A personality-based latent class typology of outpatients with major depressive disorder: association with symptomatology, prescription pattern and social function

The relationship between nomophobia and latent classes of personality

The phenomenon of nomophobia, defined as the anxiety experienced when a person is without their mobile phone or is unable to use it, has been identified as having serious negative effects on individuals, particularly students. Previous research has explored the relationship between personality traits and nomophobia, but the findings have been inconclusive. The main objective of this study was to classify personality types through latent class analysis and explore the relationship between these personality types and nomophobia. The Chinese version of the Nomophobia Scale and the Chinese brief version of the Big Five Personality Inventory were used in this study to survey 1906 Chinese college students. The results indicated that (1) a four-class model provided the best fit and categorized the personality traits as the overcontrolled class, resilient class, moderate class, and vulnerable class; (2) significant differences were observed between the four personality types and nomophobia, with overcontrolled and resilient personality types consistently scoring significantly lower than moderate and vulnerable personality types. Our finding highlights the key feature of the study.

Association between personality profiles and symptomatology patterns based on TCI and MMPI-2-RF in a transdiagnostic psychiatric sample: A person-centered approach

BACKGROUND

The temperament and character dimensions of personality appear to be networking structures that interact nonlinearly. Previous studies have attempted to classify temperament and character subtypes using a person-centered approach but have been unable to explore the relationship between the combination of temperament and character and psychopathology patterns in a transdiagnostic sample. The purpose of this study was to examine how symptomatology patterns differ according to individuals' personality profiles, employing a psychobiological model in a transdiagnostic psychiatric sample.

METHODS

Participants were 1881 patients who visited the psychiatry department of a major medical hospital in Seoul, Korea, and completed both the Temperament Character Inventory (TCI) and the Minnesota Multiphasic Personality Inventory-2-Restructed Form (MMPI-2-RF) as part of their psychological evaluation. We performed two separate latent profile analyses using four temperament and four character indicators of the TCI to identify personality profiles and nine restructured clinical scales of the MMPI-2-RF to identify symptom patterns.

RESULTS

Five personality classes emerged: "vulnerable-maladaptive," "stable-adaptive," "average," "inhibited-neurotic," and "impulsive-irrational." Moreover, six symptom classes emerged: "non-distressed," "depressed," "emotionally-distressed," "average," "dysfunctional thoughts," and "confused." The personality profiles comprising a combination of rigid temperament and immature character were related to patterns of more severe subjective pain and symptoms. However, profiles with less rigid temperament and less immature character exhibited more diverse symptom patterns.

CONCLUSIONS

This study examined the relationship between personality profiles and symptomatology patterns, suggesting that understanding patients' personality profiles may be helpful in predicting symptom manifestation and establishing treatment plans.

Latent classes of maladaptive personality traits exhibit differences in social processing

OBJECTIVE

Social processing (SP) deficits manifest across numerous mental disorders. However, this research has been plagued by heterogeneity and a piecemeal approach whereby skills are examined in isolation rather than as part of an integrated cognitive system. Here, we combined two dimensional frameworks of psychopathology to address these limitations.

METHOD

We utilized the Alternative Model for Personality Disorders (AMPD) to distill trait-related heterogeneity within a community sample (n = 200), and the Research Domain Criteria (RDoC) 'Systems for Social Processes' to comprehensively assess SP. We first applied latent class analyses (LCA) to derive AMPD-based groups and subsequently contrasted the performance of these groups on a SP test battery that we developed to align with the RDoC SP constructs.

RESULTS

Our LCA yielded four distinct subgroups. The recognizable trait profiles and psychopathological symptoms of these classes suggested they were clinically meaningful. The subgroups differed in their SP profiles: one displayed deficits regarding the self, a second displayed deficits in understanding others, a third displayed more severe deficits including affiliation problems, whilst the fourth showed normal performance.

CONCLUSIONS

Our results support the link between clusters of maladaptive personality traits and distinctive profiles of SP deficits, which may inform research on disorders involving SP dysfunctions.

Abnormal functional connectivity as neural biological substrate of trait and state characteristics in major depressive disorder

OBJECTIVE

Major depressive disorder (MDD) is a neuropsychiatric disorder associated with functional dysconnectivity in emotion regulation system. State characteristics which measure the current presence of depressive symptoms, and trait characteristics which indicate the long-term vulnerability to depression are two important features of MDD. However, the relationships between trait and state characteristics of MDD and functional connectivity (FC) within the emotion regulation system still remain unclear.

