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. 2020 Feb 13;27(2):234–245. doi: 10.1080/13218719.2020.1719374

Hating Adolescents Test (HAT): a preliminary development of a measure to assess hating among adolescents

Ugo Pace a, Giulio D’Urso a,✉, Carla Zappulla b
PMCID: PMC7476629  PMID: 32944124

Abstract

The phenomenon of haters is becoming common among adolescents. The aims of the present research were to evaluate the preliminary psychometric properties of the Hating Adolescents Test (HAT), an ad hoc questionnaire created to evaluate online and offline hate (Study 1), and possible risk factors connected with hate (Study 2). Participants (202 female and 200 male) of this study completed the HAT, the How I Think Questionnaire, the Buss–Perry Aggression Questionnaire, and the Penn State Worry Questionnaire. Descriptive statistics were calculated, and exploratory factor analysis and confirmatory factor analysis were applied. Preliminary data suggest how males reported higher level of hate than females. Cronbach’s alpha coefficient suggested excellent reliability of the measure. Results of this study also revealed satisfactory construct, convergent and divergent validity. Moreover, the results show a significant gender difference on the variables of the study (pathological worry and hostility aggressiveness). The mediation model suggests how hostile aggressiveness mediated the relationship between pathological worry and hate. HAT is a brief self-report questionnaire composed of 12 items scored on a 5-point Likert scale, with good psychometric properties.

Key words: cognitive distortions, hater, measurement, mediation model, pathological worry, social media, verbal aggression

Introduction

In recent years, it has become increasingly common among adolescents to use a language of hate on social media. In an age when media are wearable and the divisions between Self and Other are ruptured and widened, we must, as scholars and teachers, look for ways in which we can collaboratively cultivate modes of kinship, intimacy and criticism (Jackson, 2017; Pace, Zappulla, & Di Maggio, 2016). The online world of adolescents, especially social media, often also becomes a terrain where relationships and communicative exchanges are born that become surrogates of the real ones. Adolescents continually connected on social networks can sometimes lose the boundary between what is real and what is virtual (Palfrey & Urs, 2013). This loss of boundaries, especially for younger people, can make the forms of online hatred appear even in the real world.

However, many authors suggest how social media can be a means, easily usable by the adolescents, to spread and share hateful comments with a large audience (Cohen-Almagor, 2014; Pace, Schimmenti, Zappulla, & Di Maggio, 2013). ‘New adolescents’ – that is, digital natives, in particular – are exposed to the phenomenon of online hatred, as well as having difficulty establishing relationships based on respect for others and the sincere understanding of other persons. The episodes of hatred online and offline, such as indirect aggressiveness, could be considered the most direct precursors of cyberbullying (Wang, Iannotti, & Nansel, 2009). Hatred manifested among adolescents can therefore be considered a veritable form of verbal aggression or indirect aggressiveness, which, like all forms of aggression, has mechanisms involved in its maintenance. Moreover, the phenomenon of hatred, although mediated, has serious effects on the victims. In other words, online hate, particularly, is even easier to put in place, because the actor of verbal violence does not come into direct contact with the victim of offenses. Furthermore, publicly manifesting one’s hatred can amplify the consequences.

It should be emphasized that, in this sense, the use of mechanisms of moral disengagement is increasingly common among adolescents, leading them to reiterate the action of hatred, not caring of consequences and dehumanizing the victim (perhaps because not physically present), as well as, consequently, to minimize the gesture itself. These mechanisms are often connected to episodes of aggression, because they serve the person as mechanisms of moral defense (D’Urso, Petruccelli, Grilli, & Pace, 2019; D’Urso, Petruccelli, & Pace, 2018a; Petruccelli, Barbaranelli, et al., 2017; Petruccelli, Simonelli, et al., 2017). The literature emphasizes, in particular, how often these mechanisms are implemented to a greater extent in people who have committed episodes of aggression, violence or other deviant behaviors (e.g. D’Urso, Petruccelli, Zappulla, Costantino, & Pace, 2019).

