driving down danger using regulatory focus and elaborative

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Journal of Business Research

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Driving down danger: Using regulatory focus and elaborative approach toreduce intentions to text & drive

Kelly Naletelicha,⁎, Seth Ketronb, Nancy Spearsc

a James Madison University, College of Business, 800 South Main St., Harrisonburg, VA 22807, United States of Americab California State Polytechnic University, Pomona, International Business and Marketing, College of Business Administration, 3801 W Temple Ave, Pomona, CA 91768,United States of AmericacUniversity of North Texas, College of Business, 1155 Union Circle #311160, Denton, TX 76203, United States of America

A R T I C L E I N F O

Keywords:Regulatory focusEmotionsElaborative approachInformation processingMotivationCognitive load

A B S T R A C T

Texting and driving is a growing societal concern, yet few studies have examined motivational determinants andelaborative processing driving this behavior. Thus, we combine regulatory focus theory and two elaborativeapproaches to information processing (imagining versus considering) to examine the issue of texting and driving.The findings demonstrate that promotion-focused (prevention-focused) individuals have greater intentions todecrease texting and driving when asked to imagine (versus consider) potential outcomes. However, focusingspecifically on negative outcomes suppresses the effect of imagining for promotion-focused individuals, whereasa focus on negative outcomes does not significantly change the effect of imagining versus considering for pre-vention-focused individuals. Further, low (high) cognitive load renders both elaborative approaches equallyeffective for promotion-focused (prevention-focused) individuals. Finally, negative emotional intensity is iden-tified as the mediator driving these effects. The findings underscore the need to tailor texting and driving ad-vertisements to consumers' motivational and processing frames.

1. Introduction

Texting and driving is dangerous (i.e., Caird, Johnston, Willness,Asbridge, & Steel, 2014; Tractinsky, Ram, & Shinar, 2013). In 2015,mobile devices resulted in over 1.2 million motor vehicle accidents,with 341,000 of these from texting and driving (National SafetyCouncil, 2015). Further, younger generations are frequent violators,with 44.5% of high school students reporting the behavior and 92%+of college students admitting to reading a text while driving within agiven month (Atchley, Atwood, & Boulton, 2011).

The risks of texting and driving have led several organizations tolaunch advertising campaigns discouraging the behavior. For example,in 2013, AT&T spent tens of millions of dollars alone on advertisingcampaigns to dissuade consumers from distracted driving (Hall, 2013).As such, consumers are continuously reminded of the risks, dangers,and dire consequences of texting and driving through advertisementsand public service announcements (Hall, 2013). Given the constantnegative press, texting and driving should naturally be viewed nega-tively, and these negative associations and accompanying emotionsshould signal avoidance and discontinuance of the behavior (Carver &Scheier, 1990; Clore, 1994; Fredrickson, 2004; Frijda, 1994). However,

despite the prevalent negative messaging and associations, texting anddriving continues to be a consistent and pervasive problem amongconsumers (Atchley et al., 2011; National Safety Council, 2015).

Surprisingly, texting and driving has received minimal attention inmarketing. A few studies in the marketing domain have investigatedtexting and driving, including studies on campaign styles (Cismaru &Nimegeers, 2017) and salience of mortality (Kareklas & Muehling,2014). However, much remains to be learned from both academic andpractical perspectives, particularly with respect to the motivationalsystems of texting drivers or the ways in which consumers process in-formation from messages discouraging texting and driving.

Thus, we apply precepts from regulatory focus theory to investigatetwo primary motivational systems as they relate to texting and driving.The first system is a promotion focus, attuned to a positive, broadenedmindset inclined to take more risks in the hope of advancing beyond theindividual's status quo or perceived state of normalcy (“0” to “+1,” orimproving upon one's current perceived state). The second system, aprevention focus, is more attuned to a narrow, deliberative mindset in-clined to take fewer risks to avoid falling below the status quo (i.e.,maintaining a state of “0” and not reverting to “-1,” or avoiding drop-ping below one's current perceived state; Gino & Margolis, 2011;

https://doi.org/10.1016/j.jbusres.2019.03.009Received 2 April 2018; Received in revised form 3 March 2019; Accepted 4 March 2019

⁎ Corresponding author.E-mail address: [email protected] (K. Naletelich).

Journal of Business Research 100 (2019) 61–72

0148-2963/ © 2019 Published by Elsevier Inc.

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Higgins, 1997; Higgins, 1998). Although regulatory focus can be ex-amined from a chronic or situational state, researchers have shown thatconsumers respond more favorably when their chronic regulatory states(versus situational primes) match the context at hand; thus, the presentpaper examines regulatory focus from a chronic perspective (i.e., Keller& Bless, 2006).

The research also investigates the impact of fit between regulatoryfocus and two elaborative approaches on reducing texting and driving.The first approach involves imagining future outcomes, while in thesecond approach, the consumer considers the details presented in an ad(Spears & Yazdanparast, 2014). The present study finds that the ela-borations of the imagination align with a promotion focus becauseimagining is an expansive approach offering movement beyond thestatus quo, in line with promotion-focused individuals' eager strategies(i.e., Higgins & Cornwell, 2016). On the other hand, considering alignsbetter with a prevention focus because considering is a narrowing ap-proach more attuned to negative signals and a point-by-point compar-ison of ad details; this approach focuses more on maintaining the statusquo, in line with vigilant strategies. Thus, we propose that the alignmentof regulatory focus with consistent elaborative approaches reducestexting and driving through regulatory fit effects.

Further, the present investigation finds that when cognitive load isnot salient, a focus on negative outcomes reduces the effectiveness ofimagining for promotion-focused consumers because promotion-fo-cused individuals' inclination toward positive, expansive ways ofthinking are in direct conflict with negative thinking. In this case,imagining is no more effective than considering in reducing intentionsto text and drive for promotion-focused individuals. Fourth, cognitiveload moderates the effectiveness of regulatory fit with elaborative ap-proaches. We demonstrate that when under low cognitive load, pre-vention-focused consumers are more responsive to negative informa-tion when asked to consider, while imagining and considering arecomparably effective for a promotion-focused consumer. In contrast,when under high cognitive load, imagining (versus considering) canfurther boost the effects of negative thinking for promotion-focusedconsumers, while for a prevention-focused consumer, both elaborativeapproaches are comparably effective. These findings show that ela-borative approaches can be strategically used to overcome load-relatedobstacles to processing.

2. Theoretical background

2.1. Two elaborative approaches: imagining and considering

When consumers are exposed to an ad that warns of the outcomes oftexting and driving, that ad information is processed in workingmemory with elaborations that combine the information with triggeredinformation from memory store, resulting in new knowledge (Leahy &Sweller, 2008; Schau, 2000; Spears & Yazdanparast, 2014). This workinvestigates two distinct approaches to such ad elaborations, one inwhich the consumer imagines future texting and driving outcomes andone in which the consumer considers ad details.

The elaborative approach of imagining joins incoming sensory in-formation with stored episodic memories containing contextually re-lated semantic details. The result is a mental simulation of a yet-to-be-experienced scenario (Rawlings & Rawlings, 1974; Silvera et al., 2014;Sweller & Sweller, 2006). With a texting and driving ad, the mentalsimulations of the imagination combine the ad information with trig-gered episodic memories of previous texting and driving experiencesand stories along with contextually relevant semantic details, such asthe type of phone that is used, the typical persons with whom he/shetexts, the feel of the steering wheel, and smell of the automobile(Baumgartner, Sujan, & Bettman, 1992; Spears, Ketron &Ngamsiriudom, 2016; Tulving, 1972).

