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ReviewsFull Access

An Overview of Internet- and Smartphone-Delivered Interventions for Alcohol and Substance Use Disorders

Abstract

Substance use disorders are a serious public health concern that affect approximately one in 12 individuals 12 years and older. Despite the high need for effective treatments for substance use disorders, the underutilization of services is well documented. One potential method of increasing access to care is through the use of technology. Treatment through the Internet or smartphone provides attractive solutions for those who are ambivalent to seeking treatment, because these treatments are easy to access from almost anywhere, self-paced, low commitment, and anonymous. The purpose of this review is to summarize the literature on Internet and smartphone interventions for substance use disorders that were developed on the basis of evidence-based treatments. The authors discuss these interventions within two broad categories: brief motivational or feedback-oriented interventions, which typically include one or two sessions, and longer interventions, which include multiple modules and are based on cognitive-behavior therapy, relapse prevention, contingency management, or a community reinforcement approach. These therapeutic adaptations through new technologies allow for increased access to substance use treatments and appear to yield overall positive results in adjusting norms about substance use, decreasing and ceasing substance use, and improving confidence to manage substance use.

Substance use disorders are characterized by recurrent use of alcohol or other drugs resulting in health concerns; disability; and negative social, occupational, or academic implications (1). Substance use disorders and substance abuse are related to decreased workplace productivity and increased crime and need for medical care, resulting in costs of more than $740 billion annually (24). Approximately 88,000 people die per year from alcohol-related concerns, which makes alcohol misuse the third leading cause of preventable death in the United States (5).

Worldwide, roughly 5.9% of deaths were related to alcohol use and misuse in 2012, and 64,070 deaths were related to illicit drugs and prescription opioids in 2016 (3). According to the National Survey on Drug Use and Health (6), in 2014, approximately 21.5 million people 12 years of age and older (8.1%) met criteria for a substance use disorder, including 17 million with an alcohol use disorder, 7.1 million with an illicit drug use disorder, and 2.6 million who met criteria for both. Therefore, approximately one in 12 individuals 12 years and older meets criteria for a substance use disorder. Clearly, substance use disorders are a serious public health concern that needs effective preventions and interventions.

The DSM-5 (7) defines substance use disorders as pathological patterns of substance use (criterion A) resulting in at least two symptoms that occur within a 12-month period. These symptoms are summarized in four clusters: impaired control (criteria 1–4), social impairment (criteria 5–7), risky use (criteria 8–9), and tolerance (criteria 10) and withdrawal (criteria 11). Substance use disorders can be classified as mild, moderate, or severe subtypes, on the basis of the number of symptoms the individual is experiencing. Substance use disorders can also be specified as being in early remission (if no criteria for a substance use disorder have been met for at least one month but less than 12 months) or in sustained remission (if no criteria have been met for 12 months or longer). Although the DSM-5 recognizes substance use disorders from 10 classes of drugs, including caffeine and tobacco, for the purposes of this review, we focus on alcohol and illicit substance use.

Despite the high need for substance-related interventions and implementations of effective treatments for these disorders, the underutilization of services is well documented. Only 2.5 million of the 21.5 million individuals who met criteria for a substance use disorder in 2014 received treatment specific to substance use concerns (6). Problems with obtaining effective treatment include limited services, challenges maintaining consistent treatment, ineffective implementation of evidence-based interventions, and social stigma (8). Although there are empirically supported treatments for substance use disorders, community-based programs struggle to offer such interventions because of limited resources that constrain adequate training and manageable caseloads (9). Furthermore, social stigma surrounding having a substance use problem may be one of the primary factors deterring individuals from establishing and maintaining consistent care (10, 11). Thus, increasing access to evidence-based care and enabling individuals to maintain anonymity may increase utilization of substance-related services and engagement in treatment.

One potential method of increasing access to care is through the use of technology. The use of Internet- and smartphone application-based interventions has been of increased interest and has been found to be effective in a range of therapeutic contexts (12). During the last several years, the number of Internet and mobile application interventions for substance use disorders has skyrocketed. These platforms provide attractive solutions for those who are ambivalent to seeking treatment, because they are self-paced, low commitment, and anonymous (10). From the perspective of the consumer, these Internet and mobile application interventions may be more affordable than face-to-face treatment and provide accessibility to evidence-based treatments that might otherwise be unavailable (12). The utilization of technology in the dissemination of substance use disorder treatment may help to improve access to evidence-based treatment while alleviating burden on health care providers and community programs.

The purpose of this review is to summarize the literature on Internet and smartphone application-based interventions for substance use disorders that were developed on the basis of evidence-based treatments (e.g., motivational interviewing, cognitive-behavior therapy [CBT] or relapse prevention, community reinforcement approach [CRA]). We do not review interventions that solely provide educational content or interventions that are only supportive in nature. Our aim is to give an overview of the varying administration styles of these applications, the basic content of such interventions, and the outcomes of research examining the efficacy and effectiveness of these interventions. Although there are non-Internet computer-based interventions as well as large-scale prevention programs, for the purpose of this review, we focus on Internet and application-based interventions for already present substance use problems or disorders. Although the majority of online or application-based interventions focus on alcohol use, we also discuss several interventions that focus on illicit drug use. We discuss these interventions within two broad categories: brief motivational or feedback-oriented interventions, which typically include one or two sessions, and longer interventions, which include multiple modules and are based on CBT, relapse prevention, contingency management, or CRA.

