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Páginas: XX-XX Recibido: 2022-07-19 Revisado: 2022-08-10 Aceptado: 2022-10-08 Preprint: 2022-01-31 Publicación
Final: 2023-01-31 |
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Effectiveness of cyberbullying
prevention programmes on perpetration levels: a meta-analysis
|
Javier
Mula-Falcón |
||
|
Cristina
Cruz González |
Abstract
Cyberbullying is a new and growing bullying practice that generates more
harmful consequences than even traditional bullying. In this situation, the
role of education plays a decisive role in the fight against this type of
practice. In fact, in recent years there has been a significant increase in the
number of educational interventions on cyberbullying. However, the scientific
literature shows hardly any conclusive results on the effectiveness of these
interventions. Therefore, the aim of this meta-analysis is to analyse the
effects that prevention programmes on cyberbullying have on the levels of
perpetration among school students. To this end, a search strategy was carried
out according to the PICOS framework and PRISMA criteria in five different
databases: Web of Science (WoS), SCOPUS, Educational Research Information
Centre (ERIC), PubMed, ScienceDirect, SpringerLink and Google Scholar. After
searching and applying inclusion/exclusion filters, 9 studies were included in
the meta-analysis, covering a total of 17 different interventions conducted
between 2015 and 2019. These studies described the application of different
intervention programmes to students aged between 10 and 17 years. The findings
of this meta-analysis showed that educational prevention programmes could
decrease levels of bullying perpetration (SMD = 0.08; 95% CI [0.05, 0.11]; p
< 0.00001). Implications for strengthening and expanding cyberbullying
prevention programmes in the educational context are discussed. In addition,
future research is invited to go beyond the educational setting and consider
other variables and factors that extend outside the educational environment and
that are equally relevant, as well as to focus new lines of research on the
important role of the cyberassistant student as an essential part of this type
of situation.
Resumen
El ciberacoso es una nueva y creciente
práctica que genera consecuencias más dañinas que incluso el acoso tradicional.
En esta situación, el papel de la educación juega un papel decisivo en la lucha
contra este tipo de situaciones. De hecho, en los últimos años se ha producido
un aumento significativo del número de intervenciones educativas sobre el
ciberacoso. Sin embargo, la literatura científica apenas muestra resultados
concluyentes sobre la eficacia de estas intervenciones. Por lo tanto, el
objetivo de este meta-análisis es analizar los efectos que los programas de
prevención del ciberacoso tienen sobre los niveles de perpetración entre los
estudiantes escolares. Para ello, se realizó una estrategia de búsqueda según
el marco PICOS y los criterios PRISMA en cinco bases de datos diferentes: Web
of Science (WoS), SCOPUS, Educational Research Information Centre (ERIC),
PubMed, ScienceDirect, SpringerLink y Google Scholar. Tras la búsqueda y la
aplicación de los filtros de inclusión/exclusión, se incluyeron 9 estudios en
el metaanálisis, que abarcaban un total de 17 intervenciones diferentes
realizadas entre 2015 y 2019. Estos estudios describían la aplicación de
diferentes programas de intervención a estudiantes de entre 10 y 17 años. Los
hallazgos de este meta-análisis mostraron que los programas de prevención
educativa podrían disminuir los niveles de perpetración de bullying (DME =
0,08; IC del 95% [0,05, 0,11]; p < 0,00001). Se discuten las implicaciones
para reforzar y ampliar los programas de prevención del ciberacoso en el
contexto educativo. Además, se invita a futuras investigaciones a ir más allá
del ámbito educativo y considerar otras variables y factores que se extienden
fuera del entorno educativo y que son igualmente relecantes, así como enfocar
nuevas líneas de investigación al importante papel del alumnado ciberayudante
como parte esencial en este tipo de situaciones.
Palabras
clave / Keywords
Adolescence, Bullying, Education programs, Leisure,
Meta-analysis, Peer relationships, Social networking, Students, Technology
Acoso, Adolescencia, Estudiantes, Meta-análisis, Ocio, Programas de
educación, Redes sociales, Relaciones entre pares, Tecnología
1. Introduction
Thousands
of young people around the world suffer some kind of violence (Sastre, 2016).
However, within the wide range of violent experiences in which a child can be
involved, bullying stands out above all (Garaigordobil & Oñederra, 2010).
