Which Of The Following Is A Disadvantage Of A Public Service Announcement?

Commun Monogr. Writer manuscript; available in PMC 2015 Jan five.

Published in final edited form equally:

PMCID: PMC4283792

NIHMSID: NIHMS641994

Efficiently and Effectively Evaluating Public Service Announcements: Additional Evidence for the Utility of Perceived Effectiveness

Elisabeth Bigsby

Northeastern Academy

Joseph North. Cappella

Annenberg School for Communication, University of Pennsylvania

Holli H. Seitz

Annenberg School for Communication, University of Pennsylvania

Abstruse

Recent research has fabricated pregnant progress identifying measures of the perceived effectiveness (PE) of persuasive letters and providing evidence of a causal link from PE to actual effectiveness (AE). This commodity provides additional evidence of the utility of PE through unique analysis and consideration of some other dimension of PE important to understanding the PE-AE association. Current smokers (N =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 total, minimizing the likelihood that PE perceptions are consequences of an individual'southward intention to quit, supporting instead the PE→AE lodge. Linear regression analyses provide evidence of PE'southward 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 health campaigns, political and social issue campaigns, and certainly for researchers seeking to evaluate various types of message furnishings as they undertake theory testing. A skilful bargain of attention and very significant progress has been made on this upshot the past decade (east.1000., Dillard, Shen, & Vail, 2007; Dillard, Weber, & Vail, 2007; Dillard & Ye, 2008; Fishbein, Hall-Jamieson, Zimmer, von Haeften, & Nabi, 2002). The purpose of the nowadays paper is to advance the inquiry base by providing data that will enhance researchers' confidence in perceived effectiveness (PE) as a valid, if imperfect, measure of bodily effectiveness (AE).

The Need for an Efficient Measure of PE

The most direct mode to evaluate the effectiveness of a message is to conduct a test in the field with the appropriate target population. For case, Public Service Announcements (PSAs) to exist used in a public campaign can be compared on the issue variables of interest against some control. For letters aimed at behavior modify (bold the proper design and controls), this is perhaps the almost accurate way to measure bulletin effectiveness. Unfortunately, this strategy requires running at least a modest-calibration campaign in the field and and then evaluating its success in irresolute behavior, which can take months or longer, rendering it impractical and expensive.

The obvious problem with measuring AE is its inefficiency. Researchers and campaign designers need to know about the effectiveness of messages in accelerate of testing the final campaign and before deploying entrada resource. Ane strategy employed by advertisers, for example, has been to test preliminary versions of an advertising in early on stages of development before implementing the more expensive full-fledged version. But fifty-fifty these preliminary versions need to be evaluated in some fashion for their potential effectiveness in society to choose the best bulletin for production and implementation.

Research on PE

Prior enquiry has significantly advanced the development of efficient measures of PE and the validation of these measures relative to important outcomes such as attitude and behavioral intention. Although quite encouraging, the results of these studies demand to exist bolstered by other data. Specifically, three 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 ad, attitude toward the advancement of the ad, cognitive responses (idea-listing difference scores), and intention to appoint in advocated beliefs, and negatively correlated with positive emotional responses (Barrett, Cappella, Fishbein, Yzer, & Ahern, 2011; Dillard, Shen, et al., 2007; Fishbein et al., 2002). In addition, a meta-analysis of forty studies (approximately 3,000 respondents) found a pregnant consequence size, r = .41 with 95% of the effects positive, for the PE-AE (in this case attitude) relationship (Dillard, Weber, et al., 2007).

Having attitude, cognitive response, intention, and ultimately behavioral change information are necessary steps in validating the utility of any PE measure. Prior research has largely focused on attitude toward the bulletin advocacy as an indication of AE. However, in assessing the PE-AE human relationship, the gold standard for outcomes would be behavior change rather than attitude, emotion, or another indicator of behavior. Short of beliefs alter itself, which is hard to test and certainly non efficient, a change in specific intentions regarding behaviors pertinent to the target audition is a reasonable surrogate (for meta-analyses of the intention-behavior human 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 act as an result mensurate. Additionally, the measures employed were general rather than the very specific measures advocated by Fishbein and Ajzen (2010), in part considering they are more likely to correlate with behavior. To build on the previous findings, the validation presented hither focuses on intention to act in specific means where the intention is highly relevant to the individual and the time frame and behavior are quite specific. If information can exist marshaled to bear witness that letters high in PE are associated with specific intentions consistent with the messages and pertinent to the targets of the messages, while those low in PE are non (or are less and then), then confidence in PE as a test of a message volition be enhanced.

Causal Direction of the PE-AE Human relationship

In a study that did utilize behavioral intention every bit a mensurate of actual bulletin effectiveness, Zhao, Strasser, Cappella, Lerman, and Fishbein (2011) evaluated responses to anti-smoking PSAs and found that perceived argument strength was positively associated with intentions to quit smoking, r = .44, p < .001, which can be interpreted as a relationship between PE and AE. Some other study presented in the same article showed a similar pattern for adolescents exposed to anti-drug letters 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 exercise non permit inferences well-nigh causal management between PE and AE considering information technology is just as likely that those intending to quit smoking or those adolescents with low drug use intentions evaluate the related ads they run into in more positive ways. Causality is very much in question even though pertinent intentions were advisedly assessed.

