Technology-Based Interventions for Substance Use and Comorbid Disorders: An Examination of the Emerging Literature

Sugarman, Dawn E.; Campbell, Aimee N.C.; Iles, Brittany R.; Greenfield, Shelly F.

doi:10.1097/hrp.0000000000000148

Cited by 34 publications

(27 citation statements)

References 81 publications

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“…Abstract screening occurred by 2 raters in Abstrackr (Wallace et al., ). Finally, a bibliographic search of eligible studies and literature reviews was completed (Carroll and Kiluk, ; Moore et al., ; Riper et al., ; Rooke et al., ; Sugarman et al., ). Figure provides a visual representation of study inclusion, and although all drug use disorders were initially of interest, the majority of studies addressed alcohol use.…”

Section: Methodsmentioning

confidence: 99%

“…Yet, a meta‐analysis on the efficacy of technology‐delivered CBT for alcohol use has not been conducted. There are reviews of technology‐delivered interventions for alcohol as well as other drug use (Bickel et al., ; Moore et al., ; Rooke et al., ; Sugarman et al., ; Tait et al., ), but none of these reviews have evaluated the evidence of CBT or CBT‐based interventions, specifically.…”

mentioning

confidence: 99%

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Technology‐Delivered Cognitive‐Behavioral Interventions for Alcohol Use: A Meta‐Analysis

Kiluk

Ray

Walthers

et al. 2019

Alcoholism Clin & Exp Res

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Background: Cognitive-behavioral therapy (CBT) has long-standing evidence for efficacy in the treatment of alcohol use, yet implementation in clinical practice has been challenging. Delivery of CBT through technology-based platforms, such as web-based programs and mobile applications, has the potential to provide widespread access to this evidence-based intervention. While there have been reviews indicating the efficacy of technology-based delivery of CBT for various psychiatric conditions, none have focused on efficacy for alcohol use. The current meta-analysis was conducted to fill this research gap.Methods: Descriptive data were used to characterize the nature of the literature on technology-delivered, CBT-based interventions for alcohol use ("CBT Tech"). Inverse-variance-weighted effect sizes were calculated, and random effects, effect sizes were pooled in 4 subgroups.Results: Fifteen published trials conducted primarily with at-risk or heavy drinkers were identified. Of these studies, 60% explicitly targeted alcohol use moderation. The content of CBT Tech programs varied, ranging from 4 to 62 sessions/exercises, with many programs combining elements of motivational interviewing (47%). With respect to efficacy, CBT Tech as a stand-alone treatment in contrast to a minimal treatment control showed a positive and statistically significant, albeit small effect (g = 0.20: 95% CI = 0.22, 0.38, k es = 5). When CBT Tech was compared to treatment as usual (TAU), effects were nonsignificant. However, when CBT Tech was tested as an addition to TAU, in contrast to TAU only, the effect size was positive, significant (g = 0.30: 95% CI = 0.10, 0.50, k es = 7), and stable over 12-month follow-up. Only 2 studies compared CBT Tech to in-person CBT, and this pooled effect size did not suggest superior efficacy.Conclusions: These results show a benefit for technology-delivered, CBT-based interventions as a stand-alone therapy for heavy drinking or as an addition to usual care in specialty substance use settings.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Technology‐Delivered Cognitive‐Behavioral Interventions for Alcohol Use: A Meta‐Analysis

Kiluk

Ray

Walthers

et al. 2019

Alcoholism Clin & Exp Res

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“…As such, researchers studying ROOT and TBI in longitudinal work may wish to assess unhealthy use of the internet and social media over time (e.g., Bergen Social Media Addiction Scale; Andreassen, Pallesen, & Griffiths, 2017). With greater work in this area, potential risks may be considered alongside benefits offered by well-designed, theoretically-grounded interventions and services that leverage online technology platforms (Fowler et al, 2016; Litvin et al, 2013; Marsch, 2012; Sugarman et al, 2017). …”

Section: Discussionmentioning

confidence: 99%

“…Reviews suggest TBIs are generally better than inactive comparison conditions (e.g., self-help reading materials; Fowler et al, 2016; Litvin, Abrantes, & Brown, 2013). They may do as well as clinician-led approaches both for individuals with SUD (Fowler et al, 2016; Litvin et al, 2013), and co-occurring substance use and mental health problems (Sugarman, Campbell, Iles, & Greenfield, 2017). In clinical settings, TBIs that are added to, or substituted for parts of, usual treatment may yield the best outcomes (Carroll et al, 2008; Gustafson et al, 2014; Marsch et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Expanding the reach of alcohol and other drug services: Prevalence and correlates of US adult engagement with online technology to address substance problems

