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Wai-Kit Ming
Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.

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Journal article
Published: 21 July 2021 in Health and Quality of Life Outcomes
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Pregnant women experience physical, physiological, and mental changes. Health-related quality of life (HRQoL) is a relevant indicator of psychological and physical behaviours, changing over the course of pregnancy. This study aims to assess HRQoL of pregnant women during different stages of pregnancy. This cross-sectional study was performed using the The EuroQoL Group's five-dimension five-level questionnaire (EQ-5D-5L) to assess the HRQoL of pregnant women, and demographic data were collected. This study was conducted in a regional university hospital in Guangzhou, China. A total of 908 pregnant women were included in this study. Pregnant women in the early 2nd trimester had the highest HRQoL. The HRQoL of pregnant women rose from the 1st trimester to the early 2nd trimester, and dropped to the bottom at the late 3rd trimester due to some physical and mental changes. Reports of pain/discomfort problem were the most common (46.0%) while self-care were the least concern. More than 10% of pregnant women in the 1st trimester had health-related problems in at least one dimension of whole five dimensions. In the whole sample, the EuroQoL Group's visual analog scale (EQ-VAS) was 87.86 ± 9.16. Across the gestational stages, the HRQoL remained stable during the pregnancy but the highest value was observed in the 1st trimester (89.65 ± 10.13) while the lowest was in the late 3rd trimester (87.28 ± 9.13). During pregnancy, HRQoL were associated with gestational trimesters in a certain degree. HRQoL was the highest in the early 2nd trimester and then decreased to the lowest in the late 3rd trimester due to a series of physical and psychological changes. Therefore, obstetric doctors and medical institutions should give more attention and care to pregnant women in the late 3rd trimester.

ACS Style

Huailiang Wu; Weiwei Sun; Hanqing Chen; Yanxin Wu; Wenjing Ding; Shangqiang Liang; Xinyu Huang; Haitian Chen; Qing Zeng; Zhuyu Li; Peng Xiong; Jian Huang; Babatunde Akinwunmi; Casper J P Zhang; Wai-Kit Ming. Health-related quality of life in different trimesters during pregnancy. Health and Quality of Life Outcomes 2021, 19, 182 .

AMA Style

Huailiang Wu, Weiwei Sun, Hanqing Chen, Yanxin Wu, Wenjing Ding, Shangqiang Liang, Xinyu Huang, Haitian Chen, Qing Zeng, Zhuyu Li, Peng Xiong, Jian Huang, Babatunde Akinwunmi, Casper J P Zhang, Wai-Kit Ming. Health-related quality of life in different trimesters during pregnancy. Health and Quality of Life Outcomes. 2021; 19 (1):182.

Chicago/Turabian Style

Huailiang Wu; Weiwei Sun; Hanqing Chen; Yanxin Wu; Wenjing Ding; Shangqiang Liang; Xinyu Huang; Haitian Chen; Qing Zeng; Zhuyu Li; Peng Xiong; Jian Huang; Babatunde Akinwunmi; Casper J P Zhang; Wai-Kit Ming. 2021. "Health-related quality of life in different trimesters during pregnancy." Health and Quality of Life Outcomes 19, no. 1: 182.

Journal article
Published: 12 July 2021 in JMIR Serious Games
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Background Virtual reality (VR) simulators have become widespread tools for training medical students and residents in medical schools. Students using VR simulators are provided with a 3D human model to observe the details by using multiple senses and they can participate in an environment that is similar to reality. Objective The aim of this study was to promote a new approach consisting of a shared and independent study platform for medical orthopedic students, to compare traditional tendon repair training with VR simulation of tendon repair, and to evaluate future applications of VR simulation in the academic medical field. Methods In this study, 121 participants were randomly allocated to VR or control groups. The participants in the VR group studied the tendon repair technique via the VR simulator, while the control group followed traditional tendon repair teaching methods. The final assessment for the medical students involved performing tendon repair with the “Kessler tendon repair with 2 interrupted tendon repair knots” (KS) method and the “Bunnell tendon repair with figure 8 tendon repair” (BS) method on a synthetic model. The operative performance was evaluated using the global rating scale. Results Of the 121 participants, 117 participants finished the assessment and 4 participants were lost to follow-up. The overall performance (a total score of 35) of the VR group using the KS method and the BS method was significantly higher (P<.001) than that of the control group. Thus, participants who received VR simulator training had a significantly higher score on the global rating scale than those who received traditional tendon repair training (P<.001). Conclusions Our study shows that compared with the traditional tendon repair method, the VR simulator for learning tendon suturing resulted in a significant improvement of the medical students in the time in motion, flow of operation, and knowledge of the procedure. Therefore, VR simulator development in the future would most likely be beneficial for medical education and clinical practice. Trial Registration Chinese Clinical Trial Registry ChiCTR2100046648; http://www.chictr.org.cn/hvshowproject.aspx?id=90180

ACS Style

Tsz-Ngai Mok; Junyuan Chen; Jinghua Pan; Wai-Kit Ming; Qiyu He; Tat-Hang Sin; Jialin Deng; Jieruo Li; Zhengang Zha. Use of a Virtual Reality Simulator for Tendon Repair Training: Randomized Controlled Trial. JMIR Serious Games 2021, 9, e27544 .

AMA Style

Tsz-Ngai Mok, Junyuan Chen, Jinghua Pan, Wai-Kit Ming, Qiyu He, Tat-Hang Sin, Jialin Deng, Jieruo Li, Zhengang Zha. Use of a Virtual Reality Simulator for Tendon Repair Training: Randomized Controlled Trial. JMIR Serious Games. 2021; 9 (3):e27544.

