JMIR Research Protocols

Childhood obesity is a global public health concern and is a priority for researchers and policy makers. To overcome the epidemic of obesity, influencing factors throughout the life span need to be addressed, including those in the preconception period. A better understanding of the association between paternal preconception factors and childhood obesity is important for public health interventions.

Mobile technology has helped to advance health programs, and studies have shown that an automated risk prediction model can successfully be used to identify patients who exhibit a high probable risk of contracting human immunodeficiency virus (HIV). A machine-guided tool is an algorithm that takes a set of subjective and objective answers from a simple questionnaire and computes an HIV risk assessment score.

Ecological momentary assessment (EMA) is an innovative tool for capturing in-the-moment health behaviors as people go about their daily lives. EMA is an ideal tool to measure weight-related behaviors, such as parental feeding practices, stress, and dietary intake, as these occur on a daily basis and vary across time and context. A recent systematic review recommended standardized reporting of EMA design for studies that address weight-related behaviors.

Peer narratives engage listeners through personally relevant content and have been shown to promote lifestyle change and effective self-management among patients with hypertension. Incorporating key quotations from these stories into follow-up text messages is a novel way to continue the conversation, providing reinforcement of health behaviors in the patients’ daily lives.

Enamel renal syndrome (ERS) (OMIM 204690) is a rare autosomal recessive disorder characterized by hypoplastic amelogenesis imperfecta, failed tooth eruption, intrapulpal calcifications, gingival enlargement, and nephrocalcinosis. The rarity of the condition and the variability of the phenotype has led to ERS not being fully characterized.

Physical activity alleviates chronic stress. The latest research suggests a relationship between resilience and physical fitness. Beneficial adaptations of the hypothalamic-pituitary-adrenal axis, sympathetic nervous system, endocannabinoid system, and tryptophan pathway, which are induced by an active lifestyle, are considered to be conducive to resilience. However, detailed knowledge on the molecular link between the effects of acute and chronic physical exercise and improved resilience to stress in humans is missing. Moreover, the relationship between innate and acquired aerobic capacity and resilience is poorly understood.

A barrier to practicing evidence-based medicine is the rapidly increasing body of biomedical literature. Use of method terms to limit the search can help reduce the burden of screening articles for clinical relevance; however, such terms are limited by their partial dependence on indexing terms and usually produce low precision, especially when high sensitivity is required. Machine learning has been applied to the identification of high-quality literature with the potential to achieve high precision without sacrificing sensitivity. The use of artificial intelligence has shown promise to improve the efficiency of identifying sound evidence.

Accessible, safe, and client-centered SARS-CoV-2 testing services are an effective way to halt its transmission. Testing enables infected individuals to isolate or quarantine to prevent further transmission. In countries with limited health systems and laboratory capacity, it can be challenging to provide accessible and safe screening for COVID-19. Self-testing provides a convenient, private, and safe testing option; however, it also raises important concerns about lack of counseling and ensuring timely reporting of self-test results to national surveillance systems. Investigating community members’ views and perceptions regarding SARS-CoV-2 self-testing is crucial to inform the most effective and safe strategies for implementing said testing.

The widespread and unrestricted use of antibiotics has led to the emergence and spread of antibiotic-resistant bacteria (ARB), antibiotic-resistance genes (ARGs), and antibiotic residues in the environment. Conventional wastewater treatment plants (WWTPs) are not designed for effective and adequate removal of ARB, ARGs, and antibiotic residues, and therefore, they play an important role in the dissemination of antimicrobial resistance (AMR) in the natural environment.

Patients undergoing lower limb revascularization surgery for peripheral artery disease (PAD) have a high risk of perioperative morbidity and mortality and often have long hospital stays. Use of neuraxial or regional anesthesia instead of general anesthesia may represent one approach to improving outcomes and reducing resource use among these patients.

Can methods from computational models of decision-making be used to build a predictive model to identify individuals most likely to be nonadherent to personal fitness goals? Such a model may have significant value in the global battle against obesity. Despite growing awareness of the impact of physical inactivity on human health, sedentary behavior is increasingly linked to premature death in the developed world. The annual impact of sedentary behavior is significant, causing an estimated 2 million deaths. From a global perspective, sedentary behavior is one of the 10 leading causes of mortality and morbidity. Annually, considerable funding and countless public health initiatives are applied to promote physical fitness, with little impact on sustained behavioral change. Predictive models developed from multimodal methodologies combining data from decision-making tasks with contextual insights and objective physical activity data could be used to identify those most likely to abandon their fitness goals. This has the potential to enable development of more targeted support to ensure that those who embark on fitness programs are successful.

Weight bias internalization, also known as weight self-stigma, is a serious health concern for individuals with higher body weight. Weight bias internalization is associated with the greater avoidance of health care and health-promoting activities, disordered eating, social isolation, and weight gain. Elevated weight bias internalization has been associated with low self-compassion, yet few investigations have explored self-compassion as a potential mechanism for reducing internalized weight bias.