Variants of Psychopathy in Chinese Juvenile Offenders: A Latent Profile Analysis

Despite considerable understanding on the psychopathy subtypes in detained populations, the variants of psychopathy in non-Western populations are less well understood. To address this gap, the present study conducted a series of latent profile analyses with the factors of the Youth Psychopathic Traits Inventory, childhood trauma, and trait anxiety in 560 Chinese incarcerated boys ( Mage = 16.92, SD = 0.81). Four subgroups emerged: relatively normal (67.3%); callous, psychopathy-like (2.8%); moderate psychopathy-like (24.8%); and high traumatic, moderate psychopathy-like (5.1%). Moreover, the modified Bolck–Croon–Hagenaars method was used to examine the significant mean differences on covariates across profiles, including proactive aggression, reactive aggression, affective empathy, and cognitive empathy. Results showed that the psychopathic profiles displayed differences on key variables. The callous, psychopathy-like group endorsed higher aggression and lower empathy. This study provides initial empirical support for the existence of psychopathy variants and enhances the understanding of the psychopathic construct in non-Western cultures.

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Latent Profile Analysis of Personality Dimensions Among Juvenile Offenders: Relevance for Predicting Offending Seriousness

Crime & Delinquency ◽

10.1177/0011128720928920 ◽

2020 ◽

pp. 001112872092892

Author(s):

Thomas Wojciechowski

Keyword(s):

Juvenile Offenders ◽

Latent Profile Analysis ◽

Negative Binomial ◽

Profile Analysis ◽

Negative Binomial Regression ◽

Personality Profiles ◽

Personality Dimensions ◽

Binomial Regression ◽

Pathways To Desistance ◽

Latent Profile

There is a burgeoning base of research identifying personality as a predictor of offending. However, research has focused on personality dimensions, rather than full personality profiles as predictors. The present study utilized the Pathways to Desistance data to examine the relationship between personality profiles and offending. This sample comprised 1,354 juvenile offenders followed during the study period of 2000 to 2010. Latent profile analysis was used to identify patterns across dimensions to elucidate personality profiles. Negative binomial regression was used to examine profiles as predictors of offending. Results indicated that a two-profile model fit the data. Participants assigned to the Undercontrolled profile (high in neuroticism and low in all other dimensions) engaged in more serious offending than the Resilient profile.

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Using Latent Profile Analysis to Harness the Heterogeneity of Nonretained College Students

Journal of College Student Retention Research Theory & Practice ◽

10.1177/1521025115611385 ◽

2016 ◽

Vol 18 (4) ◽

pp. 457-473

Author(s):

Tracey N. Sulak ◽

Jennifer Massey ◽

David Thomson

Keyword(s):

Large Scale ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Retention Rates ◽

First Year ◽

First Year Students ◽

Private Research ◽

Key Variables ◽

The University ◽

Latent Profile

Universities struggle to raise retention rates among first-year students. Traditional analyses have not only focused on large-scale issues and addressed the needs of the majority but also done little to change overall retention numbers. The current study demonstrates the benefit of using a person-centered approach to retention research. Latent profile analysis was used to examine all nonretained, first-year students ( n = 515) from the 2011 cohort at a private, research-intensive university. The larger population of nonretained first-year students appeared to contain several smaller, subpopulations, and these smaller groups differed on key variables collected by the university. The differences in the subpopulations indicate a need for greater specificity in retention programming.

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Latent Profiles of Writing-related Skills, Knowledge, and Motivation for Elementary Students and Their Relations to Writing Performance across Multiple Genres

10.35542/osf.io/k82wd ◽

2022 ◽

Author(s):

Gary Alan Troia ◽

Heqiao Wang ◽

Frank R. Lawrence

Keyword(s):

At Risk ◽

Elementary Students ◽

Student Performance ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Empirical Support ◽

