Assessing the feasibility of using smartwatches for low burden, high temporal density capture of longitudinal health data.
评估使用智能手表低负担、高时间密度捕获纵向健康数据的可行性。
基本信息
- 批准号:MR/S003894/1
- 负责人:
- 金额:$ 40.53万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Fellowship
- 财政年份:2018
- 资助国家:英国
- 起止时间:2018 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Longitudinal health data enable researchers and clinicians to explore the causes, progression and treatments of diseases in ways that are not possible with cross-sectional data. Prospective longitudinal cohort studies enable these to be studied at the population level, while N-of-1 studies enable their exploration in individuals. In both cases, there is a trade-off between how frequently data are recorded, and the burden to the participant: higher temporal density provides greater insights into detailed patterns of health but places a higher burden on participants. For some time, researchers have used smartphones for low-cost, high temporal density data capture. Smartphone-based ecological momentary assessment (EMA) prompts participants several times a day in free-living conditions to answer questions about their health. This approach reduces recall biases and errors, increases ecological validity, and can provide very high temporal density data. However, when capturing high temporal density data, smartphone EMA can be highly disruptive. While we perceive smartphones as always nearby, on average smartphones are only within reach ~50% of the time1. This means participants need to disengage from their current tasks to respond. Also, as the smartphone is not necessarily on the body, audible rather than less distracting haptic prompts are required. These disruptions lead to poor compliance rates2, and are problematic in longitudinal cohort studies as increased burden is a concern for participant engagement3.Smartwatches enable us to retain the benefits of EMA, while reducing disruption. As they are worn on the wrist, they are never beyond reach, so time taken to access the device is significantly reduced. Less intrusive haptic prompts can also be used. The recent development of microinteraction-based EMA (uEMA) goes further in reducing disruption: requests are reduced to a single question with a limited set of answers that can be responded to with a single tap. Recent pilot testing4 found that when these elements were combined to form smartwatch-based uEMA, compared with smartphone-base EMA over a 4-week period, the smartwatch system had better compliance (82% v 64%), completion (92% v 67%), and lower levels of disruption (38% v 53%).While this pilot work is supportive of the wider use of smartwatch-based data collection, and the potential for these techniques in public health research has been acknowledged5, they have yet to be used in this context. The feasibility work proposed in this fellowship is essential in enabling the uptake of these methods, helping researchers understand; how these methods perform over longer periods, whether specific groups are more likely than others to find them acceptable, whether their feasibility varies by the type of health data collected, and the feasibility of combining multiple health data collection approaches in a single smartwatch device. The fellowship will also explore how best to analyse the data capture with these methods, which could make a step change in understanding the evolution of health and disease, enabling better causal understanding, earlier intervention and ultimately health improvements. The nature of this work, exploring