Cyberbullying Perpetration Among Spanish Adults: The Roles of Fear of Missing Out and Critical Thinking

Abstract

Adult cyberbullying remains understudied in Spain, where research has largely centered on adolescents. This study quantified the prevalence and behavioral profile of cyberbullying perpetration in Madrid adults and examined whether Fear of Missing Out (FoMO) and Critical Thinking (CT) differentiate aggressors from non-aggressors. A cross-sectional, community-based survey of 821 residents (51% women; M = 38.2 years, SD = 11.9) was conducted between July 2024 and January 2025. Participants completed a twelve-item dichotomous checklist of cyberbullying perpetration, a 10-item FoMO scale, and an 11-item CT scale. Group contrasts were analyzed with independent sample t-tests and effect sizes (Cohen’s d). Results indicated that nine of the twelve behaviors were endorsed by fewer than 7% of respondents; the most common offense was sending mocking or insulting messages (13.8%). Men and adults aged 18–33 accounted for most of the aggression across indicators. Perpetrators reported significantly higher FoMO and marginally lower CT than non-perpetrators. FoMO differences were largest for message forwarding, threats, and public humiliation. CT deficits were most pronounced for covert tactics such as impersonation and rumor-spreading, whereas threat perpetrators displayed CT scores comparable to non-aggressors. To conclude, interventions that combine FoMO-reduction strategies with ethically grounded CT training may be necessary to curb adult cyberbullying.

1. Introduction

Cyberbullying is a topic of major concern worldwide and has been the subject of much research [1,2]. One of the main reasons for interest in the subject lies in the fact that it constitutes a global public health problem, with serious consequences for the lives of the people involved [3,4]. Evidence indicates that this issue is associated with a wide range of mental health problems, such as depression, anxiety, and even suicidal thoughts and attempts, and that it occurs primarily in children, teenagers, and young adults [5]. In this context, some studies in other countries indicate that young adults (ages 18 to 25) perpetrated the highest levels of cyberbullying, while the prevalence was significantly lower among older cohorts, with the lowest rate among the 66+ age group [6]. Along the same lines, as people age, attacks decrease in frequency and intensity, sometimes because of an increased awareness of the inappropriateness of these behaviors [7]. A study conducted in the U.S. among adults [8] found that 41% of Americans have personally been victims of online harassment behaviors, although in some cases, these experiences were limited to more harmless behaviors. Nearly one in five Americans (18%) have been victims of particularly severe forms of online harassment, such as physical threats, harassment over an extended period, sexual harassment, or stalking. Furthermore, even though various studies on the subject have identified that men are more likely to engage in harassment behaviors [9], they also tend to show lower sensitivity towards the identification of these situations [10], as well as higher levels of need for social acceptance [11]. Specifically in Spain, a systematic review that included 21 studies since 2010 [12] found a medium prevalence of cyberbullying of 24.64% among children and adolescents. A scoping review of 172 empirical articles published between 2015 and 2024 identified only eight studies (4.7%) focusing on adult cyberbullying in Spain, compared with 54 studies (31.4%) devoted to Spanish adolescents [13]. This disparity underscores a critical knowledge gap concerning adult digital well-being in Spanish-speaking contexts.

Cyberbullying is defined here as intentional and repeated aggression, carried out through electronic devices, targeting an adult individual who finds it difficult to defend themself [14,15]. The roles involved in cyberbullying are like the existing roles in traditional bullying, these roles being cyberbully, cybervictim, and cyberwitness [16]. The behaviors associated with cyberbullying are diverse and the risk of generating moral damage to the victim is high, including, for example, the spreading of memes, mockery, humiliation, insults, extortion, threats, and harassment. Other behaviors also include spreading rumors, revealing private information, and posting photos [17]. Sometimes this harassment is carried out anonymously or by impersonation [14]. It is striking that there is little research that delves into the roles of aggressors and bystanders, since they tend to focus on the victims. However, the roles between victims and victimizers are often interchanged and need to be further explored [18]. For example, sometimes victims end up becoming bullies themselves with the aim of taking revenge on their aggressors [19]. The aggressors, on their part, may sometimes experience anxiety, remorse, and depression as they have low levels of empathy and do not identify aggression as cyberbullying when they commit them on the Internet [20]. In addition to examining psychosocial correlates, it is important to consider how cyberbullying indicators are operationalized and quantified in empirical research. For example, one study [21] developed the cyber bullying/victimization experiences questionnaire (CBVEQ) to systematically record the presence or absence of distinct aggressive online behaviors. Also, while some studies highlighted the importance of distinguishing between verbal, relational, and exclusion-based tactics when quantifying prevalence [12], others [6] employed behavior-specific checklists to estimate age- and gender-related differences in adult populations. These approaches show that the use of clearly operationalized behavioral indicators is crucial for producing reliable and comparable prevalence estimates.

