Impulsivity can be defined as a set of rapid and unplanned movements made without the opportunity to logically filter the results of conscious action [1]. Individuals with impulsive tendencies exhibit a set of characteristics, including risk-taking, carelessness, impatience, excitement, pleasure-seeking, inability to calculate the possibility of harm, and extroversion [2]. Impulsivity is associated with a range of conditions, including personality disorders, impulse control disorders, alcohol abuse, obesity, attention deficit hyperactivity disorder and bipolar disorder [3]. Furthermore, impulsive behaviors have been linked to negative eating behaviors [4]. Existing literature suggests that individuals with obesity are more prone to impulsive behaviors in comparison to their normal-weight counterparts [5,6]. Furthermore, a correlation has been identified between impulsivity and the pleasure derived from consuming palatable foods in the absence of hunger or satiety [7].

Nudging is a strategy designed to influence individuals’ behavior in a predictable way without imposing restrictions or significantly altering their economic incentives [8]. The nudging technique can be used to influence health-related choices, as demonstrated in a study where vending machine wraps featuring brand logos, colors, or beverage images were used as priming nudges to guide beverage selection [9]. With the increasing prevalence of online food ordering, the concept of digital nudging has emerged as a powerful tool to shape consumer decisions in digital environments. Digital nudging involves altering the user interface or design to guide choices, as demonstrated in domains such as health, e-commerce, and transportation [10,11]. Even though research into digital nudges in the context of online dining options has been conducted across a range of fields, there is a notable dearth of studies in this area [12]. Extant research has predominantly concentrated on the identification of the most significant digital stimuli, namely the default nudge and social influences [13-15].

The current study is grounded in Self-Regulation Theory, which posits that individuals with poor self-regulation are more likely to engage in impulsive behaviors, including unhealthy food choices [16]. Dual-Process Theory provides a framework for understanding how digital nudges influence decision-making by distinguishing between two cognitive systems: System 1 (automatic, intuitive processing) and System 2 (deliberate, rational processing). Decision-making models should account for both rational and behavioral assumptions, as individuals frequently rely on heuristics and cognitive biases when making choices [17]. Digital nudges primarily target System 1 by subtly guiding users toward healthier choices without requiring conscious deliberation. However, individuals with high impulsivity or alexithymia may be less responsive to such nudges because their decision-making processes are dominated by automatic, emotion-driven choices. Furthermore, Affect Regulation Theory suggests that individuals prone to emotional eating use food as a coping mechanism to regulate negative emotions [18]. This may reduce the effectiveness of digital nudges since emotionally driven food choices are motivated by immediate affective needs rather than external cues like warnings or social influence. Given these theoretical perspectives, this study seeks to investigate whether impulsivity, alexithymia, and emotional eating moderate the effectiveness of digital nudges in shaping online food selection behaviors.

The phenomenon of eating behavior is a complex process, with intrinsic, environmental and social effects [19]. Understanding the factors that shape food choices is crucial for public health as it reveals the complex and personal process by which individuals balance health with other priorities in their diets [20]. An understanding of the decision-making processes employed by consumers in the context of a complex food environment can facilitate the development of insights into the factors that influence their food purchasing choices. This is referred to as the optimization of choice architecture, which constitutes the second fundamental principle of nudging [21]. One method of achieving this is by making the act of nudging itself more visible by displaying calorie information on billboards and restaurant menus, which can then guide consumers towards lower calorie choices [22]. Although prior studies have examined digital nudging in various consumer contexts [14,15], the interaction between digital nudges and psychological traits related to eating behaviors remains insufficiently addressed. Therefore, this study aims to explore the relationship between psychological traits and the effectiveness of digital nudges in online food selection. Specifically, it investigates whether individuals with higher emotional eating scores are less responsive to digital nudges that encourage healthy choices. Additionally, the study examines whether impulsivity and alexithymia moderate the impact of digital nudges, potentially reducing their effectiveness in guiding food choices. Furthermore, it assesses whether social influence nudges are more effective among individuals with lower self-control, as they may rely more on external cues in decision-making. Lastly, the study evaluates whether warning nudges are more influential in altering food choices compared to other nudge types, particularly for individuals with high levels of self-regulation.

