Cocaine-Related DisordersAutoSenseNCT02915341
Towards Detecting Cocaine Use Using Smartwatches in the NIDA Clinical Trials Network
An observational study of Cocaine-Related Disorders, run by Dartmouth-Hitchcock Medical Center at 1 site in United States.
Trial summary
The overall objective of this study is to extend previous work in the development of methods to automatically detect the timing of cocaine use from cardiac interbeat interval and physical activity data derived from wearable, unobtrusive mobile sensor technologies. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Cocaine-Related Disorders
- How many people
- 24 participants
- Where
- 1 siteUnited States
- Study dates
- 1 May 2016to 24 Apr 2018
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The proposed study will be conducted with 25 cocaine users from the parent clinical trial who agree to wear the AutoSense smartwatches and chestband for two weeks. Participants in the parent clinical trial are unemployed, cocaine-using adults who inject drugs and are enrolled in opioid agonist treatment. There are no study groups or randomization.
Who may be able to join
- Be enrolled in the parent clinical trial for at least one week.
- Be active in the Induction Period (days 8-35) of the parent clinical trial at the time of study intake.
- Provide a cocaine-positive urine sample in the week prior (based on thrice-weekly urine samples collected as a part of the parent trial).
- Be available for the duration of the study (16 days total) and able to attend weekday research check-in sessions at the recruitment site.
Who cannot join
- There are no exclusion criteria specific to this study.
Trial locations and contacts
1 site in 1 country.
United States1 site
Center for Learning and Health, Johns Hopkins University
Baltimore, Maryland, 21205
About this study
The overall objective of this study is to extend previous work in the development of methods to automatically detect the timing of cocaine use from cardiac interbeat interval and physical activity data derived from wearable, unobtrusive mobile sensor technologies. The specific objectives of this protocol are to characterize under which conditions high quality continuous interbeat interval data and physical activity data can be obtained from a specially developed smartwatch device in the natural field setting among a population of cocaine users. In addition to identifying common failure scenarios and understanding wearability/usage patterns when collecting interbeat interval from smartwatches, this study will extend previous work in the detection of cocaine use via interbeat interval and physical activity data that were previously obtained from wearable chestband sensors. Information from this study will contribute toward the adaptation of the investigators' existing computational model for detecting cocaine use via the chest sensors, so it can be applied to the interbeat and physical activity data obtained from less obtrusive smartwatches.
Read the detailed description
This study will evaluate a smartwatch device for the continuous field assessment of physiological measures, including cardiac interbeat interval and physical activity. These measures have been previously employed using wearable chest sensors to develop a model for the automatic in-the-field detection of the timing of cocaine use; computational models using physiological data of this type have been used in prior research to detect cocaine use and moment-by-moment stress using a mobile sensor suite called AutoSense. AutoSense is a chest-worn device used to collect measures of heart rate via a two-lead electrocardiograph (ECG) and physical activity via 3-axis accelerometers that can be transmitted wirelessly to an Android-based smartphone for initial processing and data storage. The adapted AutoSense protocol will incorporate smartwatches specially designed to continuously detect heart beat timings using optical photoplethysmogram (PPG) sensors rather than ECG leads.
Prior to the start of this protocol, investigators will optimize collection of cardiac interbeat interval data on the smartwatches via a preliminary ambulatory study (with Co-Investigator Ertin at the Ohio State University). The development of the smartwatch device and the initial smartwatch computational model is currently being supported separately (outside of this human subjects protocol) by the National Drug Abuse Treatment Clinical Trials Network (CTN). Investigators and research assistants at the Ohio State University will wear prototypes of the smartwatch devices and the AutoSense chest sensor during waking hours for five days to capture cardiac interbeat interval data as well as identify initial fit and usability problems with the prototype smartwatch devices and inform its subsequent refinements. This preliminary ambulatory study is a separate protocol being conducted at Ohio State University with oversight by that institution's Institutional Review Board (IRB), and thus is not considered part of the 0073-Ot human subjects protocol.
