Psychomotor development in children aged 12-23 months from communities in southern Ecuador: a descriptive research note

Psychomotor development in children aged 12-23 months from communities in southern Ecuador: a descriptive research note | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Psychomotor development in children aged 12-23 months from communities in southern Ecuador: a descriptive research note Diana Estefanía Vásquez Muñoz, Blanca Priscila Maldonado Pacheco, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9397427/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Objective: To describe psychomotor development in children aged 12 to 23 months from rural and urban communities in southern Ecuador using the Abbreviated Development Scale (EAD-1). Results: A total of 138 children were evaluated in the cantons of Calvas and Gonzanamá. Most participants were classified in the medium developmental category (51.4%), while 24.6% were categorized in the alert level. The personal-social domain showed the highest proportion of alert classifications (42.8%), followed by the hearing-language and gross motor domains. Fine motor-adaptive performance showed a higher proportion of classifications in the medium and medium-high categories. These findings reflect developmental performance within a non-probabilistic sample and should be interpreted with caution. Child Development Developmental Screening Ecuador Early Childhood Motor Skills Psychomotor Development Figures Figure 1 Introduction Psychomotor development is an evolutionary and integrative process through which children progressively acquire physical, psychological, mental, emotional, and complex response abilities to everyday demands [ 1 , 2 ]. Although each child follows an individual rhythm of maturation, development tends to occur in predictable sequences that can be monitored using standardized parameters [ 3 , 4 ]. Early development emerges from the interaction of multiple systems, making it a multidimensional process involving motor, language, and socioemotional domains [ 5 – 8 ]. The Organization of American States (OAS) emphasizes that the lack of early interventions in childhood, combined with gender, class, and ethnic inequalities, negatively affects children’s cognitive, emotional, and educational development [ 9 ]. In Latin America, evidence shows variability in early childhood development outcomes. For example, in Chile, 14.3% of children have been reported with low developmental scores, with notable deficits in gross motor abilities [ 10 ]. In Ecuador, the National Health and Nutrition Survey (ENSANUT) shows that children from rural areas and low-income households, are exposed to fewer stimulating environments, which may limit learning opportunities [ 11 ]. Despite the implementation of early childhood programs, gaps in access to healthcare, nutrition, and educational services persist, particularly in rural areas such as the province of Loja [ 12 – 14 ]. However, coverage remains insufficient to fully address developmental needs [ 15 ]. Communities including Cariamanga, Quilanga, Lucero, Colaisaca, Chingulle, Nambacola, Sacapalca, and Changaimina experience challenging socioeconomic conditions and limited access to healthcare and educational services [ 16 , 17 ]. Previous studies in Ecuador have reported heterogeneous findings across regions. While some studies describe adequate developmental performance in certain populations, others report a high proportion of children with inadequate psychomotor development [ 18 , 19 ]. These disparities reflect variations in sampling strategies, socioeconomic conditions, and access to health services, limiting direct comparability. In this context, this study aimed to describe the psychomotor development in children aged 12 to 23 months from the cantons of Calvas and Gonzanamá, in the province of Loja, using the Abbreviated Development Scale (EAD). Given the non-probabilistic sampling design, findings are presented as a localized descriptive overview in an underserved population. Methods and materials This study employed a descriptive, cross-sectional design. Data collection was conducted in July 2023 as part of a broader community-based research initiative led by the Center of Health Research in Latin America (CISeAL), and involved assessing the psychomotor development of children residing in the communities of Cariamanga, Quilanga, Lucero, Colaisaca, Chingulle, Nambacola, Sacapalca and Changaimina, located in the cantons of Calvas and Gonzanamá in the province of Loja, Ecuador. A total of 138 participants were recruited during community health fairs. All children aged 12 to 23 months attending these events whose caregivers provided written informed consent were eligible for inclusion. This recruitment strategy may have introduced selection bias, as participants may not represent the general population. Participation was voluntary, potentially leading to overrepresentation of caregivers with greater health-seeking behavior. Assessments were conducted individually in quiet spaces within each community. Caregivers were present to provide demographic and health information but did not participate in the evaluation. All personal data were anonymized and coded to guarantee participant confidentiality. Psychomotor development was assessed through direct observation using the Abbreviated Development Scale (EAD-1), developed by Nelson Ortiz Pinilla. Data were processed and analyzed using IBM SPSS Statistics software version 30.0.0. Ethical considerations This study protocol received approval from the Research Ethics Committee on Human Beings (CEISH) of the Pontifical Catholic University of Ecuador, under approval code CEISH-493-2023. Written informed consent was obtained from the caregivers of all participating children prior to data collection. All procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki. Instrument Psychomotor development was assessed through direct observation using the EAD-1. This instrument evaluates four