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

Journal of Business Research 100 (2019) 61–72

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Journal of Business Research journal homepage: www.elsevier.com/locate/jbusres

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

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Kelly Naletelicha, , Seth Ketronb, Nancy Spearsc a

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

A R T I C LE I N FO

A B S T R A C T

Keywords: Regulatory focus Emotions Elaborative approach Information processing Motivation Cognitive load

Texting and driving is a growing societal concern, yet few studies have examined motivational determinants and elaborative processing driving this behavior. Thus, we combine regulatory focus theory and two elaborative approaches 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 to decrease texting and driving when asked to imagine (versus consider) potential outcomes. However, focusing specifically on negative outcomes suppresses the effect of imagining for promotion-focused individuals, whereas a focus on negative outcomes does not significantly change the effect of imagining versus considering for prevention-focused individuals. Further, low (high) cognitive load renders both elaborative approaches equally effective for promotion-focused (prevention-focused) individuals. Finally, negative emotional intensity is identified as the mediator driving these effects. The findings underscore the need to tailor texting and driving advertisements 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 Safety Council, 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 a given month (Atchley, Atwood, & Boulton, 2011). The risks of texting and driving have led several organizations to launch advertising campaigns discouraging the behavior. For example, in 2013, AT&T spent tens of millions of dollars alone on advertising campaigns 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 advertisements and public service announcements (Hall, 2013). Given the constant negative press, texting and driving should naturally be viewed negatively, and these negative associations and accompanying emotions should signal avoidance and discontinuance of the behavior (Carver & Scheier, 1990; Clore, 1994; Fredrickson, 2004; Frijda, 1994). However,

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despite the prevalent negative messaging and associations, texting and driving continues to be a consistent and pervasive problem among consumers (Atchley et al., 2011; National Safety Council, 2015). Surprisingly, texting and driving has received minimal attention in marketing. A few studies in the marketing domain have investigated texting 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 and practical perspectives, particularly with respect to the motivational systems of texting drivers or the ways in which consumers process information from messages discouraging texting and driving. Thus, we apply precepts from regulatory focus theory to investigate two primary motivational systems as they relate to texting and driving. The first system is a promotion focus, attuned to a positive, broadened mindset inclined to take more risks in the hope of advancing beyond the individual's status quo or perceived state of normalcy (“0” to “+1,” or improving upon one's current perceived state). The second system, a prevention focus, is more attuned to a narrow, deliberative mindset inclined 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 dropping below one's current perceived state; Gino & Margolis, 2011;

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

https://doi.org/10.1016/j.jbusres.2019.03.009 Received 2 April 2018; Received in revised form 3 March 2019; Accepted 4 March 2019 0148-2963/ © 2019 Published by Elsevier Inc.

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memory, such as the details of the last text message sent/received, words that were received in a text from a friend, etc. (Baumgartner et al., 1992; Leahy & Sweller, 2008; Tulving, 1972). This process is a more effortful point-by-point comparison (Foley, Wozniak, & Gillum, 2006; Sweller & Sweller, 2006). For example, if we assume that the consumer considers two information units from the texting and driving ad with two units from triggered memory about his/her typical texting and driving patterns, four total units of information may be combined, with 24 possible permutations of information. While both elaborative approaches rely on semantic details, the semantic details of the imagination are effortlessly retrieved as part of a triggered holistic episodic memory. Meanwhile, in the consider elaborative approach, retrieval of semantic details is an effortful point-ofparity process that compares specific ad details with relevant semantic details from memory, problem-solving to resolve differences between incoming ad information and triggered semantic details (Foley et al., 2006; Sweller & Sweller, 2006). Thus, handling sequential and multiple potential detail permutations is more likely to exceed the limitations of working memory, compared to the less effortful, more expansive, and more efficient holistic approach of the imagination (Foley et al., 2006; Leahy & Sweller, 2004, 2008; Sweller & Sweller, 2006).

Higgins, 1997; Higgins, 1998). Although regulatory focus can be examined from a chronic or situational state, researchers have shown that consumers respond more favorably when their chronic regulatory states (versus situational primes) match the context at hand; thus, the present paper examines regulatory focus from a chronic perspective (i.e., Keller & Bless, 2006). The research also investigates the impact of fit between regulatory focus and two elaborative approaches on reducing texting and driving. The first approach involves imagining future outcomes, while in the second approach, the consumer considers the details presented in an ad (Spears & Yazdanparast, 2014). The present study finds that the elaborations of the imagination align with a promotion focus because imagining is an expansive approach offering movement beyond the status quo, in line with promotion-focused individuals' eager strategies (i.e., Higgins & Cornwell, 2016). On the other hand, considering aligns better with a prevention focus because considering is a narrowing approach more attuned to negative signals and a point-by-point comparison of ad details; this approach focuses more on maintaining the status quo, in line with vigilant strategies. Thus, we propose that the alignment of regulatory focus with consistent elaborative approaches reduces texting and driving through regulatory fit effects. Further, the present investigation finds that when cognitive load is not salient, a focus on negative outcomes reduces the effectiveness of imagining for promotion-focused consumers because promotion-focused individuals' inclination toward positive, expansive ways of thinking are in direct conflict with negative thinking. In this case, imagining is no more effective than considering in reducing intentions to text and drive for promotion-focused individuals. Fourth, cognitive load moderates the effectiveness of regulatory fit with elaborative approaches. We demonstrate that when under low cognitive load, prevention-focused consumers are more responsive to negative information when asked to consider, while imagining and considering are comparably effective for a promotion-focused consumer. In contrast, when under high cognitive load, imagining (versus considering) can further boost the effects of negative thinking for promotion-focused consumers, while for a prevention-focused consumer, both elaborative approaches are comparably effective. These findings show that elaborative approaches can be strategically used to overcome load-related obstacles to processing.

