Abstract
This chapter focuses on alcohol use and related problems at the event level. The chapter examines historical and current theoretical and methodological issues related to understanding drinking events. The chapter postulates drinking events as ecological systems where individual, social, and environmental factors interact in complex and dynamic ways to influence drinking and related problems. Current interventions related to preventing alcohol-related problems at the event level are discussed. The promise of develo** real-time interventions designed to prevent in situ alcohol-related problems are also discussed. Finally, the chapter addresses potential future directions for research relating to drinking at the event level.
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References
Abernathy, K., Chandler, L. J., & Woodward, J. J. (2010). Alcohol and the prefrontal cortex. International Review of Neurobiology, 91, 289–320. https://doi.org/10.1016/S0074-7742(10)91009-X
Agyapong, V. I. O., McLoughlin, D. M., & Farren, C. K. (2013). Six-months outcomes of a randomised trial of supportive text messaging for depression and comorbid alcohol use disorder. Journal of Affective Disorders, 151(1), 100–104. https://doi.org/10.1016/j.jad.2013.05.058
Alessi, S. M., & Petry, N. M. (2013). A randomized study of cellphone technology to reinforce alcohol abstinence in the natural environment: Portable CM for alcohol abstinence. Addiction, 108(5), 900–909. https://doi.org/10.1111/add.12093
Ally, A. K., Lovatt, M., Meier, P. S., Brennan, A., & Holmes, J. (2016). Develo** a social practice-based typology of British drinking culture in 2009–2011: Implications for alcohol policy analysis. Addiction (Abingdon, England), 111(9), 1568–1579. https://doi.org/10.1111/add.13397
Bae, S., Chung, T., Ferreira, D., Dey, A. K., & Suffoletto, B. (2018). Mobile phone sensors and supervised machine learning to identify alcohol use events in young adults: Implications for just-in-time adaptive interventions. Addictive Behaviours, 83, 42–47. https://doi.org/10.1016/j.addbeh.2017.11.039
Barnett, N. P., Celio, M. A., Tidey, J. W., Murphy, J. G., Colby, S. M., & Swift, R. M. (2017). A preliminary randomized controlled trial of contingency management for alcohol use reduction using a transdermal alcohol sensor: Contingency management for alcohol use reduction. Addiction, 112(6), 1025–1035. https://doi.org/10.1111/add.13767
Barnett, N. P., Tidey, J., Murphy, J. G., Swift, R., & Colby, S. M. (2011). Contingency management for alcohol use reduction: A pilot study using a transdermal alcohol sensor. Drug and Alcohol Dependence, 118(2–3), 391–399. https://doi.org/10.1016/j.drugalcdep.2011.04.023
Barry, A. E., Stellefson, M. L., Piazza-Gardner, A. K., Chaney, B. H., & Dodd, V. (2013). The impact of pregaming on subsequent blood alcohol concentrations: An event-level analysis. Addictive Behaviours, 38(8), 2374–2377. https://doi.org/10.1016/j.addbeh.2013.03.014
Beckjord, E., & Shiffman, S. (2014). Background for real-time monitoring and intervention related to alcohol use. Alcohol Research: Current Reviews, 36(1), 9–18.
Bock, B. C., Barnett, N. P., Thind, H., Rosen, R., Walaska, K., Traficante, R., … Scott-Sheldon, L. A. J. (2016). A text message intervention for alcohol risk reduction among community college students: TMAP. Addictive Behaviours, 63, 107–113. https://doi.org/10.1016/j.addbeh.2016.07.012
Cavan, S. (1966). Liquor license: An ethnography of bar behaviour. Chicago, IL: Aldine Transaction.