Although there are measures that evaluate verbal aggression and the mechanisms that serve the individual to disengage from moral rules, in literature there is no tool that evaluates the phenomenon of haters among adolescents. The literature, however sparse and rarely of psychological nature, suggests how the phenomenon of hating in adolescence should be studied also in reference to aggression and hostility, in order to verify the possible overlap and the elements that distinguish them. Buss and Perry (1992) highlighted how hostility refers to feelings of suspicion and injustice to others and represents the cognitive component of aggressive conduct. Given the nature of the hostile component of aggression, it can be deduced how it may be a predisposing factor towards hateful attitudes. A recent study, indeed, suggested how hostile aggressiveness is influencing the relationships between peers and consequently adolescent well-being (Muñoz-Reyes et al., 2018; Pace, D’Urso, & Zappulla, 2018). Other studies showed how hostility is a very important factor related to internalizing problems (Asberg, 2013; Rude, Chrisman, Burton Denmark, & Maestas, 2012). These last, especially anxiety and depression, are characteristics strictly connected to pathological worry. Pathological worry, indeed, is a predominant feature of generalized anxiety disorder, and adolescents, engaged in the stages of developmental transitions, are more vulnerable to emotional difficulties related to anxiety and even depression. Therefore, the adolescents can manifest pathological worry episodes in order to face problems or to reflect on what happens to them in moments of their lives. A recent study suggested how pathological worry, in adolescence, may connected with hate among hating online and offline (Pace, Passanisi, & D’Urso, 2018b). Furthermore, other studies have found how individuals with higher levels of pathological worry manifested higher levels of frustration, anger and aggressiveness (Borders, Earleywine, & Jajodia, 2010; Peled & Moretti, 2007), and how the pathological worry often represents an expression of aggression (Lievaart, Huijding, van der Veen, Hovens, & Franken, 2017). The evolutionary and interactive model of Rutter and Garmezy (1983) allows the study and analysis of the risk factors underlying the maladaptive outcomes of adolescents, during their evolutionary trajectories. In any case, pathological worry may be configured as a risk factor also linked to aggressive behaviors and, more generally, to inadequate behaviors among peers. However, the pathological worry sometimes is characterized by hostile traits aimed to lead the individual to take a closing attitude towards the world and others, after an episode of rage. In this sense, pathological worry leads to a hostile vision of reality (Brosschot & Thayer, 2004). Indeed, in the light of these theoretical frameworks, this paper aims to identify the main psychometric characteristics of an instrument created ad hoc for Italian adolescents (Experiment 1). Experiment 2, which represents an extension of Experiment 1, aims to investigate the role of pathological worry and hostility related to the genesis of hate episodes among adolescents.

Method

Participants and procedure

A sample of 402 Caucasian adolescent participants (202 female and 200 male), with a mean age of 14.90 years (SD = 0.54), volunteered for this study. All participants attended the third classes of high school. A written informed consent was obtained for all by sending letters to their parents in order to inform them of the study. No parents objected to their child’s involvement in the study. We also obtained assent from all the adolescents involved in the study. All participants were allowed to leave the study at any time. The participants completed the questionnaires at the same time, during normal teaching activities, with the consent of the head teacher. The questionnaires were administered in December 2017. All procedures were performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Measures

Demographics questionnaire

A brief demographic survey was administered, obtaining information on age, gender, area of residence, sexual orientation, educational level, employment status and ethnicity.

