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Delayed Disaster Impacts on Academic Performance of Primary School
Children
Lisa Gibbs and Jane Nursey
University of Melbourne
Janette Cook
Smouldering Stump
Greg Ireton and Nathan Alkemade
University of Melbourne
Michelle Roberts
Department of Education and Training Victoria
H. Colin Gallagher
University of Melbourne and Swinburne University of Tech-
nology
Richard Bryant
University of New South Wales
Karen Block, Robyn Molyneaux, and David Forbes
University of Melbourne
Social disruption caused by natural disasters often interrupts educational opportunities for children. However,
little is known about children’s learning in the following years. This study examined change in academic
scores for children variably exposed to a major bushfire in Australia. Comparisons were made between chil-
dren attending high, medium, and low disaster-affected primary schools 2–4 years after the disaster
(n=24,642; 9–12 years). The results showed that in reading and numeracy expected gains from Year 3 to Year
5 scores were reduced in schools with higher levels of bushfire impact. The findings highlight the extended
period of academic impact and identify important opportunities for intervention in the education system to
enable children to achieve their academic potential.
Natural disasters arise from many different types of
hazards and cause widespread destruction, and
often death and injury. The size and severity of the
event often undermines the capacity of systems and
services to respond, resulting in significant loss of
infrastructure and facilities. The subsequent ongoing
stressors and social disruption add to the trauma of
the original event and can reduce mental health and
well-being for years afterward (Bonanno, Brewin,
Kaniasty, & La Greca, 2010; Bryant et al., 2014;
Bryant et al., 2017). In addition to the direct threats
of the disaster experienced by adults, children can
experience specific challenges associated with differ-
ent stages of physical, mental, emotional, cognitive,
and social stages of development (Anderson, 2005;
Bonanno et al., 2010; Peek, 2008).
One of the potential disruptions for children after
disasters involves access to schools because school
facilities may be destroyed, teachers are not avail-
able, or children are relocated (Casserly, 2006;
We appreciate the opportunity provided by the Department of
Education and Training to analyze such important data sets and
note that all research findings and opinions are those of the
authors and should not be attributed to the department. It is
noted that coauthor Michelle Roberts is employed by the Depart-
ment of Education and Training. We gratefully acknowledge the
generous funding provided by the Teachers Health Foundation.
We also acknowledge the NHMRC TRIP Fellowship held by Lisa
Gibbs and additional salary support from the Jack Brockhoff
Foundation for Lisa Gibbs and Karen Block. In addition to the
study authors, the following partners are contributing to the
ongoing Strengthening Schools Communities study: Victorian
Department of Health and Human Services, Australian Red Cross,
and Cindy Wilson and Gloria Melham from Catholiccare Wollon-
gong, and community member Jane Fraga. We also thank Shane
Kavanaugh for his comments on technical aspects of this article.
Correspondence concerning this article should be addressed to
Lisa Gibbs, Centre for Health Equity, University of Melbourne,
Level 5, 207 Bouverie Street, Carlton, VIC, Australia 3053. Elec-
tronic mail may be sent to lgibbs@unimelb.edu.au.
©2019 The Authors
Child Development published by Wiley Periodicals, Inc. on behalf of Society
for Research in Child Development.
This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs License, which permits use and
distribution in any medium, provided the original work is properly cited,
the use is non-commercial and no modifications or adaptations are made.
0009-3920/2019/xxxx-xxxx
DOI: 10.1111/cdev.13200
Child Development, xxxx 2019, Volume 00, Number 0, Pages 1–11
Sacerdote, 2008). The likely influence of the individ-
ual, family, social, and systemic stressors on child aca-
demic achievement have been known for some time
(Vogel & Vernberg, 1993), but the evidence base for
the nature, extent, and timing of postdisaster impacts
on child academic performance is still limited.
