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Identifying Digital Markers of Attention-Deficit/Hyperactivity Disorder (ADHD) in a Remote Monitoring Setting: Prospective Observational Study

Identifying Digital Markers of Attention-Deficit/Hyperactivity Disorder (ADHD) in a Remote Monitoring Setting: Prospective Observational Study

The real-world behaviors captured using such passive monitoring may, for example, provide digital signals of ADHD severity or predict outcomes. Emerging evidence from research on other disorders, such as depression and schizophrenia, indicates the potential for passive smartphone data to identify markers related to symptom severity or warning signs of relapse [11,12].

Heet Sankesara, Hayley Denyer, Shaoxiong Sun, Qigang Deng, Yatharth Ranjan, Pauline Conde, Zulqarnain Rashid, Philip Asherson, Andrea Bilbow, Madeleine J Groom, Chris Hollis, Richard J B Dobson, Amos Folarin, Jonna Kuntsi

JMIR Form Res 2025;9:e54531

Association Between Ursodeoxycholic Acid and Clinical Outcomes in Patients With COVID-19 Infection: Population-Based Cohort Study

Association Between Ursodeoxycholic Acid and Clinical Outcomes in Patients With COVID-19 Infection: Population-Based Cohort Study

(B) Study design of COVID-19 severity according to UDCA usage in the JBUH CDM database. (C) Flowchart of COVID-19 susceptibility and severity according to UDCA usage in JBUH CDM database. JBUH CDM: Jeonbuk National University Hospital Common Data Model; PS: propensity score; PSM: propensity score matching; UDCA: ursodeoxycholic acid. (A) Study design of COVID-19 susceptibility according to UDCA usage in the NHIS database. (B) Study design of COVID-19 severity according to UDCA usage in the NHIS database.

Hyunjun Lee, Min Gul Kim, Sang Woo Yeom, Sang Jae Noh, Cho Yun Jeong, Min Ji Kim, Min Gu Kang, Ji Hoon Ko, Su Cheol Park, Hyeok Tae Kweon, Sang Il Sim, Hyun Lee, Yeon Seok You, Jong Seung Kim

JMIR Public Health Surveill 2024;10:e59274

The Clinical Severity of COVID-19 Variants of Concern: Retrospective Population-Based Analysis

The Clinical Severity of COVID-19 Variants of Concern: Retrospective Population-Based Analysis

Understanding the severity of SARS-Co V-2 variants of concern (VOCs) has been important to clinical decision-making and the implementation of appropriate public health measures. While the wild-type strain dominated infections worldwide throughout the first year of the pandemic, the sudden increase in disease severity by the end of 2020 prompted the World Health Organization to implement a program that classified SARS-Co V-2 into variants of interest and VOCs [1].

Sean P Harrigan, Héctor A Velásquez García, Younathan Abdia, James Wilton, Natalie Prystajecky, John Tyson, Chris Fjell, Linda Hoang, Jeffrey C Kwong, Sharmistha Mishra, Linwei Wang, Beate Sander, Naveed Z Janjua, Hind Sbihi

JMIR Public Health Surveill 2024;10:e45513

Changes in the Frequency of Actions Associated With Mental Health During Online Treatment: Analysis of Demographic and Clinical Factors

Changes in the Frequency of Actions Associated With Mental Health During Online Treatment: Analysis of Demographic and Clinical Factors

These findings suggest that specific daily actions are associated with mental health across the severity spectrum and that changes in how often individuals are performing these actions may influence psychological treatment outcomes. There are a number of outstanding questions regarding individual differences in the frequency of daily actions associated with mental health.

Madelyne Bisby, Lauren Staples, Blake Dear, Nickolai Titov

JMIR Form Res 2024;8:e57938

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

At the population level, it has been established that interactions between diseases can increase the severity of the overall medical condition and complicate the treatment of other diseases within the combination [2,3]. In people infected with SARS-Co V-2, multimorbidity can increase the severity of the infection [4,5]. Therefore, it is important to identify specific disease combinations that could impact the severity of COVID-19 in individuals with multimorbidity.

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

JMIR Public Health Surveill 2024;10:e52353

Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey

Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey

In particular, we examined the explanatory power of the following UTAUT2 factors: performance expectancy, effort expectancy, social influence, facilitating conditions, and habit, and the additional explanatory power of perceived information insufficiency, perceived susceptibility, severity of familial cancer risk, and a cancer diagnosis by oneself as additional factors related to information seeking about familial cancer.

Paula Memenga, Eva Baumann, Hanna Luetke Lanfer, Doreen Reifegerste, Julia Geulen, Winja Weber, Andrea Hahne, Anne Müller, Susanne Weg-Remers

J Med Internet Res 2023;25:e45198