Meanwhile, the considering consumer compares the facts presentedin the ad with triggered semantic details that are drawn from stored

memory, such as the details of the last text message sent/received,words that were received in a text from a friend, etc. (Baumgartneret al., 1992; Leahy & Sweller, 2008; Tulving, 1972). This process is amore effortful point-by-point comparison (Foley, Wozniak, & Gillum,2006; Sweller & Sweller, 2006). For example, if we assume that theconsumer considers two information units from the texting and drivingad with two units from triggered memory about his/her typical textingand driving patterns, four total units of information may be combined,with 24 possible permutations of information.

While both elaborative approaches rely on semantic details, thesemantic details of the imagination are effortlessly retrieved as part of atriggered holistic episodic memory. Meanwhile, in the consider ela-borative approach, retrieval of semantic details is an effortful point-of-parity process that compares specific ad details with relevant semanticdetails from memory, problem-solving to resolve differences betweenincoming ad information and triggered semantic details (Foley et al.,2006; Sweller & Sweller, 2006). Thus, handling sequential and multiplepotential detail permutations is more likely to exceed the limitations ofworking memory, compared to the less effortful, more expansive, andmore efficient holistic approach of the imagination (Foley et al., 2006;Leahy & Sweller, 2004, 2008; Sweller & Sweller, 2006).

2.2. Achieving regulatory fit with elaborative approaches

Given the different profiles of imagining and considering as de-scribed above, marketers can align imagining and considering withconsumers' motivational frames to create more compelling ad messagesthat discourage texting and driving. One such opportunity lies in thealignment of imagining and considering with regulatory focus to createregulatory fit. Regulatory fit is an enhanced state emerging from thealignment of regulatory focus and goal pursuit strategies, such that thetactics used to approach a goal sustains one's motivational orientationand results in enhanced persuasion and behavior change (Avnet &Higgins, 2006; Cesario, Higgins, & Scholer, 2008; Higgins & Cornwell,2016; Higgins, Idson, Freitas, Spiegel, & Molden, 2003; Wang & Lee,2006). One of the most effective tactics to create regulatory fit is tomanipulate a key element within the persuasion message (Cesario et al.,2008), which in this case is the way an individual processes a textingand driving ad. According to regulatory fit theory, if the way in-formation is processed helps to maintain the regulatory goal of a pro-motion (eagerly advancing beyond the status quo) or a prevention(vigilantly maintaining the status quo) focus, fit will be achieved, re-sulting in greater intentions to reduce texting while driving.

Promotion-focused individuals tend judge the immediate environ-ment as relatively safe and make eager decisions based upon imaginedfuture outcomes. These imaginings help to focus attention on broaderoutcomes related to hopes, aspirations, and dreams and the potentialfor advancing beyond the status quo (Baas, De Dreu, & Nijstad, 2011;Higgins & Cornwell, 2016; Huttermann & Memmert, 2015). Thesecharacteristics align well with imagining (versus considering) as ima-gining allows for efficient processing that can broaden attentional focuson future outcomes (Foley et al., 2006; Leahy & Sweller, 2004, 2008).These broader imaginings keep promotion-focused consumers' proces-sing of the texting and driving message centered on their overarchinggoal of eager advancement. Thus, imagining should create regulatory fitand lead to greater intentions to reduce texting and driving amongpromotion-focused consumers.

H1. The elaborative approach of imagining is more effective thanconsidering at reducing intentions to text and drive for promotion-focused individuals.

Meanwhile, prevention-focused individuals are sensitive to loss andtend to monitor their immediate environment for direct threats. Thus,they tend to focus more on the present and make vigilant decisionsbased upon careful consideration and systematic reasoning (Avnet &Higgins, 2006; Cornwell & Higgins, 2016; Friedman & Förster, 2005;

K. Naletelich, et al. Journal of Business Research 100 (2019) 61–72

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Pham & Avnet, 2009). These characteristics align well with considering(versus imagining) as considering narrows attentional focus to the im-mediate environment and prompts a deliberative and effortful point-by-point comparison of situational details (Foley et al., 2006; Sweller &Sweller, 2006). Thus, considering (versus imagining) allows those witha prevention focus to better see immediate risks of texting and drivingand the potential for loss, keeping these individuals vigilant againstpresent threats against the status quo emerging from texting anddriving. Thus, considering should create regulatory fit and lead togreater intentions to reduce texting and driving among prevention-fo-cused consumers.

H2. The elaborative approach of considering is more effective thanimagining in reducing intentions to text and drive for prevention-focused individuals.

2.3. The effect of negative framing on regulatory fit with elaborativeapproach

Given that regulatory fit can be affected by context (Bullard &Penner, 2017), the regulatory fit effects described above may nottransfer to situations in which advertisements contain explicit negativeprimes. We argue that when negative outcomes of texting and drivingare emphasized (which is common in such ads), the imagination maywork differently. Namely, promotion-focused individuals exhibit natu-rally positive frames of mind (Brockner & Higgins, 2001), resulting inpromotion-focused consumers' being motivated by positive situationsthat signal approach and advancement (Higgins, 1998; Lockwood,Jordan, & Kunda, 2002; Van-Dijk & Kluger, 2004). However, situationsthat specifically emphasize negative thinking are incongruent with thecharacteristic of a promotion-focused mindset.

H3A. Emphasis on negative outcomes will moderate the effect ofimagining for promotion-focused individuals, such that there will beno difference in intentions to decrease texting and driving betweenelaborative approaches.

Such incongruent regulatory framing decreases motivation becausethe outcomes of processing such information do not match the corre-sponding end goals (Cesario et al., 2008; Higgins, 1997; Higgins, 1998;Higgins & Cornwell, 2016; Kim, 2006). For promotion-focused in-dividuals, the end goal is advancement. However, when a texting anddriving ad is specifically negative in its framing, emphasizing negativeoutcomes of texting and driving through either elaborative approach(imagining or considering) does not readily allow promotion-focusedindividuals to move beyond the status quo. In these cases, promotion-focused consumers are faced with a situation in which they are unableto efficiently act on negatively framed information. This creates reg-ulatory incongruence, which in turn lowers motivation to reduce in-tentions to text and drive. However, prevention-focused individuals areconcerned with maintaining the current status quo and fear regressingfrom a state of 0 to −1. As such, negatively framed information alignswith the natural mindset of a prevention focus, posing no threat toefficient information processing for these individuals.

H3B. Emphasis on negative outcomes will moderate the effect ofconsidering for prevention-focused individuals, such that consideringwill remain more effective than imagining.

2.4. The mediation of negative emotional intensity

As observation would confirm, advertisements pertaining to textingand driving often use negative emotions to persuade consumers.Negative emotions are particularly important when trying to dissuadeharmful behavior because these emotions indicate an undesirable stateand signal to stop a behavior. On the other hand, positive emotionsencourage approach-oriented behavior and signal continuance of said

behavior (Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000; Frijda,1994; Carver & Scheier, 1990; Clore, 1994). Within a texting anddriving context, negative emotions are important but can differ in theireffectiveness as a function of regulatory focus (Higgins & Cornwell,2016; Strauman et al., 2015). Compared to promotion-focused in-dividuals, prevention-focused individuals are more attuned to negativeemotions because of their sensitivity to safety and risk (Brockner &Higgins, 2001; Carver, 2004, 2006). Indeed, the identification of ne-gative emotions provides a signal of avoidance for prevention-focusedindividuals to avoid falling below the status quo (Friedman & Förster,2008).

