Persuasion and Influence

#BeSmartSwitchOff

The Problem

The development of technology has led to a significant increase in the amount of screen time individuals are exposed to, this includes devices such as phones, computers, tablets and televisions. Nearly one-third of children between the ages of 12 and 15 watch television and use a computer for at least 2 hours a day and 6.9% of children of this age spend more than 5 hours exposed to screens daily (National Center for Health Statistics Data Brief, 2014). By the age of 18 the average amount of time a European teenager spends on electronic devices adds up to shocking total of 3 years, therefore by the age of 80 years, they would have spent 17.6 years on these devices (Sigman, 2012). The 2006 Sleep in America Poll found that 97% of American adolescents had at least one electronic device in their rooms (The National Sleep Foundation, 2006). There is a huge breadth of evidence displaying the adverse effects of screen time particularly on children and adolescents, but can be generalised to a whole range of ages.

Increased screen time can influence people's sleep and diet quality, general health, productivity and be detrimental socially. The Blue Light emitted from screens has been shown to suppress melatonin secretion, which may delay sleep onset, and potentially lead to a decrease in overall sleep quality (Chellappa, Steiner, Blattner, Oelhafen, Götz, & Cajochen, 2011). It has been found that those who watch television over meal-times consume less fruits and vegetables and have an increased soft drink consumption, detrimental to people’s health. These contribute to an overall poor diet and, combined with inactivity linked to watching TV, can contribute to weight gain in individuals (Liang, Kuhle & Veugelers, 2008). Screen time can also have an impact on creativity and productivity. Corder et al. (2015) found that an extra hour of screen time at 14.5 years old, is approximately equivalent to 2 fewer GCSE grades at age 16. This clearly highlights the importance in reducing screen time. Finally, it has been found a 40-60% increased likelihood of screen activities is associated with High Social Neighbourhood Disorder; a social disorder that leads young people to stay indoors (Carson & Janssen, 2012). This disorder can have damaging consequences, such as reducing individual well-being and increasing fear, isolation and anxiety (Ross & Mirowsky, 1999). These could all be avoided or the impact reduced by reducing screen time.

Due to the wide range of effects that screen time can have on people, interventions have been put in place to try and reduce screen time and recommendations to help; these are focused particularly on children. For example, the Student Media Awareness to Reduce Television (SMART) involved 18 theory-based lessons and significantly reduced children’s television viewing and video game playing compared to the control group. This intervention also influenced family members to reduce their own screen time, showing that it is not only children that can benefit from interventions (Robinson & Borzekowski, 2006).

Therefore, our project looks at the benefits to reducing screen time and highlights some of the easiest and simplest ways in which people can do this.

Our Intervention

For this project we distributed a main poster aimed at promoting reasons for reducing screen time, as well as, ideas for how this could be done. The poster had the title “Reduce your screen time with...” and included images of different types of screens. It provided the key facts surrounding screen usage, benefits to reducing screen time and some simple ideas of how people can do this, for example, apps. They were put up around the University of Warwick, for example, in the Psychology Department, in the Learning Grid and outside the Library. We also posted it social media (Facebook, Twitter, Instagram, Snapchat) to target a wider audience than just students at Warwick and managed to get it shown on the big screen on the piazza.

We also discovered the “Screen Time” setting on our phones which showed us how how many hours we had spent on our phones each day; we were shocked to discover our average between us was around 6 hours! This motivated us to want to change our own behaviour but also encourage others to do the same, from this we created our challenge. The “challenge poster” tries to encourage people to reduce their screen time by 30 minutes per day and included the slogan “Be Smart, Switch Off”. The “challenge poster” was distributed around campus, as well as being posted on a variety of social media (Instagram, Facebook, Twitter, Snapchat).

Main Poster

Challenge

Poster on the Piazza Screen

Instagram 

Facebook

Main poster shared on facebook by someone
 of an older generation - Showing that this is not
just relatable for students  

Snapchat 

Persuasion Techniques

The psychological techniques that we used in the poster can be identified from the Yale Approach Model. Firstly, the message characteristics (‘what’) includes the quality and clarity of the message being sent. We have used a moderate fear appeal, as it displays the shocking statistic of attaining 17.6 years of screen time by the age of 80. Moderate fear appeals combined with instructions of how to respond are suggested to be an effective method of persuasion (Leventhal, Watts & Pagano, 1967) which is what we attempted in the poster and the “challenge poster”. Leventhal, Watts & Pagano, (1967) conducted an anti-smoking fear appeal campaign and found those who received both the fear and instructions compared to just instructions and just fear was successful in reducing the behaviour. This is why we tried to use this technique with our poster. Additionally, the message is very simple and logical helping to convey desirable consequences to behaviour change. For example, “Positive effect on well-being” and “Increased sleep quality”.

