Digital mental health interventions continue to expand as accessible tools for people experiencing depression and anxiety. While most research has focused on disorder-specific apps targeting a single condition, a new meta-analysis by Linardon et al. (2025) evaluates the effectiveness of transdiagnostic-focused apps—tools designed to address shared features of both depression and anxiety within a single platform. These broad-spectrum interventions may offer scalable, low-intensity support to broad populations who face barriers to traditional care.

Key Findings

The meta-analysis synthesized data from 19 randomized controlled trials including over 5,000 participants. The main findings include:

• Small but meaningful effects: Transdiagnostic apps produced modest improvements in depression, anxiety, and general distress compared with control groups (Hedges’ g = 0.29). These effects persisted at follow-up (g = 0.25).
• Comparable to disorder-specific apps: The efficacy of transdiagnostic apps was similar to apps targeting depression or anxiety individually, suggesting broad applicability without sacrificing outcomes.
• Stronger effects in CBT-based apps and waitlist comparisons: Apps grounded in cognitive-behavioral therapy (CBT) and those compared to waitlist controls showed larger improvements, highlighting the therapeutic potential of structured interventions and the impact of control type.
• Engagement and attrition challenges: Average post-test attrition was ~29%, and engagement varied widely across studies. Guided apps showed lower dropout rates than unguided apps, though only a small number of trials included therapist support.
• Core components across apps: Common features included cognitive restructuring, mindfulness, behavioral activation, goal setting, and mood monitoring, reflecting strategies that target underlying mechanisms of depression and anxiety.

Discussion and Implications

While effect sizes were small, they may be clinically relevant. The number-needed-to-treat (NNT ≈ 12) indicates that one in twelve users may benefit directly from these interventions. Transdiagnostic apps could serve as a low-intensity, scalable complement to traditional therapy, particularly for individuals with comorbid symptoms.

The findings also highlight areas for improvement in future research:

• Active control comparisons should be prioritized to avoid inflating efficacy estimates from waitlist comparisons.
• Engagement strategies and personalization need further development to reduce attrition and optimize outcomes.
• Integration with clinician-guided care or hybrid models could enhance effectiveness while maintaining scalability.

Overall, this meta-analysis supports the public health relevance of transdiagnostic apps, demonstrating their potential to reach populations who may not otherwise access evidence-based treatments, and offering a flexible tool for addressing both depression and anxiety.

Read the full study: Transdiagnostic-focused apps for depression and anxiety: a meta-analysis, Linardon et al., npj Digital Medicine, 2025