How I Think Questionnaire (HITQ; Barriga & Gibbs, 1996; Barriga, Gibbs, Potter, & Liau, 2001)

The HITQ is a 54-item self-report questionnaire designed to measure self-serving cognitive distortions. Participants respond on a 6-point Likert-type scale ranging from 1 (strongly agree) to 6 (strongly disagree), with higher scores reflecting higher levels of cognitive distortions. The HITQ contains 39 items addressing self-serving cognitive distortions: Self-Centered (e.g. ‘if I really want something, it does not matter how I get it’); Blaming Others (e.g. ‘when I lose my temper, it’s because someone tries to provoke’); Minimizing/Mislabeling (e.g. ‘what do you want me to disobey the law. Everyone disobeys the law. There’s nothing bad’); and Assuming the Worst (e.g. ‘if you cannot impose on others, they will always walk all over you’). Of the remaining 15 items, eight items control for anomalous responses (ARs) that measure social desirability (e.g. ‘Sometimes I get bored’), and seven items act as positive fillers (PFs); that is, they camouflage items with a prosocial meaning (e.g. ‘When friends need you, you should be there for them’). This questionnaire has been validated in Italian by Berti, Arcuri, and Pastore (2017). In particular, for Experiment 1 we used the scales Blaming Others (α = .75), Minimizing/Mislabeling (α = .75) and Assuming the Worst (α = .78).

Buss–Perry Aggression Questionnaire (BPAQ; Buss & Perry, 1992)

The BPAQ is a questionnaire for measuring the level of aggression in adolescents and adults. This questionnaire is composed of 29 items, subdivided in four subscales: Physical Aggression (9 items); Verbal Aggression (5 items); Anger (8 items) and Hostility (8 items). For the present studies we administered the scales Hostility (e.g. ‘I am sometimes eaten up with jealousy’; α = .70) and Verbal Aggression (e.g. ‘I often find myself disagreeing with people’; α = .71). Participants were asked to answer on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly in agreement). The questionnaire was translated into Italian and then back translated by a native speaker to ensure its comparability to the English version.

Hating Adolescents Test (HAT)

The HAT is an ad hoc questionnaire for evaluating the phenomenon of haters. The questionnaire consists of 12 items: six refer to online hate (Items 1, 3, 5, 7, 9, 11, e.g. ‘Would you use, on social media, a phrase like: “You’re so ugly that when you were born, your mom sent the apology cards to everyone”?’), and the remaining six are related to offline hate (in attendance; Items 2, 4, 6, 8, 10, 12, e.g. ‘Would you use, in someone’s presence, a phrase like: “So disgusting that when you look in the mirror he turns the other way”?’). The phrases used to create items have been extrapolated from blogs and social networks frequented by adolescents.

Moreover, we hypothesized that some items could merge on a scale related to offenses, both online and in someone’s presence, on the physical aspect (Items 1, 2, 10, 11; e.g. ‘Would you use, in someone’s presence, a phrase like: “You are so ugly that the pigs see you are proud of being themselves”?’); on intellectual abilities (Items 3, 4, 5, 7; e.g. ‘Would you use, in someone’s presence, a phrase like this: “Your brain will also be heavy, but it is useless, as it is malfunctioning”?’), and finally, on a scale related to the unworthiness (Items 12, 9, 6; e.g. ‘Would you use, on social media, a phrase like: “What a misfortune, to get to know you and meet you”?’). Participants were asked to answer on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly in agreement).

Penn State Worry Questionnaire (PSWQ; Meyer, Miller, Metzger, & Borkovec, 1990)

This is a 16-item tool designed to capture the generality, excessiveness and uncontrollability of pathological worry (Fresco, Mennin, Heimberg, & Turk, 2003). Participants are required to indicate how characteristic each item is of them (e.g. I notice that I have been worrying about things). Each item is rated on a 5-point scale ranging from 1 (not at all typical) to 5 (very typical). This tool, used for Experiment 2, shows a good reliability index (alpha = .73).

