How To Measure If Psa Is Successful Public Service

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Efficiently and Finer Evaluating Public Service Announcements: Additional Show for the Utility of Perceived Effectiveness

Elisabeth Bigsby

Northeastern University

Joseph North. Cappella

Annenberg Schoolhouse for Communication, Academy of Pennsylvania

Holli H. Seitz

Annenberg School for Communication, Academy of Pennsylvania

Abstruse

Contempo research has made significant progress identifying measures of the perceived effectiveness (PE) of persuasive messages and providing evidence of a causal link from PE to actual effectiveness (AE). This article provides additional evidence of the utility of PE through unique assay and consideration of another dimension of PE important to agreement the PE-AE association. Current smokers (Due north =1,139) watched 4 randomly selected anti-smoking Public Service Announcements (PSAs). PE scores aggregated by message were used instead of individual PE scores to create a summed full, minimizing the likelihood that PE perceptions are consequences of an private's intention to quit, supporting instead the PE→AE order. Linear regression analyses provide evidence of PE's positive and meaning influence on smoking cessation-related behavioral intentions.

Keywords: perceived effectiveness, anti-smoking, Public Service Announcements, behavioral intentions, aggregate score

Efficient procedures for evaluating the effectiveness of messages for the purposes of persuasion would exist a useful tool for those designing public wellness campaigns, political and social effect campaigns, and certainly for researchers seeking to evaluate various types of message effects equally they undertake theory testing. A good deal of attention and very pregnant progress has been made on this issue the past decade (east.g., Dillard, Shen, & Vail, 2007; Dillard, Weber, & Vail, 2007; Dillard & Ye, 2008; Fishbein, Hall-Jamieson, Zimmer, von Haeften, & Nabi, 2002). The purpose of the present newspaper is to accelerate the inquiry base by providing data that will raise researchers' confidence in perceived effectiveness (PE) equally a valid, if imperfect, measure of actual effectiveness (AE).

The Demand for an Efficient Measure of PE

The nearly direct way to evaluate the effectiveness of a message is to conduct a test in the field with the appropriate target population. For example, Public Service Announcements (PSAs) to be used in a public campaign tin can be compared on the outcome variables of interest against some control. For messages aimed at behavior change (bold the proper design and controls), this is perhaps the most authentic way to measure message effectiveness. Unfortunately, this strategy requires running at least a minor-scale entrada in the field and then evaluating its success in irresolute behavior, which tin have months or longer, rendering it impractical and expensive.

The obvious trouble with measuring AE is its inefficiency. Researchers and campaign designers need to know about the effectiveness of messages in accelerate of testing the terminal campaign and before deploying campaign resources. One strategy employed past advertisers, for example, has been to test preliminary versions of an advert in early stages of evolution earlier implementing the more than expensive full-fledged version. But even these preliminary versions need to exist evaluated in some way for their potential effectiveness in club to choose the all-time message for production and implementation.

Research on PE

Prior research has significantly avant-garde the development of efficient measures of PE and the validation of these measures relative to of import outcomes such as attitude and behavioral intention. Although quite encouraging, the results of these studies need to be bolstered past other data. Specifically, 3 issues need to be addressed: target outcomes, causal direction, and representativeness of the samples employed.

Target Outcomes

In experimental work, PE has been positively correlated with judged realism, amount learned from the ad, negative emotion in response to the advertizement, attitude toward the advocacy of the ad, cognitive responses (thought-list difference scores), and intention to engage in advocated behavior, and negatively correlated with positive emotional responses (Barrett, Cappella, Fishbein, Yzer, & Ahern, 2011; Dillard, Shen, et al., 2007; Fishbein et al., 2002). In add-on, a meta-assay of 40 studies (approximately iii,000 respondents) found a pregnant result size, r = .41 with 95% of the effects positive, for the PE-AE (in this example attitude) human relationship (Dillard, Weber, et al., 2007).

Having attitude, cerebral response, intention, and ultimately behavioral change information are necessary steps in validating the utility of whatsoever PE measure. Prior enquiry has largely focused on attitude toward the bulletin advancement every bit an indication of AE. However, in assessing the PE-AE relationship, the gold standard for outcomes would exist behavior change rather than attitude, emotion, or some other indicator of behavior. Short of behavior change itself, which is hard to test and certainly non efficient, a change in specific intentions regarding behaviors pertinent to the target audience is a reasonable surrogate (for meta-analyses of the intention-behavior relationship see Unhurt, Householder, & Greene, 2002; Webb & Sheeran, 2006). In the five studies conducted by Dillard, Shen, et al. (2007), only one used intention to human action as an outcome measure. Additionally, the measures employed were general rather than the very specific measures advocated past Fishbein and Ajzen (2010), in part because they are more likely to correlate with behavior. To build on the previous findings, the validation presented here focuses on intention to act in specific ways where the intention is highly relevant to the private and the time frame and behavior are quite specific. If data can be marshaled to prove that messages high in PE are associated with specific intentions consistent with the letters and pertinent to the targets of the messages, while those low in PE are non (or are less so), then conviction in PE every bit a test of a message will be enhanced.

Causal Management of the PE-AE Relationship

In a study that did utilize behavioral intention as a measure out of bodily message effectiveness, Zhao, Strasser, Cappella, Lerman, and Fishbein (2011) evaluated responses to anti-smoking PSAs and constitute that perceived argument strength was positively associated with intentions to quit smoking, r = .44, p < .001, which can exist interpreted as a relationship betwixt PE and AE. Another study presented in the same article showed a similar pattern for adolescents exposed to anti-drug messages and intention to use marijuana regularly, r = −.35, p < .001 (Zhao et al., 2011). While the correlations reported in these studies are substantial and consistent, they practice not let inferences most causal direction between PE and AE considering it is only as probable that those intending to quit smoking or those adolescents with low drug apply intentions evaluate the related ads they run across in more positive ways. Causality is very much in question fifty-fifty though pertinent intentions were advisedly assessed.

