Timing Personalized Feedback After Alcohol Health Education (TIME)

Heavy episodic alcohol use within the college student population is widespread, creating problems for student drinkers, their peers, and their institutions. Negative consequences from heavy alcohol use can be mild (e.g., hangovers, missed classes), to severe (e.g., assault, even death). Although online interventions targeting college student drinking reduce alcohol consumption and associated problems, they are not as effective as in-person interventions. Online interventions are cost-effective, offer privacy, reduce stigma, and may reach individuals who would otherwise not receive treatment. In a recently completed randomized, controlled trial, an emailed booster with personalized feedback improved the efficacy of a popular online intervention (Braitman & Henson, 2016). A second randomized, controlled trial confirmed efficacy for students of legal drinking age for a longer timeline (Braitman & Lau-Barraco, 2018). Although promising, the booster incorporated in the study needs further empirical refinement. The current project seeks to build on past progress by further developing and refining the booster. In particular, to identify the most efficacious timing for sending the feedback. The content will be similar across conditions, but will be disseminated at different times to identify the most impactful timeline. There will be 6 study conditions: those who receive the emailed feedback 2, 6, 10, or 14 weeks after baseline, or at all of those times, or not at all (control). Thus, the aim of the current study is to identify optimal timing for sending the tailored booster feedback via booster email.

The intervention is an online program, not an individual administering it, so masking is not necessary. Similarly, the same online survey is deployed in all follow-up assessments regardless of condition, and data are not collected by individuals, so masking of investigators is not necessary.

Participants navigate through e-checkup to go, the well-established alcohol intervention. Any follow-up emails sent to them later contain only a reminder to participate in follow-up surveys.

Participants navigate through e-checkup to go, the well-established alcohol intervention, then receive the feedback booster email 2 weeks later. It contains a reminder to participate in follow-up surveys, plus personalized feedback based on participant-reported perceived alcohol norms, actual alcohol norms, their own use, and harm reduction strategies.

Participants navigate through e-checkup to go, the well-established alcohol intervention, then receive the feedback booster email 6 weeks later. It contains a reminder to participate in follow-up surveys, plus personalized feedback based on participant-reported perceived alcohol norms, actual alcohol norms, their own use, and harm reduction strategies.

Participants navigate through e-checkup to go, the well-established alcohol intervention, then receive the feedback booster email 10 weeks later. It contains a reminder to participate in follow-up surveys, plus personalized feedback based on participant-reported perceived alcohol norms, actual alcohol norms, their own use, and harm reduction strategies.

Participants navigate through e-checkup to go, the well-established alcohol intervention, then receive the feedback booster email 14 weeks later. It contains a reminder to participate in follow-up surveys, plus personalized feedback based on participant-reported perceived alcohol norms, actual alcohol norms, their own use, and harm reduction strategies.

Participants navigate through e-checkup to go, the well-established alcohol intervention, then receive the multiple feedback booster emails, 2, 6, 10, and 14 weeks later. Each time, the email contains a reminder to participate in follow-up surveys, plus personalized feedback based on participant-reported perceived alcohol norms, actual alcohol norms, their own use, and harm reduction strategies.

The e-checkup to go alcohol program is designed to motivate individuals to reduce their alcohol consumption using personalized information about their own use and risk factors. The program is a combination of several components including alcohol education, personalized feedback, attitude-focused strategies, and skills training. It is self-guided and requires no face-to-face time with an administrator. It provides tailored feedback regarding quantity and frequency of alcohol use, normative comparisons, physical health information, amount and percent of income spent on alcohol, negative consequences feedback, explanation and advice for how to reach their goals, and resources.

Booster emails will contain normative feedback indicating average consumption for students at the same institution by sex, their perceptions of student drinkers at the same institution, their own reported consumption, and reminders of strategies they can use to protect themselves from alcohol-related harm.

Participant self-reported number of standard drinks consumed by participant over a typical week for the past 30 days.

Participant self-report on the Young Adult Alcohol Consequences Questionnaire (YAACQ; Read, Kahler, Strong, & Colder, 2006), which assesses alcohol-related problems experienced by the participant. Total scores are created by summing all individual items, and range from 0 to 48, with higher values representing more problems experienced (i.e., worse outcomes).

Inclusion Criteria: Current college students at the sponsor institution at the time of enrollment Between the ages of 18 and 24 Consumed at least standard drink of alcohol in the past 2 weeks Exclusion Criteria: Under age of 18 Over age of 24 Not a college student Did not drink alcohol in the past 2 weeks

Braitman AL, Lau-Barraco C. Personalized Boosters After a Computerized Intervention Targeting College Drinking: A Randomized Controlled Trial. Alcohol Clin Exp Res. 2018 Sep;42(9):1735-1747. doi: 10.1111/acer.13815. Epub 2018 Jul 11.

Braitman AL, Henson JM. Personalized boosters for a computerized intervention targeting college drinking: The influence of protective behavioral strategies. J Am Coll Health. 2016 Oct;64(7):509-19. doi: 10.1080/07448481.2016.1185725. Epub 2016 May 5.