Brief Motivation and Feedback-Oriented Interventions

One common approach used in online or application-based substance use interventions is to provide a brief intervention based on motivational interviewing techniques. These interventions are typically one or two sessions and are modeled after brief motivational interventions, which have been shown to be effective with a range of alcohol, substance use, and other mental health problems (13, 14). Brief interventions aim to demonstrate discrepancies between how participants view their use and population norms in a factual, nondefensive, and empathic way. It is common for participants of these brief interventions to express disbelief when told how their drinking or drug use compares with that of a similar population, and these discrepancies can help build motivation to change. Another goal of brief interventions is to help the participant to examine both positive and negative consequences of using and not using. Decisional balance exercises can help to motivate individuals through recognizing the consequences and benefits of using as well as using less or abstaining. Finally, brief interventions may assist participants in developing goals and a plan for change.

Typically, in brief online or application-based interventions, participants complete a short assessment of their current substance use and mood symptoms. Participants may complete a measure such as the Alcohol Use Disorders Identification Test (AUDIT) (15). Often, participants report on the frequency and amount of alcohol or drug consumed during a specific time period (e.g., past week, past month, past year). These programs may encourage the participants to consider problems or consequences related to their substance use. Last, participants may report beliefs about drinking or drug use patterns of others who are similar to the participant in age or demographics.

After completing the brief assessment, participants are given feedback regarding their responses, including how their frequency of use, amount of use, and problems related to use compare with other individuals. Programs differ on how similar the comparison group is to the participants. Some programs give information about people in a similar age range in the same country, whereas other programs give information on norms from the same college (if it is a college sample), year, and gender (e.g., Neighbors et al.) (16). Because individuals often underestimate their level of intoxication, interventions focused on drinking also often give information about breath alcohol concentration (BrAC), which is based on number of drinks, how quickly the drinks are consumed, and the participant’s height and weight.

If beliefs about how much participants think others are drinking or using drugs is assessed, then participants are given feedback about the accuracy of their beliefs. For example, heavy drinkers often believe that their peers drink more heavily than is accurate. After receiving feedback, participants may indicate their level of readiness to change on a “readiness ruler,” which typically is a scale from zero to 10; complete a decisional balance; and develop goals and a plan for change.

One of the most common modes of modern communication is use of text messaging. In addition to using online and smartphone application formats, recent brief interventions targeting alcohol or substance misuse have also begun to use text messaging to send messages to support participants staying sober or to give feedback about participants’ drinking or use. Typically these interventions begin with a baseline assessment, and then participants periodically receive text messages. These messages may ask participants to complete a brief assessment, provide a supportive message, provide strategies to limit use, or give personalized feedback. In some interventions, participants are also able to text keywords to get responses that may help with achieving sobriety, limiting use, or limiting risk of harm (e.g., cab company phone numbers, online BrAC calculator) (17).

In the next sections, we review some of the research findings on Internet- and smartphone-delivered brief interventions. We divide these findings into sections, including brief interventions for alcohol among college students, brief interventions for alcohol among adults, and brief interventions for illicit drugs.

Interventions for Alcohol Among College Students

A large number of computer-delivered interventions to reduce college students’ problematic drinking have been developed. In a meta-analysis, Carey et al. (18) included 35 manuscripts with 43 separate computer-delivered interventions to reduce college students’ drinking. This meta-analysis included both intervention and prevention programs and programs that were Internet- or CD-ROM-based. Results from the meta-analysis suggest that computer-delivered interventions reduced the quantity and frequency of drinks relative to assessment-only controls. However, these computer-delivered interventions rarely differed from comparison conditions that included alcohol content. Commonly used interventions for college students’ drinking include programs such as eCHECKUP TO GO (e-CHUG), which is used by more than 600 universities and institutions (19), and Alcohol 101 Plus, which is CD-ROM based and had more than 40,000 copies distributed in 2004 (20, 21).

Several studies have also examined brief interventions using text messaging. College students who received individualized, tailored messages reported drinking significantly fewer drinks per drinking day and, at follow-up, had a lower expectancy that they would get in trouble because of alcohol consumption compared with students in the control group, who received a daily survey (22). Community college students who received a text-messaging intervention were less likely than controls, who received general motivational texts unrelated to alcohol use, to report heavy drinking and negative alcohol consequences. Students in the intervention group also had increases in self-efficacy to resist drinking in high-risk situations (17). These results were maintained through a 12-week follow-up.

In addition to the large number of brief interventions that target problematic alcohol use among college students, some brief interventions have targeted specific groups of college students, such as students turning 21 or first-year students. For example, Neighbors et al. (23) developed a personalized normative feedback intervention for college students who were turning 21 in the near future and intended to consume two or more drinks. Students were given personalized feedback and a harm-reduction message. Those who received the intervention had lower levels of estimated blood alcohol concentration (BAC) on their 21st birthday.

