{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T06:19:32Z","timestamp":1787552372779,"version":"build-2736575974"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"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:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To systematically evaluate and meta-analyze the effectiveness of digital health interventions (DHIs) in reducing occupational burnout among nurses and nursing staff compared with usual care, waitlist control, or non-digital interventions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Following PRISMA 2020 guidelines, six electronic databases (PubMed\/MEDLINE, CINAHL, Embase, Web of Science, PsycINFO, and Scopus) were searched from January 2015 to March 2025 for randomized controlled trials and quasi-experimental studies. Risk of bias was assessed using Cochrane RoB 2 and JBI checklists. Random-effects meta-analysis using the DerSimonian\u2013Laird method, pre-specified subgroup and sensitivity analyses, publication-bias assessment, and GRADE certainty assessment were performed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Thirty-seven studies encompassing approximately 8,450 nurses and nursing staff across 14 countries were included, of which 28 provided data for quantitative synthesis. The pooled standardized mean difference indicated a statistically significant moderate reduction in burnout (\n                      <jats:italic>SMD<\/jats:italic>\n                      = \u22120.47; 95%\n                      <jats:italic>CI<\/jats:italic>\n                      : \u22120.65 to \u22120.29;\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001;\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      = 72%). Web-based cognitive behavioral therapy (CBT) and acceptance and commitment therapy (ACT) programs showed the largest pooled effect (\n                      <jats:italic>k<\/jats:italic>\n                      = 10;\n                      <jats:italic>SMD<\/jats:italic>\n                      = \u22120.72; 95%\n                      <jats:italic>CI<\/jats:italic>\n                      : \u22121.05 to \u22120.39), followed by AI-tailored mobile interventions (\n                      <jats:italic>k<\/jats:italic>\n                      = 3;\n                      <jats:italic>SMD<\/jats:italic>\n                      = \u22120.61; 95%\n                      <jats:italic>CI<\/jats:italic>\n                      : \u22120.93 to \u22120.29;\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      = 41%). Emotional exhaustion (EE) was the most responsive burnout dimension (\n                      <jats:italic>SMD<\/jats:italic>\n                      = \u22120.53), whereas personal accomplishment (PA) showed the weakest improvement (\n                      <jats:italic>SMD<\/jats:italic>\n                      = +0.24). Guided interventions produced larger effects than self-guided programs (\n                      <jats:italic>p<\/jats:italic>\n                      = 0.04), and longer-duration interventions showed larger pooled effects than brief programs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>DHIs, particularly structured and guided web-based CBT\/ACT programs, were associated with moderate reductions in occupational burnout among nurses and nursing staff. Early evidence for AI-tailored interventions is promising but requires independent replication. The findings support the integration of evidence-based DHIs into broader workforce well-being strategies that combine individual support with organizational action on the structural determinants of burnout.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Systematic Review Registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/www.crd.york.ac.uk\/PROSPERO\/<\/jats:ext-link>\n                      , identifier CRD420261365184.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1879258","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T05:31:00Z","timestamp":1787549460000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Digital health interventions for reducing occupational burnout in nurses: a systematic review and 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