METHODS

This study aims to examine the neural biological mechanisms of trait characteristics measured by the Affective Neuroscience Personality Scale (ANPS) and state anhedonia measured by the Snaith-Hamilton Pleasure Scale (SHAPS) in MDD. Sixty-three patients with MDD and 63 well-matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. A spatial pairwise clustering and the network-based analysis approaches were adopted to identify the abnormal FC networks. Support vector regression was utilized to predict the trait and state characteristics based on abnormal FCs.

RESULTS

Four disrupted subnetworks mainly involving the prefrontal-limbic-striatum system were observed in MDD. Importantly, the abnormal FC between the left amygdala (AMYG)/hippocampus (HIP) and right AMYG/HIP could predict the SADNESS scores of ANPS (trait characteristics) in MDD. While the aberrant FC between the medial prefrontal cortex (mPFC)/anterior cingulate gyrus (ACC) and AMYG/parahippocampal gyrus could predict the state anhedonia scores (state characteristics).

CONCLUSIONS

The present findings give first insights into the neural biological basis underlying the trait and state characteristics associated with functional dysconnectivity within the emotion regulation system in MDD.

Predictability of temperaments and negative experiences on higher-order symptom-based subtypes of depression

BACKGROUND

The identification of subtypes of depression based on higher-order symptoms of emotional, thought, and behavioral dysfunction will broaden understanding of the heterogeneity in depression. Furthermore, exploring the ability of temperaments and negative experiences to predict each subtype is an effective way of facilitating treatment decisions.

METHODS

Participants were 417 patients diagnosed with depressive disorder at the psychiatry department of a major medical hospital in Seoul, Korea. A latent profile analysis was performed based on three higher-order scales of the MMPI-2-RF: Emotional/Internalizing Dysfunction, Thought Dysfunction, and Behavioral/Externalizing Dysfunction. Four temperament dimensions were assessed by the Temperament and Character Inventory-Revised-Short, and negative experiences including recent negative life events, number of lifetime traumatic events, and severity of maltreatment, were used as covariates in a multinomial regression analysis.

RESULTS

Four classes were obtained from the latent profile analysis: a "severe mood class" (39.8%), a "moderate mood class" (37.4%), a "mild mood class" (11.3%), and a "severe mood/thought class" (11.5%). Among temperament dimensions, high harm avoidance and low persistence significantly predicted more severe mood classes. Low reward dependence, number of lifetime traumatic events, and severity of maltreatment in negative experiences were significant predictors of the severe mood/thought class.

LIMITATIONS

This study could not explain the more detailed heterogeneity within depression because of over-inclusiveness of the higher-order scales.

CONCLUSIONS

This study identified three latent classes that differed in emotional severity and one other class with thought problems. The distinct dimensions of temperament and different types of negative experiences predicted the identified subtypes.

Association of Personality Profiles with Depressive, Anxiety, and Cancer-related Symptoms in Patients Undergoing Chemotherapy

Background

This study identified latent classes of cancer patients based on Big Five personality dimensions and evaluated for differences in demographic and clinical characteristics, depression, anxiety, and cancer-related symptoms.

Methods

Patients (n=1248) with breast, gastrointestinal, gynecological, or lung cancer completed the Center for Epidemiological Studies-Depression scale, Spielberger State-Trait Anxiety Inventories, NEO-Five Factor Inventory (NEO-FFI), and Memorial Symptom Assessment Scale (MSAS). Latent class profile analysis of NEO-FFI scores was used to identify patient subgroups.

Results

Three latent classes were identified. The "Distressed" class (14.3%) scored highest on neuroticism and lowest on extraversion, agreeableness, and conscientiousness. The "Resilient" class (31.9%) scored lowest on neuroticism and highest on extraversion, agreeableness, and conscientiousness. The "Normative" class (53.8%) was intermediate on all dimensions except openness. Compared to the Resilient class, patients in the Distressed class were younger, less educated, more likely to care for another adult, had more comorbidities, and exercised less. The three classes differed by performance status, marital and employment status, and income, but not by gender, time since diagnosis, or type of prior cancer treatment. The classes differed (Distressed > Normative > Resilient) in depression, anxiety, and cancer symptoms.

Conclusions

Personality is associated with psychological and physical symptoms in cancer patients.