This consists of conduct (verbal, physical, psychological or social) that one
person (or group of them) carries out on another in an intentional and
sustained manner over time (Olweus, 1999; Nansel, et al., 2001). In general,
bullying can range from direct aggression (verbal and/or physical) to indirect
attitudes such as intimidation, extortion or defamation, among other actions
(Hinduja and Patchin, 2010). Regardless of the type carried out, they all have
a great impact on children, generating enormous problems with high social and
psychological costs for both the victims and their environment
(González-Cabrera et al., 2019; Rios et al., 2022; Yan et al., 2022).
These
traditional bullying practices have always been present in the school context
(Aboujaoude, Savage, Starcevic and Salame, 2015). According to a study
developed by UNICEF (2018) more than 150 million students have at some point in
their lives experienced bullying. Despite this, the prevalence of these
behaviours varies from one area to another. In this regard, UNESCO (2019)
points to North Africa (42.7%) and Southwest Asia (41.1%) as the areas with the
highest prevalence of this type of behaviour.
However,
the nature of bullying has changed significantly in recent times (Patchin and
Hinduja, 2011). The advent and development of new Information and Communication
Technologies (ICT) and the rapid development of digital and Social Media has
led to the emergence of a new type of bullying referred to as cyberbullying,
cyberharassment, electronic bullying or cybervictimisation (Chaves-Álvarez et
al., 2019; Alvites-Huamaní, 2019; Chan et al., 2019, Pérez and Palmar, 2021). This
new practice has been defined as "intentional and repeated harm inflicted
through computers, mobile phones and other electronic devices" (Hinduja
& Patchin, 2015, p. 11). In general, cyberbullying can be carried out in
multiple different ways such as posting compromising images or videos, sending
threatening or derogatory messages, disseminating intimate or relevant
information, etc. (Arab and Diaz, 2015; Monks et al., 2016; Hinduja and
Patchin, 2013). Furthermore, due to progress and greater social awareness, new
research suggests that a gender perspective is essential in the implementation
of programs to address cyberbullying (Cebollero et al., 2022a). In this line,
these authors propose a study on the validation of instruments related to
e-competences as a key factor for the prevention of cyberbullying and that
provides significant clues in the training of teachers and students (Cebollero
et al., 2022b).
Although
a priori it may seem that traditional bullying and cyberbullying are similar
practices, in reality they have a series of distinctive characteristics that
make the latter a much more harmful practice (Hinduja and Patchin, 2021;
Campbell and Xu, 2022). On the one hand, Neyra (2021) defines cyberbullying as
an extension of traditional bullying that allows overcoming the boundaries of
space. In this sense, cyberbullying is not only generated within the
educational centre, but the use of different digital media contributes to it
being continuous and permanent regardless of the place (Delgado and Escortell,
2018). Dredge, Gleeson, and Piedad (2014) add that this practice also
contributes to overcoming the boundaries of time, making actions permanent and
everlasting.
On the
other hand, Hinduja and Patchin (2021) highlight two other significant
differences that ICTs bring to cyberbullying: anonymity and viralisation.
Firstly, the possibility offered by digital media to anonymise identities makes
it difficult to identify the aggressors and, therefore, to solve the problem.
Moreover, this anonymity provides a certain degree of security to the
aggressors that contributes to increasing participation in this type of
practice. Secondly, these technologies also help the viralisation of these
behaviours by having an impact on two aspects: by increasing the visibility of
humiliating, harmful or degrading actions; and by increasing the number of
possible victims and witnesses.
All
these differences contribute to the fact that cyberbullying generates a series
of psychological and social consequences that are much more harmful than those
generated by traditional bullying (Slonje et al., 2013; Giménez et al., 2014;
Yan et al., 2022). In this sense, numerous studies highlight different effects
provoked in victims such as: feelings of fear, anger, frustration or stress
(Sticca et al. 2013; Hinduja and Patchins, 2010; Shpiegel et al., 2015); the
presence of anxiety or depression (Buelga et al., 2019; Yan et al., 2022); the
decrease in self-concept and self-esteem (Palermiti et al., 2017; Delgado et
al., 2019); increased social isolation (Ostrov & Kamper, 2015; Pereda &
Sicilia, 2017; Ademiluyi et al., 2022) or decreased academic performance
(Garaigordobil, 2015; González-Cabrera et al., 2019; Lara-ros et al., 2017);
among other aspects. Finally, other studies also point to extreme cases of
self-injurious behaviour and suicidal behaviour as possible consequences
(Hinduja and Patchin, 2018; Sticca et al. 2013; Holt et al., 2015; Mitchell et
al., 2018; Iranzo et al., 2019; Fadhli et al., 2022).
