Non-specific Chronic Neck PainNCT07606729
AI-Driven Programs for Non-specific Chronic Neck Pain
A study testing Pressure Biobfeedback and Hot Pack in people with Non-specific Chronic Neck Pain, run by Cairo University at 1 site in Egypt.
Trial summary
Non-specific chronic neck pain represents a major global health burden, affecting 30% to 50% of the general population. It is particularly prevalent among office workers, computer users, and women, with a notable rise in young adults aged 20 to 24. Read more about this study
- Who is it for?
- Ages 18 to 35 years
- Conditions the study is for
- Non-specific Chronic Neck Pain
- What is being tested?
- Pressure Biobfeedback and Hot Pack
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40 participants
- Where
- 1 siteEgypt
- Study dates
- 10 Jan 2026to 19 May 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 35 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- The patients were selected according to the following criteria:
- Forty subjects who have complained of Nonspecific chronic Neck pain diagnosed by a physician will be recruited from the outpatient clinics through direct referrals, Faculty of Physical Therapy, Misr University for Science and Technology.
- Having neck pain for at least three months.
- Age: between 18-35 years old
- Both genders (Males and Females).
- Normal body mass index BMI (18.5-24.9)
Who cannot join
- A history of cervical spine injury or surgery.
- Neck pain as secondary to other conditions including neoplasm, neurological diseases or vascular diseases.
- Radiculopathy with neurological deficits.
- A history of infection or inflammatory arthritis in the cervical spine.
- Physical therapy within last six months.
- Presence of pain in the shoulder, upper extremity, scapula, or cervical spine that prohibited exercise.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Efficacy of AI-Driven Program and Traditional Physical Therapy Program in Patients With Non-Specific Chronic Neck Pain
Non-specific chronic neck pain represents a major global health burden, affecting 30% to 50% of the general population. It is particularly prevalent among office workers, computer users, and women, with a notable rise in young adults aged 20 to 24. While acute episodes of neck pain may initially resolve, underlying functional impairments often persist, causing over a third of patients to develop chronic symptoms lasting three months or longer. Typically localized in the lateral and posterior neck regions without radicular signs, this condition is frequently driven by poor posture and improper ergonomics. The resulting abnormal stress on the cervical spine and musculature severely limits daily activities, lowers overall quality of life, and places a heavy socioeconomic strain on patients and their communities.
Traditional conservative management typically relies on a combination of pharmacotherapy and standard physical therapy modalities, including manual techniques, exercise programs, electrotherapy, and thermal agents. However, these conventional interventions demand frequent, in-person clinical visits, creating a significant financial and logistical barrier for many families, particularly under current economic challenges in Egypt. Consequently, there is an urgent need for cost-effective, highly accessible, and novel rehabilitation models that can streamline care and optimize clinical outcomes.
Artificial intelligence (AI) and machine learning offer a promising solution to these challenges by providing automated, data-driven remote care. Through mobile apps and smart rehabilitation platforms, AI can analyze complex clinical datasets-including patient demographics, pain intensity, and radiographic alignment-to predict treatment timelines and automate routine clinical tasks. Crucially, AI solves the problem of standardized, non-individualized home exercise plans by adjusting to a patient's daily symptom presentation, mimics a therapist's tailored approach, and offers real-time feedback. However, as these technologies advance, a clear gap remains in the physical therapy profession. Many clinicians lack a foundational understanding of AI fundamentals and harbor concerns about automation, highlighting an urgent need to evaluate physical therapists' perceptions and preparation to foster clinical trust and seamless integration.
