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The study examined the differences 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 difference between disadvantaged and non-disadvantaged adolescents was significant in all age groups in the case of negative orientation. The difference was significant 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.
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European Journal of Special Needs Education
ISSN: 0885-6257 (Print) 1469-591X (Online) Journal homepage:
Social problem-solving among disadvantaged and
non-disadvantaged adolescents
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
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Published online: 13 Mar 2017.
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Social problem-solving among disadvantaged and
non-disadvantaged adolescents
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 dierences 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 dierence between
disadvantaged and non-disadvantaged adolescents was signicant
in all age groups in the case of negative orientation. The dierence
was signicant 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
Social problem-solving;
disadvantaged and non-
disadvantaged students;
Received 20 November 2016
Accepted20 February 2017
CONTACT László Kasik
§Eötvös Loránd University Faculty of Education and Psychology, Budapest, Hungary
studies have found that deciencies in SPS are related to a wide range of adjustment out-
comes, including anxiety, depression, aggression, substance abuse and further oending
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 decit
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 inuential 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 conicts openly and constructively have children whose
SPS is more eective 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 inuence
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 signicant eect
(Hoerth 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 conicts
have been found to inuence childrens SPS (Goodman et al. 1999). Family climate, rigidity,
attachment style, attachment security, maternal sensitivity and parent–child conicts 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 inuences 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 conicts 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 conicts 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 conicts 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 dierences in the personal characteristics of family
members; for instance, by their interpersonal skills. Interpersonal skills inuence 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 conicts 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 conict between adolescents
and their parents. The SPS total score had positive correlations with all ve subscales of the
family functioning (mutuality, communication, conict/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 signicant negative
correlations with the subscales of family functioning. The avoidance style of adolescents
was a signicant predictor of conicts for three of the four dyads (mother–son, mother–
daughter, father–daughter).
According to a Hungarian longitudinal study which examined 12- to 14-year-old adoles-
cents’ SPS, parents’ educational levels has a low but signicant eect on the SPSI–R subscales
(Kasik 2014). Parents’ education inuence the SPS factors dierently: mothers’ educational
level has an eect 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 dierences 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
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 dierences 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
adolescents, respectively).
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
inuence 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 ocial documentation. Hungarian law dierentiates between disadvantaged and
multiply disadvantaged students. Based on these legal denitions, support may be granted
to alleviate the eects 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) dened 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 benets (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 qualication, 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
at home.
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 qualications 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
qualications was dierent (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 signicant dierence (χ2 = 10.23, p = .03) in terms of the proportion of the two
subsamples (non-disadvantaged/disadvantage).
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 signicant dierence (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 signiers 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 dierence was signicant
(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 denes 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 aect the decision
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 aected 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 dierences 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.
SPS’ factor/Complete
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
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
their students.
Statistical analysis
In order to identify the dierence 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 dierences
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.
Dierences 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 signicant dierence (p < .05 in all
Based on personal statements, teachers’ assessments and the combined index, there was
a signicant dierence 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
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
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 dierence between the disad-
vantaged and the non-disadvantaged was substantial in all three age groups. There was a
considerable dierence 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 dierence 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 dierence
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
socio-economic status.
Note: DA=Disadvantaged; NDA=Non-Disadvantaged. Grey background: significant difference based on z-test (p<.05).
*p<.05; **p<.01
Any signicant 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 dierence 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 dierences 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 inuencing the above-mentioned variables among 16-year
olds, while its value was signicant 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
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
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
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 signicant
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 inuential role on SPS in all age groups from the independent vari-
ables under investigation, while the mother’s education was also signicant. Free time activ-
ity and the number of books had a less signicant 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
signicant dierence 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 signicant dierence between disadvantaged and non-
disadvantaged students with regard to negative orientation in all three age groups; there
was a major dierence 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 dierences were found between disadvantaged
and non-disadvantaged adolescents.
Of the examined indicators of FB, family type played the most inuential role in the
development of SPS but the mothers’ educational level was also of signicant importance.
