AIMS:To determine the effect of an Interactive Voice Response (IVR) brief intervention (BI) to reduce alcohol consumption among adults seeking primary care.METHODS:Patients (N = 1855) with unhealthy drinking were recruited from eight academic internal medicine and family medicine clinics and randomized to IVR-BI (n = 938) versus No IVR-BI control (n = 917). Daily alcohol consumption was assessed at baseline, 3- and 6-months using the Timeline Followback.RESULTS:The IVR-BI was completed by 95% of the 938 patients randomized to that condition, and 62% of them indicated a willingness to consider a change in their drinking. Participants in both conditions significantly reduced consumption over time, but changes were not different between groups. Regardless of condition, participants with alcohol use disorder (AUD) showed significant decreases in drinking outcomes. No significant changes were observed in patients without AUD, regardless of condition.CONCLUSION:Although the IVR intervention was well accepted by patients, there was no evidence that IVR-BI was superior to No IVR-BI for reducing drinking in the subsequent 6 months. Because both the design and the intervention tested were novel, we cannot say definitively why this particular eHealth treatment lacked efficacy. It could be useful to evaluate the effect of the pre-randomization assessment alone on change in drinking. The high treatment engagement rate and successful implementation protocol are strengths, and can be adopted for future trials.SHORT SUMMARY:We examined the efficacy of a novel BI for patient self-administration by automated telephone. Alcohol consumption decreased over time but there were no between-group changes in consumption. Regardless of treatment condition, participants with alcohol use disorder (AUD) showed significant reduction in drinking but participants without AUD showed no change.

In primary care, collecting information about patient health behaviors between appointments can be advantageous. Physicians and researchers who embrace phone-based technology may find valuable ways to monitor patient-reported outcome measures of health (PROM). However, the level of phone technology sophistication should be tailored to the phone use of the population of interest. Despite the growing use of telephones as a means to gather PROM, little is known about phone use among primary care patients. As part of an ongoing study, the authors recruited primary care patients (N = 9126) for a health behavior screening study by calling them on the primary contact number listed in their medical record. The current study evaluated the frequency with which individuals were reached on landlines, basic cell phones, and smartphones, and examined participant characteristics. The majority of participants (63%) used landlines as their primary contact. Of the 37% using cell phones on the recruitment call, most (71%) were using smartphones. Landline users were significantly older than cell phone users (61.4 vs. 46.2 years; P = .001). Cell phone use did not differ significantly between participants with a college education and those without (37% vs. 38%; P = .82); however, smartphone use did differ (61% vs. 77%; P = .01). The majority of participants sampled used landlines as their primary telephone contact. Researchers designing phone-based PROM studies for primary care may have the broadest intervention reach using interactive voice response telephone technology, as patients could report health outcomes from any type of phone, including landlines. (Population Health Management 2016;19:212-215).

ObjectiveWeb-based brief alcohol intervention (WBI) programs have efficacy in a wide range of college students and have been widely disseminated to universities to address heavy alcohol use. In the majority of efficacy studies, web-based research assessments were conducted before the intervention. Web-based research assessments may elicit reactivity, which could inflate estimates of WBI efficacy. The current study tested whether web-based research assessments conducted in combination with a WBI had additive effects on alcohol use outcomes, compared to a WBI only.MethodsUndergraduate students (n=856) from universities in the United States and Canada participated in this online study. Eligible individuals were randomized to complete 1) research assessments+WBI or 2) WBI-only. Alcohol consumption, alcohol-related problems, and protective behaviors were assessed at one-month follow up.ResultsMultiple regression using 20 multiply imputed datasets indicated that there were no significant differences at follow up in alcohol use, alcohol-related problems, or protective behaviors used when controlling for variables with theoretical and statistical relevance. A repeated measures analysis of covariance revealed a significant decrease in peak estimated blood alcohol concentration in both groups, but no differential effects by randomized group. There were no significant moderating effects from gender, hazardous alcohol use, or motivation to change drinking.ConclusionsWeb-based research assessments combined with a web-based alcohol intervention did not inflate estimates of intervention efficacy when measured within-subjects. Our findings suggest universities may be observing intervention effects similar to those cited in efficacy studies, although effectiveness trials are needed.

