scholarly journals Emergent patterns of risk for psychopathology: The influence of infant avoidance and maternal caregiving on trajectories of social reticence

2015 ◽  
Vol 27 (4pt1) ◽  
pp. 1163-1178 ◽  
Author(s):  
Kathryn A. Degnan ◽  
Amie Ashley Hane ◽  
Heather A. Henderson ◽  
Olga L. Walker ◽  
Melissa M. Ghera ◽  
...  
Keyword(s):  
At Risk ◽  
Early Childhood ◽  
Latent Class ◽  
Maternal Sensitivity ◽  
Latent Class Growth Analysis ◽  
Maternal Caregiving ◽  
Latent Class Growth ◽  
Stable Trajectory ◽  
At Home

AbstractThe current study investigated the influential role of infant avoidance on links between maternal caregiving behavior and trajectories at risk for psychopathology. A sample of 153 children, selected for temperamental reactivity to novelty, was followed from infancy through early childhood. At 9 months, infant avoidance of fear-eliciting stimuli in the laboratory and maternal sensitivity at home were assessed. At 36 months, maternal gentle discipline was assessed at home. Children were repeatedly observed in the lab with an unfamiliar peer across early childhood. A latent class growth analysis yielded three longitudinal risk trajectories of social reticence behavior: a high-stable trajectory, a high-decreasing trajectory, and a low-increasing trajectory. For infants displaying greater avoidance, 9-month maternal sensitivity and 36-month maternal gentle discipline were both positively associated with membership in the high-stable social reticence trajectory, compared to the high-decreasing social reticence trajectory. For infants displaying lower avoidance, maternal sensitivity was positively associated with membership in the high-decreasing social reticence trajectory, compared to the low-increasing trajectory. Maternal sensitivity was positively associated with the high-stable social reticence trajectory when maternal gentle discipline was lower. These results illustrate the complex interplay of infant and maternal behavior in early childhood trajectories at risk for emerging psychopathology.

scholarly journals Trajectories of Developmental Functioning Among Children of Adolescent Mothers: Factors Associated With Risk for Delay

2016 ◽  
Vol 121 (4) ◽  
pp. 346-363 ◽  
Author(s):  
Laudan B. Jahromi ◽  
Adriana J. Umaña-Taylor ◽  
Kimberly A. Updegraff ◽  
Katharine H. Zeiders
Keyword(s):  
At Risk ◽  
Adolescent Mothers ◽  
Latent Class ◽  
Developmental Trajectories ◽  
Lower Income ◽  
Latent Class Growth Analysis ◽  
Factors Associated ◽  
Developmental Functioning ◽  
Group B ◽  
Latent Class Growth

Abstract Children of adolescent mothers are at risk for developmental delays. Less is known about the heterogeneity in these children's developmental trajectories, and factors associated with different patterns of development. This longitudinal study used latent class growth analysis (LCGA) to identify distinct trajectories in children of Mexican-origin adolescent mothers (N = 204). Three distinct groups emerged: (a) a Delayed/Decreasing Functioning group, (b) an At-Risk/Recovering Functioning group, and (c) a Normative/Stable Functioning group. Children with Delayed/Decreasing Functioning were more likely than those with Normative/Stable Functioning to have families with lower income, fewer learning materials at home, and adolescent mothers with more depressive symptoms and greater coparental conflict with adolescents' mother figures. The results contribute to knowledge about factors associated with risk of delay.

Identifying Students at Risk: An Examination of Computer-Adaptive Measures and Latent Class Growth Analysis

2017 ◽  
Vol 34 (1) ◽  
pp. 18-35 ◽  
Author(s):  
Milena Keller-Margulis ◽  
Samuel D. McQuillin ◽  
Juan Javier Castañeda ◽  
Sarah Ochs ◽  
John H. Jones
Keyword(s):  
At Risk ◽  
Growth Analysis ◽  
Latent Class ◽  
Latent Class Growth Analysis ◽  
Students At Risk ◽  
Latent Class Growth

scholarly journals Exploring Risk and Resilient Profiles for Functional Impairment and Baseline Predictors in a 2-Year Follow-Up First-Episode Psychosis Cohort Using Latent Class Growth Analysis

2020 ◽  
Vol 10 (1) ◽  
pp. 73
Author(s):  
Estela Salagre ◽  
Iria Grande ◽  
Brisa Solé ◽  
Gisela Mezquida ◽  
Manuel Cuesta ◽  
...  
Keyword(s):  
Psychosocial Functioning ◽  
Latent Class ◽  
First Episode Psychosis ◽  
First Episode ◽  
Latent Class Growth Analysis ◽  
Premorbid Adjustment ◽  
Episode Psychosis ◽  
Severe Impairment ◽  
Latent Class Growth ◽  
Stable Trajectory

