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Journal of Adolescence
journal homepage: www.elsevier.com/locate/adolescence
Negative emotions and behaviour: The role of regulatory emotional
self-efficacy
Belén Mesurado
a
, Elisabeth Malonda Vidal
b,∗
, Anna Llorca Mestre
c
a
National Scientific and Technical Research Council (CONICET), Austral University, Buenos Aires, Argentina
b
Dpt. Basic Psychology, University of Valencia, Spain
c
Dpt. Personality, Evaluation and Psychological Treatment, University of Valencia, Spain
ARTICLE INFO
Keywords:
Regulatory emotional self-efficacy
Prosocial behaviour
Aggression
Negative emotions
Adolescence
Longitudinal data
ABSTRACT
The objective of this study is to test a longitudinal model that analyses the direct effect of ne-
gative emotions (anger, depression and anxiety, wave 1) on prosocial and aggressive behaviour
(wave 2) in adolescents. And the indirect effect of negative emotions (wave 1) on prosocial and
aggressive behaviour (wave 2) through regulatory emotional self-efficacy. Data was obtained
from 417 adolescents in a two-wave longitudinal study (225 girls, M age = 14.70 years) from
schools located in Valencia, Spain. SEM was employed to explore longitudinal models. The results
showed that anger had a direct relationship with prosocial behaviour and aggression, measured
two years later. However, the depression and anxiety states did not predict prosociality and
aggressiveness. The mediation role of regulatory emotional self-efficacy between negative
emotion and behaviours was only partially confirmed. Finally, only the perception of self-efficacy
in expressing positive affect is related to prosociality and aggressiveness.
Aggression and prosocial behaviour are indicators of interpersonal competence in adolescence (Belgrave, Nguyen, Johnson, &
Hood, 2011). Both behaviours are related to positive and negative emotions and emotional states. In relation to positive emotionality,
several studies have shown that positive emotions (like joy, gratitude, serenity and personal satisfaction) inhibit aggressive behaviour
and promote prosocial behaviour (McCullough, Emmons, & Tsang, 2002; Richaud & Mesurado, 2016; Author, under review). With
reference to negative emotions, empirical evidence shows that aggressiveness is related to anxiety (Salaam & Mounts, 2016), de-
pression (Benarous, Hassler, Falissard, Consoli, & Cohen, 2015) and anger (DeWall, Anderson, & Bushman, 2012). On the other hand,
prosocial behaviour relates in a negative way, to negative affective states like depression (Davis et al., 2016) and anger (Roberts,
Strayer, & Denham, 2014). For example, a recent experimental study found that expressions of disappointment increase compliance
with requests for help, whereas expressions of anger undermine compliance (Van Doorn, Van Kleef, & Van der Pligt, 2015).
Adolescence is a stage of high emotional vulnerability (Steinberg, 2005). Adolescents are able to move from love to hate, from
acceptance to rejection, from pride to shame in their interpersonal relationships (Main, 2000). Therein, adjusted behaviour requires
an effective regulation of emotions, and an effective regulation of emotions includes a control over positive and negative emotions.
Emotional regulation makes social relationships easier and contributes to people's positive adjustment. Adolescents who are able to
manage negative affect and to prolong the benefits of positive affect, have more personal resources that protect them from negative
behaviours and promote positive behaviours (Caprara, Gerbino, Paciello, Di Giunta, & Pastorelli, 2010). Also, experience and ex-
pression of positive emotions are associated with rewarding social relationships and health (Gunzenhauser et al., 2013). Conversely,
those who have difficulty containing their emotions when facing stressors or negative events can show problematic interpersonal
https://doi.org/10.1016/j.adolescence.2018.01.007
Received 7 February 2017; Received in revised form 9 January 2018; Accepted 24 January 2018
∗
Corresponding author.
E-mail address: elisabeth.malonda@uv.es (E.M. Vidal).
Journal of Adolescence 64 (2018) 62–71
0140-1971/ © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
T
behaviour (Gunzenhauser et al., 2013).