The evidence related to trauma exposure in early
childhood has shown a range of developmental
impacts that may be relevant to academic perfor-
mance. This includes changes in neurodevelopmen-
tal processes such as myelination, synaptogenesis,
and pruning. These processes underlie the develop-
ment of functional neurocircuits and white matter
tracts in the brain that in turn facilitate the normal
development of cognitive, emotional, social, behav-
ioral, and physical skills (De Bellis & Zisk, 2014;
Gabowitz, Zucker, & Cook, 2008; McCrory, DeBrito,
& Viding, 2010). Neuropsychological deficits associ-
ated with early childhood trauma and posttrau-
matic stress disorder (PTSD) have been well
documented and include difficulties in attention,
working memory, speed of processing, memory
retrieval, and executive skills such as planning,
problem solving, error monitoring, and set shifting,
as well as less severe difficulties in language and
visual integration skills (Barrera-Valencia, Calder
on-
Delgado, Trejos-Castillo, & O’Boyle, 2017; Samuel-
son, Krueger, Burnett, & Wilson, 2010; Spann et al.,
2012). Although the majority of research into under-
standing the neuropsychological impacts of early
trauma exposure and PTSD has been done with
children exposed to significant maltreatment (Kava-
naugh, Dupont-Frechette, Jerskey, & Holler, 2017;
Masson, Bussieres, East-Richard, Mercier, & Cellard,
2015), a small number of studies have documented
similar cognitive deficits in children exposed to
other types of trauma including disasters (Parslow
& Jorm, 2007; Turley & Obrzut, 2012). The relation-
ship between specific neuropsychological skills and
academic achievement is complex and likely changes
as the child develops (Cragg & Gilmore, 2014). Liter-
acy skills in particular are multifactorial and each
component (e.g., spelling, reading accuracy, reading
fluency, and reading speed) is thought to have differ-
ent cognitive mechanisms underlying them (Moll
et al., 2014; Ozernov-Palchik, Yu, Wang, & Gaab,
2016). Working memory and speed of processing are
considered to be core skill requirements (among
others) for the development of both numeracy and
reading skills in early primary school children (Cragg
&Gilmore,2014;Geary,Hoard,Byrd-Craven,
Nugent, & Numtee, 2007; Moll et al., 2014; Wang
et al., 2016; Welsh, Nix, Blair, Bierman, & Nelson,
2010). However, as reading progresses, visual verbal
integration skills and rapid automatized naming (in-
volving rapid retrieval of the names of sequential
visually presented items) along with higher executive
functions become important skills that can differen-
tially impact the acquisition of literacy skills (Moll
et al., 2014; Ozernov-Palchik et al., 2016). Similarly,
continued achievement in mathematicsisdependent
upon the development of broader executive functions
(Cragg & Gilmore, 2014).
The available evidence indicates that early inter-
ruptions to the development of these cognitive skills
can have adverse impacts on academic performance
at primary, secondary, and university levels (Di Pie-
tro, 2015; Pane, McCaffrey, Kalra, & Zhou, 2008; Peek
& Richardson, 2010; P
erez-Pereira, Tinajero,
Rodr
ıguez, Peralbo, & Sabucedo, 2012; Scott, Lapr
e,
Marsee, & Weems, 2014). In the disaster context such
interruptions may arise from the development of a
trauma-related mental health disorder, such as PTSD,
or be due to ongoing stressors such as having to relo-
cate to another school in another location as a result
of the disaster (McFarlane, Policansky, & Irwin, 1987;
Pane et al., 2008; Sacerdote, 2008; Scott et al., 2014).
Age-based differences emerged in a study with pri-
mary and secondary school children 1 year after an
oil spill disaster affecting coastal towns in Spain, sug-
gesting stage of development may be a factor in
determining subsequent impacts on academic perfor-
mance (P
erez-Pereira et al., 2012). Conversely, no sig-
nificant difference was found for completion of
secondary school certificates between disaster-
affected and nondisaster-affected students 2 years
after the Canterbury, New Zealand earthquakes (Bea-
glehole, Bell, Frampton, & Moor, 2017), or in aca-
demic outcomes for primary school children in the
Netherlands up to 3 years after a major firework dis-
aster (Smilde-van den Doel, Smit, & Wolleswinkel-
van den Bosch, 2006). The authors in the Netherland
study speculated these positive outcomes may have
been due to various school-based intervention pro-
grams for affected children. This is supported by
other studies that indicate that positive school envi-
ronments can, over time, mitigate the disaster-related
impacts on academic performance (Barrett, Aus-
brooks, & Martinez-Cosio, 2012; Pane et al., 2008;
Peek & Richardson, 2010; Reich & Wadsworth, 2008;
Sacerdote, 2008). This has not been specifically evalu-
ated in disaster contexts; however, a meta-analysis of
the impact of social and emotional learning programs
in schools generally, demonstrated improved aca-
demic performance across all year levels (Durlak,
Weissberg, Dymnicki, Taylor, & Schellinger, 2011).
The trajectory for potential disaster impacts on
academic achievement over time is unknown because
2 Gibbs et al.
themajorityofthecurrentevidencebaseonly
extends to 3 years postdisaster, although a 20 year
follow-up of children affected by a disaster did
demonstrate that those who were bushfire affected
were less likely than the comparison group to extend
their education and careers (McFarlane & Van Hooff,
2009). Further examination of this issue is of para-
mount importance because of the potential for short-
term impacts on academic performance to affect per-
ceptions of capability, aspirations, and long-term
educational and employment pathways.