Once the preliminary study has concluded, investigators will conduct a field test during which the smartwatch and AutoSense chest sensors will be worn by 25 cocaine users for two weeks (5 participants will participate in pilot testing for two weeks each, after which the smartwatch device may undergo further refinements for improved wearability and/or data collection among the remaining participants). Outcomes of this study are to characterize the feasibility of the smartwatch device to continuously detect interbeat interval and physical activity data, and to characterize situations where data yield of sufficient quality for the application of more advanced computational models (e.g., cocaine detection) can take place in participants' natural field settings. Secondarily, data from the trial will be used to compare data yields from the two sensor suites being worn (the smartwatch devices and the AutoSense chest sensors). The data may also be useful for updating the computational models (e.g., cocaine detection) previously developed with the AutoSense chest sensors for data collected by the smartwatches. The results from this study may be used to inform future research of this type to investigate technological improvements and the situations during which using mobile sensors can unobtrusively characterize precipitants and use patterns (e.g., contextual) surrounding drug use events.
It is important to note that this study is not designed to assess the acceptability of the smartwatch among cocaine users, nor is it a study to evaluate the utility of using a smartwatch for measuring cocaine use outcomes as part of a clinical trial. Rather, investigators are intentionally recruiting participants who frequently use cocaine and compensating them to participate in this study designed to characterize the feasibility of using a smartwatch to collect reliable, continuous interbeat interval and physical activity data in the natural field setting, and to characterize under what conditions high quality data can be obtained from smartwatches. If results are promising, future research designs with larger sample sizes can explore some of these more clinically-relevant scientific questions.
- Conditions
- Cocaine-Related Disorders
- Medical subject headings
- Cocaine-Related Disorders
What is being measured
The primary outcome is the main question the study is designed to answer.
Ambulatory physiological and activity data
Data yield of ambulatory physiological and activity data will be used to characterize the feasibility of using smartwatches to collect reliable interbeat interval and physical activity data in the natural field setting, sensor usage patterns (e.g., hours per day of device wear, periods of device removal), and common failure scenarios (e.g., poor sensor data quality, missing data due to removal of the device, or other factors which may affect data yield). Ambulatory physiological and activity data will be collected using passive mobile sensor data collection platforms (AutoSense chest sensors and smartwatches). This data is collected via AutoSense sensors and will utilize participants' heart beats, which will be continually streamed into the database at the Mobile Sensor Data-to-Knowledge Center of Excellence (University of Memphis). This is one assessment with one unit of measurement (heart rate) that will inform the multiple aspects of this outcome.
Measured: 14 days
Device wearability
Device wearability (e.g., acceptability and burden) will be characterized via user questionnaires.
Measured: 14 days
Cocaine use
Real-time self-report of cocaine use via Ecological Momentary Assessment (EMA) questionnaire prompts via the smartphone device, retrospective recall of drug use via Timeline Followback (TLFB), and urine drug assay for cocaine and other drugs of abuse will be used to adapt the computational model, so that it can be applied to the interbeat and physical activity data obtained from smartwatches. These measurements of cocaine use will be aggregated to arrive at one reported value (cocaine use episodes) to inform the model.
Measured: 14 days
Secondary outcomes (2)
Device comparison
Data yield will be compared between the smartwatch wrist sensor platform and the AutoSense chest sensors to characterize the conditions under which reliable interbeat interval and physical activity data can be collected with the respective devices in the natural field setting. Comparisons between overall data yield, sensor usage patterns (e.g., hours per day of device wear, periods of device removal), and common failure scenarios (e.g., poor sensor data quality, missing data due to removal of the device, or other factors which may affect data yield) will be conducted between the AutoSense chest sensors and the smartwatch wrist sensor platform to determine if differences exist between the two sensor suites. To achieve this outcome data will be aggregated into one reported value (discrepancies between the devices).
Measured: Through study completion, an average of 18 months
Cocaine detection specificity
The degree of specificity of the cocaine detection model will be characterized relative to other stimulant use via precision and recall. To perform this comparison, rates of true positive and false positive cocaine detection events (obtained via physiological sensor data) will be compared when other stimulant drugs of abuse (e.g. amphetamines, methamphetamines) are determined to be present via urine assay for other drugs, real-time self-report of other amphetamine use via EMA, and retrospective recall of drug use via study assessments. Measures will be aggregated to arrive at one reported value, informing investigators of whether other stimulant use affects the model in the same way as cocaine.