On the other hand, promotion-focused individuals are less con-cerned with negative signals (such as negative emotions) and are moreconcerned with positive signals, which indicate approach and the po-tential for advancing beyond the status quo (Brockner & Higgins, 2001;Higgins, 1998; Lockwood et al., 2002; Van-Dijk & Kluger, 2004). Inscenarios with messaging aimed at triggering negative emotionswithout any additional information processing prompts, promotion-focused consumers may be less likely to respond desirably due to theirinclination to maintain a positive, achievement-oriented mindset(Brockner & Higgins, 2001; Higgins, 1998; Lockwood et al., 2002; Van-Dijk & Kluger, 2004). However, aligning regulatory focus with thecorrect elaborative approach can focus attention to strengthen negativeemotional intensity. As previously explained, imagining helps promo-tion-focused individuals to broaden their attentional focus, which fits apromotion-focused mindset and should direct attention toward theoverarching implications of texting and driving. In contrast, consideringas a more deliberative, point-by-point, analytical process more closelyfits a prevention-focused mindset. Both of these alignments should di-rect attention toward relevant details of texting and driving andstrengthen the intensity of negative emotions.

In support, scholars have shown that emotional intensity is a vitalcomponent of attitude and behavior formation, especially when theintensity is more negative in nature (Cunningham, Raye, & Johnson,2004; Russell, 2003). Therefore, negative emotional intensity shouldmediate the relationship between the interaction of regulatory focusand elaborative approach on reduced texting and driving. This mayseem counterintuitive given that promotion-focused individuals preferto experience positive affect (Van-Dijk & Kluger, 2004). However, ne-gative emotional intensity should further prompt promotion-focusedindividuals to reduce their intentions to text and drive in order to ad-vance out of the negative – and back into a more positive – state.

H4. Negative emotional intensity mediates the effect of the interactionof regulatory focus and elaborative approaches on intentions to reducetexting and driving.

2.5. Cognitive load and its effect on negative framing

Finally, an important consideration when evaluating texting anddriving intentions is cognitive load. Consumers are likely to experiencecognitive constraints across various driving situations, which makescognitive load a potentially important influence on the effectiveness oftexting and driving ads. For example, commuting in high density trafficareas (i.e., metropolitan cities), driving in hazardous conditions (i.e.,storms and/or road construction), or contending with distractions inthe vehicle (i.e., children or pets) can all induce cognitive load in adriver, which can change the influence of texting and driving ads on thedriver. Thus, we argue that cognitive load may moderate the influenceof negative framing, leading to different effects of imagining and con-sidering for promotion- and prevention-focused individuals.

Cognitive load influences the way individuals selectively processinformation that is (in)consistent with one's beliefs and motivations,including regulatory focus and negative information (i.e., Yoon, Sarial-Abi, & Gürhan-Canli, 2011). Specifically, prevention-focused in-dividuals tend to respond better to negative information and can be


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made even more responsive to such information under high cognitiveload, whereas promotion-focused individuals tend to prefer positiveinformation but may be more influenced by negative information whenunder low cognitive load (Cunningham et al., 2004; Pham & Higgins,2005; Yoon et al., 2011). Scholars have demonstrated that those with apromotion focus place greater reliance on negative information whencognitive load is low, as inconsistent information is difficult to processand requires greater cognitive resources (Yzerbyt & Demoulin, 2010).

Further, consumers may be motivated to focus on this inconsistentinformation in order to appear unbiased and to resolve the un-comfortable state emerging from processing such information (Kunda,1990; Hamilton & Sherman, 1994). Thus, when cognitive load is low,imagining and considering are likely to be comparably effectivemethods of processing negative outcomes of texting and driving forthose with a promotion focus because both approaches present an op-portunity to resolve an inconsistent state. However, when under highcognitive load, promotion-focused consumers are likely to feel un-comfortable when presented with inconsistent negative information buthave limited cognitive resources available to resolve this inconsistency.In this situation, imagining is likely to better resolve this inconsistentstate as it offers a means to more efficiently process information (Spears& Yazdanparast, 2014), requiring fewer cognitive resources than con-sidering and also naturally fits a promotion-focused mindset. Thisshould result in greater intentions to reduce texting and driving.

Second, because prevention-focused individuals naturally prefernegative information (Cunningham et al., 2004; Pham & Higgins,2005), they will not experience an inconsistent state. Thus, when underlow cognitive load, considering is likely to be more effective thanimagining (Spears & Yazdanparast, 2014) in reducing texting anddriving intentions because considering better fits a prevention-focusedmindset. Importantly, while considering requires more processing re-sources, a low-load state leaves these resources free, which does nothamper the effectiveness of considering for prevention-focused in-dividuals. In contrast, when under high cognitive load, prevention-fo-cused individuals are even more motivated by negative information(Yoon et al., 2011) but lack the necessary cognitive resources to engagein considering. This eliminates the advantage of considering, makingconsidering comparably effective to imagining in reducing texting anddriving intentions.

H5.When under low cognitive load, prevention-focused individuals willhave a greater reduction in texting and driving intentions when askedto consider (versus imagine). Meanwhile, when under low cognitiveload, imagining and considering will be comparably effective forpromotion-focused individuals.

H6. When under high cognitive load, promotion-focused individualswill have a greater reduction in texting and driving intentions whenasked to imagine (versus consider). Meanwhile, when under highcognitive load, imagining and considering will be comparablyeffective for prevention-focused individuals.

3. Study 1

Study 1 tests the proposal that elaborative approaches can be aneffective way of reducing intentions to text and drive if matched to thecorrect motivational mindsets and also tests negative emotional in-tensity as the mediating process.

3.1. Method

3.1.1. Participants and design209 participants were recruited from Amazon Mechanical Turk

(MTurk) in exchange for compensation. The sample consisted of 114males and 92 females. Study 1 used a continuous (regulatory focus) by2 (elaborative approach: imagine vs. consider) between-subjects design.

3.1.2. ProcedureParticipants first indicated their texting and driving frequency by

answering two questions: “On average, how often do you text and driveper week?” and “When you do text and drive, on average, how manytexts do you send?” Next, chronic regulatory focus was measured alonga seven-point Likert-type scale with 11 questions adopted from Higginset al. (2001), six measuring promotion focus (∝=0.74) and five forprevention focus (∝=0.83). All participants were then shown an ad-vertisement including four statistics on the dangers of texting anddriving. After seeing the advertisement, individuals were then ran-domly assigned to either the imagine or consider condition. In theimagine condition, the following instructions were presented:

Now, imagine the following scenario: After completing this survey youdecide to go to the grocery store and receive a text on the way. Use yourimagination to form a picture of what you will do based upon your ty-pical behavior with texting and driving. Please push yourself to imaginethis scenario such as how you look in your vehicle, what kind of phoneyou have, who would be texting you and what route you would take.Unleash your imagination! Then, list all of your thoughts, feelings andimpressions about the scenario that you have imagined.

In contrast, participants in the consider condition read the fol-lowing:

Now, consider the following scenario: After completing this survey youdecide to go to the grocery store and receive a text on the way. Basedupon the information provided in the advertisement and your typicaltexting and driving behavior, think about how your behavior compares tothat of the advertisement. Consider such things as how often you text anddrive, if someone would text you while driving and what you would do.List all of your thoughts, feelings and impressions about the scenario thatyou have considered.

Participants then wrote down their thoughts, feelings, and im-pressions.

Respondents were asked to indicate their agreement with howstrongly they felt negative emotions with seven-point items adaptedfrom the longer negative dimension of the PANAS scale (i.e., anxious,worried, sad, despair, fearful, shame, guilt, and remorse; ∝=0.82;Watson, Clark, & Tellegen, 1988). Respondents also rated their attitudetoward the ad along a five-item, seven-point bipolar scale (Spears &Singh, 2004: unappealing/appealing, bad/good, unpleasant/pleasant,unfavorable/favorable, and unlikeable/likeable; ∝=0.94) and in-dicated their level of involvement pertaining to the content depicted inthe ad (i.e., distracted driving) along a seven-point Likert scale(Laczniak & Muehling, 1993; relevant to my needs, important to me,meaningful to me, worth paying attention to, and interesting to me;∝=0.93).

