- Email: [email protected]
Habit predicts in-the-moment alcohol consumption
Addictive Behaviors 41 (2015) 78–80
Contents lists available at ScienceDirect
Addictive Behaviors
Short Communication
Habit predicts in-the-moment alcohol consumption Ian P. Albery, Isabelle Collins, Antony C. Moss, Daniel Frings, Marcantonio M. Spada ⁎ Department of Psychology, London South Bank University, UK
H I G H L I G H T S • First study to link habit to objective measures of alcohol consumption. • Habit predicts behavioral enacetment of alcohol consumption. • Suggestions for targeting habit in the treatment of alcohol problems are presented.
a r t i c l e
i n f o
Available online 26 September 2014 Keywords: Dual process model Habit In-the-moment alcohol consumption Metacognitive monitoring Positive alcohol expectancies Proportion of alcohol consumed
a b s t r a c t Aim: The objective of this study was to examine whether habit predicts in-the-moment behavioural intention (amount of alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed) controlling for craving and positive alcohol expectancies. Method: Forty-six college students, who defined themselves as social drinkers, were tested individually in a laboratory setting. After completing a measure of craving they were given a bottle of non-alcoholic beer and a cup, asked to pour a drink, and then drink as much as they liked. They were not informed that the beer was non-alcoholic. They were subsequently asked to complete measures of alcohol use and misuse, positive alcohol expectancies and habit. Results: Positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured and the amount and proportion of alcohol consumed. Habit was positively and significantly associated with the amount and proportion of alcohol consumed but not with the amount of alcohol poured. Hierarchical regression analyses revealed that only habit was a significant predictor of both the amount and proportion of alcohol consumed. Even though measures of intention (amount of alcohol poured) and behaviour (amount and proportion of alcohol consumed) were positively correlated, habit was shown to effectively discriminate between these measures. Conclusions: These findings suggest that habit predicts in-the-moment behavioural enactment in terms of the amount and proportion of alcohol consumed. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Changing unhelpful drinking patterns relies on identifying and modifying determinants of action. Traditionally, approaches to behaviour change have been based on reasoned action models, which portray behaviour as the outcome of conscious intention in the form of, for example, attitudes, beliefs and self-efficacy (Armitage & Conner, 2001). Explaining repeated actions, however, requires the consideration of determinants of behaviour beyond consciously experienced intentions especially in view of the fact that findings appear to indicate that intention has a small-sized effect in predicting ongoing behaviour (Webb & Sheeran, 2006). Dual-process models (e.g. Moss & Albery, 2009; Strack & Deutsch, 2004; Wiers, Houben, Roefs, de Jong, & Stacy, 2010) may offer a valuable framework for tackling the difficulties of the ‘intention–behaviour’ gap ⁎ Corresponding author. Tel.: +44 20 7815 5760. E-mail address: [email protected] (M.M. Spada).
http://dx.doi.org/10.1016/j.addbeh.2014.09.025 0306-4603/© 2014 Elsevier Ltd. All rights reserved.
