Values for the rate constants for the interactions of each NSAID by quenching with electronically excited singlet
\r\n\tAn update on clinical manifestations, their assessment, monitoring, and imagiology, including peripheral arthritis, enthesopathy, and extra-articular findings, and, the differential diagnosis with other diseases which evolves with axial and peripheral calcifications will be provided.
\r\n\r\n\t
\r\n\tAn important component of this book must be dedicated to the more recent treatments namely with biologic therapies but focusing also on new small molecule inhibitors and experimental therapies.
In the last decades, it has been a widespread use of an increasing number of chemical compounds with analgesic, antipyretic, and anti-inflammatory properties. In order to remark their differences with other group of medicines which presents known bad side effects, they were labeled as nonsteroidal anti-inflammatory drugs with the acronym NSAIDs [1–3].
At the same time, many neuroinflammatory mediators, including oxidative agents such as reactive oxygen species (ROS), were found to be upregulated in neurodegenerative disorders (ND) that affect human brain areas [4, 5]. This fact immediately allows the proposal of some kind of cause-effect link between the presence of ROS, oxidation processes, neuroinflammation, and ND pathogenesis [4, 5].
Oxidative stress is a process that occurs in early stages of ND and is considered an identifier mark for their detection as could be evaluated by DNA, RNA, lipids, and protein oxidation levels [6–8]. Simultaneously, several studies have observed an inverse correspondence between prolonged NSAID administration and the development of some ND in humans, (for review, see Ref. [9]). So, it is now accepted that NSAIDs could play a protective role on many ND and one of the reasons of the great interest for getting more insight into the elucidation of the pathways and mechanisms of the oxidative processes in which several NSAIDs and different ROS take part.
The present chapter will analyze the results presented in two relatively recent papers that have been dedicated to evaluate the possible action of some NSAIDs as protectors against ROS-mediated oxidation/deterioration of biological targets [10, 11]. Those research works are focused on NSAIDs from different chemical structure classes, one salicylic acid derivative, diflunisal (DFN), an indolic acid derivative, indomethacin (IMT) (Figure 1) and the enolic acid derivatives, oxicams, represented by meloxicam (MEL), tenoxicam (TEN) and piroxicam (PIR) (Figure 2).
Chemical structures of
Chemical structures of
Many compounds in the presence of oxygen and any electron donor can generate different ROS—by energy and/or electron transfer processes—like singlet molecular oxygen,
The generated
The
In living organisms, a great number of biomolecules essential to life such as DNA, RNA, lipids, and proteins, can be oxidized by the generated ROS producing oxidative stress [6–8, 14]. Among other substrates, NSAIDs are compounds that can be oxidized in the presence of Rf-generated ROS and as shown can act as quenchers of electronically excited states of Rf (Eqs. (4) and (5)).
The protonation of
Its bimolecular decay through a disproportionation reaction can yield the ground state of the vitamin and fully reduced Rf (Eq. (7)).
The last product, in the presence of ground state oxygen, is reoxidized to Rf radical and superoxide radical anion
The electron transfer process, in Eq. (8) is relevant as a source of
In parallel, the generated
Another possible pathway for
The
or by a substrate, as happens in the presence of NSAIDs (Eq. (14)).
Finally, Eq. (15) represents the main pathway of substrate disappearance in
In order to get more insight into the behavior of NSAIDs toward Rf-generated ROS several
In complex biological structures, Rf and NSAIDs may occupy the same locations. Kinetic and mechanistic aspects of their mutual interaction constitute the crucial information for understanding the behavior of NSAIDs toward Rf-generated ROS and the potential
Using a home-made photolyzer, aerated neutral aqueous solutions of each of the following NSAIDs DFN, IMT, MEL, TEN, and PIR, were irradiated with the light of a 150W quartz-halogen lamp, in the presence of Rf as a sensitizer. All the NSAIDs used as substrates are transparent to visible light. Nevertheless, in order to assure that they do not absorb any incident radiation, a cut-off filter at 400 nm was employed. The processes were followed by the absorption spectra using a diode array spectrophotometer (Hewlett Packard 8452A). The light irradiation induced changes in the absorption spectra of the mixtures 0.05 mM DFN + 0.04 Rf (Figure 3), 0.05 mM IMT + 0.04 mM Rf (Figure 3, inset A) and 0.05 mM MEL + 0.04 mM Rf (Figure 4). The processes could be monitored from the absorbance decay at the respective absorption maxima for each substrate. In this way, the rates of sensitized photoxygenation for each NSAID were determined.