Read the detailed description
The prevalence of chronic non-specific neck pain (CNNP) is on the rise among the young adult population. Non-specific neck pain stands as the fourth leading cause of chronic disability, with an annual prevalence rate exceeding 30%. Chronic non-specific neck pain (CNNP), is projected to affect 48%-67% of individuals at some point in their lifetime. The economic repercussions of neck pain extend to both individuals and society, encompassing costs related to healthcare, insurance, loss of productivity, and sick leave. In young adults, neck pain has been identified as a risk factor for reduced general work productivity. ( Zhang , Y ,et al,2024) Chronic nonspecific neck pain is the most frequent form of neck pain. It is commonly associated with biomechanical, functional, proprioceptive, and postural impairments. When symptoms persist for more than 12 weeks, the condition acquires the value of chronicity and is denominated chronic nonspecific neck pain (CNSNP). (Mendes-Fernandes, T, et al, 2021) Nonspecific neck pain commonly arises insidiously and is generally multifactorial in origin, including one or more of the following: poor posture, anxiety, depression, neck strain, and sporting or occupational activities. (Wilhelm, M, et al, 2023) Since proprioceptive deficit has frequently been observed following chronic neck pain, regaining neck proprioception is a critical part of neck pain rehabilitation to decrease the extra reliance and postural dependency on visual and vestibular systems while performing functional tasks. Several exercise programs have been prescribed for chronic neck pain patients to relieve pain and improve proprioceptive acuity. It hypothesized that deep flexor training can improve neck proprioception via reducing pain and strengthening the muscles which stabilize the cervical spine. ( Rahnama, L., et al,2023) Conservative care for patients with neck pain often includes pharmacologic therapies. While practice patterns may favor the use of specific agents, such as nonsteroidal anti-inflammatory drugs, corticosteroids, and opioid analgesics, providing short-term pain relief, there is limited evidence supporting their long-term use in most patients with CNNP. Exercise is a crucial component of treatment programs for patients with CNNP. Several trials have concluded that 1- to 6-month neck stretching exercises can decrease neck pain and improve neck function. However, stretching exercises may be insufficient in improving muscle strength. ( Zhang , Y ,et al,2024). Deep cervical flexors play a key role in maintaining cervical lordosis and head posture. Research in neck pain sufferers consistently shows these muscles are both under activated and fatigued compared to healthy controls. Clinically, restoring DCF endurance and activation is recommended for managing neck pain. (Iqbal, Z. A.,et al, 2021). The clinical practice guidelines suggest that manual therapy plus exercise should be the first line of defense for individuals with nonspecific neck pain without red flags. (Wilhelm, M, et al,2023) By evaluating AI-driven treatment planning, this research contributes to the emerging evidence on how technology can augment traditional care. Specifically, it explores whether AI can offer more accurate, personalized, and adaptive treatment plans, thereby enhancing treatment outcomes, improving patient engagement, and potentially reducing the burden on healthcare systems. The results of this study may support the adoption of AI tools in clinical settings, leading to more efficient and accessible rehabilitation models, especially in underserved or remote areas (Rashid \& Sharma, 2025).
The integration of artificial intelligence (AI) in patient pain medicine education has the potential to revolutionize pain management. By harnessing the power of AI, patient education becomes more personalized, interactive, and supportive, empowering patients to understand their pain, make informed decisions, and actively participate in their pain management journey. AI tailors the educational content to individual patients' needs, providing personalized recommendations. It introduces interactive elements through chatbots and virtual assistants, enhancing engagement and motivation. AI-powered platforms improve accessibility by providing easy access to educational resources and adapting content to diverse patient populations. Future AI applications in pain management include explaining pain mechanisms, treatment options, predicting outcomes based on individualized patient-specific factors, and supporting monitoring and adherence. (Robinson et al, 2024).
Expected Advantages of AI-Based Rehabilitation; Personalized plans adjusted weekly based on real-time patient input, Cost-effective model minimizes the need for frequent clinic visits, Shorter treatment duration adaptive protocols reduce unnecessary sessions, Predictive modeling uses patient data to estimate likely improvement Scalability and accessibility especially beneficial for remote or underserved populations. (Khalid et al, 2024).
