The darkness of reacculturation: examining factors influencing depression among Chinese international student returnees in the post-COVID-19 era.

Introduction: In the aftermath of the COVID-19 pandemic, the reintegration of Chinese international student returnees intersects with China's critical effort to combat a significant brain drain of highly skilled talents, highlighting an unprecedented psychological battleground. This convergence underscores the urgent need for nuanced research to navigate the uncharted territory of their mental health. Methods: Employing Bayesian analysis supported by Markov Chain Monte Carlo (MCMC) algorithms, this study examined depression prevalence and associated factors among 1,014 Chinese returnees. The sample comprised 44.87% male participants (455), 51.58% female participants (523), and 3.55% identifying as "Others" (36), with an age distribution of 61.74% aged 18-30 (626), 28.80% aged 31-40 (292), and 9.47% aged 41-50 (96). The mean age of participants was 29.6 years, ranging from 18 to 50 years. PHQ-9 diagnoses revealed alarming levels of depression, with 47.9% exhibiting a moderately severe degree of depressive disorder. Results: Our findings highlight the intricate interplay between identity clusters- "homestayers" (those leaning towards a Chinese cultural identity), "navigators" (those with a bicultural identity), and "wayfarers" (those leaning towards a foreign cultural identity)-and the likelihood of depression. Specifically, homestayers showed a clear and strong negative association, navigators demonstrated a positive association, and wayfarers had a positive yet unclear correlation with depression levels. Furthermore, acculturation, age, and gender showed no significant effects, whereas education mildly mitigated depression. Discussion: Based on these findings, we suggest the implementation of better-tailored mental health support and policies to facilitate smoother reintegration.

Vortex of regret: How positive and negative coping strategies correlate with feelings of guilt.

Bad coping behavior and guilt may reinforce each other as a negative feedback loop. Social contexts and expectations may also create cognitive dissonance in coping individuals and affect the effectiveness of coping styles. This study examines the associations between the feeling of guilt and specific coping styles belonging to both groups of positive and negative coping styles. We conducted Bayesian Multiple Regression analyses on secondary data from 3784 high school students in China. Positive coping is associated more with reduced feelings of guilt compared to negative coping. However, some positive coping styles were found to be positively associated with a sense of guilt, especially those involving confrontation against or conformity to social expectations. Most negative coping styles are positively associated with guilt, and substance use has the strongest influence among the examined negative coping styles. The findings suggest that the consideration of sociocultural contexts is very important in supporting those with guilt issues, especially adolescents in societies with dominant traditional East Asian values.

Trust Is for the Strong: How Health Status May Influence Generalized and Personalized Trust.

In the trust-health relationship, how trusting other people in society may promote good health is a topic often examined. However, the other direction of influence-how health may affect trust-has not been well explored. In order to investigate this possible effect, we employed the Bayesian Mindsponge Framework (BMF) analytics to go deeper into the information processing mechanisms underlying the expressions of trust. Conducting a Bayesian analysis on a dataset of 1237 residents from Cali, Colombia, we found that general health status is positively associated with generalized trust, but recent experiences of illnesses/injuries have a negative moderating effect. Personalized trust is largely unchanged across different general health conditions, but the trust level becomes higher with recent experiences of illnesses/injuries. Psychophysiological mechanisms of increasing information filtering intensity toward unfamiliar sources during a vulnerable state of health is a plausible explanation of found patterns in generalized trust. Because established personal relationships are reinforced information channels, personalized trust is not affected as much. Rather, the results suggest that people may rely even more on loved ones when they are in bad health conditions. This exploratory study shows that the trust-health relationship can be examined from a different angle that may provide new insights.

Examining the Influence of Exploration and Parental Education Attainment on Students' Acceptance of Collectivist Values.