Data analysis

The goal that led Experiment 1 was to verify the factorial structure of the scale. In particular, we intend to verify if, by factorial analysis, the items can saturate in two scales (haters online and haters in presence), in three scales (physical aspect, intellectual ability and unworthiness) or in one. With the aim of investigating the construct validity of the scale, two hypotheses were tested: the items built for the measurement of the ‘haters’ phenomenon are configured in the hypothetical factorial structure – that is, they measure, reliably, one or more aspects underlying of the construct. The hypothesized theoretical model is empirically confirmed and therefore there exists a statistically significant relationship between the ‘haters’ construct with the HITQ and BPAQ scales. Indeed, some aspects of concurrent validity were explored by a series of two-tailed Pearson linear correlations. A series of analyses of variance were performed for gender differences on hating scales. Moreover, the reliability of the scale was calculated using the Cronbach’s alpha coefficient (Cronbach, 1951). Statistical analyses were conducted using SPSS (Version 22).

For Experiment 2, at first, we conducted a correlation analyses among variables (pathological worry, hostility and hate); another series of analyses of variance were performed for gender differences on hostility and pathological worry. Finally, through a model of mediation, we verified how the pathological worry and the hostile component of aggressiveness influence the hate behaviors among adolescents.

Results of Experiment 1

Descriptive statistics

Means and SDs of the HAT scores are shown in Table 1. An analysis of variance with gender as the independent variable showed group differences, F(1, 396) = 18.10, p < .001; male participants (M = 2.15; SD = 0.76) obtained higher scores than females (M = 1.84; SD = 0.68). Moreover, the analysis of correlations showed a strong correlation between the two hypothesized subscales: online and offline hate (r = .78; p < .01), significant correlations between the subscale physical aspect and the subscales unworthiness (r = .688; p < .01), and intellectual abilities (r = .685; p < .01), and a significant connection between the subscale unworthiness and intellectual abilities (r = .751; p < .01).

Table 1.

Summary of means and SDs, reliability and factor loadings of the HAT.

Item M SD αiid Rit
 1. Would you use, on social media, a phrase like: ‘You’re so ugly that when you were born, your mom sent the apology cards to everyone’? 1.66 0.87 .898 .635
 2. Would you use, in someone’s presence, a phrase like: ‘You are so disgusting that when you look in the mirror he turns the other way’? 1.92 1.01 .897 .642
 3. Would you use, on social media, a phrase like: ‘When God gave intelligence to humanity, where were you?’? 2.42 1.20 .896 .675
 4. Would you use, in someone’s presence, a phrase like this: ‘your brain will also be heavy, but it is useless, since it is malfunctioning’? 2.30 1.10 .901 .699
 5. Would you use, on social media, a phrase like: ‘If all the women who reason are like you, it is better to be born headless’? 1.75 1.01 .901 559
 6. Would you use, in someone’s presence, a phrase like: ‘Try to hold your breath for five minutes thereby everyone will realize that the air we breathe is improved’? 1.93 1.06 .896 .685
 7. Would you use, on social media, a phrase like: ‘If God created ignorance, you must protest because you are the only beneficiary’? 1.89 0.98 .899 .601
 8. Would you use, in someone’s presence, a phrase like: ‘Giving yourself stupid is to outrage stupid people, then to offend you it is urgent to mint a new word’? 2.37 1.14 .896 .680
 9. Would you use, on social media, a phrase like: ‘What a misfortune, to get to know and meet you’? 2.03 1.13 .896 .668
10. Would you use, in someone’s presence, a phrase like: ‘You are so ugly that the pigs, when see you, are proud of being themselves’? 1.91 1.10 .894 .706
11. Would you use, on social media, a phrase like: ‘You are so fat that if you go to bowling people will trade you for the ball’? 1.36 0.71 .906 .444
12. Would you use, in someone’s presence, a phrase like: ‘Tonight I had a nightmare . . . I dreamed of being YOU!’? 2.35 1.19 .900 .596
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Note: N = 402. HAT = Hating Adolescents Test; αiid = α if item deleted; Rit = part–whole corrected item–total correlation (related to the total score).