Also, in the post-pandemic world, the use of social media and technological channels were consolidated as a resource of continuous use that are not exempt from being both a motive and a product of interpersonal and emotional problems [22]. In this sense, a negative aspect to cyberbullying that has resulted from the use of social media is the so-called Fear of Missing Out, hereinafter referred to as FoMO [23]. FoMO represents the desire to be permanently informed of what is going on with others on social media and the belief that others are experiencing more rewarding situations than one’s own [24,25]. Numerous recent studies suggest that FoMO is associated with highly problematic Internet and phone use [22,26], as well as mental well-being and physical health [27,28,29]. Moreover, it has been shown that people with high FoMO levels tend to pay more attention to threats, and this increases the risk of cyberbullying victimization in this group [26]. However, this attention bias toward threats may also promote aggressive behaviors online [30]. Along the same lines, cyberbullying may be an expression of antisocial compensatory behaviors resulting from an individual’s desire to avoid perceptions of social inferiority [14,31] stemming from FoMO. In an attempt to create a more positive evaluation of themselves [32], people may resort to behaviors such as interpersonal manipulation to diminish the status of others and increase their own [33]. This tendency of using social manipulation may be related to online manipulation and consequent relational aggression [34].

Nowadays, while people around the world are constantly surfing online, the ability to think, analyze, and generate ideas autonomously becomes an imperative [35]. In this sense, critical thinking becomes a fundamental tool to be able to understand and evaluate the constant flow of information and make informed and well-founded decisions regarding the origin, veracity, and intentionality of information [36]. As such, critical thinking is defined as an autonomous and systematic intellectual process that consists of identifying and analyzing information, ideas, and arguments, and then carefully evaluating them to determine their credibility, relevance, and value [2,37]. Developing citizens’ ability to think critically, analyze information, and formulate independent ideas is essential for their effective participation in contemporary society, a point highlighted in multiple works [35,38] and identified as a potential moderating factor for cyberbullying and violence on social media [39,40]. For Mishna et al. (2021) [41], within online environments such as social media platforms, messaging applications, and other digital communication spaces, critical thinking involves analyzing online behavior and communication to determine whether certain situations or events are harassment and having the ability to recognize their insidious nature. Therefore, a high level of critical thinking would help people identify and understand what is happening, a difficult task in the context of cyberbullying, where aggressions may be more subtle or covert. On the other hand, as Jenaro et al. (2018) [17] points out, critical thinking would also allow one to assess the seriousness of a specific situation and determine whether any action or intervention is required. In other words, for the author, critical thinking may help people assess the potential threat of cyberbullying by being able to analyze a situation in detail and determine whether it is a constant threat with the likelihood that it may become worse. According to Gomez Yepes et al. (2024) [2], critical thinking would also help individuals analyze the consequences of their actions, as well as options for responses to such situations, and make well-informed decisions on how to proceed (e.g., take legal action or seek professional support, among others) [17].

