The Latent Classes according to the Comorbidity of Aggression and Depression in Adolescence : An Application of the Confirmatory LCA(Latent Class Analysis) using the Loglinear Parameterization

Although many studies addressed bullying occurrence and its associations, they often use individual variables constructed from few items that probably are inadequate to evaluate bullying severity and type. We aimed to identify involvement patterns in bullying victimization and perpetration, and its association with alcohol use, school performance, and sociodemographic variables. Baseline assessment of a randomized controlled trial were used and a latent class analysis was conducted to identify bullying patterns among 1,742 fifth-grade and 2,316 seventh-grade students from 30 public schools in São Paulo, Brazil. Data were collected using an anonymous self-reported, audio-guided questionnaire completed by the participants on smartphones. Multinomial logistic regressions were performed to verify how covariant variables affected bullying latent classes. Both grades presented the same four latent classes: low bullying, moderate bullying victimization, high bullying victimization, and high bullying victimization and perpetration. Alcohol use was associated with all bullying classes in both grades, with odds ratio up to 5.36 (95% CI 3.05; 10.38) among fifth graders from the high bullying victimization and perpetration class. Poor school performance was also strongly associated with this class (aOR = 10.12, 95%CI = 4.19; 24.41). Black/brown 5th graders were 3.35 times more likely to fit into the high bullying victimization class (95% CI 1.34; 8.37). Lack of evidence for association of sociodemographic variables and bullying latent class among seventh-grade students was found. Bullying and alcohol use are highly harmful behaviors that must be prevented. However, prevention programs should consider how racial and gender issues are influencing the way students experience violence.

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Risk Factors Explaining Military Deaths From Suicide, 2008–2017: A Latent Class Analysis

Armed Forces & Society ◽

10.1177/0095327x211046976 ◽

2021 ◽

pp. 0095327X2110469

Author(s):

Scott D. Landes ◽

Janet M. Wilmoth ◽

Andrew S. London ◽

Ann T. Landes

Keyword(s):

Mental Health ◽

Risk Factors ◽

Latent Class Analysis ◽

Military Service ◽

Latent Class ◽

Service Providers ◽

Service Members ◽

Latent Classes ◽

Class Analysis ◽

Military Service Members

Military suicide prevention efforts would benefit from population-based research documenting patterns in risk factors among service members who die from suicide. We use latent class analysis to analyze patterns in identified risk factors among the population of 2660 active-duty military service members that the Department of Defense Suicide Event Report (DoDSER) system indicates died by suicide between 2008 and 2017. The largest of five empirically derived latent classes was primarily characterized by the dissolution of an intimate relationship in the past year. Relationship dissolution was common in the other four latent classes, but those classes were also characterized by job, administrative, or legal problems, or mental health factors. Distinct demographic and military-status differences were apparent across the latent classes. Results point to the need to increase awareness among mental health service providers and others that suicide among military service members often involves a constellation of potentially interrelated risk factors.

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Competence Differences in Literacy, Numeracy, and Problem Solving According to Sex

Adult Education Quarterly ◽

10.1177/0741713619827386 ◽

2019 ◽

Vol 69 (2) ◽

pp. 101-119 ◽

Cited By ~ 2

Author(s):

Seher Yalcin

Keyword(s):

Problem Solving ◽

Latent Class Analysis ◽

Latent Class ◽

Latent Classes ◽

Class Analysis ◽

Country Level ◽

Successful Group ◽

Study Population ◽

Multilevel Latent Class Analysis ◽

International Assessment

This study aimed to determine individual- and country-level latent classes in literacy, numeracy and problem-solving competencies of individuals participating in the Programme for the International Assessment of Adult Competencies 2015. Specifically, it sought to distinguish these classes in relation to individuals’ sex and to identify the state of prediction of the determined latent classes by each person’s level of education. The study population consisted of 116,301 adults aged 16 to 65 years in 20 countries. Multilevel latent class analysis was conducted to consider the nested data structure and determine the number of latent classes. According to the results of the multilevel latent class analysis, Turkey and Chile were in the low achievement group in all skills, while Japan was in the most successful group. Moreover, the results revealed that sex and education level had a considerable influence on certain competence levels.