Adolescents differ vastly in the way they manage their emotions in everyday life, not only because they have different abilities,
but also because they differ in their perceived capabilities to regulate their emotions. It is possible for a person to feel a positively
ability to manage their emotions in perturbing or stressful situations, while they are not able to do so when actually facing these
situations. However, it is more difficult for a person to actually manage their emotions if they don't believe they are able to do so;
ultimately, the feelings about their self-regulation ability will contribute to their psychological wellbeing (Azizli, Atkinson,
Baughman, & Giammarco, 2015).
Based on self-efficacy theory developed by Bandura (1997), Caprara (Caprara, Vecchione, Barbaranelli, & Alessandri, 2013;
Caprara et al., 2008) which postulated the concept of regulatory emotional self-efficacy, which includes two dimensions: self-efficacy
in managing negative affect and self-efficacy in expressing positive emotions. The former refers to the belief in one's ability to
improve negative emotions, which can arise when facing different stressing events and to prevent negative results. In the same way,
self-efficacy in expressing positive emotions refers to the belief in one's capacity to experiment or allow oneself to express positive
emotions like happiness, enthusiasm and pride as an answer to success and pleasurable events. Caprara's self-efficacy beliefs analysis
(Caprara & Gerbino, 2001), links regulatory emotional self-efficacy with social relationships in the same way as the latter with the
regulation of affections. That is, the capacity to experiment and express positive and negative affects is thought to be as decisive for
managing fulfilling and productive relationships with others as the ability to regulate affection (Caprara, Alessandri, Di Giunta,
Panerai, & Eisenberg, 2010, Caprara, Gerbino, et al., 2010; Nocentini, Pastorelli, & Menesini, 2013). In addition, self-efficacy is
specific and refers to particular domains and given times. For example, just as some people consider themselves highly efficient in
academic tasks, they may also perceive themselves as not efficient in their relations with others, and vice versa (Salavera, Usán, &
Jarie, 2017). Adolescents can feel they are efficient in regulating certain emotions but less efficient in regulating others, which could
affect or modify their subsequent behaviour.
Furthermore, a vast body of research attests to the pervasive influence of regulatory emotional self-efficacy on effective func-
tioning of adolescents and on the course of their life. The individual acts relates to the beliefs they have about their own abilities in a
particular situation. The thoughts and feelings people have about their regulatory emotional self-efficacy to control events have an
influence over the choices they make, the effort they invest, their motivation and their behaviour (Alessandri, Caprara, Eisenberg, &
Steca, 2009; Galicia-Moyeda, Sánchez-Velasco, & Robles-Ojeda, 2013). In this way, if adolescents believe they can successfully obtain
proposed objectives, they are motivated to undertake activities oriented to attain those objectives, and they persevere when facing
difficulties and failures. Therefore, regulatory-emotional self-efficacy beliefs have a direct influence on the behaviour (Bandura,
2006).
Moreover, previous findings demonstrated the role of regulatory-emotional self-efficacy beliefs in mediating the contribution of
different personal traits (e.g. agreeableness and conscientiousness) to positive behaviours in adolescents (e.g. prosociality and aca-
demic achievement, respectively) (Caprara, Alessandri, et al., 2010; Caprara, Vecchione, Alessandri, Gerbino, & Barbaranelli, 2011).
Another longitudinal study has shown primacy in the direction of the influence of emotional stability on self-efficacy beliefs (Caprara
et al., 2013). Caprara et al. (2013) suggested “that the initial levels of emotional stability are highly correlated with initial levels of
self-efficacy beliefs in managing both positive and negative emotions. Likely individuals who are more emotionally stable, also feel
more capable of exerting proper control over their emotions”(p. 152). Consequently, it is likely that emotional instability (char-
acterized by experience of negative emotions such as anger, anxiety and depression) could be associated with lower levels of reg-
ulatory-emotional self-efficacy beliefs; and this in turn, mediates the relationship between negative emotions and behaviour.
1. The present study
Previous cross-sectional studies have found a positive relation between regulatory emotional self-efficacy and prosocial beha-
viour, and a negative relation to aggressive behaviour. Specifically, the ability to express positive affect, to manage despondency or
distress, and to manage anger or irritation are associated in a positive way with prosocial behaviour and in a negative way with
aggressiveness (Caprara et al., 2008). Moreover, a longitudinal study investigated the relationship between efficacy in managing
negative emotions and in expressing positive emotions at wave 1 with prosocial behaviour and delinquency at wave 2 (Bandura,
Caprara, Barbaranelli, Gerbino, & Pastorelli, 2003). The wave 1 constructs showed a negative correlation to wave 2 prosocial be-
haviour and a positive correlation to wave 2 delinquencies.
