JMIR Research Protocols
Protocols, grant proposals, registered reports (RR1)
Editor-in-Chief:
Amy Schwartz, MSc, Ph.D., Scientific Editor at JMIR Publications, Ontario, Canada
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Recent Articles
Syphilis is a systemic, preventable, and curable infection caused by the bacterium Treponema pallidum. Despite being treatable, syphilis continues to have a high incidence, with a resurgence observed even in countries with strong health surveillance systems. This highlights the need to understand the various strategies used globally to improve access to care for individuals with syphilis.
Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries where resources and infrastructure for an adequate response are limited. The World Health Organization (WHO) Global Antimicrobial Resistance Surveillance System (GLASS) was introduced in 2016 to address these challenges, outlining recommendations for priority pathogen-antibiotic combinations. Despite this initiative, implementation in Africa remains understudied. This scoping review aims to assess the current state of implementing WHO GLASS recommendations on antimicrobial sensitivity testing (AST) in Africa.
Research in the developmental origins of health and disease provides compelling evidence that adverse events during the first 1000 days of life from conception can impact life course health. Despite many decades of research, we still lack a complete understanding of the mechanisms underlying some of these associations. The Newcastle 1000 Study (NEW1000) is a comprehensive, prospective population-based pregnancy cohort study based in Newcastle, New South Wales, Australia, that will recruit pregnant women and their partners at 11-14 weeks’ gestation, with assessments at 20, 28, and 36 weeks; birth; 6 weeks; and 6 months, in order to provide detailed data about the first 1000 days of life to investigate the developmental origins of noncommunicable diseases.
Approximately 100,000 patients undergo fecal ostomy operations annually across the United States. This patient population experiences high surgical complication rates and poor biopsychosocial outcomes. Surgical teams are not trained to address the psychosocial needs that often arise during recovery after fecal ostomy surgery.
Mucopolysaccharidosis type IVA (MPS IVA), also known as Morquio A syndrome, is a rare lysosomal storage disease characterized by autosomal recessive inheritance of mutations in the N-acetylgalactosamine-6-sulfatase (GALNS) gene. This leads to a deficiency of the GALNS enzyme, causing the accumulation of glycosaminoglycans in tissues. Morquio A syndrome primarily affects the skeletal system and joints but can also impact various organs, resulting in symptoms such as hearing and vision loss, respiratory issues, spinal cord compression, heart diseases, and hepatomegaly. The genotype-phenotype relationship is diverse, with studies highlighting variants associated with classic, nonclassic, or intermediate phenotypes. Understanding these genetic factors is crucial for predicting disease prognosis and tailoring effective treatment strategies for individuals with Morquio A syndrome.
The majority of people living with HIV in the United States are men who have sex with men (MSM), with race- and ethnicity-based disparities in HIV rates and care continuum. In order to uncover the neighborhood- and network-involved pathways that produce HIV care outcome disparities, systematic, theory-based investigation of the specific and intersecting neighborhood and social network characteristics that relate to the HIV care continuum must be engaged.
Anxiety and depression in people with epilepsy are common and associated with poor outcomes; yet, they often go untreated due to poor mental health specialist access. Collaborative care is an integrated care model with a strong evidence base in primary care and medical settings, but it has not been evaluated in neurology clinics. Evaluating implementation outcomes when translating evidence-based interventions to new clinical settings to inform future scaling and incorporation into real-world practice is important.
People diagnosed with a co-occurring serious mental illness (SMI; ie, major depressive disorder, bipolar disorder, or schizophrenia) but hospitalized for a nonpsychiatric condition experience higher rates of readmissions and other adverse outcomes, in part due to poorly coordinated care transitions. Current hospital-to-home transitional care programs lack a focus on the integrated social, medical, and mental health needs of these patients. The Thrive clinical pathway provides transitional care support for patients insured by Medicaid with multiple chronic conditions by focusing on posthospitalization medical concerns and the social determinants of health. This study seeks to evaluate an adapted version of Thrive that also meets the needs of patients with co-occurring SMI discharged from a nonpsychiatric hospitalization.
: Globally, there is significant variation in the out-of-hospital cardiac arrest (OHCA) survival rate. Early links in the chain of survival, including bystander cardiopulmonary resuscitation (CPR) and the use of an automated external defibrillator at the scene, are known to be of crucial importance, with strong evidence of increased survival rate with good neurological outcomes. The data from the Middle East are limited and report variable rates of bystander CPR and survival. It is crucial to get prospective, reliable data on bystander response in these regions to help plan interventions to improve bystander response and outcomes.
Older adults belonging to racial or ethnic minorities with low socioeconomic status are at an elevated risk of developing dementia, but resources for assessing functional decline and detecting cognitive impairment are limited. Cognitive impairment affects the ability to perform daily activities and mobility behaviors. Traditional assessment methods have drawbacks, so smart home technologies (SmHT) have emerged to offer objective, high-frequency, and remote monitoring. However, these technologies usually rely on motion sensors that cannot identify specific activity types. This group often lacks access to these technologies due to limited resources and technology experience. There is a need to develop new sensing technology that is discreet, affordable, and requires minimal user engagement to characterize and quantify various in-home activities. Furthermore, it is essential to explore the feasibility of developing machine learning (ML) algorithms for SmHT through collaborations between clinical researchers and engineers and involving minority, low-income older adults for novel sensor development.
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