangladesh, China, India, and Myanmar. Their caregivers completed the Early Childhood Development Assessment Scale-Caregiver Survey (ECDAS-CS) containing items based on the ECDI2030. Research Findings: The two measures correlated with each other and were associated with child age, maternal education, and family wealth. ECDAS-DA showed more variability by child age and provided more fine-grained analyses of emerging developmental competencies than ECDAS-CS. Practice or Policy: Given the dearth of pan-culturally appropriate tools, ECDAS-DA can be deployed in longitudinal studies and impact evaluations in low- and middle-income countries.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1357346
Database: ERIC
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  Value: <anid>AN0158177551;h4j01aug.22;2022Jul28.02:23;v2.2.500</anid> <title id="AN0158177551-1">Measuring Being "Developmentally on Track": Comparing Direct Assessment and Caregiver Report of Early Childhood Development in Bangladesh, China, India and Myanmar </title> <p>Assessment of progress toward UN Sustainable Development Goal 4 requires measurement of the proportion of children aged 24 to 59 months developmentally on track in health, learning, and psychosocial well-being (Indicator 4.2.1). UNICEF's methodological work culminated with the development of the Early Childhood Development Index 2030 (ECDI2030) to measure on track status. To compare direct assessment and caregiver report of early child development, a measure aligned to ECDI2030 – the Early Childhood Development Assessment Scale-Direct Assessment (ECDAS-DA) – was developed and administered to 510 preschoolers aged 36- to 59-months from Bangladesh, China, India, and Myanmar. Their caregivers completed the Early Childhood Development Assessment Scale-Caregiver Survey (ECDAS-CS) containing items based on the ECDI2030. Research Findings: The two measures correlated with each other and were associated with child age, maternal education, and family wealth. ECDAS-DA showed more variability by child age and provided more fine-grained analyses of emerging developmental competencies than ECDAS-CS. Practice or Policy: Given the dearth of pan-culturally appropriate tools, ECDAS-DA can be deployed in longitudinal studies and impact evaluations in low- and middle-income countries.</p> <p>A large body of research has shown that developmental competence in the earliest years of life predicts children's future physical and mental health, school achievement, and adulthood productivity (Campbell et al., [<reflink idref="bib7" id="ref1">7</reflink>]; Reynolds et al., [<reflink idref="bib37" id="ref2">37</reflink>]). These findings have led to the adoption of policies and investment in programs to support the development of young children worldwide. Further, global recognition of the importance of the early childhood period for human and societal development is reflected in the inclusion of a target focused on Early Childhood Development (ECD) in the United Nations Sustainable Development Goals (SDGs). Target 4.2 of the SDGs states that: <emph>by 2030, ensure all girls and boys have access to quality early childhood development, care and pre-primary education so that they are ready for primary education</emph>. The target has two indicators: (a) the proportion of children aged 24–59 months who are developmentally on track in health, learning, and psychosocial well-being, by sex (Indicator 4.2.1); and (b) participation rates in organized learning one year before the official primary school entry age (Indicator 4.2.2) (United Nations, [<reflink idref="bib51" id="ref3">51</reflink>]). This study illustrates the conceptual and methodological issues in measuring ECD by examining the comparability of direct child assessments and caregiver report of child outcomes with respect to the SDG Indicator 4.2.1 in Bangladesh, China, India, and Myanmar.</p> <hd id="AN0158177551-2">Caregiver Report versus Direct Assessment of Early Child Development</hd> <p>Adequate measurement ensures a viable path to accountability and progress. Regardless of whether direct assessment or caregiver report is used, the measurement of learning and psychosocial well-being in early childhood is challenging, as it must consider culture, contextual and linguistic variations. Assessment tools need to be not only culturally appropriate in terms of administration method and materials but also reflect the values and skills important within a particular cultural or national framework (Rao et al., [<reflink idref="bib34" id="ref4">34</reflink>]). The development of assessment measures that are both culturally appropriate and permit comparisons across different groups of children within or across countries pose significant challenges (Rao, Mirpuri, Sincovich, & Brinkman, [<reflink idref="bib31" id="ref5">31</reflink>]). For example, the accurate assessment of grapheme recognition in different countries is not simply a matter of changing alphabets to characters or akshara. Items need to be sensitive to widely varying exposure to early learning opportunities, cultural beliefs about early learning, parental expectations about what young children should be able to do and the emphasis on play versus academic skills in the early childhood education curriculum.</p> <p>In measuring ECD, researchers have acknowledged the unique contributions of both caregivers and trained assessors in providing information about children's behaviors (Achenbach et al., [<reflink idref="bib1" id="ref6">1</reflink>]; Renk, [<reflink idref="bib36" id="ref7">36</reflink>]), claiming that information gathered from different perspectives is necessary to generate a complete picture of an individual child. There is also considerable debate over differences between caregiver report and direct assessment measures of child development, especially when the objective of the assessment is to obtain population level information (a snapshot of how children are doing overall) rather than an individual child screening or measurement of abilities (identify developmental delay and diagnose individual children).</p> <p>Comprehensive development tests that include direct assessment of child development, such as the Bayley Scales, are often used as a gold standard to evaluate the validity of parent or teacher reports of ECD. For direct assessment, assessors often have considerable knowledge about timetables and age norms to score children's ability, which enables them to give impartial ratings based on their professional judgment and experiences with a broader cross-section of children (Eiser & Morse, [<reflink idref="bib13" id="ref8">13</reflink>]). However, direct assessment is very resource intensive, rendering it difficult to applying in large-scale national studies with representative samples. The deployment of tools that rely on direct assessment of children also poses additional issues as one needs to ensure not only technical equivalence but deal with the dearth of appropriately qualified child assessors in low- and middle-income countries. Hence, there is a need to engage in a high degree of training to ensure assessors who are used to working with children follow standardized administration procedures. There are also concerns whether test conditions during measurement at scale can be fully standardized as to ensure accurate measurement of children's true abilities (Bracken, [<reflink idref="bib6" id="ref9">6</reflink>]).</p> <p>Caregiver report (or parent report) measures, on the other hand, are typically cheaper and easier to implement. Caregivers interact with children in a variety of contexts and are able to provide information about child behaviors that are not typically observed in standardized assessment situations. Researchers have investigated the consistency between caregiver report and direct assessment of children's specific developmental skills, such as language ability and social emotional functioning. Parent ratings of children's language ability, including general language ability (e.g., milestones of child language, general language ability) and specific language skills (e.g., productive vocabulary), were found to be significantly correlated with direct assessment or professional measuring with language sample data (Bedore et al., [<reflink idref="bib4" id="ref10">4</reflink>]; Ebert, [<reflink idref="bib12" id="ref11">12</reflink>]; Sachse & von Suchodoletz, [<reflink idref="bib39" id="ref12">39</reflink>]; Weber et al., [<reflink idref="bib53" id="ref13">53</reflink>]). This consistency between caregiver and direct assessment was found in the ratings for infants and toddlers (Sachse & von Suchodoletz, [<reflink idref="bib39" id="ref14">39</reflink>]; Weber et al., [<reflink idref="bib53" id="ref15">53</reflink>]), and preschool-age and school-age children (Ebert, [<reflink idref="bib12" id="ref16">12</reflink>]). Moreover, although the correlation coefficients vary across the constructs being rated, the association between caregiver rating and direct assessment was usually very high. For example, parental estimates of toddlers' productive vocabulary were strongly correlated with (<emph>r</emph> >.80) direct assessment of word or sentence production (Sachse & von Suchodoletz, [<reflink idref="bib39" id="ref17">39</reflink>]). In the meanwhile, researchers raised the concern that caregiver rating was usually formed by making comparative judgment with children's peers and siblings that was vulnerable to the influence of memory distortion, stereotypes, expectations for children, and parents' mental health (Stifter et al., [<reflink idref="bib41" id="ref18">41</reflink>]). Others also suggested that caregivers may be more competent to assess certain domains such as language development and fine motor skills (Ebert, [<reflink idref="bib12" id="ref19">12</reflink>]; Sachse & von Suchodoletz, [<reflink idref="bib39" id="ref20">39</reflink>]; Weber et al., [<reflink idref="bib53" id="ref21">53</reflink>]) relative to other areas such as social skills (Heyman et al., [<reflink idref="bib21" id="ref22">21</reflink>]).