Dillard, Shen, et al. (2007) also attempted to establish that PE is antecedent to AE, and non the reverse, past running structural equation models with their data in both directions. In both cases, one study used attitude as a representation of AE and the other behavioral intention, the PE → AE society fit the data better than did the reverse gild model. These findings are certainly consistent with PE being causally prior to AE, but they cannot be definitive in the same style as an experiment with random assignment. Of the five studies described in the article, only the fifth manipulated PE by telling students that a given message was or was non constructive and examined the consequences of this manipulation on behavioral intention. The results showed that messages thought to be effective were more than likely to exist associated with increased behavioral intention consistent with the bulletin's advocacy. This elegant experimental approach immune the researchers to control bulletin content completely and but manipulate the perception of effectiveness. In the end, this highly suggestive finding needs to be generalized to a larger set of messages using PE measures to select letters in advance, randomly assigning individuals to messages received, and testing an outcome in the form of intention or behavior that is pertinent to the individual.

Representativeness of Samples

Participants

Non surprisingly, a majority of the participants in PE-AE related research have been college students. All of the samples employed past Dillard, Shen, et al. (2007) and the majority of the samples in Dillard, Weber, et al.'s (2007) meta-analysis were college students. Student samples surely do not invalidate the findings, merely if PE measures are to exist employed in the context of public campaigns where the audition is much broader than a college population, information technology is necessary to prove that the PE–AE relationship holds in these samples. While a few studies accept focused on adolescent samples consisting of middle school and high school students (e.g., Barrett et al., 2011; Fishbein et al., 2002), even fewer studies take recruited nationally representative developed samples.

Messages

A multifariousness of bulletin topics take been studied in this context. Dillard, Weber, et al.'due south (2007) meta-assay provides an overview of the variety of message topics, ranging from school exams to sexually transmitted diseases to flossing to city taxes. However, the number and diversity of message themes within each topic has been much more express, likely because of technology and available resources. Our research contributes to message sample representativeness past including a large number of ads (N = 100) within the same topic (anti-smoking) but with a diverseness of message themes (e.g., expiry, secondhand smoke, strategy for quitting). The theme of the message can bear upon PE because the theme is linked to the argument of the message. Therefore, it is important to include a variety of bulletin themes, not just message topics, when examining the utility of PE.

Measurement of PE

Measures of PE have varied greatly with no agreed upon set of items used for message assessment (Yzer, Vohs, Luciana, Cuthbert, & MacDonald, 2011). In fact, different operational measures of PE have been significantly correlated with dissimilar issue measures (e.1000. Barrett et al., 2011; Dillard, Shen, et al., 2007). To meliorate understand message effectiveness, Yzer et al. (2011) examined the conceptualization and operationalization of PE and the affective antecedents to PE in the context of anti-drug PSAs. Using seven global PE statements from previous enquiry, the authors conducted a factor analysis which revealed 2 PE factors: convincingness and pleasantness. However, Yzer and colleagues point out that the items most widely used are role of the convincing factor, which only captures part of how PE has been conceptualized.

Examining the differences between the two dimensions of PE more closely, Yzer et al. (2011) found that the unlike factors of PE correlated with unlike retrospective affective responses. The convincing factor was highly correlated with arousal (e.g., excited vs. bored), r = .74, and the pleasantness factor was highly correlated with valence (e.g., happy vs. unhappy), r = .66. In addition, the authors found that the anti-drug PSAs the adolescents rated highest in PE were also the messages with a combination of high arousal and negative valence ratings, which is consistent with a neat bargain of fear appeal enquiry. Even if touch on is an ancestor of PE, Yzer et al.'s results indicate that PE is strongly correlated with melancholia responses. Thus, both cognitive and affective responses should be taken into consideration when assessing the PE of a bulletin. Our study examines the impact of both emotional responses to PSAs and more traditional PE items on behavioral intentions.

Hypothesis

The case for the validity of PE of persuasive letters is solid but incomplete. The set of messages that accept been tested with measures of PE needs to grow; the population tested needs to be more representative; the outcomes need to target behaviors (or intentions likely to tap those behaviors) relevant to the target audience; and a range of PE judgments needs to exist tested in club to show that high doses of PE have greater influence than moderate doses and moderate doses more influence than low.

In the present report, a full general population of adult smokers was exposed to four anti-smoking PSAs randomly selected from a large set (N = 100). After viewing the PSAs, viewers indicated their intention to quit smoking permanently and completely likewise as other intentions apropos actions that can assist with the cessation process. We were primarily interested in intention to quit because the specific language and time frame provides a conservative test of PE and considering it is the intention closest to the behavioral gold standard by which many anti-smoking campaigns are judged successful or not. Included in the responses after each PSA are evaluative assessments of each bulletin's persuasive qualities.

There are three advantages to using a large sample of smoking cessation letters. First, the letters covered a range of themes and stylistic features, allowing letters to range in terms of perceived effectiveness. Second, both the message and message order were randomly assigned to participants, meaning each participant should have had a unique viewing feel. Third, a large sample of letters allowed united states to utilize an aggregate PE score instead of individual PE scores to predict behavioral intentions, minimizing the likelihood that the causal management is annihilation other than from PE to individual beliefs intentions (AE). The amass PE score was created by taking the boilerplate score for each message (from the set of respondents who viewed the message) and assigning information technology in place of each private score for that message. Using the boilerplate score for each message helps command for other factors that may influence an individual's evaluation of information technology (due east.1000., readiness to quit and message order) and provides what we believe to exist a less biased and more authentic reflection of the message's potential influence on behavior. The average score for each of the four messages an individual saw were then summed to create an overall aggregate PE score (see Effigy 1). The large sample of smoking cessation messages allowed the states to aggregate the scores this way because each person watched a dissimilar set of PSAs, so each person still ended upward with a unique overall PE score. Thus, the amass scores were used to accost causality considering the behavioral intentions of one private could not cause the message evaluations of the other individuals who watched the same message. This procedure is similar to conducting a written report in two parts with separate samples. For example, suppose participants of the outset sample rated the PE of all the messages and the participants of the second sample were randomly assigned to view four messages and subsequently rated their intentions to engage in smoking cessation-related behaviors. If we used the PE scores from the first sample to calculate a sum PE score for each participant in the second sample and used information technology to predict the behavioral intentions of the 2nd sample participants, in that location is no fashion the intention scores could be causally prior to the PE scores because they came from a unlike sample of people. This hypothetical study using two separate samples is virtually identical to the methodology used in the electric current report with one sample.