Despite the available evidence on the links among anger, depression, anxiety, regulatory emotional self-efficacy, prosocial be-
haviour and aggressiveness, most studies are limited to the inference of causality due to their cross-sectional design. Consequently,
the objective of this study is to test a longitudinal model that analyses the direct effect of negative emotions (anger, depression and
anxiety, measured in wave 1) on prosocial and aggressive behaviour (measured in wave 2) in adolescents. And the indirect effect of
negative emotions (wave 1) on prosocial and aggressive behaviour (wave 2) through regulatory emotional self-efficacy (1. perceived
self-efficacy in expressing positive affect, 2. perceived self-efficacy in managing anger/irritation and 3. perceived self-efficacy in
managing despondency/distress, measured in wave 2). The mediating role of regulatory emotional self-efficacy will be studied
because, previous studies have shown that emotional stability is associated with regulatory emotional self-efficacy, and the regulatory
emotional self-efficacy plays a mediating role between trait and behaviours (Caprara, Alessandri, et al., 2010; Caprara et al., 2011).
Consequently, it is likely that emotional instability -characterized by experience of negative emotions- is associated with regulatory
emotional self-efficacy, and the regulatory emotional self-efficacy mediates the relation between negative emotions and prosocial and
aggressive behaviour.
Based on these previous studies, we hypothesize that:
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
63
1. Anger (state and trait), depression and anxiety (wave 1) have a negative effect on regulatory emotional self-efficacy (wave 2) and
prosocial behaviour (wave 2), and a positive effect on aggressive behaviour (wave 2).
2. The different aspects of regulatory emotional self-efficacy (perceived self-efficacy in expressing positive affect, perceived self-
efficacy in managing anger/irritation and perceived self-efficacy in managing despondency/distress, wave 2) will mediate or
regulate the relation between negative emotions (wave 1) and prosocial and aggressive behaviour in adolescents (wave 2).
3. The different aspects of regulatory emotional self-efficacy (wave 2) are associated in a positive way with prosocial behaviour and
in a negative way with aggressive behaviour (wave 2).
Because gender differences in regulatory emotional self-efficacy (Caprara, Steca, Cervone, & Artistico, 2003), in prosocial and
aggressive behaviour were found in a previous study (Kornbluh & Neal, 2016; Mesurado et al., 2014); we will analyse this difference
in all variables included in the paper. In the case that these differences were confirmed in our data, we will test the model hy-
pothesized using gender as a control variable.
2. Method
2.1. Participants
Data was obtained from four hundred and seventeen adolescents in a two-wave longitudinal study (192 boys and 225 girls, M
age = 14.70 years, SD = .68; age range = 13–17) from public and private schools located in different geographic zones within the
school district of the city of Valencia, Spain. In the first wave, adolescents were either in the third and fourth year of secondary
school. The second wave was carried out at a two-year interval and the adolescents were between fifteen and nineteen years old.
Most adolescents were from two-parent households (84%; 16% single-parent households). Mothers' education level was less than
high school diploma in 22%, high school diploma or equivalent in 42%, and some university education in 42% of the cases. Fathers'
education level was high school diploma or less in 24%, high school diploma or equivalent in 41%, and some university education in
29% of the cases. Participating schools were randomly selected from the list of all schools in Valencia with students enrolled in
compulsory secondary education. In total, 11 schools participated in the study.
2.2. Procedure
Approval from the School Council and parental consent were obtained. Participation by students was voluntary; students were
free to decline to participate. The survey was administered by trained researchers in the classroom in 50-min sessions during school
hours. The two assessments took place during the first trimester of the school year. The study followed all ethical guidelines, re-
specting respondents' anonymity for both data collection and data analysis.
2.3. Measures
State and Trait Anger Scale (Del Barrio, Aluja, & Spielberger, 2003). This self-report questionnaire has three parts that includes
Likert-type items with three response options (1 = nothing to 3 = much). The first part evaluates Anger as a state with 13 items as
follows by having the subject answer according to the following instructions: “Mark the answer that best describes you at this time.