</p> <p>The consistency between caregiver rating and direct assessment may be affected by caregiver characteristics as well. Although some researchers suggested that parents were reliable informants of children's developmental functioning regardless of their educational levels (Glascoe, [<reflink idref="bib18" id="ref23">18</reflink>]; Guiberson et al., [<reflink idref="bib19" id="ref24">19</reflink>]; Sachse & von Suchodoletz, [<reflink idref="bib39" id="ref25">39</reflink>]), others believed that not all parents were capable of rating their children's developmental competencies accurately, especially those who were less educated and experiencing mental health problems or cognitive disabilities (Squires et al., [<reflink idref="bib40" id="ref26">40</reflink>]). This is not surprising as better educated parents might be more able to comprehend the questions in rating scales and have consistent expectation with teachers (Dinnebeil et al., [<reflink idref="bib11" id="ref27">11</reflink>]). It was suggested that parents should at least have seventh- to eighth-grade education to complete written scales (Ireton & Glascoe, [<reflink idref="bib22" id="ref28">22</reflink>]).</p> <p>Given the number of direct assessments that would be needed to have valid information about the percentage of children who are developmentally on track in high population countries – for example, in the case of monitoring country's progress against the SDG Indicator 4.2.1 – establishing psychometrically robust caregiver report measures of children's developmental status, is a necessary endeavor. In addition, given the intrinsic challenges of population level measurement, comprehensive administration protocols are also required to minimize measurement error and biases and ensure that high quality and valid data can be generated. Despite the concerns about the accuracy of caregiver reports – especially in the context of evaluation studies (Fernald & Pitchik, [<reflink idref="bib14" id="ref29">14</reflink>]), adult reports are still the preferred source of information about psychosocial development, even in the context of full development tests such as the Bayley Scales (Bayley, [<reflink idref="bib3" id="ref30">3</reflink>]).</p> <hd id="AN0158177551-3">Assessing Progress Toward Sustainable Development Goal Target 4.2</hd> <p>Following United Nation's call for the SDGs, there have been increased interests over measuring child development outcomes accurately. Among the 17 SDGs, there are 44 child-related indicators; we need high-quality data to monitor progress toward all the indicators. A key challenge related to the assessment of SDG Target 4.2 has been the lack of a single measure, appropriate for application across diverse cultures and contexts, to measure child development outcomes. The Inter-agency and Expert Group on SDG indicators had initially classified SDG Target indicator 4.2.1 as Tier 3, deeming that there was no internationally established methodology or standard to measure the indicator (United Nations, [<reflink idref="bib50" id="ref31">50</reflink>]). However, in March 2019, SDG Target indicator 4.2.1 for children aged 24–59 months was reclassified from Tier 3 to Tier 2, meaning that internationally established methodology and standards for the indicator are available, but the data are not regularly produced by countries (United Nations, [<reflink idref="bib50" id="ref32">50</reflink>]).</p> <p>Specifically designed to collect globally comparable information on children's development, the UNICEF'S Early Childhood Development Index (ECDI), a 10-item measure administered to caregivers of children aged 36 to 59 months, has been used in some 80 countries through the Multiple Indicator Cluster Surveys (UNICEF, [<reflink idref="bib44" id="ref33">44</reflink>]) and other national household surveys over the past decade (McCoy et al., [<reflink idref="bib26" id="ref34">26</reflink>]). UNICEF is the custodian agency for SDG Target Indicator 4.2.1 and the ECDI was proposed as the measure for tracking progress against this target (UNICEF, [<reflink idref="bib47" id="ref35">47</reflink>]). The SDG Target Indicator 4.2.1 focuses on the development of children aged 24 to 59 months in three domains – learning, psychosocial well-being, and health; however, the 10-item ECDI introduced in 2010 did not include items tapping health development and items capturing development for the specific age range (Cappa et al., [<reflink idref="bib8" id="ref36">8</reflink>]). To align more closely with the formulation of the SDG indicator on ECD, UNICEF led a process of methodological work to develop a new measure, building on the 10-item ECDI, to determine the percentage of children aged 24 to 59 months who are developmentally on track in the areas of learning, psychosocial well-being, and health (Cappa et al., [<reflink idref="bib8" id="ref37">8</reflink>]; UNICEF, [<reflink idref="bib45" id="ref38">45</reflink>], [<reflink idref="bib46" id="ref39">46</reflink>], [<reflink idref="bib47" id="ref40">47</reflink>]).</p> <p>From 2015 onwards, UNICEF has led a rigorous process in developing the Early Childhood Development Index 2030 (ECDI2030). The process included identifying a pool of items for the ECDI2030 through qualitative and quantitative methods, evaluating items by international experts and statisticians, and validating the scale using representative samples from Mexico and Palestine and psychometric analyses using data from a further 33 countries (Cappa et al., [<reflink idref="bib8" id="ref41">8</reflink>]; UNICEF, [<reflink idref="bib47" id="ref42">47</reflink>]). Similar to the 10-item ECDI measure, the ECDI2030 is administered as a caregiver report measure and caregivers are asked about their children's behaviors and whether their children have acquired specific skills and knowledge. The final measure consists of 20 items covering three domains and 12 sub-domains: learning (expressive language, numeracy, literacy, pre-writing, executive functioning), health (self-care, gross motor, fine motor), and psychosocial well-being (emotional skills, social skills, mental health: externalizing and internalizing) (UNICEF, [<reflink idref="bib47" id="ref43">47</reflink>]).</p> <p>In addition to caregiver reports, there have also been efforts to develop ECD measures for young children across contexts through direct assessments. The East Asia-Pacific Early Child Development Scales (EAP-ECDS) is a culturally-appropriate measurement tool which has been used to assess the holistic developmental progress of representative samples of children (3 to 5 years) in seven East Asia-Pacific countries (Rao et al., [<reflink idref="bib33" id="ref44">33</reflink>], [<reflink idref="bib34" id="ref45">34</reflink>]). Other scales that rely on direct assessments of children include the Regional Project on Child Development Indicators (PRIDI) for children 24 to 59 months (Verdisco et al., [<reflink idref="bib52" id="ref46">52</reflink>]); the International Development and Early Learning Assessment (IDELA) for children from 3.5 to 6 years (Pisani et al., [<reflink idref="bib28" id="ref47">28</reflink>]); and the Measurement of Development and Early Learning (MODEL) for children from 4 to 6 years (UNESCO, [<reflink idref="bib42" id="ref48">42</reflink>]). All of the above-mentioned tools enable population-level monitoring of ECD, albeit with different intentions and applications. Efforts have been exerted to ensure that these measurements are sensitive to the contexts of low- and middle-income countries where they have been deployed. While they address a lacuna and enable population-level monitoring of ECD that is vital to inform educational and social policy, none of the above-mentioned tools is suitable for global monitoring of SDG Target indicator 4.2.1 because the domains and items tested in the measure and age of children do not align entirely with the interest of the SDG indicator.</p> <hd id="AN0158177551-4">The Current Study</hd> <p>Against this background, the primary objective of this study was to compare the outcomes of the caregiver report measure with direct assessment measure of ECD with respect to the SDG Target Indicator 4.2.1. In order to study the comparability between the two modes of measurement, we developed two instruments to measure ECD: (a) a direct assessment measure – the Early Childhood Development Assessment Scale - Direct Assessment (ECDAS-DA, 28 items) (Rao, Chan, Lee, & Becher, [<reflink idref="bib30" id="ref49">30</reflink>]), and (b) a caregiver-based tool – the Early Childhood Development Assessment Scale - Caregiver Survey (ECDAS-CS, 50 items) (Rao, Chan, Lee, & Becher, [<reflink idref="bib29" id="ref50">29</reflink>]). Since the focus of the study was on measurement against the scope of SDG Target Indicator 4.2.1, both scales were developed based on an initial pool of 50 items that were considered for inclusion during the development of the ECDI2030, and each scale included 18 items that align to the final version of the ECDI2030 (UNICEF, [<reflink idref="bib47" id="ref51">47</reflink>]).</p> <p>As the two measures (ECDAS-DA and ECDAS-CS) were newly developed, we first examined the psychometric properties of the measures in this study. This includes examining the reliability of the ECDAS-DA and the ECDAS-CS among our sample; and analyzing the criterion validity of the ECDAS-DA and the ECDAS-CS by examining associations with concepts with strong relations to child development – child age, maternal education, household wealth, child height, and child weight. Given the exploratory nature of our study, we did not make any specific predictions regarding country differences. However, based on a large body of literature, we expected child age, maternal education and family wealth to be significantly related to developmental competence (Jeong et al., [<reflink idref="bib23" id="ref52">23</reflink>]; Lu et al., [<reflink idref="bib25" id="ref53">25</reflink>]; Richards et al., [<reflink idref="bib38" id="ref54">38</reflink>]).