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Context and Implications Document for: Positive psychology school-based interventions: a reflection on current success and future directions

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An increased focus on youth development has led to an understanding of the importance of the wellbeing, resilience and mental health of children and young people. As a result there is a growing body of research, especially over the last two decades, which increasingly recognises the complexities of learning and development across the years spent at school. Alongside this trend is the rise of positive psychology, which is changing our conceptions of youth, education and development. Support for a new era of student-centric teaching practices dedicated to enhancing student wellbeing has come not only from researchers and psychologists, but also from school and education authorities, who are showing an increased appetite for integrating positive psychology-based programs into the learning curriculum. While researchers are beginning to express cautious optimism about the effectiveness of such interventions, there is a large disparity between the initiatives being researched and what is being taught in classrooms. A set of key constraints relating to limited resources, an overcrowded curriculum, accessibility of information, teacher factors and quality training all play a role in shaping the effectiveness with which an intervention is implemented. This article reflects on the recent development of positive psychology school-based programs and offers insights into how these initiatives can be enhanced to reach a wider range of young people and translated more effectively into classroom practice.
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DOI: 10.1177/0143034316667114
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Article
Promoting positive
learning in Australian
students aged 10- to
12-years-old using
attribution retraining and
cognitive behavioral
therapy: A pilot study
Alicia R Chodkiewicz
University of New England, Australia
Christopher Boyle
The University of Exeter, UK
Abstract
This study piloted an intervention using attribution retraining and cognitive behavioral
therapy techniques to promote positive learning experiences and outcomes for stu-
dents. This research is an important step to revitalise the dwindling field of attribution
retraining research by assessing whether these techniques effectively improve student
learning in modern classrooms. Participants were 50 students from grades five and six
(age 10- to 12-years-old). Findings revealed that students in the intervention group
showed significantly greater average reading levels compared to their control group
peers at two months following the intervention. Whilst no other areas measured
(mathematics, spelling, and self-concept) reached the level of significance, a number
of interesting patterns were observed regarding student selection, intervention focus,
and the trajectory of treatment effects. These findings encourage future researchers to
expand the range of students targeted by school-based interventions, supports the use
of attribution techniques, and highlights that without follow-up data, lagged treatment
effects may go undetected. This is one of only a handful of studies to combine attribu-
tion retraining with cognitive behavioral therapy, and the results of this pilot study
support the need for further research in this area.
Corresponding author:
Christopher Boyle, PhD, Graduate School of Education, University of Exeter, UK.
Email: c.boyle2@exeter.ac.uk
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Keywords
attribution retraining, attributions, cognitive behaviour therapy, educational psychology,
inclusive education, positive psychology, school improvement, school psychology,
special education
The question asked by many school psychologists as to how one should best
support the learning and development of students is slowly being answered as
researchers uncover the complex and dynamic nature of the learning process
(Wigfield, Eccles, Schiefele, Roeser, & Davis-Kean, 2007). In response to our grow-
ing understanding of youth development and the vital role psychological factors
play there have been calls for the inclusion of positive cognitive interventions
within schools to support student well-being (Chodkiewicz & Boyle, 2014;
Stallard, 2003; Weiner, 2010). The responsibility of identifying and implementing
such intervention programs often resides with school psychologists, as they typic-
ally act as the bridge between psychological research and educational practice
(Boyle & Lauchlan, 2013). It is therefore important for school psychologists to
remain up-to-date on school-based interventions to allow them to make informed
decisions when choosing evidence-based programs for their schools. The current
research presents the findings of one such intervention, the Believing you can is the
first step to achieving program, which combines Attribution Retraining (AR)
and Cognitive Behavioral Therapy (CBT) techniques in an attempt to improve
academic outcomes and foster positive thinking styles in students aged 10- to
12-years-old.
Attribution theory and attribution retraining
Schooling, by its nature, is imbued with moments of academic success and failure.
