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The study uses a 2 (Social Threat Versus. Physical Threat) x 2 (Non-Smoker Versus Smoker) between subjects full factorial experimental design to remove the chance of repetition and carryover effects, with a further manipulated based on their critical value coping response critical value classification. The independent variables are:

type of threat; Social Threat (STr) and Physical Threat (PTr), Smoking classification;

Non-Smoker (NS) and Smoker (S) with the Coping Response Critical Value; Emotion Control (EC) and Danger Control (DC). The dependent variables are: Future Smoking Attitude (FSA), Future Smoking Intentions (FSI) and Future Smoking Intent to Quit (FSIQ). The research model includes moderating variables: coping response Critical Value (CV), Physical Emotional Response (PEm), Social Emotional Response (SEm) Susceptibility to Peer Pressure (SPP) and Parental View on smoking (PV) and mediating variables: Attention to the advert (ATAD), Attitude to the advert (AAD), message derogation (MD) and the Perceived Level of Threat towards the advert (PLT) all of the variables are interval-scaled.

Operationalization of the independent variables

The independent variable of type of threat was operationalised using a number of dimensions in the preliminary manipulation tests assessing the perception of threat, the rating of threat and the associated emotional response. The type of threat

classification assessments was adopted from Schoenbachler and Whittler (1996) and tested throughout the preliminary tests. The second independent variable was the smoker classification, with those that have smoked at least one puff classified as a smoker, whereas those that have never tried classified as a non-smoker (Pierce et al.

1996). Although a previous study split adolescents into three different groups; current smoker, previous smoker and non-smoker (Hu and Bentler 1998), due to the age and stage in the smoking models (Albaum et al. 2002; Kremers, Mudde and de Vries 2004) the dichotomous approach is sufficient. The independent samples were analysed with the critical value manipulations to assess the coping responses.

Research stimuli exposure

Although previous research created static stimuli to illustrate threat appeals (Arthur and Quester 2004; Smith and Stutts 2006; Dickinson and Holmes 2008), the reliability for adolescents is not supported and regarded inappropriate. Considering new unseen warnings and anti-smoking advertisements attract greater attention than previously published ones (Krugman et al. 1994), the content needs to be interesting, attention-capturing and culturally sensitive (Blumberg 2000). Threat appeals are a combination of graphic images and words which are shown to produce greater recall than just advertisements with words (Purdy and Luepnitz 1982). The threats were developed acknowledging findings from previous research that pictorial warnings affect intention to smoke significantly more than text-only warnings (Menon, Block and Ramanathan 2002), with visual warnings alongside verbal warnings increasing discouragement from smoking and increased intentions to quit (Kees et al. 2006). As administered in previous research four exposures were manipulated in the final

research; two physically threatening stimuli and two socially threatening stimuli congruent with adolescent views. To ensure accurate content, iterations are essential to develop, test, target, and monitor exposure (Krugman et al. 1994). The iterative process created and tested different threat appeals with two messages: one socially framed message and one physically framed message. In order to ensure the message, image and content is suitable for the target segment, audience segmentation and market research is paramount to a successful social marketing campaign, showing the need ‘to put the audience at the centre of every decision’ (Pirani and Reizes 2005; p.

134). Stimuli control measures ensured that the advertisements are comparable in length, logos, headlines and message sources (Sternthal and Craig 1974) and contained simple messages, large type and graphic images that are regarded effective at communicating the risks of smoking with adolescents (Fischer et al. 1993). The introduction of a logo illustrating a pseudo tobacco warning brand (Strahan et al.

2002) was implemented. Although previous research has varied from having no time restraint (Dickinson and Holmes 2008) to only allowed participants to witness a stimuli for 2 seconds (Pechmann and Knight 2002). The stimulus was presented for a controlled amount of time of 30 seconds as implemented by Stayman and Aaker (1988) to ensure comparable results.

Sample profile and minimum sample size

The participants’ were aged between 11-13 years to ensure the results are applicable to the research objective and stage in the smoking behaviour models (Albaum et al.

2002; Kremers, Mudde and de Vries 2004). The participants’ were from a mixture of comprehensive and grammar schools in the South East of England. The mixed

schools provided an improved generalizability of the population sampling students from various socio-economic backgrounds. Although the importance of overcoming sample bias is well regarded (Morgan 1998), this segmentation criteria creates a sample bias and reduces any general population representativeness. But, due to the specific research objective, this homogenous age group need only be investigated.

The homogeneity of participants is vital to uncovering adolescents’ behavioural intentions and attitudes dependent on smoking classification and threat appeal witnessed while aged 11-13 years old.

Previous experimental design threat appeal studies have used sample sizes from different ages, different schools and different socio economic backgrounds. To the best of the author’s knowledge, no research has compared 11-13 years olds non-smokers’ responses to non-smokers’ responses. Considering reports state that 35% of adolescents’ in the UK have tried smoking by age 13 with 11% regularly smoking, a large sample is needed. This is not adopted in previous threat appeal research, but ensures a statistically valid proportion of smokers are collected to compare against non-smokers. Central limit theorem suggests that when the sample size is large enough the sampling distribution is more approximate to normal regardless of the population distribution. Hair et al. (2006) described that a minimum of 20 participants per manipulation cell is sufficient to overcome this, which is consistent with sample sizes used in recognised academic marketing journals. This suggests that to be statistically valid, at least 200 participants are needed in each sample (5 manipulations x 20 observations). In order to obtain this at current smoking rates, at least 2000 pupils will need to be surveyed to obtain an estimated 10% (n=200) smokers enabling comparative research findings and overcome incomplete and invalid responses.