Finally, to measure reduction in texting and driving intentions,subjects were asked two final questions: “Next week, how many timesdo you think you'll text and drive?” and “Next week, how many texts doyou think you'll send while driving?” The initial texting and drivingnumbers along with the responses from these final two questions weremultiplied together and used to calculate change in texting and drivingintentions using the following equation:

Texting and driving frequency Texting and driving frequency

Texting and driving frequency

/Before After

Before

Lastly, respondents indicated their age, gender, and mood (1 –strongly disagree to 7 – strongly agree; happy, good, unhappy (R), andbad (R); ∝=0.92) and also indicated if they had ever seen the adver-tisement before.


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3.2. Results

3.2.1. Manipulation checkConsistent with the method of Spears and Yazdanparast (2014),

during the procedure, participants were asked two questions along aseven-point Likert scale: “Please indicate the extent to which you usedyour imagination in the prior scenario to form a picture of what youwill do based upon your typical texting and driving behavior” and“Please indicate the extent to which you considered the followingscenario based upon the details presented and your typical texting anddriving behavior.” Those in the imagine condition used their imagina-tion to a greater extent than those who considered (F (1, 207)= 24.65;p < 0.001; MImagine= 5.93, MConsider= 5.09), while those in the con-sider condition indicated that they considered the scenario more thanthose who imagined (F (1, 207)= 10.53; p < 0.001; MImagine= 5.31,MConsider= 5.80).

3.2.2. Main effectsThe direct effect of elaborative approach and regulatory focus was

next assessed. First, an ANOVA revealed that elaborative approach (F(1, 207)= 0.2; p > 0.10) was a non-significant predictor of intentionsto decrease texting and driving. Next, each participant's overall reg-ulatory focus score was then calculated by subtracting the preventionfocus score from the promotion focus score. A regression with theregulatory focus score entered as a continuous variable and intentionsto reduce texting and driving as the dependent variables also showed anon-significant effect (b=0.01, t=0.70, p > 0.10).

3.2.3. InteractionPROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped

samples) tested the interaction between regulatory focus and elabora-tive approach. More specifically, a spotlight analysis was employed toassess regulatory focus at± one SD from the mean, with higher num-bers indicating a promotion focus and lower numbers indicating aprevention focus. The interaction was significant (effect= 0.13;CI= 0.05 to 0.20; Fig. 1). Promotion-focused consumers had sig-nificantly greater intentions to reduce texting and driving in the ima-gine (M=81%) than in the consider condition (M=61%; ef-fect= 0.20; CI= 0.05 to 0.35). In contrast, those with a preventionfocus exhibited greater intentions to reduce texting and driving in theconsider condition (M=78%) as opposed to the imagine condition(M=62%; effect=−0.16; CI=−0.30 to −0.01). There was no sig-nificant difference between the two conditions at the mean value ofregulatory focus (MImagine= 72% vs. MConsider = 70%; effect= 0.02;CI=−0.08 to 0.13). Gender, age, mood, and attitude toward the adwere all non-significant covariates (p > 0.10). However, level of in-volvement was a significant covariate (b=0.08, t=3.43; p < 0.01).

3.2.4. Moderated mediationThe mediation analysis proceeded in two stages. In the first stage,

PROCESS Model 8 (Hayes, 2018; 95% CI; 5000 bootstrapped samples)assessed the moderated mediation of negative emotional intensity withregulatory focus as the independent variable, imagine/consider as themoderator, and intentions to reduce texting and driving as the depen-dent variable. The results confirm moderated mediation (effect= 0.03;CI= 0.02 to 0.07). Specifically, the interaction of regulatory focus andelaborative approaches on negative emotional intensity was significant(effect= 0.51; CI= 0.21 to 0.80), and negative emotional intensitysignificantly and positively predicted intentions to reduce texting anddriving (effect= 0.07; CI= 0.03 to 0.10).

In the second stage, PROCESS Model 1 probed into the interaction ofregulatory focus and elaborative approach on negative emotional in-tensity to better understand the nature of the interaction on the med-iator. The interaction was significant (effect= 0.51; CI= 0.21 to 0.80).For promotion-focused individuals, imagining resulted in a significantlyhigher negative emotional response than considering (effect= 0.61;CI= 0.03 to 1.19; MImagine= 4.67 versus MConsider= 4.06). In contrast,for prevention-focused individuals, considering resulted in a sig-nificantly higher negative emotional response than imagining (ef-fect=−0.80; MImagine= 3.89 versus MConsider = 4.70; CI=−1.39 to−0.22).

3.3. Alternative explanation

While the above results confirm negative emotional intensity as theunderlying mechanism, it is possible that depth of processing could alsobe a mediator (i.e., Jain & Maheswaran, 2000). To rule out this alter-native explanation, respondents' open-ended comments in response tothe prompt were coded by two judges who were blind to the purpose ofthe study (LaTour & LaTour, 2009; Lee & Lee, 2011). The number ofindividual thoughts per respondent represented depth of processing.For example, one respondent wrote, “My grocery store is very close andI generally have the self-control to not check texts while I drive. Also, ifI didn't have plans with anyone it can wait. The times I do look, I'm ableto display it on my car's display or have it read to me. I generally feelI'm okay to check but I'm not very good at texting at the same time asdriving.” This was unanimously coded by both judges as consisting ofsix separate thoughts. Interrater reliability was acceptable (∝=0.94).Next, PROCESS Model 8 (Hayes, 2018; 95% CI and 5000 bootstrappedsamples) assessed depth of processing as an alternative mediator, withnon-significant results (effect=−0.0002; CI=−0.01 to 0.01).

3.4. Discussion

Study 1 confirmed that when asked to make judgments based uponone's typical texting and driving actions (i.e., neutral context), promo-tion-focused individuals show greater intentions to decrease texting anddriving when asked to imagine (H1), whereas prevention-focused in-dividuals show greater intentions when asked to consider (H2). Further,negative emotional intensity is the underlying mechanism driving theintention to decrease texting and driving (H4), and depth of processingwas ruled out as a potential alternative explanation.

4. Study 2

Study 2 extends study 1 by testing the moderation of negativeoutcome-based elaboration when not accounting for cognitive load. Withnegative framing, there should be no difference in intentions to de-crease texting and driving between imagining and considering forpromotion-focused individuals (H3A). However, considering should bemore effective for prevention-focused individuals (H3B). Study 2 alsoprovides additional evidence for the mediating role of negative emo-tional intensity.

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Imagine Consider

Fig. 1. Interaction of elaborative approach (imagine vs consider) and reg-ulatory focus on reduction in texting and driving behavior.


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4.1. Methods

4.1.1. Participants and design244 participants were recruited from MTurk in exchange for

monetary compensation. However, 26 participants indicated that theyhad taken a similar survey before and thus were removed, resulting in afinal sample of 218. The sample consisted of 128 males and 90 females.Study 2 used a continuous (regulatory focus) by 2 (elaborative ap-proach with a negative frame: imagine vs. consider) between-subjectsdesign.

4.1.2. ProcedureSimilar to study 1, participants first indicated their texting and

driving frequency with the same two items and then answered ques-tions pertaining to their regulatory focus (promotion ∝=0.75, pre-vention ∝=0.83). Next, individuals were presented with the sameadvertisement about texting and driving used in study 1. After seeingthe advertisement, individuals were then randomly assigned to eitheran imagine or consider condition based on negative outcomes and againwrote down thoughts, feelings, and impressions. Specifically, the ima-gine and consider conditions were worded the same as in the priorstudy, except that participants were asked to list a negative potentialoutcome of texting and driving.

Finally, participants answered the same two questions used in study1 to capture intentions to decrease texting and driving. Lastly, the in-tensity of negative emotions was measured (∝=0.96) as well asgender, age, attitude toward the advertisement (∝=0.95), level ofinvolvement (∝=0.93),and mood (∝=0.93) as potential covariates.

