Digital health interventions for reducing occupational burnout in nurses: a systematic review and meta-analysis

<jats:sec>
<jats:title>Objective</jats:title>
<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>
</jats:sec>
<jats:sec>
<jats:title>Methods</jats:title>
<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–Laird method, pre-specified subgroup and sensitivity analyses, publication-bias assessment, and GRADE certainty assessment were performed.</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Results</jats:title>
<jats:p>
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 (
<jats:italic>SMD</jats:italic>
= −0.47; 95%
<jats:italic>CI</jats:italic>
: −0.65 to −0.29;
<jats:italic>p</jats:italic>
&amp;lt; 0.001;
<jats:italic>I</jats:italic>
<jats:sup>2</jats:sup>
= 72%). Web-based cognitive behavioral therapy (CBT) and acceptance and commitment therapy (ACT) programs showed the largest pooled effect (
<jats:italic>k</jats:italic>
= 10;
<jats:italic>SMD</jats:italic>
= −0.72; 95%
<jats:italic>CI</jats:italic>
: −1.05 to −0.39), followed by AI-tailored mobile interventions (
<jats:italic>k</jats:italic>
= 3;
<jats:italic>SMD</jats:italic>
= −0.61; 95%
<jats:italic>CI</jats:italic>
: −0.93 to −0.29;
<jats:italic>I</jats:italic>
<jats:sup>2</jats:sup>
= 41%). Emotional exhaustion (EE) was the most responsive burnout dimension (
<jats:italic>SMD</jats:italic>
= −0.53), whereas personal accomplishment (PA) showed the weakest improvement (
<jats:italic>SMD</jats:italic>
= +0.24). Guided interventions produced larger effects than self-guided programs (
<jats:italic>p</jats:italic>
= 0.04), and longer-duration interventions showed larger pooled effects than brief programs.
</jats:p>
</jats:sec>
<jats:sec>
<jats:title>Conclusion</jats:title>
<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>
</jats:sec>
<jats:sec>
<jats:title>Systematic Review Registration</jats:title>
<jats:p>
<jats:ext-link>https://www.crd.york.ac.uk/PROSPERO/</jats:ext-link&gt;
, identifier CRD420261365184.
</jats:p>
</jats:sec>