(see Sheeran, Gollwitzer, & Bargh, 2013). These models propose that behaviour results from both a ‘reflective’ pathway, which involves effortful forethought, and an ‘impulsive’ pathway, characterized by immediate stimulus–response relationships mediated by the activation of associative knowledge. From this standpoint, repetition can initially lead reasoned actions to become impulsive through the formation of ‘habits’, which are automatic behavioural responses to contextual cues, acquired through context-dependent repetition (see Ouellette & Wood, 1998; Verplanken & Aarts, 1999). Repeated performance, in stable settings, strengthens habits (Lally, van Jaarsveld, Potts, & Wardle, 2010; Lally, Wardle, & Gardner, 2011; Neal, Wood, & Quinn, 2006). It has been argued that habit reflects an automated mode of response which is reflected in core features such as lack of awareness, control and conscious intent, and mental efficiency (e.g., Wood & Neal, 2007). The Self-Report Habit Index (SRHI) was developed as a unidimensional measure of habit strength along these lines, by measuring the degree to which a target behaviour occurs frequently, requires
I.P. Albery et al. / Addictive Behaviors 41 (2015) 78–80
conscious awareness, thought and effort, is difficult to control, and is relevant in terms of personal identity (Verplanken and Orbell, 2003). Among others, choices made around food (e.g., De Bruijn, 2010; De Bruijn et al., 2007), physical exercise (Rhodes, De Bruijn, & Matheson, 2010), and self-reported alcohol consumption (Gardner, De Bruijn, & Lally, 2012) have been shown to have a habitual component. A recent meta-analysis (in nutritional/physical exercise) also showed a medium to strong relationship between habit (i.e. SRHI) and behaviour. The SRHI has also been found to moderate the effect of intended behaviour on behavioural enactment (see Gardner, de Bruijn, & Lally, 2011). A weakness of the evidence presented is that it is predominantly limited to retrospective reports using correlational designs. For example, Gardner et al. (2012) used self-reported drinking in the past week whilst prospectively predicting binge drinking from initial habit. The current study attempts to address this limitation by measuring in-the-moment alcohol consumption, planning and enactment and investigating whether habit predicts the proportion of alcohol consumed (an objective behavioural outcome measure) controlling for craving and positive alcohol expectancies (Christiansen, Smith, Roehling, & Goldman, 1989). One way of measuring in-the-moment drinking is to use a Taste Preference Task (TPT) (Morrison, Noel, & Ogle, 2012). In a TPT participants are given a number of alcohol placebos and soft drinks to taste and rate on a number of dimensions (e.g., quality, taste, and colour). Consumption is calculated as the amount drunk from a predefined known quantity. In this study we asked participants to pour their own measure (from a known quantity) to consume. This represents a measure of both behavioural intention (amount of alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed).
79
comprising 12 items assessing perceived habitual or automatic dimensions of behaviour. Following completion of the study all participants were debriefed. 3. Results An inspection of histograms, skewness and kurtosis showed that several variables were not normally distributed. One-tailed Spearman rho correlation analyses showed that positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed. Habit was found to be positively and significantly associated with the amount and proportion of alcohol consumed and not the amount of alcohol poured. No significant associations between age, self-reported alcohol use, and craving, on the one hand, and the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed were observed. The amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed were all positively and significantly correlated (see Table 1). To evaluate the contribution of habit beyond that accounted for by positive alcohol expectancies, hierarchical regression analyses were run with the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed as criterion variables. Positive alcohol expectancies were entered in step 1 and habit was entered in step 2 (see Table 2). Together habit and positive alcohol expectancies were shown to significantly predict the amount of alcohol consumed 2 [F (2, 43) = 5.38, p b .001 (R2 = .20, R = .16)] and proportion of alco2 hol consumed [F (2, 43) = 5.92, p b .01 (R2 = .22, R = .18)] but not the 2 amount of alcohol poured [F (2, 43) = 2.23, p = .12 (R2 = .09, R = .05)]. An inspection of the final equations revealed that habit significantly increased the variance explained in the amount of alcohol consumed [FΔ (1, 43) = 4.58, p b 0.05 (R2 = .16, R2Δ = .09, B = .31)] and proportion of alcohol consumed [FΔ (1, 43) = 7.39, p b 0.01 (R2 = .22, R2Δ = .14, B = .39)] over and above the variance accounted for by positive alcohol expectancies (see Table 2).
2. Method 2.1. Participants The sample consisted of 46 college students who reported being social drinkers (38 females and 8 males, mean age = 24.7 years, sd = 7.9, range = 18–53; mean AUDIT-C = 5.5, sd = 2.3, range = 1–12).