In the Spanish context, several studies show the importance of critical thinking to combat cyberbullying, not only from the position of the aggressor, but also as observers and victims [42]. In a study carried out on critical thinking, cyberbullying, and social skills in Spanish teenagers, it was reported that critical thinking is negatively related to cyberbullying, i.e., the higher the levels of critical thinking, the lower the propensity to perpetrate bullying and the greater the willingness to recognize and act on it. It was also observed that teenagers who have been victims of cyberbullying present lower levels of critical thinking [42]. Along the same lines, another study [43] evaluated the effect of an educational program in critical thinking to prevent bullying in Spanish high school students. The findings indicate that program participants showed higher levels of critical thinking and a decrease in supportive attitudes toward bullying compared to the control group.

Despite the growing interest in each of the variables mentioned in the present study, little is empirically known about the relationships between them in the context of cyberpsychology studies in Spain. In this regard, the choice of FoMO and critical thinking as main variables responds to three complementary theoretical and empirical reasons. First, FoMO has been identified as a relevant psychosocial trigger of impulsive and aggressive behaviors in digital environments, fostering an urgent need for social validation and heightened sensitivity to threats of exclusion [22,23,34]. Second, critical thinking functions as a potential protective factor, enabling individuals to analyze situations and consequences before acting, thus reducing the likelihood of engaging in online aggression [38,43]. Finally, the combination of high motivational vulnerability (FoMO) and low cognitive capacity for ethical appraisal (critical thinking) may represent a particularly relevant risk profile for understanding and preventing adult cyberbullying. This choice is therefore supported not only by existing evidence but also by the need to address factors that are prevalent, modifiable, and susceptible to educational intervention in the adult population.

It should be noted that the present study focuses exclusively on cyberbullying perpetration. While cyberbullying research often addresses both perpetration and victimization, our research design, measures, and analyses were specifically concerned with identifying aggressors’ characteristics and differentiating them from non-aggressors. This study adds value to the field of cyberbullying research by focusing on age-related differences in perpetration among adults, a population that has received considerably less attention compared to adolescents. By examining younger, middle-aged, and older adults, the study contributes to a more comprehensive understanding of how cyberbullying perpetration manifests across the lifespan of adults. Furthermore, it provides empirical evidence using validated measurement instruments, which strengthens the reliability of the findings. In doing so, this research addresses a significant gap in the literature and offers insights that may inform prevention and intervention strategies tailored to different age groups. Based on this framework, we formulated the following hypotheses:

H1. 

Men will demonstrate a higher prevalence of cyberbullying perpetration than women across most indicators.

H2. 

Younger adults (18–33 years) will report higher rates of cyberbullying perpetration than middle-aged (34–50 years) and older adults (51+ years).

H3. 

Adults who report higher levels of Fear of Missing Out (FoMO) will show a greater likelihood of engaging in any form of cyberbullying perpetration.

H4. 

Lower Critical Thinking (CT) scores will be associated with a higher probability of cyberbullying perpetration, particularly for behaviors that are covert or manipulative in nature (e.g., impersonation, spreading false rumors).

2. Materials and Methods

2.1. Participants

Participants were recruited via advertisements on Facebook and Instagram between July 2024 and January 2025. Eligibility criteria included (a) residing in Madrid, (b) being 18 years or older, and (c) having at least one active social media account. A total of 821 residents of Madrid participated in this study using incidental (non-probability) sampling, with 51.04% (n = 419) identifying as female and 48.96% (n = 402) identifying as male. The mean age of the participants was 38.21 (SD = 11.91) and their distribution was relatively similar across the selected age ranges: 31.06% (n = 255) younger adults (18–33 years); 35.20% (n = 289) middle-aged (34–50 years); and 33.74% (n = 277) older adults (51+ years).

2.2. Measures

Data was collected with a self-administered online questionnaire hosted on a secure web-based survey platform. The instrument comprised four sections presented in the order below:

Cyberbullying. The perpetration items from the cyberbullying dimension of the scale, created by Antoniadou et al. (2016) [21], were translated using a forward–backward procedure [44]. Two bilingual experts produced independent Spanish versions, which were synthesized and back translated by a third expert. Discrepancies were resolved by consensus. As a result, a scale of 12 items and a single dimension emerged (α = 0.84). Participants were asked whether they had engaged in each behavior, and responses were coded to distinguish perpetrators from non-perpetrators. The two response options included were as follows: 0 = No, I have never done this, and 1 = Yes, I have done this at least once.

