Linear Structural Equation Models Research Articles

Perceptions of animal welfare and exotic pet ownership in China

AbstractChina plays a critical role in global biodiversity conservation, as both a biodiversity hotspot and for its role in international and domestic animal trade. Efforts to promote wildlife conservation have sparked interest in the attitudes held by Chinese citizens towards animals. Using a questionnaire, we sought to investigate the attitudes of 317 Chinese nationals across 22 provincial-level administrative units regarding their uses of animals, their perceived emotional capacities and views on exotic pets. We reduced the variables related to perceived uses of animals via Principal Component Analysis and ran Generalised Linear Models and Structural Equation Modelling to test relationships between questionnaire-derived variables. Perceptions of animals were divided into two Kellert categories — Utilitarian and Humanistic uses — and 97% of participants believed in animals’ capacities to have and express emotions. We found few interactions, with exotic pets, ie playing with or taking photographs, but the acceptability of owning an exotic pet influenced the likelihood of purchasing one. A belief that animals express emotions encouraged people to look for them as pets but thinking that pets make people happy made exotic pet ownership less acceptable. The shift in attitudes to include humanistic perceptions of animals, a belief in animals as emotive beings and understanding of terminology changed from the previous utilitarian views of pre-reform China, suggesting a readiness to embrace further conservation efforts in China. This deeper understanding of Chinese attitudes toward animals and drivers of the exotic pet trade within China may enable conservation efforts to better target future campaigns.

Cyclic structural causal model with unobserved confounder effect

This study examined cyclic non linear structural equation models (SEMs) with an unobserved confounder. The determination of causal direction, identifying whether X causes Y, Y causes X, or X and Y affect each other, is a fundamental issue in science and technology. Unobserved confounding factors are so-called third variables which influence both X and Y. Inclusion of unobserved confounding factors in the model, if they exist, is highly important, as unnoticed confounding variables can result not only in biased estimates but in pseudo-correlation between X and Y, which can distort causal inference. In this article, a cyclic non linear SEM with confounding factors was developed and the causal graph identifiability of the model was proved. The model’s identifiability was confirmed by simulation studies involving synthetic datasets and by application to a real dataset, namely, a Census Income (KDD) dataset containing weighted census data extracted from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau. The model effectively described the relationship between the variables age and wages, and no strong confounding factors effect was detected.

The effect of a one-year vigorous physical activity intervention on fitness, cognitive performance and mental health in young adolescents: the Fit to Study cluster randomised controlled trial

BackgroundPhysical activity (PA) may positively stimulate the brain, cognition and mental health during adolescence, a period of dynamic neurobiological development. High-intensity interval training (HIIT) or vigorous PA interventions are time-efficient, scalable and can be easily implemented in existing school curricula, yet their effects on cognitive, academic and mental health outcomes are unclear. The primary aim of the Fit to Study trial was to investigate whether a pragmatic and scalable HIIT-style VPA intervention delivered during school physical education (PE) could improve attainment in maths. The primary outcome has previously been reported and was null. Here, we report the effect of the intervention on prespecified secondary outcomes, including cardiorespiratory fitness, cognitive performance, and mental health in young adolescents.MethodsThe Fit to Study cluster randomised controlled trial included Year 8 pupils (n = 18,261, aged 12–13) from 104 secondary state schools in South/Mid-England. Schools were randomised into an intervention condition (n = 52), in which PE teachers delivered an additional 10 min of VPA per PE lesson for one academic year (2017–2018), or into a “PE as usual” control condition. Secondary outcomes included assessments of cardiorespiratory fitness (20-m shuttle run), cognitive performance (executive functions, relational memory and processing speed) and mental health (Strength and Difficulties Questionnaire and self-esteem measures). The primary intention-to-treat (ITT) analysis used linear models and structural equation models with cluster-robust standard errors to test for intervention effects. A complier-average causal effect (CACE) was estimated using a two-stage least squares procedure.ResultsThe HIIT-style VPA intervention did not significantly improve cardiorespiratory fitness, cognitive performance (executive functions, relational memory or processed speed), or mental health (all p > 0.05). Subgroup analyses showed no significant moderation of intervention effects by sex, socioeconomic status or baseline fitness levels. Changes in cardiorespiratory fitness were not significantly related to changes in cognitive or mental health outcomes. The trial was marked by high drop-out and low intervention compliance. Findings from the CACE analysis were in line with those from the ITT analysis.ConclusionThe one-academic year HIIT-style VPA intervention delivered during regular school PE did not significantly improve fitness, cognitive performance or mental health, but these findings should be interpreted with caution given low implementation fidelity and high drop-out. Well-controlled, large-scale, school-based trials that examine the effectiveness of HIIT-style interventions to enhance cognitive and mental health outcomes are warranted.Trial registrationISRCTN registry, 15,730,512. Trial protocol and analysis plan for primary outcome prospectively registered on 30th March 2017.ClinicalTrials.gov, NCT03286725. Secondary measures (focus of current manuscript) retrospectively registered on 18 September 2017.