The other computational analyses of variance, to test the effect of gender on the other hypothesized subscales, showed that males reported in any scales higher scores than females: physical aspect: F(1, 401) = 35.41; p < .001 with Mmales= 1.92 (SD = 0.77); Ffemales= 1.51 (SD = 0.61); intellectual abilities: F(1, 401) = 6.70; p < .05 with Mmales= 2.24 (SD = 0.83); Ffemales= 2.03 (SD = 0.82); unworthiness: F(1, 401) = 11.25; p = .001 with Mmales= 2.25 (SD = 0.93); Ffemales= 1.96 (SD = 0.85); online hate: F(1, 401) = 19.65; p < .001 with Mmales= 2.31 (SD = 0.86); Ffemales= 1.95 (SD = 0.78); offline hate: F(1, 401) = 11.59; p = .001 with Mmales= 1.97 (SD = 0.75); Ffemales= 1.73 (SD = 0.65).

Reliability

A Cronbach’s alpha coefficient of .91 for the 12 items suggested excellent reliability. Item–total correlations showed very good values, ranging from .898 (Item 1) to .900 (Item 12) (see Table 1).

Construct validity

An examination of the scree plot (Cattell, 1966), and percentage of variance accounted for, revealed the presence of one factor (see Table 2). Exploratory factor analysis (EFA) showed a factor structure with one principal dimension (eigenvalue > 1; 5.930), with 50% of total variance explained. The goodness-of-t indices showed a good t of the model to the data. Bartlett’s Test of Sphericity is statistically significant, χ2 = 2115.83 (66), p =.000, indicating significant correlations among the variables. The measure of Kaiser–Meyer–Olkin of sampling adequacy was .93. Furthermore, a confirmatory factor analysis, performed using maximum likelihood (ML), approved the existence of a single factor (eigenvalue > 1; 5.4), with 45% of total variance explained (see Table 3).

Table 2.

Factor loadings of the HAT items (using EFA).

  F1(offline and online hate)
Item 1 .707
Item 2 .717
Item 3 .739
Item 4 .759
Item 5 .631
Item 6 .751
Item 7 .669
Item 8 .742
Item 9 .730
Item 10 .770
Item 11 .518
Item 12 .664
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Note: HAT = Hating Adolescents Test; EFA = exploratory factor analysis.

Table 3.

Factor loadings of the HAT items (using ML).

  F1(offline and online hate)
Item 1 .666
Item 2 .686
Item 3 .707
Item 4 .730
Item 5 .589
Item 6 .726
Item 7 .633
Item 8 .718
Item 9 .696
Item 10 .745
Item 11 .471
Item 12 .631
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Note: HAT = Hating Adolescents Test; ML = maximum likelihood.

Convergent validity

The HAT score showed strong positive and significant correlations with the Hostility scale of the BPAQ (r = .31; p < .01) and the Verbal Aggression scale of the BPAQ (r = .30; p < .01), and significant correlations with the Blaming Others (r = .44; p < .01), Minimizing/Mislabeling (r = .49; p < .01) and Assuming the Worst scales of the HITQ (r = .42; p < .01).

Results of Experiment 2

We conducted a univariate analysis of variance (ANOVA) to explore the role of gender on hostility (from the BPAQ scale) and pathological worry. Data showed significant main effects on hostility, F(1, 401) = 19.97, p < .0001, and on pathological worry, F(1, 401) = 23.63, p < .0001. In both cases females (MHostility Aggressiveness = 2.74, SD = 0.70; MPathological Worry = 51.6, SD = 12.5) report higher scores than males (MHostility Aggressiveness = 2.45, SD = 0.59; MPathological Worry = 45.7, SD = 11.6). The correlational analyses highlight how hating is positively correlated with pathological worry (r = .20; p < .05) and hostility aggression (r = .31; p < . 01), and pathological worry is positively correlated with hostility (r = .46; p < .01).

