Latent Class Research Articles

Identification of latent classes in mood and anxiety disorders and their transitions over time: a follow-up study in the adult general population.

Mood and anxiety disorders are heterogeneous conditions with variable course. Knowledge on latent classes and transitions between these classes over time based on longitudinal disorder status information provides insight into clustering of meaningful groups with different disease prognosis. Data of all four waves of the Netherlands Mental Health Survey and Incidence Study-2 were used, a representative population-based study of adults (mean duration between two successive waves = 3 years; N at T0 = 6646; T1 = 5303; T2 = 4618; T3 = 4007; this results in a total number of data points: 20 574). Presence of eight mood and anxiety DSM-IV disorders was assessed with the Composite International Diagnostic Interview. Latent class analysis and latent Markov modelling were used. The best fitting model identified four classes: a healthy class (prevalence: 94.1%), depressed-worried class (3.6%; moderate-to-high proportions of mood disorders and generalized anxiety disorder (GAD)), fear class (1.8%; moderate-to-high proportions of panic and phobia disorders) and high comorbidity class (0.6%). In longitudinal analyses over a three-year period, the minority of those in the depressed-worried and high comorbidity class persisted in their class over time (36.5% and 38.4%, respectively), whereas the majority in the fear class did (67.3%). Suggestive of recovery is switching to the healthy class, this was 39.7% in the depressed-worried class, 12.5% in the fear class and 7.0% in the high comorbidity class. People with panic or phobia disorders have a considerably more persistent and chronic disease course than those with depressive disorders including GAD. Consequently, they could especially benefit from longer-term monitoring and disease management.

Change in different classes of chronic back pain suspicious of axial spondyloarthritis: a latent transition analysis of the SPACE cohort

ObjectivesTo follow up four previously identified classes ‘pure axial spondyloarthritis’ (axSpA) (‘axial’), ‘axSpA with peripheral signs’ (‘inflammatory back pain+peripheral’), ‘axSpA at risk’ and ‘no spondyloarthritis’ (‘no SpA’). They reflect the...

Symptom Dimensions and Cognitive Impairments in Individuals at Clinical High Risk for Psychosis

BackgroundUnderstanding the intricate relationships between symptom dimensions, clusters, and cognitive impairments is crucial for early detection and intervention in individuals at clinical high risk for psychosis. This study delves into this complex interplay in a clinical high risk sample with the aim of predicting the conversion to psychosis. MethodsA comprehensive cognitive assessment was performed in 744 clinical high risk individuals. The study included a 3-year follow-up period to allow assessment of conversion to psychosis. Symptom profiles were determined using the Structured Interview for Prodromal Syndromes. By applying factor analysis, symptom dimensions were categorized as dominant negative symptoms (NSs), positive symptoms-stressful, and positive symptoms-odd. The factor scores were used to define 3 dominant symptom groups. Latent class analysis (LCA) and factor mixture model (FMM) were employed to identify discrete clusters based on symptom patterns. The 3-class solution was chosen for the LCA and FMM analysis. ResultsIndividuals in the dominant NS group exhibited significantly higher conversion rates to psychosis than those in the other groups. Specific cognitive variables, including performance on the Brief Visuospatial Memory Test–Revised (odds ratio = 0.702, p = .001) and Neuropsychological Assessment Battery Mazes Test (odds ratio = 0.776, p = .024), significantly predicted conversion to psychosis. Notably, cognitive impairments associated with NSs and positive symptoms-stressful affected different cognitive domains. LCA and FMM cluster 1, which was characterized by severe NSs and positive symptoms-odd, exhibited more impairments in cognitive domains than other clusters. No significant difference in the conversion rate was observed among the LCA and FMM clusters. ConclusionsThese findings highlight the importance of NSs in the development of psychosis and suggest specific cognitive domains that are affected by symptom dimensions.

