scholarly journals Changes in children’s attachment security to mother and father after the birth of a sibling: Risk and resilience in the family

2021 ◽  
pp. 1-17
Author(s):  
Brenda L. Volling ◽  
Wonjung Oh ◽  
Richard Gonzalez ◽  
Lauren R. Bader ◽  
Lin Tan ◽  
...  
Keyword(s):  
Externalizing Behavior ◽  
Attachment Security ◽  
Risk And Resilience ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Infant Sibling ◽  
The Family ◽  
Steep Decline ◽  
Systems Framework

Abstract Changes in children’s attachment security to mother and father were examined for 230 firstborn children (M = 31.17 months), their mothers and fathers participating in a longitudinal investigation starting in the last trimester of the mothers’ pregnancy and 1, 4, 8, and 12 months after the birth of an infant sibling. Both parents completed the Attachment Q-set at prenatal, 4, and 12 months. Growth mixture models revealed four latent classes in which children’s attachments were (a) both secure with a modest decline to both parents (68.3%); (b) more secure with father than mother with a steep decline for both (12.6%); (c) both insecure with no change (10%); and (d) more secure with mother than father with a modest increase for both (9.1%). Multi-group latent growth curve analyses revealed that parenting and coparenting differed across families. Children had lower externalizing behavior problems in families with two secure attachments than in families with one secure attachment, either to mother or to father, who, in turn, had fewer problems than children with two insecure attachments. Findings underscore the strengths of a family systems framework to understand attachment relationships with multiple caregivers and the family risks and protective factors that covary with children’s behavioral adjustment after the birth of a sibling.

scholarly journals Worldwide Patterns in Alzheimer’s Disease and other Dementias Prevalence from 1990 to 2017: A Growth Mixture Models Approach

2020 ◽  
Author(s):  
Nasrin Borumandnia ◽  
Hamid Alavi Majd ◽  
Naghmeh Khadembashi ◽  
Keyvan Olazadeh ◽  
Hojat Alaii
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mixture Models ◽  
Sharp Increase ◽  
Growth Models ◽  
Nordic Countries ◽  
Downward Trend ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture

Abstract Background This study was designed to monitor the longitudinal trends of Alzheimer’s disease and other dementias (ADD) prevalence among world countries, as well as classifying them into clusters in which countries within each cluster have similar trends over time.Methods The ADD prevalence in 195 countries during 1990–2017 were extracted from the Global Burden of Disease study’s database. The Latent Growth Models (LGMs) and also Latent Growth Mixture models (LGMM) were applied for trend analysis.Results The highest and the lowest increase in ADD were observed in Europe and Africa, respectively. Increase in ADD was higher in women. LGMM allocated Nordic Countries in the class with a downward trend with a downward trend, with rate of -11.5 in 100000 person in every 2 years. Japan alone entered a class with a dramatically sharp increase with rate of 185 in 100000 person in every 2 years, the highest rank in ADD trend. Most European and American countries were entered into classes with higher increasing trend, rate between 20.4 and 53.6 in 100000 person in every 2 years, relative to the most of Asian countries which were less likely to have the increase of ADD, with rate of 6.45 in 100000 person in every 2 years.Conclusion A substantial difference was observed in ADD trend among the countries: the decline in Nordic countries, which could be due to "Health Care of the elderly in the Nordic Countries" program, and the highly differentiated ascending trend in Japan, which is not necessarily due to the aging population; none of other countries, which have elderly population too, witnessed such sharp increase in their ADD. The clarification of the cause of the last finding calls for more epidemiological studies.

Early co-occurrence of peer victimization and aggression

2021 ◽  
pp. 1-17
Author(s):  
Wendy L. G. Hoglund ◽  
Phillip Hau
Keyword(s):  
Social Cognitive ◽  
Longitudinal Research ◽  
Relational Victimization ◽  
Low Risk ◽  
Cognitive Factors ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Grade 3 ◽  
Cognitive Problems

Abstract An accelerated longitudinal research design was used to examine heterogeneity in the developmental co-occurrence of peer relational victimization and aggression and of peer overt victimization and aggression from age 4.5 to 10.5 years. Data were gathered from four cohorts of children in kindergarten to Grade 3 (N = 503) on six occasions across 2 years. Psychopathology, peer, and social–cognitive factors were examined as predictors of the joint trajectories. Sequential process latent growth mixture models identified four distinct subgroups for the relational trajectories (co-occurring increasing aggression, co-occurring increasing victimization, high chronic victimization, typical low risk) and four distinct subgroups for the overt trajectories (co-occurring decelerating aggression, high chronic victimization, moderate chronic victimization, typical low risk). Membership in the co-occurring trajectories was associated with psychopathology and membership in the chronic victimization trajectories was related to internalizing and social–cognitive problems but also peer likeability.

scholarly journals Determinants of profiles of competence development in mathematics and reading in upper secondary education in Germany

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258152
Author(s):  
Micha-Josia Freund ◽  
Ilka Wolter ◽  
Kathrin Lockl ◽  
Timo Gnambs
Keyword(s):  
Secondary Education ◽  
Vocational Education ◽  
Mixture Models ◽  
Competence Development ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Upper Secondary Education ◽  
Growth Mixture ◽  
Upper Secondary ◽  
Latent Profiles

The registered report was targeted at identifying latent profiles of competence development in reading and mathematics among N = 15,012 German students in upper secondary education sampled in a multi-stage stratified cluster design across German schools. These students were initially assessed in grade 9 and provided competence assessments on three measurement occasions across six years using tests especially developed for the German National Educational Panel Study (NEPS). Using Latent Growth Mixture Models, Using Latent Growth Mixture Models, we aimed at identifying multiple profiles of competence development. Specifically, we expected to find at least one generalized (i.e., reading and mathematical competence develop similarly) and two specialized profiles (i.e., one of the domains develops faster) of competence development and that these profiles are explained by the specialization of interest and of vocational education of students. Contrary to our expectations, we did not find multiple latent profiles of competence development. The model describing our data best was a single-group latent growth model confirming a competence development profile, which can be described as specializing in mathematical competences, indicating a higher increase in mathematical competences as compared to reading competences in upper secondary school. Since only one latent profile was identified, potential predictors (specialization of vocational education and interest) for different profiles of competence development were not examined.