2.2. Achieving regulatory fit with elaborative approaches Given the different profiles of imagining and considering as described above, marketers can align imagining and considering with consumers' motivational frames to create more compelling ad messages that discourage texting and driving. One such opportunity lies in the alignment of imagining and considering with regulatory focus to create regulatory fit. Regulatory fit is an enhanced state emerging from the alignment of regulatory focus and goal pursuit strategies, such that the tactics used to approach a goal sustains one's motivational orientation and 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 to manipulate a key element within the persuasion message (Cesario et al., 2008), which in this case is the way an individual processes a texting and driving ad. According to regulatory fit theory, if the way information is processed helps to maintain the regulatory goal of a promotion (eagerly advancing beyond the status quo) or a prevention (vigilantly maintaining the status quo) focus, fit will be achieved, resulting in greater intentions to reduce texting while driving. Promotion-focused individuals tend judge the immediate environment as relatively safe and make eager decisions based upon imagined future outcomes. These imaginings help to focus attention on broader outcomes related to hopes, aspirations, and dreams and the potential for advancing beyond the status quo (Baas, De Dreu, & Nijstad, 2011; Higgins & Cornwell, 2016; Huttermann & Memmert, 2015). These characteristics align well with imagining (versus considering) as imagining allows for efficient processing that can broaden attentional focus on future outcomes (Foley et al., 2006; Leahy & Sweller, 2004, 2008). These broader imaginings keep promotion-focused consumers' processing of the texting and driving message centered on their overarching goal of eager advancement. Thus, imagining should create regulatory fit and lead to greater intentions to reduce texting and driving among promotion-focused consumers.

2. Theoretical background 2.1. Two elaborative approaches: imagining and considering When consumers are exposed to an ad that warns of the outcomes of texting and driving, that ad information is processed in working memory with elaborations that combine the information with triggered information from memory store, resulting in new knowledge (Leahy & Sweller, 2008; Schau, 2000; Spears & Yazdanparast, 2014). This work investigates two distinct approaches to such ad elaborations, one in which the consumer imagines future texting and driving outcomes and one in which the consumer considers ad details. The elaborative approach of imagining joins incoming sensory information with stored episodic memories containing contextually related semantic details. The result is a mental simulation of a yet-to-beexperienced scenario (Rawlings & Rawlings, 1974; Silvera et al., 2014; Sweller & Sweller, 2006). With a texting and driving ad, the mental simulations of the imagination combine the ad information with triggered episodic memories of previous texting and driving experiences and stories along with contextually relevant semantic details, such as the type of phone that is used, the typical persons with whom he/she texts, 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 presented in the ad with triggered semantic details that are drawn from stored

H1. The elaborative approach of imagining is more effective than considering at reducing intentions to text and drive for promotionfocused individuals. Meanwhile, prevention-focused individuals are sensitive to loss and tend to monitor their immediate environment for direct threats. Thus, they tend to focus more on the present and make vigilant decisions based upon careful consideration and systematic reasoning (Avnet & Higgins, 2006; Cornwell & Higgins, 2016; Friedman & Förster, 2005; 62

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behavior (Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000; Frijda, 1994; Carver & Scheier, 1990; Clore, 1994). Within a texting and driving context, negative emotions are important but can differ in their effectiveness as a function of regulatory focus (Higgins & Cornwell, 2016; Strauman et al., 2015). Compared to promotion-focused individuals, prevention-focused individuals are more attuned to negative emotions because of their sensitivity to safety and risk (Brockner & Higgins, 2001; Carver, 2004, 2006). Indeed, the identification of negative emotions provides a signal of avoidance for prevention-focused individuals to avoid falling below the status quo (Friedman & Förster, 2008). On the other hand, promotion-focused individuals are less concerned with negative signals (such as negative emotions) and are more concerned with positive signals, which indicate approach and the potential for advancing beyond the status quo (Brockner & Higgins, 2001; Higgins, 1998; Lockwood et al., 2002; Van-Dijk & Kluger, 2004). In scenarios with messaging aimed at triggering negative emotions without any additional information processing prompts, promotionfocused consumers may be less likely to respond desirably due to their inclination to maintain a positive, achievement-oriented mindset (Brockner & Higgins, 2001; Higgins, 1998; Lockwood et al., 2002; VanDijk & Kluger, 2004). However, aligning regulatory focus with the correct elaborative approach can focus attention to strengthen negative emotional intensity. As previously explained, imagining helps promotion-focused individuals to broaden their attentional focus, which fits a promotion-focused mindset and should direct attention toward the overarching implications of texting and driving. In contrast, considering as a more deliberative, point-by-point, analytical process more closely fits a prevention-focused mindset. Both of these alignments should direct attention toward relevant details of texting and driving and strengthen the intensity of negative emotions. In support, scholars have shown that emotional intensity is a vital component of attitude and behavior formation, especially when the intensity is more negative in nature (Cunningham, Raye, & Johnson, 2004; Russell, 2003). Therefore, negative emotional intensity should mediate the relationship between the interaction of regulatory focus and elaborative approach on reduced texting and driving. This may seem counterintuitive given that promotion-focused individuals prefer to experience positive affect (Van-Dijk & Kluger, 2004). However, negative emotional intensity should further prompt promotion-focused individuals to reduce their intentions to text and drive in order to advance out of the negative – and back into a more positive – state.

Pham & Avnet, 2009). These characteristics align well with considering (versus imagining) as considering narrows attentional focus to the immediate environment and prompts a deliberative and effortful point-bypoint comparison of situational details (Foley et al., 2006; Sweller & Sweller, 2006). Thus, considering (versus imagining) allows those with a prevention focus to better see immediate risks of texting and driving and the potential for loss, keeping these individuals vigilant against present threats against the status quo emerging from texting and driving. Thus, considering should create regulatory fit and lead to greater intentions to reduce texting and driving among prevention-focused consumers. H2. The elaborative approach of considering is more effective than imagining in reducing intentions to text and drive for preventionfocused individuals. 2.3. The effect of negative framing on regulatory fit with elaborative approach Given that regulatory fit can be affected by context (Bullard & Penner, 2017), the regulatory fit effects described above may not transfer to situations in which advertisements contain explicit negative primes. We argue that when negative outcomes of texting and driving are emphasized (which is common in such ads), the imagination may work differently. Namely, promotion-focused individuals exhibit naturally positive frames of mind (Brockner & Higgins, 2001), resulting in promotion-focused consumers' being motivated by positive situations that signal approach and advancement (Higgins, 1998; Lockwood, Jordan, & Kunda, 2002; Van-Dijk & Kluger, 2004). However, situations that specifically emphasize negative thinking are incongruent with the characteristic of a promotion-focused mindset. H3A. Emphasis on negative outcomes will moderate the effect of imagining for promotion-focused individuals, such that there will be no difference in intentions to decrease texting and driving between elaborative approaches. Such incongruent regulatory framing decreases motivation because the outcomes of processing such information do not match the corresponding end goals (Cesario et al., 2008; Higgins, 1997; Higgins, 1998; Higgins & Cornwell, 2016; Kim, 2006). For promotion-focused individuals, the end goal is advancement. However, when a texting and driving ad is specifically negative in its framing, emphasizing negative outcomes of texting and driving through either elaborative approach (imagining or considering) does not readily allow promotion-focused individuals to move beyond the status quo. In these cases, promotionfocused consumers are faced with a situation in which they are unable to efficiently act on negatively framed information. This creates regulatory incongruence, which in turn lowers motivation to reduce intentions to text and drive. However, prevention-focused individuals are concerned with maintaining the current status quo and fear regressing from a state of 0 to −1. As such, negatively framed information aligns with the natural mindset of a prevention focus, posing no threat to efficient information processing for these individuals.