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Clustering of Modifiable Behavioral Risk Factors and Their Association with All-Cause Mortality in Taiwan’s Adult Population: a Latent Class Analysis

International Journal of Behavioral Medicine ◽

10.1007/s12529-021-10041-x ◽

2021 ◽

Author(s):

Shikha Kukreti ◽

Tsung Yu ◽

Po Wei Chiu ◽

Carol Strong

Keyword(s):

Physical Activity ◽

Alcohol Consumption ◽

Health Behavior ◽

Latent Class Analysis ◽

Risk Behaviors ◽

Latent Class ◽

Latent Classes ◽

Class Analysis ◽

Unhealthy Behavior ◽

All Cause Mortality

Abstract Background Modifiable risk behaviors, such as smoking, diet, alcohol consumption, physical activity, and sleep, are known to impact health. This study aims toward identifying latent classes of unhealthy lifestyle behavior, exploring the correlations between sociodemographic factors, identifying classes, and further assessing the associations between identified latent classes and all-cause mortality. Methods For this study, the data were obtained from a prospective cohort study in Taiwan. The participants’ self-reported demographic and behavioral characteristics (smoking, physical activity, alcohol consumption, fruit and vegetable intake, and sleep) were used. Latent class analysis was used to identify health-behavior patterns, and Cox proportional hazard regression analysis was used to find the association between the latent class of health-behavior and all-cause mortality. Results A complete dataset was obtained from 290,279 participants with a mean age of 40 (12.4). Seven latent classes were identified, characterized as having a 100% likelihood of at least one unhealthy behavior coupled with the probability of having the other four unhealthy risk behaviors. This study also shows that latent health-behavior classes are associated with mortality, suggesting that they are representative of a healthy lifestyle. Finally, it appeared that multiple risk behaviors were more prevalent in younger men and individuals with low socioeconomic status. Conclusions There was a clear clustering pattern of modifiable risk behaviors among the adults under consideration, where the risk of mortality increased with increases in unhealthy behavior. Our findings can be used to design customized disease prevention programs targeting specific populations and corresponding profiles identified in the latent class analysis.

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The trajectories of depressive symptoms expressed in early childhood differ between boys and girls

10.13056/acamh.10572 ◽

2018 ◽

Keyword(s):

Early Childhood ◽

Depressive Symptoms ◽

Latent Class Analysis ◽

Latent Class ◽

Latent Classes ◽

Class Analysis ◽

Washington University

A study by Diana Whalen and colleagues at Washington University has used latent class analysis (LCA) to identify and define the trajectories of latent classes of depressive symptoms in early childhood.

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Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

BMC Nursing ◽

10.1186/s12912-021-00726-9 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Jing Wu ◽

Husheng Li ◽

Zhaohui Geng ◽

Yanmei Wang ◽

Xian Wang ◽

...

Keyword(s):

Latent Class Analysis ◽

Work Engagement ◽

Latent Class ◽

Mental Workload ◽

Latent Classes ◽

Interaction Patterns ◽

Class Analysis ◽

Cross Sectional ◽

Self Evaluation ◽

Evaluation Group

Abstract Background Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk. Methods A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses’ mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups. Results Three latent classes were identified based on the responses to mental workload assessment: Class 1 – low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 – medium workload perception & medium self-evaluation group (n = 455, 34.0%); and Class 3 – high workload perception & low self-evaluation group (n = 841, `62.9%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels. Conclusions The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies.

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Subtypes of nurses' mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

10.21203/rs.3.rs-70155/v1 ◽

2020 ◽

Author(s):

JING WU ◽

HUSHENG LI ◽

ZHAOHUI GENG ◽

YANMEI WANG ◽

XIAN WANG ◽

...

Keyword(s):

Latent Class Analysis ◽

Work Engagement ◽

Latent Class ◽

Mental Workload ◽

Latent Classes ◽

Interaction Patterns ◽

Class Analysis ◽

Cross Sectional ◽

Self Evaluation ◽

Evaluation Group

Abstract Background Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses’ mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk. Methods A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses’ mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups. Results Three latent classes were identified based on the responses to mental workload assessment: Class1 – low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 – medium workload perception & medium self-evaluation group (n = 455, 34.4%); and Class 3 – high workload perception & low self-evaluation group (n = 841, 62.5%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels. Conclusions The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies.

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Differentiating Individuals Convicted of Sexual Offenses: A Two-Country Latent Class Analysis

Sexual Abuse ◽

10.1177/1079063219893370 ◽

2019 ◽

Vol 32 (4) ◽

pp. 423-451

Author(s):

Pascalle Spaan ◽

Arjan Blokland ◽

Rembert De Blander ◽

Luc Robert ◽

Eric Maes ◽

...

Keyword(s):

Latent Class Analysis ◽

Latent Class ◽

Sexual Offending ◽

Criminal Career ◽

Sexual Offense ◽

Latent Classes ◽

Class Analysis ◽

Sexual Offenses ◽

Criminal Histories ◽

History Of

Sexual offenses are often part of a larger criminal career also encompassing nonsexual crimes. However, most sexual offending typologies focus on an individual’s most recent sexual offense. We compare data from Belgian and Dutch national conviction cohorts and use latent class analysis to distinguish groups of individuals based on their history of sexual and nonsexual offenses, considering continuity and variety. The resulting classification is compared between individuals convicted of sexual offenses and individuals convicted of nonsexual offenses. Results show that four latent classes can be distinguished based on continuity and variety in criminal histories of individuals convicted of sexual offenses, and that some of these classes resemble those distinguished among individuals convicted of nonsexual offenses. We find limited overlap between these latent classes and typologies based solely on the index offense. Results show marked similarities across countries. These results challenge theories of sexual offending to incorporate patterns of nonsexual offending.

