Ignite Creation Date:
2025-12-24 @ 5:18 PM
Ignite Modification Date:
2026-01-11 @ 9:57 PM
Study NCT ID:
NCT07236450
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-11-19
First Post:
2025-11-15
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Use of a Mobile Application for Tracking Physical Activity in the Management of Metabolic Syndrome in Primary Care
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D024821', 'term': 'Metabolic Syndrome'}, {'id': 'D009043', 'term': 'Motor Activity'}, {'id': 'D015438', 'term': 'Health Behavior'}, {'id': 'D010358', 'term': 'Patient Participation'}], 'ancestors': [{'id': 'D007333', 'term': 'Insulin Resistance'}, {'id': 'D006946', 'term': 'Hyperinsulinism'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D001519', 'term': 'Behavior'}, {'id': 'D010342', 'term': 'Patient Acceptance of Health Care'}, {'id': 'D000074822', 'term': 'Treatment Adherence and Compliance'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D000076251', 'term': 'Wearable Electronic Devices'}], 'ancestors': [{'id': 'D055615', 'term': 'Electrical Equipment and Supplies'}, {'id': 'D004864', 'term': 'Equipment and Supplies'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'SUPPORTIVE_CARE', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'This is a two-arm, parallel-group, superiority randomized controlled trial designed to evaluate the influence of a mobile application for physical activity tracking on exercise behavior and clinical outcomes in individuals with metabolic syndrome managed in primary care. Participants will be randomly assigned in a 1:1 ratio to either an intervention group (mobile app + wearable device) or a control group (usual care).'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2025-07-24', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-11', 'completionDateStruct': {'date': '2026-02', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-11-15', 'studyFirstSubmitDate': '2025-11-15', 'studyFirstSubmitQcDate': '2025-11-15', 'lastUpdatePostDateStruct': {'date': '2025-11-19', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-11-19', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2026-02', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Physical Literacy', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Physical literacy will be assessed using the Perceived Physical Literacy Instrument (PPLI-PT), a validated questionnaire evaluating motivation, confidence, knowledge, and participation in physical activity (5-point Likert scale, 1=Strongly disagree to 5=Strongly agree).\n\nThe questionnaire was composed by nine items distributed across three dimensions:\n\n* Knowledge and understanding: Items PPLI-PT4, PPLI-PT5, PPLI-PT17;\n* Self-perception and self-confidence: Items PPLI-PT2, PPLI-PT7, PPLI-PT8;\n* Self-expression and communication with others: Items PPLI-PT11, PPLI-PT12, PPLI-PT13.\n\nScoring and Interpretation:\n\nFor each dimension, add the responses to the corresponding items, divide the total by the number of items in the dimension (3) to obtain the average and record the scores for each dimension separately. Higher scores in each dimension reflect a greater perceived physical literacy in the respective specific area.'}, {'measure': 'EQ5D-5L', 'timeFrame': 'Baseline, 3 months, 6 months', 'description': 'An instrument to describe and value health across a wide range of disease areas.\n\n5-level EQ-5D (EuroQol instrument with 5 dimensions and 5 levels) version with five dimensions (five levels, categorical options): mobility, self-care, usual activities, pain/discomfort, and anxiety/depression.\n\nScore ranges:\n\n1. I have no problems ...walking/dressing, etc (better outcome);\n2. I have some problems ...walking/dressing, etc;\n3. I have moderate problems ...walking/dressing, etc;\n4. I have severe problems ...walking/dressing, etc;\n5. I have extreme problems ...walking/dressing, etc (worse outcome).'}, {'measure': 'Physical Activity Levels', 'timeFrame': 'Baseline, 3 months, 6 months', 'description': 'Physical activity will be measured using the International Physical Activity Questionnaire (IPAQ - Short Version, 4 topics with 2 questions each one - question 1a, question 1b, question 2a, question 2b, etc).