FoMO scale. We measured FoMO with the Spanish adaptation and validation [45] of the original scale [23]. The instrument contains 10 items (e.g., “I worry that my friends may be having more rewarding experiences than me”; “It bothers me when I miss the chance to see my friends”) (α = 0.82). Responses are given on a five-point Likert scale (1 = strongly disagree to 5 = strongly agree. Higher scores indicate greater Fear of Missing Out.

Critical Thinking Disposition Scale. The Susu’s scale [46] was used, consisting of 11 items that make up a single dimension of critical thinking (e.g., “I usually try to think about the bigger picture during a discussion”; “I tend to check the credibility of the source of information before making judgments”). The internal consistency of the scale was adequate (α = 0.85), with a 5-point response format (from 1 = “Strongly disagree” to 5 = “Strongly agree”).

Socio-demographic Data Questionnaire: Information on the gender, age, self-perceived socio-economic level, and highest level of education was collected from the participants.

2.3. Procedure and Data Analysis

Adults aged 18 years or older who lived in the target region were recruited through social media posts distributed according to preset sampling quotas. After clicking the study link, prospective participants viewed an informed consent statement describing the project’s aim, the responsible institution, and the voluntary nature of participation. They were reminded that they could exit the survey at any time without consequences and were given an email address for further questions. The SPSS for Windows, version 19.0, was used for the statistical analyzes that served as the study’s development’s roadmap. Scale reliability was assessed with KR-20 for the 12 dichotomous cyberbullying items and Cronbach’s α for the FoMO and CT scales. We computed the percentage of participants who endorsed each cyberbullying indicator and cross-tabulated these percentages by gender (men vs. women) and age group (18–33, 34–50, 51+). For every cyberbullying indicator and for the global perpetration index (0 = no item endorsed, 1 = at least one item endorsed), independent-sample t-tests contrasted FoMO and CT means between perpetrators and non-perpetrators. For each test we reported means (M), standard deviations (SD), the t statistic, two-tailed p-value, and Cohen’s d as the effect-size estimate. To control the familywise error rate across 26 contrasts (13 indicators × 2 scales), Holm–Bonferroni-adjusted p-values were applied. All tests used α = 0.05 (two-tailed) after adjustment. For Hypothesis 2, the criteria recommended by Houkamau et al. (2021) [47] were followed to compare the different age ranges of the participants in relation to cyberbullying perpetration.

3. Results

Table 1. Descriptive statistics of cyberbullying perpetration, based on gender and age ranges.

	No	Yes
	%	%	Male (%)	Female (%)	Age
					18–33	34–50	51–65
1. Have you ever sent a message to someone (over the phone or the Internet) to make fun of them or say bad things about them?	86.2	13.8	66.4	33.6	39.5	32.8	27.7
2. Have you ever sent a message to someone (over the phone or the Internet), pretending to be someone else in order to treat them badly?	98.5	1.5	76.9	23.1	69.2	7.7	23.1
3. Have you ever sent a message to someone (over the phone or the Internet) to make fun of them or say bad things about them or things that are not true?	94.2	5.8	80	20	46	44	10
4. Have you ever sent photos or videos of someone to other people, without their permission, to make fun of them?	94.4	5.6	70.8	29.2	37.5	43.8	18.8
5. Have you sent or shown messages from someone to other people (over the phone or the Internet), without their permission, to make fun of them or say bad things about them or things that are not true?	93.3	6.7	82.5	17.5	49.1	40.4	10.5
6. Have you purposely sent someone a file containing a virus?	99.8	0.2	0	100	50	0	50
7. Have you taken someone else’s phone and used it without their permission to impersonate them and send messages or make calls to their friends and acquaintances?	98.5	1.5	84.6	15.4	46.2	53.8	0
8. Have you ever written or uploaded something to someone’s social media profile (e.g., Facebook, Twitter, Instagram) to make fun of them or say bad things about them?	94.9	5.1	70.5	29.5	31.8	34.1	34.1
9. Have you ever said bad things about someone on the Internet to encourage their friends to unfollow, block, or unfriend them?	97	3	76.9	23.1	53.8	30.8	15.4
10. Have you ever sent someone a message (over the phone or the Internet) to threaten them?	98	2	88.2	11.8	52.9	35.3	11.8
11. Have you ever written something about someone on the Internet that you did not want others to see?	92.8	7.2	57.4	42.6	41	32.8	26.2
12. Have you ever logged into someone’s personal account (e.g., e-mail, social media) without their permission?	90.3	9.7	60.2	39.8	37.3	37.3	25.4

