Charlotte Buckley1, Matt Field2, Tuong Manh Vu3, Alan Brennan3, Thomas K Greenfield4, Petra S Meier5, Alexandra Nielsen4, Charlotte Probst6, Paul A Shuper7, Robin C Purshouse8. 1. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3DA, UK. Electronic address: c.m.buckley@sheffield.ac.uk. 2. Department of Psychology, University of Sheffield, Cathedral Court, 1 Vicar Lane, Sheffield S1 2LT, UK. 3. School of Health and Related Research, University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK. 4. Alcohol Research Group (ARG), Public Health Institute, 6001 Shellmound St, Emeryville, CA 94608, USA. 5. MRC/CSO Social and Public Health Sciences Unit, Berkeley Square, 99 Berkeley Street, Glasgow G3 7HR, UK. 6. Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, On M5S 2S1, Canada; Heidelberg Institute of Global Health, Medical Faculty and University Hospital, Heidelberg University, Im Neuenheimer Feld, 130.3 69120 Heidelberg, Germany. 7. Institute for Mental Health Policy Research, Centre for Addiction and Mental Health (CAMH), 33 Ursula Franklin Street, Toronto, On M5S 2S1, Canada. 8. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3DA, UK.
Abstract
INTRODUCTION: The Theory of Planned Behaviour (TPB) describes how attitudes, norms and perceived behavioural control guide health behaviour, including alcohol consumption. Dual Process Theories (DPT) suggest that alongside these reasoned pathways, behaviour is influenced by automatic processes that are determined by the frequency of engagement in the health behaviour in the past. We present a computational model integrating TPB and DPT to determine drinking decisions for simulated individuals. We explore whether this model can reproduce historical patterns in US population alcohol use and simulate a hypothetical scenario, "Dry January", to demonstrate the utility of the model for appraising the impact of policy interventions on population alcohol use. METHOD: Constructs from the TPB pathway were computed using equations from an existing individual-level dynamic simulation model of alcohol use. The DPT pathway was initialised by simulating individuals' past drinking using data from a large US survey. Individuals in the model were from a US population microsimulation that accounts for births, deaths and migration (1984-2015). On each modelled day, for each individual, we calculated standard drinks consumed using the TPB or DPT pathway. In each year we computed total population alcohol use prevalence, frequency and quantity. The model was calibrated to alcohol use data from the Behavioral Risk Factor Surveillance System (1984-2004). RESULTS: The model was a good fit to prevalence and frequency but a poorer fit to quantity of alcohol consumption, particularly in males. Simulating Dry January in each year led to a small to moderate reduction in annual population drinking. CONCLUSION: This study provides further evidence, at the whole population level, that a combination of reasoned and implicit processes are important for alcohol use. Alcohol misuse interventions should target both processes. The integrated TPB-DPT simulation model is a useful tool for estimating changes in alcohol consumption following hypothetical population interventions.
INTRODUCTION: The Theory of Planned Behaviour (TPB) describes how attitudes, norms and perceived behavioural control guide health behaviour, including alcohol consumption. Dual Process Theories (DPT) suggest that alongside these reasoned pathways, behaviour is influenced by automatic processes that are determined by the frequency of engagement in the health behaviour in the past. We present a computational model integrating TPB and DPT to determine drinking decisions for simulated individuals. We explore whether this model can reproduce historical patterns in US population alcohol use and simulate a hypothetical scenario, "Dry January", to demonstrate the utility of the model for appraising the impact of policy interventions on population alcohol use. METHOD: Constructs from the TPB pathway were computed using equations from an existing individual-level dynamic simulation model of alcohol use. The DPT pathway was initialised by simulating individuals' past drinking using data from a large US survey. Individuals in the model were from a US population microsimulation that accounts for births, deaths and migration (1984-2015). On each modelled day, for each individual, we calculated standard drinks consumed using the TPB or DPT pathway. In each year we computed total population alcohol use prevalence, frequency and quantity. The model was calibrated to alcohol use data from the Behavioral Risk Factor Surveillance System (1984-2004). RESULTS: The model was a good fit to prevalence and frequency but a poorer fit to quantity of alcohol consumption, particularly in males. Simulating Dry January in each year led to a small to moderate reduction in annual population drinking. CONCLUSION: This study provides further evidence, at the whole population level, that a combination of reasoned and implicit processes are important for alcohol use. Alcohol misuse interventions should target both processes. The integrated TPB-DPT simulation model is a useful tool for estimating changes in alcohol consumption following hypothetical population interventions.
Authors: Elizabeth McGill; Mark Petticrew; Dalya Marks; Michael McGrath; Chiara Rinaldi; Matt Egan Journal: Addiction Date: 2021-01-14 Impact factor: 6.526
Authors: Alan Brennan; Charlotte Buckley; Tuong Manh Vu; Charlotte Probst; Alexandra Nielsen; Hao Bai; Thomas Broomhead; Thomas Greenfield; William Kerr; Petra S Meier; JüRgen Rehm; Paul Shuper; Mark Strong; Robin C Purshouse Journal: Int J Microsimul Date: 2020
Authors: Tuong Manh Vu; Charlotte Probst; Alexandra Nielsen; Hao Bai; Charlotte Buckley; Petra S Meier; Mark Strong; Alan Brennan; Robin C Purshouse Journal: J Artif Soc Soc Simul Date: 2020-06-30