Measured: Through study completion, an average of 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Sep 2016 (estimated)
- Study start1 May 2016
- Primary completion24 Apr 2018
- Study completion24 Apr 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Cocaine-Related DisordersStudies of the same condition, open and under way.
- More trials run by Dartmouth-Hitchcock Medical CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 24 participants (actual)
Sponsor and investigators
- Lead sponsor
- Dartmouth-Hitchcock Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- National Drug Abuse Treatment Clinical Trials Network, University of Memphis, Johns Hopkins University, National Institute on Drug Abuse (NIDA), Dartmouth College
- Responsible party
- Principal investigator, Lisa A. Marsch, Dartmouth-Hitchcock Medical Center
- Investigators
- Lisa A. Marsch, PhD, Principal investigator, Dartmouth CollegeSantosh Kumar, PhD, Principal investigator, University of Memphis
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02915341
- Sponsor's protocol ID
- CTN-0073-Ot
- Acronym
- AutoSense
- Status last verified
- Jun 2018
- First submitted
- 20 Sep 2016
- Last updated
- 18 Jul 2018
- Results posted
- No
- Data monitoring committee
- Yes
- Individual data sharing
- Yes: De-identified data will be reviewed by IRB and shared with DSMB every 6 months, as per the monitoring protocol set forth by the CTN and this study.
Publications
Hossain SM, Ali AA, Rahman M, Ertin E, Epstein D, Kennedy A, Preston K, Umbricht A, Chen Y, Kumar S. Identifying Drug (Cocaine) Intake Events from Acute Physiological Response in the Presence of Free-living Physical Activity. IPSN. 2014;2014:71-82.
PubMed 25531010Ertin, E., Stohs, N., Kumar, S., Raij, A.B., al'Absi, M., Kwon, T., Mitra, S., Shah, S., & Jeong, J.W. (2011). AutoSense: Unobtrusively wearable sensor suite for inferencing of onset, causality, and consequences of stress in the field: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (SenSys) (pp. 274-287). New York, NY: Association for Computing Machinery.
Ertin E, Sugavanam N, Holtyn AF, Preston KL, Bertz JW, Marsch LA, McLeman B, Shmueli-Blumberg D, Collins J, King JS, McCormack J, Ghitza UE. An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches. Front Psychiatry. 2021 Jun 24;12:674691. doi: 10.3389/fpsyt.2021.674691. eCollection 2021.
PubMed 34248712
Study at a glance
From the registry record, last updated by the sponsor on 18 Jul 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Towards Detecting Cocaine Use Using Smartwatches in the NIDA Clinical Trials Network
- ClinicalTrials.gov ID
- NCT02915341
- Acronym / sponsor ID
- AutoSense / CTN-0073-Ot
- Conditions
- Cocaine-Related Disorders
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 24 participants (actual)
- Lead sponsor
- Dartmouth-Hitchcock Medical CenterUniversity, hospital or other
- Collaborators
- National Drug Abuse Treatment Clinical Trials Network, University of Memphis, Johns Hopkins University, National Institute on Drug Abuse (NIDA), Dartmouth College
- Study start
- 1 May 2016 (actual)
- Primary completion
- 24 Apr 2018 (actual)
- Study completion
- 24 Apr 2018 (actual)
- First posted
- 27 Sep 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The overall objective of this study is to extend previous work in the development of methods to automatically detect the timing of cocaine use from cardiac interbeat interval and physical activity data derived from wearable, unobtrusive mobile sensor technologies. The specific objectives of this protocol are to characterize under which conditions high quality continuous interbeat interval data and physical activity data can be obtained from a specially developed smartwatch device in the natural field setting among a population of cocaine users. In addition to identifying common failure scenarios and understanding wearability/usage patterns when collecting interbeat interval from smartwatches, this study will extend previous work in the detection of cocaine use via interbeat interval and physical activity data that were previously obtained from wearable chestband sensors. Information from this study will contribute toward the adaptation of the investigators' existing computational model for detecting cocaine use via the chest sensors, so it can be applied to the interbeat and physical activity data obtained from less obtrusive smartwatches.
