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.
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.
Authors: Ty A Ridenour; Andrea K Wittenborn; Bethany R Raiff; Neal Benedict; Sandra Kane-Gill Journal: Transl Behav Med Date: 2016-03 Impact factor: 3.046