Age-related differences in alcohol attention bias: a cross-sectional study
- 143 Downloads
Addiction models theorise that alcohol attention bias (AAB) for alcohol-related cues develops through a process of classical conditioning and that attentional processes shift from controlled to automatically modulated responses. At the point of automaticity, alcohol cues grab the attention of problem drinkers beyond conscious control and can trigger alcohol use. To fully understand this shift, AAB should be thought of as developing on a continuum from when alcohol use commences. Despite this, little is known about AAB differences in younger populations who are at an early stage in their exposure to alcohol and related cues.
This study compared AAB for alcohol cues across age groups (early adolescent, late adolescent, and young adult) and drinking groups (heavy drinkers, light drinkers, and non-drinkers) to provide a cross-sectional examination of differences in AAB and their relationship to alcohol use and age.
Eye tracking was employed to measure several elements of attentional processing during exposure to alcohol cues. Differences across age groups and drinking groups were examined.
Differences in controlled attention were found between heavy and light drinkers. As age increases, a shift towards automaticity can be seen with alcohol-related cues attracting the attention of young adult drinkers earlier in stimulus presentation.
This cross-sectional approach provides an insight into AAB across a key developmental period. It highlights that influential processes underpinning AAB may change and how rapidly it may approach automaticity. The implications of these findings are discussed.
KeywordsAlcohol Attention bias Eye tracking Cognitive processing
Compliance with ethical standards
The ethics committee at the School of Psychology, Queen’s University Belfast, approved the study.
- Albery I, Sharma D, Noyce S, Frings D, Moss A (2015) Testing a frequency of exposure hypothesis in attentional bias for alcohol-related stimuli amongst social drinkers. Addict Behav 1:68–72Google Scholar
- De Houwer J (2006) What are implicit measures and why are we using them? In: Wiers RW, Stacy AW (eds) Handbook of implicit cognition and addiction. Sage Publications Inc., London & New DelhiGoogle Scholar
- Laidlaw, K. & Risko, E. & Kingstone, A. (2012). A New Look at Social Attention: Orienting to the Eyes Is Not (Entirely) Under Volitional Control. Journal of experimental psychology. Human perception and performance. 38:1132–43Google Scholar
- MacLeod, Colin & Mathews, Andrew & Tata, Philip. (1986). Attentional Bias in Emotional Disorders. Journal of abnormal psychology. 95:15–20Google Scholar
- McCusker C (2006) Towards understanding loss of control: an automatic network theory of addictive behaviours. In: Munafó M, Albery I (eds) Cognition addiction. Oxford University Press, OxfordGoogle Scholar
- Miller MA, Fillmore MT (2011) The effect of image complexity on attentional bias towards alcohol related images in adult drinkers. Addiction 105(5):883–890Google Scholar
- Stetter F, Chaluppa С, Ackermann К, Straube E, Mann К (1994) Alcoholics’ selective processing of alcohol related words and cognitive performance on a stroop task. Eur Psychiatry 9(2):71–76Google Scholar