The relationship between healthy lifestyles and cognitive function in Chinese older adults: the mediating effect of depressive symptoms

BACKGROUND

Previous studies have proven the positive relationship between healthy lifestyles and cognitive function in older adults. However, the specific impacts and mechanisms require further investigation. Therefore, this study aimed to investigate whether healthy lifestyles and cognitive function were associated with Chinese older adults and whether depressive symptoms mediated their association.

METHODS

8272 valid samples were included using the latest data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Pearson's test was applied to investigate the relationship between the key variables. Regression models were employed to examine the mediating effects of healthy lifestyles, using Sobel's test and the bootstrap method to confirm path effects.

RESULTS

There was a significant correlation between healthy lifestyles, depressive symptoms, and cognitive function (p < 0.01). Healthy lifestyles directly impact cognitive function (β = 0.162, p < 0.01). Healthy lifestyles had a significant effect on depressive symptoms (β=-0.301, p < 0.01), while depressive symptoms have a significant impact on cognitive function (β=-0.108, p < 0.01). Depressive symptoms partially mediated the effect of healthy lifestyles on cognitive function (β = 0.032, p < 0.01). The Sobel and bootstrap tests confirmed the robustness of the regression analysis results.

CONCLUSION

Depressive symptoms mediate the relationship between healthy lifestyles and cognitive function. Our findings suggest that prevention strategies for cognitive impairment in older adults should focus on healthy lifestyles and mental health.

Neighborhood effects on the health of elderly persons: evidence from China

BACKGROUND

Presently, global aging has become increasingly serious, whereas the health concerns brought by aging have become a public issue that warrants an urgent solution from all countries across the world. Therefore, this research paper discusses the influence of neighborhood health on elderly individuals' health, and extending a realistic basis for the other economies to improve the neighborhood environment and promote the health of the elderly.

METHODS

Based on the data of CHARLS2018, this research paper adopts the samples that fulfill the study requirements (N = 7326). we constructed a comprehensive research framework integrating oprobit regression model, heterogeneity analysis, conditional mixed process(CMP)robustness testing, Furthermore, the KHB decomposition method is implemented to ascertain the influential mechanism of NMH and NPH on the mental- and physical health of elderly persons.

RESULTS

The oprobit regression model analysis indicates that NMH 0.434 and NPH 0.550 exert positive influences on the elderly's mental- and physical health. Meanwhile, the effects of conditional mixed process on NMH and NPH stand at 0.381 and4.372, which are different from the oprobit regression results; thereby, indicating the existence of endogeneity. Afterward, KHB mediating effect confirms that Internet use, gift reciprocity, and charity activity contribute 30.21% and 16.83% to mental- and physical health, respectively.

CONCLUSIONS

Firstly, the NMH and NPH demonstrate a positive influence on the mental- and physical health of the elder population. However, there exist heterogeneous differences. Secondly, the conditional mixed process deals with the endogeneity of NMH and NPH. Thirdly, social integration, social interaction, and social engagement serve as significant transmission mechanisms for the influences of NMH and NPH on the health of elderly persons.

Research on the Perceived Quality of Virtual Reality Headsets in Human-Computer Interaction

The progress of commercial VR headsets largely depends on the progress of sensor technology, the iteration of which often means longer research and development cycles, and also higher costs. With the continuous maturity and increasing competition of VR headsets, designers need to create a balance among user needs, technologies, and costs to achieve commercial competition advantages. To make accurate judgments, consumer feedback and opinions are particularly important. Due to the increasing maturity in the technology of commercial VR headsets in recent years, the cost has been continuously decreasing, and potential consumers have gradually increased. With the increase in consumer demand for virtual reality headsets, it is particularly important to establish a perceptual quality evaluation system. The relationship between consumer perception and product quality determined by evaluations of experience is improving. Using the research method implemented in this work, through semi-structured interviews and big data analysis of VR headset consumption, the perceptual quality elements of VR headsets are proposed, and the order of importance of perceptual quality attributes is determined by questionnaire surveys, quantitative analysis, and verification. In this study, the perceptual quality elements, including technical perceptual quality (TPQ) and value perceptual quality (VPQ), of 14 types of VR headsets were obtained, and the importance ranking of the VR headsets' perceptual quality attributes was constructed. In theory, this study enriches the research on VR headsets. In practice, this study provides better guidance and suggestions for designing and producing VR headsets so that producers can better understand which sensor technology has met the needs of consumers, and which sensor technology still has room for improvement.

The impact of pandemic on dynamic volatility spillover network of international stock markets

Since the beginning of the twenty-first century, several pandemics, including SARS and COVID-19, have spread faster and on a broader scale. Not only do they harm people's health, but they can also cause significant damage to the global economy within a short period of time. This study uses the infectious disease EMV tracker index to investigate the impact of pandemics on the volatility spillover effects of global stock markets. Spillover index model estimation is conducted using the time-varying parameter vector autoregressive approach, and the maximum spanning tree and threshold filtering techniques are combined to construct the dynamic network of volatility spillovers. The conclusion from the dynamic network is that when a pandemic occurs, the total volatility spillover effect increases sharply. In particular, the total volatility spillover effect historically peaked during the COVID-19 pandemic. Moreover, when pandemics occur, the density of the volatility spillover network increases, while the diameter of the network decreases. This indicates that global financial markets are increasingly interconnected, speeding up the transmission of volatility information. The empirical results further reveal that volatility spillovers among international markets have a significant positive correlation with the severity of a pandemic. The study's findings are expected to help investors and policymakers understand volatility spillovers during pandemics.