Detailed description
This study will evaluate a smartwatch device for the continuous field assessment of physiological measures, including cardiac interbeat interval and physical activity. These measures have been previously employed using wearable chest sensors to develop a model for the automatic in-the-field detection of the timing of cocaine use; computational models using physiological data of this type have been used in prior research to detect cocaine use and moment-by-moment stress using a mobile sensor suite called AutoSense. AutoSense is a chest-worn device used to collect measures of heart rate via a two-lead electrocardiograph (ECG) and physical activity via 3-axis accelerometers that can be transmitted wirelessly to an Android-based smartphone for initial processing and data storage. The adapted AutoSense protocol will incorporate smartwatches specially designed to continuously detect heart beat timings using optical photoplethysmogram (PPG) sensors rather than ECG leads.
Prior to the start of this protocol, investigators will optimize collection of cardiac interbeat interval data on the smartwatches via a preliminary ambulatory study (with Co-Investigator Ertin at the Ohio State University). The development of the smartwatch device and the initial smartwatch computational model is currently being supported separately (outside of this human subjects protocol) by the National Drug Abuse Treatment Clinical Trials Network (CTN). Investigators and research assistants at the Ohio State University will wear prototypes of the smartwatch devices and the AutoSense chest sensor during waking hours for five days to capture cardiac interbeat interval data as well as identify initial fit and usability problems with the prototype smartwatch devices and inform its subsequent refinements. This preliminary ambulatory study is a separate protocol being conducted at Ohio State University with oversight by that institution's Institutional Review Board (IRB), and thus is not considered part of the 0073-Ot human subjects protocol.
Once the preliminary study has concluded, investigators will conduct a field test during which the smartwatch and AutoSense chest sensors will be worn by 25 cocaine users for two weeks (5 participants will participate in pilot testing for two weeks each, after which the smartwatch device may undergo further refinements for improved wearability and/or data collection among the remaining participants). Outcomes of this study are to characterize the feasibility of the smartwatch device to continuously detect interbeat interval and physical activity data, and to characterize situations where data yield of sufficient quality for the application of more advanced computational models (e.g., cocaine detection) can take place in participants' natural field settings. Secondarily, data from the trial will be used to compare data yields from the two sensor suites being worn (the smartwatch devices and the AutoSense chest sensors). The data may also be useful for updating the computational models (e.g., cocaine detection) previously developed with the AutoSense chest sensors for data collected by the smartwatches. The results from this study may be used to inform future research of this type to investigate technological improvements and the situations during which using mobile sensors can unobtrusively characterize precipitants and use patterns (e.g., contextual) surrounding drug use events.
It is important to note that this study is not designed to assess the acceptability of the smartwatch among cocaine users, nor is it a study to evaluate the utility of using a smartwatch for measuring cocaine use outcomes as part of a clinical trial. Rather, investigators are intentionally recruiting participants who frequently use cocaine and compensating them to participate in this study designed to characterize the feasibility of using a smartwatch to collect reliable, continuous interbeat interval and physical activity data in the natural field setting, and to characterize under what conditions high quality data can be obtained from smartwatches. If results are promising, future research designs with larger sample sizes can explore some of these more clinically-relevant scientific questions.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The proposed study will be conducted with 25 cocaine users from the parent clinical trial who agree to wear the AutoSense smartwatches and chestband for two weeks. Participants in the parent clinical trial are unemployed, cocaine-using adults who inject drugs and are enrolled in opioid agonist treatment. There are no study groups or randomization.
Key inclusion criteria (4 listed)
- Be enrolled in the parent clinical trial for at least one week.
- Be active in the Induction Period (days 8-35) of the parent clinical trial at the time of study intake.
- Provide a cocaine-positive urine sample in the week prior (based on thrice-weekly urine samples collected as a part of the parent trial).
- Be available for the duration of the study (16 days total) and able to attend weekday research check-in sessions at the recruitment site.
