The Influence of FOMO on Shopping Motivation and Compulsive Buying in Young Adults

Abstract

In the digital age, the fear of missing out (FOMO) phenomenon is heightened by the frequent use of online stores and a constant stream of offers and digital interactions. This study explores how FOMO, amplified by digital commerce environments, influences shopping motivation and compulsive buying in young adults. Grounded in Self-Determination Theory, the FOMO scale, and cognitive–behavioral models, the study examines how FOMO interacts with push notifications, time-limited offers, and reward-based digital cues—which are associated with emotional urgency and may interfere with reflective decision-making. The research was conducted through a semi-structured questionnaire, combining Likert-scale measures with open-ended responses, employed on a sample of Romanian students (n = 258) of West University of Timisoara. A convergent mixed-methods design was applied, including Pearson correlation and qualitative thematic coding of open-ended responses. This study reveals the interaction between internal cognitive distortions and external marketing stimuli, contributes to a more nuanced understanding of online shopping behavior, and outlines key implications for the development of ethical communication practices in digital marketplaces.

1. Introduction

In today’s hyper-connected world, online shopping is no longer a transactional activity, but has evolved into an emotionally charged experience, deeply intertwined with digital interaction patterns. E-commerce platforms, once designed simply to offer convenience and accessibility, now mimic the engagement strategies of social media to capture consumer attention and stimulate buying behavior. The fear of missing out (FOMO) has emerged as a key psychological driver among young adults, influencing shopping motivation and impulsive purchasing decisions (Bläse et al., 2023; Tandon et al., 2021). Understanding the mechanisms through which FOMO operates in digital commerce contexts is critical for both academic inquiry and practical applications in marketing ethics and consumer well-being. Recent findings indicate that exposure to social media content has a significant and positive influence on the fear of missing out (FOMO) among members of Generation Z (Zafar et al., 2020; Djafarova & Bowes, 2021). This increased FOMO, in turn, serves as a key mediator that enhances individuals’ tendencies toward impulse buying. Furthermore, the propensity to impulse shop appears to be a strong predictor of actual impulse buying behavior online, implying a robust mediating pathway connecting social media engagement to consumer behavior through the mechanisms of FOMO and impulsivity (Zanjabila et al., 2023; Djafarova & Bowes, 2021).

Behavioral studies further reveal that young adults with high FOMO levels are prone to frequent and distracted use of digital devices, simultaneously experiencing conflicting emotions—such as feelings of connectedness and belonging, alongside stress and dissatisfaction (Dholakia, 2000; Alt, 2015; Elhai et al., 2016; Bläse et al., 2023). These emotional dynamics set the stage for behavioral patterns such as compulsive app checking, impulsive actions, and compulsive consumer behaviors.

In response to these psychological vulnerabilities, e-commerce platforms have increasingly adopted push notification strategies. Originally developed by social media platforms to deliver personalized updates, they are now used as a powerful tool for maintaining engagement and encouraging frequent platform visits (Westermann et al., 2015; Hodkinson, 2019). Studies have shown that consumers exposed to notifications infused with FOMO triggers report heightened impulsivity and reduced deliberation in purchase decisions, and a heightened sense of anxiety about missing out (Good & Hyman, 2020; Zhang et al., 2018; Tandon et al., 2021).

Notably, the psychological framework underlying FOMO’s operation can be contextualized within Self-Determination Theory (SDT). According to SDT, individuals are motivated to satisfy their needs for autonomy, competence, and relatedness (Deci & Ryan, 2000). FOMO emerges in response to unmet psychological needs, prompting individuals to seek external validation and a sense of belonging via digital platforms (Przybylski et al., 2013). In the context of online shopping, purchasing products during exclusive offers or limited-time sales may momentarily fulfill these psychological needs, offering a fleeting sense of competence (I secured a great deal), autonomy (I made an independent choice), and relatedness (I am keeping up with others).

This study aims to examine the relationship between FOMO and compulsive buying behavior in the context of online shopping among young adults. Through a correlational design, the research explores how FOMO, urgency, and shopping motivation are associated in digital purchasing situations. The findings contribute to a better understanding of how digital environments may reinforce psychological vulnerabilities that influence consumer behavior.

2. Literature Review

Young adulthood (ages 18–25), as defined by Arnett (2004), is a sensitive developmental stage marked by identity exploration, psychological fluctuation, emotional vulnerability, and self-focus. These characteristics make emerging adults especially sensitive to external cues related to opportunity or exclusion. Thus, their shopping behaviors are not merely economic choices but are deeply rooted in their psychosocial development processes (Arnett et al., 2014; Rocha et al., 2023; Zhang et al., 2018). Digital commerce platforms, by mimicking social media dynamics, effectively capitalize on this developmental vulnerability, reinforcing the salience of FOMO in purchase motivations (Djafarova & Bowes, 2021).

Despite the growing academic interest in FOMO, relatively few studies have systematically examined the specific ways in which it shapes online shopping behavior, particularly among emerging adults. Even fewer have investigated the cognitive processes underlying these behaviors, such as cognitive distortions that may exacerbate impulsive or compulsive consumption patterns. Cognitive distortions, understood as systematic errors in reasoning (Beck, 1976), may play a crucial role in how young consumers reinterpret or misjudge digital marketing messages, thus influencing their susceptibility to FOMO-laden tactics.

2.1. Theoretical Foundations of FOMO

A central contribution to the theoretical grounding of FOMO was made by Przybylski et al. (2013), who defined FOMO as “a pervasive apprehension that others might be having rewarding experiences from which one is absent” (Przybylski et al., 2013, p. 1841). Their empirical studies demonstrated that individuals with high FOMO scores were more likely to engage excessively with social networking platforms, manifesting compulsive behaviors in their attempts to remain socially connected. Przybylski et al.’s model positions FOMO not merely as an occasional emotion but a stable personality-related factor that shapes online engagement patterns.