domains: gross motor, fine motor-adaptive, hearing-language, and personal-social skills [ 20 ]. Each item is scored dichotomously (1 = achieved, 0 = not achieved), and total scores are categorized as high, medium-high, medium, or alert level according to age-specific criteria [ 21 ]. The EAD-1 has demonstrated strong reliability (ICC = 0.9; Kappa = 0.8) in Latin American pediatric populations [ 22 ]. However, although widely used in the region, it has not been formally validated in Ecuadorian populations. Statistical analysis Statistical analyses were conducted using IBM SPSS Statistics version 30.0.0. Descriptive statistics, including absolute frequencies, percentages, means, and 95% confidence intervals, were used to summarize sociodemographic characteristics and developmental outcomes. Given the non-probabilistic sampling design, inferential analyses were considered exploratory and interpreted with caution. Associations between developmental domains and overall classifications were explored using contingency tables and Cramer’s V as a measure of effect size. Key sociodemographic variables such as maternal education, socioeconomic status, and ethnicity were not available, limiting the ability to assess potential confounding factors. Results Results are presented as descriptive findings within this specific sample and should not be interpreted as representative of the broader population. Sociodemographic characteristics Table 1 shows the sociodemographic characteristics of the study population. The sample consisted of 138 participants, of whom 56.5% were male. The mean age of the children was 17.75 months [CI = 17.14–18.36]. Most participants were from the canton of Calvas (51.4%), while 48.6% were from Gonzanamá. The majority of the sample was from rural areas (60.1%), compared to 39.9% from urban settings. Regarding the community distribution, Cariamanga accounted for the highest proportion of participants (21.7%), whereas Chingulle represented the smallest proportion (2.2%). Table 1 Sociodemographic characteristics of the study population Variable Category n (%) Mean [95% CI] Sex Female 60 (43.5%) Male 78 (56.5%) Age (months) 17.75 [17.14–18.36] Canton Calvas 71 (51.4%) Gonzanamá 67 (48.6%) Community Cariamanga 30 (21.7%) Colaisaca 11 (8.0%) Lucero 13 (9.4%) Quilanga 14 (10.1%) Chingulle 3 (2.2%) Gonzanamá 28 (20.3%) Nambacola 25 (18.1%) Sacapalca 5 (3.6%) Changaimina 9 (6.5%) Zone Rural 83 (60.1%) Urban 55 (39.9%) 1 CI: 95% confidence interval Score by psychomotor development domain Table 2 summarizes the distribution of scores across the four psychomotor development domains evaluated by the EAD-1 scale. In the gross motor domain, 37.0% of children were classified in the medium category, while 28.3% were classified in the alert category. In the fine motor-adaptive domain, 52.9% of children were classified in the medium category, whereas 2.9% reached the high category. In the hearing and language domain, 58.7% of participants presented adequate development, whereas 28.3% were classified as alert. Also, in the personal-social domain, 42.8% of children were classified in the alert category, followed by 39.9% in the medium category. Table 2 Distribution of scores by psychomotor development area Variable Category n (%) [95% CI] Gross motor Alert 39 (28.3%) [15.64–16.84] Medium 51 (37.0%) Medium-High 44 (31.9%) High 4 (2.9%) Fine motor-adaptive Alert 17 (12.3%) [15.19–16.11] Medium 73 (52.9%) Medium-High 44 (31.9%) High 4 (2.9%) Hearing-language Alert 39 (28.3%) [13.27–13.96] Medium 81 (58.7%) Medium-High 17 (12.3%) High 1 (0.7%) Personal-social Alert 59 (42.8%) [13.12–14.11] Medium 55 (39.9%) Medium-High 24 (17.4%) High 0 (0%) Total psychomotor development Alert 34 (24.6%) [57.46–60.79] Medium 71 (51.4%) Medium-High 32 (23.2%) High 1 (0.7%) 2 CI: 95% confidence interval Psychomotor development by community The distribution of psychomotor development by community is presented in Supplementary Table S1 . Most children were categorized in the medium level of psychomotor development 51.4% (n = 71), with some variability between communities. The community of Lucero reported the only case classified in the high category (0.7%). In contrast, Chingulle showed a higher proportion of children classified in the alert category (66.7%); however, this finding should be interpreted with caution due to the small sample size in that community (n = 3). To explore the relationship between domain-specific performance and overall developmental classification, Cramer’s V was calculated for each domain of the EAD-1. Moderate associations were observed across domains, with the strongest association found for the personal-social domain (V ≈ 0.62), followed by the fine motor-adaptive domain (V ≈ 0.53). Gross motor (V ≈ 0.47) and hearing-language (V ≈ 0.49) domains also showed moderate associations. These findings reflect the degree of association between domain-specific classifications and the overall developmental classification within this sample and should be interpreted as exploratory. Geographic distribution of participants in alert category Figure 1 illustrates the geographic distribution of participants in the province of Loja, highlighting the proportion of children classified in the alert category across communities. Discussion Neurodevelopment results from the interaction between biological and environmental factors, including family, social, and community contexts, which influence developmental outcomes [ 10 ]. Children raised in socioeconomically disadvantaged environments may experience limited access to stimulation and learning opportunities, which can affect developmental progress across domains [ 6 , 11 , 23 ]. The findings of this study should be interpreted as descriptive observations within a non-representative sample rather than population-level estimates. Most children were classified in the medium category, while 24.6% were categorized in alert level, reflecting potential developmental vulnerability within this group. Comparisons with previous studies