Recent Articles
![Mindful Self-Compassion Smartphone Intervention for Worker Mental Health in Japan: Protocol for a Randomized Controlled Trial Article Thumbnail](https://asset.jmir.pub/assets/784b27d6a2ea50baf83147b5e333d461.png 480w,https://asset.jmir.pub/assets/784b27d6a2ea50baf83147b5e333d461.png 960w,https://asset.jmir.pub/assets/784b27d6a2ea50baf83147b5e333d461.png 1920w,https://asset.jmir.pub/assets/784b27d6a2ea50baf83147b5e333d461.png 2500w)
![AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review Article Thumbnail](https://asset.jmir.pub/assets/c192df1696fc6ca0d73c0746bd299e98.png 480w,https://asset.jmir.pub/assets/c192df1696fc6ca0d73c0746bd299e98.png 960w,https://asset.jmir.pub/assets/c192df1696fc6ca0d73c0746bd299e98.png 1920w,https://asset.jmir.pub/assets/c192df1696fc6ca0d73c0746bd299e98.png 2500w)
The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack of knowledge of how to report AEs, and a general culture of nonreporting. The introduction of artificial intelligence as a medical device (AIaMD) requires a robust safety monitoring environment that recognizes both generic risks of a medical device and some of the increasingly recognized risks of AIaMD (such as algorithmic bias). There is an urgent need to understand the limitations of current AE reporting systems and explore potential mechanisms for how AEs could be detected, attributed, and reported with a view to improving the early detection of safety signals.
![Web-Based Group Conversational Intervention on Cognitive Function and Comprehensive Functional Status Among Japanese Older Adults: Protocol for a 6-Month Randomized Controlled Trial Article Thumbnail](https://asset.jmir.pub/assets/11ba22795f12d44cd35403833fac1b1e.png 480w,https://asset.jmir.pub/assets/11ba22795f12d44cd35403833fac1b1e.png 960w,https://asset.jmir.pub/assets/11ba22795f12d44cd35403833fac1b1e.png 1920w,https://asset.jmir.pub/assets/11ba22795f12d44cd35403833fac1b1e.png 2500w)
![Effect of Menstrual Cycle and Hormonal Contraception on Musculoskeletal Health and Performance: Protocol for a Prospective Cohort Design and Cross-Sectional Comparison Article Thumbnail](https://asset.jmir.pub/assets/5b9b3dde0e078134247cbbf38b9f02c3.png 480w,https://asset.jmir.pub/assets/5b9b3dde0e078134247cbbf38b9f02c3.png 960w,https://asset.jmir.pub/assets/5b9b3dde0e078134247cbbf38b9f02c3.png 1920w,https://asset.jmir.pub/assets/5b9b3dde0e078134247cbbf38b9f02c3.png 2500w)
Women of reproductive age experience cyclical variation in the female sex steroid hormones 17β-estradiol and progesterone during the menstrual cycle that is attenuated by some hormonal contraceptives. Estrogens perform a primary function in sexual development and reproduction but have nonreproductive effects on bone, muscle, and sinew tissues (ie, ligaments and tendons), which may influence injury risk and physical performance.
![Combining Federated Machine Learning and Qualitative Methods to Investigate Novel Pediatric Asthma Subtypes: Protocol for a Mixed Methods Study Article Thumbnail](https://asset.jmir.pub/assets/55050d124cbc7f0a8889f09730f2441d.png 480w,https://asset.jmir.pub/assets/55050d124cbc7f0a8889f09730f2441d.png 960w,https://asset.jmir.pub/assets/55050d124cbc7f0a8889f09730f2441d.png 1920w,https://asset.jmir.pub/assets/55050d124cbc7f0a8889f09730f2441d.png 2500w)
Pediatric asthma is a heterogeneous disease; however, current characterizations of its subtypes are limited. Machine learning (ML) methods are well-suited for identifying subtypes. In particular, deep neural networks can learn patient representations by leveraging longitudinal information captured in electronic health records (EHRs) while considering future outcomes. However, the traditional approach for subtype analysis requires large amounts of EHR data, which may contain protected health information causing potential concerns regarding patient privacy. Federated learning is the key technology to address privacy concerns while preserving the accuracy and performance of ML algorithms. Federated learning could enable multisite development and implementation of ML algorithms to facilitate the translation of artificial intelligence into clinical practice.