Key exclusion criteria (1 listed)
- There are no exclusion criteria specific to this study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Ambulatory physiological and activity data
Time frame: 14 days
Data yield of ambulatory physiological and activity data will be used to characterize the feasibility of using smartwatches to collect reliable interbeat interval and physical activity data in the natural field setting, sensor usage patterns (e.g., hours per day of device wear, periods of device removal), and common failure scenarios (e.g., poor sensor data quality, missing data due to removal of the device, or other factors which may affect data yield). Ambulatory physiological and activity data will be collected using passive mobile sensor data collection platforms (AutoSense chest sensors and smartwatches). This data is collected via AutoSense sensors and will utilize participants' heart beats, which will be continually streamed into the database at the Mobile Sensor Data-to-Knowledge Center of Excellence (University of Memphis). This is one assessment with one unit of measurement (heart rate) that will inform the multiple aspects of this outcome.
Device wearability
Time frame: 14 days
Device wearability (e.g., acceptability and burden) will be characterized via user questionnaires.
Cocaine use
Time frame: 14 days
Real-time self-report of cocaine use via Ecological Momentary Assessment (EMA) questionnaire prompts via the smartphone device, retrospective recall of drug use via Timeline Followback (TLFB), and urine drug assay for cocaine and other drugs of abuse will be used to adapt the computational model, so that it can be applied to the interbeat and physical activity data obtained from smartwatches. These measurements of cocaine use will be aggregated to arrive at one reported value (cocaine use episodes) to inform the model.
2 secondary outcomes
Device comparison
Time frame: Through study completion, an average of 18 months
Cocaine detection specificity
Time frame: Through study completion, an average of 18 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Jul 2018.
- Background: PubMed 25531010Hossain SM, Ali AA, Rahman M, Ertin E, Epstein D, Kennedy A, Preston K, Umbricht A, Chen Y, Kumar S. Identifying Drug (Cocaine) Intake Events from Acute Physiological Response in the Presence of Free-living Physical Activity. IPSN. 2014;2014:71-82.
- BackgroundErtin, E., Stohs, N., Kumar, S., Raij, A.B., al'Absi, M., Kwon, T., Mitra, S., Shah, S., & Jeong, J.W. (2011). AutoSense: Unobtrusively wearable sensor suite for inferencing of onset, causality, and consequences of stress in the field: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (SenSys) (pp. 274-287). New York, NY: Association for Computing Machinery.
- Derived from this study: PubMed 34248712Ertin E, Sugavanam N, Holtyn AF, Preston KL, Bertz JW, Marsch LA, McLeman B, Shmueli-Blumberg D, Collins J, King JS, McCormack J, Ghitza UE. An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches. Front Psychiatry. 2021 Jun 24;12:674691. doi: 10.3389/fpsyt.2021.674691. eCollection 2021.
- Individual participant dataSharing planned: Yes. De-identified data will be reviewed by IRB and shared with DSMB every 6 months, as per the monitoring protocol set forth by the CTN and this study.
Related trials for Cocaine-Related Disorders
Recruiting
rTMS and Cognitive-behavioral Therapy for Cocaine Use Disorder
Cocaine Use, Cocaine Dependence
Not yet recruiting
QAIAx - SGI/SI Smart Health Cities: Microcity Enclave Program (Quantum SI/AGI Agency a/k/a AI City Hall Project - UPSTO App Nos. 64/074,526, 64/063,557, 64/105,164, 63/903,181, 63/729,428, 64/125,360; USPTO EO 9424 Assignment ID: 2101042 / ARN: REEL/FRAME: 76481/0026 - OUSD-R&E, Department of War)
Asperger's Disorder, Asperger Disorder
Recruiting
Transcranial Direct Current Stimulation (tDCS) for Treatment of Substance Use Disorder
Cocaine Use Disorder, Cocaine Dependence
Active, not recruitingEarly Phase 1
Targeting Drug Memories With Methylphenidate
Substance Use Disorder, Cocaine Use Disorder
RecruitingPhase 1
Safety Study of a Disrupted Adenovirus (Ad) Serotype Cocaine Vaccine for Cocaine-dependent Individuals
Cocaine Dependence
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lisa A. Marsch, PhD principal investigator
Dartmouth College
Santosh Kumar, PhD principal investigator
University of Memphis
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cocaine-Related Disorders, run by Dartmouth-Hitchcock Medical Center at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 18 Jul 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Ambulatory physiological and activity data (time frame: 14 days). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02915341, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Jul 2018; AzTrials last refreshed its copy on 7 Nov 2026.