ClinicalTrials.gg
Not yet recruitingNCT07902778Updated Oct 29, 2026

Hybrid mHealth for Low Back Pain

An interventional study of Face-to-face physiotherapy and psychological care (for hybrid arm) and WhatsApp-based AI chatbot for self-management (for hybrid and WhatsApp-only arms) in Chronic Low-back Pain (cLBP) and Non-specific Low Back Pain (NSLBP), sponsored by The Hong Kong Polytechnic University. Not yet recruiting at 1 site in Hong Kong. Open to participants aged 18 Years to 65 Years. Per ClinicalTrials.gov, last updated 2026-10-29.

Sponsored by The Hong Kong Polytechnic University · Not applicable, Interventional, and Treatment

Updated Oct 29, 2026Newly registeredGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
60
Allocation
Randomized
Ages
18 Years to 65 Years
Sex
All
01

Study summary

The goal of this clinical trial is to evaluate whether adding a WhatsApp-based AI chatbot to standard physiotherapy and psychological care can improve self-management and outcomes in adults aged 18-65 with chronic low back pain (CLBP).

The main questions it aims to answer are:

Is it feasible and acceptable to use a WhatsApp-based AI chatbot as an adjunct to standard care in adults with CLBP? Does the addition of an AI chatbot improve pain, disability, mental health, and quality of life compared to standard care or digital self-management alone?

Researchers will compare three groups:

Standard care (face-to-face physiotherapy and education) with the AI chatbot, Standard care alone, AI chatbot alone.

Participants will:

Attend weekly sessions for 8 weeks (depending on group assignment, this may be face-to-face, digital, or both); Use a WhatsApp-based AI chatbot for personalized exercise and self-management support, gamification, and optional peer-support; Complete questionnaires and provide feedback on pain, function, mental health, and program usability at several time points; Receive onboarding and privacy safeguards for digital components.

Read the detailed description

Low back pain (LBP) is the leading cause of disability globally, with many individuals struggling to engage in self-management activities after leaving the clinic. This study aims to address these challenges by testing a new hybrid intervention that integrates face-to-face physiotherapy and psychological care with a WhatsApp-based AI chatbot for adults with chronic LBP.

The project is organized into two main stages:

Stage 1 involves co-designing and developing the intervention. Researchers will work with clinicians, digital health experts, and people living with chronic LBP to create the content and functions of the intervention manual and AI chatbot. The chatbot delivers personalized educational content, reminders, gamification features (like achievement badges), mindfulness-based stress reduction tips, and access to a moderated peer support group. Safety and privacy measures are built into the system, and the chatbot offers escalation to clinicians for safety concerns.

Stage 2 is a pilot, assessor-blinded randomized controlled trial in which 60 adults with chronic LBP will be randomly assigned to one of three groups:

An intervention group (receiving face-to-face care and the WhatsApp chatbot), A control group (face-to-face care only), or A digital-only group (WhatsApp chatbot only).

All groups follow an 8-week program. Face-to-face sessions focus on motor control, general conditioning, functional exercises, and back care education, with a prescribed home exercise program. The chatbot groups receive multiple digital touchpoints per week tailored to their symptoms, engagement, and needs. Optional peer support is available via moderated WhatsApp group chats.

The primary goals are to assess the program's feasibility, acceptability, adherence, safety, and usability, as well as to gather preliminary information about its possible benefits for pain, disability, mental health, and quality of life. Outcomes will be measured at baseline, after the 8-week program, and at 1- and 3-month follow-ups.

Findings from this study will inform the design of a larger trial and will help define best practices for integrating AI-driven digital health tools with conventional care for chronic low back pain management.

02

Conditions studied

  • Chronic Low-back Pain (cLBP)
  • Non-specific Low Back Pain (NSLBP)

Keywords

  • Chronic low back pain
  • Non-specific low back pain
  • mHealth
  • Mobile health
  • AI chatbot
  • WhatsApp
  • Digital health intervention
  • Physiotherapy
  • Self-management
  • Randomized controlled trial
  • Pain management
  • Telehealth
03

In context

Lead sponsor

The Hong Kong Polytechnic University is the lead sponsor of 679 studies on the registry; 257 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 65 Years
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Adults aged 18-65 years
  • Diagnosed with [target condition, e.g., chronic low back pain] for at least 3 months
  • Able to communicate in Chinese (written and spoken)
  • Access to a smartphone with WhatsApp installed
  • Willing and able to attend face-to-face physiotherapy and/or use digital interventions as assigned
  • Provide written

Exclusion criteria

Exclusion Criteria:

  • Presence of red flag symptoms or serious spinal pathology (e.g., tumor, infection, fracture)
  • Previous spine surgery within the past 12 months
  • Severe psychiatric disorders or active suicidal ideation
  • Currently participating in other intervention studies targeting the same condition
  • Inability to comply with study procedures or follow-up assessments
Terms in these criteria, in plain language(1)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Outcomes assessor)
Enrollment
60 participants (estimated)

Study arms

  • Experimental
    Intervention Arm

    Participants in this arm receive eight weekly, face-to-face physiotherapy and psychological care sessions. In addition, they receive access to a WhatsApp-based AI chatbot for digital self-management support. The chatbot provides personalized exercise and education content, gamification features, mindfulness-based stress reduction, and access to a moderated peer support group.

    Behavioral: Face-to-face physiotherapy and psychological care (for hybrid arm) · Behavioral: WhatsApp-based AI chatbot for self-management (for hybrid and WhatsApp-only arms)

  • Active comparator
    Control Arm

    Participants in this arm receive eight weekly, face-to-face physiotherapy and psychological care sessions. They do not receive any digital adjuncts, gamification, or access to the WhatsApp-based AI chatbot. Home exercise and educational handouts are provided in person.