4.2. Results

4.2.1. Manipulation checkFollowing the same check procedure from study 1, the primes for

imagining (F (1, 217)= 15.21; p < 0.01; MImagine= 6.15,MConsider= 5.59) and considering (F (1, 217)= 5.20; p= 0.02;MImagine= 5.68, MConsider= 6.01) worked as intended.

4.2.2. Main effectsANOVA revealed that elaborative approach (F (1, 217)= 1.44;

p > 0.10) was a non-significant predictor of intentions to decreasetexting and driving, and a regression with regulatory focus as the in-dependent variable and texting and driving percent change as the de-pendent variable also showed a non-significant effect (b=−0.02,t=−1.22, p > 0.10).


samples) was used to test the interaction between regulatory focus andelaborative approaches on negative outcomes using a similar procedureto that of study 1 to distinguish levels of regulatory focus (spotlightanalysis at± one SD above/below the mean). As predicted, the inter-action was significant (effect= 0.08; CI= 0.004 to 0.15; Fig. 2). Morespecifically, prevention-focused individuals displayed the greatest in-tentions to decrease texting and driving (effect=−0.18; CI=−0.32to CI=−0.03) when asked to consider (M=84%) versus imagine(M=66%) a negative consequence of texting and driving. In contrast,for a promotion focus, there was no significant difference (effect 0.05;CI=−0.10 to CI= 0.19) between imagine (M=70%) and consider(M=66%). There was also no significant difference between the twoconditions at the mean value of regulatory focus (MImagine= 72% vs.MConsider= 70%; effect=−0.07; CI=−0.08 to 0.13) Age, attitudetoward the advertisement, mood, and level of involvement were non-significant covariates (p > 0.10). However, gender was a significantcovariate (b=0.14, t=2.66, p < 0.01).

4.2.4. Moderated mediationFollowing the same method as study 1, Process Model 8 (Hayes,

2018; 95% CI and 5000 bootstrapped samples) assessed the mediationof negative emotional intensity with regulatory focus as the in-dependent variable, imagine/consider as the moderator, and intentionsto decrease texting and driving as the dependent variable. The resultsconfirmed moderated mediation (effect= 0.04; CI= 0.008 to 0.07).Specifically, the interaction of regulatory focus and elaborative ap-proach on negative emotional intensity was significant (effect= 0.44;CI= 0.11 to 0.78), and negative emotional intensity significantly andpositively predicted intentions to reduce texting and driving (ef-fect= 0.09; CI= 0.06 to 0.11).

PROCESS Model 1 then probed the interaction of regulatory focusand elaborative approach on negative emotional intensity. The inter-action was significant (effect= 0.45; CI= 0.11 to 0.78). For preven-tion-focused individuals, considering a negative outcome resulted in asignificantly higher negative emotional response than imagining (ef-fect=−0.67; CI=−1.34 to −0.006; MConsider= 4.15 versusMImagine= 3.48). In contrast, there was no significant difference be-tween imagining and considering a negative outcome of texting anddriving for promotion-focused individuals (effect= 0.60 CI=−0.07 to1.26; MConsider= 3.50 versus MImagine= 4.10). There was also no dif-ference at the mean value of regulatory focus (effect=−0.04;CI=−0.51 to 0.43; MConsider = 3.83 versus MImagine= 3.79).


To further rule out depth of processing as an alternative explana-tion, separate thought listings were once again coded by two in-dependent judges following the same procedure as study 1. Interraterreliability was acceptable (∝=0.95). PROCESS Model 8 (Hayes, 2018;95% CI and 5000 bootstrapped samples) assessed the mediation ofdepth of processing with regulatory focus as the independent variable,imagine/consider as the moderator, and intentions to decrease textingand driving as the dependent variable. The moderated mediation resultswere not significant, ruling out depth of processing as an alternativeexplanation (effect= 0.008; CI=−0.01 to 0.03).

4.4. Discussion

Study 2 builds upon the findings of study 1 by demonstrating therole of negative-based imagining/considering and regulatory focus onintentions to reduce texting and driving. Specifically, without accountingfor cognitive load, prevention-focused individuals exhibit greater inten-tions to reduce texting and driving when prompted to consider (versusimagine) a negative outcome of texting and driving. However, negativebased elaboration shuts down the effectiveness of imagining for pro-motion-focused individuals, such that there was no significant differ-ence and intentions to reduce texting and driving between imagining

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Fig. 2. Interaction of negative focused elaborative approach (imagine vs con-sider) and regulatory focus on reduction in texting and driving behavior.


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and considering. Overall, study 2 demonstrates that when negativeoutcomes are emphasized, there is no difference in intentions to de-crease texting and driving between elaborative approaches for thosewith a promotion focus (H3A). On the other hand, prevention-focusedindividuals revert to their natural inclination to consider, which re-duces intentions to text and drive (H3B). Negative emotional intensityonce again fully mediated these findings (H4), with depth of processingruled out as an alternative explanation.

5. Study 3A

The purpose of study 3A/B is to build upon the findings of study 2by testing a boundary condition common to driving scenarios: cognitiveload. As the first of two studies examining the moderating influence ofcognitive load, study 3A tests the prediction of H5 that under conditionsof low cognitive load, prevention-focused individuals will have greaterintentions to reduce texting and driving when asked to consider (versusimagine), while imagining and considering should be comparably ef-fective for promotion-focused individuals. Study 3A also provides ad-ditional evidence for the mediating role of negative emotional intensity(H4).

5.1. Methods

5.1.1. Participants and design230 participants were recruited from MTurk in exchange for

monetary compensation. However, 21 individuals indicated that theyhave taken a similar survey and were thus removed, resulting in a finalsample of 209. The sample consisted of 86 males and 123 females.Study 3A used a continuous (regulatory focus) by 2 (elaboration onnegative outcomes: imagine vs consider) between-subjects design.

5.1.2. ProcedureLike the prior studies, participants first indicated their texting and

driving frequency with the same two items and then answered ques-tions pertaining to their regulatory focus (promotion ∝=0.74, pre-vention ∝=0.83). To prime low cognitive load, individuals were nextasked to remember a two-digit number/letter sequence (as opposed toan eight-digit sequence in study 3B) that they would later be asked torecall (Shiv & Huber, 2000). After the load task, participants followedthe same procedure as study 2. Specifically, all saw the same adver-tisement, were randomly assigned to imagine or consider, and thenwere asked to list a negative outcome of texting and driving. Lastly,respondents indicated their texting and driving behavior change in-tentions, emotional intensity (∝=0.96), mood (∝=0.91), gender,age, attitude toward the ad (∝=0.94), and level of involvement(∝=0.91) with the same items from prior studies. Additionally, sub-jects indicated ease of processing with three seven-point Likert-typeitems (“In the previous scenarios, when I was writing about a negativeoutcome that could occur from texting and driving, the informationwas: difficult/easy to process; difficult/ease to comprehend; difficult/easy to understand;” ∝=0.95).

5.2. Results

5.2.1. Manipulation checksThose in the imagine condition used their imagination to a greater

extent than those in the consider condition (F (1, 208)= 116.93;p < 0.01; MImagine= 6.20, MConsider= 4.09). In contrast, those in theconsider condition indicated that they considered the scenario morethan those in the imagine condition (F (1, 208)= 7.07; p < 0.01;MImagine= 5.81, MConsider= 6.23). The cognitive load task was alsoeffective. Those who received the low cognitive load task in study 3Aindicated they had less difficulty concentrating (i.e., “How difficult wasit to concentrate in the previous scenario (listing a negative outcome oftexting and driving)?;” “How difficult was it to remember the number/

letter sequence?;” “How distracted did you feel in the previous sce-nario?” ∝=0.75) than those who received the high cognitive load(∝=0.70) task in study 3B (F (1, 424)= 352.68; p < 0.01; MLow

load= 1.82, MHigh load= 4.05).