In
recent years, this type of bullying practices has increased considerably due to
the expansion in the use of new technologies by the younger population (Arnaiz
et al., 2016). As reported in a study by the National Institute of Statistics
(2020), 94.5 % of young Spaniards aged 10-15 are internet users, and more than
69 % have a mobile device at their disposal. As a result, young people have
made the use of ICTs a fundamental part of their lives, sometimes leading to
their misuse. It is therefore not surprising that more than 36% of young people
surveyed in a study conducted by Patchin and Hinduja (2020) among more than
5000 adolescents admitted to having suffered cyberbullying at some point.
In this
context, the role of families and, in particular, of the educational space play
a decisive role in the fight against this type of bullying practices among
peers (Hinduja and Patchin, 2013; 2021). In fact, although this new bullying
practice is a recent phenomenon (Delgado and Escortell, 2018), its rise in
recent years has led to the development of numerous educational intervention
programmes around the world (Calvete et al., 2021). In this regard, we find
some examples such as: prev@Cib (Ortega-Barón et al., 2019), the Asegúrate
programme (del Rey et al., 2018), the Cyberprograma 2.0 (Garaigordobil &
Martínez- Valderrey, 2015) or the social ViSC (Gradinger et al., 2015), among
others. Despite the numerous existing intervention programmes, there are hardly
any studies that analyse their effectiveness (Ng, Chua & Shorey, 2020).
For all
these reasons, there is a need to develop studies that allow a synthesis of the
results of empirical research that analyse the effectiveness of these
interventions. To this end, the present research consists of a meta-analysis
whose main objective is to analyse the effects that intervention programmes on
cyberbullying generate in the levels of perpetration of students at school.
This study aims to draw conclusions based on the results of previous research
on the effectiveness of educational interventions. Likewise, it also aims to
establish biases and future lines of research on which to guide the future of
the field under investigation.
2.
Methodology
The
present research consisted of the development of a meta-analysis. This research
strategy has the fundamental objective of determining the overall effect size
of quantitative research on a given topic (Piggot and Polanin, 2019). In this
case, the meta-analysis focused on the study of the effect of educational
intervention programmes on cyberbullying on the perpetration of cyberbullying
in adolescents. In order to provide the highest degree of systematisation,
scientific rigour and objectivity possible, the principles and premises of the
PRISMA and Cochrane protocols were applied. The procedure for the selection and
analysis of the studies comprising this research will be described below.
2.1. Search for studies
Multiple
searches were conducted through a combination of the following keywords:
cyberbullying, cyber aggression, online bullying, electronic bullying;
perpetration; intervention, program*; experimental and quasi-experimental. These
were selected through a process in which one or more words were derived from
each constituent element of the PICO(S) format (Martínez et al., 2016; Schardt,
et al., 2007). Different thesauri (ERIC and UNESCO) were used to translate
these terms.
The
searches were carried out in different databases (WoS, SCOPUS, ERIC, PubMed,
ScienceDirect and SpringerLink). In order to complement the search process, an
additional search was carried out in Google Scholar to investigate the possible
existence of grey literature in this field of research. Finally, a series of
inclusion/exclusion criteria were applied, as shown in Table 1.
Table 1
Inclusion/exclusion criteria
|
Inclusion Criteria |
Exclusion Criteria |
|
1) Empirical studies with experimental and
quasi-experimental design with control and experimental group. 2) Studies that analyse the perpetration
variable. 3) Studies focused on primary, secondary,
baccalaureate and university stages. 4) Publications from the last six years
(2015-2022). |
5) Failure to meet the inclusion criteria. 6) Studies that do not contain mean and
standard deviation data. 7) Studies without a control group. 8) Studies without Post-test data. 9) Duplicate articles. 10) Reviews or theoretical studies. |
After
the application of the search equation and of the inclusion/exclusion criteria
number 4 in the different databases, a total of 614 documents were obtained. Of
these, a total of 263 duplicate documents were eliminated. This process was
carried out manually. Subsequently, the remaining 275 studies were screened by
applying inclusion/exclusion criteria 1, 2, 3 and 10. As a result, 107 studies
were selected and assessed for eligibility by applying inclusion/exclusion
criteria 5, 6, 7 and 8. Following this search process and application of the
different inclusion/exclusion criteria, a total of 9 studies were selected. Figure
1 shows the search and screening process up to the selection of the final
sample.