Prevalence, patterns and predictors of paranormal beliefs in The Netherlands: a several-analysts approach

Paranormal beliefs encompass a wide variety of phenomena, including the existence of supernatural entities such as ghosts and witches, as well as extraordinary human abilities such as telepathy and clairvoyance. In the current study, we used a nationally representative sample ( N = 2534 ) to investigate the presence and correlates of paranormal beliefs among the secular Dutch population. The results indicated that most single paranormal phenomena (e.g. belief in clairvoyance) are endorsed by 10–20% of Dutch respondents; however, 55.6% of respondents qualify as paranormal believers based on the preregistered criterion that they believe in at least one phenomenon with considerable certainty. In addition, we invited four analysis teams with different methodological expertise to assess the structure of paranormal beliefs using traditional factor analysis, network analysis, Bayesian network analysis and latent class analysis (LCA). The teams’ analyses indicated adequate fit of a four-factor structure reported in a 1985 study, but also emphasized different conclusions across techniques; network analyses showed evidence against strong connectedness within most clusters, and suggested a five-cluster structure. The application of various analytic techniques painted a nuanced picture of paranormal beliefs and believers in The Netherlands and suggests that despite increased secularization, subgroups of the general population still believe in paranormal phenomena.

Profiles of community support and challenges associated with insomnia symptoms: Findings from the pilot Bhutanese Community of Central Ohio Health Study

Study objectivesWe investigated profiles of community support and challenges in relation to insomnia symptoms among the Bhutanese living in the United States. MethodsUsing data from the pilot Bhutanese Community of Central Ohio Health Study (N = 495; 51.5% men, 69.8% aged 18-44years), we used latent class analysis to identify distinct profiles of neighborhood social cohesion, social support, and community challenges (e.g., limited access to healthcare services and transportation, crime and safety issues, substance use, intimate partner violence) and their associations with insomnia symptoms. Insomnia symptoms were self-reported as difficulty falling and staying asleep and dichotomized as “not at all” vs. “some to always.” Identified classes/profiles were further differentiated by self-reported sociodemographic, socioeconomic, health, acculturative, and discrimination factors. ResultsLatent class analysis revealed four distinct classes/profiles. The High Cohesion (class 1) profile (30.1% of sample) had the lowest likelihood of insomnia symptoms at 6.5%, followed by class 2 or High Support (23.6%) with a 15.3% likelihood. Class 3 or High Challenges profile (11.5%) had a moderate likelihood of insomnia symptoms at 49%. Class 4 or the Low Cohesion/Support profile (34.7%) had a 100% likelihood of reporting insomnia symptoms. Class 4 when compared to class 1 was more likely to report cardiometabolic conditions, experiences of everyday discrimination, limited English linguistic proficiency, and not using telehealth. ConclusionCommunity social cohesion and support may play an important role in mitigating insomnia symptoms among Bhutanese refugees. Further investigations are warranted.

Diverse pathways to permanent childlessness in Singapore: A latent class analysis.

The proportions of adults reaching midlife without having children have been rising rapidly across the globe, particularly in Asia. However, little is known about the pathways to permanent childlessness within the region's childless population. This study utilized latent class analysis (LCA) to typologize pathways to childlessness based on dynamic characteristics of multiple life domains (i.e., partnership, education, and occupation) among 489 childless Singaporeans aged 50 and above from a 2022 nationwide survey. Additionally, we utilized multinomial logistic regressions to examine the sociodemographic correlates of pathway profiles and Shannon's entropy index to assess the heterogeneity in pathways to childlessness among successive cohorts. Results revealed five distinct profiles of pathways to childlessness: the Never-Married Semi-Professionals, the Low-Flex Blue-Collars, the Highly Educated Professionals, the Ever-Married Semi-Professionals, and the Flexible Blue-Collars. These pathway profiles were significantly associated with sociodemographic characteristics such as gender and family background. Women's pathways to childlessness were more standardized and heavily influenced by partnership characteristics, compared to those of men. The childless from privileged family background were less likely to follow pathways characterized by disadvantageous education and occupational status. There were also rising trends of voluntary childlessness among married childless individuals and increasing heterogeneity in pathways to childlessness across successive birth cohorts. In sum, our findings are consistent with some of the predictions of the Second Demographic Transition theory, suggesting that Singapore may be experiencing a demographic transition characterized by rising childlessness, decoupling of marriage and childbearing, and de-standardization of the life course.

