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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
223
Reinforcement learning algorithm powered cognitive and behavioral intervention
cognitive and behavioral intervention
the First Hospital of China Medical University
Shenyang, Liaoning, China
PHQ9 Response
A user is said to responded to the intervention if the PHQ9 score dropped no less than 50% compared to the baseline
Time frame: Immeidately after intervention
GAD7 Response
A user is said to responded to the intervention if the PHQ9 score dropped no less than 50% compared to the baseline
Time frame: Immeidately after intervention
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