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BACKGROUND: Mental disorders have ranked among the top 10 prevalent causes of burden on a global scale. Generative artificial intelligence (GAI) has emerged as a promising and innovative technological advancement that has significant potential in the field of mental health care. Nevertheless, there is a scarcity of research dedicated to examining and understanding the application landscape of GAI within this domain. OBJECTIVE: This review aims to inform the current state of GAI knowledge and identify its key uses in the mental health domain by consolidating relevant literature. METHODS: Records were searched within 8 reputable sources including Web of Science, PubMed, IEEE Xplore, medRxiv, bioRxiv, Google Scholar, CNKI and Wanfang databases between 2013 and 2023. Our focus was on original, empirical research with either English or Chinese publications that use GAI technologies to benefit mental health. For an exhaustive search, we also checked the studies cited by relevant literature. Two reviewers were responsible for the data selection process, and all the extracted data were synthesized and summarized for brief and in-depth analyses depending on the GAI approaches used (traditional retrieval and rule-based techniques vs advanced GAI techniques). RESULTS: In this review of 144 articles, 44 (30.6%) met the inclusion criteria for detailed analysis. Six key uses of advanced GAI emerged: mental disorder detection, counseling support, therapeutic application, clinical training, clinical decision-making support, and goal-driven optimization. Advanced GAI systems have been mainly focused on therapeutic applications (n=19, 43%) and counseling support (n=13, 30%), with clinical training being the least common. Most studies (n=28, 64%) focused broadly on mental health, while specific conditions such as anxiety (n=1, 2%), bipolar disorder (n=2, 5%), eating disorders (n=1, 2%), posttraumatic stress disorder (n=2, 5%), and schizophrenia (n=1, 2%) received limited attention. Despite prevalent use, the efficacy of ChatGPT in the detection of mental disorders remains insufficient. In addition, 100 articles on traditional GAI approaches were found, indicating diverse areas where advanced GAI could enhance mental health care. CONCLUSIONS: This study provides a comprehensive overview of the use of GAI in mental health care, which serves as a valuable guide for future research, practical applications, and policy development in this domain. While GAI demonstrates promise in augmenting mental health care services, its inherent limitations emphasize its role as a supplementary tool rather than a replacement for trained mental health providers. A conscientious and ethical integration of GAI techniques is necessary, ensuring a balanced approach that maximizes benefits while mitigating potential challenges in mental health care practices.
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BACKGROUND: Generation Z (born 1995-2010) members are digital residents who use technology and the internet more frequently than any previous generation to learn about their health. They are increasingly moving away from conventional methods of seeking health information as technology advances quickly and becomes more widely available, resulting in a more digitalized health care system. Similar to all groups, Generation Z has specific health care requirements and preferences, and their use of technology influences how they look for health information. However, they have often been overlooked in scholarly research. OBJECTIVE: First, we aimed to identify the information-seeking preferences of older individuals and Generation Z (those between the ages of 18 and 26 years); second, we aimed to predict the effects of digital health literacy and health empowerment in both groups. We also aimed to identify factors that impact how both groups engage in digital health and remain in control of their own health. METHODS: The Health Information National Trends Survey was adopted for further use in 2022. We analyzed 1862 valid data points by conducting a survey among Chinese respondents to address the research gap. A descriptive analysis, 2-tailed t test, and multiple linear regression were applied to the results. RESULTS: When compared with previous generations, Generation Z respondents (995/1862, 53.44%) were more likely to use the internet to find out about health-related topics, whereas earlier generations relied more on traditional media and interpersonal contact. Web-based information-seeking behavior is predicted by digital health literacy (Generation Z: ß=.192, P<.001; older population: ß=.337, P<.001). While this was happening, only seeking health information from physicians positively predicted health empowerment (Generation Z: ß=.070, P=.002; older population: ß=.089, P<.001). Despite more frequent use of the internet to learn about their health, Generation Z showed lower levels of health empowerment and less desire to look for health information, overall. CONCLUSIONS: This study examined and compared the health information-seeking behaviors of Generation Z and older individuals to improve their digital health literacy and health empowerment. The 2 groups demonstrated distinct preferences regarding their choice of information sources. Health empowerment and digital health literacy were both significantly related to information-seeking behaviors.
