Game-based digital interventions for depression therapy: a systematic review and meta-analysis

Area of Science:

• Digital Health
• Psychiatry
• Behavioral Science

Background:

• Depression is a prevalent mental health disorder with significant global impact.
• Traditional treatments for depression have limitations, necessitating exploration of novel therapeutic approaches.
• Game-based digital interventions offer a potentially engaging and accessible modality for depression management.

Purpose of the Study:

• To systematically review and meta-analyze randomized controlled trials (RCTs) of game-based digital interventions for depression.
• To examine the overall effectiveness and identify factors influencing treatment outcomes.
• To inform future research and clinical application of these interventions.

Main Methods:

• Systematic literature search of databases using defined keywords and inclusion criteria.
• Meta-analysis of 10 RCTs (from 19 included studies) using a random effects model.
• Calculation of effect sizes (Cohen's d) and subgroup analyses based on intervention type and support level.

Main Results:

• Game-based digital interventions demonstrated a moderate effect size for depression therapy at posttreatment (d=-0.47).
• Psycho-education and training interventions showed a smaller effect compared to other game types.
• Self-help interventions and use of a waiting list as control yielded better outcomes.

Conclusions:

• The findings support the effectiveness of game-based digital interventions as a viable treatment option for depression.
• Intervention design, delivery mode (self-help vs. supported), and control group selection may influence efficacy.
• Further large-scale, high-quality RCTs with long-term follow-up are recommended to solidify evidence and optimize treatment strategies.