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European Journal of Special Needs Education
ISSN: 0885-6257 (Print) 1469-591X (Online) Journal homepage: http://www.tandfonline.com/loi/rejs20
Social problem-solving among disadvantaged and
László Kasik, Fejes József Balázs, Kornél Guti, Csaba Gáspár & Anikó Zsolnai
To cite this article: László Kasik, Fejes József Balázs, Kornél Guti, Csaba Gáspár & Anikó
Zsolnai (2017): Social problem-solving among disadvantaged and non-disadvantaged adolescents,
European Journal of Special Needs Education, DOI: 10.1080/08856257.2017.1300166
To link to this article: http://dx.doi.org/10.1080/08856257.2017.1300166
Published online: 13 Mar 2017.
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EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION, 2017
Social problem-solving among disadvantaged and
László Kasika,b, Fejes József Balázsa, Kornél Gutic, Csaba Gáspárd and Anikó Zsolnaia,b§
aInstitute of Education, University of Szeged, Szeged, Hungary; bUniversity of Szeged Social Competence
Research Group, Szeged, Hungary; cDr. Farkasinszky Terézia Drug Ambulance, Szeged, Hungary; dDoctoral
School of Education, University of Szeged, Szeged, Hungary
The study examined the dierences of social problem-solving (SPS)
among 12-, 14- and 16-year-old Hungarian disadvantaged and non-
disadvantaged adolescents (N=382) and investigated the relationship
between SPS and family background (FB). SPS was measured
through students’ own and their teachers’ evaluations by an adapted
questionnaire (Social Problem-Solving Inventory–Revised, factors:
negative/positive problem orientation, rationality, impulsivity and
avoidance). Based on the total values of SPS, the dierence between
disadvantaged and non-disadvantaged adolescents was signicant
in all age groups in the case of negative orientation. The dierence
was signicant in the case of impulsivity at the age of 12; in the case
of avoidance at the age of 14; in the case of rationality and avoidance
at the age of 16. FB had the strongest link with negative orientation,
impulsivity and avoidance. In case of impulsivity and avoidance,
variance explained by FB was higher among 16-year olds than among
12- and 14-year olds.
A growing number of school-based intervention programmes are available to promote stu-
dents’ social and emotional learning (SEL), and improving social problem-solving (SPS) is an
important area of SEL interventions. The target groups of these programmes are usually
classes or school communities where students have a lower or mixed socio-economic status
(SES) (e.g. Durlak et al. 2011; Webster-Stratton 2011). Although family background (FB) plays
a key role in the development of SPS and intervention programmes aim to form SPS among
disadvantaged students, relatively little attention has been devoted to the relationship
between SES and SPS thinking and behaviour. Exploring this area may help to identify target
groups more precisely and to organise special intervention programmes which suit their
needs more appropriately.
SPS is the cognitive-behavioural process by which individuals attempt to resolve problems
in their social environment (Chang, D’Zurilla, and Sanna 2004). SPS plays an important role
in the quality of social interactions as well as in the well-being of the individual. Empirical
© 2017 Informa UK Limited, trading as Taylor & Francis Group
disadvantaged and non-
Received 20 November 2016
Accepted20 February 2017
CONTACT László Kasik email@example.com
§Eötvös Loránd University Faculty of Education and Psychology, Budapest, Hungary
2 L. KASIK ET AL.
studies have found that deciencies in SPS are related to a wide range of adjustment out-
comes, including anxiety, depression, aggression, substance abuse and further oending
behaviour (Dodge and Price 1994; Keltikangas-Järvinen 2005). SPS has a moderating and a
mediating role in the relationship between life events and social adjustment. A number of
studies have found that developed SPS can reduce the impact of negative life stress, depres-
sive symptoms, anxiety and support behavioural and academic adjustment, whereas decit
in SPS increases the negative impacts on well-being (Chang, D’Zurilla, and Sanna 2004).
