The application of digital technologies to better assess, understand and treat substance use disorders is a particularly promising and vibrant area of scientific research . Among the many applications of digital technologies, digital tools may be useful in the screening and assessment of SUD. Indeed, research evaluating the use of electronic screeners has demonstrated that individuals more accurately report risk behavior, including substance use and sexual risk behavior, when responding to questions posed by an electronic screener instead of by another individual . Embedding standardized, validated clinical assessments of SUD into electronic health records may also facilitate the assessment and treatment of SUDs as part of the routine clinical workflow in a wide variety of clinical settings . Digital health interventions are interactive, self-directed software tools that can overcome some of the striking disparities in treatment access and treatment quality evident in healthcare settings across the globe . For example, digital therapeutics can teach people effective, scientifically validated skills to recognize and change unhealthy thoughts and behavior and provide tools to help people apply these skills to their everyday lives. Digital therapeutics can be available 24/7 and thus allow for “on-demand” access to therapeutic support, thereby creating unprecedented models of intervention delivery and reducing barriers to accessing care. Telehealth, the use of telecommunication technologies to deliver long-distance clinical care, may also allow SUD expert clinicians to deliver care in communities where SUD treatment needs are high but SUD workforce capacity is limited . Telehealth can be used in concert with digital therapeutics to provide real-time distance communication with SUD clinicians via video technology, complemented by digital therapeutic software that does not rely on synchronous communication with another individual but rather can be available at all times. Digital therapeutics and telehealth models of care may be transformative in the treatment of SUDs in many ways .

As most persons with SUDs spend the majority of their time outside of a treatment facility,cannabis dryer digital technologies can extend the reach and impact of treatment by offering anytime/anywhere SUD care. Digital tools can function like a therapist “in your pocket” and can be accessible at times when individuals struggling with SUDs may be in greatest need of therapeutic support. Additionally, a large part of care offered in SUD treatment settings does not reflect the state of the science of SUD care . Digital therapeutics can ensure the delivery of SUD care with fidelity to the most evidence-based practices. Further, the behavioral health clinician workforce cannot meet the large population-level needs for SUDs or offer anytime/anywhere care . Digital therapeutics provide science based, scalable solutions to meet SUD needs at a population-level. This may be particularly relevant in tackling the current U.S. opioid crisis, in which the number of Americans with an opioid use disorder has surged, especially in rural communities, while the trained SUD workforce has not grown at a comparable rate , 2019. Digital technologies also afford new opportunities to examine clinical trajectories and identify novel digital biomarkers within-individuals through intensive collection of individual-level data using mobile devices, wearable sensors, and mapping digital footprints. Indeed, digital tools may capture information about individual’s physiology “in vivo” as they live their daily lives . Specifically, mobile technologies enable ecological momentary assessment a method that prompts individuals to respond to queries on mobile devices, and which enables near real-time monitoring, of individuals’ behavior while they engage in daily activities. Because EMA allows for intensive longitudinal assessment in naturalistic contexts, these data offer promise to enhance our understanding of mechanisms of health behavior, including drug-taking behavior . Digital technologies also enable passive sensing and inference from smartphones or sensing devices worn on the body, which is transforming how we understand human behavior . Mobile sensing allows for the continuous measurement of physiological and behavioral data in the real world.

This sensor data can be streamed to a smartphone and processed immediately to infer information about a person’s health behavior, physiology, and context. These data from sensors can be combined with data from self-report EMA assessments to enhance an understanding of the individual’s behavior in context . This information can then be used to trigger the delivery of interventions in real time . Further, the use of social media sites has exploded in recent years. Social media enables multi-directional communication anywhere and anytime. Social media may be leveraged to recruit individuals into research, often allowing for rapid, cost-effective recruitment of national and hard-to-reach populations . Social media data have also been used to predict many phenomena, ranging from purchasing patterns to disease epidemics , and a growing body of literature shows how social media data may enable a rich understanding of the topology and functioning of social networks and their relationships to health/risk behavior . For example, social media has been shown to contain signals of depression among individuals, such as decreased social activity, increased negative affect, highly clustered egocentric networks, and heightened concerns about relations and medications . Also, data derived from social media has been shown to predict a range of sensitive personal attributes including sexual orientation, political views, personality traits, and use of addictive substances . Digitally-derived data offer great potential to refine and advance our understanding of health behavior, including SUDs. These granular-level data captured in daily life allow for the development of dynamic models of SUDs to understand behavior in real-time and in response to changing environmental, social, physiological, and intrapersonal factors . And, they can help us understand when individuals may be most receptive to interventions , with a goal of providing the right type/amount of therapeutic support at the right time by adapting to an individual’s changing internal and contextual state . Collectively, these digital technologies enable an entirely new offering of tools for collecting rich data about individuals’ behavior, health, and environment, provide personalized interventions and resources based on individuals’ needs and preferences, and enable dynamic computational models to predict and characterize individuals’ changing needs and health trajectories over time.

