Motivation and emotion/Book/2019/Prototype willingness model
What is the prototype willingness model and how can it be applied?
Overview[edit | edit source]
The Prototype Willingness Model (PWM) is a decision-making model which is primarily used to explain and predict adolescent behaviours, particularly health-related behaviours. The model provides valuable insight into adolescent decision-making, and has applications for interventions. Given the vulnerability of adolescents to fall into harmful behaviours, and the devastating long-term impacts such behaviours can have, the development of effective theoretical frameworks through which to create interventions is important. This chapter examines the PWM to ascertain how the model works, its applications in research and interventions, and how it fits within the existing body of research.
Prototype Willingness Model[edit | edit source]
The PWM is a dual process decision-making model (Davies, Gibson-Miller, & Foxcroft, 2015). Gibbons, Gerrard and McCoy (1995) proposed the model as an explanatory framework for risky adolescent behaviours, with an emphasis on health related behaviours. According to the model, there are two routes to behaviour (Davies et al., 2015). The first of these is a rational, planned route using intentions (Davies et al., 2015). The second is a reactive, social pathway (Davies et al., 2015). Within this pathway, the "prototypes" that adolescents have about their peers who engage in a particular behaviour influence their willingness to engage in that behaviour. The rational pathway comprises attitudes, norms and behavioural willingness, all of which influence behavioural intentions (Davies et al., 2015). The social reaction pathway involves the impact of risk prototypes and social comparison on behavioural willingness (Davies et al., 2015). Both pathways are influenced by past behaviour (Davies et al., 2015).
Applications[edit | edit source]
The PWM can be applied to many types of adolescent behaviour to explain, predict and prevent these behaviours.
Adolescent Health Behaviours[edit | edit source]
Smoking[edit | edit source]
Several studies have examined the PWM as a means of explaining adolescent smoking behaviour. For example, a study of Norwegian youths found the social reaction pathway useful for explaining abstinence from smoking (Hukkelberg & Dykstra, 2009). Specifically, participants with negative images of smokers were more likely to abstain from smoking (Hukkelberg & Dykstra, 2009). This study is consistent with a vast body of research that has found a significant link between an individual's idea of the "typical smoker" and whether they engage in smoking (Amos, Gray, Currie & Elton, 1997; Lloyd, Lucas, Holland, McGrellis, & Arnold, 1998; Rivis, Sheeran, & Armitage, 2006). This relationship can be attributed to an implicit social comparison, whereby an individual compares their prototype of a smoker with their self-image (Hukkelberg & Dykstra, 2009). For adolescents, social image also plays a part (Gerrard, Gibbons, Stock, Vande Lune & Cleveland, 2005). Young people are pre-occupied with what others think of them, and this plays a part in their behaviour (Gerrard et al., 2005). If an adolescent has a negative idea of the typical smoker, they would not want to be perceived as a smoker by their peers, which means they could shy away from smoking (Gerrard et al., 2005). Similarly, if an adolescent has a positive image of smokers, they would presumably like to be perceived as one, which may make them more likely to smoke (Gerrard et al., 2005)
John grew up in a family where nobody smoked, and his only exposure to smoking wasthe "rebellious" characters he saw on television. As a result, John's idea of a "typical smoker" is someone with a rebellious nature and little direction in life. This is contrary to John's self-image, as he sees himself as a good student and model citizen. John also does not want to portray himself as a smoker to his friends, since he sees this as a bad thing. Both of these factors make it less likely that John will engage in smoking.
The PWM is not only useful for explaining smoking behaviour, but also for predicting it. A study of 742 African-American children found that the cognitions associated with the PWM, such as images of smokers and willingness to smoke, were useful for predicting whether children as young as 10 will engage in smoking (Gerrard et al., 2005). In fact, this study found that these cognitive factors mediated the impact of distal factors, such as living in a high-risk environment (Gerrard et al., 2005). This suggests that it may be possible to modify smoking images to prevent adolescents from initiating smoking (Gerrard et al., 2005). Similar interventions with other risky behaviours, such as use of tanning beds, have had promising results (Gerrard et al., 2005). Mirroring other successful interventions, the PWM could form the basis for smoking interventions in adolescents. By altering adolescents' prototype favourability for smoking, either by increasing favourability of non-smokers or increasing unfavourability of smokers, it may be possible to prevent smoking behaviours in adolescents (Gerrard et al., 2005).
An Iranian web-based educational intervention program for adolescent smoking, which used the PWM as a framework, found a significant difference in willingness to smoke between program participants and the control group using PWM concepts (Heidarnia, Barati, Niknami, Allahverdipour, & Bashirian, 2016). Similarly, a computer-based PWM intervention program developed for 5th and 6th graders was successful at lowering intention and willingness to smoke (Andrews et al., 2014).
