Predictive Model Construction for Social–Emotional Competence of Toddlers in Shanghai, China: A Population-Based Study

OBJECTIVE: To construct a simple model containing predictors derived from Chinese Learning Accomplishment Profile (C-LAP) to better the evaluation of the social–emotional development of toddlers aged 24–36 months. METHOD: The test results by C-LAP system and demographic information of toddlers aged 24–36 months were collected between 2013 and 2019 in Shanghai, China, whose guardians were voluntary to accept the investigation. We developed a norm with the dataset based on the study population. With the norm, stepwise regression and best subset analysis were applied to select predictors. RESULTS: Relying on the norm established and stepwise regression and also the best subset analysis, an optimal model containing only 6 indicators was finally determined and the nomogram of the model was constructed. In the training and validation dataset, the AUCs of the optimal model were 0.95 (95% CI: 0.94–0.96) and 0.88 (95% CI: 0.85–0.90), respectively. When the cutoff point of the model was set at 0.04, its sensitivity in training and validation dataset was 0.969 and 0.949, respectively, and the specificity in training and validation dataset is 0.802 and 0.736, respectively. CONCLUSION: A simplified predictive model which includes only 6 items derived from C-LAP is developed to evaluate the probabilities of being at risk of developmental problem in social–emotional development for toddlers aged 24–36 months. Meanwhile, specificity and sensitivity of the model may be high enough for future fast screening.