Family members serve as role models in SPS; in addition, parenting and interactions
among family members are also important (Keltikangas-Järvinen 2005). Especially mothers,
as most often primary caregivers, are inuential in the development of their children’s SPS
thinking and behaviour. Research suggests that mothers providing positive reinforcement
to their children, asking guiding questions, modelling good listening skills, displaying
warmth and sensitivity and resolving conicts openly and constructively have children whose
SPS is more eective in their family as well as in other social environments (Martin et al. 2011;
Miller, Murry, and Brody 2005). Family structure and one’s position within that structure
during childhood and adolescence might be one of the most important factors to inuence
problem-solving behaviour (Grusec and Davidov 2007). The parents’ behaviour during family
free time activities and during learning with their children can also have a signicant eect
(Hoerth and Sandberg 2001; Kasik 2014). Higher parental SPS has been found to be related
to the SPS of children and youth (Martin et al. 2011). Mothers’ strategies in marital conicts
have been found to inuence children’s SPS (Goodman et al. 1999). Family climate, rigidity,
attachment style, attachment security, maternal sensitivity and parent–child conicts have
also been associated with children’s SPS (Arslan, Arslan, and Ari 2012; Ciarrochi, Leeson, and
Heaven 2009; Raikes and Thompson 2008).
Although the link between SES and children’s social competence is not as consistent as
the link with cognitive development, there is substantial evidence that children from low
SES families more often manifest symptoms of maladaptive social functioning than children
from more favourable circumstances (Bradley and Corwyn 2002; Yeung, Linver, and Brooks-
Gunn 2002). However, there is no empirical study which focuses on how the disadvantaged
FB inuences the development of SPS, yet all the indirect evidence suggests that there is an
association between the disadvantaged FB and the underdeveloped SPS thinking and behav-
iour. In families with low SES circumstances, supporting the development of SPS is presum-
ably more unfavourable and conicts among family members are more likely. A number of
reports have shown that SES has an impact on family life, such as parents’ relationship,
parent–child conicts and, through these factors, the adjustment of children and adolescents
(Bradley and Corwyn 2002; Conger, Conger, and Martin 2010). Some studies suggest that
poverty hampers maternal sensitivity, so the likelihood of insecure attachment is higher in
families with low SES than in more favourable counterparts (Diener, Nievar, and Wright 2003;
van IJzendoorn and Bakermans-Kranenburg 2010). Family economic hardship and pressure
predict interparental conicts and problems in parenting; for instance, harsh, inconsistent
and uninvolved child-rearing practices (Solantaus, Leinonen, and Punamäki 2004). In addi-
tion, families with favourable economic resources are able to make considerable investments
in the development of their children, whereas families with low SES must invest in more
immediate needs (Bradley and Corwyn 2002; Duncan and Magnuson 2003; Linver, Brooks-
Gunn, and Kohen 2002). According to an alternative line of reasoning, both SES and family
processes are explained by individual dierences in the personal characteristics of family
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 3
members; for instance, by their interpersonal skills. Interpersonal skills inuence the positions
in the labour market and the parenting skills or the relationships of family members (Lykken
2002; McLanahan and Percheski 2008). Moreover, there is a link between SES and family
structure; for instance, living in poverty is more likely in the case of single-parent families
than in the case of two-parent families. Probably, the reason for this is the conicts between
parents which are more likely in economic hardship (Brown 2010; de Graaf and Kalmijn 2006;
Liu and Vikat 2004; Thomson and McLanahan 2012).
The theoretical framework used in present study is a model developed by D’Zurilla, Nezu,
and Maydeu-Olivares (2004). For the formulation of the detailed hypothesis about the dif-
ferences between disadvantaged and non-disadvantaged adolescents’ SPS, we could mainly
rely on empirical works that used the questionnaire of this model, which is the Social
Problem-Solving Inventory–Revised (SPSI–R, D’Zurilla, Nezu, and Maydeu-Olivares 2002).
The SPSI–R is a theory-based measure of social problem-solving processes and it consists of
ve dimensions (negative and positive problem orientation, rationality, impulsivity and
avoidance style). This inventory provides a comprehensive assessment of all theoretical
components in relation to contemporary models of SPS and it is one of the most widely
accepted instruments in SPS assessment.
Siu and Shek (2010) explored the relationship between 11- and 17-year-old adolescents’
SPS and well-being of their families with the help of the Chinese version of the SPSI–R and
questionnaires for family functioning and the perceived level of conict between adolescents
and their parents. The SPS total score had positive correlations with all ve subscales of the
family functioning (mutuality, communication, conict/harmony, parental concern and con-
trol). The negative problem-solving subscales (avoidance, negative problem orientation and
impulsivity) are associated with lower family functioning, while the positive subscales (ration-
ality, positive problem orientation) are associated with higher family functioning. The highest
correlation was found in the case of avoidance style. This subscale had signicant negative
correlations with the subscales of family functioning. The avoidance style of adolescents
was a signicant predictor of conicts for three of the four dyads (mother–son, mother–
According to a Hungarian longitudinal study which examined 12- to 14-year-old adoles-
cents’ SPS, parents’ educational levels has a low but signicant eect on the SPSI–R subscales
(Kasik 2014). Parents’ education inuence the SPS factors dierently: mothers’ educational
level has an eect on negative orientation and impulsivity and fathers’ educational level has
an impact on rationality. Results have suggested that the impact of the amount of common
free time activities on children’s SPS is similar to the level of parental education.
