JMIR Publications

ABSTRACT

Background:

Depression and anxiety are common mental disorders across all age groups. Digital intelligent interventions have not only overcome the time and space limitations of traditional psychotherapy but also provided innovative pathways for treating these conditions. However, the specific effectiveness of such interventions among groups with different demographic characteristics remains to be further clarified.

Objective:

To evaluate the effectiveness of digital intelligence interventions on symptoms of depression and anxiety using meta-analytic methods

Methods:

We searched the PubMed, Embase, Cochrane Library, Web of Science, and BIOSIS databases from inception through June 2025 for randomized controlled trials (RCTs) of digital interventions targeting depression or anxiety. Two reviewers independently screened the studies, extracted the data, and assessed the risk of bias using the Cochrane Risk of Bias tool. Meta-analyses were performed using RevMan 5.4 and Stata 15.0. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were used to assess continuous outcomes. Heterogeneity and subgroup analyses were performed.

Results:

Nineteen RCTs involving 4,679 participants were included. Compared with controls, digital interventions significantly reduced depressive symptoms (SMD = −0.25; 95% CI, −0.41 to −0.09; P = .002) and anxiety symptoms (SMD = −0.20; 95% CI, −0.32 to −0.08; P = .0009). Subgroup analysis by intervention duration indicated the largest effect for depressive symptoms at approximately 4 weeks (SMD = −0.26; 95% CI, −0.40 to −0.11; P = .0006). The greatest reduction in anxiety symptoms was observed at 5–8 weeks (SMD = −0.22; 95% CI, −0.47 to 0.03; P = .08), though this did not reach statistical significance.App-based interventions demonstrated the most significant effects on depression and anxiety, with effect sizes of (SMD=-0.44 (95% CI: -0.82, -0.06; P = .02) ;SMD= -0.36 (95% CI: -0.59, -0.12; P = .003), respectively. Furthermore, therapeutic efficacy was superior among the older adult population, showing values of SMD= -0.37 (95% CI: -0.64, -0.09; P = .009) ;SMD= -0.51 (95% CI: -0.87, -0.14; P = .006).

Conclusions:

Nineteen RCTs involving 4,679 participants were included. Compared with controls, digital interventions significantly reduced depressive symptoms (SMD = −0.25; 95% CI, −0.41 to −0.09; P = .002) and anxiety symptoms (SMD = −0.20; 95% CI, −0.32 to −0.08; P = .0009). Subgroup analysis by intervention duration indicated the largest effect for depressive symptoms at approximately 4 weeks (SMD = −0.26; 95% CI, −0.40 to −0.11; P = .0006). The greatest reduction in anxiety symptoms was observed at 5–8 weeks (SMD = −0.22; 95% CI, −0.47 to 0.03; P = .08), though this did not reach statistical significance.App-based interventions demonstrated the most significant effects on depression and anxiety, with effect sizes of (SMD=-0.44 (95% CI: -0.82, -0.06; P = .02) ;SMD= -0.36 (95% CI: -0.59, -0.12; P = .003), respectively. Furthermore, therapeutic efficacy was superior among the older adult population, showing values of SMD= -0.37 (95% CI: -0.64, -0.09; P = .009) ;SMD= -0.51 (95% CI: -0.87, -0.14; P = .006). Clinical Trial: CRD420251069160