Changes in UV-vis absorption spectra of a pH 7 aqueous solution of 0.05 mM DFN plus 0.04 mM Rf upon photoirradiation taken vs. a 0.04 mM Rf aqueous solution (spectrum
Changes in UV-vis absorption spectra of aqueous solution of 0.05 mM MEL plus 0.05 mM Rf upon photoirradiation taken vs. 0.05 mM Rf aqueous solution (spectrum
In parallel experiments, using a specific oxygen electrode (Orion 97-08) the oxygen concentration was measured during irradiation of the same mixtures in aqueous solutions in a closed Pyrex cell [10]. Under these conditions, all the NSAIDs under study showed oxygen consumption. Regarding the oxicams family, TEN and PIR presented the lowest rate of oxygen consumption. It was a little bit higher for MEL (Figure 4, inset B). In the corresponding set for DFN and IMT, the rate of oxygen uptake was significantly higher for the latter (Figure 3, inset B).
From all these preliminary findings, we assume that the transformations in NSAIDs can be attributed to interactions with electronically excited states of Rf with the possible participation of photogenerated ROS.
The xantenic dye Rose Bengal (RB) is one of the most frequently employed photosensitizers that exclusively generate
The combination of stationary and time-resolved experiments unambiguously demonstrates the participation of
NSAID | ||||
---|---|---|---|---|
(1.1) (d) | (0.61) (d) | |||
| | (1.6) (e) |
Values for the rate constants for the interactions of each NSAID by quenching with electronically excited singlet
Some compounds that are specific ROS quenchers have been used to elucidate which species are effectively involved in a given oxidative event [20, 21]. Catalase from bovine liver (
The enzyme superoxide dismutase from bovine erythrocytes (SOD) dismutates the species
Meanwhile, sodium azide (
Bar diagrams for the relative rates of oxygen consumption with aqueous solutions pH 7, 0.5 mM IMT plus Rf (A445 = 0.5) as function of photoirradiation time (cut-off 400 nm): ITM: alone; IMT + CAT: in the presence of 1µg mL−1 CAT; IMT + SOD: in the presence of 1µg mL−1 SOD; IMT + NaN3: in the presence of 1 mM NaN3. Reprinted from Purpora et al. [
Similar experiments were performed using solutions 0.5 mM of the three oxicams and
Bar diagrams for the relative rates of oxygen consumption upon photoirradiation as function of photoirration time (cut-off filter 400 nm) in the presence of Rf 0.05 mM with the following solutions: 0.5 mM PIR in MeOH-H2O (buffer pH 7) 1:1 v/v plus 1 µg mL−1 SOD; 0.5 mM PIR in MeOH-H2O (buffer pH 7) 1:1 v/v; 0.5 mM TEN in MeOH-H2O (buffer pH 7) 1:1 v/v plus 1 µg mL−1 SOD; 0.5 mM TEN in MeOH-H2O (buffer pH 7) 1:1 v/v; 0.5 mM MEL plus 1 µg mL−1 SOD in aqueous buffer pH 7; 0.5 mM MEL in aqueous buffer pH 7. Reprinted from Ferrari et al. [
In order to evaluate an eventual antioxidant/protective effect of NSAIDs towards biologically relevant substrates, amino acids (AA) and peptides may be employed as typical oxidizable targets in a proteinaceous medium.