H4. Negative emotional intensity mediates the effect of the interaction of regulatory focus and elaborative approaches on intentions to reduce texting and driving. 2.5. Cognitive load and its effect on negative framing Finally, an important consideration when evaluating texting and driving intentions is cognitive load. Consumers are likely to experience cognitive constraints across various driving situations, which makes cognitive load a potentially important influence on the effectiveness of texting and driving ads. For example, commuting in high density traffic areas (i.e., metropolitan cities), driving in hazardous conditions (i.e., storms and/or road construction), or contending with distractions in the vehicle (i.e., children or pets) can all induce cognitive load in a driver, which can change the influence of texting and driving ads on the driver. Thus, we argue that cognitive load may moderate the influence of negative framing, leading to different effects of imagining and considering for promotion- and prevention-focused individuals. Cognitive load influences the way individuals selectively process information that is (in)consistent with one's beliefs and motivations, including regulatory focus and negative information (i.e., Yoon, SarialAbi, & Gürhan-Canli, 2011). Specifically, prevention-focused individuals tend to respond better to negative information and can be

H3B. Emphasis on negative outcomes will moderate the effect of considering for prevention-focused individuals, such that considering will remain more effective than imagining. 2.4. The mediation of negative emotional intensity As observation would confirm, advertisements pertaining to texting and driving often use negative emotions to persuade consumers. Negative emotions are particularly important when trying to dissuade harmful behavior because these emotions indicate an undesirable state and signal to stop a behavior. On the other hand, positive emotions encourage approach-oriented behavior and signal continuance of said 63

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3.1.2. Procedure Participants first indicated their texting and driving frequency by answering two questions: “On average, how often do you text and drive per week?” and “When you do text and drive, on average, how many texts do you send?” Next, chronic regulatory focus was measured along a seven-point Likert-type scale with 11 questions adopted from Higgins et al. (2001), six measuring promotion focus (∝ = 0.74) and five for prevention focus (∝ = 0.83). All participants were then shown an advertisement including four statistics on the dangers of texting and driving. After seeing the advertisement, individuals were then randomly assigned to either the imagine or consider condition. In the imagine condition, the following instructions were presented:

made even more responsive to such information under high cognitive load, whereas promotion-focused individuals tend to prefer positive information but may be more influenced by negative information when under low cognitive load (Cunningham et al., 2004; Pham & Higgins, 2005; Yoon et al., 2011). Scholars have demonstrated that those with a promotion focus place greater reliance on negative information when cognitive load is low, as inconsistent information is difficult to process and requires greater cognitive resources (Yzerbyt & Demoulin, 2010). Further, consumers may be motivated to focus on this inconsistent information in order to appear unbiased and to resolve the uncomfortable 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 effective methods of processing negative outcomes of texting and driving for those with a promotion focus because both approaches present an opportunity to resolve an inconsistent state. However, when under high cognitive load, promotion-focused consumers are likely to feel uncomfortable when presented with inconsistent negative information but have limited cognitive resources available to resolve this inconsistency. In this situation, imagining is likely to better resolve this inconsistent state as it offers a means to more efficiently process information (Spears & Yazdanparast, 2014), requiring fewer cognitive resources than considering and also naturally fits a promotion-focused mindset. This should result in greater intentions to reduce texting and driving. Second, because prevention-focused individuals naturally prefer negative information (Cunningham et al., 2004; Pham & Higgins, 2005), they will not experience an inconsistent state. Thus, when under low cognitive load, considering is likely to be more effective than imagining (Spears & Yazdanparast, 2014) in reducing texting and driving intentions because considering better fits a prevention-focused mindset. Importantly, while considering requires more processing resources, a low-load state leaves these resources free, which does not hamper the effectiveness of considering for prevention-focused individuals. In contrast, when under high cognitive load, prevention-focused individuals are even more motivated by negative information (Yoon et al., 2011) but lack the necessary cognitive resources to engage in considering. This eliminates the advantage of considering, making considering comparably effective to imagining in reducing texting and driving intentions.

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

In contrast, participants in the consider condition read the following: Now, consider the following scenario: After completing this survey you decide to go to the grocery store and receive a text on the way. Based upon the information provided in the advertisement and your typical texting and driving behavior, think about how your behavior compares to that of the advertisement. Consider such things as how often you text and drive, if someone would text you while driving and what you would do. List all of your thoughts, feelings and impressions about the scenario that you have considered.

Study 1 tests the proposal that elaborative approaches can be an effective way of reducing intentions to text and drive if matched to the correct motivational mindsets and also tests negative emotional intensity as the mediating process.

Participants then wrote down their thoughts, feelings, and impressions. Respondents were asked to indicate their agreement with how strongly they felt negative emotions with seven-point items adapted from 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 attitude toward 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 indicated their level of involvement pertaining to the content depicted in the 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 times do you think you'll text and drive?” and “Next week, how many texts do you think you'll send while driving?” The initial texting and driving numbers along with the responses from these final two questions were multiplied together and used to calculate change in texting and driving intentions using the following equation:

3.1. Method

Texting and driving frequencyBefore / Texting and driving frequencyAfter

H5. When under low cognitive load, prevention-focused individuals will have a greater reduction in texting and driving intentions when asked to consider (versus imagine). Meanwhile, when under low cognitive load, imagining and considering will be comparably effective for promotion-focused individuals. H6. When under high cognitive load, promotion-focused individuals will have a greater reduction in texting and driving intentions when asked to imagine (versus consider). Meanwhile, when under high cognitive load, imagining and considering will be comparably effective for prevention-focused individuals.

