Classifying and characterizing the development of self-reported overall quality of life among the Chinese elderly: a twelve-year longitudinal study.

BACKGROUND: To promote healthy aging, the information about the development of quality of life (QoL) is of great importance. However, the explorations of the heterogeneity in the change of QoL under the Chinese context were limited. This study aimed to identify potential different development patterns of QoL and the influential factors using a longitudinal, nationally representative sample of the Chinese elderly. METHODS: We adopted a five-wave longitudinal dataset from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), and a total of 1645 elderly were obtained. The sample had a mean age of 72.7 years (SD = 6.64) and was 47.2% male. Overall QoL was measured through self-report during the longitudinal process. We utilized the conditional growth mixture model (GMM) with time-invariant covariates (TICs) to explore various development patterns and associated factors. RESULTS: Three distinct trajectories of self-reported overall QoL were identified: the High-level Steady Group (17.08%), the Mid-level Steady Group (63.10%), and the Low-level Growth Group (19.82%). Results also indicated that several factors predicted distinct trajectories of self-reported overall QoL. Those elderly who received enough financial resources, had adequate nutrition, did not exhibit any disability, engaged in leisure activities, and did less physical labor or housework at the baseline were more likely to report a higher level of overall QoL over time. CONCLUSIONS: There existed three development patterns of self-reported overall QoL in elders, and the findings provided valuable implications for the maintenance and improvement of QoL among the Chinese elderly. Future studies could examine the influence of other confounding factors.

Psychometric Properties and Factor Structures of the CERQ, DERS, and RESE Measures: A Bifactor Approach.

This study aims to simultaneously compare the psychometric properties and examine the factor structures of 3 emotion regulation (ER) strategy scales using a bifactor approach. Due to good reliability and validity, extensive use, and the same scoring method, the Cognitive Emotion Regulation Questionnaire, Difficulties in Emotion Regulation Scale, and Regulatory Emotional Self-Efficacy Scale were used to assess ER strategies in 1,036 Chinese respondents. A bifactor confirmatory factor analysis was designed to address the multidimensionality of the factor structure, and the corresponding bifactor structures were then applied in a subsequent bifactor multidimensional item response theory (MIRT) analysis. Finally, bifactor MIRT was used to compare the psychometric properties of the 3 measures. The results indicated that bifactor structures were appropriate for the 3 ER strategy measures, which performed well overall. Different measures provide the highest accuracy for specific groups and designs. Some strengths and limitations of this article are discussed.

Examining the Process of Responding to Circumplex Scales of Interpersonal Values Items: Should Ideal Point Scoring Methods Be Considered?

The Circumplex Scales of Interpersonal Values (CSIV) is a 64-item self-report measure of goals from each octant of the interpersonal circumplex. We used item response theory methods to compare whether dominance models or ideal point models best described how people respond to CSIV items. Specifically, we fit a polytomous dominance model called the generalized partial credit model and an ideal point model of similar complexity called the generalized graded unfolding model to the responses of 1,893 college students. The results of both graphical comparisons of item characteristic curves and statistical comparisons of model fit suggested that an ideal point model best describes the process of responding to CSIV items. The different models produced different rank orderings of high-scoring respondents, but overall the models did not differ in their prediction of criterion variables (agentic and communal interpersonal traits and implicit motives).

Personality Profiles and Frequent Heavy Drinking in Young Adulthood.

Few studies examining the link between personality and alcohol use have adopted a comprehensive modeling framework to take into account individuals' profiles across multiple personality traits. In this study, latent profile analysis (LPA) was applied to a national sample of young adults in the United States to identify subgroups defined by their profiles of mean scores on the Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness personality factors. Personality profiles were then used to predict heavy drinking. Five profiles were identified: Reserved, Rigid, Confident, Ordinary, and Resilient. Compared to individuals in the Ordinary profile, those with Reserved and Resilient profiles were at increased risk of frequent heavy drinking. These findings suggest which comprehensive personality profiles may place individuals at risk for problematic alcohol-related outcomes.

STRUCTURE OF THE UNIVERSITY PERSONALITY INVENTORY FOR CHINESE COLLEGE STUDENTS.

The University Personality Inventory, a mental health instrument for college students, is frequently used for screening in China. However, its unidimensionality has been questioned. This study examined its dimensions to provide more information about the specific mental problems for students at risk. Four subsamples were randomly created from a sample (N = 6,110; M age = 19.1 yr.) of students at a university in China. Principal component analysis with Promax rotation was applied on the first two subsamples to explore dimension of the inventory. Confirmatory factor analysis was conducted on the third subsample to verify the exploratory dimensions. Finally, the identified factors were compared to the Symptom Checklist-90 (SCL-90) to support validity, and sex differences were examined, based on the fourth subsample. Five factors were identified: Physical Symptoms, Cognitive Symptoms, Emotional Vulnerability, Social Avoidance, and Interpersonal Sensitivity, accounting for 60.3% of the variance. All the five factors were significantly correlated with the SCL-90. Women scored significantly higher than men on Cognitive Symptoms and Interpersonal Sensitivity.

