Latent Groups Research Articles

Analysis on Validity and Academic Competency of Mock Test for Korean Medicine National Licensing Examination Using Item Response Theory

The national licensing examination is used to evaluate the medical competency at the time of graduation, however no study has been performed on the validity of traditional Korean medicine license examination yet. The purpose of this study was to develop learning analytics using item response theory (IRT) to examine the validity and academic competency of the mock test of the national licensing exam. Classical test theory and IRT were used to evaluate the validity of test items, and IRT was used for test validity and competency analysis. The correlation between competency score of 12 subjects was analyzed using Pearson’s correlation. The distribution of students’ latent competencies was examined by gender and administrative group using a Kernel density map, Latent Profile Analysis, and χ<sup>2</sup>. The guessing parameter of 340 items was relatively high, and the information level of 12 subjects were relatively low. Significant correlations (r = 0.49–0.83, <i>p</i> < 0.05) were observed between the competency scores of total and 12 subjects. Two (high and low) latent academic competency groups were identified based on the competency score of 12 subjects. The low academic competency group requiring intensive management has a significantly higher frequency of male students with the experience of academic fail in the seven-year course. This study presented the quantitative learning analytics for the national licensing exam of traditional Korean medicine. The multifaceted item and test validities of the mock license test were provided, and an evidence-based approach to competency-based student management and national licensing exam of traditional Korean medicine was suggested.

Relative importance of multimodal risk factors to discriminate memory trajectories: Similarities and differences across ethnoracial groups in cognitively normal older adults

AbstractBackgroundInequalities in dementia incidence and heterogeneities observed on memory decline are present across ethnic/racial groups. Research suggests that inequities in risk/protective factors contribute towards these differences. We examine risk factors across multiple domains to identify those that best discriminate differences in memory trajectories across ethnoracial groups.MethodWe used an ethnoracially diverse longitudinal cohort of cognitively normal older adults (n = 299; mean age = 73.47 (6.90) years; 63.9% female) from the University of California, Davis‐Alzheimer’s Disease Research Center. First, we applied latent class growth analysis to objectively classify memory trajectories into distinct latent groups across a maximum of 10 follow‐ups. Second, we used random forest analyses (RFA) to examine relative importance of 22 risk/protective factors from seven domains (demographic, genetic, brain morphometry, plasma and functional biomarkers, psychological and lifestyle factors) to discriminate low/high memory performers as stratified by three ethnoracial groups (African Americans [AA; n = 111]; Hispanics [n = 108], Whites [n = 66]).ResultFirst, we observed that four latent classes (low, intermediate, high, very high) best represented memory trajectories (Figure 1). Second, for our RFA analyses, we collapsed low and intermediate groups to a low group (n = 136; 40.4% AA, 25.6% Hispanics, 28.8% Whites), and high and very high to a high performing group (n = 148; 34.6% AA, 50% Hispanics, 15.4% Whites). High memory class was predicted (Figure 2) in AA by lower smoking years, lower Functional Assessment Questionnaire (FAQ), younger age, higher education, lower neurofilament light (NfL), Apolipoprotein E non‐carriers, low neuropsychiatric inventory (NPI) severity, men, and higher hippocampal volume (AUC = 0.73); in Hispanics with men, lower FAQ, lower Geriatric Depression Scale (GDS), smaller third ventricle, larger hippocampal volume, lower NPI severity, smaller lateral ventricle, and lower NfL (AUC = 0.86); and in Whites, with lower FAQ, higher education, higher alcohol use frequency, lower NfL, lower GDS, smaller lateral ventricles, and low white matter hyperintensities (AUC = 0.82).ConclusionWe observed similarities and differences in predictors to discriminate low versus high memory performers in three ethnoracial groups. Identifying relative importance of risk factors will promote the integration of multimodal risk factors across ethnoracial groups to develop novel and complex risk profiles leading to early detection and identification of asymptomatic or preclinical older adults.