Tryptophan (Trp) and tyrosine (Tyr) are AAs that can be affected by photo-damages through photodynamic activity [23, 24]. They are known quenchers of
PIR and Trp, as isolated substrates, are efficient
Bar diagrams for the relative rates of oxygen consumption upon RB (A560 = 0.4) photosensitization in pH 7 buffered aqueous solution by: 0.5 mM PIR; 0.5 mM Trp; 0.5 mM PIR plus 0.5 mM Trp. And upon Rf (A445 = 0.5) photosensitization in pH 7 buffered aqueous solution by: 0.5 mM PIR; 0.5 mM Trp; 0.5 mM PIR plus 0.5 mM Trp. Reprinted from Ferrari et al. [
In neutral pH, Tyr is present in a very low reactive form. The interaction Tyr with
Bar diagrams for the relative rates of oxygen consumption upon RB (A560 = 0.4) photosensitization in pH 7 buffered aqueous solution by: 0.5 mM PIR; 0.5 mM Tyr; 0.5 mM PIR plus 0.5 mM Tyr. And upon Rf (A445 = 0.5) photosensitization in pH 7 buffered aqueous solution by: 0.5 mM PIR; 0.5 mM Tyr; 0.5 mM PIR plus 0.5 mM Tyr. Reprinted from Ferrari et al. [
A relevant result was that PIR in the presence of Rf showed an interesting degree of protection against Trp or Tyr oxidation by the
The dipeptide Trp-Tyr in a 0.5 mM aqueous solution was employed as a biologically relevant model compound, with RB or Rf as photosensitizers and IMT or DFN as potential photo-protective substrates. The
Bar diagram for the relative rates of oxygen consumption upon RB (A560 = 0.4) photosensitization in pH 7 buffered aqueous solution of: 0.5 mM Trp-Tyr; 0.5 mM IMT; 0.5 mM DFN; 0.5 mM Trp-Tyr plus 0.5 IMT; 0.5 mM Trp-Tyr plus 0.5 DFN. Reprinted from Purpora et al. [
Meanwhile, the rate for the mixture Trp-Tyr + DFN decreased more than 50% of the one for the isolated dipeptide. Upon Rf-sensitization, similar results were obtained for DFN and IMT (Figure 10). This fact suggested that the photoxidation occurs mainly by reaction with the Rf-photogenerated
Bar diagram for the relative rates of oxygen consumption upon Rf (A445 = 0.5) photosensitization in pH 7 buffered aqueous solution of: 0.5 mM Trp-Tyr; 0.5 mM IMT; 0.5 mM DFN; 0.5 mM Trp-Tyr plus 0.5 IMT; 0.5 mM Trp-Tyr plus 0.5 DFN. Reprinted from Purpora et al. [
The results presented for the NSAIDs under study pointed out their efficiency as quenchers of photogenerated
DNF could be considered as an ideal scavenger of
Based on the discussed results, the NSAIDs studied herein present, in principle, promising properties for medicinal use as bio-antioxidants against
High sugar consumption is becoming a serious problem that threats public health in many countries. Excessive sugar intake can cause a series of health consequences, such as tooth decay, obesity, diabetes, and heart diseases [1]. These health problems greatly increase the expenditure on healthcare. In the United States, one trillion dollars are spent on healthcare each year due to the national addiction to sugar [2].
The World Health Organization (WHO) is urging people to reduce the amount of sugar they eat, suggesting restriction of added sugar to less than 5% of one’s dietary intake [3]. However, it is not easy for people to control sugar intake because sugar is added to so many foods in the market [3]. Given the reality of added sugar in the market, WHO suggests that people should change eating behaviors, rather than waiting for the reformulation of products [3]. Thus, it is urgent to develop effective messages to persuade people to reduce their sugar consumptions.
This study aimed at examining the effectiveness of advertising on people’s intention to limit sugar intake. Specifically, three types of message framing were investigated in this study: gain-framed ads, loss-framed ads, neither gain- nor loss-framed ads.
Gain vs. loss frame is a common approach in health message design (e.g., [4, 5]). Gain frame usually emphasizes the positive results if an individual adopts a recommended behavior, while loss frame stresses the negative consequences if someone does not adopt a recommended behavior. A large amount of research in health communication has suggested that gain vs. loss frame can influence people’s preferences of whether or not to adopt a health behavior. However, most health-related research focuses on behaviors related to smoking, drinking, or fitness; little research investigates the impacts of gain vs. loss framing on changing behaviors regarding sugar intake. One contribution of the current study is to fill this gap by applying message framing in the advertising of limited sugar intake and examining the effects of gain vs. loss framing in this specific health context.