Subject(s)
Health Literacy , Telemedicine , Humans , Adolescent , Young Adult , Adult , Information Seeking Behavior , Health Literacy/methods , Cross-Sectional Studies , Telemedicine/methods , Surveys and Questionnaires , Internet , Power, PsychologicalABSTRACT
BACKGROUND: Understanding factors that influence healthy or unhealthy eating can inform intervention strategies. This study ascertained whether and how unintentional exposure to food and nutrition information influenced healthy eating concerns. The study tested body comparison, body satisfaction, and body mass index as three mechanisms that potentially link food information encounter, commonly known as information scanning, to healthy eating concerns. METHODS: A sample of 440 online participants (mean age = 29.15 years) was used to investigate: (1) how unintentional exposure to food and nutrition information, i.e., information encounter (IE), affects healthy eating concerns (HEC); (2) how the effect of IE on HEC is mediated by body comparison (BC); (3) how the paths of the mediation model are moderated by body satisfaction (BS) or body mass index (BMI). RESULTS: The findings show a positive and sizable total effect of IE on HEC - a whole-scale increase in information encounter is associated with a substantial increase in healthy eating concerns by 15 percentage points (bp = 0.150). BC is found to mediate the effect of IE on HEC in an all-positive complementary mediation. Both the indirect and the direct-and-remainder paths show sizable effects. The mediated path contributes about 20% of the total effect between IE and HEC (cp = 20%), while the direct-and-remainder path contributes the rest (cp = 80%). BS was found to moderate the relationship between IE and BC, the first leg of the mediation. The moderation effect is large - the effect of IE on BC is much smaller on the highly and the moderately satisfied than on the lowly satisfied (slope differential bp = -.60). BMI was found to moderate the direct-and-remainder effect of IE on HEC, controlling BC. That is, the effect of IE on HEC, after filtering out the mediated effect through BC, is much larger for those with high or low BMI than those with healthy BMI (slope differential bp = .32). CONCLUSIONS: Exposure, even if unintentional, to food and nutrition information is an important predictor of HEC. BC, BS, and BMI are important factors that help to explain the process through which information affects behaviors.
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Diet, Healthy , Weight Loss , Humans , Adult , Body Mass Index , Nutritional Status , Personal Satisfaction , Feeding Behavior , EatingABSTRACT
The COVID-19 pandemic has caused a global public health emergency, increasing the prevalence of emotional distress, and potentially leading to altered diet behavior. Self-efficacy measures various aspects of perceiving and understanding emotions. The present study was carried out with the objective of understanding the effect of emotional self-efficacy on dietary behavior and quality. It also shed light on which elements contributed to the link between food-related behavior and perceived dietary quality during the first lockdown of the COVID-19 pandemic. Based on the factor analysis of nineteen food groups, choices, consumption, and socioeconomic status were examined in a sample of 441 Chinese participants. Multiple linear regression examined the association between food consumption, dietary quality, and self-efficacy. Contrary to prior research, the intake of salty snacks and alcoholic beverages dropped by 3.3% and 2.8%, respectively, during the first lockdown. Emotional self-efficacy negatively mediated the relationship between socioeconomic status and dietary quality. In conclusion, emotional self-efficacy is a well-established tool for evaluating how Chinese people cope with negative emotions. As an individual's dietary quality was affected during the imposed lockdown, the present study offers valuable insight into psychosocial factors that may contribute to health disparities by advocating for organized nutritional support in future epidemic-related quarantines.
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The COVID-19 outbreak has caused significant stress in our lives, which potentially increases frustration, fear, and resentful emotions. Managing stress is complex, but helps to alleviate negative psychological effects. In order to understand how the public coped with stress during the COVID-19 pandemic, we used Macao as a case study and collected 104,827 COVID-19 related posts from Facebook through data mining, from 1 January to 31 December 2020. Divominer, a big-data analysis tool supported by computational algorithm, was employed to identify themes and facilitate machine coding and analysis. A total of 60,875 positive messages were identified, with 24,790 covering positive psychological themes, such as "anti-epidemic", "solidarity", "hope", "gratitude", "optimism", and "grit". Messages that mentioned "anti-epidemic", "solidarity", and "hope" were the most prevalent, while different crisis stages, key themes and media elements had various impacts on public involvement. To the best of our knowledge, this is the first-ever study in the Chinese context that uses social media to clarify the awareness of solidarity. Positive messages are needed to empower social media users to shoulder their shared responsibility to tackle the crisis. The findings provide insights into users' needs for improving their subjective well-being to mitigate the negative psychological impact of the pandemic.