in Ecuador should be made cautiously due to methodological differences. For example, Córdova Cando et al. [ 19 ] reported a high proportion of inadequate gross motor development in Loja, whereas Molina Calderón y Piñon Gamez [ 18 ] reported generally adequate performance in Chone. These discrepancies may reflect differences in sampling strategies, socioeconomic conditions, and access to health services rather than true population differences. In this study, fine motor-adaptive development showed relatively more favorable distributions, with 52.9% of children classified in the medium category and 31.9% in the medium-high category, compared with reports of delays in other populations. Studies in Latin America have described a substantial proportion of infants at risk of developmental delay, particularly in low-income settings [ 24 ]. Psychomotor delay during early childhood may affect later motor, communication, and problem-solving skills [ 25 ]. The personal-social domain showed the highest proportion of alert classifications (42.8%). This domain reflects social interaction and emotional expression [ 9 , 26 ]; however, the use of the EAD-1 without prior validation in Ecuador may introduce measurement bias, particularly in culturally sensitive domains. Exploratory analysis using Cramer’s V showed moderate associations between domain-specific performance and overall classification, with the personal-social domain showing the strongest association. These findings reflect patterns within this sample and should not be interpreted as causal. In the hearing-language domain, most children were classified in the medium category (58.7%). Variability in language development has been reported in similar socioeconomic contexts and may be influenced by environmental and cultural factors [ 1 ]. Although socioeconomic differences between communities were not formally assessed, most participants were from rural areas, which may influence access to early stimulation and developmental opportunities [ 27 ]. Early childhood interventions may support developmental outcomes in such contexts [ 28 ]. It is also noteworthy that only one child (0.7%) was classified in the high developmental category, reflecting limited representation at this level within the sample. Overall, these findings highlight the importance of monitoring psychomotor development in early childhood, particularly in underserved settings. Results should be interpreted cautiously and understood as preliminary observations. Future research should include larger and more representative samples and incorporate key sociodemographic variables. Limitations Nevertheless, several limitations should be considered when interpreting the findings of this study. The use of a non-probabilistic convenience sample limits the generalizability of the results to the broader population. In addition, participants were recruited during community health fairs, which may have introduced selection bias, as caregivers attending these events may differ from the general population in terms of health-seeking behavior. The distribution of participants across communities was also uneven, with some localities represented by a small number of observations, limiting comparability between communities and restricting the interpretation of local-level differences. Furthermore, key sociodemographic variables such as socioeconomic status, maternal education, and ethnicity were not available, limiting the ability to assess potential confounding factors influencing developmental outcomes. Finally, the cross-sectional design precludes causal inference and limits the ability to assess developmental trajectories over time. Abbreviations The following abbreviations are used in this manuscript: EAD-1 Abbreviated Development Scale OAS Organization of American States ENSANUT National Health and Nutrition Survey ICC Intraclass Correlation Coefficient CISeAL Center for Health Research in Latin America CEISH Human Research Ethics Committee Declarations Ethics approval and consent to participate This study was approved by the Human Research Ethics Committee (CEISH) of the Pontifical Catholic University of Ecuador with the code CEISH-493-2023, approved on July 4, 2023. Written informed consent was obtained from the caregivers of all participating children prior to data collection. All procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki. Consent for publication Not applicable Availability of data and materials The datasets generated and analyzed for the execution of this study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Author’s contributions Conceptualization, B.P.M.P. and D.E.V.M.; methodology, B.P.M.P., D.E.V.M. and S.O.I.J.; software, S.O.I.J. and D.E.V.M.; validation, S.O.I.J.; formal analysis, S.O.I.J.; investigation, B.P.M.P. and D.E.V.M.; resources, B.P.M.P.; data curation, S.O.I.J.; writing—original draft preparation, D.E.V.M., B.P.M.P and S.O.I.J.; writing—review and editing, B.P.M.P., D.E.V.M. and S.O.I.J.; visualization, S.O.I.J.; supervision, B.P.M.P. and S.O.I.J.; project administration, B.P.M.P.; funding acquisition, B.P.M.P and D.E.V.M. All authors have read and agreed to the published version of the manuscript. Acknowledgements The authors would like to express their sincere gratitude to Camila Ayala for providing training on the application of the EAD-1 instrument as well as for sharing her knowledge on child development from a psychological perspective; to Belen Allauca and Adriana Espín for their valuable support in data collection and in the administration of the development assessment; and to Raúl Parra for preparing the map graphic illustrating the distribution of the communities with alert diagnoses. In addition, we also acknowledge Dr. Mario J. Grijalva for his essential role in facilitating the financial and institutional support required for the implementation of this project. His leadership and guidance in promoting research excellence and fostering collaborative initiatives in southern Ecuador were fundamental to the successful completion of this study. During the preparation of this manuscript, the author(s) used an artificial intelligence language model (ChatGPT-4/5, OpenAI, San Francisco, CA, USA) to assist with the English translation and minor linguistic polishing of the manuscript. This tool was used only to improve clarity and grammar; all scientific content, data interpretation, and conclusions were entirely generated and verified by authors. All authors have reviewed and edited the output and take full responsibility for the content of this publication. References Román Sacón J, Calle Contreras P. Psychomotor development status in healthy children attending a child center in Santo Domingo. Ecuador Enfermería: Cuidados Humanizados. 