Clapp, J. D., Holmes, M. R., Reed, M. B., Shillington, A. M., Freisthler, B., & Lange, J. E. (2007). Measuring college students’ alcohol consumption in natural drinking environments: Field methodologies for bars and parties. Evaluation Review, 31(5), 469–489. https://doi.org/10.1177/0193841X07303582
Clapp, J. D., Madden, D. R., Gonzalez Villasanti, H., Giraldo, L. F., Passino, K. M., Reed, M. B., & Fernandez Puentes, I. (2018). A system dynamic model of drinking events: Multi-level ecological approach: A system dynamic model of drinking events. Systems Research and Behavioural Science, 35(3), 265–281. https://doi.org/10.1002/sres.2478
Clapp, J. D., Madden, D. R., Mooney, D. D., & Dahlquist, K. E. (2017). Examining the social ecology of a bar-crawl: An exploratory pilot study. PLoS One, 12(9), e0185238. https://doi.org/10.1371/journal.pone.0185238
Clapp, J. D., Min, J. W., Shillington, A. M., Reed, M. B., & Croff, J. K. (2008). Person and environment predictors of blood alcohol concentrations: A multi-level study of college parties. Alcoholism: Clinical and Experimental Research, 32(1), 100–107. https://doi.org/10.1111/j.1530-0277.2007.00547.x
Clapp, J. D., Reed, M. B., Min, J. W., Shillington, A. M., Croff, J. M., Holmes, M. R., & Trim, R. S. (2009). Blood alcohol concentrations among bar patrons: A multi-level study of drinking behaviour. Drug and Alcohol Dependence, 102(1–3), 41–48. https://doi.org/10.1016/j.drugalcdep.2008.12.015
Clapp, J. D., Reed, M. B., & Ruderman, D. E. (2014). The relationship between drinking games and intentions to continue drinking, intentions to drive after drinking, and adverse consequences: Results of a field study. The American Journal of Drug and Alcohol Abuse, 40(5), 374–379. https://doi.org/10.3109/00952990.2014.933838
Cohn, A. M., Hunter-Reel, D., Hagman, B. T., & Mitchell, J. (2011). Promoting behaviour change from alcohol use through Mobile technology: The future of ecological momentary assessment. Alcoholism: Clinical and Experimental Research, 35(12), 2209–2215. https://doi.org/10.1111/j.1530-0277.2011.01571.x
Denzin, N. K. (1987). The alcoholic self. London, England: Sage.
Dougherty, D. M., Hill-Kapturczak, N., Liang, Y., Karns, T. E., Cates, S. E., Lake, S. L., … Roache, J. D. (2014). Use of continuous transdermal alcohol monitoring during a contingency management procedure to reduce excessive alcohol use. Drug and Alcohol Dependence, 142, 301–306. https://doi.org/10.1016/j.drugalcdep.2014.06.039
Dulin, P. L., & Gonzalez, V. M. (2017). Smartphone-based, momentary intervention for alcohol cravings amongst individuals with an alcohol use disorder. Psychology of Addictive Behaviours, 31(5), 601–607. https://doi.org/10.1037/adb0000292
Fairbairn, C. E., Rosen, I. G., Luczak, S. E., & Venerable, W. J. (2018). Estimating the quantity and time course of alcohol consumption from transdermal alcohol sensor data: A combined laboratory-ambulatory study. Alcohol, 81, 111. https://doi.org/10.1016/j.alcohol.2018.08.015
Fitzpatrick, B., & Martinez, J. (2011). Agent-based modeling of ecological niche theory and assortative drinking. Journal of Artificial Societies and Social Simulation, 15(2), 4.