Other interventions have targeted first-year students identified as hazardous or risk drinkers. Saitz et al. (24) found that first-year students who were given an individualized minimal brief intervention decreased unhealthy alcohol use when compared with students who received only individualized feedback. Walters et al. (25) found that first-year students with heavy episodic drinking who received personalized feedback (through e-CHUG) had significant decreases in drinks per week and peak BAC when compared with assessment only at eight weeks. However, by week 16 the control group had also decreased drinking, and there were no significant differences between the groups. In a two-year randomized controlled trial, Neighbors et al. (16) examined gender-specific feedback compared with nongender-specific feedback among first-year college students who reported one or more heavy drinking episodes in the previous month. The researchers found modest effects on weekly drinking and alcohol-related problems but not on heavy episodic drinking. In addition, gender-specific biannual personalized normative feedback was associated with reductions over time in weekly drinking among women but not men.

Interventions for Alcohol Among Adults

Although most brief interventions have been developed for college students, there is also research on interventions for problematic alcohol use among adults. Problem drinkers who participated in a brief computer-based alcohol intervention (the Drinker’s Checkup) reduced quantity and frequency of drinking by 50% and had similar reductions in alcohol-related problems, which were sustained through 12 months (26). When compared with a control group, young adults in the workplace who receive online feedback regarding their drinking (Check Your Drinking) had significantly lower levels of drinking at a 30-day follow-up (27, 28). Text messages delivered daily appeared to help adult problem drinkers reduce drinking frequency and quantity more than did once-a-week self-tracking messages only, and tailored adaptive texts had the largest effect size (29). In the tailored adaptive text messages group, text messages varied on the basis of participants’ goal achievement in the prior week, and participants were able to text keywords for support.

Online and smartphone-delivered brief interventions may also be an accessible and cost-effective way to reach medical patients with problematic alcohol use. In a pilot feasibility study for text messaging to reduce alcohol relapse among 15 prelisting liver transplant candidates, participants had high satisfaction, looked forward to messages, and had better treatment outcomes than those who received standard care (30). When compared with control groups, injured trauma patients who receive computerized feedback had significantly lower levels of drinking 12 months later, but the proportion of at-risk drinkers did not significantly differ between groups (27, 28). A text-delivered feedback intervention among young adult emergency department patients was related to a decrease in number of binge drinking days and number of drinks per drinking day from baseline to three months (31). No significant decreases were found among the other groups, which included assessment-only texts and a control group that received no texts (31).

Interventions for Illicit Drug Use

Few studies have examined the impact of brief Internet and application-based interventions on illicit drug use, and findings have been mixed. Brief feedback through the Internet (eScreen.se) was more effective than assessment only for reducing alcohol use among illicit drug users over a 12-month period (32). However, no changes were found in illicit drug use. Ondersma et al. (33) compared a brief computer-based intervention based on motivational interviewing with assessment only among a sample of postpartum women who self-reported illicit drug use in the month before pregnancy. Findings demonstrated that the frequency of illicit drug use decreased among the intervention group as compared with a control group. In a study examining web-based personalized feedback among college marijuana users, Lee et al. (34) found no differences between personalized feedback and assessment.

Limitations and Summary of Motivation and Feedback-Oriented Interventions

Although much past research has shown positive effects of motivational interventions, several studies, which are mentioned in the previous sections, found no overall intervention effect or found that other modes of intervention were more successful than computer or application-based interventions. Furthermore, brief face-to-face interventions may outperform computer-delivered interventions (3537). Significant reductions in alcohol consumption were found for a brief face-to-face intervention when compared with a control group, but significant reductions were not found for a similar computer-delivered intervention (35). Similarly, Murphy et al. (37) found that Brief Alcohol Screening and Intervention for College Students (BASICS) (38), which is a face-to-face brief intervention, was associated with greater postsession self-ideal discrepancy than e-CHUG, an online brief intervention among college students. However, there were no differences in motivation or normative discrepancy, and the advantages of BASICS were often small and insignificant.

Overall, brief interventions for alcohol or drug use over the phone or Internet appear to be better than no treatment or assessment only (18). Because services for substance use disorders are underutilized, partially because of stigma and lack of access, Internet and application-based brief interventions may be a useful tool to help individuals rethink their substance use and to motivate them to think about changing harmful or hazardous substance use. In addition, one or two sessions of a motivational-enhancement-based Internet or smartphone application intervention appears to be enough to begin to have an impact on individuals’ use. Additional feedback or motivational-based sessions may not increase the effects of a brief intervention.

Among college students identified as hazardous drinkers in a primary care setting, a single web-based motivational interviewing session reduced hazardous drinking, as compared with receiving an informational pamphlet at 6 and 12 months (39). However, additional sessions of motivational interviewing beyond the first session did not enhance the effect of the intervention. Although some research suggests face-to-face brief interventions may have a stronger impact on reducing substance use, more research is needed to compare and contrast Internet and application-based brief interventions with face-to-face interventions and to identify ways of improving Internet- and smartphone-delivered interventions.

Longer Interventions

In addition to brief motivational interventions, researchers have also developed longer interventions that have multiple learning modules for participants. These interventions help participants to develop skills, such as cognitive-behavioral or relapse-prevention skills, or use CRA or a contingency management approach.