3. Study 1

Texting and driving frequencyBefore 3.1.1. Participants and design 209 participants were recruited from Amazon Mechanical Turk (MTurk) in exchange for compensation. The sample consisted of 114 males and 92 females. Study 1 used a continuous (regulatory focus) by 2 (elaborative approach: imagine vs. consider) between-subjects design.

Lastly, respondents indicated their age, gender, and mood (1 – strongly disagree to 7 – strongly agree; happy, good, unhappy (R), and bad (R); ∝ = 0.92) and also indicated if they had ever seen the advertisement before. 64

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3.2.4. Moderated mediation The 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 with regulatory focus as the independent variable, imagine/consider as the moderator, and intentions to reduce texting and driving as the dependent variable. The results confirm moderated mediation (effect = 0.03; CI = 0.02 to 0.07). Specifically, the interaction of regulatory focus and elaborative approaches on negative emotional intensity was significant (effect = 0.51; CI = 0.21 to 0.80), and negative emotional intensity significantly and positively predicted intentions to reduce texting and driving (effect = 0.07; CI = 0.03 to 0.10). In the second stage, PROCESS Model 1 probed into the interaction of regulatory focus and elaborative approach on negative emotional intensity to better understand the nature of the interaction on the mediator. The interaction was significant (effect = 0.51; CI = 0.21 to 0.80). For promotion-focused individuals, imagining resulted in a significantly higher 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 significantly higher negative emotional response than imagining (effect = −0.80; MImagine = 3.89 versus MConsider = 4.70; CI = −1.39 to −0.22).

3.2. Results 3.2.1. Manipulation check Consistent with the method of Spears and Yazdanparast (2014), during the procedure, participants were asked two questions along a seven-point Likert scale: “Please indicate the extent to which you used your imagination in the prior scenario to form a picture of what you will do based upon your typical texting and driving behavior” and “Please indicate the extent to which you considered the following scenario based upon the details presented and your typical texting and driving behavior.” Those in the imagine condition used their imagination 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 consider condition indicated that they considered the scenario more than those who imagined (F (1, 207) = 10.53; p < 0.001; MImagine = 5.31, MConsider = 5.80).

3.2.2. Main effects The 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 intentions to decrease texting and driving. Next, each participant's overall regulatory focus score was then calculated by subtracting the prevention focus score from the promotion focus score. A regression with the regulatory focus score entered as a continuous variable and intentions to reduce texting and driving as the dependent variables also showed a non-significant effect (b = 0.01, t = 0.70, p > 0.10).

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

3.2.3. Interaction PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) tested the interaction between regulatory focus and elaborative approach. More specifically, a spotlight analysis was employed to assess regulatory focus at ± one SD from the mean, with higher numbers indicating a promotion focus and lower numbers indicating a prevention focus. The interaction was significant (effect = 0.13; CI = 0.05 to 0.20; Fig. 1). Promotion-focused consumers had significantly greater intentions to reduce texting and driving in the imagine (M = 81%) than in the consider condition (M = 61%; effect = 0.20; CI = 0.05 to 0.35). In contrast, those with a prevention focus exhibited greater intentions to reduce texting and driving in the consider condition (M = 78%) as opposed to the imagine condition (M = 62%; effect = −0.16; CI = −0.30 to −0.01). There was no significant difference between the two conditions at the mean value of regulatory focus (MImagine = 72% vs. MConsider = 70%; effect = 0.02; CI = −0.08 to 0.13). Gender, age, mood, and attitude toward the ad were all non-significant covariates (p > 0.10). However, level of involvement was a significant covariate (b = 0.08, t = 3.43; p < 0.01).

REDUCTION IN TEXTING AND DRIVING BEHAVIOR

Imagine 85% 80% 75% 70% 65% 60% 55% 50%

78%

3.4. Discussion Study 1 confirmed that when asked to make judgments based upon one's typical texting and driving actions (i.e., neutral context), promotion-focused individuals show greater intentions to decrease texting and driving when asked to imagine (H1), whereas prevention-focused individuals show greater intentions when asked to consider (H2). Further, negative emotional intensity is the underlying mechanism driving the intention to decrease texting and driving (H4), and depth of processing was ruled out as a potential alternative explanation.

Consider 81% 72%

4. Study 2

70% 62%

Study 2 extends study 1 by testing the moderation of negative outcome-based elaboration when not accounting for cognitive load. With negative framing, there should be no difference in intentions to decrease texting and driving between imagining and considering for promotion-focused individuals (H3A). However, considering should be more effective for prevention-focused individuals (H3B). Study 2 also provides additional evidence for the mediating role of negative emotional intensity.

61%

P r e ve n t i o n

Mean

P r o mo t i o n

Fig. 1. Interaction of elaborative approach (imagine vs consider) and regulatory focus on reduction in texting and driving behavior. 65

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4.1. Methods

Reduction in Texting and Driving Behavior

4.1.1. Participants and design 244 participants were recruited from MTurk in exchange for monetary compensation. However, 26 participants indicated that they had taken a similar survey before and thus were removed, resulting in a final sample of 218. The sample consisted of 128 males and 90 females. Study 2 used a continuous (regulatory focus) by 2 (elaborative approach with a negative frame: imagine vs. consider) between-subjects design.

90% 85% 80% 75% 70% 65% 60% 55% 50%

84% 75% 70% 66%

Prevention

4.1.2. Procedure Similar to study 1, participants first indicated their texting and driving frequency with the same two items and then answered questions pertaining to their regulatory focus (promotion ∝ = 0.75, prevention ∝ = 0.83). Next, individuals were presented with the same advertisement about texting and driving used in study 1. After seeing the advertisement, individuals were then randomly assigned to either an imagine or consider condition based on negative outcomes and again wrote down thoughts, feelings, and impressions. Specifically, the imagine and consider conditions were worded the same as in the prior study, except that participants were asked to list a negative potential outcome of texting and driving. Finally, participants answered the same two questions used in study 1 to capture intentions to decrease texting and driving. Lastly, the intensity of negative emotions was measured (∝ = 0.96) as well as gender, age, attitude toward the advertisement (∝ = 0.95), level of involvement (∝ = 0.93),and mood (∝ = 0.93) as potential covariates.