Chicago/Turabian Style

Tsz-Ngai Mok; Junyuan Chen; Jinghua Pan; Wai-Kit Ming; Qiyu He; Tat-Hang Sin; Jialin Deng; Jieruo Li; Zhengang Zha. 2021. "Use of a Virtual Reality Simulator for Tendon Repair Training: Randomized Controlled Trial." JMIR Serious Games 9, no. 3: e27544.

Journal article
Published: 14 June 2021 in Vaccines
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Objectives: To investigate the differences in vaccine hesitancy and preference of the currently available COVID-19 vaccines between two countries, namely, China and the United States (U.S.). Method: A cross-national survey was conducted in both China and the United States, and discrete choice experiments, as well as Likert scales, were utilized to assess vaccine preference and the underlying factors contributing to vaccination acceptance. Propensity score matching (PSM) was performed to enable a direct comparison between the two countries. Results: A total of 9077 (5375 and 3702 from China and the United States, respectively) respondents completed the survey. After propensity score matching, over 82.0% of respondents from China positively accepted the COVID-19 vaccination, while 72.2% of respondents from the United States positively accepted it. Specifically, only 31.9% of Chinese respondents were recommended by a doctor to have COVID-19 vaccination, while more than half of the U.S. respondents were recommended by a doctor (50.2%), local health board (59.4%), or friends and families (64.8%). The discrete choice experiments revealed that respondents from the United States attached the greatest importance to the efficacy of COVID-19 vaccines (44.41%), followed by the cost of vaccination (29.57%), whereas those from China held a different viewpoint, that the cost of vaccination covered the largest proportion in their trade-off (30.66%), and efficacy ranked as the second most important attribute (26.34%). Additionally, respondents from China tended to be much more concerned about the adverse effect of vaccination (19.68% vs. 6.12%) and have a lower perceived severity of being infected with COVID-19. Conclusion: Although the overall acceptance and hesitancy of COVID-19 vaccination in both countries are high, underpinned distinctions between these countries were observed. Owing to the differences in COVID-19 incidence rates, cultural backgrounds, and the availability of specific COVID-19 vaccines in the two countries, vaccine rollout strategies should be nation-dependent.

ACS Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola Akinwunmi; Babatunde Akinwunmi; Casper Zhang; Yibo Wu; Wai-Kit Ming. A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States. Vaccines 2021, 9, 649 .

AMA Style

Taoran Liu, Zonglin He, Jian Huang, Ni Yan, Qian Chen, Fengqiu Huang, Yuejia Zhang, Omolola Akinwunmi, Babatunde Akinwunmi, Casper Zhang, Yibo Wu, Wai-Kit Ming. A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States. Vaccines. 2021; 9 (6):649.

Chicago/Turabian Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola Akinwunmi; Babatunde Akinwunmi; Casper Zhang; Yibo Wu; Wai-Kit Ming. 2021. "A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States." Vaccines 9, no. 6: 649.

Journal article
Published: 20 May 2021 in Health and Quality of Life Outcomes
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Background With the increase of the number of smokers, tobacco exposure among pregnant women is becoming more and more common. Pregnant women exposed to first-hand smoke and second-hand smoke are susceptible to physiological and psychological health issues has been proved in previous studies. Nevertheless, there are no enough studies focus on the impact of third-hand smoke during pregnancy. This study aimed to assess and compare health-related quality of life for pregnant women with exposure to first-hand smoke, second-hand smoke, third-hand smoke and non-exposure to tobacco in mainland China. Methods National-based cross-sectional study is based on a questionnaire survey which collects information including demographics, smoking behaviors and self-evaluation. All questionnaires were delivered and collected from August to September 2019. EuroQol group’s visual analog scale and EuroQoL Five-dimension Questionnaire were used to collect data in mainland China. Results Totally, 15,682 pregnant women were included in this study, among which non-exposure to smoke were 7564 (48.2%), exposed to first-hand smoke, second-hand smoke and third-hand smoke were 89 (0.6%), 2349 (15.0%), and 5680 (36.2%) respectively. Pregnant women without tobacco exposure had the highest EuroQol group’s visual analog scale score (mean value = 85.4[SD = 14.0]), while those with first-hand smoke had the lowest score (mean value = 77.4[SD = 22.2]). Among all five dimensions of EuroQoL Five-dimension Questionnaire, there were significant differences of EQ-index among groups with different tobacco exposure in usual activity and anxiety or depression dimensions (p < 0.001). Conclusions Third-hand smoke exposure had close relationship with low health-related quality of life in pregnant women. Moreover, second-hand smoke exposure significantly led more problems on mental dimension of pregnant women.

ACS Style

Weiwei Sun; Xinyu Huang; Huailiang Wu; Casper J. P. Zhang; Zongzhi Yin; Qianqian Fan; Huiyun Wang; Pallavi Jayavanth; Babatunde Akinwunmi; Yanxin Wu; Zilian Wang; Wai-Kit Ming. Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China. Health and Quality of Life Outcomes 2021, 19, 1 -9.

AMA Style

Weiwei Sun, Xinyu Huang, Huailiang Wu, Casper J. P. Zhang, Zongzhi Yin, Qianqian Fan, Huiyun Wang, Pallavi Jayavanth, Babatunde Akinwunmi, Yanxin Wu, Zilian Wang, Wai-Kit Ming. Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China. Health and Quality of Life Outcomes. 2021; 19 (1):1-9.

