MoodRing: A multi-stakeholder platform to monitor and manage adolescents' depression in primary care with passive mobile sensing.
MoodRing: A multi-stakeholder platform to monitor and manage adolescents' depression in primary care with passive mobile sensing.
批准号:
10023371
负责人:
Afsaneh Doryab
金额:
$79.07万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-24 至 2023-04-30
关键词:
AccelerometerAcuteAddressAdolescentAdultAffectAlgorithmsAwarenessBehaviorBehavioralBile fluidBipolar DisorderBusinessesCar PhoneCaringCase ManagerCellular PhoneChildhoodClinic VisitsClinicalCluster randomized trialCodeCommunicationCost SavingsDataData CollectionData ReportingDepression and SuicideDevelopmentDevicesDiagnosticEthnic OriginFamilyFeedbackFocus GroupsFoundationsFrequenciesGoalsGuidelinesHealthHealth Care CostsHealth PersonnelHealth Services AccessibilityHealthcareHealthcare SystemsHomeHospitalizationHumanHuman ResourcesIncomeIndividualInformation Resources ManagementInternetInterventionInterviewKnowledgeLeadMachine LearningMajor Depressive DisorderManicMedical centerMental DepressionMental HealthMental Health ServicesMethodsModelingMonitorMoodsMovementNational Institute of Mental HealthOutcomeParentsPatient Self-ReportPatientsPatternPharmaceutical PreparationsPhasePopulationPrimary Health CareProviderQuestionnairesRaceRandomized Controlled TrialsRecommendationReportingResearch PersonnelResolutionSecureSelf EfficacySelf ManagementServicesSeveritiesSeverity of illnessSleepSmall Business Technology Transfer ResearchSocial supportSolidSuicideSymptomsSystemTechnologyTelephoneTestingTimeTranslatingTravelTriageUpdateVisitYouthadolescent healthagedcare coordinationcare providerschild depressionclinical decision-makingcollegecomputer sciencecostdepressive symptomsdesignefficacy evaluationefficacy trialexperiencefollow-upfrontierhealth beliefhealth care service utilizationhealth service useheart rate variabilityimprovedimproved outcomeinnovationmedication compliancemobile applicationmobile computingpediatric patientspersistent symptomphase 1 studyphase 2 studyphysical conditioningpopulation basedprimary care settingremote screeningroutine screeningsatisfactionsensorskillssleep qualitysocial mediasuicide ratesystem architecturetherapy adherencetreatment as usualtreatment responsetrenduniversity studentusability
中文摘要
摘要
随着青少年抑郁症和自杀率继续上升,医疗保健系统正在努力
解决精神卫生服务使用的需求和缺乏。以病人为中心的儿科医疗之家
该模型还可以通过增加获得和协调护理来改善青少年抑郁症的结果,
提供持续监控。不幸的是,尽管有指南的建议,超过2/3的青少年
在初级保健中确定有抑郁症状的人没有接受症状监测,19%的人没有重新接受监测。
接受症状再评估。这种缺乏症状监测和重新评估可能会导致不良的
健康结果,包括功能下降,急性和危机服务的使用增加,以及住院治疗,
因自杀而引起的。目前的技术,包括从智能手机被动收集的数据
为患者就诊之间的并发监测提供了机会,这限制了患者的自我负担,
报告和限制医疗保健系统的负担,允许初级保健团队对接触者进行分类,
对系统识别为疾病严重程度增加的患者进行评估。这项研究将证明
MoodRing的可用性和潜在临床效用,这是一种技术干预,将收集被动运动,
胆汁手机传感器数据,关于青少年手机使用与抑郁症状严重程度相关的方面(例如,com,
通信模式,社交媒体使用,旅行),并将这些数据集成到多用户(青少年,父母,小学生,
玛丽护理提供者/护理管理者)平台,从该平台可以查看症状并保护通信
可能发生。健康信念模型支持的MoodRing可能会改善抑郁症患者的质量-
通过提高自我效能感来改善(增加症状重新评估,治疗/药物依从性),
家长和照顾小组社会支持,以及鼓励运用自我管理技能
通过增加自我管理知识、技能和症状反馈。MoodRing建立在一个坚实的
在设计技术干预措施以提高青少年启蒙方面经验丰富的调查人员的基础
他们已经开发出了被动感知的机器算法和一个小的
在与健康研究人员合作开发多用户Web/移动的方面拥有丰富经验的业务合作伙伴
平台本STTR第一阶段研究旨在实现两个目标。首先是应用机器学习
管道开发的大学适龄青年到青少年抑郁症,并确定是否自我报告
抑郁症状可以从被动数据中可靠地预测,准确率至少为85%。二是
MoodRing的用户设计和系统架构。如果达到了里程碑,则模型在
预测抑郁症状和建议的MoodRing干预是可以接受的青少年,部分-
如果我们有足够的时间和时间,以及初级保健提供者/护理管理人员,那么我们将继续进行STTR II期研究。的目的
第二阶段包括MoodRing的开发和随后的疗效试验。具体而言,我们将进行一项
在初级保健环境中进行的MoodRing与常规护理相比的随机对照试验。
英文摘要
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.
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会议论文
MoodRing: A multi-stakeholder platform to monitor and manage adolescents' depression in primary care with passive mobile sensing.
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批准号:10399975
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项目类别:
-
资助金额:$68.57万
-
财政年份:2019
-
负责人:Afsaneh Doryab
-
依托单位:
MoodRing: A multi-stakeholder platform to monitor and manage adolescents' depression in primary care with passive mobile sensing.
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批准号:9908603
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项目类别:
-
资助金额:$22.34万
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财政年份:2019
-
负责人:Afsaneh Doryab
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依托单位:
海外基金