Both the family type and the mother’s educational level primarily associate with negative
problem orientation, impulsivity and avoidance. The eects of the family type and the moth-
er’s educational level were identiable 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
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
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
eect 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 intensies 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 eective 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 inuencing the following
factors: negative problem orientation, avoidance and impulsivity. Results have suggested
that the eectiveness 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
inuence social outcomes (Juvonen and Cadigan 2002), yet little attention has been paid to
the role of classmates in aecting adolescents’ SPS. Considering the characteristics of the
Hungarian school system, the inuence 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 aect
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.
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 qualications are more likely to teach in classrooms
with higher adversity (OECD 2014), so it may be useful to assign more experienced and
qualied teachers to challenging classrooms in order to enhance disadvantaged adolescents
SPS. However, relatively little is known about how classroom contexts inuence 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 inuence
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 benecial. 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 inuence 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 inuence 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.
Disclosure statement
No potential conict 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.
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
disadvantaged students.
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.
Arslan, E., C. Arslan, and R. Ari. 2012. “An Investigation of Interpersonal Problem Solving Approaches
with Respect to Attachment Styles.Educational Sciences: Theory & Practice 12: 15–23.
Berg, C. A., and J. Strough. 2011. “Problem Solving across the Life Span. In Handbook of Life-Span
Psychology, edited by K. Fingerman, C. A. Berg, T. Antonnuci, and J. Smith, 239–267. New York:
Bierman, K. L., J. D. Coie, K. A. Dodge, M. T. Greenberg, J. E. Lochman, R. J. McMahon, and E. Pinderhughes.
2010. “The Eects of a Multiyear Universal Social-Emotional Learning Program: The Role of Student
and School Characteristics.Journal of Consulting and Clinical Psychology 78: 156–168.
Bradley, R. H., and R. F. Corwyn. 2002. “Socioeconomic Status and Child Development.Annual Review
of Psychology 53: 371–399.
Brophy-Herb, H. E., R. E. Lee, M. A. Nievar, and G. Stollak. 2007. “Preschoolers’ Social Competence:
Relations to Family Characteristics, Teacher Behaviors and Classroom Climate.Journal of Applied
Developmental Psychology 28: 134–148.
Brown, S. L. 2010. “Marriage and Child Well-being: Research and Polic y Perspectives.Journal of Marriage
and Family 72: 1059–1077.
Chang, L. 2004. “The Role of Classroom Norms in Contextualizing the Relations of Children’s Social
Behaviors to Peer Acceptance. Developmental Psychology 40: 691–702.
Chang, E. C., T. J. D’Zurilla, and L. J. Sanna. 2004. Social Problem Solving. Theory, Research, and Training.
Washington, DC: American Psychological Association.
Ciarrochi, J., P. Leeson, and P. C. L. Heaven. 2009. “A Longitudinal Study into the Interplay between
Problem Orientation and Adolescent Well-being.Journal of Counseling Psychology 56: 441–449.
Conger, R. D., K. J. Conger, and M. J. Martin. 2010. “Socioeconomic Status, Family Processes,and Individual
Development.Journal of Marriage and Family 72: 685–704.
D’ Zurilla, T. J., A. Maydeu-Olivares, and G. L. Kant. 1998. “Age and Gender Dierences in Social Problem
Solving in College Students, Middle Age, and Elderly Adults.Personality and Individual Dierences
25: 241–252.
D’Zurilla, T. J., A. Nezu, and A. Maydeu-Olivares. 2002. Social Problem-solving Inventory–Revised (SPSI–R):
Technical Manual. North Tonawanda, NY: Multi-Health Systems.
D’Zurilla, T. J., A. Nezu, and A. Maydeu-Olivares. 2004. Social Problem Solving. Theory and Assessment.
In Social Problem Solving. Theory, Research, and Training, edited by E. C. Chang, T. J. D’Zurilla, and
L. J. Sanna, 11–27. Washington, DC: American Psychological Association.
Diener, M., M. A. Nievar, and C. Wright. 2003. “Attachment Security among Mothers and Their Young
Children Living in Poverty: Associations with Maternal, Child, and Contextual Characteristics.Merrill-
Palmer Quarterly 49: 254–282.
Dodge, K., and J. M. Price. 1994. “On the Relation between Social Information Processing and Socially
Competent Behavior in Early School-aged Children.Child Development 65: 1385–1397.
