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{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003924', 'term': 'Diabetes Mellitus, Type 2'}, {'id': 'D007319', 'term': 'Sleep Initiation and Maintenance Disorders'}, {'id': 'D003863', 'term': 'Depression'}], 'ancestors': [{'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D020919', 'term': 'Sleep Disorders, Intrinsic'}, {'id': 'D020920', 'term': 'Dyssomnias'}, {'id': 'D012893', 'term': 'Sleep Wake Disorders'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D001523', 'term': 'Mental Disorders'}, {'id': 'D001526', 'term': 'Behavioral Symptoms'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 150}, 'targetDuration': '1 Day', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2023-04-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-10', 'completionDateStruct': {'date': '2024-06-15', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-11-18', 'studyFirstSubmitDate': '2024-10-22', 'studyFirstSubmitQcDate': '2024-10-29', 'lastUpdatePostDateStruct': {'date': '2024-11-20', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-10-30', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-02-25', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Evaluating carbohydrate quality', 'timeFrame': 'Baseline', 'description': "A total of 132 food groups obtained from the food consumption frequency questionnaire were analyzed. Intake (g/day) was calculated using the BeBiS program with a global database, taking into account the amount and frequency of food consumed by each participant. Glycemic Index (GI) values were determined using the BeBiS program's global nutrient database, considering the amount and frequency of food consumed by each participant. To determine the Carbohydrate Quality Index (CQI) score, each of these four components (fiber intake, whole grain ratio, glycemic index, and total carbohydrate ratio) was evaluated on a scale of 1 to 5 points. The scores for each component were then calculated, with Q5 indicating the best and Q1 indicating the worst carbohydrate quality."}], 'secondaryOutcomes': [{'measure': 'Calculating sleep quality', 'timeFrame': 'Baseline', 'description': 'The Sleep Quality Scale (SQS) was used to evaluate the sleep quality of individuals diagnosed with Type 2 diabetes mellitus. The scale consists of a total of 8 questions, each with 3 response options. Scores can range from a minimum of 7 to a maximum of 21. As the score obtained from the scale increases, sleep quality decreases. Questions 5 and 6 were reverse-scored, and a total score was calculated.'}, {'measure': 'Depression, anxiety and stress scores', 'timeFrame': 'Baseline', 'description': 'The Depression Scale was used to evaluate the psychological status of patients with Type 2 diabetes during this process. The scale consists of a total of 21 questions, each graded on a scale from normal to very advanced (mild, moderate, severe, advanced). It has three sub-dimensions: depression, anxiety, and stress. As the scores in the subscales increase, levels of depression, anxiety, and stress also increase.'}, {'measure': 'Sociodemographic characteristics (age,)', 'timeFrame': 'Baseline', 'description': 'Sociodemographic characteristics will be assessed using a structured questionnaire developed by the researchers. The questionnaire will include items measuring age, gender, education level, and income status. The results will be presented as numbers and percentages for each characteristic'}, {'measure': 'Body Mass Index (BMI)', 'timeFrame': 'Baseline', 'description': 'Kilograms per square meter (kg/m2)'}, {'measure': 'Body weight', 'timeFrame': 'Baseline', 'description': 'Body weight in kg'}, {'measure': 'Height', 'timeFrame': 'Baseline', 'description': 'Height in cm'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['carbohydrate quality', 'type 2 diabetes mellitus', 'sleep quality', 'depression', 'stress'], 'conditions': ['Type 2 DM']}, 'descriptionModule': {'briefSummary': 'The aim of this study was to evaluate the effect of carbohydrate quality on sleep quality and depression in patients with Type 2 diabetes. Data were collected from 150 patients with Type 2 diabetes mellitus using a demographic structure questionnaire, the Sleep Quality Scale (SQS), the Depression, Anxiety, and Stress Scale (DASS), and a Food Consumption Frequency Form. The data were analyzed using SPSS 26.', 'detailedDescription': 'Objective: The aim of this study was to evaluate the effect of carbohydrate quality on sleep quality and depression in patients with Type 2 diabetes.\n\nMethod: A total of 150 individuals with Type 2 diabetes were included in the study. A demographic questionnaire, the Sleep Quality Scale (SQS) (where a higher SQS score indicates lower sleep quality), and the Depression Anxiety and Stress Scale were administered to the participants. Additionally, data on the frequency of food consumption for 132 foods were obtained from the participants. To determine the Carbohydrate Quality Index (CQI) score, each of these four components (fiber intake, whole grain ratio, glycemic index, and total carbohydrate ratio) was evaluated on a scale of 1 to 5 points. The score for each component was then calculated, with Q5 indicating the best and Q1 indicating the worst carbohydrate quality. The data were analyzed using SPSS 24 software.\n\nDetailed Description: This study will evaluate carbohydrate quality index ranges (Q1-Q5), sleep quality scale score, depression, stress, anxiety score, body mass index, diabetic age, sleep duration, body weight, daily macro and micro nutrients.\n\nConclusion: Results will be analyzed and interpreted after data collection is completed, and conclusions will be drawn accordingly.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '64 Years', 'minimumAge': '19 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Community sample in Ankara, Turkey', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients aged 19 to 64 years\n* Diagnosed with Type 2 diabetes mellitus\n* Voluntary participation\n\nExclusion Criteria:\n\n* Patients with cancer\n* Pregnant and lactating women\n* Individuals with alcohol or drug addiction\n* Individuals diagnosed with psychiatric or neurological disorders'}, 'identificationModule': {'nctId': 'NCT06666205', 'briefTitle': 'Carbohydrate Quality and Its Impact on Sleep and Depression in Type 2 Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'Ankara Yildirim Beyazıt University'}, 'officialTitle': 'Evaluation of the Effect of Carbohydrate Quality on Sleep Quality and Depression in Patients with Type 2 Diabete', 'orgStudyIdInfo': {'id': 'AYBUELİBOL002'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Type 2 DM patients', 'description': 'This study focuses on patients with Type 2 diabetes and examines the impact of carbohydrate quality on sleep quality and depression. Participants were assessed using a demographic questionnaire, and their dietary carbohydrate intake was analyzed. Sleep patterns were monitored, and depression levels were measured using validated assessment scales. The study aims to investigate the relationship between carbohydrate quality, sleep health, and depression in this population.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '06760', 'city': 'Ankara', 'country': 'Turkey (Türkiye)', 'facility': 'Ankara Yıldırım Beyazıt University', 'geoPoint': {'lat': 39.91987, 'lon': 32.85427}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Ankara Yildirim Beyazıt University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assist. Prof.', 'investigatorFullName': 'Emine Elibol', 'investigatorAffiliation': 'Ankara Yildirim Beyazıt University'}}}}