Ignite Creation Date:
2026-03-26 @ 3:19 PM
Ignite Modification Date:
2026-03-30 @ 2:28 AM
Study NCT ID:
NCT07420634
Status:
RECRUITING
Last Update Posted:
2026-02-19
First Post:
2026-02-12
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Multilevel Ecological and COM-B Determinants of Medication Adherence in Adults With Diabetes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D003924', 'term': 'Diabetes Mellitus, Type 2'}, {'id': 'D055118', 'term': 'Medication Adherence'}], 'ancestors': [{'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': 'D010349', 'term': 'Patient Compliance'}, {'id': 'D010342', 'term': 'Patient Acceptance of Health Care'}, {'id': 'D000074822', 'term': 'Treatment Adherence and Compliance'}, {'id': 'D015438', 'term': 'Health Behavior'}, {'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 220}, 'targetDuration': '1 Day', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2025-12-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-02', 'completionDateStruct': {'date': '2026-08-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-02-12', 'studyFirstSubmitDate': '2026-02-12', 'studyFirstSubmitQcDate': '2026-02-12', 'lastUpdatePostDateStruct': {'date': '2026-02-19', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-02-19', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-06-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Medication Adherence', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Medication adherence assessed using the 12-item Adherence to Refills and Medications Scale (ARMS-12). Total scores range from 12 to 48, with higher scores indicating lower adherence.'}], 'secondaryOutcomes': [{'measure': 'Medication Literacy', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Medication literacy assessed using the Single Item Literacy Screener (SILS), evaluating the need for assistance in reading medical instructions.'}, {'measure': 'Beliefs About Medicines', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Reflective motivation assessed using the Beliefs about Medicines Questionnaire (BMQ-Specific), measuring necessity and concern beliefs regarding prescribed medicines.'}, {'measure': 'Family Involvement in Medication Management', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Level of family participation in medication management categorized by degree of responsibility sharing.'}, {'measure': 'Perceived Social Support', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Social opportunity assessed using the Medical Outcomes Study Social Support Survey (MOS-SSS)'}, {'measure': 'Quality of Medication-Related Communication', 'timeFrame': 'Single assessment at enrollment (Day 1)', 'description': 'Healthcare interaction quality measured using selected items from the Communication Assessment Tool (CAT).'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Health Ecology Model', 'COM-B Model', 'Medication Adherence', 'Diabetes Mellitus', 'Capability Opportunity Motivation', 'Behavioral Determinants', 'Medication Literacy'], 'conditions': ['Diabetes Mellitus', 'Diabetes Mellitus Type 2', 'Medication Adherence']}, 'descriptionModule': {'briefSummary': "This observational study aims to understand why some adults with diabetes find it difficult to take their medicines as prescribed. Medication adherence is essential for controlling blood sugar levels and preventing complications, yet many patients face challenges that go beyond personal motivation.\n\nThe study will examine multiple factors that may influence medication-taking behavior, including patients' understanding of their medicines, beliefs about treatment, family and social support, communication with healthcare providers, and practical issues such as medicine cost, availability, and distance to care. These factors will be analyzed using a structured behavioral framework to better understand how capability, opportunity, and motivation contribute to adherence.\n\nBy identifying the most important barriers and supports across different levels, this research aims to provide evidence that can guide patient-centered care strategies and improve medication adherence in diabetes management.", 'detailedDescription': 'This study is a cross-sectional, observational investigation designed to examine multilevel determinants of medication adherence among adults with diabetes using an integrated Health Ecology and Capability-Opportunity-Motivation-Behavior (COM-B) theoretical framework. The study is grounded in the premise that medication adherence is a complex health behavior shaped by interacting contextual and behavioral mechanisms rather than solely by individual patient choice.\n\nFrom an ecological perspective, medication-taking behavior occurs within nested environments that include intrapersonal characteristics, interpersonal relationships, healthcare interactions, and broader structural or access-related conditions. Individual-level influences include cognitive and perceptual factors that shape how patients understand and interpret medication-related information. Interpersonal influences include family involvement and social support structures that may facilitate or hinder routine medicine-taking. Healthcare interaction-level determinants reflect the quality of communication between patients and healthcare providers, including clarity of explanations and comprehensibility of prescriptions. Structural and access-related determinants encompass practical constraints such as medication availability, affordability, geographic access to care, and regimen complexity.\n\nWhile ecological models provide contextual organization of determinants, they do not fully explain how these determinants translate into observable behavior. Therefore, this study incorporates the COM-B framework to provide a mechanistic explanation. According to COM-B, behavior occurs when three essential components are present: psychological and physical capability, social and physical opportunity, and reflective and automatic motivation. Within the integrated framework used in this study, ecological determinants are mapped onto COM-B domains to examine how contextual influences operate through behavioral mechanisms to shape medication adherence.