By searching the literature there is no study based on our knowledge compare between AI driven exercise and traditional program in pain intensity level , neck ROM, neck proprioception, neck functional ability level in patients with Non-Specific Chronic Neck Pain so, the aim of this study is to investigate the efficacy of AI-driven program \& traditional physical therapy programs on pain intensity level , neck ROM, neck proprioception , neck functional ability level in patients with Non-Specific Chronic Neck Pain .
- Conditions
- Non-specific Chronic Neck Pain
- Being tested
- Pressure Biobfeedback, Hot Pack
- Keywords
- NON-SPECIFIC CHRONIC NECK PAIN, TRADITIONAL PHYSICAL THERAPY, AI-DRIVEN PROGRAM
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Pressure BiobfeedbackDevice
Pressure biofeedback is a noninvasive technique that provides knowledge of performance through the hand held apparatus that can augment the patient's sensory feedback mechanism. In clinical practice, pressure biofeedback devices have primarily been used to test and train the deep neck flexor muscles to improve endurance
Hot PackDevice
used for warming up before exercises
| Study group | Role | What they receive |
|---|---|---|
| AI-Driven Program | Experimental | Week 1 Hot pack / warm shower Chin to chest Gaze to ceiling Head rotation Shoulder rolls Cranio-cervical flexion (CCF) with pressure biofeedback Wall scapular clocks Week 2 Hot pack / warm shower Cat-cow exercise Thread-the-needle stretch Cranio-cervical flexion (CCF) with pressure biofeedback Theraband rows Serratus wall slides Week 3 Thoracic extension on foam roller Cranio-cervical flexion (CCF) with pressure biofeedback Theraband rows Prone T exercise Week 4 Dynamic pectoral corner stretch Cranio-cervical flexion (CCF) with pressure biofeedback Supine serratus punch Week 5 Prone chin tuck Serratus punch Prone Y exercise Week 6 Cranio-cervical flexion (CCF) with pressure biofeedback Band external rotation Theraband rows Receives: Device: Pressure Biobfeedback |
| Traditional Physical Therapy Program | Experimental | This Group Will receive neck ROM exercises including: (neck extension, flexion, rotation, lateral bending motions, and scapular retraction, with no resistance), conventional physical therapy including: (Isometric training exercises for neck flexors, extensors, lateral flexors and rotators, Passive stretching exercises for neck extensor muscles, neck lateral flexor muscles, and scalene muscle, Hot packs), Dynamic pec stretch, Chin in exercise, core stabilization exercise including Bridging exercise and Quadruped with leg extension exercise. Receives: Device: Hot Pack |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pain Intensity
For evaluating the pain degree of severity, the visual analogue scale was employed. It is a 10 cm or 100 mm psychometric response scale to measure pain intensity based on numerical values, anchored by a score of 0 no pain and score 10 worst ever pain.
Measured: up to 6 weeks
Cervical Range of Motion
Cervical Range of Motion (CROM) device is a clinical tool commonly used to measure cervical ROM. The CROM device utilizes three inclinometers to measure active mobility of the cervical spine. Many studies have reported strong validity and reliability of the CROM device supporting the clinical value of the instrument. It was shown to have moderate to good intra-rater and inter-rater reliability of 0.84 to 0.96 and 0.73 to 0.94, respectively.
Measured: up to 6 weeks
Cervical Proprioception
The Cervical Range of Motion (CROM) device also used to measure proprioception.Cervical proprioception was assessed by determining joint position error (JPE). JPE can be used to measure the ability of the individual to reposition their head back to its neutral head position (NHP) or to a predefined target head position (THP).
Measured: up to 6 weeks
Secondary outcomes (1)
Neck Disability Index
The Neck Disability Index (NDI) is a patient-reported questionnaire used to assess pain and functional limitation in individuals with neck pain. It consists of 10 items, each scored from 0-5, with total scores converted into percentages. A score of 0% indicates no disability, while 100% indicates complete disability. The NDI is considered a reliable and valid tool for neck pain assessment, with high interclass correlation values (0.50-0.98). Disability levels are classified as: no disability (0-8%), mild (10-28%), moderate (30-48%), severe (50-64%), and complete disability (70-100%).