잠재프로파일 분석을 통한 교수역량 유형 분류 및 영향요인 탐색

Purpose: The purpose of this study was to classify college faculty members’ group types for the levelof teaching competency using latent profile analysis and to confirm the influencing factors of individualcharacteristics on latent profile group types. Methods: The data were collected from 482 faculty members at A University using an online survey,and 328 pieces of data were collected. After removing outliers through Z-score, 302 were used for latentprofile analysis. Results: The results of this study are as follows: (1) as a result of the latent profile analysis, four groupswere created according to the level of teaching competency, and we named the groups ‘adaptive’, ‘growth’,‘competent’, and ‘proficient’ referring to the expert development level, (2) individual characteristics (gender,major, career) had a statistically non-significant effect on teaching competency based on the latent profile,(3) faculty members who participated in sustaining teaching support programs were in a higher probabilityaffiliated proficient group rather than an adaptive group, and faculty members who applied programcontent in their classes showed a higher probability of belonging to the proficient group rather thanan adaptive, growth, or competent group. Conclusion: Based on these results, this study suggested a significant implication and the necessityof developing teaching support programs according to group types and constructing a system forcontinuous support. Also, this study suggested that colleges should encourage faculty members toapply the content of teaching support programs in their classes.

Exploring latent profiles of disordered eating using an indicator of dietary restriction in an undergraduate sample of men and women.

Latent class or latent profile analysis (LPA) studies in patients with eating disorders consistently identify a low-weight, restrictive eating subgroup that does not endorse weight/shape concerns. To date, similar studies in samples unselected for disordered eating symptoms have not identified a high restriction-low weight/shape concerns group, which may be due to a lack of inclusion of measures of dietary restriction. We conducted an LPA using data from 1623 college students (54% female) recruited across three different studies. The Eating Pathology Symptoms Inventory Body Dissatisfaction, Cognitive Restraint, Restricting, and Binge Eating subscales were used as indicators, and body mass index, gender, and dataset were covaried. Purging, excessive exercise, emotion dysregulation, and harmful alcohol use were compared across resulting clusters. Fit indices supported a 10-class solution, including five disordered eating groups (largest to smallest): "Elevated General Disordered Eating", "Body Dissatisfied Binge Eating," "Most Severe General Disordered Eating," "Non-Body Dissatisfied Binge Eating," and "Non-Body Dissatisfied Restriction." The "Non-Body Dissatisfied Restriction" group scored as low on other measures of traditional eating pathology and harmful alcohol use as non-disordered eating groups but scored as high on a measure of emotion dysregulation as other disordered eating groups. This study is the first to identify a latent restrictive eating group that does not endorse traditional disordered eating cognitions in an unselected sample of undergraduate students. Results underscore the importance of using measures of disordered eating behaviors without implied motivation to capture overlooked problematic eating patterns in the population that are distinct from our "traditional" understanding of disordered eating. We identified a group of individuals with high levels of restrictive eating but low body dissatisfaction and intent to diet in an unselected adult sample of men and women. Results underscore the need to investigate restrictive eating outside of the traditional lens of body shape concerns. Findings also suggest that individuals with nontraditional eating difficulties may struggle with emotion dysregulation, putting them at risk of poor psychological and relational outcomes.

Multimodal Biomarkers That Predict the Presence of Gleason Pattern 4: Potential Impact for Active Surveillance.

Latent grade group ≥2 prostate cancer can impact the performance of active surveillance protocols. To date, molecular biomarkers for active surveillance have relied solely on RNA or protein. We trained and independently validated multimodal (mRNA abundance, DNA methylation, and/or DNA copy number) biomarkers that more accurately separate grade group 1 from grade group ≥2 cancers. Low- and intermediate-risk prostate cancer patients were assigned to training (n=333) and validation (n=202) cohorts. We profiled the abundance of 342 mRNAs, 100 DNA copy number alteration loci, and 14 hypermethylation sites at 2 locations per tumor. Using the training cohort with cross-validation, we evaluated methods for training classifiers of pathological grade group ≥2 in centrally reviewed radical prostatectomies. We trained 2 distinct classifiers, PRONTO-e and PRONTO-m, and validated them in an independent radical prostatectomy cohort. PRONTO-e comprises 353 mRNA and copy number alteration features. PRONTO-m includes 94 clinical, mRNAs, copy number alterations, and methylation features at 14 and 12 loci, respectively. In independent validation, PRONTO-e and PRONTO-m predicted grade group ≥2 with respective true-positive rates of 0.81 and 0.76, and false-positive rates of 0.43 and 0.26. Both classifiers were resistant to sampling error and identified more upgrading cases than a well-validated presurgical risk calculator, CAPRA (Cancer of the Prostate Risk Assessment; P < .001). Two grade group classifiers with superior accuracy were developed by incorporating RNA and DNA features and validated in an independent cohort. Upon further validation in biopsy samples, classifiers with these performance characteristics could refine selection of men for active surveillance, extending their treatment-free survival and intervals between surveillance.