</p> <p>Our study focused on children from four countries – Bangladesh, China, India, and Myanmar. Notably, these four countries account for about 34% of the world's children below five years. The number of children who are developmentally on track in these countries clearly influences global statistics on progress toward SDG 4.2. The four countries are in an economic corridor that is part of China's Belt and Road Initiative (McKinsey, [<reflink idref="bib27" id="ref55">27</reflink>]). China wishes to establish an economic land belt through Central Asia, West Asia, the Middle East and Europe and a maritime route that links China to the Mediterranean. The focus is on regional infrastructure, trade and collaboration with relevant countries. In a similar vein, international organizations such as UNESCO, UNICEF and OECD have taken initiatives for countries to work together and learn from each other to enhance the quality of their ECE, partly because of the link between problems arising in early childhood and the long-term economic costs of addressing these problems. Hence, the choice of our countries was motivated by their sharing at least one border and the sheer size of their population under five years.</p> <p>Building on the psychometric properties of the two instruments, we then examined the association between the caregiver report (ECDAS-CS) and direct assessment (ECDAS-DA), two measures of ECD of children from Bangladesh, China, India, and Myanmar. Both direct assessment and caregiver-report based measures of ECD present advantages and limitations, especially in the context of measurement at scale (Fernald et al., [<reflink idref="bib15" id="ref56">15</reflink>]). Using a direct assessment measure may potentially offer insights into children's development that complement caregiver report measure. Although the study is exploratory in nature, based on studies that generally found agreement across direct assessment and caregiver report on certain developmental domains, we hypothesized that the overall composite ECDAS-CS and ECDAS-DA scores will be positively associated with each other. Further, the simultaneous application of the ECDAS-DA and the ECDAS-CS can contribute toward the wider knowledge base on similarities and differences between direct assessment and caregiver report measures of ECD.</p> <hd id="AN0158177551-5">Method</hd> <p></p> <hd id="AN0158177551-6">Participants</hd> <p>Our full sample included 956 children (476 girls) aged 36 to 71 months. We have excluded children older than 59 months in our analyses because they were beyond the age range of the interest of the SDG Target indicator 4.2.1. In light of the relation between participation in ECE and developmental competence (Rao, Richards, Sun, Weber, & Sincovich, [<reflink idref="bib32" id="ref57">32</reflink>]) and the high rate of ECE participation in our full sample, analyses in this paper focused on ECE attenders. Statistical analyses therefore only included 510 children, ranging in age from 36 to 59 months from Bangladesh (<emph>n</emph> = 145), China (<emph>n</emph> = 156), India (<emph>n</emph> = 156), and Myanmar (<emph>n</emph> = 53) who attended ECE and their primary caregivers (Table 1). Caregivers in the sample included 77% mothers, 15% fathers, and 6% other caregiving relatives (remaining 2% were missing data).</p> <p>Table 1. Composition of the sample.</p> <p> <ephtml> <table><thead><tr><td /><td>Urban</td><td /><td>Rural</td><td /></tr><tr><td /><td>36 to 47 months</td><td>48 to 59 months</td><td /><td>36 to 47 months</td><td>48 to 59 months</td><td /></tr><tr><td /><td>Girls</td><td>Boys</td><td>Girls</td><td>Boys</td><td /><td>Girls</td><td>Boys</td><td>Girls</td><td>Boys</td><td>Total</td></tr></thead><tbody><tr><td>Bangladesh</td><td>22</td><td>19</td><td>19</td><td>21</td><td /><td>13</td><td>17</td><td>18</td><td>16</td><td>145</td></tr><tr><td>China</td><td>20</td><td>20</td><td>18</td><td>20</td><td /><td>18</td><td>20</td><td>22</td><td>18</td><td>156</td></tr><tr><td>India</td><td>20</td><td>19</td><td>18</td><td>20</td><td /><td>16</td><td>23</td><td>21</td><td>19</td><td>156</td></tr><tr><td>Myanmar</td><td>8</td><td>12</td><td>9</td><td>10</td><td /><td>2</td><td>4</td><td>6</td><td>2</td><td>53</td></tr></tbody></table> </ephtml> </p> <hd id="AN0158177551-7">Sampling and Recruitment Procedures</hd> <p>The full sample was stratified by urbanicity, with the urban children drawn from a major city in each country (Dhaka, Beijing, Delhi, and Yangon) and the other children from a "rural" area outside each city, as defined by the national census. In Bangladesh, China and India, university-based collaborators identified early childhood centers that served children from low- to middle-class backgrounds in urban and rural areas. The sample was designed purposively to capture sociodemographic diversity, including differences by urbanicity, age, and gender. Children with special needs were excluded and only typically developing children were in the sample. Ethical approval for the study was obtained from the Human Research Ethics Committee of the University of Hong Kong and written informed consent was obtained from all caregivers prior to data collection.</p> <p>Our study was exploratory in nature and we note that our sample was somewhat privileged in terms of ECE attendance and maternal education. For example, in 2017, Gross Enrollment Ratios (GERs) for pre-primary education were 41.74% in Bangladesh; 84.8% in China; 60.65% in India; and 9.78% in Myanmar (UNESCO Institute for Statistics, [<reflink idref="bib43" id="ref58">43</reflink>]). We need to acknowledge that these data may be inaccurate as not all ECE programs are registered with the authorities in Bangladesh and India. Hence, participation in ECE may be underestimated in national statistics if data are based on government reports rather than household surveys. Regarding maternal education, as Supplementary Figure 1 shows, our sample demonstrated higher levels of maternal education than the general population in the countries concerned.</p> <hd id="AN0158177551-8">Measures</hd> <p></p> <hd id="AN0158177551-9">Early Childhood Development Assessment Scale – Direct Assessment (ECDAS-DA)</hd> <p>The development of ECDAS-DA was undertaken in two phases. As noted earlier, in Phase 1, we developed direct assessment items to align with the pool of items considered for the ECDI2030. Where applicable, items were adapted from the EAP-ECDS (Rao et al., [<reflink idref="bib33" id="ref59">33</reflink>], [<reflink idref="bib34" id="ref60">34</reflink>]). The ECDAS-DA (28 items) excludes two items from the ECDI2030 because they are not amenable to direct assessment procedures. These include, "How often does <emph>(name)</emph> seem to be very sad or depressed?" and "Does (<emph>name</emph>) ask about familiar people other than parents when they are not there?" Another two items from the ECDI2030 (ECD4 [fasten and unfasten buttons without help] and ECD7 [speaks with sentences of 5 or more words that go together], see Appendix A) from the health and learning domains, respectively, were not included in our 28-item measure. This is because we did not know exactly which items from the 50-item testing pool would be in the final version of the ECDI2030 when we developed the tool. We also excluded one item (ECD5 [says 10 or more words]) that shared the score of an object naming task with another item (ECD9 [naming objects consistently]) to avoid double counting. For ECD13, that tapped whether children could give a correct number of objects when asked, the ECDAS-DA scored for children's ability to give five objects instead of three. In some psychosocial well-being items, we provided a context and asked children what they would do if they were the child in the picture shown. For example, for the item on offering help (ECD17), children were shown a picture of a woman who dropped some fruits in the market, and were asked what they would do if he/she was the child in picture standing nearby.</p> <p>As a result, a total of 15 items were common across the ECDI2030, ECDAS-CS and ECDAS-DA (see Appendix A for item list). The 15 items cover three domains: The learning domain (9 items) includes five subdomains of expressive language, literacy, numeracy, pre-writing, and executive functioning; the psychosocial well-being domain (3 items) divides into the subdomains of social skills, emotional skills, and externalizing; and the health domain (3 items) forms three subdomains of self-care and gross motor. These domains represent several different child competencies but, in alignment with UNICEF's approach to constructing a single summative score on the ECDI2030, we also used one single ECDAS-DA score, rather than breaking the tool into domains. Among the 15 items, 14 ECDI2030 items require a Yes/No response. The only exception was the item on kicking, biting, or hitting other children or adults (ECD20) which is scored on a 4-point scale. All 15 ECDAS-CS items required a Yes/No response and each item was scored 0 or 1. On the other hand, the ECDAS-DA has multiple sub-items to capture a range of capability for each indicator, and all items were scaled from 0 to 1 regardless of the number of sub-items. For example, scoring for the item, <emph>writes own name</emph> (ECD11) had three sub-items as follows: One point was awarded for writing a letter/symbol, another for writing about half of the name, and the third point for writing first or family name in full. This means that children who were only able to write half of the name would be scored.66 out of 1 in the item, but would be scored as 0 in the ECDAS-CS because the child was not yet able to write his or her name.</p> <p>In Phase 2, we adapted the measure for each country. The measure was originally developed in English and then was translated into Bengali, Chinese, Hindi, and Myanmar using standard back-translation procedures. After back-translation, items were reviewed by a panel of researchers and educators in the field of ECE in each country. Recommendations made by the panel were followed and items were modified to make them contextually appropriate. In each country, pilot studies were conducted with a 3-year-old boy and a 5-year-old girl as our prior experience suggested that this would provide an estimation of the range of competence of 3- to 5-year-olds in a country. The review and pilot studies resulted in modification of the stimuli and instructions. For example, the alphabets tapping children's knowledge of letters were changed to reflect the local language and ECE curriculum (see Appendix B). Modifications were made to some items with pictures based on the local context to ensure that the items provided a fair assessment of children's competence. For example, the ECDAS-DA items for ECDI2030 item 9 is shown in Appendix B, the objects cup, bucket, pencil, chair in Bangladesh, China, India and Myanmar are common, respectively and the towel/bed/television varies across countries.