Dillard, Shen, et al. (2007) too attempted to establish that PE is antecedent to AE, and not the reverse, by 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 order fit the data improve than did the reverse social club model. These findings are certainly consistent with PE being causally prior to AE, simply they cannot be definitive in the same style every bit an experiment with random assignment. Of the v studies described in the commodity, only the 5th 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 exist effective were more likely to be associated with increased behavioral intention consistent with the message's advocacy. This elegant experimental approach allowed the researchers to control message content completely and merely 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 messages in advance, randomly assigning individuals to letters received, and testing an outcome in the course 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 inquiry take 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 audience is much broader than a higher population, it is necessary to show that the PE–AE relationship holds in these samples. While a few studies accept focused on adolescent samples consisting of middle schoolhouse and high school students (e.one thousand., Barrett et al., 2011; Fishbein et al., 2002), even fewer studies accept recruited nationally representative developed samples.

Messages

A multifariousness of message topics have been studied in this context. Dillard, Weber, et al.'s (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 multifariousness of message themes within each topic has been much more limited, probable because of technology and bachelor resource. Our research contributes to message sample representativeness by including a large number of ads (N = 100) within the same topic (anti-smoking) but with a variety of message themes (e.k., death, secondhand smoke, strategy for quitting). The theme of the bulletin tin can affect PE because the theme is linked to the argument of the bulletin. Therefore, information technology is important to include a variety of bulletin themes, not but bulletin 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 bulletin assessment (Yzer, Vohs, Luciana, Cuthbert, & MacDonald, 2011). In fact, different operational measures of PE have been significantly correlated with different issue measures (due east.g. Barrett et al., 2011; Dillard, Shen, et al., 2007). To better 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 research, the authors conducted a cistron assay which revealed two PE factors: convincingness and pleasantness. However, Yzer and colleagues point out that the items most widely used are part of the convincing factor, which merely captures office of how PE has been conceptualized.

Examining the differences between the two dimensions of PE more closely, Yzer et al. (2011) found that the different factors of PE correlated with different retrospective melancholia responses. The convincing cistron was highly correlated with arousal (e.g., excited vs. bored), r = .74, and the pleasantness factor was highly correlated with valence (due east.k., happy vs. unhappy), r = .66. In improver, 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 consequent with a great deal of fear entreatment inquiry. Even if touch is an antecedent of PE, Yzer et al.'south results signal that PE is strongly correlated with affective responses. Thus, both cerebral and affective responses should exist taken into consideration when assessing the PE of a bulletin. Our study examines the impact of both emotional responses to PSAs and more than traditional PE items on behavioral intentions.

Hypothesis

The case for the validity of PE of persuasive messages is solid simply incomplete. The set of messages that take 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 lodge to testify that high doses of PE take greater influence than moderate doses and moderate doses more than influence than low.

In the present study, a general population of developed smokers was exposed to iv anti-smoking PSAs randomly selected from a large fix (N = 100). After viewing the PSAs, viewers indicated their intention to quit smoking permanently and completely too as other intentions concerning actions that can assist with the cessation procedure. We were primarily interested in intention to quit because the specific language and time frame provides a conservative test of PE and because it is the intention closest to the behavioral gold standard by which many anti-smoking campaigns are judged successful or non. Included in the responses subsequently each PSA are evaluative assessments of each message's persuasive qualities.

In that location are 3 advantages to using a big sample of smoking cessation messages. First, the messages covered a range of themes and stylistic features, allowing messages to range in terms of perceived effectiveness. Second, both the message and bulletin order were randomly assigned to participants, meaning each participant should accept had a unique viewing feel. 3rd, a big sample of messages immune u.s. to utilise an aggregate PE score instead of private PE scores to predict behavioral intentions, minimizing the likelihood that the causal direction is anything other than from PE to individual behavior intentions (AE). The aggregate PE score was created by taking the average score for each message (from the gear up of respondents who viewed the message) and assigning it in place of each individual score for that message. Using the average score for each message helps control for other factors that may influence an individual'southward evaluation of it (eastward.k., readiness to quit and message order) and provides what we believe to be a less biased and more accurate reflection of the message's potential influence on beliefs. The boilerplate score for each of the four messages an individual saw were and then summed to create an overall aggregate PE score (see Figure 1). The big sample of smoking cessation messages allowed us to aggregate the scores this way because each person watched a different gear up of PSAs, so each person still ended upwards with a unique overall PE score. Thus, the amass scores were used to accost causality because the behavioral intentions of 1 private could not cause the bulletin evaluations of the other individuals who watched the same message. This procedure is like to conducting a written report in ii parts with dissever samples. For example, suppose participants of the first sample rated the PE of all the messages and the participants of the second sample were randomly assigned to view 4 messages and subsequently rated their intentions to engage in smoking cessation-related behaviors. If we used the PE scores from the starting time sample to calculate a sum PE score for each participant in the 2d sample and used it to predict the behavioral intentions of the second sample participants, in that location is no way the intention scores could be causally prior to the PE scores because they came from a different sample of people. This hypothetical study using two separate samples is virtually identical to the methodology used in the current written report with one sample.