Moreover, neutral framing (neither gain- nor loss-framing) has been seldom examined in the previous research. The current research included neutral framing that only presented the neutral information about sugar but emphasized neither loss nor gain in order to fully examine the effects of message framing.
Although the effects of message framing (gain vs. loss) on people’s health behaviors has been found in many studies, meta-analyses (e.g., [6, 7, 8, 9, 10]) have shown that gain- and loss-framed messages do not have meaningful different effects on message persuasiveness. According to the results of meta-analyses, researchers have suggested that the studies of gain vs. loss framing should be focused on potential moderators that lead to meaningful framing differences [5, 7, 11]. Following this suggestion, the current study specifically investigated the moderation effects of regulatory focus on gain- vs. loss-framing.
According to regulatory focus theory [12, 13], people mainly adopt two self-regulatory orientations: promotion focus and prevention focus. Promotion focus is based on hopes and aspirations; prevention focus is motivated by security and safety emphasizes. Research showed that positively framed promotion-focused messages were more effective for people with a promotion focus, while negatively framed prevention-focused messages were more persuasive for people with a prevention focus (e.g., [14, 15]). This is most likely because people may experience regulatory fit when a message matches their regulatory focus orientation, which in turn leads them to “feel right” and then process the message more fluently (i.e., more easily) [14, 16]. The enhanced processing fluency (i.e., the ease of processing the information) further results in better persuasiveness of the message [14].
Therefore, processing fluency may play a mediator role in the interaction effect of message framing and regulatory focus on people’s behavioral intention. Nevertheless, little research investigated the abovementioned relationship. Hence, another expected contribution of this study was to fill the research gaps by examining a mediated moderation relationship between regulatory focus and processing fluency in influencing the effectiveness of gain- vs. loss-framing in the context of promoting less sugar intake.
Health professionals often attempt to maximize the impact of a health message on people’s attitudes and behaviors by framing the message in different ways [17]. Gain-framed health information stresses the benefits of taking a health action, while loss-framed information emphasizes the costs of failing to engage in that action. It is necessary to note that a gain-framed message can stress the benefits by presenting either positive results that will happen or negative consequences that will not happen, whereas a loss-framed message can present either negative consequences that will happen or positive results that will not happen to address the costs [17].
Rothman et al. suggested that, based on the conceptualization of prospect theory, the impact of a given frame on a behavior depends on whether the behavior is perceived as a risk-seeking or a risk-averse course of action [17]. They further proposed that people consider a behavior as safe or risky depending on how they perceive the extent to which that behavior will cause an unpleasant outcome. For example, a detection behavior of getting a mammogram can be seen as risky (i.e., a risk-seeking behavior) because it is possible to discover breast cancer; a prevention behavior of using sunscreen is relatively safe or low risk (i.e., a risk-averse behavior) because the purpose is to prevent an unpleasant outcome of skin cancer and maintain current health.
Consistent with this viewpoint, Rothman et al. argued that loss framing is more persuasive in promoting disease detection behaviors that involve perceived risk of unpleasant outcomes, whereas gain framing is more persuasive in promoting prevention behaviors that have little risk of bad outcomes [17]. This argument has been supported by a plethora of research (e.g., [18, 19, 20, 21, 22, 23, 24]).
Since lower sugar intake can be considered a preventative behavior with little risk of bad consequences, gain framing may be more persuasive than loss framing in convincing people to adopt the recommendation to limit sugar intake. In the present study, a control condition of neither gain nor loss framing was added to further examine the effects of message framing; however, little literature provides information about the different effects among three types of framing (i.e., gain, loss, and neither gain nor loss in this study). Hence, the following hypothesis is proposed for testing and a research question is raised for exploring:
H1: Gain-framed ads lead to greater intention to limit sugar intake than loss-framed ads.
RQ1: Will ads that are neither gain nor loss framed lead to different intent to reduce sugar intake than ads that are gain and loss framed (i.e., will the effect of neutral framing on sugar-reduction intention be different than the effects of gain or loss framing)?
