Ignite Creation Date:
2025-12-25 @ 1:20 AM
Ignite Modification Date:
2026-02-12 @ 2:45 AM
Study NCT ID:
NCT02249793
Status:
COMPLETED
Last Update Posted:
2020-01-18
First Post:
2014-03-25
Is NOT Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
Exploratory Study of Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics
Sponsor:
Organization:
Raw JSON
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'reportingStatus': 'POSTED'}, {'type': 'PRIMARY', 'title': 'Unique Contacts', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Awake', 'categories': [{'measurements': [{'value': '7.2', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '71'}]}]}, {'title': 'Sleeping', 'categories': [{'measurements': [{'value': '0.5', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '29'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity', 'unitOfMeasure': 'Unique contacts', 'dispersionType': 'Full Range', 'reportingStatus': 'POSTED'}, {'type': 'PRIMARY', 'title': 'Call Duration', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Awake', 'categories': [{'measurements': [{'value': '820.4', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '16590'}]}]}, {'title': 'Sleeping', 'categories': [{'measurements': [{'value': '22.0', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '3162'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'The duration of calls (made + received)', 'unitOfMeasure': 'Seconds', 'dispersionType': 'Full Range', 'reportingStatus': 'POSTED'}, {'type': 'PRIMARY', 'title': 'Text Message Length', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Awake', 'categories': [{'measurements': [{'value': '868.0', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '14840'}]}]}, {'title': 'Sleeping', 'categories': [{'measurements': [{'value': '47.0', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '3089'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'The total length of all sms messages (sent + received) in characters', 'unitOfMeasure': 'n (characters)', 'dispersionType': 'Full Range', 'reportingStatus': 'POSTED'}, {'type': 'PRIMARY', 'title': 'Text Messages', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Awake', 'categories': [{'measurements': [{'value': '16.0', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '166'}]}]}, {'title': 'Sleeping', 'categories': [{'measurements': [{'value': '0.8', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '75'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'The number of sms messages (sent + received)', 'unitOfMeasure': 'messages', 'dispersionType': 'Full Range', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Self-reported Sleep Times [Survey]', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Session 1, 48-hour', 'description': 'Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 \\& 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.'}], 'classes': [{'categories': [{'measurements': [{'value': '7.6', 'spread': '2.9', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.', 'unitOfMeasure': 'hour', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Time Asleep', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'categories': [{'measurements': [{'value': '7.931449224', 'spread': '0.7044404472', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'Hours asleep per each 24 hour period measured by actigraphy', 'unitOfMeasure': 'hours', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Physical Activity', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Awake', 'categories': [{'measurements': [{'value': '1904.0', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '55757.7'}]}]}, {'title': 'Sleeping', 'categories': [{'measurements': [{'value': '307.2', 'groupId': 'OG000', 'lowerLimit': '0', 'upperLimit': '29642.7'}]}]}], 'paramType': 'MEAN', 'timeFrame': '3-4 months', 'description': 'Difference in locomotion between wake and sleep times', 'unitOfMeasure': 'Counts/min', 'dispersionType': 'Full Range', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Changes Over Time in Nutrient Intake - Energy', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Session 1', 'categories': [{'measurements': [{'value': '1967', 'spread': '488', 'groupId': 'OG000'}]}]}, {'title': 'Session 2', 'categories': [{'measurements': [{'value': '1609', 'spread': '601', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': '48 hours', 'description': 'Nutrient intake will be measured using food photography', 'unitOfMeasure': 'Kcals', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'title': 'Morning', 'categories': [{'measurements': [{'value': '23.3', 'spread': '13.5', 'groupId': 'OG000'}]}]}, {'title': 'Evening', 'categories': [{'measurements': [{'value': '17.9', 'spread': '9.4', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': '48 hours', 'unitOfMeasure': 'relative expression', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'categories': [{'measurements': [{'value': '3', 'groupId': 'OG000'}]}]}], 'paramType': 'NUMBER', 'timeFrame': '48 hours', 'description': 'Analysis was performed for all participants as a group.', 'unitOfMeasure': 'genera', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Study Group', 'description': 'Healthy volunteers'}], 'classes': [{'categories': [{'measurements': [{'value': '2', 'groupId': 'OG000'}]}]}], 'paramType': 'NUMBER', 'timeFrame': '48 hours', 'description': 'Analysis was performed for all participants as a group.', 'unitOfMeasure': 'Proteins', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Changes Over Time in Kidney Function', 'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Session 1, 48-hour', 'description': 'Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 \\& 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.'