68%

Mean

66%

Promotion

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

4.2.4. Moderated mediation Following the same method as study 1, Process Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) assessed the mediation of negative emotional intensity with regulatory focus as the independent variable, imagine/consider as the moderator, and intentions to decrease texting and driving as the dependent variable. The results confirmed moderated mediation (effect = 0.04; CI = 0.008 to 0.07). Specifically, the interaction of regulatory focus and elaborative approach on negative emotional intensity was significant (effect = 0.44; CI = 0.11 to 0.78), and negative emotional intensity significantly and positively predicted intentions to reduce texting and driving (effect = 0.09; CI = 0.06 to 0.11). PROCESS Model 1 then probed the interaction of regulatory focus and elaborative approach on negative emotional intensity. The interaction was significant (effect = 0.45; CI = 0.11 to 0.78). For prevention-focused individuals, considering a negative outcome resulted in a significantly higher negative emotional response than imagining (effect = −0.67; CI = −1.34 to −0.006; MConsider = 4.15 versus MImagine = 3.48). In contrast, there was no significant difference between imagining and considering a negative outcome of texting and driving for promotion-focused individuals (effect = 0.60 CI = −0.07 to 1.26; MConsider = 3.50 versus MImagine = 4.10). There was also no difference at the mean value of regulatory focus (effect = −0.04; CI = −0.51 to 0.43; MConsider = 3.83 versus MImagine = 3.79).

4.2. Results 4.2.1. Manipulation check Following 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 effects ANOVA revealed that elaborative approach (F (1, 217) = 1.44; p > 0.10) was a non-significant predictor of intentions to decrease texting and driving, and a regression with regulatory focus as the independent variable and texting and driving percent change as the dependent variable also showed a non-significant effect (b = −0.02, t = −1.22, p > 0.10).

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

4.2.3. Interaction PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) was used to test the interaction between regulatory focus and elaborative approaches on negative outcomes using a similar procedure to that of study 1 to distinguish levels of regulatory focus (spotlight analysis at ± one SD above/below the mean). As predicted, the interaction was significant (effect = 0.08; CI = 0.004 to 0.15; Fig. 2). More specifically, prevention-focused individuals displayed the greatest intentions to decrease texting and driving (effect = −0.18; CI = −0.32 to 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 two conditions at the mean value of regulatory focus (MImagine = 72% vs. MConsider = 70%; effect = −0.07; CI = −0.08 to 0.13) Age, attitude toward the advertisement, mood, and level of involvement were nonsignificant covariates (p > 0.10). However, gender was a significant covariate (b = 0.14, t = 2.66, p < 0.01).

4.4. Discussion Study 2 builds upon the findings of study 1 by demonstrating the role of negative-based imagining/considering and regulatory focus on intentions to reduce texting and driving. Specifically, without accounting for cognitive load, prevention-focused individuals exhibit greater intentions to reduce texting and driving when prompted to consider (versus imagine) a negative outcome of texting and driving. However, negative based elaboration shuts down the effectiveness of imagining for promotion-focused individuals, such that there was no significant difference and intentions to reduce texting and driving between imagining 66

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and considering. Overall, study 2 demonstrates that when negative outcomes are emphasized, there is no difference in intentions to decrease texting and driving between elaborative approaches for those with a promotion focus (H3A). On the other hand, prevention-focused individuals revert to their natural inclination to consider, which reduces intentions to text and drive (H3B). Negative emotional intensity once again fully mediated these findings (H4), with depth of processing ruled out as an alternative explanation.

Reduction in Texting and Driving Behavior

Imagine

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

Consider

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Fig. 3. Interaction of negative focused elaborative approach (imagine vs consider) and regulatory focus on reduction in texting and driving behavior when under a low cognitive load.

letter sequence?;” “How distracted did you feel in the previous scenario?” ∝ = 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).

5.1. Methods 5.2.2. Main effects An ANOVA revealed that imagining versus considering (F (1, 208) = 0.07; p > 0.10) was a non-significant predictor of texting and driving behavior change intentions. Additionally, a regression with regulatory focus as the independent variable and intentions to decrease texting and driving as the dependent variable also showed a non-significant effect (b = 0.02, t = 1.40, p > 0.10).

5.1.1. Participants and design 230 participants were recruited from MTurk in exchange for monetary compensation. However, 21 individuals indicated that they have taken a similar survey and were thus removed, resulting in a final sample of 209. The sample consisted of 86 males and 123 females. Study 3A used a continuous (regulatory focus) by 2 (elaboration on negative outcomes: imagine vs consider) between-subjects design.

5.2.3. Interaction PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) employed a spotlight analysis to assess regulatory focus at ± one SD above/below the mean, similar to studies 1 and 2. As predicted, the interaction was significant (effect = 0.08; CI = 0.02 to 0.14; Fig. 3). More specifically, prevention-focused individuals displayed the greatest intentions to reduce texting and driving (effect = −0.15; CI = −0.27 to CI = −0.02) when asked to consider (M = 84%) versus imagine (M = 69%) a negative consequence of texting and driving. In contrast, for a promotion focus, there was no significant difference (effect = 0.08; CI = −0.05 to CI = 0.21) between imagine (M = 88%) and consider (M = 80%). There was also no significant difference between the two conditions at the mean value of regulatory focus (MImagine = 78% vs. MConsider = 82%; effect = −0.03; CI = −0.12 to 0.06) Age, attitude toward the ad, gender, and level of involvement were non-significant covariates (p > 0.10). However, mood was a significant covariate (b = 0.31, t = 2.23, p = 0.03).

5.1.2. Procedure Like the prior studies, participants first indicated their texting and driving frequency with the same two items and then answered questions pertaining to their regulatory focus (promotion ∝ = 0.74, prevention ∝ = 0.83). To prime low cognitive load, individuals were next asked to remember a two-digit number/letter sequence (as opposed to an eight-digit sequence in study 3B) that they would later be asked to recall (Shiv & Huber, 2000). After the load task, participants followed the same procedure as study 2. Specifically, all saw the same advertisement, were randomly assigned to imagine or consider, and then were asked to list a negative outcome of texting and driving. Lastly, respondents indicated their texting and driving behavior change intentions, 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, subjects indicated ease of processing with three seven-point Likert-type items (“In the previous scenarios, when I was writing about a negative outcome that could occur from texting and driving, the information was: difficult/easy to process; difficult/ease to comprehend; difficult/ easy to understand;” ∝ = 0.95).