2017;6(2):49–65. 10.22235/ECH.V6I2.1467 . de la Cala E, Pinero-Pinto E. Motor development scales validated in spanish populations of children aged 0–18 months: systematic review. Children. 2025;12(9):1106. 10.3390/CHILDREN12091106 . Gloria C. Frontera Pedro. 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Rev Argent Salud Publica [Internet]. 2014 Jun 2 [cited 2025 Apr 22];5(19):17–24. Available from: https://www.rasp.msal.gov.ar/index.php/rasp/article/view/266 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 May, 2026 Reviews received at journal 12 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 20 Apr, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 19 Apr, 2026 First submitted to journal 19 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9397427","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":630948056,"identity":"5daf72a6-9e7c-46e7-8d19-4d3041da766d","order_by":0,"name":"Diana Estefanía Vásquez Muñoz","email":"","orcid":"","institution":"Pontificia Universidad Católica del Ecuador","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"Estefanía Vásquez","lastName":"Muñoz","suffix":""},{"id":630948057,"identity":"39674697-59e8-45a4-ba4d-c114d5ef6f77","order_by":1,"name":"Blanca Priscila Maldonado Pacheco","email":"","orcid":"","institution":"Pontificia Universidad Católica del Ecuador","correspondingAuthor":false,"prefix":"","firstName":"Blanca","middleName":"Priscila Maldonado","lastName":"Pacheco","suffix":""},{"id":630948058,"identity":"80a5bb68-2b37-4bdb-9729-7bfcd98a241f","order_by":2,"name":"Samuel Olegario Iñiguez Jimenez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYFACxgaGBBDN3gAVOEC0Fh6YUsJaYEAigUgt8u3NbQ8e/DosJz/z7TGJHxUMcnw3Ehgf/MCjxeDMwXaDxL7Dxoyz89Ike84wGEveSGA27MGnRSKxTSKx53Bis3SOmTRjG0PihhsJbNJ4HTYDoqW+TfIMUMs/hnqgFvbfeD1zA6gl4cfhBB4JHqAWYOgZAG1hxqcD6BegLQ3phjN48pIte45JGM4887BZEp9f5Nvbn0n++GMtL99+9uCNHzU28nzHkw9+wBdiYAD0NRDwgAgJBnDkEgZ/4FpGwSgYBaNgFGACAGobTo1Oku56AAAAAElFTkSuQmCC","orcid":"","institution":"Pontificia Universidad Católica del Ecuador","correspondingAuthor":true,"prefix":"","firstName":"Samuel","middleName":"Olegario Iñiguez","lastName":"Jimenez","suffix":""}],"badges":[],"createdAt":"2026-04-13 01:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9397427/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9397427/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108384151,"identity":"7b47b9fc-3462-4aaa-8052-3d92df0ec9b9","added_by":"auto","created_at":"2026-05-04 05:51:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":698683,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Loja province showing the geographic distribution of participants and percentages in the alert category.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9397427/v1/cb43b428c4527af803e5969e.png"},{"id":108804091,"identity":"2fbf3763-0f90-4d88-9022-23ca97c5d0e3","added_by":"auto","created_at":"2026-05-08 15:15:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":882943,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9397427/v1/4226262b-b7c6-45d9-a7c7-1a892260bafd.pdf"},{"id":108493462,"identity":"0ea0d1d6-8a74-4046-a40b-e37f05d6f610","added_by":"auto","created_at":"2026-05-05 10:00:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15997,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9397427/v1/21aacf9697f3a476e8698b46.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychomotor development in children aged 12-23 months from communities in southern Ecuador: a descriptive research note","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePsychomotor development is an evolutionary and integrative process through which children progressively acquire physical, psychological, mental, emotional, and complex response abilities to everyday demands [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although each child follows an individual rhythm of maturation, development tends to occur in predictable sequences that can be monitored using standardized parameters [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Early development emerges from the interaction of multiple systems, making it a multidimensional process involving motor, language, and socioemotional domains [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Organization of American States (OAS) emphasizes that the lack of early interventions in childhood, combined with gender, class, and ethnic inequalities, negatively affects children\u0026rsquo;s cognitive, emotional, and educational development [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In Latin America, evidence shows variability in early childhood development outcomes. For example, in Chile, 14.3% of children have been reported with low developmental scores, with notable deficits in gross motor abilities [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In Ecuador, the National Health and Nutrition Survey (ENSANUT) shows that children from rural areas and low-income households, are exposed to fewer stimulating environments, which may limit learning opportunities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Despite the implementation of early childhood programs, gaps in access to healthcare, nutrition, and educational services persist, particularly in rural areas such as the province of Loja [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, coverage remains insufficient to fully address developmental needs [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Communities including Cariamanga, Quilanga, Lucero, Colaisaca, Chingulle, Nambacola, Sacapalca, and Changaimina experience challenging socioeconomic conditions and limited access to healthcare and educational services [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies in Ecuador have reported heterogeneous findings across regions. While some studies describe adequate developmental performance in certain populations, others report a high proportion of children with inadequate psychomotor development [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These disparities reflect variations in sampling strategies, socioeconomic conditions, and access to health services, limiting direct comparability.