Duncan, G. J., and K. A. Magnuson. 2003. “O with Hollingshead: Socioeconomic Resources, Parenting,
and Child Development.” In Socioeconomic Status, Parenting, and Child Development, edited by
M. H. Bornstein and R. H. Bradley, 83–106. Mahwah, NJ: Erlbaum.
Durlak, J. A., R. P. Weissberg, A. B. Dymnicki, R. D. Taylor, and K. Schellinger. 2011. “The Impact of
Enhancing Students’ Social and Emotional Learning: A Meta-analysis of School-based Universal
Interventions.Child Development 82: 405–432.
Fejes, J. B. 2012. “Learning Motivation of Disadvantaged Students.” In Encyclopedia of the Sciences of
Learning, edited by N. M. Seel, 1935–1937. New York: Springer.
Goodman, S. H., B. Barfoot, A. A. Frye, and A. A. Belli. 1999. “Dimensions of Marital Conict and Children’s
Social Problem-solving Skills.Journal of Family Psychology 13: 33–45.
de Graaf, P. M., and M. Kalmijn. 2006. “Change and Stability in the Social Determinants of Divorce: A
Comparison of Marriage Cohorts in the Netherlands. European Sociological Review 22: 561–572.
Grusec, J. E., and M. Davidov. 2007. “Socialization in the Family: The Roles of Parents.” In Handbook of
Socialization, edited by J. Grusec and P. Hastings, 284–308. New York: Guildford Press.
Hoerth, S. L., and J. F. Sandberg. 2001. “How American Children Spend Their Time.Journal of Marriage
and Family 63: 295–308.
Hughes, J. N., T. A. Cavell, B. T. Meehan, D. Zhang, and C. Collie. 2005. “Adverse School Context Moderates
the Outcomes of Selective Interventions for Aggressive Children.Journal of Consulting and Clinical
Psychology 73: 731–736.
van IJzendoorn, M. H., and M. J. Bakermans-Kranenburg. 2010. “Invariance of Adult Attachment across
Gender, Age, Culture, and Socioeconomic Status?” Journal of Social and Personal Relationships 27:
Jennings, P. A., and M. T. Greenberg. 2009. “The Prosocial Classroom: Teacher Social and Emotional
Competence in Relation to Student and Classroom Outcomes.Review of Educational Research 79:
Junttila, N., M. Vauras, P. Niemi, and E. Laakkonen. 2012. “Multisource Assessed Social Competence as
a Predictor for Later Loneliness, Social Anxiety, and Social Phobia.Journal for Educational Research
Online 4: 73–98.
Juvonen, J., and J. Cadigan. 2002. “Social Determinants of Public Behavior of Middle School Youth:
Perceived Peer Norms and Need to Be Accepted.” In Adolescence and Education: Vol. 2. Academic
Motivation of Adolescents, edited by F. Pajares, and T. Urdan, 277–297. Greenwich, CT: Information
Kasik, L. 2014. “Development Of Social Problem Solving – A Longitudinal Study (2009–2011) in
AHungarian Context.European Journal of Developmental Psychology 12: 142–157.
Kasik, L., Cs Gáspár, K. Guti, and A. Zsolnai. 2016. “Relationship between Social Problem-solving, Anxiety
and Empathy among Adolescents in Hungarian Context.” In Problem-solving: Strategies, Challenges
and Outcomes, edited by K. Newton, 177–196. New York:Nova Science.
Keltikangas-Järvinen, L. 2005. “Social Problem Solving and the Development of Aggression.” In Social
Problem Solving and Oending: Evidence, Evaluation, and Evolution, edited by M. McMurran and J.
McGuire, 31–49. New York: Wiley.
Linver, M. R., J. Brooks-Gunn, and D. Kohen. 2002. “Family Processes as Pathways from Income to Young
Children’s Development.” Developmental Psychology 38: 719–734.
Liu, G., and Vikat, A. (2004). Does Divorce Risk Depend on Spouses’ Relative Income? A Register Based
Study of First Marriages in Sweden in 1981–1998. MPIDR Working Paper No. 2004–010. Rostock;
Max-Planck Institute for Demographic Research.