Fjeldsoe, B. S., Marshall, A. L., & Miller, Y. D. (2009). Behaviour change interventions delivered by mobile telephone short-message service. American Journal of Preventive Medicine, 36(2), 165–173. https://doi.org/10.1016/j.amepre.2008.09.040
Fowler, L. A., Holt, S. L., & Joshi, D. (2016). Mobile technology-based interventions for adult users of alcohol: A systematic review of the literature. Addictive Behaviours, 62, 25–34. https://doi.org/10.1016/j.addbeh.2016.06.008
Free, C., Phillips, G., Felix, L., Galli, L., Patel, V., & Edwards, P. (2010). The effectiveness of M-health technologies for improving health and health services: A systematic review protocol. BMC Research Notes, 3, 250. https://doi.org/10.1186/1756-0500-3-250
Giraldo, L. F., Passino, K. M., & Clapp, J. D. (2017). Modeling and analysis of group dynamics in alcohol-consumption environments. IEEE Transactions on Cybernetics, 47(1), 165–176. https://doi.org/10.1109/TCYB.2015.2509444
Giraldo, L. F., Passino, K. M., Clapp, J. D., & Ruderman, D. (2017). Dynamics of metabolism and decision making during alcohol consumption: Modeling and analysis. IEEE Transactions on Cybernetics, 47(11), 3955–3966. https://doi.org/10.1109/TCYB.2016.2593009
Gonzalez, V. M., & Dulin, P. L. (2015). Comparison of a smartphone app for alcohol use disorders with an internet-based intervention plus bibliotherapy: A pilot study. Journal of Consulting and Clinical Psychology, 83(2), 335–345. https://doi.org/10.1037/a0038620
Gonzalez Villasanti, H., Passino, K. M., Clapp, J. D., & Madden, D. R. (2018). A control-theoretic assessment of interventions during drinking events. IEEE Transactions on Cybernetics, 49, 1–12. https://doi.org/10.1109/TCYB.2017.2782010
Gorman, D. M., Mezic, J., Mezic, I., & Gruenewald, P. J. (2006). Agent-based Modeling of drinking behaviour: A preliminary model and potential applications to theory and practice. American Journal of Public Health, 96(11), 2055–2060. https://doi.org/10.2105/AJPH.2005.063289
Gusfield, J. R. (1996). Contested meanings: The construction of alcohol problems. Madison, WI: University of Wisconsin Press.
Gustafson, D. H., McTavish, F. M., Chih, M. Y., Atwood, A. K., Johnson, R. A., Boyle, M. G., … Shah, D. (2014). A smartphone application to support recovery from alcoholism: A randomized clinical trial. JAMA Psychiatry, 71(5), 566–572. https://doi.org/10.1001/jamapsychiatry.2013.4642
Harford, T. C., & Gaines, L. S. (1979). Social drinking contexts. In Proceedings of a Workshop (DHHS-ADM-81-1097). National Institute of Alcohol Abuse and Alcoholism. https://files.eric.ed.gov/fulltext/ED227373.pdf
Hasin, D. S., Aharonovich, E., & Greenstein, E. (2014). HealthCall for the smartphone: Technology enhancement of brief intervention in HIV alcohol dependent patients. Addiction Science & Clinical Practice, 9. https://doi.org/10.1186/1940-0640-9-5
Hawe, P., Shiell, A., & Riley, T. (2009). Theorising interventions as events in systems. American Journal of Community Psychology, 43(3–4), 267–276. https://doi.org/10.1007/s10464-009-9229-9
Heron, K. E., & Smyth, J. M. (2010). Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behaviour treatments. British Journal of Health Psychology, 15(1), 1–39. https://doi.org/10.1348/135910709X466063
Holder, H. D. (2006). Alcohol and the community: A systems approach to prevention. Cambridge, England: Cambridge University Press.