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A latent class analysis of bullying among students: associations with social factors and alcohol use

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.935 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

V Ferreira Júnior ◽

J Yurgel Valente ◽

Z van der Meer Sanchez

Keyword(s):

Public Schools ◽

Alcohol Use ◽

Latent Class Analysis ◽

Latent Class ◽

Public Health Problem ◽

Prevention Programs ◽

Bullying Victimization ◽

Latent Classes ◽

Class Analysis ◽

5Th Grade

Abstract Bullying is a behavior highly prevalent in schools worldwide and is associated with several mental disorders later in life. Considering its prevalence and impact in mental health, it is being recognized as a public health problem. We aimed to identify patterns of bullying victimization and perpetration in children and adolescence, and investigated its association with school performance, alcohol use and sociodemographic factors. A latent class analysis was conducted using baseline data collected from a randomized controlled trial conducted to evaluate the effectiveness of the drug prevention program PROERD (the Brazilian adaptation of the the US program 'Keepin it REAL”) carried out among 1.742 students in 5th grade and 2.316 in 7th grade, from 30 public schools of São Paulo city, Brazil. Two models of four latent classes each were identified among the students, in 5th and 7th grade: Low bullying, Moderate bullying victimization, High bullying victimization and High bullying victimization and perpetration. In both grades, we found that alcohol use were associated to all bullying latent classes (e.g High bullying victimization and perpetration (aOR=5,63; 95%CI = [3,05; 10,38] and aOR=3,29; 95%CI = [1,28; 8,43], 5th and 7th grade respectively). In 5th grade, girls were more likely to belong to the “High bullying victimization” class and to “Moderate bullying victimization” (aOR=1,75; 95%CI = [1,02; 3,01] and aOR=1,47; 95%CI = [1,16; 1,87], respectively); students who reported to belonging to black or brown races were more likely to belong to 'High bullying victimization' class (aOR=3,35; 95%CI = [1,34; 8,37]); low and medium school grades were associated to High bullying victimization and perpetration (aOR=10,12; 95%CI = [4,19; 24,41]) and Moderate bullying victimization (aOR=1,63; 95%CI = [1,17; 2,27]). The results show the need to implement school prevention programs that simultaneously address alcohol use and bullying components, besides taking into account race and gender norms. Key messages Bullying profiles help us to understand how this type of violence happens among students. And the associated factors indicate which groups are at greatest risk and need more attention. The use of alcohol associated with all latent classes, besides showing the impacts of bullying, it also indicates the importance of bullying prevention programs to address substance use prevention.

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“Who Are at Higher Sexual Risk?” Latent Class Analysis of Behavioral Intentions among Spanish Adolescents

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041855 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1855

Author(s):

Alexandra Morales ◽

Samuel Tomczyk ◽

Mireia Orgilés ◽

José Pedro Espada

Keyword(s):

Condom Use ◽

Latent Class Analysis ◽

Sexual Risk ◽

Educational Level ◽

Behavioral Intentions ◽

Latent Class ◽

Sexual Experience ◽

Latent Classes ◽

Class Analysis ◽

Risk Profiles

Consistent condom use tends to be limited in youth, which makes this group especially vulnerable for sexually transmitted infections (STIs) and unplanned pregnancies. It is known that sexual risk may vary as a function of behavioral intentions (e.g., condom use intention or having sex under the influence of alcohol), but no studies have yet characterized the sexual risk profiles considering behavioral intentions. This study utilizes latent class analysis (LCA) to explore the subtyping of behavioral intentions related to sexual risk in a community-based sample of adolescents aged 14 to 16 years from Spain. Multinomial logistic regression was used to assess the association between class membership and participants’ sociodemographic variables (sex, age, educational level, socioeconomic status, and family situation), and behavioral variables (sexual experience and percentage of condom use). Among the 1557 participants, four latent classes of risk were identified: “Condom + drugs”, “abstinent”, “condom + no drugs”, and “no condom + drugs”. Differences in adolescents’ sex, age, educational level, sexual experience, and condom use across latent classes were found. Findings highlight opportunities for psychologists, educators, and health-care providers to promote condom use in adolescents with differing sexual risk profiles. Increased understanding of behavioral intentions among adolescents may help to reduce sexual risk behaviors in this group.

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