𝗟𝗼𝗻𝗲𝗹𝗶𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝗪𝗲𝗹𝗹 𝗕𝗲𝗶𝗻𝗴 𝗶𝗻 𝗙𝗶𝗻𝗻𝗶𝘀𝗵 𝗜𝗺𝗺𝗶𝗴𝗿𝗮𝗻𝘁𝘀: 𝗔 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗗𝗮𝘁𝗮𝘀𝗲𝘁 𝗳𝗿𝗼𝗺 𝗪𝗲𝗮𝗿𝗮𝗯𝗹𝗲𝘀 𝗮𝗻𝗱 𝗣𝗮𝘀𝘀𝗶𝘃𝗲 𝗗𝗮𝘁𝗮 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 provides one of the most comprehensive resources to date on daily behavior, physiology, and emotional states in real life.
The study followed 39 first generation immigrants in Finland for 28 days and combined continuous data from wearables with smartphone derived digital behavior and validated ecological momentary assessments.
𝗧𝗵𝗲 𝗱𝗮𝘁𝗮𝘀𝗲𝘁 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝘀:
• Raw physiological signals, sleep metrics, heart rate and heart rate variability
• Activity and movement data from wearables
• Screen events, calls, messages and notifications from smartphones
• Daily short surveys on loneliness and affect delivered multiple times each day
• Weekly questionnaires on stress, depression, social connectedness and well being
This multimodal structure makes the dataset valuable for modeling temporal patterns, identifying digital markers of loneliness, and building new approaches for early detection, prevention and support in mental health.
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Centralive supported data collection on this project by enabling continuous monitoring, participant engagement and secure data flow.