This article reports on a study of academic scores
for primary school children in Victoria, Australia
up to 4 years after a major bushfire event in Febru-
ary 2009, commonly referred to as the Black Satur-
day bushfires (another term for “bushfire”is
“wildfire”). The aim was to identify whether:
1. students in schools with high and medium
bushfire impact showed reduced progression
in their academic scores from Year 3 to Year 5
compared to their peers in schools with low or
no impact, and;
2. if there were differences in impact for different
school subjects.
Black Saturday Bushfires
The 2009 fires in rural Victoria began in January
after a decade-long drought. The fire conditions
became extreme, beginning in the east of the state
and continuing to burn for several weeks. On satur-
day 7, February temperatures climbed to 47°C
(117°F), winds gusted at over 100 km/h (60 mph),
and multiple new fires ignited across the rural and
regional parts of the state. The fires burned 400,000
hectares of landscape, completely destroyed two
townships and significantly damaged others result-
ing in widespread destruction and the loss of 173
lives including 35 children and young people. Six-
teen children and young people were orphaned,
and many more were injured and traumatized by
their experiences (Victorian Bushfires Royal Com-
mission, 2009). One hundred and nine communities
self-identified as being affected by bushfires. Over
2,000 homes were destroyed, three schools and at
least three preschools were completely destroyed in
the fires with staff and students housed in tempo-
rary accommodation for up to 2 years. Over 70
schools and childcare settings in high impact areas
were highly affected through building and student
exposure, as were other community resources such
as sporting facilities and playgrounds, resulting in
family, school, and community level disruption for
years after the event.
Methods
Participants
This study utilized two major data sets held by
the Victorian Department of Education and Training:
(a) Enrollment in the first year at a Victorian primary
school is accompanied by a parent completed School
Entrant Health Questionnaire (SEHQ), which collects
health, well-being, development, and demographic
information about the student; (b) Standardized
National Assessment Program—Literacy and Numer-
acy (NAPLAN) academic assessments are conducted
in Grades 3 and 5 in primary school and Years 7 and
9 in secondary school. The students included in this
study were 33,690 students who in 2008 were
enrolled in first year at a Victorian government pri-
mary school and completed their standardized
NAPLAN academic assessments in 2011 (Grade 3)
and 2013 (Grade 5). Students were excluded if they
changed schools between Grade 3 and Grade 5. Stu-
dents’NAPLAN results were matched with their
SEHQ data. After this matching process the final
sample available for the analyses was n=24,642 stu-
dents (female =11,982; male =12,660).
Measures
Bushfire Affectedness
Schools included in this study were located in
areas that receive fire protection from the Country
Fire Authority (CFA) rather than the Metropolitan
Fire Brigade. This classification was used as a proxy
indicator to identify schools located in peri-urban,
rural, regional, and remote communities to mini-
mize confounding factors that would arise from
comparison with urban schools. The included schools
were then classified into three levels of bushfire
affectedness (0—low, 1—moderate, 2—high). Classifi-
cation followed a complicated geospatial procedure
using the Victorian Bushfire Reconstruction and
Recovery Authority data. There were 78 primary
schools (n=1,285) in localities defined as a “high”
bushfire affectedness region based on loss of lives
and properties. There were an additional 50 schools
(n=832) that were defined as being in a “moderate”
affected region because they were located in a catch-
ment zone adjacent to a high impact locality. The
remaining 1,073 schools (n=22,525) were defined as
being in a “low”affected region because very limited
Disaster Impacts on Child Academic Performance 3
or no damage occurred and there was no loss of
lives. They were all classified as “low”rather than
“no”impact because even the areas that did not have
fire come through were at risk on the day of the
fires, their local CFA services were all involved in
fire response, and many of the communities were
affected by subsequent road closures and service dis-
ruptions. This classification procedure was designed
by the University of Melbourne Centre for Disaster
Management and Public Safety.
National Assessment Program—Literacy and Numeracy
The NAPLAN tests are run annually in Aus-
tralian primary schools for students in Grade 3
and Grade 5. They are designed to assess four
education domains of reading, writing, numeracy,
and language conventions. The language conven-
tions are further subdivided into spelling and
grammar.
School Entrant Health Questionnaire
Household language. Is the primary household
language English? (0—no, 1—yes).
Aboriginal or Torres Strait Islander. Is the student
an Aboriginal or Torres Strait Islander (ATSI)? (0—
no, 1—yes).
Lives with both parents. Does the student live
with both parents? (0—no, 1—yes).
