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Kunchay S, Linden-Carmichael AN, Abdullah S. Using a Smartwatch App to Understand Young Adult Substance Use: Mixed Methods Feasibility Study. JMIR Hum Factors 2024; 11:e50795. [PMID: 38901024 PMCID: PMC11224702 DOI: 10.2196/50795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 03/14/2024] [Accepted: 04/08/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND Young adults in the United States exhibit some of the highest rates of substance use compared to other age groups. Heavy and frequent substance use can be associated with a host of acute and chronic health and mental health concerns. Recent advances in ubiquitous technologies have prompted interest and innovation in using technology-based data collection instruments to understand substance use and associated harms. Existing methods for collecting granular, real-world data primarily rely on the use of smartphones to study and understand substance use in young adults. Wearable devices, such as smartwatches, show significant potential as platforms for data collection in this domain but remain underused. OBJECTIVE This study aims to describe the design and user evaluation of a smartwatch-based data collection app, which uses ecological momentary assessments to examine young adult substance use in daily life. METHODS This study used a 2-phase iterative design and acceptability evaluation process with young adults (aged 18-25 y) reporting recent alcohol or cannabis use. In phase 1, participants (8/15, 53%) used the data collection app for 14 days on their Apple Watches to report their substance use patterns, social contexts of substance use, and psychosocial risk factors (eg, affect). After this 14-day deployment, the participants completed a user experience survey and a semistructured interview to record their perspectives and experiences of using the app. Formative feedback from this phase informed feature modification and refinement of the app. In phase 2, an additional cohort (7/15, 47%) used the modified app for 14 days and provided feedback through surveys and interviews conducted after the app use period. RESULTS Analyses of overall app use patterns indicated high, consistent use of the app, with participants using the app for an average of 11.73 (SD 2.60) days out of 14 days of data collection. Participants reported 67 instances of substance use throughout the study, and our analysis indicates that participants were able to respond to ecological momentary assessment prompts in diverse temporal and situational contexts. Our findings from the user experience survey indicate that participants found the app usable and functional. Comparisons of app use metrics and user evaluation scores indicate that the iterative app design had a measurable and positive impact on users' experience. Qualitative data from the participant interviews highlighted the value of recording substance use patterns, low disruption to daily life, minimal overall burden, preference of platforms (smartphones vs smartwatches), and perspectives relating to privacy and app use in social contexts. CONCLUSIONS This study demonstrated the acceptability of using a smartwatch-based app to collect intensive, longitudinal substance use data among young adults. The findings document the utility of smartwatches as a novel platform to understand sensitive and often-stigmatized behaviors such as substance use with minimal burden.
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Affiliation(s)
- Sahiti Kunchay
- College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA, United States
| | - Ashley N Linden-Carmichael
- Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, United States
| | - Saeed Abdullah
- College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA, United States
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Coughlin LN, Salino S, Jennings C, Lacek M, Townsend W, Koffarnus MN, Bonar EE. A systematic review of remotely delivered contingency management treatment for substance use. JOURNAL OF SUBSTANCE USE AND ADDICTION TREATMENT 2023; 147:208977. [PMID: 36804352 PMCID: PMC10936237 DOI: 10.1016/j.josat.2023.208977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 11/23/2022] [Accepted: 02/05/2023] [Indexed: 02/15/2023]
Abstract
BACKGROUND Substance use and related consequences (e.g., impaired driving, injuries, disease transmission) continue to be major public health concerns. Contingency management (CM) is a highly effective treatment for substance use disorders. Yet CM remains vastly underutilized, in large part due to implementation barriers to in-person delivery. If feasible and effective, remote delivery of CM may reduce barriers at both the clinic- and patient-level, thus increasing reach and access to effective care. Here, we summarize data from a systematic review of studies reporting remote delivery of CM for substance use treatment. METHODS We conducted a systematic review, reported according to PRISMA guidelines. The study team identified a total of 4358 articles after deduplication. Following title and abstract screening, full-text screening, and reference tracking, 39 studies met the eligibility criteria. We evaluated the methodological quality of the included studies using the Effective Public Health Practice Project Quality tool. RESULTS Of 39 articles included in the review, most (n = 26) targeted cigarette smoking, with others focusing on alcohol (n = 9) or other substance use or targeting multiple substances (n = 4). Most remotely delivered CM studies focused on abstinence (n = 29), with others targeting substance use reduction (n = 2), intervention engagement (n = 5), and both abstinence and intervention engagement (n = 3). CM was associated with better outcomes (either abstinence, use reduction, or engagement), with increasingly more remotely delivered CM studies published in more recent years. Studies ranged from moderate to strong quality, with the majority (57.5 %) of studies being strong quality. CONCLUSIONS Consistent with in-person CM, remotely delivered CM focusing on abstinence or use reduction from substances or engagement in substance use treatment services improves outcomes at the end of treatment compared to control conditions. Moreover, remotely delivered CM is feasible across a variety of digital delivery platforms (e.g., web, mobile, and wearable), with acceptability and reduced clinic and patient burden as technological advancements streamline monitoring and reinforcer delivery.