From a psychological perspective, the mechanisms underlying FOMO can be also interpreted through the lens of Self-Determination Theory (Deci & Ryan, 2000). According to SDT, humans possess innate needs for autonomy, competence, and relatedness. FOMO arises when these psychological needs are thwarted, particularly the need for relatedness. Digital environments, especially social media and e-commerce platforms, create a context where constant exposure to others’ experiences can intensify perceptions of exclusion, thereby fueling FOMO (Przybylski et al., 2013). Individuals seek to restore a sense of belonging and self-worth through behaviors that reconnect them with the perceived sources of opportunity—be it social participation or consumption of desirable goods. Moreover, FOMO is not limited to social domains; it has clear implications for consumer behavior. The intersection of FOMO with marketing practices has created a psychological landscape wherein consumers fear missing not only social events but also product launches, limited-time offers, and exclusive deals. The emotional arousal induced by such stimuli can lower cognitive defenses, making consumers more susceptible to impulsive and sometimes compulsive buying patterns (Hodkinson, 2019).

Thus, FOMO can be understood as both a state triggered by environmental cues (e.g., social media posts, flash sales) and a trait reflecting an individual’s chronic sensitivity to perceived social and experiential exclusion. Its duality—situationally induced yet trait-reinforced—makes it a very effective driver in the context of digital commerce, where curated content and scarcity tactics are strategically deployed to activate consumer vulnerabilities.

2.2. FOMO and Consumer Behavior: Impulse Buying and Compulsive Shopping

The intersection between FOMO and consumer behavior has become a central point for researchers aiming to understand how digital environments alter traditional purchasing patterns. FOMO, originally associated with social interaction and the need of inclusion and belonging, has gained fertile ground in recent years within e-commerce ecosystems, where marketing strategies use social proof and artificial scarcity to trigger consumer attention and prompt immediate action (Hodkinson, 2019; Dittmar, 2005; Dholakia, 2000). Contemporary marketing campaigns often blur the boundaries between social influence and commercial persuasion, using tactics such as “limited-time offers,” “only a few items left,” and “most popular right now” labels to instill urgency. These messages are carefully designed to activate FOMO, encouraging consumers to make purchases without careful consideration or reflective judgment. In this sense, FOMO acts as a psychological trigger that overrides rational evaluation in favor of immediate psychological and emotional satisfaction (Good & Hyman, 2020; Djafarova & Bowes, 2021; Zanjabila et al., 2023).

Previous studies suggest that individuals with high FOMO are more susceptible to time-sensitive marketing strategies, as they are driven by a perceived need to act quickly in order to avoid missing out on opportunities (Milyavskaya et al., 2018; Rozgonjuk et al., 2020). The compulsive aspect of FOMO-driven consumption behavior is particularly observed among young adults (Tandon et al., 2021). Research suggests that individuals experiencing high levels of FOMO are more likely to engage in impulse buying, characterized by sudden, unplanned purchases made with little or no regard for consequences (Good & Hyman, 2020; Bläse et al., 2023; Puspitasari et al., 2025). In addition, Zhang et al. (2018) demonstrate that FOMO not only stimulates impulsive buying but can also act as a catalyst for the escalation of compulsive buying behaviors over time.

It is important to distinguish between impulse buying—a common, often benign consumer behavior—and compulsive buying, which entails repetitive, uncontrollable purchasing that leads to psychological distress and impairments. Impulsivity reflects short-term, spontaneous reactions, whereas compulsivity reflects repeated, poorly controlled behavior over time (Dittmar, 2005; Black, 2007; Elhai et al., 2016; Bläse et al., 2023). In digital commerce environments, where users are incessantly bombarded with FOMO-inducing stimuli, the risk of escalation from impulsive to compulsive behavior is heightened. As Elhai et al. (2016) note, the same psychological mechanisms that underlie problematic smartphone use—such as deficits in emotional regulation and cognitive distortions—may also explain compulsive online consumer behaviors, such as compulsive buying.

In this context, the highly curated nature of e-commerce platforms, which constantly present “best-sellers,” “just dropped” items, and “friends also bought” suggestions, create a digital social environment where consumer actions are framed as expressions of social inclusion and belonging. Purchasing a product is no longer a solitary transaction; it is positioned as an affirmation of one’s inclusion within desirable social trends. Thus, for young adults, especially those navigating identity formation, social and peer acceptance, FOMO-induced shopping may serve deeper psychosocial functions (Arnett, 2004; Hodkinson, 2019; Tandon et al., 2021).

As prior studies have suggested, individuals may underestimate or fail to recognize the influence that FOMO employs on their behavior. While self-reported assessments often downplay the role of FOMO, behavioral observations and deeper cognitive analyses reveal its pervasive impact (Good & Hyman, 2020; Przybylski et al., 2013; Elhai et al., 2016). This discrepancy between perceived and actual influences on consumer behavior constitutes a significant avenue for further empirical investigation and will be further considered in future research.

2.3. Push Notifications and Behavioral Influence in E-Commerce

At the intersection of mobile technology and e-commerce strategies, push notifications have become an omnipresent tool for retailers to shift and retain attention and also to influence buying behavior. These messages sent directly to users’ devices—from discount alerts in shopping apps to pop-ups in the browser—aim at triggering immediate responses. Research suggests that push information strategies in e-commerce rely on a mix of emotional and cognitive mechanisms that shape purchase decisions. In other words, the effectiveness of a notification depends both on its ability to generate emotions (such as excitement or fear of missing out on an offer) and on how the recipient rationally evaluates the usefulness of the offer and the credibility of the source (Joston, 2025). The influence of FOMO on receptiveness to digital cues such as push notifications has also been documented, with research indicating that individuals with higher FOMO levels are more likely to respond impulsively to marketing notifications (Wohllebe et al., 2021; Djafarova & Bowes, 2021; Hodkinson, 2019).

Hodkinson (2019) also suggests that such externally induced FOMO-based urgency can lead to impulsive purchases by consumers, even when the purchase was not originally planned or needed. Studies underlined that individuals with higher impulsivity are more likely to engage in frequent online shopping due to reduced self-regulatory capacities and sensitivity to immediate rewards (Rook & Fisher, 1995; Verplanken & Herabadi, 2001).