4. Discussion 2.2. Materials and procedure This study sought to examine whether habit predicts in-the-moment amount of alcohol poured, and the amount and proportion of alcohol consumed controlling for craving and positive alcohol expectancies. A focus on how much an individual pours to drink, and the actual amount they drink, allows us to distinguish between one's intention and the enactment of this behavioural intention. Importantly, however, these measures are both behavioural in nature and as such provide evidence as indirect measures. Correlational analyses showed dissociation between positive alcohol expectancies and habit, with the amount of alcohol poured (behavioural intention) and the amount and proportion of alcohol consumed (behavioural enactment). Positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured, and the amount and proportion of alcohol consumed. Habit was positively and significantly associated with the amount of alcohol consumed and
Ethics approval for the study was obtained from a UK University. Once briefed and consent achieved participants completed the Penn Alcohol Craving Scale (PACS; Flannery, Volpicelli, & Pettinati, 1999) which measures duration, frequency and intensity of craving. They were then given a bottle of non-alcoholic beer and a cup, and asked to pour themselves a drink (behavioural intention) and drink as much as they liked (behavioural enactment). Participants were not informed that the beer was non-alcoholic. They were then asked to complete the Alcohol Use Disorder Identification Test Consumption (AUDIT-C; Bush, Kivlahan, McDonell, Fihn, & Bradley, 1998) which comprises three items assessing quantity and frequency of alcohol use, the Alcohol Outcome Expectancies Scale (AOES; Leigh & Stacy, 1993) measuring social facilitation, fun, sex, and tension reduction and the SRHI (Verplanken & Orbell, 2003) Table 1 Descriptive statistics and Spearman's rho correlations coefficients (one tailed).
Age AUDIT-C PACS AOEQ positive SHRI Amount of alcohol poured (ml) Amount of alcohol consumed (ml) Proportion of alcohol consumed (%) ⁎ p b .05. ⁎⁎ p b .001.
Mean
SD
Range
AUDIT-C
PACS
AOEQ positive
SRHI
Amount of alcohol poured (ml)
Amount of alcohol consumed (ml)
Proportion of alcohol consumed (%)
24.7 5.5 7.2 81.0 30.4 52.2 34.9 60.9
7.9 2.3 4.3 9.1 7.5 36.8 37.9 30.4
18–53 1–12 0–23 64–100 13–49 7–175 2–146 7.4–98.7
−.04 –
−.11 .36⁎⁎
−.01 .32⁎⁎ .27⁎
.17 .41⁎⁎ .35⁎⁎ .36⁎⁎
.01 .06 .21 .25⁎ .19 –
.09 .05 .02 .27⁎ .32⁎ .73⁎⁎ –
.07 .09 −.10 .26⁎ .45⁎⁎ .28⁎ .74⁎⁎
–
–
–
–
80
I.P. Albery et al. / Addictive Behaviors 41 (2015) 78–80
Table 2 Hierarchical multiple linear regression statistics with the amount of alcohol poured and consumed and proportion of alcohol consumed as criterion variables and positive alcohol expectancies and habit as predictor variables.
Step 1 AOEQ positive
Step 2 AOEQ positive SRHI
Amount of alcohol poured (ml)
Amount of alcohol consumed (ml)
Proportion of alcohol consumed (%)
β
p
β
p
β
.25 1.67 R2 = 0.06
.10
0.34 2.39 R2 = 0.12
0.02
0.29 1.97 R2 = 0.08
0.05
.18 1.19 .19 1.26 R2 = 0.09
.24 .22
0.24 1.63 0.31 2.14 R2 = 0.20
0.10 0.04
0.16 1.01 0.39 2.71 R2 = 0.22
0.28 0.01
t
t
t
Contributors Ian P. Albery and Isabelle Collins designed the study and wrote an outline of the manuscript. The manuscript was co-written by Marcantonio M. Spada, Ian P Albery, Dan Frings and Antony C. Moss. Conflict of interest There are no conflicts of interest to declare.