Following moments of academic evaluation, students typically seek explanations as
to why they may or may not be doing well in school. Attribution researchers have
been attempting to understand the interaction between how these causal explana-
tions for success and failure (otherwise known as attribution style) influence learn-
ing and achievement (Weiner, 2010; Weiner & Sierad, 1975). A slightly optimistic
outlook, one in which a student believes s/he is capable of improving upon past
failures and will achieve future success, is seen to be advantageous. Such a belief
comes from attributions that reflect the personal controllability of academic situa-
tions. These types of events would be characterized by thoughts such as ‘I suc-
ceeded because I have the ability to achieve my goal’ and ‘I failed because I did not
use the correct learning strategy’. Conversely, a maladaptive attribution style
involves pessimistic expectations of future failure, where failure is seen to be inevi-
table, and success is viewed to be beyond one’s control. Maladaptive explanations
include, ‘I only succeeded because I was lucky, it won’t happen again’ and ‘I failed
because I am not clever enough’.
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The link between maladaptive attribution styles and academic underachieve-
ment has been well documented (Au, Watkins, & Hattie, 2010; Chan & Moore,
2006; Shmulsky & Gobbo, 2007). Students endorsing adaptive attribution styles
have been shown to have higher levels of self-concept, to work harder, and persist
longer in the face of difficulty (Marsh & Scalas, 2011; Nu´ n
˜ez et al., 2005). While
students holding maladaptive attribution beliefs have been observed to employ the
following: Low self-beliefs and motivation, limited effort, task avoidance, and little
resilience (Hsieh & Kang, 2010; Swinton, Kurtz-Costes, Rowley, & Okeke-
Adeyanju, 2011). Of these factors, self-perceptions have attracted arguably the
most research attention. The degree to which an individual believes him or herself
to be capable of achieving a goal impacts the extent to which that student invests
time and effort in the learning activity and subsequently what s/he achieves
(Pinxten, Marsh, De Fraine, Van Den Noorgate, & Van Damme, 2014; Yeung,
Craven, & Kaur, 2014). With research observing these trends across the lifespan
(Chan & Moore, 2006; Swinton et al., 2011), there is growing insight into the
potential for psychological interventions targeting attribution styles to combat
lifelong underachievement.
AR is an intervention designed to disrupt and discontinue the cycle of under-
achievement linked to maladaptive attribution styles and is based on the premise
that academic improvements can be fostered through cognitive restructuring with-
out the need for extra academic remediation (Koles & Boyle, 2013). Weiner and
Sierad (1975) implemented one of the first AR interventions over four decades ago,
finding that they could improve students’ mathematical performance through
encouraging adaptive attributions. Since then, research has emerged investigating
the potential benefits of this intervention form. Encouraging results have shown
AR intervention leads to improvements in academic performance, attribution style,
motivation, and self-concept (Chan & Moore, 2006; Dresel & Haugwitz, 2008;
Haynes Stewart et al., 2011; Perry, Stupnisky, Hall, Chipperfield, & Weiner,
2010; Toland & Boyle, 2008). Not all studies, however, have found consistent
positive outcomes following AR interventions (Fulk, Mastropieri, & Scruggs,
1992; Morris, 2013).
Unfortunately, over the past 20 years this field of research has been losing
momentum (Chodkiewicz & Boyle, 2014). Of the small number of contemporary
researchers still studying AR interventions, a handful have been looking to CBT as
a means of rejuvenating interest in the field. For example, Toland and Boyle (2008)
designed a program combining AR and CBT techniques to improve the reading
skills of middle school students in Scotland. Similarly, Berkeley, Mastropieri, and
Scruggs (2011) in the USA combined AR instruction with techniques taken from
CBT, finding that such instruction was instrumental in maintaining the positive
reading improvements following what they termed academic strategy training.
CBT is one of the most widely used modern therapeutic techniques (Dawood,
2013), making it a good option for researchers looking to strengthen AR interven-
tions. Three decades ago Fo
¨rsterling (1985) stated that ‘because there are many
similarities between cognitive behavior modification and attributional approaches
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to psychopathology ...attributional change could easily be implemented in the
practice of cognitive therapy’ (p. 510). Both forms of therapy look to restructure
thinking styles and perceptual patterns to induce behavioural changes. However,
AR remains distinct from typical CBT interventions by specifically targeting the
causal reasons used to explain events and inducing change through challenging and
reshaping future expectations based on these causal assessments. Combining AR
and CBT techniques promises to therefore improve both the quality of AR inter-
ventions and add a new dimension not often seen in current CBT based programs.