5.2.2. Main effectsAn ANOVA revealed that imagining versus considering (F (1,

208)= 0.07; p > 0.10) was a non-significant predictor of texting anddriving behavior change intentions. Additionally, a regression withregulatory focus as the independent variable and intentions to decreasetexting and driving as the dependent variable also showed a non-sig-nificant effect (b=0.02, t=1.40, p > 0.10).


samples) employed a spotlight analysis to assess regulatory focusat± one SD above/below the mean, similar to studies 1 and 2. Aspredicted, the interaction was significant (effect= 0.08; CI= 0.02 to0.14; Fig. 3). More specifically, prevention-focused individuals dis-played the greatest intentions to reduce texting and driving (ef-fect=−0.15; CI=−0.27 to CI=−0.02) when asked to consider(M=84%) versus imagine (M=69%) a negative consequence oftexting and driving. In contrast, for a promotion focus, there was nosignificant difference (effect= 0.08; CI=−0.05 to CI= 0.21) betweenimagine (M=88%) and consider (M=80%). There was also no sig-nificant difference between the two conditions at the mean value ofregulatory focus (MImagine= 78% vs. MConsider = 82%; effect=−0.03;CI=−0.12 to 0.06) Age, attitude toward the ad, gender, and level ofinvolvement were non-significant covariates (p > 0.10). However,mood was a significant covariate (b=0.31, t=2.23, p=0.03).


PROCESS Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped sam-ples) assessed the mediation of negative emotional intensity with reg-ulatory focus as the independent variable, elaborative approach as themoderator, and intention to reduce texting and driving as the depen-dent variable. The results confirmed moderated mediation (ef-fect= 0.01; CI= 0.005 to 0.04). Specifically, the interaction of reg-ulatory focus and elaborative approaches on negative emotionalintensity was significant (effect= 0.33; CI= 0.02 to 0.64), and nega-tive emotional intensity significantly and positively predicted inten-tions to reduce texting and driving (effect= 0.04; CI= 0.01 to 0.07).

PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrappedsamples) probed into the interaction of regulatory focus and elaborativeapproach on negative emotional intensity to better understand thenature of the interaction on the mediator. The interaction was sig-nificant (effect= 0.33; CI= 0.02 to 0.64). For prevention-focused

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Fig. 3. Interaction of negative focused elaborative approach (imagine vs con-sider) and regulatory focus on reduction in texting and driving behavior whenunder a low cognitive load.


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individuals, considering a negative outcome resulted in a significantlyhigher negative emotional response than imagining (effect=−0.75;CI=−1.37 to −0.13; MConsider= 4.61 versus MImagine= 3.86). Incontrast, there was no significant difference between imagining andconsidering a negative outcome of texting and driving for promotion-focused individuals (effect= 0.18; CI=−0.44 to 0.81;MConsider= 4.25 versus MImagine= 4.43). There was also no differenceat the mean value of regulatory focus (effect=−0.28; CI=−0.72 to0.15; MConsider= 4.61 versus MImagine= 3.86).


Using the same method as the prior studies, depth of processing wasonce again ruled out as an alternative explanation (interrater reliability∝=0.94; effect= 0.004; CI=−0.002 to 0.01). Ease of processing wasalso ruled out as an alternative explanation using Process Model 8(Hayes, 2018; 95% CI and 5000 bootstrapped samples), with regulatoryfocus as the independent variable, elaborative approach as the mod-erator, ease of processing as the mediator, and intentions to reducetexting and driving as the dependent variable. The moderated media-tion results were not significant, ruling out ease of processing as analternative explanation (effect= 0.003; CI=−0.01 to 0.003).

5.4. Discussion

Study 3A shows that when asked to elaborate on negative outcomesin conditions of low cognitive load, prevention-focused individualshave a significantly greater intentions to reduce texting and drivingwhen asked to consider (versus imagine). However, promotion-focusedindividuals demonstrate no significant difference in intentions to re-duce texting and driving between the two elaborative approaches.Negative emotional intensity is once again shown to fully mediate thisprocess, with depth of processing and ease of processing both ruled outas alternative explanations.

6. Study 3B

Study 3B seeks to build upon study 3A by testing the prediction ofH6 that under conditions of high cognitive load, promotion-focusedindividuals will have greater intentions to decrease texting and drivingwhen asked to imagine (versus consider). Meanwhile, for a preventionfocus, imagining and considering should be comparably effective. Study3B also provides additional evidence for the mediating role of negativeemotional intensity.

6.1. Methods

6.1.1. Participants and design250 participants were recruited from Amazon Mechanical Turk in

exchange for monetary compensation. However, 34 individuals in-dicated that they have taken a similar survey and were thus removedresulting in a final sample of 216. The sample consisted of 103 malesand 113 females. Study 3B used a continuous (regulatory focus) by 2(elaboration on negative outcomes: imagine vs consider) between-subjects design with a high cognitive load task.

6.1.2. ProcedureThe same procedure and variables from study 3A were used in study

3B. Alphas ranged from 0.70 to 0.96. The only difference is that re-spondents were instructed to memorize an eight-digit number/lettersequence as opposed to a two-digit sequence in the low cognition study(3A).

6.2. Results

6.2.1. Manipulation checkThose in the imagine condition used their imagination to a greater

extent than those in the consider condition (F (1, 215)= 101.92;p < 0.01; MImagine= 6.13, MConsider = 4.24). In contrast, those in theconsider condition indicated that they considered the scenario morethan those in the imagine condition (F (1, 215)= 15.09; p < 0.01;MImagine= 5.68, MConsider = 6.26). As stated in study 3A, those whoreceived the high cognitive load task in study 3B indicated they hadmore difficulty concentrating than those who received the low cogni-tive load task in study 3A (F (1, 424)= 352.68; p < 0.01;, MHigh

load= 4.05; MLow load= 1.82).

6.2.2. Main effectsThe direct effect of imagine/consider and regulatory focus was next

assessed. First, an ANOVA revealed that imagine/consider (F (1,215)= 0.61; p > 0.10) was a non-significant predictor of texting anddriving behavior change intentions, and a regression with regulatoryfocus as the independent variable and intentions to reduce texting anddriving as the dependent variable also showed a non-significant effect(b=0.00, t=−0.02, p > 0.10).


samples) used a spotlight analysis to assess regulatory focus at± oneSD above/below the mean, with higher numbers indicating a promotionfocus and lower numbers indicating a prevention focus. As predicted,the interaction was significant (effect= 0.08; CI= 0.007 to 0.15;Fig. 4). More specifically, promotion-focused individuals displayedgreater intentions to decrease texting and driving (effect= 0.13;CI= 0.008 to CI= 0.25) when asked to imagine (M=79%) versusconsider (M=66%) a negative outcome of texting and driving. Incontrast, for a prevention focus, there was no significant difference(effect=−0.06; CI=−0.19 to CI= 0.06) between imagine(M=76%) and consider (M=82%). There was also no significantdifferent between the two conditions at the mean value of regulatoryfocus (MImagine= 77% vs. MConsider= 74%; effect= 0.03; CI=−0.05to 0.12) Age, attitude toward the advertisement, and gender were non-significant covariates (p > 0.10). However, level of involvement(b=0.11, t=5.24, p < 0.01) and mood (b=0.46, t=3.58,p < 0.01) were significant covariates.


PROCESS Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped sam-ples) assessed the mediation of negative emotional intensity with reg-ulatory focus as the independent variable, elaborative approach as the

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Fig. 4. Interaction of negative focused elaborative approach (imagine vs con-sider) and regulatory focus on reduction in texting and driving behavior whenunder a high cognitive load.


