Background High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The development of the medical AI industry depends to a certain extent on whether industry experts have a comprehensive understanding of the public’s views on medical AI. Currently, the opinions of the general public on this matter remain unclear. Objective The purpose of this study is to explore the public perception of AI in medical care through a content analysis of social media data, including specific topics that the public is concerned about; public attitudes toward AI in medical care and the reasons for them; and public opinion on whether AI can replace human doctors. Methods Through an application programming interface, we collected a data set from the Sina Weibo platform comprising more than 16 million users throughout China by crawling all public posts from January to December 2017. Based on this data set, we identified 2315 posts related to AI in medical care and classified them through content analysis. Results Among the 2315 identified posts, we found three types of AI topics discussed on the platform: (1) technology and application (n=987, 42.63%), (2) industry development (n=706, 30.50%), and (3) impact on society (n=622, 26.87%). Out of 956 posts where public attitudes were expressed, 59.4% (n=568), 34.4% (n=329), and 6.2% (n=59) of the posts expressed positive, neutral, and negative attitudes, respectively. The immaturity of AI technology (27/59, 46%) and a distrust of related companies (n=15, 25%) were the two main reasons for the negative attitudes. Across 200 posts that mentioned public attitudes toward replacing human doctors with AI, 47.5% (n=95) and 32.5% (n=65) of the posts expressed that AI would completely or partially replace human doctors, respectively. In comparison, 20.0% (n=40) of the posts expressed that AI would not replace human doctors. Conclusions Our findings indicate that people are most concerned about AI technology and applications. Generally, the majority of people held positive attitudes and believed that AI doctors would completely or partially replace human ones. Compared with previous studies on medical doctors, the general public has a more positive attitude toward medical AI. Lack of trust in AI and the absence of the humanistic care factor are essential reasons why some people still have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.
Face recognition is not rooted in a universal eye movement information-gathering strategy. Western observers favor a local facial feature sampling strategy, whereas Eastern observers prefer sampling face information from a global, central fixation strategy. Yet, the precise qualitative (the diagnostic) and quantitative (the amount) information underlying these cultural perceptual biases in face recognition remains undetermined. To this end, we monitored the eye movements of Western and Eastern observers during a face recognition task, with a novel gaze-contingent technique: the Expanding Spotlight. We used 2° Gaussian apertures centered on the observers’ fixations expanding dynamically at a rate of 1° every 25 ms at each fixation – the longer the fixation duration, the larger the aperture size. Identity-specific face information was only displayed within the Gaussian aperture; outside the aperture, an average face template was displayed to facilitate saccade planning. Thus, the Expanding Spotlight simultaneously maps out the facial information span at each fixation location. Data obtained with the Expanding Spotlight technique confirmed that Westerners extract more information from the eye region, whereas Easterners extract more information from the nose region. Interestingly, this quantitative difference was paired with a qualitative disparity. Retinal filters based on spatial-frequency decomposition built from the fixations maps revealed that Westerners used local high-spatial-frequency information sampling, covering all the features critical for effective face recognition (the eyes and the mouth). In contrast, Easterners achieved a similar result by using global low-spatial-frequency information from those facial features. Our data show that the face system flexibly engages into local or global eye movement strategies across cultures, by relying on distinct facial information span and culturally tuned spatially filtered information. Overall, our findings challenge the view of a unique putative process for face recognition.
Westerners habitually think in analytical ways, whereas East Asians tend to favor holistic styles of thinking. We replicated this difference but showed that it disappeared after control deprivation (Experiment 1). Brief experiences of control deprivation, which stimulate increased desire for control, caused Chinese participants to shift toward Western-style analytical thinking in multiple ways (Experiments 2-5). Western Caucasian participants also increased their use of analytical thinking after control deprivation (Experiment 6). Manipulations that required Chinese participants to think in Western, analytical ways caused their sense of personal control to increase (Experiments 7-9). Prolonged experiences of control deprivation, which past work suggested foster an attitude more akin to learned helplessness than striving for control, had the opposite effect of causing Chinese participants to shift back toward a strongly holistic style of thinking (Experiments 10-12). Taken together, the results support the reality of cultural differences in cognition but also the cross-cultural similarity of using analytical thinking when seeking to enhance personal control.
Culture shapes how people gather information from the visual world. We recently showed that Western observers focus on the eyes region during face recognition, whereas Eastern observers fixate predominantly the center of faces, suggesting a more effective use of extrafoveal information for Easterners compared to Westerners. However, the cultural variation in eye movements during scene perception is a highly debated topic. Additionally, the extent to which those perceptual differences across observers from different cultures rely on modulations of extrafoveal information use remains to be clarified. We used a gaze-contingent technique designed to dynamically mask central vision, the Blindspot, during a visual search task of animals in natural scenes. We parametrically controlled the Blindspots and target animal sizes (0°, 2°, 5°, or 8°). We processed eye-tracking data using an unbiased data-driven approach based on fixation maps and we introduced novel spatiotemporal analyses in order to finely characterize the dynamics of scene exploration. Both groups of observers, Eastern and Western, showed comparable animal identification performance, which decreased as a function of the Blindspot sizes. Importantly, dynamic analysis of the exploration pathways revealed identical oculomotor strategies for both groups of observers during animal search in scenes. Culture does not impact extrafoveal information use during the ecologically valid visual search of animals in natural scenes.
The Chinese Big Five Personality Inventory (CBF-PI), a 134-item self-report scale, and its 40-item brief version (CBF-PI-B) are sound psychometric instruments used to measure the Big Five personality domains in the Chinese population. However, their applicability is limited by their length, as well as restricted by assessment conditions. In this study, we developed and validated a new shortened version with 15 items (CBF-PI-15) through exploratory factor analysis and confirmatory factor analysis in a large sample (Sample 1) of 10,738 Chinese adults (mean = 33.90 years, SD = 9.39 years, range 17–57 years). Measurement invariance results suggested the CBF-PI-15 were invariant across gender and age groups. Convergent, discriminant and criterion validities were tested in Sample 2 (N = 256, mean = 21.62 years, SD = 3.06 years, range 18–35 years) and findings showed an expected correlational pattern with external variables. Results revealed positive correlations of Neuroticism with the Barratt Impulsiveness Scale Brief Version (BIS-Brief), the Patient Health Questionnaire, and the Generalized Anxiety Disorder Screener, as well as a strongly negative correlation between Conscientiousness and BIS-Brief. Additionally, Conscientiousness positively correlated with academic performance as expected. In conclusion, the CBF-PI-15 holds promise as an informative alternative for the original CBF-PI-B when administration time or conditions are limited, and our findings provide preliminary support for the utility of the CBF-PI-15.
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