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COVID-19 , Health Communication , Social Media , COVID-19/epidemiology , Disease Outbreaks , Humans , PandemicsABSTRACT
BACKGROUND: The fact that the number of individuals with obesity has increased worldwide calls into question media efforts for informing the public. This study attempts to determine the ways in which the mainstream digital news covers the etiology of obesity and diseases associated with the burden of obesity. OBJECTIVE: The dual objectives of this study are to obtain an understanding of what the news reports on obesity and to explore meaning in data by extending the preconceived grounded theory. METHODS: The 10 years of news text from 2010 to 2019 compared the development of obesity-related coverage and its potential impact on its perception in Mainland China, Hong Kong, and Taiwan. Digital news stories on obesity along with affliction and inferences in 9 Chinese mainstream newspapers were sampled. An automatic content analysis tool, DiVoMiner was proposed. This computer-aided platform is designed to organize and filter large sets of data on the basis of the patterns of word occurrence and term discovery. Another programming language, Python 3, was used to explore connections and patterns created by the aggregated interactions. RESULTS: A total of 30,968 news stories were identified with increasing attention since 2016. The highest intensity of newspaper coverage of obesity communication was observed in Taiwan. Overall, a stronger focus on 2 shared causative attributes of obesity is on stress (n=4483, 33.0%) and tobacco use (n=3148, 23.2%). The burdens of obesity and cardiovascular diseases are implied to be the most, despite the aggregated interaction of edge centrality showing the highest link between the "cancer" and obesity. This study goes beyond traditional journalism studies by extending the framework of computational and customizable web-based text analysis. This could set a norm for researchers and practitioners who work on data projects largely for an innovative attempt. CONCLUSIONS: Similar to previous studies, the discourse between the obesity epidemic and personal afflictions is the most emphasized approach. Our study also indicates that the inclination of blaming personal attributes for health afflictions potentially limits social and governmental responsibility for addressing this issue.
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Communication , Obesity , China , Hong Kong/epidemiology , Humans , Obesity/epidemiology , Taiwan/epidemiologyABSTRACT
In a number of emerging markets such as China, native consumers may avoid certain domestic products when foreign products are available. However, the studies on the unfavorable attitudes toward the products of one's own country are not sufficient. This article aims to develop a construct to explain this phenomenon. The measurement scale was developed and validated using responses from 318 Chinese consumers with respect to electronics and clothing. The judgment sampling method produced representative distributions in terms of age and gender. The items were first generated and refined based on the content validity. Exploratory factor analysis, confirmatory factor analysis, and convergent and discriminant validity were then established. Finally, this study investigates relationships among consumer repulsion, domestic product ownership, and negative word of mouth, to confirm the nomological validity. This study develops a construct-consumer repulsion-that can be used to articulate native consumers' unfavorable attitudes toward domestic products from consumers' individual identity-expressiveness perspective. First, this study develops a scale for consumer repulsion. The scale shows good reliability, unidimensionality, convergent validity, discriminant validity, and nomological validity. The scale helps explain the nature and impact of country biases, and integrates and expands current studies in this field, which should prove helpful in further research on this topic. Furthermore, this study proposes a three-dimensional model of consumer repulsion consisting of affective repulsion, cognitive repulsion, and conative repulsion. Finally, these findings have shown that linking domestic products to social identity and self-identity will likely influence domestic product ownership and word of mouth of native consumers.
Subject(s)
Attitude , Consumer Behavior , China , Humans , Language , Reproducibility of ResultsABSTRACT
BACKGROUND: Information about a new coronavirus emerged in 2019 and rapidly spread around the world, gaining significant public attention and attracting negative bias. The use of stigmatizing language for the purpose of blaming sparked a debate. OBJECTIVE: This study aims to identify social stigma and negative sentiment toward the blameworthy agents in social communities. METHODS: We enabled a tailored text-mining platform to identify data in their natural settings by retrieving and filtering online sources, and constructed vocabularies and learning word representations from natural language processing for deductive analysis along with the research theme. The data sources comprised of ten news websites, eleven discussion forums, one social network, and two principal media sharing networks in Taiwan. A synthesis of news and social networking analytics was present from December 30, 2019, to March 31, 2020. RESULTS: We collated over 1.07 million Chinese texts. Almost two-thirds of the texts on COVID-19 came from news services (n=683,887, 63.68%), followed by Facebook (n=297,823, 27.73%), discussion forums (n=62,119, 5.78%), and Instagram and YouTube (n=30,154, 2.81%). Our data showed that online news served as a hotbed for negativity and for driving emotional social posts. Online information regarding COVID-19 associated it with China-and a specific city within China through references to the "Wuhan pneumonia"-potentially encouraging xenophobia. The adoption of this problematic moniker had a high frequency, despite the World Health Organization guideline to avoid biased perceptions and ethnic discrimination. Social stigma is disclosed through negatively valenced responses, which are associated with the most blamed targets. CONCLUSIONS: Our sample is sufficiently representative of a community because it contains a broad range of mainstream online media. Stigmatizing language linked to the COVID-19 pandemic shows a lack of civic responsibility that encourages bias, hostility, and discrimination. Frequently used stigmatizing terms were deemed offensive, and they might have contributed to recent backlashes against China by directing blame and encouraging xenophobia. The implications ranging from health risk communication to stigma mitigation and xenophobia concerns amid the COVID-19 outbreak are emphasized. Understanding the nomenclature and biased terms employed in relation to the COVID-19 outbreak is paramount. We propose solidarity with communication professionals in combating the COVID-19 outbreak and the infodemic. Finding solutions to curb the spread of virus bias, stigma, and discrimination is imperative.