The mediating effect of hostility on the relationship between pathological worry and hating

Following the steps enumerated by Baron and Kenny (1986), on the basis of preliminary results we conducted three set of regression analysis to examine whether hostility mediated the relationship between pathological worry and hating. As far as the first set is concerned, the following steps must be met to establish mediation (see Figure 1): (a) the independent variable (X; pathological worry) positively predicts the dependent variable (Y; hating); (b) the independent variable (X) predicts the mediator (M; hostility); (c) the mediator (M) and the independent variable (X) predict the dependent variable (Y) with the effect of X on Y that becomes not significant or that decreases when controlling for M. Results from regression analyses are presented in Table 4. The first set of analyses examined whether hostility aggression mediated the relationship between pathological worry and hating. The total effect of pathological worry on hating [path c of Figure 1(a)] was statistically significant (β = .10, t = 1.85; p < .05), the effect of pathological worry on hostility aggression [path a of Figure 1(b)] was statistically significant (β = .46, t = 10.4; p < .000), and the effect of hostility aggression on hating [path b of Figure 1(b)] was statistically significant (β = .21, t = 4.3; p < .000). Finally, the magnitude of the direct effect of pathological worry on hating when controlling for the effect of hostility aggression [path c′ of Figure 1(b)] has increased (β = −.006, t = −0.11; p = ns) compared with the total effect of pathological worry on hating, suggesting a total mediation. Bootstrapping analyses indicated that pathological worry has exerted an indirect effect [−.010; ab in Figure 1(b)] on hating through the intervention of hostility aggression (95% confidence interval, CI [−.018, −.0012]).

Figure 1.

Figure 1.

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(a) Illustration of the total effect: X affects Y. (b) Illustration of the mediation design: X affects Y indirectly through M.

Table 4.

Hostility mediating the association between pathological worry and hating.

  t SE β F(1, 401) R2
           
1. Pathological worry → hating (path c) .01 0.003 .10* 3.8* .01
2. Hostility aggression → pathological worry (path a) 8.6 0.82 .46** 108.7** .21
3. Hostility aggression → hating (path b) .20 0.05 .21* 18.31* .04
4. Pathological worry → hating (path c′) .00 0.003 −.006    
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*p < .05. **p < .001.

Discussion and conclusion

In the psychological literature it is well known that aggressiveness, including verbal, can have negative effects on the victims, especially during adolescence, which represents a crucial period for development. However, episodes of aggression can be related to use of cognitive distortions or mechanisms of moral disengagement (e.g. Bussey, Quinn, & Dobson, 2015; Visconti, Ladd, & Kochenderfer-Ladd, 2015).

Experiment 1 assessed the preliminary psychometric properties of the HAT, a new tool for evaluating online and offline hate, in a sample of adolescents. Indeed, adolescence is the period when episodes of verbal aggression, which can lead to episodes of cyberbullying, are very common in adolescent groups. In particular, from the preliminary analysis emerges how the male participants are more likely than female participants to manifest episodes of online and offline hate – episodes of hatred linked to the physical characteristics and intellectual abilities of the injured person, and to indignity towards the other. These data are in accordance with literature (e.g. Björkqvist, 1994; Lips, 2017), although other studies (e.g. Björkqvist, 2018) suggest how women showed more forms of verbal aggression, as males choose other ways to translate their anger into action.

With regard to the tool developed, the preliminary analyses suggest a strong correlation between the subscales assumed for the instrument, as well as a good reliability index for each item of the scale. With concern to the main psychometric properties of the HAT, we found good internal consistency and a one-factor solution and a satisfactory index of construct validity. Furthermore, the analysis showed a very good reliability of HAT. The hypotheses linked to the presence of several subscales of the instrument have not been proved by factorial analysis.

The positive and significant inter-correlations between HAT and the other self-report measures used for the assessment of characteristics immediately connected to hate online and offline – the HITQ scales and the BPAQ scales – offer support for the concurrent validity of HAT scale.