</p> <hd id="AN0158177551-10">Early Childhood Development Assessment Scale – Caregiver Survey (ECDAS-CS)</hd> <p>Caregivers provided sociodemographic information and responded to 50 questions on child development outcomes. The format resembled that of the ECDI2030 which requires caregivers to indicate whether their children have acquired certain behaviors, skills and knowledge. As noted earlier, the caregiver survey included 18 items that are highly similar to those in the ECDI2030. The two ECDI2030 items that were not available in the ECDAS-CS in our caregiver survey were ECD4 (Fastens and unfastens buttons without help) and ECD6 (speaks using sentences of 3 or more words that go together) (see Appendix A). Since we were interested in measuring child development according to the expectations of the SDG indicator 4.2.1, only the 18 items that overlapped with the final version of the ECDI2030 were subject to statistical analyses.</p> <hd id="AN0158177551-11">Sociodemographic Variables</hd> <p>Caregivers also reported on a number of sociodemographic variables in a survey. Child age was measured in months. Maternal education was measured based on the mother's highest qualification which was categorized into five levels (no formal education, preschool, primary school education, secondary school, and some tertiary education). For each country, a continuous wealth index variable was calculated from questions on household assets, such as ownership of a mobile phone, television, computer, or tablet, and using weights taken from the first component of a principal components analysis, following the technique outlined by Filmer and Pritchett ([<reflink idref="bib16" id="ref61">16</reflink>]). Information on ECE experience was also obtained from the caregiver survey. A binary variable indicating urban or rural residence was created based on the classification of the local area from official census in each country.</p> <hd id="AN0158177551-12">Procedure</hd> <p>Assessors, who had qualifications and experience in ECE, attended a two-day training workshop on the administration of the ECDAS-DA and associated caregiver survey and on measuring height and weight. Assessors had to assign the same score as a gold standard (an expert in the scale) to at least 85% of the items on the ECDAS-DA prior to data collection. Data on children's height and weight were also collected using the same type of weighing scale and measuring tape, following procedures of the WHO Multicentre Growth Reference Study (De Onis et al., [<reflink idref="bib10" id="ref62">10</reflink>]). The height and weight scores were then transformed into height-for-age and weight-for-age <emph>z</emph> scores. During data collection, inter-assessor consistency in administration and scoring was assessed at regular intervals by comparing the assessors' scores with the gold standard of the local team.</p> <p>Children were individually administered the ECDAS-DA, between May and October 2018, by researchers who had experience in ECE. Caregivers were also interviewed individually in Bangladesh, Myanmar, and India. Given the relatively high literacy rates in the sample in China, caregivers completed a paper-and-pencil version of the survey. To ensure comparability of the two administration methods, we administered the caregiver survey using both face-to-face interview and the paper-and-pencil version to six caregivers in China with order counterbalanced before data collection. The responses were highly consistent across the two versions.</p> <hd id="AN0158177551-13">Analysis Plan</hd> <p>All analyses were conducted using Stata 13.1. Descriptive statistics were calculated for key variables – ECDAS-DA, ECDAS-CS, age, sex, wealth index, maternal education, urban-rural residence, height, and weight – for the sample overall and by individual country. Cronbach's alphas were calculated for ECDAS-DA and ECDAS-CS. Next, ECDAS-DA and ECDAS-CS scores were standardized for each country individually such that in each country the mean score was 0 and the standard deviation was 1. A series of OLS regressions was used to examine associations between the country-specific standardized ECDAS-DA scores (outcome variable) and several predictors in separate regressions, controlling for age, sex, and country, and adjusting standard errors for eight clusters (rural and urban in the four countries) within the sample. This process was replicated for each country to provide country-specific estimates of associations between each predictor and country-standardized ECDAS-DA score. Next, the same procedure was used, with the standardized ECDAS-CS score as the outcome variable.</p> <p>In the next step, Pearson correlation coefficients were calculated to index bivariate relations between each of the child outcome variables and predictors. Correlations between ECDAS-DA and ECDAS-CS scores were also calculated for each country individually. To examine whether the strength of associations between country-standardized ECDAS-DA and ECDAS-CS scores varied by maternal education, we ran an OLS regression with ECDAS-DA score as the outcome variable and an interaction term between the ECDAS-CS score and maternal education as the predictor. Three levels of maternal education were used: primary or lower; secondary; and higher. The regression controlled for age and country, and adjusted for eight sample clusters.</p> <p>The determination of whether a child is developmentally on track is based on his or her age and the number of developmental milestones (ECDI2030 items scored 1) that he/she has achieved (UNICEF, [<reflink idref="bib47" id="ref63">47</reflink>]). To be considered developmentally on-track children aged 24 to 29 months have to achieve at least 7 milestones; children aged 30 to 35 months have to achieve at least 9 milestones; children aged 36 to 41 months have to achieve at least 11 milestones; children aged 42 to 47 months have to achieve at least 13 milestones; children aged 48 to 59 months have to achieve at least 15 milestones (UNICEF, [<reflink idref="bib47" id="ref64">47</reflink>]).</p> <p>Recall that we did not administer all 20 ECDI2030 items. Hence, we did not use the above-mentioned cutoffs. Instead, to determine whether children in our sample were developmentally on track, we compared children's scores to those of their same-age peers (across all countries) by calculating the residuals from a regression model predicting the ECDAS-DA and ECDAS-CS scores from age and age squared. Using ECDAS-DA, three different indicators of being "developmentally on track" were created, measuring the proportion of children scored (i) not more than 2 <emph>SD</emph>s below the mean age-adjusted ECDAS-DA score, (ii) not more than 1.5 <emph>SD</emph>s below the mean age-adjusted ECDAS-DA score, and (iii) not more than 1 <emph>SD</emph> below the mean age-adjusted ECDAS-DA score. For ECDAS-CS, three indicators of being "developmentally on track" were developed using the same method. Therefore, we obtain the percentages of children that would be considered developmentally on track indicated by different criteria and different measures.</p> <p>Missing values were found for maternal education (<emph>n</emph> = 8), wealth index (<emph>n</emph> = 2), child height (<emph>n</emph> = 3), and child weight (<emph>n</emph> = 1). Values were imputed using multiple imputations with chained equations to calculate 25 imputations from linear and ordered logistic regressions. No other variables had missing values.</p> <hd id="AN0158177551-14">Results</hd> <p>Table 2 shows descriptive statistics for key variables. Raw ECDAS-DA scores were highest in the Bangladesh sample and lowest in the Indian sample. ECDAS-CS scores were highest in the Chinese sample and lowest in the Indian sample. The Chinese sample had the highest proportion of mothers with higher education, while the Indian sample had the lowest. Indicated by the proportion of children whose height-for-age <emph>z</emph> score was more than 2 <emph>SD</emph>s below the median age- and sex-specific value of the WHO Child Growth Standards (World Health Organization, [<reflink idref="bib54" id="ref65">54</reflink>]), the prevalence of stunting was 9.7% in Bangladesh, 0.6% in China, 18.6% in India, and 13.2% in Myanmar.</p> <p>Table 2. <emph>Descriptive statistics for key variables</emph> (for children aged 36–59 months that attend preschools).