MoodRing: A multi-stakeholder platform to monitor and manage adolescents' depression in primary care with passive mobile sensing.

MoodRing：一个多利益相关者平台，通过被动移动传感来监测和管理初级保健中的青少年抑郁症。

• 批准号: 10023371
• 负责人: Afsaneh Doryab
• 金额: $ 79.07万
• 依托单位: NURELM E-BUSINESS SOFTWARE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-24 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10023371
• 关键词: Accelerometer; Acute; Address; Adolescent; Adult; Affect; Algorithms; Awareness; Behavior; Behavioral; Bile fluid; Bipolar Disorder; Businesses; Car Phone; Caring; Case Manager; Cellular Phone; Childhood; Clinic Visits; Clinical; Cluster randomized trial; Code; Communication; Cost Savings; Data; Data Collection; Data Reporting; Depression and Suicide; Development; Devices; Diagnostic; Ethnic Origin; Family; Feedback; Focus Groups; Foundations; Frequencies; Goals; Guidelines; Health; Health Care Costs; Health Personnel; Health Services Accessibility; Healthcare; Healthcare Systems; Home; Hospitalization; Human; Human Resources; Income; Individual; Information Resources Management; Internet; Intervention; Interview; Knowledge; Lead; Machine Learning; Major Depressive Disorder; Manic; Medical center; Mental Depression; Mental Health; Mental Health Services; Methods; Modeling; Monitor; Moods; Movement; National Institute of Mental Health; Outcome; Parents; Patient Self-Report; Patients; Pattern; Pharmaceutical Preparations; Phase; Population; Primary Health Care; Provider; Questionnaires; Race; Randomized Controlled Trials; Recommendation; Reporting; Research Personnel; Resolution; Secure; Self Efficacy; Self Management; Services; Severities; Severity of illness; Sleep; Small Business Technology Transfer Research; Social support; Solid; Suicide; Symptoms; System; Technology; Telephone; Testing; Time; Translating; Travel; Triage; Update; Visit; Youth; adolescent health; aged; care coordination; care providers; child depression; clinical decision-making; college; computer science; cost; depressive symptoms; design; efficacy evaluation; efficacy trial; experience; follow-up; frontier; health belief; health care service utilization; health service use; heart rate variability; improved; improved outcome; innovation; medication compliance; mobile application; mobile computing; pediatric patients; persistent symptom; phase 1 study; phase 2 study; physical conditioning; population based; primary care setting; remote screening; routine screening; satisfaction; sensor; skills; sleep quality; social media; suicide rate; system architecture; therapy adherence; treatment as usual; treatment response; trend; university student; usability

ABSTRACT As rates of adolescent depression and suicidality continue to trend upwards, the healthcare system struggles to address the need for and lack of mental health service use. The pediatric patient-centered medical home model may improve adolescent depression outcomes by enhancing access to and coordinating care, as well as providing ongoing monitoring. Unfortunately, despite guideline recommendations, over 2/3 of adolescents identified with depression symptoms in primary care do not receive symptom monitoring and 19% do not re- ceive symptom reassessment. This lack of symptom monitoring and reassessment can result in untoward health outcomes including a decrease in functioning, increased use of acute and crisis services, and hospitali- zations due to suicidality. Current technologies which incorporate data passively collected from smartphones offer an opportunity for intercurrent monitoring between patient visits which limits burden on the patient to self- report and limits burden on the healthcare system, allowing primary care teams to triage contacting and as- sessing patients a system identifies with an increase in disease severity. This formative study will demonstrate the usability and potential clinical utility of MoodRing, a technology intervention which will collect passive mo- bile phone sensor data on aspects of adolescent phone use related to depressive symptom severity (e.g. com- munication patterns, social media use, travel) and integrate this data into a multi-user (adolescent, parent, pri- mary care provider/care manager) platform from which symptoms can be viewed and secure communication can occur. MoodRing, as supported by Health Belief Model, may lead to improved quality of depression man- agement (increased symptom reassessment, therapy/medication adherence) through increasing self-efficacy, social support from parent and care team, as well as encouraging application of self-management skills through increased self-management knowledge, skills, and symptom feedback. MoodRing builds on a solid foundation of investigators experienced in design of technology interventions to increase adolescent initiation of depression treatment, who have already developed machine algorithms for passive sensing and a small business partner with vast experience in working with health researchers to develop multi-user web/mobile platforms. This STTR Phase I study seeks to accomplish two aims. The first is to apply a machine learning pipeline developed for college-aged youth to adolescents with depression and determine whether self-reported depressive symptoms can be reliably predicted from passive data with at least 85% accuracy. The second is the user design and system architecture of MoodRing. If milestones are achieved that models are successful at predicting depressive symptoms and the proposed MoodRing intervention is acceptable to adolescents, par- ents, and primary care providers/care managers, then we will pursue the STTR Phase II study. The aims of Phase II include the development and subsequent efficacy trial of MoodRing. Specifically, we will conduct a cluster randomized controlled trial in a primary care setting of MoodRing as compared to usual care.

摘要