summarizes the prevalence of each of the twelve cyberbullying perpetration behaviors and shows how they are distributed across gender and age groups.

A detailed analysis of twelve self-reported indicators of cyberbullying perpetration shows that aggressive online behaviors are relatively uncommon among the adults in our Madrid-based sample, yet the pattern that does emerge is both nuanced and informative. Nine of the twelve behaviors were admitted by fewer than seven percent of respondents, underscoring the generally low prevalence of digital aggression in this cohort. The most widespread offense, sending mocking or insulting messages, was acknowledged by 13.8% of participants, confirming direct verbal harassment as the principal mode of cyber-aggression. Considerably fewer adults reported breaking into someone else’s personal account without permission (9.7%) or publicly posting harmful comments about another person (7.2%). At the opposite extreme, deliberately transmitting malware (0.2%) and impersonating another individual via phone or social network profiles (1.5% each) were almost non-existent, indicating that technically sophisticated or time-intensive attacks are rare in everyday adult interactions.

Pronounced gender differences surface across almost every item. Men constitute the majority of aggressors for nearly all behaviors, accounting for 82.5% of those who shared someone’s private messages without consent and 88.2% of those who issued direct threats. These figures suggest that men are disproportionately responsible for overtly hostile or confrontational online acts.

Age adds a second layer of differentiation. Young adults between 18 and 33 years reported the highest perpetration rates on most indicators, comprising nearly 70% of impersonation cases and a clear majority of other direct attacks. This heightened involvement may correlate with their greater daily use of social media and messaging platforms, which raises both exposure to and opportunities for hostile encounters. The middle-aged group (34–50 years) occupies an intermediate position; interestingly, they surpass younger adults in the specific behavior of unauthorized sharing of personal photos or videos, perhaps reflecting life-stage stressors such as workplace disputes or contentious relationship dissolutions. Adults aged 51 years and above display the lowest perpetration rates, rarely exceeding 25% of any single behavior, which may stem from more cautious online practices or limited engagement with high-risk digital spaces.

After having performed a descriptive analysis of the various indicators of cyberbullying perpetration, we proceeded to evaluate whether there were differences in the levels of Fear of Missing Out (FoMO) and critical thinking between those who had perpetrated cyberbullying and those who had not. The analysis was conducted considering each of the cyberbullying perpetration indicators separately and as a whole (

Table 2. Differences between those who perpetrated cyberbullying and those who did not based on FoMO and critical thinking levels.