p
References
proportion of alcohol consumed. On this basis positive alcohol expectancies appear to be associated with the planning of behaviour. In contrast, habit appears to be associated with behavioural enactment. These indications were confirmed by hierarchical regression analyses which revealed that: (i) positive alcohol expectancies and habit did not predict the amount of alcohol poured; (ii) habit added significant variance to the prediction of the amount and proportion of alcohol consumed beyond expectancies; and (iii) only habit was a significant predictor of both the amount and proportion of alcohol consumed. Although measures of intention (alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed) were positively and significantly correlated, habit was shown to effectively discriminate between these measures. This highlights the role of habit in guiding behavioural enactment and not behavioural intention. These results have potential implications for behaviour change practice, highlighting the importance of disrupting the cue–response association underpinning habit (Verplanken & Wood, 2006). The purposive discontinuation of exposure to the everyday cues that support habit may be an unrealistic intervention strategy, however, using volitional strategies such as vigilant monitoring (Quinn, Pascoe, Wood, & Neal, 2010) or the enhancement of metacognitive monitoring (Spada, Caselli, & Wells, 2013; Spada & Wells, 2006), respectively aimed at heightening attention to behaviour so as to detect habit initiation or stop signals for engaging in a behaviour, may be helpful in inhibiting the performance of unhelpful habits. An example of a metacognitive monitoring enhancement strategy would be the use of Situational Attentional Refocusing (SAR; Wells, 2000), which aims to increase the flow of adaptive information in awareness so the individual is better able to regulate cognition and behaviour. This technique would require the purposeful direction of attention onto cues related to the use of alcohol, such as quantity of alcohol consumed and proximity to desired goals, with the objective of enhancing self-awareness during enactment and help identify a stop signal for use. This study has several limitations. Firstly, it partially relies on selfreport instruments, which are subject to errors in measurement. Secondly, a cross-sectional design was adopted which precludes causal inferences. Thirdly, the sample comprised predominantly of female college students so generalisations based on the current findings should be considered with caution. Directions for future research include ascertaining further the role of habit in predicting drinking behaviour, particularly through in-themoment dynamic longitudinal studies and through the examination of more representative samples (including clinical samples). It would also be interesting to ascertain the efficacy of treatments, aimed at problem drinking, that focus on heightening attention to behaviour and stop signals for engaging in behaviour. Role of funding sources The study was completely self-funded.
Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A metaanalytic review. British Journal of Social Psychology, 40, 471–499. Bush, K., Kivlahan, D. R., McDonell, M. B., Fihn, S. D., & Bradley, K. A. (1998). The AUDIT alcohol consumption questions (AUDIT-C): An effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Archives of Internal Medicine, 158, 1789–1795. Christiansen, B.A., Smith, G. T., Roehling, P. V., & Goldman, M. S. (1989). Using alcohol expectancies to predict adolescent drinking behaviour after one year. Journal of Consulting and Clinical Psychology, 57, 93–99. De Bruijn, G. J. (2010). Understanding college students' fruit consumption: Integrating habit strength in the theory of planned behaviour. Appetite, 54, 16–22. De Bruijn, G. J., Kremers, S. P., De Vet, E., De Nooijer, J., Van Mechelen, W., & Brug, J. (2007). Does habit strength moderate the intention–behaviour relationship in the theory of planned behaviour? The case of fruit consumption. Psychology and Health, 22, 899–916. Flannery, B.A., Volpicelli, J. R., & Pettinati, H. M. (1999). Psychometric properties of the Penn Alcohol Craving Scale. Alcoholism: Clinical and Experimental Research, 23, 1289–1295. Gardner, B., de Bruijn, G. J., & Lally, P. (2011). A systematic review and meta-analysis of applications of the self-report habit index to nutrition and physical activity behaviours. Annals of Behavioral Medicine, 42, 174–187. Gardner, B., De Bruijn, G. J., & Lally, P. (2012). Habit, identity, and repetitive action: A prospective study of binge‐drinking in UK students. British Journal of Health Psychology, 17, 565–581. Lally, P., van Jaarsveld, C. H. M., Potts, H. W. W., & Wardle, J. (2010). How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, 40, 998–1009. Lally, P., Wardle, J., & Gardner, B. (2011). Experiences of habit formation: A qualitative study. Psychology, Health & Medicine, 16, 484–489. Leigh, B. C., & Stacy, A. W. (1993). Alcohol outcome expectancies: Scale construction and predictive utility in higher order confirmatory models. Psychological Assessment, 5, 216–229. Morrison, P.M., Noel, N. E., & Ogle, R. E. (2012). Do angry women choose alcohol? Addictive Behaviors, 37, 908–913. Moss, A.C., & Albery, I. P. (2009). A dual-process model of the alcohol-behavior link for social drinking. Psychological Bulletin, 135, 516–530. Neal, D. T., Wood, W., & Quinn, J. M. (2006). Habits: A repeat performance. Current Directions in Psychological Science, 15, 198–202. Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124, 54. Quinn, J. M., Pascoe, A., Wood, W., & Neal, D. T. (2010). Can't control yourself? Monitor those bad habits. Personality and Social Psychology Bulletin, 36, 499–511. Rhodes, R., De Bruijn, G. -J., & Matheson, D. H. (2010). Habit in the physical activity domain: Integration with intention temporal stability and action control. Journal of Sport and Exercise Psychology, 32, 84–98. Sheeran, P., Gollwitzer, P.M., & Bargh, J. A. (2013). Nonconscious processes and health. Health Psychology, 32, 460. Spada, M. M., Caselli, G., & Wells, A. (2013). A triphasic metacognitive formulation of problem drinking. Clinical Psychology & Psychotherapy, 20, 494–500. Spada, M. M., & Wells, A. (2006). Metacognitions about alcohol use in problem drinkers. Clinical Psychology & Psychotherapy, 13, 138–143. Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behaviour. Personality and Social Psychology Review, 8, 220–247. Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behavior: Is habit an empty construct or an interesting case of goal-directed automaticity? European Review of Social Psychology, 10, 101–134. Verplanken, B., & Orbell, S. (2003). Reflections on past behavior: A self-report index of habit strength. Journal of Applied Social Psychology, 33, 1313–1330. Verplanken, B., & Wood, W. (2006). Interventions to break and create consumer habits. Journal of Public Policy and Marketing, 25, 90–103. Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? An analysis of the experimental evidence. Psychological Bullettin, 132, 249–268. Wells, A. (2000). Emotional disorders & metacognition: Innovative cognitive therapy. Chichester, UK: Wiley. Wiers, R. W., Houben, K., Roefs, A., de Jong, P., & Stacy, A. W. (2010). Implicit cognition in health psychology: Why common sense goes out the window. In B. Gawronski, & B. Keith Payne (Eds.), Handbook of implicit social cognition: Measurement, theory, and applications (pp. 463–488). New York, London: The Guilford Press. Wood, W., & Neal, D. T. (2007). A new look at habits and the habit–goal interface. Psychological Review, 114, 843.
Contents lists available at ScienceDirect
Addictive Behaviors
Short Communication
Habit predicts in-the-moment alcohol consumption Ian P. Albery, Isabelle Collins, Antony C. Moss, Daniel Frings, Marcantonio M. Spada ⁎ Department of Psychology, London South Bank University, UK
H I G H L I G H T S • First study to link habit to objective measures of alcohol consumption. • Habit predicts behavioral enacetment of alcohol consumption. • Suggestions for targeting habit in the treatment of alcohol problems are presented.
a r t i c l e
i n f o
Available online 26 September 2014 Keywords: Dual process model Habit In-the-moment alcohol consumption Metacognitive monitoring Positive alcohol expectancies Proportion of alcohol consumed
a b s t r a c t Aim: The objective of this study was to examine whether habit predicts in-the-moment behavioural intention (amount of alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed) controlling for craving and positive alcohol expectancies. Method: Forty-six college students, who defined themselves as social drinkers, were tested individually in a laboratory setting. After completing a measure of craving they were given a bottle of non-alcoholic beer and a cup, asked to pour a drink, and then drink as much as they liked. They were not informed that the beer was non-alcoholic. They were subsequently asked to complete measures of alcohol use and misuse, positive alcohol expectancies and habit. Results: Positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured and the amount and proportion of alcohol consumed. Habit was positively and significantly associated with the amount and proportion of alcohol consumed but not with the amount of alcohol poured. Hierarchical regression analyses revealed that only habit was a significant predictor of both the amount and proportion of alcohol consumed. Even though measures of intention (amount of alcohol poured) and behaviour (amount and proportion of alcohol consumed) were positively correlated, habit was shown to effectively discriminate between these measures. Conclusions: These findings suggest that habit predicts in-the-moment behavioural enactment in terms of the amount and proportion of alcohol consumed. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Changing unhelpful drinking patterns relies on identifying and modifying determinants of action. Traditionally, approaches to behaviour change have been based on reasoned action models, which portray behaviour as the outcome of conscious intention in the form of, for example, attitudes, beliefs and self-efficacy (Armitage & Conner, 2001). Explaining repeated actions, however, requires the consideration of determinants of behaviour beyond consciously experienced intentions especially in view of the fact that findings appear to indicate that intention has a small-sized effect in predicting ongoing behaviour (Webb & Sheeran, 2006). Dual-process models (e.g. Moss & Albery, 2009; Strack & Deutsch, 2004; Wiers, Houben, Roefs, de Jong, & Stacy, 2010) may offer a valuable framework for tackling the difficulties of the ‘intention–behaviour’ gap ⁎ Corresponding author. Tel.: +44 20 7815 5760. E-mail address: [email protected] (M.M. Spada).
