Class Analysis Research Articles

Pathways to Sustainable Careers: Exploring Motivational Profiles Through Latent Class Analysis

The purpose of this study is to identify motivational profiles in sustainable career trajectories via emerging latent class methods using a multilevel schema between engagement in sustainable career practices, developing and utilizing job competency—a key marker for human capital development—and leader–member interaction. Using latent class analysis (LCA), we further identify different types of motivational profiles that reflect the principle and adaptable nature with which individuals can relate their sustainability values to career decisions. Results indicate large practical differences within latent classes, evidencing higher career adaptability and sustainability principles congruence in some groups. These differences highlight that intrinsic motivation, adaptability, and elements connected to the sector drive sustainable career engagement that should ensure enduring satisfaction with commitment to a chosen profession. In explaining why sustainability drives career advancement, this study takes a theoretical standpoint from three overarching theories: Career Construction Theory, Social Cognitive Career Theory (SCCT), and Sustainable Career Theory. The practical recommendations are that companies must offer programs at the sector level to increase career adaptability (readiness) and help employees build sustainable careers. This study calls attention to the importance of producing participative content that is demanded by organizations seeking greater resilience, well-being in work contexts, and their long-lasting survival as institutions.

Identifying Subgroups of Intersectional Stigma, Discrimination, and the Association with Mental Health Outcomes Among HIV-Positive Men Who Have Sex with Men: A Latent Class Analysis.

This study aimed to (1) identify latent classes of stigma and discrimination experiences among men who have sex with men (MSM) living with HIV; (2) examine the associations between class membership and mental health outcomes, and (3) investigate the moderating effects of social support and resilience. The study used the baseline (N = 224) and six-month follow-up data (N = 118) from a longitudinal cohort study on HIV and hypertension among African American and Asian Pacific American MSM in Hawai'i and Philadelphia from 2019 to 2023. Latent class analysis was conducted to characterize the patterns of stigma and discrimination experience. Multivariable regression was conducted to examine the association between class membership and mental health outcomes. Interaction terms were added to examine the moderation effects of social support and resilience on the association between class memberships and mental health outcomes. A five-class model was identified: Class (1) high on internalized homophobia and low on all discrimination experiences; Class (2) high on racial discrimination; Class (3) high on sexual identity discrimination; Class (4) low on internalized homophobia and all discrimination experiences; Class (5) high on physical disability discrimination and internalized homophobia. Class 5 consistently predicted worse mental health outcomes, compared to Class 4. The association between Class 2 (high racial discrimination) and depression was moderated by perceived social support. The study reveals complex experiences of intersectional stigma and discrimination among MSM living with HIV, highlighting the need for further research on the intersecting effects of multiple disadvantages among aging sexual minorities.

The mediating role of psychological equilibrium in the relationship between dietary variety and self-reported health among older adults in rural China.

Self-Reported Health (SRH) is an important covariate in health and gerontology research and may be related to dietary diversity. Therefore, this study aimed to analyze this association in a large-scale general population of rural older adults from China. It also investigates the mediating effect of the psychological equilibrium (PE) in the association between dietary variety and SRH in this population. Based on data from the 2018 Chinese Longitudinal Healthy Longevity Study (CLHLS), 4,643 rural older adults were included in the study. The Dietary Variety Index was found across seven food classes using latent class analysis (LCA). We examined the factors impacting self-reported health using unordered multiple logistic regression analysis. Model 4 of the PROCESS version 4.1 software was used to evaluate the mediation impact of psychological balance. 4,643 rural seniors from the CLHLS were included in the study. Four distinct dietary variation indices (DVIs) were identified for each of the seven food categories through Latent Class Analysis. Fruit, vegetables, meat, fish, eggs, nuts, and milk significantly influenced self-reported health (SRH), according to unordered multinomial logistic regression. Positive correlations between DVI and psychological equilibrium (PE) (r = 0.052, P < 0.001), DVI and SRH (r = 0.054, P < 0.001), and PE and SRH (r = 0.220, P < 0.001) were revealed by Pearson correlation analysis. PE modifies the connection between DVI and SRH, with a significant indirect effect (β = 0.002, 95% CI = 0.001 to 0.003), according to mediation analysis. The self-reported health (SRH) of older people living in rural areas has unique classification features; fruits, vegetables, meat, fish, eggs, nuts, and milk have all been found to be important influencing factors. The relationship between psychological equilibrium (PE) and SRH is indirect. Our results emphasize how critical it is to support a varied diet in order to improve SRH in older adults living in rural areas. Furthermore, this population's psychological balance needs to be taken into consideration.