Aims and hypothesis
This study examines the role of FB in the characteristics of SPS among adolescents in order
to tailor the intervention programmes to disadvantaged youth, which is one of the most
frequent target groups of the interventions programmes that address SPS. On the one hand,
the aim was to reveal the dierences of SPS between disadvantaged and non-disadvantaged
adolescents according to their own as well as their teachers’ evaluations. On the other hand,
the study mapped the connection of SPS and some basic indicators of FB.
Based on theoretical arguments, we hypothesised that the SPS of disadvantaged adoles
cents was less improved than that of their non-disadvantaged peers. According to previous
4 L. KASIK ET AL.
research, SES has an impact on family life, and family life has been related to the SPS of
adolescents. Based on empirical ndings we hypothesised that disadvantaged adolescents
approach social problems negatively more often, they prefer to use the avoidance style in
social problems, and they tend to solve interpersonal problems based on emotions.
The surveys were carried out in the primary and secondary (vocational) schools of ve coun-
ties in Hungary with the participation of 382 adolescents (182 boys and 200 girls). However,
age-related dierences exist in many aspects of SPS; according to international and Hungarian
studies, changes in SPS are robust during the period of adolescence (Berg and Strough 2011;
D’ Zurilla, Maydeu-Olivares, and Kant 1998; Kasik 2014; Rich and Bonner 2004). In order to
increase the generalisability of our results and considering the age factor of the instrument
used, three adolescent age groups were chosen: 12-, 14- and 16-year olds (126, 124, 132
The sample is not representative. The selection criteria was twofold: not only did we select
classes with disadvantaged adolescents, it was also essential that these classes were heter-
ogeneous in terms of socio-economic background in order to compensate for the potential
inuence of peers (see Chang 2004; Juvonen and Cadigan 2002). There were ve classes
involved in each age group. The classes were categorised based on their proportion of dis-
advantaged adolescents. One class in each age group fell into one of the following categories:
1–20%; 21–40%; 41–60%; 61–80%; and above 81%.
The disadvantaged status of participants was reported by the teachers based on the
available ocial documentation. Hungarian law dierentiates between disadvantaged and
multiply disadvantaged students. Based on these legal denitions, support may be granted
to alleviate the eects of the unfavourable FB and home environment in educational insti-
tutions (e.g. free books, lunch and extracurricular activities or a reduced rate for these ser-
vices, special development programmes). At the time of data collection, the law in force
(Public Education Act of 1993) dened students as disadvantaged if they were taken into
protection by the notary pursuant due to their family conditions or social status and/or
children whom the notary declared eligible for regular child protection benets (households,
where the monthly income per person in the family was low relative to the current minimum
pension). Within this group, the status of being multiply disadvantaged resulted from par-
ents’ educational level, which may not be higher than primary school qualication, and also
from placement in long-term state care. A relatively low rate (22%) of the disadvantaged
students of the sample were multiply disadvantaged, therefore, we combined these two
categories in our research. Both directly and indirectly, the criteria of the disadvantaged
status used by Hungarian laws concern the nancial status of the students’ family; in other
words, the disadvantaged status means low SES. The ratio of the disadvantaged status was
similar in each subgroup (12-year olds: 48%, 14-year olds: 50%, 16-year olds: 52%).