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moderator, and intentions to reduce texting and driving as the depen-dent variable. The results confirmed moderated mediation (ef-fect= 0.03; CI= 0.006 to 0.07). Specifically, the interaction of reg-ulatory focus and elaborative approaches on negative emotionalintensity was significant (effect= 0.45; CI= 0.08 to 0.83), and nega-tive emotional intensity significantly and positively predicted inten-tions to reduce texting and driving (effect= 0.07; CI= 0.05 to 0.10).

In the second stage, PROCESS Model 1 (Hayes, 2018; 95% CI and5000 bootstrapped samples) probed into the interaction of regulatoryfocus and elaborative approach on negative emotional intensity. Theinteraction was significant (effect= 0.45; CI= 0.08 to 0.83). For pro-motion-focused individuals, imagining a negative outcome resulted in asignificantly higher negative emotional response than considering (ef-fect= 0.90; CI= 0.25 to 1.55; MConsider = 3.16 versusMImagine= 4.06). In contrast, there was no significant difference be-tween imagining and considering a negative outcome of texting anddriving for prevention-focused individuals (effect=−0.21;CI=−0.86 to 0.44; MConsider= 3.86 versus MImagine= 3.66). Therewas also no difference at the mean value of regulatory focus (ef-fect= 0.35; CI=−0.11 to 0.81; MConsider = 3.51 versusMImagine= 3.86).


Using the same method as the prior studies, depth of processing wasonce again ruled out as an alternative explanation (interrater reliability∝=0.96; effect=−0.001; CI=−0.01 to 0.003) in addition to ease ofprocessing (effect=−0.003; CI=−0.02 to 0.002).

6.4. Discussion

Study 3B shows that when asked to elaborate on negative outcomesin conditions of high cognitive load, promotion-focused individualshave a significantly greater intentions to reduce texting and drivingwhen asked to imagine (versus consider). However, prevention-focusedindividuals demonstrate no significant difference in intentions to re-duce texting and driving between the two elaborative approaches.Negative emotional intensity is once again shown to fully mediate thisprocess, with depth of processing and ease of processing both ruled outas alternative explanations.

7. General discussion

Texting while driving is a growing societal concern (Atchley et al.,2011; Caird et al., 2014; National Safety Council, 2015; Tractinskyet al., 2013) yet has received minimal attention within marketing. Thisis especially true as it pertains to consumer-centric factors and the waysin which consumers process information when thinking about textingand driving. Thus, this paper combines regulatory focus theory withtwo elaborative approaches (imagining versus considering) to demon-strate across four studies the optimal conditions for decreasing inten-tions to text and drive.

Study 1 demonstrates that when consumers are not prompted toimagine negative outcomes and when cognitive load is not a con-sideration, promotion-focused consumers demonstrate greater inten-tions to reduce texting and driving behavior when shown an adver-tisement and asked to imagine themselves in the scenario. Meanwhile,prevention consumers report greater intentions to decrease texting anddriving behavior when asked to consider the scenario. Study 2 extendsthese findings by revealing the effects of negative-based elaborationwithout considering cognitive load. Namely, when promotion-focusedindividuals are asked to consider negative outcomes, intentions to de-crease texting and driving do not significantly differ between imaginingand considering, whereas prevention-focused individuals' responses toconsidering and imagining are not affected by negative-based ela-boration.

Study 3A/B tests the moderating role of cognitive load on negative-based elaboration. Findings from study 3A demonstrate that whenunder low cognitive load, imagining and considering are comparablyeffective for promotion-focused individuals. On the other hand, pre-vention-focused individuals display greater intentions to reduce textingand driving when prompted to consider negative outcomes. In contrast,study 3B demonstrates that when under high cognitive load, imaginingand considering are comparably effective for a prevention focus.However, promotion-focused individuals exhibit greater intentions toreduce texting and driving when asked to imagine. Further, in eachstudy, negative emotional intensity is shown to mediate results, whileboth depth and ease of processing are ruled out as alternative ex-planations.

7.1. Theoretical implications

First, research shows that matching regulatory focus to the correctapproach creates a fit effect that enhances persuasion and effectiveness(Avnet & Higgins, 2006). This premise has been examined across anarray of contexts, but this paper is the first to examine regulatory fit asit pertains to elaborative approach to reduce texting and driving in-tentions. This is particularly insightful as scholars have called for ad-ditional research that explores how regulatory fit can be achievedthrough various methods of ‘thinking about a message,’ especially as itpertains to health and behavior change (Cesario et al., 2008). We bridgethis gap by demonstrating that when prompted to imagine (consider)one's own texting and driving behavior, promotion-focused (preven-tion-focused) individuals indicate greater intentions to decrease textingand driving. These results are the first to document the relationshipbetween regulatory focus and the two elaborative approaches of ima-gining and considering.

Second, we demonstrate processing obstacles to reducing textingand driving behavior and show how imagining/considering negativeoutcomes aligns with regulatory focus. Namely, promotion-focused in-dividuals tend to think in a positive, broadened manner to advancebeyond the status quo, whereas prevention-focused individuals thinknegatively and narrowly to avoid falling below the status quo. We de-monstrate that imagining negative outcomes suppresses the effects ofimagining for promotion-focused individuals because imagining nega-tive outcomes results in potential loss situations that block advance-ment beyond the status quo. In contrast, for prevention-focused con-sumers, considering negative outcomes aligns with their natural risk-averse states by allowing a narrower focus on negative outcomes oftexting and driving behavior. Thus, for prevention-focused consumers,considering (versus imagining) negative outcomes creates regulatoryfit, which results in greater intentions to decrease texting and driving.In this regard, we demonstrate the conditions under which regulatoryfit results in desirable responses in the case of negatively-focused ela-boration.

Third, the present research provides important theoretical con-tributions concerning the effects of cognitive load as a moderator ofregulatory focus, which have heretofore remained largely unexamined.The exception is Yoon et al. (2011), who demonstrated that under highcognitive load, promotion-focused individuals form stronger responsesto positive information, while prevention-focused individuals respondmore strongly to negative information. Meanwhile, these effects reverseunder low cognitive load, such that prevention-focused (promotion-focused) individuals are more responsive to positive (negative) in-formation. Our findings build upon that prior work by demonstratingelaborative approach as a key moderator of cognitive load and reg-ulatory focus when negative information is present. Namely, we de-monstrate that when under low cognitive load, prevention-focusedconsumers are responsive to negative information when asked to con-sider, while imagining and considering are comparably effective for apromotion-focused consumer. In contrast, when under high cognitiveload, imagining (versus considering) can further boost the effects of


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negative thinking for promotion-focused consumers, while for a pre-vention-focused consumer, both elaborative approaches are compar-ably effective. Overall, concerning regulatory focus, these findings offerimportant theoretical insights as to how elaborative approaches canovercome limitations of cognitive load when negative information ispresent.

Fourth, we demonstrate that negative emotional intensity is amediator driving the effects of regulatory focus and imagining/con-sidering on intentions to decrease texting and driving. These results addto our knowledge in that promotion-focused individuals tend to thinkmore positively, which creates a barrier that, under the right elabora-tive conditions, negative emotional intensity can overcome. In contrast,prevention-focused individuals tend to think less positively, so enhan-cing negative emotional intensity results in greater intentions to de-crease texting and driving. Depth and ease of processing were ruled outas alternative explanations, further underpinning the theoretical insightthat negative emotions can, at times, benefit promotion-focused andprevention-focused individuals.

Lastly, this research adds to the complexity of how we perceive theeffectiveness of fear appeals in advertising. The above studies demon-strate that the success of fear appeals may depend upon four factors: anindividual's regulatory focus, the elaborative approach used, cognitiveload, and negative emotional intensity. Theoretically, this opens adiscussion that fear appeals may need to be examined across a variety offactors that were previously not considered if expected to be influential.For example, we found that using a fear appeal and negative-basedelaboration suppressed the alignment of elaborative approach andregulatory focus when cognitive load was not induced.

