The impact of sleep and movement behaviour on daily mood in people with type 2 diabetes: A smartphone‐based digital phenotyping study

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OBJECTIVE: To examine how sleep and movement behaviours, measured on smartphones via ecological momentary assessment (EMA), GPS and accelerometer, impact subsequent daily mood in people with type 2 diabetes (T2D) compared to those without. METHODS: Sixty-one participants with (n = 32) and without (n = 29) T2D underwent 2 months of smartphone-based data collection through phone sensors (GPS, accelerometer) and EMAs. Daily sleep, movement and mood (happiness, sadness, stress, anger) were assessed. Dynamic structural equation modelling examined the impact of sleep and movement on subsequent mood, adjusted for age, gender and employment status. RESULTS: We found 18 significant within-person effects between smartphone-derived behaviour and subsequent mood, with 17 within-person effects indicating behaviour had a positive effect on mood. For people with and without T2D, higher physical activity, better sleep quality and visiting more locations predicted increased happiness, and higher physical activity predicted lower sadness. However, unique behaviour-mood effects were also found for each group, such as greater actigraphy-derived step count predicting greater anger in people with T2D (0.13 [0.05, 0.2]) but having no effect for those without. CONCLUSIONS: Though effects were small, results indicate smartphone-derived behaviour influences daily mood for both people with and without T2D, but that the nuances of these relationships may differ. If daily mood correlates differ between people with and without T2D, digital phenotyping for early detection and intervention may need to be tailored to those with T2D.

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