Smoking Cessation
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Evaluation of EX: A National Mass Media Smoking Cessation Campaign Donna M. Vallone, PhD, MPH, Jennifer C. Duke, PhD, Jennifer Cullen, PhD, MPH, Kristen L. McCausland, MPH, and Jane A. Allen, MA
Mass media campaigns can be used to change smoking-related cognitions and to prompt quitting behavior, particularly when combined with other tobacco control efforts.1,2 Media campaigns at the national, community, and city level have been effectively used to increase smoking cessation among adults.3–8 The EX campaign (National Alliance for Tobacco Ces- sation, Washington, DC) was designed as a branded, mass media campaign aimed to en- courage adult smokers to quit.9,10 This campaign was pilot tested in 4 US cities in 2006 and 2007.10 In a longitudinal pilot study, confirmed campaign awareness was associated with statis- tically significant change in campaign-related cognitions over approximately 6 months.10 Given these findings, in the spring of 2008 the National Alliance for Tobacco Cessation (NATC)—a part- nership of states, national public health organi- zations, foundations, and corporations—launched EX as a national campaign.
The EX campaign is grounded in behavior change theory11–13 and the evidence regarding effective mass media campaigns.1,14–18 Given the evidence that branding can enhance the impact of a public health campaign, all messages are branded ‘‘EX.’’19,20 The target audience was defined as ‘‘smokers who are open to quitting but may not know how to successfully quit.’’ The campaign message strategy was based on quali- tative data from smokers at various stages in the quitting process, derived from more than 40 focus groups (more than 300 participants), 48 in-depth interviews, and a national survey of more than 1000 smokers. Messages are charac- terized by an empathetic, smoker-to-smoker voice that encourages smokers to relearn their life without cigarettes. Emphasis is placed on disassociating smoking from common daily ac- tivities that would otherwise function as smoking cues, such as driving or drinking coffee.
During the 6-month national campaign pe- riod, March 31 through September 28, 2008, EX advertisements aired on cable television at 549 average quarterly targeted rating points
(TRPs). TRPs are the standard unit of mea- surement for media delivery and reflect both the reach and the frequency of an advertise- ment. Reach describes the total percentage of the targeted population that is exposed to the advertisement; frequency describes the num- ber of times individuals in the targeted pop- ulation saw the advertisement, on average. TRPs are identical to gross rating points (GRPs), except that they are delivered to, and measured within, a specific and defined audience.2 EX advertising was not evenly distributed across the campaign period; 68% of the EX TRPs aired in the first 3 months of the campaign. Pfizer’s My Time to Quit campaign aired nationally at 382 average quarterly TRPs during the same period as the national EX campaign. The Phillip Morris campaign, Quit Assist, did not air during the study period; however, because it aired nationally in 2007 awareness of the campaign was measured and was included as a covariate in the present study to control for any residual campaign effects. No local or state-level tobacco control media was airing in 6 of the 8 designated
market areas (DMAs) from which the study sample was drawn. In one DMA, occasional public service announcements aired; in another, no information was available as to whether public service announcements would air. Public service announcements generally air at a low TRP level.
According to the Centers for Disease Control and Prevention, campaigns that deliver 1200 or more average quarterly TRPs during the introductory year of a campaign can expect to reach 75% to 85% of the target audience, in which case evaluators may expect to detect campaign awareness at 6 months, attitude change at 12 to 18 months, and behavior change at 18 to 24 months.2 Given funding constraints, the total media delivery of the EX campaign was approximately 47% of the level recommended by the Centers for Disease Con- trol and Prevention.2 Nevertheless, on the basis of the findings noted in the evaluation of the EX pilot campaign we hypothesized that EX awareness would be associated with significant change in campaign-related cognitions and
Objectives. We used longitudinal data to examine the relationship between
confirmed awareness of a national, branded, mass media smoking cessation
campaign and cessation outcomes.
Methods. We surveyed adult smokers (n = 4067) in 8 designated market areas
(‘‘media markets’’) at baseline and again approximately 6 months later. We used
multivariable models to examine campaign effects on cognitions about quitting,
quit attempts, and 30-day abstinence.
Results. Respondents who demonstrated confirmed awareness of the EX
campaign were significantly more likely to increase their level of agreement
on a cessation-related cognitions index from baseline to follow-up (odds
ratio [OR] = 1.6; P = .046). Individuals with confirmed campaign awareness
had a 24% greater chance than did those who were not aware of the cam-
paign of making a quit attempt between baseline and follow-up (OR = 1.24;
P = .048).
