Postmenopausal PeriodNCT07302750
AI-Assisted Relaxation and Breathing Training in Postmenopausal Women
A study testing Physiotherapist-Guided Relaxation and Breathing Training and Artificial Intelligence-Assisted Relaxation and Breathing Training in people with Postmenopausal Period and Postmenopausal Women, run by Baskent University at 1 site in Turkey (Türkiye).
Trial summary
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. Read more about this study
- Who is it for?
- Ages 45 to 65 years, women only
- Conditions the study is for
- Postmenopausal Period, Postmenopausal Women
- What is being tested?
- Physiotherapist-Guided Relaxation and Breathing Training and Artificial Intelligence-Assisted Relaxation and Breathing Training
- Type of treatment
- Pill or oral medicine
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 48 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Apr 2026to Feb 2027
- 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 45 to 65 years
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Turkey (Türkiye)1 site, 1 recruiting
- Recruiting
Baskent University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Cardiopulmonary Rehabilitation Unit
Ankara
About this study
Official title: The Effectiveness of Artificial Intelligence-Assisted Relaxation and Breathing Training on Pain Intensity and Quality of Life in Postmenopausal Women
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.
Read the detailed description
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.
- Conditions
- Postmenopausal Period, Postmenopausal Women
- Being tested
- Physiotherapist-Guided Relaxation and Breathing Training, Artificial Intelligence-Assisted Relaxation and Breathing Training, Control Group - No Structured Training Program
- Keywords
- postmenopausal, artificial intelligence, pain management, quality of life
- Medical subject headings
- Agnosia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Physiotherapist-Guided Relaxation and Breathing TrainingOther
Also called Supervised 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.
Artificial Intelligence-Assisted Relaxation and Breathing TrainingOther
Also called AI-Based Relaxation and Breathing Training Program
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 approximately 30 minutes. They will also be asked to keep a daily practice log.
Control Group - No Structured Training ProgramOther
Also called Control Group - No Structured Training
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.
| Study group | Role | What they receive |
|---|---|---|
| Physiotherapist-Guided Relaxation and Breathing Training | Active comparator | Participants will receive individual face-to-face relaxation and breathing training supervised by a physiotherapist. Receives: Other: Physiotherapist-Guided Relaxation and Breathing Training |
| Artificial Intelligence-Assisted Relaxation and Breathing Training | Experimental | Participants will follow an AI-generated relaxation and breathing training program. Receives: Other: Artificial Intelligence-Assisted Relaxation and Breathing Training |
| Control Group | Sham comparator | Participants receive general information about relaxation and breathing exercises but do not participate in a structured program during the eight-week study period. Receives: Other: Control Group - No Structured Training Program |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pain Intensity
Pain intensity will be assessed using the Visual Analog Scale (VAS). Participants will rate their pain on a 10 cm horizontal line ranging from 0 ("no pain") to 10 ("unbearable pain").
Measured: Baseline and Week 8
Pressure Pain Threshold
Pressure pain threshold will be measured using a digital algometer. Participants will indicate when they first perceive pain. Three measurements will be taken from each site, and the mean value will be used for analysis. All measurements will be completed by the same trained researcher.
Measured: Baseline and Week 8
Menopause-Specific Quality of Life
The Menopause-Specific Quality of Life Questionnaire will be used to evaluate the impact of menopausal symptoms on quality of life. The scale consists of 32 items and four domains: vasomotor, psychosocial, physical, and sexual. The minimum possible score is 1, and the maximum possible score is 8, with higher scores indicating worse outcomes. An increase in the total score reflects greater symptom severity and a decrease in quality of life.
Measured: Baseline and Week 8
Secondary outcomes (4)
Musculoskeletal Symptoms
Musculoskeletal symptoms will be assessed using the Extended Nordic Musculoskeletal Questionnaire. This questionnaire evaluates pain, discomfort, and functional limitations in nine body regions (neck, shoulder, upper back, lower back, elbow, hand/wrist, hip, knee, ankle/foot) over the past 12 months. Additional items assess pain duration, severity, and impact on daily activities.The questionnaire primarily provides categorical (yes/no) responses rather than a total scale score.
Measured: Baseline and Week 8
Psychological Status
The Hospital Anxiety and Depression Scale (HADS) will be used to assess the severity of anxiety and depression symptoms. The scale includes 14 items with two subscales-anxiety and depression-each scored using a 4-point Likert scale (0-3). Higher scores indicate greater severity of anxiety or depressive symptoms, representing worse outcomes.
Measured: Baseline and Week 8
Dyspnea
Dyspnea severity will be evaluated using the Modified Medical Research Council (mMRC) Dyspnea Scale. Participants will indicate the level of physical activity that triggers shortness of breath. The mMRC Dyspnea Scale is a 5-grade scale ranging from 0 to 4, with higher grades indicating greater breathlessness during daily activities. Higher scores indicate more severe dyspnea and a worse outcome.
Measured: Baseline and Week 8
Sleep Quality
Sleep quality will be assessed using the Pittsburgh Sleep Quality Index (PSQI). The scale evaluates sleep habits and sleep-related problems over the past month. Component scores range from 0 to 3, producing a total score between 0 and 21. Scores of 5 or higher indicate poor sleep quality.