http://dx.doi.org/10.1016/j.addbeh.2014.09.025 0306-4603/© 2014 Elsevier Ltd. All rights reserved.
(see Sheeran, Gollwitzer, & Bargh, 2013). These models propose that behaviour results from both a ‘reflective’ pathway, which involves effortful forethought, and an ‘impulsive’ pathway, characterized by immediate stimulus–response relationships mediated by the activation of associative knowledge. From this standpoint, repetition can initially lead reasoned actions to become impulsive through the formation of ‘habits’, which are automatic behavioural responses to contextual cues, acquired through context-dependent repetition (see Ouellette & Wood, 1998; Verplanken & Aarts, 1999). Repeated performance, in stable settings, strengthens habits (Lally, van Jaarsveld, Potts, & Wardle, 2010; Lally, Wardle, & Gardner, 2011; Neal, Wood, & Quinn, 2006). It has been argued that habit reflects an automated mode of response which is reflected in core features such as lack of awareness, control and conscious intent, and mental efficiency (e.g., Wood & Neal, 2007). The Self-Report Habit Index (SRHI) was developed as a unidimensional measure of habit strength along these lines, by measuring the degree to which a target behaviour occurs frequently, requires
I.P. Albery et al. / Addictive Behaviors 41 (2015) 78–80
conscious awareness, thought and effort, is difficult to control, and is relevant in terms of personal identity (Verplanken and Orbell, 2003). Among others, choices made around food (e.g., De Bruijn, 2010; De Bruijn et al., 2007), physical exercise (Rhodes, De Bruijn, & Matheson, 2010), and self-reported alcohol consumption (Gardner, De Bruijn, & Lally, 2012) have been shown to have a habitual component. A recent meta-analysis (in nutritional/physical exercise) also showed a medium to strong relationship between habit (i.e. SRHI) and behaviour. The SRHI has also been found to moderate the effect of intended behaviour on behavioural enactment (see Gardner, de Bruijn, & Lally, 2011). A weakness of the evidence presented is that it is predominantly limited to retrospective reports using correlational designs. For example, Gardner et al. (2012) used self-reported drinking in the past week whilst prospectively predicting binge drinking from initial habit. The current study attempts to address this limitation by measuring in-the-moment alcohol consumption, planning and enactment and investigating whether habit predicts the proportion of alcohol consumed (an objective behavioural outcome measure) controlling for craving and positive alcohol expectancies (Christiansen, Smith, Roehling, & Goldman, 1989). One way of measuring in-the-moment drinking is to use a Taste Preference Task (TPT) (Morrison, Noel, & Ogle, 2012). In a TPT participants are given a number of alcohol placebos and soft drinks to taste and rate on a number of dimensions (e.g., quality, taste, and colour). Consumption is calculated as the amount drunk from a predefined known quantity. In this study we asked participants to pour their own measure (from a known quantity) to consume. This represents a measure of both behavioural intention (amount of alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed).