Push notifications are known to prompt immediate consumer action and can increase shopping frequency by reinforcing digital engagement patterns (Wohllebe et al., 2021; Djafarova & Bowes, 2021; Puspitasari et al., 2025). Alongside this, notifications also trigger the positive side of emotions: anticipated pleasure. A personalized offer or a surprise reward conveyed through a notification can arouse the buyer’s excitement, anticipating the satisfaction of acquiring the desired product or price advantage (Dholakia, 2000; Djafarova & Bowes, 2021). Hence, against the backdrop of the fear of missing the opportunity, the attractiveness of the promise of reward is added, both of which increase the immediate drive to buy. However, the literature also notes another important aspect: unplanned purchases generated under the FOMO impulse can subsequently lead to feelings of regret and dissatisfaction (Hodkinson, 2019), suggesting a potential emotional cost of these tactics.

There are several common categories of push notifications used in online commerce, each with specific behavioral purposes (Özdemir et al., 2025; Wohllebe et al., 2021). One common type is the discount notification—sending a coupon or promo code designed to produce an immediate sense of winning and to trigger an impulse purchase. Another type targets scarcity: notifications such as “limited offer” or messages such as “last pieces in stock” exploit urgency and FOMO to hasten the purchase decision (Hodkinson, 2019; Barton et al., 2022; Hamilton et al., 2018). There are also availability-focused notifications, such as back-in-stock alerts for out-of-stock products, which rather capitalize on the usefulness of the information—letting the shopper know that they have the chance to buy a desired item again (Joston, 2025). Finally, loyalty reward notifications (e.g., messages about loyalty points earned, gifts, vouchers or exclusive offers for loyal customers) aim to strengthen the relationship with the customer and encourage them to return for new purchases (Hodkinson, 2019; Dholakia, 2000; Özdemir et al., 2025). Although different in form, all these notifications share the same fundamental objective: influencing purchase behavior by combining psychological and emotional appeal with practicality, all of which support FOMO-driven consumer behavior.

The effect of push notifications on young adults is a crucial aspect for understanding purchase motivation in the digital age. This demographic group, being educated in a tech-forward environment, is among the most highly exposed to such marketing strategies due to their avid use of mobile technology. The literature suggests that young adults simultaneously exhibit a high susceptibility to FOMO and a heightened awareness of intrusive marketing tactics (Bidargaddi et al., 2018; Hodkinson, 2019; Wohllebe, 2020). Consequently, urgency cues such as scarcity indicators, countdown timers, or low-stock messages exert psychological pressure that increases both purchase intent and frequency (Wohllebe, 2020; Bidargaddi et al., 2018; Tandon et al., 2021; Fahad et al., 2025).

2.4. Cognitive Distortions in Digital Consumption Contexts

Cognitive distortions are defined as systematic errors in thinking that lead to distorted interpretations of reality (Beck, 1976). In other words, they are irrational and exaggerated thoughts or beliefs that individuals believe to be true, even though their objective evaluation would show otherwise. Aron T. Beck described how depressed or anxious individuals often interpret experiences through distorted lenses—for example, catastrophizing (expecting the worst possible outcome) or black-and-white thinking (viewing situations in all-or-nothing terms). David D. Burns later built on Beck’s work to catalog a taxonomy of common cognitive distortions, enumerating about ten recurrent thinking errors (Burns, 1980). These include patterns such as emotional reasoning (believing that feelings reflect facts, e.g., “I feel anxious, therefore something bad is happening”) and overgeneralization (drawing broad negative conclusions from a single event). Burn’s taxonomy remains, with minor variations, a cornerstone in cognitive–behavioral therapy and research for identifying how thoughts can deviate from reality. Researchers have even formalized measures to assess an individual’s propensity for such distorted thinking—for instance, the Cognitive Distortions Scale (Covin et al., 2011) quantifies ten types of cognitive errors (like mind-reading, catastrophizing, and all-or-nothing thinking) in everyday scenarios. This rich theoretical foundation provides the lens through which we examine digital consumption behaviors in current research.

Research in the digital age has begun to link such distorted cognition with problematic online behaviors. The concept of fear of missing out (FOMO), for instance, has a strong cognitive component and illustrates distortions in action. FOMO involves the irrational belief that others are continually having rewarding experiences from which one is absent—essentially a combination of catastrophizing (“missing out will ruin my happiness”) and fortune-telling (assuming, without firm evidence, that one will be left out of rewarding loops). Research demonstrates that among young adults, higher level of anxiety and depression symptoms were associated with more severe and almost problematic use of smartphones, and this relationship was mediated by FOMO (Covin et al., 2011; Horváth & Adıgüzel, 2018; Elhai et al., 2020; Wohllebe et al., 2021; Özdemir et al., 2025). In other words, distorted thoughts about missing out and needing to stay constantly connected contribute to compulsive digital consumption (Elhai et al., 2020; Han, 2020). This finding underscores that cognitive distortions are not only relevant in clinical disorders but also play a role in everyday maladaptive behaviors like excessive social media engagement and smartphone addiction.

Given this backdrop, the current research adopts the Beck and Burns taxonomy of cognitive distortions as an analytical tool for examining open-ended survey responses about digital consumption. The decision to use this taxonomy is grounded in its strong theoretical pedigree and practical utility. First, the Beck–Burns taxonomy is comprehensive: it captures a wide spectrum of thinking errors (Burns, 1980; Covin et al., 2011), enabling us to systematically categorize the diverse thoughts and behaviors the participants might report. Prior applications of this taxonomy have shown it can be meaningfully applied beyond therapy sessions. Covin et al. (2011) demonstrated that even in a non-clinical sample of university students, the tendency to think in distorted ways can be measured reliably. This supports the approach to analyze everyday communications (like survey comments) for cognitive distortions as such distortions are not only clinical phenomena but occur in the general population’s thought patterns.