</p> <p> <ephtml> <table><thead><tr><td /><td>Overall sample</td><td /><td>Bangladesh</td><td /><td>China</td><td /><td>India</td><td /><td>Myanmar</td></tr><tr><td /><td><italic>M</italic> (<italic>SD</italic>)</td><td>Range</td><td /><td><italic>M</italic> (<italic>SD</italic>)</td><td>Range</td><td /><td><italic>M</italic> (<italic>SD</italic>)</td><td>Range</td><td /><td><italic>M</italic> (<italic>SD</italic>)</td><td>Range</td><td /><td><italic>M</italic> (<italic>SD</italic>)</td><td>Range</td></tr></thead><tbody><tr><td>Sample size <italic>n</italic> (%)</td><td>510</td><td /><td>145 (28.43)</td><td /><td>156 (30.59)</td><td /><td>156 (30.59)</td><td /><td>53 (10.39)</td></tr><tr><td>ECDAS-DA</td><td>9.64 (2.76)</td><td>1.20–15</td><td /><td>10.43 (2.92)</td><td>3.60–15</td><td /><td>10.29 (2.14)</td><td>4.70–14.45</td><td /><td>8.44 (2.63)</td><td>1.20–14.67</td><td /><td>9.14 (3.02)</td><td>1.20–14.13</td></tr><tr><td>ECDAS-CS</td><td>14.74 (2.19)</td><td>7.50–18</td><td /><td>15.15 (2.23)</td><td>8.50–18</td><td /><td>15.43 (1.65)</td><td>8.50–18</td><td /><td>13.90 (2.37)</td><td>7.50–18</td><td /><td>14.02 (1.89)</td><td>9–17</td></tr><tr><td>Child age (months)</td><td>48.98 (6.50)</td><td>36–59.97</td><td /><td>49.11 (6.61)</td><td>36–59.77</td><td /><td>50.31 (5.49)</td><td>40.30–59.87</td><td /><td>47.77 (6.82)</td><td>36.43–59.97</td><td /><td>48.23 (7.31)</td><td>36.57–59.27</td></tr><tr><td>Child sex</td><td>0.49 (0.50)</td><td>0–1</td><td /><td>0.50 (0.50)</td><td>0–1</td><td /><td>0.49 (0.50)</td><td>0–1</td><td /><td>0.48 (0.50)</td><td>0–1</td><td /><td>0.47 (0.50)</td><td>0–1</td></tr><tr><td>Height (cm)</td><td>103.77 (8.31)</td><td>81–150</td><td /><td>104.39 (8.85)</td><td>81–133.50</td><td /><td>106.63 (5.53)</td><td>93–120</td><td /><td>101.11 (9.52)</td><td>83–150</td><td /><td>101.54 (6.80)</td><td>86–116</td></tr><tr><td>Weight (kg)</td><td>16.08 (4.03)</td><td>8.60–39</td><td /><td>17.07 (4.63)</td><td>10.40–36</td><td /><td>17.99 (2.95)</td><td>12.55–31.90</td><td /><td>13.57 (2.54)</td><td>8.60–23.20</td><td /><td>15.16 (4.61)</td><td>9–39</td></tr><tr><td>Maternal education <italic>n</italic> (%)</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>No formal education</td><td>28 (5.63)</td><td /><td /><td>10 (7.14)</td><td /><td /><td>1 (0.66)</td><td /><td /><td>16 (10.46)</td><td /><td /><td>1 (1.89)</td></tr><tr><td>Preschool</td><td>5 (1.01)</td><td /><td /><td>5 (3.57)</td><td /><td /><td>0</td><td /><td /><td>0</td><td /><td /><td>0</td></tr><tr><td>Primary</td><td>60 (12.07)</td><td /><td /><td>25 (17.86)</td><td /><td /><td>2 (1.32)</td><td /><td /><td>29 (18.95)</td><td /><td /><td>4 (7.55)</td></tr><tr><td>Secondary</td><td>139 (27.97)</td><td /><td /><td>35 (25.00)</td><td /><td /><td>34 (22.52)</td><td /><td /><td>46 (30.07)</td><td /><td /><td>24 (45.28)</td></tr><tr><td>Higher</td><td>265 (53.32)</td><td /><td /><td>65 (46.43)</td><td /><td /><td>114 (75.50)</td><td /><td /><td>62 (40.52)</td><td /><td /><td>24 (45.28)</td></tr><tr><td>Wealth index</td><td>0.05 (1.00)</td><td>−2.94–2.98</td><td /><td>0.13 (1.04)</td><td>−2.23–2.94</td><td /><td>−0.01 (0.94)</td><td>−2.93–2.27</td><td /><td>0.04 (1.01)</td><td>−2.62–2.02</td><td /><td>0.03 (1.04)</td><td>−2.10–2.98</td></tr><tr><td>Urbanicity</td><td>0.54 (0.50)</td><td>0–1</td><td /><td>0.56 (0.50)</td><td>0–1</td><td /><td>0.50 (0.50)</td><td>0–1</td><td /><td>0.49 (0.50)</td><td>0–1</td><td /><td>0.74 (0.45)</td><td>0–1</td></tr></tbody></table> </ephtml> </p> <p>1 ECDAS-DA and ECDAS-CS are raw scores.</p> <p>We looked at the correlations of ECDAS-DA with the 18-item (all ECDAS-CS items) and 15-item (15 items common across ECDAS-DA and ECDAS-CS) versions of ECDAS-CS separately. Since correlations of the 18-item ECDAS-CS (<emph>r</emph> =.52, <emph>p</emph> <.001; for individual countries: <emph>r</emph>s =.34-.55, <emph>p</emph> <.001) and 15-item ECDAS-CS versions (<emph>r</emph> =.53, <emph>p</emph> <.001; for individual countries: <emph>r</emph>s =.34-.57, <emph>p</emph> <.001) with the ECDAS-DA were similar, the subsequent analyses of ECDAS-CS were conducted using the 18-item version because it aligns more closely with the ECDI2030 than the 15-item version. Examination of scale reliability showed that Cronbach's alphas for the ECDAS-DA and the ECDAS-CS, were.75 and.62, respectively. Table 3 shows Pearson correlations between key variables. ECDAS-DA scores were positively and significantly (<emph>p</emph>s <.05) correlated with age (<emph>r</emph> =.44), wealth (<emph>r</emph> =.14), maternal education (<emph>r</emph> =.19), height-for-age <emph>z</emph> score (<emph>r</emph> =.30), and weight-for-age <emph>z</emph> score (<emph>r</emph> =.31). ECDAS-CS scores were positively and significantly (<emph>p</emph>s <.05) correlated with age (<emph>r</emph> =.34), wealth (<emph>r</emph> =.19), maternal education (<emph>r</emph> =.23), height-for-age <emph>z</emph> score (<emph>r</emph> =.22), and weight-for-age <emph>z</emph> score (<emph>r</emph> =.31).</p> <p>Table 3. Pearson correlations between key variables (36–59 months).</p> <p> <ephtml> <table><thead><tr><td /><td>ECDAS-DA</td><td>ECDAS-CS score</td><td>Age in months</td><td>Sex (female)</td><td>Wealth index</td><td>Maternal education</td><td>Urbanicity (urban)</td><td>HAZ</td><td>WAZ</td></tr></thead><tbody><tr><td>ECDAS-CS score</td><td>0.52*</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Age in months</td><td>0.44*</td><td>0.34*</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Sex (female)</td><td>0.10*</td><td>0.07</td><td>0.04</td><td /><td /><td /><td /><td /><td /></tr><tr><td>Wealth index</td><td>0.14*</td><td>0.19*</td><td>−0.06</td><td>0.03</td><td /><td /><td /><td /><td /></tr><tr><td>Maternal education</td><td>0.19*</td><td>0.23*</td><td>−0.01</td><td>0.06</td><td>0.47*</td><td /><td /><td /><td /></tr><tr><td>Urbanicity (urban)</td><td>0.08</td><td>0.01</td><td>−0.08</td><td>0.01</td><td>0.21*</td><td>0.12*</td><td /><td /><td /></tr><tr><td>HAZ</td><td>0.30*</td><td>0.22*</td><td>0.01</td><td>−0.07</td><td>0.11*</td><td>0.21*</td><td>−0.19*</td><td /><td /></tr><tr><td>WAZ</td><td>0.31*</td><td>0.31*</td><td>0.15*</td><td>−0.08</td><td>0.12*</td><td>0.25*</td><td>−0.16*</td><td>0.60*</td><td /></tr></tbody></table> </ephtml> </p> <p>2 ECDAS-DA and ECDAS-CS are country-specific standardized scores. HAZ = height-for-age <emph>z</emph> score, WAZ = weight-for-age <emph>z</emph> score. Significant correlations (<emph>p</emph> <.05) are indicated by *.</p> <p>Country-specific correlations between age-adjusted ECDAS-DA and ECDAS-CS scores were.51 in Bangladesh (<emph>p</emph> <.001),.33 in China (<emph>p</emph> <.001),.36 in India (<emph>p</emph> <.001), and.18 in Myanmar (<emph>p</emph> >.05, not shown). Figure 1 shows raw ECDAS-DA and ECDAS-CS scores by age, with each line showing a smoothed mean, and the shaded areas showing 95% confidence intervals. ECDAS-DA scores were lower than ECDAS-CS scores. At older ages, mean ECDAS-DA and ECDAS-CS scores were more similar, but at younger ages there was a larger difference. ECDAS-DA scores showed more variation across age than ECDAS-CS scores.</p> <p>PHOTO (COLOR): Figure 1. Caregiver reported ECDAS-CS and directly assessed ECDAS-DA, by age (Raw scores scaled from 0 to 100).</p> <p>Table 4 shows a series of separate OLS regressions between country-standardized ECDAS-DA scores and each of age, wealth, maternal education, urban-rural residence, height-for-age <emph>z</emph> score, and weight-for-age <emph>z</emph> score as predictors, for the overall sample, and then for each country. Effect size was calculated using the formula <emph>b</emph>*<emph>SD<subs>X</subs></emph>/<emph>SD<subs>Y</subs></emph> (<emph>b</emph> is the coefficient estimate, <emph>SD<subs>X</subs></emph> is the <emph>SD</emph> for a predictor and <emph>SD<subs>Y</subs></emph> is the <emph>SD</emph> for the outcome variable) for continuous predictors and using <emph>b</emph>/<emph>SD<subs>Y</subs></emph> for categorical predictors. For the overall sample, ECDAS-DA scores were significantly (<emph>p</emph>s <.05) associated with age (<emph>B</emph> =.07, <emph>ES</emph> =.46), wealth (<emph>B</emph> =.18, <emph>ES</emph> =.18), maternal education (<emph>B</emph> =.18, <emph>ES</emph> =.19), height-for-age <emph>z</emph> score (<emph>B</emph> =.15, <emph>ES</emph> =.26), and weight-for-age <emph>z</emph> score (<emph>B</emph> =.12, <emph>ES</emph> =.19). ECDAS-DA scores were positively associated with age in all individual countries (<emph>p</emph>s <.001), with the predicting power of child age larger than that of household wealth and maternal education. Urban compared to rural residence was associated with higher scores in China and India (<emph>p</emph>s <.05), but not in Bangladesh and Myanmar.</p> <p>Table 4. Associations between ECDAS-DA directly assessed child development and key variables.</p> <p> <ephtml> <table><thead><tr><td /><td>Overall sample</td><td>Bangladesh</td><td>China</td><td>India</td><td>Myanmar</td></tr><tr><td /><td>b (SE)</td><td>ES</td><td>b (SE)</td><td>ES</td><td>b (SE)</td><td>ES</td><td>b (SE)</td><td>ES</td><td>b (SE)</td><td>ES</td></tr></thead><tbody><tr><td>Age in months</td><td>0.07 (0.01)***</td><td>0.46</td><td>0.05 (0.01)***</td><td>0.33</td><td>0.08 (0.01)***</td><td>0.44</td><td>0.08 (0.01)***</td><td>0.55</td><td>0.06 (0.02)**</td><td>0.44</td></tr><tr><td>Wealth (SD units)</td><td>0.18 (0.05)**</td><td>0.18</td><td>0.16 (0.07)*</td><td>0.17</td><td>0.31 (0.07)***</td><td>0.29</td><td>0.11 (0.07)</td><td>0.11</td><td>0.16 (0.12)</td><td>0.17</td></tr><tr><td>Mat education (5 levels)</td><td>0.18 (0.06)*</td><td>0.19</td><td>0.16 (0.07)*</td><td>0.19</td><td>0.62 (0.12)***</td><td>0.35</td><td>0.11 (0.06)</td><td>0.14</td><td>0.21 (0.16)</td><td>0.16</td></tr><tr><td>Urbanicity (urban)</td><td>0.27 (0.12)</td><td>0.27</td><td>−0.08 (0.16)</td><td>0.08</td><td>0.66 (0.13)***</td><td>0.66</td><td>0.29 (0.14)*</td><td>0.29</td><td>−0.21 (0.29)</td><td>0.21</td></tr><tr><td>HAZ</td><td>0.15 (0.05)*</td><td>0.26</td><td>0.26 (0.04)***</td><td>0.49</td><td>0.17 (0.07)*</td><td>0.18</td><td>0.07 (0.03)*</td><td>0.15</td><td>0.18 (0.10)</td><td>0.13</td></tr><tr><td>WAZ</td><td>0.12 (0.04)*</td><td>0.19</td><td>0.19 (0.04)***</td><td>0.33</td><td>−0.03 (0.07)</td><td>0.03</td><td>0.10 (0.06)</td><td>0.12</td><td>0.08 (0.08)</td><td>0.14</td></tr></tbody></table> </ephtml> </p> <p>3 HAZ = height-for-age <emph>z</emph> score, WAZ = weight-for-age <emph>z</emph> score. Results are from a series of separate OLS regressions with the country-specific standardized score of ECDAS-DA as the dependent variable, and each of age, wealth, maternal education, urban-rural residence, HAZ and WAZ as independent variables. All regressions included sex and age as a control variable (aside from the regressions using age as an independent variable). Regressions for the overall sample also included a control for country. Standard errors were adjusted for eight clusters within the sample.