Figure
1. Flow chart.
2.2. Data extraction and coding
Once the
studies had been selected, a data extraction and coding phase was carried out.
The following characteristics were extracted from each study for both the
control group (CG) and the experimental group (EG): (1) sample size; (2) mean
(M) and (3) standard deviation (SD). In addition, other data such as sample
characteristics, methodological approach and type of intervention were also
considered. All this information was collected in an Excel spreadsheet
(Microsoft, Seattle, USA) after detailed reading of each of the studies. This
process was carried out by two independent researchers in order to provide
maximum reliability to the coding process.
Table 2
shows the information on the sample size of each research, the mean and standard
deviation of the dependent variable analysed (perpetration of cyberbullying) in
this study.
Table 2
Correlation
of each study with the analysed variable
|
Author (year) |
Group |
N |
Measures Variable
Perpetration |
|
|
M |
SD |
|||
|
Cross et al (2016a) |
GC |
1548 |
0.03 |
0.14 |
|
GE |
1297 |
0.03 |
0.26 |
|
|
Cross et al (2016b) |
GC |
1245 |
0.03 |
0.25 |
|
GE |
1538 |
0.03 |
0.22 |
|
|
Chauz et al. (2016a) |
GC |
347 |
0.1 |
0.48 |
|
GE |
135 |
0.08 |
0.24 |
|
|
Chauz et al. (2016b) |
GC |
347 |
0.1 |
0.48 |
|
GE |
227 |
0.04 |
0.11 |
|
|
Ortega-Barón (2019) |
GC |
236 |
1.23 |
0.41 |
|
GE |
434 |
1.14 |
0.32 |
|
|
Palladino et al. (2016a) |
GC |
171 |
0.047 |
0.11 |
|
GE |
451 |
0.13 |
0.04 |
|
|
Palladino et al. (2016b) |
GC |
227 |
0.045 |
0.8 |
|
GE |
234 |
0.016 |
0.3 |
|
|
Schultze-Krumbholz et al. (2016a) |
GC |
350 |
0.079 |
0.217 |
|
GE |
136 |
0.081 |
0.184 |
|
|
Schultze-Krumbholz et al. (2016b) |
GC |
350 |
0.079 |
0.217 |
|
GE |
228 |
0.101 |
0.289 |
|
|
Solomontos-kountouri et al. (2016a) |
GC |
478 |
0.12 |
0.46 |
|
GE |
286 |
0.10 |
0.31 |
|
|
Solomontos-kountouri et al. (2016b) |
GC |
542 |
0.13 |
0.42 |
|
GE |
280 |
0.31 |
0.66 |
|
|
Solomontos-kountouri et al. (2016c) |
GC |
478 |
0.13 |
0.43 |
|
GE |
286 |
0.09 |
0.25 |
|
|
Solomontos-kountouri et al. (2016d) |
GC |
542 |
0.14 |
0.42 |
|
GE |
280 |
0.16 |
0.42 |
|
|
DeSmet et al. (2018a) |
GC |
96 |
2.60 |
1.04 |
|
GE |
120 |
2.70 |
1.03 |
|
|
DeSmet et al. (2018b) |
GC |
96 |
2.70 |
0.92 |
|
GE |
120 |
2.85 |
0.92 |
|
|
Gradinger et al. (2015) |
GC |
665 |
0.39 |
0.93 |
|
GE |
1377 |
0.33 |
0.82 |
|
|
Garaigordobil y Martínez-Valderrey (2015) |
GC |
83 |
0.93 |
1.39 |
|
GE |
93 |
0.70 |
1.09 |
|
2.3. Statistical analysis
For the
present meta-analysis, Review Manager (Revman) software version 5.3 was used.
The main analysis tools used were the forest plot and funnel plot (Chen et al.,
2018; Gillette et al., 2018; Hu et al., 2018). The analyses performed were:
effect size, degree of heterogeneity, sensitivity analysis and publication
bias.