2.5. Present Study—Theoretical Justification of Hypotheses

Research literature has established a connection between FOMO and impulsive actions especially in psychology and cognitive sciences (Hodkinson, 2019; Przybylski et al., 2013; Good & Hyman, 2020; Tandon et al., 2021; Bläse et al., 2023). We identified, however, that less is known about the specific pathways through which FOMO influences shopping motivation and the escalation toward compulsive buying, especially in young adult consumers. Building on the existing literature and the objectives of this study, the following hypotheses are formulated to explore the relationships between psychological variables and online consumer behavior. The fear of missing out (FOMO) has been associated with increased susceptibility to external stimuli, particularly in digital environments (Przybylski et al., 2013; Milyavskaya et al., 2018). Prior research also indicates that FOMO can intensify the urgency of decision-making and amplify responsiveness to persuasive cues such as push notifications (Wohllebe et al., 2021; Djafarova & Bowes, 2021; Hodkinson, 2019), while urgency perception and mobile app notifications have been recognized as triggers for impulsive or compulsive behaviors in online retail settings (Özdemir et al., 2025; Wohllebe et al., 2021). These insights support a correlational exploration between psychological traits and consumer responses in digital commerce contexts. Based on this literature review, the following research questions and hypotheses were formulated:

H1. 

Fear of Missing Out (FOMO) is positively correlated with impulsive buying behavior.

H2. 

FOMO is positively correlated with perceived urgency in online shopping contexts.

H3. 

FOMO is positively correlated with the perceived influence of push notifications.

H4. 

Impulsivity is positively correlated with online purchase frequency.

H5. 

Urgency perception is positively correlated with online purchase frequency.

H6. 

Notification influence is positively correlated with online purchase frequency.

These hypotheses were tested using the Pearson correlation analysis, which is appropriate given the non-experimental, cross-sectional nature of the data. While the conceptual framework outlines theoretical links between variables, the study does not infer causality. Instead, the goal is to examine whether statistically significant associations exist between psychological constructs (e.g., FOMO, impulsivity) and behavioral outcomes (e.g., purchase frequency). The correlational approach is consistent with exploratory studies in digital consumer studies, where identifying such associations provides a basis for future experimental validation (Djafarova & Bowes, 2021; Özdemir et al., 2025; Wohllebe et al., 2021). In this sense, the model serves as a diagnostic tool to map potential psychological predictors of online buying patterns, without assuming directional effects.

3. Methodology

This study employed a mixed-method research design to investigate how the fear of missing out (FOMO) influences shopping motivation and compulsive buying tendencies among young adults. A combined approach was essential to capture both the participants’ explicit self-perceptions and the implicit cognitive mechanisms embedded in their open-ended reflections. The aim was not merely to quantify FOMO-related behaviors, but to explore the discursive and cognitive dissonances that often emerge between declared attitudes and actual thought patterns—particularly those shaped by emotional and psychological biases in digital consumption.

The research was designed as a cross-sectional survey, conducted online, and comprised two main sections: a quantitative component using Likert-scale items and a qualitative component with open-ended questions. The questionnaire was distributed between October 2024 and January 2025.

3.1. Participants and Procedure

Participants’ sociodemographic and academic profiles are presented in

Table 1. Demographic distribution of respondents.

Age	Frequency	Percentage (%)
19	95	36.82%
18	44	17.05%
21	39	15.11%
20	30	11.62%
22	16	6.20%
23+	34	13.17%
Gender
Female	170	65.89%
Male	76	29.54%
Non-binary	3	1.16%
Not declared	9	3.48%
Area of residence
Urban	184	71.31%
Rural	74	28.68%

and

Table 2. Academic profile of the participants (n = 258).

Specialization	Frequency	Percentage (%)
Digital Media (BA)	95	36.82%
Advertising (BA)	58	22.48%
Communication and Public Relations (BA)	57	22.09%
Journalism (BA)	31	12.01%
Master’s in Mass Media and Public Relations (MA)	17	6.58%
Study level
Bachelor’s	241	93.41%
Master’s	17	6.58%
Year of study
1st Year (BA)	137	53.10%
2nd Year (BA)	104	40.31%
Master level (MA)	17	6.58%

, respectively. These tables include age, gender, residence, study level, year of study, and field of specialization.

The sample consisted of 258 Romanian graduate and undergraduate students, primarily enrolled in Communication Sciences programs, with a concentration in Advertising and Digital Media. Most respondents had urban residence, aged between 19 and 23 years old, with 65.89% female respondents (non-stratified sample) as illustrated in Table 1.

Most participants were enrolled in undergraduate programs (93.41%), while 6.58% were master’s students. Regarding the year of study, first-year students were the most represented group (53.10%). Participant academic profile is summarized in Table 2.

The decision to sample undergraduate and graduate students from West University of Timișoara (n = 258) was guided by both logistical and theoretical considerations. Practically, university students represented a cohesive population, enabling efficient and reliable data collection within a controlled academic environment. Developmentally, students—positioned within the young adult life stage—are particularly susceptible to digital marketing pressures, social comparison, and impulsive consumer behavior as the literature review shows (Tandon et al., 2021; Bläse et al., 2023; Djafarova & Bowes, 2021; Mert & Tengilimoğlu, 2023). By highlighting these issues in young adults, the research aligns with pressing societal concerns, such as understanding psychological mechanisms (like distorted thinking) that may underline problems such as smartphone overuse, social media anxiety, or impulsive online buying in emerging adulthood. The study combined both quantitative and qualitative methods, where depth of insight—particularly in the analysis of cognitive distortions—was prioritized over representativeness.

Data collection was conducted via an online survey platform. Respondents were informed about the voluntary nature of the study and the academic purpose behind the research. They were assured of complete anonymity and confidentiality and were explicitly asked to respond as sincerely as possible. Informed consent was obtained prior to participation. The average time to complete the questionnaire was approximately 10–12 min.

3.2. Instruments

The quantitative section of the questionnaire included an adapted version of Przybylski et al.’s (2013) FOMO Scale, tailored to reflect digital shopping contexts. The original 10-item scale was reframed to evaluate shopping-related FOMO manifestations, statements such as “I fear missing discounts that others might take advantage of” or “When I see others talking about what they bought, I feel left out.” All items were rated on a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). The questionnaire also included items evaluating the frequency of online shopping and the preferred device used for purchases (such as smartphones or desktop computers). The questionnaire also included items adapted from Rook and Fisher’s (1995) framework to measure impulsive purchasing behavior. Furthermore, participants were asked to evaluate their post-purchase satisfaction, with specific attention to app-based rewards and time-limited promotions. Finally, additional scales measured how urgency-based messages, reward incentives, and scarcity cues correlate with shopping decisions.