5.2.4. Moderated mediation The mediation analysis proceeded in two stages. In the first stage, PROCESS Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) assessed the mediation of negative emotional intensity with regulatory focus as the independent variable, elaborative approach as the moderator, and intention to reduce texting and driving as the dependent variable. The results confirmed moderated mediation (effect = 0.01; CI = 0.005 to 0.04). Specifically, the interaction of regulatory focus and elaborative approaches on negative emotional intensity was significant (effect = 0.33; CI = 0.02 to 0.64), and negative emotional intensity significantly and positively predicted intentions to reduce texting and driving (effect = 0.04; CI = 0.01 to 0.07). PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) probed into the interaction of regulatory focus and elaborative approach on negative emotional intensity to better understand the nature of the interaction on the mediator. The interaction was significant (effect = 0.33; CI = 0.02 to 0.64). For prevention-focused

5.2. Results 5.2.1. Manipulation checks Those 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 the consider condition indicated that they considered the scenario more than those in the imagine condition (F (1, 208) = 7.07; p < 0.01; MImagine= 5.81, MConsider= 6.23). The cognitive load task was also effective. Those who received the low cognitive load task in study 3A indicated they had less difficulty concentrating (i.e., “How difficult was it to concentrate in the previous scenario (listing a negative outcome of texting and driving)?;” “How difficult was it to remember the number/ 67

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6.2. Results

individuals, considering a negative outcome resulted in a significantly higher negative emotional response than imagining (effect = −0.75; CI = −1.37 to −0.13; MConsider = 4.61 versus MImagine = 3.86). In contrast, there was no significant difference between imagining and considering a negative outcome of texting and driving for promotionfocused individuals (effect = 0.18; CI = −0.44 to 0.81; MConsider = 4.25 versus MImagine = 4.43). There was also no difference at the mean value of regulatory focus (effect = −0.28; CI = −0.72 to 0.15; MConsider = 4.61 versus MImagine = 3.86).

6.2.1. Manipulation check Those 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 the consider condition indicated that they considered the scenario more than 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 who received the high cognitive load task in study 3B indicated they had more difficulty concentrating than those who received the low cognitive load task in study 3A (F (1, 424) = 352.68; p < 0.01;, MHigh load = 4.05; MLow load = 1.82).

5.3. Alternative explanation Using the same method as the prior studies, depth of processing was once again ruled out as an alternative explanation (interrater reliability ∝ = 0.94; effect = 0.004; CI = −0.002 to 0.01). Ease of processing was also ruled out as an alternative explanation using Process Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped samples), with regulatory focus as the independent variable, elaborative approach as the moderator, ease of processing as the mediator, and intentions to reduce texting and driving as the dependent variable. The moderated mediation results were not significant, ruling out ease of processing as an alternative explanation (effect = 0.003; CI = −0.01 to 0.003).

6.2.2. Main effects The 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 and driving behavior change intentions, and a regression with regulatory focus as the independent variable and intentions to reduce texting and driving as the dependent variable also showed a non-significant effect (b = 0.00, t = −0.02, p > 0.10). 6.2.3. Interaction PROCESS Model 1 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) used a spotlight analysis to assess regulatory focus at ± one SD above/below the mean, with higher numbers indicating a promotion focus 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 displayed greater intentions to decrease texting and driving (effect = 0.13; CI = 0.008 to CI = 0.25) when asked to imagine (M = 79%) versus consider (M = 66%) a negative outcome of texting and driving. In contrast, 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 significant different between the two conditions at the mean value of regulatory focus (MImagine = 77% vs. MConsider = 74%; effect = 0.03; CI = −0.05 to 0.12) Age, attitude toward the advertisement, and gender were nonsignificant 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.

5.4. Discussion Study 3A shows that when asked to elaborate on negative outcomes in conditions of low cognitive load, prevention-focused individuals have a significantly greater intentions to reduce texting and driving when asked to consider (versus imagine). However, promotion-focused individuals demonstrate no significant difference in intentions to reduce texting and driving between the two elaborative approaches. Negative emotional intensity is once again shown to fully mediate this process, with depth of processing and ease of processing both ruled out as alternative explanations.

6. Study 3B Study 3B seeks to build upon study 3A by testing the prediction of H6 that under conditions of high cognitive load, promotion-focused individuals will have greater intentions to decrease texting and driving when asked to imagine (versus consider). Meanwhile, for a prevention focus, imagining and considering should be comparably effective. Study 3B also provides additional evidence for the mediating role of negative emotional intensity.

6.2.4. Moderated mediation The mediation analysis proceeded in two stages. In the first stage, PROCESS Model 8 (Hayes, 2018; 95% CI and 5000 bootstrapped samples) assessed the mediation of negative emotional intensity with regulatory focus as the independent variable, elaborative approach as the

6.1. Methods

Imagine Reduction in Texting and Driving Behavior

6.1.1. Participants and design 250 participants were recruited from Amazon Mechanical Turk in exchange for monetary compensation. However, 34 individuals indicated that they have taken a similar survey and were thus removed resulting in a final sample of 216. The sample consisted of 103 males and 113 females. Study 3B used a continuous (regulatory focus) by 2 (elaboration on negative outcomes: imagine vs consider) betweensubjects design with a high cognitive load task.

6.1.2. Procedure The 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 respondents were instructed to memorize an eight-digit number/letter sequence as opposed to a two-digit sequence in the low cognition study (3A).

Consider

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Fig. 4. Interaction of negative focused elaborative approach (imagine vs consider) and regulatory focus on reduction in texting and driving behavior when under a high cognitive load. 68

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

moderator, and intentions to reduce texting and driving as the dependent variable. The results confirmed moderated mediation (effect = 0.03; CI = 0.006 to 0.07). Specifically, the interaction of regulatory focus and elaborative approaches on negative emotional intensity was significant (effect = 0.45; CI = 0.08 to 0.83), and negative emotional intensity significantly and positively predicted intentions 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 and 5000 bootstrapped samples) probed into the interaction of regulatory focus and elaborative approach on negative emotional intensity. The interaction was significant (effect = 0.45; CI = 0.08 to 0.83). For promotion-focused individuals, imagining a negative outcome resulted in a significantly higher negative emotional response than considering (effect = 0.90; CI = 0.25 to 1.55; MConsider = 3.16 versus MImagine = 4.06). In contrast, there was no significant difference between imagining and considering a negative outcome of texting and driving for prevention-focused individuals (effect = −0.21; CI = −0.86 to 0.44; MConsider = 3.86 versus MImagine = 3.66). There was also no difference at the mean value of regulatory focus (effect = 0.35; CI = −0.11 to 0.81; MConsider = 3.51 versus MImagine = 3.86).