Chicago/Turabian Style

Weiwei Sun; Xinyu Huang; Huailiang Wu; Casper J. P. Zhang; Zongzhi Yin; Qianqian Fan; Huiyun Wang; Pallavi Jayavanth; Babatunde Akinwunmi; Yanxin Wu; Zilian Wang; Wai-Kit Ming. 2021. "Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China." Health and Quality of Life Outcomes 19, no. 1: 1-9.

Journal article
Published: 20 May 2021 in Health and Quality of Life Outcomes
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ACS Style

Weiwei Sun; Xinyu Huang; Huailiang Wu; Casper J P Zhang; Zongzhi Yin; Qianqian Fan; Huiyun Wang; Pallavi Jayavanth; Babatunde Akinwunmi; Yanxin Wu; Zilian Wang; Wai-Kit Ming. Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China. Health and Quality of Life Outcomes 2021, 19, 152 .

AMA Style

Weiwei Sun, Xinyu Huang, Huailiang Wu, Casper J P Zhang, Zongzhi Yin, Qianqian Fan, Huiyun Wang, Pallavi Jayavanth, Babatunde Akinwunmi, Yanxin Wu, Zilian Wang, Wai-Kit Ming. Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China. Health and Quality of Life Outcomes. 2021; 19 (1):152.

Chicago/Turabian Style

Weiwei Sun; Xinyu Huang; Huailiang Wu; Casper J P Zhang; Zongzhi Yin; Qianqian Fan; Huiyun Wang; Pallavi Jayavanth; Babatunde Akinwunmi; Yanxin Wu; Zilian Wang; Wai-Kit Ming. 2021. "Maternal tobacco exposure and health-related quality of life during pregnancy: a national-based study of pregnant women in China." Health and Quality of Life Outcomes 19, no. 1: 152.

Preprint content
Published: 02 May 2021
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Objectives To investigate the differences in vaccine hesitancy and preference of the currently available COVID-19 vaccines between two countries, viz. China and the United States (US). Method A cross-national survey was conducted in both China and the US, and discrete choice experiments as well as Likert scales were utilized to assess vaccine preference and the underlying factors contributing to the vaccination acceptance. A propensity score matching (PSM) was performed to enable a direct comparison between the two countries. Results A total of 9,077 (5,375 and 3,702, respectively, from China and the US) respondents have completed the survey. After propensity score matching, over 82.0% respondents from China positively accept the COVID-19 vaccination, while 72.2% respondents form the US positively accept it. Specifically, only 31.9% of Chinese respondents were recommended by a doctor to have COVID-19 vaccination, while more than half of the US respondents were recommended by a doctor (50.2%), local health board (59.4%), or friends and families (64.8%). The discrete choice experiments revealed that respondents from the US attached the greatest importance to the efficacy of COVID-19 vaccines (44.41%), followed by the cost of vaccination (29.57%), whereas those from China held a different viewpoint that the cost of vaccination covers the largest proportion in their trade-off (30.66%), and efficacy ranked as the second most important attribute (26.34%). Also, respondents from China tend to concerned much more about the adverse effect of vaccination (19.68% vs 6.12%) and have lower perceived severity of being infected with COVID-19. Conclusion While the overall acceptance and hesitancy of COVID-19 vaccination in both countries are high, underpinned distinctions between countries are observed. Owing to the differences in COVID-19 incidence rates, cultural backgrounds, and the availability of specific COVID-19 vaccines in two countries, the vaccine rollout strategies should be nation-dependent.

ACS Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola M Akinwunmi; Babatunde Akinwunmi; Casper J.P Zhang; Yibo Wu; Wai-Kit Ming. The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States. 2021, 1 .

AMA Style

Taoran Liu, Zonglin He, Jian Huang, Ni Yan, Qian Chen, Fengqiu Huang, Yuejia Zhang, Omolola M Akinwunmi, Babatunde Akinwunmi, Casper J.P Zhang, Yibo Wu, Wai-Kit Ming. The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States. . 2021; ():1.

Chicago/Turabian Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola M Akinwunmi; Babatunde Akinwunmi; Casper J.P Zhang; Yibo Wu; Wai-Kit Ming. 2021. "The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States." , no. : 1.

Journal article
Published: 21 April 2021 in Nutrients
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Background: The role of low-carbohydrate ketogenic diet (LCKD) as an adjuvant therapy in antitumor treatment is not well established. This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to investigate the efficacy of LCKD as an adjuvant therapy in antitumor treatment compared to non-ketogenic diet in terms of lipid profile, body weight, fasting glucose level, insulin, and adverse effects; Methods: In this study, databases such as PubMed, Web of Science, Scopus, CINAHL, and Cochrane trials were searched. Only RCTs that involved cancer participants that were assigned to dietary interventions including a LCKD group and a control group (any non-ketogenic dietary intervention) were selected. Three reviewers independently extracted the data, and the meta-analysis was performed using a fixed effects model or random effects model depending on the I2 value or p-value; Results: A total of six articles met the inclusion/exclusion criteria. In the overall analysis, the post-intervention results = standard mean difference, SMD (95% CI) showed total cholesterol (TC) level = 0.25 (−0.17, 0.67), HDL-cholesterol = −0.07 (−0.50, 0.35), LDL-cholesterol = 0.21 (−0.21, 0.63), triglyceride (TG) = 0.09 (−0.33, 0.51), body weight (BW) = −0.34 (−1.33, 0.65), fasting blood glucose (FBG) = −0.40 (−1.23, 0.42) and insulin = 0.11 (−1.33, 1.55). There were three outcomes showing significant results in those in LCKD group: the tumor marker PSA, p = 0.03, the achievement of ketosis p = 0.010, and the level of satisfaction, p = 0.005; Conclusions: There was inadequate evidence to support the beneficial effects of LCKDs on antitumor therapy. More trials comparing LCKD and non-KD with a larger sample size are necessary to give a more conclusive result.

