A Mixed Methods Exploration of the Relationship between Activities within the Home and Health in Older People with Heart Failure: Implications for Lifestyle Monitoring

Introduction Older people and those with long-term conditions are more vulnerable to declining health. One experimental method of detecting early signs of a health decline is lifestyle monitoring (LM) based on the idea that the health state of an individual can be inferred via indirect measurement of home activities. This primarily qualitative research explored activities within the context of heart failure (HF), and range of factors that shape everyday activity. Quantitative analysis tested whether home activities vary according to the health state. Methods A mixed methods approach was utilised. Quantitative: analysis of secondary LM data explored associations between proxy activity and self-reported measures of health from 17 participants with HF, aged 60 years and over. Qualitative: twenty older people with HF were interviewed (and 11 partners) to explore whether activities changed during variations in their symptoms; and wider influences on everyday activity. Data was analysed using template analysis. Views of 6 specialist nurses, 27 attendees of a HF support group, and 2 experts on LM, were summarised. Results LM data analysis proved that proxy activity levels varied according to self-reported health states, within a significant proportion of the analysis. However results were complex, without any observable patterns in activity according to health. Qualitative enquiry confirmed that health does influence everyday activity but this occurs in a complex way, and is influenced by individual, psychological, contextual, and environmental factors. However during an exacerbation of symptoms common activities were undertaken to ease symptoms. Discussion This study adds to the understanding of everyday life lived within the context of HF, and debate about how to improve health monitoring technology. Home activity has many influences, and of these attitudes and psychological factors are key and thus this poses a challenge to LM based on the idea that the health state of an individual can be inferred from home activity. The technology therefore requires further consideration of purpose, methods, and target audience.