how new digital technologies can be used to capture health data, aligns strongly with MRC and HDR UK priorities in the areas of Digital Technologies and Informatics for Health.From a personal development perspective, the fellowship will provide the time and resources necessary for me to focus on building my skills and profile in the field of digital phenotyping, moving me closer to my goal of becoming a fully independent researcher leading a digital phenotyping team with an international reputation for excellence.References1.Dey,A,...(2011).UbiComp:163-172. 2.Courvoisier,D...(2012).Psychol Assess,24:713-20.3.Lucas,P,...(2013).BMC Med Res Method,13:564.Intille,S,...(2016).UbiComp:1124-11285.China,G,...(2017).CHI-EA: 2767-277
纵向健康数据使研究人员和临床医生能够以横断面数据无法实现的方式探索疾病的原因,进展和治疗。前瞻性纵向队列研究使这些研究能够在人群水平上进行,而N-of-1研究使其能够在个体中进行探索。在这两种情况下,在记录数据的频率和参与者的负担之间存在权衡:较高的时间密度可以更好地了解详细的健康模式,但会给参与者带来更大的负担。一段时间以来,研究人员一直使用智能手机进行低成本、高时间密度的数据采集。基于智能手机的生态瞬时评估(EMA)每天多次提示自由生活条件下的参与者回答有关其健康的问题。这种方法减少了回忆偏差和错误,增加了生态有效性,并可以提供非常高的时间密度数据。然而,在捕获高时间密度数据时,智能手机EMA可能具有高度破坏性。虽然我们认为智能手机总是在附近,但平均而言,智能手机只有约50%的时间在可及范围内1。这意味着参与者需要从当前的任务中解脱出来才能做出反应。此外,由于智能手机不一定在身体上,因此需要可听的而不是较少分散注意力的触觉提示。这些中断导致依从性差2,并且在纵向队列研究中存在问题,因为增加的负担是参与者依从性的一个问题3。智能手表使我们能够保留EMA的好处,同时减少中断。由于它们戴在手腕上,因此永远不会超出范围,因此访问设备所需的时间大大减少。也可以使用侵入性较小的触觉提示。最近开发的基于微交互的EMA(uEMA)在减少中断方面走得更远:请求被减少到一个问题,只有一组有限的答案,可以通过单击来响应。最近的试点测试4发现,当这些元素结合起来形成基于智能手表的uEMA时,与基于智能手机的EMA相比,在4周的时间内,智能手表系统具有更好的合规性(82%对64%),完成(92%对67%),以及较低的中断水平(38%对53%)。虽然这项试点工作支持更广泛地使用基于智能手表的数据收集,并且这些技术在公共卫生研究中的潜力已经得到证实5,它们尚未在这方面得到使用。这项研究中提出的可行性工作对于采用这些方法至关重要,帮助研究人员了解这些方法在较长时间内的表现,特定群体是否比其他人更容易接受它们,它们的可行性是否因收集的健康数据类型而异,以及在单个智能手表设备中结合多种健康数据收集方法的可行性。该研究金还将探讨如何最好地分析这些方法收集的数据,这可能会在理解健康和疾病的演变方面发生一步变化,从而能够更好地理解因果关系,早期干预并最终改善健康状况。这项工作的性质,探索如何新的数字技术可以用来捕捉健康数据,与MRC和HDR英国在数字技术和信息学领域的优先事项强烈一致健康。从个人发展的角度来看,奖学金将提供必要的时间和资源,让我专注于建立我的技能和个人资料在数字表型领域,移动我更接近我的目标,成为一个完全独立的研究人员领导一个数字表型团队与卓越的国际声誉。(2011).UbiComp:163-172. 2.Courvoisier,D.(2012).Psychol Assess,24:713- 20.3.Lucas,P,.(2013).BMC Med Res Method,13:564.(2016).UbiComp:1124- 11285.China,G,.(2017).CHI-EA:2767-277
项目成果
期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Assessing the feasibility of using smartwatch-based Ecological Momentary Assessment techniques for determining longitudinal patterns and contexts of alcohol use in UK adults (study protocol)
评估使用基于智能手表的生态瞬时评估技术来确定英国成年人饮酒的纵向模式和背景的可行性(研究方案)
- DOI:
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Skinner A
- 通讯作者:Skinner A
Future directions for integrative objective assessment of eating using wearable sensing technology
使用可穿戴传感技术对饮食进行综合客观评估的未来方向
- DOI:10.31232/osf.io/udwf2
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Skinner A
- 通讯作者:Skinner A
Identifying stakeholder priorities in use of wearable cameras for researching parent-child interactions
确定利益相关者在使用可穿戴相机研究亲子互动时的优先事项
- DOI:10.3389/frcha.2023.1111299
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Skinner A
- 通讯作者:Skinner A
Does repeatedly viewing overweight versus underweight images change perception of and satisfaction with own body size?
- DOI:10.1098/rsos.190704
- 发表时间:2020-04-01
- 期刊:
- 影响因子:3.5
- 作者:Bould, Helen;Noonan, Katharine;Harmer, Catherine J.
- 通讯作者:Harmer, Catherine J.
alcoWatch - Exploring the feasibility of using smartwatch-based Ecological Momentary Assessment for longitudinal measurement of lifestyle health behaviours
alcoWatch - 探索使用基于智能手表的生态瞬时评估来纵向测量生活方式健康行为的可行性
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Skinner AL
- 通讯作者:Skinner AL
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Andy Skinner的其他文献
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