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Modern dietary health is characterized by a stark contrast between clinical recommendations and the pervasive availability of processed sugars. This conflict is heavily influenced by the strategic efforts of the food industry, where advertising and persuasion often bypass simple nutritional knowledge. Research indicates that even when individuals possess significant knowledge about nutrition, their food choices are frequently driven by hedonistic orientations and the social appeal of products (Tarabashkina et al., 2016). Consequently, understanding how to effectively promote healthy eating requires a deep examination of the persuasion processes that shape consumer behavior (Requero et al., 2021). 
Central to this understanding is the concept of message framing, which emphasizes either the benefits of a behavior (gain-framing) or the risks of a behavior (loss-framing). In the context of sugar reduction, research suggests that loss-framed warnings may be more efficient than gain-framed logos in encouraging healthier choices (Alcantara et al., 2020). The way sugar is symbolically presented also significantly impacts perception; for example, labeling an ingredient as “fruit sugar” can create a “health halo” effect, leading consumers to perceive a product as healthier than when it is simply labeled as “sugar” (Sütterlin & Siegrist, 2015). Furthermore, the format of the information, whether abstract or concrete, plays a vital role. Providing concrete imagery of sugar content, such as visualizing the physical amount of sugar in a beverage, has been shown to reduce the attraction to and selection of sugary drinks more effectively than providing abstract nutritional facts (Adams et al., 2014). 
However, the efficacy of these frames is not universal and is often moderated by the internal emotional state of the recipient. The interaction between a person’s current emotions and the frame of the message is critical; for instance, individuals in a state of fear may respond more effectively to loss-framed messages, whereas those in a state of anger may show greater increases in healthy behavior when presented with gain-framed information (Gerend & Maner, 2011). This suggests that baseline psychological states, such as anxiety, may dictate whether a “sugar is addictive” narrative motivates a healthier choice or triggers defensive dismissal. 
Much of the existing literature on nutritional framing has focused on “behavioral intentions” —what a person intends to eat in the future—rather than actual, immediate choices; this creates a significant “intention-behavior gap.” To address this, the current study moves beyond self-reported intentions by measuring immediate impulse choice: the physical selection of a candy item following exposure to a message-framed article. The primary purpose of this research is to determine if exposure to a “sugar is addictive” frame versus a neutral or “sugar is good” frame significantly impacts a participant’s immediate choice. 
This study is driven by one primary research question and three exploratory research questions. The primary research question investigates the extent to which a participant’s baseline current state, as measured by the State-Trait Anxiety Inventory (STAI), influences the relationship between the article frame and the reported level of influence. It is hypothesized that participants reporting higher levels of anxiety or stress will demonstrate a stronger behavioral reaction to the “sugar is addictive” narrative. The exploratory research questions examine how self-reported perceptions of diet healthiness fluctuate across measurement intervals and whether the perceived credibility of the information source affects candy choice. By synthesizing behavioral data with research on persuasion and emotional moderators, this study seeks to extend the understanding of how individuals navigate complex narratives surrounding sugar consumption.

Method Participants Participants (N = 20) were psychology undergraduate students at James Madison University enrolled in Dr. Irons’ psychological research methods class. Of the total sample, 12 students were Sophomores (n = 12), 7 students were Juniors (n = 7), and 1 student was a Senior (n = 1). Participants were recruited with a convenience sample and received in-class participation credit as an incentive. Materials Exposure Framing Articles Participants were randomly assigned to read one of two brief articles regarding the addictive nature of sugar; one article utilized positive framing while the other utilized negative framing. State-Trait Anxiety Inventory (STAI) To measure current affective states, participants completed the STAI. This 20-question inventory assesses feelings of stress, confidence, and confusion on a 4-point Likert scale ranging from 1 (not at all) to 4 (very much so). Visual Analog Scale (VAS) Participants completed several self-report measures on a 1-100 VAS. These included assessments of overall lifestyle healthiness, diet healthiness, and current physiological states, including hunger, cravings, and enjoyment of sweet or savory/salty foods.

Candy Selection A physical selection of four candy types was provided: regular chocolate, sugar-free chocolate, regular Starburst, and sugar-free Starburst. Procedure Upon arriving in the classroom, participants provided informed consent and were randomly assigned to read one of the two exposure framing articles. After reading, participants selected one of the four available candy options; to ensure consistency and reduce social influence, participants were instructed to wait until others had finished their selection before choosing their own. Immediately following the selection, participants completed a survey to collection demographic information (age, school year, and dietary restrictions) and identify their primary source of health information. Throughout the survey, participants rated the healthiness of their diet and lifestyle on a 1-100 scale, completed the STAI and VAS, and recorded which candy they had chosen. Finally, participants rated the extent to which the article they read influenced their survey responses on a scale of 1-100.