Psychological well-being and coping strategies of elderly people during the COVID-19 pandemic in Hungary

Objective During COVID-19 lockdown the enforced social isolation and other pandemic-related changes highly increased the risk of mental health problems. We aimed to discover how elderly people coped with the psychological burdens of pandemic and the social isolation in Hungary. Methods This study included 589 (441 females) Hungarian individuals, aged 60–83 (M = 68.1, SD = 4.46). We collected online survey data to reach a wide population of elderly. Results of hierarchical linear modelling and structural equation modelling (SEM) analyses established how the current life-changing circumstances, the intolerance of uncertainty, loneliness and social support influence the mental health (e.g. depression, anxiety, well-being) of the elderly. The model was used to explore how adaptive and maladaptive emotion regulation strategies mediated the effects. Results Findings showed that perceived change in mood, social connectedness, and quality of life was negatively affected by catastrophizing and loneliness; whereas positive refocusing and contamination fear had a positive effect. According to the SEM analysis, intolerance of uncertainty and loneliness directly affected mental health. Further, maladaptive emotion regulation strategies mediated the connection between intolerance of uncertainty, contamination fear, loneliness and mental health. Whereas adaptive emotion regulation strategy mediated the connection between social support from friends, contamination fear, loneliness and mental health. Conclusion Overall, our research might help the understanding of how external and internal factors contributed to the well-being of elderly people during the COVID-19. The model can also be translated into professional interventions to develop coping strategies among elderly for the challenges of COVID-19 pandemic in their lives.

Hemodialysis nurse burnout in 31 provinces in mainland China: A cross-sectional survey.

Job burnout is an occupational psychological syndrome with a high prevalence among nurses in China. Hemodialysis (HD) nursing work has the characteristics of high intensity, high technical content, and high risk. The aims of this study were to investigate the prevalence and level of job burnout among HD nurses in China and explore the potential factors associated with burnout among HD nurses. This was a cross-sectional study in 2019. Survey data were collected from 2738 HD centers in mainland China. Job burnout was measured by the Chinese version of the Maslach Burnout Inventory. The working atmosphere, interpersonal relationships with colleagues, and intention to leave were each assessed by a single question respectively. Multiple linear regression and structural equation modeling were used for the analysis. A total of 10,570 surveys were collected. A total of 1199 (11.34%) HD nurses reported a high level of emotional exhaustion, 782 (7.40%) reported a high level of depersonalization, and 6767 (64.02%) reported a low level of personal accomplishment. Job burnout in the Northeastern region of mainland China was higher than that in other regions (p < 0.05). The working atmosphere, interpersonal relationships, region, hospital level, educational level, career planning, age, and number of children were significantly associated with burnout among HD nurses (p < 0.001, adjusted R2 = 0.313). The working environment, individual factors, and specialist nurse training were significantly associated with HD nurse burnout and intention to leave (comparative fit index = 0.907; goodness of fit index = 0.930; root mean square error of approximation = 0.055). There were notable regional differences in the burnout of HD nurses. This study contributes to the knowledge of the possible relationship of job burnout and intention to leave in HD nurses. It is suggested that improving the working atmosphere or interpersonal relationships and providing more training opportunities can alleviate job burnout in HD nurses.