Heterogeneous Diffusion of Government Microblogs and Public Agenda Networks during Public Policy Communication in China

During public policy information diffusion, policy interpretation on government microblogs and public attention interact, but there are certain differences. We construct a research framework for the heterogeneous diffusion of public policy information on government microblogs. An empirical study is conducted based on the Network Agenda Setting (NAS) model. First, a combination of topic mining and content analysis is used to identify the issues discussed by government microblogs and citizens. Then, we use the importance of nodes in Degree Structure (DS) and Flow Structure (FS) entropy to measure their attention to different issues. Finally, the Quadratic Assignment Procedure (QAP) correlation and regression analysis explore the degree of heterogeneity and causal relationship between government microblog agenda networks (GMANs) and public agenda networks (PANs). We find that GMANs influence PANs and the degree of heterogeneity between them is relatively low at the beginning of policy implementation. However, as government microblogs reveal positive effects of policy implementation, they fail to influence PANs effectively, and there is a greater degree of heterogeneity between them. Moreover, PANs do not significantly affect GMANs. The dynamic leading relationship between GMANs and PANs in public policy diffusion is clarified, helping to shape the image of digital government in public opinion.

A survey on the publics discrimination rate of typical rumors during the coronavirus disease 2019 epidemic

OBJECTIVES

During the epidemic of coronavirus disease-2019 (COVID-19), the wide spread of rumors caused significant public hazards. This study aims to understand the situation of discrimination for typical COVID-19 rumors by the public and related factors.

METHODS

An anonymous online survey was carried out using Questionnaire Star. The contents included participants' gender, age, education level, the COVID-19 information sources, and the judgmental questions about 14 representative COVID-19 rumors. The discrimination rate and 95% confidence interval of 14 rumors were estimated, and the association of discrimination rate with gender, age, and education level was analyzed by binary logistic regression.

RESULTS

A total of 2 087 valid questionnaires were collected. The participants were mainly female (62.7%) and below 35 years old (63.4%); the education level was predominantly college/bachelor's degree (47.3%) and master's degree or above (39.1%); the participants, who accessed to COVID-19 information included internet media, accounted for 91%. The participants with different gender, age, and education level had significant differences in the distribution of COVID-19 information sources (all P<0.01). The participants' discrimination rate for 14 rumors ranged from 67.4% to 98.6%, with 4 rumors less than 80%. Women's discrimination rate of 9 rumors was significantly higher than men's (all P<0.05). There was no significant difference in the discrimination rate of rumors among the different age groups (all P>0.05), but the differences in the discrimination rate of other rumors among the different age groups varied according to the rumor. Compared to those with high school or less education levels, the discrimination rates were also higher in the respondents with high education levels (P<0.05).

CONCLUSIONS

A few publics are still unable to identify typical rumors during the COVID-19 epidemic. There are associations among genders, age, and the education levels with the discrimination of some rumors. The government authorities should strengthen the true information regarding COVID-19, and therefore enhance the public's ability to identify rumors.

Neural underpinnings of morality judgment and moral aesthetic judgment

Morality judgment usually refers to the evaluation of moral behavior`s ability to affect others` interests and welfare, while moral aesthetic judgment often implies the appraisal of moral behavior's capability to provide aesthetic pleasure. Both are based on the behavioral understanding. To our knowledge, no study has directly compared the brain activity of these two types of judgments. The present study recorded and analyzed brain activity involved in the morality and moral aesthetic judgments to reveal whether these two types of judgments differ in their neural underpinnings. Results reveled that morality judgment activated the frontal, parietal and occipital cortex previously reported for motor representations of behavior. Evaluation of goodness and badness showed similar patterns of activation in these brain regions. In contrast, moral aesthetic judgment elicited specific activations in the frontal, parietal and temporal cortex proved to be involved in the behavioral intentions and emotions. Evaluation of beauty and ugliness showed similar patterns of activation in these brain regions. Our findings indicate that morality judgment and moral aesthetic judgment recruit different cortical networks that might decode others' behaviors at different levels. These results contribute to further understanding of the essence of the relationship between morality judgment and aesthetic judgment.

Resiliencebased multifactorial model of depression among people who lost an onlychild in China

OBJECTIVES

There are almost one million families who lost their only child in China, and 65.6% of them had severe and long lasting depression and needed timely psycho-intervention. This study aims to explore the relationship among resilience and its influential factors, and to compare their effect on depression.

METHODS

A total of 212 only-child loss person in 9 administrative regions in Changsha were assessed by using Connor-Davidson Resilience Scale, Zung Self-rating Depression Scale, Simplified Coping Style Questionnaire, Simplified Eysenck Personality Questionnaire, Social Support Rating Scale, and General Self-efficacy Scale. A hypothetical model was tested based on Kumpfer resilience framework and stress-coping theory.

RESULTS

The influential factors of resilience were: positive coping (the total effect value was 0.480), support utilization (the total effect value was 0.359), neuroticism (the total effect value was -0.326), negative coping (the total effect value was 0.279), extraversion (the total effect value was 0.219), and objective support (the total effect value was 0.077). The process of individual-environment interaction showed a greater impact on resilience, which had a direct effect on depression (the total effect value was -0.344, 67.1%), and also indirect effect through self-efficacy (the total effect value was -0.169). The total effect of resilience accounted for 20.1% of the total effect of all variables.

CONCLUSIONS

Resilience mainly impacts depression directly, and can negatively predict depression in only-child loss parents. Resilience, located before self-efficacy, is a significant stress mediating variables. Personality traits and support utilization indirectly impact resilience via negative and positive coping. The key to promote the reorganization of resilience is the process of individual-environmental interaction, involving support utilization, positive coping, and some sorts of negative coping strategies, which plays an important role in developing a resilience intervention program and can improve the depression of the only-child loss person.

Learning to Select Supplier Portfolios for Service Supply Chain

The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.