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The creation of participant sum perceived effectiveness scores aggregated past video. Private PE ratings of each video were get-go aggregated by video, then aggregate video PE scores were substituted for each individual'southward 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 full number for that variable.

We hypothesized that exposure to anti-smoking letters rated equally persuasive in aggregate would be associated with college reported intentions to quit smoking, reduce smoking, and talk about 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 forcefulness, 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 (phase of modify), need for cognition, and other individual differences were included in all analyses.

Method

Information were collected from two dissimilar samples with only minor differences in design; these are referred to as Study i and Study 2. The method for both studies is presented in this section; all differences betwixt the studies are presented in text.

Participants

Participants (Report one North = 566, Study 2 North = 630) were drawn from a nationally representative sample and were current smokers who reported smoking at to the lowest degree five cigarettes a day and more than 100 cigarettes in their lifetime. The mean age for Study 1 was 49.sixty, SD = 11.01, range: 19–66. For Study 2, the hateful historic period was 46.20, SD = xi.85, range: eighteen–65. All participants were part of the KnowledgePanel, established and maintained past Noesis Networks (KN). Potential KnowledgePanel participants are first selected through random digit dialing and address-based sampling and are and so contacted past trained interviewers and recruiters at KN. Participants without a computer or cyberspace access are provided with the necessary equipment at no charge if they would similar to participate in the KnowledgePanel. Incentive points tin be earned for completing surveys and redeemed for greenbacks. KnowledgePanel participants are notified most surveys for which they qualify and each panelist determines which surveys southward/he would like to consummate. Recruitment was washed by KN through their KnowledgePanel and connected until the desired number of completes was obtained.

Dropped participants in Study 2

Twenty-six individuals were dropped from analyses considering 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 immune for differences between broadband, dial-up, and other internet connectedness users). In improver, 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 amass calculations and the individual behavioral responses used in analyses.

PSA Videos

One hundred anti-smoking television PSAs (60 in Study 1, forty in Written report 2) were selected from a collection compiled from various sources including the American Legacy Foundation and various land health agencies. All PSAs were professionally produced and many, simply not all, had aired as role of either state or national campaigns betwixt 1998 and 2007. The major themes of the PSAs were (a) disease and expiry, (b) selling disease and death, (c) endangers others-secondhand fume, (d) endangers others–burden (negative consequences your family may suffer if you lot get ill and/or die), (e) smokers' negative life circumstance, (f) marketing tactics (how tobacco companies market their product), and (g) strategy for quitting. However, these themes are full general categorizations of the primary themes; many of the PSAs had two or fifty-fifty 3 themes.

In both studies, each participant watched four PSAs that were embedded within the online questionnaire. Inside the survey, both PSA choice and order were completely random. Thus, each person was probable to receive a different set of smoking cessation PSAs. When there was PSA overlap, individuals were likely to have received them in a unlike order 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 selection process and were therefore not immune to participate in the 2d study. Selected participants received an email notifying them of a new survey with a link to the questionnaire. Reminder emails were sent to all initial participants after 3 days of non-response before additional participants were randomly selected and emailed. Surveys could exist taken by KnowledgePanel members on any reckoner with an internet connection. Kickoff, a screen providing a cursory clarification of the study was displayed; continuing to the next screen provided unsaid consent. Later viewing the initial screens, individuals answered several questions near smoking, their health, and individual differences. Participants so watched one PSA and answered questions near that specific message; this procedure was repeated for each of the next iii PSAs. Finally, individuals answered questions almost their behavioral intentions, self-efficacy, and beliefs and attitudes related to smoking and wellness. At the terminate of the questionnaire, participants were thanked for their time and were given an opportunity to provide boosted thoughts or feedback. On boilerplate, it took betwixt 23 and 28 minutes for participants to complete either study.

Independent Measures

Perceived message effectiveness

PE was assessed past iv items on a 5-point Likert-type scale (1 = SD, v = SA). The items included "This advertising was convincing" and "Watching this advertisement helped me feel confident near how to best bargain with smoking." Similar to Zhao et al. (2011), favorable and unfavorable thoughts about the message were besides measured on this scale: "The ad put thoughts in my mind about quitting smoking" and "the advertizement put thoughts in my heed virtually continuing to smoke."

To create the PE score, unfavorable thoughts (b) were commencement subtracted from favorable thoughts (a). The resulting score was divided by two and added to iii ([(a-b)/2]+3) and so that it was on the aforementioned five-betoken scale as the other PE items. The newly created thoughts score was then added to the other two items and the sum of those items was divided by 3 (Cronbach's α = .75, m = 2.98, SD = .82). The PE scores were then aggregated across respondents past PSA (by study to preserve whatsoever differences in PE that may exist). Finally, the hateful PE scores for the four PSAs each individual saw were added together to create a sum amass PE score (see Figure 1), range: four–20. The hateful and standard deviation can exist found in Table one.