Anthropometric Measures Among Children and Teens With Classic 46,XX Congenital Adrenal Hyperplasia in Relation to Improvements in Diagnosis and Care

ObjectivesTo examine anthropometric changes of patients with classic 46,XX congenital adrenal hyperplasia (CAH) and matched referents; and 2) To investigate the impact of improvements in diagnosis and care on growth patterns in these patients by comparing changes in anthropometric parameters before and after CAH consensus guidelines. MethodsThis was a retrospective cohort study nested within 3 large integrated health-systems. Seventy-six patients with classic 46XX CAH and 1102 matched referents <21 years of age were identified. Anthropometric measurements including age-specific percentiles for height, weight, and body mass index were examined and compared between groups using linear mixed-effect models. Anthropometric trajectories were explored using latent class analyses. ResultsCAH patients had lower height percentiles than referents at all time points. Differences ranged from 10.7% to 28.4%. After age 5, differences in height were only significant among study participants born before the publication of CAH consensus guidelines. Latent class analyses of height detected a “gradual growth increase” pattern in 28% of CAH cases and only 4% of referents, and a “growth stunting” pattern was observed in 13% of CAH cases and 6% of referents. Height percentile measures did not differ in CAH patients with or without evidence of hormonal interventions (growth hormone and/or puberty blockers) used to increase adult height. ConclusionsThere is substantial heterogeneity in growth trajectories of CAH patients. Although stunting may affect CAH patients, advances in diagnosis and care improved anthropometric outcomes in this population. Understanding the disease- and therapy-related mechanisms that explain the different growth patterns requires additional research.

Heterogeneity in trajectories of traumatic distress at the start of the COVID-19 pandemic.

The COVID-19 outbreak has led to an increase in posttraumatic stress symptoms (PTSSs; Prout et al., 2020) for some individuals, whereas others appeared to be more resilient. It remains relatively unclear what characterizes these potentially different response trajectories ( Chen & Bonanno, 2020). This study sought to (a) assess individuals' PTSS levels at the start of the pandemic and at two subsequent timepoints 3 and 6 months later, (b) identify different trajectories of PTSSs over time, and (c) describe which individual characteristics influenced the likelihood of each of these different trajectories to occur. A community sample (n = 317) responded to an online survey during the first weeks of the pandemic, 3 and 6 months later. Among those who reported acute levels of PTSSs, latent class growth analyses identified three different resilience trajectories-resilient (low baseline PTSSs and a slight decrease over time), chronic (severe PTSSs at baseline and no change over time), and recovered (severe PTSSs at baseline but a sharp improvement over time). Baseline childhood adversity, depression, anxiety, defensive functioning, and somatization predicted trajectories. Demographics (age, gender, preexisting chronic illness) and COVID-related factors (knowing someone diagnosed with or who died of COVID-19) were unrelated to trajectories. Results suggest that although high PTSS levels decreased over time on average, heterogenous change trajectories can be identified based on baseline psychological characteristics. This implies that mental health, including past and present experiences, as well as adaptational mechanisms may shape individuals' experiences with pandemic-related ongoing stress. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Latent Class Analysis Reveals, in patient profiles, COVID-19–related better prognosis by calcifediol treatment than glucocorticoids