AR interventions have typically been targeted at students experiencing learning
difficulties (Berkeley et al., 2011; Toland & Boyle, 2008). While the link between
underachievement and maladaptive attribution styles is well established (Au et al.,
2010; Shmulsky & Gobbo, 2007), not all students who may be struggling actually
demonstrate maladaptive attributions (Nu´ n
˜ez et al., 2005) nor do they always feel
that they are in need of intervention (Boyle, 2007). It is accepted that self-percep-
tions are shaped through social comparisons (Nagengast & Marsh, 2012) and that
perceptions are a better predictor of attribution style than actual academic ability
(Banks & Woolfson, 2008). It is therefore possible that even high achievers can feel
as if they are struggling and develop maladaptive attribution styles. By widening
the eligibility criterion for AR interventions beyond just academically low achiev-
ing students, there is the potential to reach a much broader population of students
in need.
Current research aims and hypotheses
The current study set out to pilot an intervention combining both AR and CBT
techniques to foster positive learning in students aged 10- to 12-years-old. This
pilot study investigated the viability of strengthening an AR intervention by incor-
porating techniques of CBT, such as the analysis of self-talk and teaching coping
skills. Following the footsteps of some noted researchers (Berkeley et al., 2011;
Toland & Boyle, 2008) this study aims to take the concept of a combined AR and
CBT program one step further by using a highly structured program with an
interactive and engaging format. The design of a student workbook and teacher
manual allows this program to be easily translated into real classrooms by school
psychologists or classroom teachers, making it a distinct addition to the few such
interventions that have come before it. As part of the current study, small groups of
five to seven students were withdrawn from their classrooms to participate
in hourly lessons each week across a single school term. A provisional school
psychologist ran these sessions.
A key aim of this study was to identify whether a purely cognitive based inter-
vention would have positive ramifications for student academic achievement.
Measures of student reading, spelling, and mathematics were predicted to increase
following the intervention. It was also predicted that all students would show
positive outcomes from the intervention, regardless of initial levels of academic
ability.
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Method
Participants
Participants were from six public primary schools in inner city Melbourne,
Australia. Initially, 170 students in Grade 5 and 6 (aged 10- to 12-years-old) com-
pleted a screener survey (The Children’s attribution style questionnaire – revised).
A total of 58 students were selected based on signs of maladaptive attribution
profiles. Of the sample 60% were male and 40% female. The age ranged from
10:2 to 12:6 years, with a mean age of 11:1 years (SD ¼0.62). From each school
between five to seven students from various grade five and six classrooms were
randomly allocated into the AR group. The remaining students were allocated to
the control group. Due to the small number of participants in each school this
resulted in a larger number of students being allocated to the intervention group
(N¼34) than the control group (N¼24). During the research project eight stu-
dents withdrew from the study. Reasons for participant attrition included extended
school absence (AR: N¼2; Control: N¼2), school relocation (Control: N¼2),
and voluntary withdrawal (AR: N¼1; Control: N¼1). The final sample consisted
of 50 participating students; 31 students in the intervention group and 19 in the
control group.
The intervention
The Believing you can is the first step to achieving intervention uses both
AR and CBT techniques (Chodkiewicz & Boyle, 2015) to teach three core
elements: The link between thoughts, feelings, and actions; the identification
of unhelpful thinking patterns/causal attributions; and the learning of coping
skills through challenging unhelpful thoughts and restructuring attributions used
to explain success and failure situations (refer to Table 1 for a description of
topics covered). The program is made up of eight core sessions running for
approximately one hour each. The sessions were highly structured and followed
a student workbook and teacher’s manual. Each session began with a class
discussion of the new topic followed by a group-based activity/game, and
ended with independent workbook activities. Students were also required
to complete home learning sheets between each session. Further elaboration
of the content along with copies of all worksheet material can be located in
Chodkiewicz and Boyle (2015).
Materials
The Children’s attribution style questionnaire – revised (CASQ-R; Thompson,
Kaslow, Weiss, & Nolen-Hoeksema, 1998) consists of 24 vignettes asking a student
to choose causal explanations to match each event. Scores on the CASQ-R indicate
the degree to which a student attributes internal, stable, and global factors to
positive and negative events. The CASQ-R has been shown to have a moderate
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Table 1. Outline of AR Program content.