ACS Style

Ya-Feng Yang; Preety Mattamel; Tanya Joseph; Jian Huang; Qian Chen; Babatunde Akinwunmi; Casper Zhang; Wai-Kit Ming. Efficacy of Low-Carbohydrate Ketogenic Diet as an Adjuvant Cancer Therapy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients 2021, 13, 1388 .

AMA Style

Ya-Feng Yang, Preety Mattamel, Tanya Joseph, Jian Huang, Qian Chen, Babatunde Akinwunmi, Casper Zhang, Wai-Kit Ming. Efficacy of Low-Carbohydrate Ketogenic Diet as an Adjuvant Cancer Therapy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2021; 13 (5):1388.

Chicago/Turabian Style

Ya-Feng Yang; Preety Mattamel; Tanya Joseph; Jian Huang; Qian Chen; Babatunde Akinwunmi; Casper Zhang; Wai-Kit Ming. 2021. "Efficacy of Low-Carbohydrate Ketogenic Diet as an Adjuvant Cancer Therapy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials." Nutrients 13, no. 5: 1388.

Preprint content
Published: 18 April 2021
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BACKGROUND Previous researches didn’t explore the influence of smoking before pregnancy on the health-related quality of life (HRQoL)of Chinese pregnant women, which is a big population in the largest developing country in the world and cannot be neglected. OBJECTIVE To evaluate the HRQoL of pregnant women in China with different smoking status and further to estimate the association between pre-pregnancy smoking and HRQoL. METHODS A nationwide-based cross-sectional study was conducted to determine the association between different smoking status (smoking currently, quit smoking, never smoking) and HRQoL in pregnant women across China. A web-based questionnaire was administered during prenatal examinations. EuroQoL Group’s five-dimension (EQ-5D-5L) scale with EuroQoL Group’s visual analog scale (EQ-5D VAS) scale were used for measuring HRQoL. RESULTS A total of 16,811 participants were included in the study. Significant difference in EQ-5D VAS was detected between non-smokers and ex-smokers (P<.001). Among ex-smokers, the proportion of pregnant women who suffer from depression/anxiety is higher compared with non-smokers (P<.001). We found that the increased cigarette consumption before pregnancy could result in lower EQ-5D VAS (P=.04) and EQ-5D index (P=.005) of pregnant women in China. CONCLUSIONS Chinese pregnant women with smoking history tend to have lower HRQoL. Smoking cessation during pregnancy doesn’t not significantly improve the HRQoL of Chinese pregnant women compared to smokers. Compared to non-smokers, ex-smokers are more likely to suffer from depression/anxiety. Among ex-smokers, the more cigarettes the Chinese pregnant women smoked, the lower their HRQoL. We suggest that the Chinese government should strengthen the education of stopping smoking and avoiding second-hand smoke for women who have pregnancy plan and their family members.

ACS Style

Kadi Hu; Shiqian Zou; Casper J. P. Zhang; Huailiang Wu; Babatunde Akinwunmi; Zilian Wang; Wai-Kit Ming. Health-Related Quality of Life Among Pregnant Women with Pre-pregnancy Smoking in China: A National Cross-sectional Study (Preprint). 2021, 1 .

AMA Style

Kadi Hu, Shiqian Zou, Casper J. P. Zhang, Huailiang Wu, Babatunde Akinwunmi, Zilian Wang, Wai-Kit Ming. Health-Related Quality of Life Among Pregnant Women with Pre-pregnancy Smoking in China: A National Cross-sectional Study (Preprint). . 2021; ():1.

Chicago/Turabian Style

Kadi Hu; Shiqian Zou; Casper J. P. Zhang; Huailiang Wu; Babatunde Akinwunmi; Zilian Wang; Wai-Kit Ming. 2021. "Health-Related Quality of Life Among Pregnant Women with Pre-pregnancy Smoking in China: A National Cross-sectional Study (Preprint)." , no. : 1.

Preprint content
Published: 14 April 2021
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Background: Education informatization is still in the early stage in China. The sudden outbreak of the COVID-19 pandemic led medical educators passively incorporating information technology for remote medical teaching, in which challenges and opportunities have co-existed.Objectives: The objectives of this study were to (1) explore the medical educators' perception and experience of online teaching in medical education before and after emergency remote teaching (ERT) experience during the COVID-19 pandemic; (2) illustrate the medical educators' satisfaction on the contribution of online teaching on medical teaching, and (3) reveal the main challenges medical educators met when they conduct the ERT during the COVID-19 epidemic, and to demonstrate whether the challenges are a different by age or gender including some other factors.Methods: A web-based questionnaire was disseminated to the faculty of medical education departments at higher institutions in China. The collected quantitative data of the questionnaire were analyzed by using the SPSS software package. Descriptive statistics were conducted on demographic data and the perception and experience of medical educators before and after the COVID-19 were shown as the frequencies and percentages, while the teachers' opinions on contribution of online teaching on medical education were analyzed by descriptive statistics with means and standard deviations. Multiple response analysis combined with crosstabulation chi-square test was applied, and a P-value <.05 was considered to be statistically significant to exams the relationship between age as well as gender and difficulties met in online teaching respectively.Results: A total of 26 medical educators (65.38%, n=17 female and 34.62%, n=9 male) were valid participants. Total 57.69% (n=15) of them had used web-based teaching before the COVID-19 pandemic, whereas 43.21% (n=11) had not. The agreement level on the teaching effect of online teaching was medium, with a mean value of 2.55 (range from 1-5). The first two difficulties medical teachers came across in online teaching were the web-based instructional design (27%), and the unfamiliarity with web-based teaching tools (25 %). No significant difference in the types of difficulties encountered by different ages (P=0.969) or gender (P = 0.873) in online teaching.Conclusions: The majority of medical educators are open-minded to incorporating online teaching into their teaching practice in the future. However, medical educators in China commonly faced shared difficulties when they adopted online teaching during the COVID-19 pandemic. Identify these challenges and proposing some relevant suggestions to promote a further increase in the active adoption of information technology in medical education.