Conclusions. A national, branded, mass media smoking cessation campaign
can change smokers’ cognitions about quitting and increase quit attempts. We
strongly recommend that federal and state governments provide funding for
media campaigns to increase smoking cessation, particularly for campaigns that
have been shown to impact quit attempts and abstinence. (Am J Public Health.
2011;101:302–309. doi:10.2105/AJPH.2009.190454)
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behaviors despite the lower media delivery level. To test this hypothesis, we examined a longitudi- nal cohort of adult smokers drawn from 8 DMAs, with control for baseline and contextual vari- ables.
METHODS
We based our study on longitudinal data collected from a sample of 18- to 49-year-old current smokers from 8 US DMAs or media markets. A DMA is the standard geographic unit of measurement for mass media. Within DMAs, a population receives a uniform or a very similar mass media offering; across DMAs, however, levels of mass media delivery can vary markedly as a result of greater or lesser cable television penetration and popula- tion density. The DMAs from which this study sample was drawn were selected on the basis of several criteria. Each of the selected DMAs had at least 700 000 television households, as estimated by Nielsen in 2007 to 2008, and 5 DMAs had over 1 million television house- holds (Table 1).21,22 In addition, most of the selected DMAs had the potential for greater media delivery, as compared with other DMAs, on the basis of Nielsen data. These factors likely increased the proportion of the sample that was exposed to the campaign, and thus the likelihood of detecting campaign effects. Each of the selected DMAs had a sufficient population size to ensure that a random sample would yield
an adequate sample of smokers. Finally, the DMAs were selected to ensure cross-market variation with respect to key factors thought to potentially influence cessation outcomes: geo- graphic location, racial/ethnic composition, strength of tobacco control policy efforts (clean indoor air legislation, state tobacco control ex- penditures, cigarette price), and smoking preva- lence (Table 2). The 8 DMAs from which the sample was drawn were Birmingham, Alabama;
Columbus, Ohio; Fort Smith–Fayetteville, Arkansas; Houston, Texas; Kansas City, Missouri; Phoenix–Prescott, Arizona; Pittsburgh, Pennsyl- vania; and Portland, Oregon.
We conducted the baseline survey from February 5 through April 15, 2008, before the national launch of the EX media campaign. We used a list-assisted, random-digit-dial method to select a single-stage, unclustered sample of telephone numbers across the 8 DMAs, which generated approximately 874 000 numbers. Roughly 24% of the sampled telephone num- bers were determined to be residential after known nonworking and business-only num- bers were classified as ineligible, and residen- tial status was estimated for telephone numbers of unknown status. Of these, 6663 telephone numbers were for households consisting of at least one person who met the age and tobacco- use status eligibility criteria for this study. For each household contacted, up to 2 smokers were randomly selected and administered the survey in either English or Spanish. In this way, 8489 eligible respondents were identified. A total of 5616 of those eligible (66%) completed the baseline interview.
All baseline survey respondents were invited to participate in a follow-up survey conducted approximately 6 months after the campaign launch, August 23 through October 19, 2008.
TABLE 1—Characteristics of Selected Designated Market Areas: EX Campaign, 8 US
States, 2007–2008
Designated Market Area Sample Size, No. of Individuals No. of Television Householdsa Total TRPs Deliveredb,c
Birmingham, AL 756 730 430 1863.0
Columbus, OH 495 905 690 1367.4
Ft. Smith–Fayetteville, AR 456 1 039 890 875.5
Houston, TX 410 2 050 550 1279.8
Kansas City, MO 843 927 060 1336.7
Phoenix–Prescott, AZ 378 1 802 550 1091.5
Pittsburgh, PA 363 1 158 210 1381.2
Portland, OR 366 1 150 320 1566.6
Note. DMA = designated market area; TRP = targeted rating point. a Source. Nielsen DMA Market Universe Estimates, 2007–2008.
21
bSource. Nielsen Ad*Views data, 2008.22 cTRPs are the standard unit of measurement for media delivery and reflect both the reach and the frequency of an advertisement. Reach describes the total percentage of the targeted population that is exposed to the advertisement; frequency describes the number of times individuals in the targeted population saw the advertisement, on average.
TABLE 2—Characteristics of the Selected Designated Market Areas, by State: EX
Campaign, 2007–2008
State
State Smoking
Prevalence,a %
Total Tax per cigarette
pack,b $
State Per Capita
Funding,c $
Clean Indoor
Air Laws,d % Covered
Alabama 22.1 1.44 0.45 13.3
Ohio 20.1 2.26 0.64 100.0
Arkansas 22.3 2.16 6.55 4.4
Oklahoma 24.7 2.04 5.72 0
Texas 18.5 2.42 0.54 39.0
Missouri 25.0 1.18 0.40 14.9
Kansas 17.9 1.80 0.82 22.8
Arizona 15.9 3.01 3.55 100.0
Pennsylvania 21.3 2.61 1.51 11.7
Oregon 16.3 2.19 2.40 8.5
Washington 15.7 3.04 2.58 100.0
aSource. Behavioral Risk Factor Surveillance Survey 2008.23 b Data reflect state and national tax combined.