Lykken, D. T. 2002. “How Relationships Begin and End: A Genetic Perspective.” In Stability and Change in
Relationships, edited by A. L. Vangelisti, H. T. Reis and M. A. Fitzpatrick, 83–102. New York: Cambridge
University Press.
Martin, J., D. M. Stack, L. A. Serbin, J. E. Ledingham, and A. E. Schwartzman. 2011. “Social Problem
Solving in High-risk Mother-child Dyads: An Intergenerational Study.Social Development 21: 47–67.
McLanahan, S., and C. Percheski. 2008. “Family Structure and the Reproduction of Inequalities.Annual
Review of Sociology 34: 257–276.
Miller, S. R., V. M. Murry, and G. H. Brody. 2005. “Parents’ Problem Solving with Preadolescents and
Its Association with Social Withdrawal at School: Considering Parents’ Stress and Child Gender.
Fathering 3: 147–163.
Nowicki, E. A. 2003. “A Meta-analysis of the Social Competence of Children with Learning Disabilities
Compared to Classmates of Low and Average to High Achievement.Learning Disabilities Quarterly
26: 171–188.
OECD. 2013. PISA 2012 Results: Excellence through Equity: Giving Every Student the Chance to Succeed.
Vol. II. Paris: OECD Publishing.
OECD. 2014. TALIS 2013 Results: An International Perspective on Teaching and Learning. Paris: OECD
Pakaslahti, L., and L. Keltikangas-Järvinen. 2000. “Comparison of Peer, Teacher and Self-assessments
on Adolescent Direct and Indirect Aggression.Educational Psychology 20: 177–190.
Public Education Act of 1993 § 79.
Raikes, H. A., and R. A. Thompson. 2008. “Attachment Security and Parenting Quality Predict Children’s
Problem-solving, Attributions, and Loneliness with Peers.Attachment & Human Development 10:
Rich, A. R., and R. L. Bonner. 2004. “Mediators and Moderators of Social Problem-solving. In Social
Problem-solving: Theory, Research, and Training, edited by E. Chang, T. D’Zurilla and L. Sanna, 29–45.
Washington, DC: American Psychological Assocation.
Siu, A. M. H., and D. T. L. Shek. 2010. “Social Problem Solving as a Predictor of Wellbeing in Adolescents
and Young Adults.Social Indicators Research 95: 393–406.
Solantaus, T., J. Leinonen, and R. L. Punamäki. 2004. “Children’s Mental Health in times of Economic
Recession: Replication and Extension of the Family Economic Stress Model in Finland.Developmental
Psychology 40: 412–429.
Thomson, E., and S. S. McLanahan. 2012. “Reections on Family Structure and Child Well B eing: Economic
Resources Vs. Parental Socialization.Social Forces 91: 45–53.
Webster-Stratton, C. (2011). The Incredible Years. Parents, Teachers, and Children’s Training Series. Seattle,
WA: The Incredible Years, Inc.
Yeung, W., M. Linver, and J. Brooks-Gunn. 2002. “How Money Matters for Young Children's Development:
Parental Investment and Family Processes.” Child Development 73: 1861–1879.
Youngstrom, E. A., and K. W. Green. 2003. “Reliability Generalization of the Self-report of Emotions
across Gender, Ethnicity, Age, and Socioeconomic Status When Using the Dierential Emotions
Scale.Educational & Psychological Measurement 63: 279–295.
Zhai, F., C. C. Raver, and C. Li-Grining. 2011. “Classroom-based Interventions and Teachers’ Perceived Job
Stressors and Condence: Evidence from a Randomized Trial in Head Start Settings.Early Childhood
Research Quarterly 26: 442–452.
Zsolnai, A., and L. Kasik. 2016. Coping Strategies and Social Problem Solving in Adolescence In Open
Spaces for Interactions and Learning Diversities, edited by A. Surian, 121–126. Rotterdam: Sense
... Refs. [2,49]). The factor structure of the Hungarian-language version of the SPSI-R and that of the original instrument agreed in both the previous and present studies. ...