ACS Style

Meiling Chen; Shiqian Zou; Siyi Wang; Babatunde Akinwunmi; Wai-Kit Ming. COVID-19 Pandemics and Impacts on Medical Educators in China. 2021, 1 .

AMA Style

Meiling Chen, Shiqian Zou, Siyi Wang, Babatunde Akinwunmi, Wai-Kit Ming. COVID-19 Pandemics and Impacts on Medical Educators in China. . 2021; ():1.

Chicago/Turabian Style

Meiling Chen; Shiqian Zou; Siyi Wang; Babatunde Akinwunmi; Wai-Kit Ming. 2021. "COVID-19 Pandemics and Impacts on Medical Educators in China." , no. : 1.

Preprint content
Published: 05 April 2021
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BACKGROUND Hospice care, a type of end-of-life care provided for dying patients and their families, has been rooted in China since the 1980s. It can improve receivers’ quality of life as well as ease their economic burden. The Chinese mass media have continued to actively dispel misconceptions of hospice care and deliver the latest information to citizens. OBJECTIVE This study aimed to retrieve and analyze news reports on hospice care to gain insight into whether any differences exist in delivered heath information as time went by and the role the mass media played in health communication in recent years. METHODS We searched the Huike (WiseSearch) database for related news from Chinese mass media between 2014 and 2019. We set January 1, 2014 to December 31, 2016 as the first time period and January 1, 2017 to December 31, 2019 as the second time period. Python was used to complete the data cleaning process. We determined appropriate topic numbers for these two periods based on coherence score and applied the latent Dirichlet allocation topic modeling. Keywords of each topic and corresponding topics’ names were then generated. The topics were plotted into different circles and their distances on the two-dimensional plane was represented by multidimensional scaling. RESULTS After removing the duplicated and irrelevant news articles, we obtained a total of 2227 articles. We chose eight as the suitable topic number for both time periods and generated topics’ name and their keywords. The top three most reported topics in the first period were patient treatment, hospice care stories, and development of health care services and health insurance, accounting for 18.68% (n = 178), 16.58% (n = 158), and 14.17% (n = 135) of the collected reports, respectively. The top three most reported topics in the second period were hospice care stories, patient treatment, and development of health care services, accounting for 15.62% (n = 199), 15.38 (n = 15.38), and 14.27% (n = 182), respectively. CONCLUSIONS Topic modeling of news reports gives us a better understanding of patterns of health communication about hospice care by mass media. Chinese mass media frequently reported on hospice care in April due to a traditional Chinese festival. An increase in coverage in the second period was observed. These two periods share six similar topics, among which patient treatment outstrips hospice care stories as the most-reported topic in the second period, showing the humanistic spirit behind the reports. We suggest stakeholders cooperate with the mass media when planning to update policies.

ACS Style

Qian Liu; Zequan Zheng; Jingsen Chen; Winghei Tsang; Jin Shan; Yimin Zhang; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. Health Communication for Hospice Care through Chinese media: Digital Topic Modeling Approach (Preprint). 2021, 1 .

AMA Style

Qian Liu, Zequan Zheng, Jingsen Chen, Winghei Tsang, Jin Shan, Yimin Zhang, Babatunde Akinwunmi, Casper Jp Zhang, Wai-Kit Ming. Health Communication for Hospice Care through Chinese media: Digital Topic Modeling Approach (Preprint). . 2021; ():1.

Chicago/Turabian Style

Qian Liu; Zequan Zheng; Jingsen Chen; Winghei Tsang; Jin Shan; Yimin Zhang; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. 2021. "Health Communication for Hospice Care through Chinese media: Digital Topic Modeling Approach (Preprint)." , no. : 1.

Journal article
Published: 05 April 2021 in JMIR Public Health and Surveillance
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ACS Style

Qian Liu; Zequan Zheng; Jingsen Chen; Winghei Tsang; Jin Shan; Yimin Zhang; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. Health Communication for Hospice Care through Chinese Media: Digital Topic Modeling Approach (Preprint). JMIR Public Health and Surveillance 2021, 1 .

AMA Style

Qian Liu, Zequan Zheng, Jingsen Chen, Winghei Tsang, Jin Shan, Yimin Zhang, Babatunde Akinwunmi, Casper Jp Zhang, Wai-Kit Ming. Health Communication for Hospice Care through Chinese Media: Digital Topic Modeling Approach (Preprint). JMIR Public Health and Surveillance. 2021; ():1.

Chicago/Turabian Style

Qian Liu; Zequan Zheng; Jingsen Chen; Winghei Tsang; Jin Shan; Yimin Zhang; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. 2021. "Health Communication for Hospice Care through Chinese Media: Digital Topic Modeling Approach (Preprint)." JMIR Public Health and Surveillance , no. : 1.

