Reporting errors on combined use of caffeine and alcohol questions in a qualitative questionnaire

s / Drug and Alcohol Dependence 156 (2015) e102–e182 e179 Reporting errors on combined use of caffeine and alcohol questions in a qualitative questionnaire Kathryn M. Polak2, Dace Svikis1, Linda Hancock2, David Pomm2 1 Virginia Commonwealth University, Richmond, VA, United States 2 Psychology, Virginia Commonwealth University, Henrico, VA, United States Aims: The increasing prevalence of combined caffeine and alcohol drink (CAD) consumption is concerning. Those using CADs are more likely to report alcohol dependence, marijuana use, and risktaking behavior compared to those who report comparable alcohol consumptionwithout caffeine (Arria et al., 2010, 2011). Thepresent exploratory study investigated the extent to which reports of CAD use are accurate. Methods: Participants (N=111) were undergraduate students in a Biology 101 class attending a central Virginia university. Students completed a paper-and-pencil survey with questions examining CAD use and side effects of caffeine. Qualitative responses were coded based on a grounded approach. The present study focused on the three survey items addressing CAD use. Results: From the total number of responses (excluding N/A), 51.00% included reporting errors. Out of the entire sample, 15.32% of participants reported CADs that listed a non-caffeinated mixer in their response to at least one of the questions. Out of the participants that responded to at least one of the three questions (excluding N/A), 17.89% responded with a non-caffeinated mixer. From the total number of responses, 8.03% contained noncaffeinated mixer errors. Conclusions: Findings show a high rate of reporting errors, which is a potential barrier to the accurate assessment of CAD use. The high rate of misreporting non-caffeinated mixers could suggest there is a general lack of knowledge about what contains caffeine. Further study is warranted to investigate if these errors significantly impact survey reporting. Financial support: Not applicable. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.485 Predictors of HIV risk among ex-offenders entering sober living recovery residences for drug problems Douglas L. Polcin1, Tooru Nemoto2, Rachael Korcha1, Amy Mericle1, Elizabeth Mahoney1 1 Alcohol Research Group, Emeryville, CA, United States 2 Public Health Institute, Oakland, CA, United States Aims: 1. Describe demographic characteristics, HIV risk factors, and past 12-month drug and alcohol dependence among probationers and parolees entering sober living houses (SLHs). 2. Assess the extent to which unstable housing prior to entering the SLH and other factors predicts HIV risk. 3. Assess rates of HIV testing over the past 6 months. Methods:Using data froman ongoing study of SLHs for parolees and probationers in Los Angeles, we examined HIV risk among 108 participants within the first month of entering a SLH. Study instruments included a measure of demographic characteristics, the DSM-IV checklist for alcohol and drug dependence, and the Risk Assessment Battery for HIV. Logistic regressionwas used to predict HIV risk. Results: Sample characteristics included 76% male, 39% white, 28%AfricanAmerican, and 19%Hispanic. Twenty percentwas selfidentified as LGBT. The most common drug dependencies were methamphetamine (58%) andalcohol (37%).HIV riskbehaviorsduring the 6 months prior to the interview were high: 23% reported injection drug use, 17% shared needles, 32% had sex with 2 or more partners and 47% of those having sex never used condoms. However, only 61% had been tested for HIV during the past 6 months. Unstable housing prior to entering the SLHwas a significant predictor of injection drug use (OR=3.2, CI = 1.3–8.1, p< .05), number of sexual partners (OR=2.8, CI = 1.3–5.9, p< .01) and trading or buying sex for drugs (OR=2.9, CI = 1.1–7.9, p< .05). Other predictors of risk included 6-month measures of alcohol and drug use. Conclusions: Results highlight the need for increased HIV testing for parolees and probationers entering sober living recovery houses. Findings also document the important role of stable housing for preventing HIV risk among this population. Expanding the availability of SLHs for ex-offenders could play an important role in meeting thee housing needs. Future analyseswill examine changes in risk behaviors and HIV testing over 12 months. Financial support: DA034973. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.486 Predictors of caffeine-withdrawal headache in college students David Pomm2, Dace Svikis1, Kathryn M. Polak2, Danielle Dick2, Kenneth S. Kendler1 1 Virginia Commonwealth University, Richmond, VA, United States 2 Psychology, Virginia Commonwealth University, Henrico, VA, United States Aims:Thepurposeof this studywas to examinewhether reports of caffeine-withdrawal headache varied by gender, daily caffeine use, alcohol use, and nicotine use in a sample of college freshmen. We hypothesized that gender, daily caffeine use, current alcohol use, and current cigarette use would predict caffeine-withdrawal headache. Methods: Participants were N=1958 freshmen (age 18 and older)who completed anon-line research survey (Spit for Science*) and reported recent caffeine use. The present study focused on survey demographic items, type(s) of caffeinated beverages consumed (coffee, tea, sodas, energy drinks (e-drinks) and occurrence of caffeine withdrawal symptoms (e.g., headache, fatigue, anxiety, depression, and/or nausea after stopping all caffeine for a day or more). Descriptive statistics were used to characterize caffeine use and occurrence of caffeine withdrawal. Logistic regression analysis was used to assess whether gender, daily caffeine use, and current alcohol and nicotine use predicted participant report of caffeinewithdrawal headache. Results: One-fifth (20.6%) of current caffeine users reported 1+ symptoms of withdrawal, with headaches most prevalent (15.6%). A test of the full model against a constant-only model was significant, c2(4, N=423) =17.24, p= .002, indicating that as a set, the predictors reliably distinguished between those with and without caffeine-withdrawal headache. According to Wald tests, only gender (c2(1) =9.21, p= .002) and nicotine use (c2(1) =7.80, p= .005) reliably predicted caffeine-withdrawal headache. Conclusions: Not as predicted, gender and current nicotine use significantly predicted caffeine-withdrawal headache, while current alcohol use and daily caffeine use did not. Financial support: NIH R37 AA011408* and RO1 DA026091. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.487