Cognitive-Behavior and Relapse-Prevention Skills Interventions

The majority of longer online and smartphone application interventions combine techniques used in brief interventions and skills and techniques used in CBT for alcohol or substance use. CBT-oriented interventions focus on teaching skills to prevent or manage relapse. Relapse prevention is based on the idea that relapse is a transitional process or a series of events that unfold over time and is influenced by immediate determinants (e.g., high-risk situations, coping skills, outcome expectancies) and covert antecedents (e.g., urges and cravings, lifestyle factors) (40). CBT-oriented interventions focus on developing skills to manage the factors influencing relapse. Face-to-face relapse prevention has been found to be generally effective, particularly for alcohol problems (41).

CBT Internet and application-based interventions generally begin with a brief assessment and feedback, similar to the brief interventions. Most CBT Internet and application-based interventions have ways for participants to set goals and to track their drinking or drug use over time. CBT Internet and smartphone application interventions have modules on skills such as identifying risky situations and coping plans, dealing with cravings, dealing with relapses, building problem-solving skills, identifying and changing thoughts about drug and alcohol, refusing offers of drugs or alcohol, and handling emotions. Programs vary in whether participants can go to any module or lesson at any point or have to go through the modules in a set order. Several online and application-based treatments also include access to peer-to-peer support group discussion rooms (e.g., 42, 43). CBT-oriented Internet and smartphone-delivered interventions have been developed for problematic drinking (4245), problematic substance use (46, 47), and veterans with alcohol or substance use problems and a comorbid posttraumatic stress disorder (PTSD) diagnosis (48, 49).

CBT interventions for alcohol.

Research examining online and smartphone-delivered CBT interventions for alcohol use have generally found that participants reduce alcohol use more than control groups or groups that are given feedback only. An observational study demonstrated that completers of an eight-module CBT-based program called eChange had lower levels of alcohol severity at a three-week follow-up (50). Participants of a CBT-based intervention (Drinking Less) reduced alcohol more than control participants, who were given a brochure (42). A study examining Change Your Drinking, which includes the brief intervention Check Your Drinking, found that alcohol use days, alcohol intake in grams, binge drinking, alcohol-related problems, and risk drinking were reduced three months after the intervention (51). Cunningham et al. (43) found that those who participated in a CBT online intervention after a brief intervention had a significantly greater reduction in their drinking as compared with individuals who only participated in the brief intervention. Thus, individuals may benefit from access to CBT interventions after completing a motivational brief intervention.

In addition to the CBT interventions described above, developers are beginning to use more technological tools available with smartphones, such as location-based monitoring (5254). The Location-Based Monitoring and Intervention for Alcohol Use Disorders (LBMI-A) (55) includes assessment and feedback, identification of high-risk locations, craving-coping strategies, access to supportive people (participant identifies supportive persons, and these persons are sent instructions on how to help a person with an alcohol problem), communication skills training, and assistance with scheduling pleasurable activities. LBMI-A was more effective in reducing craving-cued drinking as compared with a web-based brief intervention (Drinker’s Check-Up) (26, 56) plus bibliography (57).

The Addiction-Comprehensive Health Enhancement Support System (A-CHESS) (54), which targets continued care after people leave residential substance use treatment, includes GPS for high-risk locations (initiates an alert), a panic button, and skills for people to use when distressed. Participants in the A-CHESS intervention reported significantly fewer risky drinking days during the intervention and at a four- and 12-month follow-up (but not at an eight-month follow-up) as compared with a control group (54). A-CHESS participants were also more likely to report abstinence than control participants at all three time points. However, there were no significant differences found between groups for any of the negative consequences of drinking (e.g., not eating properly, hurting someone, being arrested). This lack of differences between groups may be because, overall, very few of these negative consequences were reported by participants.

Several CBT Internet and application-based interventions have also included online chatting with a therapist. Blankers et al. (44) compared seven individual text-based chat-therapy sessions (therapy alcohol online), which consisted of about 40 minutes with a CBT therapist; a self-help alcohol online intervention, which was based on motivational interviewing and CBT; and a wait list. The authors found that the interventions outperformed the wait-list condition, but the three conditions were not different from each other at three months. However, larger effects were found for drink reductions and AUDIT scores in the therapy alcohol online group as compared with the self-help alcohol online group at six months. In addition, Blankers et al. (58) found that the Internet-based therapy was more cost-effective than the Internet-based self-help over six months.

CBT interventions for illicit substance use.

Research examining the impact of online and smartphone-delivered CBT interventions on substance use has also demonstrated promising results. Schaub et al. (47) examined Can Reduce (with and without chat) and a waiting-list control group among problematic cannabis users. Can Reduce is based on motivational interviewing, self-control practices, and CBT. The self-help plus chat group had more days of abstinence and fewer days of cannabis use at follow-up (47). When standard treatment for drugs and alcohol was compared with standard treatment plus biweekly access to a computerized CBT program (CBT4CBT) in a private room at a clinic, those who received access to CBT4CBT had significantly more negative urine specimens and tended to have longer continuous periods of abstinence during treatment (59), which suggests that CBT web-based treatment can be used in conjunction with treatment as usual. These findings suggest that providing patients CBT Internet or application-based resources may help to improve treatment effects.

CBT interventions for veterans.

Two CBT interventions were developed specifically for veterans: Thinking Forward, and VetChange. Both interventions are self-directed and self-paced and were designed for returning veterans with PTSD and alcohol or substance use problems. Thinking Forward targets any hazardous substance use, whereas VetChange focuses on problematic alcohol use.