A model of destination consumption, attitude, religious involvement, satisfaction, and revisit intention

This study aimed to develop the destination consumption-customer attitude model to explain tourist travel satisfaction and revisit intention with the moderating effect of religious involvement. Data were collected using a survey questionnaire. Respondents of 392 tourists who visited four major Buddhist monasteries in Taiwan have been analysed, and research hypotheses were assessed by employing partial linear square structural equation modelling (PLS-SEM). The findings revealed that destination consumption has positive and significant effects on rational attitude and emotional attitude toward revisiting a destination, which further facilitates travel satisfaction and revisit intention. Furthermore, this study supported the moderating role of religious involvement on the influence of national and emotional attitude and travel satisfaction on revisit intention. The results emphasized that symbolic experiential and functional consumption of a certain religious destination will significantly influence the rational and emotional attitudes toward revisiting the same destination. These results suggested that destination marketer should design a tourist’s destination consumption based on not only functional factors but also symbolic factors (such as self-concept, lifestyle, and destination) and experiential factors (such as entertainment, joy, pleasure, escape). Since the issues of destination consumption were still subject to further validation, this study provided an important reference for destination marketing to develop marketing strategies. The results were also valuable to provide as a theoretical base for further empirical validation.

Social support and quality of life among rural family caregivers of persons with severe mental illness in Sichuan Province, China: mediating roles of care burden and loneliness.

To explore the relationship between social support and quality of life (QoL) among family caregivers of persons with severe mental illness (SMI) and examine the mediating roles of care burden and loneliness. A cross-sectional study was carried out between December 2017 and May 2018. A random sample of 256 family caregivers of persons with SMI in rural areas of Sichuan Province, China was recruited for participation. Survey data on socio-demographics, social support, care burden, loneliness, and QoL were collected via in-person interviews. Multiple linear regression analysis and structural equation modeling (SEM) were used to test the hypothesized relationships. The majority (72.7%) of family caregivers of persons with SMI in this study reported having low QoL. Social support was positively associated with QoL and negatively associated with care burden and loneliness. The findings suggested the mediating roles of care burden and loneliness on the association between social support and QoL. The hypothesized model was found to be a suitable model for predicting QoL among family caregivers of persons with SMI. The findings can help inform the design of future interventions aimed at enhancing social support, reducing care burden and loneliness, which may be helpful to improve caregivers' QoL. Future study is required to find a causal path to promote QoL among family caregivers of persons with SMI.

Generalized Structural Equations Approach in the of Elderly Self-rated Health

To model classified and ordinal data, the Generalized Structural Equation Model (GSEM), which is based on the integration of two generalized linear model (GLM) and Structural Equation Modeling (SEM) algorithms, is applied. Unlike the SEM, this model does not require the normality assumption. The main purpose of this paper is to introduce and compare weighted (WLSMV) and unweighted (ULSMV) least squares mean and variance adjusted methods, two of the most applicable estimators of GSEM, for studying factors affecting the elderly self-rated health in 2015 in Tehran, Iran. 600 elderly people aged 60 years and above from 22 regions of Tehran were selected using multi-stage sampling. Self-rated health of the elderly variable (a 5-point Likert scale) was analyzed as an ordinal variable and was modeled considering the variables of social support, financial and environment security, spirituality, mental and physical health, functional health and health-related behaviors by Mplus software. The results showed that WLSMV outperformed ULSMV according to the smaller values of RMSEA and larger values for CFI and TLI indexes (RMSEA WLSMV = 0.04, CFI WLSMV = 0.965, and TLI WLSMV = 0.936). To prevent concluding invalid results in studying ordinal data due to considering them as a continues variable, it is important selecting correct statistical method according to the type of variables.