Background questionnaires were lled out by the parents (mothers in 86% of the cases)
who also stated the following: (1) level of education (mother and father), (2) type of family
(family structure), (3) the most common family free time activity and (4) number of books
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 5
We used four categories to indicate parents’ level of education (1 = primary school;
2 = vocational school; 3 = high school; and 4 = college/university). The ratio of parents with
primary school education, including mothers and fathers, was the lowest among non-dis-
advantaged children (mothers: 19–28%; fathers: 22–33%) and that of parents with high
school qualications was the highest (mothers: 29–37%; fathers: 25–35%). In the case of
disadvantaged adolescents, most of the mothers, including all age subsamples, held a voca-
tional degree (45–76%), and this was true of the fathers as well (37–65%), among whom the
ratio of primary school graduates was the highest (25–39%). The distribution of educational
qualications was dierent (χ
= 12.15, p = .04) in the two subsamples (non-disadvantaged/
Parents also stated who the child lives with within the family and thus, based on this
information, we created eight categories: 1 = child with mother and father; 2 = child only
with mother; 3 = child only with father; 4 = child with mother, father and sibling; 5 = child
with mother and sibling; 6 = child with father and sibling; 7 = child with grandparent(s); and
8 = child with parents and grandparents. Non-disadvantaged adolescents, in all age sub-
samples, fell into categories 1, 2 and 5, whose percentage added up to 59–81%. The com-
bined number of disadvantaged adolescents who fell into categories 2, 4 and 5 was 61–84%.
There was a signicant dierence (χ2 = 10.23, p = .03) in terms of the proportion of the two
We established categories for the most common family free time activities based on
parents’ answers: 1 = excursion; 2 = watching TV; 3 = theatre, cinema, exhibition; 4 = shop-
ping; 5 = gardening, household chores; 6 = playing sports; 7 = none. 62–82% of the parents
of disadvantaged adolescents stated that they either watched TV together (2) or did nothing
(7) as they did not organise programmes together. Number 2 as well as numbers 5 and 6
were the most common mutual activities among non-disadvantaged adolescents, their
percentage being 65–83%. The distribution showed a signicant dierence (χ2 = 11.01,
p = .04) in the case of two subsamples (non-disadvantaged/disadvantage).
In order to indicate the number of books at home, one of the signiers of cultural capital,
we used ve categories: 1 = we do not own any books; 2 = less than 50; 3 = 50–200; 4 = 200–
1000; and 5 = more than 1000. The combined percentage of categories 2, 3 and 4 added up
to 80–92% in the case of non-disadvantaged adolescents, a similar number to the disadvan-
taged adolescents’ (82–94%) for categories 1, 2 and 3. The dierence was signicant
(χ2 = 10.23, p = .03).
An adapted questionnaire was applied to evaluate SPS (SPSI–R, D’Zurilla, Nezu, and Maydeu-
Olivares 2002). The instrument measured ve aspects of SPS: positive and negative problem
orientation towards the problem (the motivational background that denes the decision)
as well as rationality, impulsivity and avoidance. The SPSI–R consists of 25 statements (5 × 5
items). The items of positive orientation explored the frequency of one’s positive orientation
to the problem (as well as how the problem-solvers saw themselves, the situation and the
other person), while the items of negative orientation revealed the frequency of negative
orientation. Items that belonged to the rationality factor may account for the method of
information management which plays a role in decision-making, while items regarding
impulsivity may help to analyse the method of handling emotions that aect the decision
6 L. KASIK ET AL.
as well as the solution. Items in relation to avoidance are connected to the rejection of the
problem and the avoidance of making a decision and seeking a solution. The level of agree-
ment or disagreement with the statements of the questionnaire was rated on a ve-level
scale (1 = Not at all true of me; 5 = Extremely true of me).
According to previous studies in the eld of social competence, the accuracy of self-
assessment and the agreement among evaluators are aected by several factors. What is
relevant from these factors for the present research is the fact that the accuracy of self-
perception in some areas of social competence is poorer among students with lower SES,
among young students (Youngstrom and Green 2003) and among low-achieving students
(Nowicki 2003). In addition to this, agreement among evaluators is dependent on which
component of social competence is examined (Junttila et al. 2012; Pakaslahti and Keltikangas-
Järvinen 2000). It is essential to use another source to compare the agreement between the
adolescents’ own assessments and to compare the agreement between evaluators in order
to interpret the dierences found between disadvantaged and non-disadvantaged adolescents.
We used two variants of SPSI–R: adolescents’ personal statements and evaluations by
teachers. The latter was identical with the adolescents’ version, however, it contained state-
ments about the adolescents in third-person singular. The original questionnaire was rst
translated into Hungarian, then the resulting Hungarian version was translated back to
English, and the Hungarian version to be used was nalised only after clarifying all points
that turned out to be potentially problematic in the process. This nal Hungarian version,
which contains questionnaires for adolescents, for their parents as well as for their teachers,
was used in several previous studies in heterogeneous age groups (12–18-year-old adoles-
cents). Psychometric indicators of the instrument were satisfactory in all cases; factor analysis
shows that the Hungarian version has the same factor structure as the original questionnaire.
