Longitudinal Data Analysis in Child and Adolescent Mental Health

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Editorial

03 October 2022

Editorial: Longitudinal data analysis in child and adolescent mental health

Tomoya Hirota

,

Eoin McElroy

,

Takeo Fujiwara

and

Joseph Boden

3,153 views

2 citations

Editors

4

Tomoya Hirota

University of California, San Francisco

Eoin McElroy

Ulster University

Takeo Fujiwara

Tokyo Medical and Dental University

Joseph M Boden

University of Otago

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About

Many psychiatric disorders and problems, including depression, anxiety, ADHD, ASD, and behavioral problems, can have their onset in childhood and persist into adolescence and adulthood. Thus, developmental perspective is pivotal in understanding child and adolescent mental health. Yet, the majority of scientific findings on psychopathology have sprung from cross-sectional studies, prohibiting us from further understandings of how symptoms/problems change over time.

Studies using longitudinal data promote our understandings of developmental psychopathology. Data obtained from different time points would allow for the examination of causality and changes with age in multiple domains related to the field of child psychiatry and psychology. These domains can include, but not limited to, psychopathology (emotions, behaviors, social challenges, for example) and well-being. Despite this advantage, there have been much fewer studies published using longitudinal study designs due to difficulty with data collection (time, cost) and analytic methods.

Therefore, the main goal of this Research Topic is to broaden our understandings of how the child’s social, emotional, and behavioral strengths and challenges change over time.

In this Research Topic, we will call for papers using longitudinal data analyses and addressing the following themes in the field of child and adolescent mental health:

· Studies that elucidate longitudinal changes in or different trajectory patterns of domains/constructs related to child psychiatry and psychology. These include, but not limited to, psychopathology (affect, behavior, attention, social communication challenges, substance use), traits (temperament, self-regulation), well-being, and parental variables (parenting stress, for example);

· Studies that explore the predictors and or distant outcomes of different trajectory patterns;

· Studies using other longitudinal analyses (cross-lagged analyses, for example) to estimate the reciprocal relationship between variables over time.

Many psychiatric disorders and problems, including depression, anxiety, ADHD, ASD, and behavioral problems, can have their onset in childhood and persist into adolescence and adulthood. Thus, developmental perspective is pivotal in understanding child and adolescent mental health. Yet, the majority of scientific findings on psychopathology have sprung from cross-sectional studies, prohibiting us from further understandings of how symptoms/problems change over time.

Studies using longitudinal data promote our understandings of developmental psychopathology. Data obtained from different time points would allow for the examination of causality and changes with age in multiple domains related to the field of child psychiatry and psychology. These domains can include, but not limited to, psychopathology (emotions, behaviors, social challenges, for example) and well-being. Despite this advantage, there have been much fewer studies published using longitudinal study designs due to difficulty with data collection (time, cost) and analytic methods.

Therefore, the main goal of this Research Topic is to broaden our understandings of how the child’s social, emotional, and behavioral strengths and challenges change over time.

In this Research Topic, we will call for papers using longitudinal data analyses and addressing the following themes in the field of child and adolescent mental health:

· Studies that elucidate longitudinal changes in or different trajectory patterns of domains/constructs related to child psychiatry and psychology. These include, but not limited to, psychopathology (affect, behavior, attention, social communication challenges, substance use), traits (temperament, self-regulation), well-being, and parental variables (parenting stress, for example);

· Studies that explore the predictors and or distant outcomes of different trajectory patterns;

· Studies using other longitudinal analyses (cross-lagged analyses, for example) to estimate the reciprocal relationship between variables over time.

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Editors

Tomoya Hirota

University of California, San Francisco

Eoin McElroy

Ulster University

Takeo Fujiwara

Tokyo Medical and Dental University

Joseph M Boden

University of Otago

Impact

40,495 Total views

28,846 Article views

10,243 Article downloads

1,406 Topic views

Published In

Frontiers in Psychiatry

Child and Adolescent Psychiatry

Frontiers in Pediatrics

Child and Adolescent Psychiatry

Frontiers in Neuroscience

Child and Adolescent Psychiatry

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