AI-Assisted Relaxation and Breathing Training in Postmenopausal Women

Официальное название

The Effectiveness of Artificial Intelligence-Assisted Relaxation and Breathing Training on Pain Intensity and Quality of Life in Postmenopausal Women

Обзор

This study aims to evaluate the effectiveness of relaxation and breathing training delivered by a physiotherapist and by an artificial intelligence-assisted system in postmenopausal women with non-specific chronic musculoskeletal pain. Menopause and the postmenopausal period are associated with decreased estrogen levels, structural and functional changes in the musculoskeletal system, increased pain prevalence, reduced muscle function, and impaired quality of life. Relaxation techniques, breathing-focused exercises, and mind-body practices have been shown to reduce pain, improve psychological well-being, and enhance sleep quality. With the growing use of digital health technologies, AI-supported relaxation training may offer personalized guidance, easy accessibility, and sustainable home-based practice, although its effectiveness in postmenopausal women has not yet been demonstrated. In this three-arm randomized controlled trial, participants will be assigned to physiotherapist-led relaxation and breathing training, AI-assisted relaxation and breathing training, or a control group. Interventions will last eight weeks and include sessions three days per week, each approximately 30 minutes. The physiotherapist-guided group will perform sessions face-to-face, while the AI-assisted group will complete prerecorded relaxation and breathing exercises created with AI-generated scripts and voice recordings. The control group will continue daily routines without structured training during the study period. Assessments will be conducted at baseline and at the end of eight weeks. Outcome measures will include pain severity, pressure pain threshold, musculoskeletal symptoms, menopause-specific quality of life, psychological status, sleep quality, dyspnea, and participant satisfaction. The study aims to compare the effects of physiotherapist-led and AI-assisted training modalities on pain, musculoskeletal health, sleep, psychological well-being, and quality of life. Findings are expected to contribute to the development of accessible and cost-effective interventions that support symptom management and improve the daily functioning of postmenopausal women.

Подробное описание

Menopause is a natural biological process defined by the 12 months following a woman's last menstrual cycle. It typically occurs between the ages of 40 and 50, with an average age of onset of around 51. The menopause process is divided into three main phases: perimenopause, menopause, and postmenopause. Perimenopause encompasses the few years preceding menopause, when menstrual cycles become irregular and vasomotor symptoms such as hot flashes and night sweats first appear. The menopausal period is defined as the absence of menstrual bleeding for 12 consecutive months, during which time typical menopausal symptoms become apparent. Postmenopause is the period that lasts for the remainder of a woman's life after menopause. During postmenopause, the decline in estrogen levels causes structural and functional changes in the musculoskeletal system, negatively affecting the integrity of bones, muscles, tendons, and ligaments. The risk of developing sarcopenia and osteoporosis increases during this period. Estrogen contributes to energy metabolism by regulating mitochondrial function in muscle cells; estrogen deficiency results in a decrease in mitochondrial numbers and impaired muscle metabolism. Furthermore, decreased estrogen can increase apoptosis in skeletal muscle, disrupt muscle protein balance, and negatively affect muscle strength. During this period, the prevalence of musculoskeletal pain increases with age, from premenopause to perimenopause and postmenopause. The prevalence of musculoskeletal pain in perimenopausal women has been reported to be approximately 71%; it has also been found that postmenopausal women have a significantly increased risk of experiencing moderate to severe pain compared to premenopausal women. In the literature, methods such as progressive muscle relaxation, breathing-focused awareness exercises and meditation-based relaxation techniques have been shown to reduce pain severity, reduce stress levels and improve quality of life in individuals experiencing chronic pain. These techniques facilitate control of pain perception by reducing muscle tension, improving breathing patterns, and balancing autonomic nervous system responses. For chronic musculoskeletal pain seen in menopausal and postmenopausal women, relaxation training stands out as an effective complementary physiotherapy-based method and significantly contributes to maintaining women's quality of life. Furthermore, chronic pain and menopausal symptoms are closely related to sleep disorders. Studies have shown that relaxation techniques and body-mind-based practices improve sleep quality. It has been reported that relaxation techniques can have positive effects not only on psychological well-being but also on musculoskeletal health. In particular, they have been reported to increase ease of movement and contribute to functional capacity by reducing muscle tension. While the effectiveness of traditional relaxation methods is well known, it is also thought that digital health technologies developed in recent years may offer new opportunities for physiotherapy practices. It has been reported that AI-based systems can be integrated into relaxation and mindfulness applications, providing personalized feedback to guide exercises and enabling sustainable practice in the home environment. Web-based interventions have been found effective in improving the health and quality of life of individuals across various diseases, health behaviors, and psychological conditions due to their advantages such as easy access, low cost, and anonymity. However, despite these strengths, the current status of AI-supported interventions, particularly those related to menopause, remains unclear. However, AI technologies hold the potential to provide personalized care, symptom prediction, and digital support in the management of menopausal symptoms. Furthermore, the effectiveness of AI-based relaxation training applications has not yet been demonstrated. There is a need for long-term, sustainable approaches to the management of chronic pain during menopause and postmenopause that will enhance the potential health benefits. In this context, our study aims to contribute to the literature and clinical practice by comparing the effectiveness of physiotherapist-assisted and AI-assisted relaxation training in postmenopausal women.