Journal article
Published: 24 March 2021 in JMIR Serious Games
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Background The use of virtual reality is popular in clinical rehabilitation, but the effects of using commercial virtual reality games in patients with stroke have been mixed. Objective We developed a depth camera–based, task-specific virtual reality game, Stomp Joy, for poststroke rehabilitation of the lower extremities. This study aims to assess its feasibility and clinical efficacy. Methods We carried out a feasibility test for Stomp Joy within representative user groups. Then, a clinical efficacy experiment was performed with a randomized controlled trial, in which 22 patients with stroke received 10 sessions (2 weeks) of conventional physical therapy only (control group) or conventional physical therapy plus 30 minutes of the Stomp Joy intervention (experimental group) in the clinic. The Fugl-Meyer Assessment for Lower Extremity (FMA-LE), Modified Barthel Index (MBI), Berg Balance Scale (BBS) score, single-leg stance (SLS) time, dropout rate, and adverse effects were recorded. Results This feasibility test showed that Stomp Joy improved interest, pressure, perceived competence, value, and effort using the Intrinsic Motivation Inventory. The clinical efficacy trial showed a significant time-group interaction effect for the FMA-LE (P=.006), MBI (P=.001), BBS (P=.004), and SLS time (P=.001). A significant time effect was found for the FMA-LE (P=.001), MBI (P<.001), BBS (P<.001), and SLS time (P=.03). These indicated an improvement in lower extremity motor ability, basic activities of daily living, balance ability, and single-leg stance time in both groups after 2 weeks of the intervention. However, no significant group effects were found for the FMA-LE (P=.06), MBI (P=.76), and BBS (P=.38), while a significant group interaction was detected for SLS time (P<.001). These results indicated that the experimental group significantly improved more in SLS time than did the control group. During the study, 2 dropouts, including 1 participant who fell, were reported. Conclusions Stomp Joy is an effective depth camera–based virtual reality game for replacing part of conventional physiotherapy, achieving equally effective improvement in lower extremity function among stroke survivors. High-powered randomized controlled studies are now needed before recommending the routine use of Stomp Joy in order to confirm these findings by recruiting a large sample size.

ACS Style

Yangfan Xu; MeiQinzi Tong; Wai-Kit Ming; Yangyang Lin; Wangxiang Mai; Weixin Huang; Zhuoming Chen. A Depth Camera–Based, Task-Specific Virtual Reality Rehabilitation Game for Patients With Stroke: Pilot Usability Study. JMIR Serious Games 2021, 9, e20916 .

AMA Style

Yangfan Xu, MeiQinzi Tong, Wai-Kit Ming, Yangyang Lin, Wangxiang Mai, Weixin Huang, Zhuoming Chen. A Depth Camera–Based, Task-Specific Virtual Reality Rehabilitation Game for Patients With Stroke: Pilot Usability Study. JMIR Serious Games. 2021; 9 (1):e20916.

Chicago/Turabian Style

Yangfan Xu; MeiQinzi Tong; Wai-Kit Ming; Yangyang Lin; Wangxiang Mai; Weixin Huang; Zhuoming Chen. 2021. "A Depth Camera–Based, Task-Specific Virtual Reality Rehabilitation Game for Patients With Stroke: Pilot Usability Study." JMIR Serious Games 9, no. 1: e20916.

Preprint content
Published: 23 March 2021
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UNSTRUCTURED In the integrated management of gestational diabetes mellitus (GDM), health education plays an important role and directly affects patients’ blood glucose level control, pregnancy, and neonatal outcome. The rapid growth of the Internet has ushered in an era of big data and the rational use of the Internet. We developed an innovative mobile application (app) combining a teaching model of the flipped classroom and GDM management, which allows pregnant women to learn about and help prevent GDM. This app can overcome the treatment barriers for those patients that cannot go to the hospital, enhance health promotion efforts, and improve GDM management.

ACS Style

Guanrui Feng; Dexia Huang; Fengqiu Huang; Qian Chen; Juan Gan; Suhan Zhang; Feiling Huang; Nana Liu; Hang Lin; Yongji Li; Liangkun Ma; Wai-Kit Ming. An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint). 2021, 1 .

AMA Style

Guanrui Feng, Dexia Huang, Fengqiu Huang, Qian Chen, Juan Gan, Suhan Zhang, Feiling Huang, Nana Liu, Hang Lin, Yongji Li, Liangkun Ma, Wai-Kit Ming. An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint). . 2021; ():1.

Chicago/Turabian Style

Guanrui Feng; Dexia Huang; Fengqiu Huang; Qian Chen; Juan Gan; Suhan Zhang; Feiling Huang; Nana Liu; Hang Lin; Yongji Li; Liangkun Ma; Wai-Kit Ming. 2021. "An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint)." , no. : 1.

Journal article
Published: 23 March 2021 in JMIR Diabetes
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ACS Style

Guanrui Feng; Tak-Hap Wong; Fengqiu Huang; Qian Chen; Juan Gan; Suhan Zhang; Feiling Huang; Nana Liu; Hang Lin; Yongji Li; Liangkun Ma; Wai-Kit Ming. An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint). JMIR Diabetes 2021, 1 .

AMA Style

Guanrui Feng, Tak-Hap Wong, Fengqiu Huang, Qian Chen, Juan Gan, Suhan Zhang, Feiling Huang, Nana Liu, Hang Lin, Yongji Li, Liangkun Ma, Wai-Kit Ming. An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint). JMIR Diabetes. 2021; ():1.