Moreover, still concerning the Yale Approach Model, the audience characteristics (‘whom’) involves factors such as the age, intelligence and mood of the target audience. In our case, we aimed to influence students at the University of Warwick as well as a wider audience on social media. Therefore, they are all of a similar age and academia, relating this to our poster, we had images of devices, such as an Iphone, which are appropriate images for the target audience. Additionally, the message is very relatable for undergraduates as studies show increased screen time is detrimental to academic results. Due to the sensitivity for rewards, there is the incentive to turn off the electronic devices in the hope of attaining better grades.

When designing the poster, we aimed for the font to be colourful, eye-catching and bold so to grab the attention of as many people as possible. According to the Elaboration Likelihood Model, the dual process model of persuasion, shows the factors the affect the ways a message is elaborated on (Petty & Cacioppo, 1986). We wanted to use the automatic/ peripheral route of persuasion, also known as heuristic processing. This involves low effort processing from the audience which is why we wanted the font and pictures to be as visually pleasing as possible. The source attractiveness will promote the behaviour change due to system one processing which is fast and unconscious. This technique is appropriate for our poster as is placed in busy locations, such as the piazza and common room, where students walk past daily. This poster stands out so passers-by will notice it, and not need to deeply analyse the content as is simple and clear.

Finally, the “challenge poster” uses the Foot-in-the-Door technique which is a gradual induction. We have advised to decrease screen time by 30 minutes a day, a relatively small step towards behaviour change. Burger, (1999) found you are more likely to comply with smaller requests which is why we utilize this technique. This technique would be beneficial, it would be too much of shock to ban students completely from using electronic devices and would also be unrealistic. By gradually decreasing the amount of screen time, they can slowly adapt and accept the new routine.

Future / Measuring Behaviour Change

Through putting the poster up around campus it is difficult to directly measure the extent of the behaviour change of the Warwick students; there is no easy way to be able to find out who has taken the message on board and have decided to cut down on screen time. However, when posting it on social media, such as, Facebook and Instagram you are able to see who has liked / shared the post, it may not give direct information on actual behaviour change but it gives an idea of who might be motivated to give it a go.

However, there may be some problems en route to goal completion. One issue is the failure to get started, some might forget to take part. To overcome this issue, we could encourage people to set reminders, or on Iphones there is a setting to limit the amount of times spent on apps, so when they go over the usage, the phone will not let you use the apps. This will eventually become a part of their routine so will become an automatic behaviour (Gollwitzer & Brandstätter, 1997).

With the hope that the persuasive techniques will encourage people to reduce their screen time, it will influence more people to do so. People take their cues from what others do due to conformity, prevalent amongst young adults (Costanzo & Shaw, 1966). Thus, the more people who are persuaded to reduce screen time, the more people will follow their lead. A positive feedback loop in behaviour will be induced because of conforming to the social norm.

References

Burger, J. M. (1999). The foot-in-the-door compliance procedure: A multiple-process analysis and review. Personality and social psychology review, 3(4), 303-325.

Carson, V., & Janssen, I. (2012). Neighborhood disorder and screen time among 10-16 year old Canadian youth: a cross-sectional study. International journal of behavioral nutrition and physical activity, 9(1), 66.

Chellappa, S. L., Steiner, R., Blattner, P., Oelhafen, P., Götz, T., & Cajochen, C. (2011). Non-visual effects of light on melatonin, alertness and cognitive performance: can blue-enriched light keep us alert?. PloS one, 6.

Corder, K., Atkin, A. J., Bamber, D. J., Brage, S., Dunn, V. J., Ekelund, U., Owens, M., Van Slujis, M. F.,& Goodyer, I. M. (2015). Revising on the run or studying on the sofa: prospective associations between physical activity, sedentary behaviour, and exam results in British adolescents. International Journal of Behavioral Nutrition and Physical Activity, 12(1), 106.

Costanzo, P. R., & Shaw, M. E. (1966). Conformity as a function of age level. Child development, 967-975.

Drake, C., Kryger, M., & Phillips, B. (2005). National Sleep Foundation. 2005 sleep in America poll: summary of findings.

Gollwitzer, P. M., & Brandstätter, V. (1997). Implementation intentions and effective goal pursuit. Journal of personality and social psychology, 73(1), 186.

Herrick, K. A., Fakhouri, T. H., Carlson, S. A., & Fulton, J. E. (2014). TV watching and computer use in US youth aged 12-15, 2012. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics.

Leventhal, H., Watts, J. C., & Pagano, F. (1967). Effects of fear and instructions on how to cope with danger. Journal of personality and social psychology, 6(3), 313.

Liang, T., Kuhle, S., & Veugelers, P. J. (2009). Nutrition and body weights of Canadian children watching television and eating while watching television. Public health nutrition, 12,, 2457-2463.

Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication and persuasion (pp. 1-24). Springer, New York, NY.

Robinson, T. N., & Borzekowski, D. L. (2006). Effects of the SMART classroom curriculum to reduce child and family screen time. Journal of Communication, 56(1), 1-26.

Ross, C. E., & Mirowsky, J. (1999). Refining the association between education and health: the effects of quantity, credential, and selectivity. Demography, 36(4), 445-460.

Sigman, A. (2012). Time for a view on screen time. Archives of disease in childhood, 97(11), 935-942.