Do not think too much about the answer and answer your first impression about how you feel NOW”(example item: “I'm furious”,“I
feel like kicking”). The second part evaluates Anger as a trait with 10 items. The subject must answer according to the following
instructions: “Mark the answer that best describes you habitually. Do not think too much about the answer and answer your first
impression about how you feel USUALLY”(example item: “I have a strong character”,“It infuriates me to be corrected in front of
others”). The third one assesses the level of self control and the coping mechanisms (externalisation or self control) that the subject
uses in anger inducing situations (example item: “when I'm furious I hide my feelings”,“I take a deep breath to calm myself”). The
total score for each scale was obtained with the mean of the scores of each item. In this study, Anger state (α= .82 at wave 1) and
Anger trait (α= .92 at wave 1) were used in obtaining good reliability indexes.
DASS-Anxiety (Norton, 2007). This 7 items scale measures the negative emotional state of anxiety, and the frequency and severity
in which negative emotions were experienced the previous week using a four-point likert scale ranging from never happened (0) to
happens often (3). The total score for each scale was obtained with the mean of the scores for each item. For this study, only the
anxiety scale was used (α= .82 at wave 1).
CES-D Scale (Radloff, 1977). This measure assesses the frequency and severity of negative emotions experienced and depressive
symptoms in the previous week. Example of item: “I was upset by things that don't normally upset me”. In addition to internal
consistency, CES–D scores have demonstrated an acceptable reliability, with cronbach's alphas from .70 to .90 in others studies
(Edwards, Cheavens, Heiy, & Cukrowicz, 2010; Russell, Crockett, Shen, & Lee, 2008). Cronbach's alpha for this study was α= .76 at
wave 1.
Regulatory Emotional Self-Efficacy Scale (Caprara et al., 2008). This scale evaluates self-efficacy beliefs in the domain of emotion
regulation, using a five-point Likert scale ranging from be unable (1) to fully capable (5). Two scales are included: (a) Perceived self-
efficacy to express positive affect was measured by five items in terms of perceived ability to express liking and affection toward
others, to get oneself to express enthusiasm and enjoyment, and to feel satisfaction with personal accomplishments. A sample of item
is ‘‘I can show liking for a person toward whom I am attracted”(α= .90 at wave 2). Perceived self-efficacy in regulating negative
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
64
affect was assessed by nine items in two subscales: (b) perceived self-efficacy in managing anger/irritation assessed the perceived
ability to manage negative affect in the face of anxiety-arousing threats, anger provocation, rejection, and disrespect, and to control
worrisome ruminations when things go wrong (“I can Manage negative feelings when reprimanded by my parents or significant
others”,α= .84 at wave 2); and (c) perceived self-efficacy in managing despondency/distress, measured the perceived ability to
manage negative affect in the face of despondency and discouragement (“I can keep from getting discouraged in the face of diffi-
culties”,α= .85 at wave 2). The total score of each scale is the mean of the items score.
Prosocial Behaviour Scale (Caprara & Pastorelli, 1993; Del Barrio, Moreno, & López, 2001). This instrument uses 15 items to
evaluate the behaviour of help, trust and sympathy. Respondents indicate the frequency with which the behaviour in each statement
occurs (often,sometimes,never). Example items are, “I help my peers to do their homework”and “I try to console those who are sad”.
The total score of the Scale is the mean of the items score. Cronbach's alpha for this study was .75 at wave 2.
Physical and Verbal Aggression Scale (Caprara & Pastorelli, 1993; Del Barrio et al., 2001). This scale uses 20 items with three
possible answers (often, sometimes or never) to evaluate behaviours that harm others physically or verbally. Example item: “I hit, kick
and punch”. The total score of the scale is the mean of the items score. Cronbach's alpha for this study was .83 at wave 2.