Moreover, there is information on the convergent and divergent validity of the instrument
(Kasik 2014; Kasik et al. 2016; Zsolnai and Kasik 2016). All versions of the Hungarian adapta-
tion (adolescents’ and teachers’) showed adequate factor structure in all ages under exam-
ination: the KMO index was .81 for the adolescents’ questionnaire and .84 for the teachers’.
Table 1 contains the questionnaire’s reliability indicators according to the age subsamples
and according to those giving the evaluations.
The research was conducted with the permission of the headmasters and in accordance
with privacy regulations. The heads of the selected institutions were informed in advance
about the purpose of the survey. Students were asked to forward the parent questionnaires
Table 1.Cronbach-α values according to age subsamples and those giving the evaluations.
12-year olds 14-year olds 16-year olds
Student Teacher Student Teacher Student Teacher
Positive problem orientation .77 .84 .81 .88 .82 .97
Negative problem orientation .85 .89 .87 .91 .92 .90
Rationality .84 .87 .90 .92 .91 .87
Impulsivity .82 .90 .88 .90 .89 .89
Avoidance .88 .92 .92 .92 .91 .88
Complete questionnaire .84 .90 .90 .92 .91 .89
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 7
on FB aspects to their parents. Students had 30 min to ll out the questionnaire. Their work
was observed by their teachers. Teachers were asked to rate their students without checking
students’ own personal statements and give information about the disadvantaged status of
In order to identify the dierence between disadvantaged and non-disadvantaged adoles-
cents’ SPS in the case of some of the subsamples, we utilised an independent sample t-test.
In order to determine how the raters’ judgements relate to the factors, Pearson’s r was com-
puted, completed with a z-test to check the generalisability of the strength dierences
between the correlations. The distribution of the family variables was determined with the
χ2 test. In order to reveal the relation of the background variables to the factors, regression
analysis was used.
First, we discuss the results of disadvantaged and non-disadvantaged adolescents in the
light of their personal statements, teachers’ evaluations and the average of these two scores
(on a combined index). Then, we summarise the results of the analysis aimed at mapping
the connection between the students’ and the teachers’ evaluations and, following this, we
present the connection of family characteristics with the factors of the combined index.
Dierences in SPS between disadvantaged and non-disadvantaged students
Table 2 contains the characteristics of disadvantaged and non-disadvantaged students’ SPS
split-up according to age and assessor. Column CI contains the results of the combined index.
Values represented against a grey background indicate a signicant dierence (p < .05 in all
Based on personal statements, teachers’ assessments and the combined index, there was
a signicant dierence between disadvantaged and non-disadvantaged adolescents in case
of two factors in all three age groups (Table 2). According to personal statements, negative
orientation and impulsivity were typical of the disadvantaged in all three age groups: they
more often interpreted the problem as an absolutely negative phenomenon, they did not
have faith in the possibility of its solution and they believed that attempting to solve the
problem would only lead to negative consequences rather than positive, both in the short
and long run. In addition to this, they attributed bad, negative and unpleasant feelings to
problem-solving. Avoidance, abandoning the problem situation and postponing the solution
was also frequent among the 14- and 16-year-old disadvantaged. Rationality, taking into
consideration causal relations and facts regarding the people in the problem situation as
well as seeking other, alternative means of solution and evaluation was more common
among 16-year-old non-disadvantaged students.
Teachers rated the youngest adolescents similarly: negative orientation and impulsivity
were more common in the case of the disadvantaged and positive orientation was typical
of the non-disadvantaged, and teachers thought positive orientation was more typical
among non-disadvantaged adolescents in the oldest age group as well. Negative orientation
8 L. KASIK ET AL.
Table 2.Means and standard deviations in the factors according to age, person evaluating and sub-sample.
Notes: PO=Positive Problem Orientation; NO=Negative Problem Orientation; R=Rationality; I=Impulsivity; A=Avoidance; DA=Disadvantaged; NDA=Non-Disadvantaged; CI=Combined Index;
M=Mean; SD=Standard Deviation; grey background: p<.05
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 9
and avoidance were more frequent among 14- and 16-year-old disadvantaged students
than among the non-disadvantaged and, in the meantime, teachers believed that rationality
occurred more frequently when adolescents of the latter group solved an interpersonal
Based on negative orientation in the combined index, the dierence between the disad-
vantaged and the non-disadvantaged was substantial in all three age groups. There was a
considerable dierence in terms of impulsivity among 12-year olds, avoidance among 14-
and 16-year olds and rationality among the oldest adolescents.