}], 'classes': [{'categories': [{'measurements': [{'value': '12.925', 'spread': '115.468246', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': '48 hours', 'unitOfMeasure': 'mg/dL', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED', 'populationDescription': 'Kidney function was done to evaluate healthy volunteers during Session 1 and 2. Delta was calculated between Session 1 and 2 and averaged across subjects. Note that values for session1 was missing for two subjects, meaning that below reported mean and standard deviation reflect changes for four subjects.'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Session 1, 48-hour', 'description': 'Healthy volunteers; The observation time for the biosensor-derived data was a total of four months with two 48-hour sessions (Session 1 \\& 2) scheduled two weeks apart to extend the biosensor platform by ambulatory blood pressure monitoring (ABPM) and timestamped dietary intake (SmartIntake) as well as by collection of timed biospecimens for multiomics analysis at 12-hour intervals.'}], 'periods': [{'title': 'Session 1, 48-hours Healthy Volunteers', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '6'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '6'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '0'}]}]}, {'title': 'Session 2, 48-Hours Healthy Volunteers', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '6'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '6'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '0'}]}]}], 'recruitmentDetails': 'Study Started 9/24/14, Ended 3/11/15 located at the Clinical and Translational Research Center, CTRC located at the University of Pennsylvania Hospital'}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '6', 'groupId': 'BG000'}]}], 'groups': [{'id': 'BG000', 'title': 'Male Healthy Volunteers', 'description': 'Males'}], 'measures': [{'title': 'Age, Categorical', 'classes': [{'categories': [{'title': '<=18 years', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Between 18 and 65 years', 'measurements': [{'value': '6', 'groupId': 'BG000'}]}, {'title': '>=65 years', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Sex: Female, Male', 'classes': [{'categories': [{'title': 'Female', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Male', 'measurements': [{'value': '6', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Ethnicity (NIH/OMB)', 'classes': [{'categories': [{'title': 'Hispanic or Latino', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Not Hispanic or Latino', 'measurements': [{'value': '6', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race (NIH/OMB)', 'classes': [{'categories': [{'title': 'American Indian or Alaska Native', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Asian', 'measurements': [{'value': '1', 'groupId': 'BG000'}]}, {'title': 'Native Hawaiian or Other Pacific Islander', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Black or African American', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'White', 'measurements': [{'value': '3', 'groupId': 'BG000'}]}, {'title': 'More than one race', 'measurements': [{'value': '2', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2014-07-11', 'size': 1275417, 'label': 'Informed Consent Form', 'hasIcf': True, 'hasSap': False, 'filename': 'ICF_000.pdf', 'typeAbbrev': 'ICF', 'uploadDate': '2018-10-01T17:16', 'hasProtocol': False}, {'date': '2014-07-11', 'size': 2052435, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_001.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2018-10-01T17:22', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Whole blood, serum, plasma, urine, stool, and mucosal swabs from nose, mouth and rectum'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 6}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2014-09'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-01', 'completionDateStruct': {'date': '2017-12', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-01-05', 'studyFirstSubmitDate': '2014-03-25', 'resultsFirstSubmitDate': '2018-10-01', 'studyFirstSubmitQcDate': '2014-09-25', 'lastUpdatePostDateStruct': {'date': '2020-01-18', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2020-01-05', 'studyFirstPostDateStruct': {'date': '2014-09-26', 'type': 'ESTIMATED'}, 'resultsFirstPostDateStruct': {'date': '2020-01-18', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2017-12', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Calls and Text Messages', 'timeFrame': '3-4 months', 'description': 'Aggregate communication as behavioral features has been collected using the cell phone data streams.'