Andersen\u2019s utilization model for cataract surgical rate and empirical evidence from economically-developing areas

BackgroundUn-operated cataract is the leading cause of vision loss worldwide, responsible for 33% of visual impairment, and half of global blindness. The study aimed to build a fast evaluation method utilizing Andersen’s utilization framework and identify predictors of cataract surgical rate in sub-Saharan Africa and China.MethodsThe study was a cross-over ecological epidemiology study with a total of 19 countries in sub-Saharan Africa, and 31 provinces in China. Information was extracted from public data and published studies. Linear regression and structural equation modeling with Bootstrap were used to analyze predictors of CSR and their pathways to impact in sub-Saharan Africa and China separately.ResultsCataract surgical resources in sub-Saharan Africa were linearly correlated with CSR (β = 0.74, 95% CI: 0.09, 0.91), while GDP/P didn’t impact cataract surgical resources (β = 0.29, 95% CI: − 0.12, 0.75). In China, residents’ average ability to pay was confirmed as the mediator between GDP/P and CSR (p = 0.32, RMSEA = 0.07; βCSR-paying = 0.77, 95% CI: 0.25, 0.90; βpaying-GDP/P = 0.89, 95% CI: 0.82, 0.93).ConclusionsIn sub-Saharan Africa, CSR is determined by health care provision. Local economic development may not directly influence CSR. Therefore, international assistance aimed to providing free cataract surgery directly is crucial. In China, CSR is determined principally by health care demand (ability to pay). To increase CSR in underserved areas of China, ability to pay must be enhanced through social insurance, and reduced surgical fees.

Stand structure determines aboveground biomass across temperate forest types and species mixture along a local-scale elevational gradient

Greater variation in stand structure (i.e., individual tree size variation and stand density) is thought to promote aboveground biomass (AGB) better than species richness due to the canopy packing by different sized trees in the forest community. Here, we hypothesized that the relationships amongst species richness, stand density, individual tree size variation and AGB are dependent on forest types but single-species dominated forest stands matter much for higher AGB through higher stand density and individual tree size variation. To do this, we analyzed the forest inventory data (i.e., tree diameter, tree height, and species names) from 365 forest plots (each 0.1 ha) which was taken at different elevational gradients of temperate forest types (i.e., dense pure conifer, dense mixed forests, sparse mixed forests, sparse pure broadleaved, sparse pure conifer, and dense pure broadleaved) as well as species mixture groups (single-species and multi-species stands) in the northern area (namely Gilgit-Baltistan) of Pakistan. We mainly used piecewise structural equation modeling for testing the fixed effects of elevation, species richness, individual tree size variation and stand density as well as the random effect of either forest types or species mixture on AGB, and then we used linear structural equation modeling to test the models across forest types and species mixtures. We found the consistent positive effect of stand density on AGB across whole data, forest types and species mixtures, albeit species richness also showed a positive effect in some of the forest types. Individual tree size variation had a greater positive effect on AGB in single-species dominated stands compared to multi-species dominated stands. Elevation declined AGB directly and indirectly via stand density. We conclude that variation in stand structures (stand density and individual tree size variation of single-species dominated stands) are key to higher AGB in most of the temperate forest types. The positive effects of stand density and species richness on AGB may provide support to the niche complementarity effect through stand packing, whereas the greater effect of individual tree size variation on AGB in single-species rather than multi-species dominated stands may also confirm the selection or competitive exclusion effect. Therefore, we argue that both of the niche complementarity and selection effects are acting simultaneously to determine the relationships amongst species richness, stand structure and AGB in the studied temperate forests.

Biodiverse urban forests, happy people: Experimental evidence linking perceived biodiversity, restoration, and emotional wellbeing

Here we investigate whether perceived biodiversity is linked to emotional wellbeing, taking into account the individual level of connection to nature, and whether such relationship is mediated by perceived restorativeness. We exposed participants to urban trails of different biodiversity levels and analysed the data using linear mixed-effects and structural equation models. Our results show that animal diversity and nature relatedness are positively linked to perceived restorativeness that, in turn, increases positive affect and decreases negative affect; thus suggesting that restoration mediates the effect of biodiversity on emotional wellbeing. We also found walk duration is linked to increased positive affect and reduced negative affect while crowdedness level in the trail has the opposite effect. Our results show an important link between urban biodiversity conservation and public mental health.