Relationship between students’ and teachers’ evaluations
The opinions of those preparing the evaluations were compared according to the ve factors
of SPS with the help of correlation analysis. We studied whether there is a dierence with
regard to the disadvantaged status in the relationship between the evaluators among the
three age groups. Results are summarised in Table 3.
The relationship between students’ personal statements and teachers’ evaluations was
in line with earlier observations, especially in the subsample of the disadvantaged and less
among the non-disadvantaged students: correlations were stronger in terms of most of the
factors in the case of secondary school students. Based on z-tests, there was no dierence
in terms of the strength of the relationship between positive orientation, impulsivity and
avoidance in the subsample of non-disadvantaged students. The relationship was stronger
among 14- and 16-year olds than among the youngest age group in terms of negative ori-
entation (z = 3.14, p = .03) and rationality (z = 2.48, p = .01). There was no deviation in terms
of the strength of the connection between positive and negative orientation among disad-
vantaged students. The relationship was stronger in terms of rationality (z = 2.54, p = .02)
and avoidance (z = 3.09, p = .03) among 16- than among 12- and 14-year olds. The connection
in terms of impulsivity was stronger among 14- (z = 4.05, p = .02) and 16-year olds (z = 4.74,
p = .02) than among the youngest.
Table 3. Correlation between students’ and teachers’ evaluations split up according to age and
Note: DA=Disadvantaged; NDA=Non-Disadvantaged. Grey background: signiﬁcant diﬀerence based on z-test (p<.05).
10 L. KASIK ET AL.
Any signicant discrepancy between the age groups and factors examined according to
the relationship between students’ (disadvantaged and non-disadvantaged) and teachers’
evaluations was indicated with a grey background in Table 3. The dierence was notable
only among 12-year olds in terms of positive and negative orientation, in terms of rationality
only among 14-year olds, in terms of impulsivity among 14- and 16-year olds, and in terms
of avoidance only among 16-year olds. Evaluations were more similar with regard to positive
orientation (z = 3.29, p = .03) and rationality (z = 2.95, p = .03) among non-disadvantaged
students, while they were more similar with regard to impulsivity (z = 2.55, p = .02) and
avoidance (z = 2.59, p = .03) among disadvantaged students. According to the patterns of
correlations, the agreement among evaluators was higher in the case of those factors (neg-
ative orientation, impulsivity, avoidance) where notable dierences were found between
disadvantaged and non-disadvantaged adolescents.
Relationship between SPS and FB variables
We performed regression analysis based on the combined index of students’ personal state-
ments and teachers’ assessments. Dependent variables were the factors of SPS; the charac-
teristics of the FB (mother’s education, type of family, free time activity in family, number of
books at home) were the independent variables. Tables 4, 5 and 6 contain the results of the
analysis broken down by age.
Based on the results of the regression analysis, the role of the mother’s education was
predictive in the case of impulsivity among 12-year olds, and in the case of impulsivity,
negative problem orientation and avoidance among 14- and 16-year olds. The type of family
had the most important role in inuencing the above-mentioned variables among 16-year
olds, while its value was signicant in the case of negative orientation among 12-year olds.
Table 4.Results of regression analysis (12-year olds).
Notes: PO=Positive Problem Orientation; NO=Negative Problem Orientation; R=Rationality; I=Impulsivity; A=Avoid-
ance; ME=Mother’s education; TOF=Type of family; FTA=Free time activity in family; NOB=Number of books at home;
the values are the products of B (unstandardised estimates) and β (standardised estimates); n.s.=not signiﬁcant.
Independent variables Dependent variables
PO NO R I A
ME .046 .052 .051 .068 .045
TOF .082 .10 .086 .084 .083
FTA .012 .042 .025 .019 .024
NOB .013 n.s. .022 .014 n.s.
Explained variance (R2, %) 15.9 20.1 19.5 20.2 18.1
Table 5.Results of regression analysis (14-year olds).
Note: See Table 4.
Independent variables Dependent variables
PO NO R I A
ME .052 .069 .057 .068 .075
TOF .079 .078 .063 .072 .069
FTA .026 .011 .017 .014 .027
NOB .013 n.s .019 .013 n.s.