... This is, firstly, because the sample only consisted of students at an institute of higher education. Secondly, the socioeconomic status of university students is typically average or above (cf [56]), and, according to our previous study, socioeconomic background plays an important role in the development of social problem-solving [49]. Third, the students were mainly Note: The numbers for the clusters can be found in the column comparing the inter-group differences; > indicates the direction of the significant difference (p < 0.05). ...
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... This kind of assistance that school counselors provide to students can generally be expressed as help with problem-solving skills. Problemsolving skills have a crucial role in solving adolescents' developmental problems (Kasik et al., 2017). In addition, students can more easily solve their interpersonal problems with the social problem-solving skills fostered by school psychological counselors (Merrill et al., 2017). ...
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In this study, it was investigated whether adolescents' developmental guidance needs predicted by their interpersonal problem-solving skills. Adolescents' Determination of Developmental Guidance Needs Scale, Interpersonal Problem Solving Skills Scale, and Personal Information Form used as data collection tools. The sample group of the study consists of 1002 high school students. While obtaining the findings of the study, correlational analysis, and multiple linear regression analysis performed. Adolescents' interpersonal problem-solving skills predicted 18.8% of their developmental guidance needs. It is concluded that adolescents' interpersonal problem-solving skills predict their developmental guidance needs.
... It is worth to note that, there is scarcity of research on the problem solving skills of particularly, students studying in Special Education so the researcher believed that such an exploration has the potential of drawing a clearer picture of the situation in the education faculties in this respect. It is surprising that the studies investigating problem solving have been carried out with individuals who need special education (Marschark & Everhart, 2013 ;Cote et al., 2010;Kasik et al., 2017) but not with the teacher candidates who are responsible to help these individuals. In addition, there has not been a research study investigating the perceptions of the students studying in the Department of Special Education in Turkish Cypriot context regarding interpersonal problem solving skills. ...
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Bu araştırma Özel Eğitim Öğretmenliği Bölümü’nde okuyan 221 öğretmen adayının kişilerarası problem çözme becerileriyle ilgili algılarını belirlemeyi amaçlamaktadır. Araştırma, katılımcıların kişilerarası problem çözme becerilerinin cinsiyete, yaşa ve sınıflarına göre anlamlı farklılık gösterip göstermediğini de belirlemeyi hedeflemektedir. Bu amaçla,1982 yılında Heppner ve Peterson tarafından geliştirilen ve daha sonra 1993 yılında Şahin, Şahin ve Heppner tarafından Türkçe’ye çevirilen “Problem Çözme Envanteri” bu araştırmada veri toplama aracı olarak kullanılmıştır. Problem Çözme Envanteri’nin altı tane alt boyutu bulunmaktadır: ‘Aceleci Yaklaşım’, ‘Düşünen Yaklaşım’, ‘Kaçıngan Yaklaşım’, ‘Değerlendirici Yaklaşım’, ‘Kendine Güvenli Yaklaşım’ ve ‘Planlı Yaklaşım’. Araştırma bulguları öğretmen adaylarının kisilerarası problem çözme becerileriyle ilgili algılarının orta düzeyde olduğunu göstermiştir. Bayan ve erkek öğretmen adaylarının algılarının sadece beş tane maddeyle ilgili olarak anlamlı farkılık gösterdiği saptanmıştır. Buna ek olarak, öğretmen adaylarının algıları yaşa göre de anlamlı farklılık göstermiştir. Fakat, katılımcıların algılarında okudukları sınıfa göre herhangi bir algı farklılığı saptanmamıştır. Öğretmen adaylarının kişilerarası problem çözme becerileri hakkındaki algılarına ilişkin bulgular, sırasıyla ‘düşünen yaklaşım’, ‘kaçıngan yaklaşım’, ‘aceleci yaklaşım’ ve ‘değerlendirici yaklaşım’ın en çok tercih edilen problem çözme beceri alt gurupları olduğunu gösterirken, öğretmen adaylarının ‘kaçıngan yaklaşım’ ve ‘kendine güvenli yaklaşım’da kendilerini yeterli bulmadıklarını göstermiştir.