The Mediating Roles of Future Work Self and Hope on the Association Between Perceived Social Support and Depressive Symptoms Among Chinese Vocational School Students: A Cross-Sectional Study.

Purpose: Depressive symptoms are serious mental health problems, which are harmful for adolescents' physical and psychological development. Limited studies have focused on depressive symptoms of vocational high school students, who are more susceptible to mental health problems than high school students. Based on the main effect model of social support and self-regulation theory, the current study aims at exploring two potential mediating roles of hope and future work self on the relationship between perceived social support and depressive symptoms among vocational high school students by a cross-sectional study. Participants and Methods: A total of 521 vocational high school students aged 14-21 (M= 16.45; SD= 0.91) participated in the survey. There were 266 males (51.1%) and 255 females (48.9%). The multidimensional scale of perceived social support, the future work self scale, the children's hope scale, and the center for epidemiologic studies depression scale were applied in the study. Results: The results revealed that: (1) perceived social support, future work self, and hope were negatively related to depressive symptoms (r = -0.25 to -0.35, p < 0.001); (2) students who perceived more social support have fewer depressive symptoms (ß = -0.22, p < 0.001); (3) perceived social support predicted a more salient future work self and then was associated with higher levels of hope, which in turn, was related to lower levels of depressive symptoms (ß = -0.02, and 95% CI = [-0.035, -0.005]). Conclusion: Perceived social support was the protective factor against vocational school students' depressive symptoms. More specifically, stronger perceived social support predicted a more salient future work self, which promoted high level of hope, and ultimately decreased vocational school students' depressive symptoms. The findings provide enlighten implications for interventions on depressive symptoms among vocational high school students.

Growth patterns of activity of daily living disability and associated factors among the Chinese elderly: A twelve-year longitudinal study.

OBJECTIVES: The acceleration of population aging has brought a lot of attention to the disability among older populations, but existing results about the development patterns of disability were mixed. The current study aimed to identify the potential different development patterns of disability and the influential factors using a large, nationally representative sample of the Chinese elderly. METHODS: We adopted a five-wave longitudinal dataset from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), and 1,654 elderly aged 65 and over were obtained. Disability was measured by the Katz index scale grading individuals on a scale of difficulty to carry out activities of daily living (ADL). We utilized the conditional growth mixture model (GMM) to identify various development patterns and associated factors. RESULTS: Compared with those without disability (n = 1,140), individuals with ADL disability (n = 514) were more likely to be old, female, or Han ethnic, eat more healthy food and suffer from chronic disease. Two groups with distinct trajectories of ADL disability were identified, including the Slightly Increasing Group and the Quickly Increasing Group. People who did less housework (OR=0.33, 95%CI: 0.12-0.90; p = 0.030), suffered from stroke (OR=5.39, 95%CI: 1.43-20.35; p = 0.013) or dementia (OR=10.29, 95%CI: 1.01-104.44; p = 0.049) were more likely to be classified into the Quickly Increasing Group. CONCLUSION: There existed two development patterns of ADL disability among the Chinese elderly. Besides, doing housework could help prevent the deterioration of disability, and suffering from stroke or dementia may accelerate the deterioration of ADL ability in later years. Implications are provided for public health interventions.

Effects of the COVID-19 Pandemic on Chinese Graduate Students' Learning Activities: A Latent Class Analysis.

To investigate the impact of the pandemic on graduate students' learning activities, a series of questionnaires were distributed to graduate students in universities across China, and 2,818 responses were collected. A latent class analysis was performed to classify the effects of the pandemic on graduate students' learning activities. Then, a multinomial logistic regression analysis and an analysis of variance analysis were carried out to explore the impact of demographic variables on the classification and their mental health status. The analysis identified four latent classes: "the overall less affected" (34.83%), "the overall more affected" (31.97%), "course activities were more affected" (19.40%), and "social activities were more affected" (13.79%). The multinomial logistic regression analysis indicated that during the pandemic, the learning activities of graduate students in all grades were affected to varying degrees, and the impacts on second-year and third-year graduate students were greater than those of first-year graduate students. The analysis of variance revealed that the scores for anxiety, depression, and social anxiety of "the overall more affected" were significantly greater than those of the other three groups, and nearly one-third of students belonged to this class, suggesting that more attention and care should be given to these students. As a result of the COVID-19 pandemic, a number of graduate students have suffered mental problems (anxiety and depression). Under the current backdrop of a new normal, schools and teachers should pay attention to graduate students' mental health, providing targeted assistance to different types of students.