\u003c/p\u003e \u003cp\u003eIn this context, this study aimed to describe the psychomotor development in children aged 12 to 23 months from the cantons of Calvas and Gonzanam\u0026aacute;, in the province of Loja, using the Abbreviated Development Scale (EAD). Given the non-probabilistic sampling design, findings are presented as a localized descriptive overview in an underserved population.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cp\u003eThis study employed a descriptive, cross-sectional design. Data collection was conducted in July 2023 as part of a broader community-based research initiative led by the Center of Health Research in Latin America (CISeAL), and involved assessing the psychomotor development of children residing in the communities of Cariamanga, Quilanga, Lucero, Colaisaca, Chingulle, Nambacola, Sacapalca and Changaimina, located in the cantons of Calvas and Gonzanam\u0026aacute; in the province of Loja, Ecuador.\u003c/p\u003e \u003cp\u003eA total of 138 participants were recruited during community health fairs. All children aged 12 to 23 months attending these events whose caregivers provided written informed consent were eligible for inclusion. This recruitment strategy may have introduced selection bias, as participants may not represent the general population. Participation was voluntary, potentially leading to overrepresentation of caregivers with greater health-seeking behavior.\u003c/p\u003e \u003cp\u003eAssessments were conducted individually in quiet spaces within each community. Caregivers were present to provide demographic and health information but did not participate in the evaluation. All personal data were anonymized and coded to guarantee participant confidentiality.\u003c/p\u003e \u003cp\u003ePsychomotor development was assessed through direct observation using the Abbreviated Development Scale (EAD-1), developed by Nelson Ortiz Pinilla. Data were processed and analyzed using IBM SPSS Statistics software version 30.0.0.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e This study protocol received approval from the Research Ethics Committee on Human Beings (CEISH) of the Pontifical Catholic University of Ecuador, under approval code CEISH-493-2023. Written informed consent was obtained from the caregivers of all participating children prior to data collection. All procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInstrument\u003c/h3\u003e\n\u003cp\u003ePsychomotor development was assessed through direct observation using the EAD-1. This instrument evaluates four domains: gross motor, fine motor-adaptive, hearing-language, and personal-social skills [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Each item is scored dichotomously (1\u0026thinsp;=\u0026thinsp;achieved, 0\u0026thinsp;=\u0026thinsp;not achieved), and total scores are categorized as high, medium-high, medium, or alert level according to age-specific criteria [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe EAD-1 has demonstrated strong reliability (ICC\u0026thinsp;=\u0026thinsp;0.9; Kappa\u0026thinsp;=\u0026thinsp;0.8) in Latin American pediatric populations [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, although widely used in the region, it has not been formally validated in Ecuadorian populations.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using IBM SPSS Statistics version 30.0.0. Descriptive statistics, including absolute frequencies, percentages, means, and 95% confidence intervals, were used to summarize sociodemographic characteristics and developmental outcomes. Given the non-probabilistic sampling design, inferential analyses were considered exploratory and interpreted with caution. Associations between developmental domains and overall classifications were explored using contingency tables and Cramer\u0026rsquo;s V as a measure of effect size.\u003c/p\u003e \u003cp\u003eKey sociodemographic variables such as maternal education, socioeconomic status, and ethnicity were not available, limiting the ability to assess potential confounding factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eResults are presented as descriptive findings within this specific sample and should not be interpreted as representative of the broader population.\u003c/p\u003e\n\u003ch3\u003eSociodemographic characteristics\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the sociodemographic characteristics of the study population. The sample consisted of 138 participants, of whom 56.5% were male. The mean age of the children was 17.75 months [CI\u0026thinsp;=\u0026thinsp;17.14\u0026ndash;18.36]. Most participants were from the canton of Calvas (51.4%), while 48.6% were from Gonzanam\u0026aacute;. The majority of the sample was from rural areas (60.1%), compared to 39.9% from urban settings.\u003c/p\u003e \u003cp\u003eRegarding the community distribution, Cariamanga accounted for the highest proportion of participants (21.7%), whereas Chingulle represented the smallest proportion (2.2%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMean [95% CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e60 (43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c6\" namest=\"c5\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e78 (56.