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Digital health interventions (DHIs) offer potential solutions to supplement traditional mental health services, though the relative efficacy of different types of interventions remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to systematically compare the treatment effects of digital health interventions driven by different mechanisms on depression and anxiety symptoms in this population through a Bayesian network meta-analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic search was conducted in major databases such as PubMed, Embase, and PsycINFO (up to September 2025), including randomized controlled trials (RCTs) targeting depression or anxiety symptoms in individuals aged 12\u201325 years. Interventions were categorized based on treatment mechanisms into four types: cognitive behavioral therapy-based digital interventions (CBT-DI), third-wave digital therapies (TWDT), general digital mental health support (GDMHS), and technology-enhanced innovative interventions (TEII). The primary outcome measure was the standardized mean difference (SMD), with the cumulative ranking probability assessed using the surface under the cumulative ranking curve (SUCRA).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 18 RCTs involving 5, 821 participants were included. Network meta-analysis indicated that CBT-DI achieved the highest surface under the cumulative ranking curve (SUCRA) values for both depression (79.3%) and anxiety (83.4%). In pairwise comparisons with no intervention controls, CBT-DI demonstrated a statistically significant improvement in anxiety symptoms (SMD\u2009=\u20090.33, 95% CrI: 0.05 to 0.69). However, for depression, the improvement associated with CBT-DI did not reach statistical significance (SMD\u2009=\u20090.44, 95% CrI: -0.02 to 0.91), suggesting that the high ranking probability reflects a potential trend rather than confirmatory evidence of superiority. TWDT and GDMHS demonstrated moderate efficacy for both symptoms, ranking above usual care and no intervention controls. The evidence quality assessment (GRADE) indicated that the primary outcomes were of low to moderate quality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Digital health interventions, particularly CBT-based interventions (CBT-DI), were associated with statistically significant improvements in anxiety symptoms. For depression, while CBT-DI ranked highest in probability, it did not demonstrate statistical superiority over controls. Given the imprecision in effect estimates, CBT-DI may be considered a potential complementary measure within a stepped-care mental health system. Results should be interpreted with caution due to wide credible intervals, and further high-quality studies are required to confirm these findings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13034-026-01042-3","type":"journal-article","created":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T05:08:10Z","timestamp":1771045690000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Comparative efficacy of digital health interventions for depression and anxiety symptoms in adolescents and young adults: a systematic review and bayesian network meta-analysis"],"prefix":"10.1186","volume":"20","author":[{"given":"Haozhe","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiguan","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjia","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujie","family":"Guan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyu","family":"Liao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enliang","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghua","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,14]]},"reference":[{"issue":"1","key":"1042_CR1","doi-asserted-by":"publisher","first-page":"e42","DOI":"10.1192\/j.eurpsy.2025.29","volume":"68","author":"V Baldini","year":"2025","unstructured":"Baldini V, Gnazzo M, Maragno M, et al. 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