OBJECTIVE: Employing the extended theory of social normative behavior, this study examines the influence of individual and collective norms on COVID-19 vaccination intention across eight Asian countries. We examine how cultural tightness-looseness, defined as the degree of a culture's emphasis on norms and tolerance of deviant behavior, shapes normative social influence on COVID-19 vaccination intention.
METHODS: We conducted a multicountry online survey (N = 2676) of unvaccinated individuals in China, Indonesia, Japan, Malaysia, Singapore, South Korea, Thailand, and Vietnam in May and June 2021, when COVID-19 vaccination mandates had not yet been implemented in those countries. We conducted hierarchical regression analyses with interaction terms for the total sample and then re-categorizied the eight countries as either "tight" (n = 1102) or "loose" (n = 1574) to examine three-way interactions between individual norms, collective norms, and cultural tightness-looseness.
RESULTS: Perceived injunctive norms exerted the strongest impact of all normative factors on vaccination intention. Collective injunctive norms' influence depended on both perceived injunctive and descriptive norms, which was larger when norms were lower (vs. higher). The interactive pattern between perceived and collective norms was more pronounced in countries with greater cultural tightness.
CONCLUSION: Our findings reveal nuanced patterns of how individual and collective social norms influence health behavioral decisions, depending on the degree of cultural tightness-looseness.
METHODS AND RESULTS: Using a Delphi-based approach, a multidisciplinary panel of 50 international experts from 26 countries reached a consensus on some of the open research questions regarding the link between MAFLD and CKD.
CONCLUSIONS: This Delphi-based consensus statement provided guidance on the epidemiology, mechanisms, management and treatment of MAFLD and CKD, as well as the relationship between the severity of MAFLD and risk of CKD, which establish a framework for the early prevention and management of these two common and interconnected diseases.
METHODS: Individual data were collected from 14 registry centers on patients with biopsy-proven non-alcoholic fatty liver disease (NAFLD), and in all patients, circulating CK-18 M30 levels were measured. Individuals with a NAFLD activity score (NAS) ≥5 with a score of ≥1 for each of steatosis, ballooning, and lobular inflammation were diagnosed as having definite NASH; individuals with a NAS ≤2 and no fibrosis were diagnosed as having non-alcoholic fatty liver (NAFL).
RESULTS: A total of 2571 participants were screened, and 1008 (153 with NAFL and 855 with NASH) were finally enrolled. Median CK-18 M30 levels were higher in patients with NASH than in those with NAFL (mean difference 177 U/L; standardized mean difference [SMD]: 0.87 [0.69-1.04]). There was an interaction between CK-18 M30 levels and serum alanine aminotransferase, body mass index (BMI), and hypertension ( P
METHODS AND RESULTS: A total of 16 cannabinoids are determined in optimized microwave pretreatment of hemp oil using the developed approach. Untargeted metabolomics analysis reveals that cannabinoid extract (CE) and its major constituent (cannabidiol, CBD), can alleviate high glucose-induced increases in lipids and carbohydrates, and decreases in amino acid and nucleic acid. Moreover, CE and CBD are also found to suppress the expression levels of mdt-15, sbp-1, fat-5, fat-6, fat-7, daf-2, and elevate the expression level of daf-1, daf-7, daf-16, sod-3, gst-4, lipl-4, resulting in the decrease of lipid synthesis and the enhance of kinetism. Canonical correspondence analysis (CCA) uncovers strong associations between specific metabolic alterations and gene expression levels.
CONCLUSION: These findings from this exploratory study offer a new insight into the roles of cannabinoids in the treatment of obesity and related complications.
METHOD/PROCESS: We study SNS' effects on well-being by accounting for users' personal (i.e., self-disclosure) and situational (i.e., social networks) attributes, using a mixed design of content analysis and social network analysis.
RESULT/CONCLUSION: We compare users' within-person changes in self-disclosure and social networks in two phases (over half a year), drawing on Weibo Depression SuperTalk, an online community for depression, and find: ① Several network attributes strengthen social support, including network connectivity, global efficiency, degree centralization, hubs of communities, and reciprocal interactions. ② Users' self-disclosure attributes reflect positive changes in mental well-being and increased attachment to the community. ③ Correlations exist between users' topological and self-disclosure attributes. ④ A Poisson regression model extracts self-disclosure attributes that may affect users' received social support, including the writing length, number of active days, informal words, adverbs, negative emotion words, biological process words, and first-person singular forms.
INNOVATION: We combine social network analysis with content analysis, highlighting the need to understand SNS' effects on well-being by accounting for users' self-disclosure (content) and communication partners (social networks).
IMPLICATION/CONTRIBUTION: Authentic user data helps to avoid recall bias commonly found in self-reported data. A longitudinal within-person analysis of SNS' effects on well-being is helpful for policymakers in public health intervention, community managers for group organizations, and users in online community engagement.
METHODS/PROCESS: We used a web crawler to obtain a corpus of an online depression community. We introduced a three-stage procedure for metaphor identification in a Chinese Corpus: (1) combine MIPVU to identify metaphorical expressions (ME) bottom-up and formulate preliminary working hypotheses; (2) collect more ME top-down in the corpus by performing semantic domain analysis on identified ME; and (3) analyze ME and categorize conceptual metaphors using a reference list. In this way, we have gained a greater understanding of how depression sufferers conceptualize their experience metaphorically in an under-represented language in the literature (Chinese) of a new genre (online health community).
RESULTS/CONCLUSION: Main conceptual metaphors for depression are classified into PERSONAL LIFE, INTERPERSONAL RELATIONSHIP, TIME, and CYBERCULTURE metaphors. Identifying depression metaphors in the Chinese corpus pinpoints the sociocultural environment people with depression are experiencing: lack of offline support, social stigmatization, and substitutability of offline support with online support. We confirm a number of depression metaphors found in other languages, providing a theoretical basis for researching, identifying, and treating depression in multilingual settings. Our study also identifies new metaphors with source-target connections based on embodied, sociocultural, and idiosyncratic levels. From these three levels, we analyze metaphor research's theoretical and practical implications, finding ways to emphasize its inherent cross-disciplinarity meaningfully.