Does disaster shocks affect farmers’ willingness for insurance? Mediating effect of risk perception and survey data from risk-prone areas in East China

The study estimates the impact of disaster shocks and risk perception on farmers’ willingness for insurance. Based on data of 328 farmers from the Shandong province of East China, the study uses cluster analysis, analysis of variance, hierarchical linear model and structural equation model to determine the impact of disaster shocks and risk perception on farmers’ willingness for insurance. A bootstrap method of bias correction was used to test the mediating effect of risk perception between disaster shocks and insurance willingness. Results revealed that the overall willingness of farmers for crop insurance was low. However, the farmers’ willingness for crop insurance increased with an increase in disaster shocks and risk perception. The parametric analysis also confirmed that disaster shocks and risk perceptions have a significant and positive impact on the farmers’ willingness for crop insurance. Risk perception has a partial mediating effect between disaster shock and farmers’ willingness for crop insurance. It indicates that disaster shock not only impacts on farmers’ willingness for crop insurance directly but also has an indirect impact on farmers’ willingness for crop insurance through risk perception. Farmers are encouraged to participate in the early warning disaster programs to increase awareness of climate change and resilience against weather aberrations.

Measuring Lean Culture: Designing a Research Instrument

Transformation from conventional manufacturing system to lean manufacturing system has enabled many manufacturing companies to reduce waste and ultimately achieve operational excellence. Unfortunately, there were also many reported cases where manufacturers failed to sustain the transformation until they achieve the ultimate result. Converting organization’s culture into the lean culture is often claimed as one of the mechanisms to sustain lean transformation in manufacturing organizations. Thus, measuring to what level lean manufacturers have converted their organization’s culture relative to lean culture characteristics is critical. Selfadministered questionnaire is a practical research instrument to measure the level of lean culture in multiple manufacturing organizations that are located in far-reaching geographical as it saves time, money and effort. In this paper, 36 questionnaire items for measuring lean culture has been designed. These items can be used as parameters for predicting sustainability of lean transformation using statistical analysis such as linear regression or structural equation modelling.

Elevation and micro environmental conditions directly and indirectly influence forests’ soil seed bank communities

The soil seed bank (SSB) plays an important role in determining future community composition and health of forests. The extent to which abiotic conditions alter the abundance and diversity of the future forest composition via modulating the regenerative capacity of the SSB and their relationship with each other is not fully understood. We studied how elevation and abiotic conditions (canopy openness, slope, aspect, soil pH, and a natural gradient of these soil nutrients: total nitrogen [N], total carbon [C], C:N ratio, available phosphorus [P], available potassium [K], calcium [Ca], iron [Fe], magnesium [Mg], manganese [Mn], and sulfur [S]) affect community characteristics, calculated as: (1) seedling abundance, (2) species richness, (3) Shannon-Weiner diversity index, (4) Simpson index, (5) Chao 2 richness estimator, (6) number of species represented by only one individual, and (7) number of species that occur only in one plot. We used soils sampled in 13 1-ha plots along an altitudinal gradient from 400 to 1850 m above sea level. We determined both direct and indirect causal relationships between abiotic factors and SSB community characteristics using linear mixed models and structural equation modeling. Increased elevation and canopy openness resulted in lower species richness and diversity as well as fewer rare species. However, greater canopy openness resulted in higher abundance. Abundance and richness of the SSB were lower in steeper slopes, but this negative effect appeared to be along an indirect pathway through soil pH and nutrients such as soil Mn and S. Soil P had a significant negative relationship with SSB characteristics for all indices evaluated here, except for SSB abundance, which was positively affected by increased soil pH. Our results highlight the role of abiotic factors in forest regeneration and resilience through their influence on the soil seed bank community. This study is one of the very first to provide data on the SSB along a wide elevational range in subtropical forests, and can be the basis to assess the regeneration potential and health of the study region.