The qualitative section includes four open-ended questions designed to stimulate self-reflective insights into the participants’ motivations for shopping, their reactions to e-commerce push notifications, and their personal evaluation of how such stimuli affect their purchase decisions. These prompts invited respondents to describe, in their own words, how notifications, limited-time offers, and social comparison influenced their shopping decisions, perceived sense of urgency, and general emotional state. We applied thematic analysis and cognitive distortion coding for an in-depth analysis.

3.3. Data Analysis

The analysis proceeded in two stages. First, quantitative data from the closed-ended items were processed using descriptive statistics (means, standard deviations), followed by correlational analysis to examine the relationship between FOMO scores, impulsivity, notification influence, and compulsive buying tendencies. Participants responded to a Likert-scale questionnaire evaluating several psychological constructs, including: a 10-item FOMO scale adapted from Przybylski et al. (2013), 6 items assessing impulsive/compulsive buying tendency (inspired by Rook & Fisher, 1995), 5 items on post-purchase satisfaction, 6 items on the influence of notifications, 6 items on perceived urgency, and an ordinal item indicating the number of online purchases in the last month. All Likert items were scored 1 to 5 (with higher scores indicating greater agreement or frequency), and composite scores were computed by averaging item responses for each construct. Below, we report the core findings, with emphasis on FOMO levels and their associations with shopping-related motivations and behaviors.

The qualitative analysis followed a three-step interpretive procedure. First, a sentiment analysis was conducted to evaluate the emotional valence of each response, categorizing statements as positive, neutral, or negative based on evaluative language and contextual framing. Responses expressing satisfaction, convenience, or enjoyment were coded as positive; expressions of dissatisfaction or frustration were coded as negative; and responses with mixed or descriptive tones were marked as neutral.

Second, thematic analysis was conducted to identify latent patterns of meaning (Braun & Clarke, 2006). The open-ended responses were reviewed in full to ensure contextual familiarity, and then systematically coded using both descriptive and interpretive strategies. Particular attention was paid to ambivalent expressions and implicit contradictions, between stated attitudes and actual described behaviors—phenomena that are particularly relevant to exploring cognitive–affective dissonance and vulnerability in digital consumer behavior.

Third, we examined responses through the lens of cognitive distortion theory, using the taxonomy developed by Beck (1976) and Burns (1980). Responses were classified according to common cognitive distortions, such as black-and-white thinking, catastrophizing, or fortune-telling. Particular attention was also paid to FOMO-related language (e.g., urgency, scarcity, or anticipatory regret), as these provide insight into irrational or emotionally driven consumption triggers.

All coding was performed manually and iteratively, with internal cross-checking to ensure consistency and analytical saturation. Frequency counts were calculated for each thematic code to enable comparative interpretations.

4. Results

4.1. Quantitative Analyses—Descriptive Statistics for Main Psychological Constructs

The following subsection presents the results of hypothesis testing (H1–H6), using Pearson correlation coefficients to assess the relationships between psychological constructs related to FOMO, urgency, notifications, and impulsive buying.

Composite scores were calculated for each psychological construct by averaging the relevant Likert-scale items (ranging from 1 = strongly disagree to 5 = strongly agree). The results indicate moderate levels of impulsivity (M = 2.37), urgency (M = 2.07), FOMO (M = 1.98), and notification influence (M = 1.87). Descriptive statistics were calculated for each psychological construct based on the valid responses (n = 258). Mean scores and standard deviations are presented in

Table 3. Descriptive statistics for main psychological constructs.

Construct	Mean	Standard Deviation	Minimum	Maximum
FOMO	1.98	0.79	1.00	4.67
Impulsivity	2.37	0.87	1.00	5.00
Notification	1.87	0.80	1.00	4.44
Urgency	2.07	0.86	1.00	5.00

.

4.1.1. Correlational Analysis Between Psychological Constructs

Pearson correlation coefficients were calculated between FOMO, impulsivity, urgency, and notification-related perceptions to test hypotheses H1–H3. The results indicate significant positive associations between all constructs. FOMO was strongly correlated with notification influence (r = 0.87) and urgency (r = 0.86), and moderately with impulsivity (r = 0.38). These results support H1, H2, and H3. The full correlation matrix is presented in

Table 4. Pearson correlation matrix among psychological constructs (H1–H3).

	FOMO	Impulsivity	Notification	Urgency
FOMO	1.00	0.38	0.87	0.86
Impulsivity	0.38	1.00	0.40	0.46
Notification	0.87	0.40	1.00	0.79
Urgency	0.86	0.46	0.79	1.00

.

Interpretatively, the high correlation between FOMO and both urgency and notification suggests conceptual overlap and emotional reactivity. The moderate correlation with impulsivity aligns with previous findings showing that FOMO can reduce self-regulatory capacities and increase susceptibility to unplanned purchases (Milyavskaya et al., 2018; Elhai et al., 2021).

4.1.2. Correlational Analysis Between Psychological Constructs and Online Shopping Frequency

To test hypotheses H4 through H6, participants’ self-reported frequency of online shopping (ordinal scale: from “never”—0 to “daily”—5) was correlated with the four psychological constructs. All correlations were statistically significant and positive. Notification influence had the strongest correlation with shopping frequency (r = 0.42), followed by urgency (r = 0.36), FOMO (r = 0.35), and impulsivity (r = 0.32). These findings support hypotheses H4–H6 and suggest that emotional and attentional dimensions play a role in digital shopping behaviors. Results are presented in

Table 5. Pearson correlations between psychological constructs and online shopping frequency (H4–H6).

Construct	Correlation with Online Shopping Frequency
FOMO	0.35
Impulsivity	0.32
Notification	0.42
Urgency	0.36

.

Although no mediation analysis was conducted, the relative strength of associations suggests that urgency and notification influence may act as intermediary mechanisms between FOMO and shopping frequency. This remains a hypothesis for future research.

4.2. Qualitative Analysis

4.2.1. Integrated Interpretation of Open-Ended Responses

A general sentiment analysis across the four open question responses was conducted with the help of the Azure Machine learning app, as shown in

Table 6. Sentiment analysis across the four open-ended questions responses.