Relationship between Entrepreneurship Education and Entrepreneurial Intention among College Students: A Meta-Analysis.

Meta-analysis was used to investigate the impact of entrepreneurship education on college students' entrepreneurial intention. Based on the rules of meta-analysis, 389 empirical studies were selected from more than 1000 entrepreneurship education-related documents. The current study processed and analyzed data from 36 records (including 24 journal articles, 11 master's theses, and 1 doctoral thesis) with a total sample of 29,736 students. The results suggested that: (1) entrepreneurship education is positively associated with entrepreneurial intention; (2) national context differences among students have a significant and moderating effect on the relationship between entrepreneurship education and entrepreneurial intention. As compared to other countries, Chinese college students' entrepreneurial intention is more strongly related with entrepreneurship education.

The Difference in Learning Activities of Postgraduate Students of Different Qualification Types Under the COVID-19 Pandemic: A Multi-Group Latent Class Analysis.

Introduction: There are two types of master's qualifications in China. One is the academic qualification that pays more attention to academic research, aiming to cultivate research-oriented talents; while the other is the application-oriented qualification that focuses more on practical ability, aiming to cultivate applied-oriented talents. The purpose of this study is to explore the impact of the COVID-19 on the learning activities of postgraduate students, as well as the differences in the extent to which the learning activities of postgraduate students of different qualification types are affected and their mental health status. Methods: A self-constructed scale for the pandemic's impact on master's students, the self-rating anxiety scale and the self-rating depression scale were applied in the study. The single- and multi-group latent class analyses were used to investigate the impact of the pandemic on postgraduate students of different qualification types. Results: A total of 2818 responses were collected. The single-group latent class analysis identified four classes. The multi-group latent class analysis showed that no absolute homogeneity existed between different groups. In general, the number of academic master's students affected was greater than application-oriented master's students. Application-oriented master's students were more affected by course activities, while academic master's students were more affected by academic and social activities. Results show that individuals more affected had higher levels of anxiety and depression. Compared to course activities, impacts on social activities were more likely to cause anxiety and depression. Discussion: Universities can provide a more flexible way of assistance to different qualification types of postgraduate students. Furthermore, social activities play an important role in the mental health of postgraduate students. Therefore, under the background of normalization of pandemic prevention and control, schools should pay more attention to students' interpersonal communication activities to help relieve students' anxiety, depression, and other negative emotions.

Does Involution Cause Anxiety? An Empirical Study from Chinese Universities.

The debate over whether involution causes anxiety has persisted because no studies have attempted to quantify introversion and study its relationship to anxiety. This study quantified involution and explored its relationship with anxiety, provided evidence about whether involution was related to anxiety, and created a foundation for other scholars to carry out research on involution. Interviews and questionnaires were conducted to investigate the characteristics of 535 Chinese college students' involution behavior and its relationship with anxiety. We found that involution was not necessarily positively related to anxiety. The specific results were as follows: (1) The involution behavior of the Chinese college students could be divided into three types: the passive involution, reward-oriented involution, and achievement-motivated involution; (2) Significant differences in the involvement of involution existed at the college level; (3) Three motivations that resulted in involution, from primary to secondary, were achievement-motivation, reward-orientation, and passive engagement; and (4) Passive involution, reward-oriented involution, and the total scores for the involution behavior of the college students were significantly and positively correlated with anxiety. Among the three types of involution behavior, the college students' passive involution had a significant and positive predictive effect on their anxiety, while achievement-motivated involution had a significant and negative predictive effect.

Relationship between Parental Involvement and Mathematics Achievement of Chinese Early Adolescents: Multiple Mediating Roles of Mental Health and Mathematics Self-Efficacy.

This study conceptualized the multidimensional construct of parental involvement, including cognitive involvement, behavioral involvement, and personal involvement, and examined the mediating effects of student's mental health and mathematics self-efficacy. Questionnaires were administered to 2866 early adolescents and their parents in China; structural equation modeling and bias-corrected bootstrap methods were used. The results show that different dimensions of parental involvement had different effects on mathematics achievement. Additionally, results indicate that the influences of the multidimensional construct of parental involvement on mathematics achievement were either partially or completely mediated by student's mental health and mathematics self-efficacy. The findings also offer insight into possible interventions designed to explore how parental involvement promotes students' mathematics achievement through their children's mental health and mathematics self-efficacy.

