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JMIR Publications
Content Update Alert, Friday 17th March 2023
RECENTLY PUBLISHED
DIGITAL-ASSISTED SELF-INTERVIEW OF HIV OR SEXUALLY TRANSMITTED INFECTION RISK BEHAVIORS IN TRANSMASCULINE ADULTS: DEVELOPMENT AND
FIELD TESTING OF THE TRANSMASCULINE SEXUAL HEALTH ASSESSMENT
Sari L Reisner, David R Pletta, Dana J Pardee, Madeline B Deutsch, Sarah M Peitzmeier, Jaclyn MW Hughto, Meg Quint, Jennifer
Potter
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JMIR Public Health Surveill 2023 (Mar 17); 9(1):e40503
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Background: The sexual health of transmasculine (TM) people—those who identify as male, men, or nonbinary and were assigned a
female sex at birth—is understudied. One barrier to conducting HIV- and sexually transmitted infection (STI)–related research with
this population is how to best capture sexual risk data in an acceptable, gender-affirming, and accurate manner.
Objective: This study aimed to report on the community-based process of developing, piloting, and refining a digitally deployed
measure to assess self-reported sexual behaviors associated with HIV and STI transmission for research with TM adults...
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ELECTRONIC HEALTH RECORD–BASED ABSOLUTE RISK PREDICTION MODEL FOR ESOPHAGEAL CANCER IN THE CHINESE POPULATION: MODEL DEVELOPMENT
AND EXTERNAL VALIDATION
Yuting Han, Xia Zhu, Yizhen Hu, Canqing Yu, Yu Guo, Dong Hang, Yuanjie Pang, Pei Pei, Hongxia Ma, Dianjianyi Sun, Ling Yang,
Yiping Chen, Huaidong Du, Min Yu, Junshi Chen, Zhengming Chen, Dezheng Huo, Guangfu Jin, Jun Lv, Zhibin Hu, Hongbing Shen, Liming
Li
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License: Licensed by JMIR. B o R
JMIR Public Health Surveill 2023 (Mar 15); 9(1):e43725
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Background: China has the largest burden of esophageal cancer (EC). Prediction models can be used to identify high-risk
individuals for intensive lifestyle interventions and endoscopy screening. However, the current prediction models are limited by
small sample size and a lack of external validation, and none of them can be embedded into the booming electronic health records
(EHRs) in China.
Objective: This study aims to develop and validate absolute risk prediction models for EC in the Chinese population. In
particular, we assessed whether models that contain only EHR-available predictors performed well...
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THE BIDIRECTIONAL ASSOCIATION BETWEEN COGNITIVE FUNCTION AND GAIT SPEED IN CHINESE OLDER ADULTS: LONGITUDINAL OBSERVATIONAL STUDY
Haibin Li, Jiajia Zhang, Xinye Zou, Xiuqin Jia, Deqiang Zheng, Xiuhua Guo, Wuxiang Xie, Qi Yang
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License: Licensed by JMIR.
JMIR Public Health Surveill 2023 (Mar 14); 9(1):e44274
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Background: Cognitive and gait speed decline are common conditions in older adults and are often associated with future adverse
consequences. Although an association between cognitive function and gait speed has been demonstrated, its temporal sequence
remains unclear, especially in older Chinese adults. Clarifying this could help identify interventions to improve public health in
older adults.
Objective: This study aims to examine the longitudinal reciprocal association between gait speed and cognitive function and the
possible temporal sequence of changes in both factors in a national longitudinal cohort...
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DISPARITY IN LUNG CANCER SCREENING AMONG SMOKERS AND NONSMOKERS IN CHINA: PROSPECTIVE COHORT STUDY
Le Wang, Youqing Wang, Fei Wang, Yumeng Gao, Zhimei Fang, Weiwei Gong, Huizhang Li, Chen Zhu, Yaoyao Chen, Lei Shi, Lingbin Du, Ni
Li
Participant taking an LDCT screening examination. Source: Image created by the authors; Copyright: The Authors; URL:
JMIR Public Health Surveill 2023 (Mar 14); 9(1):e43586
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Background: Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality in smokers; however, the
evidence in nonsmokers is scarce.
Objective: This study aimed to evaluate the participant rate and effectiveness of one-off LDCT screening for lung cancer among
smokers and nonsmokers...
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PERITONEAL DIALYSIS CARE IN MAINLAND CHINA: NATIONWIDE SURVEY
Ping Li, Xueying Cao, Weicen Liu, Delong Zhao, Sai Pan, Xuefeng Sun, Guangyan Cai, Jianhui Zhou, Xiangmei Chen
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JMIR Public Health Surveill 2023 (Mar 14); 9(1):e39568
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Background: Peritoneal dialysis (PD) care in mainland China has been progressing in the past 10 years.
Objective: To complement information from the dialysis registry, a large-scale nationwide survey was conducted to investigate the
current infrastructure and management of PD care at hospitals of different tiers...