Session Session title Session content
1 Thoughts !Feelings !
Actions
This session introduces students to the program,
introduced feeling vocabulary and demonstrates
the link between thoughts feelings and actions
2 Helpful and Unhelpful
Pathways
This session demonstrates how thoughts influence
behaviour in helpful and unhelpful ways through
the thought – feeling – action pathway. Students
work on identifying helpful thoughts to use in
difficult situations
3 Where do we have helpful
and unhelpful thoughts?
This session helps students identify unhelpful
thoughts in their own lives. Students are encour-
aged to be aware of places/situations in which
unhelpful thoughts are more likely to arise, and to
prepare helpful thoughts in advance of difficult
situations. The session also encourages students
to identify and appreciate moments of personal
success through the use of self-congratulations
4 How does this all relate to
school and learning?
This session introduces the concept that thoughts
can have a big impact on how well students per-
form in school and what they are able to achieve.
Students are shown examples of how thoughts
can change a student’s motivation, persistence,
and learning behaviours. Students are then given
the chance to practice replacing unhelpful
thoughts with more helpful ones
5 Why do we succeed and
fail?
This session introduces students to attribution
theory. Adaptive and maladaptive attributions for
success and failure situations are outlined.
Students then have the chance to practice using
adaptive explanations in response to hypothetical
situations
6 Becoming Super Heroes –
Stopping unhelpful
thoughts
This session teaches students skills to overcome
unhelpful thoughts in their every day lives using
three super powers. Students are encouraged to
identify if their thoughts are helpful/unhelpful,
analyse whether their causal explanations are
adaptive/evidence-based, and restructure unhelp-
ful thinking
7 Practicing Super Powers This session is a chance for students to further
practice the skills learnt in the last session and
apply them to a range of different situations
8 Review This session is used to consolidate what students
have learnt in the program by creating a video that
can be used to teach others about the program
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internal consistency, with reliability measures (Cronbach alphas) of 0.61 for posi-
tive composite results and from 0.53–0.60 for negative composite, with an overall
test–retest reliability coefficient of 0.53 (Thompson et al., 1998). The reliability of
the CASQ-R in the current pilot study were as follows: Positive composite
a¼0.526 and negative composite a¼0.525.
The Wechsler individual achievement test,second edition (Australian) abbreviated
(WIAT-IIA: Wechsler, 2007) is a standardized brief measure of academic achieve-
ment across the three academic domains of reading, mathematics, and spelling. The
grade based reliability coefficients of the three subtests, Word Reading, Numerical
Operations, and Spelling are respectively: Grade 5: 0.96, 0.91, and 0.91; Grade 6:
0.95, 0.91, and 0.94 (Wechsler, 2007).
The Myself-as-a-learner scale (MALS; Burden, 1998) is a student self-report
measure of academic self-concept. The 20-item questionnaire asks students to
rate enjoyment of learning and ability to learn on a five-point Likert scale.
Scores range from 20–100. The scale was shown to have an alpha reliability
index of 0.85 (Burden, 1998).
Procedure
Across the six participating schools a total of 170 students completed a group
screener (CASQ-R) used to identify students showing low levels of adaptive attri-
bution styles (0 overall index and/or 5 negative or positive index). This screener
was group administered. All eligible students completed pre-intervention assess-
ments consisting of the WIAT-IIA and MALS.
Five to seven students from each school were then randomly allocated to the
intervention group with all remaining students being assigned to the control group.
Students in the intervention group attended eight weekly sessions, which were
conducted by the first author across the six participating schools. This helped
ensure that treatment fidelity was maintained and measures were built into the
project as suggested by Houghton et al. (2013). Students in the control group
did not take part in any of the intervention sessions and remained in their regular
classes. Post-intervention and follow-up (two-months) assessments included indi-
vidually administered CASQ-R, WIAT-A, and MALS.
Results
Initial group differences
A multivariate analysis of variance (MANOVA) was conducted to identify
initial differences between intervention and control groups. The intervention
group was observed to hold significantly lower academic self-concept beliefs
when compared to their control group peers, F(1,48) ¼6.03, p¼0.018, which repre-
sents a medium effect size (Z
2
¼0.112). As a result, the initial levels of student
academic self-concept were included as a covariate in all further analyses.