</p> <p>Table 5 shows a series of separate OLS regressions between country-standardized ECDAS-CS scores and each of age, wealth, maternal education, urban-rural residence, height-for-age <emph>z</emph> score, and weight-for-age <emph>z</emph> score as predictors, for the overall sample, and then for each country. For the overall sample, ECDAS-CS scores were significantly (<emph>p</emph>s <.05) associated with age (<emph>B</emph> =.05, <emph>ES</emph> =.33), wealth (<emph>B</emph> =.22, <emph>ES</emph> =.22), maternal education (<emph>B</emph> =.19, <emph>ES</emph> =.2), and weight-for-age <emph>z</emph> score (<emph>B</emph> =.12, <emph>ES</emph> =.19). ECDAS-CS scores were positively associated with age in Bangladesh, India, and Myanmar, but not in China. Urban compared to rural residence positively associated in China (<emph>p</emph>s <.001), but not in the other countries. Indicated by the effect sizes, there seemed to be a stronger association between ECDAS-DA and child age than for ECDAS-CS and child age.</p> <p>Table 5. Associations between ECDAS-CS caregiver reported child development and key variables.</p> <p> <ephtml> <table><thead><tr><td /><td>Overall sample</td><td>Bangladesh</td><td>China</td><td>India</td><td>Myanmar</td></tr><tr><td /><td>B (SE)</td><td>ES</td><td>B (SE)</td><td>ES</td><td>B (SE)</td><td>ES</td><td>B (SE)</td><td>ES</td><td>B (SE)</td><td>ES</td></tr></thead><tbody><tr><td>Age in months</td><td>0.05 (0.01)**</td><td>0.33</td><td>0.04 (0.01)***</td><td>0.26</td><td>0.03 (0.01)</td><td>0.16</td><td>0.06 (0.01)***</td><td>0.41</td><td>0.05 (0.02)*</td><td>0.37</td></tr><tr><td>Wealth (SD units)</td><td>0.22 (0.03)***</td><td>0.22</td><td>0.20 (0.08)**</td><td>0.21</td><td>0.24 (0.08)**</td><td>0.23</td><td>0.21 (0.07)**</td><td>0.21</td><td>0.18 (0.13)</td><td>0.19</td></tr><tr><td>Mat education (5 levels)</td><td>0.19 (0.03)**</td><td>0.20</td><td>0.22 (0.07)**</td><td>0.23</td><td>0.31 (0.14)*</td><td>0.17</td><td>0.17 (0.06)**</td><td>0.21</td><td>0.04 (0.17)</td><td>0.03</td></tr><tr><td>Urbanicity (urban)</td><td>0.12 (0.11)</td><td>0.12</td><td>−0.23 (0.16)</td><td>0.23</td><td>0.48 (0.15)**</td><td>0.48</td><td>0.07 (0.15)</td><td>0.07</td><td>0.08 (0.31)</td><td>0.08</td></tr><tr><td>HAZ</td><td>0.10 (0.04)</td><td>0.17</td><td>0.16 (0.04)***</td><td>0.30</td><td>0.14 (0.07)</td><td>0.15</td><td>0.05 (0.03)</td><td>0.11</td><td>0.14 (0.10)</td><td>0.18</td></tr><tr><td>WAZ</td><td>0.12 (0.03)*</td><td>0.19</td><td>0.15 (0.05)**</td><td>0.26</td><td>0.11 (0.08)</td><td>0.11</td><td>0.11 (0.06)</td><td>0.14</td><td>0.10 (0.08)</td><td>0.18</td></tr></tbody></table> </ephtml> </p> <p>4 HAZ = height-for-age <emph>z</emph> score, WAZ = weight-for-age <emph>z</emph> score. Results are from a series of separate OLS regressions with the directly assessed country-standardized ECDAS-CS score as the dependent variable, and each of age, wealth, maternal education, urban-rural residence, HAZ and WAZ as independent variables. All regressions included sex and age as control variables (aside from the regressions using age as an independent variable). Regression for the overall sample also included a control for country. Standard errors were adjusted for 8 clusters within the sample.</p> <p>Figure 2 shows variation in associations between country-standardized ECDAS-DA and ECDAS-CS scores by maternal education. Results are from an OLS regression with an interaction term between ECDAS-CS scores and maternal education, controlling for country and age. Associations between ECDAS-DA and ECDAS-CS scores were not statistically significant for mothers with different levels of education (i.e., primary education or lower, secondary education, and above secondary). When comparing mothers with "above secondary" to those with secondary education or lower, there was a borderline significant difference between these two groups in the association between ECDAS-DA and ECDAS-CS (<emph>p</emph> =.05).</p> <p>PHOTO (COLOR): Figure 2. Association between country-standardized ECDAS-DA and ECDAS-CS scores, by level of maternal education.</p> <p>As previously noted, based on the ECDAS-DA and ECDAS-CS scores, we used three indicators to determine whether children were developmentally on track. Table 6 reports the means and standard deviations of ECDAS-DA and ECDAS-CS scores by country and age. Appendix C shows the proportion of children who would be considered on track by country, maternal education, and household wealth quintile, measured by ECDAS-CS. Results showed that 96%, 90% and 85% of children would be considered on track, indicated by that their ECDAS-CS scores not being more than 2 <emph>SD</emph>s, 1.5 <emph>SD</emph>s, and 1 <emph>SD</emph>, respectively, below the mean age-adjusted ECDAS-CD score. On the other hand, 97%, 94%, and 83% of children would be considered on track based on ECDAS-DA data, using the three indicators (Appendix D). Notably, both Appendices C and D show gradients in on track development status by maternal education and wealth.</p> <p>Table 6. Means and standard deviations of ECDAS-DA and ECDAS-CS by country and child age.</p> <p> <ephtml> <table><thead><tr><td>Country</td><td>ECDAS-DA</td><td>ECDAS-CS</td></tr><tr><td>36–41 months</td><td>42–47 months</td><td>48–59 months</td><td>36–41 months</td><td>42–47 months</td><td>48–59 months</td></tr></thead><tbody><tr><td>Bangladesh</td><td>9.12 (2.37)</td><td>10.12 (3.13)</td><td>11.04 (2.81)</td><td>14.50 (1.89)</td><td>14.67 (2.32)</td><td>15.67 (2.17)</td></tr><tr><td>China</td><td>8.69 (2.55)</td><td>9.45 (1.97)</td><td>11.19 (1.89)</td><td>14.83 (1.69)</td><td>15.22 (1.64)</td><td>15.68 (1.64)</td></tr><tr><td>India</td><td>6.70 (1.77)</td><td>7.66 (2.38)</td><td>9.70 (2.47)</td><td>12.52 (2.06)</td><td>13.64 (2.26)</td><td>14.72 (2.24)</td></tr><tr><td>Myanmar</td><td>6.70 (2.30)</td><td>9.65 (2.80)</td><td>10.30 (2.72)</td><td>12.90 (1.57)</td><td>14.23 (2.37)</td><td>14.57 (1.62)</td></tr><tr><td>Overall</td><td>7.53 (2.36)</td><td>9.24 (2.63)</td><td>10.60 (2.51)</td><td>13.32 (2.10)</td><td>14.64 (2.12)</td><td>15.27 (2.04)</td></tr></tbody></table> </ephtml> </p> <p>5 Standard deviations are presented in parentheses.</p> <hd id="AN0158177551-15">Discussion</hd> <p>An indicator of the Sustainable Development Goal 4 requires measurement of the percentages of children aged 24–59 months who are developmentally on track in the areas of health, learning, and psychosocial well-being (SDG indicator 4.2.1). A reliable measure of on-track status is essential to generate pan-culturally relevant data to monitor global progress toward SDG Target 4.2. To meet this requirement, UNICEF, in consultation with key partners, developed a caregiver-report measure, the ECDI2030 (UNICEF, [<reflink idref="bib47" id="ref66">47</reflink>]), which may be administered under the auspices of its Multiple Indicator Cluster Survey program or other national household surveys. The present study examined the comparability between direct child assessment and caregiver-based report of ECD relevant to the SDG Target 4.2. In order to allow comparison between the two means of assessing, we first developed the ECDAS-CS and the ECDAS-DA based on the ECDI2030 (UNICEF, [<reflink idref="bib47" id="ref67">47</reflink>]) and examined their psychometric properties. This was followed by examining the associations between the two measures.</p> <p>The process of ECDAS-DA development and the findings from its application illustrate issues that are particularly pertinent to measuring ECD at scale in low- and middle-income countries. Efforts were exerted to ensure that the ECDAS-DA was contextually and developmentally appropriate. However, we are aware that the meaning of an item or endorsement of a behavior may vary across cultures. For example, a psychosocial well-being item is concerned with aggression (ECD20 [Frequency of kicking, biting, or hitting other children or adults compared with children of the same age]) but cultural factors may influence the endorsement of aggression (Gallardo-Pujol et al., [<reflink idref="bib17" id="ref68">17</reflink>]).</p> <p>The ECDAS-DA and the ECDAS-CS were administered to children and caregivers of children aged 36 to 59 months, respectively, in Bangladesh, China, India, and Myanmar. Findings showed that the ECDAS-DA has adequate psychometric properties, including an acceptable reliability that was higher than the corresponding figures for the caregiver-reported ECDAS-CS. Across countries, the ECDAS-DA and the ECDAS-CS scores showed a clear developmental trend, with regression results indicating that both scores were significantly and positively related to child age, and that the association with age was stronger for the ECDAS-DA than for the ECDAS-CS. An exception to this finding was the insignificant association between ECDAS-CS and age in China. In keeping with our hypotheses and findings from other studies in low- and middle-income countries (Jeong et al., [<reflink idref="bib23" id="ref69">23</reflink>]; Lu et al., [<reflink idref="bib25" id="ref70">25</reflink>]), both the ECDAS-DA and ECDAS-CS scores were also positively associated with maternal education and family wealth. However, the associations with the two measures of socioeconomic status (SES) were not significant in Myanmar for both ECDAS-DA and ECDAS-CS, and in India for ECDAS-DA. Several interpretations of this finding are possible: either that child development may not vary among children from families of different socioeconomic backgrounds in these countries; that the range of SES in our sample was not large enough to capture differences that exist based on SES; or that the tool is not sensitive enough to tap SES differences in India and Myanmar. All these explanations are speculative without further data to substantiate them. However, it should also be noted that the sample size of ECE attenders for Myanmar was substantially smaller than the other countries, which would increase the likelihood of statistically insignificant findings in Myanmar.</p> <p>In China and India, urban children scored significantly higher than rural children. This finding is consistent with evidence generated from previous studies with large representative samples of children from Asia (Rao et al., [<reflink idref="bib34" id="ref71">34</reflink>]). Children living in urban areas might have benefited from more demographic and environmental advantages than those living in rural areas, such as housing conditions, clean water, community safety, and quality of health care and education. Surprisingly, urban-rural difference in child outcomes was not significant in Bangladesh and Myanmar. This might have been driven by other factors such as quality of preschool education, which we did not consider in this study. Moreover, given the small sizes of the samples, this finding might not accurately reflect the situation in Bangladesh and Myanmar.