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LATEST ANNOUNCEMENTS
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JMIR Publications to Showcase Top Public Health Journals at APHA 2022 Expo
Visit JMIR Publication Staff and Journal EiC’s at Booth #145 in Boston, MA November 6-9.JMIR Publications is excited to be
exhibiting at this year's APHA (American Public Health Association) Annual Meeting & Expo.APHA 2022 Annual Meeting & Expo will be
held at the Boston Convention & Exhibition Center in Boston, MA from November 6-8 where the APHA will be celebrating its 150th
anniversary and the theme of “150 Years of Creating the Healthiest Nation: Leading the Path Toward Equity.”Join JMIR Publications
at Booth #145 to meet with us and learn about our public health focused journals, including JMIR Public Health and Surveillance
(Impact Factor 15.56) and JMIR Infodemiology. JMIR Publications staff on hand will include David Kim, Director of Partnerships and
Open Access Research and Stephanie Savu, Managing Editor. Throughout the expo we will also have many of our editors and editorial
board members from our 30+ journals stopping by.Stop by...
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JMIR Public Health and Surveillance Receives Impact Factor of 14.56
(Toronto, June 28, 2022) JMIR Publications today announced that JMIR Public Health and Surveillance has received an Impact Factor
of 14.56 in Clarivate’s 2022 Journal Citation Report. This is a 254% increase on the 2021 score. The journal sits within the first
quartile (Q1) of the Public, Environmental & Occupational Health category in both the Social Sciences Citation Index (SSCI) and
Science Citation Index Expanded (SCIE). The journal's inclusion in the Web of Science is the culmination of the incredible work of
our editors and reviewers, and the generous submission of impactful papers on the part of our authors in such a short timeframe.
JMIR Public Health and Surveillance launched in 2015, and received its first Impact Factor in 2021.Notably, the flagship
journal, Journal of Medical Internet Research, increased 30%+ to a 2022 IF of 7.08 and continues to retain its historical position
in the first quartile of both the ‘Medical Informatics’...
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JMIR Public Health and Surveillance Now Indexed in CABI’s Global Health Database
JMIR Publications is pleased to announce that JMIR Public Health and Surveillance has been accepted and now indexed in CABI’s
Global Health database dedicated to public health research and practice.Additional JMIR Publications’ journals indexed in CABI’s
Global Health database include: Journal of Medical Internet Research, JMIR mHealth and uHealth, JMIR Mental Health and JMIR
Dermatology. To review all JMIR Publication journals included in CABI’s Global Health database, click here.About CABICAB Direct
incorporating the leading bibliographic databases CAB Abstracts and Global Health. CAB Direct provides a convenient, single point
of access to all of your CABI database subscriptions. Facebook Twitter
LATEST SUBMISSIONS OPEN TO PEER REVIEW
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Forecasting Artificial Intelligence Trends in Healthcare: An International Patent Analysis
Bertalan Meskó, Stan Benjamens, Pranavsingh Dhunnoo, Márton Görög
Date Submitted: Mar 14, 2023
Open Peer Review Period: Mar 14, 2023 - May 09, 2023
Background:
Background: Artificial intelligence (AI)/machine learning (ML)-based medical devices and algorithms are rapidly changing the
medical field. To provide an insight into the trends in AI and ML in healthcare, we conducted an international patent analysis.
Objective: -
Methods:
Methods: A systematic patent analysis, focusing on AI/ML-based patents in healthcare, was performed using the Espacenet database
(from 01-2012 until 07-2022). This database includes patents from the China National Intellectual Property Administration (CNIPA),
European Patent Office (EPO), Japan Patent Office (JPO), Korean Intellectual Property Office (KIPO), United States Patent and
Trademark Office (USPTO).
Results:
Results: We identified 10967 patents: 7332 (66.9%) from CNIPA, 191 (1.7%) from EPO, 163 (1.5%) from JPO, 513 (4.7%) from KIPO and
2768 (25.2%) from USPTO. The number of published patents showed a yearly doubling from 2015 until 2021. Five international
companies had the greatest impact on this increase: Ping An Medical and Healthcare Management with 568 (5.2%) patents, Siemens
Healthineers with 273 (2.5%), IBM with 226 (2.1%), Philips Healthcare with 150 (1.4%) and Shanghai United Imaging Healthcare with
144 (1.3%).
Conclusions:
Conclusion: This international patent analysis showed a linear increase in patents published by the five largest patent offices.
An open access database with interactive search options was launched for AI/ML-based patents in healthcare.
Results:
Results: We identified 10967 patents: 7332 (66.9%) from CNIPA, 191 (1.7%) from EPO, 163 (1.5%) from JPO, 513 (4.7%) from KIPO and
2768 (25.2%) from USPTO. The number of published patents showed a yearly doubling from 2015 until 2021. Five international
companies had the greatest impact on this increase: Ping An Medical and Healthcare Management with 568 (5.2%) patents, Siemens
Healthineers with 273 (2.5%), IBM with 226 (2.1%), Philips Healthcare with 150 (1.4%) and Shanghai United Imaging Healthcare with
144 (1.3%).