Explained variance (R2, %) 20.2 18.1 17.1 18.2 18.4
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 11
Free time activity in the family had a relevant relationship with negative orientation among
12-year olds. The number of books at home did not play a considerable role in the operation
of the examined SPS areas. Moreover, the number of books at home did not have a signicant
role in negative orientation and avoidance in any age group.
Variances explained by all background variables were similar in all age groups, except for
positive problem orientation, which had a lower explained variance among 12-year olds,
and impulsivity and avoidance, which had a higher variance among 16-year olds. The type
of family had the most inuential role on SPS in all age groups from the independent vari-
ables under investigation, while the mother’s education was also signicant. Free time activ-
ity and the number of books had a less signicant role in the status of SPS compared to the
above-mentioned variables. The indicators describing FB were the highest in the case of
negative orientation, impulsivity and avoidance and their role was stronger among 16-year
olds than among 12- and 14-year olds.
We studied the characteristics of SPS and some indicators of FB among 12-, 14- and 16-year-
old disadvantaged and non-disadvantaged students. Our results provide new information
about disadvantaged adolescents which may support the establishment of intervention
programmes, while they also indicate the need for further research.
The characteristics explored supported our hypothesis: on the one hand, there was a
signicant dierence in the SPS of disadvantaged and non-disadvantaged students; on the
other hand, unfavourable FB could be primarily associated with negative orientation,
impulsivity and avoidance. Based on the mean of the evaluations of teachers and students,
we concluded that there was a signicant dierence between disadvantaged and non-
disadvantaged students with regard to negative orientation in all three age groups; there
was a major dierence with regard to impulsivity among 12-year olds; with regard to
avoidance among 14- and 16-year olds; and with regard to rationality in the eldest age group.
The agreement of evaluators was higher in case of those factors (negative orientation,
impulsivity, avoidance) where remarkable dierences were found between disadvantaged
and non-disadvantaged adolescents.
Of the examined indicators of FB, family type played the most inuential role in the
development of SPS but the mothers’ educational level was also of signicant importance.
Both the family type and the mother’s educational level primarily associate with negative
problem orientation, impulsivity and avoidance. The eects of the family type and the moth-
er’s educational level were identiable in all three age groups; however, the impact of the
Table 6.Results of regression analysis (16-year olds).
Note: See Table 4.
Independent variables Dependent variables
PO NO R I A
ME .042 .072 .049 .010 .010
TOF .084 .010 .057 .012 .011
FTA .022 .011 .021 .013 n.s.
NOB .012 n.s. .019 n.s. n.s.
Explained variance (R2, %) 19.3 20.3 18.4 23.5 24.1
12 L. KASIK ET AL.
family type on impulsivity and avoidance was stronger among the 16-year-old adolescents
than among the 12- and 14-year olds. As for the other indicators of FB, the number of books
at home and the free time activities carried out together proved to have a less important
eect on SPS. Negative orientation and emotion management problems are more frequently
observed during adolescence and, in addition, these components of SPS are more unfavour-
able among older adolescents (Kasik 2014). We found that a low SES intensies these char-
acteristics. However, these results do not tell us the underlying causes. These may be objective
causes, meaning that disadvantaged students are indeed faced with more problematic social
situations over time, or they may be subjective causes, meaning that students feel they are
less eective in such situations.
Our results showed that the family type and the parents’ educational level as well as the
status of being disadvantaged (which was based on family income in our study) may help
to select the appropriate schools and class communities during the organisation of school-
based intervention programmes to enhance SPS. Results suggest that SES provides valuable
information in the selection of the target groups for interventions; moreover, the family type
and the mother’s educational level are types of data that are not only easy to gather but
they are also useful in the preparation process of interventions. Interventions targeting
children and adolescents with low SES should primarily focus on inuencing the following
factors: negative problem orientation, avoidance and impulsivity. Results have suggested
that the eectiveness of these programmes could be improved if interventions are tailored
to the target group.
Several pieces of research have found that the peer composition of a student’s class may
inuence social outcomes (Juvonen and Cadigan 2002), yet little attention has been paid to
the role of classmates in aecting adolescents’ SPS. Considering the characteristics of the
Hungarian school system, the inuence of classmates is of key importance. The Hungarian
school system is extremely selective; school and class communities are homogenous in
terms of FB (OECD 2013). Performance is usually lower in disadvantaged communities, where
motivational characteristics of classmates together with their social norms are of central
importance besides the individual motivational characteristics of students. In these classes,
where students are generally disadvantaged and their academic performance is poor, aca-
demic achievement may not be highly appreciated or emphasised as a group norm. Students
may receive approval and endorsement from each other for their shared anti-school attitudes
and socially deviant behaviours in these classes (Fejes 2012). Peer-to-peer learning may be
limited in these communities, while most probably there are more problems to be solved
due to the fact that students’ SPS is less developed.