The National Drug Abuse Treatment Clinical Trials Network , 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. The CTN is a unique research infrastructure for conducting practical, rigorous, and highly impactful trials focused on improving the treatment of SUDs and promoting widespread implementation and sustainability of effective and accessible SUD care in community systems across the nation. Among its many contributions, the CTN has supported a broad array of innovative and impactful research projects that have leveraged digital health. This manuscript provides an overview of the digital health portfolio of the CTN and outlines a vision for the many 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, and reduce barriers in access to science-based SUD service delivery models both within and outside of healthcare. Note that we recognize that additional, rigorous research supported by NIDA focused on the application of digital health to SUDs has been conducted outside of the CTN ; however, consistent with the focus of this journal Special Issue, this article focuses on the breadth of work within the CTN. Collectively, this research within the CTN is focused on addressing important scientific questions such as how to use digital health to routinize and standardize validated SUD screening in health care settings; how to use digital health to detect substance use in real time and in “the wild”; how to implement and scale up effective SUD treatment; and how to leverage social media for recruitment and intervention. The majority of digital health studies in the CTN have focused on the use of electronic health records for SUD screening and/or assessment. One of the earliest projects in this area was the development and validation of a brief screening and assessment instrument, the Tobacco, Alcohol, Prescription Medication, and Other Substance Use Tool,vertical farming systems for use in primary care patients . The TAPS tool is comprised of a 4-item screening survey, followed by a more detailed, substance-specific assessment of risk for any substances for which an individual has a positive initial screen . An early multi-site CTN trial with 2000 adult patients in 5 adult primary care clinics compared an interviewer-administered version of the TAPS tool to a version of the tool that was self administered on a tablet computer . Results demonstrated that the interviewer- and self-administered versions of the TAPS tool had comparable diagnostic characteristics, but the self-administered version yielded higher rates of reporting of past year alcohol, illicit drug and prescription medication misuse . The most notable discrepancy was for reports of prescription medication misuse, such that disclosure rates were 50% higher on the self-administered version. In addition, the tool showed promising sensitivity and specificity for detecting several types of substance use disorders, including tobacco and alcohol. It also identified adult primary care patients with high risk scores on the World Health Organization’s Alcohol, Smoking and Substance Involvement Screening Test as well as moderate risk scores for tobacco, alcohol and marijuana . Overall, the TAPs tool showed a more modest ability to identify some illicit and prescription medication SUDs in comparison to the ASSIST.

Despite this, the TAPS tool is much briefer than the ASSIST and provides primary care providers with information about current substance use, thus underscoring its strong appeal for use in primary care. Given that visits to primary care represent an important window of opportunity to systematically screen and identify SUDs among a broad population , the TAPS tool is an example of a validated, brief and practical resource that can be routinely delivered, including in a digital format, in general medical settings. The CTN’s work has extended beyond development and validation of the TAPS SUD screening tool to evaluate the feasibility of embedding SUD screeners into EHRs in primary care and integrating screening into the primary care workflow. One trial evaluated how implementation of drug screening in primary care impacts rates of SUD assessment and subsequent care and demonstrated that screening led to an increase in SUD diagnoses, particularly cannabis use disorder diagnoses . Another multi-site study being conducted in both urban primary care and rural Federally Qualified Health Centers has identified barriers and facilitators of embedding screening into these settings and underscored the importance of clearly communicating with patients about the goals of screening to counteract stigma, addressing staff concerns regarding time and workflow, and providing SUD education and treatment resources to primary care clinicians . Several ongoing CTN projects have further extended this work to evaluate the feasibility, usability, acceptability and impact of OUD clinical decision support tools embedded in EHRs to help guide primary care providers in evidence-based treatment of OUD. Of considerable promise, and influenced by the research conducted within the CTN, the U.S. Preventive Services Task Force has just released a draft recommendation to screen for drug use among adults in general medical settings , 2019.The CTN has had a marked impact in the field of digital therapeutics for SUDs — interactive software used to treat SUDs. The most impactful clinical trial with a digital therapeutic conducted within the CTN evaluated the clinical effectiveness of the web-based Therapeutic Education System  . TES is a web-based, self-directed version of the strongly evidence-based Community Reinforcement Approach to behavior therapy developed by Azrin . This intensive behavioral treatment is designed to teach individuals with SUDs how to better understand and disrupt harmful behaviors and cognitions related to their drug-taking behavior and to develop new skills to restructure their lives. In this pivotal CTN trial, the CRA-based behavioral treatment was offered along with incentives targeting drug abstinence and treatment participation. In this trial, conducted in partnership with 10 SUD treatment sites, individuals in outpatient SUD treatment were randomly assigned to receive either 12 weeks of standard outpatient SUD treatment or a treatment model in which TES partially replaced 2 hours of patient-clinician therapy time or psychoeducation . This study found that participants who received TES as part of their care model had a markedly lower rate of treatment dropout and a higher rate of drug abstinence , an effect that was most evident among patients who had a drug-positive urine and/or alcohol-positive breath screen at the time of entering the study .