Sleep patterns and smartphone use among left-behind children: a latent class analysis and its association with depressive symptoms

BackgroundLeft-behind children in China face challenges in sleep patterns, technology use, and mental health. This study uses an individual-centered approach to derive behavioral profiles associated with depressive symptoms.MethodsData from 131,586 left-behind children aged 8 to 18 years from the Chinese Psychological Health Guard for Children and Adolescents Project were analyzed. Participants were recruited from 569 centers across schools, community institutes, orphanages, and children’s hospitals throughout China. Latent class analysis was conducted using weekday and weekend sleep duration and smartphone use as indicators. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D).ResultsFour distinct classes emerged: Sufficient Sleep Low Users (23.6%), Moderate Sleep Medium Users (25.2%), Limited Sleep High Users (22.1%), and Healthy Sleep Low Users (29.2%). Significant differences in CES-D scores were found between classes (F(3, 131579) = 4929, p &amp;lt;.001, η² = 0.101). The Limited Sleep High Users class reported the highest levels of depressive symptoms (M = 11.60, SE = 0.0658), while the Sufficient Sleep Low Users class reported the lowest (M = 3.67, SE = 0.0346). A linear relationship between sleep duration and depressive symptoms was observed. Significant weekday-weekend differences in smartphone use were noted in the unhealthy categories.ConclusionsThis study reveals complex associations between sleep patterns, smartphone use, and depressive symptoms among left-behind children. The identified behavioral profiles provide insights into population heterogeneity and inform targeted intervention strategies. Findings emphasize the importance of addressing both sleep and technology use in mental health initiatives for this vulnerable population.

Phenotypic Trajectories From Acute to Stable Phase in Heart Failure With Preserved Ejection Fraction: Insights From the PURSUIT-HFpEF Study.

Using machine learning for the phenotyping of patients with heart failure with preserved ejection fraction (HFpEF) has emerged as a novel approach to understanding the pathophysiology and stratifying the patients. Our objective is to perform phenotyping of patients with HFpEF in stable phase and to investigate the phenotypic trajectory from acute worsening phase to stable phase. The present study is a post hoc analysis of the PURSUIT-HFpEF (Prospective Multicenter Observational Study of Patients with Heart Failure with Preserved Ejection Fraction) study. We applied the latent class analysis to the discharge data of patients hospitalized for acute decompensated heart failure. We finally included patient data of 1100 cases and 63 features in the latent class analysis. All patients were subclassified into 5 phenogroups as follows: Phenotype 1, characterized by better renal function and lower NT-proBNP (N-terminal pro-B-type natriuretic peptide) level [N=325 (29.5%)]; Phenotype 2, higher blood pressure, sinus rhythm, and poor renal function. [N=242 (22.0%)]; Phenotype 3, higher prevalence of atrial fibrillation, higher tricuspid pressure gradient, and lower tricuspid annular plane systolic excursion [N=214 (19.5%)]; Phenotype 4, higher C-reactive protein level and higher tricuspid pressure gradient [N=245 (22.3%)]; and Phenotype 5, poor nutritional status, poor renal function, and higher NT-proBNP level [N=74 (6.7%)]. A particular phenotype observed at the time of discharge was correlated with a distinct phenotype of acute worsening. We identified 5 distinct stable phase phenotypes of the patients with HFpEF from the data at discharge. A specific phenotype at discharge was associated with a particular phenotype of acute worsening. This grouping can be a basis for future precision medicine of patients with HFpEF. URL: https://www.umin.ac.jp/ctr/; Unique identifier: UMIN000021831.

The Attitudes of the General Student Body Toward Gifted Students and Gifted Education: Attitude Profiles and Predictors

ABSTRACTIn this study, an investigation was conducted into the nature of the attitudes of the general student body (comprising all students) toward gifted students and gifted education, along with the predictors of such attitudes. For this purpose, survey data were collected from 400 secondary students enrolled in a faith‐based school system in Australia. Data were analyzed using exploratory factor analysis, latent class analysis, and multiple regression analysis. Among the study findings were: (a) student attitudes toward gifted students and gifted education exist along two dimensions (i.e., support for gifted student adaptations and perceptions of non‐elitism), (b) students may be classified into three groups with distinct attitude profiles that differ from one another along these two dimensions (i.e., strong supporters of gifted students/gifted education, students with neutral attitudes toward gifted students/gifted education and non‐supporters of gifted students/gifted education, comprising 13%, 82%, and 5% of students respectively), and (c) the key predictors of student attitudes are school administrative support, academic impact, respect for authority, knowledge of giftedness and contact with gifted persons. The contributions of the study to the research literature are discussed.

