Ignite Creation Date:
2025-12-24 @ 4:55 PM
Ignite Modification Date:
2026-01-01 @ 6:58 PM
Study NCT ID:
NCT07302750
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-12-24
First Post:
2025-12-11
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
AI-Assisted Relaxation and Breathing Training in Postmenopausal Women
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000377', 'term': 'Agnosia'}], 'ancestors': [{'id': 'D010468', 'term': 'Perceptual Disorders'}, {'id': 'D019954', 'term': 'Neurobehavioral Manifestations'}, {'id': 'D009461', 'term': 'Neurologic Manifestations'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'SUPPORTIVE_CARE', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 48}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2026-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2027-02', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-12-11', 'studyFirstSubmitDate': '2025-12-11', 'studyFirstSubmitQcDate': '2025-12-11', 'lastUpdatePostDateStruct': {'date': '2025-12-24', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-12-24', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Participant Satisfaction', 'timeFrame': 'Week 8', 'description': '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."'}, {'measure': 'Sociodemographic and Clinical Characteristics', 'timeFrame': 'Baseline', 'description': "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.\n\nData 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."}], 'primaryOutcomes': [{'measure': 'Pain Intensity', 'timeFrame': 'Baseline and Week 8', 'description': '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").'}, {'measure': 'Pressure Pain Threshold', 'timeFrame': 'Baseline and Week 8', 'description': '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.'}, {'measure': 'Menopause-Specific Quality of Life', 'timeFrame': 'Baseline and Week 8', 'description': '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. Higher scores indicate higher symptom severity.'}], 'secondaryOutcomes': [{'measure': 'Musculoskeletal Symptoms', 'timeFrame': 'Baseline and Week 8', 'description': '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.'}, {'measure': 'Psychological Status', 'timeFrame': 'Baseline and Week 8', 'description': '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.'}, {'measure': 'Dyspnea', 'timeFrame': 'Baseline and Week 8', 'description': '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.'}, {'measure': 'Sleep Quality', 'timeFrame': 'Baseline and Week 8', 'description': '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.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['postmenopausal', 'artificial intelligence', 'pain management', 'quality of life'], 'conditions': ['Postmenopausal Period', 'Postmenopausal Women']}, 'referencesModule': {'references': [{'type': 'BACKGROUND', 'citation': 'Ağargün et al. Turkish PSQI validity. Turkish Journal of Psychiatry. 1996;7:107-115.'}, {'pmid': '2748771', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '2889937', 'type': 'BACKGROUND', 'citation': '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.'}, {'type': 'BACKGROUND', 'citation': 'Aydemir O. Turkish validation of HADS. Turkish Journal of Psychiatry. 1997;8:187-280.'}, {'pmid': '6880820', 'type': 'BACKGROUND', 'citation': '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.'}, {'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '8844630', 'type': 'BACKGROUND', 'citation': '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': '31789298', 'type': 'BACKGROUND', 'citation': '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': '6226917', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '39145262', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '36680381', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '34485731', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '34900019', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '25142566', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '26524978', 'type': 'BACKGROUND', 'citation': 'Dunford E, DClinPsy MT. Relaxation and Mindfulness in Pain: A Review. Rev Pain. 2010 Mar;4(1):18-22. doi: 10.1177/204946371000400105.'}, {'pmid': '25039019', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '39992004', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '38669625', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '33299396', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '30930293', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '39640884', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '35101087', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '26653408', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '35624141', 'type': 'BACKGROUND', 'citation': '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.'}]}, 'descriptionModule': {'briefSummary': '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.\n\nIn 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.\n\nAssessments 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.', 'detailedDescription': "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."}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '65 Years', 'minimumAge': '45 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Women aged 45 to 65 years\n* Being in natural menopause (no menstrual bleeding for at least 12 months)\n* Having non-specific chronic musculoskeletal pain for at least 3 months (reporting a pain intensity of at least 4 cm on the VAS)\n* Using only standard analgesic medications for pain management\n* Being literate\n* Owning a smartphone or tablet, having the ability to listen to audio recordings, and having adequate skills to participate in online sessions\n* Being willing to participate in the study and providing written informed consent\n\nExclusion Criteria:\n\n* Surgical or medication-induced menopause\n* Regular use of opioid analgesics, anticonvulsants, antidepressants, or similar medications\n* Uncontrolled advanced cardiovascular, oncological, metabolic, rheumatologic, or neurological diseases\n* Body Mass Index (BMI) of 40 kg/m² or higher\n* History of major surgery or severe trauma within the past 3 months'}, 'identificationModule': {'nctId': 'NCT07302750', 'briefTitle': 'AI-Assisted Relaxation and Breathing Training in Postmenopausal Women', 'organization': {'class': 'OTHER', 'fullName': 'Baskent University'}, 'officialTitle': 'The Effectiveness of Artificial Intelligence-Assisted Relaxation and Breathing Training on Pain Intensity and Quality of Life in Postmenopausal Women', 'orgStudyIdInfo': {'id': 'KA25/405'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'ACTIVE_COMPARATOR', 'label': 'Physiotherapist-Guided Relaxation and Breathing Training', 'description': 'Participants will receive individual face-to-face relaxation and breathing training supervised by a physiotherapist.', 'interventionNames': ['Other: Physiotherapist-Guided Relaxation and Breathing Training']}, {'type': 'EXPERIMENTAL', 'label': 'Artificial Intelligence-Assisted Relaxation and Breathing Training', 'description': 'Participants will follow an AI-generated relaxation and breathing training program.', 'interventionNames': ['Other: Artificial Intelligence-Assisted Relaxation and Breathing Training']}, {'type': 'SHAM_COMPARATOR', 'label': 'Control Group', 'description': 'Participants receive general information about relaxation and breathing exercises but do not participate in a structured program during the eight-week study period.', 'interventionNames': ['Other: Control Group - No Structured Training Program']}], 'interventions': [{'name': 'Physiotherapist-Guided Relaxation and Breathing Training', 'type': 'OTHER', 'description': '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.', 'armGroupLabels': ['Physiotherapist-Guided Relaxation and Breathing Training']}, {'name': 'Artificial Intelligence-Assisted Relaxation and Breathing Training', 'type': 'OTHER', 'description': '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.', 'armGroupLabels': ['Artificial Intelligence-Assisted Relaxation and Breathing Training']}, {'name': 'Control Group - No Structured Training Program', 'type': 'OTHER', 'description': '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.', 'armGroupLabels': ['Control Group']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Ankara', 'country': 'Turkey (Türkiye)', 'facility': 'Baskent University, Faculty of Health Sciences, Department of Physiotherapy and Rehabilitation, Cardiopulmonary Rehabilitation Unit', 'geoPoint': {'lat': 39.91987, 'lon': 32.85427}}], 'centralContacts': [{'name': 'Neslihan Durutürk, Prof. Dr.', 'role': 'CONTACT', 'email': 'nalkan@baskent.edu.tr', 'phone': '+90312 246 66 66', 'phoneExt': '1633'}], 'overallOfficials': [{'name': 'Neslihan Durutürk, Prof. Dr.', 'role': 'STUDY_DIRECTOR', 'affiliation': 'Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation'}, {'name': 'Aslıcan Çağlar, Asst. Prof.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation'}, {'name': 'Şeyma Mutlu Kayaarslan, MSc.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation'}, {'name': 'Hilal Yazici İlhan, MSc.', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Başkent University, Faculty of Health Sciences, Department of Physical Therapy and Rehabilitation'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Baskent University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Prof. Dr.', 'investigatorFullName': 'Neslihan Duruturk', 'investigatorAffiliation': 'Baskent University'}}}}