Exploration can help students access a wider range of information and make connections among values within the natural and social world. This study investigated the relationship between students' previous exploration of their surroundings and their acceptance of collectivist values in the context of China. A sample of 343 college students was analyzed based on the Bayesian Mindsponge Framework to explore this relationship. The results revealed a positive association between students' prior exploration of surroundings and their degree of collectivist orientation. Furthermore, parental education attainment was found to negatively moderate this association, albeit with a small effect size. These findings contribute to the understanding of how information acquisition influences students' acceptance of collectivist values and highlight the potential role of the family infosphere in shaping this relationship.

A dataset of Chinese drivers' driving behaviors and socio-cultural factors related to driving.

Given the high fatality rate due to road traffic accidents in China, understanding the factors influencing aggressive driving behaviors among Chinese drivers is essential to alleviate the problem. The paper describes a dataset of 1039 Chinese drivers' driving behaviors and the socio-cultural factors associated with the behaviors. The dataset was collected through an online survey. The dataset comprises five main categories: 1) driving information, 2) aggressive driving behaviors, 3) friend/peer influence, 4) family influence, and 5) socio-demographic information. The dataset is valuable for public health and transportation researchers to explore factors influencing drivers' driving behaviors and public safety in China. The dataset's construct validity was confirmed by the Bayesian Mindsponge Framework (BMF) analytics. Specifically, the analysis shows that safe driving behaviors are affected by information promoting safe driving that is passively and actively absorbed from friends/peers (friends/peers being role models and friends'/peers' support, respectively). The result is consistent with the Mindsponge Theory's information-processing mechanism in human minds.

How AI's Self-Prolongation Influences People's Perceptions of Its Autonomous Mind: The Case of U.S. Residents.

The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI's capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, to make assessments. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents in the United States, we found that the more people believe that an AI agent seeks continued functioning, the more they believe in that AI agent's capability of having a mind of its own. Moreover, we also found that the above association becomes stronger if a person is more familiar with personally interacting with AI. This suggests a directional pattern of value reinforcement in perceptions of AI. As the information processing of AI becomes even more sophisticated in the future, it will be much harder to set clear boundaries about what it means to have an autonomous mind.

Near-Suicide Phenomenon: An Investigation into the Psychology of Patients with Serious Illnesses Withdrawing from Treatment.

Patients with serious illnesses or injuries may decide to quit their medical treatment if they think paying the fees will put their families into destitution. Without treatment, it is likely that fatal outcomes will soon follow. We call this phenomenon "near-suicide". This study attempted to explore this phenomenon by examining how the seriousness of the patient's illness or injury and the subjective evaluation of the patient's and family's financial situation after paying treatment fees affect the final decision on the treatment process. Bayesian Mindsponge Framework (BMF) analytics were employed to analyze a dataset of 1042 Vietnamese patients. We found that the more serious the illnesses or injuries of patients were, the more likely they were to choose to quit treatment if they perceived that paying the treatment fees heavily affected their families' financial status. Particularly, only one in four patients with the most serious health issues who thought that continuing the treatment would push themselves and their families into destitution would decide to continue the treatment. Considering the information-filtering mechanism using subjective cost-benefit judgments, these patients likely chose the financial well-being and future of their family members over their individual suffering and inevitable death. Our study also demonstrates that mindsponge-based reasoning and BMF analytics can be effective in designing and processing health data for studying extreme psychosocial phenomena. Moreover, we suggest that policymakers implement and adjust their policies (e.g., health insurance) following scientific evidence to mitigate patients' likelihood of making "near-suicide" decisions and improve social equality in the healthcare system.

An analytical framework-based pedagogical method for scholarly community coaching: A proof of concept.