Вмешательства

• Другое Physiotherapist-Guided Relaxation and Breathing Training
  Participants will perform the sessions individually and face-to-face under the supervision of a physiotherapist. Relaxation positions and breathing exercises will be guided and monitored by the physiotherapist. The training will be conducted three days a week for eight weeks, with each session lasting approximately 30 minutes.
• Другое Artificial Intelligence-Assisted Relaxation and Breathing Training
  In this group, a 30-minute relaxation and breathing training script will be created by the researchers based on instructional prompts provided to the artificial intelligence system. The generated script will be reviewed and finalized by the researchers and then converted into an audio file using an AI-based voice generation program. Participants will listen to these audio recordings asynchronously via smartphone or tablet, three days a week for eight weeks, with each session lasting approximatel
• Другое Control Group - No Structured Training Program
  Participants will be informed about relaxation and breathing exercises. After the initial assessments, they will be asked to continue their daily routines and not to participate in any structured exercise training program for eight weeks. After the intervention period, participants in the control group will be invited to join one of the training groups if they wish.

Первичные конечные точки

• Pain Intensity [Срок оценки: Baseline and Week 8]
• Pressure Pain Threshold [Срок оценки: Baseline and Week 8]
• Menopause-Specific Quality of Life [Срок оценки: Baseline and Week 8]

Вторичные конечные точки (4)

• Musculoskeletal Symptoms [Срок оценки: Baseline and Week 8]
• Psychological Status [Срок оценки: Baseline and Week 8]
• Dyspnea [Срок оценки: Baseline and Week 8]
• Sleep Quality [Срок оценки: Baseline and Week 8]

Критерии участия

Критерии включения

• Women aged 45 to 65 years
• Being in natural menopause (no menstrual bleeding for at least 12 months)
• Having non-specific chronic musculoskeletal pain for at least 3 months (reporting a pain intensity of at least 4 cm on the VAS)
• Using only standard analgesic medications for pain management
• Being literate
• Owning a smartphone or tablet, having the ability to listen to audio recordings, and having adequate skills to participate in online sessions
• Being willing to participate in the study and providing written informed consent

Критерии исключения

• Surgical or medication-induced menopause
• Regular use of opioid analgesics, anticonvulsants, antidepressants, or similar medications
• Uncontrolled advanced cardiovascular, oncological, metabolic, rheumatologic, or neurological diseases
• Body Mass Index (BMI) of 40 kg/m² or higher
• History of major surgery or severe trauma within the past 3 months

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Поддерживающая терапия

Центры проведения

Turkey (Türkiye) · 1 центр

• Baskent University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilita — Ankara

Публикации

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• Cotes JE. Medical Research Council Questionnaire on Respiratory Symptoms (1986). Lancet. 1987 Oct 31;2(8566):1028. doi: 10.1016/s0140-6736(87)92593-1. No abstract available. PMID 2889937
• Aydemir O. Turkish validation of HADS. Turkish Journal of Psychiatry. 1997;8:187-280.
• Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983 Jun;67(6):361-70. doi: 10.1111/j.1600-0447.1983.tb09716.x. PMID 6880820
• Turhan E, Inandi T. Assessment of reliability and validity of the Menopause-Specific Quality of Life Questionnaire in a Turkish population. HealthMED. 2011;5:111.
• Hilditch JR, Lewis J, Peter A, van Maris B, Ross A, Franssen E, Guyatt GH, Norton PG, Dunn E. A menopause-specific quality of life questionnaire: development and psychometric properties. Maturitas. 1996 Jul;24(3):161-75. doi: 10.1016/s0378-5122(96)82006-8. PMID 8844630
• Alaca N, Safran EE, Karamanlargil AI, Timucin E. Translation and cross-cultural adaptation of the extended version of the Nordic musculoskeletal questionnaire into Turkish. J Musculoskelet Neuronal Interact. 2019 Dec 1;19(4):472-481. PMID 31789298

Идентификаторы

NCT: NCT07302750 · KA25/405

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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