3. Results
In this
section, the 9 studies included in the meta-analysis will be analysed. First, a
general description of the studies will be given (time course, research designs
and samples). Then, the results extracted from the meta-analysis will be
interpreted.
General
description of the studies.
Most of
the studies selected for this meta-analysis were published in 2016 (n=6). The
remaining articles were published in 2015 (n=2), 2018 (n=1) and 2019 (n=1).
Regarding the geographical distribution of these research studies, a wide
variety of different regions can be observed, such as Spain, Italy, Cyprus, the
Netherlands, Belgium, Austria and Germany. However, of all of them, Germany
(n=3) and Spain (n=3) stand out as the areas with the highest number of
studies.
In terms
of the most commonly used methodological designs, the experimental design with
QA and EG with a pre-test and a single post-test (33.4%) stands out. Other
designs used in the studies were experimental with QA and EG with pre-test and
several post-tests (22.2 %); quasi-experimental with QA and EG with pre-test
and several post-tests (22.2 %); and quasi-experimental with QA and EG with
pre-test and a single post-test (22.2 %). Within these studies we found several
investigations with one CG and more than one EG (Solomontos-kountouri et al.,
2016; Chaux at el., 2016).
It is
important to note that in the present meta-analysis all possible alternatives
for comparison between groups and post-test measures have been considered. In
this sense, in the study by Solomontos-kountouri et al. (2016) all comparisons
between CG and GE and the different post-test results have been considered
(represented in the diagram as a, b, c and d); in the research by Chaux et al.
(2016) all comparisons between CG and GE have been taken into account (a and
b); and in the studies by Palladino, Nocentini and Menesini (2016),
Schultze-Krumbholz et al. (2016); Cross et al. (2016), DeSmet et al. (2018) the
different measures over time have been taken into account (a, b).
Ultimately,
the research focused on comparing the results obtained by groups that did not
receive any type of intervention (CG) with those that did (GE). The
intervention used in the different studies consisted of the application of
different educational intervention programmes on cyberbullying. These
programmes, although with different strategies and methods, had as fundamental
objectives: conceptualising cyberbullying, raising awareness and sensitisation
towards it, fostering commitment to intervention, developing prevention and
coping strategies; etc. These programmes employed very different methods and
strategies such as the use of ICT (Cross et al., 2016; Palladino et al., 2016),
the use of experts (Gradinger et al., 2015; Palladino et al., 2016; Palladino
et al., 2016), cooperative work (Gradinger et al., 2015; Solomontos-kountouri
et al., 2016) and gamification (Chaux et al., 2016; Schultze-Krumbholz et al.,
2016; DeSmet et al., 2018), among others.
With
regard to the duration of interventions, there is variation between studies,
ranging from one session (Chaux et al., 2016; Schultze-Krumbholz et al., 2016)
to a full year (Gradinger et al. 2015; Cross et al., 2016; Palladino et al.,
2016; Solomontos-Kountori et al., 2016; DeSmet et al., 2018). We also found
studies with a duration of several sessions (Garaigordobil and
Martínez-Valderrey, 2015; Chaux et al., 2016), as well as two
(Schultze-Krumbholz et al., 2016) and 9 months (Ortega-Barón et al., 2019).
With
regard to the study samples, it is worth highlighting the predominance of
studies at the Secondary Education stage (77.8 %), and therefore on subjects
aged between 13 and 17 years (Garaigordobil and Martínez-Valderrey; 2015; Chaux
et al., 2016; Cross et al. 2016; DeSmet et al., 2018; Palladino et al., 2016;
Schultze-Krumbholz et al., 2016; Ortega-Barón et al., 2019). However, there is
also a study focusing on the Primary Education stage (11.1 %) with subjects
aged 10-12 years (Gradinger et al., 2015); and another (11.1 %) focusing on
both stages (Solomontos-Kountori et al., 2016).
Finally,
by way of summary, Table 3 shows the relationship between the different
characteristics of each of the studies selected for the meta-analysis.
Table 3.
