Videoconference Coaching Sessions for Distance Caregivers
Results of a randomized, controlled trial demonstrated that videoconference support improves anxiety and distress in DCGs of patients with cancer.
Diagnosis & Disease Information
Phone-Based Therapy Beneficial for Depression in Parkinson Disease
Telephone-based cognitive behavioral therapy seems to be an effective intervention for depression in Parkinson disease, outperforming treatment-as-usual on all depression, anxiety, and quality-of-life measures.
Importance of Temporal Glucose Profiles During Pregnancy in Type 1 Diabetes
Applying functional data analysis to continuous glucose monitoring data can assist in identifying differences in maternal glucose control during pregnancy, which might go unnoticed using standard metrics.
Online Intervention May Reduce Stress, Increase Pregnancy Rates in Women With Infertility
An internet-based cognitive therapy intervention for women with infertility may reduce anxiety, depression, and stress and increase the likelihood of pregnancy.
Fitbit Data Significantly Improves Prediction of Influenza-like Illnesses
Fitbit data significantly improved detection of influenza-like illness (ILI) in US patients.
Noninvasive Wearable Sensor Accurately Predicts HF Rehospitalization
A wearable sensor featuring a personalized machine learning platform can accurately predict heart failure (HF) rehospitalization.
Telementoring Shows Promise in Opioid Management
The project, which began in New Mexico in 2003, uses videoconferencing to connect remote physicians to specialists who provide mentorship and insight into specific disease states.
EULAR Develops Points to Consider for Big Data Analysis and Use in Rheumatic and Musculoskeletal Diseases
The European League Against Rheumatism developed recommendations for the collection, analysis, and use of big data in rheumatic and musculoskeletal disorders.
The Case for Crowdsourcing in Health Research
Crowdsourcing has been used in the health and medical research fields to potentially create low-cost, community-driven interventions.
AI and Machine Learning Technology Can Detect Nocturnal Hypoglycemic Events
Researchers have developed an artificial intelligence (AI)-driven, noninvasive technology that is capable of detecting nocturnal hypoglycemic events from raw ECG signals without the need for a finger-prick test.
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