ClinicalTrials.gg
RecruitingNCT07302750Updated Jun 10, 2026

AI-Assisted Relaxation and Breathing Training in Postmenopausal Women

An interventional study of Physiotherapist-Guided Relaxation and Breathing Training and Artificial Intelligence-Assisted Relaxation and Breathing Training in Postmenopausal Period and Postmenopausal Women, sponsored by Baskent University. Recruiting at 1 site in Turkey (Türkiye). Open to female participants aged 45 Years to 65 Years. Per ClinicalTrials.gov, last updated 2026-06-10.

Sponsored by Baskent University · Not applicable, Interventional, and Supportive care

From the registry’s dates

  • Started Apr 2026; still recruiting 7 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
48
Allocation
Randomized
Ages
45 Years to 65 Years
Sex
Female
01

Study 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. 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.

02

Conditions studied

  • Postmenopausal Period
  • Postmenopausal Women

Keywords

  • postmenopausal
  • artificial intelligence
  • pain management
  • quality of life
03

In context

Lead sponsor

Baskent University is the lead sponsor of 209 studies on the registry; 35 are open to participants now.

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

04

Who can participate

Ages eligible
45 Years to 65 Years
Sexes eligible
Female
Accepts healthy volunteers
No

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

Inclusion criteria

  • 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

Exclusion criteria

Exclusion Criteria:

  • Surgical or medication-induced menopause
  • Regular use of opioid analgesics, anticonvulsants, antidepressants, or similar medications
  • Uncontrolled advanced cardiovascular, oncological, metabolic, rheumatologic, or neurological diseases
  • (BMI) of 40 kg/m² or higher
  • History of major surgery or severe trauma within the past 3 months
Terms in these criteria, in plain language(2)

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

Informed consent

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

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

BMI (body mass index)

Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.

What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.

05

Study design

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

Study arms

  • Active comparator
    Physiotherapist-Guided Relaxation and Breathing Training

    Participants will receive individual face-to-face relaxation and breathing training supervised by a physiotherapist.

    Other: Physiotherapist-Guided Relaxation and Breathing Training

  • Experimental
    Artificial Intelligence-Assisted Relaxation and Breathing Training

    Participants will follow an AI-generated relaxation and breathing training program.

    Other: Artificial Intelligence-Assisted Relaxation and Breathing Training

  • Sham comparator
    Control Group

    Participants receive general information about relaxation and breathing exercises but do not participate in a structured program during the eight-week study period.

    Other: Control Group - No Structured Training Program

Interventions

  • OtherPhysiotherapist-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.

    Also known as: Supervised Relaxation and Breathing Training

  • OtherArtificial 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 approximately 30 minutes. They will also be asked to keep a daily practice log.

    Also known as: AI-Based Relaxation and Breathing Training Program

  • OtherControl 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.

    Also known as: Control Group - No Structured Training

06

What researchers measure

Primary outcomes

  1. 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").

    Time frame: Baseline and Week 8

  2. 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.

    Time frame: Baseline and Week 8

  3. 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.

    Time frame: Baseline and Week 8

Secondary outcomes

  1. 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.

    Time frame: Baseline and Week 8

  2. 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.

    Time frame: Baseline and Week 8

  3. 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.

    Time frame: Baseline and Week 8

  4. 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.

    Time frame: Baseline and Week 8

Other outcomes

  1. Participant Satisfaction

    Satisfaction with the relaxation and breathing training program will be measured using a 10 cm Visual Analog Scale (VAS), where 0 cm indicates "not satisfied at all" and 10 cm indicates "completely satisfied."

    Time frame: Week 8

  2. Sociodemographic and Clinical Characteristics

    Participants' sociodemographic and clinical characteristics will be recorded using a personal information form. The form will include name, age, height, weight, body mass index, education level, marital status, employment status, and exercise habits. In addition to medical history, menopausal age and menopausal type will be determined based on participants' self-reports. Data collected before and after the training will be obtained from participant self-reports and medical records. Participants' ability to use a smartphone, listen to audio recordings, and participate in online sessions will also be assessed through self-report.