Main
characteristics of the studies analysed.
|
Study |
Territory |
Educational Level |
N |
Methodological Design |
Duration |
|
Chaux et al. (2016a) |
Germany |
High School Education |
482 |
R CG O1 – O2 EG O1 X O2 |
1 session |
|
Chaux et al. (2016a) |
Germany |
High School Education |
574 |
R CG O1 – O2 EG O1 X O2 |
15 sessions |
|
Cross et al. (2016a) |
Germany |
High School Education |
2845 |
R CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Cross et al. (2016b) |
Germany |
High School Education |
2783 |
R CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
DeSmet et al. (2018a) |
Belgium |
High School Education |
216 |
R CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
DeSmet et al. (2018b) |
Belgium |
High School Education |
216 |
R CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Garaigordobil y Martínez-Valderrey (2015) |
Spain |
High School Education |
176 |
NE CG O1 – O2 EG O1 X O2 |
19 sessions |
|
Gradinger et al. (2015) |
Austria |
Elementary Education |
2042 |
R CG – O2 EG X O2 |
1 year |
|
Ortega-Barón et al. (2019) |
Spain |
High School Education |
670 |
NE CG O1 – O2 EG O1 X O2 |
9 months |
|
Palladino et al. (2016a) |
Italy |
High School Education |
622 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Palladino et al. (2016b) |
Italy |
High School Education |
461 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Schultze-Krumbholz et al. (2016a) |
Germany |
High School Education |
486 |
R CG – O2 EG X O2 |
1 session |
|
Schultze-Krumbholz et al. (2016b) |
Germany |
High School Education |
578 |
R CG – O2 EG X O2 |
2 months |
|
Solomontos-kountouri et al. (2016a) |
Cyprus |
High school and primary education |
764 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Solomontos-kountouri et al. (2016b) |
Cyprus |
High school and primary education |
822 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Solomontos-kountouri et al. (2016c) |
Cyprus |
High school and primary education |
764 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
|
Solomontos-kountouri et al. (2016d) |
Cyprus |
High school and primary education |
822 |
NE CG O1 – O2 – O3 EG O1 X O2– O3 |
1 year |
3.1.
Meta-analysis results
This
section analyses the overall effects of cyberbullying prevention programmes on
the perpetration of cyberbullying among students. To this end, Figure X shows
the results of the 17 studies (15845 participants) included in the
meta-analysis measuring such an effect (Cross et al., 2016a, 2016b; Chauz et
al, 2016a, 2016b; Ortega-Barón, 2019; Palladino et al., 2016a, 2016b;
Schultze-Krumbholz et al., 2016a, 2016b; Solomontos-Kountouri et al., 2016a,
2016b, 2016c, 2016d; DeSmet et al., 2018a, 2018b; Gradinger et al., 2015;
Garaigordobil and Martínez-Valderrey, 2015).
Overall,
most studies show a significant effect (p < 0.05) in favour of the programme
effect, which could mean that the intervention has decreased the target
variable, i.e. the perpetuation of cyberbullying situations online. The
findings of this meta-analysis show, through the forest plot, that the
educational intervention has a significant effect (P=0.00001) in reducing
bullying behaviour. Thus, the rhombus image to the right of the no effect line
confirms that the difference between groups is statistically significant (P
< 0.05). Therefore, a priori, prevention programmes on cyberbullying exert a
positive effect by decreasing the perpetuation of this type of virtual bullying
situations. In fact, the estimate of the overall effect of the investigations
considered verifies this difference between the EG (n = 7778) and the CG (n =
8067) (SMD = 0.08; CI 95% [0.05, 0.11]; p < 0.00001), showing an oscillation
of the effects between -0.18 and 1.24.
The meta-analysis reported a moderately heterogeneous pooled result
(p=0.00001, I2= 91%) in accordance with the principles of Cohen (1988) and
Hattie (2015). This shows that there are moderate inconsistencies between
studies due to possible differences in samples, experimental conditions or even
in the measures used. However, the heterogeneity could be decreased by applying
a sensitivity of analysis (P=0.16, I2= 26%), with the exclusion of 2 studies
(Palladino et al., 2016a; Solomontos-Kountouri et al. 2016b), after which the
overall effect estimate would still show a statistically significant difference
(SMD=0.03; 95% CI [-0.01, 0.06]; P= 0.16). Therefore, this analysis determines
that the studies by Palladino et al., (2016a) and Solomontos-Kountouri et al.
(2016b) resulted in moderate heterogeneity among the studies analysed in the
meta-analysis.