Calcifediol and glucocorticoids have been repositioned for the treatment of COVID-19 and may reduce severity, the need for intensive care unit admission and death. Objectiveto identify class or profiles of patients hospitalized and treated with COVID-19 pneumonia using latent class clustering methods to assess the clinical and prognostic relevance of the resulting patients’ profiles. Poor prognosis was defined as death or need for ICU admission, good prognosis, the opposite. With special interest in differential responses to calcifediol. SettingReina Sofia University Hospital, Córdoba Spain. PatientsRetrospective observational cohort study of patients admitted for COVID-19. ClinicalTrials.gov public database (NCT05819918). Inclusion criteria: (i) Age ≥ 18 and ≤ 90 years, (ii) Pneumonia characterized by the presence of infiltrates on chest X-ray or CT scan, (iii) SARS-CoV-2 infection, confirmed, and (iv) CURB Scale 65 >1. DesignLatent class analysis, for obtaining homogeneous clusters, without specifying a priori the belonging group, and selecting the optimal number of clusters by minimizing information criteria. Evaluating the differences between groups for each variable by means of chi-square, Fisher's exact test and Kruskal-Wallis test. Results707 patients hospitalized from 10 March 2020 until 4 March 2022 were included. For the treatment variable, differences were found between class 3 (60 % treated with calcifediol only) and classes 1 (less than 1 % calcifediol only vs. 82 % treated with both), 2 (less than 1 % calcifediol only vs. 82 % treated with both) and 4 (1 % calcifediol only vs. 84 % treated with both). Class 3, (60 % with calcifediol), had a significantly better prognosis compared to patients treated with glucocorticoids alone (OR: 15.2, 95 % CI: [3.73–142], p<0.001) or no treatment (OR: 7.38, 95 % CI: [2.63–30.2], p<0.001). Conclusionsour real-life study shows that calcifediol treatment significantly reduces the need for ICU admission and improved prognosis in patients hospitalized for COVID-19 pneumonia, especially in the profile of patients receiving it without glucocorticoids.

A method for rapid assessment of visual ergonomics and lighting conditions (RAVEL): An in-depth development and psychometrics study.

In workplaces heavily reliant on visual tasks, various factors can significantly influence an individual's performance, necessitating the use of reliable tools to identify and mitigate these factors. This study aimed to develop a swift assessment method for visual ergonomics and lighting conditions, evaluating its validity in real-world scenarios. The questionnaire's content validity was determined by a panel of experts using the content validity ratio (CVR) and content validity index (CVI). Construct validity was assessed through exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and latent class analysis (LCA). Internal consistency was measured using Cronbach's alpha coefficient. The RAVEL index, derived from the calculated effect coefficients of items, classified total scores through receiver operator curves (ROCs). The rapid assessment method, comprising two parts with 30 items, demonstrated acceptable reliability with CVR, CVI, and Cronbach's alpha coefficient (α) at 0.75, 0.87, and 0.896, respectively. The EFA on the first part's 22 items identified three factors, confirmed by CFA. The LCA on the second part's eight items revealed that a two-class model best fit the data, with Bayesian information criterion (BIC) = 24249, 17, Akaik information criterion (AIC) = 2179.89, and an entropy R-squared of 0.83, indicating appropriate subject classification based on the model. The RAVEL score was categorized into three levels, with optimal cut points of 55 and 63. In conclusion, the study demonstrated that this method based on visual ergonomics serves as a rapid and reliable tool for assessing visual ergonomic risks of display users in the workplace.

Trajectories and influencing factors of psychological resilience among Chinese patients with maintenance hemodialysis