![Suicidal Ideation and Attempts Among Youth With Physical-Mental Comorbidity in Canada: Proposal for an Epidemiological Study Article Thumbnail](https://asset.jmir.pub/assets/03bc06076836511e95fa7bbcca10d950.png 480w,https://asset.jmir.pub/assets/03bc06076836511e95fa7bbcca10d950.png 960w,https://asset.jmir.pub/assets/03bc06076836511e95fa7bbcca10d950.png 1920w,https://asset.jmir.pub/assets/03bc06076836511e95fa7bbcca10d950.png 2500w)
Evidence suggests that having a chronic physical illness (CPI; eg, asthma, diabetes, and epilepsy) is an independent risk factor for suicidality (ie, suicidal ideation or attempts) among youth. Less is known about the mechanisms linking CPI and suicidality. Some evidence suggests that mental illness (eg, depression and anxiety) or neurodevelopmental disorder (eg, attention-deficit/hyperactivity disorder) mediates or moderates the CPI-suicidality association. Missing from the knowledge base is information on the association between having co-occurring CPI and mental illness or neurodevelopmental disorder (MIND) on youth suicidality.
![Gender Inequalities of Health and Quality of Life in Informal Caregivers in Spain: Protocol for the Longitudinal and Multicenter CUIDAR-SE Study Article Thumbnail](https://asset.jmir.pub/assets/4b8a750e855156dc3a0d4e183fca0ff3.png 480w,https://asset.jmir.pub/assets/4b8a750e855156dc3a0d4e183fca0ff3.png 960w,https://asset.jmir.pub/assets/4b8a750e855156dc3a0d4e183fca0ff3.png 1920w,https://asset.jmir.pub/assets/4b8a750e855156dc3a0d4e183fca0ff3.png 2500w)
The aging population and increased disability prevalence in Spain have heightened the demand for long-term care. Informal caregiving, primarily performed by women, plays a crucial role in this scenario. This protocol outlines the CUIDAR-SE study, focusing on the gender-specific impact of informal caregiving on health and quality of life among caregivers in Andalusia and the Basque Country from 2013 to 2024.
![Body Composition and Energy Expenditure in Youth With Spina Bifida: Protocol for a Multisite, Cross-Sectional Study Article Thumbnail](https://asset.jmir.pub/assets/5a9101778e6bb7f1556d67824e2de7c1.png 480w,https://asset.jmir.pub/assets/5a9101778e6bb7f1556d67824e2de7c1.png 960w,https://asset.jmir.pub/assets/5a9101778e6bb7f1556d67824e2de7c1.png 1920w,https://asset.jmir.pub/assets/5a9101778e6bb7f1556d67824e2de7c1.png 2500w)
Obesity prevalence in youth with spina bifida is higher than in their typically developing peers. Obesity is associated with lifelong medical, psychological, and economic burdens. Successful prevention or treatment of obesity in individuals with spina bifida is compromised by (1) the lack of valid and reliable methods to identify body fat in a clinical setting and (2) limited data on energy expenditure that are necessary to provide daily caloric recommendations.