The creation of participant sum perceived effectiveness scores aggregated by video. Individual PE ratings of each video were first aggregated by video, then aggregate video PE scores were substituted for each individual's PE score for the videos they watched. Finally, the aggregate video scores were summed to create a unique summed aggregate PE score for each participant. In the figure, P = participant, PE = perceived effectiveness score, Five = video, x = the total number for that variable.

We hypothesized that exposure to anti-smoking messages rated as persuasive in amass would be associated with college reported intentions to quit smoking, reduce smoking, and talk near quitting with others at the individual level. Because messages were assigned to persons at random, and because amass scores across PSAs are used to predict message force, PSAs and their evaluations are a random variable. To insure that the results from the random variable (perceived message effectiveness) are not confounded by other factors, controls like readiness to quit (stage of change), need for cognition, and other private differences were included in all analyses.

Method

Data were nerveless from two different samples with only minor differences in design; these are referred to equally Study 1 and Report 2. The method for both studies is presented in this section; all differences between the studies are presented in text.

Participants

Participants (Study 1 Northward = 566, Study 2 North = 630) were drawn from a nationally representative sample and were current smokers who reported smoking at least five cigarettes a day and more than 100 cigarettes in their lifetime. The hateful age for Report i was 49.60, SD = 11.01, range: 19–66. For Written report two, the hateful historic period was 46.twenty, SD = 11.85, range: 18–65. All participants were role of the KnowledgePanel, established and maintained by Noesis Networks (KN). Potential KnowledgePanel participants are starting time selected through random digit dialing and address-based sampling and are and then contacted by trained interviewers and recruiters at KN. Participants without a figurer or internet admission are provided with the necessary equipment at no accuse if they would like to participate in the KnowledgePanel. Incentive points tin can be earned for completing surveys and redeemed for cash. KnowledgePanel participants are notified about surveys for which they qualify and each panelist determines which surveys south/he would similar to complete. Recruitment was done by KN through their KnowledgePanel and connected until the desired number of completes was obtained.

Dropped participants in Study 2

Xx-six individuals were dropped from analyses because their video viewing times were either under 25 seconds (all PSAs were at least 25 seconds in length) or over 600 seconds (the longer time allowed for differences between broadband, punch-upward, and other internet connection users). In addition, 49 responses from 39 individuals were deleted due to the video viewing time of 1 or two PSAs. The other responses of these individuals were included in aggregate calculations and the private behavioral responses used in analyses.

PSA Videos

One hundred anti-smoking television PSAs (60 in Written report i, forty in Written report 2) were selected from a collection compiled from various sources including the American Legacy Foundation and diverse state health agencies. All PSAs were professionally produced and many, merely not all, had aired as part of either state or national campaigns betwixt 1998 and 2007. The major themes of the PSAs were (a) affliction and death, (b) selling affliction and expiry, (c) endangers others-secondhand smoke, (d) endangers others–burden (negative consequences your family may endure if you become ill and/or die), (eastward) smokers' negative life circumstance, (f) marketing tactics (how tobacco companies market their production), and (one thousand) strategy for quitting. Withal, these themes are full general categorizations of the master themes; many of the PSAs had two or even iii themes.

In both studies, each participant watched 4 PSAs that were embedded within the online questionnaire. Within the survey, both PSA choice and order were completely random. Thus, each person was likely to receive a dissimilar set of smoking abeyance PSAs. When there was PSA overlap, individuals were likely to have received them in a different club and in a different context. In the context of each study and the sets of potential PSAs, total PSA exposure is truly a random variable.

Procedures

Participants were randomly selected from active KnowledgePanel members; individuals who participated in the first report were excluded from the option process and were therefore not allowed to participate in the second written report. Selected participants received an e-mail notifying them of a new survey with a link to the questionnaire. Reminder emails were sent to all initial participants after three days of non-response before additional participants were randomly selected and emailed. Surveys could exist taken by KnowledgePanel members on whatever computer with an internet connectedness. First, a screen providing a brief description of the report was displayed; continuing to the next screen provided unsaid consent. Afterwards viewing the initial screens, individuals answered several questions near smoking, their health, and individual differences. Participants then watched one PSA and answered questions near that specific message; this process was repeated for each of the adjacent three PSAs. Finally, individuals answered questions well-nigh their behavioral intentions, cocky-efficacy, and beliefs and attitudes related to smoking and health. At the end of the questionnaire, participants were thanked for their time and were given an opportunity to provide additional thoughts or feedback. On average, it took betwixt 23 and 28 minutes for participants to complete either study.

Independent Measures

Perceived message effectiveness

PE was assessed by four items on a five-point Likert-type scale (i = SD, 5 = SA). The items included "This ad was convincing" and "Watching this ad helped me feel confident almost how to best bargain with smoking." Similar to Zhao et al. (2011), favorable and unfavorable thoughts about the message were too measured on this scale: "The ad put thoughts in my mind virtually quitting smoking" and "the advert put thoughts in my listen nigh continuing to fume."

To create the PE score, unfavorable thoughts (b) were first subtracted from favorable thoughts (a). The resulting score was divided by two and added to three ([(a-b)/2]+iii) and so that it was on the same v-point scale every bit the other PE items. The newly created thoughts score was then added to the other 2 items and the sum of those items was divided by three (Cronbach's α = .75, m = ii.98, SD = .82). The PE scores were so aggregated across respondents by PSA (by study to preserve any differences in PE that may exist). Finally, the mean PE scores for the four PSAs each private saw were added together to create a sum aggregate PE score (meet Figure 1), range: 4–twenty. The hateful and standard deviation can be found in Table 1.

