Conference Poster


Applying the Prototype Willingness Model to predict binge-drinking and investigate the influence of gain, loss, and combined message-framing

Abstract

Introduction: Binge-drinking is harmful, but despite people's health concerns, intentions and behaviour are often conflicting. Message framing may remedy this, although research findings are inconsistent and the literature contains gaps. This study investigated message framing’s influence on binge-drinking using the Prototype Willingness Model (PWM). Method: Overall, 124 participants (M age = 36.1, range 18-80, SD = 17.8, 70% female; 56% non-students) conducted an online experiment. Past behaviour, social norms, attitudes, and prototype perceptions were assessed before participants were randomly allocated to a gain, loss, or combined message framed condition, concerning binge-drinking’s outcomes. Thereafter, intentions, willingness, and implicit attitudes were assessed. Results: More than three-quarters of participants binge-drank, drinking roughly three-to-four drinks on three-to-four days during a fortnight. Message-framing had no effect on intentions, willingness, and implicit attitudes towards binge-drinking. The PWM had partial predictive utility for binge-drinking intentions (with prototype similarity being the strongest predictor) and willingness (with past behaviour being the strongest predictor). Lastly, implicit attitudes correlated with explicit attitudes and binge-drinker similarity. Discussion: Longitudinal research investigating message framing’s influence on binge-drinking, assessing behaviour alongside implicit and explicit PWM constructs is warranted. Going forward, interventions should target anti-binge drinking values, specifically past behaviour and prototype similarity, for behavioural change.

DOI (Digital Object Identifier)

Permanent link to this resource: https://doi.org/10.24384/5w14-4p35

Attachments

Authors

Griffin, Liberty

Oxford Brookes departments

Department of Psychology, Health and Professional Development

Dates

Year: 2023


© Griffin, Liberty

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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