Acosta et al. (49) found significant treatment (Thinking Forward) effects for heavy drinking but not for PTSD or quality of life. When an initial intervention (VetChange) was compared with delayed intervention, the initial intervention participants demonstrated greater reductions in drinking and PTSD, and the delayed intervention participants showed similar improvements after receiving the intervention (48). In addition, baseline levels of PTSD and combat severity did not affect alcohol outcomes for participants in VetChange (60). Both of these interventions for veterans appear to be helpful in reducing harmful drinking, and VetChange may also help to reduce PTSD symptoms.

CRA

Longer interventions also include those that have used CRA and contingency management. CRA is a treatment approach that aims to achieve sobriety by eliminating positive reinforcements for drinking and increasing positive reinforcement for sobriety. Contingency management involves giving participants tangible rewards to reinforce sobriety. Contingency management has been shown to promote sobriety during the treatment of substance use disorders (61). Evidence suggests that CRA is more effective than usual care for alcohol use disorders, and CRA with incentives is more effective than usual care and CRA without contingent incentives for cocaine use disorders (62).

The Therapeutic Education System (TES) (63), which is also known as reSET, includes contingency management and 62 interactive multimedia modules based on CRA, each requiring 20–30 minutes to complete (63). TES promotes skills training to teach, encourage, and increase satisfaction with drug-free sources of reinforcement. It includes modules on basic CBT skills (e.g., refusing drugs, managing thoughts about using drugs, conducting functional analysis); modules aimed at improving psychosocial functioning (e.g., communication, mood management, family and social relations, time management); and modules on the prevention of HIV, hepatitis, and sexually transmitted infections. Incentives take the form of opportunities to draw vouchers from a virtual “fishbowl.” Some vouchers provide congratulatory messages, whereas others are exchangeable for prizes (usually worth around $1, occasionally around $20, and rarely around $80–$100). Draws are awarded for abstinence (based on negative urine or breath alcohol screens) and for completion of modules (up to the recommended four per week). In one study, participants in the TES group had a lower dropout rate and a greater abstinence rate compared with the treatment-as-usual group (63).

One intervention used contingency management techniques by smartphone among adults who drank frequently but were not physiologically dependent (64). Participants received a cell phone, a breathalyzer, and training on video-recording alcohol breath tests and texting results. Participants received texts one to three times daily indicating a BrAC was due within the hour. The contingency management group received escalating vouchers (promissory notes redeemable for a gift card or check) for valid on-time negative BrACs. Vouchers began at $2 and increased $0.50 for each consecutive negative BrAC, up to the maximum, which was $10. The percentage of negative BrACs was greater in the contingency management group than in the BrAC-monitoring-only group.

Overall, findings from research examining Internet- and smartphone-delivered interventions using cognitive-behavioral, relapse prevention, CRA, or contingency management approaches suggest that these interventions help individuals reduce their drinking or drug use. In addition, these interventions have been shown to be helpful as stand-alone treatments and in the context of treatment as usual. Several studies suggest that there is a greater intervention effect for treatments that include chat sessions with a CBT therapist instead of only including modules that the individual progresses through on his or her own. Although including chats sessions may increase the costs for providers up front, some research suggests that including the chat sessions is more cost beneficial in the long term (58). Further research is needed to examine the effectiveness of Internet and application-based interventions.

Summary and Implications

Given the global public health burden posed by substance use disorders, the stigma related to substance use disorders, and the underutilization of substance use interventions, there has been an increase in research and implementation of Internet and application-based treatments. These administration styles are attractive because they are self-paced, easily accessible, anonymous, and cost-effective. In addition, they reduce the burden on providers and community programs to facilitate up-to-date training in evidence-based treatments. Generally, these application- and Internet-based interventions are administered as either brief motivational interventions or longer-term interventions. The longer-term interventions tend to adopt a CBT and relapse-prevention approach or draw from community reinforcement or contingency management. Overall results of studies examining Internet and application interventions for substance use disorders have been positive and promising. These interventions have been developed primarily for alcohol use disorders, with some for illicit drug and marijuana use.

Despite these generally positive results, several studies have found no overall intervention effect for brief interventions. In particular, findings from research examining brief interventions for illicit substance use are mixed. In addition, findings from several studies suggest that face-to-face brief interventions may have a stronger impact on reducing substance use than computerized interventions (3537). Thus, brief interventions delivered by computer or smartphone may be best used in efforts to reach a large population that otherwise would not be reached or when these brief interventions can be paired with longer interventions that help individuals develop CBT or relapse-prevention skills.

Longer interventions frequently include personalized feedback and supportive messages, skills-based modules, relapse-prevention skills, and community reinforcement. Internet- and smartphone-delivered cognitive-behavioral interventions have been shown to decrease alcohol and drug use and are cost-effective. Utilization of contingency management through community reinforcement leads to increase in negative BrACs among individuals attempting to reduce or abstain from alcohol. In addition, these interventions appear to be effective when used with treatment as usual. Some research also suggests that including several chat sessions with a CBT therapist may have a stronger impact on reducing substance use than self-guided CBT Internet interventions without access to a therapist by chat (44, 58).

