Identifying affective personality profiles: A latent profile analysis of the Affective Neuroscience Personality Scales

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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Defining Subtypes in Children with Nail Biting: A Latent Profile Analysis of Personality

Psychiatry Investigation ◽

10.30773/pi.2019.0015 ◽

2020 ◽

Vol 17 (6) ◽

pp. 517-525 ◽

Cited By ~ 1

Author(s):

Yunhye Oh ◽

Jungwon Choi ◽

Yul-Mai Song ◽

Kyungun Jhung ◽

Young-Ryeol Lee ◽

...

Keyword(s):

Behavioral Problems ◽

Latent Profile Analysis ◽

Profile Analysis ◽

Developmental Trajectory ◽

Personality Profile ◽

Personality Profiles ◽

Problematic Behavior ◽

Significant Group ◽

Nail Biting ◽

Latent Profile

Objective This study aimed to examine personality profiles and behavioral problems of children with nail biting (NB) to gain insight into the developmental trajectory of pathological NB.Methods 681 elementary school students were divided into non NB (n=436), occasional NB (n=173) and frequent NB group (n=72) depending on the frequency of NB reported in Child Behavioral Checklist (CBCL). Children’s personality was assessed using the Junior Temperament and Character Inventory (JTCI), and behavioral problems were assessed using the CBCL. Latent Profile Analysis (LPA) was performed using JTCI profiles to classify personalities of the children with NB (belonging to frequent and occasional NB group, n=245).Results For subscale scores of CBCL, the total, internalizing, externalizing, anxious/depressed withdrawn/depressed, depression, thought, rule-breaking, and aggressive behavior problems, were most severe in the frequent NB group followed by occasional NB and non NB group. LPA of personality profile in children with NB revealed four classes (‘adaptiveness,’ ‘high reward dependence,’ ‘low self-directedness,’ and ‘maldaptiveness’). The four personality classes demonstrated significant group differences in all of the CBCL subscales. Children who showed low self-directedness and cooperativeness and high novelty seeking and harm avoidance personality profiles demonstrated highest tendency for problematic behavior irrespective of the frequency of NB.Conclusion Children with NB reported significantly more problematic behaviors compared to children without NB. Children with specific personality profile demonstrated higher tendency for problematic behavior irrespective of the frequency of NB. Therefore, accompanying personality profiles should be considered when assessing behavioral problems in children with NB.

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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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Mental Health and Personality Traits during COVID-19 in China: A Latent Profile Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18168693 ◽

2021 ◽

Vol 18 (16) ◽

pp. 8693

Author(s):

Mei Li ◽

Md Zahir Ahmed ◽

Fatema Akhter Hiramoni ◽

Aibao Zhou ◽

Oli Ahmed ◽

...

Keyword(s):

Mental Health ◽

Personality Traits ◽

Latent Profile Analysis ◽

Mental Health Problems ◽

Profile Analysis ◽

Health Problems ◽

Ptsd Symptoms ◽

Personality Profiles ◽

Anxiety Depression ◽

Latent Profile

During the COVID-19 pandemic, mental health problems have increased and are likely to be influenced by personality traits. The present study investigated the association between personality traits and mental health problems (anxiety, depression, post-traumatic stress syndrome (PTSD) symptoms, and obsessive–compulsive disorder (OCD) symptoms) through the person-centered approach because this has some advantages over the variable-centered approach. The data were collected from a sample of 765 Chinese citizens who participated in an online survey in October 2020. Latent profile analysis identified three latent personality profiles—highly adaptive, adaptive, and maladaptive. Highly adaptive individuals had higher extroversion, agreeableness, conscientiousness, openness, and lower neuroticism, while maladaptive individuals had lower extroversion, agreeableness, conscientiousness, openness, and higher neuroticism. Multivariate analysis of variance results showed that individuals with highly adaptive profiles had lower anxiety, depression, and PTSD symptoms compared to individuals with adaptive and maladaptive profiles. The findings of the present study indicate mental health professionals would benefit from formulated intervention plans given the association between latent personality profiles and mental health problems.

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