Brief interventions for unhealthy drinking in primary care settings are efficacious, but underutilized. Efforts to improve rates of brief intervention though provider education and office systems redesign have had limited impact. Our novel brief intervention uses interactive voice response (IVR) to provide information and advice directly to unhealthy drinkers before a physician office visit, with the goals of stimulating in-office dialogue about drinking and decreasing unhealthy drinking. This automated approach is potentially scalable for wide application.We aimed to examine the effect of a pre-visit IVR-delivered brief alcohol intervention (IVR-BI) on patient-provider discussions of alcohol during the visit.This was a parallel group randomized controlled trial with two treatment arms: 1) IVR-BI or 2) usual care (no IVR-BI).In all, 1,567 patients were recruited from eight university medical center-affiliated internal medicine and family medicine clinics.IVR-BI is a brief alcohol intervention delivered by automated telephone. It has four components, based on the intervention steps outlined in the National Institute of Alcohol Abuse and Alcoholism guidelines for clinicians: 1) ask about alcohol use, 2) assess for alcohol use disorders, 3) advise patient to cut down or quit drinking, and 4) follow up at subsequent visits.Outcomes were patient reported: patient-provider discussion of alcohol during the visit; patient initiation of the discussion; and provider's recommendation about the patient's alcohol use.Patients randomized to IVR-BI were more likely to have reported discussing alcohol with their provider (52 % vs. 44 %, p = 0.003), bringing up the topic themselves (20 % vs. 12 %, p < 0.001), and receiving a recommendation (20 % vs. 14 %, p < 0.001). Other predictors of outcome included baseline consumption, education, age, and alcohol use disorder diagnosis.Providing automated brief interventions to patients prior to a primary care visit promotes discussion about unhealthy drinking and increases specific professional advice regarding changing drinking behavior.

Background: Screening of primary care patients for unhealthy behaviors and mental health issues is recommended by numerous governing bodies internationally, yet evidence suggests that provider-initiated screening is not routine practice. The objective of this study was to implement systematic pre-screening of primary care patients for common preventive health issues on a large scale.Methods: Patients registered for non-acute visits to one of 40 primary care providers from eight clinics in an Academic Medical Center health care network in the United States from May, 2012 to May, 2014 were contacted one-to three-days prior to their visit. Patients were invited to complete a questionnaire using an Interactive Voice Response (IVR) system. Six items assessed pain, smoking, alcohol use, physical activity, concern about weight, and mood.Results: The acceptance rate among eligible patients reached by phone was 65.6 %, of which 95.5 % completed the IVR-Screen (N = 8,490; mean age 57; 57 % female). Sample demographics were representative of the overall primary care population from which participants were drawn on gender, race, and insurance status, but participants were slightly older and more likely to be married. Eighty-seven percent of patients screened positive on at least one item, and 59 % endorsed multiple problems. The majority of respondents (64.2 %) reported being never or only somewhat physically active. Weight concern was reported by 43.9 % of respondents, 36.4 % met criteria for unhealthy alcohol use, 23.4 % reported current pain, 19.6 % reported low mood, and 9.4 % reported smoking.Conclusions: The percent endorsement for each behavioral health concern was generally consistent with studies of screening using other methods, and contrasts starkly with the reported low rates of screening and intervention for such concerns in typical PC practice. Results support the feasibility of IVR-based, large-scale pre-appointment behavioral health/lifestyle risk factor screening of primary care patients. Pre-screening in this population facilitated participation in a controlled trial of brief treatment for unhealthy drinking, and also could be valuable clinically because it allows for case identification and management during routine care.

