Reactance

Although this study was particularly concerned with determining how an individual’s personal networks and baseline beliefs about e-cigarettes are associated with his or her assessments of an advertisement’s likely effectiveness (PME), it is also theoretically and

empirically viable to assess the extent to which these factors may influence negative reactance to anti-vaping messages. In order to assess this possibility, this study incorporated a brief negative reactance measure that has been previously validated to examine reactance in anti-vaping messages among young adults (Hall et al., 2019; Hall et al., 2017).

3.6 Perceived message effectiveness

Finally, this study examined respondent perceptions of the likely effectiveness of anti- vaping messages by utilizing a scale adapted from two separately validated PME measures (Baig et al., 2018; Davis et al., 2013). As has been discussed in the previous chapter, there is an

ongoing scholarly debate about the dimensionality of PME with some scholars arguing for a unidimensional concept (Dillard & Ye, 2008) while others have suggested multidimensional theoretical constructs (Noar et al., 2010; Yzer et al., 2015). While these debates have been assessed in anti-tobacco literatures before, the existing literature showing demonstrating

conceptualizations of the dangers and social utility of e-cigarettes suggests the need to examine dimensionality of PME in relation to e-cigarettes. As PME is situated in attitude towards the ad (Shimp, 1981) and functional attitude theories (D. Katz, 1960), the presence of differential attitudes toward e-cigarette use compared to combustible cigarette use may manifest itself in distinct PME dimensionality.

In order to account for this potential, this study employed a 6-item message perceptions

scale (Davis et al., 2013) that has been widely used to test messages for previous Real Cost

campaigns (e.g., Zhao et al., 2016) as well as a recently developed 3-item message effects scale (Baig et al., 2018) that has been validated for examining anti-tobacco advertisement reception among adults. The message perceptions scale used in this study is derived from an anti-tobacco messaging study that has proven to be one of the most influential studies in the literature in terms of conceptualizing PME (Barker, Noar, Bell, Saffer, & Morehouse, 2019) and has demonstrated validity in longitudinally predicting key changes in tobacco behavioral outcomes (Davis et al., 2017; Noar, Barker, Bell, et al., 2018). The message perceptions scale utilized in this study has been previously analyzed to examine a unidimensional construct (Davis et al., 2013), although evidence from comparative testing against the message effects scale this study employed suggests the potential for multiple dimensions (Baig et al., 2018). The scale utilized a 7-point Likert scale (Strongly disagree – Strongly agree) and asks respondents to provide information about the message such as the extent to which an advertisement grabs their attention, is

informative, or is powerful (see Table 4). Utilizing the message perceptions scale in this study allowed for the collection of respondent perceptions using an instrument that has guided multiple FDA anti-smoking campaigns and has been highly influential in guiding the existing PME literature. This study sought to provide further empirical evidence about the utility of this measure in predicting short-term changes in intentions or susceptibility as well as contribute to the scant literature employing this measure to examine the effectiveness of anti-vaping messages (Duke et al., 2016).

Table 4: Perceived message effectiveness items

This study supplemented the message perceptions PME scale with a 3-item message effects measured on a 7-point Likert scale (Strongly disagree – Strongly agree). There are two key reasons why this study used an effects-based measurement to assess PME as well as a

perceptions-based measure: 1.) evidence suggesting potentially greater explanatory power in predicting intentions and behavioral change from effects-based measures; and 2.) satisfying theoretical assertions about the need for referents and correspondence between the construction of PME measures and the overall purpose of the persuasive message they are used to evaluate. While there are few studies that have extensively explored multidimensional PME constructs, evidence from Australian assessments of a multi-dimensional PME scale suggest the utility of including message effects measures. In a 2013 study examining Australian adult assessments of anti-smoking advertisements Brennan and colleagues utilized a six-item PME measure that was eventually split into separate scales measuring message perceptions (ad-based perceived

effectiveness [ADPE]) and perceptions of message effects (personalized perceived effectiveness [PPE]). In a pre-post exposure experiment, perceptions of message effects [PPE] significantly outperformed message perception items [ADPE] and were the only items that predicted changes

Items

Message perceptions (Davis et al., 2013) 1. This ad is worth remembering 2. This ad grabbed my attention 3. This ad is powerful

4. This ad is informative 5. This ad is meaningful 6. This ad is convincing

Message effects (Baig et al., 2018)

1. This message discourages me from wanting to use e- cigarettes

2. This message makes me concerned about the health effects of vaping

in quit intentions. Additionally, when contacted for a follow-up telephone interview three weeks after exposure, higher PPE scores were the only scale to predict changes in smoking behavior (Brennan et al., 2013). In addition to these findings, recent research suggests that message effects measures may provide greater conceptual clarity to respondents which manifests as greater explained variance and lower cognitive burden to respondents (Baig et al., 2018).

The adapted UNC message effects scale was employed in this study to more closely adhere to theoretical best practices in constructing PME scales. The use of personal referents in PME scales is an important consideration as it increases the likelihood that respondents will consider themselves the focal point of a PME item (Yzer et al., 2015). This increased

correspondence increases item validity by reducing the potential for social distance effects to bias responses by asking individuals to project their personal assessments to other people (Perloff, 2009). While widely used to assess FDA campaigns, the Davis message perceptions

scale includes only a single first-person referent within the six-item scale (“This ad grabbed my attention”). Finally, this study employed an adaptation of the UNC message effects scale in order to provide greater correspondence between the stimulus message’s general purpose and the measurement instrument. As described in the previous chapter, researchers have called for the inclusion of both perceptions and effects items in PME measures (Dillard & Ye, 2008). Additionally, effects items have been theorized to be most valid when they directly address the specific aims of the advertisements that they are being employed to assess (Yzer et al., 2015). The three items adapted from the UNC message effects address both of these suggestions, adding key effects assessments (e.g., discouragement from wanting to use e-cigarettes) as well as items that speak to the specific aims of the messages that were tested (e.g., making e-cigarettes seem unhealthy or vaping seem unpleasant).

In conclusion, the measurements that were chosen for this study are constructed from previously validated scales addressing tobacco behaviors, beliefs, assessments of anti-tobacco persuasive messages, or personal network studies. They have been rigorously tested in previous large-scale studies and have been theoretically situated to efficiently provide empirical data that will fill in key gaps in scholarly understanding of how personal networks influence existing beliefs about e-cigarettes and, in turn, reception of anti-vaping advertisements. Each instrument has been chosen and adapted to achieve the greatest correspondence between the items within the scale as well as theoretical correspondence across data collection instrumentation. The next section will describe how the data gathered in this study is to be transformed and analyzed in order to answer the specific research questions and hypotheses stated in the previous chapter.

3.7 Data analysis