Measured: up to 6 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 May 2026
- Study start10 Jan 2026
- Primary completion10 Apr 2026
- Study completion19 May 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Non-specific Chronic Neck PainStudies of the same condition, open and under way.
- More trials run by Cairo UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Investigator
- Enrolment
- 40 participants (actual)
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Mariam Hassan Abdelmotaleb Elmasry, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07606729
- Sponsor's protocol ID
- P.T.REC/012/006233
- Status last verified
- May 2026
- First submitted
- 19 May 2026
- Last updated
- 26 May 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Efficacy of AI-Driven Program and Traditional Physical Therapy Program in Patients With Non-Specific Chronic Neck Pain
- ClinicalTrials.gov ID
- NCT07606729
- Acronym / sponsor ID
- P.T.REC/012/006233
- Conditions
- Non-specific Chronic Neck Pain
- Keywords
- NON-SPECIFIC CHRONIC NECK PAIN, TRADITIONAL PHYSICAL THERAPY, AI-DRIVEN PROGRAM
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 40 participants (actual)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 10 Jan 2026 (actual)
- Primary completion
- 10 Apr 2026 (actual)
- Study completion
- 19 May 2026 (estimated)
- First posted
- 26 May 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Non-specific chronic neck pain represents a major global health burden, affecting 30% to 50% of the general population. It is particularly prevalent among office workers, computer users, and women, with a notable rise in young adults aged 20 to 24. While acute episodes of neck pain may initially resolve, underlying functional impairments often persist, causing over a third of patients to develop chronic symptoms lasting three months or longer. Typically localized in the lateral and posterior neck regions without radicular signs, this condition is frequently driven by poor posture and improper ergonomics. The resulting abnormal stress on the cervical spine and musculature severely limits daily activities, lowers overall quality of life, and places a heavy socioeconomic strain on patients and their communities.
Traditional conservative management typically relies on a combination of pharmacotherapy and standard physical therapy modalities, including manual techniques, exercise programs, electrotherapy, and thermal agents. However, these conventional interventions demand frequent, in-person clinical visits, creating a significant financial and logistical barrier for many families, particularly under current economic challenges in Egypt. Consequently, there is an urgent need for cost-effective, highly accessible, and novel rehabilitation models that can streamline care and optimize clinical outcomes.
Artificial intelligence (AI) and machine learning offer a promising solution to these challenges by providing automated, data-driven remote care. Through mobile apps and smart rehabilitation platforms, AI can analyze complex clinical datasets-including patient demographics, pain intensity, and radiographic alignment-to predict treatment timelines and automate routine clinical tasks. Crucially, AI solves the problem of standardized, non-individualized home exercise plans by adjusting to a patient's daily symptom presentation, mimics a therapist's tailored approach, and offers real-time feedback. However, as these technologies advance, a clear gap remains in the physical therapy profession. Many clinicians lack a foundational understanding of AI fundamentals and harbor concerns about automation, highlighting an urgent need to evaluate physical therapists' perceptions and preparation to foster clinical trust and seamless integration.