24
c Funding for tobacco control for FY 2008 divided by 2008 state census population.
25
d Source. American Nonsmokers’ Rights Foundation, US Tobacco Control Laws Database.
26
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Among the baseline respondents, 4067 suc- cessfully completed the follow-up survey, resulting in a follow-up response rate of 73% and an overall response rate of 48% among known eligible households.27 Interviews were conducted as computer-assisted telephone inter- views. Respondents were offered an incentive to complete each survey.
Measures
The primary independent variable in this study was exposure to the EX campaign as measured by confirmed awareness of individ- ual EX advertisements. Confirmed awareness of EX advertisements was measured by ask- ing respondents whether they had ‘‘recently seen an ad on TV’’ followed by a brief de- scription of the beginning of the advertisement. Respondents were then asked to describe the end of the advertisement. Only those who were able to accurately describe one or more of the EX advertisements were classified as having confirmed awareness.
Control variables assessed at baseline in- cluded age, gender, race/ethnicity, educational attainment, number of cigarettes smoked per day, and having made a quit attempt within the 6 months before the baseline interview. Moti- vation to quit was also assessed at baseline with the item, ‘‘On a scale of 1 to 10, where 1 equals ‘not at all’ and 10 equals ‘very much,’ how much do you want to quit smoking?’’ Control variables assessed at follow-up included nico- tine dependence, as measured by using the Fagerstrom Test for Nicotine Dependence item ‘‘Time to First Cigarette’’ of the day28; whether the respondent lived with another smoker; and hours of television, radio, and Internet use per day.
Awareness of other cessation-related cam- paigns, including Pfizer’s My Time to Quit and Philip Morris’ Quit Assist campaigns, was also measured. Aided awareness was measured by asking respondents ‘‘Have you seen a My Time to Quit ad such as the one that shows a woman describing the specific times during the day when she smokes?’’ and ‘‘Have you seen a Quit Assist ad by Philip Morris to help people quit smoking cigarettes?’’ Use of pharmacotherapy was assessed by using 2 items: (1) ‘‘Have you ever used nicotine replacement products to help you quit smoking?’’ and (2) ‘‘Have you ever used a prescription medication called
TABLE 3—Demographics and Smoking Behaviors of a Longitudinal Sample of Smokers
at Baseline and Follow-up: EX Campaign, 8 US States, 2007–2008
Demographics and Smoking Behaviors
Baseline (n = 5616), %
or Mean 6SE
Follow-upa (n = 4067), %
or Mean 6SE
Designated Market Area
Birmingham, AL 18.7 18.6
Kansas City, MO 19.6 20.7
Columbus, OH 11.4 12.2
Fort Smith–Fayetteville, AR 11.4 11.2
Houston, TX 11.2 10.1
Phoenix–Prescott, AZ 10.0 9.3
Pittsburgh, PA 8.5 8.9
Portland, OR 9.2 9.0
Gender
Male 46.9 45.2
Female 53.1 54.8
Race/ethnicity
Non-Hispanic White 71.9 74.1
Non-Hispanic Black 12.2 11.5
Hispanic 8.5 7.4
Other 7.3 7.0
Age, y
18–24 16.2 15.2
25–39 41.4 39.1
40–49 42.5 45.8
Education level
Less than high school, high school diploma, or GED 63.6 62.7
Some college, technical or associate’s degree 26.1 26.6
At least a college degree 10.3 10.7
Media exposure (daily h of television, radio, and Internet) 8.5 60.07 8.5 60.08
Smokers in household (yes) 58.4 58.6
Smoking status
Current smoker 100.0 94.7
Daily smoker 87.2 83.7
Some day smoker 12.8 10.9
Current smoker with at least 1 quit attempt 46.3 40.3
Former smoker 0.0 5.3
Recent quitter (quit in the past 30 d) 0.0 3.9
Time to first cigarette b
Within 5 min 29.9 30.0
6–30 min 33.0 33.7
> 30 min 37.1 36.3
Cigarettes smoked per d 16.0 60.0.14 16.2 60.16
Use of pharmacotherapy cessation aids
Yes 39.1 41.2
No 60.9 58.8
Motivation to quit (1–10 scale) b,c
6.78 60.0.039 6.78 60.046
Continued
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Bupropion, Zyban, or Wellbutrin to help you quit smoking?’’ Respondents who answered ‘‘yes’’ to either item were classified as having a history of use of pharmacological cessation aids, whereas those who responded ‘‘no’’ to both items were classified as not having such a history.
