Objective: To collect preliminary data and assess the preliminary effectiveness of a game-based digital therapeutics (DTx) intervention for individuals with symptoms of anxiety and depression, and to investigate whether reinforcement learning (RL) can personalize the intervention and enhance effectiveness. Design: Randomized controlled trial with three arms. Setting: Internet-based recruitment and delivery of the intervention. Participants: 223 individuals with symptoms of anxiety and depression, aged between 18 and 50 years. Interventions: Participants were randomly assigned to one of three groups: game-based DTx with RL algorithm (RL algorithm group), game-based DTx without RL algorithm (no algorithm group), and a blank control group. Main Outcomes and Measures: The primary outcomes were reductions in symptoms of anxiety and depression, measured using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder 7-item scales. Response rates and rates of recovery, as well as the impact of demographic variables, were also examined.

Inclusion Criteria:

1. age between 18 and 60 years;
2. having a PHQ-9 score or a GAD-7 score upon enrollment;
3. being able to operate a smartphone fluently;
4. having normal vision after correction

Exclusion Criteria:

1. clinical diagnoses of severe psychiatric conditions such as schizophrenia or bipolar disorder;
2. at high risk of suicide or self-harm;
3. having significant cognitive impairments;
4. active substance abuse or dependence;
5. currently undergoing other psychological or pharmacological treatments for depression or anxiety;
6. pregnant individuals or those with postpartum depression, and those with serious physical health conditions that could impact mental health.