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Social problem-solving (SPS) involves the cognitive-behavioral processes through which an individual identifies and copes with everyday problems; it is considered to contribute to anxiety and depression. The Social Problem-Solving Inventory Revised is a popular tool measuring SPS problem orientations and problem-solving styles. Only a negative problem orientation (NPO) is considered strongly related to anxiety and depression. In the present study, we investigated the detailed connections among the five components of SPS and 14 anxiety-depression symptoms and specified the role of NPO and other components in the anxiety-depression network. We employed network analysis, constructed circular and multi-dimensional scaling (MDS) networks, and calculated the network centrality, bridge centrality, and stability of centrality indices. The results were as follows: (1) the MDS network showed a clustering of anxiety and depression symptoms, with NPO and avoidance style components from SPS being close to the anxiety-depression network (demonstrated by large bridge betweenness and bridge closeness); (2) the NPO and positive problem orientation from SPS were most influential on the whole network, though with an opposite effect; (3) strength was the most stable index [correlation stability (CS) coefficient = 0.516] among the centrality indices with case-dropping bootstraps. We also discussed this network from various perspectives and commented on the clinical implications and limitations of this study.
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The relationship between increasing women’s earnings and rising divorce rates frequently has been explained by the so-called independence effect: If a wife enjoys a higher earning than her husband does, she gains less from marriage. It has also been argued that in a society with egalitarian gender attitudes this effect is less important. In this paper, we test if the independence effect applies to Sweden, a country in which egalitarian gender views dominate and female labor-force participation and divorce rates are high. Our analysis is based on a large register data set and intensity regression models. We found support for the ‘independence effect’: The linear relationship between the share of a wife’s income and the divorce risk is positive. We also found that the higher the total income of the couple, the lower their divorce risk, but this relationship appears to be less strong.
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A keresztmetszeti vizsgálatok eredményei az egyes életkori csoportokba tartozó gyere-kekről nyújtanak képet, általuk jó becslést kaphatunk arról, hogy a mintába tartozó diá-kok esetében milyen változások következnek be, ám ezek a vizsgálatok arra nem adnak lehetőséget, hogy az egyéni változásokat elemezni lehessen. Erre a longitudinális (hossz-metszeti) felmérések alkalmasak, melyek pontosítják a keresztmetszeti kutatások adatait, megvizsgálhatók a feltárt jelenségek időbeli előzményei (Csapó, 2007; Józsa, 2013).
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The phrase learning motivation of disadvantaged students refers to the assumption that learning motivation, being different from, and usually lower than that of students from average or advantaged environments, plays a crucial role in the educational failures of students with low socioeconomic status. On a theoretical basis it is effortless to verify the motivational deficit of disadvantaged students that can be traced back, on one hand, to the parents' influential role in the formation of learning motivation, and, on the other hand, to school failures evolving as a consequence of less advanced cognitive skills. However, unequivocal empirical evidence supporting the central role of unfavorable family background in the development of a lower level of learning motivation is unavailable.
Understanding interpersonal relationships requires understanding actors, behaviors, and contexts. This 2002 volume presents research from a variety of disciplines that examine personal relationships on all three levels. The first section focuses on the factors that influence individuals to enter, maintain, and dissolve relationships. The second section emphasizes ongoing processes that characterize relationships and focuses on issues such as arguing and sacrificing. The third and final section demonstrates that the process of stability and change are embedded in social, cultural, and historical contexts. Chapters address cultural universals as well as cross-cultural differences in relationship behaviors and outcomes. The emergence of relational forms, such as the interaction between people and computers, is also explored. Stability and Change in Relationships will be of interest to a broad range of fields, including psychology, sociology, communications, gerontology, and counselling.
