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Global Health care Professionals’ Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study

Global Health care Professionals’ Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study

Additionally, little is known regarding global health care professionals’ perspectives and the extent and impact of Chat GPT’s integration in health care settings [11,12]. Most studies to date, have been limited to localized settings or specific subgroups. Yet, successful and ethical integration of Chat GPT into health care workflows depends heavily on end-user acceptance, awareness of limitations, and perceptions regarding safety, usability, and value [5-7].

Ecem Ozkan, Aysun Tekin, Mahmut Can Ozkan, Daniel Cabrera, Alexander Niven, Yue Dong

JMIR Med Educ 2025;11:e58801

The Association Between Cultural Tightness and COVID-19 Vaccine Confidence From 28 Countries: Cross-Sectional Study

The Association Between Cultural Tightness and COVID-19 Vaccine Confidence From 28 Countries: Cross-Sectional Study

The WHO has identified vaccine hesitancy as one of the ten greatest threats to global health [3], and COVID-19 vaccine hesitancy has attracted a lot of attention [4,5]. The acceptance of COVID-19 vaccination varied across countries: among 23 countries in a global survey, the COVID-19 vaccine acceptance rate ranged between 51.6% (Russia) and 97.6% (China) [5].

Qiang Wang, Ana Bolio, Leesa Lin

JMIR Public Health Surveill 2025;11:e66872

Lessons From a Rapid Project Management Exercise in the Time of Pandemic: Methodology for a Global COVID-19 VIRUS Registry Database

Lessons From a Rapid Project Management Exercise in the Time of Pandemic: Methodology for a Global COVID-19 VIRUS Registry Database

The recognition for the necessity of conception of a COVID-19 global critical care database rapidly developed with the growing crisis hospitals experienced from the spread of the disease [4,5]. This would allow for near real-time data collection, analysis, and display. The design of the registry would be consistent with data analytic requirements [4,5].

Janice R Turek, Vikas Bansal, Aysun Tekin, Shuchita Singh, Neha Deo, Mayank Sharma, Marija Bogojevic, Shahraz Qamar, Romil Singh, Vishakha Kumar, Rahul Kashyap

JMIR Res Protoc 2022;11(3):e27921

Factors Associated With Psychological Disturbances During the COVID-19 Pandemic: Multicountry Online Study

Factors Associated With Psychological Disturbances During the COVID-19 Pandemic: Multicountry Online Study

The emergence of novel SARS-Co V-2 in December 2019 and the global spread of COVID-19 have become the most severe and publicized human crises in recent history. As of June 29, 2021, the global burden of COVID-19 has exceeded 180 million cases worldwide [1]. The impact of COVID-19 on mental health has recently emerged as a matter of enormous concern [2].

Martyna Plomecka, Susanna Gobbi, Rachael Neckels, Piotr Radzinski, Beata Skorko, Samuel Lazzeri, Kristina Almazidou, Alisa Dedic, Asja Bakalovic, Lejla Hrustic, Zainab Ashraf, Sarvin Es Haghi, Luis Rodriguez-Pino, Verena Waller, Hafsa Jabeen, A Beyza Alp, Mehdi Behnam, Dana Shibli, Zofia Baranczuk-Turska, Ali Jawaid, Salah Qureshi, Adriana M Strutt, Ali Jawaid

JMIR Ment Health 2021;8(8):e28736

The Global Infectious Diseases Epidemic Information Monitoring System: Development and Usability Study of an Effective Tool for Travel Health Management in China

The Global Infectious Diseases Epidemic Information Monitoring System: Development and Usability Study of an Effective Tool for Travel Health Management in China

For these purposes, we developed the GIDEIMS to provide a simple, effective, and sustainable tool for obtaining information on global human infectious disease epidemics. Websites used in the Global Infectious Diseases Epidemic Information Monitoring System.

Dayong Gu, Jianan He, Jie Sun, Xin Shi, Ying Ye, Zishuai Zhang, Xiangjun Wang, Qun Su, Wenjin Yu, Xiaopeng Yuan, Ruiling Dong

JMIR Public Health Surveill 2021;7(2):e24204

Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis

Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis

This study analyzes the global trends, patterns, and development of interdisciplinary landscapes in AI and cancer studies. We searched and retrieved all papers related to AI in cancer care on the Web of Science (WOS) that is a Web-based database covering the largest proportion of peer-reviewed literature in this field. The full search strategy has been presented elsewhere [2].

Bach Xuan Tran, Carl A Latkin, Noha Sharafeldin, Katherina Nguyen, Giang Thu Vu, Wilson W S Tam, Ngai-Man Cheung, Huong Lan Thi Nguyen, Cyrus S H Ho, Roger C M Ho

JMIR Med Inform 2019;7(4):e14401

Perspectives From Authors and Editors in the Biomedical Disciplines on Predatory Journals: Survey Study

Perspectives From Authors and Editors in the Biomedical Disciplines on Predatory Journals: Survey Study

Authors and editors represented a global academic community (see Figure 2). Of all articles selected, 40.03% (544/1359) had corresponding authors from high-income countries, as defined by the World Bank [20]. The overall survey response rate was 13.0%, with editor response rates significantly lower than those for authors (6.5% vs 18.9%, respectively, P Responding authors had a median age of 43 years (IQR 33-54), with 47.0% (95/202) reporting that they had been in practice for over 15 years (see Table 1).

Andrew J Cohen, German Patino, Puneet Kamal, Medina Ndoye, Anas Tresh, Jorge Mena, Christi Butler, Samuel Washington, Benjamin N Breyer

J Med Internet Res 2019;21(8):e13769