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P44 Smarter social housing: user perspectives on technology adoption for healthy homes
  1. Tim Walker1,
  2. Tamaryn Menneer2,
  3. Gengyang Tu2,
  4. Markus Mueller3,
  5. Catherine Leyshon1,
  6. Michael Leyshon1,
  7. Karyn Morrissey4,
  8. Emma Bland2,
  9. Sarah Buckingham5
  1. 1Centre for Geography and Environmental Science, University of Exeter, Penryn, UK
  2. 2European Centre for Environment and Human Health, Medical School, University of Exeter, Truro, UK
  3. 3College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn, UK
  4. 4Sustainability Division, Department of Technology, Management and Economics, Technical University of Denmark, Lyngby, Denmark
  5. 5European Centre for Environment and Human Health, University of Exeter Medical School, Exeter, UK


Background Living in poor quality housing is a significant contributor to public health problems, and represent a considerable societal and economic burden worldwide. However, detecting and responding to a poor home environment remains a challenge, as the causes are often invisible and the impact on health is cumulative and long term. Smart homes are residences augmented with sensors to observe the environment and devices to provide proactive services. Evidence indicates that smart technology can improve home environment management and has potential health benefits. User perspectives on factors for adoption of a smart technology systems are under researched. In response this research examines the factors for adoption, and non-adoption, of a smart technology system to support home environment management for social housing tenants.

Methods 221 social housing tenants were recruited. Participant homes were fitted with sensors to monitor temperature, humidity, and air quality. Participants were provided with a digital dashboard to access their sensor data. Data was collected on participant health, dashboard use, and subsequent changes in home environment. A mixed method sequential research design was employed. Quantitative methods were used to understand determinants and patterns of technology use. Qualitative interviews (n20, strategically sampled) were used to understand factors of feasibility and acceptability.

Results From a user perspective, this study found little evidence of interaction with the sensor data, and almost no evidence of changes in the sensor data as a result of viewing. Ease of use and usefulness were found to be the most important barriers to technology adoption. Both these factors related to how the information was communicated and how effective the dashboard was in converting data into insight. We found that the Housing Association provided important facilitating conditions to the adoption of the smart home technology, specifically for participant trust regarding how the data will be used. We also found that the Housing Assocation were using the dashboard to successful intervene with high-risk properties and provide wellbeing support for their tenants.

Conclusion It is clear from this study that smart home technology is not a panacea. While smart technology was useful for identifying risk, the technology could not identify the exact cause of the risk nor instigate an acceptable intervention. Human intervention was required to fully identify and subsequently offer solutions that addressed the problems. We argue that to improve the home environment for tenants, smart technology capacity must be matched to human capacity for intervention. In sum, this study has shown the potential of smart home technology, which is integrated with a Housing Association tenant support programme, to improve health and wellbeing.

  • Home environment
  • health
  • smart home technology

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