Linking Multi-Dimensional Religiosity in Childhood and Later Adulthood: Implications for Later Life Health.

This study examines religiosity patterns across childhood and later adulthood and their associations with later-life health using an experimental module from the 2016 Health and Retirement Study (N = 1649; Mean Age = 64.0). Latent class analysis is used to categorize individuals by commonalities in religious attendance, religious identity, and spiritual identity. Cross-sectional and longitudinal associations are then explored using probable depression, disability, and mortality as health indicators. Results reveal complex patterns, often characterized by declining attendance and fluctuating identity. Relationships with health appear stronger in cross-sectional analyses, suggesting that some associations may be non-causal. Individuals with consistently strong religiosity show significantly better psychological health compared to their relatively non-religious counterparts. Moreover, the absence of religiosity in later adulthood is associated with an increased risk of mortality. Overall, the findings support the promotion of religiosity whilst acknowledging individual variations and highlighting the need for more individualistic approaches to the study of religion and health.

Prolonged grief and posttraumatic stress in parents who lost a child in a road traffic accident: A latent class analysis

Prolonged grief and posttraumatic stress in parents who lost a child in a road traffic accident: A latent class analysis

Social isolation and depressive symptoms among older adults with different functional status in China: A latent class analysis.

Social isolation is considered a risk factor for depression in older adults. Since there may be heterogeneity in the experience of social isolation, we aimed to investigate social isolation patterns and their association with depressive symptoms, for older adults with different functional status separately. This study used data from the fifth wave of the China Health and Retirement Longitudinal Study (CHARLS). A total of 8262 participants, defined as older adults aged 60 years and above, were included in the analysis, comprising 49.9 % (n = 4124) men and 50.1 % (n = 4138) women. Latent class analysis was conducted to identify social isolation patterns. Binary logistic regression was used to estimate the association between latent classes and depressive symptoms. Two distinct classes were identified in participants with functional dependency and three classes were identified in participants without functional dependency. The severely isolated with minimal family and social contact group was associated with a higher risk of depressive symptoms in both subgroups (participants with functional dependency: OR = 1.319, 95%CI: 1.032-1.686; participants without functional dependency: OR = 1.537, 95%CI: 1.209-1.953). No difference was found in the risk of depressive symptoms between the moderately isolated with family contact group and the low isolated group among participants without functional dependency (OR = 1.020, 95%CI: 0.83-1.252). Risk of depressive symptoms varies with different social isolation patterns among older people with different functional status.

Profiles of chemotherapy-induced peripheral neuropathy in breast cancer patients undergoing taxane-based chemotherapy: A latent class analysis.

This study aimed to identify the potential subgroups of chemotherapy-induced peripheral neuropathy (CIPN) in breast cancer patients undergoing taxane-based chemotherapy and examine the association of the latent subtype with patient characteristics. This multi-center, cross-sectional investigation was conducted between April 2022 and March 2023. CIPN was evaluated using the Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity scale. Latent class analysis was employed to identify distinct CIPN subgroups, and multinomial logistic regression was used to analyze the associations between these subgroups and patient characteristics. In total, 397 individuals were categorized into three subgroups: high symptoms with high dysfunction (Class 1; 25.4%), moderate symptoms with low dysfunction (Class 2; 39.2%), and low symptoms with low dysfunction (Class 3; 35.3%). Taxane type, chemotherapy cycles, fatigue, β-blocker use, and depression were significant predictors of the subgroups (P<.05). CIPN symptoms in breast cancer patients are heterogeneous. Significant factors for the latent subgroups included taxane type, chemotherapy cycles, β-blocker use, fatigue, and depression. Identifying different subgroups of chemotherapy-induced peripheral neuropathy would help develop interventions tailored to the patients.

