View clinical trials related to Mobile Technology.
Filter by:Type 2 diabetes patients were divided into experimental and control groups. Patients in the control group received regular nursing care, while those in the experimental group received MI, which is empowered by game-based mobile technology. Pre-test, post-test and follow-up test self-management, quality of life and satisfaction levels scores were determined.
In non-alcoholic fatty liver disease (NAFLD), it is established that calorie restriction is the most essential dietary modification. The time-restricted diet is successful lowering total calorie consumption and insulin resistance, and is anticipated to be beneficial for patients with NAFLD. Therefore, this study aims to conduct a prospective study to determine the effect of time-restricted diet via a mobile application on the amount of intrahepatic fat and 10-year cardiovascular disease risk in patients with NAFLD.
New and creative approaches are needed to address childhood obesity. Current strategies result in suboptimal outcomes and are intensive and costly. It has been theorized that overeating, may have addictive qualities, although few weight management interventions have tested therapeutic techniques founded on addiction medicine principles, such as, withdrawal, tolerance and craving control1, 2. A pilot study utilizing an addiction model based mobile health (mHealth) weight-loss intervention in adolescents showed that the app intervention reduced BMI Z-score (zBMI) to a greater extent than youth participating in an in-clinic multidisciplinary weight management intervention, and appeared to be a cost-effective, labor efficient method for adolescent weight management. The proposed multi-site randomized control trial (RCT) will test the effectiveness of an addiction-based weight loss intervention, embodied first as a smartphone app with telephone coaching and second as an identical approach phone-coaching alone intervention compared to age matched controls participating in an in-clinic weight management interventions in a larger sample of economically, racially and ethnically diverse adolescents (ages 14-18). One hundred and eighty adolescents will be recruited from pediatric interdisciplinary weight management clinics operating out of five different hospital systems in Southern California and through targeted mailing to 40 ethnically, racially and economically diverse neighborhoods in Los Angeles County. The adolescents will be randomized 1:1 via stratified block randomization to either receive 1) interactive addiction model based mobile health (mHealth) weight-loss intervention with personalized phone-coaching (AppCoach), 2) interactive addiction model based mHealth weight-loss intervention alone (App) or 3) Multidisciplinary in-clinic weight management program (Clinic). Assessment of the intervention's effect on zBMI and percent over the 95th percentile (%BMIp95), fasting metabolic parameters, addictive eating habits, executive function, and motivation for change will be obtained at enrollment, 3, 6, 12 and 18 months (1 year post intervention follow up). In addition, a real-life economic analysis (cost, cost-saving and non-monetary benefits) analysis will be completed comparing AppCoach to 1) App and 2) Clinic. We will further explore whether primary and secondary outcomes differ by race and whether race moderates the relationship between initial intervention efficacy and prolonged weight maintenance.
Retention in care and virologic suppression are the key final steps of the HIV treatment cascade. Poor or intermittent retention has been associated with later initiation of antiretroviral therapy, virologic failure, and death. Regular HIV care has also been associated with a decrease in HIV transmission risk behavior. Despite the proven health and prevention benefits of consistent HIV care, only 40-50% of those infected with HIV in the United States are estimated to meet current retention in care standards and even fewer - only about 25% - are estimated to be virologically suppressed. The Behavioral Model for Vulnerable Populations provides a useful framework for understanding broad areas that may impact adherence to care and treatment. Individual-level domains include vulnerable (e.g., depression, stigma), enabling (e.g., social support, positive affect), and need (e.g., co-morbidities) factors, and structural domains include, for example, features or the clinic and the provider-patient relationship. Short message service (SMS) technology represents a new and exciting tool to help retain HIV-infected patients in care and treatment. SMS interventions have been deployed successfully in support of antiretroviral adherence and virologic suppression in sub-Saharan Africa, where two randomized trials have showed clear benefits. A pilot study conducted in our clinic suggests that use of SMS messages to promote adherence to care and treatment in the urban HIV-infected poor is both feasible and acceptable. The investigators believe that combining SMS technology with content-specific messages designed to impact factors highlighted in the Behavioral Model for Vulnerable Populations can improve retention in care and virologic suppression for an urban public hospital population living with HIV, thus the investigators propose the following specific aims. Specific Aim 1: Determine whether a behavioral theory-based SMS intervention improves virologic suppression [primary outcome] and retention in care [secondary outcome] for a vulnerable urban HIV-infected population through a randomized trial of this technology compared to SMS appointment reminders alone. Retention in care will also be analyzed as a mediator of virologic suppression. Exploratory outcomes include time to virologic suppression, sustained virologic suppression, emergency department utilization and antiretroviral adherence, as well as levels of depression, positive affect, social support and empowerment. Specific Aim 2: Examine patient experiences with the SMS intervention, focusing specifically on: 1) satisfaction with this technology; 2) identifying barriers to and facilitators of patient use of this technology, and; 3) the preferred frequency and content of intervention messages. Specific Aim 3: Conduct cost and cost-effectiveness analyses of the SMS intervention.