Growth Mixture Modelling for Life Course Epidemiology

2012 ◽  
pp. 223-241 ◽  
Author(s):  
Darren L. Dahly
Keyword(s):  
Life Course ◽  
Life Course Epidemiology ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Growth Mixture Modelling

An application of Bayesian growth mixture modelling to estimate infection incidences from repeated serological tests

2012 ◽  
Vol 12 (6) ◽  
pp. 551-578 ◽  
Author(s):  
J Menten ◽  
M Boelaert ◽  
E Lesaffre
Keyword(s):  
Serological Tests ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Growth Mixture Modelling

The utility of estimating population-level trajectories of terminal wellbeing decline within a growth mixture modelling framework

2014 ◽  
Vol 50 (3) ◽  
pp. 479-487 ◽  
Author(s):  
R. A. Burns ◽  
J. Byles ◽  
D. J. Magliano ◽  
P. Mitchell ◽  
K. J. Anstey
Keyword(s):  
Population Level ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Modelling Framework ◽  
Growth Mixture Modelling

scholarly journals Examining changes in parent-reported child and adolescent mental health throughout the UK’s first COVID-19 national lockdown.

2021 ◽  
Author(s):  
Jasmine Raw ◽  
Polly Waite ◽  
Samantha Pearcey ◽  
Cathy Creswell ◽  
Adrienne Shum ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Children And Adolescents ◽  
Conduct Problems ◽  
Emotional Symptoms ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Health Trajectories ◽  
Growth Mixture Modelling ◽  
Over Time

Background The COVID-19 pandemic has significantly changed the lives of children and adolescents, forcing them into periods of prolonged social isolation and time away from school. Understanding the psychological consequences of the UK’s lockdown for children and adolescents, the associated risk factors, and how trajectories may vary for children and adolescents in different circumstances is essential so that the most vulnerable children and adolescents can be identified and appropriate support can be implemented. Methods Parents and carers (n = 2988) in the U.K. with children and adolescents aged between 4 and 16 years completed an online survey about their child’s mental health. Growth curve analysis was used to examine the changes in conduct problems, hyperactivity/inattention and emotional symptoms between the end of March/beginning of April and July using data from four monthly assessments. Additionally, growth mixture modelling identified mental health trajectories for conduct problems, hyperactivity/inattention and emotional symptoms separately and subsequent regression models were used to estimate predictors of mental health trajectory membership. Results Overall levels of hyperactivity and conduct problems increased over time whereas emotional symptoms remained relatively stable, though declined somewhat between June and July. Change over time varied according to child age, the presence of siblings, and with Special Educational Needs (SEN)/ Neurodevelopmental Disorders (ND). Subsequent growth mixture modelling identified three, four and five trajectories for hyperactivity/inattention, conduct problems and emotional symptoms, respectively. Though many children maintained “stable3low” symptoms, others experienced elevated symptoms by July. These children were more likely to have a parent/carer with higher levels of psychological distress, to have SEN/ND, or to be younger in age. Conclusions The findings support previous literature and highlight that certain risk factors were associated with poorer mental health trajectories for children and adolescents during the pandemic.

scholarly journals Distinct trajectories of perinatal depression in Chinese women: application of latent growth mixture modelling

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Lan Hong ◽  
Tao Le ◽  
Yinping Lu ◽  
Xiang Shi ◽  
Ludan Xiang ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Protective Factor ◽  
Perinatal Depression ◽  
Gestational Hypertension ◽  
Depression Scale ◽  
Depression Symptoms ◽  
Latent Growth ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Growth Mixture Modelling