Patterns of Polysubstance Use Among People who Inject Drugs Using the National HIV Behavioral Surveillance System: A Latent Class Analysis

Patterns of Polysubstance Use Among People who Inject Drugs Using the National HIV Behavioral Surveillance System: A Latent Class Analysis

New Psychoactive Substance and Polysubstance Use Patterns Among Adults in 19 US Cities: A Latent Class Analysis

New Psychoactive Substance and Polysubstance Use Patterns Among Adults in 19 US Cities: A Latent Class Analysis

Identifying Distinct Cannabis Use Disorder Symptom Profiles among Past-Year Cannabis Users in the United States: A Latent Class Analysis

Identifying Distinct Cannabis Use Disorder Symptom Profiles among Past-Year Cannabis Users in the United States: A Latent Class Analysis

Patterns of socioeconomic marginalization and non-fatal overdose among people who use drugs: A gender-stratified repeated measures latent class analysis.

While marked gender-based differences in drug-related risk and harm between men women who use drugs have been characterized to some extent, the complex relationship between gendered socioeconomic conditions, overdose risk, and drug use patterns and behaviours remains underexplored. We conducted gender-stratified repeated measures latent class analyses (RMLCA) with data from two ongoing cohorts of people who use drugs in Vancouver, Canada to identify discrete subgroups based on socioeconomic exposures. Multivariable generalized estimating equations models weighted by the respective posterior membership probabilities were applied to estimate the associations between socioeconomic class membership and non-fatal overdose. Sub-analyses investigated whether these relationships were explained by drug use-related variables. Between June 2014 and March 2020, 1723 participants provided 12120 observations. At study baseline, 1074 (62.3%) were men and 649 (37.7%) were women. In RMLCA, five distinct profiles of socioeconomic exposures emerged for men, and four emerged for women. Classes were presented in ascending order of socioeconomic disadvantage (i.e., ranging from Class 1 [least disadvantage] to Class 4/Class 5 [most disadvantage]) and were primarily distinguished by variations in income, material and housing in/security, participation in illegal/informal income generation, and criminal justice involvement. In analyses adjusting for demographic characteristics, for both men and women, progressive increases in exposure to multiple dimensions of disadvantage were positively and independently associated with non-fatal overdose when compared to the least socioeconomically disadvantaged subgroup. Subsequent analyses revealed that systematic differences in drug use patterns and behaviours across categories of socioeconomic disadvantage largely accounted for these relationships. Addressing multiple forms of mutually reinforcing health inequities may offer additional opportunity to mitigate non-fatal overdose in men and women who use drugs.

Latent Class Analysis of Changes in Substance Use and Depressive Symptoms following Naturalistic Psilocybin Use: Results from a Prospective Longitudinal Survey

Latent Class Analysis of Changes in Substance Use and Depressive Symptoms following Naturalistic Psilocybin Use: Results from a Prospective Longitudinal Survey

Using Latent Class Analysis to Examine Polysubstance Use Patterns in Adolescents Aged 10-18: A Systematic Review

Using Latent Class Analysis to Examine Polysubstance Use Patterns in Adolescents Aged 10-18: A Systematic Review

Early Childhood Income Instability and Mental Health in Adolescence: Parenting Stress and Child Maltreatment as Mediators.

Ample research has examined how point-in-time or static measures of economic deprivation are associated with children's mental health outcomes. Less is known about the relationship between early childhood unstable income and mental health outcomes. Using the Future of Families and Child Wellbeing Study, this study examined (1) the latent patterns of early childhood economic well-being, predicted by income level and instability (i.e., direction and frequency of income change); (2) the association of income deprivation patterns with subsequent anxiety and depression symptoms, paying particular attention to the mediating roles of parenting stress and child maltreatment risk. The latent class analysis results suggested four distinct groups representing different combinations of income level and instability. Structural equation modeling results indicated indirect links between income deprivation patterns and mental health outcomes, through parenting stress and physical and psychological abuse. Findings indicated the importance of policies and programs promoting economic stability over the long run.

Who is living near different types of US Superfund sites: A latent class analysis considering site contaminant profiles.