Sentiment	Observed Range (Approx.)
Positive	30–50%
Neutral	30–40%
Negative	20–35%

. The analysis shows that, although many participants describe positive experiences, particularly in relation to securing deals or completing purchases, negative or conflicted sentiments appear prominently in experiences involving regret for purchasing, perceived pressure, or lack of control. These affective ambivalences underline the emotional volatility of FOMO-driven digital commerce.

In the second phase, research focused on common themes and argumentative structures used by respondents with the aim of highlighting patterns of behavior and argumentation. The following

Table 7. Dominant themes across all open-ended questions.

Core Theme	Observed Patterns
Defensive Neutrality and Controlled Self-Image	Respondents frequently claim to be uninfluenced (e.g., “Nu mă afectează”—I’m not affected), yet describe behaviors (e.g., checking apps, reacting to discounts) that imply subtle or indirect influence.
Commodification of Emotion	Positive feelings such as satisfaction, joy, or relief are consistently tied to discounted purchases (“M-am bucurat”, “Am fost mulțumit(ă)”), revealing emotional reasoning patterns.
Contradictory Self-Perceptions (Emotional Bifurcation)	Many present themselves as rational decision-makers (“Nu cumpăr impulsiv”—I do not buy impulsively), while simultaneously reporting actions indicative of FOMO or compulsivity (“Am cumpărat chiar dacă nu aveam nevoie”—I bought it although I did not need it).
Lack of Coping Strategies	The majority of participants admitted to having no real strategy to manage impulsive buying urges, relying instead on intuition, momentary avoidance, or denial.

presents the most common themes and patterns identified.

Consumer Motivations for Online Shopping

The analysis of Question 1 of n = 258 responses highlights that convenience and efficiency are the main drivers of online shopping. “Convenience/comfort” (21.32%) and “Time-saving/fast delivery” (20.93%) together account for over 42% of motivations, showing that consumers prioritize ease and speed (see

Table 8. Key motivations for choosing online shopping.

Core Motives	Frequency	Percentage (%)
Time-saving/fast delivery	54	20.93
Convenience/comfort	55	21.32
Trends	6	2.33
Discounts	35	13.57
Accessibility	41	15.89
Product variety	46	17.83
Well-being	12	4.65

).

Other key factors include “Accessibility” (15.89%) and “Discounts” (13.57%), emphasizing the importance of easy access and cost savings. In contrast, “Trends” (2.33%) and “Well-being” were less significant, indicating that emotional or lifestyle-related reasons are less influential in the decision to shop online.

Emotional Bifurcation and Dissonance

The qualitative coding of n = 258 open-ended responses regarding temporary discounts in Question 3 revealed several recurring emotional patterns. Notably, 9.24% of participants explicitly described impulsive purchases, often accompanied by affective triggers such as urgency or excitement (e.g., “Am simțit că trebuie să cumpăr atunci”—I felt compelled to purchase immediately; “M-am bucurat de oferte si am cumpărat imediat”—I was happy about the offer and I bought them immediately). The responses presented in

Table 9. Thematic coding frequencies for responses on temporary discount experiences.

Theme	Frequency	Percentage (%)
Ambiguous/unclear	84	33.73%
Clear satisfaction	71	28.51%
Impulsive purchases	23	9.24%
Neutral experience	19	7.63%
Initially positive, then regret (emotional bifurcation)	14	5.62%

are consistent with previous correlational findings and reinforce the idea that FOMO operates as an emotional amplifier in online shopping contexts for the targeted group.

Of particular theoretical interest is the “emotional bifurcation” theme, observed in 5.62% of responses. This refers to cases in which respondents initially express enthusiasm for a limited-time offer (e.g., “M-am bucurat să prind oferta…”—I was happy to catch the deal), followed by a reflective regret or admission of unnecessary spending (e.g., “…dar nu aveam neapărat nevoie de ea”—…but I didn’t really need it). These emotional fluctuations illustrate a cognitively dissonant pattern of consumption, beginning with gratification, followed by ambivalence, characteristic of FOMO-driven behaviors.

The predominance of ambiguous or unclear responses (33.73%) may reflect a low level of emotional introspection or difficulties in articulating inner contradictions. As discussed in Section 4.2.1, many participants claim rational control while simultaneously reporting behaviors indicative of impulsivity or affective dissonance.

Defensive Neutrality and Controlled Self-Image

In Question 2 (on the influence of notifications), participants expressed neutral or dismissive attitudes (e.g., “nu mă influențează”—they don’t influence me), yet describe behaviors that contradict this stance in other questions (e.g., opening apps or checking offers daily). This defensiveness, framed as autonomy, suggests that young adults attempt to preserve a rational self-image, even when their behaviors indicate susceptibility to platform triggers.

Of the 258 participants who responded to this item, as discussed in

Table 10. Thematic coding frequencies for the influence of notifications. (n = 258 open-ended responses).

Thematic Code	Frequency	Percentage (%)
Defensive neutrality/controlled self-image	82	33.33%
Disengagement/disinterest	71	28.86%
Influence acknowledged (conscious or direct)	57	23.17%
Unclear or minimal response	16	6.50%
Passive exposure/indirect impact	13	5.28%

, one third (33.3%) exhibited defensive neutrality, denying influence, yet implicitly revealing behaviors that contradict their stated neutrality (e.g., checking notifications daily). This indicates affective dissonance and an attempt to preserve a cognitively controlled self-image. Another 28.9% explicitly rejected any influence (disengagement), whereas 23.2% acknowledged some degree of impact, either behaviorally or reflectively. These patterns support the premise that narratives of autonomy may obscure actual susceptibility to marketing stimuli, potentially limiting conscious self-regulation.

Emotional Resignation and Strategic Absence

The majority of respondents (72.86%), out of n = 258, according to

Table 11. Strategy categories for managing impulsive buying.