Predictions of the community assemblage in a temperate forest through indicators that evaluate the anthropogenic disturbance effect on natural regeneration

The causal pathways of the anthropogenic disturbance effect on the above-ground vegetation, seed bank, and seed rain can provide information to understand the dynamic of natural regeneration in order to predict changes in the community assemblage. However, due to the spatial and temporal complexity of the natural regeneration process, these pathways have rarely been tested empirically. Therefore, to understand these pathways on natural regeneration, we propose the integration of composition, richness and functional diversity as indicators of assemblage vulnerability, and apply them to the above-ground vegetation, seed bank, and seed rain. In an Abies religiosa forest, in Mexico City, we determined anthropogenic disturbance indicators, environmental indicators and indicators of assemblage vulnerability. In order to assess if anthropogenic disturbances increase the abundance of weeds and modify functional diversity, we built linear mixed models (LMMs), generalized linear mixed models (GLMMs) and structural equation models (SEMs) and selected the best-fitting models according to Akaike's information criterion. We carried out RLQ/Fourth-corner tests in order to determine those regeneration functional traits of weeds that favor their tolerance to anthropogenic disturbances. We found that the anthropogenic disturbances could drive the community into an alternative stable state, in which the presence of weeds could homogenize its functional diversity. Our results showed that the applied indicators reduce the complexity of the study of the natural regeneration process and determine the causal pathways of the anthropogenic disturbance, in order to predict the trends of the community assemblage.

Predicting operating speed: comparison of linear regression and structural equation models

The aim of this research was to predict operating speed by considering geometric and roadside factors. Although most previous studies have employed linear regression modelling (LRM) to predict operating speed, this study recommends structural equation modelling (SEM) for the prediction of operating speed on rural multi-lane highways. In addition to geometric variables, LRM takes roadside variables into account. When employing SEM in this work, two latent variables were defined, namely ‘roadside effects’ and ‘geometric effects’. The first latent variable was the combination of land-use type, land-use density and number of accesses per segment, while the second was extracted from the segment length, highway grade, curvature, the presence of a guardrail and flat roadside slope, and the posted speed limits. The residual analysis and R2 values for LRM and SEM suggest that SEM demonstrates superior modelling performance compared with LRM. These results show the significant role of latent variables in predicting speed, which cannot be achieved through ordinary LRM.

Validation of the Hungarian PHQ-15. A latent variable approach.

Somatic symptoms without a clear-cut organic or biomedical background, also called "medically unexplained" or "somatoform" symptoms, are frequent in primary and secondary health care. They are often accompanied by depression and/or anxiety, and cause functional impairment. The Patient Health Question-naire Somatic Symptom Scale (PHQ-15) was developed to measure somatic symptom distress based on the frequency and bothersomeness of non-specific somatic symptoms. The study aimed to (1) evaluate the Hungarian version of the PHQ-15 from a psychometric point of view; (2) replicate the bifactor structure and associations with negative affect described in the literature; and (3) provide the Hungarian clinical and scientific community with reference (normal) values split by sex and age groups. PHQ-15, depression (BDI-R), and subjective well-being (WHO-5) scores obtained from a large (n = 5020) and close to representative community sample (Hun-garostudy 2006) were subjected to correlation analysis and linear structural equation modeling. The PHQ-15 showed good internal consistency (Cronbach's α = 0.810; McDonald's ω = 0.819) and moderate to strong correlation with the BDI-R (rs = .49, p < 0.001) and WHO-5 (rs = -.48, p < 0.001). Fit of the bifactor structure was excellent; in independent analyses, the general factor was strongly associated with depression (β = 0.656±0.017, p < 0.001) and well-being (β = -0.575±0.015, p < 0.001), whereas the symptom specific factors were only weakly or not related to these constructs. The PHQ-15 score was higher in females and showed a weak positive association with age. The Hungarian PHQ-15 is a psychometrically sound scale which is positively associated with depression and ne-gatively related to subjective well-being. The bifactor structure indicates the existence and meaningfulness of a gene-ral factor representing the affective-motivational component of somatic symptom distress. The Hungarian version of the PHQ-15 is a brief and usable tool for the pre-screening of somatization disorder (DSM-IV) or somatic symptom disorder (DSM-5). The reported reference values can be used in the future for both clinical and research purposes.