Millions of people in the United States live near Superfund sites and may be exposed to hazardous chemicals from those sites. However, there is limited research on chemicals present at sites and the demographics of nearby communities. We aimed to identify subgroups of Superfund sites with similar contaminant profiles and evaluate whether sociodemographic characteristics vary by type of site. We used US Environmental Protection Agency Superfund data to identify sites active in the year 2000. Census tract centroids located within 3 miles of every Superfund site were identified and a weighted average of census tract-level sociodemographics using the 2000 US Census was calculated. Superfund sites with similar contaminant profiles were identified using latent class analysis. We compared the median sociodemographic characteristics, overall and by contaminant latent class, with those of the overall 2000 US Census. We identified seven latent classes based on 12 contaminant categories from 1332 Superfund sites active in 2000. Overall, there were few differences in sociodemographics observed by the presence of any Superfund site compared with the overall US Census. After stratifying by contaminant profile, we observed evidence of disparities for two classes of sites, defined by (1) high diversity of chemical exposure and lumber industry and (2) batteries and metals, which were more likely to have higher hazard scores and to be near communities with higher proportions of non-White individuals, lower socioeconomic status, and higher social vulnerability. Disadvantaged communities, with higher social vulnerability, were more likely to be near certain Superfund sites with higher hazard scores.

Suboptimal dietary patterns are associated with accelerated biological aging in young adulthood: A study with twins.

Suboptimal diets increase morbidity and mortality risk. Epigenetic clocks are algorithms that can assess health and lifespan, even at a young age, before clinical manifestations of diseases. We investigated the association between dietary patterns and biological aging in young adult twins. The data were drawn from the population-based FinnTwin12 study and consisted of twins aged 21-25 years (n=826). Food and beverage intakes were assessed using a food frequency questionnaire. Biological aging was estimated using the epigenetic clocks GrimAge and DunedinPACE. Latent class analysis was used to identify dietary patterns. The association between dietary patterns and biological aging was assessed using linear regression modeling at the individual level, followed by within-twin pair analyses to account for genetic liabilities and shared familial confounders. Six dietary patterns were identified: 1) High fast food, low fruits and vegetables (F&V), 2) Plant-based, 3) Health-conscious, 4) Western with infrequent fish, 5) Western with regular fish, and 6) Balanced average. At the individual level, GrimAge acceleration was slower in the Plant-based, Health-conscious, and Balanced-average patterns compared to the High fast food, low F&V, and faster in the Western with infrequent fish pattern compared to the Balanced average, regardless of sex, nonalcoholic energy intake, smoking, and alcohol consumption. After further adjustment for BMI and sports participation, the strengths of the associations modestly decreased; however, the difference between the Balanced-average and High fast food, low F&V patterns remained significant. The pace of aging (DunedinPACE) was slower in the Plant-based pattern compared to the High fast food, low F&V and the Western with infrequent fish patterns after adjustment for sex, nonalcoholic energy intake, smoking, and alcohol. The effect sizes were attenuated and reached a non-significant level when BMI and sports participation were added to the model. Most of the associations were replicated in the within-pair analyses among all twin pairs and among dizygotic twin pairs, but the effect sizes tended to be smaller among monozygotic twin pairs. This suggests that genetics, but not a shared environment, may partially explain the observed associations between diet and biological aging. Diets high in fast food, processed red meat, and sugar-sweetened beverages and low in fruits and vegetables are associated with accelerated biological aging in young adulthood. The clustering effect of lifestyle factors and genetic confounders should be considered when interpreting the findings.

Racial Differences in Adverse Childhood Experiences: Timing and Patterns.

Traditional research on adverse childhood experiences (ACEs) often retrospectively assesses ACEs and treats ACEs as a composite score, potentially overlooking the distinct effects of specific ACE patterns and their critical timing, which may influence health outcomes differently. It is crucial to explore variations in the patterns and timing of ACE exposure across racial/ethnic groups to improve ACE screening and intervention strategies. In 2023, this study analyzed data of the Future of Families and Child Wellbeing Study (FFCWS) initially conducted in 1998. FFCWS sampled children from three racial/ethnic groups (N_Black = 2,587; N_Latine = 1,577; N_White = 770). ACEs were assessed through seven indicators from ages three to 15, including physical and psychological abuse, neglect, witnessing maternal intimate partner violence (IPV), parental depression, separation, and material hardship. Using Longitudinal Latent Class Analysis (LLCA), this research aimed to identify distinctive patterns and timing of ACEs among White, Black, and Latine youth. The analysis revealed a 9-class model applicable to these three racial/ethnic youth groups. Classes combining material hardship with other ACEs and those featuring adolescent abuse were more prevalent among Black and Latine youth. This study also identified a class displaying a temporal pattern, such as early maternal IPV followed by late parental separation. This study highlights the necessity of analyzing diverse class structures and the timing of ACEs across different racial/ethnic groups. Understanding these nuances is vital for developing culturally tailored interventions to reduce health disparities.