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Alcohol hangover is a cause of considerable social and economic burden. Identification of predictors of alcohol hangover severity have the potential to contribute to reductions in costs associated with both absenteeism/presenteeism and health care. Pain catastrophising (PC) is the tendency to ruminate and describe a pain experience in more exaggerated terms. The current study examines the possibility that this cognitive coping strategy may influence experience of alcohol hangover. The aims of the current study were to (1) examine the relationship between hangover severity and PC, (2) explore and identify discreet factors within the Acute Hangover Scale (AHS) and (3) explore whether independent factors/dimensions of acute hangover are differentially predicted by PC. A retrospective survey (n = 86) was conducted in which participants completed the Acute Hangover Scale (AHS); the Pain Catastrophising Scale (PCS); a questionnaire pertaining to the amount of alcohol consumed; and a demographic information questionnaire. Regression analyses showed a significant relationship between PC and hangover severity scores and demonstrated that PC was, in fact, a stronger predictor of perceived hangover severity than estimated peak blood alcohol concentrations (eBACs). Factor analysis of the AHS scale, resulted in the identification of two distinct symptom dimensions; 'Headache and thirst', and 'Gastric and cardiovascular' symptoms. Regression analyses showed that both eBAC and PCS score were significantly associated with 'Headache and thirst'. However, only PCS score was associated with 'Gastric and cardiovascular' symptoms. These novel findings implicate a role for cognitive coping strategies in self-reports of alcohol hangover severity, and may have implications for understanding behavioural response to hangover, as well as suggesting that hangover and PC may be important factors mediating the motivation to drink and/or abuse alcohol, with potential implications in addiction research. Furthermore, these findings suggest that distinct alcohol hangover symptoms may be associated with different mechanisms underlying the experience of alcohol hangover. [ABSTRACT FROM AUTHOR]

Aims: Positive family history of alcohol use disorder (FHP), a variable associated with propensity for alcohol use disorder (AUD), has been linked with elevated hangover frequency and severity, after controlling for alcohol use. This implies that hangover experiences may be related to AUD. However, inadequate control of alcohol consumption levels, low alcohol dose and testing for hangover during the intoxication phase detract from these findings. Here, we present further data pertinent to understanding the relationship between family history and alcohol hangover. Methods: Study 1 compared past year hangover frequency in a survey of 24 FHP and 118 family history negative (FHN) individuals. Study 2 applied a quasi-experimental naturalistic approach assessing concurrent hangover severity in 17 FHP and 32 FHN individuals the morning after drinking alcohol. Both studies applied statistical control for alcohol consumption levels. Results: In Study 1, both FHP status and estimated blood alcohol concentration on the heaviest drinking evening of the past month predicted the frequency of hangover symptoms experienced over the previous 12 months. In Study 2, estimated blood alcohol concentration the previous evening predicted hangover severity but FHP status did not. Conclusions: FHP, indicating familial risk for AUD, was not associated with concurrent hangover severity but was associated with increased estimates of hangover frequency the previous year. [ABSTRACT FROM AUTHOR]

The effect of alcohol hangover on cognitive processing has received little attention. We explored the effect of alcohol hangover on choice response time (RT), a dominant dependent variable (DV) in cognitive research. Prior research of the effect of hangover on RT has produced mixed findings; all studies reviewed relied exclusively on estimates of central tendency (e.g. mean RT), which has limited information value. Here we present novel analytical methods by going beyond mean RT analysis. Specifically, we examined performance in hangover conditions (n=31) across the whole RT distribution by fitting ex-Gaussian models to participant data, providing a formal description of the RT distribution. This analysis showed detriments to performance under hangover conditions at the slower end of the RT distribution and increased RT variance under hangover conditions. We also fitted an explicit mathematical process model of choice RT - the diffusion model - which estimates parameters reflecting psychologically-meaningful processes underlying choice RT. This analysis showed that hangover reduced information processing efficiency during response selection, and increased response caution; changes in these parameters reflect hangover affecting core decisional-components of RT performance. The implications of the data as well as the methods used for hangover research are discussed. [ABSTRACT FROM AUTHOR]