Resolving the masculinity dilemma: Identifying subtypes of male meat consumers with latent profile analysis

Reducing meat consumption is necessary to meet Paris Agreement climate change targets. Efforts to reduce meat consumption should target male consumers, who are the biggest meat-eaters worldwide. However, men are often unwilling to reduce their meat intake, due partly to pressures to conform to dominant masculine ideological expectations that “real” men should eat meat (i.e., the masculinity dilemma). To build theoretical insights and more accurately inform interventions, the current study sought to identify latent subgroups of male consumers based on 20 psychosocial indicators related to meat consumption. A latent profile analysis of 575 Australian and English participants who self-identified as male yielded three distinct latent subgroups that differed significantly in indicator variables, self-reported meat consumption, and willingness to reduce their meat intake: “Resistant” consumers ate the most meat and were very unwilling to reduce, “Ambivalent” consumers ate moderate-to-high amounts of meat and were slightly unwilling to reduce, and “Meat-averse” consumers ate minimal quantities of meat and were very willing to reduce. Results suggest that previous meat-reduction intervention attempts may have been impeded by failing to target latent male consumer groups. Efforts to reduce men’s meat consumption will require further focus on within- rather than between-gender differences in male populations.

수용자의 자녀 교류 유형과 설명 요인

The purpose of this study is to analyze the types of exchanges between prisoners and their children and the explanatory factors. For this purpose, latent group analysis and general structural equation model were used. As a result of the analysis, first, 64.9% of the prisoners were interacting with their children, and correspondence was used the most. Second, the type of exchange of prisoners can be divided into a passive group and an active group. Overall, the active group used a variety of child exchange methods compared to the passive group. Third, the higher the age, the better the relationship with the child caregiver, and the more female than male, the higher the possibility of belonging to the active group than the passive group in the case of recognizing the fact of acceptance. Based on these research results, measures to expand exchanges between children of inmates and their implications were proposed.

온라인 학습 기반 LDA 모형을 이용한 이미지 주석 군집화에 대한 연구

LDA model is one of the latent topic models used to investigate latent topics by analyzing documents and words in corpus, and has been widely used in various fields. However, LDA model proposed by Blei, Ng, Jordan (2003) is based on batch learning, which estimates parameters using whole data at once, which has limitations such as large memory requirement and computation time for large data. To resolve this problems, an online learning-based LDA model has been proposed. This method has been known to consume less memory and have a faster analysis speed than batch learning. In this paper, we investigate the topic of each image by applying an online learning-based LDA model to corpus composed of annotations for more than 10,000 images provided by Visual Genome. For analysis, preprocessing was performed on image annotations. Various combinations of the number of latent topic and several hyper-parameters were set, and measures of perplexity and coherence are compared to find optimal model. As a result of comparison, a model with 10 latent groups was selected, and topics such as ‘human’, ‘animal’, ‘downtown’, ‘sea’, ‘bathroom’, and ‘kitchen’ were derived through the top words of each group.