2.4. Statistical procedure
First, means and standard deviations were calculated using SPSS 19, and analysis of variance (ANOVA) or multivariate analysis of
variance (MANOVA) were carried out to study gender differences in all variables included in the study. Correlation analysis was
carried out, and finally, three longitudinal models were tested using structural equations modelling (SEM) in AMOS 17.0 (SPSS Inc.,
2007). The following goodness-of-fit indices were used: chi-square, chi-square divided by degrees of freedom (χ
2
/fd), goodness-of-fit
index (GFI), adjusted goodness-of-fit index (AGFI) and Bentler comparative fit index (CFI). Root mean residual (RMR), was used to
measure error. To assess the significance of the mediating effects of regulatory emotional self-efficacy between negative emotion and
prosocial and aggressive behaviour, bootstrapping criteria was used (Shrout & Bolger, 2002).
3. Results
3.1. Preliminary analyses and descriptive statistics
Means, standard deviations and mean differences between boys and girls (based on ANOVA/MANOVA designs) for each variable
at each wave are provided in Tables 1 and 2. The results show that girls were higher than boys in Anxiety and Depression in wave 1.
Moreover, girls were higher than boys in Perceived self-efficacy in expressing positive affect and Prosocial Behaviour in wave 2; while
boys were higher than girls in Perceived self-efficacy in managing despondency/distress and Aggression in wave 2.
3.2. Correlations
Table 3 despite the correlation analysis between variables in both groups: boys and girls.
The results indicate that state anger and trait anger correlate with each other and positively with anxiety and depression at wave 1
in both boys and girls. Moreover, state anger and trait anger correlate negatively with perceived self-efficacy in expressing positive
affect (wave 2) and positively with physical and verbal aggression in both genders. Only girls reached a negative correlation between
state anger, trait anger and prosocial behaviour. The correlation between trait anger and perceived self-efficacy in managing anger/
irritation is negative in both genders. Only in girls, a negative correlation was reached between anxiety and depression with per-
ceived self-efficacy in managing despondency/distress. Finally, it was observed that the three aspects of self-efficacy were positively
and highly related to each other, both in boys and girls, and they reach a positive correlation with prosocial behaviour and a negative
Table 1
ANOVAS for waves 1 variables by gender.
Wave 1
η
p
2
Boys
n = 192
Girls
n = 225
F(1, 415)
Mean SD Mean SD
Anger
a
State Anger 1.10 .17 1.08 .19 1.80 .00
Trait Anger 1.77 .36 1.79 .36 .22 .00
Anxiety .46 .50 .60 .56 7.57** .02
Depression 1.71 .38 1.87 .46 14.65*** .03
Note:F, statistics based on one-way ANOVAs;
η
p
2
, Partial Eta squared, effect size measure (.01 = small effect; .06 = medium effect; .13 = large effect; Cohen, 1988).
**p< .01; ***p< .001.
a
One-Way MANOVA, Hotelling trace F(2, 414) = 1.31, p= 2.7,
η
p
2
= .01.
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
65
correlation with aggression.
3.3. Test of longitudinal model
Three longitudinal hybrid models (Kline, 2015) were tested using AMOS 17 and maximum likelihood estimation with robust
standard errors. Since we found differences between girls and boys, all models were gender controlled. The objective of this study is
to test a longitudinal model that analyses the direct effect of negative emotions (anger, depression and anxiety, wave 1) on prosocial
and aggressive behaviour (wave 2) in adolescents. And the indirect effect of negative emotion (wave 1) on prosocial and aggressive
behaviour (wave 2) through regulatory emotional self-efficacy (1. perceived self-efficacy to express positive affect, 2. perceived self-
efficacy in managing anger/irritation and 3. perceived self-efficacy in managing despondency/distress, wave 2). The same model was
carried out three times changing the mediator variable.
The first model used perceived self-efficacy as a mediator variable, to express positive affect (first aspect of regulatory emotional
self-efficacy). This first model test (controlling for gender) yielded acceptable fit to the data, χ
2
(6) = 22.43, p< .001, χ
2
/fd = 3.71;
GFI = .99; AGFI = .92; CFI = .96 and RMR = .004. Standardized path coefficients of the first model shows that depression (wave 1)
is negatively related to perceived self-efficacy in expressing positive affect (wave 2). Anger (wave 1) is positively associated with
aggression (wave 2) but negatively associated with prosocial behaviour (wave 2).
