Nurse-led Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) in University Students With Mild to Moderate Mental Health Problems

Summary

This study aims to evaluate the feasibility, acceptability, and potential effectiveness of a nurse-led digital cognitive behavioral therapy for insomnia (dCBT-I) via large language model based-chatbot among university students with mental health problems.

Conditions

• Mental Health

Interventions

BEHAVIORAL

Brief sleep health advice

At baseline, both groups will receive a 1-on-1 brief sleep health advice developed using guidelines by U.S. Centers for Diseases Control and Prevention and a booklet providing behavioral guidance on lifestyle and environmental factors related to sleep and insomnia.

BEHAVIORAL

2 weeks of chatbot-based daily sleep diary

Following randomization, participants in the intervention group will complete a 2-week chatbot-based daily sleep diary. Each morning (e.g., 8:00 am), participants will be prompted via Whatsapp message delivered by chatbot to report key sleep parameters from the previous night, including bedtime, wake time, sleep onset latency, number and duration of nocturnal awakenings, total sleep time, and perceived sleep quality. The collected sleep diary data will be processed by the chatbot to generate tailored and personalized feedback, supporting individualized sleep recommendations and behavioral adjustments. At the initiation of the intervention, participants will also complete a brief baseline questionnaire to establish personalized treatment goals related to sleep improvement. Throughout the intervention period, participants will have continuous access to chatbot-delivered support, including adaptive guidance based on diary inputs, reinforcement of recommended sleep strategies, and progress

BEHAVIORAL

10 weeks chatbot-based IM support

Participants in the intervention group will also receive cognitive behavioral therapy for insomnia (CBT-I) delivered via an LLM-based chatbot through WhatsApp over a 10-week period. The intervention is fully automated and available 24/7, with underlying algorithms enabling the delivery of information, therapeutic support, and advice in a personalized and adaptive manner, informed by participants' ongoing inputs and interaction patterns. The intervention will be structured into 20 chatbot-delivered instant messaging (2 pieces per week). The therapeutic content is adapted from established CBT-I manuals and led by research nurse, incorporating evidence-based behavioral, cognitive, and educational components. Behavioral strategies include sleep restriction, stimulus control, and relaxation techniques. Cognitive components comprise paradoxical intention, cognitive restructuring, mindfulness-based techniques, positive imagery, and strategies for "putting the day to rest." Educational compone

Sponsors & Collaborators

• The University of Hong Kong

  lead OTHER

Principal Investigators

• Shengzhi Zhao · The University of Hong Kong

Study Design

Allocation

RANDOMIZED

Purpose

HEALTH_SERVICES_RESEARCH

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-09-01

Primary Completion

2027-09-30

Completion

2027-10-31

Countries

• Hong Kong

Study Locations