Being able to predict functional outcomes after First-Episode Psychosis (FEP) is a major goal in psychiatry. Thus, we aimed to identify trajectories of psychosocial functioning in a FEP cohort followed-up for 2 years in order to find premorbid/baseline predictors for each trajectory. Additionally, we explored diagnosis distribution within the different trajectories. A total of 261 adults with FEP were included. Latent class growth analysis identified four distinct trajectories: Mild impairment-Improving trajectory (Mi-I) (38.31% of the sample), Moderate impairment-Stable trajectory (Mo-S) (18.39%), Severe impairment-Improving trajectory (Se-I) (12.26%), and Severe impairment-Stable trajectory (Se-S) (31.03%). Participants in the Mi-I trajectory were more likely to have higher parental socioeconomic status, less severe baseline depressive and negative symptoms, and better premorbid adjustment than individuals in the Se-S trajectory. Participants in the Se-I trajectory were more likely to have better baseline verbal learning and memory and better premorbid adjustment than those in the Se-S trajectory. Lower baseline positive symptoms predicted a Mo-S trajectory vs. Se-S trajectory. Diagnoses of Bipolar disorder and Other psychoses were more prevalent among individuals falling into Mi-I trajectory. Our findings suggest four distinct trajectories of psychosocial functioning after FEP. We also identified social, clinical, and cognitive factors associated with more resilient trajectories, thus providing insights for early interventions targeting psychosocial functioning.

Mother's Perspective About Using the Gadget Safeness for Children

2020 ◽  
Vol 14 (2) ◽  
pp. 313-320
Author(s):  
Colti Sistiarani ◽  
Bambang Hariyadi ◽  
Saudin Yuniarno ◽  
Endo Dardjito
Keyword(s):  
Early Childhood ◽  
Young Children ◽  
Digital Technology ◽  
Media Use ◽  
Parental Mediation ◽  
Early Years ◽  
Special Issue ◽  
Children's Media ◽  
At Home

The rapid development of technology makes it easier for mothers to provide stimulation related to growth and development using gadgets. However, parental knowledge is needed about the safe limits of using a gadget in early childhood. This study aims to determine the perspective and behavior of mothers about the use of gadgets in toddlers. The method used is quantitative research with a cross-sectional approach. The participants of this study were thirty-one mothers who have early childhood and who are empowering family welfare. The inclusion criteria were mothers who agreed to be respondents, the exclusion criteria for mothers who did not have gadgets. This study uses a questionnaire measurement instrument for data collection. Data analysis was performed univariate and bivariate using the chi-square test. The results of the study concluded that the mother's knowledge regarding the safety of using a gadget was still lacking, with a value of around 54.8%, while the mother's behavior related to the same thing was better, which was around 58.1%. The relationship test shows that there is a strong enough relationship between maternal knowledge and maternal behavior in introducing or using gadgets in toddlers.  Keywords: Early Childhood, Mother Perspective, Gadget Safeness  References Appel, M. (2012). Are heavy users of computer games and social media more computer literate? Computers and Education, 59(4), 1339–1349. https://doi.org/10.1016/j.compedu.2012.06.004 Bandura, A. (1977). Social learning theory. Prentice-Hall. Cingel, D. P., & Krcmar, M. (2013). Predicting Media Use in Very Young Children: The Role of Demographics and Parent Attitudes. Communication Studies, 64(4), 374–394. https://doi.org/10.1080/10510974.2013.770408 Connell, S. L., Lauricella, A. R., & Wartella, E. (2015). Parental Co-Use of Media Technology with their Young Children in the USA. Journal OfChildren and Media, 9(1), 5–21. https://doi.org/10.1080/17482798.2015.997440 Haines, J., O’Brien, A., McDonald, J., Goldman, R. E., Evans-Schmidt, M., Price, S., King, S., Sherry, B., & Taveras, E. M. (2013). Television Viewing and Televisions in Bedrooms: Perceptions of Racial/Ethnic Minority Parents of Young Children. Journal of Child and Family Studies, 22(6), 749–756. https://doi.org/10.1007/s10826-012-9629-6 Jones, I., & Park, Y. (2015). Virtual worlds: Young children using the internet. Young children and families in the information age. Educating the young child (Advances in theory and research, implications for practice) (I. K. Heider & J. M. Renck (eds.); Volume 10). Springer. Lauricella, A. R., Wartella, E., & Rideout, V. J. (2015). Young children’s screen time: The complex role of parent and child factors. Journal of Applied Developmental Psychology, 36, 11–17. https://doi.org/10.1016/j.appdev.2014.12.001 Livingstone, S, Görzig, A., & Ólafsson, K. (2011). Disadvantaged children and online risk. http://eprints.lse.ac.uk/39385/ Livingstone, Sonia, Mascheroni, G., Dreier, M., Chaudron, S., & Lagae, K. (2015). How parents of young children manage digital devices at home: The role of income, education and parental style (Issue September). Livingstone, Sonia, Ólafsson, K., Helsper, E. J., Lupiáñez-Villanueva, F., Veltri, G. A., & Folkvord, F. (2017). Maximizing Opportunities and Minimizing Risks for Children Online: The Role of Digital Skills in Emerging Strategies of Parental Mediation. Journal of Communication, 67(1), 82–105. https://doi.org/10.1111/jcom.12277 M, S. (2017). The Impact of using Gadgets on Children. Journal of Depression and Anxiety, 07(01), 1–3. https://doi.org/10.4172/2167-1044.1000296 Marsh, J., Hannon, P., Lewis, M., & Ritchie, L. (2017). Young children’s initiation into family literacy practices in the digital age. Journal of Early Childhood Research, 15(1), 47–60. https://doi.org/10.1177/1476718X15582095 Mifsud, C. L., & Petrova, R. (2017). Young Children (0-8) and Digital Technology. In JRC Science and Policies Reports. Nevski, E., & Siibak, A. (2016). The role of parents and parental mediation on 0–3-year olds’ digital play with smart devices: Estonian parents’ attitudes and practices. Early Years, 36(3), 227–241. https://doi.org/10.1080/09575146.2016.1161601 Nikken, P. (2017). Implications of low or high media use among parents for young children’s media use. Cyberpsychology, 11(3 Special Issue). https://doi.org/10.5817/CP2017-3-1 Nikken, P., & de Haan, J. (2015). Guiding young children’s internet use at home: Problems that parents experience in their parental mediation and the need for parenting support. Cyberpsychology, 9(1). https://doi.org/10.5817/CP2015-1-3 Piotrowski, J. (2017). Media exposure during infancy and early childhood: The effect of content and context on learning and development. In I. R. Barr & D. Linebarger (Eds.), The parental media mediation context of young children’s media use.(pp. 205–219). Springer International Publishing. Plowman, L., Stevenson, O., Stephen, C., & McPake, J. (2012). Preschool children’s learning with technology at home. Computers and Education, 59(1), 30–37. https://doi.org/10.1016/j.compedu.2011.11.014 Rasmussen, E. E., Shafer, A., Colwell, M. J., White, S., Punyanunt-Carter, N., Densley, R. L., & Wright, H. (2016). Relation between active mediation, exposure to Daniel Tiger’s Neighborhood, and US preschoolers’ social and emotional development. Journal of Children and Media, 10(4), 443–461. https://doi.org/10.1080/17482798.2016.1203806 Smahelova, M., Juhová, D., Cermak, I., & Smahel, D. (2017). Mediation of young children’s digital technology use: The parents’ perspective. Cyberpsychology, 11(3 Special Issue). https://doi.org/10.5817/CP2017-3-4 Troseth, G. L., Strouse, G. A., & Russo Johnson, C. E. (2017). Early Digital Literacy: Learning to Watch, Watching to Learn. In Cognitive Development in Digital Contexts. Elsevier Inc. https://doi.org/10.1016/B978-0-12-809481-5.00002-X Vaala, S. E. (2014). The Nature and Predictive Value of Mothers’ Beliefs Regarding Infants’ and Toddlers’ TV/Video Viewing: Applying the Integrative Model of Behavioral Prediction. Media Psychology, 17(3), 282–310. https://doi.org/10.1080/15213269.2013.872995 Zaman, B., & Mifsud, C. L. (2017). Editorial: Young children’s use of digital media and parental mediation. Cyberpsychology, 11(3 Special Issue), 9. https://doi.org/10.5817/CP2017-3-xx

