A developmental typology of adolescent personality

2010 ◽  
Vol 24 (4) ◽  
pp. 309-323 ◽  
Author(s):  
Theo A. Klimstra ◽  
William W. Hale ◽  
Quinten A. W. Raaijmakers ◽  
Susan J. T. Branje ◽  
Wim H. J. Meeus
Keyword(s):  
Growth Analysis ◽  
Latent Class ◽  
Developmental Trajectories ◽  
Personality Types ◽  
Latent Class Growth Analysis ◽  
Problem Behaviour ◽  
Cross Sectional ◽  
Wave Data ◽  
Low Levels ◽  
Latent Class Growth

The purpose of the current study is to examine whether Block's personality types (i.e. Resilients, Undercontrollers and Overcontrollers) are replicable as developmental trajectories. We applied a Latent Class Growth Analysis (LCGA) framework to five‐ annual‐wave data on a sample of early to middle adolescents (n = 923). Our results showed that Block's Resilients, Undercontrollers and Overcontrollers are indeed replicable as developmental trajectories across adolescence. These developmental types were related to problem behaviour in a similar way as types found in studies using cross‐sectional data. As such, Resilients reflected low levels of problem behaviour, Undercontrollers had high levels of delinquency and Overcontrollers had high levels of depression. Implications and suggestions for further research are discussed. Copyright © 2009 John Wiley & Sons, Ltd.

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.

Impacts of Low Self-control and Opportunity Structure on Cyberbullying Developmental Trajectories: Using a Latent Class Growth Analysis

2020 ◽  
pp. 001112872095001
Author(s):  
Sujung Cho ◽  
Steven Glassner
Keyword(s):  
High School Students ◽  
Early Onset ◽  
Growth Analysis ◽  
Latent Class ◽  
Developmental Trajectories ◽  
Self Control ◽  
Latent Class Growth Analysis ◽  
School Students ◽  
Low Self Control ◽  
Latent Class Growth

This study tested self-control and opportunities theories to examine cyberbullying developmental trajectories through the estimation of a latent class growth analysis. Data from a 6-year longitudinal study of middle- and high-school students from South Korea were analyzed to examine if there are unique growth trajectories for cyberbullying perpetration when accounting for low self-control and opportunity factors. Results suggest that there are three distinct subgroups: (1) a normative trajectory group, (2) an increasing and late-peak group, and (3) an early onset and decreasing group. Low self-control was found to be significantly associated with early onset/decreasing cyberbullying. Opportunity to utilize cyberspace was significantly related with increasing/ late peak cyberbullying but did not significantly mediate the effect of low self-control on class membership.

scholarly journals Exploring distinct trajectories of use of telehealth devices among adults with hypertension: a latent class growth analysis approach

2018 ◽  
Vol 18 (s1) ◽  
pp. 159
Author(s):  
Ting Ye ◽  
Pei Zhang ◽  
Chengzhong Xu ◽  
Zijing Pan ◽  
Yongfei Wang ◽  
...  
Keyword(s):  
Growth Analysis ◽  
Latent Class ◽  
Analysis Approach ◽  
Latent Class Growth Analysis ◽  
Latent Class Growth

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

A Longitudinal, Latent Class Growth Analysis of the Association of Aggression and Special Education in an Urban Sample

2017 ◽  
Vol 22 (2) ◽  
pp. 135-147
Author(s):  
Shelley R. Hart ◽  
Rashelle J. Musci ◽  
Tal Slemrod ◽  
Emily Flitsch ◽  
Nicholas Ialongo
Keyword(s):  
Special Education ◽  
Growth Analysis ◽  
Latent Class ◽  
Latent Class Growth Analysis ◽  
Urban Sample ◽  
Latent Class Growth

Depression symptoms are persistent in Type 2 diabetes: risk factors and outcomes of 5-year depression trajectories using latent class growth analysis

2017 ◽  
Vol 34 (8) ◽  
pp. 1108-1115 ◽  
Author(s):  
S. R. Whitworth ◽  
D. G. Bruce ◽  
S. E. Starkstein ◽  
W. A. Davis ◽  
T. M. E. Davis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Growth Analysis ◽  
Latent Class ◽  
Diabetes Risk ◽  
Depression Symptoms ◽  
Latent Class Growth Analysis ◽  
Diabetes Risk Factors ◽  
Latent Class Growth

Constructive, illusory, and distressed posttraumatic growth among survivors of breast cancer: A 7-year growth trajectory study

2018 ◽  
Vol 25 (13-14) ◽  
pp. 2233-2243 ◽  
Author(s):  
Chih-Tao Cheng ◽  
Samuel MY Ho ◽  
Yi-Chen Hou ◽  
Yihuan Lai ◽  
Ging-Long Wang
Keyword(s):  
Breast Cancer ◽  
Posttraumatic Growth ◽  
Growth Analysis ◽  
Breast Cancer Survivors ◽  
Latent Class ◽  
Growth Trajectory ◽  
Latent Class Growth Analysis ◽  
Frequent Use ◽  
Trajectory Pattern ◽  
Latent Class Growth

A total of 84 breast cancer survivors completed a package of psychological inventories in 2009 (Time 1), 2012 (Time 2), and 2016 (Time 3). Latent class growth analysis revealed three posttraumatic growth trajectory patterns: distressed posttraumatic growth ( n = 5, 6.7%), illusory posttraumatic growth ( n = 42, 56.0%), and constructive posttraumatic growth ( n = 28, 37.3%). Women with more frequent use of helplessness–hopelessness coping and lower depression levels at Time 1 were more likely to display an illusory than a constructive posttraumatic growth trajectory pattern. Illusory posttraumatic growth might represent a form of coping rather than authentic positive changes. Researchers and clinicians should understand different patterns of posttraumatic growth.

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