Tabular array one

Means, Standard Deviations, and Correlations of Major Variables

	Mean (SD)	one	ii	3	4	5	vi	seven	viii	nine	ten	11	12
ane. Amass PE	xi.91 (.57)	1
two. Readiness	five.50 (2.89)	.08*	1
three. NFC	two.50 (.77)	−.06	−.06*	1
iv. Dependence	4.22 (ii.35)	.05	−.07*	.14**	one
5. Aggregate Fearfulness	9.60 (.84)	.82**	.04	−.04	.07*	one
6. Aggregate Pride	viii.08 (.33)	.45**	.08**	−.03	.05	.37**	1
7. Aggregate Promise	ix.31 (.57)	.64**	.09**	−.05	.04	.43**	.83**	one
eight. Aggregate Guilt	10.12 (.83)	.85**	.05	−.06*	.06	.92**	.42**	.l**	ane
9. Aggregate Anger	9.82 (.54)	.44**	.04	−.04	.04	.63**	.03	.05	.55**	1
10. Quit	2.twenty (.75)	.09**	.55**	−.03	−.05	.06*	.ten**	.x**	.07*	.04	one
11. Reduce	2.81 (.83)	.13**	.56**	−.08**	−.09**	.08*	.11**	.13**	.09**	.02	.66**	ane
12. Talk	2.52 (.95)	.15**	.46**	−.05	.00	.12**	.09**	.xi**	.12**	.07*	.54**	.60**	1

Emotional responses to PSAs

Yzer et al. (2011) found that the pleasant dimension of PE, captured by semantic differential items that assessed the advertising as good-bad and negative-positive, was highly correlated with the valance (happy vs. unhappy) dimension of affect. In other studies, emotional connotations of letters take been significantly correlated with PE (e.g., Biener, McCallum-Keeler, & Nyman, 2000; Dillard & Peck, 2000) and highly emotional narratives have been positively associated with smoking quit attempts (Durkin, Biener, & Wakefield, 2009), providing more evidence for the need to business relationship for emotional responses to messages as well equally traditional cognitive components of PE.

The five potential emotional responses chosen were fear, guilt, anger, hope, and pride. The items asked the respondents to betoken their agreement with the argument "I felt…" on a 5-point Likert-blazon scale (1 =SD, v = SA). Emotional response scores were also aggregated by PSA (by study) and individual sum scores were created based on the four messages each person saw, score range: 4–20. Means and standard deviations for each emotional response are presented in Table one.

Dependent Measures

Behavioral intentions

Properly measured behavioral intentions accept often been used in advice and psychological inquiry as a good predictor of behavior (Hale et al., 2002; Webb & Sheeran, 2006). Individuals responded to three different behavioral intention items ¹ on a 4-point scale (1 = definitely will not, 4 = definitely will). Items asked participants how probable it was in the next three months they would "quit smoking completely and permanently," "reduce the number of cigarettes you lot fume in a day," and "talk to someone (friend, family member, spouse) about quitting." These 3 items were examined both as an overall measure of smoking cessation intention and private behavioral intentions. Means and standard deviations are provided in Table 1 for the individual intentions.

Control Measures (Pre-PSA Exposure)

Variables that may affect participant responses to the PSAs were also measured and included in analyses for control purposes. The means and standard deviations for all control measures are too included in Tabular array i.

Readiness to quit

An individual's intention to act or not act must start with a decision about the beliefs; this thought is outlined in particular in the transtheoretical model'due south construct stages of change (Prochaska & DiClemente, 1982). Therefore, it was expected that an individual's readiness to quit smoking would take an influence on their future quitting-related behavior, regardless of the PE of the message.

The participant'due south level of mental and/or physical preparation to attempt to quit smoking was represented by a modified ladder of contemplation (Biener & Abrams, 1991). Response options ranged from 0 (I have no thoughts about quitting smoking) to x (I am taking action to quit smoking). Biener and Abrams (1991) accept validated this scale as a measure of motivation to stop smoking.

Nicotine dependence

Participants too responded to the Fagerström Test for Nicotine Dependence (FTND), a revision of the Fagerström Tolerance Questionnaire (FTQ), that is meant "to provide a short, convenient cocky-report measure of dependency on nicotine" (Heatherton, Kozlowski, Frecker, & Fagerström, 1991, p. 1119). Items were a mix of open-ended and stock-still response. Stock-still response options were either on a four-point calibration (range: 0–3) or a 2-indicate scale (range: 0–1) (Heatherton et al., 1991). Cronbach's alpha was .59, which is similar to previous inquiry that reports Cronbach's alpha ranges of .61 to .64 (Heatherton et al., 1991; Pomerleau, Carton, Lutzke, Flessland, & Pomerleau, 1994).

Both the FTQ and FTND exhibit only moderate levels of internal consistency (come across Heatherton et al., 1991). However, prior enquiry has assessed the test-retest reliability of the scales and the relationship of the scales to biochemical indicators of smoking heaviness and other measures of external validity (e.g., years smoking, other addiction scales) (Heatherton et al., 1991; Pomerleau et al., 1994). Pomerleau et al. (1994) establish the FTND had a higher Cronbach'due south alpha and ameliorate examination-retest reliability than the FTQ, although the scales were not significantly unlike on their measures of external validity. Given that the FTND is meant to measure a biochemical experience and we are using information technology every bit a command variable, we do not believe the depression reliability negatively affects our data analyses.