Results For lifestyle ratings, an independent samples t-test indicated a notable trend between the framing groups. Although the “sugar is less addictive” group reported higher health scores (M = 70.64, SD = 14.12) than the “sugar is more addictive” group (M = 57.78, SD = 17.83), the differences did not reach statistical significance at the .05 level, t(18) = 1.80, p = .088. However, the effect size was large, Cohen’s d = .81, suggesting that the framing had a substantial practical impact on participant perceptions despite the small sample size. A similar pattern was observed regarding the enjoyment of savory/salty foods. Participants in the “less addictive” framing group reported higher enjoyment (M = 79.91, SD = 10.39) compared to the “more addictive” group (M = 67.78, SD = 15.64). While the result sat just outside the standard threshold for significance, t(18) = 2.08, p = .052, the large effect size (Cohen’s d = .93) underscores a meaningful difference in mean scores between the two conditions. To examine demographic differences, an independent samples t-test compared Sophomores (n = 12) and Juniors (n = 7) on their self-reported diet healthiness. Juniors reported significantly healthier diets (M = 76.13, SD = 11.78) than Sophomores (M = 60.00, SD = 15.67), t(18) = 2.47, p = .024, Cohen’s d = 1.13. Finally, a Pearson correlation was conducted to assess the relationship between self-reported hunger and the volume of food participants felt they “could eat.” A strong, positive correlation was found, r(18) = .77, p < .001, indicating the higher levels of hunger were associated with a greater perceived capacity for food consumption. Table 1. Independent Samples t-Test Results for Perceived Reading Influence Descriptive Inferential M SD t df p d CI 95% Sugar is less addictive 25.55 27.97 .75 18 .462 .34 [-14.55, 30.76] Sugar is more addictive 17.44 17.81 Note. df = 18 for all tests. Ratings were self-reported on a scale of 1-100.

Discussion The primary objective of the current study was to examine how message framing—specifically framing sugar consumption as “less addictive” vs. “more addictive” —influences individuals’ self -reported healthiness of their overall lifestyle and diet. The results partially supported the initial hypothesis; while the differences did not reach the standard threshold for statistical significance, the large effect sizes (d = .81 and d = .70) suggest that the framing intervention had a substantial practical impact. The lack of statistical significance is likely attributable to the small sample size (N = 20), which resulted in low statistical power and may have masked the true impact of the message framing. Beyond the primary research question, several exploratory findings emerged. Participants who received the “less addictive” framing reported higher mean scores for lifestyle healthiness and a higher enjoyment of savory and salty foods. The latter result particularly stood out, as it approached significance (p = .052) with a very large effect size. Additionally, a significant demographic difference was observed, with Juniors reporting healthier diets than Sophomores. The study also identified a strong positive relationship between current hunger levels and the perceived volume of food participants felt they could eat (r = .77), highlighting the role of immediate physiological states in health-related perceptions. These findings suggest that the way health information is framed can significantly alter internal perceptions of behavior. The tendency for the “less addictive” group to view their lifestyle more favorably may be explained by a reduction in the “forbidden fruit” effect. When a substance is framed as less addictive, it may lower defensive processing in participants, making them feel more in control of their choices rather than feeling restricted by an external “addiction” narrative. These results align with broader research on message framing, which often suggests that gain-framed or low-threat messaging can be more effective for encouraging positive health perceptions than high-threat, loss-framed messaging. Strengths and Limitations A notable strength of this research was the use of a controlled framing intervention and the inclusion of multi-dimensional dependent variables, which allowed for a nuanced look at both lifestyle and diet. Furthermore, the inclusion of exploratory analyses regarding demographics and physiological states, like hunger, provided a more holistic view of the factors influencing health perceptions. However, several limitations must be addressed. The most significant limitation was the small sample size (n = 20). As noted, this led to reduced statistical power, increasing the risk of a Type II error—where the null hypothesis is retained despite a present effect. The large effect sizes found across multiple tests strongly suggest that a larger sample would likely yield statistically significant results. Future research should utilize a formal power analysis to determine a larger required N to ensure sufficient sensitivity and to further validate the impact of addictive framing on health behaviors.

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