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AI-Driven Programs for Non-specific Chronic Neck Pain

19 maggio 2026 aggiornato da: Mariam Hassan Abdelmotaleb Elmasry, Cairo University

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.

Panoramica dello studio

Stato

Attivo, non reclutante

Descrizione dettagliata

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 .

Tipo di studio

Interventistico

Iscrizione (Effettivo)

40

Fase

  • Non applicabile

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Luoghi di studio

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Adulto

Accetta volontari sani

No

Descrizione

Inclusion Criteria:

The patients were selected according to the following criteria:

  1. 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.
  2. Having neck pain for at least three months.
  3. Age: between 18-35 years old
  4. Both genders (Males and Females).
  5. Normal body mass index BMI (18.5-24.9)

Exclusion Criteria:

  1. A history of cervical spine injury or surgery.
  2. Neck pain as secondary to other conditions including neoplasm, neurological diseases or vascular diseases.
  3. Radiculopathy with neurological deficits.
  4. A history of infection or inflammatory arthritis in the cervical spine.
  5. Physical therapy within last six months.
  6. Presence of pain in the shoulder, upper extremity, scapula, or cervical spine that prohibited exercise.

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

  • Scopo principale: Trattamento
  • Assegnazione: Randomizzato
  • Modello interventistico: Assegnazione parallela
  • Mascheramento: Doppio

Armi e interventi

Gruppo di partecipanti / Arm
Intervento / Trattamento
Sperimentale: AI-Driven Program
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
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
Sperimentale: Traditional Physical Therapy Program
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.
used for warming up before exercises

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Pain Intensity
Lasso di tempo: 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.
up to 6 weeks
Cervical Range of Motion
Lasso di tempo: 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.
up to 6 weeks
Cervical Proprioception
Lasso di tempo: 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).
up to 6 weeks

Misure di risultato secondarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Neck Disability Index
Lasso di tempo: up to 6 weeks
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%).
up to 6 weeks

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Effettivo)

10 gennaio 2026

Completamento primario (Effettivo)

10 aprile 2026

Completamento dello studio (Stimato)

19 maggio 2026

Date di iscrizione allo studio

Primo inviato

19 maggio 2026

Primo inviato che soddisfa i criteri di controllo qualità

19 maggio 2026

Primo Inserito (Effettivo)

26 maggio 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

26 maggio 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

19 maggio 2026

Ultimo verificato

1 maggio 2026

Maggiori informazioni

Termini relativi a questo studio

Altri numeri di identificazione dello studio

  • P.T.REC/012/006233

Piano per i dati dei singoli partecipanti (IPD)

Hai intenzione di condividere i dati dei singoli partecipanti (IPD)?

NO

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

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