Category	Frequency	Percentage %	Examples (RO/EN)
No strategy	188	72.86	“Nu”/“No” “Nu am nicio strategie.”/“I have no strategy.” “Nu am.”/“I don’t have any.”
Critical thinking before buying	6	2.32	“Încerc să nu iau decizii impulsive, mă gândesc înainte.”/“I try not to make impulsive decisions, I think beforehand.” “Încerc să analizez dacă chiar merită cumpărarea.”/“I try to analyze whether the purchase is really worth it.”
Needs assessment	8	3.10	“Mă întreb dacă am cu adevărat nevoie de acel produs.”/“I ask myself if I really need that product.” “Îmi evaluez nevoia înainte să cumpăr.”/“I assess my need before buying.”
Planning purchases	1	0.38	“Îmi fac o listă de cumpărături și mă țin de ea.”/“I make a shopping list and stick to it.”
Ignoring notifications	5	1.93	“Nu le bag în seamă.”/“I don’t pay attention to them.” “Le ignor complet.”/“I completely ignore them.”
Budget/balance checking	2	0.77	“Verific banii din cont înainte să cumpăr.”/“I check my account balance before buying.”
Notification deactivation	5	1.93	“Am dezactivat notificările aplicației.”/“I turned off the app notifications.”
Postponing the decision	2	0.77	“Aștept o zi sau două înainte să cumpăr.”/“I wait a day or two before buying.”
Unclear answers	41	16.27	“.”, “…” “?” etc.

, reported having no strategy to manage impulsive purchases caused by notifications. Forty-one participants provided ambiguous or uninterpretable responses. Only a minority reported using critical thinking, needs assessment, or budget monitoring strategies. A small fraction of respondents reported deactivating notifications or intentionally delaying purchase decisions. These results suggest that most young adults lack structured methods to resist digital shopping stimuli and remain vulnerable to impulsive behavior.

The common themes analysis of the four open-ended questions reveals a nuanced portrait of young adult consumers navigating digital commerce environments. While participants tend to articulate rational motives and demonstrate a superficial awareness of marketing techniques, their open responses expose underlying emotional influences and cognitive vulnerabilities, especially in relation to FOMO (fear of missing out) dynamics and post-purchase satisfaction.

To further explore this preliminary conclusion, we conducted a cross-question analysis using the Beck–Burns taxonomy and thematic coding was conducted. An analysis of the participants’ answers revealed a recurring pattern: many responders state explicitly that they are not influenced by notifications from online shopping platforms (e.g., “I don’t feel influenced”, “Not at all, I usually ignore them”). Responses revealed increased exposure to persuasive digital stimuli and reported frequent shopping behaviors influenced by urgency or discount cues. The identified distortions, along with illustrative respondent quotes, are summarized in

Table 12. Distortions prevalence.

Distortion Type	Manifestations in Participant Responses	Prevalence (Responses)
Minimization/Denial	“Nu mă influențează” (It does not influence me), “Nu am nevoie de strategii” (I don’t need strategies), “(promoțiile)Mă lasă fără bani” ([promotions] “They leave me without money”)—assertions contradicted by behavior	15 (≈1.5%)
Emotional Reasoning	“Mă simt bine când cumpăr”, “Îl vreau, deci merit”—buying justified through affect; ”Era în coș și era redus, deci era logic să îl iau”—post hoc justification	~30 (≈3%)
All-or-nothing Thinking	“Ori îl cumpăr acum, ori îl pierd, (“I buy it now, or I lose it”) “In 80% din cazuri primesc cu totul altceva” (“In 80% of cases I receive something completely different”)”—loss framed as binary	56 (5.6%)
Overgeneralization	“Dacă nu îl iau acum, dispare” (“If I don’t buy it now, it disappears”), “Consider că notificările îmi influențează deciziile de achiziție prin reamintirea mesajului că alte persoane vizionează produsul, astfel făcând-mă să-l cumpăr cât mai repede.” (“I find that the notifications influence my purchase decisions by reminding me that other people are viewing the product, thus getting me to buy it as quickly as possible.”)—imagined high-stakes loss from action and inaction	6 (0.6%)
Labeling/Mislabeling	“Nu sunt genul de persoană care cumpără impulsiv.” (“I am not the kind of person who buys on impulse.”). “Nu mă las influențat de un asemenea marketing.” (“I don’t let myself be influenced by that kind of marketing.”)—using a dismissive tone; “…știu că este doar o strategie de marketing.” (“…I know it’s just a marketing strategy.”)	27 (≈2.7%)
“Should” Statements	“…trebuie să le cumpăr înainte să nu mai fie pe site-ul respectiv.” (“…I have to buy them before they’re no longer on that site.”). “…făcându-mă să simt că trebuie să acționez rapid.” (“…making me feel that I should act quickly.”); “…reduceri favorabile care nu trebuie ratate.” (“…favorable discounts that should not be missed.”)	3 (≈0.3%)

below.

Although respondents often denied being influenced, their descriptions indicated internal pressure and fear of missing out, reflected in emotionally loaded language. The recurrence of such language suggests that time-limited offers, reward-based notifications, and scarcity framing effectively target cognitive shortcuts, overriding slower, reflective processes.

5. Discussions

Positioned at the intersection of digital behavior and the psychology of communication, this research analyzed how impulsivity, urgency, and reactivity to notifications are intricately linked with FOMO in shaping online shopping tendencies among young adults. The mixed-methods framework employed allowed the identification of statistical associations and the uncovering of deeper patterns underlying these behaviors.

The quantitative component confirmed all six hypotheses for the sample group. FOMO showed robust positive correlations with impulsivity (H1), urgency perception (H2), and sensitivity to push notifications (H3), reinforcing the view that this construct acts as a core emotional amplifier in digital environments. In turn, impulsivity (H4), urgency (H5), and notification influence (H6) were significantly associated with self-reported online shopping frequency, which supports prior studies indicating that attentional reactivity and time-based pressure facilitate impulsive purchasing behaviors (Przybylski et al., 2013; Wohllebe et al., 2021; Dholakia, 2000; Bidargaddi et al., 2018).

Statistical findings indicate strong positive correlations between FOMO and both urgency perception (r = 0.86) and notification sensitivity (r = 0.87), alongside a moderate association with impulsivity (r = 0.38). These results align with previous research that frames FOMO as an emotional driver that intensifies reactivity to digital cues (Djafarova & Bowes, 2021; Özdemir et al., 2025; Hodkinson, 2019). The data also confirm that all four psychological variables positively correlate with self-reported online shopping frequency, reinforcing the idea that attentional and emotional mechanisms are central to digital purchasing behavior (Wohllebe et al., 2021; Dholakia, 2000).