Tabular array 1

Ways, Standard Deviations, and Correlations of Major Variables

	Hateful (SD)	1	two	3	four	5	half dozen	7	8	9	10	11	12
1. Amass PE	eleven.91 (.57)	1
ii. Readiness	five.50 (2.89)	.08^*	1
3. NFC	two.l (.77)	−.06	−.06^*	1
4. Dependence	4.22 (2.35)	.05	−.07^*	.14^**	1
5. Aggregate Fear	9.60 (.84)	.82^**	.04	−.04	.07^*	1
6. Aggregate Pride	eight.08 (.33)	.45^**	.08^**	−.03	.05	.37^**	i
seven. Aggregate Hope	nine.31 (.57)	.64^**	.09^**	−.05	.04	.43^**	.83^**	i
8. Aggregate Guilt	10.12 (.83)	.85^**	.05	−.06^*	.06	.92^**	.42^**	.50^**	1
9. Aggregate Anger	ix.82 (.54)	.44^**	.04	−.04	.04	.63^**	.03	.05	.55^**	one
ten. Quit	2.twenty (.75)	.09^**	.55^**	−.03	−.05	.06^*	.ten^**	.10^**	.07^*	.04	1
11. Reduce	two.81 (.83)	.13^**	.56^**	−.08^**	−.09^**	.08^*	.11^**	.13^**	.09^**	.02	.66^**	1
12. Talk	2.52 (.95)	.15^**	.46^**	−.05	.00	.12^**	.09^**	.xi^**	.12^**	.07^*	.54^**	.60^**	i

Emotional responses to PSAs

Yzer et al. (2011) found that the pleasant dimension of PE, captured by semantic differential items that assessed the ad as good-bad and negative-positive, was highly correlated with the valance (happy vs. unhappy) dimension of affect. In other studies, emotional connotations of messages have been significantly correlated with PE (e.g., Biener, McCallum-Keeler, & Nyman, 2000; Dillard & Peck, 2000) and highly emotional narratives take been positively associated with smoking quit attempts (Durkin, Biener, & Wakefield, 2009), providing more show for the need to account for emotional responses to messages likewise 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 indicate their agreement with the argument "I felt…" on a 5-signal Likert-blazon scale (1 =SD, five = 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 i.

Dependent Measures

Behavioral intentions

Properly measured behavioral intentions take often been used in communication and psychological inquiry as a adept predictor of behavior (Hale et al., 2002; Webb & Sheeran, 2006). Individuals responded to three different behavioral intention items^{^one} on a 4-indicate calibration (one = definitely volition non, 4 = definitely will). Items asked participants how likely it was in the next three months they would "quit smoking completely and permanently," "reduce the number of cigarettes you lot smoke in a solar day," and "talk to someone (friend, family member, spouse) about quitting." These three items were examined both equally an overall mensurate of smoking cessation intention and private behavioral intentions. Ways and standard deviations are provided in Table i for the individual intentions.

Command Measures (Pre-PSA Exposure)

Variables that may bear on 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 also included in Table 1.

Readiness to quit

An private'southward intention to act or not human action must commencement with a decision virtually the behavior; this idea is outlined in detail in the transtheoretical model's construct stages of change (Prochaska & DiClemente, 1982). Therefore, it was expected that an individual's readiness to quit smoking would have an influence on their future quitting-related behavior, regardless of the PE of the message.

The participant's level of mental and/or physical training to attempt to quit smoking was represented by a modified ladder of contemplation (Biener & Abrams, 1991). Response options ranged from 0 (I take no thoughts nearly quitting smoking) to 10 (I am taking action to quit smoking). Biener and Abrams (1991) have validated this calibration as a measure of motivation to end smoking.

Nicotine dependence

Participants likewise responded to the Fagerström Test for Nicotine Dependence (FTND), a revision of the Fagerström Tolerance Questionnaire (FTQ), that is meant "to provide a brusk, convenient self-study measure of dependency on nicotine" (Heatherton, Kozlowski, Frecker, & Fagerström, 1991, p. 1119). Items were a mix of open-concluded and fixed response. Fixed response options were either on a four-signal scale (range: 0–3) or a 2-point scale (range: 0–ane) (Heatherton et al., 1991). Cronbach's blastoff was .59, which is like to previous research that reports Cronbach'south 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 (see Heatherton et al., 1991). However, prior inquiry 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 (due east.grand., years smoking, other addiction scales) (Heatherton et al., 1991; Pomerleau et al., 1994). Pomerleau et al. (1994) found the FTND had a higher Cronbach's alpha and amend test-retest reliability than the FTQ, although the scales were not significantly different on their measures of external validity. Given that the FTND is meant to measure a biochemical experience and we are using it as a control variable, we do not believe the low reliability negatively affects our data analyses.