\n\nScore based on the formula:\n\nMET-min/week = MET × minutes per day × days per week (values for minutes and days per week are answered through questions 1a, 1b, 2a, 2b, 3a, 3b, 4a, 4b)\n\nStandard MET values for each activity type:\n\n* Walking: 3.3 METs\n* Moderate activity: 4.0 METs\n* Vigorous activity: 8.0 METs'}, {'measure': 'Clinical and Metabolic Health Parameters - Total cholesterol', 'timeFrame': 'Baseline, 3 months, 6 months', 'description': 'Total cholesterol (mg/dl)'}, {'measure': 'Clinical and Metabolic Health Parameters - HDL cholesterol', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'HDL cholesterol (mg/dl - milligrams per deciliter)'}, {'measure': 'Clinical and Metabolic Health Parameters - LDL cholesterol', 'timeFrame': 'Baseline, 3 months, 6 months', 'description': 'HDL cholesterol (mg/dl - milligrams per deciliter) -- calculated field:\n\nLDL Cholesterol = Total Cholesterol - HDL Cholesterol - (Triglycerides / 5)'}, {'measure': 'Clinical and Metabolic Health Parameters - nHDL cholesterol', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'non-HDL cholesterol (mg/dl - milligrams per deciliter) -- calculated field: nHDL = Colesterol Total - Colesterol HDL'}, {'measure': 'Clinical and Metabolic Health Parameters - Triglycerides', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Triglycerides (mg/dl - milligrams per deciliter)'}, {'measure': 'Clinical and Metabolic Health Parameters - Fasting Glucose', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Fasting Glucose (mg/dl - milligrams per deciliter)'}, {'measure': 'Clinical and Metabolic Health Parameters - Glycated Hemoglobin', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Glycated Hemoglobin (%)'}, {'measure': 'Clinical and Metabolic Health Parameters - Aspartate Aminotransferase', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Aspartate Aminotransferase (U/L - units per liter)'}, {'measure': 'Clinical and Metabolic Health Parameters - Alanine Aminotransferase', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Alanine Aminotransferase (U/L - units per liter)'}, {'measure': 'Anthropometric Data - Body Mass Index (BMI)', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'BMI-Body Mass Index (kg/m² - kilograms per square meter)'}, {'measure': 'Anthropometric Data - Abdominal circumference', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Abdominal circumference (cm)'}, {'measure': 'Anthropometric Data - Waist-to-height ratio', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Waist-to-height ratio (WHtR, cm-centimeter) WHtR = Waist Circumference (cm-centimeter) ÷ Height (cm-centimeter)'}, {'measure': 'Anthropometric Data - Blood pressure', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Blood pressure (mm Hg-millimeters of mercury)'}, {'measure': 'Anthropometric Data - Heart rate', 'timeFrame': 'Baseline, 3 months, 6 months.', 'description': 'Heart rate (beat per minute)'}], 'secondaryOutcomes': [{'measure': 'App Usage Metrics - Daily Active Users', 'timeFrame': '3 months, 6 months.', 'description': 'Number of users engaging with the app daily (integer).'}, {'measure': 'App Usage Metrics - Monthly Active Users', 'timeFrame': '3 months, 6 months.', 'description': 'Number of users engaging with the app at least once per month (integer).'}, {'measure': 'App Usage Metrics - Session Frequency', 'timeFrame': '3 months, 6 months.', 'description': 'How often users open the app per day or week (number/day or /week).'}, {'measure': 'App Usage Metrics - Session Duration', 'timeFrame': '3 months, 6 months.', 'description': 'Average time spent in the app per session (minutes).'}, {'measure': 'Push Notification Engagement - Open Rate (%)', 'timeFrame': '3 months, 6 months.', 'description': 'Percentage of push notifications opened.'}, {'measure': 'Push Notification Engagement - Dismissal Rate (%)', 'timeFrame': '3 months, 6 months.', 'description': 'Percentage of notifications ignored or dismissed.'}, {'measure': 'Wearable activity tracker - measure 1', 'timeFrame': '3 months and 6 months', 'description': 'Data from the wearable activity tracker (e.g., step count and app usage patterns) - DESCREVER EXATAMENTE QUAIS SÃO AS MEDIÇÕES ANALISADAS'}, {'measure': 'Motivational Content Interaction - Message Open Rate (%)', 'timeFrame': '3 months, 6 months.', 'description': 'Percentage of users who open motivational messages.'}, {'measure': 'Motivational Content Interaction - Completion Rate (%)', 'timeFrame': '3 months, 6 months', 'description': 'Percentage of users who fully read the messages.'}, {'measure': 'Motivational Content Interaction - Feedback Responses', 'timeFrame': '3 months, 6 months', 'description': 'Number of "thumbs up" or "thumbs down" clicks on messages, reflecting their perceived usefulness'}, {'measure': 'Physical Activity Metrics - Step Count Increase (%)', 'timeFrame': '3 months, 6 months.', 'description': 'Change in the average daily step count over time.'}, {'measure': 'Retention Rate by Users (%)', 'timeFrame': '3 months, 6 months.', 'description': 'Percentage of users returning to the app after 1 week, 1 month, etc.'