코로나19 이전과 비교한 한부모의 주관적 행복감, 경제적 여건의 변화에 기초한 잠재집단 분류 및 영향 요인 탐색

Objectives The purpose of this study is to identify the latent groups according to changes in subjective happiness and economic conditions of single parents compared to before COVID-19 and to explore variables affecting the identified potential groups. Furthermore, the study confirmed how groups of adolescent has changed compared to before COVID-19.&#x0D; Methods Using the Living Status of Korean Single-Parent Families Survey in 2021, this study analyzed 2,420 single parents through Latent Profile Analysis. In specific, R3STEP were used to determine whether single parent's gender, age, education, type of government support, and duration were affected by the potential group classification, and BCH were used to determine whether there was a difference in children's changes compared to before COVID-19.&#x0D; Results First, the latent groups based on subjective happiness and economic conditions compared to before COVID-19 perceived by single parents were identified as seven groups. Second, educational background of single parents, the type of government support, the period of becoming a single parent, and their age had an effect on the classification of latent groups. Third, it was confirmed that the degree of positive change of children was different for each group.&#x0D; Conclusions This study suggests that children from single parents family can have more positive changes in school life when subjective happiness and economic conditions of their single parents improve compared to before COVID-19.

Associations of Renal Function Trajectories and Long-Term Cardiovascular Risks Among a Population Without Chronic Kidney Disease.

Background The longitudinal trajectories of renal function have been associated with cardiovascular events in patients with chronic kidney disease (CKD). However, the change pattern of renal function in those without CKD has not yet been reported. We aim to explore patterns of renal function change in a non-CKD population and its associated risks with cardiovascular outcomes. Methods and Results The present study analyzed data from 4 prospective cohorts and was restricted to participants without baseline CKD. The primary outcome was major adverse cardiovascular events, defined as a composite of myocardial infarction, chronic heart failure, stroke, and cardiovascular deaths. We used a group-based trajectory model to identify latent groups and analyzed the associated risk with Cox regression models. The complete dates of this study were June 1, 2020, through January 1, 2021. The final sample comprised 23 760 participants (mean age, 58.63 [9.12] years, 10 618 men, and 17 799 White participants). During 20.56 years follow-up, 8328 (35.05%) first major adverse cardiovascular events happened. Four trajectories in estimated glomerular renal function and 3 patterns of CKD progression were identified. Compared with subjects assigned to class I trajectory (high to mildly decreased group), the adjusted hazard ratios of major adverse cardiovascular events for class II (normal to mildly decreased group), class III (normal to moderately decreased group), and class IV (mildly to severely decreased group) were 1.11 (95% CI, 1.01-1.23), 1.27 (95% CI, 1.14-1.40), and 1.56 (95% CI, 1.38-1.77), respectively. Likewise, participants assigned to the slow and rapid progression groups had elevated HRs for major adverse cardiovascular events (1.75 [95% CI, 1.39-2.21] and 2.19 [95% CI, 1.68-2.86], respectively) when compared with the stable group. Findings were generally consistent in stratification analysis, but significant interaction effects by age and smoking status were detected. Conclusions In this study, we identified unique trajectory groups for renal function. These findings may signal an underlying high-risk population and inspire future studies on individualized risk management.

Scrutiny of Sudan's Consumption Share to GDP

This paper examines the contribution of the consumption share to GDP from 1970 to 2019 to assess how income groups contributed to the share's stability, as well as the factors influencing its path and policy implications. Because the dependent variable is expressed in percentages and is not normally distributed, the Beta regression finite mixed model is the best tool for detecting latent income groups. We used Robust standard error to ensure the stability of the consumption share (i.e. the average propensity to consume APC). The analytical tool predicts the discovery of three previously unknown income groups. The following three latent groups were identified by the group means following the analysis: 0.82, 0.87, and 0.90 represent low-, medium-, and high-income groups, respectively, with probabilities of 0.27, 0.47, and 0.26 for their share contribution. The explanatory variables include employment, human capital (hc), total factor productivity at constant national prices (rtfpna), and the share of labor compensation in GDP. Each estimated parameter has a high significance and the expected sign. The policy implication is that the consumption share should be reduced in favor of the saving share by increasing employment opportunities and total factor productivity because it is relatively high. Furthermore, fighting inflation increases consumption while increasing spending on health care, education, and training stimulates economic growth by increasing the percentage saving ratio but at different levels.