Outcome variables included changes in a cessation-related cognitions index, having made a quit attempt of 24 hours or longer between the baseline and follow-up interviews, and 30-day point prevalence abstinence, de- fined as both not smoking at the time of the follow-up survey as well as not having smoked even 1 puff of a cigarette for 30 days or more before the date of the follow-up survey. The cognitions index was composed of 8 items. The first 4 items were statements, with responses measured along a 4-point Likert scale ranging from ‘‘strongly agree’’ to ‘‘strongly disagree’’: ‘‘I have been thinking a lot about quitting smok- ing recently’’; ‘‘I am eager for a life without smoking’’; ‘‘Lately, I have been thinking about which cigarettes during my day would be the hardest to give up’’; and ‘‘I am not prepared to make changes in my life to quit smoking.’’ The next 3 items measured motivation to quit, readiness to quit, and quitting as a priority by asking, ‘‘On a scale of 1–10, where 1 equals not at all and 10 equals very much, how much do you want to quit smoking?’’; ‘‘Are you seriously thinking of quitting in the next 30 days, the next 6 months, or not at all?’’; and ‘‘On a scale of 1–5, where 1 is the lowest and 5 is the highest, how would you rate quitting smoking as a pri- ority in your life?’’ The final item asked re- spondents, ‘‘During the last 30 days, would you
say you have thought about the changes you will have to make in your life to quit smoking?’’ Response options for this item were every day, most days, some days, or rarely. The cognitions index score (Cronbach a = 0.79) was calculated by recoding the items to a standard scale, which ranged from –24 to 40 and then averaging across the 8 items. A higher score on the index represented more favorable cognitions about quitting smoking.
Data Analyses
All statistical analyses were performed by using SAS version 9.13 (SAS Institute Inc, Cary, NC). We weighted all data to account for differential sampling rates, to reduce the bias due to nonresponse to both the screening and the interview, and to weight the data to key demographic characteristics of the US popula- tion. The weights were constructed from 2007 population totals for persons aged 18 to 49 years in each DMA and 2008 smoking rates calculated by age, race, gender, and education level from the Behavioral Risk Factor Surveil- lance Study.23 Because of the probability that up to 2 adults per household could be selected for study inclusion, we made adjustments to account for clustering at the household level (intracluster correlation).
We conducted multivariable logistic and linear regression analyses to assess the strength of the association between the key independent variable, confirmed awareness of EX, and the cessation-related outcomes—cognitions and quit behaviors—at 6 months after the campaign launch. We used a multivariable linear regres- sion model to model the cognitions index
change score, with adjustment for study cova- riates. We analyzed quit attempts by using a multivariable logistic regression model with a dichotomous outcome of 1 or more attempts as compared with no quit attempts between baseline and the follow-up interview. We ana- lyzed smoking abstinence in the past 30 days by using a multivariable logistic regression model with a dichotomous outcome of staying quit for 30 or more days as compared with less than 30 days. We used likelihood ratio tests to assess goodness of fit for all models. The models included a fixed-effect DMA indicator variable to account for any unmeasured con- textual factors, including state tobacco control policies. An alternate set of models explored the effect of adding state tobacco control policy variables in addition to the DMA indicator; however, this resulted in multicollinearity. In the final models, the DMA indicator was in- cluded, and the policy variables were omitted, because the DMA indicator served to control for policy variables as well as any unknown, and therefore unmeasured, factor associated with the outcomes.
RESULTS
The longitudinal sample consisted of 4067 smokers at follow-up, of whom 74% were non-Hispanic White, 12% were non-Hispanic Black, and 7% were Hispanic (Table 3). The mean age of the sample was 37 years; 85% of the sample fell within the media campaign’s primary age target of 25 to 49 years. The sample was skewed toward female. Approxi- mately 63% of the sample reported earning a high school diploma or general equivalency diploma or having less than a high school education. More than half of the sample (59%) reported living with at least 1 other smoker.