Measured: Baseline and Week 8
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Dec 2025
- Study start1 Apr 2026
- Primary completionJan 2027 (estimated)
- Study completionFeb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (24)Papers the sponsor has linked to this study.
- Other trials for Postmenopausal PeriodStudies of the same condition, open and under way.
- 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
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 48 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Baskent University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Neslihan Duruturk, Baskent University
- Investigators
- Neslihan Durutürk, Prof. Dr., Study director, Başkent University, Faculty of Health Sciences, Department of Physical Therapy and RehabilitationAslıcan Çağlar, Asst. Prof., Principal investigator, Başkent University, Faculty of Health Sciences, Department of Physical Therapy and RehabilitationŞeyma Mutlu Kayaarslan, MSc., Principal investigator, Başkent University, Faculty of Health Sciences, Department of Physical Therapy and RehabilitationHilal Yazici İlhan, MSc., Principal investigator, Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07302750
- Sponsor's protocol ID
- KA25/405
- Status last verified
- Jun 2026
- First submitted
- 11 Dec 2025
- Last updated
- 10 Jun 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Ağargün et al. Turkish PSQI validity. Turkish Journal of Psychiatry. 1996;7:107-115.
Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.
PubMed 2748771Cotes 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.
PubMed 2889937Aydemir 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.
PubMed 6880820Turhan 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.
PubMed 8844630Alaca 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.
PubMed 31789298Price DD, McGrath PA, Rafii A, Buckingham B. The validation of visual analogue scales as ratio scale measures for chronic and experimental pain. Pain. 1983 Sep;17(1):45-56. doi: 10.1016/0304-3959(83)90126-4.
PubMed 6226917Garg R, Munshi A. Revolutionizing Menopause Management: Harnessing the Potential of Artificial Intelligence. J Midlife Health. 2024 Apr-Jun;15(2):53-54. doi: 10.4103/jmh.jmh_104_24. Epub 2024 Jul 5. No abstract available.
PubMed 39145262Rughani G, Nilsen TIL, Wood K, Mair FS, Hartvigsen J, Mork PJ, Nicholl BI. The selfBACK artificial intelligence-based smartphone app can improve low back pain outcome even in patients with high levels of depression or stress. Eur J Pain. 2023 May;27(5):568-579. doi: 10.1002/ejp.2080. Epub 2023 Jan 27.
PubMed 36680381Vambheim SM, Kyllo TM, Hegland S, Bystad M. Relaxation techniques as an intervention for chronic pain: A systematic review of randomized controlled trials. Heliyon. 2021 Aug 20;7(8):e07837. doi: 10.1016/j.heliyon.2021.e07837. eCollection 2021 Aug.
PubMed 34485731Doorley J, Greenberg J, Stauder M, Vranceanu AM. The role of mindfulness and relaxation in improved sleep quality following a mind-body and activity program for chronic pain. Mindfulness (N Y). 2021 Nov;12(11):2672-2680. doi: 10.1007/s12671-021-01729-y. Epub 2021 Sep 1.
PubMed 34900019Ong JC, Manber R, Segal Z, Xia Y, Shapiro S, Wyatt JK. A randomized controlled trial of mindfulness meditation for chronic insomnia. Sleep. 2014 Sep 1;37(9):1553-63. doi: 10.5665/sleep.4010.
PubMed 25142566Dunford E, DClinPsy MT. Relaxation and Mindfulness in Pain: A Review. Rev Pain. 2010 Mar;4(1):18-22. doi: 10.1177/204946371000400105.
PubMed 26524978
Study at a glance
From the registry record, last updated by the sponsor on 10 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Effectiveness of Artificial Intelligence-Assisted Relaxation and Breathing Training on Pain Intensity and Quality of Life in Postmenopausal Women
- ClinicalTrials.gov ID
- NCT07302750
- Acronym / sponsor ID
- KA25/405
- Conditions
- Postmenopausal Period, Postmenopausal Women
- Keywords
- postmenopausal, artificial intelligence, pain management, quality of life
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 48 participants (estimated)
- Lead sponsor
- Baskent UniversityUniversity, hospital or other
- Study start
- 1 Apr 2026 (actual)
- Primary completion
- Jan 2027 (estimated)
- Study completion
- Feb 2027 (estimated)
- First posted
- 24 Dec 2025 (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.
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.