부모와 자녀가 지각한 양육 특성의 잠재집단에 따른 고등학생의 심리적, 사회적, 행동적 적응 특성 차이

Objectives The purpose of this study was to identify latent profiles of parenting characteristics which were perceived by 11th graders and their parents, and to verify differences in the psychological, social, and behavioral adjustment of children according to the classified types in their 12th grade. Methods 4,553 longitudinal data of 8th (2019) and 9th (2020), Gyeonggi Education Panel Study(GEPS) were used to identify the latent group. In specific, BCH auxiliary variable were used to verify differences among identified latent groups. Results First, the study found six latent classes depend on each of children’s perception and parents’ perception of parenting characteristics. Second, both classes which were identified with low perception of children and average perception of parents and with average perception of children and above average perception of parents reported lower psychological adjustment and growth mildest, but higher delinquency behaviors than other four latent classes. However, classes which were identified with highest perception of both children and parents and with highest perception of children and above high perception of parents reported higher self-esteem, academic self-efficacy, and school adjustment as well as lower academic stress than other four latent classes. Conclusions This study suggests that there is a difference in perception of parenting characteristics between parents and their children, and when parents perceive their parenting characteristics more positively than adolescents, it can negatively affect the social, psychological, and behavioral adaptation characteristics of adolescents.

Tungsten Oxo and Tungsten Imido Alkylidene N-Heterocyclic Carbene Complexes for the Visible-Light-Induced Ring-Opening Metathesis Polymerization of Dicyclopentadiene

A system for the visible-light-controlled ring-opening metathesis polymerization (ROMP) of endo,endo-dicyclopentadiene (DCPD) was developed by combining thermally latent group 6 olefin metathesis initiators, whose vacant binding site is occupied by an N-heterocyclic carbene (NHC), with a photoredox catalyst. Similar ruthenium-based systems have previously been utilized in numerous photolithographic applications. Here, we were able to adapt the approach to group 6 metathesis catalysts for the first time. Extensive screening of 31 different olefin metathesis initiators and five different photoredox catalysts revealed that both tungsten oxo and tungsten imido alkylidene NHC complexes together with 2,4,6-triphenylpyrylium tetrafluoroborate (TPPT) as a photocatalyst are most suitable for the desired application. We propose that, upon irradiation of a mixture of the corresponding olefin metathesis catalyst and TPPT with visible light (440 nm), the excited pyrylium compound oxidizes the NHC ligand and a metathesis-active Schrock-type catalyst is formed. This system can be applied to two-dimensional (2D) photolithography in the ROMP of DCPD. Photomasks were employed to produce cross-linked polymers with great spatial resolution within minutes by applying visible light as the sole stimulus giving access to polymers those compared to many other systems do not require thermal or UV post-curing. Notably, mixtures of the two catalysts and DCPD were latent for several days, and catalyst loadings as low as 100 ppm were sufficient for the desired applications proving the robustness and high activity of the developed system.

Cultural Consensus Analysis of Stakeholder Beliefs toward Coastal Restoration in Southeast Louisiana

Coastal land loss is a singular threat to the people, economies, and biodiversity of Louisiana. Though opinion polls indicate broad support for restoration efforts, aspects of current plans remain contentious for some stakeholders. We used cultural consensuses analysis (CCA) to go beneath the surface of restoration policy debates and identify shared beliefs about coastal land loss and restoration efforts among select occupational stakeholder groups in Louisiana. Three latent consensus groups, spanning stakeholder groupings, were identified. Data indicate broad consensus on core beliefs related to the peril of land loss and the urgency of action. And though staunch disagreement exists, there is some evidence that differences are not wholly intractable. These findings highlight a need to better understand the nature of beliefs and the frames that motivate those beliefs in policy debates and offer CCA as avenue for doing so.

Positive correlation between latent Epstein-Barr virus infection and severity of illness in inflammatory bowel disease patients.