ObjectiveTo identify distinct trajectories of psychological resilience among Chinese patients with maintenance hemodialysis, explore influencing factors and inform the formulation of corresponding interventions. MethodsThis was a multi-center longitudinal study with a 6-month follow-up. With convenience sampling, a total of 231 patients with maintenance hemodialysis were recruited between September 2020 and July 2021. Patients’ characteristics, including sociodemographic information, social support and family resilience was collected through structured questionnaires as potential baseline influencing factors of psychological resilience trajectories. Psychological resilience was evaluated using the 25-item Chinese version of the Conner and Davidson resilience scale. Latent class growth modeling was conducted to identify homogeneous subgroups with distinct trajectories of psychological resilience. Univariable and multinomial logistic regression analysis were used to examine whether baseline influencing factors were associated with trajectories in patients with maintenance hemodialysis. ResultsFive distinct psychological resilience trajectory groups were identified: declining group (n = 20, 8.7 %), rising group (n = 17, 7.4 %), moderate-stable group (n = 128, 55.4 %), high-stable group (n = 7, 3.0 %) and low-stable group (n = 59, 25.5 %). High-stable group and moderate-stable group were combined into the well-psychological resilience group for multinomial logistic regression analysis. The multinomial logistic regression analysis showed that influencing factors associated with trajectories of psychological resilience were age, religion, monthly household income per capita, and baseline family resilience. ConclusionsThe results highlight the heterogeneity in the development of psychological resilience among Chinese patients with maintenance hemodialysis. There is a need for healthcare professionals to screen for trajectories of psychological resilience in Chinese maintenance hemodialysis patients and prepare individual mental healthcare interventions.

Classifying Latent Classes by the bicultural acceptance attitude of adolescents from multicultural families : Investigation of influential factors and differences between depression and school adjustment in group

Classifying Latent Classes by the bicultural acceptance attitude of adolescents from multicultural families : Investigation of influential factors and differences between depression and school adjustment in group

British consumer perspectives on terroir in cheese

PurposeThis paper reports on a project looking at consumer perceptions of terroir in the UK, using cheese as a stimulus for the data collection.Design/methodology/approachData collection was based on a consumer survey using a discrete choice experiment which included a number of cues to, and stories about, terroir. Analysis of preferences produced three latent classes with varying attitudes towards terroir cues for cheese. There was also an open-ended question giving rise to a qualitative analysis of respondents understanding of the work “terroir”.FindingsWhen faced with the terroir cues most used some positively to make their choices. A PDO label and stories about the production region and method and business structure all generally offered positive utility.Originality/valueTerroir is a widely used term in the marketing of (especially) wine, particularly in Europe, offering a form of authenticity and has been very important in policies to sustain the economies of otherwise declining rural areas. It has been adopted by producers in the English-speaking world but is less widely recognised, by consumers. The significance of this study is that it is the first large-scale survey of British consumer perceptions around a key tool for rural businesses – terroir – and one of the first around a non-wine product, and it explores the stories which resonate most effectively with consumers.

Consumer Preference and Willingness to Pay for Rice Attributes in China: Results of a Choice Experiment.

Understanding urban consumers' preferences for rice attributes is crucial for rice breeders, producers, and retailers to meet diverse and evolving market demands. Based on the sample data of 629 rice consumers in Shanghai, China, obtained through the choice experiment (CE) approach, this study uses the mixed logit (ML) model to analyze consumers' preferences and willingness to pay (WTP) for food safety labels, brands, nutritional quality, and taste quality. Furthermore, the latent class (LC) model examines the heterogeneity in consumer group preferences. The research findings highlight that consumers prioritize taste quality as the most crucial attribute, followed by nutritional quality, food safety labels, and brand attributes. The premium rates for superior taste quality, organic certification labels, and green certification labels exceeded 100%. Interestingly, while combining organic certification with well-known international or domestic brands does not uniformly boost consumer preferences, incorporating green certification alongside well-known international or domestic brands significantly elevates those preference levels. Factors such as the external environment, consumption habits, and personal characteristics significantly influence individuals' preferences for rice attributes. Based on these insights, the study puts forth policy recommendations for rice breeders, producers, and retailers.