79
comprising 12 items assessing perceived habitual or automatic dimensions of behaviour. Following completion of the study all participants were debriefed. 3. Results An inspection of histograms, skewness and kurtosis showed that several variables were not normally distributed. One-tailed Spearman rho correlation analyses showed that positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed. Habit was found to be positively and significantly associated with the amount and proportion of alcohol consumed and not the amount of alcohol poured. No significant associations between age, self-reported alcohol use, and craving, on the one hand, and the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed were observed. The amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed were all positively and significantly correlated (see Table 1). To evaluate the contribution of habit beyond that accounted for by positive alcohol expectancies, hierarchical regression analyses were run with the amount of alcohol poured, amount of alcohol consumed and proportion of alcohol consumed as criterion variables. Positive alcohol expectancies were entered in step 1 and habit was entered in step 2 (see Table 2). Together habit and positive alcohol expectancies were shown to significantly predict the amount of alcohol consumed 2 [F (2, 43) = 5.38, p b .001 (R2 = .20, R = .16)] and proportion of alco2 hol consumed [F (2, 43) = 5.92, p b .01 (R2 = .22, R = .18)] but not the 2 amount of alcohol poured [F (2, 43) = 2.23, p = .12 (R2 = .09, R = .05)]. An inspection of the final equations revealed that habit significantly increased the variance explained in the amount of alcohol consumed [FΔ (1, 43) = 4.58, p b 0.05 (R2 = .16, R2Δ = .09, B = .31)] and proportion of alcohol consumed [FΔ (1, 43) = 7.39, p b 0.01 (R2 = .22, R2Δ = .14, B = .39)] over and above the variance accounted for by positive alcohol expectancies (see Table 2).
2. Method 2.1. Participants The sample consisted of 46 college students who reported being social drinkers (38 females and 8 males, mean age = 24.7 years, sd = 7.9, range = 18–53; mean AUDIT-C = 5.5, sd = 2.3, range = 1–12).
4. Discussion 2.2. Materials and procedure This study sought to examine whether habit predicts in-the-moment amount of alcohol poured, and the amount and proportion of alcohol consumed controlling for craving and positive alcohol expectancies. A focus on how much an individual pours to drink, and the actual amount they drink, allows us to distinguish between one's intention and the enactment of this behavioural intention. Importantly, however, these measures are both behavioural in nature and as such provide evidence as indirect measures. Correlational analyses showed dissociation between positive alcohol expectancies and habit, with the amount of alcohol poured (behavioural intention) and the amount and proportion of alcohol consumed (behavioural enactment). Positive alcohol expectancies were positively and significantly associated with the amount of alcohol poured, and the amount and proportion of alcohol consumed. Habit was positively and significantly associated with the amount of alcohol consumed and
Ethics approval for the study was obtained from a UK University. Once briefed and consent achieved participants completed the Penn Alcohol Craving Scale (PACS; Flannery, Volpicelli, & Pettinati, 1999) which measures duration, frequency and intensity of craving. They were then given a bottle of non-alcoholic beer and a cup, and asked to pour themselves a drink (behavioural intention) and drink as much as they liked (behavioural enactment). Participants were not informed that the beer was non-alcoholic. They were then asked to complete the Alcohol Use Disorder Identification Test Consumption (AUDIT-C; Bush, Kivlahan, McDonell, Fihn, & Bradley, 1998) which comprises three items assessing quantity and frequency of alcohol use, the Alcohol Outcome Expectancies Scale (AOES; Leigh & Stacy, 1993) measuring social facilitation, fun, sex, and tension reduction and the SRHI (Verplanken & Orbell, 2003) Table 1 Descriptive statistics and Spearman's rho correlations coefficients (one tailed).
Age AUDIT-C PACS AOEQ positive SHRI Amount of alcohol poured (ml) Amount of alcohol consumed (ml) Proportion of alcohol consumed (%) ⁎ p b .05. ⁎⁎ p b .001.