Emerging studies indicate the critical involvement of microorganisms, such as Epstein-Barr virus (EBV), in the pathogenesis of inflammatory bowel disease (IBD). Immunosuppressive therapies for IBD can reactivate latent EBV, complicating the clinical course of IBD. Moreover, the clinical significance of EBV expression in B lymphocytes derived from IBD patients' intestinal tissues has not been explored in detail. To explore the clinical significance of latent EBV infection in IBD patients. Latent EBV infection was determined by double staining for EBV encoded RNA and CD20 in colon specimens of 43 IBD patients who underwent bowel resection. Based on the staining results, the patients were divided into two groups, according to their latent EBV infection states - negative (n = 33) and positive (n = 10). Illness severity of IBD were assigned according to Crohn's disease activity index (ulcerative colitis) and Mayo staging system (Crohn's disease). The clinic-pathological data were analyzed between the two different latent EBV groups and also between the mild-to-moderate and severe disease groups. Systolic pressure (P = 0.005), variety of disease (P = 0.005), the severity of illness (P = 0.002), and pre-op corticosteroids (P = 0.025) were significantly different between the EBV-negative and EBV-positive groups. Systolic pressure (P = 0.001), variety of disease (P = 0.000), pre-op corticosteroids (P = 0.011) and EBV infection (P = 0.003) were significantly different between the mild-to-moderate and severe disease groups. IBD patients with latent EBV infection may manifest more severe illnesses. It is suggested that the role of EBV in IBD development should be further investigated, latent EBV infection in patients with serious IBD should be closely monitored, and therapeutic course should be optimized.

Associations Between Pornography Consumption Patterns, Pornography Consumption Motives, and Social Wellbeing among U.S. College Students: A Latent Profile Analysis with a Primarily Female Sample

This study identified profiles of pornography motivations and outcomes and assessed differences between profiles on three measures of social well-being: social support, fear of intimacy, and loneliness. Latent profile analysis and group comparisons were conducted using cross-sectional data from college students (N = 389). Results indicated four profiles: low motivation/average distress, porn for enjoyment, high motivation/average guilt, low motivation/high distress. Those in the high motivation/average guilt profile reported more social well-being difficulties relative to the other profiles and non-pornography consumers. Results suggest that individuals who report varying pornography use motivations and negative outcomes may report difficulties with social well-being, with implications for intimate relationships.

Identifying latent group structures in spatial dynamic panels

This paper considers the identification of latent group structures in spatial dynamic panels. We follow Lee and Yu (2010) and consider a rich spatial dynamic panel data (SDPD) model with two-way fixed effects. In addition, we also allow for latent panel structures where individuals can be classified into a few groups such that individuals within the same group share the common slope parameters and do not otherwise. Both the number of groups and the individuals’ group membership are unknown. To identify the latent group structures, we first adopt the GMM to obtain the preliminary unconstrained estimates of the slope coefficients. Then we apply the sequential binary segmentation algorithm (SBSA) of Wang and Su (2021) to these estimates and obtain the clusters. A BIC-type information criterion is proposed to choose the number of latent groups consistently. The asymptotic analysis shows that this method can identify the true group structure consistently, and the post-classification estimators enjoy the oracle property. Monte Carlo simulations demonstrate that our method has good finite sample performance. Finally, we apply our approach to the US housing market and identify two latent Metropolitan Statistical Areas groups.

Novel Clustering Methods Identified Three Caries Status-Related Clusters Based on Oral Microbiome in Thai Mother–Child Dyads

Early childhood caries (ECC) is a disease that globally affects pre-school children. It is important to identify both protective and risk factors associated with this disease. This paper examined a set of saliva samples of Thai mother-child dyads and aimed to analyze how the maternal factors and oral microbiome of the dyads influence the development of ECC. However, heterogeneous latent subpopulations may exist that have different characteristics in terms of caries development. Therefore, we introduce a novel method to cluster the correlated outcomes of dependent observations while selecting influential independent variables to unearth latent groupings within this dataset and reveal their association in each group. This paper describes the discovery of three heterogeneous clusters in the dataset, each with its own unique mother-child outcome trend, as well as identifying several microbial factors that contribute to ECC. Significantly, the three identified clusters represent three typical clinical conditions in which mother-child dyads have typical (cluster 1), high-low (cluster 2), and low-high caries experiences (cluster 3) compared to the overall trend of mother-child caries status. Intriguingly, the variables identified as the driving attributes of each cluster, including specific taxa, have the potential to be used in the future as caries preventive measures.

The presence, nature and network characteristics of behavioural phenotypes in temporal lobe epilepsy.

