{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:18:42Z","timestamp":1787635122649,"version":"build-2736575974"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>Digital engagement has become an important factor influencing mental health, yet the complex effects of different usage patterns still require deeper clarification. This study distinguishes digital engagement into instrumental-oriented digital engagement (IE) and affect-oriented digital engagement (AE), and utilizes panel data on the working-age population from the China Family Panel Studies (CFPS) from 2016 to 2022 to examine their associations with depression and their underlying competitive resource mechanisms. The results indicate that IE is associated with higher depression levels, whereas AE is associated with lower depression levels. Mechanism analysis reveals that both types of digital engagement contribute to enhancing psychological mastery resources, but also consume physiological recovery resources such as sleep and exercise. Among them, the physiological loss associated with IE is more likely to offset its psychological gains, whereas AE is more likely to perform an emotional recovery function under conventional intensity levels. Further analysis shows that the association between IE and depression is stronger among populations with high social role stress, and the association between AE and depression exhibits nonlinear characteristics. The study suggests that different digital engagement patterns exhibit asymmetric and competitive resource characteristics. Public health interventions should not simply emphasize reducing digital use, but rather guide individuals to maintain a dynamic balance between instrumental digital loads and moderate emotional recovery.<\/jats:p>","DOI":"10.3389\/fpubh.2026.1887437","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T04:23:15Z","timestamp":1787631795000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The divergent impacts of digital engagement on depression: a longitudinal study of competitive resource mechanisms"],"prefix":"10.3389","volume":"14","author":[{"given":"Jidong","family":"Hu","sequence":"first","affiliation":[{"name":"School of Marxism, Henan Normal University","place":["Xinxiang, Henan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Liu","sequence":"additional","affiliation":[{"name":"Graduate School of Education, Dalian University of Technology","place":["Dalian, Liaoning, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zou","sequence":"additional","affiliation":[{"name":"Graduate School of Education, Dalian University of Technology","place":["Dalian, Liaoning, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"106160","DOI":"10.1016\/j.chb.2019.106160","article-title":"Does time spent using social media impact mental health?: an eight year longitudinal study","volume":"104","author":"Coyne","year":"2020","journal-title":"Comput Hum Behav"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1177\/2167702618812727","article-title":"The longitudinal association between social-media use and depressive symptoms among adolescents and young adults: an empirical reply to Twenge et al. 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