</p> <hd id="AN0158177551-16">Associations between Direct Assessment and Parent Report</hd> <p>The significant correlation between the ECDAS-DA and the ECDAS-CS scores indicate a substantial consistency between directly-assessed and caregiver-reported developmental status, at least in the samples of the countries included in this study. However, the magnitude of correlation was low to modest and varied across countries, with a relatively higher association in India and lower association in China, indicating that congruence between direct assessment and caregiver report may differ across social-cultural contexts. This finding is consistent with previous evidence that caregiver reports and direct assessment generated similar, while not fully consistent, results with regard to child outcomes (Weber et al., [<reflink idref="bib53" id="ref72">53</reflink>]). These may reflect differences in time spent looking after the child or even cultural differences in reporting on children's competence. The difference in the consistency between countries may be partly explained by the cross-cultural differences in parental expectations of children, child-rearing behaviors, and parental perception of progress of their children's development, which may have affected caregiver rating of child outcomes (Heo et al., [<reflink idref="bib20" id="ref73">20</reflink>]). Furthermore, we cannot rule out the possibility that this finding could also be a reflection of the difference in administration procedures applied in China where the caregiver survey was self-administered as opposed to interviewer-administered as in the other countries, although we had established high agreement between the two procedures in China before the data collection. These findings indicate that parent report can be a useful supplement to direct assessment, as a first step in a multi-stage screening process. At the same time, contextual characteristics that would affect the results of direct assessment or caregiver report should be considered.</p> <p>Notably, the ECDAS-DA showed a greater range of scores than the ECDAS-CS, indicating that the ECDAS-DA captured a larger variability of early childhood development than the ECDAS-CS. On the whole, the greater variability in ECDAS-DA reflects the wider range of competency tapped and the wider scoring rubric than the ECDAS-CS. This is expected given that most ECDAS-CS items were scored on a Yes/No basis, with caregivers indicating whether or not children can perform particular skills. These types of questions do not always capture children's emerging capabilities because caregivers may respond "no" if the child is only able to demonstrate the skill some, but not all, of the time. The items and scoring rubric of the ECDAS-DA enabled the capture of more nuanced variation in children's developmental functioning than the caregiver survey. This result reflects the importance of adequate interview techniques as a core element to improve data quality and minimize false negative and false positive answers. In particular, interviewers administering caregiver-based ECD instruments should receive adequate training on interview techniques, probing, clarification and overall question scoring instructions. It is also important that caregivers who are the respondents of ECD questions receive clear information on the objectives of questions before these are administered. However, we should be cautious when interpreting the findings because the scoring rules of the direct assessment differ from those used with the caregiver report. We should also be mindful that the ECDAS-DA is reliant on children's performance at the time of testing; external factors (including familiarity with the testing environment, rapport with assessors) may influence whether children are participating fully with their actual competence.</p> <p>Comparisons of the association between ECDAS-DA and ECDAS-CS scores by the level of maternal education showed that maternal education might moderate associations between the two measures. Specifically, mothers with some tertiary education might have reported ECDAS-CS scores that were more correlated with the ECDAS-DA than those with secondary education or lower. This finding might suggest that more educated mothers might be more accurate when reporting their children's developmental competencies than less educated mothers. In countries such as India and Myanmar, wherein national statistics indicate that less than half of women of child-bearing age have some secondary education (see Supplementary Figure 1), particular efforts should be exerted to ensure that respondents understand the survey questions. At the same time, given the small sample size for each country and the borderline significance of the association, the examination of the relevant association needs to be replicated with a larger sample size that would increase the rigor of analysis. On the other hand, children of lower socio-economic backgrounds have been shown to underperform on standardized tests, compared to their less vulnerable peers, regardless of their intelligence scores (Croizet & Claire, [<reflink idref="bib9" id="ref74">9</reflink>]). Additionally, accuracy of direct testing of preschool children has been found to be extremely dependent on testing conditions (Bracken, [<reflink idref="bib6" id="ref75">6</reflink>]), therefore, findings from the current study should be considered in light of other available evidence on how socio-economic background and child ability can impact direct assessment.</p> <p>As shown in Appendices C and D, the proportion of children who may be considered developmentally on track varied by measure. An indication of the socially advantaged nature of our sample comes from the large proportion of children who are developmentally on track in countries that have relatively high rates of stunting. A large body of research indicates that stunting impairs cognitive development and achievement throughout childhood and adolescence (Black et al., [<reflink idref="bib5" id="ref76">5</reflink>]). For example, stunting rates were 31% in Bangladesh (2018); 8% in China (2013); 35% in India (2016–2018); and 29% in Myanmar (2015–2016) in national population-based surveys (UNICEF, World Health Organization and World Bank Group, [<reflink idref="bib49" id="ref77">49</reflink>]). In our sample, the prevalence of stunting was much lower than national estimates in the four countries.</p> <p>It should be noted that a number of studies have used MICS ECDI data to determine whether children are developmentally on track. These studies have focused on a single country such as Nepal (Rayhan et al., [<reflink idref="bib35" id="ref78">35</reflink>]) and Ghana (Bago et al., [<reflink idref="bib2" id="ref79">2</reflink>]), on a region such as South Asia (Kang et al., [<reflink idref="bib24" id="ref80">24</reflink>]), or on a large pool of low- and middle-income countries (McCoy et al., [<reflink idref="bib26" id="ref81">26</reflink>]). All of these studies have attempted to provide an estimate of the percentage of children that are developmentally on track and of the factors that might have affected children's on-track development. However, the criteria for determining whether or not a child is developmentally on track has varied across studies, with some studies using the total ECDI score while others only reported particular subdomains. Hence, they do not permit an appropriate comparison with the findings of our study.</p> <hd id="AN0158177551-17">Limitations</hd> <p>This study has several limitations. First, the study used a purposive sampling design and purposive recruitment strategies rather than drawing a randomly-selected nationally representative sample. In the original dataset, we included equal numbers of participants from urban and rural areas in each context. However, since we only included ECE attenders in our analysis, the sample from Myanmar was smaller. Hence, caution should be exercised in interpreting the findings. Future studies should consider children who attend ECE and those do not when we look at scale properties. Further, our sample across the four countries had relatively low levels of stunting and relatively high levels of maternal education compared to relevant national statistics (see Supplementary Figure 1 for national statistics on women's education). However, for China, the data presented in the Supplementary Figure are based on 2010 census data and women's highest level of education should have increased markedly in the past ten years.</p> <p>Second, the ECDAS-DA items were not entirely aligned with the 18 items of the ECDAS-CS. Two of the items were not included because they were more related to children's disposition (being sad and depressed) and reactions in specific situations (asking about familiar people when they are not around). We also excluded one item (says ten or more words) which was not uniquely scored in the ECDAS-DA. As a result, the ECDAS-DA only included 15 items that were comparable to the ECDI2030, which might have reduced its capability of capturing more variations in children's early development and thus influenced the association between the ECDAS-DA and the caregiver-report measures. Following the release of ECDI2030, we have developed additional items to capture these skills that can be tested in future studies. Furthermore, as a newly developed tool based on the items selected to form a caregiver-report tool by the UNICEF, the reliability and sensitiveness of the ECDAS-DA as a direct assessment tool of child development needs to be established using a more rigorous examination.