Additionally, the results indicate that perceived self-efficacy to express positive affect, mediated only the relation between de-
pression and prosociality (indirect effect = −.05, 95% CIs = −.10 to −.02, p = 0.05) and between depression and aggression
(indirect effect = .03, 95% CIs = 0.02 to 0.07, p = 0.05). However, the perceived self-efficacy to express positive affect (wave 2) did
not mediate the relation between other negative emotions (anger and anxiety, wave 1) and prosocial and aggressive behaviour (wave
2). Moreover, perceived self-efficacy in expressing positive affect (wave 2) was positively related to prosocial behaviour (wave 2) and
negatively related to aggression (wave 2) (See Fig. 1). The R
2
values for the mediator and outcomes are as follows: Perceived self-
efficacy in expressing positive affect = .10; aggression = .38 and prosocial behaviour = .25.
Later, the same model was tested using the perceived self-efficacy in managing despondency/distress as mediator variable (second
aspect of regulatory emotional self-efficacy). The second model test (control for gender) yielded acceptable fit to the data, χ
2
(6) = 28.22, p< .001, χ
2
/fd = 4.03; GFI = .98; AGFI = .91; CFI = .94 and RMR = .01. Standardized path coefficients of the second
model shows that anger (wave 1) was positively associated with aggression (wave 2) but negatively associated with perceived self-
Table 2
ANOVAS for waves 2 variables by gender.
Wave 2
η
p
2
Boys
n = 192
Girls
n = 225
F(1, 415)
Mean SD Mean SD
Regulatory emotional self-efficacy
a
Perceived self-efficacy in expressing positive affect 3.98 .75 4.32 .71 22.24*** .05
Perceived self-efficacy in managing despondency/distress 3.41 .77 3.13 .81 12.19*** .03
Perceived self-efficacy in managing anger/irritation 3.22 .81 3.27 .82 .51 .00
Aggression 1.36 .29 1.22 .19 31.72*** .07
Prosocial Behaviour 2.48 .30 2.60 .27 17.03*** .04
Note:F, statistics based on one-way ANOVAs;
η
p
2
, Partial Eta squared, effect size measure. *p< .05; **p< .01; ***p< .001.
a
One-Way MANOVA, Hotelling trace F(3, 413) = 20.35, p< .001,
η
p
2
= .13.
Table 3
Correlations between variables in male and female participants.
Variables 1 2 3 4 5 6 7 8 9
1. State Anger (wave 1) –.27*** .26*** .31*** −.23*** −.01 −.08 .34*** −.15*
2. Trait Anger (wave 1) .25*** –.24*** .22*** −.16* −.13* −.27*** .37*** −.13*
3. Anxiety (wave 1) .14* .18** –.58*** −.12 −.20* −.15* .27*** −.12
4. Depression (wave 1) .18** .25*** .62*** –−.36*** −.32*** −.24*** .21** −.20**
5. Perceived self-efficacy in expressing positive affect (wave 2) −.17** .07 −.05 −.10 –−.37*** −.21*** −.03 .31***
6. Perceived self-efficacy in managing despondency/distress
(wave 2)
−.09 .01 −.01 −.15* .50*** –−.63*** −.07 .03
7. Perceived self-efficacy in managing anger/irritation (wave 2) −.08 −.19** −.04 −.16* .38*** .55** –−.28*** .14*
8. Aggression (wave 2) .20** .18** .08 .08 −.22** −.16* −.28*** –−.31***
9. Prosocial Behaviour (wave 2) −.13 −.08 −.07 −.14* .22** .15* .22** −.32*** –
Note: intercorrelations for female participants are presented above the diagonal, and intercorrelations for male participants are presented below the diagonal.
*p < .05; **p< .01; ***p< .001.
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
66
efficacy in managing despondency/distress (wave 2) and prosocial behaviour (wave 2).
Additionally, the results indicate that the perceived self-efficacy in managing despondency/distress (wave 2) did not mediate the
relation between different negative emotions (wave 1) and prosocial and aggressive behaviour in adolescents (wave 2). Moreover,
perceived self-efficacy in managing despondency/distress (wave 2) was not related to prosocial behaviour (wave 2) and aggression
(wave 2) (See Fig. 2). The R
2
values for the mediator and outcomes are as follows: perceived self-efficacy in managing despondency/
distress = .04; aggression = .42 and prosocial behaviour = .22.