Need for cognition

Need for cognition is an individual difference variable that influences the persuasion processes (for a review see Cacioppo, Petty, Feinstein, & Jarvis, 1996) and was therefore included to control for any message elaboration differences that occurred between individuals. Four items were selected from Cacioppo and Petty'due south (1982) calibration and two were reverse coded. Participants responded to items on a 5-point scale (1 = a lot like me, v = not at all like me). Cronbach'south alpha for this scale was depression (.56), which was probable due to the small-scale number of items and fact that ii were reverse coded. Negatively worded items and reverse coding have been establish to reduce scale reliability and validity (e.thousand., Barnette, 2000; Schriesheim, Eisenbach, & Hill, 1991). Regardless of the depression reliability, demand for cognition was kept because factor analysis suggested the items loaded all-time on i factor and because it was a control variable.

Preliminary Analyses

A correlation matrix of the major variables of involvement is presented in Table 1. The data sets were combined for analyses with a dummy variable for study employed to control for study effects. It is of import to note that readiness to quit was moderately correlated (p ≤ .01) with all of the behavioral intentions, which is not surprising considering the original exam of the readiness to quit measure. Biener and Abrams (1991) provided the significant correlation between readiness to quit and intention to quit as evidence of concurrent validity for their measure out (.64 correlation, p < .001). In addition, two of the labels provided on their ladder (ten: I am taking action to quit smoking, and viii: I am starting to recollect about how to reduce the number of cigarettes I smoke a day) are very similar to two of our intentions ("How likely is it that in the adjacent 3 months you will quit smoking completely and permanently", "How likely is it in the adjacent 3 months you will reduce the number of cigarettes you lot fume in a day"). Thus, the similarity between these measures is expected to produce positive and significant relationships. It is for this reason that decision-making for readiness to quit smoking was considered crucial to testing PE's human relationship with behavioral intention. If PE is significantly associated with the behavioral intentions when decision-making for readiness to quit, it provides prove that PE explains variance in behavioral intention over and in a higher place that due to an individual's readiness or stage of alter.

The correlation matrix also shows moderate to loftier levels of correlation between the amass emotion variables. Four of the variables yielded highly correlated pairs, fright and guilt (r = .92) and promise and pride (r = .83). Considering of the high correlations and to avoid collinearity issues, these pairs were summed to create index scores of negative and positive emotional responses, fright-guilt (Cronbach's α = .84, m = nineteen.73, SD = 1.64, range: viii–40) and hope-pride (Cronbach's α = .78, m = 17.39, SD = .87, range: 8–40). Acrimony was moderately correlated with guilt (r = .55, p ≤ .001) and fear (r = .63, p ≤ .001) and one of the behavioral intentions (r = .07, p = .02). However, because of concerns over the vague wording of the anger item, it was not used in the analyses. ²

Nosotros conducted an exploratory factor analysis in SPSS 18 using the maximum likelihood procedure to determine the ceremoniousness of creating an overall behavioral intention calibration. The results showed that the iii intentions loaded all-time on 1 dimension; factor loadings ranged from .83 to .86. Therefore, the intentions were summed to create an overall intention score with a Cronbach'southward blastoff of .82, demonstrating adequate internal reliability. The mean score was 7.52 with a standard deviation of ii.18 (range: 3–12).

Analysis Program

In order to fully examine the information, ii analysis strategies were used. Starting time, we ran linear regression models with each of the three independent variables (aggregate PE, aggregate guilt-fear, aggregate hope-pride) and the overall behavioral intention score. 2d, separate linear regression models were estimated for each behavioral intention, again with each of the three independent variables. The 3 independent variables could not exist included in the same model estimate considering of collinearity; aggregate PE was significantly correlated with all of the amass emotion evaluations (Pearson's r ranged from .45 to .86) and all of the aggregate emotion scores were significantly correlated with each other (see Tabular array 1) ³ . In addition to the command variables listed above, study (Report i = 0, Written report 2 = 1) and demographic information (historic period, gender, racial/ethnic identity, educational activity, income) were also included as controls ^four . Race/ethnicity and education were dummy coded for the regressions (European American/White = 0; less than high school education = 0; all other categories were compared to these). The results of both strategies are detailed and presented below. All regression analyses were conducted in STATA 11.

Results

Tabular array 2 contains the results for the three independent variables on each intention including the overall intention score; the table likewise includes the R² for each model (including all controls). ^v–six The results of the control variables are only discussed in text. Stata employs listwise deletion past default and resulted in a final Northward = 1,139. We kept this strategy because the number of missing observations was not not bad, less than 5% of the possible observations (1,196), and would likely not change results.

Tabular array ii

Summary of Separate Linear Regressions of the IVs on the Six Behavioral Intentions (with Study as a Control Variable)

4	Intention (DV)
Amass Perceived Effectiveness	Overall Intention	Quit Smoking	Reduce Cigarettes	Talk to Someone
B	.36	.05	.thirteen	.17
SE	.10	.04	.04	.05
β	.ten *	.04	.09 ***	.11 ***
Rtwo	.41	.33	.36	.26
Aggregate Fearfulness-Guilt
B	.ten	.01	.02	.06
SE	.04	.01	.02	.02
β	.07 *	.03	.05	.10 **
Rii	.40	.33	.35	.25
Aggregate Hope-Pride
B	.15	.04	.06	.04
SE	.06	.02	.03	.03
β	.06 * a	.04 #	.07 **	.04 a
R2	.twoscore	.33	.35	.25

Demographic Differences

Demographic variables (age, gender, racial/indigenous identity, educational activity, income) were included in all regression models as controls because of the large and diverse samples, and considering many public health practitioners are interested in such differences. Still, considering they are not a primary interest in this study, but the significant differences are reported here. Consistent differences in behavioral intentions were found based on race/ethnicity, gender, and age. For all behavioral intentions, African Americans/Blacks reported significantly college levels of intention than European Americans/Whites (p-values ≤ .001). Women were significantly more than probable than men to written report intentions to reduce the number of cigarettes smoked a solar day (p-value < .001), and age was positively and significantly associated with intention to talk to someone about quitting (p-value < .001).