Background:Alcohol brief intervention (BI) in primary care (PC) is effective, but remains underutilized despite multiple efforts to increase provider-initiated BI. An alternative approach to promote BI is to prompt patients to initiate alcohol-related discussions. Little is known about the role of patients in BI delivery. Objectives:To determine the characteristics of PC patients who reported initiating BI with their providers, and to evaluate the association between the initiator (patient vs provider) and drinking after a BI. Methods:In the context of clinical trial, patients (n = 267) who received BI during a PC visit reported on the manner in which the BI was initiated, readiness to change, demographics, and recent history of alcohol consumption. Drinking was assessed again at 6-months after the BI. Results:Fifty percent of patients receiving a BI reported initiating the discussion of drinking themselves. Compared with those who reported a provider-initiated discussion, self-initiators were significantly younger (43.7 years vs 47.1 years; P = 0.03), more likely to meet Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria for current major depression (24% vs 14%; P = 0.04), and more likely to report a history of alcohol withdrawal symptoms (68% vs 52%; P < 0.01). Baseline readiness to change, baseline consumption rates, and current DSM-IV alcohol dependence were not different between groups. In the 2 to 3 weeks after BI, self-initiators reported greater decreases in drinks per week (5.7 vs 2.4; P = 0.02), and drinking days per week (1.0 vs 0.3; P = 0.002). At 6-month follow-up, self-initiators showed significantly greater reductions in weekly drinking compared to those whose provider initiated the BI (P = 0.002). Conclusions:Patient- and provider-initiated BI occurred with equal frequency, and patient-initiated BIs were associated with greater reductions in alcohol use. Future efforts to increase the BI rate in PC should include a focus on prompting patients to initiate alcohol-related discussions.

OBJECTIVERecruiting young adults for health research is challenging. Social media provides wide access to potential research participants. We evaluated the feasibility of recruiting students via free message postings on Facebook and Twitter to participate in a web-based brief intervention study. The sample comprised students attending U.S. and Canadian universities.METHODDuring three semesters, institutional review board-approved recruitment messages were posted in 281 Facebook groups, 7 Facebook pages, and 27 message "tweets" on Twitter.RESULTSA total of 708 eligible participants were recruited from Facebook. The mean enrollment rate per Facebook group was 0.21%; the rate was higher for host university groups (1.56%) compared with groups at other universities (0.10%). We recruited seven participants from Twitter. The sample was predominantly female (70%) with a mean age of 20.0 years. There were no significant differences between host university participants recruited through social media and traditional methods. The web-based intervention completion rate was 65%, and participants from the host university were more likely to complete the intervention than were groups at other universities (p = .01).CONCLUSIONSSocial media provides access to a large number of potential participants, and social media recruitment may be useful to researchers who can harness this broad reach. Facebook recruitment was feasible and free and resulted in a large number of enrolled participants. Social media recruitment for researchers at their own universities may be particularly fruitful. Despite wide access to students with Twitter, recruitment was slow. Social media recruitment allowed us to extend web-based intervention access to students in the United States and Canada.

Aims: The goal of this study was to better understand the predictive relationship in both directions between negative (anger, sadness) and positive (happiness) moods and alcohol consumption using daily process data among heavy drinkers. Methods: Longitudinal daily reports of moods, alcohol use and other covariates such as level of stress were assessed over 180 days using interactive voice response telephone technology. Participants were heavy drinkers (majority meeting criteria for alcohol dependence at baseline) recruited through their primary care provider. The sample included 246 (166 men, 80 women) mostly Caucasian adults. Longitudinal statistical models were used to explore the varying associations between number of alcoholic drinks and mood scores the next day and vice versa with gender as a moderator. Results: Increased alcohol use significantly predicted decreased happiness the next day (P < 0.005), more strongly for females than males. Increased anger predicted higher average alcohol use the next day for males only (P < 0.005). Conclusion: This daily process study challenges the notion that alcohol use enhances positive mood for both males and females. Our findings also suggest a strong association between anger and alcohol use that is specific to males. Thus, discussions about the effects of drinking on one's feeling of happiness may be beneficial for males and females as well as anger interventions may be especially beneficial for heavy-drinking males.