scholarly journals The course of social media use problems in secondary school adolescents: A latent class growth analysis

2021 ◽  
Author(s):  
Maartje Boer ◽  
gonneke stevens ◽  
Catrin Finkenauer ◽  
Regina van den Eijnden
Keyword(s):  
Social Media ◽  
Secondary School ◽  
Growth Analysis ◽  
Latent Class ◽  
Media Use ◽  
Latent Class Growth Analysis ◽  
Social Media Use ◽  
Immigrant Background ◽  
Low Levels ◽  
Latent Class Growth

Little is known about how addiction-like social media use (SMU) problems evolve over time. Using four waves of longitudinal data collected in 2015-2019 from 1,414 adolescents (Mage = 12.5, 46.0% girl, 21.9% immigrant background), this study aimed to identify adolescents’ trajectories of SMU problems in parallel with their trajectories of SMU intensity. Latent class growth analysis identified two subgroups with persistently high levels of SMU problems, of which one with high (24.7%) and one with average SMU intensity (14.8%), and two subgroups with persistently low levels of SMU problems, of which one with low (22.3%) and one with high SMU intensity (38.2%). Compared to the largest subgroup, the two subgroups with high levels of SMU problems showed more problematic profiles.

scholarly journals Symptom Trajectories in Children Receiving Treatment for Leukemia: A Latent Class Growth Analysis With Multitrajectory Modeling

2017 ◽  
Vol 54 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Marilyn J. Hockenberry ◽  
Mary C. Hooke ◽  
Cheryl Rodgers ◽  
Olga Taylor ◽  
Kari M. Koerner ◽  
...  
Keyword(s):  
Growth Analysis ◽  
Latent Class ◽  
Latent Class Growth Analysis ◽  
Symptom Trajectories ◽  
Latent Class Growth
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