SCH: Control Systems Engineering for Counteracting Notification Fatigue: An Examination of Health Behavior Change
SCH: Control Systems Engineering for Counteracting Notification Fatigue: An Examination of Health Behavior Change
批准号:
10116465
负责人:
Eric Hekler
金额:
$23.87万
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:
2019-03-06 至 2023-02-28
关键词:
Alcohol consumptionApple watchAreaBehaviorCellular PhoneComputerized Medical RecordDataDietDrug InteractionsEngineeringFatigueFosteringHealthHealth behaviorHealth behavior changeHospitalsIndividualInterventionLabelLeadLocationMedicalMedical DeviceNatureNotificationOutcomePersonsPhysical activityPredictive FactorProcessProviderRiskSafetySmokingStressSuggestionSystemTechnologyTimeVacuumWalkingWeatherWorkadvanced analyticsbehavior changecostdigitalexercise interventionfitbitmedication compliancemeetingsnovel
中文摘要
点击翻译按钮获取中文摘要
英文摘要
A wide range of technologies, such as smartphones, wearables (e.g., Fitbit, Apple Watch), and medical
devices use alerts to inspire actions of users. Potentially useful alerts come at the cost of alert fatigue
whereby individuals ignore alerts over time. For example, several physical activity interventions use alerts
to inspire activity; notifications work initially but with diminished efficacy over time. Ignoring alerts is
problematic in a variety of domains. For example, notification fatigue reduces the potency of interventions
(e.g., notifications to inspire walking) and can be a safety risk in other areas such as in hospitals where
notification fatigue can lead providers to ignore safety alerts (e.g., cross-drug interaction) provided by the
electronic medical record. There is a need for novel solutions for reducing alert fatigue.
Location, digital traces, and other data enable inference of states when a person would desire/need alerts,
henceforth labeled just-in-time states, but more advanced analytics are needed. For example, a
suggestion to walk (e.g., SMS saying, "Want to go for a walk?") may only produce the desired outcome
when a person's state (e.g., low stress) and context (e.g., no meetings, nice weather) align such that the
person appreciates the notification (what we label receptivity) and can act on it (what we label
opportunity). Estimating the likelihood that a given moment is a just-in-time state requires not only data
but also an approach to manage the multivariate, dynamic, idiosyncratic, and multi-timescale nature of the
problem. Returning to the walking example, stress, weather, and location change dynamically with each
influencing the likelihood that a notification will inspire walking. In our work, results suggest idiosyncrasy in
the factors that predict steps: some people walk more when stressed, others less, and still others are not
influenced by stress. Further, just-in-time notifications cannot be viewed in a vacuum and, instead, are
often part of a more long-term process, such as sustained engagement in a health behavior, thus making
it a multi-timescale problem.
The purpose of this work is to develop a just-in-time state estimation strategy and to stage a
multi-timescale controller for walking as a concrete use-case of a control systems approach to counteract
alert fatigue.
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海外基金