Chicago/Turabian Style

Guanrui Feng; Tak-Hap Wong; Fengqiu Huang; Qian Chen; Juan Gan; Suhan Zhang; Feiling Huang; Nana Liu; Hang Lin; Yongji Li; Liangkun Ma; Wai-Kit Ming. 2021. "An innovative mobile application for gestational diabetes health education during the COVID-19 pandemic (Preprint)." JMIR Diabetes , no. : 1.

Journal article
Published: 02 March 2021 in Journal of Medical Internet Research
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Background Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people’s preferences for AI clinicians and traditional clinicians are worth exploring. Objective We aimed to quantify and compare people’s preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people’s preferences were affected by the pressure of pandemic. Methods We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people’s preferences for different diagnosis methods. Results In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. Conclusions Individuals’ preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

ACS Style

Taoran Liu; Winghei Tsang; Yifei Xie; Kang Tian; Fengqiu Huang; Yanhui Chen; Oiying Lau; Guanrui Feng; Jianhao Du; Bojia Chu; Tingyu Shi; Junjie Zhao; Yiming Cai; Xueyan Hu; Babatunde Akinwunmi; Jian Huang; Casper J P Zhang; Wai-Kit Ming. Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study. Journal of Medical Internet Research 2021, 23, e26997 .

AMA Style

Taoran Liu, Winghei Tsang, Yifei Xie, Kang Tian, Fengqiu Huang, Yanhui Chen, Oiying Lau, Guanrui Feng, Jianhao Du, Bojia Chu, Tingyu Shi, Junjie Zhao, Yiming Cai, Xueyan Hu, Babatunde Akinwunmi, Jian Huang, Casper J P Zhang, Wai-Kit Ming. Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study. Journal of Medical Internet Research. 2021; 23 (3):e26997.

Chicago/Turabian Style

Taoran Liu; Winghei Tsang; Yifei Xie; Kang Tian; Fengqiu Huang; Yanhui Chen; Oiying Lau; Guanrui Feng; Jianhao Du; Bojia Chu; Tingyu Shi; Junjie Zhao; Yiming Cai; Xueyan Hu; Babatunde Akinwunmi; Jian Huang; Casper J P Zhang; Wai-Kit Ming. 2021. "Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study." Journal of Medical Internet Research 23, no. 3: e26997.

Journal article
Published: 23 February 2021 in Journal of Medical Internet Research
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Background Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. Objective This study aims to visualize and measure patients’ heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. Methods A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables’ coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. Results A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis “accuracy” attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. Conclusions Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People’s preferences for the “accuracy” and “diagnostic expenses” attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

ACS Style

Taoran Liu; Winghei Tsang; Fengqiu Huang; Oi Ying Lau; Yanhui Chen; Jie Sheng; Yiwei Guo; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment. Journal of Medical Internet Research 2021, 23, e22841 .

AMA Style

Taoran Liu, Winghei Tsang, Fengqiu Huang, Oi Ying Lau, Yanhui Chen, Jie Sheng, Yiwei Guo, Babatunde Akinwunmi, Casper Jp Zhang, Wai-Kit Ming. Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment. Journal of Medical Internet Research. 2021; 23 (2):e22841.

Chicago/Turabian Style

Taoran Liu; Winghei Tsang; Fengqiu Huang; Oi Ying Lau; Yanhui Chen; Jie Sheng; Yiwei Guo; Babatunde Akinwunmi; Casper Jp Zhang; Wai-Kit Ming. 2021. "Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment." Journal of Medical Internet Research 23, no. 2: e22841.

Review
Published: 10 February 2021 in BMJ Open
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Objective To determine the effects of the intraocular injection of antivascular endothelial growth factor (anti-VEGF) drugs on the refractive status of infants with retinopathy of prematurity (ROP). Design Systematic review and meta-analysis of the refractive status of infants with ROP who receive anti-VEGF drugs. Data sources The PubMed, Web of Science and Embase databases and the ClinicalTrials.gov website were searched up to June 2020. Eligibility criteria when selecting studies We included randomised controlled trials (RCTs) and observational studies that compared refractive errors between anti-VEGF drug and laser therapies. Data extraction and synthesis Data extraction and risk-of-bias assessments were conducted by two independent reviewers. We used a random-effect model to pool outcomes. The outcome measures were the spherical equivalents, axial length (AL), anterior chamber depth (ACD) and lens thickness (LT). Results Thirteen studies involving 1850 eyes were assessed: 914 in the anti-VEGF drug group, and 936 in the control (laser) group. Children who received anti-VEGF drug treatment had less myopia than those who received laser therapy (mean difference=1.80 D, 95% CI 0.97 to 2.63, p<0.0001, I2=78%). The AL, ACD and LT did not reach statistical significance difference between the two groups. The current evidence indicates that the refractive safety in children with ROP is better for anti-VEGF drug treatment than for laser therapy. Conclusions This meta-analysis indicates that anti-VEGF drug therapy results in less myopia compared with laser therapy. However, there are relatively few published articles on refractive errors in ROP, and so high-quality and powerful RCTs are needed in the future. PROSPERO registration number CRD42020160673.

ACS Style

Qihang Kong; Wai-Kit Ming; Xue-Song Mi. Refractive outcomes after intravitreal injection of antivascular endothelial growth factor versus laser photocoagulation for retinopathy of prematurity: a meta-analysis. BMJ Open 2021, 11, e042384 .

AMA Style

Qihang Kong, Wai-Kit Ming, Xue-Song Mi. Refractive outcomes after intravitreal injection of antivascular endothelial growth factor versus laser photocoagulation for retinopathy of prematurity: a meta-analysis. BMJ Open. 2021; 11 (2):e042384.