7.2. Managerial and societal implications

First, managers in the public service context can utilize the abovefindings in that aligning elaborative approach in congruent ways withregulatory focus can increase the effectiveness of campaigns to reduceintentions to text and drive. This not only boosts success of publicservice announcements but also offers the potential for society to re-duce deaths, injuries, and property damage that can result from textingand driving. For example, if an advertisement asks a consumer toevaluate his/her own texting and driving behavior, promotion-focused(prevention-focused) drivers should be instructed to imagine (con-sider). However, if the advertisement is framed in a way as to promptconsumers to think of negative outcomes, prevention-focused driversshould be instructed to imagine outcomes, whereas promotion-focusedindividuals' resistance to negative thinking suppresses the regulatory fitof imagining, resulting in no difference between the two elaborativeapproaches.

Second, drivers are likely to be under varying degrees of cognitiveload when driving. For example, some drivers may be driving in highdensity traffic areas, through road construction, or have distractionswithin the vehicle such as animals or children. The above findings offerimportant insights for managers and policy makers for dealing withlikely distraction levels. Namely, when a consumer is likely to experi-ence a high cognitive load situation, managers should create and postads that prompt one to imagine (versus consider) negative con-sequences of distracted driving. This strategy should lead to greaterintentions to reduce texting and driving for both promotion-focusedand prevention-focused individuals. Such a strategy would proveespecially important in construction zones, where many cognitive dis-tractions exist, and accidents are a growing concern: a crash occursevery 5.4 seconds within road work zones (U.S. Department ofTransportation, 2015). On the other hand, when a consumer is likely toexperience low cognitive load, such as driving in a rural area, adsshould encourage one to consider (versus imagine) negative outcomesof distracted driving, which is more effective for prevention-focusedindividuals and can also be just as effective as imagining for promotion-focused consumers.

Additionally, the above findings need not necessarily be restrictedto texting and driving. Other social causes such as nutrition and obesity,smoking, alcoholism, sexual health, and conservation may also utilizethe above findings. This is especially true for contexts in which negativeemotional intensity is easily activated or can be believably primed.Therefore, our findings are not limited to one context, and public ser-vice campaigns could match regulatory focus to the appropriate cor-responding elaborative approach across an array of societal concerns.

Further, managers can place or sequence advertisements, pro-gramming, and messages in such a way as to capitalize on regulatoryfocus and increase the efficiency of texting and driving ad placement.For example, since younger consumers tend to be more promotion-fo-cused (Lockwood, Chasteen, & Wong, 2005), managers can place ad-vertisements in areas with higher populations of younger consumers(i.e., university communities) based on elaborative primes and cogni-tive load (i.e., imagining when negative emotions are not emphasized,considering when negative emotions are emphasized, and imaginingwhen negative emotions are emphasized and cognitive load is high).Other studies suggest that regulatory focus may differ along lines ofself-construal, with independent consumers more likely to have a pro-motion focus and interdependent individuals leaning more toward aprevention focus (i.e., Aaker & Lee, 2001; Zhao & Pechmann, 2007). Forexample, in the United States and other highly individualistic cultures,consumers tend to be more promotion-focused, which should lead togreater use of ads that prime the imagination. Meanwhile, consumers incollectivist cultures such as China or Japan tend to be more prevention-focused, so advertisements encouraging the consider approach wouldlikely be more effective. Additionally, when an ad can prime regulatoryfocus, managers can ensure that the elaborative and emotional frame ofa following ad aligns with the regulatory prime of the initial ad.

7.3. Limitations and future research

The present work has a few limitations. First, none of the studiesincludes measures of actual behavior, so future studies should validatethe findings in laboratory or field settings. Second, while reducingtexting and driving behavior is a worthwhile, timely endeavor, thiscontext is only one of many social causes and the above findings shouldbe tested across multiple social marketing contexts. Third, the abovestudies utilized measures of chronic regulatory focus, so to enhance thestrategic benefits of the above findings, future research should validatethe effects after priming situational regulatory focus. On a related note,the ads used could have induced state-level regulatory focus that dif-fered from chronic regulatory focus, though we did attempt to minimizeany such effects by holding the ads within each study constant for allparticipants.

Fourth, given the potentially sensitive nature of reporting textingand driving, some participants could have answered in a socially de-sirable way, but we did try to minimize such responses by emphasizinganonymity of responses. Fifth, the manipulations used to prime the twoelaborative approaches closely followed those of Spears andYazdanparast (2014), but the present context was different; this re-sulted in a slightly longer prime for imagining than for considering. Theimagine prime also indicated for participants to ‘push themselves,’whereas the consider approach did not use this exact verbiage, andsome may argue that the stimuli are different. Sixth, some studies havea slight gender imbalance, although gender was controlled for and non-significant in all but one of the studies.

In addition to addressing the above limitations, future researchcould follow a few key avenues. First, beyond texting and driving andother social causes popular with marketers, contexts such as impulsebuying, experiences, and entertainment heavily rely on emotionalprocesses. Could aligning regulatory focus and elaborative approachesboost responses in such domains through alterations to negative emo-tional intensity? If so, how does this affect consumer responses in thosesituations, and how might these responses be directed toward greater


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product success and profitability?Second, what other ways might emotional biases of regulatory focus

be overcome? While the present investigation demonstrates thataligned elaborative approaches are effective at doing so, imaginingversus considering may not always be feasible or desirable. For ex-ample, if a consumer only has a few seconds to view an advertisement,it is unlikely that the consumer will have sufficient time to engage in anoptimal level of imagining or considering, which would reduce thepotential impact of regulatory fit. Furthermore, is it possible that ima-gine and consider could be primed to work in tandem or even se-quentially and if so, how would the observed effects change? As such,other means of achieving regulatory fit, or determining how elaborativeapproach could be engaged in a faster, more efficient manner, wouldcontribute substantively to these findings. For example, future researchcould examine other forms of information processing, such as visualand sensory processing.

Third, how would other forms of message framing such as a focus onpositive emotions change the effects above? While the focus on thispaper is on negative emotional intensity and framing, emphasizingpositive emotions could change the nature of regulatory fit in thecontext of texting and driving. This may prove especially fruitful inother areas in which positive emotions are more desirable and believ-able (i.e., meeting a health goal or recycling). Finally, some researchershave found that the experienced arousal levels of positive and negativeemotions differ between promotion- and prevention-focused in-dividuals (i.e., Brockner & Higgins, 2001; Idson, Liberman, & Higgins,2000). Thus, future research should investigate arousal as a potentialmediator in the process of negative emotional intensity.

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Kelly Naletelich is an Assistant Professor of Marketing, Department of Marketing, JamesMadison University, Harrisonburg, VA. Her research interests reside within the domain ofconsumer behavior/psychology and include sensory marketing, motivation, and in-formation processing with a specific focus on co-creation, creativity, and art.

Seth Ketron is an Assistant Professor of Marketing, Department of International Businessand Marketing, California State Polytechnic University, Pomona, Pomona, CA. His re-search interests include retailing and consumer behavior/psychology, especially topicsrelated to size perceptions.

Nancy Spears is an Associate Professor (Marketing) at the University of North Texas. Shereceived her Ph.D. from Oklahoma State University. Her research interests are in the areaof advertising and consumer behavior. She has published in the Journal of Advertising,Journal of Consumer Psychology, Psychology & Marketing, Journal of Business Research,Journal of Current Issues & Research in Advertising, Journal of Business Logistics, Journalof Consumer Behavior, and others. In particular, she has published papers that deal withadvertising's visual elements, historical perspectives in advertising, sales promotions, andcreating cohesive ad gestalts. She has also published papers in the area of time orientationand intertemporal choice. Recently, Dr. Spears was recognized directly and indirectly forcontributions to the body of thought in the area of Advertising. She was rated 16th of 50leading researchers publishing in the area of Advertising Research.


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