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e17.75 [17.14\u0026ndash;18.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCanton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCalvas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e71 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c6\" namest=\"c5\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGonzanam\u0026aacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e67 (48.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eCommunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCariamanga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e30 (21.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"8\" nameend=\"c6\" namest=\"c5\" rowspan=\"9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColaisaca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLucero\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e13 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuilanga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e14 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChingulle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGonzanam\u0026aacute;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e28 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNambacola\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e25 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSacapalca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChangaimina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e9 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eZone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e83 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c6\" namest=\"c5\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e55 (39.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003e CI: 95% confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eScore by psychomotor development domain\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the distribution of scores across the four psychomotor development domains evaluated by the EAD-1 scale. In the gross motor domain, 37.0% of children were classified in the medium category, while 28.3% were classified in the alert category.\u003c/p\u003e \u003cp\u003eIn the fine motor-adaptive domain, 52.9% of children were classified in the medium category, whereas 2.9% reached the high category.\u003c/p\u003e \u003cp\u003eIn the hearing and language domain, 58.7% of participants presented adequate development, whereas 28.3% were classified as alert. Also, in the personal-social domain, 42.8% of children were classified in the alert category, followed by 39.9% in the medium category.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of scores by psychomotor development area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[95% CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGross motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[15.64\u0026ndash;16.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium-High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (31.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFine motor-adaptive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[15.19\u0026ndash;16.11]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (52.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium-High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (31.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHearing-language\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[13.27\u0026ndash;13.96]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (58.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium-High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePersonal-social\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (42.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[13.12\u0026ndash;14.11]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (39.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium-High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTotal psychomotor development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[57.46\u0026ndash;60.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium-High\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (23.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e2\u003c/sup\u003e CI: 95% confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePsychomotor development by community\u003c/h3\u003e\n\u003cp\u003eThe distribution of psychomotor development by community is presented in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Most children were categorized in the medium level of psychomotor development 51.4% (n\u0026thinsp;=\u0026thinsp;71), with some variability between communities.\u003c/p\u003e \u003cp\u003eThe community of Lucero reported the only case classified in the high category (0.7%). In contrast, Chingulle showed a higher proportion of children classified in the alert category (66.7%); however, this finding should be interpreted with caution due to the small sample size in that community (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003cp\u003eTo explore the relationship between domain-specific performance and overall developmental classification, Cramer\u0026rsquo;s V was calculated for each domain of the EAD-1. Moderate associations were observed across domains, with the strongest association found for the personal-social domain (V\u0026thinsp;\u0026asymp;\u0026thinsp;0.62), followed by the fine motor-adaptive domain (V\u0026thinsp;\u0026asymp;\u0026thinsp;0.53). Gross motor (V\u0026thinsp;\u0026asymp;\u0026thinsp;0.47) and hearing-language (V\u0026thinsp;\u0026asymp;\u0026thinsp;0.49) domains also showed moderate associations.\u003c/p\u003e \u003cp\u003eThese findings reflect the degree of association between domain-specific classifications and the overall developmental classification within this sample and should be interpreted as exploratory.