Future research is needed to examine Internet- and smartphone-delivered interventions for alcohol and substance use disorders. Most research examining motivational and feedback-focused brief interventions has been conducted on alcohol use among college samples. Further research is needed to investigate the generalizability of these interventions to other populations and other substances. Furthermore, because the majority of people now carry a smartphone with them at all times, the development and study of more smartphone application-based programming would be beneficial. Additionally, investigation regarding the utilization of application-based interventions is needed to understand which programs are being accessed and what treatment components are effective in this modality. Finally, it appears that a large number of interventions are developed for research purposes but then are not disseminated. Accessibility to Internet and application-based interventions grounded in evidence-based treatments could be improved.

Conclusions

Therapeutic adaptations and new technologies may allow for increased access to substance use treatments. Internet and smartphone interventions appear to yield positive results in adjusting norms about substance use, decreasing or ceasing substance use, and improving individuals’ confidence about managing use. Deriving programs from evidence-based principles (i.e., CBT, feedback, motivational enhancement, relapse prevention, and CRA) allows for dissemination of more effective and empirically supported methodologies to a population that tends to avoid intervention. The individual, social, financial, and health implications of decreasing substance use or reducing harm are substantial, and the impact of effective substance use treatment on work, productivity, health care burden, and criminality can provide relief to the global public health strain imposed by substance abuse. There is a need for future studies to examine the generalizability of these interventions to a broader population and ensure the treatments are evidence based and efficacious.

Dr. Watkins and Dr. Sprang are with the Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta.
Send correspondence to Dr. Watkins (e-mail: ).

The authors report no financial relationships with commercial interests.

References

1 Bouchery EE, Harwood HJ, Sacks JJ, et al.: Economic costs of excessive alcohol consumption in the U.S., 2006. Am J Prev Med 2011; 41:516–524CrossrefGoogle Scholar

2 Florence CS, Zhou C, Luo F, et al.: The economic burden of prescription opioid overdose, abuse, and dependence in the United States, 2013. Med Care 2016; 54:901–906CrossrefGoogle Scholar

3 National Institute on Drug Abuse: Trends and Statistics 2017. https://www.drugabuse.gov/related-topics/trends-statistics. Accessed July 23, 2018Google Scholar

4 Centers for Disease Control and Prevention: Excessive drinking is draining the U.S. economy 2016. https://www.cdc.gov/features/costsofdrinking/. Accessed July 23, 2018Google Scholar

5 Mokdad AH, Marks JS, Stroup DF, et al.: Actual causes of death in the United States, 2000. JAMA 2004; 291:1238–1245CrossrefGoogle Scholar

6 Behavioral Health Trends in the United States: Results From the 2014 National Survey on Drug Use and Health. HHS Publication No. SMA 15-4927, NSDUH Series H-50. Rockville, MD, Center for Behavioral Health and Statistics Quality, 2015.Google Scholar

7 Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Arlington, VA, American Psychiatric Publishing, 2013Google Scholar

8 McLellan AT, Carise D, Kleber HD: Can the national addiction treatment infrastructure support the public’s demand for quality care? J Subst Abuse Treat 2003; 25:117–121CrossrefGoogle Scholar

9 Marsch LA, Carroll KM, Kiluk BD: Technology-based interventions for the treatment and recovery management of substance use disorders: a JSAT special issue. J Subst Abuse Treat 2014; 46:1–4CrossrefGoogle Scholar

10 Sundström C, Blankers M, Khadjesari Z: Computer-based interventions for problematic alcohol use: a review of systematic reviews. Int J Behav Med 2017; 24:646–658CrossrefGoogle Scholar

11 Cohen E, Feinn R, Arias A, et al.: Alcohol treatment utilization: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. Drug Alcohol Depend 2007; 86:214–221CrossrefGoogle Scholar

12 Bickel WK, Christensen DR, Marsch LA: A review of computer-based interventions used in the assessment, treatment, and research of drug addiction. Subst Use Misuse 2011; 46:4–9CrossrefGoogle Scholar

13 Miller WR, Wilbourne PL, Hettema JE: What works? A summary of alcohol treatment outcome research; in Handbook of Alcoholism Treatment Approaches: Effective Alternatives, 3rd ed. Edited by Hester RK, Miller WR.. Boston, Allyn & Bacon, 2003.Google Scholar

14 Lundahl BW, Kunz C, Brownell C, et al.: A meta-analysis of motivational interviewing: twenty-five years of empirical studies. Res Soc Work Pract 2010; 20:137–160CrossrefGoogle Scholar

15 Babor TF, Higgins-Biddle JC, Saunders JB, et al.: The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Care, 2nd ed. Geneva, World Health Organization, 2001Google Scholar

16 Neighbors C, Lewis MA, Atkins DC, et al.: Efficacy of web-based personalized normative feedback: a two-year randomized controlled trial. J Consult Clin Psychol 2010; 78:898–911CrossrefGoogle Scholar

17 Bock BC, Barnett NP, Thind H, et al.: A text message intervention for alcohol risk reduction among community college students: TMAP. Addict Behav 2016; 63:107–113CrossrefGoogle Scholar

