Hargreaves Sarah, Hawley Mark S, Haywood Annette, Enderby Pamela M
Centre for Assistive Technology and Connected Healthcare, School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
Public Health, School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
J Med Internet Res. 2017 Jun 28;19(6):e231. doi: 10.2196/jmir.6931.
Health technologies are being developed to help people living at home manage long-term conditions. One such technology is "lifestyle monitoring" (LM), a telecare technology based on the idea that home activities may be monitored unobtrusively via sensors to give an indication of changes in health-state. However, questions remain about LM technology: how home activities change when participants experience differing health-states; and how sensors might capture clinically important changes to inform timely interventions.
The objective of this paper was to report the findings of a study aimed at identifying changes in activity indicative of important changes in health in people with long-term conditions, particularly changes indicative of exacerbation, by exploring the relationship between home activities and health among people with heart failure (HF). We aimed to add to the knowledge base informing the development of home monitoring technologies designed to detect health deterioration in order to facilitate early intervention and avoid hospital admissions.
This qualitative study utilized semistructured interviews to explore everyday activities undertaken during the three health-states of HF: normal days, bad days, and exacerbations. Potential recruits were identified by specialist nurses and attendees at an HF support group. The sample was purposively selected to include a range of experience of living with HF.
The sample comprised a total of 20 people with HF aged 50 years and above, and 11 spouses or partners of the individuals with HF. All resided in Northern England. Participant accounts revealed that home activities are in part shaped by the degree of intrusion from HF symptoms. During an exacerbation, participants undertook activities specifically to ease symptoms, and detailed activity changes were identified. Everyday activity was also influenced by a range of factors other than health.
The study highlights the importance of careful development of LM technology to identify changes in activities that occur during clinically important changes in health. These detailed activity changes need to be considered by developers of LM sensors, platforms, and algorithms intended to detect early signs of deterioration. Results suggest that for LM to move forward, sensor set-up should be personalized to individual circumstances and targeted at individual health conditions. LM needs to take account of the uncertainties that arise from placing technology within the home, in order to inform sensor set-up and data interpretation. This targeted approach is likely to yield more clinically meaningful data and address some of the ethical issues of remote monitoring.
正在研发健康技术以帮助居家生活的人们管理长期疾病。其中一项技术是“生活方式监测”（LM），这是一种远程护理技术，其基于这样的理念：可以通过传感器对家庭活动进行不引人注意的监测，以指示健康状况的变化。然而，关于LM技术仍存在一些问题：当参与者处于不同健康状态时家庭活动如何变化；以及传感器如何捕捉具有临床重要意义的变化以指导及时干预。
本文的目的是报告一项研究的结果，该研究旨在通过探索心力衰竭（HF）患者的家庭活动与健康之间的关系，确定表明长期疾病患者健康发生重要变化的活动变化，特别是表明病情加重的变化。我们旨在增加知识库，为旨在检测健康恶化以促进早期干预并避免住院的家庭监测技术的开发提供信息。
这项定性研究采用半结构化访谈来探索HF患者在三个健康状态下（正常日子、糟糕日子和病情加重期）所进行的日常活动。潜在参与者由专科护士和HF支持小组的参与者确定。样本是有目的地选择的，以包括一系列HF患者的生活经历。
样本包括20名50岁及以上的HF患者以及11名HF患者的配偶或伴侣。他们都居住在英格兰北部。参与者的描述显示，家庭活动部分受HF症状干扰程度的影响。在病情加重期间，参与者会专门进行一些活动来缓解症状，并确定了详细的活动变化。日常活动还受到健康以外的一系列因素的影响。
该研究强调了精心开发LM技术以识别健康发生临床重要变化期间出现的活动变化的重要性。旨在检测恶化早期迹象的LM传感器、平台和算法的开发者需要考虑这些详细的活动变化。结果表明，为了推动LM的发展，传感器设置应根据个人情况进行个性化定制，并针对个人健康状况。LM需要考虑将技术置于家庭环境中所产生的不确定性，以便为传感器设置和数据解释提供信息。这种有针对性的方法可能会产生更具临床意义的数据，并解决远程监测的一些伦理问题。