Mean
SD
Range
AUDIT-C
PACS
AOEQ positive
SRHI
Amount of alcohol poured (ml)
Amount of alcohol consumed (ml)
Proportion of alcohol consumed (%)
24.7 5.5 7.2 81.0 30.4 52.2 34.9 60.9
7.9 2.3 4.3 9.1 7.5 36.8 37.9 30.4
18–53 1–12 0–23 64–100 13–49 7–175 2–146 7.4–98.7
−.04 –
−.11 .36⁎⁎
−.01 .32⁎⁎ .27⁎
.17 .41⁎⁎ .35⁎⁎ .36⁎⁎
.01 .06 .21 .25⁎ .19 –
.09 .05 .02 .27⁎ .32⁎ .73⁎⁎ –
.07 .09 −.10 .26⁎ .45⁎⁎ .28⁎ .74⁎⁎
–
–
–
–
80
I.P. Albery et al. / Addictive Behaviors 41 (2015) 78–80
Table 2 Hierarchical multiple linear regression statistics with the amount of alcohol poured and consumed and proportion of alcohol consumed as criterion variables and positive alcohol expectancies and habit as predictor variables.
Step 1 AOEQ positive
Step 2 AOEQ positive SRHI
Amount of alcohol poured (ml)
Amount of alcohol consumed (ml)
Proportion of alcohol consumed (%)
β
p
β
p
β
.25 1.67 R2 = 0.06
.10
0.34 2.39 R2 = 0.12
0.02
0.29 1.97 R2 = 0.08
0.05
.18 1.19 .19 1.26 R2 = 0.09
.24 .22
0.24 1.63 0.31 2.14 R2 = 0.20
0.10 0.04
0.16 1.01 0.39 2.71 R2 = 0.22
0.28 0.01
t
t
t
Contributors Ian P. Albery and Isabelle Collins designed the study and wrote an outline of the manuscript. The manuscript was co-written by Marcantonio M. Spada, Ian P Albery, Dan Frings and Antony C. Moss. Conflict of interest There are no conflicts of interest to declare.
p
References
proportion of alcohol consumed. On this basis positive alcohol expectancies appear to be associated with the planning of behaviour. In contrast, habit appears to be associated with behavioural enactment. These indications were confirmed by hierarchical regression analyses which revealed that: (i) positive alcohol expectancies and habit did not predict the amount of alcohol poured; (ii) habit added significant variance to the prediction of the amount and proportion of alcohol consumed beyond expectancies; and (iii) only habit was a significant predictor of both the amount and proportion of alcohol consumed. Although measures of intention (alcohol poured) and behavioural enactment (amount and proportion of alcohol consumed) were positively and significantly correlated, habit was shown to effectively discriminate between these measures. This highlights the role of habit in guiding behavioural enactment and not behavioural intention. These results have potential implications for behaviour change practice, highlighting the importance of disrupting the cue–response association underpinning habit (Verplanken & Wood, 2006). The purposive discontinuation of exposure to the everyday cues that support habit may be an unrealistic intervention strategy, however, using volitional strategies such as vigilant monitoring (Quinn, Pascoe, Wood, & Neal, 2010) or the enhancement of metacognitive monitoring (Spada, Caselli, & Wells, 2013; Spada & Wells, 2006), respectively aimed at heightening attention to behaviour so as to detect habit initiation or stop signals for engaging in a behaviour, may be helpful in inhibiting the performance of unhelpful habits. An example of a metacognitive monitoring enhancement strategy would be the use of Situational Attentional Refocusing (SAR; Wells, 2000), which aims to increase the flow of adaptive information in awareness so the individual is better able to regulate cognition and behaviour. This technique would require the purposeful direction of attention onto cues related to the use of alcohol, such as quantity of alcohol consumed and proximity to desired goals, with the objective of enhancing self-awareness during enactment and help identify a stop signal for use. This study has several limitations. Firstly, it partially relies on selfreport instruments, which are subject to errors in measurement. Secondly, a cross-sectional design was adopted which precludes causal inferences. Thirdly, the sample comprised predominantly of female college students so generalisations based on the current findings should be considered with caution. Directions for future research include ascertaining further the role of habit in predicting drinking behaviour, particularly through in-themoment dynamic longitudinal studies and through the examination of more representative samples (including clinical samples). It would also be interesting to ascertain the efficacy of treatments, aimed at problem drinking, that focus on heightening attention to behaviour and stop signals for engaging in behaviour. Role of funding sources The study was completely self-funded.
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