The Impact of the COVID-19 Pandemic on Chinese Postgraduate Students' Mental Health.

To understand the mental health status of Chinese postgraduate students during the COVID-19 pandemic, we used three online questionnaires: self-rating anxiety (SAS) scale, self-rating depression (SDS) scale, and social avoidance and distress (SAD) scale. A total of 3137 postgraduate students from different regions of China participated in our study. We explored the relationship between participant characteristics and mental health using an analysis of variance (ANOVA). We found that the proportions of respondents with severe, mild, and moderate depression were 1.4%, 10.48%, and 21.99%, respectively, and the corresponding proportions of respondents with anxiety were 1.56%, 4.65%, and 14.69%, respectively. A one-way ANOVA revealed that the mental health statuses of the participants were different between the subgroups based on majors, classes, degree types, and the method of communication with advisors and students. A two-way ANOVA revealed significant effects on interaction and the method of communication with advisors and peers. These findings suggest that the mental health of postgraduate students should be monitored during the pandemic, especially when they are unable to communicate directly with their advisors or peers, and targeted psychological counselling must be focused on anxiety and depression.

Predicting Students' Attitudes Toward Collaboration: Evidence From Structural Equation Model Trees and Forests.

Numerous studies have shed some light on the importance of associated factors of collaborative attitudes. However, most previous studies aimed to explore the influence of these factors in isolation. With the strategy of data-driven decision making, the current study applied two data mining methods to elucidate the most significant factors of students' attitudes toward collaboration and group students to draw a concise model, which is beneficial for educators to focus on key factors and make effective interventions at a lower cost. Structural equation model trees (SEM trees) and structural equation model forests (SEM forests) were applied to the Program for International Student Assessment 2015 dataset (a total of 9,769 15-year-old students from China). By establishing the most important predictors and the splitting rules, these methods constructed multigroup common factor models of collaborative attitudes. The SEM trees showed that home educational resources (split by "above-average or not"), home possessions (split by "disadvantaged or not"), mother's education (split by "below high school or not"), and gender (split by "male or female") were the most important predictors among the demographic variables, drawing a 5-group model. Among all the predictors, achievement motivation (split by "above-average or not") and sense of belonging at school (split by "above-average or not" and "disadvantaged or not") were the most important, drawing a 6-group model. The SEM forest findings proved the relative importance of these variables. This paper discusses various interpretations of these results and their implications for educators to formulate corresponding interventions. Methodologically, this research provides a data mining approach to discover important information from large-scale educational data, which might be a complementary approach to enhance data-driven decision making in education.

An Extension of Testlet-Based Equating to the Polytomous Testlet Response Theory Model.

Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling. However, the violation of the local item independence assumption is inevitable when tests are built using testlet items. In this study, simulations are conducted to evaluate the performance of item response theory models and testlet response theory models for both the dichotomous and polytomous items in the context of equating tests composed of testlets. We also examine the impact of testlet effect, length of testlet items, and sample size on estimating item and person parameters. The results show that more accurate performance of testlet response theory models over item response theory models was consistently observed across the studies, which supports the benefits of using the testlet response theory models in equating for tests composed of testlets. Further, results of the study indicate that when sample size is large, item response theory models performed similarly to testlet response theory models across all studies.

How Course Support and Academic Support Impact on Chinese Graduate Students during the COVID-19: The Multiple Mediating Roles of Thesis Writing and Anxiety.

Because of the impact of the COVID-19 pandemic, the learning style of graduate students has changed considerably, making them more susceptible to psychological problems. This study aimed to explore the mediating roles of thesis writing and anxiety between course support (including course-arrangement, course-assessment, and course-learning), academic support (including academic exchange with colleges, tutors and schoolmates) and depression. There were 3137 graduate students investigated by self-developed Graduate Students' Academic Affected Questionnaire, Self-Rating Anxiety Scale and Self-Rating Depression Scale. The results showed that (1) 82% of graduate students reported their course support, academic support and thesis writing were affected to varying degrees; (2) course support and academic support correlated with thesis writing, anxiety and depression (p < 0.001); (3) the mediation model fitted well, the mediating effect of anxiety between academic support and depression was significant (ß = 0.086, SE = 0.02, p < 0.001), the serial multiple mediating effects of thesis writing and anxiety between academic support and depression were significant (ß = 0.02, SE = 0.008, p = 0.013) and the serial multiple mediating effects of thesis writing and anxiety between course support and depression were also found to be significant (ß = 0.014, SE = 0.006, p = 0.014).

Examining the Structure of Difficulties in Emotion Regulation Scale with Chinese Population: A Bifactor Approach.