Approximately 64% of the sample reported smoking their first cigarette of the day within 30 minutes of waking. The mean number of cigarettes smoked per day was 16.2. More than two thirds of the sample (67%) was seriously considering a quit attempt within the next 6 months. Approximately 46% had made at least 1 quit attempt of 24 hours or longer between baseline and the follow-up interviews. At fol- low-up, 5.3% of the respondents (n = 217) reported having stopped smoking. Among
TABLE 3—Continued
Readiness to quitb
Seriously thinking about quitting smoking in the next 30 d 17.2 16.5
Seriously thinking about quitting smoking sometime in the next 6 mo 50.0 50.9
Not thinking of quitting smoking 32.9 32.7
Quit attempt in past 6 mo (yes) 46.3 45.6
Confirmed awareness of EX campaign n/a 41.3
Aided awareness of Philip Morris Quit Assist campaign 49.8 41.7
Aided awareness of Pfizer My Time to Quit campaign 62.6 42.5
Note. GED = general equivalency diploma. Column percentages are unweighted. aIncludes 217 respondents who reported smoking at baseline and were not smoking at follow-up. bFor follow-up, n = 3850 respondents who reported smoking at both baseline and follow-up. cOn a scale of 1 to 10, where 1 equals not at all and 10 equals very much, how much do you want to quit smoking?
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those still smoking, the average number of cigarettes smoked per day did not decline.
Awareness of EX Advertising
At follow-up, approximately 41% of the re- spondents in the overall sample demonstrated confirmed awareness of EX advertisements. Confirmed awareness levels ranged from 30% to 51% across the 8 DMAs. Smokers with confirmed awareness did not differ signifi- cantly from those who were unaware of EX in terms of demographic characteristics or smoking-related variables, with the exception of DMA, gender, My Time to Quit ad aware- ness, and cognitions index change score. Fe- male respondents were 20% more likely to be aware of EX (odds ratio [OR] =1.2; P = .037) than were male respondents. Respondents who were aware of the My Time to Quit ads were 2.2 times as likely to demonstrate confirmed awareness of EX (OR = 2.2; P < .001) as were those who were not aware.
Influence of Confirmed Awareness
on Campaign-Related Cognitions and
Quit Behavior
Respondents who demonstrated confirmed awareness of EX were significantly more likely to increase their level of agreement on the cessation-related cognitions index from base- line to follow-up (OR =1.6; P = .046), as calcu- lated from the b coefficient of 0.463 presented in Table 4. However, those who made 1 or more quit attempts before the baseline survey were less likely to report agreement on the cessation-related cognitions index (OR = 0.44; P < .001).
Those with confirmed awareness of EX were more likely to make at least 1 quit attempt between baseline and the follow-up interviews (OR =1.24; P = .048; Table 5). Other factors that were significantly related to having made a quit attempt within the study period included time to first cigarette (OR =1.45; P = .022), motivation to quit (OR =1.15; P < .001), recent quit attempts before baseline (OR = 4.6; P < .001), and media exposure (OR =1.03; P = .014).
With respect to the 30-day point prevalence for abstinence, the results showed a trend to- ward greater abstinence among those with confirmed awareness of EX; however, this find- ing was not significant (OR =1.51; P = .16; data
TABLE 4—Results of the Multivariable Linear Regression Predicting the Cognitions Index
Change Score: EX Campaign, 8 US States, 2007–2008
Independent Variable b (SE) Stratum-Specific P P
Designated Market Area .81
Birmingham, AL (Ref) 1.00 NA
Columbus, OH 0.1717 (0.311) .58
Fort Smith–Fayetteville, AR 0.2253 (0.3767) .55
Houston, TX 0.4576 (0.3897) .24
Kansas City, MO –0.0211 (0.2763) .94
Phoenix–Prescott, AZ 0.4729 (0.4047) .24
Pittsburg, PA –0.0558 (0.3422) .87
Portland, OR –0.0912 (0.4329) .83
Age, y .97
18–24 (Ref) 1.00 NA
25–39 0.0705 (0.3369) .83
40–49 0.0200 (0.3141) .94
Gender .11
Female (Ref) 1.0 NA
Male 0.3565 (0.2242) .11
Race/Ethnicity .36
Non-Hispanic White (Ref) 1.00 NA
Hispanic –0.4468 (0.4653) .34
Non-Hispanic Black 0.4218 (0.3383) .21
Other –0.2873 (0.4674) .54
Education level .22
High school or GED (Ref) 1.00 NA
Less than high school 0.0406 (0.2982) .89
Some college, technical or associate’s degree 0.066 (0.2681) .806
College degree or more 0.7007 (0.3437) .042
Time to first cigarette .74
Within 5 min (Ref) 1.00 NA
6–30 min 0.1883 (0.2626) .47
> 30 min 0.0484 (0.3109) .88
Cigarettes smoked a
per day. –0.0071 (0.0128) .58 .58
Quit attempts in 6 mo before baseline >.001
0 (Ref) 1.00 NA
‡ 1 –0.8151 (0.2253) <.001 Media exposure (television, radio, and Internet)b per day. 0.0233 (0.0181) .2 .2
Lives with a smoker .3
No (Ref) 1.00 NA
Yes 0.221 (0.215) .3
Aided awareness of Quit Assist .24
No 1.000 NA
Yes –0.2642 (0.2229) .24
Aided awareness of My Time to Quit .67
No 1.00 NA
Yes 0.1001 (0.2347) .67
Confirmed awareness of EX .046
No (Ref) 1.00 NA
Yes 0.463 (0.2323) .046
Note. GED = general equivalency diploma; NA = not applicable; SE = standard error. aMeasured in 1-cigarette increments and presented as a continuous variable. bMeasured in 1-hour increments and presented as a continuous variable.
