An Analysis of Latent Profiles of Father-Child Interaction: Classification Predictors and Differences in Children’s Socio-Emotional Development

2021 ◽  
Vol 52 (3) ◽  
pp. 424-446
Author(s):  
Saerom Park ◽  
Boram No
Keyword(s):  
Emotional Development ◽  
Latent Profile Analysis ◽  
Interaction Analysis ◽  
First Graders ◽  
Multinomial Logistic Regression ◽  
Research Question ◽  
Panel Study ◽  
Korean Children ◽  
Child Interaction ◽  
Complex Sample

The purpose of this study was to (1) classify subgroups of father-child interaction based on the type of interaction activity (routine, learning, and play interaction), (2) examine the effects of socio-demographic factors, father’s psycho-emotional factors, and maternal factors on the different types of father-child interaction groups, and (3) analyze differences in socio-emotional development of first graders in elementary school according to the type of father-child interaction. Analysis of 1,469 families (mothers, fathers, and children) was conducted using latent profile analysis (research question 1), complex sample multinomial logistic regression (RQ 2), and complex sample general linear modeling (RQ 3). Samples originated from the eighth wave (2015) of the Panel Study on Korean Children (PSKC). The main results were as follows. First, three distinct latent groups of father-child interaction based on the quantitative level of daily interaction were found: high-interaction (HI, 7.85%), medium-interaction (MI, 51.73%), and low-interaction (LI, 40.42%). Second, factors such as father’s happiness, positive evaluation of work-family balance, and mother-child interaction level were significant correlates for the classification of father-child interaction. Third, first graders in the HI group showed the highest levels of self-esteem in comparison to the other two groups and reported a higher level of subjective happiness in comparison to the LI group. These results bring to attention the importance of father-child interaction affecting the outcomes of children’s socio-emotional development.

Developmental Trajectories of Negative Peer Play in Preschool: Predictors and Outcomes1

2021 ◽  
Vol 52 (3) ◽  
pp. 447-479
Author(s):  
Suhyun Lee ◽  
Seri Kim ◽  
Kangyi Lee
Keyword(s):  
School Readiness ◽  
Emotional Development ◽  
Developmental Trajectories ◽  
Panel Study ◽  
Policy Implications ◽  
Social And Emotional Development ◽  
Peer Play ◽  
Korean Children ◽  
Approach To Learning ◽  
Social And Emotional

This study aims to identify age-related trajectories of preschoolers’ negative peer play, their predictors, and school-related outcomes. The participants were 1,547 children in the Panel Study on Korean Children and their teachers and parents. Using latent class growth analysis, we identified negative peer play trajectories of children between 4 and 6 years old. Analyses of variances were conducted to investigate whether children’s school readiness at 6 years old differed between the trajectories. Finally, multinomial logistic regressions were conducted to explore how teacher-child interactions influenced membership in the trajectories. Three developmental trajectories of play disruption were found: “Low” (64.3%), “Constant-higher” (34.3%), and “U-curve” (1.4%). In the case of play disconnection, four trajectories were found: “Low-increase” (57.6%), “Moderate-decrease” (26.5%), “Sharp-increase” (10.1%), and “High-decrease” (5.8%). The trajectories of play disruption were related to social and emotional development and approach to learning. The trajectories of play disconnection were related to all aspects of school readiness including social and emotional development, approach to learning, communication, and cognitive development. Teacher-child interactions that encourage children’s prosocial behaviors and positive peer interactions predicted likely membership in “Low-increase” play disconnection development. Also, teachers’ affectionate and sensitive qualities during the interaction with children predicted a “Low” trajectory of play disruption. Together, the results emphasized the protective power of positive teacher-child interactions in the development of preschool negative peer play. Based on the findings, policy implications are discussed with regard to teacher education.

scholarly journals Effects of mother–child interaction on school adaptation of children according to maternal depression

2021 ◽  
Vol 8 (1) ◽  
pp. 33-42
Author(s):  
Hanna Lee ◽  
Jeong-Won Han
Keyword(s):  
Maternal Depression ◽  
Panel Study ◽  
Developmental Trajectory ◽  
Latent Growth ◽  
Normal Range ◽  
Korean Children ◽  
School Adaptation ◽  
School Aged Children ◽  
Child Interaction ◽  
Mother Child Interaction