Finally, the same model was tested using the perceived self-efficacy in managing anger/irritation as mediator variable (third
aspect of regulatory emotional self-efficacy). The third model test (control for gender) also yielded acceptable fit to the data, χ
2
(6) = 20.76, p< .004, χ
2
/fd = 2.96; GFI = .99; AGFI = .93; CFI = .96 and RMR = .003.
Standardized path coefficients of third model shows that anger (wave 1) was positively associated with aggression (wave 2) but
negatively associated with perceived self-efficacy in managing anger/irritation (wave 2) and prosocial behaviour (wave 2).
However, the results indicate that the perceived self-efficacy in managing anger/irritation (wave 2) did not mediate the relation
between different negative emotions (wave 1) and prosocial and aggressive behaviour in adolescents (wave 2).
Moreover, perceived self-efficacy in managing anger/irritation (wave 2) was not related to prosocial behaviour (wave 2) and
aggression (wave 2) (See Fig. 3). The R
2
values for the mediator and outcomes are as follows: perceived self-efficacy in managing
anger/irritation = .24; aggression = .42 and prosocial behaviour = .22.
4. Discussion
The findings of this study provide good evidence on how negative emotions (anger, anxiety and depression) operate in relation to
Fig. 1. Longitudinal model testing the associations between negative emotions (wave 1), perceived self-efficacy in expressing positive affect (wave 2), aggression
(wave 2) and prosocial behaviour (wave 2).
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
67
regulatory emotional self-efficacy in promoting aggression and mitigating prosocial behaviour. Because there is an important pattern
of gender differences in several variables included in this research, in our preliminary analyses, gender differences were analysed.
The results showed that girls reported higher level of anxiety, depression and prosocial behaviour than boys, while boys reported
higher level of aggression than girls. These findings are consistent with several previous studies (Carlo, Mestre, Samper, Tur, &
Armenta, 2010; Del Barrio & Carrasco, 2013; Diamantopoulou, Verhulst, & Van Der Ende, 2011; Mestre, Samper, Frías, & Tur, 2009).
Moreover, girls showed higher level of self-efficacy in expressing positive affect than boys, while boys showed higher level of self-
efficacy in managing despondency and distress than girls, these results are consistent with others studies in adolescent population,
that could justify less depressive symptoms in boys (Alessandri et al., 2009). As Alessandri, Vecchione, and Caprara (2015) indicated,
and aligned with the above, that the weight of gender-role socialization makes most females develop relatively high levels of positive
interpersonal abilities, such as prosocial behaviour and a modulated expression of positive emotion (Else-Quest, Hyde, Goldsmith, &
Van Hulle, 2006), whereas males tend to report higher level of ability to manage the expression of negative emotions, in accordance
with the masculine role. However, it is important to note that a research done in populations of different countries did not show
consistent results in gender differences and they vary by country (Caprara et al., 2008).
The main objective of this study is to test a longitudinal model that analyses the direct effect of negative emotions on prosocial
and aggressive behaviour in adolescents. And the indirect effect of negative emotion on prosocial and aggressive behaviour through
regulatory emotional self-efficacy (perceived self-efficacy in expressing positive affect, perceived self-efficacy in managing anger/
irritation and perceived self-efficacy in managing despondency/distress). The results of the three models tested, indicated a good fit
Fig. 2. Longitudinal model testing the associations between negative emotions (wave 1), perceived self-efficacy in managing despondency/distress (wave 2), ag-
gression (wave 2) and prosocial behaviour (wave 2).
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
68
between the proposed model and the empirical data. However, our hypotheses were only partially confirmed.
The first hypothesis was that anger (state and trait), depression and anxiety have a negative effect on regulatory emotional self-
efficacy and prosocial behaviour and a positive effect on aggressive behaviour. The results showed that anger had a direct re-
lationship with prosocial behaviour and aggression in adolescents, measured two years later. Within negative emotions included in
this study, the state and trait of anger were the best predictors of physical and verbal aggression, while anger also inhibited prosocial
behaviour in adolescence. The depression and anxiety states did not predict prosociality and aggressiveness, which were measured
two years later, a possible explanation for these results, could be that the measure of anger included a combination of state and trait,
while the other variables (depression and anxiety) were measured only as states. Consequently, it is possible that when mental states
become more permanent mental traits, they have a greater influence on both positive and negative behaviour in adolescents. Our
findings substantially replicated earlier reports that anger is directly related to unfriendly behaviours, for example Roberts et al.