Overall Intention

The amass PE score, aggregate fear-guilt index, and amass hope-pride alphabetize were each significantly associated with overall intention to engage in smoking cessation behaviors. Readiness to quit was the merely command variable significant in each regression model, p < .001.

Separate Behavioral Intentions

Quit smoking completely and permanently

None of the iii contained variables were significantly associated with this intention. In each model, report neared significance (p-values ranged from .11 to .15) and readiness to quit was again a meaning predictor (p < .001).

Reduce the number of cigarettes smoked a solar day

Both aggregate PE and aggregate promise-pride were significant. Readiness to quit was positive and significant (p < .001), while need for cognition was negative and meaning (p-values ranged from .01 to .04) in all three regressions.

Talk to someone (friend, family fellow member, spouse) near quitting smoking

Amass PE and aggregate fear-guilt were significantly associated with intention to talk to someone nigh quitting. Once more, readiness to quit was a significant predictor (p < .001).

Additional Analyses

In several of the regression models, the control variable for study was significant or about significance (p ≤ .15). As a upshot, the findings may be affected by differences in characteristics of the two studies. Thus, the two data sets were compared on each of the major variables. The aggregate PE scores were significantly different (t = 18.18, p < .05, equal variances not assumed); PE scores were significantly higher in Study 1 (grand = 12.xx, SE = .02) than Study 2 (g = 11.66, SE = .02). There was too a significant difference in responses to the fearfulness-guilt index (t = 27.xx, p < .05, equal variances not causeless); Study 1 again had higher scores (yard = 20.81, SE = .06) than Study 2 (m = 18.76, SE = .05). Study ane also had significantly higher hope-pride scores (m = 17.77, SE = .03) than Report 2 (thou = 17.04, SE = .03), t = sixteen.01, p < .05. However, the two studies were similar in terms of the participant samples including nicotine dependence, readiness to quit, and gender (p-values ranged from .xiv to .48).

To better understand the differences between the studies on the contained variables, nosotros re-ran the regression models for each written report separately. Because our main interest is in the most difficult intention, to quit completely and permanently in the next 3 months, only it and the overall intention measure were re-estimated. The results of the additional analyses are presented in Table three, which again includes the R² for each model with command variables.

Table three

Summary of Linear Regressions by Written report

	Intention (DV)
IV	Study 1		Study 2
Amass Perceived Effectiveness	Overall Intention	Quit Smoking	Overall Intention	Quit Smoking
B	.38	.05	.37	.06
SE	.xiii	.05	.xv	.05
β	.10 **	.04	.08 *	.03
Rii	.37	.31	.44	.36
Aggregate Fright-Guilt
B	.10	.01	.10	.02
SE	.05	.02	.06	.02
β	.07 *	.02	.05	.03
R2	.36	.31	.44	.36
Aggregate Hope-Pride
B	.25	.08	.07	.00
SE	.09	.03	.09	.03
β	.09 **	.08 *	.02	.00
R2	.36	.31	.44	.36

Discussion

We conducted a conservative examination of the PE→AE relationship and found additional evidence that PE precedes AE. Using aggregated message scores to predict individual behavioral intentions reduces the possibility that individuals motivated to appoint in behavioral changes prior to message exposure also rated those messages as more effective and and so reported higher intentions to engage in related behaviors, diminishing the influence of the individual's motivations prior to bulletin exposure on their perception of the messages. In addition to using aggregate PE scores, we likewise controlled for private factors that are known to influence behavioral intentions, such as readiness to quit smoking (which was the most pregnant predictor variable). Obtaining significant results on specific intentions thus supports the claim that PE precedes AE. Our study likewise asked specific intention questions framed in a specific time menstruation, included a big sample of smoking abeyance PSAs (randomly assigned so no individual saw the aforementioned combination of messages), and included a nationally representative sample of developed smokers. Therefore, 3 issues in previous PE research were directly addressed: causal direction, measures of intention, and representativeness of the samples. It should also be noted that the primary behavioral intention evaluated here is hard to change with a few anti-smoking ads. Whatsoever success in irresolute smokers' intentions to quit suggests that PE is a proficient indicator of bulletin effectiveness.

PE, Emotional Responses, and Smoking Cessation Intentions

PSAs rated as more effective, as judged by both traditional cerebral responses and emotional responses, were associated with intentions to engage in smoking cessation activities, although not uniformly or under all conditions tested. The ii most of import findings are: (a) PE was positively and significantly associated with the overall intention measure and (b) the hope-pride index was positively associated with intention to quit smoking completely and permanently in the next three months (near significance in the combined data, significant in Study ane). Although significant results for overall intention and intention to quit smoking were merely obtained in one of the data sets, it is particularly encouraging as all analyses included several control variables that were known or anticipated to have pregnant relationships with smoking cessation intentions. In improver to the command variables that made for a conservative test, the diction of the intention measures was particularly strong. Emphasizing that the intention measures refer to permanent and complete behavior alter within a curt time frame makes them an adequate and more realistic substitute for measures of actual beliefs, which adds to our confidence in the predictive validity of PE.

While intention to quit smoking is the most desirable intention from a public health perspective, information technology is also the nearly hard to obtain and least likely to occur later on exposure to a PSA (or several). That PE and emotional responses significantly predicted some of the other smoking cessation-related behavioral intentions is as well of import from a applied standpoint. PE significantly predicted the other smoking cessation-related behavioral intentions: reduce the number of cigarettes smoked a day in the adjacent three months, and talk to someone (friend, family member, spouse) about quitting smoking in the next three months. These results propose that PSAs can at least contribute to behavioral intentions, which may be the most nosotros can expect from an anti-smoking campaign (as opposed to expecting outright behavior alter).

Other Influences on Smoking Abeyance Intentions

In addition to the relationship between PE and smoking cessation intentions, two other patterns emerged. First, readiness to quit had a articulate and pregnant association with all smoking abeyance intentions. As previously discussed, this result is not surprising, especially because how Biener and Abrams (1991) created their smoking cessation intention scale, merely it is worth pointing out every bit this issue is consistent with the smoking cessation literature. Second, African American/Black individuals were consistently more likely to intend to engage in these cessation-related behaviors than European American/White individuals. No other racial/ethnic identity was significantly dissimilar from European American/White individuals on any of the cessation intentions.

