Game-Based Digital Intervention for Relieving Depression and Anxiety Symptoms

NCT ID: NCT06301555

Last Updated: 2024-03-08

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 223 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-11-01
• Study Completion Date: 2024-02-01

Brief Summary

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.

Conditions

Depression; Anxiety

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: SINGLE

Study Groups

Blank Control

No intervention

Group Type: NO_INTERVENTION

No interventions assigned to this group

RL Algorithm Intervention

Group Type: EXPERIMENTAL

Reinforcement learning algorithm powered cognitive and behavioral intervention

Intervention Type: BEHAVIORAL

Reinforcement learning algorithm powered cognitive and behavioral intervention

No Algorithm Active Control

Group Type: ACTIVE_COMPARATOR

cognitive and behavioral intervention

Intervention Type: BEHAVIORAL

cognitive and behavioral intervention

Interventions

Reinforcement learning algorithm powered cognitive and behavioral intervention

Reinforcement learning algorithm powered cognitive and behavioral intervention

Intervention Type: BEHAVIORAL

cognitive and behavioral intervention

cognitive and behavioral intervention

Intervention Type: BEHAVIORAL

Eligibility Criteria

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.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 60 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Adai Technology (Beijing) Co., Ltd.

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

the First Hospital of China Medical University

Shenyang, Liaoning, China

Countries

China

References

Shao X, Liu L, Zhu X, Tian C, Li D, Zhang L, Liu X, Liu Y, Zhu G, Li L. Personalized game-based digital intervention for relieving depression and anxiety symptoms: a pilot RCT. Npj Ment Health Res. 2025 Jul 3;4(1):27. doi: 10.1038/s44184-025-00141-x.

Reference Type: DERIVED

PMID: 40610644 (View on PubMed)

Other Identifiers

db2023

Identifier Type: -

Identifier Source: org_study_id