An Integrated Approach to Addressing Addiction and Depression in College Students

Eisen, Arri; Kushner, Howard I.; McLeod, Mark; Queen, Edward L.; Gordon, Jonathan; Ford, Jesse

doi:10.3200/jach.57.4.455-456

Cited by 10 publications

(6 citation statements)

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“…Several studies assessed alcohol use in relation to specific events (eg, 21 st birthdays [44], homecomings, holidays, or pub nights [45]). A number of studies included measures of personal, social, sexual, or legal consequences of drinking [34,36,46,47], protective factors [45], alcohol-related knowledge [19,36], readiness to change [40,45,48], intention to seek help [48], drinking related self–efficacy [46], or outcome expectancies [36,46]. …”

Section: Resultsmentioning

confidence: 99%

“…Current Internet programs range from user-generated content applications such as Web logs/blogs, Web-based instant messaging technologies, or discussion boards (eg, AlcoholHelpCenter.net [17]), to interactive software applications. Even within interactive applications there is substantial variability, from brief normative feedback interventions [18] to multi-session modularized programs (eg, AlcoholEdu [19]) and psychotherapy substance mediation services involving a therapist [20,21]. Many of these program applications include brief intervention strategies and educational content based on a harm-reduction philosophy [22] and motivational interviewing techniques that are presented in a self-help workbook style [23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Online Alcohol Interventions: A Systematic Review

White¹,

Kavanagh²,

Stallman³

et al. 2010

J Med Internet Res

281

226

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Background There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely.Objectives Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention.Results The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to posttreatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66.Conclusions The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online Alcohol Interventions: A Systematic Review

White¹,

Kavanagh²,

Stallman³

et al. 2010

J Med Internet Res

281

226

View full text Add to dashboard Cite

show abstract

“…These findings generally support previous research in addiction, 11,47–49 although there is some evidence for a relationship between socioeconomic status and relapse in OD patients 11,50 . Given that most substance abuse treatment research has been conducted within publicly funded programs (eg, Department of Veterans Affairs health care system and specialty SAT programs) 43 or at university‐based substance abuse treatment units, 51,52 which likely differ from the current buprenorphine sample (recruited from private practice offices), future research may be needed to further investigate possible OD sample‐specific differences in relapse propensity. The emergence of a relapse profile may assist treatment providers in identifying high‐risk patients at treatment onset.…”

Section: Discussionmentioning

confidence: 99%

Compliance with Buprenorphine Medication‐Assisted Treatment and Relapse to Opioid Use

et al. 2011

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Opioid dependence (OD), often characterized as a chronic relapsing disorder, affects millions of people worldwide. The purpose of this study was to examine the effect of compliance with buprenorphine on reducing relapse among a sample of patients in treatment for OD. Patients new to buprenorphine (N = 703) completed the Addiction Severity Index (ASI) at baseline, and at 1, 2, and 3 months postbaseline. The ASI is a semistructured interview designed to measure problem severity in seven functional areas known to be affected by alcohol and drug dependence. Compliance was defined as taking buprenorphine medication on at least 22 of the past 28 days (80%), while relapse classification was based on resumed use of opioids during the follow-up period (months 2 and 3). Relapse was regressed onto demographic indicators, baseline ASI composite scores, and compliance with buprenorphine. Noncompliant patients were over 10 times more likely to relapse than those who were compliant (exp β= 10.55; p < .001). Neither demographics nor baseline ASI composite scores were predictive of relapse (p's > .05). Compliance with medication-assisted treatment supports abstinence, essential for patient recovery. Understanding the factors that drive treatment compliance and noncompliance may assist providers in supporting patient compliance and recovery.

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“…In response, more than 15,000 practitioners have become certified to provide buprenorphine medicationassisted treatment (B-MAT) in their offices. By contrast, most substance abuse treatment (SAT) research has been conducted within or through affiliations with publicly funded programs (e.g., Department of Veterans Affairs health care system and specialty SAT programs; Barnett, 2009) or at university-based SAT units that largely rely upon resident or recruited patients (Eisen et al, 2009;Harvard Mental Health Letter, 2009). Consistent with DATA 2000, SAT is increasingly becoming a recognized part of and integrated into behavioral and general health care.…”

Section: Introductionmentioning

confidence: 97%