Kauer, S. D., Reid, S. C., Sanci, L., & Patton, G. C. (2009). Investigating the utility of mobile phones for collecting data about adolescent alcohol use and related mood, stress and co** behaviours: Lessons and recommendations. Drug and Alcohol Review, 28(1), 25–30. https://doi.org/10.1111/j.1465-3362.2008.00002.x
Kazemi, D. M., Borsari, B., Levine, M. J., Li, S., Lamberson, K. A., & Matta, L. A. (2017). A systematic review of the mHealth interventions to prevent alcohol and substance abuse. Journal of Health Communication, 22(5), 413–432. https://doi.org/10.1080/10810730.2017.1303556
Kennedy, A. P., Epstein, D. H., Jobes, M. L., Agage, D., Tyburski, M., Phillips, K. A., … Preston, K. L. (2015). Continuous in-the-field measurement of heart rate: Correlates of drug use, craving, stress, and mood in polydrug users. Drug and Alcohol Dependence, 151, 159–166. https://doi.org/10.1016/j.drugalcdep.2015.03.024
Lagoa, C. M., Bekiroglu, K., Lanza, S. T., & Murphy, S. A. (2014). Designing adaptive intensive interventions using methods from engineering. Journal of Consulting and Clinical Psychology, 82(5), 868–878. https://doi.org/10.1037/a0037736
Langley, H. (2017). Bactrack’s wearable will tell you how drunk you are. Wareable. https://www.wareable.com/health-and-wellbeing/bactrack-sync-wearable-alcohol-monitor-release-date-price-3735
Leffingwell, T. R., Cooney, N. J., Murphy, J. G., Luczak, S., Rosen, G., Dougherty, D. M., & Barnett, N. P. (2013). Continuous objective monitoring of alcohol use: Twenty-first century measurement using transdermal sensors. Alcoholism: Clinical and Experimental Research, 37(1), 16–22. https://doi.org/10.1111/j.1530-0277.2012.01869.x
Leonard, N. R., Silverman, M., Sherpa, D. P., Naegle, M. A., Kim, H., Coffman, D. L., & Ferdschneider, M. (2017). Mobile health technology using a wearable sensorband for female college students with problem drinking: An acceptability and feasibility study. JMIR mHealth and uHealth, 5(7), e90. https://doi.org/10.2196/mHealth.7399
Lewin, K. (1951). Field theory in social science: Selected theoretical papers (Ed. D. Cartwright). Harpers.
Luczak, S. E., Hawkins, A. L., Dai, Z., Wichmann, R., Wang, C., & Rosen, I. G. (2018). Obtaining continuous BAC/BAC estimates in the field: A hybrid system integrating transdermal alcohol biosensor, Intellidrink smartphone app, and BAC estimator software tools. Addictive Behaviours, 83, 48–55. https://doi.org/10.1016/j.addbeh.2017.11.038
Marques, P. R., & McKnight, A. S. (2009). Field and laboratory alcohol detection with 2 types of transdermal devices. Alcoholism: Clinical and Experimental Research, 33(4), 703–711. https://doi.org/10.1111/j.1530-0277.2008.00887.x
Mason, M., Ola, B., Zaharakis, N., & Zhang, J. (2015). Text messaging interventions for adolescent and young adult substance use: A meta-analysis. Prevention Science: The Official Journal of the Society for Prevention Research, 16(2), 181–188. https://doi.org/10.1007/s11121-014-0498-7
McKnight, A. S., Fell, J. C., & Auld-Owens, A. (2012). Transdermal alcohol monitoring: Case studies. Washington, DC: National Highway Traffic Safety Administration.
McQuoid, J., Thrul, J., & Ling, P. (2018). A geographically explicit ecological momentary assessment (GEMA) mixed method for understanding substance use. Social Science & Medicine, 202, 89–98. https://doi.org/10.1016/j.socscimed.2018.02.014
Miller, J. H., & Page, S. E. (2009). Complex adaptive systems: An introduction to computational models of social life. Princeton, NJ: Princeton University Press.
Monk, R. L., Heim, D., Qureshi, A., & Price, A. (2015). “I have no clue what I drunk last night” using smartphone technology to compare in-vivo and retrospective self-reports of alcohol consumption. PLoS One, 10(5). https://doi.org/10.1371/journal.pone.0126209
Morgenstern, J., Kuerbis, A., & Muench, F. (2014). Ecological momentary assessment and alcohol use disorder treatment. Alcohol Research: Current Reviews, 36(1), 101–110.
Muench, F., van Stolk-Cooke, K., Kuerbis, A., Stadler, G., Baumel, A., Shao, S., McKay, J. R., & Morgenstern, J. (2017). A randomized controlled pilot trial of different mobile messaging interventions for problem drinking compared to weekly drink tracking. PLoS One, 12(2), e0167900. https://doi.org/10.1371/journal.pone.0167900.
Nahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (2018). Just-in-time adaptive interventions (JITAIs) in Mobile Health: Key components and design principles for ongoing health behaviour support. Annals of Behavioural Medicine: A Publication of the Society of Behavioural Medicine, 52(6), 446–462. https://doi.org/10.1007/s12160-016-9830-8
National Institute of Health. (2000). 10th special report to the U.S. Congress on Alcohol and Health. Bethesda, MD: U.S. Department of Health and Human Services.
Nees, F., Diener, C., Smolka, M. N., & Flor, H. (2012). The role of context in the processing of alcohol-relevant cues. Addiction Biology, 17(2), 441–451. https://doi.org/10.1111/j.1369-1600.2011.00347.x
Patrick, M. E., & Lee, C. M. (2010). Comparing numbers of drinks: College students’ reports from retrospective summary, followback, and prospective daily diary measures. Journal of Studies on Alcohol and Drugs, 71(4), 554–561.
Quinn, P. D., & Fromme, K. (2011). Predictors and outcomes of variability in subjective alcohol intoxication among college students: An event-level analysis across 4 years. Alcoholism: Clinical and Experimental Research, 35(3), 484–495. https://doi.org/10.1111/j.1530-0277.2010.01365.x
Reed, M. B., Clapp, J. D., Weber, M., Trim, R., Lange, J., & Shillington, A. M. (2011). Predictors of partying prior to bar attendance and subsequent BAC. Addictive Behaviours, 36(12), 1341–1343. https://doi.org/10.1016/j.addbeh.2011.07.029
Rehm, J., Mathers, C., Popova, S., Thavorncharoensap, M., Teerawattananon, Y., & Patra, J. (2009). Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders. Lancet, 373(9682), 2223–2233.
Riley, W. T., Rivera, D. E., Atienza, A. A., Nilsen, W., Allison, S. M., & Mermelstein, R. (2011). Health behaviour models in the age of mobile interventions: Are our theories up to the task? Translational Behavioural Medicine, 1(1), 53–71. https://doi.org/10.1007/s13142-011-0021-7
Saltz, R. F., Paschall, M. J., McGaffigan, R. P., & Nygaard, P. M. O. (2010). Alcohol risk management in college settings: The safer California universities randomized trial. American Journal of Preventive Medicine, 39(6), 491–499. https://doi.org/10.1016/j.amepre.2010.08.020
Scribner, R., Ackleh, A. S., Fitzpatrick, B. G., Jacquez, G., Thibodeaux, J. J., Rommel, R., & Simonsen, N. (2009). A systems approach to college drinking: Development of a deterministic model for testing alcohol control policies. Journal of Studies on Alcohol and Drugs, 70(5), 805–821.
Shiffman, S. (2009). Ecological momentary assessment (EMA) in studies of substance use. Psychological Assessment, 21(4), 486–497. https://doi.org/10.1037/a0017074
Smyth, J. M., & Stone, A. A. (2003). Ecological momentary assessment research in behavioural medicine. Journal of Happiness Studies; Dordrecht, 4(1), 35–52. http://dx.doi.org.libproxy1.usc.edu/10.1023/A:1023657221954
Song, T., Qian, S., & Yu, P. (2019). Mobile health interventions for self-control of unhealthy alcohol use: Systematic review. JMIR mHealth and uHealth, 7(1). https://doi.org/10.2196/10899
Stevely, A. K., Holmes, J., & Meier, P. S. (2020). Contextual characteristics of adults’ drinking occasions and their association with levels of alcohol consumption and acute alcohol-related harm: A map** review. Addiction, 115(2), 218–229. https://doi.org/10.1111/add.14839
Stokols, D. (2000). Social ecology and behavioural medicine: Implications for training, practice, and policy. Behavioural Medicine (Washington, D.C.), 26(3), 129–138. https://doi.org/10.1080/08964280009595760
Stone, A. A., & Shiffman, S. (1994). Ecological momentary assessment (Ema) in behavioural medicine. Annals of Behavioural Medicine, 16(3), 199–202. https://doi.org/10.1093/abm/16.3.199