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No significant differences in any of the other measures of interest were observed
(age, grade, gender, attribution style, or academic skill). Pre-intervention means
and standard deviations are displayed in Table 2.
Academic achievement
Reading. Based on observed average reading levels, the intervention group showed
greater levels of reading growth across the year compared to their control group
peers. A mixed ANOVA was conducted to assess whether the observed group
differences were significant, with initial levels of academic self-concept included
as a covariate. Results indicated no significant main effect of time, F(2,94) ¼1.0,
p¼0.36 or group, F(1,47) ¼0.87, p¼0.36. However, a significant interaction
between time and group was observed, F(2,94) ¼3.82, p¼0.025, which was classi-
fied as having a medium effect size (Z
2
¼0.075). That is, students in the intervention
group achieved significantly greater average reading levels compared to students in
the control group. Contrast analyses revealed a significant difference between
groups on average reading performance only between post-intervention and
follow-up measures F(1,47) ¼6.9, p¼0.012, which was found to have a large
effect size (Z
2
¼0.128). These results indicate that the intervention group had a
significantly greater increase in average reading compared to the control group,
however this difference only began to appear after the completion of the program,
in the two months following the intervention. Such a result suggests that students
require time to internalize and practice intervention skills before reading outcomes
can be influenced.
A post hoc analysis was undertaken to investigate the link between initial
academic ability and reading outcomes among students in the intervention
group. Each student in the intervention group was assigned to one of three aca-
demic classifications (Low: Standard score below 90, Average: Standard score of
90–110 and High: Standard score above 110) based on the pre-intervention reading
assessment. A mixed ANOVA was then conducted to assess differences in reading
improvements. A significant main effect for both time, F(2,56) ¼54.7, p<0.001,
and group, F(2,28) ¼51.1, p<0.001 were observed. However, no significant inter-
action effects between academic group and reading achievement over time were
Table 2. Pre-intervention means and standard deviations categorized by
group.
Intervention Control
Reading 98.77 (10.57) 100.11 (9.71)
Mathematics 93.77 (14.49) 97.63 (22.34)
Spelling 96.19 (14.90) 101.53 (15.22)
Academic Self-concept 68.90 (9.15) 75.42 (9.05)
Attribution Style 3.10 (2.99) 2.95 (2.17)
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found, F(4,56) ¼1.5, p¼0.20, suggesting that students of all ability level in the
intervention group demonstrated an equivalent degree of change in reading ability.
Mathematics. A mixed ANOVA was conducted to assess whether there were group
differences in mathematics achievement measured across the three time-periods,
with initial levels of academic self-concept included as a covariate. Results indicated
no significant main effect of time, F(2,94) ¼2.38, p¼0.12 or group F(1,47) ¼0.14,
p¼0.71, as well as no significant interaction effect, F(2,94) ¼0.30, p¼0.71.
Spelling. A mixed ANOVA was conducted to assess whether there were group differ-
ences in spelling achievement measured across the three time-periods, with initial
levels of academic self-concept included as a covariate. Results indicated
no significant main effect of time, F(2,94) ¼0.20, p¼0.82 or group F(1,47) ¼0.15,
p¼0.71, as well as no significant interaction effect, F(2,94) ¼1.10, p¼0.34.
Academic self-concept
A spike and then a subsequent drop in self-concept immediately following the
intervention implementation was seen in the intervention group but not the control
group. A mixed ANOVA was conducted to assess if these patterns of academic
self-concept were significant. Results indicated a significant main effect of time,
F(2,96) ¼88.62, p¼0.043, which was found to have a medium effect size
(Z
2
¼0.063). Contrast analyses revealed a significant difference of academic self-
concept over time only between pre-intervention and post-intervention measures
F(1,48) ¼4.47, p¼0.04, suggesting the greatest change in self-concept occurred
during the intervention period. As indicated by the initial analysis significant
main effect for the groups was confirmed F(1,48) ¼5.5, p¼0.023. No significant
interaction effect between time and group were observed, F(2,96) ¼0.74, p¼0.48,
suggesting that the intervention did not have a significant impact on academic
self-concept.