Working in academia is challenging, even more so for those with limited resources and opportunities. Researchers around the world do not have equal working conditions. The paper presents the structure, operation method, and conceptual framework of the SM3D Portal's community coaching method, which is built to help Early Career Researchers (ECRs) and researchers in low-resource settings overcome the obstacle of inequality and start their career progress. The community coaching method is envisioned by three science philosophies (cost-effectiveness, transparency spirit, and proactive attitude) and established and operated based on the Serendipity-Mindsponge-3D knowledge (SM3D) management framework (i.e., mindsponge thinking and Bayesian Mindsponge Framework analytics serve as the coaching program's foundational theory and analytical tools). The coaching method also embraces Open Science's values for lowering the cost of doing science and encouraging the trainees to be transparent, which is expected to facilitate the self-correcting mechanism of science through open data, open review, and open dialogue. Throughout the training process, members are central beneficiaries by gaining research knowledge and skills, acquiring publication as the training's product, and shifting their mindsets from "I can't do it" to "I can do it," and at the same time transforming a mentee to be ready for a future mentor's role. The coaching method is thus one of the members, for the member, by the members.•The paper provides the structure, operation method, and conceptual framework of the SM3D Portal's community coaching method, which is built to help Early Career Researchers (ECRs) and researchers in low-resource settings overcome the obstacle of inequality and start their career progress.•The paper presents three major science philosophies envisioning the establishment and operation of scholarly community coaching.•The paper employs the mindsponge theory and BMF analytics to construct a conceptual framework explaining how an environment is created to help shift members' mindsets from "I can't do it" to "I can do it."

Escaping from Air Pollution: Exploring the Psychological Mechanism behind the Emergence of Internal Migration Intention among Urban Residents.

Rapid urbanization with poor city planning has resulted in severe air pollution in urban areas of low- and middle-income countries. Given the adverse impacts of air pollution, citizens may develop ideation of averting behaviors, including migration to another region. The current study explores the psychological mechanism and demographic predictors of internal migration intention among urban people in Hanoi, Vietnam-one of the most polluted capital cities in the world. The Bayesian Mindsponge Framework (BMF) analytics was used to construct a model and perform Bayesian analysis on a stratified random sampling dataset of 475 urban people. We found that migration intention was negatively associated with an individual's satisfaction with air quality. The association was moderated by the perceived availability of a nearby alternative (i.e., a nearby province/city with better air quality). The high migration cost due to geographical distance made the moderation effect of the perceived availability of a faraway alternative negligible. These results validate the proposed psychological mechanism behind the emergence of migration intention. Moreover, it was found that male and young people were more likely to migrate. While the brain drain effect did not clearly show, it is likely due to complex underlying interactions of various related factors (e.g., age and gender). The results hint that without air pollution mitigation measures, the dislocation of economic forces might occur and hinder sustainable urban development. Therefore, collaborative actions among levels of government, with the environmental semi-conducting principle at heart, are recommended to reduce air pollution.

Introduction to Bayesian Mindsponge Framework analytics: An innovative method for social and psychological research.

The paper introduces Bayesian Mindsponge Framework (BMF) analytics, a new analytical tool for investigating socio, psychological, and behavioral phenomena. The strengths of this method derive from the combination of the mindsponge mechanism's conceptual formulation power and Bayesian analysis's inferential advantages. The BMF-based research procedure includes six main steps, in which the mindsponge-based conceptualization and model construction is the key step that makes the method unique. Therefore, we elaborate on the fundamental components and functions of the mindsponge mechanism and summarize them into five memorable principles so that other researchers can capitalize directly. An exemplary analysis was performed using a dataset of 3071 Vietnamese entrepreneurs' decisiveness and perceptions of the likelihood of success/continuity to validate the method.•The paper provides five strong points of BMF analytics, originating from the good match between the mindsponge mechanism and Bayesian inference.•The paper also provides a step-by-step procedure for conducting BMF-based research.•The mindsponge mechanism's basic components and functions are elaborated and summarized into five core principles that can be applied directly for research conceptualization and model construction.

The psychological mechanism of internet information processing for post-treatment evaluation.

Digital healthcare has been greatly benefiting the public health system, especially during the COVID-19 pandemic. In digital healthcare, information communication through the Internet is crucial. The current study explores how patients' accessibility and trust in Internet information influence their decisions and ex-post assessment of healthcare providers by employing the Bayesian Mindsponge Framework (BMF) on a dataset of 1,459 Vietnamese patients. We find that patients' accessibility to Internet information positively affects the perceived sufficiency of information for choosing a healthcare provider, and their trust in the information intensifies this effect. Internet information accessibility is negatively associated with post-treatment assessment of healthcare providers, and trust also moderates this effect. Moreover, patients considering professional reputation important while making a decision are more likely to regard their choices as optimal, whereas patients considering services important have contradicting tendencies. Based on these findings, a concern about the risk of eroding trust toward Internet sources about healthcare information is raised. Thus, quality control and public trust-building measures need to be taken to improve the effectiveness of healthcare-related communication through the Internet and facilitate the implementation of digital healthcare.

