Purpose
This study aimed to identify ecological risk and protective factors associated with membership in latent classes characterized by heterogeneous associations between parental adverse childhood experiences (ACEs) and the intergenerational transmission of child maltreatment (ITCM).
Methods
This secondary analysis used data from the 2017 Family with Children’s Life Experience Survey. Participants were parents who had a spouse and children younger than 18 years. Guided by Belsky’s ecological model, the covariates were categorized as parent-, family/household-, and community-level contextual factors. Latent class regression was used to identify classes with differing associations between parental ACEs and child maltreatment, and multinomial logistic regression was used to examine factors associated with class membership.
Results
Three classes were identified: the “None-ACE-Association” class (58.5%), the “Partial-ACE-Association” class (23.3%), and the “Comprehensive-ACE-Association” class (18.2%). Factors across multiple ecological domains differentiated class membership. Acceptance of corporal punishment significantly distinguished the None-ACE-Association class from the Partial-ACE-Association class. In comparisons involving the Comprehensive-ACE-Association class, membership was significantly associated with several parent- and family/household-level factors, including depressive symptoms, parenting stress, partner violence/control, and family relationship quality. Significant associations were also observed for the number of children, the age group of the youngest child, and residential area.
Conclusion
Distinct latent class profiles characterized by heterogeneous associations between parental ACEs and child maltreatment support the need for tailored, risk-stratified prevention strategies. Combining the assessment of parental ACEs with the assessment of modifiable factors could improve early identification and inform nursing and community-based interventions intended to interrupt the ITCM.

Purpose
Adolescents with same-sex or both-sex sexual experience face disproportionate health risks, yet research has predominantly examined single health problems rather than their multidimensional patterns. This study employed latent class analysis (LCA) to identify distinct health typological classes among Korean adolescents and characterize the distribution of sexual behavior patterns across these classes.
Methods
We analyzed 278,066 middle- and high-school students in the 2013–2016 Korea Youth Risk Behavior Survey. The LCA used 17 indicators encompassing sexual behavior patterns, health behaviors, health perceptions, and mental health. Complex-sample weighted analyses examined associations between latent classes and sociodemographic characteristics, sexual behaviors, and diseases.
Results
Four distinct classes were identified: mental health high-risk group (10.1%), substance use high-risk group (6.5%), average group (36.3%), and healthy group (47.1%). Adolescents with same-sex or both-sex sexual experience were disproportionately concentrated in the two high-risk classes, comprising 3.3% of the mental health high-risk group and 4.1% of the substance use high-risk group, compared with only 0.3% and 0.5% of the average group and the healthy group. The mental health high-risk group exhibited extremely elevated prevalence rates of suicidal ideation (96.2%), depressive symptoms (88.5%), and suicide attempts (27.5%), while the substance use high-risk group showed high rates of smoking (82.4%) and alcohol use (84.6%) but better mental health.
Conclusion
Adolescents with same-sex or both-sex sexual experience demonstrate health inequality through disproportionate classification in the mental health high-risk group and the substance use high-risk group. The findings underscore the need for integrated interventions combining mental health support and substance use prevention.

Purpose
The number of Korean adolescents engaging in gambling is increasing, especially among out-of-school adolescents. This study aimed to identify patterns of gambling activities and factors related to specific subgroups of out-of-school adolescent gambling activities.
Methods
This descriptive study analyzed secondary data from the 2015 Korea Youth Gambling Problem Survey, including 1,200 out-of-school adolescents. Latent class analysis was conducted to identify patterns of gambling activities. The factors related to gambling subgroups were verified with multinomial logistic regression.
Results
Three latent classes of gambling activities were identified: rarely gambling (RG), immediate gain gambling (IGG), and broad gambling (BG). These subgroups differed significantly in terms of gender, age at and type of first gambling experience, number and type of gambling activities, gambling frequency, time and money spent on gambling, problem gambling severity, and motivation for gambling. Compared to the RG subgroup, both the IGG and BG subgroups were strongly associated with an older age at the first gambling experience.
Conclusion
Out-of-school adolescents who first gambled at an older age and who gambled mainly in order to gain money immediately were at risk of problem gambling. Developing strategies for early screening and referral to professionals is necessary to prevent gambling problems from worsening.

Citations

• What is known about population level programs designed to address gambling-related harm: rapid review of the evidence
  Samantha Clune, Deepika Ratnaike, Vanessa White, Alex Donaldson, Erica Randle, Paul O’Halloran, Virginia Lewis
  Harm Reduction Journal.2024;[Epub]     CrossRef
• Perceived Gambling Availability and Adolescent Gambling Behavior: the Moderating Role of Self-Efficacy
  Alberto Parrado-González, Fermín Fernández-Calderón, José C. León-Jariego
  International Journal of Mental Health and Addicti.2023; 21(4): 2737.     CrossRef
• Attitudes, Risk Factors, and Behaviours of Gambling among Adolescents and Young People: A Literature Review and Gap Analysis
  Ben J. Riley, Candice Oster, Mubarak Rahamathulla, Sharon Lawn
  International Journal of Environmental Research an.2021; 18(3): 984.     CrossRef