Chicago/Turabian Style

Qihang Kong; Wai-Kit Ming; Xue-Song Mi. 2021. "Refractive outcomes after intravitreal injection of antivascular endothelial growth factor versus laser photocoagulation for retinopathy of prematurity: a meta-analysis." BMJ Open 11, no. 2: e042384.

Preprint content
Published: 30 January 2021
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BACKGROUND The use of virtual reality (VR) simulators in medical schools has become widespread to train medical students and residents. The students using VR simulators are provided with a three-dimensional human model to observe human details using multiple senses and can participate in an environment relatively close to the reality. This paper promotes a new approach consisting of a sharing and independent study platform for medical orthopedics students. OBJECTIVE This study compared traditional tendon repair training and VR simulation of tendon repair and evaluated future applications of VR simulation in the medical academic field. METHODS One-hundred twenty-one participants were allocated into the VR and control groups. The participants in the VR group were studying the tendon repair technique via the VR simulator; while the control group followed traditional tendon suture teaching methods. RESULTS A total of 117 participants finished the assessment, and four participants were lost during follow-up. The overall performance (a total 35 score) for the VR group using the “Kessler tendon repair with 2 interrupted tendon repair knots” method was significantly higher score (P <.001) than the control group (24.13 ± 1.71 versus 20.38 ± 1.21). Moreover, for the “Bunnell tendon repair with figure 8 tendon repair” method, the VR group also had a significantly better result (P < .001) than the control group (22.8 ± 1.81 versus 19.9 ± 2.27). The participants using the VR simulator training had a significantly higher score than those using the traditional training method. CONCLUSIONS Use of the VR simulator for learning the tendon suture produced a significant improvement in the time in motion, suture skill, flow of operation, and knowledge of procedure for medical students than using traditional tendon suture method. Therefore, future VR simulator development would likely be beneficial for medical education and clinical practice.

ACS Style

Mok Tsz Ngai; Layla Li; Junyuan Chen; Wai-Kit Ming; Qiyu He; Tat Hang Sin; Jialin Deng; Shinning Yu; Jinghua Pan; Jieruo Li; Zhengang Zha. The New Approach for Tendon Repair Training: Virtual Reality Simulator (Preprint). 2021, 1 .

AMA Style

Mok Tsz Ngai, Layla Li, Junyuan Chen, Wai-Kit Ming, Qiyu He, Tat Hang Sin, Jialin Deng, Shinning Yu, Jinghua Pan, Jieruo Li, Zhengang Zha. The New Approach for Tendon Repair Training: Virtual Reality Simulator (Preprint). . 2021; ():1.

Chicago/Turabian Style

Mok Tsz Ngai; Layla Li; Junyuan Chen; Wai-Kit Ming; Qiyu He; Tat Hang Sin; Jialin Deng; Shinning Yu; Jinghua Pan; Jieruo Li; Zhengang Zha. 2021. "The New Approach for Tendon Repair Training: Virtual Reality Simulator (Preprint)." , no. : 1.

Journal article
Published: 25 January 2021 in JMIR Public Health and Surveillance
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Background The influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated. Objective This study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities. Methods Pearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. Results The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=–0.565, P<.001), Shanghai (r=–0.47, P<.001), and Guangzhou (r=–0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model. Conclusions The findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

ACS Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis. JMIR Public Health and Surveillance 2021, 7, e20495 .

AMA Style

Zonglin He, Yiqiao Chin, Shinning Yu, Jian Huang, Casper J P Zhang, Ke Zhu, Nima Azarakhsh, Jie Sheng, Yi He, Pallavi Jayavanth, Qian Liu, Babatunde O Akinwunmi, Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis. JMIR Public Health and Surveillance. 2021; 7 (1):e20495.

Chicago/Turabian Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. 2021. "The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis." JMIR Public Health and Surveillance 7, no. 1: e20495.

Preprint content
Published: 07 January 2021
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BACKGROUND Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people’s preferences for AI clinicians and traditional clinicians are worth exploring. OBJECTIVE We aimed to quantify and compare people’s preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people’s preferences were affected by the pressure of pandemic. METHODS We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people’s preferences for different diagnosis methods. RESULTS In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. CONCLUSIONS Individuals’ preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

ACS Style

Taoran Liu; Winghei Tsang; Yifei Xie; Kang Tian; Fengqiu Huang; Yanhui Chen; Oiying Lau; Guanrui Feng; Jianhao Du; Bojia Chu; Tingyu Shi; Junjie Zhao; Yiming Cai; Xueyan Hu; Babatunde Akinwunmi; Jian Huang; Casper J P Zhang; Wai-Kit Ming. Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study (Preprint). 2021, 1 .

AMA Style

Taoran Liu, Winghei Tsang, Yifei Xie, Kang Tian, Fengqiu Huang, Yanhui Chen, Oiying Lau, Guanrui Feng, Jianhao Du, Bojia Chu, Tingyu Shi, Junjie Zhao, Yiming Cai, Xueyan Hu, Babatunde Akinwunmi, Jian Huang, Casper J P Zhang, Wai-Kit Ming. Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study (Preprint). . 2021; ():1.

Chicago/Turabian Style

Taoran Liu; Winghei Tsang; Yifei Xie; Kang Tian; Fengqiu Huang; Yanhui Chen; Oiying Lau; Guanrui Feng; Jianhao Du; Bojia Chu; Tingyu Shi; Junjie Zhao; Yiming Cai; Xueyan Hu; Babatunde Akinwunmi; Jian Huang; Casper J P Zhang; Wai-Kit Ming. 2021. "Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study (Preprint)." , no. : 1.