Detailed description
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.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Physiotherapist-Guided Relaxation and Breathing Training | Active comparator | Other: Physiotherapist-Guided Relaxation and Breathing TrainingParticipants will receive individual face-to-face relaxation and breathing training supervised by a physiotherapist. |
| Artificial Intelligence-Assisted Relaxation and Breathing Training | Experimental | Other: Artificial Intelligence-Assisted Relaxation and Breathing TrainingParticipants will follow an AI-generated relaxation and breathing training program. |
| Control Group | Sham comparator | Other: Control Group - No Structured Training ProgramParticipants receive general information about relaxation and breathing exercises but do not participate in a structured program during the eight-week study period. |
Who may qualify
- Ages
- 45 to 65 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- 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
Key exclusion criteria (5 listed)
- 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
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 |
|---|---|---|
| Physiotherapist-Guided Relaxation and Breathing TrainingAlso: Supervised Relaxation and Breathing TrainingParticipants 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. | Other | Physiotherapist-Guided Relaxation and Breathing Training |
| Artificial Intelligence-Assisted Relaxation and Breathing TrainingAlso: AI-Based Relaxation and Breathing Training ProgramIn 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 approximately 30 minutes. They will also be asked to keep a daily practice log. | Other | Artificial Intelligence-Assisted Relaxation and Breathing Training |
| Control Group - No Structured Training ProgramAlso: Control Group - No Structured TrainingParticipants 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. | Other | Control Group |
Primary outcome
Pain Intensity
Time frame: Baseline and Week 8
Pain intensity will be assessed using the Visual Analog Scale (VAS). Participants will rate their pain on a 10 cm horizontal line ranging from 0 ("no pain") to 10 ("unbearable pain").
Pressure Pain Threshold
Time frame: Baseline and Week 8
Pressure pain threshold will be measured using a digital algometer. Participants will indicate when they first perceive pain. Three measurements will be taken from each site, and the mean value will be used for analysis. All measurements will be completed by the same trained researcher.
Menopause-Specific Quality of Life
Time frame: Baseline and Week 8
The Menopause-Specific Quality of Life Questionnaire will be used to evaluate the impact of menopausal symptoms on quality of life. The scale consists of 32 items and four domains: vasomotor, psychosocial, physical, and sexual. The minimum possible score is 1, and the maximum possible score is 8, with higher scores indicating worse outcomes. An increase in the total score reflects greater symptom severity and a decrease in quality of life.
4 secondary outcomes
Musculoskeletal Symptoms
Time frame: Baseline and Week 8
Psychological Status
Time frame: Baseline and Week 8
Dyspnea
Time frame: Baseline and Week 8
Sleep Quality
Time frame: Baseline and Week 8
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 10 Jun 2026.
- BackgroundAğargün et al. Turkish PSQI validity. Turkish Journal of Psychiatry. 1996;7:107-115.
- Background: PubMed 2748771Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.
- Background: PubMed 2889937Cotes 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.
- BackgroundAydemir O. Turkish validation of HADS. Turkish Journal of Psychiatry. 1997;8:187-280.
- Background: PubMed 6880820Zigmond 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.
- BackgroundTurhan E, Inandi T. Assessment of reliability and validity of the Menopause-Specific Quality of Life Questionnaire in a Turkish population. HealthMED. 2011;5:111.
- Background: PubMed 8844630Hilditch 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.
- Background: PubMed 31789298Alaca 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.
- Background: PubMed 6226917Price DD, McGrath PA, Rafii A, Buckingham B. The validation of visual analogue scales as ratio scale measures for chronic and experimental pain. Pain. 1983 Sep;17(1):45-56. doi: 10.1016/0304-3959(83)90126-4.
- Background: PubMed 39145262Garg R, Munshi A. Revolutionizing Menopause Management: Harnessing the Potential of Artificial Intelligence. J Midlife Health. 2024 Apr-Jun;15(2):53-54. doi: 10.4103/jmh.jmh_104_24. Epub 2024 Jul 5. No abstract available.
- Background: PubMed 36680381Rughani G, Nilsen TIL, Wood K, Mair FS, Hartvigsen J, Mork PJ, Nicholl BI. The selfBACK artificial intelligence-based smartphone app can improve low back pain outcome even in patients with high levels of depression or stress. Eur J Pain. 2023 May;27(5):568-579. doi: 10.1002/ejp.2080. Epub 2023 Jan 27.
- Background: PubMed 34485731Vambheim SM, Kyllo TM, Hegland S, Bystad M. Relaxation techniques as an intervention for chronic pain: A systematic review of randomized controlled trials. Heliyon. 2021 Aug 20;7(8):e07837. doi: 10.1016/j.heliyon.2021.e07837. eCollection 2021 Aug.
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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.
Neslihan Durutürk, Prof. Dr. study director
Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation
Aslıcan Çağlar, Asst. Prof. principal investigator
Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation
Şeyma Mutlu Kayaarslan, MSc. principal investigator
Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Physiotherapist-Guided Relaxation and Breathing Training and Artificial Intelligence-Assisted Relaxation and Breathing Training in people with Postmenopausal Period and Postmenopausal Women, run by Baskent University at 1 site in Turkey (Türkiye).
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 7 inclusion and 5 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: looking for participants now, as of the sponsor's last update on 10 Jun 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 Turkey (Türkiye). 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. Some participants in this study may receive a placebo. 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?
Contact Neslihan Durutürk, Prof. Dr. (+90312 246 66 66 ext. 1633, nalkan@baskent.edu.tr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pain Intensity (time frame: Baseline and Week 8). 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?
On the ClinicalTrials.gov record for NCT07302750, which also lists 24 linked publications.
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 10 Jun 2026.