}, {'measure': 'Streak Tracking', 'timeFrame': '3 months, 6 months', 'description': 'Number of consecutive days comprising interaction with the app.'}, {'measure': 'Dropout rate (%)', 'timeFrame': '3 months, 6 months', 'description': 'Participants will be classified as dropouts if they have not used the mobile application and wearable device for a continuous period of 60 days.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Metabolic Syndrome', 'Physical Activity', 'Family Medicine', 'Mobile Health', 'mHealth', 'Mobile Application', 'Physical Activity Monitoring', 'Wearable Device', 'Digital Health', 'Self-Monitoring', 'Lifestyle Intervention', 'Exercise Promotion', 'Physical Literacy', 'Health Behavior', 'Patient Engagement'], 'conditions': ['Metabolic Syndrome (MetS)']}, 'descriptionModule': {'briefSummary': "This study will explore whether integrating a mobile app to track physical activity-recommended by family doctors during routine primary care visits-can help individuals with metabolic syndrome become more active. Participants will be randomly assigned to one of two groups: the intervention group will use the mobile app combined with an activity-tracking wristband; the control group will receive usual care without digital tools.\n\nFamily doctors will introduce and support the use of the mobile app during standard consultations. The study will also assess physicians' perceptions of using digital technologies, such as mobile apps and telemedicine, to encourage physical activity.\n\nResearchers will monitor the frequency of app use, step counts and changes in physical activity habits over time.\n\nThe primary goal is to determine whether digital health tools can be feasibly implemented in primary care to promote healthier lifestyles and improve chronic disease management in people with metabolic syndrome.", 'detailedDescription': "This study examines the impact of a mobile application for tracking physical activity (PA) on the management of metabolic syndrome in a primary care setting. It also explores family physicians' attitudes and behavioral intentions regarding the adoption of telemedicine tools for health promotion.\n\nThis is a two-arm, parallel-group, superiority randomized controlled pilot study. Adult patients diagnosed with metabolic syndrome, who own a compatible smartphone, will be recruited from primary care units. Eligible participants will be randomly assigned to one of two groups: an intervention group, receiving a mobile health application (Polis Saúde®) integrated with a wearable PA-tracking device (Fitbit Inspire 3), or to a control group receiving the usual care without digital tools. Follow-up assessments will be conducted at baseline, 3 months, and 6 months.\n\nThe mobile application offers personalized motivational messages, health education content, and real-time PA monitoring. Data will be collected on app usage, engagement with motivational content, step counts, and participant feedback. Clinical and anthropometric data, such as lipid profiles, fasting glucose, blood pressure, BMI, and waist circumference, will also be collected.\n\nPrimary outcomes include adherence to the intervention (app usage, engagement with motivational content), retention, step count data, and dropout rates. Secondary outcomes include assessment of physical literacy, PA habits (via IPAQ), app usage metrics (frequency, session duration, feedback responses, completion and dismissal rates, etc).\n\nThe study will further assess family physicians' attitudes and intentions toward telemedicine (using the PAIT questionnaire).\n\nData will be analyzed using descriptive and inferential statistics, including regression and survival models.\n\nThe study aims to assess the feasibility, adherence, and potential effectiveness of mobile health technologies for promoting PA and managing chronic conditions in primary care. It will also provide insights into the behavioral determinants of physician adoption of digital health tools. The findings will inform future large-scale trials and contribute to clinical strategies and public health policies that integrate digital health solutions into chronic disease care."