7.1. Theoretical implications First, research shows that matching regulatory focus to the correct approach creates a fit effect that enhances persuasion and effectiveness (Avnet & Higgins, 2006). This premise has been examined across an array of contexts, but this paper is the first to examine regulatory fit as it pertains to elaborative approach to reduce texting and driving intentions. This is particularly insightful as scholars have called for additional research that explores how regulatory fit can be achieved through various methods of ‘thinking about a message,’ especially as it pertains to health and behavior change (Cesario et al., 2008). We bridge this gap by demonstrating that when prompted to imagine (consider) one's own texting and driving behavior, promotion-focused (prevention-focused) individuals indicate greater intentions to decrease texting and driving. These results are the first to document the relationship between regulatory focus and the two elaborative approaches of imagining and considering. Second, we demonstrate processing obstacles to reducing texting and driving behavior and show how imagining/considering negative outcomes aligns with regulatory focus. Namely, promotion-focused individuals tend to think in a positive, broadened manner to advance beyond the status quo, whereas prevention-focused individuals think negatively and narrowly to avoid falling below the status quo. We demonstrate that imagining negative outcomes suppresses the effects of imagining for promotion-focused individuals because imagining negative outcomes results in potential loss situations that block advancement beyond the status quo. In contrast, for prevention-focused consumers, considering negative outcomes aligns with their natural riskaverse states by allowing a narrower focus on negative outcomes of texting and driving behavior. Thus, for prevention-focused consumers, considering (versus imagining) negative outcomes creates regulatory fit, which results in greater intentions to decrease texting and driving. In this regard, we demonstrate the conditions under which regulatory fit results in desirable responses in the case of negatively-focused elaboration. Third, the present research provides important theoretical contributions concerning the effects of cognitive load as a moderator of regulatory focus, which have heretofore remained largely unexamined. The exception is Yoon et al. (2011), who demonstrated that under high cognitive load, promotion-focused individuals form stronger responses to positive information, while prevention-focused individuals respond more strongly to negative information. Meanwhile, these effects reverse under low cognitive load, such that prevention-focused (promotionfocused) individuals are more responsive to positive (negative) information. Our findings build upon that prior work by demonstrating elaborative approach as a key moderator of cognitive load and regulatory focus when negative information is present. Namely, we demonstrate that when under low cognitive load, prevention-focused consumers are responsive to negative information when asked to consider, while imagining and considering are comparably effective for a promotion-focused consumer. In contrast, when under high cognitive load, imagining (versus considering) can further boost the effects of

6.3. Alternative explanation Using the same method as the prior studies, depth of processing was once again ruled out as an alternative explanation (interrater reliability ∝ = 0.96; effect = −0.001; CI = −0.01 to 0.003) in addition to ease of processing (effect = −0.003; CI = −0.02 to 0.002). 6.4. Discussion Study 3B shows that when asked to elaborate on negative outcomes in conditions of high cognitive load, promotion-focused individuals have a significantly greater intentions to reduce texting and driving when asked to imagine (versus consider). However, prevention-focused individuals demonstrate no significant difference in intentions to reduce texting and driving between the two elaborative approaches. Negative emotional intensity is once again shown to fully mediate this process, with depth of processing and ease of processing both ruled out as 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; Tractinsky et al., 2013) yet has received minimal attention within marketing. This is especially true as it pertains to consumer-centric factors and the ways in which consumers process information when thinking about texting and driving. Thus, this paper combines regulatory focus theory with two elaborative approaches (imagining versus considering) to demonstrate across four studies the optimal conditions for decreasing intentions to text and drive. Study 1 demonstrates that when consumers are not prompted to imagine negative outcomes and when cognitive load is not a consideration, promotion-focused consumers demonstrate greater intentions to reduce texting and driving behavior when shown an advertisement and asked to imagine themselves in the scenario. Meanwhile, prevention consumers report greater intentions to decrease texting and driving behavior when asked to consider the scenario. Study 2 extends these findings by revealing the effects of negative-based elaboration without considering cognitive load. Namely, when promotion-focused individuals are asked to consider negative outcomes, intentions to decrease texting and driving do not significantly differ between imagining and considering, whereas prevention-focused individuals' responses to considering and imagining are not affected by negative-based elaboration. 69

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Additionally, the above findings need not necessarily be restricted to texting and driving. Other social causes such as nutrition and obesity, smoking, alcoholism, sexual health, and conservation may also utilize the above findings. This is especially true for contexts in which negative emotional intensity is easily activated or can be believably primed. Therefore, our findings are not limited to one context, and public service campaigns could match regulatory focus to the appropriate corresponding elaborative approach across an array of societal concerns. Further, managers can place or sequence advertisements, programming, and messages in such a way as to capitalize on regulatory focus and increase the efficiency of texting and driving ad placement. For example, since younger consumers tend to be more promotion-focused (Lockwood, Chasteen, & Wong, 2005), managers can place advertisements in areas with higher populations of younger consumers (i.e., university communities) based on elaborative primes and cognitive load (i.e., imagining when negative emotions are not emphasized, considering when negative emotions are emphasized, and imagining when negative emotions are emphasized and cognitive load is high). Other studies suggest that regulatory focus may differ along lines of self-construal, with independent consumers more likely to have a promotion focus and interdependent individuals leaning more toward a prevention focus (i.e., Aaker & Lee, 2001; Zhao & Pechmann, 2007). For example, in the United States and other highly individualistic cultures, consumers tend to be more promotion-focused, which should lead to greater use of ads that prime the imagination. Meanwhile, consumers in collectivist cultures such as China or Japan tend to be more preventionfocused, so advertisements encouraging the consider approach would likely be more effective. Additionally, when an ad can prime regulatory focus, managers can ensure that the elaborative and emotional frame of a following ad aligns with the regulatory prime of the initial ad.