Previous research has identified regulatory focus is a moderator of gain and loss frames [14]. Higgins developed regulatory focus theory and posited that when people pursue certain goals, they self-regulate their behaviors according to their regulatory orientations [12]. Two kinds of regulatory orientations were proposed by Higgin: Promotion focus and prevention focus [12]. People with promotion focus tend to take actions that advance desired results, while people with prevention focus are more likely to adopt actions that avoid undesired results.
The promotion orientation is associated with aspirations and advancement, while the prevention orientation is associated with responsibilities and safety [25]. Thus, promotion-focused people tend to approach pleasure and positive outcomes; prevention-focused people tend to avoid pain and negative outcomes [12]. Cesario, Higgins, and Scholer claimed that promotion focus and prevention focus are present in every individual to some degree because both nurturance and security are necessary survival needs [26]. However, people may have a predominant focus due to chronic individual differences, and additionally, situational features can momentarily activate one focus or the other [26].
Regulatory focus theory also posits that there are different goal-pursuit strategies for each system [25]. It distinguishes between eager means and vigilant means [25, 26]. Eager strategic means are associated with ensuring the presence of positive outcomes or against the absence of positive outcomes; therefore, this is a natural approach for promotion focus self-regulation, which concerns advancement and accomplishment [25]. In contrast, vigilance strategies ensure the absence of negative consequences or against the presence of negative consequences; accordingly, this is a natural means for prevention focus self-regulation, which concerns safety and responsibility [25]. This can be illustrated with an example of two students with different regulatory orientations. When they want to achieve the same goal of getting a decent grade in a course, the student with a promotion-focus orientation may read extra materials beyond the required readings (i.e., an eager means) to attain a good score, whereas the student with a prevention-focus orientation may make sure to fulfill all course requirements (i.e., a vigilant means) to attain a decent grade.
Higgins argued that there is a natural fit between eager means (e.g., making sure everything goes right) and promotion-focus orientation; and there is a natural fit between vigilance means (e.g., making sure nothing goes wrong) and prevention-focus orientation [27]. The value from fit is that regulatory fit experienced by a person can increase the value of what he/she is doing [27].
When a persuasive message is designed in a way that matches audiences’ regulatory focus, the audiences will feel right about the conveyed information, and regulatory fit emerges [14, 28]. Cesario et al. summarized that there are two main effects when people experience regulatory fit: First, people feel right about what they are doing during the process of goal pursuit; second, the strength of their engagement in the activity of goal pursuit can be enhanced [26].
Based upon the examination of 202 studies in a variety of topics over 13 years (1998–2010), a recent meta-analyzed study conducted by Grewal et al. also found that fit match is a way to create regulatory fit [29]. According to the discussion regarding fit match [29], gain-framed and loss-framed messages separately match people’s promotion regulatory focus and prevention focus, which in turn can create regulatory fit and lead people to feel right about the message. This feeling will be further transferred into the evaluation of the message and increase the message persuasiveness [30]. Hence, from another perspective, regulatory focus moderates the persuasive effect of message framing. That is, gain- and loss-framed messages have different persuasiveness under different circumstances of regulatory focus. Therefore, the following hypotheses are proposed:
H2a: For promotion-focused individuals, gain-framed ads lead to greater intentions to limit sugar intake than loss-framed ads.
H2b: For prevention-focused individuals, loss-framed ads lead to greater intentions to limit sugar intake than gain-framed ads.
It should be noted that the moderating effects of regulatory focus on the persuasiveness of framing may be mediated by processing fluency. A great deal of research has examined the impact of fluency [14]. Processing fluency refers to the extent of ease of processing a piece of information [14]. In previous research, processing fluency is often measured by reaction time or by subjective assessment of how easy/difficult to process the information [29].
Lee and Aaker [14] summarized that research has been using various stimuli across a variety of settings to promote processing fluency, such as prior exposure (e.g., [31]), expectancy (e.g., [32]), or enhanced visual clarity (e.g., [33]). It also has been suggested that process fluency can be enhanced by regulatory fit [14, 16, 34]. The reason is that compared to a message that is regulatory nonfit, people can process the message that fits their regulatory focus more easily [16]. It also can be explained as when the information is consistent rather than inconsistent with the way people naturally think when they face issues involving both positive and negative outcomes, the information might be easier to process [14].