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available upon request from the authors). Other key covariates associated with the 30-day point prevalence for abstinence include fewer cigarettes smoked per day (OR = 0.95; P = .008), as well as Hispanic (OR =1.7; P = .007) and other race/ethnicity (OR = 0.19; P = .019).
DISCUSSION
The results of our study showed that expo- sure to a branded, mass media smoking cessa- tion campaign can shift smokers’ cognitions about cessation and increase quit attempts over a relatively short period of time. These find- ings confirm those of the EX pilot campaign evaluation,10 which showed that confirmed awareness of EX was associated with change in campaign-related cognitions and a trend toward prompting quitting behavior. To our knowledge, this is the first longitudinal study of a national, branded, mass media smoking cessation cam- paign in the United States. Moreover, this is the first study to demonstrate an association between individual-level confirmed exposure to specific media messages and quit attempts, rather than linking GRPs or other measures of media de- livery with declines in tobacco consumption or smoking prevalence at the population level.
There were several limitations to our study. First, our analysis may have been limited by the lack of randomization, which did not allow us to rule out the influence of an unknown factor related to the outcomes. However, our results do reflect a temporally ordered effect that controlled for known baseline factors before the campaign launched. Second, those who recalled the EX campaign messages may have differed from those who did not. How- ever, additional analyses indicated that aware- ness of EX was not associated with baseline quit attempts, readiness to quit, or cessation- related cognitions, findings which suggested that selective attention bias did not affect the validity of the study. Third, we measured aided rather than confirmed awareness of the Phillip Morris and Pfizer advertisements. Analysis of EX pilot campaign data indicated that respon- dents were not able to differentiate between the highly similar Phillip Morris and Pfizer advertisements, thus resulting in low levels of confirmed awareness for these campaigns. Be- cause aided awareness is a less conservative measure than is confirmed awareness, we used
TABLE 5—Results of the Logistic Regression Model Predicting Quit Attempts:
EX Campaign, 8 US States, 2007–2008
Independent Variable OR (95% CI) Stratum-Specific P Summary P
Designated Market Area .6
Birmingham, AL (Ref) 1.00 (Ref) NA
Columbus, OH 1.025 (0.75, 1.39) .93
Fort Smith–Fayetteville, AR 1.1 (0.77, 1.59) .64
Houston, TX 1.27 (0.85, 1.89) .18
Kansas City, MO 0.88 (0.66, 1.18) .11
Phoenix–Prescott, AZ 0.97 (0.69, 1.38) .63
Pittsburg, PA 0.92 (0.66, 1.28) .32
Portland, OR 1.16 (0.80, 1.68) .4
Age, y .13
18–24 (Ref) 1.00 NA
25–39 0.75 (0.56, 0.99) .087
40–49 0.80 (0.60, 1.07) .49
Gender .63
Female (Ref) 1.00 NA
Male 1.05 (0.87, 1.27) .63
Race/Ethnicity .104
Non-Hispanic White (Ref) 1.00 NA
Hispanic 1.09 (0.73, 1.65) .83
Non-Hispanic Black 1.57 (1.10, 2.26) .038
Other 0.96 (0.57, 1.63) .44
Education level .102
High school or GED (Ref) 1.00 NA
Less than high school 1.15 (0.87, 1.53) .95
Some college, technical, or associate’s degree 1.02 (0.80, 1.30) .17
College degree or more 1.47 (1.06, 2.05) .036
Time to first cigarette .022
Within 5 min (Ref) 1.00 NA
6–30 min 1.10 (0.85, 1.41) .37
> 30 min 1.45 (1.10, 1.92) .006
Cigarettes smokeda 0.989 (0.978, 1.00) .072 .072
Motivation to quit: 1–10 scale 1.15 (1.11, 1.19) <.001 <.001
Quit attempts in 6 months before baseline <.001
0 (Ref) 1.00 NA
‡ 1 4.60 (3.73, 5.67) <.001 Media exposure (television, radio, and Internet)
b 1.03 (1.01, 1.05) .014 .014
Lives with a smoker .902
No (Ref) 1.00 NA
Yes 1.01 (0.83, 1.24) .902
Aided awareness of Quit Assist .36
No (Ref) 1.00 NA
Yes 0.91 (0.73, 1.12) .36
Aided awareness of My Time to Quit .54
No (Ref) 1.00 NA
Yes 1.07 (0.87, 1.31) .54
Continued
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it as a control variable (although it may over- estimate the effects of the Pfizer and Philip Morris campaigns) but was not suitable for use in comparing these campaigns with EX. Fourth, the sample was drawn from 8 DMAs; thus, the findings of the study may not reflect a national response to the campaign.
