家庭環境因素對臺灣學齡前幼兒長期睡眠發展類型的影響

Abstract

健康的睡眠對於幼兒發育與身心功能至關重要，包含身體健康、社會情緒調節與認知功能等，因此，本研究旨在探討影響學齡前幼兒睡眠發展的關鍵因素，試圖依據幼兒睡眠發展軌跡進行群體分類，並分析幼兒自身條件、家庭環境因素及父母教養態度對其睡眠發展的影響。本研究使用「臺灣幼兒發展調查資料庫建置計畫（Kids in Taiwan: National Longitudinal Study of Child Development& Care, KIT）」數據資料，收集1,822名幼兒三歲、四歲、五歲和六歲時四個波段的睡眠狀態，輔以使用三歲時的背景資料，以探討睡眠發展軌跡與幼兒自身條件、家庭環境及父母教養之間的關聯性。 研究方法上，本研究採用潛在類別成長分析（Latent Class Growth Analysis, LCGA）來分類幼兒睡眠發展軌跡，再以卡方檢定（The Chi-Squared Test of Independence）和單因子變異數分析（ANOVA）來檢驗睡眠軌跡與各變數之間的關聯，最後採用多元羅吉斯迴歸分析（Multiple logistic regression analysis），進一步探討各變數對睡眠發展的影響。 研究結果區分出三種不同的幼兒睡眠發展群體，分別為「睡眠良好組」、「睡眠穩定組」和「睡眠不佳組」。不同的睡眠發展軌跡與幼兒三歲時是否參與托育、是否獨立睡眠、健康狀況、父母教育程度、家庭收入充足性、父母憂鬱程度、共親職程度、使用3C螢幕時間，以及回應教養等因素存在顯著關聯；運用多元羅吉斯迴歸模型分析後，更確定是否獨立睡眠、家庭收入充足性，以及使用3C螢幕時間對於幼兒睡眠發展軌跡的影響最為顯著。 透過確認影響幼兒睡眠發展的主要因素，不僅可提醒家長在學齡前期採取適切的育兒方法，以幫助幼兒養成良好的健康睡眠習慣，亦可為公部門制定與推行促進幼兒睡眠發展政策提供參考依據。Healthy sleep is crucial for early childhood development and overall physiological and psychological well-being, including physical health, socio-emotional regulation, and cognitive functioning. This study aims to investigate the key factors influencing sleep development in preschool-aged children by categorizing them into different developmental trajectories based on their sleep patterns. Furthermore, the study examines the impact of individual child characteristics, family environmental factors, and parental parenting practices on children's sleep development. The research utilizes data from the Kids in Taiwan: National Longitudinal Study of Child Development & Care (KIT), collecting sleep-related information across four waves when children were aged three, four, five, and six years old. Additionally, background data from age three were incorporated to analyze the associations between sleep development trajectories, child characteristics, family environment, and parenting practices. Methodologically, this study employs Latent Class Growth Analysis (LCGA) to classify sleep development trajectories. Subsequently, Chi-Squared Test of Independence and Analysis of Variance (ANOVA) are used to examine associations between sleep trajectories and various predictor variables. Finally, Multiple Logistic Regression Analysis is conducted to further investigate the effects of these variables on sleep development.The findings identify three distinct sleep development trajectories: the"Healthy Sleep Group", "Stable Sleep Group", and "Poor Sleep Group." The results indicate that variations in sleep trajectories are significantly associated with multiple factors, including participation in childcare at age three, independent sleeping habits, overall health status, parental educational attainment, family income adequacy, parental depression levels, co-parenting quality, screen time exposure to 3C devices, and responsive parenting practices. Furthermore, multiple logistic regression analysis confirms that independent sleeping, family income adequacy, and screen time duration are the most significant predictors of children's sleep development trajectories. By identifying the key factors influencing early childhood sleep development, this study provides valuable insights for parents to adopt appropriate caregiving strategies during the preschool years to foster healthy sleep habits. Additionally, the findings offer empirical evidence for policymakers in designing and implementing interventions aimed at promoting optimal sleep development in young children.