Design and Evaluation of an Intelligent Mental Health System Based on Voice Analysis and an Empathetic Cognitive Behavioral Therapy (CBT) Chatbot for Perceived Stress Management: A Three-Arm Pilot Randomized Controlled Trial

This study is a three-arm, parallel-group pilot randomized controlled trial designed to evaluate the feasibility, acceptability, psychological safety, and preliminary effectiveness of a Persian-language artificial intelligence (AI)-based cognitive behavioral therapy (CBT) chatbot for the management of perceived stress. A separate research component will use voice recordings collected during the study to develop and preliminarily evaluate an AI model for stress detection. The voice-based model is independent of the randomized psychological intervention and will not be used to guide or modify the intervention during this trial. The study consists of two complementary research components. The first component is a pilot randomized controlled trial evaluating an AI-based CBT chatbot. The second component involves the collection and analysis of voice data for the development of a machine-learning model capable of detecting or estimating stress from acoustic and paralinguistic characteristics of speech.

Randomized Controlled Trial Component

Following completion of the study entry procedures and baseline assessments, eligible participants will be randomly allocated in a 1:1:1 ratio to one of three parallel study conditions: an AI-based CBT chatbot intervention, an active mental health content condition, or a waitlist control condition. The intervention period will last 14 days. Randomization will be performed using variable block randomization, with stratification based on baseline stress level and sex. The allocation sequence will be generated independently or through a secure allocation procedure. Due to the nature of the psychological interventions, participants cannot be blinded to the type of support they receive. Where feasible, the data analyst responsible for the primary analysis will remain unaware of group allocation until completion of the main analysis. Participants assigned to the experimental condition will interact with a Persian-language AI-based chatbot designed to deliver structured psychological support based on cognitive behavioral therapy principles. The intervention will be delivered through structured sessions during the 14-day study period. The chatbot intervention is designed to incorporate core CBT-oriented components including psychoeducation about stress, identification of stress-related thoughts and behavioral patterns, cognitive restructuring, development of adaptive coping strategies, behavioral exercises, and stress-management techniques. The system is intended to provide interactive and contextually relevant conversations while maintaining the predefined scope of the intervention. A large language model will support the conversational functionality of the chatbot. The language model will operate within a predefined prompting, intervention, and safety framework rather than providing unrestricted mental health advice. The system will be designed to maintain conversations within the intended CBT and stress-management scope and to reduce the likelihood of inappropriate, unsafe, or clinically unsupported responses. Before participant use, candidate language models and intervention components will undergo preliminary evaluation using predefined mental health scenarios. These evaluations will include CBT-related scenarios, psychologically sensitive situations, crisis-related scenarios, and adversarial or Red-Team testing intended to identify unsafe, inappropriate, or out-of-scope model behavior. Mental health professionals will contribute to the evaluation of therapeutic appropriateness, adherence to CBT principles, empathy, safety, and response quality. Participants assigned to the active comparator condition will receive non-adaptive mental health and stress-management content. This content may include psychoeducational information and structured material related to stress management, relaxation, breathing techniques, mindfulness, coping strategies, and self-care. Unlike the experimental condition, the active comparator will not provide individualized, adaptive, conversational CBT interactions generated in response to participant messages. Participants assigned to the waitlist control condition will not receive an active psychological intervention during the 14-day study period. They will complete the study assessments according to the study schedule and will remain subject to the same safety procedures applicable to the study population.

Psychological Safety and Human Oversight

Psychological safety is an important component of the study design. The chatbot will be explicitly presented to participants as an artificial intelligence system and not as a human therapist, psychiatrist, psychologist, or substitute for professional mental health care. Participants will be informed that AI-generated responses may have limitations and should not be interpreted as independent medical or psychiatric diagnosis or treatment. The system will incorporate predefined safety guardrails intended to identify potentially high-risk interactions, including indications of acute psychological crisis or possible self-harm or suicidal risk. When a potentially high-risk situation is identified, the automated intervention will not be relied upon as the sole response mechanism. The study safety protocol will provide procedures for escalation, human review where appropriate, and referral to suitable professional or emergency mental health services. A human-in-the-loop framework will therefore be incorporated into the safety architecture of the chatbot component. Mental health professionals will participate in the development and review of CBT protocols, assessment of chatbot response quality, review of potentially unsafe interactions, evaluation of therapeutic fidelity, and review of relevant safety events. Interaction data generated during the intervention may also be used to characterize participant engagement and to evaluate how the system performs within the intended CBT framework. These data may include the number and timing of interactions, session duration, participant engagement with exercises, and anonymized conversational information required for research evaluation.