The significant correlation coefficients between FOMO and urgency (r = 0.86), and between FOMO and notification sensitivity (r = 0.87), reflect the extent to which emotionally vulnerable individuals may respond to time-limited offers and platform-generated alerts as pressing triggers. These findings corroborate the existing literature on the role of digital urgency cues in enhancing consumer responsiveness while undermining rational processing (Barton et al., 2022; Zhang et al., 2018; Hamilton et al., 2018).

The qualitative data complement the statistical findings by revealing how participants cognitively processed their purchasing decisions.

Responses reflected cognitive distortions such as emotional reasoning, minimization, or dichotomous thinking (Beck, 1976; Burns, 1980; Covin et al., 2011). For instance, individuals who claimed not to be influenced by digital stimuli described behaviors suggesting otherwise—such as reacting to discounts or checking daily app alerts. This supports the view that emotional and behavioral awareness is often misaligned, particularly in high-FOMO individuals (Alt, 2015; Elhai et al., 2016; Przybylski et al., 2013; Zhang et al., 2018; Hamilton et al., 2018).

These cognitive tendencies indicate that consumer behavior is shaped not only by external digital stimuli but also by internal, emotionally charged reasoning patterns. This is in line with the previous literature identifying cognitive–affective dissonance as a key mechanism in digital overconsumption (Alt, 2015; Good & Hyman, 2020; Elhai et al., 2020).

The findings also underscore how emotional factors—such as excitement, or urgency—can increase consumers’ susceptibility to digital marketing tactics. While rational justifications were frequently invoked by participants, the emotional valence of notifications, scarcity, and discounts emerged as strong behavioral motivators in their answers—often more powerful than conscious intent. This reinforces previous conclusions that consumer decisions are shaped by affective dynamics masked as rational choices (Verplanken & Herabadi, 2001; Hamilton et al., 2018). Such findings support the broader view that digital consumption cannot be understood without accounting for underlying emotional and motivational mechanisms (Milyavskaya et al., 2018; Arnett, 2004; Arnett et al., 2014). For example, thematic coding in Question 3 indicates a notable divergence between perceived autonomy and actual responsiveness to digital stimuli. One third of respondents (33.3%) exhibited defensive neutrality, rejecting influence while describing reactive behaviors; 28.9% denied any influence, while 23.2% acknowledged being affected, either behaviorally or reflectively. These findings reflect a dissonant cognitive dynamic in the target group that may hinder conscious self-regulation (Elhai et al., 2020; Alt, 2015; Arnett et al., 2014). The prevalence of implicit susceptibility despite declarative disengagement supports the idea that autonomy narratives obscure the influence of subtle digital cues (Milyavskaya et al., 2018; Barton et al., 2022).

The qualitative findings indicate that online shopping among young adults is primarily driven by functional motives such as convenience (21.32%) and time efficiency (20.93%), while emotional or trend-based factors play a lesser role. Despite dismissing the impact of notifications, participants often displayed behaviors indicating subtle influence. Responses to time-limited discounts revealed an emotional bifurcation—initial excitement followed by regret, highlighting FOMO’s destabilizing role. Most participants lacked conscious coping strategies, relying instead on passive mechanisms like avoidance or denial. These results underscore a cognitive–emotional gap between perceived control and actual behavior in digital commerce contexts, with limited emotional regulation capacity.

From a theoretical perspective, this study supports the notion that FOMO acts as a central psychological disposition that interacts with digital affordances (e.g., notifications, time-limited offers) to amplify consumer responsiveness. While the cross-sectional design prevents causal inferences, the consistency between quantitative correlations and qualitative accounts strengthens the argument that emotional and attentional factors deserve greater focus in digital consumer research.

Practically, these results suggest that app developers, communication specialists and marketers should be aware of the psychological cost of constant connectivity, particularly for vulnerable users. While urgency-based marketing (e.g., “limited-time offer”) may be effective, it also raises ethical concerns, especially when it leads to financial overextension or emotional distress.

6. Conclusions

The findings of this study reveal a complex interplay between emotional vulnerability and digital influence mechanisms in young adults’ online shopping behavior. By employing a convergent mixed-methods design, the research confirmed six theoretically grounded hypotheses, revealing robust associations between the fear of missing out (FOMO), impulsiveness, urgency perception, notification sensitivity, and shopping frequency.

The integration of qualitative data added further depth to these findings. Participants’ open-ended responses revealed recurring cognitive distortions—such as catastrophizing, emotional reasoning, and dichotomous thinking—that magnify the psychological salience of platform-generated triggers. These insights, which align with Beck and Burns’ cognitive frameworks, reinforce the argument that compulsive digital consumption is not solely externally driven, but also shaped by distorted internal appraisals. The analysis highlighted how distorted cognitive patterns exacerbate the impact of external digital triggers. The compulsive urge to shop was shown not only to stem from platform design, but also from how individuals emotionally and cognitively interpret those cues.

These results can inform multiple domains of practice. In educational contexts, they call for improved digital literacy curricula that include emotional self-regulation. For designers, communication specialists and marketing professionals, the findings offer a framework for ethically responsible design and marketing campaigns, sensitive to their users. For researchers, the study expands the utility of cognitive distortion frameworks beyond therapeutic settings, into applied domains of digital behavior.

Limitations and Future Research

Despite its contributions, this study has several limitations. The use of a non-random sample of Romanian university students restricts the generalizability of the findings and the cross-sectional nature of the research precludes any causal interpretations. Moreover, although the observed correlations suggest potential mediation pathways (e.g., from FOMO to shopping behavior via urgency), no formal mediation or moderation models were tested in this study. Future research could address these gaps through longitudinal designs, potentially offering more robust insights into the link between emotional dispositions and digital consumer actions.

Ultimately, this research advances the understanding of how cognitive, emotional, and technological factors converge in shaping consumption in the digital age. It encourages further interdisciplinary inquiry and fosters a critical dialogue on user agency, emotional well-being, and ethical responsibility in digital commerce communication.