BACKGROUND:Relapse rates following cognitive behavioral therapy (CBT) for alcohol dependence are high. Continuing care programs can prolong therapeutic effects but are underutilized. Thus, there is need to explore options having greater accessibility.METHODS:This randomized controlled trial tested the efficacy of a novel, fully automated continuing care program, Alcohol Therapeutic Interactive Voice Response (ATIVR). ATIVR enables daily monitoring of alcohol consumption and associated variables, offers targeted feedback, and facilitates use of coping skills. Upon completing 12weeks of group CBT for alcohol dependence, participants were randomly assigned to either four months of ATIVR (n=81) or usual care (n=77). Drinking behavior was assessed pre- and post-CBT, then at 2weeks, 2months, 4months, and 12months post-randomization.RESULTS:Drinking days per week increased over time for the control group but not the intervention group. There were no significant differences between groups on the other alcohol-related outcome measures. Comparisons on the subset of participants abstinent at the end of CBT (n=72) showed higher rates of continuous abstinence in the experimental group. Effect sizes for the other outcome variables were moderate but not significant in this subgroup.CONCLUSIONS:For continuing care, ATIVR shows some promise as a tool that may help clients maintain gains achieved during outpatient treatment. However, ATIVR may not be adequate for clients who have not achieved treatment goals at the time of discharge.

Background: The DSM specifies categorical criteria for psychiatric disorders. In contrast, a dimensional approach considers variability in symptom severity and can significantly improve statistical power. The current study tested whether a categorical, DSM-defined diagnosis of Alcohol Dependence (AD) was a better fit than a dimensional dependence measure for predicting change in alcohol consumption among heavy drinkers following a brief alcohol intervention (BI). DSM-IV and DSM-5 alcohol use disorder (AUD) measures were also evaluated.Methods: Participants (N = 246) underwent a diagnostic interview after receiving a BI, then reported daily alcohol consumption using an Interactive Voice Response system. Dimensional AD was calculated by summing the dependence criteria (mean = 4.0; SD = 1.8). The dimensional AUD measure was a summation of positive Alcohol Abuse plus AD criteria (mean = 5.8; SD = 2.5). A multi-model inference technique was used to determine whether the DSM-IV categorical diagnosis or dimensional approach would provide a more accurate prediction of first week consumption and change in weekly alcohol consumption following a BI.Results: The Akaike information criterion (AIC) for the dimensional AD model (AIC = 7625.09) was 3.42 points lower than the categorical model (AIC = 7628.51) and weight of evidence calculations indicated there was 85% likelihood that the dimensional model was the better approximating model. Dimensional AUD models fit similarly to the dimensional AD model. All AUD models significantly predicted change in alcohol consumption (p's = .05).Conclusion: A dimensional AUD diagnosis was superior for detecting treatment effects that were not apparent with categorical and dimensional AD models. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

Introduction: This study provides a prospective fine-grain description of the incidence and pattern of intentions to quit, quit attempts, abstinence, and reduction in order to address several clinical questions about self-quitting.Methods: A total of 152 smokers who planned to quit in the next 3 months called nightly for 12 weeks to an Interactive Voice Response system to report cigarettes/day, quit attempts, intentions to smoke or not in the next day, and so forth. No treatment was provided.Results: Most smokers (60%) made multiple transitions among smoking, reduction, and abstinence. Intention to not smoke or quit often did not result in a quit attempt but were still strong predictors of a quit attempt and eventual abstinence. Most quit attempts (79%) lasted less than 1 day; about one fifth (18%) of the participants were abstinent at 12 weeks. The majority of quit attempts (72%) were not preceded by an intention to quit. Such quit attempts were shorter than quit attempts preceded by an intention to quit (<1 day vs. 25 days). Most smokers (67%) used a treatment, and use of a treatment was nonsignificantly associated with greater abstinence (14 days vs. 3 days). Making a quit attempt and failing early predicted an increased probability of a later quit attempt compared to not making a quit attempt early (86% vs. 67%). Smokers often (17%) failed to report brief quit attempts on an end-of-study survey.Conclusions: Cessation is a more chronic, complex, and dynamic process than many theories or treatments assume.