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Affiliation(s)
- Lara N Coughlin
- Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Injury Prevention Center, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Sarah Salino
- Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Claudia Jennings
- Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Madelyn Lacek
- Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Whitney Townsend
- Taubman Health Sciences Library, University of Michigan, Ann Arbor, MI 48109, USA
| | - Mikhail N Koffarnus
- Department of Family and Community Medicine, University of Kentucky, Lexington, KY 40506, USA
| | - Erin E Bonar
- Addiction Center, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Injury Prevention Center, University of Michigan, Ann Arbor, MI 48109, USA
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Hojjatinia S, Daly ER, Hnat T, Hossain SM, Kumar S, Lagoa CM, Nahum-Shani I, Samiei SA, Spring B, Conroy DE. Dynamic models of stress-smoking responses based on high-frequency sensor data. NPJ Digit Med 2021; 4:162. [PMID: 34815538 PMCID: PMC8611062 DOI: 10.1038/s41746-021-00532-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 10/26/2021] [Indexed: 11/09/2022] Open
Abstract
Self-reports indicate that stress increases the risk for smoking; however, intensive data from sensors can provide a more nuanced understanding of stress in the moments leading up to and following smoking events. Identifying personalized dynamical models of stress-smoking responses can improve characterizations of smoking responses following stress, but techniques used to identify these models require intensive longitudinal data. This study leveraged advances in wearable sensing technology and digital markers of stress and smoking to identify person-specific models of stress and smoking system dynamics by considering stress immediately before, during, and after smoking events. Adult smokers (n = 45) wore the AutoSense chestband (respiration-inductive plethysmograph, electrocardiogram, accelerometer) with MotionSense (accelerometers, gyroscopes) on each wrist for three days prior to a quit attempt. The odds of minute-level smoking events were regressed on minute-level stress probabilities to identify person-specific dynamic models of smoking responses to stress. Simulated pulse responses to a continuous stress episode revealed a consistent pattern of increased odds of smoking either shortly after the beginning of the simulated stress episode or with a delay, for all participants. This pattern is followed by a dramatic reduction in the probability of smoking thereafter, for about half of the participants (49%). Sensor-detected stress probabilities indicate a vulnerability for smoking that may be used as a tailoring variable for just-in-time interventions to support quit attempts.
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Affiliation(s)
- Sahar Hojjatinia
- School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Elyse R Daly
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Timothy Hnat
- Department of Computer Science, University of Memphis, Memphis, TN, 38152, USA
| | | | - Santosh Kumar
- Department of Computer Science, University of Memphis, Memphis, TN, 38152, USA
| | - Constantino M Lagoa
- School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Inbal Nahum-Shani
- Institute for Social Research, University of Michigan, Ann Arbor, MI, 48106, USA
| | - Shahin Alan Samiei
- Department of Computer Science, University of Memphis, Memphis, TN, 38152, USA
| | - Bonnie Spring
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - David E Conroy
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Department of Kinesiology, The Pennsylvania State University, University Park, PA, 16802, USA.