}, {'measure': 'Changes Over Time in Ambulatory Blood Pressure - Systolic Blood Pressure', 'timeFrame': '48 hours', 'description': 'Ambulatory blood pressure monitoring'}, {'measure': 'Percentage of Total Metabolites', 'timeFrame': '48 hours', 'description': 'Percentage of metabolites displaying different abundances in biosamples collected during the morning hours versus evening hours. Analysis was performed for all participants as a group.'}, {'measure': 'Mobility Radius', 'timeFrame': '3-4 months', 'description': 'The approximate radius of an imaginary circle encompassing the various locations that a user has traveled across on a particular day (in miles)'}, {'measure': 'Calls', 'timeFrame': '3-4 months', 'description': 'Number of phone calls placed and received'}, {'measure': 'Changes Over Time in Ambulatory Blood Pressure - Diastolic Blood Pressure', 'timeFrame': '48 hours', 'description': 'Ambulatory blood pressure monitoring'}, {'measure': 'Unanswered Calls', 'timeFrame': '3-4 months', 'description': 'The number of calls unanswered.'}, {'measure': 'Unique Contacts', 'timeFrame': '3-4 months', 'description': 'The total number of unique individuals with whom a participant interacted through phone calls or sms messages indicating interaction diversity'}, {'measure': 'Call Duration', 'timeFrame': '3-4 months', 'description': 'The duration of calls (made + received)'}, {'measure': 'Text Message Length', 'timeFrame': '3-4 months', 'description': 'The total length of all sms messages (sent + received) in characters'}, {'measure': 'Text Messages', 'timeFrame': '3-4 months', 'description': 'The number of sms messages (sent + received)'}], 'secondaryOutcomes': [{'measure': 'Self-reported Sleep Times [Survey]', 'timeFrame': '3-4 months', 'description': 'Cell phone administered survey where participants indicated start and end of sleep times. From this the total hours of sleep per night was calculated.'}, {'measure': 'Time Asleep', 'timeFrame': '3-4 months', 'description': 'Hours asleep per each 24 hour period measured by actigraphy'}, {'measure': 'Physical Activity', 'timeFrame': '3-4 months', 'description': 'Difference in locomotion between wake and sleep times'}, {'measure': 'Changes Over Time in Nutrient Intake - Energy', 'timeFrame': '48 hours', 'description': 'Nutrient intake will be measured using food photography'}, {'measure': 'Changes Over Time in Ribonucleic Acids (RNA) - ARNTL (BMAL1) Normalized to GAPDH', 'timeFrame': '48 hours'}, {'measure': 'Genera Displaying Different Abundances Measured During Morning Versus Evening Hours in the Oral Microbiome', 'timeFrame': '48 hours', 'description': 'Analysis was performed for all participants as a group.'}, {'measure': 'Proteins Displaying Different Abundances Measured in the Morning Versus Evening Hours', 'timeFrame': '48 hours', 'description': 'Analysis was performed for all participants as a group.'}, {'measure': 'Changes Over Time in Kidney Function', 'timeFrame': '48 hours'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['circadian', 'oscillation', 'clock', 'human', 'social behavior', 'cell phone with internet access (so-called smartphone)', 'social sensing', 'behavioral feature', 'Ginger.io', 'blood pressure', 'metabolism', 'metabolomics', 'gut bacteria', 'microbiome'], 'conditions': ['Healthy']}, 'referencesModule': {'references': [{'pmid': '29215023', 'type': 'RESULT', 'citation': 'Skarke C, Lahens NF, Rhoades SD, Campbell A, Bittinger K, Bailey A, Hoffmann C, Olson RS, Chen L, Yang G, Price TS, Moore JH, Bushman FD, Greene CS, Grant GR, Weljie AM, FitzGerald GA. A Pilot Characterization of the Human Chronobiome. Sci Rep. 2017 Dec 7;7(1):17141. doi: 10.1038/s41598-017-17362-6.'}], 'seeAlsoLinks': [{'url': 'https://zenodo.org/communities/human-chronobiome/?page=1&size=20', 'label': 'Zenodo data repository'}]}, 'descriptionModule': {'briefSummary': "As citizens of the information age, humans leave digital traces of behavior in their communication and movement patterns through our cell phone. The Global Positioning System (GPS) technology tracks the way persons commute to school or work or when visiting family and friends. Circadian rhythmicity describes the concept that many of the bodily functions follow a roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best during daytime while humans rest and sleep during nighttime. The current study wishes to look for a relationship between patterns in participants' cell phone use (Android only at this point) and several of their bodily functions.", 'detailedDescription': 'Cell phones with internet access (so-called smartphones) represent a rich source for user activity data. Each time one places a call, sends a text message, or uses an app, a data trace is being produced which overall reflects the user\'s social activity and behavior. This data is called \'social sensing data\'. Researchers connected this type of data to the health status of the person operating the cell phone. An example is that an outbreak of seasonal flu may lead to fewer calls and text messages among cell phone users. Thus, the social sensing data may show for example how severe an outbreak is and how fast it is spreading.