    Behavioral: Face-to-face physiotherapy and psychological care (No Digital Support) (for control arm)

  • Experimental
    WhatsApp Arm

    Participants in this arm receive digital self-management only: a WhatsApp-based AI chatbot delivering personalized exercise and education content, gamification features, mindfulness-based stress reduction, and moderated peer support. No face-to-face physiotherapy or psychological care is provided.

    Behavioral: WhatsApp-based AI chatbot for self-management (for hybrid and WhatsApp-only arms)

Interventions

  • BehavioralFace-to-face physiotherapy and psychological care (for hybrid arm)

    Eight weekly, 60-minute in-person sessions focusing on exercise, back care education, pain science, ergonomic advice, symptom monitoring, and home exercise, with brief psychological guidance.

    Also known as: Physiotherapy, Psychological care

  • BehavioralWhatsApp-based AI chatbot for self-management (for hybrid and WhatsApp-only arms)

    A WhatsApp-delivered AI chatbot providing personalized exercise and education content, gamification (badges/dashboard), mindfulness-based stress reduction, reminders, and optional peer support, delivered weekly for eight weeks, with clinical escalation as needed.

    Also known as: Digital self-management, AI digital adjunct

  • BehavioralFace-to-face physiotherapy and psychological care (No Digital Support) (for control arm)

    Eight weekly, 60-minute in-person sessions providing physiotherapy and brief psychological guidance. Focuses on exercise, education, home exercise, and functional training. Participants do not receive any digital self-management or WhatsApp support.

06

What researchers measure

Primary outcomes

  1. Pain Intensity (Numeric Rating Scale)

    Change in pain intensity measured on an 11-point Numeric Rating Scale (0 = no pain, 10 = worst possible pain).

    Time frame: Baseline, 8 weeks, 12 weeks

  2. Disability score (Roland-Morris Disability Questionnaire)

    Change in disability as measured by the Roland-Morris Disability Questionnaire (RMDQ); total score ranges from 0 (no disability) to 24 (maximum disability).

    Time frame: Baseline, 8 weeks (post-intervention), and 12 weeks (follow-up)

  3. Psychological Distress (Depression, Anxiety and Stress Scale-21)

    Change in psychological distress levels as measured by DASS-21. Higher scores indicate greater distress.

    Time frame: Baseline, 8 weeks, 12 weeks

Secondary outcomes

  1. Global Impression of Change Scale

    Change in participant-reported global impression of symptom change and treatment response using a 7-point scale (from "very much worse" to "very much improved").

    Time frame: Baseline, 8 weeks, and 12 weeks

  2. EQ-5D-5L (Chinese version)

    Change in health-related quality of life (HRQOL) across five domains (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) as measured by the Chinese EQ-5D-5L; higher scores indicate better quality of life.

    Time frame: Baseline, 8 weeks, and 12 weeks

  3. Hong Kong - Pain Catastrophizing Scale (HK-PCS)

    Change in pain catastrophizing as measured by the 13-item HK-PCS, covering rumination, magnification, and helplessness. Higher scores indicate more catastrophic thinking.

    Time frame: Baseline, 8 weeks, and 12 weeks

  4. General Self-Efficacy Scale (Chinese version)

    Change in self-efficacy, measured using the 10-item General Self-Efficacy Scale. Higher scores reflect greater confidence in overcoming obstacles.

    Time frame: Baseline, 8 weeks, and 12 weeks

Other outcomes

  1. Digital Engagement Metrics (WhatsApp)

    WhatsApp read receipts, message response rates, and self-reported adherence to digital self-management content.

    Time frame: Over 8 weeks

  2. Chinese System Usability Scale

    Usability of WhatsApp-delivered self-management content assessed by the 10-item Chinese System Usability Scale. Scores range from 0 (lowest) to 100 (highest usability).

    Time frame: 8 weeks

  3. Participant Satisfaction with Hybrid Delivery

    Participant-reported satisfaction and perceived benefit of receiving hybrid/integrated telehealth consultations, measured via feedback forms.

    Time frame: 8 weeks and 12 weeks

07

Study locations

1 site
08

References and documents

Individual participant data

Plan to share: Undecided — The decision regarding sharing IPD has not yet been finalized. IPD sharing will depend on institutional policies, participant consent, and potential ethical or privacy considerations. Further information may be provided after the study is completed.

No publications or documents are linked to this record.

09

Timeline

1 registry update since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Start is estimated for Nov 2026; primary completion for Nov 2027, 12 months later.

How these figures are worked out, and which studies are left out of them.

Registered
Oct 22, 2026
First posted
Oct 29, 2026
StartEst.
Nov 2, 2026
Primary completionEst.
Nov 2, 2027
CompletionEst.
Nov 2, 2027
Last update
Oct 29, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
Registered
First appeared on the registry. No changes since
Oct 29, 2026
Show all 1 update
  1. Oct 29, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07902778
Responsible party
Prof. Fadi AL ZOUBI (https://www.polyu.edu.hk/rs/people/academic-staff/prof-fadi-al-zoubi/, The Hong Kong Polytechnic University) — Principal investigator
First posted
Oct 29, 2026
Start date
Nov 2, 2026 (estimated)
Primary completion
Nov 2, 2027 (estimated)
Completion
Nov 2, 2027 (estimated)
Last update
Oct 29, 2026

Study contacts

Fadi M Al Zoubi, PhD
Contact
fadi.alzoubi@polyu.edu.hk
+85227666705

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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