Abstract Objective Factors influencing school adaptation of school-aged children include both executive function (EF) and parent–child interaction. This study aims to investigate the developmental trajectory of mother–child interaction longitudinally using latent growth model analysis. Methods A longitudinal descriptive survey study was conducted. The participants comprised of 1,614 mothers and school-aged children, who participated in the Panel Study on Korean Children (6th–8th panel surveys). A model was designed and analyzed using latent growth modeling to estimate the pattern of change over time. Results In the group where the maternal depression was within the normal range, only the path by which the change rate of mother–child interaction affected school adaptation of children was statistically nonsignificant (t = 1.007, p = 0.314). In the group where maternal depression was mild or higher, only the paths by which the initial value of mother–child interaction affected EF difficulty (t = −2.75, p = 0.032) and EF difficulty affected school adaptation (t = −7.876, p < 0.001) were statistically significant. Conclusions This study confirms the research models developed by dividing mother–child interaction into two groups according to depression levels (i.e., normal range and mild or higher-level depression). The findings provide a basis for construction of individualized interventions.

Providing instrumental support to older parents of multi-child families in China: are there different within-family patterns?

2021 ◽  
pp. 1-18
Author(s):  
Jia Chen ◽  
Xiaochen Zhou ◽  
Nan Lu
Keyword(s):  
Adult Children ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Multinomial Logistic Regression ◽  
Adult Child ◽  
Instrumental Support ◽  
Older Parents ◽  
Older Mothers ◽  
Family Patterns ◽  
Using Data

Abstract Older parents in China rely heavily on their adult children for instrumental assistance. In different multi-child families, multiple offspring may co-operate in providing instrumental support to older parents in distinct ways in terms of how much support they provide on average and how much differentiation exists between them when they provide such support within a family. We aimed to identify different within-family patterns in relation to multiple offspring's instrumental support to an older parent in Chinese multi-child families, and to investigate potential predictors for different within-family patterns. Using data from the China Family Panel Studies (2016), we had a working sample of 5,790 older adults aged 60+ (mean = 68.54, standard deviation = 6.60). We employed latent profile analysis (LPA) to classify within-family patterns and multinomial logistic regression to investigate predictors. Our findings identified three within-family patterns: dissociated (59.10%), highly differentiated (29.60%) and united-filial (11.30%). Older parents in the highly differentiated families tended to be older, mothers, divorced/widowed and to have poorer physical health compared to their counterparts in the dissociated families. In contrast, the composition characteristics of multiple adult children played more important roles in determining the united-filial within-family pattern. The united-filial families were more likely to have fewer adult children, at least one adult daughter and at least one co-residing adult child.

scholarly journals The Reciprocal Longitudinal Relationship between Executive Dysfunction and Happiness in Korean Children

2021 ◽  
Vol 18 (15) ◽  
pp. 7764
Author(s):  
Yoonhee Sung ◽  
Eunsil Choi
Keyword(s):  
Elementary School ◽  
Child Care ◽  
Panel Study ◽  
Executive Dysfunction ◽  
Clinical Implications ◽  
Korean Children ◽  
Time Points ◽  
Lagged Effects ◽  
Reciprocal Influences ◽  
Longitudinal Relationships

The goal of this study was to examine the reciprocal longitudinal relationships between executive dysfunction and happiness for Korean children. We used data from the Panel Study of Korean Children (PSKC) conducted by the Korean Institute of Child Care and Education. A total of 1240 valid responses from the first to third grade in elementary school were analyzed using autoregressive crossed-lagged modeling. As a result, executive dysfunction and happiness were found to have reciprocal influences over the three time points. We also found that the cross-lagged effects of executive dysfunction and happiness were stronger than those of happiness on executive dysfunction. Clinical implications and limitations were discussed.

scholarly journals RMR-Related MAP2K6 Gene Variation on the Risk of Overweight/Obesity in Children: A 3-Year Panel Study

2021 ◽  
Vol 11 (2) ◽  
pp. 91
Author(s):  
Myoungsook Lee ◽  
Yunkyoung Lee ◽  
Inhae Kang ◽  
Jieun Shin ◽  
Sungbin R. Sorn
Keyword(s):  
Dietary Intake ◽  
Resting Metabolic Rate ◽  
Panel Study ◽  
Snp Array ◽  
Fat Intake ◽  
Nucleotide Polymorphisms ◽  
Korean Children ◽  
Gene Variation ◽  
Genome Wide ◽  
Prevalence Of Obesity