Need for knowledge

Need for cognition is an private 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 betwixt individuals. Four items were selected from Cacioppo and Piffling's (1982) scale and two were reverse coded. Participants responded to items on a v-bespeak calibration (1 = a lot like me, 5 = not at all like me). Cronbach'southward blastoff for this scale was low (.56), which was probable due to the pocket-size number of items and fact that two were reverse coded. Negatively worded items and reverse coding take been institute to reduce scale reliability and validity (e.thou., Barnette, 2000; Schriesheim, Eisenbach, & Hill, 1991). Regardless of the low reliability, need for knowledge was kept because cistron analysis suggested the items loaded best on ane factor and because it was a control variable.

Preliminary Analyses

A correlation matrix of the major variables of interest is presented in Tabular array 1. The data sets were combined for analyses with a dummy variable for written report employed to command for study effects. Information technology is important to annotation that readiness to quit was moderately correlated (p ≤ .01) with all of the behavioral intentions, which is non 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 mensurate (.64 correlation, p < .001). In improver, two of the labels provided on their ladder (ten: I am taking activity to quit smoking, and 8: I am starting to retrieve about how to reduce the number of cigarettes I smoke a solar day) are very similar to 2 of our intentions ("How probable is it that in the next 3 months you will quit smoking completely and permanently", "How probable is it in the next 3 months you lot will reduce the number of cigarettes y'all smoke in a twenty-four hours"). 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, information technology provides evidence that PE explains variance in behavioral intention over and above that due to an individual'south readiness or stage of change.

The correlation matrix besides shows moderate to high levels of correlation between the aggregate emotion variables. Four of the variables yielded highly correlated pairs, fear and guilt (r = .92) and hope and pride (r = .83). Considering of the high correlations and to avert collinearity issues, these pairs were summed to create alphabetize scores of negative and positive emotional responses, fear-guilt (Cronbach'due south α = .84, m = 19.73, SD = 1.64, range: 8–forty) and hope-pride (Cronbach's α = .78, grand = 17.39, SD = .87, range: 8–40). Anger was moderately correlated with guilt (r = .55, p ≤ .001) and fear (r = .63, p ≤ .001) and i 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

We conducted an exploratory gene assay in SPSS 18 using the maximum likelihood process to determine the appropriateness of creating an overall behavioral intention scale. The results showed that the iii intentions loaded best on 1 dimension; factor loadings ranged from .83 to .86. Therefore, the intentions were summed to create an overall intention score with a Cronbach's alpha of .82, demonstrating acceptable internal reliability. The hateful score was 7.52 with a standard deviation of 2.18 (range: 3–12).

Analysis Programme

In social club to fully examine the data, two assay strategies were used. Commencement, nosotros ran linear regression models with each of the three contained variables (aggregate PE, aggregate guilt-fear, aggregate promise-pride) and the overall behavioral intention score. Second, separate linear regression models were estimated for each behavioral intention, again with each of the three contained variables. The 3 contained variables could not be included in the aforementioned model estimate because of collinearity; aggregate PE was significantly correlated with all of the aggregate emotion evaluations (Pearson'south r ranged from .45 to .86) and all of the aggregate emotion scores were significantly correlated with each other (run into Tabular array 1)^{^three}. In addition to the control variables listed above, study (Study one = 0, Report two = 1) and demographic information (age, gender, racial/indigenous identity, education, income) were also included as controls^{^iv}. Race/ethnicity and educational activity were dummy coded for the regressions (European American/White = 0; less than loftier school education = 0; all other categories were compared to these). The results of both strategies are detailed and presented beneath. All regression analyses were conducted in STATA eleven.

Results

Table two contains the results for the iii independent variables on each intention including the overall intention score; the tabular array too includes the R² for each model (including all controls). ^{^five–⁶} The results of the control variables are only discussed in text. Stata employs listwise deletion by default and resulted in a final N = ane,139. Nosotros kept this strategy considering the number of missing observations was not bang-up, less than 5% of the possible observations (1,196), and would likely not alter results.

Table two

Summary of Carve up Linear Regressions of the IVs on the Six Behavioral Intentions (with Report as a Command Variable)

4	Intention (DV)

Aggregate Perceived Effectiveness	Overall Intention	Quit Smoking	Reduce Cigarettes	Talk to Someone
B	.36	.05	.13	.17
SE	.10	.04	.04	.05
β	.10 ^*	.04	.09 ^***	.xi ^***
R²	.41	.33	.36	.26

Aggregate Fear-Guilt
B	.10	.01	.02	.06
SE	.04	.01	.02	.02
β	.07 ^*	.03	.05	.ten ^**
R²	.40	.33	.35	.25

Amass Hope-Pride
B	.15	.04	.06	.04
SE	.06	.02	.03	.03
β	.06 ^* ^a	.04 ^#	.07 ^**	.04 ^a
R²	.40	.33	.35	.25

Demographic Differences

Demographic variables (historic period, gender, racial/ethnic identity, educational activity, income) were included in all regression models as controls because of the large and diverse samples, and because many public wellness practitioners are interested in such differences. However, because they are not a principal interest in this study, simply the meaning 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 higher levels of intention than European Americans/Whites (p-values ≤ .001). Women were significantly more probable than men to study intentions to reduce the number of cigarettes smoked a 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 index were each significantly associated with overall intention to appoint in smoking cessation behaviors. Readiness to quit was the just control variable significant in each regression model, p < .001.