</p> <p>In light of the above limitations, the results presented here on the proportion of children classified as developmentally on-track according to the ECDAS-CS should not be interpreted as equivalent to estimates that would be obtained from the use of the ECDI2030. Data collection with nationally representative samples and the final official ECDI2030 is required to generate estimates that can be used for global reporting on SDG indicator 4.2.1. In addition, ECDAS-DA has been developed and tested only in Asian countries, it is important to be further tested on its applicability and validity as a measure in other contexts in future studies. Future studies can also evaluate the construct validity of the measures, this includes the study of their factor structure and underlying dimensions.</p> <hd id="AN0158177551-18">Conclusion</hd> <p>The study focused on comparing the direct child assessment and caregiver report of ECD in the context of the SDG indicator which is concerned with percentages of children aged 24 to 59 months who are developmentally on track in health, learning, and psychosocial well-being. While it is much easier to go to scale with a caregiver report measure like the ECDAS-CS, the value of a direct assessment ECDAS-DA lies in its ability to provide a more fine-grained analyses of emerging developmental competencies and its potential utility in longitudinal studies of policy and program impact in low- and middle-income countries. Given its unique contribution, the ECDAS-DA can be used to complement findings from the ECDAS-CS which includes a subset of items from the ECDI2030, a measure that is anticipated to be used extensively across countries to measure SDG indicator 4.2.1. The ECDAS-DA also has the potential to provide population-based information to inform policy decisions, cross-context comparisons, and program evaluation.</p> <hd id="AN0158177551-19">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <hd id="AN0158177551-20">Supplementary material</hd> <p>Supplemental data for this article can be accessed on the https://doi.org/10.1080/10409289.2021.1928446</p> <hd id="AN0158177551-21">Appendix A</hd> <p> <emph>Alignment between ECDAS Direct Assessment Items (ECDAS-DA) with ECDAS Caregiver Report Measure Items (ECDAS-CS)</emph> </p> <p></p> <p> <ephtml> <table><thead><tr><td>Correspondence to ECDI2030 item (Cappa et al., <xref ref-type="bibr" rid="bibr8">2018</xref>)</td><td>ECDAS-CS item</td><td>ECDAS-DA item</td></tr></thead><tbody><tr><td>ECD1</td><td>Walks on an uneven surface without falling</td><td>Balances when hopping on a hopscotch (4)</td></tr><tr><td>ECD2</td><td>Jumps up with both feet leaving the ground</td><td>Jumps with both feet leaving the ground (2)</td></tr><tr><td>ECD3</td><td>Dresses up, put on pants and a shirt without help</td><td>Puts on pants and shirt (2)</td></tr><tr><td>ECD4</td><td><italic>Not included</italic></td><td><italic>Not included</italic></td></tr><tr><td>ECD5</td><td>Says 10 or more words</td><td><italic>Not included</italic></td></tr><tr><td>ECD6</td><td>Speaks using sentences of 3 or more words that go together</td><td>Tells story with sequenced pictures using sentences of three or more words (1)</td></tr><tr><td>ECD7</td><td><italic>Not included</italic></td><td><italic>Not included</italic></td></tr><tr><td>ECD8</td><td>Correct use of pronouns</td><td>Uses pronouns (1)</td></tr><tr><td>ECD9</td><td>Consistently names objects that the child knows well</td><td>Names common objects (10)</td></tr><tr><td>ECD10</td><td>Recognize at least 5 letters of the akshara alphabet (Bengali, Hindi, Myanmar)/characters (China)</td><td>Identifies letters of the akshara alphabet (Bengali, Hindi, Myanmar)/characters (China) (1)</td></tr><tr><td>ECD11</td><td>Writes child's own name</td><td>Writes own name (3)</td></tr><tr><td>ECD12</td><td>Knows all numbers from 1 to 5</td><td>Rote counting (1)</td></tr><tr><td>ECD13</td><td>Gives the correct amount when asking child to give 3 objects</td><td>Counts blocks (1)</td></tr><tr><td>ECD14</td><td>Counts 10 objects without mistakes</td><td>Counts blocks (1)</td></tr><tr><td>ECD15</td><td>Do an activity without repeatedly asking for help or giving up too quickly</td><td>Focuses on coloring or playing with toy cars (1)</td></tr><tr><td>ECD16</td><td>Asks about familiar people other than parents when they are not there</td><td><italic>Not able to test</italic></td></tr><tr><td>ECD17</td><td>Offers help</td><td>Offers help (1)</td></tr><tr><td>ECD18</td><td>Gets along well with other children</td><td>Engages in cooperative play (1)</td></tr><tr><td>ECD19</td><td>Frequency of being very sad or depressed</td><td><italic>Not able to test</italic></td></tr><tr><td>ECD20</td><td>Kicking, biting, or hitting other children or adults</td><td>Not hitting another child (1)</td></tr></tbody></table> </ephtml> </p> <p>6 Number of sub-items in parentheses.</p> <hd id="AN0158177551-22">Appendix B</hd> <p> <emph>Sample ECDAS-DA Items for the Four Contexts</emph> </p> <p>Graph</p> <hd id="AN0158177551-23">Appendix C</hd> <p> <emph>Percentage of Children Developmentally on Track by Country (<reflink idref="bib1" id="ref82">1</reflink>), Level of Maternal Education (<reflink idref="bib2" id="ref83">2</reflink>), and Wealth Quintile (<reflink idref="bib3" id="ref84">3</reflink>), Measured by ECDAS-CS</emph> </p> <p>Graph</p> <hd id="AN0158177551-24">Appendix D</hd> <p> <emph>Percentage of Children who are Considered Developmentally on Track Children by Country (<reflink idref="bib1" id="ref85">1</reflink>), Level of Maternal Education (<reflink idref="bib2" id="ref86">2</reflink>), and Wealth Quintile (<reflink idref="bib3" id="ref87">3</reflink>), Measured by ECDAS-DA</emph> </p> <p>Graph</p> <ref id="AN0158177551-25"> <title> References </title> <blist> <bibl id="bib1" idref="ref6" type="bt">1</bibl> <bibtext> Achenbach, T. 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  Data: Measuring Being 'Developmentally on Track': Comparing Direct Assessment and Caregiver Report of Early Childhood Development in Bangladesh, China, India and Myanmar
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  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Bangladesh%22">Bangladesh</searchLink><br /><searchLink fieldCode="DE" term="%22China%22">China</searchLink><br /><searchLink fieldCode="DE" term="%22India%22">India</searchLink><br /><searchLink fieldCode="DE" term="%22Burma%22">Burma</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/10409289.2021.1928446
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1040-9289<br />1556-6935
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Assessment of progress toward UN Sustainable Development Goal 4 requires measurement of the proportion of children aged 24 to 59 months developmentally on track in health, learning, and psychosocial well-being (Indicator 4.2.1). UNICEF's methodological work culminated with the development of the Early Childhood Development Index 2030 (ECDI2030) to measure on track status. To compare direct assessment and caregiver report of early child development, a measure aligned to ECDI2030 -- the Early Childhood Development Assessment Scale-Direct Assessment (ECDAS-DA) -- was developed and administered to 510 preschoolers aged 36- to 59-months from Bangladesh, China, India, and Myanmar. Their caregivers completed the Early Childhood Development Assessment Scale-Caregiver Survey (ECDAS-CS) containing items based on the ECDI2030. Research Findings: The two measures correlated with each other and were associated with child age, maternal education, and family wealth. ECDAS-DA showed more variability by child age and provided more fine-grained analyses of emerging developmental competencies than ECDAS-CS. Practice or Policy: Given the dearth of pan-culturally appropriate tools, ECDAS-DA can be deployed in longitudinal studies and impact evaluations in low- and middle-income countries.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2022
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1357346
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1357346
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/10409289.2021.1928446
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 1013
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Child Development
        Type: general
      – SubjectFull: Preschool Children
        Type: general
      – SubjectFull: Age Differences
        Type: general
      – SubjectFull: Mothers
        Type: general
      – SubjectFull: Parent Background
        Type: general
      – SubjectFull: Educational Attainment
        Type: general
      – SubjectFull: Socioeconomic Status
        Type: general
      – SubjectFull: Sustainable Development
        Type: general
      – SubjectFull: Caregiver Attitudes
        Type: general
      – SubjectFull: Evaluation Methods
        Type: general
      – SubjectFull: Parent Attitudes
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Cultural Differences
        Type: general
      – SubjectFull: Bangladesh
        Type: general
      – SubjectFull: China
        Type: general
      – SubjectFull: India
        Type: general
      – SubjectFull: Burma
        Type: general
    Titles:
      – TitleFull: Measuring Being 'Developmentally on Track': Comparing Direct Assessment and Caregiver Report of Early Childhood Development in Bangladesh, China, India and Myanmar
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Rao, Nirmala
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          Name:
            NameFull: Chan, Stephanie W. Y.
      – PersonEntity:
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            NameFull: Su, Yufen
      – PersonEntity:
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            NameFull: Richards, Ben
      – PersonEntity:
          Name:
            NameFull: Cappa, Claudia
      – PersonEntity:
          Name:
            NameFull: De Castro, E. Filipa
      – PersonEntity:
          Name:
            NameFull: Petrowski, Nicole
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-print
              Value: 1040-9289
            – Type: issn-electronic
              Value: 1556-6935
          Numbering:
            – Type: volume
              Value: 33
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Early Education and Development
              Type: main
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