The Centers for Disease Control and Prevention indicates that 9 out of 10 smokers try smoking before the age of 18, with many of them becoming regular smokers. These statistics emphasise the importance of early intervention and prevention for youth smoking. Given its proven efficacy for predicting and modifying adolescent smoking behaviour, the PWM should play a very important role as the basis for future youth smoking intervention programs.
Drinking[edit | edit source]
The PWM is also a useful framework for studying adolescent drinking (Gibbons et al., 2004; Davies, Martin & Foxcroft, 2013). Adolescent drinking often occurs in situations where peer influence is high (Gibbons, Gerrard, & Lane, 2003). Naturally, the PWM, particularly the social reaction pathway, is a good framework through which to study adolescent alcohol use. Studies suggest that a gradual shift from reactive to planned drinking behaviour occurs as individuals progress through adolescence (Coleman & Cater, 2005; Todd & Mullan, 2011). This shift is illustrated by the results of a qualitative study of UK adolescents, where younger participants reported that social situations influence their drinking, while older participants said they made plans to drink (Davies, Martin & Foxcroft, 2013). Consequently, the PWM is most useful for explaining drinking behaviour in younger adolescents (Davies, Martin & Foxcroft, 2013; Davies, Martin & Foxcroft, 2016).
Litt and Stock (2011) found that young adolescents who are exposed to Facebook profiles of older peers that portray drinking as normative may form positive prototypes of drinkers and become more willing to consume alcohol. A longitudinal study of Indigenous North American young adolescents indicated that positive drinker prototypes are associated with greater drinking willingness, and eventually increased drinking behaviour (Armenta, Hautala, & Whitbeck, 2015). Since the PWM is most useful for predicting drinking behaviour in adolescents on the younger end of the spectrum, future research should focus on developing PWM-based interventions targeted at this age group.
According to the USA National Institute on Alcohol Abuse and Alcoholism, drinking during adolescence can have many detrimental effects. These consequences include academic failure, increased risk of suicide, memory problems and increased risk of alcohol-related car crashes. The potentially harmful short and long-term effects of adolescent alcohol use mean the PWM could play a crucial role in preventing and modifying adolescent alcohol use.
Eating[edit | edit source]
The PWM can also be applied to adolescent eating behaviours. Specifically, the PWM is useful in explaining and predicting the unhealthy eating behaviours of adolescents (Dohnke, Steinhilber, & Fuchs, 2015). Adolescents who have favourable prototypes of unhealthy eaters are more likely to consume unhealthy foods, particularly fatty foods and soft drinks (Gerrits, de Ridder, de Wit, & Kuijer, 2009). A large part of why the PWM is so powerful for explaining eating behaviour is because adolescent food behaviour is largely driven by willingness, as opposed to intention (Fuchs, Steinhilber, & Dohnke, 2015).
Australian Institute of Health and Welfare statistics show that adolescent obesity rates have grown, with 25% of Australian adolescents being overweight, and that overweight people suffer higher rates of death and illness. These statistics are concerning, and the predictive power of the PWM for adolescent eating behaviour means it could be very useful for combatting the adolescent obesity crisis. If the favourability of prototypes of unhealthy eaters are modified, adolescents could be discouraged from consuming unhealthy foods (Gerrits et al., 2009).
Sexting[edit | edit source]
Although the PWM was developed for explaining adolescent health behaviours, it has also proven useful for explaining other adolescent behaviours. For example, the PWM has been shown to explain why adolescents engage in sexting, or predict whether they will engage in it. Adolescents with a favourable prototype of people who engage in sexting are more likely to send sext messages, especially if they perceived this prototype as being similar to their self-image (Walrave et al., 2015). Prototype favourability was also a strong predictor of the willingness of adolescents to engage in sexual communication with a stranger online (Branley & Covey, 2018).
The model has also been useful for understanding adolescents' behaviour on social media more broadly. A combination of the social reaction and reasoned pathways of the PWM can be used to explain and predict adolescents' disclosure of details about peer relationships online, since this behaviour can involve both reasoned decisions and spontaneous reactions (Van Gool, Van Ouytsel, Ponnet, & Walrave, 2015).
Many of these behaviours can have significant detrimental consequences. Sexting, for example, could lead to legal consequences or a damaged reputation (Russo & Arndt, 2010; D'Antona, Kevorkian, & Russom, 2010). Given the potential consequences, and the predictive power of the PWM regarding these behaviours, the model could play an important part in developing education programs to prevent adolescents from engaging in such behaviours.