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4
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Nahum-Shani I, Potter LN, Lam CY, Yap J, Moreno A, Stoffel R, Wu Z, Wan N, Dempsey W, Kumar S, Ertin E, Murphy SA, Rehg JM, Wetter DW. The mobile assistance for regulating smoking (MARS) micro-randomized trial design protocol. Contemp Clin Trials 2021; 110:106513. [PMID: 34314855 PMCID: PMC8824313 DOI: 10.1016/j.cct.2021.106513] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/13/2021] [Accepted: 07/16/2021] [Indexed: 11/30/2022]
Abstract
Smoking is the leading preventable cause of death and disability in the U.S. Empirical evidence suggests that engaging in evidence-based self-regulatory strategies (e.g., behavioral substitution, mindful attention) can improve smokers' ability to resist craving and build self-regulatory skills. However, poor engagement represents a major barrier to maximizing the impact of self-regulatory strategies. This paper describes the protocol for Mobile Assistance for Regulating Smoking (MARS) - a research study designed to inform the development of a mobile health (mHealth) intervention for promoting real-time, real-world engagement in evidence-based self-regulatory strategies. The study will employ a 10-day Micro-Randomized Trial (MRT) enrolling 112 smokers attempting to quit. Utilizing a mobile smoking cessation app, the MRT will randomize each individual multiple times per day to either: (a) no intervention prompt; (b) a prompt recommending brief (low effort) cognitive and/or behavioral self-regulatory strategies; or (c) a prompt recommending more effortful cognitive or mindfulness-based strategies. Prompts will be delivered via push notifications from the MARS mobile app. The goal is to investigate whether, what type of, and under what conditions prompting the individual to engage in self-regulatory strategies increases engagement. The results will build the empirical foundation necessary to develop a mHealth intervention that effectively utilizes intensive longitudinal self-report and sensor-based assessments of emotions, context and other factors to engage an individual in the type of self-regulatory activity that would be most beneficial given their real-time, real-world circumstances. This type of mHealth intervention holds enormous potential to expand the reach and impact of smoking cessation treatments.
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Affiliation(s)
- Inbal Nahum-Shani
- Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America.
| | - Lindsey N Potter
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States of America
| | - Cho Y Lam
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States of America
| | - Jamie Yap
- Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America
| | - Alexander Moreno
- College of Computing, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Rebecca Stoffel
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States of America
| | - Zhenke Wu
- School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Neng Wan
- Department of Geography, University of Utah, Salt Lake City, UT, United States of America
| | - Walter Dempsey
- School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Santosh Kumar
- Department of Computer Science, University of Memphis, Memphis, TN, United States of America
| | - Emre Ertin
- Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States of America
| | - Susan A Murphy
- Departments of Statistics & Computer Science, Harvard University, Cambridge, MA, United States of America
| | - James M Rehg
- College of Computing, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - David W Wetter
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States of America
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Kwon S, Wan N, Burns RD, Brusseau TA, Kim Y, Kumar S, Ertin E, Wetter DW, Lam CY, Wen M, Byun W. The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings. SENSORS 2021; 21:s21041411. [PMID: 33670507 PMCID: PMC7922785 DOI: 10.3390/s21041411] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/05/2021] [Accepted: 02/10/2021] [Indexed: 12/12/2022]
Abstract
MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland–Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.
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Affiliation(s)
- Sunku Kwon
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Neng Wan
- Department of Geography, University of Utah, Salt Lake City, UT 84112, USA;
| | - Ryan D. Burns
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Timothy A. Brusseau
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Youngwon Kim
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong;
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SL, UK
| | - Santosh Kumar
- Department of Computer Science, University of Memphis, Memphis, TN 38152, USA;
| | - Emre Ertin
- Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA;
| | - David W. Wetter
- Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA; (D.W.W.); (C.Y.L.)
| | - Cho Y. Lam
- Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA; (D.W.W.); (C.Y.L.)
| | - Ming Wen
- Department of Sociology, University of Utah, Salt Lake City, UT 84112, USA;
| | - Wonwoo Byun
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
- Correspondence: ; Tel.: +1-801-585-1119
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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; 12:674691. [PMID: 34248712 PMCID: PMC8264124 DOI: 10.3389/fpsyt.2021.674691] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/14/2021] [Indexed: 12/18/2022] Open
Abstract
As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02915341.