(2014), reported that anger predicts hostile behaviour toward peers and resistant behaviour with adults.
Our results contribute to understanding the role of certain negative emotions and their impact on positive and negative social
interaction. Moreover, these results may have an implication on intervention programs like Kellner and colleagues proposed “anger
management programs' attempt to reduce aggressive behaviour by reducing the cognitive, behavioural, and physiological responses
associated with aggression, while increasing nonaggressive, socially appropriate responses”(2008, p. 216). Indeed, Kellner, Bry, and
Salvador (2008) found that an intervention program based on managing anger increased prosocial behaviour toward teachers, and
promotes less aggressive behaviour towards peers.
Furthermore, the results showed that both, the state and trait of anger, have an important negative influence on perception of self-
efficacy in managing despondency or distress and in managing anger or irritation. On the other hand, depression as a state inhibits
the perception of self-efficacy in expressing positive affect. Although previous studies have shown that failures in different aspects of
Fig. 3. Longitudinal model testing the associations between negative emotions (wave 1), perceived self-efficacy in managing anger/irritation (wave 2), aggression
(wave 2) and prosocial behaviour (wave 2).
B. Mesurado et al. Journal of Adolescence 64 (2018) 62–71
69
regulatory emotional self-efficacy promote negative emotions like depression (Bandura et al., 2003; Bandura, Pastorelli, Barbaranelli,
& Caprara, 1999; Caprara, Alessandri, et al., 2010; Caprara, Gerbino, et al., 2010), our findings show that this relationship may also
be reverse. This means that the experience of negative emotions could undermine the perception of regulatory emotional self-
efficacy. However, more studies are necessary to confirm a bidirectional relationship.
Concerning the second hypothesis that different aspects of regulatory emotional self-efficacy mediate or regulate the relation
between different negative emotions and prosocial and aggressive behaviour in adolescents, was only partially confirmed. We found
that the perceived self-efficacy in expressing positive affect mediates the relation between depression and prosocial behaviour, and
between depression and aggression. In contrast with our expectations, perceived self-efficacy in regulating negative affect failed in
the regulation of the relation between negative emotions and behaviour. These findings could be explained by the arousal level of the
negative emotions, maybe negative emotion with low arousal (eg. depression or sadness) could be managed through perceived self-
efficacy in expressing positive affect; but in the case of emotions with high level of arousal (eg. anger), this would not be possible
because in the face of provocative circumstances there is an immediate effect on the behaviour without the possibility of reflection.
Finally, our third hypothesis was that the different aspects of regulatory emotional self-efficacy are associated in a positive way
with prosocial behaviour and in a negative way with aggressive behaviour. This hypothesis was only confirmed with one aspect of
regulatory emotional self-efficacy: the perception of self-efficacy in expressing positive affect. The perception of self-efficacy in
expressing positive affects had a negative relation to verbal and physical aggression and a positive relation to prosociality. These
results are consistent with previous studies that found that the perception of self-efficacy in expressing positive affect is related to
prosociality and aggressiveness (Alessandri et al., 2009; Caprara et al., 2008).
4.1. Limitations
This is a research based on self-assessments, even though depressive symptomatology and anxiety involves internal states, future
research could add the assessment of aggressive or prosocial behaviour done by the teachers or the classmates.
Another limitation was that the longitudinal design included only two waves. Even though longitudinal designs allows the
analysis of the evolution of the variables and how they relate at different times, this study has only carried out two assessments in a
two year interval, in future studies, an assessment of these variables could be done over a longer period.
In conclusion, there is ample evidence on the links among anger, depression, anxiety, regulatory emotional self-efficacy, prosocial
behaviour and aggressiveness; most studies are limited to the inference of causality due to their cross-sectional design. Maybe this
study would contribute to narrow that gap. This study supports the notion that negative emotion plays an important role in regulatory
emotional self-efficacy and especially in positive and negative adolescents' behaviour such as prosociality and aggression.
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