	FoMO (α = 0.82)				Critical Thinking (α = 0.85)
	No (M, SD)	Yes (M, SD)	t	d	No (M, SD)	Yes (M, SD)	t	d
CB1	2.91 (0.81)	3.10 (0.82)	−2.377 *	0.233	4.26 (0.61)	4.26 (0.52)	−0.001	n.s.
CB2	2.94 (0.81)	2.73 (1.00)	0.907	n.s.	4.27 (0.59)	3.81 (0.54)	2.718 **	0.813
CB3	2.92 (0.80)	3.17 (0.89)	−2.035 *	0.295	4.28 (0.56)	4.00 (1.00)	3.154 ***	0.345
CB4	2.93 (0.81)	3.08 (0.84)	−1.247	n.s.	4.26 (0.61)	4.18 (0.45)	0.960	n.s.
CB5	2.90 (0.81)	3.43 (0.65)	−4.834 ***	0.721	4.27 (0.60)	4.16 (0.61)	1.295	n.s.
CB6	2.94 (0.81)	2.60 (0.28)	1.689	n.s.	4.26 (0.60)	4.27 (0.64)	−0.014	n.s.
CB7	2.93 (0.81)	3.13 (1.02)	−0.844	n.s.	4.26 (0.60)	4.43 (0.34)	−1.011	n.s.
CB8	2.92 (0.80)	3.30 (0.90)	−3.069 ***	0.446	4.26 (0.61)	4.27 (0.37)	−0.144	n.s.
CB9	2.94 (0.81)	2.91 (0.84)	0.167	n.s.	4.26 (0.60)	4.38 (0.48)	−1.007	n.s.
CB10	2.92 (0.80)	3.47 (0.81)	−2.754 **	0.683	4.26 (0.61)	4.62 (0.24)	−5.762 ***	0.776
CB11	2.91 (0.80)	3.41 (0.80)	−4.743 ***	0.625	4.28 (0.59)	4.03 (0.64)	3.141 ***	0.406
CB12	2.91 (0.82)	3.20 (0.70)	−3.460 ***	0.380	4.28 (0.60)	4.10 (0.64)	2.621 **	0.290
CB Total	2.87 (0.79)	3.24 (0.84)	−4877 ***	0.453	4.29 (0.61)	4.14 (0.55)	2.772 **	0.258

***. p < 0.001; **. p < 0.01; *. p < 0.05. Note. n.s. = not significant (p ≥ 0.05); Total CB is calculated from the presence of one or more of the 12 indicators.

).

The comparison of Fear of Missing Out (FoMO) and Critical Thinking (CT) scores between adults who admitted engaging in each cyberbullying perpetration behavior and those who did not paints a coherent, albeit nuanced, picture. Perpetrators consistently reported stronger feelings of FoMO than non-perpetrators. On the global index, the average score climbed to 3.24 for aggressors, whereas it remained at 2.87 for their non-aggressive peers, a moderate, statistically significant difference. The gap widened when the offense involved forwarding private messages without permission, sending threats, or posting humiliating public comments. In each of these situations, the perpetrators’ FoMO scores were roughly two-thirds of a standard deviation higher than those of non-aggressors. By contrast, behaviors such as impersonation, unauthorized photo sharing, the dispatch of virus-laden files, or attempts at social exclusion showed little or no FoMO elevation, implying that these acts may be fueled by motives other than the anxiety of missing out.

Critical thinking followed a more complex pattern. Overall, adults who confessed to any form of cyberbullying perpetration displayed slightly poorer CT (M = 4.14) than those who refrained from such conduct (M = 4.29). The disparity was most pronounced among those who impersonated another person online, spread false insults, or posted damaging comments visible to third parties; in these groups, CT deficits are more categorical.

To further explore the relationships among the main study variables, Pearson correlation analyses were conducted between Cyberbullying perpetration, Fear of Missing Out (FoMO), Critical Thinking (CT), and relevant demographic factors (age, gender, and education level) (

Table 3. Pearson correlations among cyberbullying perpetration, FoMO, critical thinking, and demographic variables.

	1	2	3	4	5	6
1. Cyberbullying perpetration	-	0.30 **	−0.25 **	−0.12	0.03	−0.08
2. FoMO		-	−0.32 **	−0.18 *	0.24 **	0.05
3. Critical Thinking			-	0.21 **	−0.27 **	0.12
4. Age				-	−0.04	0.08
5. Gender					-	0.09
6. Educational Level						-

**. p < 0.01; *. p < 0.05.

).

As shown in Table 3, Cyberbullying perpetration was positively correlated with FoMO and negatively correlated with Critical Thinking, indicating that individuals with higher FoMO scores tend to report higher levels of cyberbullying perpetration, whereas higher Critical Thinking is associated with lower cyberbullying perpetration. Age, gender, and education level showed weaker and non-significant correlations with Cyberbullying perpetration, suggesting that the main behavioral associations are primarily linked to the psychological constructs rather than demographic factors.