Table 1 shows the demographic characteristics of students. A total of 356 students (87.1% female) participated in the study. The mean age of the students was 21.53±2.14 years and BMI was 22.02±3.70 kg/m². The distribution of academic majors showed that 39.6% of participants were enrolled in Nutrition and Dietetics, while 60.4% were from other disciplines. Most participants reported no chronic disease (76.1%), and the majority (37.1%) ordered food online 1-3 times per month. The psychological trait scores were as follows: the mean BIS-11-SF score was 34.08±8.63, the mean TAS-20 score was 53.08±9.75, and the mean EEQ-TR score was 11.81±5.80.

Among the three main food categories presented, the hamburger category was selected by the majority of participants (n=282, 79.2%), indicating a strong preference for fast-food options among university students. Regarding the nudge types, the warning nudge in the dessert category was the most effective, influencing 43.3% (n=196) of participants to modify or reconsider their choices, followed by the social influence nudge in the hamburger category (31.3%, n=129). Figure 1 illustrates the distribution of food category and nudge selections.

Spearman correlation analyses were conducted to assess the relationships between BMI and psychological traits. As shown in Table 2, EEQ-TR scores were positively moderate correlated with BMI and TAS-20 (r=0.315, p<0.001, r=0.347, p<0.001, respectively). A weak but significant correlation was also observed between BIS-11-SF and TAS-20 scores (r=0.127, p<0.05), indicating that impulsivity was moderately associated with alexithymic tendencies.

Table 3 shows the relationship between the choice of digital nudge types and some demographic characteristics, BIS-11-SF, TAS-20 and EEQ-TR scales. Among all nudge types, only the social influence nudge showed a statistically significant gender difference: females were more likely to choose social influence nudges compared to males (p=0.032). No statistically significant differences were observed between the nudge groups in terms of BMI, department, or psychological trait scores (BIS-11-SF, TAS-20, EEQ-TR).

This study is to our knowledge the first to investigate the moderating effects of impulsivity, alexithymia, and emotional eating on the effectiveness of digital nudges in online food selection. The preferred category of the participants was the hamburger category. The warning nudge was the preferred nudge with 43.3%, followed by social influence nudge with 31.3%. Furthermore, a statistical difference was found for genders only between those who chose social impact nudge type and those who did not. However, department BMI, emotional eating, alexithymia, and impulsivity did not statistically affect digital nudge selection.

Notably, individuals with higher emotional eating scores demonstrated lower responsiveness to digital nudges promoting healthy choices. This finding supports prior research indicating that emotional eaters tend to consume energy-dense foods as a coping mechanism, making them less receptive to nudges aimed at healthier selections [38]. Arexis et al. [39], further emphasize that emotional eating is associated with deficits in emotion regulation and inhibition, reinforcing the challenge of modifying such behaviors through external interventions. These results suggest that addressing the underlying mechanisms of emotional eating – such as difficulties in emotion regulation – may be essential for enhancing the effectiveness of nudging strategies.

Gender differences in nudge effectiveness were also observed with female participants responding more strongly to social influence nudges. This finding is consistent with studies suggesting that women are more sensitive to social norms and external cues when making food-related decisions [36]. In contrast, Jesse et al., suggest that men may respond more favorably to digital nudges, experiencing fewer decision-making difficulties [14]. Additional research indicates that women prioritize personal preferences and product quality in food selection, whereas men are more influenced by environmental and social factors [40-42]. Our study supports these findings, as gender was a significant factor only in the social influence nudge condition. Therefore, it is important to consider gender-specific trends when designing digital interventions.

Among the various nudge types examined, warning nudges in the dessert category had the strongest effect, followed by social influence nudges in the hamburger category. This is consistent with prior studies showing that consumers are significantly influenced by textual warnings and user-generated reviews in online food ordering environments [43]. Additionally, Jesse et al. [14], demonstrated that hybrid models combining default and social influence nudges exert the greatest impact, particularly when participants are warned about unhealthy options. Furthermore, our study found a positive correlation between emotional eating, impulsivity, and alexithymia. This aligns with research showing that alexithymic individuals – who struggle to identify and express emotions – are more prone to emotional eating [44,45]. Given that our sample was predominantly female and comprised health sciences students, this may have influenced the overall results, as this population tends to have greater nutritional awareness and healthier eating behaviors.