![Erlotinib or Gefitinib for Treating Advanced Epidermal Growth Factor Receptor Mutation–Positive Lung Cancer in Aotearoa New Zealand: Protocol for a National Whole-of-Patient-Population Retrospective Cohort Study and Results of a Validation Substudy Article Thumbnail](https://asset.jmir.pub/assets/f14ad01c9bcd9e89680b52a122490ca3.png 480w,https://asset.jmir.pub/assets/f14ad01c9bcd9e89680b52a122490ca3.png 960w,https://asset.jmir.pub/assets/f14ad01c9bcd9e89680b52a122490ca3.png 1920w,https://asset.jmir.pub/assets/f14ad01c9bcd9e89680b52a122490ca3.png 2500w)
![Assessment of the Feasibility of Objective Parameters as Primary End Points for Patients Affected by Knee Osteoarthritis: Protocol for a Pilot, Open Noncontrolled Trial (:SMILE:) Article Thumbnail](https://asset.jmir.pub/assets/259c9d9410600c31ba7ce57327aeb67e.png 480w,https://asset.jmir.pub/assets/259c9d9410600c31ba7ce57327aeb67e.png 960w,https://asset.jmir.pub/assets/259c9d9410600c31ba7ce57327aeb67e.png 1920w,https://asset.jmir.pub/assets/259c9d9410600c31ba7ce57327aeb67e.png 2500w)
Osteoarthritis (OA) is a disabling condition that affects more than one-third of people older than 65 years. Currently, 80% of these patients report movement limitations, 20% are unable to perform major activities of daily living, and approximately 11% require personal care. In 2014, the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) recommended, as the first step in the pharmacological treatment of knee osteoarthritis, a background therapy with chronic symptomatic slow-acting osteoarthritic drugs such as glucosamine sulfate, chondroitin sulfate, and hyaluronic acid. The latter has been extensively evaluated in clinical trials as intra-articular and oral administration. Recent reviews have shown that studies on oral hyaluronic acid generally measure symptoms using only subjective parameters, such as visual analog scales or quality of life questionnaires. As a result, objective measures are lacking, and data validity is generally impaired.
![mHealth-Based Just-in-Time Adaptive Intervention to Improve the Physical Activity Levels of Individuals With Spinal Cord Injury: Protocol for a Randomized Controlled Trial Article Thumbnail](https://asset.jmir.pub/assets/d0daf0e72af5ab3ddefafd708657c14d.png 480w,https://asset.jmir.pub/assets/d0daf0e72af5ab3ddefafd708657c14d.png 960w,https://asset.jmir.pub/assets/d0daf0e72af5ab3ddefafd708657c14d.png 1920w,https://asset.jmir.pub/assets/d0daf0e72af5ab3ddefafd708657c14d.png 2500w)
The lack of regular physical activity (PA) in individuals with spinal cord injury (SCI) in the United States is an ongoing health crisis. Regular PA and exercise-based interventions have been linked with improved outcomes and healthier lifestyles among those with SCI. Providing people with an accurate estimate of their everyday PA level can promote PA. Furthermore, PA tracking can be combined with mobile health technology such as smartphones and smartwatches to provide a just-in-time adaptive intervention (JITAI) for individuals with SCI as they go about everyday life. A JITAI can prompt an individual to set a PA goal or provide feedback about their PA levels.
![Assessing Functional Capacity in Directly and Remotely Monitored Home-Based Settings in Individuals With Chronic Respiratory Diseases: Protocol for a Multinational Validation Study Article Thumbnail](https://asset.jmir.pub/assets/cf5634a4c62b4e4fbd8fbb09b18d7964.png 480w,https://asset.jmir.pub/assets/cf5634a4c62b4e4fbd8fbb09b18d7964.png 960w,https://asset.jmir.pub/assets/cf5634a4c62b4e4fbd8fbb09b18d7964.png 1920w,https://asset.jmir.pub/assets/cf5634a4c62b4e4fbd8fbb09b18d7964.png 2500w)
Pulmonary rehabilitation is widely recommended to improve functional status and as secondary and tertiary prevention in individuals with chronic pulmonary diseases. Unfortunately, access to timely and appropriate rehabilitation remains limited. To help close this inaccessibility gap, telerehabilitation has been proposed. However, exercise testing is necessary for effective and safe exercise prescription. Current gold-standard tests, such as maximal cardiopulmonary exercise testing (CPET) and the 6-minute walk test (6MWT), are poorly adapted to home-based or telerehabilitation settings. This was an obstacle to the continuity of services during the COVID-19 pandemic. It is essential to validate tests adapted to these new realities, such as the 6-minute stepper test (6MST). This test, strongly inspired by 6MWT, consists of taking as many steps as possible on a “stepper” for 6 minutes.
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