Conclusions:
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Mapping the evidence on the impact of mHealth interventions on patient-reported outcomes in breast cancer patients: A systematic
review
Santiago Frid, Clara Amat Fernández, Ángeles Fuentes Expósito, Monsterrat Muñoz Mateu, Antonis Velachis, Antoni Sisó-Almirall,
Immaculada Grau-Corral
Date Submitted: Mar 13, 2023
Open Peer Review Period: Mar 13, 2023 - May 08, 2023
Background: The field of mHealth has grown exponentially in the last decade due to the widespread use of smartphones and the
advancements in mobile technology, which has created opportunities to find solutions to unmet healthcare needs for patients with
chronic diseases. Furthermore, healthcare is entering a new value-based paradigm, founded on three main pillars: efficiency,
safety, and value for patients.
Objective: The objective of this review is to summarize the current knowledge on the impact of mHealth on patient-reported
outcomes in breast cancer (BC) patients.
Methods: Three databases were systematically searched to identify studies that met eligibility criteria: PubMed, PsychInfo, and
Google Scholar. Relevant systematic reviews and the references of the research articles they contained were also searched in case
that studies were missed during the initial search. Searches were made on December 17th, 2021. Two investigators independently
reviewed the titles and abstracts of the identified studies and then read the full text of all selected papers. In case a
discrepancy was found, It was discussed with a third investigator in order to make a final decision. The quality of the included
studies was analyzed by the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies.
Results: Twenty-two unique studies involving 3,502 patients were included. The focus of the interventions in the studies included
in the review were physical activity (11 studies), tailored information for better self-management of the disease (8 studies),
mental health therapies (6 studies), symptom tracker (4 studies), and others (6 studies). All interventions were at least 8 weeks
long of duration, with a median duration of 12 weeks (interquartile range 4-18 weeks). mHealth interventions showed better results
on symptom burden, fatigue, quality of life and physical activity. Likewise, tailored information, symptom tracker, nutrition and
physical activity were the interventions that yielded better results. Apps with interactive support had a higher rate of positive
findings, while interventions targeted to survivors showed worse results.
Conclusions: mHealth applications in BC patients is a highly heterogeneous field. Our study suggests that interventions focused on
newly diagnosed patients or patients while on chemotherapy, interventions with interactive human support and those with a duration
of 12 weeks or more showed better results in terms of patient-reported outcome. Interventions must be adapted to each patient’s
characteristics and disease stage to meet their specific needs at the time of deployment. Positive impact on endpoints show what
can be achieved with the right mHealth intervention. The reproducibility of the studies reporting mHealth interventions is
currently uncertain.
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Large Language Models in Surgical Education: Do they Reach Human Level on Fundamentals of Robotic Surgery Test?
Andrea Moglia, Konstantinos Georgiou, Richard Satava, Alfred Cuschieri
Date Submitted: Mar 13, 2023
Open Peer Review Period: Mar 13, 2023 - May 08, 2023
Background: Large language models are capable of answering questions as if they were engaged in active conversation with users.
However, currently, there are no data on whether their performances will remain static or vary over time when answering questions
in the medical domain.
Objective: The aim of the present study was to assess ChatGPT and InstructGPT on multiple trials on the Fundamentals of Robotic
Surgery (FRS) test. Additionally, different releases of ChatGPT were compared to establish whether its performance improved after
retraining.
Methods: We tested the performance of ChatGPT and InstructGPT on the 44 multiple choice questions of FRS didactic test, for which
a pass mark requires 35 correct answers (79.5%). Seven attempts were performed using ChatGPT on the January 30, 2023 release and
seven with the February 13, 2023 version. Three trials were performed with InstructGPT.
Results: ChatGPT achieved a mean score of 64.6% and 65.6% respectively for the first and second release, without any significant
difference between the two (p = 0.32). The score ranged from 54.5% to 72.7% with both versions. On baseline it achieved 54.5% in
both releases, higher than InstructGPT (50.0%). The highest rate of correct answers of ChatGPT was observed for questions on team
training and communication (77.5% with both releases), followed by those on the introduction of the robotic system (67.5% and 62.7
% respectively for the first and second versions), psychomotor skills (64.3% and 57.1%), and naming correctly clinical steps of a
procedure of robot-assisted surgery (53.8% and 65.9%).
Conclusions: Even though ChatGPT did not pass FRS test in any of the 14 trials, the 72.7% score observed by the present study
represents a remarkable result, taking into consideration the generic nature of ChatGPT as distinct from a domain specific LLM.
This level represents the highest score by ChatGPT in a high-stake examination in medicine.
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