Attribution style
A mixed ANOVA was conducted to assess if patterns of attribution style were
significant between the two groups, with initial levels of academic self-concept
included as a covariate. Results indicated no significant main effect of time,
F(2,94) ¼0.29, p¼0.75 or group F(1,47) ¼0.04, p¼0.84, as well as no significant
interaction effect, F(2,94) ¼3.1, p¼0.052.
Discussion
Schools and school psychologists around the world are looking for psychological-
based interventions to support the well-being, achievement, and development of
their students (Chodkiewicz & Boyle, in press). This research aimed to investigate
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an intervention that can be used within schools by piloting a program combining
AR and CBT techniques to foster changes in students aged 10- to 12-years-old. It
was hypothesized that the intervention would lead to positive improvements in
attribution styles, self-concept, and ultimately academic achievement among stu-
dents involved in the intervention. It was also hypothesized that students of all
academic ability levels would benefits from the intervention.
Academic improvement
Toland and Boyle (2008) observed that through a combined AR and CBT inter-
vention they could affect academic improvements without conducting any aca-
demic based remediation. When attempting to replicate these findings the current
study found significant improvements in one, but not all, academic domains.
Domains of academic improvement. Students in the intervention group were observed
to show significantly greater average reading ability across the year compared to
their control group peers. No differential effects were found when measuring
mathematic and spelling achievement. This once again mirrors the earlier work
of Toland and Boyle (2008) who observed improvements in reading but not
spelling achievement following their AR and CBT intervention. Toland and
Boyle (2008) explained this finding by postulating that specific academic domains
may be more malleable to improvements using AR because they lend themselves
more easily to independent practice. Such an explanation fits with the findings of
this pilot study, as many primary school students are encouraged to read for
pleasure outside of school but may not independently practice mathematics or
spelling.
Trajectory of treatment effect. The authors were also interested in understanding the
trajectory of treatment effects, by looking at both immediate and delayed academic
achievement outcomes. An analysis of the trajectory of improvements in students
reading ability across the study provided an interesting observation – a lagged
effect. Over the intervention period, no real changes in reading ability were
observed between the two groups of students. It was only in the two-month
period following the intervention that students in the intervention group displayed
a significant difference in average reading ability compared to their peers.
A lagged effect of academic change following AR interventions is in line with
Weiner and Sierad’s (1975) and Weiner’s (2010) view of an indirect relationship
between attribution interventions and academic attainment. Weiner claims that it is
through an increase in positive study behaviours brought about by adaptive attri-
bution beliefs that leads to gradual improvement in academic skills. The current
finding of lagged academic outcomes is also consistent with previous research by
Berkeley et al. (2011), who measured reading achievement six weeks following
an intervention, and Ziegler and Heller (2000) who assessed physics results
months after the completion of their intervention. Both research teams found
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that the greatest levels of academic improvements were made in the weeks and
months following the intervention. It may therefore stand to reason that spelling
and mathematical improvements may simply take more time to appear than read-
ing. Furthermore, the limited follow-up provisions of this research project (only
two months) could be an explanation as to the failure to observe differences
between the intervention and control group in these academic domains.
Selection criteria. As the question of who stands to benefit most from an AR and
CBT intervention remains unclear, there is a growing body of evidence challenging
the mainstream view that academically low achieving students should be the only
focus of an intervention (Banks & Woolfson, 2008; Nu´ n
˜ez et al., 2005). The current
study attempted to assess if selection based on a students’ attribution profile may
be a viable selection alternative. The results showed no differential treatment effects
between students of differing abilities. This finding supports previous research by
Hall, Hladkyj, Perry, and Ruthig (2004) and Toland and Boyle (2008) who
observed AR interventions having positive impacts on both average and above
average students. This study, therefore, adds support to the argument for extending
the student selection beyond just struggling learners to support the learning of all
students; a position which fits well within the current educational psychology
thinking with regards to inclusive schools (Boyle, Topping, Jindal-Snape, &
Norwich, 2012; Boyle, Topping, & Jindal-Snape (2013); Kraska & Boyle, 2014).