Fifth, the relatively brief duration of this study period made it difficult to detect longer- term effects, such as 30-day abstinence. We plan to examine this relationship further in the second follow-up. Sixth, because of the small proportion of the sample that achieved 30-day abstinence, we were underpowered to dem- onstrate a statistically significant effect between EX awareness and this outcome. Last, the attrition of the sample may have resulted in biases among the smokers at this follow-up. However, our analyses with baseline data in- dicated few differences between the respon- dents in the completed sample and those lost to follow-up.
Although the EX campaign was created by Legacy, the national implementation of the campaign is headed by the NATC, a public- private media collaborative of states, national public health organizations, foundations, and corporations. This model allows states and other localities to air EX in coordination with their quit line availability and other local services while leveraging exposure to the na- tional branded campaign. As a result, states and localities can avoid or reduce the costly efforts associated with advertising concept develop- ment, testing, production, and evaluation.
Despite the strengths of the NATC, the EX campaign is expected to transition to a public service announcement campaign in the com- ing year. As a public service announcement campaign, EX will air at fewer GRPs than it did during the period of this study. Furthermore, given the annual changes to state budgets,
many state NATC members have not been able to guarantee future support to the Alli- ance.
Our study suggests that a robust, evidence- based, national mass media campaign can change cessation-related cognitions and in- crease quit attempts over a relatively short period. Stronger campaign effects—and thus greater benefits to society—would likely be found if the campaign were aired at a higher level of media delivery and were sustained over the course of several years.
We strongly recommend that federal and state governments provide funding for mass media campaigns aimed at increasing smoking cessation, with a particular focus on those that have been shown to affect quit attempts and abstinence. Given that smoking remains the primary cause of death in the United States, and given the escalating costs of health care, reducing smoking may well be the simplest contribution to ‘‘bending the health care cost curve’’ in the future. This recommendation is a public health opportunity that is long overdue and can help to leverage the efforts of state and local public health organizations to reduce smoking rates in the United States and ulti- mately save lives. j
About the Authors Donna M. Vallone, Jennifer Cullen, Kristen L. McCausland, and Jane A. Allen are with Legacy’s Research and Evaluation Department, Washington, DC. Jennifer C. Duke is with Research Triangle Institute, Raleigh, NC.
Correspondence should be sent to Donna M. Vallone, 1724 Massachusetts Avenue, NW, Washington, DC 20036 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the ‘‘Reprints/Eprints’’ link.
This article was accepted May 3, 2010.
Contributors D. M. Vallone originated and designed this study and directed the analysis and writing. J. C. Duke contributed to the study design, developed the survey instrument,
managed the data collection, and developed the initial analytic models. J. Cullen refined the analytic models, analyzed and interpreted the data, and contributed to writing the article. K. L. McCausland contributed sub- stantively to the development of the survey instrument, management of the data collection process, and inter- pretation of the data. J. A. Allen contributed to the interpretation of the data and prepared the final article.
Acknowledgments The authors thank Cheryl G. Healton for her thoughtful comments on this study, Haijun Xiao for his assistance with data analysis, and Jeff Costantino for his help in obtaining and interpreting the gross rating point data.
Human Participant Protection This study was approved by the human subjects review committees of Westat, the organization that conducted the data collection, and Copernicus Group Independent Review Board, the external institutional review board used by Legacy.
References 1. NCI Tobacco Control Monograph Series. The Role of the Media in Promoting and Reducing Tobacco Use. Monograph 19. Rockville, MD: National Cancer Institute, US Dept of Health and Human Services, National In- stitutes of Health; 2008.
2. Best Practices for Comprehensive Tobacco Control Programs—2007. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Pre- vention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2007.
3. Warner KE. The effects of the anti-smoking cam- paign on cigarette consumption. Am J Public Health. 1977;67(7):645–650.
4. Warner KE. Effects of the antismoking campaign: an update. Am J Public Health. 1989;79(2):144–151.
5. Reducing the Health Consequences of Smoking: 25 Years of Progress. A Report of the Surgeon General. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention, Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 1989. DHHS publication no. (CDC) 89-8411.