Abstract Background Current research on perinatal depression rarely pays attention to the continuity and volatility of depression symptoms over time, which is very important for the early prediction and prognostic evaluation of perinatal depression. This study investigated the trajectories of perinatal depression symptoms and aimed to explore the factors related to these trajectories. Methods The study recruited 550 women during late pregnancy (32 ± 4 weeks of gestation) and followed them up 1 and 6 weeks postpartum. Depressive symptoms were measured using the Edinburgh Postnatal Depression Scale (EPDS). Latent growth mixture modelling (LGMM) was used to identify trajectories of depressive symptoms during pregnancy. Results Two trajectories of perinatal depressive symptoms were identified: “decreasing” (n = 524, 95.3%) and “increasing” (n = 26, 4.7%). History of smoking, alcohol use and gestational hypertension increased the chance of belonging to the increasing trajectories, and a high level of social support was a protective factor for maintaining a decreasing trajectory. Conclusions This study identified two trajectories of perinatal depression and the factors associated with each trajectory. Paying attention to these factors and providing necessary psychological support services during pregnancy would effectively reduce the incidence of perinatal depression and improve patient prognosis.

Developmental trajectories of psychotic-like experiences across adolescence: impact of victimization and substance use

2010 ◽  
Vol 41 (1) ◽  
pp. 47-58 ◽  
Author(s):  
C. J. Mackie ◽  
N. Castellanos-Ryan ◽  
P. J. Conrod
Keyword(s):  
Substance Use ◽  
Developmental Trajectories ◽  
Cigarette Use ◽  
Depression And Anxiety ◽  
Class Membership ◽  
Time Points ◽  
Mixture Modelling ◽  
Adolescent Population ◽  
Growth Mixture ◽  
Growth Mixture Modelling

BackgroundResearch suggests that psychotic-like experiences (PLEs) in the general population are common, but can reflect either transitory or persistent developmental phenomena. Using a general adolescent population it was examined whether different developmental subtypes of PLEs exist and whether different trajectories of PLEs are associated with certain environmental risk factors, such as victimization and substance use.MethodSelf-reported PLEs were collected from 409 adolescents (mean age 14 years 7 months) at four time points, each 6 months apart. General growth mixture modelling was utilized to identify classes of adolescents who followed distinct trajectories of PLEs across this period. Predictors of class membership included demographics, personality, victimization, depression, anxiety and substance use.ResultsWe identified the following three developmental subgroups of PLEs: (1) persistent; (2) increasing; (3) low. Adolescents on the persistent trajectory reported frequent victimization and consistent elevated scores in depression and anxiety. Adolescents on the increasing trajectory were engaging in cigarette use prior to any increases in PLEs and were engaging in cocaine, cannabis and other drug use as PLEs increased at later time points.ConclusionsThe findings suggest that different developmental subgroups of PLEs exist in adolescence and are differentially related to victimization and substance use.

scholarly journals Sex differences in ADHD trajectories across childhood and adolescence

2018 ◽  
Author(s):  
Aja Louise Murray ◽  
Tom Booth ◽  
Manuel Eisner ◽  
Bonnie Auyeung ◽  
George Murray ◽  
...  
Keyword(s):  
Sex Differences ◽  
Secondary School ◽  
Early Adolescence ◽  
Age Of Onset ◽  
Developmental Trajectories ◽  
Childhood And Adolescence ◽  
Mixture Modelling ◽  
Growth Mixture ◽  
Growth Mixture Modelling ◽  
Males And Females

Background: Previous studies have hinted at sex differences in developmental trajectories in ADHD symptoms; however, little is known about the nature or cause of these differences and their implications for clinical practice.Method: We used growth mixture modelling in a community-ascertained cohort of n=1571 participants to study sex differences in ADHD symptom developmental trajectories across the elementary and secondary school years. Participants were measured at ages 7, 8, 9, 10, 11, 12, 13, and 15.Results: We found that females were more likely to show large symptom increases in early adolescence while males were more likely to show elevated symptoms from childhood. For both males and females, early adolescence represented a period of vulnerability characterised by relatively sudden symptom increases. Conclusions: Females affected by hyperactivity/impulsivity may be more likely to be excluded from diagnosis due to current age of onset criteria. More attention should be paid to early adolescence as a period of risk for hyperactivity/impulsivity symptom onset or worsening.

The potential of growth mixture modelling

2006 ◽  
Vol 15 (6) ◽  
pp. 623-625 ◽  
Author(s):  
Bengt Muthén
Keyword(s):  
Mixture Modelling ◽  
Growth Mixture ◽  
Growth Mixture Modelling
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