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Effects of a Monophasic Hormonal Contraceptive With Norgestimate+Ethinyl Estradiol on Menstrual Bleeding: Protocol and Design of a Multicenter, Prospective, Open-Label, Noncomparative Study in Italy

Effects of a Monophasic Hormonal Contraceptive With Norgestimate+Ethinyl Estradiol on Menstrual Bleeding: Protocol and Design of a Multicenter, Prospective, Open-Label, Noncomparative Study in Italy

Combined oral contraceptives (COCs) are the most commonly prescribed form of hormonal contraception in Italy and in other European countries [1]. These contraceptive pills contain a combination of estrogen and progestin to suppress ovulation (the primary contraceptive effect) and to change endometrial and cervical secretions, hindering the passage of sperm [2]. COCs may be monophasic or multiphasic.

Angelo Cagnacci, Giovanni Grandi, Giampiero Capobianco, Anna Maria Fulghesu, Giuseppe Morgante, Vincenzo Biondelli, Elena Piccolo, Elena Casolati, Mario Mangrella

JMIR Res Protoc 2025;14:e63683

Cross-Cultural Sense-Making of Global Health Crises: A Text Mining Study of Public Opinions on Social Media Related to the COVID-19 Pandemic in Developed and Developing Economies

Cross-Cultural Sense-Making of Global Health Crises: A Text Mining Study of Public Opinions on Social Media Related to the COVID-19 Pandemic in Developed and Developing Economies

In order to contextualize the developmental differences between Egypt, Italy, and the United Kingdom, we made reference to the Human Capital Index [13]. This is a quantitative measure of development based on health and education outcomes. According to this index, Italy scores 0.73, the United Kingdom 0.78, and Egypt 0.49. The index highlights how there is a substantial developmental gap between Italy and Egypt (0.73 vs 0.49) compared to the gap between Italy and the United Kingdom (0.73 vs 0.78).

Adham Kahlawi, Firas Masri, Wasim Ahmed, Josep Vidal-Alaball

J Med Internet Res 2025;27:e58656

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data

Italy was among the countries hardest hit by the COVID-19 pandemic, with Piedmont, a region in the northwest, experiencing a high number of cases during the first wave. Multimorbidity refers to the presence of multiple coexisting medical conditions in a patient, which interact with each other, resulting in a complex and multidimensional health condition [1].

Dayana Benny, Mario Giacobini, Alberto Catalano, Giuseppe Costa, Roberto Gnavi, Fulvio Ricceri

JMIR Public Health Surveill 2024;10:e52353

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Europe: Longitudinal Trend Analysis

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Europe: Longitudinal Trend Analysis

We adopt the World Bank’s definition of Europe, which is based on economic development and geographical proximity, encompassing Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Greenland, Hungary, Iceland, Ireland, the Isle of Man, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Moldova, Monaco, Montenegro, the Netherlands, Norway, Poland, Portugal, Romania, San Marino, Serbia, Slovakia, Slovenia

Alexander L Lundberg, Scott A Wu, Alan G Soetikno, Claudia Hawkins, Robert L Murphy, Robert J Havey, Egon A Ozer, Charles B Moss, Sarah B Welch, Maryann Mason, Yingxuan Liu, Lori A Post

JMIR Public Health Surveill 2024;10:e53551

Community-Dwelling Older Adults’ Readiness for Adopting Digital Health Technologies: Cross-Sectional Survey Study

Community-Dwelling Older Adults’ Readiness for Adopting Digital Health Technologies: Cross-Sectional Survey Study

In Italy, a potential digital health gap among older adults due to infrastructural issues and the lack of digital skills have been described, with differences between age groups and educational levels [13]. In a cross-sectional survey study, less than half of the 1002 respondents were aware of telemedicine services in their region [14].

Dietmar Ausserhofer, Giuliano Piccoliori, Adolf Engl, Angelika Mahlknecht, Barbara Plagg, Verena Barbieri, Nicoletta Colletti, Stefano Lombardo, Timon Gärtner, Waltraud Tappeiner, Heike Wieser, Christian Josef Wiedermann

JMIR Form Res 2024;8:e54120

The Use of ICD-9-CM Coding to Identify COVID-19 Diagnoses and Determine Risk Factors for 30-Day Death Rate in Hospitalized Patients in Italy: Retrospective Study

The Use of ICD-9-CM Coding to Identify COVID-19 Diagnoses and Determine Risk Factors for 30-Day Death Rate in Hospitalized Patients in Italy: Retrospective Study

In Italy, despite early data provided by the COVID-19 Integrated Surveillance System [11], it has been difficult to accurately quantify hospital admissions of patients with a COVID-19 diagnosis using the Hospital Information System (HIS), mainly due to the heterogeneity of codes used in the hospital discharge records (HDRs) during different waves of the COVID-19 pandemic.

Barbara Giordani, Alessandra Burgio, Francesco Grippo, Alessandra Barone, Erica Eugeni, Giovanni Baglio

JMIR Public Health Surveill 2024;10:e44062

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

This is a peer-review report submitted for the paper “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.” This brief paper [1] examines the effective approach to investigating vaccine adherence against COVID-19 via Google Trends. The topic is interesting and important to provide actionable data to the World Health Organization or other related health organizations to prioritize their risk communication efforts.

Angela Chang

JMIRx Med 2022;3(2):e38726

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Peer Review of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

This is a peer-review report submitted for the paper “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.” The paper [1] uses Google Trends (GT) to identify correlations between search queries and vaccinations. GT has been used previously by others for similar and other problems. The paper is well written. The Methods section can be improved. The Results section has a good explanation. The novelty of the paper is limited.

Zubair Shah

JMIRx Med 2022;3(2):e38724

Authors’ Response to Peer Reviews of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

Authors’ Response to Peer Reviews of “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis”

The author’s response to peer-review reports for “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.” Comment: The subject of the brief paper [2] “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: a Retrospective Infodemiological Analysis” is timely and valuable to the audience of JMIRx Med. Overall, the paper is well structured, reads exceptionally well, and covers the existing literature quite well.

Alessandro Rovetta

JMIRx Med 2022;3(2):e38695