\u003c/p\u003e\n\u003ch3\u003eGeographic distribution of participants in alert category\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the geographic distribution of participants in the province of Loja, highlighting the proportion of children classified in the alert category across communities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNeurodevelopment results from the interaction between biological and environmental factors, including family, social, and community contexts, which influence developmental outcomes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Children raised in socioeconomically disadvantaged environments may experience limited access to stimulation and learning opportunities, which can affect developmental progress across domains [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe findings of this study should be interpreted as descriptive observations within a non-representative sample rather than population-level estimates. Most children were classified in the medium category, while 24.6% were categorized in alert level, reflecting potential developmental vulnerability within this group.\u003c/p\u003e \u003cp\u003eComparisons with previous studies in Ecuador should be made cautiously due to methodological differences. For example, C\u0026oacute;rdova Cando et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] reported a high proportion of inadequate gross motor development in Loja, whereas Molina Calder\u0026oacute;n y Pi\u0026ntilde;on Gamez [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] reported generally adequate performance in Chone. These discrepancies may reflect differences in sampling strategies, socioeconomic conditions, and access to health services rather than true population differences.\u003c/p\u003e \u003cp\u003eIn this study, fine motor-adaptive development showed relatively more favorable distributions, with 52.9% of children classified in the medium category and 31.9% in the medium-high category, compared with reports of delays in other populations. Studies in Latin America have described a substantial proportion of infants at risk of developmental delay, particularly in low-income settings [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Psychomotor delay during early childhood may affect later motor, communication, and problem-solving skills [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe personal-social domain showed the highest proportion of alert classifications (42.8%). This domain reflects social interaction and emotional expression [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]; however, the use of the EAD-1 without prior validation in Ecuador may introduce measurement bias, particularly in culturally sensitive domains.\u003c/p\u003e \u003cp\u003eExploratory analysis using Cramer\u0026rsquo;s V showed moderate associations between domain-specific performance and overall classification, with the personal-social domain showing the strongest association. These findings reflect patterns within this sample and should not be interpreted as causal.\u003c/p\u003e \u003cp\u003eIn the hearing-language domain, most children were classified in the medium category (58.7%). Variability in language development has been reported in similar socioeconomic contexts and may be influenced by environmental and cultural factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough socioeconomic differences between communities were not formally assessed, most participants were from rural areas, which may influence access to early stimulation and developmental opportunities [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Early childhood interventions may support developmental outcomes in such contexts [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is also noteworthy that only one child (0.7%) was classified in the high developmental category, reflecting limited representation at this level within the sample.\u003c/p\u003e \u003cp\u003eOverall, these findings highlight the importance of monitoring psychomotor development in early childhood, particularly in underserved settings. Results should be interpreted cautiously and understood as preliminary observations. Future research should include larger and more representative samples and incorporate key sociodemographic variables.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eNevertheless, several limitations should be considered when interpreting the findings of this study. The use of a non-probabilistic convenience sample limits the generalizability of the results to the broader population. In addition, participants were recruited during community health fairs, which may have introduced selection bias, as caregivers attending these events may differ from the general population in terms of health-seeking behavior. The distribution of participants across communities was also uneven, with some localities represented by a small number of observations, limiting comparability between communities and restricting the interpretation of local-level differences.\u003c/p\u003e \u003cp\u003eFurthermore, key sociodemographic variables such as socioeconomic status, maternal education, and ethnicity were not available, limiting the ability to assess potential confounding factors influencing developmental outcomes. Finally, the cross-sectional design precludes causal inference and limits the ability to assess developmental trajectories over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript:\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eEAD-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eAbbreviated Development Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eOAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eOrganization of American States\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eENSANUT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eNational Health and Nutrition Survey\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eICC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eIntraclass