Quiz[edit | edit source]
Relationship to Other Theories[edit | edit source]
Theory of Reasoned Action[edit | edit source]
In the reasoned action path of decision-making outlined by the PWM, attitudes and norms are antecedents to decisions, which are also regulated by intention (Van Gool et al., 2015). This process is the same as that which is outlined by the Theory of Reasoned Action or TRA (Fishbein & Ajzen, 1975). TRA argues that intention is the primary influencer on behaviour (Albarracín, Johnson, Fishbein, & Muellerleile, 2001). Although the PWM also explores the intention-behaviour relationship through the reasoned pathway, its social reaction pathway presents an alternative way of making decisions that does not involve intentions (Gerrard et al., 2005). Since the relationship between intention and behaviour is relatively weak during adolescence, the PWM, and its unique social reaction pathway, is more effective at predicting adolescent behaviours than the TRA (Gerrard et al., 2005).
Theory of Planned Behaviour[edit | edit source]
The Theory of Planned Behaviour (TPB) proposes that there is an additional variable, perceived behavioural control, that influences behaviour (Albarracín et al., 2001). The TPB holds that perceived behavioural control influences intention, in that someone who believes they have greater control over a particular behaviour is more likely to have a strong intention to either engage or abstain from that behaviour (Albarracín et al., 2001). With regards to health behaviours, the TWM has been found to be a more effective predictor for adolescents than the TPB, since it accounts for "unplanned" risk-conducive contexts, the impulsivity of adolescents and the influence of peers (Davies, Martin & Foxcroft, 2013). The TPB, however, has been found to be a better predictor of risky health behaviours, such as binge drinking, in older adolescents (Todd & Mullan, 2011). This is likely because of the shift from reactive to planned drinking behaviours as adolescents grow older, and the gradual growth of the intention-behaviour link (Coleman & Cater, 2005; Gerrard et al., 2005).
There is also a strong case for the combined use of both the PWM and the TPB. Studies have supported using the PWM to augment the TPB. Rivis, Sheeran and Armitage (2006) found that using variables from the PWM have been found to increase the predictive validity of the TPB with regards to adolescent health behaviours. Similarly, Dohnke, Steinhilber and Fuchs (2014) proposed that the PWM could be used along with reasoned models, such as the TPB, to gain a rich understanding of unhealthy adolescent eating behaviour.
Conclusion[edit | edit source]
The PWM is a dual-process decision-making model that is particularly useful for studying adolescent behaviours. By proposing a second decisional pathway, which is influenced by prototypes, social comparison and behaviour willingness, the PWM provides an effective means of understanding and predicting the often impulsive behaviours of adolescents. The model can be applied to various aspects of adolescent behaviour, particularly health behaviour. Since adolescents are at high risk of initiating harmful behaviours, and engaging in such behaviours can be devastating long-term, the intervention applications of the PWM make it a very significant model.
See also[edit | edit source]
- Health behaviours (Book chapter, 2013)
- Risk taking motivation (Book chapter, 2010)
- Peer influence in adolescence (Book chapter, 2011)
- Underage binge drinking motivation (Book chapter, 2016)
- Alcohol motivation (Book chapter, 2011)
- Binge drinking motivation in young people (Book chapter, 2015)
References[edit | edit source]
Andrews, J.A., Gordon, J.S., Hampson, S.H., Gunn, B., Christiansen, S.M., & Slovic, P. (2014). Long-Term Efficacy of Click City: Tobacco: A School-Based Tobacco Prevention Program. Nicotine & Tobacco Research 16(1), 33-41. doi: 10.1093/ntr/ntt106
Armenta, B. E., Hautala, D. S., & Whitbeck, L. B. (2015). The utility of the prototype/willingness model in predicting alcohol use among North American indigenous adolescents. Developmental Psychology, 51(5), 697-705. doi: 10.1037/a0038978
Branley, D. B., & Covey, J. (2018). Risky behavior via social media: The role of reasoned and social reactive pathways. Computers in Human Behavior, 78, 183–191. doi:10.1016/j.chb.2017.09.036
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Heidarnia, A., Barati, M., Niknami, S., Allahverdipour, H., & Bashirian, S. (2016). Effect of a Web-Based Educational Program on Prevention of Tobacco Smoking among Male Adolescents: An Application of Prototype Willingness Model. Journal of Education and Community Health, 3(1), 1-11. doi: 10.21859/jech-03011
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Van Gool, E., Van Ouytsel, J., Ponnet, K., & Walrave, M. (2015). To share or not to share? Adolescents’ self-disclosure about peer relationships on Facebook: An application of the Prototype Willingness Model. Computers In Human Behavior, 44, 230-239. doi: 10.1016/j.chb.2014.11.036
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