Suffoletto, B., Kristan, J., Callaway, C., Kim, K. H., Chung, T., Monti, P. M., & Clark, D. B. (2014). A text message alcohol intervention for young adult emergency department patients: A randomized clinical trial. Annals of Emergency Medicine, 64(6), 664–672.e4. https://doi.org/10.1016/j.annemergmed.2014.06.010
Suffoletto, B., Kristan, J., Chung, T., Jeong, K., Fabio, A., Monti, P., & Clark, D. B. (2015). An interactive text message intervention to reduce binge drinking in young adults: A randomized controlled trial with 9-month outcomes. PLoS One, 10(11), e0142877. https://doi.org/10.1371/journal.pone.0142877
Thrul, J., & Kuntsche, E. (2015). The impact of friends on young adults’ drinking over the course of the evening-an event-level analysis: Impact of friends on young adults’ drinking. Addiction, 110(4), 619–626. https://doi.org/10.1111/add.12862
Verster, J. C., Benjaminsen, J. M. E., van Lanen, J. H. M., van Stavel, N. M. D., & Olivier, B. (2015). Effects of mixing alcohol with energy drink on objective and subjective intoxication: Results from a Dutch on-premise study. Psychopharmacology, 232(5), 835–842. https://doi.org/10.1007/s00213-014-3715-y
Wechsler, H., Davenport, A., Dowdall, G., Moeykens, B., & Castillo, S. (1994). Health and behavioural consequences of binge drinking in college: A National Survey of students at 140 campuses. JAMA, 272(21), 1672–1677. https://doi.org/10.1001/jama.1994.03520210056032
Wells, S., Dumas, T. M., Bernards, S., Kuntsche, E., Labhart, F., & Graham, K. (2015). Predrinking, alcohol use, and breath alcohol concentration: A study of young adult bargoers. Psychology of Addictive Behaviours, 29(3), 683–689. https://doi.org/10.1037/adb0000065
Wells, S., Graham, K., & Purcell, J. (2009). Policy implications of the widespread practice of “pre-drinking” or “pre-gaming” before going to public drinking establishments: Are current prevention strategies backfiring? Addiction (Abingdon, England), 104(1), 4–9. https://doi.org/10.1111/j.1360-0443.2008.02393.x
World Health Organization. (2018). Global status report on alcohol and health 2018. Geneva, Switzerland: World Health Organization.
Wray, T. B., Merrill, J. E., & Monti, P. M. (2014). Using ecological momentary assessment (EMA) to assess situation-level predictors of alcohol use and alcohol-related consequences. Alcohol Research: Current Reviews, 36(1), 19–27.
Yu, P., Wu, M. X., Yu, H., & **ao, G. Q. (2006). The challenges for the adoption of M-health. In 2006 IEEE International Conference on Service Operations and Logistics, and Informatics (pp. 181–186). https://doi.org/10.1109/SOLI.2006.329059
Zamboanga, B. L., Kenney, S. R., Van Tyne, K., Olthuis, J. V., Correia, C. J., Ham, L. S., & Borsari, B. (2014). Not just fun and games: A review of college drinking games research from 2004 to 2013. Psychology of Addictive Behaviours: Journal of the Society of Psychologists in Addictive Behaviours, 28(3), 682–695. https://doi.org/10.1037/a0036639.
Zhang, M. W. B., & Ho, R. C. M. (2016). Tap** onto the potential of smartphone applications for psycho-education and early intervention in addictions. Frontiers in Psychiatry, 7. https://doi.org/10.3389/fpsyt.2016.00040
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Clapp, J.D., Madden, D.R. (2021). Alcohol Use and Problems at the Event Level: Theory, Methods, and Intervention. In: Cooke, R., Conroy, D., Davies, E.L., Hagger, M.S., de Visser, R.O. (eds) The Palgrave Handbook of Psychological Perspectives on Alcohol Consumption. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-66941-6_8
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