JMIR Formative Research

Search Results (1 to 10 of 470 Results)

Download search results: CSV END BibTex RIS

Sort by:

Benefits and Costs of Digital Consulting in Clinics Serving Young People With Long-Term Conditions: Mixed-Methods Approach

Among them, we could not get sufficient data from 4 sites—Dermatology, Mental health 3, Sickle cell, and Diabetes 2. This is because sites were counted only if their overall completion rate was over 50%. If less than 50% of the questionnaires were completed at a site, we did not attempt to calculate clinic-level costs. A regression analysis was carried out to estimate the main drivers for the time spent on digital consulting activity.

Sung Wook Kim, Jason Madan, Melina Dritsaki, Carol Bryce, Vera Forjaz, Joe Fraser, Frances Griffiths, Kathryn Hamilton, Caroline Huxley, Jackie Sturt

JMIR Med Inform 2018;6(4):e48

Download Citation: END BibTex RIS

Download PDF Download XML

eHealth as the Next-Generation Perinatal Care: An Overview of the Literature

All articles were categorized in 6 domains, which will be addressed accordingly: information and e Health use, lifestyle (gestational weight gain, exercise, and smoking cessation), gestational diabetes, mental health, low- and middle-income countries, and telemonitoring/teleconsulting (see also Figure 1). Tables 1-3 show the overview of 71 publications in 6 domains of perinatal care in which e Health use in patient care was described, implemented, or compared with standard care.

Josephus FM FransiscusMaria van den Heuvel, T Katrien Groenhof, Jan HW Veerbeek, Wouter W van Solinge, A Titia Lely, Arie Franx, Mireille N Bekker

J Med Internet Res 2018;20(6):e202

Download Citation: END BibTex RIS

Download PDF Download XML

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults

An estimated 30.3 million Americans, or 9.4% of the US population, have type 2 diabetes (T2 D). Another 84.1 million, or 33.9% of the adult US population, has prediabetes and is at risk for developing T2 D [1]. The estimated cost of diabetes in 2012 was US $245 billion [2]. Another estimated cost is an extra annual per-patient cost of US $4217 [3].

Natalie Stein, Kevin Brooks

JMIR Diabetes 2017;2(2):e28

Download Citation: END BibTex RIS

Download PDF Download XML

Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material

Diabetes is a major health crisis for Hispanics and Asian Americans. According to the Centers for Disease Control and Prevention (CDC), 29.1 million people (9.3% of the US population) have diabetes; 12.8% Hispanics and 9% Asian Americans above 20 years old were diagnosed with diabetes, compared to 7.6% non-Hispanic whites [1]. From 1997-2014, diabetes rates increased 103% for Asian Americans and 60% for Hispanics [2].

Xuewei Chen, Sandra Acosta, Adam E Barry

JMIR Diabetes 2017;2(1):e13

Download Citation: END BibTex RIS

Download PDF Download XML

The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology

Depression and diabetes are highly comorbid disorders that are of major public health concern, particularly among low-income populations [1]. Having diabetes doubles the risk of depression [2]. Comorbidity of the 2 disorders is associated with increased mortality [3] and worse clinical outcomes, including increased diabetes symptoms, poorer glycemic control, poorer self-management, and higher likelihood of complications [4].

Adrian Aguilera, Courtney Rees Lyles

JMIR Diabetes 2017;2(1):e1

Download Citation: END BibTex RIS

Download PDF Download XML

Increasing Consumer Engagement by Tailoring a Public Reporting Website on the Quality of Diabetes Care: A Qualitative Study

Those with diabetes mellitus are particularly representative of this group because more than 90% have multiple chronic conditions (diabetes plus at least one more condition) [22]. Additionally, persons with diabetes may be more receptive to publicly reported information on quality [23] because of their emotional connection to their disease, awareness of symptoms and consequences, and information-seeking behaviors.

Maureen A A Smith, Lauren Bednarz, Peter A Nordby, Jennifer Fink, Robert T Greenlee, Daniel Bolt, Elizabeth M Magnan

J Med Internet Res 2016;18(12):e332

Download Citation: END BibTex RIS

Download PDF Download XML

Peer Review of “Machine Learning–Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals”

diabetes

Akhil Chaturvedi

JMIRx Med 2024;5:e60853

Download Citation: END BibTex RIS

Download PDF Download XML

Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa

Diabetes is a global epidemic, affecting more than 500 million people in 2021 and a projected 783 million by 2045, with DR as the most common complication of systemic diabetes [2]. Retinal CFPs have been used for screening of referable cases, optimizing the referral process worldwide, and more recently they have been used in the development of artificial intelligence (AI) algorithms for automatic DR screening [3].

Simon Arunga, Katharine Elise Morley, Teddy Kwaga, Michael Gerard Morley, Luis Filipe Nakayama, Rogers Mwavu, Fred Kaggwa, Julius Ssempiira, Leo Anthony Celi, Jessica E Haberer, Celestino Obua

JMIR Form Res 2024;8:e59914

Download Citation: END BibTex RIS

Download PDF Download XML

Implementation of Artificial Intelligence–Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study

Diabetes mellitus is a prevalent metabolic disease affecting 5.7 million Canadians, or 14% of the population, in 2022. This number is expected to increase to 7.3 million by 2032 [1]. Diabetic retinopathy (DR) is a common complication of the disease, affecting up to 25% of patients in Canada [2]. DR is also the leading cause of vision loss in people of working age and is associated with increased mortality [3].

Fares Antaki, Imane Hammana, Marie-Catherine Tessier, Andrée Boucher, Maud Laurence David Jetté, Catherine Beauchemin, Karim Hammamji, Ariel Yuhan Ong, Marc-André Rhéaume, Danny Gauthier, Mona Harissi-Dagher, Pearse A Keane, Alfons Pomp

JMIR Diabetes 2024;9:e59867

Download Citation: END BibTex RIS

Download PDF Download XML

Lightening the Load: Generative AI to Mitigate the Burden of the New Era of Obesity Medical Therapy

Highly effective antiobesity and diabetes medications such as glucagon-like peptide 1 (GLP-1) agonists have ushered in a new era of treatment of these highly prevalent, morbid conditions that have increased across the globe over the past few decades. It is estimated that by 2030 nearly 30 million people in the United States will be on GLP-1 or glucose-dependent insulinotropic polypeptide/GLP-1 (dual) receptor agonists (RAs; henceforth referred to as GLP-1/dual RA) medications.

Elizabeth R Stevens, Arielle Elmaleh-Sachs, Holly Lofton, Devin M Mann

JMIR Diabetes 2024;9:e58680

Download Citation: END BibTex RIS

Download PDF Download XML

Search Articles

Search Results (1 to 10 of 470 Results)