4. Discussion

The present study set out to chart the landscape of cyberbullying perpetration among adults in Madrid and to explore how two psychological variables that have garnered significant attention in the international literature, Fear of Missing Out (FoMO) and Critical Thinking (CT), shape that landscape. Although cyberbullying research has flourished over the past decade, the overwhelming majority of studies have centered on adolescents; Spanish adults have remained an almost invisible population in this field [13]. By analyzing self-reports from 821 participants we furnish a more complete life-span perspective, showing that cyberbullying does not vanish in adulthood, but follows distinctive patterns that call for age-tailored explanations and interventions.

Our descriptive findings confirm the often-cited view that cyber-aggression recedes after adolescence [6], yet the picture is nuanced. Fully nine of the twelve aggressive behaviors investigated were admitted by fewer than seven percent of respondents, attesting to the rarity of adult cyberbullying. Nevertheless, rarity should not be equated with irrelevance. The most common offense -sending mocking or insulting messages- was reported by 13.8% of the sample. In Madrid, a prevalence of 13.8% equates to tens of thousands of cyberbullying incidents every month, posing risks to mental health, workplace morale, and social cohesion [5,28,29]. Moreover, the rank-order of behaviors sheds light on offender decision-making. Adults gravitate toward low-effort, low-skill tactics such as verbal insults or minor privacy invasions, presumably because these acts require little technical know-how and carry minimal legal risk compared to sophisticated intrusions like malware distribution, confessed by only 0.2%. These results are consistent with prior studies that have employed behavior-specific measurement strategies. This study is related with the recommendations of Zych et al., (2016) [12] to distinguish between multiple forms of cyber-aggression, and with Wang et al., (2019) [6], who demonstrated that disaggregating behaviors by type and demographic group can reveal nuanced prevalence patterns. This methodological convergence supports the interpretation that the low rates observed in the Madrid sample could reflect actual behavioral trends rather than measurement artifacts.

A striking gender asymmetry emerge across the dataset: men dominated the perpetrator profile for nearly every behavior. This echoes adolescent trends linking masculine norms to confrontational online conduct [11] and suggests that the social scripts encouraging men to assert status or retaliate continue into adulthood. The effect was particularly strong for threats and the unauthorized disclosure of private content, behaviors that exert direct control over a target’s sense of safety. One implication is that prevention programs should not only teach men digital etiquette but also tackle deeper cultural scripts that legitimize hostile masculinity in online spaces. Engaging male role models and fostering positive digital masculinities could be pivotal steps toward reducing these sex-based disparities. Taken together, these patterns confirm H1: men exhibit a higher prevalence of cyberbullying perpetration across most indicators.

Age emerged as a second axis of differentiation. The youngest adults (18–33 years) reported the highest perpetration frequencies, a trend that tapered steadily among the middle-aged (34–50 years) and dropped to minimal levels in the 51+ cohort. Developmental psychology attributes such gradients to maturation of impulse control and a waning concern for peer status. Another plausible factor is digital habitat: younger adults inhabit always-connected ecosystems where frictionless communication can facilitate impulsive aggression, whereas older adults often occupy more delimited digital spaces and value privacy [12]. Although our design is cross-sectional, the steep age curve underscores the urgency of targeting early adulthood in universities, vocational institutes and first-job settings before aggressive habits consolidate. This age gradient substantiates H2: younger adults (18–33) report higher rates of perpetration than middle-aged (34–50) and older adults (51+).

The psychological variables provided complementary Insight. First, the data strongly support the proposition that FoMO is a proximal motivator for adult online aggression. Perpetrators reported substantially higher FoMO than non-perpetrators, lending weight to theoretical arguments that anxiety about social exclusion fuels status-seeking and retaliatory behaviors [23,24,31]. Notably, the FoMO gap expanded for verbal and reputational offenses, implying that these tactics may serve offenders as quick corrective actions to regain perceived social equilibrium. These results support H3: higher FoMO is associated with a greater likelihood of engaging in cyberbullying perpetration.