Academic self-concept
When considering the effect a combined AR and CBT intervention has on a stu-
dent’s academic self-concept, the current study did not find significant differences in
self-reported self-concept between the two research groups. Students who took part
in the intervention however, did show a slight spike in their average self-concept
directly following the intervention, a phenomenon that was not seen for the control
group. This observed spike may suggest that any small gains in self-concept from
taking part in the intervention may be short lived. These findings raise concerns
regarding the true capacity for a one-off intervention to bring about marked and
enduring change in students’ academic self-concept.
Attribution style
Given that the current intervention did not show significant differences in attribu-
tion style among the target students, but did show a higher level of reading ability
for the intervention group compared to their control group peers, the question
must be asked: What caused students to improve in reading?
It is possible that other factors not measured in this study may have
been responsible for the interventions positive effect on reading achievement.
For example, an increase in student motivation and persistence behaviors has
previously been linked to both AR interventions and improved academics
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(Chan & Moore, 2006; Dresel & Haugwitz, 2008). It would be important for future
research to include a greater breadth of cognitive and behavioral measures to more
clearly identify potentially links between the intervention and achievement
outcomes.
Similarly it remains unclear to what degree the AR and CBT techniques sepa-
rately influenced student outcomes. The finding of no change in attribution styles
following the intervention may suggest that academic achievement is influenced
most strongly by the CBT components of the program. Alternatively the amount of
AR techniques present in the combined form of intervention may not have been
large enough to foster changes in student attribution styles robust enough to be
identified by the form of self-report measurement used.
While AR is one method used to shape attributions, a number of extraneous
variables also influence a student’s attribution style as they learn, such as previous
learning experiences, teacher feedback, and the home environment (Morris, 2013;
Perry & Hall, 2009). The findings of the current study may further reflect an
inability for small-scale research projects to control for all the key external factors
that may be influencing a student’s attribution style. These findings might, on the
other hand, highlight that there is still a high level of uncertainty in the field as to
what changes are conceivably achieved by AR interventions.
Limitations of the current study
The current study was affected by a number of limitations. Firstly, although a
reasonable sample size was sourced as compared to other pilot studies in this
area, the size of the sample may have limited the ability to find significant results.
Conducting research within school settings can be fraught with obstacles and soft
variable difficulties, with research designs being influenced by school schedules,
policies, available resources, and attitudes of teachers and/or students. One such
implication for the current study was the use of a passive control group as opposed
to an active attention comparison sample. This decision was based on the ethical
dilemma and schools’ justified reticence to simply remove students from learning in
the classroom to be in a control group. It can therefore not be ruled out that the
observed results may have been due to the extra attention the students in the
intervention group received. Having a single researcher deliver the program
across all groups further limited the research findings, as it may be possible that
the personal qualities of the program administrator may have led to improved
scores. The same principle applies to the students having different teachers who
may have taught reading using different approaches. The results of this pilot study
should therefore be viewed as providing preliminary support for the viability of a
combined AR and CBT intervention and not causal proof of its’ effectiveness.
Further research is needed to understand the true effectiveness and generalizability
of the intervention in varied school settings.
A further area of potential limitation in the current study was the attribution
style measure, CASQ-R. While the CASQ-R has been widely used in research
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(Collett & Gimpel, 2004; O’Kearney, Kang, Christensen, & Griffiths, 2009;
Roberts et al., 2010; Sheikh et al., 2008), in this study a number of issues were
observed. For one, both the current research and Thompson et al. (1998) found
rather low reliability estimates when using the CASQ-R. During the research,
concerns were also raised over the validity of student responses to the CASQ-R
questions, as some students struggled to relate to the hypothetical situations
presented. Furthermore, the use of hypothetical scenarios may not be the most
ideal form of measuring attribution styles as evidence has shown that the attribu-
tion beliefs a student demonstrates in response to hypothetical scenarios can
be drastically different to the causal reasons used in real life situations (Gipps
& Tunstall, 1998). Upon reflection the CASQ-R may not have been the ideal
measure for use in this study. Future researchers may benefit from using an
attribution scale with a higher reliability rating and multi-modal assessment
approach.