The role of human errors and violations in pedestrian-related crashes: Harnessing a unique database and accounting for heterogeneity

IntroductionHuman factors are often major contributors to pedestrian crashes. However, police-reported pedestrian-involved crash data often have gaps in crash details. Overcoming this limitation, the Pedestrian and Bicycle Crash Data Tool (PBCAT) provides a more comprehensive high-quality database capturing the sequence of events. MethodsIn addition to human and roadway environmental factors, there could be unobserved factors (e.g., pedestrian conspicuity, impact speed, or riskiness by a driver) that could be either unavailable or not used in the analysis; however, these unobserved factors could have a significant influence on pedestrian injuries. This study applies finite mixture models to address unobserved heterogeneity in pedestrian injuries which is usually overlooked. As a result, the associations of one or more of the observed factors with pedestrian injuries across different latent (unobserved) classes can be different. ResultsHarnessing this unique database for North Carolina reveals that in most (95%) of the crashes (N=24,886) occurring between 2009 and 2019, pedestrians were either killed or injured. Risky behaviors by drivers and pedestrians contributed to 7.91% and 50.59% of these crashes, respectively. Recognition errors (e.g., dash or dart-out) and violations (e.g., failure to yield) by pedestrians contributed to 22.08% and 28.58% of crashes, respectively. Recognition errors and violations by drivers contributed to only 2.12% and 3.11% of crashes respectively each of which is significantly lower than those by pedestrians. Results of the ordered Probit model indicate that the chance of pedestrian fatality is significantly higher if a pedestrian makes recognition errors and violations, a driver makes performance errors, and either the pedestrian or driver is impaired. Conclusions and practical implicationsThe finite mixture model shows that pedestrians belong to two latent groups across which there is significant heterogeneity in pedestrian injuries and variations in the associations of observed factors with pedestrian injuries. The practical implications are discussed in the paper.

Boosting beach clean-up participation through community resilience hypothetical scenarios

Engaging coastal communities in beach clean-up initiatives is crucial for the sustainability of marine ecosystems and the support of the blue economy. This study aims to examine the influence of various resilience attributes on community willingness to participate in these activities. It uses choice experiment framework to test three distinct scenarios: (1) cultural recycling education, (2) social media task force, and (3) resilience debris recovery. The study surveyed 647 valid samples from metropolitan Bali, Indonesia to assess their preferences across these scenarios. Advanced econometric models, specifically the Random Parameter Logit (RPL) and Latent Class Model (LCM), were used to analyze the data. The results indicate that integrating cultural and digital engagement strategies can significantly enhance community participation in beach clean-ups, providing a model that can be applied in various coastal regions. Each scenario improves community engagement by aligning beach clean-up efforts with broader economic and cultural dynamics.

Distinct impulsivity profiles in subtypes of violence among community-dwelling patients with severe mental disorders: a longitudinal study

BackgroundAlthough only a few patients with severe mental disorders (SMD) can commit violent behaviour in the community, violent behaviour aggravates the stigma towards patients with SMD. Understanding the subtypes of violent behaviour may be beneficial for preventing violent behaviour among patients with SMD, but it has rarely been studied.MethodsThis longitudinal study investigated 1914 patients with SMD in the community at baseline, and the follow-up period ranged from February 2021 to August 2021. The Barratt Impulsiveness Scale Version-11, the Buss-Perry Aggression Questionnaire, the Impulsive/Premeditated Aggression Scale, the Personality Diagnostic Questionnaire and the MacArthur Community Violence Instrument were used at baseline. The Modified Overt Aggression Scale was used to assess the occurrence of violent behaviour (outcome) during the follow-up period. Cox regression models were used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). Latent class analysis was used to characterise the subtypes of patients with SMD who engaged in violent behaviour at follow-up.ResultsWe found that 7.2% of patients with SMD presented violent behaviour within six months in the community. Younger age (OR = 0.98, 95% CI = 0.96-1.00, p = 0.016) and no economic source (OR = 1.60, 95% CI = 1.10–2.33, p = 0.014) were risk factors for violent behaviour. Patients with SMD who engaged in violent behaviour could be classified into three subtypes: one class characterised by a history of violence and impulsivity, another class characterised by high levels of aggression and motor impulsivity, and the last class characterised by median cognitive impulsivity.ConclusionsSocio-demographic factors were risk factors for violent behaviour among patients with SMD, which could eliminate the discrimination toward this group. Impulsivity played a vital role in identifying the three subtypes of patients with SMD who engaged in violent behaviour. These findings may be helpful for the development of a personalised violence risk management plan for patients with SMD who commit violent behaviour in the community.