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Affiliation(s)
- Emre Ertin
- Dreese Lab, Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH, United States
| | - Nithin Sugavanam
- Dreese Lab, Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH, United States
| | - August F Holtyn
- Center for Learning and Health, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Kenzie L Preston
- National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, United States
| | - Jeremiah W Bertz
- National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, MD, United States
| | - Lisa A Marsch
- Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Bethany McLeman
- Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | | | | | | | | | - Udi E Ghitza
- Center for the Clinical Trials Network, National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, United States
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Rosa C, Marsch LA, Winstanley EL, Brunner M, Campbell ANC. Using digital technologies in clinical trials: Current and future applications. Contemp Clin Trials 2020; 100:106219. [PMID: 33212293 DOI: 10.1016/j.cct.2020.106219] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 10/05/2020] [Accepted: 11/10/2020] [Indexed: 12/20/2022]
Abstract
In 2015, we provided an overview of the use of digital technologies in clinical trials, both as a methodological tool and as a mechanism to deliver interventions. At that time, there was limited guidance and limited use of digital technologies in clinical research. However, since then smartphones have become ubiquitous and digital health technologies have exploded. This paper provides an update to our earlier publication and an overview of how technology has been used in the past five years in clinical trials, providing examples with varying levels of technological integration and across different health conditions. Digital technology integration ranges from the incorporation of artificial intelligence in diagnostic devices to the use of real-world data (e.g., electronic health records) for study recruitment. Clinical trials can now be conducted entirely virtually, eliminating the need for in-person interaction. Much of the published research demonstrates how digital approaches can improve the design and implementation of clinical trials. While challenges remain, progress over the last five years is encouraging, and barriers can be overcome with careful planning.
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Affiliation(s)
- Carmen Rosa
- National Institutes of Health, National Institute on Drug Abuse, Bethesda, MD, USA.
| | - Lisa A Marsch
- Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, USA.
| | - Erin L Winstanley
- West Virginia University, School of Medicine and Rockefeller Neuroscience Institute, Department of Behavioral Medicine and Psychiatry, Morgantown, West Virginia, USA; West Virginia University, School of Medicine, Department of Neuroscience Morgantown, West Virginia, USA.
| | - Meg Brunner
- Alcohol and Drug Abuse Institute, University of Washington, Seattle, WA, USA.
| | - Aimee N C Campbell
- New York State Psychiatric Institute, Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, USA.
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8
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Aronson ID, Bennett AS, Freeman R. Toward a human-centered use of technology: a stakeholder analysis of harm reduction and CBO staff. Harm Reduct J 2020; 17:77. [PMID: 33076911 PMCID: PMC7570409 DOI: 10.1186/s12954-020-00422-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 10/06/2020] [Indexed: 11/16/2022] Open
Abstract
Background Technology can enable syringe service programs (SSPs) and other community-based organizations (CBOs) operating under a harm reduction framework to work with an increased number of clients and can also enable organizations to offer services more effectively (e.g., offering HIV testing in ways participants may be more likely to accept). In the current time of COVID-19 social distancing, technology can also help organizations more safely provide services to people with compromised immune systems and to clients who might otherwise not be reached. However, technology projects implemented in harm reduction settings are frequently conceptualized and developed by researchers or technology specialists rather than by SSP staff or clients. Methods To more effectively meet the needs of SSPs and other CBOs across the USA, our team conducted qualitative interviews with 16 individuals who have extensive backgrounds working in the field of harm reduction. Interviews were digitally recorded and professionally transcribed, and the transcripts were checked for accuracy by the interviewers. The resulting transcripts were coded and analyzed to determine emerging themes. Results Interviewees mentioned the ability of technology to deliver consistent quality messaging to multiple clients at the same time and the potential to customize or tailor technology-based messaging to specific client populations as positive benefits. Clear barriers to technology use also emerged, in particular regarding privacy, data security, and the need to maintain client trust when discussing sensitive issues (e.g., illicit drug use). Conclusions Technology offers the potential to deliver consistently high-quality health communication and maintain contact with clients who may have no other access to care. If designed and managed effectively, technology can also address issues related to providing services during times when physical contact is limited due to COVID-19 social distancing measures.
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Affiliation(s)
- Ian David Aronson
- Digital Health Empowerment, Brooklyn, USA. .,New York University, School of Global Public Health, New York, USA.