Early Life Metal Exposures and Neurodevelopmental Trajectory Profiles: Assessment Using Parallel Latent Growth Mixture Models

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Shelley Han Liu ◽  
Jack Rowland ◽  
Qixuan Chen ◽  
Martha María Téllez-Rojo ◽  
Lourdes Schnaas ◽  
...  
Keyword(s):  
Mixture Models ◽  
Early Life ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture

scholarly journals Trajectories of functioning in a population-based sample of veterans: contributions of moral injury, PTSD, and depression

2020 ◽  
pp. 1-10
Author(s):  
Shira Maguen ◽  
Brandon J. Griffin ◽  
Laurel A. Copeland ◽  
Daniel F. Perkins ◽  
Cameron B. Richardson ◽  
...  
Keyword(s):  
Posttraumatic Stress ◽  
Psychological Symptoms ◽  
Population Based ◽  
Moral Injury ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Trajectories Of Change ◽  
Relationship Health ◽  
Over Time

Abstract Background Although research has shown that exposure to potentially traumatic and morally injurious events is associated with psychological symptoms among veterans, knowledge regarding functioning impacts remains limited. Methods A population-based sample of post-9/11 veterans completed measures of intimate relationship, health, and work functioning at approximately 9, 15, 21, and 27 months after leaving service. Moral injury, posttraumatic stress, and depression were assessed at ~9 months post-separation. We used Latent Growth Mixture Models to identify discrete classes characterized by unique trajectories of change in functioning over time and to examine predictors of class membership. Results Veterans were assigned to one of four functioning trajectories: high and stable, high and decreasing, moderate and increasing, and moderate and stable. Whereas posttraumatic stress, depression, and moral injury associated with perpetration and betrayal predicted worse outcomes at baseline across multiple functioning domains, moral injury associated with perpetration and depression most reliably predicted assignment to trajectories characterized by relatively poor or declining functioning. Conclusions Moral injury contributes to functional problems beyond what is explained by posttraumatic stress and depression, and moral injury due to perpetration and depression most reliably predicted assignment to trajectories characterized by functional impairment over time.

Understanding Variation in Longitudinal Data Using Latent Growth Mixture Modeling

2021 ◽  
Vol 46 (2) ◽  
pp. 179-188
Author(s):  
Constance A Mara ◽  
Adam C Carle
Keyword(s):  
Longitudinal Data ◽  
Mixture Models ◽  
Growth Models ◽  
Growth Mixture Modeling ◽  
Mixture Modeling ◽  
Individual Variability ◽  
Latent Growth ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Latent Growth Mixture Modeling

Abstract Objective This article guides researchers through the process of specifying, troubleshooting, evaluating, and interpreting latent growth mixture models. Methods Latent growth mixture models are conducted with small example dataset of N = 117 pediatric patients using Mplus software. Results The example and data show how to select a solution, here a 3-class solution. We also present information on two methods for incorporating covariates into these models. Conclusions Many studies in pediatric psychology seek to understand how an outcome changes over time. Mixed models or latent growth models estimate a single average trajectory estimate and an overall estimate of the individual variability, but this may mask other patterns of change shared by some participants. Unexplored variation in longitudinal data means that researchers can miss critical information about the trajectories of subgroups of individuals that could have important clinical implications about how one assess, treats, and manages subsets of individuals. Latent growth mixture modeling is a method for uncovering subgroups (or “classes”) of individuals with shared trajectories that differ from the average trajectory.

It’s About Time! Identifying and Explaining Unique Trajectories of Solidarity-Based Collective Action to Support People in Developing Countries

2021 ◽  
pp. 014616722110470
Author(s):  
Emma F. Thomas ◽  
Craig McGarty ◽  
Winnifred R Louis ◽  
Michael Wenzel ◽  
Simon Bury ◽  
...  
Keyword(s):  
Collective Action ◽  
Social Identification ◽  
Latent Growth ◽  
Group Efficacy ◽  
Longitudinal Methods ◽  
Growth Mixture Models ◽  
Growth Mixture ◽  
Over Time ◽  
Do So

Social change occurs over years and decades, yet we know little about how people sustain, increase or diminish their actions over time, and why they do so. This article examines diverging trajectories of solidarity-based collective action to support people in developing nations more than 5 years. We suggest that sustained, diminished, and/or increased action over time will be predicted by identification as a supporter, group efficacy beliefs, and discrete emotions about disadvantage. Latent Growth Mixture Models ( N = 483) revealed two trajectories with unique signatures: an activist supporter trajectory with a higher intercept and weakly declining action; and a benevolent supporter trajectory with a lower intercept but weakly increasing action. The activist trajectory was predicted by social identification, outrage, and hope, whereas the benevolent supporter trajectory was predicted by sympathy. The results highlight the role of combinations of emotions and the need for person-centered longitudinal methods in collective action research.

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