Brain Drain out of the Blue: Pollution-Induced Migration in Vietnam.

Air pollution is a major problem that severely affects the health of inhabitants in developing countries' urban areas. To deal with the problem, they may consider migration to another place as an option, which can result in the loss of skillful and talented workforces. This situation is called the brain drain phenomenon. The current study employed the Bayesian mindsponge framework (BMF) on the responses of 475 urban inhabitants in Hanoi, Vietnam-one of the most polluted capital cities in the world-to examine the risk of losing talented workforces due to air pollution. Our results show that people with higher educational levels are more likely to have intentions to migrate both domestically and internationally due to air pollution. Regarding the domestic migration intention, younger people and males have a higher probability of migrating than their counterparts. Age and gender also moderate the association between educational level and international migration intention, but their reliability needs further justification. Based on these findings, we suggest that environmental stressors caused by air pollution can influence citizen displacement intention on a large scale through the personal psychological mechanism of cost-benefit judgment. Due to the risk of air pollution on human resources, building an eco-surplus culture is crucial for enhancing environmental and socio-economic resilience.

Home Scholarly Culture, Book Selection Reason, and Academic Performance: Pathways to Book Reading Interest among Secondary School Students.

Although studies have explored the predictors of book reading interest among children, little is known about the underlying mechanism that helps children become interested in reading books. This study attempt to demonstrate: (1) how book-reading interest is driven by reasons for choosing books (recommendation or personal preference), (2) how students with high and low academic achievements are motivated by different thinking pathways, and (3) how home scholarly culture improves book-reading interest through such pathways. Using Bayesian analysis on a dataset of survey responses from 4966 Vietnamese secondary students (11-15 years old, sixth to ninth grade), we found: (i) Reading interest is positively associated with a book recommendation and parental book reading activities (parents read books to children); (ii) High-achieving students are more interested in reading books if they can choose those books according to personal preferences; (iii) Parental book reading activities can promote book reading interest through recommendations and also by understanding children's personal preferences. We advocate a more personalized approach in educational policymaking, curriculum design, and home scholarly culture based on students' abilities and perceptions.

Alice in Suicideland: Exploring the Suicidal Ideation Mechanism through the Sense of Connectedness and Help-Seeking Behaviors.

On average, one person dies by suicide every 40 s. However, extant studies have largely focused on the risk factors for suicidal behaviors, not so much on the formation of suicidal thoughts. Therefore, we attempt to explain how suicidal thoughts arise and persist inside one's mind using a multifiltering information mechanism called Mindsponge. Bayesian analysis with Hamiltonian Markov Chain Monte Carlo (MCMC) technique was run on a dataset of multinational students (N = 268) of an international university in Japan. Item 9 in the PHQ-9 was used to survey suicidal ideation. The associations among four main variables, namely, (i) suicidal ideation, (ii) help-seeking willingness (informal and formal sources), (iii) sense of connectedness, and (iv) information inaccessibility (represented by being international students), were tested in four models. Sense of connectedness is negatively associated with suicidal ideation, but its effect becomes less impactful when interacting with international students. The impact of a sense of connectedness on informal help-seeking willingness (toward family members) among international students is also lessened. Informal help-seeking is negatively associated with suicidal ideation, whereas formal help is positive. The findings support our assumption on three fundamental conditions for preventing suicidal thoughts: (i) a high degree of belongingness, (ii) accessibility to help-related information, and (iii) healthy perceived cultural responses towards mental health. Therefore, systematically coordinated programs are necessary to effectively tackle suicidal ideation.