Background: Most of the harm from marijuana use is experienced by daily users. Despite this, there has not been a detailed prospective description of daily marijuana use.Methods: We recruited daily marijuana users (n = 142) by intemet ads, Craigslist, flyers, etc. Participants were mostly women (58%) with a mean age of 33 and 47% were minorities. Participants called an Interactive Voice Response phone system to report marijuana and other drug use daily for 3 months.Results: Participants averaged using marijuana 32 times per day. Almost all participants used multiple modes of delivery during the study. Bongs/vaporizers/pipes were the most common mode of use (45% of uses). Day-to-day variability in amount of use was relatively small. The median rating of intoxication was 3.8 on a 0-6 scale with no intoxication reported on 1% of days and severe intoxication on 24% of days. The large majority binge drank (71%) or used tobacco (73%). Fifteen during-study variables were associated with the frequency of marijuana use; running out of marijuana and social setting were the strongest correlates. Retrospective reports of "usual" use at study entry were often significantly different than daily reports of use during the study.Conclusions: This is the first detailed prospective description of daily marijuana use. Most users used multiple times/day, used multiple modes to administer marijuana, were often intoxicated, and under-reported high rates of using alcohol and tobacco. The frequency of marijuana use was especially influenced by social factors. These results will help future studies better describe daily marijuana use. (C) 2014 Elsevier Ltd. All rights reserved.

Background: For the DSM-5-defined alcohol use disorder (AUD) diagnosis, a tri-categorized scale that designates mild, moderate, and severe AUD was selected over a fully dimensional scale to represent AUD severity. The purpose of this study was to test whether the DSM-5-defined AUD severity measure was as proficient a predictor of alcohol use following a brief intervention, compared to a fully dimensional scale.Methods: Heavy drinking primary care patients (N = 246) received a physician-delivered brief intervention (BI), and then reported daily alcohol consumption for six months using an Interactive Voice Response (IVR) system. The dimensional AUD measure we constructed was a summation of all AUD criteria met at baseline (mean = 6.5; SD = 2.5). A multi-model inference technique was used to determine whether the DSM-5 tri-categorized severity measure or a dimensional approach would provide a more precise prediction of change in weekly alcohol consumption following a BI.Results: The Akaike information criterion (AIC) for the dimensional AUD model (AIC= 7623.88) was four points lower than the tri-categorized model (AIC = 7627.88) and weight of evidence calculations indicated there was 88% likelihood the dimensional model was the better approximating model. The dimensional model significantly predicted change in alcohol consumption (p =.04) whereas the DSM-5 tri-categorized model did not.Conclusion: A dimensional AUD measure was superior, detecting treatment effects that were not apparent with tri-categorized severity model as defined by the DSM-5. We recommend using a dimensional measure for determining AUD severity. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

AIMS:We present methodology to identify statistically distinct patterns of daily alcohol use and classify them into categories that could be further used in monitoring of transitions between patterns such as transitions from regular to problem use. DATA:The study analyzed individual patterns of adult alcohol consumption from two datasets containing short (<6 month) and long (up to 2years) daily records of drinking. These data were collected over the period between 1999 and 2003. RESULTS:By using a non-parametric (Kolmogorov-Smirnov) test we have identified distinct drinking patterns and classified them into 8 types according to their means, percentages of non-drinking days and variances of consumed amount during drinking days. For each studied individual we calculated a transition chart that characterizes transitions between the types. CONCLUSIONS:Individual daily consumption patterns can be identified, and classified into distinct patterns. Changes between the patterns could be related to life events or environmental trends, and thus provide insights into pathways towards either heavier use or recovery.

