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Capacity to Invest Effort as a Predictor of Preference for Digital Mental Health Interventions Over Psychotherapy: Cross-Sectional Study Using an Ecological Digital Screening Tool

Capacity to Invest Effort as a Predictor of Preference for Digital Mental Health Interventions Over Psychotherapy: Cross-Sectional Study Using an Ecological Digital Screening Tool

The current severity of individuals’ psychological distress and their capacity to invest effort in a mental health intervention reflect both their need for mental health care and their actual capability to pursue it. While distress severity has sometimes been explored as a predictor of intervention preferences, the capacity to invest effort has not yet been studied as a predictor of preferences.

Tomer Savir, Amit Baumel

J Med Internet Res 2025;27:e77802


Association Between Age and Severity at Disability Onset and All-Cause Mortality: Longitudinal Observational Study From the Health and Retirement Study

Association Between Age and Severity at Disability Onset and All-Cause Mortality: Longitudinal Observational Study From the Health and Retirement Study

Despite these contrasting perspectives, most existing research estimates health outcomes based primarily on prevalent disability age, without fully accounting for the duration or severity of disability at onset, which may play a crucial role in shaping long-term survival.

Anying Bai, Cuie Liu, Yu Jiang, Weihao Xu, Jian Cao

JMIR Aging 2025;8:e73254


Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

Recent observational studies have reported that increasing COVID-19 severity may be responsible for a worse prognosis [17] among diabetes patients [18] and increased severity of lung disease [19]. Two meta-analyses showed that supplementation with antioxidants (in the form of vitamins and trace elements) in critically ill patients was associated with decreased mortality and counteracted OS damage [20,21].

Olivier Raspado, Michel Brack, Olivier Brack, Mélanie Vivancos, Aurélie Esparcieux, Emmanuelle Cart-Tanneur, Abdellah Aouifi

JMIR Form Res 2025;9:e66509


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