\n\n"Circadian rhythmicity" describes the concept that many of the bodily functions follow a roughly 24-hour rhythm. Usually, the ability to do concentrated and focused work is best during daytime while rest and sleep occurs during nighttime. A disturbance of this pattern, for example by regular nightshift work, may lead to an increased disease risk, such as for the cardiovascular system, the heart and blood vessels. Natural factors within a body produce our 24-hour rhythm. This rhythm is affected by outside cues such as sunlight. Jet lag is a short-term form of a disturbed 24-hour rhythm. When a person travels fast through several time zones, by plane for example from the East to the West Coast of the US, s/he arrives with a time difference of 3 hours. Upon arrival, the body runs still at East Coast time, but is exposed to the environmental cues following the West Coast time, which may make the person feel groggy and disoriented at first. Within a couple of days the body time usually adjusts and the complaints discontinue.\n\nThe current study wishes to look for a relationship between patterns in the participant\'s cell phone use (Android only at this point) and several of the bodily functions. As bodily functions the investigators will measure blood pressure and breakdown products (metabolites) in urine, blood and saliva samples. The investigators will collect stool samples and use swabs to collect the microbes inhabiting the mouth as well as the rectum. The investigators will also measure messenger ribonucleic acid (mRNA), messenger products of the participant\'s heritable information, in the blood. A cell phone application called "Ginger.io" will collect the participants\' cell phone usage information. This application will also ask the participant several questions during the installation, during participation as well as at the end. Furthermore, the investigators will ask the participant about the dietary intake and habits.\n\nThe aim is to learn how the 24-hour rhythm is connected to the social activity and behavior as well as blood pressure and metabolites as markers for the health status.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '35 Years', 'minimumAge': '25 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Healthy volunteers', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Volunteers must be in good health as based on medical history, physical examination, vital signs, and laboratory tests as deemed by PI;\n* Volunteers are capable of giving informed consent;\n* 25-35 years of age;\n* Own a cell phone with internet access (smartphone with Android operating system only at this point) which installs the social sensing application ginger.io;\n* Non-smoking;\n* Male subjects only if feasible during recruitment; and\n* In case female volunteers are invited to enroll: non-pregnant, female subjects must consent to a urine pregnancy test.\n\nExclusion Criteria:\n\n* Recent travel across time zones (within the past month);\n* Planned travel across time zones during the planned study activities;\n* Volunteers with irregular work hours, e.g. night shifts.\n* Use of illicit drugs;\n* Subjects, who have received an experimental drug, used an experimental medical device within 30 days prior to screening, or who gave a blood donation of ≥ one pint within 8 weeks prior to screening.\n* Subjects with any abnormal laboratory value or physical finding that according to the investigator may interfere with interpretation of the study results, be indicative of an underlying disease state, or compromise the safety of a potential subject.'}, 'identificationModule': {'nctId': 'NCT02249793', 'briefTitle': 'Exploratory Study of Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics', 'organization': {'class': 'OTHER', 'fullName': 'University of Pennsylvania'}, 'officialTitle': 'Exploratory Study in Healthy Volunteers to Define Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics', 'orgStudyIdInfo': {'id': '817759'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Study group', 'description': 'Healthy volunteers'}]}, 'contactsLocationsModule': {'locations': [{'zip': '19104', 'city': 'Philadelphia', 'state': 'Pennsylvania', 'country': 'United States', 'facility': 'Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania', 'geoPoint': {'lat': 39.95238, 'lon': -75.16362}}], 'overallOfficials': [{'name': 'Carsten Skarke, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Pennsylvania'}, {'name': 'Garret A FitzGerald, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Pennsylvania'}, {'name': 'Aalim Weljie, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Pennsylvania'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Pennsylvania', 'class': 'OTHER'}, 'collaborators': [{'name': 'Ginger.io', 'class': 'INDUSTRY'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Research Assistant Professor', 'investigatorFullName': 'Carsten Skarke, MD', 'investigatorAffiliation': 'University of Pennsylvania'}}}}