Differences Between the Studies

The results from the ii studies yielded inconsistent results. The studies were secondary analyses from existing data sets with the two sets of PSAs selected, originally, for different reasons. The ads used in Written report 1 had greater variance in the PE and emotional response scores than those is Report 2. In Study 1, the ads were chosen from a large sample (about i,000) of anti-smoking PSAs to maximize variance in statement strength and message sensation value. The highs and lows on these factors drove the selection of ads. In Written report 2, ads were selected based on message theme (east.yard., disease and death, positive frame of quitting, etc.) to fill in the gaps left past Written report ane and so that when combined, the multifariousness of message themes was an approximation of the set equally a whole. As a consequence, the iii message themes judged to be the least constructive in both studies–marketing tactics messages, cosmetics messages, and smokers' negative life circumstances messages ⁷ –fabricated upwardly a greater majority of the ads in Study 2. These iii themes accounted for approximately thirty% of the ads used in Study 2, while comprising 11% of the ads in Study 1. The higher probability of seeing one or more of the less effective themes dropped the PE scores in Study 2 and resulted in less variance among the participants' responses. In the end, the two studies together yield a set of themes that map, in their frequency, the full gear up of themes in the i,000 ads. Therefore, in our view, the results from the total set of combined PSAs are more representative of anti-smoking ads in full general.

A strong argument can be made that PE is a good mensurate of AE. In the combined data, PE predicts overall intention and for each of the three components of intention, the management is positive for all and near (t > i.4) or past significance for ii of the three individual intention measures. Two of the 3 intention measures are most quitting or reducing smoking, while the other is about quitting with assist, which is known to increment the success charge per unit for quitting by a factor of two (Sutherland, 2002). The two sets of aggregate emotion scores – one positive and 1 negative – add no variance explained of whatsoever effect to any of the intention measures, aggregate or individual. These findings suggest that emotional characteristics are inconsequential additions to any measures of PE employed hither and tap primarily into believability and convincingness.

Nosotros would offer one caveat to the to a higher place claims. The almost of import intentions are those linked to reducing smoking directly, with intentions to seek quit help secondary. In the combined data, hope-pride was at or about significance in predicting intentions to quit and reduce smoking, more often than not due to the effects of Study 1. These results may seem too inconsistent to exist trustworthy, except that some survey studies of intentions to quit smoking take reported substantial increases in variance explained when hope and pride – emotions clearly related to elevated levels of positive self-affirmation – were included as predictors (Cappella, 2007). We would suggest serious consideration of request questions about pride and hope, which are appeals to positive self-affidavit, in evaluating ads for their effectiveness.

Implications

These results support the use of PE as an indicator of potential beliefs modify (AE) and demonstrate the utility of a concise closed-ended measure of PE. Although changes in behavior are ultimately the aureate standard for successful messages (run into Snyder, 2001), messages associated with healthy behavioral intentions are important to identify for two reasons. First, the link between behavioral intention and actual behavior is positive and meaning, suggesting that past predicting behavioral intention we tin predict actual behavior. As demonstrated in this study, messages that are perceived every bit more effective are associated with intentions to engage in behaviors consequent with the message advancement. Even when the focus of the bulletin is to advocate a difficult behavior, similar smoking cessation, effective letters afflicted important intentions similar reducing the number of cigarettes smoked a day, while controlling for several primal variables. The results of this report provide additional evidence of the important office persuasive mediated letters play in behavior alter in combination with well understood factors similar readiness (stages of change) and efficacy in health related behaviors.

Equally has been pointed out past other scholars, tracking and measuring actual behavior is difficult, time consuming, and plush (e.g., Dillard, Weber, et al., 2007; Snyder, 2001). One of the goals of this report was to provide bear witness of the utility of a curt mensurate of PE. Based on a mensurate of argument forcefulness developed and tested by Zhao et al. (2011) and message evaluation by Fishbein et al. (2002), this mensurate of PE uses only 4 items and had an adequate internal reliability. Also made clear in this measure out is the referent, which has non been consistently specified in previously used measures (Dillard, Weber, et al., 2007) and has been found in some studies to measure out multiple referents (Dillard & Ye, 2008). Specifically, the thought items used the linguistic communication, "the ad put thoughts in my listen virtually…", making 3rd-person furnishings less likely. Using a short and articulate measure of PE is advantageous for researchers and practitioners alike, providing accurate evaluations of messages that can exist used with a diverseness of populations (due east.yard., young, less educated) without taking up valuable time or resources.

Practically, the results of this study provide guidance for researchers, marketers and others who want to evaluate the effectiveness of PSAs. Determining the ads with the highest PE scores will allow evaluators to select the ads with the greatest potential to influence behavioral intentions. In the context of these studies, that means selecting the ads that were associated with people intending to quit smoking completely and permanently, reduce the number of cigarettes they smoke daily, and intending to engage in more than 1 smoking cessation related action – all within the next 3 months. Addressing the pleasant-unpleasant dimension of PE by assessing emotional responses to the ads also aids in selecting the PSAs with the most potential to positively bear upon intentions. While emotional responses did not result in more variance explained than PE, different emotional responses (positive or negative) were associated with unlike behavioral intentions. Most important, in this context, messages that elicit feelings of hope and pride may contribute to intentions to reduce smoking behaviors directly (e.chiliad., quitting and reducing the number of cigarettes).

