Background There are disadvantages—largely related to cost, participant burden, and missing data—associated with traditional electronic methods of assessing drinking behavior in real time. This potentially diminishes some of the advantages—namely, enhanced sample size and diversity—typically attributed to these methods. Download of smartphone apps to participants’ own phones might preserve these advantages. However, to date, few researchers have detailed the process involved in developing custom-built apps for use in the experimental arena or explored methodological concerns regarding compliance and reactivity. Objective The aim of this study was to describe the process used to guide the development of a custom-built smartphone app designed to capture alcohol intake behavior in the healthy population. Methodological issues related to compliance with and reactivity to app study protocols were examined. Specifically, we sought to investigate whether hazard and nonhazard drinkers would be equally compliant. We also explored whether reactivity in the form of a decrease in drinking or reduced responding (“yes”) to drinking behavior would emerge as a function of hazard or nonhazard group status. Methods An iterative development process that included elements typical of agile software design guided the creation of the CNLab-A app. Healthy individuals used the app to record alcohol consumption behavior each day for 21 days. Submissions were either event- or notification-contingent. We considered the size and diversity of the sample, and assessed the data for evidence of app protocol compliance and reactivity as a function of hazard and nonhazard drinker status. Results CNLab-A yielded a large and diverse sample (N=671, mean age 23.12). On average, participants submitted data on 20.27 (SD 1.88) out of 21 days (96.5%, 20.27/21). Both hazard and nonhazard drinkers were highly compliant with app protocols. There were no differences between groups in terms of number of days of app use ( P =.49) or average number of app responses ( P =.54). Linear growth analyses revealed hazardous drinkers decreased their alcohol intake by 0.80 standard drinks over the 21-day experimental period. There was no change to the drinking of nonhazard individuals. Both hazard and nonhazard drinkers showed a slight decrease in responding (“yes”) to drinking behavior over the same period. Conclusions Smartphone apps participants download to their own phones are effective and methodologically sound means of obtaining alcohol consumption information for research purposes. Although further investigation is required, such apps might, in future, allow for a more thorough examination of the antecedents and consequences of drinking behavior.
Background:The alcohol consumption patterns of young adults are of concern.Critically, tertiary students consume greater quantities of alcohol, are at increased risk of injury/harm, and have higher rates of alcohol use disorders (AUD) as compared to their non-university enrolled peers. The Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ) is one of several tools utilised to explore adverse alcoholrelated outcomes among tertiary students. Alcohol intake behaviour, assessed via retrospective summary measures, has been linked to BYAACQ score. It is unclear, however, how drinking assessed in real-time, in conjunction with variables such as age of drinking onset, might predict severity of adverse alcohol consequences as captured by the BYAACQ. Methods:The psychometric properties of the BYAACQ were explored using a large Australian sample of tertiary students (N = 893). A subsample (n = 504) provided alcohol intake information in real-time (21 days; event-and notification-contingent) via a smartphone app (CNLab-A) plus details related to age of drinking onset, drug use, parental alcohol/drug use, and anxiety/depression symptomology.Results: Average BYAACQ score was 7.23 (SD = 5.47). Classical and item response theory analyses revealed inconsistencies related to dimensionality, progressive item severity, and male/female differential item functioning. Current drinking -namely, frequency of intake and quantity per drinking occasion -plus age of drinking onset predicted BYAACQ score after controlling for age, other drug use, and depression symptomology. Conclusions:The BYAACQ is a sound tool for use with Australian samples.Information related to current drinking, age of drinking onset, and drug use is useful for predicting severity of alcohol use consequences. These markers might enable tertiary institutions to better target students who could benefit from prevention/intervention programs.
Background: There are disadvantages -largely related to cost, participant burden,
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