You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Socioeconomic Predictors of Adherence Behavior Among HIV-Positive Patients Receiving Antiretroviral Therapy in Selangor, Malaysia Medication adherence remains a critical link between the prescribed ART regimen and treatment outcome. Several factors may influence adherence behavior. This cross-sectional study aimed to highlight socioeconomic predictors of adherence behavior among a cohort of 242 adult Malaysian patients receiving antiretroviral therapy in Hospital Sungai Buloh, Malaysia, where they were enrolled in a parent study (single-blinded randomized controlled trial) between January and December 2014. Statistical analysis of secondary data on adherence behavior and sociodemographic characteristics of the patients revealed mean age of 33.4 years and ranged from 18 to 64 years; 88.8% were males. A total of 224 (93%) patients who completed 6 months' adherence assessment were included in the model. Of these, 135 (60.3%) achieved optimal adherence. Multivariate binary logistic regression analysis revealed that patient's income and ethnicity were significant predictors of adherence behavior. This may be valuable for targeted programmatic interventions to further enhance successful treatment outcomes among the target population.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": [], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": ["successful treatment"], "Eukaryote": [], "Finding": ["Adherence Behavior", "achieved", "Medication adherence", "HIV-Positive", "adherence behavior", "mean age"], "Food": [], "HealthCareActivity": ["regimen", "antiretroviral therapy", "Antiretroviral Therapy", "programmatic interventions", "ART"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Multivariate binary logistic regression analysis"], "MedicalDevice": [], "Organization": ["Hospital Sungai Buloh"], "PopulationGroup": ["target population", "Malaysian", "cohort"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["cross-sectional study", "randomized controlled trial", "single-blinded"], "SpatialConcept": ["Malaysia", "Selangor"], "Virus": []}