Individual Knowledge ◽

Latent Profiles ◽

Latent Profile

Our goal in this study is to expand the limited research on writer profiles using the advantageous model-based approach of latent profile analysis and independent tasks to evaluate aspects of individual knowledge, motivation, and cognitive processes that align with Hayes’ (1996) writing framework, which has received empirical support. We address three research questions. First, what latent profiles are observed for late elementary writers using measures aligned with an empirically validated model of writing? Second, do student sociodemographic characteristics—namely grade, gender, English learner status, and special education status—influence latent profile membership? Third, how does student performance on narrative, opinion, and informative writing tasks, determined by quality of writing, vary by latent profiles? A five-profile model had the best fit statistics and classified student writers as Globally Weak, At Risk, Average Motivated, Average Unmotivated, and Globally Proficient. Overall, fifth graders, female students, students without disabilities, and native English speakers had greater odds of being in the Globally Proficient group of writers. For all three genres, other latent profiles were significantly inversely related to the average quality of papers written by students who were classified as Globally Proficient; however, the Globally Weak and At Risk writers were not significantly different in their writing quality, and the Average Motivated and Average Unmotivated writers did not significantly differ from each other with respect to quality. These findings indicate upper elementary students exhibit distinct patterns of writing-related strengths and weaknesses that necessitate comprehensive yet differentiated instruction to address skills, knowledge, and motivation to yield desirable outcomes.

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The Big Five Model in Bipolar Disorder: A Latent Profile Analysis and its Impact on Longterm Illness Severity

10.21203/rs.3.rs-895712/v1 ◽

2021 ◽

Author(s):

Niklas Ortelbach ◽

Jonas Rote ◽

Alice Mai Ly Dingelstadt ◽

Anna Stolzenburg ◽

Cornelia Koenig ◽

...

Keyword(s):

Bipolar Disorder ◽

Regression Analysis ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Illness Severity ◽

Personality Profiles ◽

Latent Profile Analyses ◽

Big Five Model ◽

Morbidity Index ◽

Latent Profile

Abstract Background Using a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the current study firstly aimed to identify latent classes of NEO-FFI profiles, and, secondly, to examine their impact on the longterm prognosis of BD. Methods Based on the NEO-FFI profiles of 134 euthymic patients diagnosed with BD (64.2% female, mean age = 44.3 years), successive latent profile analyses were conducted. Subsequently, a subsample (n = 80) was examined prospectively by performing multiple regression analysis to evaluate the longitudinal course of the disease (mean: 54.7 weeks) measured using a modified Morbidity Index. Results The latent profile analyses suggested a 3-class model typifying in a resilient (n = 68, 51%), vulnerable (n = 55, 41%) and highly vulnerable (n = 11, 8%) class. In the regression analysis, higher vulnerability predicted a higher longterm Morbidity Index ( R 2 = .28). Conclusions Subgroups of patients with BD share a number of discrete personality features and their illness is characterized by a similar clinical course. This knowledge is valuable in a variety of clinical contexts including early detection, intervention planning and treatment process.

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Beyond the Liberal–Conservative Binary: Generosity, Religion, and a Latent Profile Analysis of Moral Foundations in a Christian Sample

American Behavioral Scientist ◽

10.1177/0002764219850867 ◽

2019 ◽

Vol 63 (14) ◽

pp. 1938-1964 ◽

Cited By ~ 1

Author(s):

Tyler S. Greenway ◽

Joel Jin ◽

Abigail M. Shepherd ◽

Sarah A. Schnitker

Keyword(s):

Political Ideology ◽

Latent Profile Analysis ◽

Profile Analysis ◽

The Other ◽

Religious Fundamentalism ◽

Moral Foundations ◽

Christian Church ◽

Charitable Organization ◽

Latent Profile Analyses ◽

Latent Profile

This study conducted an experiment to examine the associations between moral foundations profiles, religion, and generosity ( N = 313). Previously identified profiles were replicated with latent profile analyses based on the Moral Foundations Questionnaire (MFQ). Four MFQ profiles (Neutral, High Moralist, Moderate, and Individuator) were identified in this study of Christian church attenders. Significant differences across these four profiles are associated with distinctions in generosity, some components of empathy, religiousness, and political ideology. Compared with the other three profiles, individuals with the Individuator profile donated more of their participant payment to a charitable organization run by a religious out-group (Muslims). In contrast, there were no differences between profiles on donations to the in-group, secular groups, or total donations. Religious fundamentalism was lowest among Individuators and highest among High Moralists, the latter of whom also reported higher interpersonal generosity than Moderates.

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