Research on social problem solving have been focusing on age, gender and cultural differences and development for a very long time. It is a widely known fact that the development of social problem solving depends on many mediator (e.g., super traits, anxiety, emotions) and moderator variables (e.g., family and school background). International studies agree that social problem solving has a profound influence on success in personal life, on mental health (e.g., Elliott et al., 2006), on academic achievement (e.g., Rodriguez-Fornells & Maydeu-Olivares, 2000), and, in turn, on the functioning of different social groups and society as a whole (e.g., Lindsay et al., 2011). Several studies have pointed out that mental health and school success also have an impact on social problem solving (e.g., McMurran & McGuire, 2005). The aim of our study was to examine the relationship between social problem solving and some mediator and moderator variables among 12- and 16-year-old Hungarian students (N = 445). We examined the relationship between social problem solving, state and trait anxiety and empathy, and we also intended to find relationship between social problem solving and some family background variables (e.g., family structure, parents’ educational level). We used the short version of SPSI–R (2002, Social Problem Solving Inventory–Revised, D’Zurilla, Nezu, & Maydeu-Olivares – factors: positive problem orientation, negative problem orientation, rationality, impulsivity, avoidance); Davis’s IRI (1980, Interpersonal Reactivity Index – factors: perspective taking, fantasy, empathic concern, and personal distress) and Spielberger’s State-Trait Anxiety Inventory (1983). All of these measurements showed good reliability indices. According to the results, positive problem orientation was more typical of 12-year-olds and negative problem orientation, rationality, state anxiety, perspective taking and empathic concern were more common among 16-year-olds. The fitting of impulsivity and trait anxiety, and avoidance and trait anxiety are more solid in 16-year-olds. Regardless of age, the degree of negative problem orientation and avoidance is higher among those with increased anxiety as compared to those with lower levels of anxiety. Perspective taking has a strong connection to positive problem orientation and rationality in almost every age, while personal distress has greater influence only on negative problem orientation at the age of 16. The family structure and parents’ educational levels are the most profoundly influential in terms of social problem solving.
Social competence has traditionally been defined as the complex system of social abilities, habits, skills and knowledge (e.g. Rose-Krasnor, 1997; Semrud-Clikeman, 2007). Social competence has the function to organise social behaviour, and to trigger the operation of the individual elements of the system (Nagy, 2007).
The aims of the longitudinal study were to investigate the development of social problem solving (SPS) among adolescents (N = 180) in Hungary, to describe the nature of correlations between the raters' judgements (child, mother, teacher) and to examine what the correlations are between SPS factors and family background. At the beginning of the study students were 12-year-olds and they were 14 at the last time of measurement. The questionnaire of SPS was adapted [SPSI-R:S, D'Zurilla, T. J., Nezu, A., & Maydeu-Olivares, A. (2002). Social Problem-Solving Inventory-Revised (SPSI-R): Technical manual. North Tonawanda, NY: Multi-Health Systems]. The factors were the following: negative and positive problem orientation (NPO, PPO, respectively), rational problem solving (RPS), impulsivity/carelessness style (ICS) and avoidance style (AS). Based on self-assessment, NPO, RPS, ICS and ACS show increasing tendency with age; however, in the case of PPO, significant age differences have not been found. The mothers' ratings are the same in the case of NPO, PPO and RPS, but they think that their 12-year-olds show lower impulsivity and avoidance than their children of 13 and 14 years. According to the teachers' rating, NPO, RPS and AS show increasing tendency; however, the values of ICS and PPO decrease with age. Correlations between children's and mothers' ratings are strongest, and the most divergent evaluations were given by teachers and mothers. Parents' educational levels influence the SPS factors differently: mothers' educational level has an effect on NPO and ICS; fathers' educational level has an impact on RPS in all years. The effects of free-time activities in family are stronger than those of the time spent learning with children in all years.
This study examined the contribution of maternal childhood histories of aggression and social withdrawal to the prediction of mother–child social problem solving in the next generation. Fifty‐seven women (M = 37.32 years), previously rated (on a version of the pupil evaluation inventory) by their peers during childhood on measures of aggression and withdrawal, discussed conflicts with their 9‐ to 13‐year‐old children. Problem‐defining statements, solutions, and resolution strategies were coded using an observational measure developed by the authors. Maternal childhood histories of aggression and withdrawal predicted poorly sophisticated solutions in both mothers and children as well as antisocial solutions in children. Histories of withdrawal predicted solitary solutions in children as well as less guidance and structure during decision making. Findings suggest that mothers who were withdrawn, and those aggressive and withdrawn in childhood, display less sophisticated problem solving, which may be mirrored in children. Results have implications for the development of aggressive and withdrawn girls into parenthood and highlight a potential pathway for the transfer of risk.