Objective Recently, there has been a gradual shift from inpatient-only electroconvulsive therapy (ECT) toward outpatient administration. Potential advantages include convenience and reduced cost. But providers do not have the same opportunity to monitor treatment response and adverse effects as they do with inpatients. This can obviate some of the potential advantages of outpatient ECT, such as tailoring treatment intervals to clinical response. Scheduling is typically algorithmic rather than empirically based. Daily monitoring through an automated telephone, interactive voice response (IVR), is a potential solution to this quandary. Methods To test feasibility of clinical monitoring via IVR, we recruited 26 patients (69% female; mean age, 51 years) receiving outpatient ECT to make daily IVR reports of affective symptoms and subjective memory for 60 days. The IVR also administered a word recognition task daily to test objective memory. Every seventh day, a longer IVR weekly interview included questions about suicidal ideation. Results Overall daily call compliance was high (mean, 80%). Most participants (96%) did not consider the calls to be time-consuming. Longitudinal regression analysis using generalized estimating equations revealed that participant objective memory functioning significantly improved during the study (P < 0.05). Of 123 weekly IVR interviews, 41 reports (33%) in 14 patients endorsed suicidal ideation during the previous week. Conclusions Interactive voice response monitoring of outpatient ECT can provide more detailed clinical information than standard outpatient ECT assessment. Interactive voice response data offer providers a comprehensive, longitudinal picture of patient treatment response and adverse effects as a basis for treatment scheduling and ongoing clinical management.

AIMS:In HIV-infected individuals, heavy drinking compromises survival. In HIV primary care, the efficacy of brief motivational interviewing (MI) to reduce drinking is unknown, alcohol-dependent patients may need greater intervention and resources are limited. Using interactive voice response (IVR) technology, HealthCall was designed to enhance MI via daily patient self-monitoring calls to an automated telephone system with personalized feedback. We tested the efficacy of MI-only and MI+HealthCall for drinking reduction among HIV primary care patients.DESIGN:Parallel random assignment to control (n = 88), MI-only (n = 82) or MI+HealthCall (n = 88). Counselors provided advice/education (control) or MI (MI-only or MI+HealthCall) at baseline. At 30 and 60 days (end-of-treatment), counselors briefly discussed drinking with patients, using HealthCall graphs with MI+HealthCall patients.SETTING:Large urban HIV primary care clinic.PARTICIPANTS:Patients consuming ≥4 drinks at least once in prior 30 days.MEASUREMENTS:Using time-line follow-back, primary outcome was number of drinks per drinking day, last 30 days.FINDINGS:End-of-treatment number of drinks per drinking day (NumDD) means were 4.75, 3.94 and 3.58 in control, MI-only and MI+HealthCall, respectively (overall model χ(2) , d.f. = 9.11,2, P = 0.01). For contrasts of NumDD, P = 0.01 for MI+HealthCall versus control; P = 0.07 for MI-only versus control; and P = 0.24 for MI+HealthCall versus MI-only. Secondary analysis indicated no intervention effects on NumDD among non-alcohol-dependent patients. However, for contrasts of NumDD among alcohol-dependent patients, P < 0.01 for MI+HealthCall versus control; P = 0.09 for MI-only versus control; and P = 0.03 for MI+HealthCall versus MI-only. By 12-month follow-up, although NumDD remained lower among alcohol-dependent patients in MI+HealthCall than others, effects were no longer significant.CONCLUSIONS:For alcohol-dependent HIV patients, enhancing MI with HealthCall may offer additional benefit, without extensive additional staff involvement.