{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T07:17:51Z","timestamp":1792135071410,"version":"4.4.0"},"reference-count":66,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education of the Republic of Korea","award":["NRF-2022S1A5A2A03050428"],"award-info":[{"award-number":["NRF-2022S1A5A2A03050428"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Depression contributes to a wide range of maladjustment problems. With the development of technology, objective measurement for behavior and functional indicators of depression has become possible through the passive sensing technology of digital devices. Focusing on location data, we systematically reviewed the relationship between depression and location data. We searched Scopus, PubMed, and Web of Science databases by combining terms related to passive sensing and location data with depression. Thirty-one studies were included in this review. Location data demonstrated promising predictive power for depression. Studies examining the relationship between individual location data variables and depression, homestay, entropy, and the normalized entropy variable of entropy dimension showed the most consistent and significant correlations. Furthermore, variables of distance, irregularity, and location showed significant associations in some studies. However, semantic location showed inconsistent results. This suggests that the process of geographical movement is more related to mood changes than to semantic location. Future research must converge across studies on location-data measurement methods.<\/jats:p>","DOI":"10.3390\/ijerph20115984","type":"journal-article","created":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T03:39:36Z","timestamp":1685331576000},"page":"5984","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["A Systematic Review of Location Data for Depression Prediction"],"prefix":"10.3390","volume":"20","author":[{"given":"Jaeeun","family":"Shin","sequence":"first","affiliation":[{"name":"Department of psychology, Chung-Ang University, Seoul 06974, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sung Man","family":"Bae","sequence":"additional","affiliation":[{"name":"Department of Psychology and Psychotherapy, Dankook University, Cheonan 31116, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,29]]},"reference":[{"key":"ref_1","unstructured":"WHO (2023, April 13). 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