It has been suggested that processing fluency results in enhanced affective judgment [14]. People may have more favorable attitudes toward a message when they can process that message fluently [35]. Once processing fluency is enhanced, people will evaluate the message more positively, so that it will be much easier to persuade them [14, 16].
Based on the above discussion, gain and loss framing separately fits people’s promotion- and prevention-focused orientation. Compared to regulatory nonfit, the regulatory fit may enhance processing fluency, and further increase the message persuasiveness. Thus, in the context of persuading people to lower their sugar intake, the following hypotheses are generated:
H3a: For promotion-focused individuals, gain-framed ads lead to greater processing fluency than loss-framed ads.
H3b: For prevention-focused individuals, loss-framed ads lead to greater processing fluency than gain-framed ads.
H4: Processing fluency mediates the interaction effects between ads’ gain vs. loss framing and individuals’ regulatory focus on intentions to limit sugar intake.
Since there is no literature comparing the effects of regulatory fit and processing fluency on all three types of framing (gain, loss, neither gain nor loss), the related research question is proposed to compare these effects:
RQ2: Does regulatory focus moderate three types of framing (gain, loss, neither gain nor loss) differently via processing fluency in changing people’s intention to limit sugar intake?
Based on all the hypotheses and research questions, a hypothesized model is also proposed and tested in the present study (see Figure 1).
Hypothesized model.
This study employed a three (message framing: gain vs. loss vs. neither gain nor loss framing) × two (regulatory focus: promotion focus vs. prevention focus) between-subjects online experiment design. In the experiment, the participants completed an online survey, which contained a presentation of stimuli (six ads). The questionnaire was built and distributed via an online survey tool, Qualtrics.
The subjects were paid and recruited via an online recruiting system Amazon Mechanical Turk (MTurk). In total, there were 1,104 people who resided in the US participated in this study. About 49% of them were female and 51% were male (544 vs. 558). They aged 18 to 74 years, with a mean age of 36.26 years (SD = 12.72). Most participants (70%) were white.
After the participants agreed with a digital consent form, they were directed to the online survey. The participants were randomly assigned into three experimental conditions (gain vs. loss vs. neither gain nor loss framing). They first answered a number of questions about their sugar-eating habits, regulatory focus orientations, and risk perceptions of excessive sugar consumption. Then they viewed an ad stimulus and responded to a following questionnaire to answer their processing fluency of viewing the ads, behavioral intention to limit sugar-eating, and demographic information.
Six ads were designed for three experimental conditions (gain vs. loss vs. neither gain nor loss framing). Two ads were created for each condition in order to increase the external validity of the experiment: one was mainly designed by using arguments; the other one was designed by telling a personal story. All ads presented both images (e.g., a background picture with a variety of sweet snacks and beverages) and text.
The ads in the gain-framing conditions addressed the benefits of lowering sugar intake (e.g., lose weight, look younger, improve health), while the ads in the loss-framing conditions stressed the negative consequences of continuing a high-sugar diet (e.g., gain weight, look older, get diseases). In the control conditions of neither gain nor loss framing, the ads just kept neutral statements by just addressing that Americans eat too much sugar in their daily life and burning the extra calories gained from high sugar intake needs a large amount of exercise. Manipulation check was conducted, and the results showed that the stimuli ads were appropriate.
The measures of the main variables (i.e., behavioral intention, processing fluency, regulatory focus) were all drawn from the previous literature. Two control variables (i.e., sugar-eating habit, risk perception) were measured by self-created questions.