The strong correlations between the HAT and the disengagement mechanisms (e.g. Minimizing/Mislabeling and Blaming Others) or cognitive distortions in a more general sense (e.g. Assuming the Worst) suggest precisely how the social–cognitive aspect is predominant, as well as directly connected to the phenomenon of haters. Moreover, the connection between (online and offline) hate and verbal and hostile aggressiveness, even if significant, needs to be examined more deeply in relation to hater phenomenon. However, it is possible to deduce that verbal aggression can also be experienced in the virtual world. In the virtual world aggression can occur more frequently as the screen – so the fact of not having the victim in front – can exploit as a facilitator and promoter of verbal aggression among adolescents.

In Experiment 2, the analysis of data, in accordance with previous studies, highlights how females have a greater tendency to pathological worry than males (e.g. Ziegert & Kistner, 2002). Furthermore, females report higher level of hostility aggression. This result may suggest how female adolescents tend to develop more feelings of aggression, which can be considered as a result of a threat to self-esteem or status, or whenever there is a lack of respect for them. In this sense, aggressiveness originates from anger (Berkowitz, 1993).

The regression analysis shows how pathological worry, in adolescence, is positively connected to hate. In this sense, tendencies towards internalization and therefore frustration can lead the adolescent to externalizing behaviors of aggression mediated by technological tools. Furthermore, in line with literature (Berle et al., 2011; Brosschot & Thayer, 2004), the data suggest how pathological worry predicts hostile aggression. It can be deduced how the tendency to hostility is a characteristic connected to pathological worry in adolescence – that is, sometimes the adolescents’ tendency to pathological worry can lead to hostile responses following a rabid event. In other words, the tendency to pathological worry may be a predisposing factor linked to the tendency to assume a hostile attitude towards the world and others. Finally, the mediation model suggests how hostility aggression totally mediates the relationship between pathological worry and hate online and offline. The tendency to manifest hostile form of aggressiveness can lead the adolescent to enact hate online and offline as a defense against his own hostilities and fears. In other words, this model suggests how an adolescent, who tends to appear hostile and discouraged towards others and the world, may be more inclined to implement hate behavior without thinking too much, regardless of the consequences of his own action. In line with the model of Rutter and Garmezy (1983), the hostile component of aggression can be a maladaptive response to pathological thinking, as well as being a significant risk factor connected to the genesis of hating episodes. Therefore, the hating in adolescence is a dysfunctional evolutionary outcome, and an indication of an unhealthy adaptation that depends on the person’s internal states. In other words, the almost cumulative internalizing and externalizing psychopathological characteristics can be transformed into a maladaptive response when the person has the opportunity to let off steam through the use of unmotivated forms of hating (Sameroff & Mackenzie, 2003).

These studies suggest how the phenomenon of haters can be considered an indirect form of aggression among adolescents. Therefore, the study of hating, and its risk factors, is useful to prevent it and create targeted interventions. However, the present studies should also be considered in light of the limitations it presents. The first limitation is connected to the number of participants. Therefore, it is not possible to generalize the results obtained to the whole population of adolescents. Moreover, future studies can verify whether socio-cultural variables or age of participants can influence this phenomenon, perhaps in a longitudinal perspective. It could be important to verify whether this phenomenon is connected to familiar and/or other individual factors (e.g. temperament, personality characteristics; e.g. D’Urso, Petruccelli, & Pace, 2018b; Pace, D’Urso, et al., 2018a). Indeed, despite these limitations, the results of these studies are promising and indicate how this short and simple tool is useful for investigating the phenomenon of haters among adolescents, how it has good psychometric properties and how it could be of use to increase research in the fields of developmental psychology, to identify the risk and protection factors linked to new phenomena (e.g. cyberbullying).

Ethical standards

Declaration of conflicts of interest

Ugo Pace has declared no conflicts of interest

Giulio D’Urso has declared no conflicts of interest

Carla Zappulla has declared no conflicts of interest

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

A written informed consent was obtained for all by sending letters to their parents in order to inform them of the study. No parents objected to their child’s involvement in the study. We also obtained assent from all the adolescents involved in the study.

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