Second, CT appeared largely protective, but in a behavior-specific manner. Lower CT characterized offenders who impersonated others or spread false rumors, strategies demanding some strategic planning yet evidently carried out without deep ethical appraisal. Conversely, aggressors who issued direct threats displayed CT levels similar to or marginally higher than non-aggressors. This paradox suggests that cognitive skill is ethically malleable: robust analytical abilities can bolster empathy and restraint, but they can also be weaponized to craft more persuasive threats if moral disengagement is high. Therefore, CT training must be coupled with ethics education rather than delivered as a value-neutral cognitive upgrade. Overall, the pattern provides qualified support for H4: lower CT is linked to higher perpetration risk, particularly for covert or manipulative behaviors (e.g., impersonation, rumor-spreading).

These insights are tempered by methodological limitations. Reliance on self-report raises social-desirability bias, perhaps underestimating true aggression rates, especially among men for whom admitting hostile acts may conflict with a self-presentational desire for respectability. In the specific case of FoMO, future research could incorporate methodologies beyond self-report to reduce response bias. For instance, experience sampling methods (ESM) or ecological momentary assessments (EMA) could capture real-time fluctuations in FoMO during daily digital interactions. Behavioral indicators, such as frequency of app switching or response latency to social media notifications, could also serve as objective proxies. Combining these approaches with self-report scales would provide a more robust and multidimensional assessment of FoMO. Second, the incidental Madrid sample invites caution in generalizing to other provinces or to rural areas where digital cultures differ. Third, the cross-sectional study precludes causal inference; longitudinal designs could clarify whether FoMO precedes aggression or whether aggressive involvement heightens FoMO through fear of retaliation. Finally, CT was measured at a trait level; future work might deploy scenario-based tasks to observe how analytical reasoning translates into real-time ethical decisions online.

Notwithstanding those caveats, the study contributes in significant ways. First, it fills a pronounced national gap by mapping adult cyberbullying in Madrid, complementing adolescent-centered research. Second, it synergizes motivational (FoMO) and cognitive (CT) frameworks, illustrating that psychological risk factors do not operate in isolation but interact with demographic forces such as age and gender.

5. Conclusions

To conclude, cyberbullying perpetration among Madrid adults is infrequent yet consequential. When incidents arise, they cluster among men and younger adults and manifest chiefly as mocking messages, private-content leaks and account intrusions, behaviors strongly linked to heightened FoMO. Critical Thinking generally shields against covert forms of aggression but proves insufficient when moral disengagement overrides ethical restraint. To curb adult cyberbullying, Madrid requires a twin-pillar approach as follows: reducing FoMO through digital well-being education and fostering ethically grounded critical thinking skills. Implementing these measures across higher education, workplace, and community settings holds promise for cultivating safer, more respectful digital spaces throughout the adult life course.

As anticipated (H1), men were more likely than women to report perpetration across most indicators, and, in keeping with developmental accounts (H2), young adults (18–33) showed higher involvement than their middle-aged and older counterparts. The motivational lens also proved informative. Consistent with H3, higher FoMO was linked to a greater likelihood of engaging in cyberbullying perpetration, particularly in verbal and reputational behaviors. Evidence for H4 also indicated that lower CT was associated with perpetration, mainly in covert or manipulative tactics, such as impersonation and rumor-spreading. By contrast, direct threats showed little attenuation with higher CT.

This study provides empirical data on adult cyberbullying perpetration in a context where such studies are scarce and often focused on adolescent populations. This contribution is enhanced by the integration of motivational (FoMO) and cognitive (critical thinking) frameworks, demonstrating that individual risk factors are not isolated drivers of behavior but operate in synergy with demographic variables such as age and gender. This multi-layered approach provides a more nuanced understanding of offender profiles and suggests targeted avenues for prevention that combine psychological intervention with demographically informed outreach.

Looking ahead, future research could expand this work by including longitudinal designs to track changes in cyberbullying perpetration over time, as well as cross-cultural comparisons to identify sociocultural moderators of FoMO, critical thinking, and demographic effects. Incorporating multi-method assessments—such as behavioral and digital trace data—could enhance the reliability of findings. Additionally, applying this motivational–cognitive–demographic framework to specific contexts, such as workplace or political cyberbullying, may offer valuable insights for targeted prevention and policy development.