The Difficulties in Emotion Regulation Scale (DERS), as one of the most frequently employed measures of emotion regulation (ER), has increasingly been used in numerous researches and applications. However, the structures derived from previous factor-analytic studies have a high degree of inconsistency. In the current study, both the traditional factor analysis method and novel (bifactor) modeling approaches were employed to examine the most optimal measurement structure of the DERS in a sample of 1036 Chinese participants. After a series of comparisons, the findings indicated that the bifactor model, with a general ER factor and four distinct subdimensions, was the most optimal structure for the DERS. Based on the study's findings, the discussion was focused mainly on the future directions and the implications of this bifactor model. The impact and limitations of the study were also discussed, and several suggestions for future research were provided at the end of the paper.

Cognitive decline trajectories and influencing factors in China: A non-normal growth mixture model analysis.

BACKGROUND: With the increase in the aging population worldwide, cognitive decline has become an important research topic. The purpose of this study is to examine the cognitive development trajectories and influencing factors of different latent classes of Chinese elderly people. This will provide us with effective guidance for prevention and intervention. METHODS: Four waves of data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) were collected and included 2440 Chinese elderly individuals. The cognitive function of elderly individuals was measured using the Mini Mental State Examination (MMSE). A nonnormal Growth Mixture model (GMM) with five time-invariant covariates was used to identify the different trajectories of cognitive decline in elderly individuals. RESULTS: Three latent decline trajectory groups were identified: stable cognitive group (SCG), high initial level - cognitive decline group (HIL-CDG), and high initial level - cognitive decline group (LIL-CDG). Elderly women were more likely to be assigned to a lower level subgroup than men. People who smoked and played cards or mahjong were more likely to be assigned to a cognitively stable group. CONCLUSION: Education may help raise the upper limit of cognition. Smoking may impair cognitive upper limit. A small amount of alcohol intake and participation in cognitive and physical activities may help the elderly to delay cognitive decline in their later years.

Impact of Academic Support on Anxiety and Depression of Chinese Graduate Students During the COVID-19 Pandemic: Mediating Role of Academic Performance.

INTRODUCTION: The COVID-19 pandemic broke out and has spread globally since 2019. It became a public health concern. This pandemic has brought tremendous changes in students' lives and modes of learning. Graduate students are likely to be more affected as they are a part of a special training program. According to the main-effect model, social support has a positive effect on mental health. The pandemic has exerted a negative impact on the social support of individuals, and as a result, the behavior of a person is more likely to be at risk and has resulted in psychological crisis in people/individuals. METHODS: A sample of 3137 graduate students responded to the instrument developed to assess the impact of the pandemic on the academic activities and performance, Self-rating Anxiety Scale and Self-rating Depression Scale. RESULTS: The results showed that: 1) the pandemic impacted the academic support and performance of graduate students in varying degrees, 21% of graduate students experienced anxiety, and 33.9% of graduate students experienced depressive symptoms in varying degrees; 2) academic support variables (ie, academic exchange with mentors and peers) and academic performance variables (ie, data collection and thesis writing) were significantly associated with anxiety and depressive symptoms; 3) the model fitted the data well (RMSEA = 0.029; SRMR = 0.014; TLI = 0.99; CFI = 0.996). The direct effects of academic support on anxiety and depressive symptoms were significant. The impact on academic performance played a mediating role between the impact on academic support, anxiety, and depressive symptoms. DISCUSSION: Academic support significantly affected academic performance, which in turn affected anxiety and depressive symptoms. So, it implies that, due to the pandemic, the academic support for graduate students had decreased, resulting in deterioration in academic performance, causing anxiety and depressive symptoms.

A Comparison of IRT Observed Score Kernel Equating and Several Equating Methods.

Item response theory (IRT) observed score kernel equating was evaluated and compared with equipercentile equating, IRT observed score equating, and kernel equating methods by varying the sample size and test length. Considering that IRT data simulation might unequally favor IRT equating methods, pseudo tests and pseudo groups were also constructed to make equating results comparable with those from the IRT data simulation. Identity equating and the large sample single group rule were both set as criterion equating (or true equating) on which local and global indices were based. Results show that in random equivalent groups design, IRT observed score kernel equating is more accurate and stable than others. In non-equivalent groups with anchor test design, IRT observed score equating shows lowest systematic and random errors among equating methods. Those errors decrease as a shorter test and a larger sample are used in equating; nevertheless, effect of the latter one is ignorable. No clear preference for data simulation method is found, though still affecting equating results. Preferences for true equating are spotted in random Equivalent Groups design. Finally, recommendations and further improvements are discussed.