Study Limitations and Strengths

As with whatever study, at that place are limitations. Self-reported behavioral intention was used every bit the effect measure instead of actual behavior, which would have been more than desirable. Due to the fourth dimension and cost associated with collecting behavioral measures, intention was selected equally an adequate, if imperfect, alternative. Cocky-option bias is too a limitation of any online questionnaire (east.thou., Wright, 2005). While participants were randomly selected from the KnowledgePanel, they ultimately chose whether or not to participate and there may be important differences between individuals who chose to participant and those who did not. The low variance amid the PE scores in both studies may accept also limited analyses, only of course, the messages selected were not designed to be ineffective. But the opposite is the case. And so the limited variance may reflect our decision to use a range of professionally designed and produced PSAs.

The design of the studies too presents a limitation; they were non designed as true experiments. That is, at that place was no condition and no pre-decision of strong or weak messages. Even so, our analysis represents this treatment in a more natural, if somewhat messy, way. Participants received a random combination of four PSAs; they might encounter four weak or 4 strong or a combination of weak and strong. Our results propose that those who receive a combination of the ads rated equally most constructive have the greatest intention to engage in smoking abeyance-related behaviors in the near time to come. Some other arroyo would be to blueprint and run an experiment that gives participants either all ads rated high in PE or all ads rated low in PE. Finally, the results may be interpreted to be small to moderate effect sizes. In the combined information, standardized regression coefficients ranged from .09 to .11 for aggregate PE on behavioral intentions, and .06 to .10 for aggregate emotional responses on behavioral intentions. Still, smoking related campaigns accept 1 of the everyman outcome levels on behavior change, hateful r = .05, likely due to the addictive nature of cigarettes (Snyder et al., 2004). The fact that we obtained significant results in the context of anti-smoking ads is encouraging for their affect in natural settings. As Snyder et al. (2004) argue, small experimental furnishings can have substantive furnishings in a population. In their example, 5% of a city population of 100,000 still equates to five,000 people irresolute their beliefs. Snyder and colleagues also argue nosotros should not expect health campaigns to result in large numbers of people irresolute their behavior, but should take more pocket-sized expectations.

A primary strength of this written report is that it is a conservative test. Nosotros controlled for many factors, including readiness to quit, which is clearly the strongest predictor of future smoking-related intentions. We also asked participants to focus on specific intentions and a specific time menses, just as Fishbein and Ajzen (2010) recommended. In add-on, instead of using each individual'south perception of bulletin effectiveness to predict their future smoking cessation-related intentions, an aggregate score was calculated from the ratings of each individual who saw that message, providing a measure gratuitous of individual bias and ane that more accurately reflects the persuasive potential of each message. As well, the sample was fatigued nationally from adults aged 18 and older and included only individuals who reported existence current and regular cigarette smokers. Finally, messages were selected randomly from a large pool instead of being categorized into less and more effective messages and no two individuals saw the same PSAs in the same guild.

Conclusion

These analyses were conducted to provide boosted bear witness of the utility of PE as a predictor of actual effectiveness. Results demonstrated that even when controlling for key behavioral intention predictors, PE was positively associated with smoking cessation-related intentions. This study adds to the literature supporting PE as a measure of a successful message and one that can be used past researchers and practitioners alike to assistance place and construct successful health letters.

Acknowledgments

The authors wish to acknowledge the funding support of the National Cancer Institute'due south Center of Excellence in Cancer Advice Research (CECCR) located at the Annenberg School for Communication, University of Pennsylvania (P20-CA095856).

Footnotes

^aneIn both studies, participants received additional behavioral intention items if they answered "probably volition non," "probably will," or "definitely volition" to quit smoking completely and permanently. The additional items asked almost their intentions in the side by side three months to purchase a nicotine replacement product, seek counseling/support to help quit, and enroll in a smoking cessation program. These items are non analyzed here because the sample would not be ane of smokers in general simply rather those intending to quit. Although this is an interesting and important sub-group of smokers and their intentions to use diverse methods to assist in quitting matters in tobacco command, they are not comparable to the full set of smokers that includes those who are very difficult to reach.

²In reaction to the message, participants were asked to respond to the item, "I felt aroused." Withal, from the responses, information technology is unclear what their anger was directed at: the message or themselves. That is, were participants aroused after watching an anti-smoking bulletin because they did not similar something about the message or because it reminded them they engage in a socially undesirable beliefs? In Report ii, a follow-up question was asked of those who reported feeling some level of acrimony. Respondents were asked to agree or disagree with the following ii statements: "I was angry about my being a smoker" and "I was angry at the ad and its sponsors." Unfortunately, considering these follow-up questions were only asked in the 2nd study, we were unable to include them in this newspaper.

³When all independent variables were examined in the same regression model, the collinearity trouble was apparent equally several of the coefficient signs reversed direction from the correlations.

⁴Sensation seeking was initially included in all analyses simply was non significant; therefore, it was removed from the model estimations reported here.

⁵Individual behavioral intention analyses were conducted with both linear and ordinal logistic regression. The significance of the ordinal logistic regression results did non differ from the linear regression results presented in this paper. Therefore, assumptions made almost the dependent variable did not change the results.

⁶Analyses were also conducted with a three-level ordinal measure out of readiness to quit smoking (low, medium, loftier). The significance of the aggregate PE-behavioral intention relationships did non modify in any of the models.

^sevenMarketing tactics messages were characterized by claims that tobacco companies utilise powerful and targeted (i.due east., women, children, minority groups) marketing strategies. Cosmetic messages were characterized past arguments that smokers must bargain with unattractive and abrasive side effects similar yellow teeth and bad jiff. Smokers' negative life circumstances messages were characterized by suggestions that smoking is a bulwark to achieving goals of import to adolescents like bewitchery/coolness and independence/maturity.

The content is solely the responsibleness of the authors and does non necessarily correspond the official views of the National Cancer Institute or the National Institutes of Health.

An before version of this manuscript, with only one sample of participants, was presented at the annual meeting of the International Communication Association, Boston, MA, May 2011.

Contributor Information

Elisabeth Bigsby, Northeastern University.

Joseph N. Cappella, Annenberg School for Communication, Academy of Pennsylvania.

Holli H. Seitz, Annenberg School for Communication, University of Pennsylvania.

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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283792/

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