Structural Equation Modeling (SEM) was used to explore the research questions and test the hypotheses and the model. Mplus 7 software [36] was employed to conduct the analysis. Since ad framing (gain vs. loss vs. neither gain nor loss) was a variable that had three categories, it was dummy coded into three variables in order to avoid having the analysis treat it as a continuous variable. Gain framing was first selected to be the reference group, so that the results could show the difference between gain and loss framing, as well as the difference between gain and neither gain nor loss framing. Then loss framing was chosen as the reference group for the analysis in order to compare the difference between loss framing and neither gain nor loss framing. The results showed that the model fit the data well, χ2 (18) = 32.872,
The results of the direct effects of ad framing (gain vs. loss vs. neither gain nor loss) on behavioral intention showed that gain framing is significantly more effective than loss framing in leading to greater intention to limit sugar intake, γ = −.09,
For the Research Question 1, the results showed that gain framing was not only more effective than loss framing but was also significantly more effective than neither gain nor loss framing in changing behavioral intention, γ = −.16,
Individuals’ regulatory focus (prevention vs. promotion) was found to moderate the effect of ad framing (gain vs. loss) on behavioral intention, γ = .12,
The results showed that there was no interaction effect between ad framing (gain vs. loss) and regulatory focus on processing fluency (γ = .02,
For Research Question 2, the results showed that the interaction effects between other types of ad framing and regulatory focus on behavioral intention were also not significantly mediated by processing fluency. That is, there were no moderated mediation effects among the tested ad framing, regulatory focus, and processing fluency on behavioral intention.
However, based on the results of SEM analysis, it was found several additional findings. First, the results showed that regulatory focus not only had a significantly direct effect on behavioral intention to limit sugar intake (γ = −.20,
In addition, processing fluency mediated both the effect of ad framing (gain vs. neutral) and the effect of ad framing (loss vs. neutral) on people’s behavioral intention: Processing fluency significantly affected people’s behavioral intention, β = .21,
Based on the results, the statistical diagrams of the final model were presented as follows (See Figures 2–4).
Final model (ad framing: Gain vs. loss). Note: 1. χ2 (18) = 32.872, p < .05; CFI = .995; TLI = .991; RMSEA = .027. 2. The model was evaluated by using gain framing as the reference group. 3. * indicates p < .05, ** indicates p < .01, *** indicates p < .001. 4. Dotted line indicates the effect is not statistically significant at 95% level of confidence. 5. The indirect effect of regulatory focus on behavioral intention through processing fluency is −.04, p < .01.
Final model (ad framing: Gain vs. neither gain nor loss). Note: 1. χ2 (18) = 32.872, p < .05; CFI = .995; TLI = .991; RMSEA = .027. 2. The model was evaluated by using gain framing as the reference group. 3. * indicates p < .05, ** indicates p < .01, *** indicates p < .001. 4. Dotted line indicates the effect is not statistically significant at 95% level of confidence. 5. The indirect effect of gain vs. neither gain nor loss framing on behavioral intention through processing fluency is −.03, p < .01. 6. The indirect effect of regulatory focus on behavioral intention through processing fluency is −.04, p < .01.
Final model (ad framing: Loss vs. neither gain nor loss). Note: 1. χ2 (18) = 32.872, p < .05; CFI = .995; TLI = .991; RMSEA = .027. 2. The model was evaluated by using loss framing as the reference group. 3. * indicates p < .05, ** indicates p < .01, *** indicates p < .001. 4. Dotted line indicates the effect is not statistically significant at 95% level of confidence. 5. The indirect effect of loss vs. neither gain nor loss framing on behavioral intention through processing fluency is −.08, p < .001.
The purpose of this study was to investigate the effectiveness of advertising on people’s intentions to control sugar intake. Specifically, three types of ad framing were examined: gain vs. loss vs. neither gain nor loss framing. Moreover, the moderator role of individuals’ regulatory focus (promotion focus vs. prevention focus) on the effects of ad framing was explored. In addition, processing fluency was tested as a mediator.
By considering the influences of all tested variables in a whole SEM model, it was found that gain framing was more effective than loss framing in leading people to have greater intentions to limit sugar intake. The positive reaction toward gain-framed ads may be because people do not want to be told not to eat sugar: Many people may find it pleasant to consume sweets and foods with sugar, and limiting sugar intake is a prevention behavior that asks people to give up some kind of pleasure in order to pursue other desirable outcomes. Therefore, using a positive blueprint to persuade them to pursue desirable outcomes may be more effective than using negative illustrations to scare them into giving up their current pleasure.