18 Carey KB, Scott-Sheldon LA, Elliott JC, et al.: Computer-delivered interventions to reduce college student drinking: a meta-analysis. Addiction 2009; 104:1807–1819CrossrefGoogle Scholar

19 San Diego State University: What is the eCHECKUP TO GO? http://www.echeckuptogo.com/about. Accessed July 23, 2018Google Scholar

20 Alcohol 101 Plus. Arlington, VA, Century Council, 2003.Google Scholar

21 Walters ST, Miller E, Chiauzzi E: Wired for wellness: e-interventions for addressing college drinking. J Subst Abuse Treat 2005; 29:139–145CrossrefGoogle Scholar

22 Weitzel JA, Bernhardt JM, Usdan S, et al.: Using wireless handheld computers and tailored text messaging to reduce negative consequences of drinking alcohol. J Stud Alcohol Drugs 2007; 68:534–537CrossrefGoogle Scholar

23 Neighbors C, Lee CM, Lewis MA, et al.: Internet-based personalized feedback to reduce 21st-birthday drinking: a randomized controlled trial of an event-specific prevention intervention. J Consult Clin Psychol 2009; 77:51–63CrossrefGoogle Scholar

24 Saitz R, Palfai TP, Freedner N, et al.: Screening and brief intervention online for college students: the iHealth Study. Alcohol Alcohol 2007; 42:28–36CrossrefGoogle Scholar

25 Walters ST, Vader AM, Harris TR: A controlled trial of web-based feedback for heavy drinking college students. Prev Sci 2007; 8:83–88CrossrefGoogle Scholar

26 Hester RK, Squires DD, Delaney HD: The Drinker’s Check-Up: 12-month outcomes of a controlled clinical trial of a stand-alone software program for problem drinkers. J Subst Abuse Treat 2005; 28:159–169CrossrefGoogle Scholar

27 Doumas DM, Hannah E: Preventing high-risk drinking in youth in the workplace: a web-based normative feedback program. J Subst Abuse Treat 2008; 34:263–271CrossrefGoogle Scholar

28 Neumann T, Neuner B, Weiss-Gerlach E, et al.: The effect of computerized tailored brief advice on at-risk drinking in subcritically injured trauma patients. J Trauma 2006; 61:805–814CrossrefGoogle Scholar

29 Muench F, Van Stolk-Cooke K, Kuerbis A, et al.: A randomized controlled pilot trial of different mobile messaging interventions for problem drinking compared to weekly drink tracking. PLoS One 2017; 12:e0167900CrossrefGoogle Scholar

30 DeMartini KS, Schilsky ML, Palmer A, et al.: Text messaging to reduce alcohol relapse in prelisting liver transplant candidates: A pilot feasibility study. Alcohol Clin Exp Res 2018; 42:761–769CrossrefGoogle Scholar

31 Suffoletto B, Kristan J, Callaway C, et al. A text message alcohol intervention for young adult emergency department patients: a randomized clinical trial. Ann Emerg Med 2014; 64:664-672 e4CrossrefGoogle Scholar

32 Sinadinovic K, Wennberg P, Berman AH: Internet-based screening and brief intervention for illicit drug users: a randomized controlled trial with 12-month follow-up. J Stud Alcohol Drugs 2014; 75:313–318CrossrefGoogle Scholar

33 Ondersma SJ, Svikis DS, Schuster CR: Computer-based brief intervention: a randomized trial with postpartum women. Am J Prev Med 2007; 32:231–238CrossrefGoogle Scholar

34 Lee CM, Neighbors C, Kilmer JR, et al.: A brief, web-based personalized feedback selective intervention for college student marijuana use: a randomized clinical trial. Psychol Addict Behav 2010; 24:265–273CrossrefGoogle Scholar

35 Leffingwell TR, Hopper R, Mignogna J: A randomized trial of a computerized multimedia feedback intervention for high-risk drinking among college students. Washington, DC, Society of Behavioral Medicine, 2007Google Scholar

36 Carey KB, Henson JM, Carey MP, et al.: Computer versus in-person intervention for students violating campus alcohol policy. J Consult Clin Psychol 2009; 77:74–87CrossrefGoogle Scholar

37 Murphy JG, Dennhardt AA, Skidmore JR, et al.: Computerized versus motivational interviewing alcohol interventions: impact on discrepancy, motivation, and drinking. Psychol Addict Behav 2010; 24:628–639CrossrefGoogle Scholar

38 Dimeff LA, Baer JS, Kivlahan DR, et al.: Brief Alcohol Screening and Intervention for College Students: A Harm Reduction Approach. New York, Guilford Press, 1999Google Scholar

39 Kypri K, Langley JD, Saunders JB, et al.: Randomized controlled trial of web-based alcohol screening and brief intervention in primary care. Arch Intern Med 2008; 168:530–536CrossrefGoogle Scholar

40 Marlatt GA, Gordon JR: Relapse Prevention: Maintenance Strategies in the Treatment of Addictive Behaviors. New York, Guilford Press, 1985Google Scholar

41 Irvin JE, Bowers CA, Dunn ME, et al.: Efficacy of relapse prevention: a meta-analytic review. J Consult Clin Psychol 1999; 67:563–570CrossrefGoogle Scholar

42 Riper H, Kramer J, Smit F, et al.: Web-based self-help for problem drinkers: a pragmatic randomized trial. Addiction 2008; 103:218–227CrossrefGoogle Scholar