From a theoretical perspective, these results highlight the complex interplay between psychological traits and digital nudging strategies. While impulsivity and alexithymia did not act as significant moderators, emotional eating emerged as a key factor, reinforcing the need for interventions that integrate emotion regulation strategies [46]. Practical applications of this research suggest that integrating mindfulness-based prompts or stress management tools into digital platforms could mitigate the effects of emotional eating and enhance the overall effectiveness of nudging strategies. These findings have practical implications for digital marketing, public health strategies, and online food platforms. For example, social influence nudges can be enhanced by integrating real-time user-generated ratings or peer reviews to increase credibility and persuasion. Similarly, warning nudges could be personalized using data from users’ previous food choices – such as suggesting lower-calorie alternatives when a high-calorie item is selected. Such strategies could improve user engagement while promoting healthier decision-making in digital food environments.

Understanding these dynamics is crucial for analyzing how individuals make food choices, particularly in digital environments where nudges are employed. Nudges emphasizing healthier alternatives may be particularly effective for individuals with lower self-control, as they may be more prone to impulsive decision-making [47]. Moreover, individuals with high levels of alexithymia – who often experience difficulties in emotional processing – may struggle to engage with emotion-driven nudging strategies, potentially limiting the effectiveness of such interventions in promoting healthier food choices [48]. Interestingly, the findings suggest that low self-control could facilitate healthier choices when nudges are appropriately tailored [49]. Our findings indicate that impulsivity, as measured by the BIS-11 SF, did not significantly influence the effectiveness of digital nudges on online food choices. This suggests that regardless of an individual’s level of impulsivity, digital nudges can still play a role in guiding food selection behaviors. These results imply that digital nudging strategies may be broadly applicable across different impulsiveness, and alexithymia levels, offering a promising approach for promoting healthier food choices in online environments.

Additionally, emotional eating can significantly influence dietary choices and overall health outcomes [50]. This behavior can often lead individuals to choose energy-dense and palatable foods, exacerbating problems such as obesity and related health conditions [51]. However, our findings revealed no significant relationship between the emotional eating tendencies, as measured by the EEQ-TR, and the effectiveness of different types of digital nudges on online food choices. This indicates that emotional eating tendencies, as measured by the questionnaire, do not appear to interact with or influence the impact of digital nudging strategies. This suggests that digital nudges may be effective across various eating behavior profiles, including those prone to emotional eating.

In practical terms, these findings suggest that digital nudges can be tailored to specific user profiles to maximize their impact. For instance, social influence nudges may be particularly effective for female users, while warning nudges could be designed to target individuals with higher levels of self-regulation. Moreover, understanding the role of emotional regulation in eating behavior may guide the development of more comprehensive and personalized digital interventions.

While this study provides valuable insights, certain limitations must be acknowledged. First, this study was cross-sectional, therefore, no direct cause and effect relationship can be established. Secondly, the study consisted of university students, which affects the generalizability of the study among other age groups. Thirdly, 39.6% of the participants were studying in the department of nutrition and dietetics. This may have reduced the effectiveness of the selection of digital nudge models due to their tendency to choose healthier foods due to nutritional education. Fourth, most of the participants were women. Considering that women are more likely to make healthy food choices, this may have reduced the selection of digital nudge models. Furthermore, it is important to acknowledge that the statistical power of some comparisons may be limited due to uneven distribution of nudge selection across categories. Future studies with larger and more balanced samples could further validate and deepen the interpretation of these results. However, the study also has strengths. To our knowledge, this is the first study to assess the relationship between impulse, alexithymia, emotional eating and digital nudge in online food selection. Moreover, the digital nudge types examined are some of the most analyzed in the literature.

In conclusion, while digital nudges hold potential for guiding healthier food choices, their effectiveness appears contingent on individual psychological traits. Future research should explore personalized nudging approaches tailored to emotional eaters, as well as gender-based variations in responsiveness. These insights could inform the development of more effective digital interventions for promoting healthier eating behaviors in online food environments.