From a pilot GWAS, seven MAP2K6 (MEK6) SNPs were significantly associated with resting metabolic rate (RMR) in obese children aged 8–9 years. The aim of this study was to investigate how RMR-linked MEK6 variation affected obesity in Korean children. With the follow-up students (77.9%) in the 3-year panel study, the changes of the variables associated with obesity (such as anthropometrics, blood biochemistry, and dietary intake) were collected. After the MEK6 SNPs were screened by Affymetrix Genome-Wide Human SNP array 6.0, the genotyping of the seven MEK6 SNPs was performed via SNaPshot assay. As the prevalence of obesity (≥85th percentile) increased from 19.4% to 25.5%, the rates of change of the variables RMR, body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), and dietary intake (energy and carbohydrate intakes) increased. The rate of overweight/obesity was higher in all mutant alleles of the seven MEK6 SNPs than it was in the matched children without mutant alleles. However, over the 3-year study period, RMRs were only significantly increased by the mutants of two single nucleotide polymorphisms (SNPs), rs996229 and rs756942, mainly related to male overweight/obesity as both WC and SBP levels increased. In the mutants of two of the SNPs, the odds ratio of overweight/obesity risk was six times higher in the highest tercile of fat intake and SBP than those of the lowest tercile. For personalized medicine to prevent pediatric obesity, SBP, WC, and dietary fat intake should be observed, particularly if boys have mutants of MEK6 SNPs, rs9916229, or rs756942.

scholarly journals Associations between Child and Family Level Correlates and Behavioural Patterns in School-Aged Children

Children ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 1023
Author(s):  
Ninoshka J. D’Souza ◽  
Miaobing Zheng ◽  
Gavin Abbott ◽  
Sandrine Lioret ◽  
Kylie D. Hesketh
Keyword(s):  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Multinomial Logistic Regression ◽  
Working Hours ◽  
Target Population ◽  
Older Children ◽  
Increased Risk ◽  
Behavioural Patterns ◽  
Family Level ◽  
The Individual

Identifying correlates of behavioural patterns are important to target population sub-groups at increased health risk. The aim was to investigate correlates of behavioural patterns comprising four behavioural domains in children. Data were from the HAPPY study when children were 6–8 years (n = 335) and 9–11 years (n = 339). Parents reported correlate and behavioural data (dietary intake, physical activity, sedentary behaviour, and sleep). Behavioural data were additionally captured using accelerometers. Latent profile analysis was used to derive patterns. Patterns were identified as healthy, unhealthy, and mixed at both time points. Multinomial logistic regression tested for associations. Girls were more likely to display healthy patterns at 6–8 years and display unhealthy and mixed patterns at 9–11 years than boys, compared to other patterns at the corresponding ages. Increased risk of displaying the unhealthy pattern with higher age was observed at both timepoints. At 9–11 years, higher parental working hours were associated with lower risk of displaying mixed patterns compared to the healthy pattern. Associations observed revealed girls and older children to be at risk for unhealthy patterns, warranting customisation of health efforts to these groups. The number of behaviours included when deriving patterns and the individual behaviours that dominate each pattern appear to be drivers of the associations for child level, but not for family level, correlates.

scholarly journals Talent Performance Analysis Using People Analytics Approach

2021 ◽  
Vol 4 (1) ◽  
pp. 216-230
Author(s):  
Fahreza Nasril ◽  
Dian Indiyati ◽  
Gadang Ramantoko
Keyword(s):  
Logistic Regression ◽  
Multinomial Logistic Regression ◽  
Research Question ◽  
Development Program ◽  
Individual Performance ◽  
Study Data ◽  
Regression Method ◽  
Process Data ◽  
Logistic Regression Method ◽  
The Right

The purpose of this study was to answer the research question "How is the prediction of Talent Performance in the following year with the application of People Analytics?" and knowing the description of employees who are potential talents, the resulting performance contributions, to the description of the development and retention efforts needed by Talent in order to be able to maintain their future performance and position as Talents compared to the previous People Analytics method using predictive analysis, namely prediction of Talent Performance in the year next. In this study, data analysis using the Multivariate Logistic Regression method is used to get the Prediction of the Performance of Talents who become the object of research in the form of individual performance quickly and precisely in accordance with the patterns drawn by individual Performance score data in previous years. And can provide insight regarding the projected strategies that need to be done to maintain the improvement of individual talent performance in the years of the assessment period. It also helps management in making decisions about the right Talent development program and determining which Talents are priorities. The population in this study were the talents of employees of PT. Angkasa Pura II (Persero) with a managerial level consisting of: Senior Leader, Middle Leader, and First Line Leader who has a Person Grade (PG) range of 13 to 21. The sample used is Middle Leader level talent with specified criteria and through a process data cleansing. The results of this study indicate that the variable that significantly affects the performance of the following year is the performance of the previous 2 years. Then prediction analysis can be done using these independent variables with the Multinomial Logistic Regression method, and to get prediction results with better accuracy can be done by the Random Forest method.

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