Adrian Aguilera
20 records found
1
Authored
Effectiveness of a Digital Health Intervention Leveraging Reinforcement Learning
Results From the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation (DIAMANTE) Randomized Clinical Trial
Background: Digital and mobile health interventions using personalization via reinforcement learning algorithms have the potential to reach large number of people to support physical activity and help manage diabetes and depression in daily life. Objective: The Diabetes and Me ...
The effect of cognitive behavioral therapy text messages on mood
A micro-randomized trial
The StayWell at Home intervention, a 60-day text-messaging program based on Cognitive Behavioral Therapy (CBT) principles, was developed to help adults cope with the adverse effects of the global pandemic. Participants in StayWell at Home were found to show reduced depressive ...
Background: Women are less physically active, report greater perceived barriers for exercise, and show higher levels of depressive symptoms. This contributes to high global disability. The relationship between perceived barriers for physical activity and depressive symptoms in ...
Ratings and experiences in using a mobile application to increase physical activity among university students
Implications for future design
Daily Motivational Text Messages to Promote Physical Activity in University Students
Results From a Microrandomized Trial
A text messaging intervention for coping with social distancing during COVID-19 (staywell at home)
Protocol for a randomized controlled trial
Promoting physical activity through conversational agents
Mixed methods systematic review
Adaptive learning algorithms to optimize mobile applications for behavioral health
Guidelines for design decisions
Conducting internet-based visits for onboarding populations with limited digital literacy to an mhealth intervention
Development of a patient-centered approach
Conversational Physical Activity Coaches for Spanish and English Speaking Women
A User Design Study
Developing messaging content for a physical activity smartphone app tailored to low-income patients
User-centered design and crowdsourcing approach
MHealth app using machine learning to increase physical activity in diabetes and depression
Clinical trial protocol for the DIAMANTE Study
Introduction Depression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions tar ...