Exploring drinking dynamics using interactive voice response technology

Neurocognitive models of alcohol use and mathematical models of drinking patterns suggest that levels of drinking on one day should affect probabilities of drinking on subsequent days. However, there has been no demonstration in the alcohol literature that these structured temporal dependencies appear in daily patterns of alcohol use. A model of daily drinking is presented that relates probabilities of drinking on any day to amounts consumed 1 day and 1 week before. It is assumed that positive and negative experiences with alcohol shape drinking levels and probabilities of subsequent drinking. The model predicts that nonmonotonic functions will relate drinking levels to subsequent drinking probabilities. Maxima of these functions represent optimal drinking levels that provide greatest positive returns from any drinking occasion for each drinker.

Interactive Voice Response technology was used to obtain annual time series of daily drinking levels from 33 drinkers sampled from public establishments in Vermont. Two predictions from the model were tested: (1) Temporal dependencies exist between the onset of drinking events over time; and (2) these dependencies are nonmonotonically related to prior drinking levels. Dynamics were separately assessed for each drinker using bootstrapped logistic regression models.

Thirty respondents provided data suitable for analysis. Time series data from five of these respondents exhibited no temporal dynamics (17%). Data from 25 respondents exhibited either daily or weekly dynamics (83%). Data from 18 respondents exhibited the expected nonmonotonic relationship between drinking levels and subsequent drinking events (60%).

Daily probabilities of drinking were conditional upon and nonmonotonically related to prior drinking levels among a majority of respondents. The results of the study support models of daily drinking in which positive and negative experiences with alcohol shape daily drinking patterns.