Separate Behavioral Intentions

Quit smoking completely and permanently

None of the 3 contained variables were significantly associated with this intention. In each model, written report neared significance (p-values ranged from .11 to .15) and readiness to quit was again a significant predictor (p < .001).

Reduce the number of cigarettes smoked a 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 significant (p-values ranged from .01 to .04) in all three regressions.

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

Amass PE and amass fearfulness-guilt were significantly associated with intention to talk to someone about quitting. Again, readiness to quit was a significant predictor (p < .001).

Additional Analyses

In several of the regression models, the control variable for study was pregnant or almost significance (p ≤ .15). As a result, 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 = eighteen.18, p < .05, equal variances not assumed); PE scores were significantly higher in Study 1 (m = 12.xx, SE = .02) than Study ii (m = xi.66, SE = .02). There was also a significant difference in responses to the fear-guilt alphabetize (t = 27.20, p < .05, equal variances not assumed); Study i once again had higher scores (m = 20.81, SE = .06) than Study 2 (yard = 18.76, SE = .05). Study i also had significantly higher hope-pride scores (m = 17.77, SE = .03) than Study 2 (grand = 17.04, SE = .03), t = 16.01, 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 .fourteen to .48).

To better understand the differences between the studies on the independent variables, we re-ran the regression models for each study separately. Because our principal interest is in the almost difficult intention, to quit completely and permanently in the side by side iii months, only it and the overall intention measure were re-estimated. The results of the additional analyses are presented in Tabular array 3, which again includes the R² for each model with command variables.

Table three

Summary of Linear Regressions past Study

	Intention (DV)

IV	Written report 1		Report 2

Aggregate Perceived Effectiveness	Overall Intention	Quit Smoking	Overall Intention	Quit Smoking
B	.38	.05	.37	.06
SE	.13	.05	.xv	.05
β	.10 ^**	.04	.08 ^*	.03
Rⁱⁱ	.37	.31	.44	.36

Aggregate Fright-Guilt
B	.x	.01	.10	.02
SE	.05	.02	.06	.02
β	.07 ^*	.02	.05	.03
R²	.36	.31	.44	.36

Amass Hope-Pride
B	.25	.08	.07	.00
SE	.09	.03	.09	.03
β	.09 ^**	.08 ^*	.02	.00
R²	.36	.31	.44	.36

Give-and-take

Nosotros conducted a conservative test 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 bulletin exposure also rated those messages every bit more than effective and then reported higher intentions to appoint in related behaviors, diminishing the influence of the individual'south motivations prior to message exposure on their perception of the letters. In addition to using aggregate PE scores, we as well controlled for individual factors that are known to influence behavioral intentions, such as readiness to quit smoking (which was the near significant predictor variable). Obtaining significant results on specific intentions thus supports the merits that PE precedes AE. Our study also asked specific intention questions framed in a specific time period, included a large sample of smoking cessation PSAs (randomly assigned and then no individual saw the aforementioned combination of messages), and included a nationally representative sample of adult smokers. Therefore, 3 issues in previous PE research were directly addressed: causal direction, measures of intention, and representativeness of the samples. It should too exist noted that the primary behavioral intention evaluated here is difficult to change with a few anti-smoking ads. Whatsoever success in changing smokers' intentions to quit suggests that PE is a good indicator of bulletin effectiveness.

PE, Emotional Responses, and Smoking Cessation Intentions

PSAs rated as more constructive, equally judged by both traditional cognitive responses and emotional responses, were associated with intentions to engage in smoking cessation activities, although not uniformly or under all weather condition tested. The ii most important 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 adjacent iii months (near significance in the combined data, meaning in Study one). Although significant results for overall intention and intention to quit smoking were but obtained in one of the data sets, information technology is especially encouraging as all analyses included several command variables that were known or predictable to take significant relationships with smoking cessation intentions. In addition to the control variables that made for a conservative test, the wording of the intention measures was particularly stiff. Emphasizing that the intention measures refer to permanent and complete behavior change within a curt time frame makes them an acceptable and more realistic substitute for measures of actual behavior, which adds to our confidence in the predictive validity of PE.

While intention to quit smoking is the nigh desirable intention from a public wellness perspective, it is also the most difficult to obtain and to the lowest degree likely to occur afterward exposure to a PSA (or several). That PE and emotional responses significantly predicted some of the other smoking cessation-related behavioral intentions is also important from a applied standpoint. PE significantly predicted the other smoking abeyance-related behavioral intentions: reduce the number of cigarettes smoked a twenty-four hour period in the side by side 3 months, and talk to someone (friend, family member, spouse) near quitting smoking in the next three months. These results suggest that PSAs can at to the lowest degree contribute to behavioral intentions, which may exist the virtually we tin expect from an anti-smoking entrada (as opposed to expecting outright behavior change).