| | - Alex S Bennett
- Digital Health Empowerment, Brooklyn, USA.,New York University, School of Global Public Health, New York, USA
| | - Robert Freeman
- New York University, School of Global Public Health, New York, USA
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Coughlin LN, Bonar EE, Bickel WK. Considerations for remote delivery of behavioral economic interventions for substance use disorder during COVID-19 and beyond. J Subst Abuse Treat 2020; 120:108150. [PMID: 33298296 PMCID: PMC7532990 DOI: 10.1016/j.jsat.2020.108150] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 08/10/2020] [Accepted: 09/22/2020] [Indexed: 12/24/2022]
Abstract
The response to the COVID-19 crisis has created direct pressure on health care providers to deliver virtual care, and has created the opportunity to develop innovations in remote treatment for people with substance use disorders. Remote treatments provide an intervention delivery framework that capitalizes on technological innovations in remote monitoring of behaviors and can efficiently use information collected from people and their environment to provide personalized treatments as needed. Interventions informed by behavioral economic theories can help to harness the largely untapped potential of virtual care in substance use treatment. Behavioral economic treatments, such as contingency management, the substance-free activity session, and episodic future thinking, are positioned to leverage remote monitoring of substance use and to use personalized medicine frameworks to deliver remote interventions in the COVID-19 era and beyond. With increased remote care, there is an opportunity for virtual treatment development. Treatments can capitalize on remote technology to increase effectiveness. Behavioral economic interventions are well positioned to fill this need. Remote behavioral economic interventions can add to current treatments.
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Affiliation(s)
- Lara N Coughlin
- Addiction Center, Department of Psychiatry, University of Michigan, United States of America.
| | - Erin E Bonar
- Addiction Center, Department of Psychiatry, University of Michigan, United States of America; Injury Prevention Center, University of Michigan, United States of America
| | - Warren K Bickel
- Fralin Biomedical Research Institute at Virginia Tech, United States of America
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Abstract
Digital technologies are rapidly changing how we understand and promote health. A robust and growing line of research has examined how digital health may enhance our understanding and treatment of addiction. This manuscript highlights innovations in the application of digital health approaches to addiction medicine, with a particular emphasis on advances in (1) real-time measurement of drug use events, (2) real-time measurement of the confluence of factors that surround drug use events, and (3) research examining how real-time measurement can inform responsive, in-the-moment interventions to prevent and treat substance use disorder. Although this manuscript focuses on addiction medicine as one exemplar of the striking impact of digital health, science-based digital health offers generalizable solutions to scaling-up unprecedented models of precision healthcare delivery across a broad spectrum of diseases across the globe.
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Affiliation(s)
- Lisa A Marsch
- Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Suite 315, Lebanon, New Hampshire USA
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11
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Goldfine C, Lai JT, Lucey E, Newcomb M, Carreiro S. Wearable and Wireless mHealth Technologies for Substance Use Disorder. CURRENT ADDICTION REPORTS 2020; 7:291-300. [PMID: 33738178 DOI: 10.1007/s40429-020-00318-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Purpose of review The goal of this scoping review is to evaluate the advances in wearable and other wireless mobile health (mHealth) technologies in the treatment of substance use disorders. Recent findings There are a variety of wireless technologies under investigation for the treatment of substance use disorder. Wearable sensors are the most commonly used technology. They can be used to decrease heavy substance use, mitigate factors related to relapse, and monitor for overdose. New technologies pose distinct advantages over traditional therapies by increasing geographic availability and continuously providing feedback and monitoring while remaining relatively non-invasive. Summary Wearable and novel technologies are important to the evolving landscape of substance use treatment. As technologies continue to develop and show efficacy, they should be incorporated into multifactorial treatment plans.