\n\nData will be collected during a single outpatient encounter using structured, validated self-report instruments and prescription audit methods. Medication adherence will be assessed using a standardized adherence scale. Measures representing ecological determinants will capture literacy-related capability, beliefs and perceptions influencing motivation, interpersonal and social support influencing social opportunity, communication quality influencing capability and opportunity, and structural or access-related constraints influencing physical opportunity. No intervention will be delivered, and no follow-up assessments will occur.\n\nThe analytical strategy is theory-guided. Descriptive statistics will summarize adherence levels and determinant distributions. Bivariate analyses will explore associations between adherence and individual predictors. Hierarchical multivariable regression models will be constructed sequentially according to COM-B domains to quantify their relative contribution to explained variance in adherence behavior. Mediation analyses will examine whether capability, opportunity, and motivation domains statistically account for the relationship between ecological determinants and adherence outcomes.\n\nThe study is designed to generate empirically grounded, theory-informed evidence clarifying which contextual layers and behavioral mechanisms are most strongly associated with medication adherence in diabetes care. By integrating ecological breadth with behavioral specificity, the findings are expected to support development of future pharmacist-led and health system-level strategies targeting modifiable determinants of adherence in resource-constrained settings.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '70 Years', 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Adult patients receiving routine outpatient care for diabetes at a tertiary-care teaching hospital in North India. Participants are recruited from specialty outpatient clinics managing chronic disease pharmacotherapy. The source population represents individuals undergoing long-term medical management within a structured hospital-based care setting.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults aged 18 years or older\n* Diagnosed with at least one chronic disease (e.g., diabetes mellitus, hypertension, cardiovascular disease, chronic respiratory disease, chronic kidney disease) for a minimum duration of six months\n* Prescribed long-term medication therapy\n* Able to understand and respond to the study questionnaire\n* Willing to provide written informed consent\n\nExclusion Criteria:\n\n* Patients with acute medical conditions requiring immediate care\n* Individuals with severe cognitive impairment or psychiatric illness that would preclude reliable participation\n* Patients who are terminally ill\n* Patients unwilling to participate or provide consent'}, 'identificationModule': {'nctId': 'NCT07420634', 'acronym': 'ADHECOM', 'briefTitle': 'Multilevel Ecological and COM-B Determinants of Medication Adherence in Adults With Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'University of Malaya'}, 'officialTitle': 'Multilevel Ecological Determinants of Medication Adherence Among Diabetes Patients: A Health Ecology-COM-B Framework Analysis', 'orgStudyIdInfo': {'id': 'IEC3618'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Adults With Diabetes Receiving Long-Term Pharmacotherapy', 'description': 'This group includes adult outpatients with diagnosed diabetes who are receiving long-term pharmacotherapy and attending routine follow-up care at a tertiary-care teaching hospital. Participants will complete structured questionnaires assessing medication adherence and multilevel determinants mapped to capability, opportunity, and motivation domains. Prescription records will be reviewed to assess regimen complexity. No intervention will be delivered, and no follow-up assessments will occur.', 'interventionNames': ['Other: Multilevel Ecological Determinants of Medication Adherence']}], 'interventions': [{'name': 'Multilevel Ecological Determinants of Medication Adherence', 'type': 'OTHER', 'otherNames': ['Health Ecology-COM-B Determinants Framework'], 'description': 'Assessment of contextual and behavioral determinants associated with medication adherence among adults with diabetes receiving routine clinical care. Determinants include individual-level factors (medication literacy, beliefs about medicines), interpersonal factors (family involvement, social support), healthcare interaction factors (communication quality, regimen complexity), and structural/access-related factors (availability, affordability, distance). These exposures are measured through validated questionnaires and prescription review during a single outpatient encounter. No intervention is assigned as part of the study.', 'armGroupLabels': ['Adults With Diabetes Receiving Long-Term Pharmacotherapy']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Ambāla', 'state': 'Haryana', 'status': 'RECRUITING', 'country': 'India', 'contacts': [{'name': 'Kanika Dr', 'role': 'CONTACT', 'email': 'rajat.rana@um.edu.my', 'phone': '01731 304 100'}, {'name': 'Ananya Dr', 'role': 'CONTACT'}, {'name': 'Rajat Rana', 'role': 'PRINCIPAL_INVESTIGATOR'}, {'name': 'Jyoti Jain', 'role': 'SUB_INVESTIGATOR'}, {'name': 'Kanika Dr', 'role': 'SUB_INVESTIGATOR'}, {'name': 'Ananya Dr', 'role': 'SUB_INVESTIGATOR'}], 'facility': 'MM Superspeciality Hospital, Maharishi Markandeshwar (Deemed to be University)', 'geoPoint': {'lat': 30.36099, 'lon': 76.79782}}], 'centralContacts': [{'name': 'Rajat Rana, PhD', 'role': 'CONTACT', 'email': 'rajatrana91@gmail.com', 'phone': '+91-9876543210'}, {'name': 'Jyoti Jain, Pharm.D', 'role': 'CONTACT', 'email': 'jyotijj182@gmail.com', 'phone': '+91-9876543210'}], 'overallOfficials': [{'name': 'Rajat Rana, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Universiti Malaya'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Individual participant data will not be shared due to institutional data governance policies and the protection of participant confidentiality. The study involves survey-based data collected in a single-center hospital setting, and de-identified datasets may still carry a risk of indirect identification. Aggregate results will be reported in publications and presentations. Any future data-sharing considerations would require additional data protection safeguards.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Malaya', 'class': 'OTHER'}, 'collaborators': [{'name': 'Maharishi Markendeswar University (Deemed to be University)', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Researcher', 'investigatorFullName': 'Dr. Rajat Rana', 'investigatorAffiliation': 'University of Malaya'}}}}