Detailed description
The prevalence of chronic non-specific neck pain (CNNP) is on the rise among the young adult population. Non-specific neck pain stands as the fourth leading cause of chronic disability, with an annual prevalence rate exceeding 30%. Chronic non-specific neck pain (CNNP), is projected to affect 48%-67% of individuals at some point in their lifetime. The economic repercussions of neck pain extend to both individuals and society, encompassing costs related to healthcare, insurance, loss of productivity, and sick leave. In young adults, neck pain has been identified as a risk factor for reduced general work productivity. ( Zhang , Y ,et al,2024) Chronic nonspecific neck pain is the most frequent form of neck pain. It is commonly associated with biomechanical, functional, proprioceptive, and postural impairments. When symptoms persist for more than 12 weeks, the condition acquires the value of chronicity and is denominated chronic nonspecific neck pain (CNSNP). (Mendes-Fernandes, T, et al, 2021) Nonspecific neck pain commonly arises insidiously and is generally multifactorial in origin, including one or more of the following: poor posture, anxiety, depression, neck strain, and sporting or occupational activities. (Wilhelm, M, et al, 2023) Since proprioceptive deficit has frequently been observed following chronic neck pain, regaining neck proprioception is a critical part of neck pain rehabilitation to decrease the extra reliance and postural dependency on visual and vestibular systems while performing functional tasks. Several exercise programs have been prescribed for chronic neck pain patients to relieve pain and improve proprioceptive acuity. It hypothesized that deep flexor training can improve neck proprioception via reducing pain and strengthening the muscles which stabilize the cervical spine. ( Rahnama, L., et al,2023) Conservative care for patients with neck pain often includes pharmacologic therapies. While practice patterns may favor the use of specific agents, such as nonsteroidal anti-inflammatory drugs, corticosteroids, and opioid analgesics, providing short-term pain relief, there is limited evidence supporting their long-term use in most patients with CNNP. Exercise is a crucial component of treatment programs for patients with CNNP. Several trials have concluded that 1- to 6-month neck stretching exercises can decrease neck pain and improve neck function. However, stretching exercises may be insufficient in improving muscle strength. ( Zhang , Y ,et al,2024). Deep cervical flexors play a key role in maintaining cervical lordosis and head posture. Research in neck pain sufferers consistently shows these muscles are both under activated and fatigued compared to healthy controls. Clinically, restoring DCF endurance and activation is recommended for managing neck pain. (Iqbal, Z. A.,et al, 2021). The clinical practice guidelines suggest that manual therapy plus exercise should be the first line of defense for individuals with nonspecific neck pain without red flags. (Wilhelm, M, et al,2023) By evaluating AI-driven treatment planning, this research contributes to the emerging evidence on how technology can augment traditional care. Specifically, it explores whether AI can offer more accurate, personalized, and adaptive treatment plans, thereby enhancing treatment outcomes, improving patient engagement, and potentially reducing the burden on healthcare systems. The results of this study may support the adoption of AI tools in clinical settings, leading to more efficient and accessible rehabilitation models, especially in underserved or remote areas (Rashid \& Sharma, 2025).
The integration of artificial intelligence (AI) in patient pain medicine education has the potential to revolutionize pain management. By harnessing the power of AI, patient education becomes more personalized, interactive, and supportive, empowering patients to understand their pain, make informed decisions, and actively participate in their pain management journey. AI tailors the educational content to individual patients' needs, providing personalized recommendations. It introduces interactive elements through chatbots and virtual assistants, enhancing engagement and motivation. AI-powered platforms improve accessibility by providing easy access to educational resources and adapting content to diverse patient populations. Future AI applications in pain management include explaining pain mechanisms, treatment options, predicting outcomes based on individualized patient-specific factors, and supporting monitoring and adherence. (Robinson et al, 2024).
Expected Advantages of AI-Based Rehabilitation; Personalized plans adjusted weekly based on real-time patient input, Cost-effective model minimizes the need for frequent clinic visits, Shorter treatment duration adaptive protocols reduce unnecessary sessions, Predictive modeling uses patient data to estimate likely improvement Scalability and accessibility especially beneficial for remote or underserved populations. (Khalid et al, 2024).
By searching the literature there is no study based on our knowledge compare between AI driven exercise and traditional program in pain intensity level , neck ROM, neck proprioception, neck functional ability level in patients with Non-Specific Chronic Neck Pain so, the aim of this study is to investigate the efficacy of AI-driven program \& traditional physical therapy programs on pain intensity level , neck ROM, neck proprioception , neck functional ability level in patients with Non-Specific Chronic Neck Pain .
