AI Chatbot-Assisted Aerobic Exercise Guided by the Transtheoretical Model and Self-determination Theory With Machine Learning Algorithms to Provide Real-time, Personalized Feedback in Traumatic Brain Injury

National Defense Medical Center, Taiwan

Status: Enrolling

Conditions: Tramatic Brain Injury

Treatments: Behavioral: Active Control; Behavioral: AI-PEF

Study type: Interventional

Funder types: Other

Identifiers

NCT07783828

AI chatbot-assisted exercise

Details and patient eligibility

About

This study aims to develop and evaluate an AI-driven Personalized Exercise Feedback Program (AI-PEF) to enhance health outcomes in mTBI patients.

Methods: AI-PEF integrates the transtheoretical model and self-determination theory with machine learning algorithms to provide real-time, personalized feedback. A phased randomized controlled trial will be conducted: Phase I,small-Scale Pilot Study (Early Feedback): A single-arm pilot study with 5 patients will be conducted over four weeks to gather feedback on usability, engagement, and content clarity.Phase II assesses the program's impact on functional capacity, sleep quality and depressive symptoms, with 50 participants in a 2-arm randomized trial in 3 months.Phase III will assess the program's impact on functional capacity, sleep quality and depressive symptoms, with 50 participants of waitlist control evaluation in a two-arm randomized trial.

Full description

The study will employ a stepwise, multi-phase design, combining two-arm randomized controlled trial (RCT) to evaluate the functional capacity, sleep quality and depressive symptoms of the AI-PEF.Participants will be recruited from the neurosurgery clinics at Tri-Service General Hospital, Taipei. Recruitment will be facilitated through referrals by attending physicians and registered nurses, who will be briefed on the study protocol.

Study procedures

1. Phase I (Year 1): small-Scale Pilot Study (Early Feedback for aim 1):

   A single-arm pilot study with 5 patients will be conducted over four weeks to gather feedback on usability, engagement, and content clarity.

2. Phase II : two-arm RCT (Aim 2) Phase I will focus on evaluating the functional capacity, sleep quality and depressive symptoms of the AI-PEF intervention in mTBI patient. A two-parallel-group design will be employed, with 50 participants, 25 participants per group, randomly assigned in a 1:1 ratio to the AI-PEF group and Active control group. Over three months, AI-PEF participants will engage in personalized exercise guided by AI, while active control participants will follow standard exercise recommendations. Both qualitative and quantitative data will be collected. Assessments will occur at baseline (T0), 1month (T1),2months(T2),and 3months(T3), including fitness tracker data, questionnaires (motivation, sleep, symptoms), and semi-structured interviews. The primary outcome will be functional capacity in mTBI patients, while secondary outcomes will focus on sleep quality and depressive symptoms in mTBI patients.

3. Phase III : a waitlist two-arm RCT (Aim 3):Phase III will assess the long-term impact of the AI-PEF on health outcomes through a waitlist 2-arm RCT randomly assigned to one of two groups: (1) the AI-PEF group, receiving a machine learning-powered personalized exercise program; (2) the Active control group, receiving general exercise recommendations as part of standard care in a 1:1 ratio.(3)After three months, the Active control group will receive AI-PEF interventions to be the waitlist control group, with assessments conducted at 6 months (T4). Primary outcomes, including functional capacity in mTBI patients, while secondary outcomes will focus on sleep quality and depressive symptoms in mTBI patients.It will be assessed through standardized questionnaires and qualitative interviews. These standardized questionnaires are being used in our current digital remote exercise trial in patients with mild TBI (NSTC 112-2314-B-016-007-MY2) and have performed well on physiological performance. Data will be collected and analyzed using both quantitative and qualitative methods to compare health outcomes across the two groups, identifying the efficacy of AI-PEF relative to Active control group . Procedures will adhere to the blinding and randomization protocols described in Intervention Fidelity, ensuring unbiased assignment and data collection processes. This proposed study protocol is closely aligned with those that have been successfully implemented in our previous digital exercise trial.

Enrollment: 50 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Eligible participants are patients aged over 18 with mild TBI (GCS 13-15)
• who can walk independently,
• reside in the Greater Taipei area,
• and possess sufficient Chinese or Taiwanese language proficiency to understand the trial
• complete self-administered questionnaires.

Exclusion criteria

include individuals with severe medical conditions (e.g., respiratory failure, epilepsy, psychiatric disorders), musculoskeletal or neurological impairments

• hindering physical activity in the 6-minute walk test,
• cognitive impairments (MMSE < 24),
• frontal lobe injuries or penetrating injury causing significant psychological dysfunction.
• Patients regularly engaging in moderate-to-high-intensity aerobic exercise or participating in other studies will also be excluded to avoid bias.

Trial design

Primary purpose: Supportive Care

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

---

50 participants in 2 patient groups

AI-PEF

Experimental group

Description:

the AI-PEF group, receiving a machine learning-powered personalized exercise program.

Treatment:

Behavioral: AI-PEF

Active control group

Active Comparator group

Description:

the Active control group, receiving general exercise recommendations as part of standard care in a 1:1 ratio.

Treatment:

Behavioral: Active Control