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Affiliation(s)
- Charlotte Goldfine
- University of Massachusetts Medical School, Department of Emergency Medicine, Division of Medical Toxicology, Worcester, MA
| | - Jeffrey T Lai
- University of Massachusetts Medical School, Department of Emergency Medicine, Division of Medical Toxicology, Worcester, MA
| | - Evan Lucey
- University of Massachusetts Medical School, Department of Emergency Medicine, Division of Medical Toxicology, Worcester, MA
| | - Mark Newcomb
- University of Massachusetts Medical School, Department of Emergency Medicine, Division of Medical Toxicology, Worcester, MA
| | - Stephanie Carreiro
- University of Massachusetts Medical School, Department of Emergency Medicine, Division of Medical Toxicology, Worcester, MA
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Marsch LA, Campbell A, Campbell C, Chen CH, Ertin E, Ghitza U, Lambert-Harris C, Hassanpour S, Holtyn AF, Hser YI, Jacobs P, Klausner JD, Lemley S, Kotz D, Meier A, McLeman B, McNeely J, Mishra V, Mooney L, Nunes E, Stafylis C, Stanger C, Saunders E, Subramaniam G, Young S. The application of digital health to the assessment and treatment of substance use disorders: The past, current, and future role of the National Drug Abuse Treatment Clinical Trials Network. J Subst Abuse Treat 2020; 112S:4-11. [PMID: 32220409 PMCID: PMC7134325 DOI: 10.1016/j.jsat.2020.02.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/30/2020] [Accepted: 02/08/2020] [Indexed: 01/17/2023]
Abstract
The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research that leverages digital technologies to glean new insights into SUDs and provide science-based therapeutic tools to a diverse array of persons with SUDs. This manuscript provides an overview of the breadth and impact of research conducted in the realm of digital health within the CTN. This work has included the CTN's efforts to systematically embed digital screeners for SUDs into general medical settings to impact care models across the nation. This work has also included a pivotal multi-site clinical trial conducted on the CTN platform, whose data led to the very first "prescription digital therapeutic" authorized by the U.S. Food and Drug Administration (FDA) for the treatment of SUDs. Further CTN research includes the study of telehealth to increase capacity for science-based SUD treatment in rural and under-resourced communities. In addition, the CTN has supported an assessment of the feasibility of detecting cocaine-taking behavior via smartwatch sensing. And, the CTN has supported the conduct of clinical trials entirely online (including the recruitment of national and hard-to-reach/under-served participant samples online, with remote intervention delivery and data collection). Further, the CTN is supporting innovative work focused on the use of digital health technologies and data analytics to identify digital biomarkers and understand the clinical trajectories of individuals receiving medications for opioid use disorder (OUD). This manuscript concludes by outlining the many potential future opportunities to leverage the unique national CTN research network to scale-up the science on digital health to examine optimal strategies to increase the reach of science-based SUD service delivery models both within and outside of healthcare.
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Affiliation(s)
- Lisa A Marsch
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA; Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA.
| | - Aimee Campbell
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA; Department of Psychiatry, Columbia University, 1051 Riverside Dr, New York, NY 10032, USA
| | - Cynthia Campbell
- Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 94612, USA
| | - Ching-Hua Chen
- Computational Health Behavior and Decision Science Research, IBM Thomas J. Watson Research, 1101 Kitchawan Rd, Yorktown Heights, NY 10598, USA
| | - Emre Ertin
- The Ohio State University College of Engineering, 2070 Neil Ave, Columbus, OH 43210, USA
| | - Udi Ghitza
- The National Institute on Drug Abuse, 6001 Executive Blvd, Rockville, MD 20852, USA
| | - Chantal Lambert-Harris
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Saeed Hassanpour
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - August F Holtyn
- Psychiatry and Behavioral Sciences, Johns Hopkins Medicine, 5255 Loughboro Road, N.W., Washington, DC 20016, USA
| | - Yih-Ing Hser
- Department of Psychiatry and Behavioral Sciences at the UCLA Integrated Substance Abuse Programs, 11075 Santa Monica Blvd., Ste. 200, Los Angeles, CA 90025, USA
| | - Petra Jacobs
- The National Institute on Drug Abuse, 6001 Executive Blvd, Rockville, MD 20852, USA
| | - Jeffrey D Klausner
- Epidemiology UCLA Fielding School of Public Health, Box 951772, Los Angeles, CA 90095-1772, USA
| | - Shea Lemley
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - David Kotz
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Andrea Meier
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Bethany McLeman
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Jennifer McNeely
- Department of Population Health, Department of Medicine, NYU School of Medicine, 227 East 30th Street, Seventh Floor, New York, NY 10016, USA
| | - Varun Mishra
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Larissa Mooney
- Resnick Neuropsychiatric Hospital at UCLA, Ronald Reagan UCLA Medical Center, 150 Medical Plaza Driveway, Los Angeles, CA 90095, USA
| | - Edward Nunes
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA; Department of Psychiatry, Columbia University, 1051 Riverside Dr, New York, NY 10032, USA
| | | | - Catherine Stanger
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Elizabeth Saunders
- Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, 46 Centerra Dr, Lebanon, NH 03766, USA
| | - Geetha Subramaniam
- The National Institute on Drug Abuse, 6001 Executive Blvd, Rockville, MD 20852, USA
| | - Sean Young
- University of California, Irvine, UC Institute for Prediction Technology, Donald Bren Hall: 6135, Irvine, CA 92697, USA
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