    Time frame: Baseline

07

Study locations

1 of 1 sites recruiting
  • Baskent University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Cardiopulmonary Rehabilitation Unit
    Ankara, Turkey (Türkiye)
    Recruiting
08

References and documents

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 2748771 ↗
  • 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. PubMed 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. PubMed 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. PubMed 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. PubMed 31789298 ↗
  • Price 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 6226917 ↗
  • Garg 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 39145262 ↗
  • Rughani 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 36680381 ↗
  • Vambheim 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 34485731 ↗
  • Doorley 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 34900019 ↗
  • Ong 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 25142566 ↗
  • Dunford E, DClinPsy MT. Relaxation and Mindfulness in Pain: A Review. Rev Pain. 2010 Mar;4(1):18-22. doi: 10.1177/204946371000400105. PubMed 26524978 ↗
  • Saensak S, Vutyavanich T, Somboonporn W, Srisurapanont M. Relaxation for perimenopausal and postmenopausal symptoms. Cochrane Database Syst Rev. 2014 Jul 20;2014(7):CD008582. doi: 10.1002/14651858.CD008582.pub2. PubMed 25039019 ↗
  • Amin SM, El-Gazar HE, Zoromba MA, El-Sayed MM, Awad AGE, Atta MHR. Mindfulness for Menopausal Women: Enhancing Quality of Life and Psychological Well-Being Through a Randomized Controlled Intervention. J Nurs Scholarsh. 2025 Jul;57(4):563-575. doi: 10.1111/jnu.70003. Epub 2025 Feb 24. PubMed 39992004 ↗
  • Xu H, Liu J, Li P, Liang Y. Effects of mind-body exercise on perimenopausal and postmenopausal women: a systematic review and meta-analysis. Menopause. 2024 May 1;31(5):457-467. doi: 10.1097/GME.0000000000002336. PubMed 38669625 ↗
  • Lu CB, Liu PF, Zhou YS, Meng FC, Qiao TY, Yang XJ, Li XY, Xue Q, Xu H, Liu Y, Han Y, Zhang Y. Musculoskeletal Pain during the Menopausal Transition: A Systematic Review and Meta-Analysis. Neural Plast. 2020 Nov 25;2020:8842110. doi: 10.1155/2020/8842110. eCollection 2020. PubMed 33299396 ↗
  • Collins BC, Laakkonen EK, Lowe DA. Aging of the musculoskeletal system: How the loss of estrogen impacts muscle strength. Bone. 2019 Jun;123:137-144. doi: 10.1016/j.bone.2019.03.033. Epub 2019 Mar 28. PubMed 30930293 ↗
  • Zhang C, Feng X, Zhang X, Chen Y, Kong J, Lou Y. Research progress on the correlation between estrogen and estrogen receptor on postmenopausal sarcopenia. Front Endocrinol (Lausanne). 2024 Nov 21;15:1494972. doi: 10.3389/fendo.2024.1494972. eCollection 2024. PubMed 39640884 ↗
  • Ambikairajah A, Walsh E, Cherbuin N. A review of menopause nomenclature. Reprod Health. 2022 Jan 31;19(1):29. doi: 10.1186/s12978-022-01336-7. PubMed 35101087 ↗
  • Santoro N. Perimenopause: From Research to Practice. J Womens Health (Larchmt). 2016 Apr;25(4):332-9. doi: 10.1089/jwh.2015.5556. Epub 2015 Dec 10. PubMed 26653408 ↗
  • Davis SR, Baber RJ. Treating menopause - MHT and beyond. Nat Rev Endocrinol. 2022 Aug;18(8):490-502. doi: 10.1038/s41574-022-00685-4. Epub 2022 May 27. PubMed 35624141 ↗
09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Started Apr 2026 (actual). Primary completion is estimated for Jan 2027, 9 months after the start.

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

Registered
Dec 11, 2025
First posted
Dec 24, 2025
StartActual
Apr 1, 2026
Primary completionEst.
Jan 2027
CompletionEst.
Feb 2027
Last update
Jun 10, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Jun 10, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07302750
Lead sponsor
Baskent University
Responsible party
Neslihan Duruturk (Prof. Dr., Baskent University) — Principal investigator
First posted
Dec 24, 2025
Start date
Apr 1, 2026
Primary completion
Jan 2027 (estimated)
Completion
Feb 2027 (estimated)
Last update
Jun 10, 2026

Study contacts

Neslihan Durutürk, Prof. Dr.
Contact
nalkan@baskent.edu.tr
+90312 246 66 66 ext. 1633
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
Hilal Yazici İlhan, MSc.
principal investigator · Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation

Oversight

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

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