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, investigator)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-Driven Program | Experimental | Device: Pressure BiobfeedbackWeek 1 Hot pack / warm shower Chin to chest Gaze to ceiling Head rotation Shoulder rolls Cranio-cervical flexion (CCF) with pressure biofeedback Wall scapular clocks Week 2 Hot pack / warm shower Cat-cow exercise Thread-the-needle stretch Cranio-cervical flexion (CCF) with pressure biofeedback Theraband rows Serratus wall slides Week 3 Thoracic extension on foam roller Cranio-cervical flexion (CCF) with pressure biofeedback Theraband rows Prone T exercise Week 4 Dynamic pectoral corner stretch Cranio-cervical flexion (CCF) with pressure biofeedback Supine serratus punch Week 5 Prone chin tuck Serratus punch Prone Y exercise Week 6 Cranio-cervical flexion (CCF) with pressure biofeedback Band external rotation Theraband rows |
| Traditional Physical Therapy Program | Experimental | Device: Hot PackThis Group Will receive neck ROM exercises including: (neck extension, flexion, rotation, lateral bending motions, and scapular retraction, with no resistance), conventional physical therapy including: (Isometric training exercises for neck flexors, extensors, lateral flexors and rotators, Passive stretching exercises for neck extensor muscles, neck lateral flexor muscles, and scalene muscle, Hot packs), Dynamic pec stretch, Chin in exercise, core stabilization exercise including Bridging exercise and Quadruped with leg extension exercise. |
Who may qualify
- Ages
- 18 to 35 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (6 listed)
- Forty subjects who have complained of Nonspecific chronic Neck pain diagnosed by a physician will be recruited from the outpatient clinics through direct referrals, Faculty of Physical Therapy, Misr University for Science and Technology.
- Having neck pain for at least three months.
- Age: between 18-35 years old
- Both genders (Males and Females).
- Normal body mass index BMI (18.5-24.9)
Key exclusion criteria (6 listed)
- A history of cervical spine injury or surgery.
- Neck pain as secondary to other conditions including neoplasm, neurological diseases or vascular diseases.
- Radiculopathy with neurological deficits.
- A history of infection or inflammatory arthritis in the cervical spine.
- Physical therapy within last six months.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Pressure BiobfeedbackPressure biofeedback is a noninvasive technique that provides knowledge of performance through the hand held apparatus that can augment the patient's sensory feedback mechanism. In clinical practice, pressure biofeedback devices have primarily been used to test and train the deep neck flexor muscles to improve endurance | Device | AI-Driven Program |
| Hot Packused for warming up before exercises | Device | Traditional Physical Therapy Program |
Primary outcome
Pain Intensity
Time frame: up to 6 weeks
For evaluating the pain degree of severity, the visual analogue scale was employed. It is a 10 cm or 100 mm psychometric response scale to measure pain intensity based on numerical values, anchored by a score of 0 no pain and score 10 worst ever pain.
Cervical Range of Motion
Time frame: up to 6 weeks
Cervical Range of Motion (CROM) device is a clinical tool commonly used to measure cervical ROM. The CROM device utilizes three inclinometers to measure active mobility of the cervical spine. Many studies have reported strong validity and reliability of the CROM device supporting the clinical value of the instrument. It was shown to have moderate to good intra-rater and inter-rater reliability of 0.84 to 0.96 and 0.73 to 0.94, respectively.
Cervical Proprioception
Time frame: up to 6 weeks
The Cervical Range of Motion (CROM) device also used to measure proprioception.Cervical proprioception was assessed by determining joint position error (JPE). JPE can be used to measure the ability of the individual to reposition their head back to its neutral head position (NHP) or to a predefined target head position (THP).
1 secondary outcome
Neck Disability Index
Time frame: up to 6 weeks
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 May 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Pressure Biobfeedback and Hot Pack in people with Non-specific Chronic Neck Pain, run by Cairo University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 26 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pain Intensity (time frame: up to 6 weeks). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 May 2026.