Previous studies have emphasised that the student composition at schools plays a crucial
role in the success of SEL programmes (Bierman et al. 2010; Hughes et al. 2005). The majority
of programmes aimed at developing the SPS of children and adolescents is embedded in a
school context; therefore, it is worth concentrating on the relationship of the school com-
munity as well as on the development of SPS in the future.
More research is needed to further explore the link between the mechanisms that aect
the SPS of the family environment and the SES. Nonetheless, we may gather more informa-
tion from parents as additional evaluators about their children’s SPS; they may provide inval-
uable information about the home environment. Our data show that family structure has a
key role in the operation of SPS, thus a more thorough examination of this variable is needed.
EUROPEAN JOURNAL OF SPECIAL NEEDS EDUCATION 13
This study is cross sectional, for a clearer picture a longitudinal study is needed with a focus
on the interaction between the development of SPS and the family characteristics.
On the one hand, opportunities for enhancing the less developed SPS of disadvantaged
adolescents can be placed on system-level. In several countries, teachers who have fewer
years of teaching experience and weaker qualications are more likely to teach in classrooms
with higher adversity (OECD 2014), so it may be useful to assign more experienced and
qualied teachers to challenging classrooms in order to enhance disadvantaged adolescents’
SPS. However, relatively little is known about how classroom contexts inuence the social
competence of adolescents, dispersing disadvantaged students across classrooms may sup-
port social–behavioural adjustment. In addition, teacher training and teacher in-service
programmes should emphasise the need to develop teachers’ awareness of peer inuence
and provide strategies to support positive group processes.
On the other hand, on the school or classroom level, the adaptation of available inter-
vention programmes which contain components for developing SPS of children and ado-
lescents would be benecial. In this respect, programmes which target not only the students
but also their parents with low SES could be especially successful (e.g. Webster-Stratton
2011). Moreover, teachers should also be aware that their behaviour in certain situations as
well as the general classroom climate both have an inuence on the development of social
competence (Brophy-Herb et al. 2007; Jennings and Greenberg 2009). Lastly, working with
disadvantaged students can be particularly stressful, and there is a relationship between
the proportion of disadvantaged students in a classroom and the perception of job stress
and satisfaction by teachers, which in turn may have a negative inuence on the classroom
climate, on the social interaction of students with each other and on the teacher–student
relationship (Zhai, Raver, and Li-Grining 2011). Thus, prevention programmes that support
the motivation of teachers, moderate the perception of stress level and prevent burnout in
these challenging schools may indirectly improve social competence and SPS.
No potential conict of interest was reported by the authors.
This work was supported by the European Union and the State of Hungary, co-nanced by the European
Social Fund in the framework of TÁMOP 4.2.4. A/2–11-1–2012-0001 ‘National Excellence Program’. At the
time of research, László Kasik and József Balázs Fejes were holders of the Zoltán Magyary Postdoctoral
Fellowship. At the time of writing this paper, László Kasik was the holder of the János Bolyai Research
Fellowship of the Hungarian Academy of Sciences.
Notes on contributors
László Kasik is an assistant professor of social and emotional education at the University of Szeged,
Hungary and head of the Social Competence Research Group at the University of Szeged, Hungary.
His research areas include development of social competence, coping, social problem-solving and
avoidance among adolescents.
14 L. KASIK ET AL.
Fejes József Balázs is an assistant professor of social and emotional education at the University of
Szeged, Hungary. His research elds are learning motivation, and family and school background of
Kornél Guti is a psychologist at the Dr. Farkasinszky Terézia Drug Ambulance in Szeged, Hungary. His
research areas include development of social problem-solving and anxiety.
Csaba Gáspár is a PhD student at the Doctoral School of Education at the University of Szeged, Hungary.
His research eld is relationship between social problem-solving and empathy among adolescents.
Anikó Zsolnai is a professor at the Eötvös Loránd University, Budapest, Hungar y. Her research interests
are varied and span the eld of education, educational psychology and social psychology. Her main
research interest is in developing children’ social skills.
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