43 Cunningham JA: Comparison of two Internet-based interventions for problem drinkers: randomized controlled trial. J Med Internet Res 2012; 14:e107CrossrefGoogle Scholar

44 Blankers M, Koeter MW, Schippers GM: Internet therapy versus Internet self-help versus no treatment for problematic alcohol use: a randomized controlled trial. J Consult Clin Psychol 2011; 79:330–341CrossrefGoogle Scholar

45 Sundström C, Gajecki M, Johansson M, et al.: Guided and unguided Internet-based treatment for problematic alcohol use—a randomized controlled pilot trial. PLoS One 2016; 11:e0157817CrossrefGoogle Scholar

46 Berman AH, Wennberg P, Sinadinovic K: Changes in mental and physical well-being among problematic alcohol and drug users in 12-month Internet-based intervention trials. Psychol Addict Behav 2015; 29:97–105CrossrefGoogle Scholar

47 Schaub MP, Wenger A, Berg O, et al.: A web-based self-help intervention with and without chat counseling to reduce cannabis use in problematic cannabis users: three-arm randomized controlled trial. J Med Internet Res 2015; 17:e232CrossrefGoogle Scholar

48 Brief DJ, Rubin A, Keane TM, et al.: Web intervention for OEF/OIF veterans with problem drinking and PTSD symptoms: a randomized clinical trial. J Consult Clin Psychol 2013; 81:890–900CrossrefGoogle Scholar

49 Acosta MC, Possemato K, Maisto SA, et al.: Web-delivered CBT reduces heavy drinking in OEF-OIF veterans in primary care with symptomatic substance use and PTSD. Behav Ther 2017; 48:262–276CrossrefGoogle Scholar

50 Johansson M, Sinadinovic K, Hammarberg A, et al.: Web-based self-help for problematic alcohol use: a large naturalistic Study. Int J Behav Med 2017; 24:749–759CrossrefGoogle Scholar

51 Tensil MD, Jonas B, Stuber E: Two fully automated web-based interventions for risky alcohol use: randomized controlled trial. Journal of Medical Internet Research 2013; 15:e110CrossrefGoogle Scholar

52 Dulin PL, Gonzalez VM, Campbell K: Results of a pilot test of a self-administered smartphone-based treatment system for alcohol use disorders: usability and early outcomes. Subst Abus 2014; 35:168–175CrossrefGoogle Scholar

53 Gonzalez VM, Dulin PL: Comparison of a smartphone app for alcohol use disorders with an Internet-based intervention plus bibliotherapy: a pilot study. J Consult Clin Psychol 2015; 83:335–345CrossrefGoogle Scholar

54 Gustafson DH, McTavish FM, Chih MY, et al.: A smartphone application to support recovery from alcoholism: a randomized clinical trial. JAMA Psychiatry 2014; 71:566–572CrossrefGoogle Scholar

55 Dulin PL, Gonzalez VM, King DK, et al.: Smartphone-based, self-administered intervention system for alcohol use disorders: theory and empirical evidence basis. Alcohol Treat Q 2013; 31:321–3436CrossrefGoogle Scholar

56 Hester RK, Delaney HD, Campbell W: The college Drinker’s Check-Up: outcomes of two randomized clinical trials of a computer-delivered intervention. Psychol Addict Behav 2012; 26:1–12CrossrefGoogle Scholar

57 Dulin PL, Gonzalez VM: Smartphone-based, momentary intervention for alcohol cravings amongst individuals with an alcohol use disorder. Psychol Addict Behav 2017; 31:601–607CrossrefGoogle Scholar

58 Blankers M, Nabitz U, Smit F, et al.: Economic evaluation of Internet-based interventions for harmful alcohol use alongside a pragmatic randomized controlled trial. J Med Internet Res 2012; 14:e134CrossrefGoogle Scholar

59 Carroll KM, Ball SA, Martino S, et al.: Computer-assisted delivery of cognitive-behavioral therapy for addiction: a randomized trial of CBT4CBT. Am J Psychiatry 2008; 165:881–888CrossrefGoogle Scholar

60 Brief DJ, Solhan M, Rybin D, et al.: Web-based alcohol intervention for veterans: PTSD, combat exposure, and alcohol outcomes. Psychol Trauma 2018; 10:154–162CrossrefGoogle Scholar

61 Prendergast M, Podus D, Finney J, et al.: Contingency management for treatment of substance use disorders: a meta-analysis. Addiction 2006; 101:1546–1560CrossrefGoogle Scholar

62 Roozen HG, Boulogne JJ, Van Tulder MW, et al.: A systematic review of the effectiveness of the community reinforcement approach in alcohol, cocaine and opioid addiction. Drug Alcohol Depend 2004; 74:1–13CrossrefGoogle Scholar

63 Campbell AN, Nunes EV, Matthews AG, et al.: Internet-delivered treatment for substance abuse: a multisite randomized controlled trial. Am J Psychiatry 2014; 171:683–690CrossrefGoogle Scholar

64 Alessi SM, Petry NM: A randomized study of cellphone technology to reinforce alcohol abstinence in the natural environment. Addiction 2013; 108:900–909CrossrefGoogle Scholar