The relationship between temporal lobe epilepsy and psychopathology has had a long and contentious history with diverse views regarding the presence, nature and severity of emotional-behavioural problems in this patient population. To address these controversies, we take a new person-centred approach through the application of unsupervised machine learning techniques to identify underlying latent groups or behavioural phenotypes. Addressed are the distinct psychopathological profiles, their linked frequency, patterns and severity and the disruptions in morphological and network properties that underlie the identified latent groups. A total of 114 patients and 83 controls from the Epilepsy Connectome Project were administered the Achenbach System of Empirically Based Assessment inventory from which six Diagnostic and Statistical Manual of Mental Disorders-oriented scales were analysed by unsupervised machine learning analytics to identify latent patient groups. Identified clusters were contrasted to controls as well as to each other in order to characterize their association with sociodemographic, clinical epilepsy and morphological and functional imaging network features. The concurrent validity of the behavioural phenotypes was examined through other measures of behaviour and quality of life. Patients overall exhibited significantly higher (abnormal) scores compared with controls. However, cluster analysis identified three latent groups: (i) unaffected, with no scale elevations compared with controls (Cluster 1, 37%); (ii) mild symptomatology characterized by significant elevations across several Diagnostic and Statistical Manual of Mental Disorders-oriented scales compared with controls (Cluster 2, 42%); and (iii) severe symptomatology with significant elevations across all scales compared with controls and the other temporal lobe epilepsy behaviour phenotype groups (Cluster 3, 21%). Concurrent validity of the behavioural phenotype grouping was demonstrated through identical stepwise links to abnormalities on independent measures including the National Institutes of Health Toolbox Emotion Battery and quality of life metrics. There were significant associations between cluster membership and sociodemographic (handedness and education), cognition (processing speed), clinical epilepsy (presence and lifetime number of tonic-clonic seizures) and neuroimaging characteristics (cortical volume and thickness and global graph theory metrics of morphology and resting-state functional MRI). Increasingly dispersed volumetric abnormalities and widespread disruptions in underlying network properties were associated with the most abnormal behavioural phenotype. Psychopathology in these patients is characterized by a series of discrete latent groups that harbour accompanying sociodemographic, clinical and neuroimaging correlates. The underlying neurobiological patterns suggest that the degree of psychopathology is linked to increasingly dispersed abnormal brain networks. Similar to cognition, machine learning approaches support a novel developing taxonomy of the comorbidities of epilepsy.

Association between multimorbidity trajectories, healthcare utilization, and health expenditures among middle-aged and older adults: China Health and Retirement Longitudinal Study

BackgroundTo identify the latent groups of multimorbidity trajectories among middle-aged and older adults and examine their associations with healthcare utilization and health expenditures. MethodsWe included adults aged ≥45 years who participated in the China Health and Retirement Longitudinal Study from 2011 to 2015 and were without multimorbidities (<2 chronic conditions) at baseline. Multimorbidity trajectories underlying 13 chronic conditions were identified using group-based multi-trajectory modeling based on the latent dimensions. Healthcare utilization included outpatient care, inpatient care, and unmet healthcare needs. Health expenditures included healthcare costs and catastrophic health expenditures (CHE). Random-effects logistic regression, random-effects negative binomial regression, and generalized linear regression models were used to examine the association between multimorbidity trajectories, healthcare utilization, and health expenditures. ResultsOf the 5548 participants, 2407 developed multimorbidities during follow-up. Three trajectory groups were identified among those with new-onset multimorbidity according to the increasing dimensions of chronic diseases: “digestive-arthritic” (N = 1377, 57.21 %), “cardiometabolic/brain” (N = 834, 34.65 %), and “respiratory/digestive-arthritic” (N = 196, 8.14 %). All trajectory groups had a significantly increased risk of outpatient care, inpatient care, unmet healthcare needs, and higher healthcare costs than those without multimorbidities. Notably, participants in the “digestive-arthritic” trajectory group had a significantly increased risk of incurring CHE (OR = 1.70, 95%CI: 1.03–2.81). LimitationsChronic conditions were assessed using self-reported measures. ConclusionsThe growing burden of multimorbidity, especially multimorbidities of digestive and arthritic diseases, was associated with a significantly increased risk of healthcare utilization and health expenditures. The findings may help in planning future healthcare and managing multimorbidity more effectively.