6. McAlister A, Morrison TC, Hu S, et al. Media and community campaign effects on adult tobacco use in Texas. J Health Commun. 2004;9(2):95–109.
7. Wakefield MA, Durkin S, Spittal MJ, et al. Impact of tobacco control policies and mass media campaigns on monthly adult smoking prevalence. Am J Public Health. 2008;98(8):1443–1450.
8. Centers for Disease Control and Prevention. Decline in Smoking Prevalence—New York City, 2002—2006. MMWR Morb Mortal Wkly Rep. 2007;56(24):604–608.
9. McCausland KL, Allen JA, Duke JC, et al. Piloting EX, a Social Marketing Campaign to Prompt Smoking Cessa- tion. Soc Mar Q. 2009;15(suppl 1):81–101.
10. Vallone DM, Duke JC, Mowery PD, et al. The impact of EX: results from a pilot smoking-cessation media campaign. Am J Prev Med. 2010;38(suppl 3):S312– S318.
11. Fishbein MA. Consideration of beliefs and their role in attitude measurement. In: Fishbein M, ed. Readings in
TABLE 5—Continued
Confirmed awareness of EX .048
No (Ref) 1.00 NA
Yes 1.24 (1.00, 1.54) .0475
Note. CI = confidence interval; GED = general equivalency diploma; NA = not applicable; OR = odds ratio. a Measured in 1-cigarette increments and presented as a continuous variable.
b Measured in 1-hour increments and presented as a continuous variable.
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308 | Research and Practice | Peer Reviewed | Vallone et al. American Journal of Public Health | February 2011, Vol 101, No. 2
Attitude Theory and Measurement. New York, NY: Wiley; 1967:257–266.
12. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall; 1986.
13. Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the Health Belief Model. Health Educ Q. 1988;15(2):175–183.
14. Designing and Implementing an Effective Tobacco Counter-Marketing Campaign. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2003.
15. Flay BR, Burton D. Effective mass media commu- nication strategies or health campaigns. In: Atkin C, Wallack L, eds. Mass Communication and Public Health: Complexities and Conflicts. Newbury Park, CA: Sage; 1990:129–146.
16. McKenna J, Gutierrez K, McCall K. Strategies for an effective youth counter-marketing program: recommen- dations from commercial marketing experts. J Public Health Manag Pract. 2000;6(3):7–13.
17. Hornik R. Public Health Communication: Evidence for Behavior Change. Mahwah, NJ: Lawrence Erlbaum Asso- ciates; 2002.
18. Bala M, Strzeszynski L, Cahill K. Mass media interventions for smoking cessation in adults. Cochrane Database Syst Rev. 2008;23(1):CD004704.
19. Evans WD, Price S, Blahut S. Evaluating the truth brand. J Health Commun 2005;10(2):181–192.
20. Asbury LD, Wong FL, Price SM, Nolin MJ. The VERB campaign: applying a branding strategy in public health. Am J Prev Med. 2008;34(suppl 6):S183–S187.
21. Nielsen Media Research. Nielsen DMA Market Universe Estimates, 2007–2008. New York, NY: The Nielsen Company; 2008.
22. Nielsen Media Research. Nielsen Ad*Views Data, 2008. New York, NY: The Nielsen Company; 2008.
23. Centers for Disease Control and Prevention. State- specific secondhand smoke exposure and current ciga- rette smoking among adults—United States, 2008. MMWR Morb Mortal Wkly Rep. 2009;58(44):1232– 1235.
24. State Cigarette Excise Tax Rates & Rankings. Washington, DC: Campaign for Tobacco-Free Kids. Available at: http://www.tobaccofreekids.org/research/ factsheets/pdf/0097.pdf. Accessed November 11, 2010.
25. FY2008 Rankings of State Funding for Tobacco Prevention. Washington, DC: Campaign for Tobacco- Free Kids. Available at: http://www.tobaccofreekids.org/ reports/settlements/2008/staterankings.pdf. Accessed November 8, 2010.
26. US Tobacco Control Laws Database. Berkeley, CA: American Nonsmokers Rights Foundation; 1998–2010.
27. American Association of Public Opinion Research. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. Revised 2008. Available at: http://www.aapor.org/uploads/Standard_Defini- tions_07_08_Final.pdf. Accessed November 8, 2010.
28. Baker TB, Piper ME, McCarthy DE, et al. Time to first cigarette in the morning as an index of ability to quit smoking: implications for nicotine dependence. Nicotine Tob Res. 2007;9(4):S555–S570.
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