Bergman

Greene

Hoeppner

et al. 2018

Addictive Behaviors

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Online technologies are well integrated into the day-to-day lives of individuals with alcohol and other drug (i.e., substance use) problems. Interventions that leverage online technologies have been shown to enhance outcomes for these individuals. To date, however, little is known about how those with substance use problems naturally engage with such platforms. In addition, the scientific literatures on health behavior change facilitated by technology and harms driven by technology engagement have developed largely independent of one another. In this secondary analysis of the National Recovery Study (NRS), which provides a geo-demographically representative sample of US adults who resolved a substance use problem, we examined a) the weighted prevalence estimate of individuals who engaged with online technologies to "cut down on substance use, abstain from substances, or strengthen one's recovery" (i.e., recovery-related use of online technology, or ROOT), b) clinical/recovery correlates of ROOT, controlling for demographic covariates, and c) the unique association between ROOT and self-reported history of internet addiction. Results showed one in ten (11%) NRS participants reported ROOT. Significant correlates included greater current psychological distress, younger age of first substance use, as well as history of anti-craving/anti-relapse medication, recovery support services, and drug court participation. Odds of lifetime internet addiction were 4 times greater for those with ROOT (vs. no ROOT). These data build on studies of technology-based interventions, highlighting the reach of ROOT, and therefore, the potential for a large, positive impact on substance-related harms in the US.

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“…For example, among AC patients in the United Kingdom, women were less likely to have alcohol use recorded and were overall less likely to interact with the healthcare system in the period prior to their AC diagnosis (Otete et al, 2015). Despite evidence that women are less likely to seek face-to-face treatment, when women do access psychosocial treatment, they may have better treatment outcomes than men (Green et al, 2009;Sugarman et al, 2017). Low treatment utilization among women is particularly concerning given a higher proportion of American women now meet criteria for AUD than ever before, with rates rising more rapidly in women than in men (Grant et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Gender Disparities in Alcohol Use Disorder Treatment Among Privately Insured Patients with Alcohol‐Associated Cirrhosis

Mellinger

Fernandez

Shedden

et al. 2019

Alcoholism Clin & Exp Res

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Background: The burden of alcohol-associated cirrhosis (AC) is high, and though alcohol cessation improves mortality, many patients fail to engage in alcohol use disorder (AUD) treatment and continue drinking. Our aim was to determine rates, predictors, and outcomes of AUD treatment utilization in AC patients with private insurance. Methods: We collected data from persons with AC (diagnosed by ICD-9/ICD-10 codes), aged 18 to 64 years, enrolled in the Truven MarketScan Commercial Claims and Encounters database (2009 to 2016). We determined rates and predictors of substance abuse treatment visits as well as rates of alcohol relapse prevention medication prescriptions, weighted to the national employer-sponsored insured population. Effects of AUD treatment utilization on decompensation rates were calculated using proportional hazards regression with propensity score adjustment. Results: A total of 66,053 AC patients were identified, 32% were female, and mean age at diagnosis was 54.5 years. About 72% had insurance coverage for substance abuse treatment. Overall, AUD treatment utilization rates were low, with only 10% receiving a face-to-face mental health or substance abuse visit and only 0.8% receiving a Food and Drug Administration (FDA)-approved relapse prevention medication within 1 year of index diagnosis. Women were less likely to receive a face-to-face visit (hazard ratio [HR] 0.84, p < 0.001) or an FDA-approved relapse prevention medication (0.89, p = 0.05) than men. AC patients who had a clinic visit for AUD treatment or used FDA-approved relapse medication showed decreased risk of decompensation at 1 year (HR 0.85, p < 0.001 for either). Conclusions: AUD treatment utilization is associated with lower decompensation rates among privately insured patients with AC. Women were less likely to utilize AUD treatment visits. Efforts to reduce gender-specific barriers to treatment are urgently needed to improve outcomes.

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Technology-Based Interventions for Substance Use and Comorbid Disorders: An Examination of the Emerging Literature

Cited by 34 publications

References 81 publications

Technology‐Delivered Cognitive‐Behavioral Interventions for Alcohol Use: A Meta‐Analysis

Technology‐Delivered Cognitive‐Behavioral Interventions for Alcohol Use: A Meta‐Analysis

Expanding the reach of alcohol and other drug services: Prevalence and correlates of US adult engagement with online technology to address substance problems

Gender Disparities in Alcohol Use Disorder Treatment Among Privately Insured Patients with Alcohol‐Associated Cirrhosis

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