Implications and future directions
The findings of this pilot study have provided support for the effectiveness of
combined AR and CBT interventions to impact reading positively and suggest
that school psychologists should consider such interventions when selecting pro-
grams to support students learning and development. Though the results of the
current study were modest, they nevertheless support the viability of this positive
cognitive intervention developed by the authors. The results demonstrate that a
purely cognitive based intervention can have positive ramifications for student
academic achievement, albeit not in every curricula area.
It is important, however, to note that between group differences were not noted
in all the targeted areas. While fewer significant results are not uncommon for a
small scale pilot study such as this, it would nonetheless be beneficial for future
researchers to investigate whether a larger sample size coupled with longer mea-
surement follow-up periods would lead to a wider range of positive outcomes.
The findings also help to address the question of who should be the target of
attribution interventions. The current observations discourage the narrow view
of selection based on learning difficulties, encouraging school psychologists to
consider the growing evidence that all students can benefit from school-based
interventions, regardless of their initial level of academic ability.
Another interesting findings was that significant changes in average reading
levels between groups were only seen after a delay of two months, once students
had time to implement newly learnt skills into everyday life. This finding under-
scores the importance for school psychologists not to see such interventions as a
‘quick fix’; rather these interventions are the first part of a longer process.
To further our understanding of combined AR and CBT interventions future
researchers are encouraged to investigate the unique contribution that the two
therapeutic techniques separately have on learning. For example, comparing
groups of students who receive either CBT only, AR only, or both CBT and
Chodkiewicz and Boyle 13
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AR may add some interesting insight into the potential benefits of a combined
intervention form.
Conclusion
The aim of this pilot study was to investigate the potential benefits of combining AR
and CBT to better support student learning. School psychologists are continually
expected to be innovative and to consider various methods to improve the learning
of students, especially those lacking in motivation. This pilot study has indicated that
there is potential in using this type of intervention, which may benefit the learning of
students with the support of the school psychologist whilst working in conjunction
with school teaching staff. The observed change in average reading achievement
suggests interventions combining AR and CBT can positively improve learning in
some academic domains. While change was not seen across all areas measured, the
preliminary findings of this pilot study indicate that such interventions bode well for
attribution retraining interventions and are worthy of further investigation.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, author-
ship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication
of this article.
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Author biographies
Alicia R Chodkiewicz is a Psychologist working in the areas of Education and Child
Development, and a member of the Australian Psychological Society. Alicia has
completed a Bachelor of Psychology at the University of Sydney, a Master’s
Degree in Psychology at Monash University, and is currently completing a
Doctor of Philosophy at the University of New England, Australia. Recent pub-
lications include Believing you can is the first step to achieving (with Christopher
Boyle), published by Jessica Kingsley Press (2015).
Christopher Boyle, PhD, is a Registered and Chartered Psychologist with the
Australian and British Psychological Societies, respectfully. He is as Associate
Professor in Inclusive Education and Psychology at the University of Exeter,
UK. He is also the Editor in Chief of The Educational and Developmental
Psychologist. Recent publications include Ethical practice in applied psychology
published by Oxford University Press (2014), and Believing you can is the first
step to achieving (with Alicia Chodkiewicz), published by Jessica Kingsley Press
(2015).
Chodkiewicz and Boyle 17
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Article
Psychological school-based (SB) interventions are long standing and increasingly influenced by the evolving evidence-base. The current consensus of interventions utilises predominantly cognitive behavioural therapy (CBT) techniques. Despite their efficacy, they possess a number of weaknesses and there is an argument to propose the application of positive psychology (PP) to address these shortcomings. This paper reviews the efficacy of PP interventions in schools by evaluating 28 articles from a number of databases, focusing on child, adolescent and school professionals’ populations globally. Included articles focus on SBPP interventions revealing outcomes for mental health or well-being in children and adolescents between the ages of 5 to 16. Articles with a solely educational focus were excluded. Meta-analysis and review articles in SB CBT are also considered as a comparison for the SB PP evidence base. Articles are synthesised according to intervention purpose. The results are varied revealing PP to be effective in improving positive traits and well-being, but a scarcity of data does not support the reliability of these findings for the purpose of introducing large-scale PP SB intervention programmes. Further, discrepancies in certain results are found due to sex differences highlighting the need for extensive research into such inconsistencies. An in-depth description of the context of school-based interventions and a discussion of these findings are provided. Conclusions are made regarding recommendations for future research.