Types and Predictors of Acculturative Stress Among Multicultural Adolescents in Middle School

Objectives: This study examines how acculturative stress in multicultural adolescents changes during their middle school years and categorizes groups with similar patterns of change. Additionally, the study explores predictive variables influencing these distinct acculturative stress trajectories and verifies how depression and life satisfaction vary according to different patterns of change.Methods: Leveraging data from the Multicultural Adolescent Panel (MAPS 1) conducted by the Korea Institute for Health and Social Affairs across the fourth to sixth waves, the researchers analyzed a cohort of 1,316 participants, including multicultural adolescents and their parents. Logistic regression analysis and ANOVA were employed to investigate potential disparities in growth mixture modeling and acculturative stress latent classes based on predictive factors.Results: Three latent groups of multicultural adolescents’ acculturative stress were identified: low-retention group, persistent increasing group, persistent decrease group. The logistic regression analysis revealed that gender, bicultural acceptance attitude, Korean-language proficiency, foreign parent’s native-language proficiency, parental acculturative stress, and peer support were significantly associated with latent groups. Additionally, significant differences in depression and life satisfaction during the third grade of middle school were observed according to the types of acculturative stress changes.Conclusion: Our study results indicate the need for various support programs aimed at promoting the psychosocial adaptation of multicultural adolescents. These programs should take into account the characteristics and individual differences in acculturative stress and should be implemented at the family level to facilitate social adaptation.

Eight types of video game experience

The study of game experience is a well-established area within game research, supported by numerous models. These models, while valuable, often focus on analyzing game experiences within specific contexts rather than facilitating comparative analyses. Addressing this research gap, our study empirically identifies prevalent game experience types that are common across various games. By analyzing 5,372 game experience descriptions provided by 1,193 survey respondents, this research employs a survey design inspired by the flow of qualitative interviews, facilitating a comprehensive understanding of the diverse factors shaping these experiences. Through latent class analysis, we delineate eight distinct game experience types: Compelling Challenge, Immersive Exploring, Creative Caring, Energetic Rushing, Competitive Shooting, Cheerful Bouncing, Strategic Management, and Daily Dwelling. Each type is analyzed in terms of both the variables from the latent class analysis and additional survey variables, enhancing our understanding of their unique and comparative characteristics. This approach sheds light on the multifaceted nature of game experiences and broadens our insights into player engagement across different game genres, offering practical implications for game design, marketing, and future research.

가정 내 아동학대 행위자 특성에 따른 유형분류: 잠재계층분석(Latent Class Analysis)을 중심으로

The purpose of this study is to identify the type of group classification through latent class analysis for domestic child abuse and to examine the characteristics of each group and various psychosocial factors. As a result of the analysis, domestic child abuser was classified into three sub-types: “personality problems and recidivism”, “improper parenting attitude”, and “complex causes and drinking”. Next, chi-square test was conducted to confirm the characteristics of the classified groups. The “personality problems and recidivism” had high rates of characteristic deficit, and recidivism, and the usual marital relationship was not good. In the “improper parenting attitude”, the motive of the crime was improper parenting attitude and skill, and the type to which the most abusers belonged. The “complex causes and drinking” was were found to be the most at-risk group, with accomplices, likely recidivism, and the possibility that the abuser experienced abuse. In this study, it is meaningful that groups were classified, including the characteristics of child abuser in the family and the context of child abuse crimes recognized by criminal justice agencies, and intervention measures were suggested accordingly.