Multi-Trek Separation in Linear Structural Equation Models

Building on the theory of causal discovery from observational data, we study interactions between multiple (sets of) random variables in a linear structural equation model with non-Gaussian error terms. We give a correspondence between structure in the higher-order cumulants and combinatorial structure in the causal graph. It has previously been shown that low rank of the covariance matrix corresponds to trek separation in the graph. Generalizing this criterion to multiple sets of vertices, we characterize when determinants of subtensors of the higher-order cumulant tensors vanish. This criterion applies when hidden variables are present as well. For instance, it allows us to identify the presence of a hidden common cause of $k$ of the observed variables.

Related factors of quality of life among the public during the COVID-19 epidemic.

Objective: To explore the quality of life and its related factors among the public during the COVID- 19 epidemic. Methods: A total of 2026 questionnaires were collected through wjx.cn (991 males, 1035 females). The12-item short form Health Survey (SF-12), Public Perception Survey of COVID-19 (COVID-PPS), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS) and Perceived Social Support Scale (PSSS) were implemented to evaluate the quality of life of the public, and multiple linear regression and structural equation model were used to analyze the related factors. Results: The median score of SF-12 was 65. 4(53. 9, 81. 1). According to the multiple linear regression, the SF-12 scores were positively associated with the scores of COVID-19 PSS, living in Northeastern China, being single and family per capital income more than 5000 yuan (β = 0. 05, 0. 04, 0. 04, 0. 06), and negatively associated with the scores of SAS and SDS, age of > 60 years, living in Central China, and with no formal education or primary education(β = -0. 31, -0. 30, -0. 08, -0. 04, -0. 07, -0. 04) . According to the structural equation model, COVID perception, scores of SAS and SDS were correlated with the SF-12 scores (λ= 0. 06, - 0. 33, - 0. 29). Conclusion: The quality of life of the public may be fairly good during COVID- 19. People who are over 60 years old, living in Central China, wi1h poor education background tend to have poorer life quality than other people. Anxiety and depression may negatively affect the life quality of the public. (English) [ABSTRACT FROM AUTHOR] 目的：探究新冠肺炎流行期间公众生活质量及相关因素。方法：使用问卷星收集有效问卷 2026 份［男 991 人，女 1035 人］，采用 12 条目简短生命质量量表（SF-12）、自编公众对新冠肺炎的认知 调查问卷（COVID-PPS）、焦虑自评量表（SAS）、抑郁自评量表（SDS）、领悟社会支持量表（PSSS） 进 行评估，采用多重线性回归和结构方程模型探究生活质量的相关因素。结果：SF-12 中位得分为 65.4 （53.9，81.1）分。回归分析结果显示，COVID-PPS 得分、生活在东北地区、单身、家庭人均月收入 ≥ 5000 元与 SF-12 总分正向关联（β = 0.05、0.04、0.04、0.06）；SAS 得分、SDS 得分、> 60 岁、生活在华 中地区、未接受过正规教育或受教育程度为小学与 SF-12 总分负向关联（β = -0.31、-0.30、-0.08、-0.04、-0.07、-0.04）；结构方程模型显示，COVID-PPS、SAS、SDS 得分与 SF-12 总分存在相关（λ = 0.06、-0.33、-0.29）。结论：疫情下公众的生活质量处于中等偏上程度。60 岁以上，华中地区，受教 育程度低的人群生活质量更差，焦虑抑郁症状可能对公众的生活质量造成负面影响。 (Chinese) [ABSTRACT FROM AUTHOR] Copyright of Chinese Mental Health Journal / Zhongguo Xinli Weisheng Zazhi is the property of Chinese Mental Health Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An ECM-ISC Based on College Students’ Continued Learning Intention toward E-Learning Space Post COVID-19

The “Suspending Classes without Stopping Learning”, which is an emergency policy launched by the Chinese government to continue teaching activities as schools across the country, gives a new opportunity to popularize the application of E-learning space for college students. In order to explain college students’ continued learning intention toward E-learning space post COVID-19, this study combines theories from the fields of ECM-ISC (Expectation Confirmation Model for Information Systems Continuance). By adding two latent variables, namely students’ initial intention and teacher guidance factor, an improved ECM-ISC model for college students’ continued learning intention was put forward. Results from Linear regression analysis and structural equation modeling (SEM) demonstrate a strong explanatory power of the new model. Based on the results of the empirical analysis, corresponding suggestions are proposed.