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults aged 18 years or older;\n* Diagnosed with metabolic syndrome;\n* Presence of at least one of the following ICPC-2 (International Classification of Primary Care - 2nd edition), used in primary health care:codes in the medical record:\n\n * T83 (Overweight) or T82 (Obesity), with waist circumference ≥ 94 cm (men) or ≥ 80 cm (women)\n * T89 (Non-insulin-dependent diabetes)\n * T93 (Lipid metabolism disorder: HDL \\< 40 mg/dl for men, \\< 50 mg/dl for women; or triglycerides ≥ 150 mg/dl)\n * K86 (Hypertension without complications) or K87 (Hypertension with complications);\n* Access to a smartphone compatible with the mobile application;\n* Does not currently use any physical activity monitoring device (e.g., pedometer, smartwatch, fitness tracker);\n* Willing and able to provide informed consent.\n\nExclusion Criteria:\n\n* No scheduled medical appointments in the past three years;\n* Refusal to participate or withdraws consent;\n* Change of primary care unit during the study period;\n* Pregnant at the time of enrollment or becomes pregnant during the study;\n* Diagnosed mental incapacity that prevents answering questionnaires;\n* Does not own a smartphone;\n* Inability to use a mobile application;\n* Inability to use a physical activity tracking wristband.'}, 'identificationModule': {'nctId': 'NCT07236450', 'acronym': 'IMAFIL', 'briefTitle': 'Use of a Mobile Application for Tracking Physical Activity in the Management of Metabolic Syndrome in Primary Care', 'organization': {'class': 'OTHER', 'fullName': 'Unidade Local de Saúde de Coimbra, EPE'}, 'officialTitle': 'Exploring the Role of a Mobile Application for Physical Activity Tracking in the Management of Metabolic Syndrome in Primary Care', 'orgStudyIdInfo': {'id': 'EECC-2024_4-220 e 335/25 CE'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'NO_INTERVENTION', 'label': 'Usual Care Without Digital Monitoring', 'description': 'Participants will receive usual primary care for the management of metabolic syndrome, without access to digital tools for physical activity monitoring. No mobile application or wearable device will be provided. Clinical follow-up will adhere standard practice guidelines, and no additional digital health interventions will be introduced throughout the study period.'}, {'type': 'EXPERIMENTAL', 'label': 'Mobile Application and Wearable Device for Physical Activity Monitoring', 'description': 'Participants will receive usual primary care along with access to a mobile health application (Polis Saúde®) integrated with a wearable activity-tracking device (Fitbit Inspire 3). The application provides real-time physical activity monitoring, motivational messages, and educational content. Participants will be instructed to use the app and wearable device regularly throughout the 6-month study period. Engagement with the app, step count data, and interaction with motivational content will be tracked to assess adherence and behavior change.', 'interventionNames': ['Device: Mobile Application and Wearable Device for Physical Activity Monitoring']}], 'interventions': [{'name': 'Mobile Application and Wearable Device for Physical Activity Monitoring', 'type': 'DEVICE', 'otherNames': ['Fitbit Inspire 3', 'Mobile Health Application for Physical Activity Monitoring', 'Digital Health Intervention for Metabolic Syndrome', 'Polis Saúde App'], 'description': 'This intervention consists of a mobile health application (Polis Saúde®) integrated with a wearable activity tracker (Fitbit Inspire 3) designed to support physical activity monitoring and behavior change in adults with metabolic syndrome. The mobile application delivers personalized motivational messages and educational content twice weekly and records user engagement, including app usage and interaction with content. The wearable device continuously tracks step count and synchronizes data with the app. Participants are encouraged to use the app and device daily over a 6-month period. Data on adherence, physical activity, and health metrics will be collected to evaluate the impact on lifestyle and clinical outcomes.', 'armGroupLabels': ['Mobile Application and Wearable Device for Physical Activity Monitoring']}]}, 'contactsLocationsModule': {'locations': [{'zip': '3000-011', 'city': 'Coimbra', 'state': 'Portugal', 'country': 'Portugal', 'facility': 'USF Cruz de Celas', 'geoPoint': {'lat': 40.20686, 'lon': -8.41996}}], 'overallOfficials': [{'name': 'Andreia Filipa Lobo, Master', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Unidade Local de Saude de Coimbra'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Andreia Lobo', 'class': 'OTHER'}, 'collaborators': [{'name': 'University of Beira Interior', 'class': 'OTHER'}, {'name': 'Centro Hospitalar Universitário de Coimbra', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'MD, Primary-care Physician, Principal Investigator', 'investigatorFullName': 'Andreia Lobo', 'investigatorAffiliation': 'Unidade Local de Saúde de Coimbra, EPE'}}}}