Other Influences on Smoking Abeyance Intentions

In improver to the relationship betwixt PE and smoking cessation intentions, 2 other patterns emerged. First, readiness to quit had a articulate and significant association with all smoking cessation intentions. Every bit previously discussed, this result is not surprising, especially considering how Biener and Abrams (1991) created their smoking abeyance intention scale, but information technology is worth pointing out equally this result 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 different from European American/White individuals on whatsoever of the cessation intentions.

Differences Between the Studies

The results from the two studies yielded inconsistent results. The studies were secondary analyses from existing data sets with the 2 sets of PSAs selected, originally, for different reasons. The ads used in Written report ane had greater variance in the PE and emotional response scores than those is Study 2. In Study 1, the ads were called from a large sample (about i,000) of anti-smoking PSAs to maximize variance in statement forcefulness and message sensation value. The highs and lows on these factors drove the selection of ads. In Study 2, ads were selected based on message theme (e.one thousand., disease and death, positive frame of quitting, etc.) to fill in the gaps left by Study one and so that when combined, the diverseness of message themes was an approximation of the set up as a whole. Equally a issue, the three bulletin themes judged to exist the to the lowest degree effective in both studies–marketing tactics messages, cosmetics messages, and smokers' negative life circumstances messages^⁷–fabricated up a greater majority of the ads in Study two. These iii themes accounted for approximately 30% of the ads used in Study 2, while comprising 11% of the ads in Study 1. The college probability of seeing i or more of the less effective themes dropped the PE scores in Written report 2 and resulted in less variance among the participants' responses. In the end, the two studies together yield a gear up of themes that map, in their frequency, the full set of themes in the ane,000 ads. Therefore, in our view, the results from the full set of combined PSAs are more than representative of anti-smoking ads in full general.

A stiff statement tin can exist fabricated that PE is a good measure of AE. In the combined information, PE predicts overall intention and for each of the three components of intention, the direction is positive for all and virtually (t > i.iv) or past significance for two of the three individual intention measures. Two of the three intention measures are near quitting or reducing smoking, while the other is about quitting with help, which is known to increase the success rate for quitting by a factor of two (Sutherland, 2002). The two sets of aggregate emotion scores – one positive and ane negative – add no variance explained of any consequence to whatsoever of the intention measures, aggregate or private. These findings suggest that emotional characteristics are inconsequential additions to any measures of PE employed here and tap primarily into believability and convincingness.

We would offer i caveat to the higher up claims. The near important intentions are those linked to reducing smoking direct, with intentions to seek quit help secondary. In the combined data, hope-pride was at or near significance in predicting intentions to quit and reduce smoking, mostly due to the furnishings of Study 1. These results may seem too inconsistent to be trustworthy, except that some survey studies of intentions to quit smoking have reported substantial increases in variance explained when hope and pride – emotions conspicuously related to elevated levels of positive self-affirmation – were included as predictors (Cappella, 2007). Nosotros would suggest serious consideration of request questions near 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 behavior change (AE) and demonstrate the utility of a concise airtight-ended measure of PE. Although changes in behavior are ultimately the gold standard for successful messages (see Snyder, 2001), letters associated with good for you behavioral intentions are important to identify for ii reasons. First, the link between behavioral intention and actual beliefs is positive and significant, suggesting that by predicting behavioral intention we can predict actual behavior. As demonstrated in this study, messages that are perceived equally more effective are associated with intentions to appoint in behaviors consequent with the message advocacy. Even when the focus of the message is to advocate a difficult behavior, like smoking cessation, effective letters afflicted important intentions like reducing the number of cigarettes smoked a day, while controlling for several key variables. The results of this written report provide additional evidence of the of import role persuasive mediated letters play in behavior change in combination with well understood factors like readiness (stages of change) and efficacy in health related behaviors.

Equally has been pointed out by other scholars, tracking and measuring actual beliefs is hard, time consuming, and plush (e.g., Dillard, Weber, et al., 2007; Snyder, 2001). 1 of the goals of this study was to provide evidence of the utility of a short measure of PE. Based on a measure of argument strength adult and tested past Zhao et al. (2011) and bulletin evaluation by Fishbein et al. (2002), this measure of PE uses merely 4 items and had an adequate internal reliability. Also fabricated articulate in this measure out is the referent, which has not been consistently specified in previously used measures (Dillard, Weber, et al., 2007) and has been found in some studies to measure multiple referents (Dillard & Ye, 2008). Specifically, the thought items used the language, "the ad put thoughts in my mind about…", making third-person furnishings less probable. Using a curt and clear mensurate of PE is advantageous for researchers and practitioners alike, providing accurate evaluations of letters that can be used with a variety of populations (e.g., young, less educated) without taking upwardly 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 fume daily, and intending to appoint in more than one smoking cessation related activity – all within the next three months. Addressing the pleasant-unpleasant dimension of PE by assessing emotional responses to the ads also aids in selecting the PSAs with the nearly potential to positively affect intentions. While emotional responses did non upshot in more variance explained than PE, different emotional responses (positive or negative) were associated with different behavioral intentions. Most important, in this context, messages that arm-twist feelings of hope and pride may contribute to intentions to reduce smoking behaviors directly (due east.1000., quitting and reducing the number of cigarettes).