Figure
2. Forest plot with all results
Figure
3. Forest plot after sensitivity analysis
Regarding
publication bias, Figure 3 shows the distribution of interventions according to
the significance of the effect and the precision of the studies on the
perpetuation of cyberbullying situations in pupils. The graph shows an
asymmetric distribution of studies, of which one of them falls outside the 95%
CI parameters. This could be due to the presence of high heterogeneity (I2:
91%). Furthermore, the distribution of studies in terms of effect size reflects
heterogeneity with respect to the Y-axis, with one study falling outside the
parameters of the research cluster.
Figure
4. Funnel Plot on the distribution of studies of cyberbullying prevention
programmes and their effect on the perpetuation of cyberbullying
4.
Discussion y conclusions
The aim
of this meta-analysis was to analyse the effects of cyberbullying intervention
programmes on the levels of perpetration among students at school. After
searching and applying the inclusion/exclusion filters, 9 studies were included
in the meta-analysis, including a total of 17 different interventions carried
out between 2016 and 2019; 2016 being the year with the highest productivity in
this area with a total of 6 investigations (37.5% of the total). The samples of
the studies are characterised by coming from different geographical locations
but the most predominant were Germany (n=3) and Spain (n=3).
On the
other hand, it should be noted that the most predominant research designs were
characterised by experimental designs with QA and EG and a pre-test and post-test
(33.4%). Furthermore, we consider it very opportune to highlight that in our
review study we have included and assessed all the existing alternatives of
comparison between groups and post-test measures.
With
regard to the purposes of the selected studies, it is important to point out
that, despite pursuing a common objective, namely to assess the effectiveness
of a cyberbullying prevention programme in the sample/participants, they also
had other relevant objectives. These included making these situations of
bullying visible in the educational centre, providing a conceptualisation of
the term, raising awareness and encouraging greater commitment to eradicating
this phenomenon, among others. The use of ICTs and collaborative and active
didactic and methodological strategies were key points in the interventions
analysed. In terms of the duration of the programmes, the time usually ranged
from one session to a full year. It should be noted that the target population
was concentrated in the Secondary Education stage, specifically in the 13-17
age group.
Our
results show that cyberbullying prevention programmes can affect the decrease
in the perpetration of this type of situations in the educational context,
mainly in the secondary school stage. So far, no up-to-date and conclusive
meta-analysis has been conducted on cyberbullying prevention programmes on the
perpetration of online bullying. However, Tanrikulu (2018) conducted a
systematic review of 16 empirical studies published up to 2016. His findings revealed
that in all interventions there were positive effects of this type of
educational programmes in terms of variables of victimisation and perpetration
of bullying situations in students.
Other studies such as that of Lee et al. (2013) concur in this aspect,
reporting that the implementation of a cyberbullying prevention programme in
seventh grade secondary school students immediately and effectively improved
knowledge about cyberbullying, reduced intentions and retained after-learning
effects. In fact, studies such as that of Williford et al., (2010) with a large
sample of participants/school children showed that after the implementation of
Kiva (a cyberbullying prevention programme) students decreased levels of
victimisation and perpetration of bullying situations. Therefore, it was
concluded that Kiva could be an effective programme to address cyber forms of
bullying and victimisation.
In line
with this, a large body of research has echoed the need for education on the
prevention of this type of bullying (Aboujaoude et al. 2015; de la Caba and
Atxurra, 2013; Field, 2018). These studies not only warn of the significant
consequences of its effects, but also highlight its new characteristics, which
raise new questions about the role of the agents involved. Cyberbullying among
students and more specifically, school-aged adolescents has received increased
attention in recent literature (Chisholm, 2014). Moreover, Walker, Craven and
Tokunaga (2013) noted that there is currently a pressing need for meta-analyses
that evaluate the effectiveness of intervention and prevention programmes on
cyberbullying outcomes.
However,
there is currently insufficient empirical evidence on whether existing
school-based anti-bullying programmes are effective in addressing the unpublished
aspects of cyberbullying. To address this important gap, this meta-analysis was
proposed and provides findings that are consistent with other major
international research. Saarento, Boulton and Salmivalli (2015) in their
longitudinal study indicated that, after implementing an anti-bullying
prevention programme, students improved their knowledge about psychosocial
developmental processes contributing to bullying and victimisation.
Furthermore, this study shed light on those key mechanisms by which bullying
can be successfully counteracted.