Correlation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eCISeAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eCenter for Health Research in Latin America\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.8855%;\"\u003e\n \u003cp\u003eCEISH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85.1145%;\"\u003e\n \u003cp\u003eHuman Research Ethics Committee\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Human Research Ethics Committee (CEISH) of the Pontifical Catholic University of Ecuador with the code CEISH-493-2023, approved on July 4, 2023. Written informed consent was obtained from the caregivers of all participating children prior to data collection. All procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed for the execution of this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, B.P.M.P. and D.E.V.M.; methodology, B.P.M.P., D.E.V.M. and S.O.I.J.; software, S.O.I.J. and D.E.V.M.; validation, S.O.I.J.; formal analysis, S.O.I.J.; investigation, B.P.M.P. and D.E.V.M.; resources, B.P.M.P.; data curation, S.O.I.J.; writing\u0026mdash;original draft preparation, D.E.V.M., B.P.M.P and S.O.I.J.; writing\u0026mdash;review and editing, B.P.M.P., D.E.V.M. and S.O.I.J.; visualization, S.O.I.J.; supervision, B.P.M.P. and S.O.I.J.; project administration, B.P.M.P.; funding acquisition, B.P.M.P and D.E.V.M. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Camila Ayala for providing training on the application of the EAD-1 instrument as well as for sharing her knowledge on child development from a psychological perspective; to Belen Allauca and Adriana Esp\u0026iacute;n for their valuable support in data collection and in the administration of the development assessment; and to Ra\u0026uacute;l Parra for preparing the map graphic illustrating the distribution of the communities with alert diagnoses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, we also acknowledge Dr. Mario J. Grijalva for his essential role in facilitating the financial and institutional support required for the implementation of this project. His leadership and guidance in promoting research excellence and fostering collaborative initiatives in southern Ecuador were fundamental to the successful completion of this study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this manuscript, the author(s) used an artificial intelligence language model (ChatGPT-4/5, OpenAI, San Francisco, CA, USA) to assist with the English translation and minor linguistic polishing of the manuscript. This tool was used only to improve clarity and grammar; all scientific content, data interpretation, and conclusions were entirely generated and verified by authors. All authors have reviewed and edited the output and take full responsibility for the content of this publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRom\u0026aacute;n Sac\u0026oacute;n J, Calle Contreras P. Psychomotor development status in healthy children attending a child center in Santo Domingo. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rasp.msal.gov.ar/index.php/rasp/article/view/266\u003c/span\u003e\u003cspan address=\"https://www.rasp.msal.gov.ar/index.php/rasp/article/view/266\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Child Development, Developmental Screening, Ecuador, Early Childhood, Motor Skills, Psychomotor Development","lastPublishedDoi":"10.21203/rs.3.rs-9397427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9397427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo describe psychomotor development in children aged 12 to 23 months from rural and urban communities in southern Ecuador using the Abbreviated Development Scale (EAD-1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 138 children were evaluated in the cantons of Calvas and Gonzanamá. Most participants were classified in the medium developmental category (51.4%), while 24.6% were categorized in the alert level. The personal-social domain showed the highest proportion of alert classifications (42.8%), followed by the hearing-language and gross motor domains. Fine motor-adaptive performance showed a higher proportion of classifications in the medium and medium-high categories. These findings reflect developmental performance within a non-probabilistic sample and should be interpreted with caution.\u003c/p\u003e","manuscriptTitle":"Psychomotor development in children aged 12-23 months from communities in southern Ecuador: a descriptive research note","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 05:51:31","doi":"10.21203/rs.3.rs-9397427/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-12T10:57:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T09:18:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233634710206821173256140252777578601167","date":"2026-04-28T09:38:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T12:48:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52767409937200333666307907306299136252","date":"2026-04-23T11:13:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169661050229799758603363511442972583624","date":"2026-04-23T07:56:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T00:26:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-21T00:24:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T15:03:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-19T18:21:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2026-04-19T18:18:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0182d836-db08-44cb-88a1-1a8a65654730","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-12T10:57:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T09:18:39+00:00","index":34,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T14:23:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 05:51:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9397427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9397427","identity":"rs-9397427","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}