How did you sleep?: Exploring by-proxy sleep assessment in a field study setup

Objectives/Introduction: Sleep is crucial for both mental and physical health, and sleep disorders can pose a severe burden on health‐related quality of life. Importantly, family members may be affected by each other's sleep and wake behavior. Finally, there may be differences in sleep perception between family members. As a tool for future studies, we designed a concept for ‘By‐Proxy Sleep Assessment’, namely, the rating of one's partner's or children's sleep quality. This might provide a useful additional sleep quality measure, especially when assessing people with difficulties reporting their own sleep, such as children and people with intellectual disabilities or dementia. Methods: We used data from the FieldLab study, created to collect data on sleep and sleep related behaviors in five households, using an IoT ecosystem to combine subjective and objective information from connected objects measuring variables such as sleep, physical activity and environmental factors. A chat application enabled communication between researchers and participants and qualitative data was obtained through means of questionnaires and scheduled chatbot messages. Participants were asked to rate subjective sleep quality as well as the sleep quality of their partners and children on a scale of 0 to 10 each morning. Results: A total of 143 nights of partner By‐Proxy Sleep Assessment were collected from three couples and 40 nights of By‐Proxy Sleep Assessment for children from two couples. Subject‐proxy differences were averaged over the study period and varied between −0.38 ± 1.32 (−3 ‐ +2) and 1.23 ± 1.30 (−1 ‐ +3) for partners and −0.11 ± 0.97 (−3 ‐ +2) and 0.61 ± 1.50 (−1 ‐ +4) for children/parents. Preliminary analysis of IoT data and qualitative measurements through the chatbot revealed that both internal (e.g. migraines) and external factors (e.g. room temperature) contribute to discrepancies in sleep quality assessment by a proxy. Conclusions: Experience sampling studies can offer a new perspective on sleep quality and sleep perception. Although the By‐Proxy Sleep Assessment ratings already correlated rather well with the subjects’ own ratings, the IoT data may aid in improving the reliability of this approach.