The findings also showed that both gain and loss framing were more persuasive than the neutral framing in changing peoples’ intentions to limit sugar intake. These findings suggest that ad framing (gain vs. loss vs. neither gain nor loss) matters in leading people to have greater intentions to adopt the recommended behavior of limiting sugar intake. Among the three types of ad framing, the neutral framing without emphasizing gain or loss cannot persuade people effectively to reduce sugar intake, while gain framing is the most effective framing to increase people’s intention to eat less sugar.
Moreover, there was a significant interaction effect between ad framing (gain vs. loss) and regulatory focus on people’s behavioral intentions. Gain framing was more effective in leading promotion-focused individuals to have greater intentions to limit sugar intake than loss framing, while loss framing was more effective in leading prevention-focused individuals to have greater behavioral intentions than gain framing. Based on regulatory focus theory [12], this result may indicate that gain-framed and loss-framed ads separately match people’s promotion regulatory focus and prevention focus, which in turn create regulatory fit and lead people to feel right about the message. Therefore, regulatory focus is a moderator in the effects of ad framing (gain vs. loss) on behavioral intention.
Additionally, it was found that processing fluency mediated both the effects of ad framing (gain vs. neutral) and ad framing (loss vs. neutral) on people’s behavioral intention to control sugar intake. That is, compared to the neutral-framed ads, both gain- and loss-framed ads were easier for participants to process, and then the greater processing fluency further led to greater advertising persuasiveness. This may be because people already have some knowledge or common sense about the negative consequences of high sugar intake or positive outcomes of controlling sugar intake; thus, compared to the neutral framing, they may process gain and loss framing more fluently with their existing knowledge, and then were better persuaded by the message.
This research provided several implications. The findings insinuate that to persuade the general population (i.e., without knowing their regulatory orientation) to control sugar intake, gain-framed advertising would be the best choice. Instead of always stressing the bad consequences of high sugar consumption to scare people, health professionals should design some positive-framed messages that stress the benefits of lowering sugar intake to stimulate people’s stronger desires to control their sugar consumption. Moreover, neutral framing of neither gain nor loss is not a good choice to persuade people to lower their sugar intake. However, if possible, it should be encouraged to find out people’s regulatory orientation in order to better persuade them. For example, hospitals or other health organizations can ask obese patients or the patients with high blood sugar to fill out a questionnaire to know their regulatory focus; and then the health professionals can use different strategies tailored to different patients to help them control sugar intake. Specifically, gain-framed messages could be used more often for promotion-focused people, while loss-framed messages should get the priority to be selected for prevention-focused people. In addition, since the findings showed that processing fluency can increase message persuasiveness, making the messages easy to process should be a way to better persuade people to lower sugar intake.
Controlling sugar intake is important for individuals since today many people have an appetite disorder [37, 38, 39]. The chronical diseases associated with sugar consumption such as obesity and diabetes are epidemic globally [37, 38]. While sugar stimulates individuals’ appetites, it also threatens public health if people appetite dysregulation and take excessive sugar [37, 38]. From a communication perspective, the present research contributes to this issue by investigating how to frame advertising messages to more effectively persuade individuals to actively reduce sugar consumptions. Prevention is better cure. More future research could be conducted to help individuals control sugar intake and build better health conditions.
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He has taught at Thompson Rivers University, Canada; University of Paris-Est, France; Osnabruck University of Applied Science, Germany; and Shanghai Institute of Technology and Tianjin University of Technology, China. He has published research in Research Policy, Applied Economics, Review of Economic Philosophy, Strategic Change, International Journal of Logistics, Sustainability, Journal of Environmental Management, Journal of Global Information Management, Journal of Cleaner Production, M@N@GEMENT, and more. He is a member of CEDIMES Institut (France), Academy of International Business (AIB), Strategic Management Society (SMS), Academy of Management (AOM), Administrative Science Association of Canada (ASAC), and Canadian council of small business and entrepreneurship (CCSBE). He is currently the director of the Research Group on Contemporary Asia (GERAC) at Laval University. 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