{"paper":{"title":"Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.QM"],"primary_cat":"stat.AP","authors_text":"Amos A Folarin, Brenda WJH Penninx, Callum Stewart, Carolin Oetzmann, David C. Mohr, Faith Matcham, Femke Lamers, Heet Sankesara, Inez Myin-Germeys, Josep Maria Haro, Katie M White, Matthew Hotopf, Nicholas Cummins, Pauline Conde, Peter Annas, Petroula Laiou, RADAR-CNS consortium, Richard JB Dobson, Sara Siddi, Sara Simblett, Shaoxiong Sun, Srinivasan Vairavan, Til Wykes, Vaibhav A Narayan, Yatharth Ranjan, Yuezhou Zhang, Zulqarnain Rashid","submitted_at":"2023-12-05T18:39:39Z","abstract_excerpt":"Objective: This study aimed to explore the associations between depression severity and wearable-measured circadian rhythms, accounting for seasonal impacts and quantifying seasonal changes in circadian rhythms.Materials and Methods: Data used in this study came from a large longitudinal mobile health study. Depression severity (measured biweekly using the 8-item Patient Health Questionnaire [PHQ-8]) and behaviors (monitored by Fitbit) were tracked for up to two years. Twelve features were extracted from Fitbit recordings to approximate circadian rhythms. Three nested linear mixed-effects mode"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02953","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2312.02953/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}