negative thinking for promotion-focused consumers, while for a prevention-focused consumer, both elaborative approaches are comparably effective. Overall, concerning regulatory focus, these findings offer important theoretical insights as to how elaborative approaches can overcome limitations of cognitive load when negative information is present. Fourth, we demonstrate that negative emotional intensity is a mediator driving the effects of regulatory focus and imagining/considering on intentions to decrease texting and driving. These results add to our knowledge in that promotion-focused individuals tend to think more positively, which creates a barrier that, under the right elaborative conditions, negative emotional intensity can overcome. In contrast, prevention-focused individuals tend to think less positively, so enhancing negative emotional intensity results in greater intentions to decrease texting and driving. Depth and ease of processing were ruled out as alternative explanations, further underpinning the theoretical insight that negative emotions can, at times, benefit promotion-focused and prevention-focused individuals. Lastly, this research adds to the complexity of how we perceive the effectiveness of fear appeals in advertising. The above studies demonstrate that the success of fear appeals may depend upon four factors: an individual's regulatory focus, the elaborative approach used, cognitive load, and negative emotional intensity. Theoretically, this opens a discussion that fear appeals may need to be examined across a variety of factors that were previously not considered if expected to be influential. For example, we found that using a fear appeal and negative-based elaboration suppressed the alignment of elaborative approach and regulatory focus when cognitive load was not induced. 7.2. Managerial and societal implications First, managers in the public service context can utilize the above findings in that aligning elaborative approach in congruent ways with regulatory focus can increase the effectiveness of campaigns to reduce intentions to text and drive. This not only boosts success of public service announcements but also offers the potential for society to reduce deaths, injuries, and property damage that can result from texting and driving. For example, if an advertisement asks a consumer to evaluate his/her own texting and driving behavior, promotion-focused (prevention-focused) drivers should be instructed to imagine (consider). However, if the advertisement is framed in a way as to prompt consumers to think of negative outcomes, prevention-focused drivers should be instructed to imagine outcomes, whereas promotion-focused individuals' resistance to negative thinking suppresses the regulatory fit of imagining, resulting in no difference between the two elaborative approaches. Second, drivers are likely to be under varying degrees of cognitive load when driving. For example, some drivers may be driving in high density traffic areas, through road construction, or have distractions within the vehicle such as animals or children. The above findings offer important insights for managers and policy makers for dealing with likely distraction levels. Namely, when a consumer is likely to experience a high cognitive load situation, managers should create and post ads that prompt one to imagine (versus consider) negative consequences of distracted driving. This strategy should lead to greater intentions to reduce texting and driving for both promotion-focused and prevention-focused individuals. Such a strategy would prove especially important in construction zones, where many cognitive distractions exist, and accidents are a growing concern: a crash occurs every 5.4 seconds within road work zones (U.S. Department of Transportation, 2015). On the other hand, when a consumer is likely to experience low cognitive load, such as driving in a rural area, ads should encourage one to consider (versus imagine) negative outcomes of distracted driving, which is more effective for prevention-focused individuals and can also be just as effective as imagining for promotionfocused consumers.

7.3. Limitations and future research The present work has a few limitations. First, none of the studies includes measures of actual behavior, so future studies should validate the findings in laboratory or field settings. Second, while reducing texting and driving behavior is a worthwhile, timely endeavor, this context is only one of many social causes and the above findings should be tested across multiple social marketing contexts. Third, the above studies utilized measures of chronic regulatory focus, so to enhance the strategic benefits of the above findings, future research should validate the effects after priming situational regulatory focus. On a related note, the ads used could have induced state-level regulatory focus that differed from chronic regulatory focus, though we did attempt to minimize any such effects by holding the ads within each study constant for all participants. Fourth, given the potentially sensitive nature of reporting texting and driving, some participants could have answered in a socially desirable way, but we did try to minimize such responses by emphasizing anonymity of responses. Fifth, the manipulations used to prime the two elaborative approaches closely followed those of Spears and Yazdanparast (2014), but the present context was different; this resulted in a slightly longer prime for imagining than for considering. The imagine prime also indicated for participants to ‘push themselves,’ whereas the consider approach did not use this exact verbiage, and some may argue that the stimuli are different. Sixth, some studies have a slight gender imbalance, although gender was controlled for and nonsignificant in all but one of the studies. In addition to addressing the above limitations, future research could follow a few key avenues. First, beyond texting and driving and other social causes popular with marketers, contexts such as impulse buying, experiences, and entertainment heavily rely on emotional processes. Could aligning regulatory focus and elaborative approaches boost responses in such domains through alterations to negative emotional intensity? If so, how does this affect consumer responses in those situations, and how might these responses be directed toward greater 70

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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 that aligned elaborative approaches are effective at doing so, imagining versus considering may not always be feasible or desirable. For example, 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 an optimal level of imagining or considering, which would reduce the potential impact of regulatory fit. Furthermore, is it possible that imagine and consider could be primed to work in tandem or even sequentially and if so, how would the observed effects change? As such, other means of achieving regulatory fit, or determining how elaborative approach could be engaged in a faster, more efficient manner, would contribute substantively to these findings. For example, future research could examine other forms of information processing, such as visual and sensory processing. Third, how would other forms of message framing such as a focus on positive emotions change the effects above? While the focus on this paper is on negative emotional intensity and framing, emphasizing positive emotions could change the nature of regulatory fit in the context of texting and driving. This may prove especially fruitful in other areas in which positive emotions are more desirable and believable (i.e., meeting a health goal or recycling). Finally, some researchers have found that the experienced arousal levels of positive and negative emotions differ between promotion- and prevention-focused individuals (i.e., Brockner & Higgins, 2001; Idson, Liberman, & Higgins, 2000). Thus, future research should investigate arousal as a potential mediator in the process of negative emotional intensity.

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Kelly Naletelich is an Assistant Professor of Marketing, Department of Marketing, James Madison University, Harrisonburg, VA. Her research interests reside within the domain of consumer behavior/psychology and include sensory marketing, motivation, and information processing with a specific focus on co-creation, creativity, and art. Seth Ketron is an Assistant Professor of Marketing, Department of International Business and Marketing, California State Polytechnic University, Pomona, Pomona, CA. His research interests include retailing and consumer behavior/psychology, especially topics related to size perceptions. Nancy Spears is an Associate Professor (Marketing) at the University of North Texas. She received her Ph.D. from Oklahoma State University. Her research interests are in the area of 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, Journal of Consumer Behavior, and others. In particular, she has published papers that deal with advertising's visual elements, historical perspectives in advertising, sales promotions, and creating cohesive ad gestalts. She has also published papers in the area of time orientation and intertemporal choice. Recently, Dr. Spears was recognized directly and indirectly for contributions to the body of thought in the area of Advertising. She was rated 16th of 50 leading researchers publishing in the area of Advertising Research.

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