Study Limitations and Strengths

As with whatsoever study, there are limitations. Cocky-reported behavioral intention was used as the outcome measure instead of actual behavior, which would have been more desirable. Due to the time and cost associated with collecting behavioral measures, intention was selected as an adequate, if imperfect, culling. Self-choice bias is also a limitation of any online questionnaire (east.one thousand., Wright, 2005). While participants were randomly selected from the KnowledgePanel, they ultimately chose whether or not to participate and there may be of import differences between individuals who chose to participant and those who did not. The depression variance amidst the PE scores in both studies may have also limited analyses, but of course, the messages selected were non designed to exist ineffective. Simply the opposite is the instance. And then the express variance may reverberate our conclusion to apply 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, there was no condition and no pre-determination of potent or weak messages. However, our analysis represents this treatment in a more than natural, if somewhat messy, fashion. Participants received a random combination of four PSAs; they might run across four weak or four strong or a combination of weak and stiff. Our results suggest that those who receive a combination of the ads rated every bit well-nigh effective have the greatest intention to engage in smoking cessation-related behaviors in the well-nigh future. Another approach would exist to design and run an experiment that gives participants either all ads rated loftier in PE or all ads rated low in PE. Finally, the results may be interpreted to be pocket-sized to moderate effect sizes. In the combined information, standardized regression coefficients ranged from .09 to .xi for amass PE on behavioral intentions, and .06 to .10 for aggregate emotional responses on behavioral intentions. However, smoking related campaigns have 1 of the lowest effect levels on behavior change, hateful r = .05, probable due to the addictive nature of cigarettes (Snyder et al., 2004). The fact that we obtained meaning results in the context of anti-smoking ads is encouraging for their impact in natural settings. Equally Snyder et al. (2004) argue, small experimental effects can have substantive effects in a population. In their case, 5% of a city population of 100,000 however equates to 5,000 people changing their beliefs. Snyder and colleagues besides fence we should not expect health campaigns to result in large numbers of people changing their behavior, merely should accept more pocket-size expectations.

A principal strength of this study is that it is a conservative test. We controlled for many factors, including readiness to quit, which is conspicuously the strongest predictor of hereafter smoking-related intentions. We besides asked participants to focus on specific intentions and a specific time period, only every bit Fishbein and Ajzen (2010) recommended. In improver, instead of using each individual'southward perception of message effectiveness to predict their hereafter smoking cessation-related intentions, an aggregate score was calculated from the ratings of each individual who saw that message, providing a measure free of individual bias and i that more accurately reflects the persuasive potential of each message. Besides, the sample was drawn nationally from adults aged eighteen 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 letters and no two individuals saw the same PSAs in the same order.

Decision

These analyses were conducted to provide additional testify of the utility of PE equally a predictor of bodily effectiveness. Results demonstrated that even when controlling for cardinal behavioral intention predictors, PE was positively associated with smoking cessation-related intentions. This report adds to the literature supporting PE as a measure of a successful message and one that tin exist used by researchers and practitioners alike to assistance identify and construct successful wellness messages.

Acknowledgments

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

Footnotes

¹In both studies, participants received additional behavioral intention items if they answered "probably will not," "probably will," or "definitely will" to quit smoking completely and permanently. The boosted items asked about their intentions in the next 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 one of smokers in general but rather those intending to quit. Although this is an interesting and of import sub-group of smokers and their intentions to use various methods to assist in quitting matters in tobacco command, they are not comparable to the full fix of smokers that includes those who are very difficult to reach.

²In reaction to the bulletin, participants were asked to respond to the detail, "I felt angry." However, from the responses, it is unclear what their acrimony was directed at: the message or themselves. That is, were participants angry after watching an anti-smoking bulletin because they did not like something most the message or because it reminded them they engage in a socially undesirable behavior? In Study 2, a follow-up question was asked of those who reported feeling some level of anger. Respondents were asked to agree or disagree with the following two statements: "I was angry almost my existence a smoker" and "I was angry at the advertisement and its sponsors." Unfortunately, because these follow-upwards questions were only asked in the 2nd study, nosotros were unable to include them in this newspaper.

³When all independent variables were examined in the same regression model, the collinearity problem was credible every bit several of the coefficient signs reversed management from the correlations.

⁴Sensation seeking was initially included in all analyses but was not significant; therefore, information technology was removed from the model estimations reported hither.

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

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

⁷Marketing tactics letters were characterized past claims that tobacco companies use powerful and targeted (i.e., women, children, minority groups) marketing strategies. Cosmetic messages were characterized by arguments that smokers must deal with unattractive and abrasive side effects like yellow teeth and bad jiff. Smokers' negative life circumstances messages were characterized past suggestions that smoking is a barrier to achieving goals important to adolescents similar attractiveness/coolness and independence/maturity.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

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

Contributor Information

Elisabeth Bigsby, Northeastern Academy.

Joseph Northward. Cappella, Annenberg School for Communication, University of Pennsylvania.

Holli H. Seitz, Annenberg Schoolhouse for Communication, Academy of Pennsylvania.

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