This
study focused on studying the effects of cyberbullying prevention programs on
the variable of perpetration over time. Some similar studies found significant
findings in this particular area of study. For example, in the United States
(Espelage et al., 2018), Canada (Riddell et al., 2018) or the United Kingdom (Gaffney and
Farrington, 2018) positive effects of prevention programmes on this study
variable were reported. Even in the Spanish context, systematic reviews of the
literature have been developed that have clarified the potential of this type
of programme (Zych et
al., 2016). This
research also pointed to the influence of factors such as gender, family, age
or ethnicity on the prevalence of variables such as victimisation and
perpetration of cyberbullying. Despite this, research suggests that
cyberbullying is a prevalent form of interpersonal aggression in today's modern
society and is therefore an important topic for intervention and prevention.
4.1. Research limitations and strengths
This
meta-analysis shows as main weakness the inaccuracy of some cyberbullying
prevention programmes. Applications of educational prevention programmes can be
very diverse. Some research does not describe in depth the type of programme
used, the duration and the internal organisation. Also, some studies do not
take into account contextual and situational factors and other variables
performed by students during their daily habits, which may bias the results.
These moderating factors could be important in explaining the conceptual
heterogeneity of cyberbullying prevention programmes. In this sense, it would
be interesting to include contextual, situational and methodological moderators
in future proposals. These limitations make it difficult to know the true
effectiveness of cyberbullying prevention programmes. Despite the above, this
is the first time that a meta-analysis classifies and analyses solely and in
details the effects of cyberbullying perpetration, making it one of the most
specialised reviews in this particular line. The scope of this work has been
limited to educational prevention programmes and we have provided educational
implications of this type of interventions in the educational context for
students which are developed below.
4.2. Findings and educational implications of
cyberbullying prevention programmes in the educational context
This
meta-analysis has shown that cyberbullying prevention programmes have a
potential that had not been recognised until now. Incorporating active and
collaborative methodologies in this type of programmes was an added value that
reinforced the desired study variable: to decrease the perpetration of bullying
on the web over time. Therefore, we consider that one of the main educational
implications of this study should be to increase the use of cyberbullying
prevention programmes in schools. In this sense, it would be necessary to
promote the introduction of these programmes in the classroom in educational
legislation. Cyberbullying prevention programmes could be used as a point to be
included in teaching planning and teaching units. In fact, it would be
interesting to train teachers in this type of programmes, in order to
incorporate the whole mechanism and the correct structure in their professional
teaching performance. One recommendation is to use technology and active
learning. In line with this, it is necessary to highlight that at the public
policy level, Spain is making efforts to eradicate this type of violence and
this has been reflected in the new educational law LOMLOE (2020). This organic
law aims to deal with bullying and other highly relevant issues, such as sexual
identity or ecological awareness, developing critical skills and attitudes in
students towards situations in which respect for peers and life in general are
basic and indisputable.
Within
the school context, other alternatives that are proving interesting are peer
group structures, where young people socialize and group with each other to
conform to peer expectations and learn how social organizations work from an
ethical and committed perspective (Romera et al., 2016). Even educational
centers are betting on a new figure, the cyber helper. This figure promotes
student participation by freely assuming a commitment to identify and denounce
these situations of harassment, and as a mediator in the resolution of such
conflicts arising from the use of the Internet (Wachs, 2012).
In
addition, these initiatives should be supported by training actions and
comprehensive bullying prevention programs for the entire educational
community. The development of this training should move towards the learning of
e-skills. In this way, different interventions and activities could be directed
to promote communication skills, empathy and peaceful conflict resolution among
peers (Bautista et al., 2022; Montoro and Ballesteros, 2016).
There is
a need for more scientific production aimed at analysing the duration, frequency
and type of stimuli suitable for structuring bullying prevention programmes in
the school context. In addition, future research is invited to go beyond the
educational setting and consider other variables and factors that extend
outside the educational environment and that are equally relevant, as well as
to focus new lines of research on the important role of the cyberassistant
student as an essential part of this type of situation. Furthermore, little is
known about possible age and gender differences in their effects, so these
results should be considered with caution. It would also be necessary to
clarify the possible impact of unanalysed confounding factors, such as
socio-economic and cultural background. Finally, It is suggested that the possible
effects of cyberbullying prevention programmes on other potential variables
such as educational values, emotional intelligence, psychosocial aspects, among
others, should be explored further.
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