Parents Evaluation of Developmental Status. The
Parents Evaluation of Developmental Status path-
way is based on parent responses to questions
about the child covering eight domains; (a) expres-
sive language and articulation; (b) receptive lan-
guage; (c) fine motor skills; (d) gross motor skills;
(e) behavior; (f) social-emotional; (g) self-help;
(h) school. Parents report whether they have con-
cerns in these domains (yes or no). Children are
rated for risk, from 1 to 4, with higher scores indi-
cating lower risk, based on the number of items
which are scored as “yes.”
Mother’s education/father’seducation. The mother’s
and father’s education was a self-report question
whereby the parent’s highest level of school educa-
tion was selected as either: “Year 9 or Equivalent or
below”;“Year 10 or Equivalent”;“Year 11 or
Equivalent”; or, “Year 12 or Equivalent.”
Statistical Analyses
When data intrinsically have a hierarchical or
clustered structure then multilevel models (MLM)
are specifically designed for these types of analyses
(Hox, 1998). As is the case in most educational
research the data in this study are nested at the
individual (Level 1) and within schools (Level 2),
which supports the use of MLM analyses. Regard-
less of whether the primary variables of interest are
at the individual or school level, failure to account
for the clustering effects can lead to incorrect con-
clusions due to inaccurate calculations of standard
errors and confidence intervals (Maas & Hox, 2004).
We ran our analysis using Mplus version 7.4
(Muth
en & Muth
en, 2013) with the robust maxi-
mum likelihood estimator. Our analysis is a specific
type of MLM—random slope analysis. Furthermore,
we include the test of whether the random slopes
are predicted by the level of bushfire affectedness
(i.e., low, moderate or high level of affectedness).
Our analysis will control for school clustering
effects when defining the slope of change at the
individual level, predicting Year 5 NAPLAN
domain scores based on corresponding Year 3
NAPLAN domain scores.
In our study, we are primarily focused on
whether the level of bushfire affectedness predicts a
difference in academic performance at the school
level. Therefore, at the higher level of the model we
will include bushfire affectedness as a predictor of
the slope. If this affectedness level significantly pre-
dicts the slope, then the rate of change between
Year 3 NAPLAN domain scores and Year 5
NAPLAN domain scores is different between the
schools within the three affectedness levels. To
account for the influence of demographic factors,
we have included “Lives with both parents,”
“Home language English,”“ATSI status,”
“Mother’s level of education,”“Father’s level of
education,”“Gender,”and “Pediatric Health”as
controlling variables for the Year 3 and Year 5
NAPLAN scores. The analysis will account for
these demographic influences prior to defining the
slope between Year 5 and Year 3 NAPLAN scores.
In simple terms, our analysis will define a slope
that represents the relationship between Year 3
NAPLAN scores predicting Year 5 NAPLAN scores.
The scores at both year levels are controlled for by
relevant demographic variables to minimize noise.
As the data are clustered we run this analysis using
the recommended MLM approach. Finally, at the
school level we investigate the impact of bushfires on
the slopes, which were defined at the individual
level. This will investigate whether the 2009 Black
Saturday bushfires are influencing the natural rela-
tionship between Year 3 and Year 5 NAPLAN scores.
These analyses have been run five times separately
for each of the NAPLAN domains: (a) reading, (b)
4 Gibbs et al.
writing, (c) spelling, (d) numeracy, and (e) grammar.
We ran the multilevel analyses with list wise deletion
for missing data enabled, as per the Mplus default
settings.
Results
Descriptive Statistics
Demographic details are provided in Table 1.
Dependant samples T-tests found that both overall
and for each affectedness region separately,
NAPLAN domain scores in Grade 5 were signifi-
cantly higher compared with domain scores in
Grade 3 (all p<.001). Chi-square tests were con-
ducted to compare categorical variables across
affectedness regions and found the proportion of
students who lived with both parents was signifi-
cantly lower (p=.004) in the high impact region
(84.4%) compared with the medium impact (88.9%)
and the low impact (87.4%) regions. Additionally,
the proportion of mothers who had a minimum
level of education being Year 12 or equivalent was
significantly lower (p<.001) in the high impact
(51.8%) and medium impact (56.0%) regions com-
pared with the low impact region (64.4%). Simi-
larly, the proportion of fathers who had a
minimum level of education being Year 12 or
equivalent was significantly lower (p<.001) in the
high impact (40.2%) and medium impact (42.4%)
regions compared with the low impact region
(56.2%). There were no other differences in the
demographic variables.
Multilevel Results
The full details of the separate multilevel analy-
ses for each of the five NAPLAN domains can be
seen in Table 2. In Level 1 we see across all five
NAPLAN domains 29 of 35 controlling variables
were significant for Year 3 scores, and there were
28 of 35 that were significant for Year 5 scores,
although there were some differences in which vari-
ables were significant at each year level.
At Level 2 we find the predictive relationship
between Year 3 and Year 5 NAPLAN scores is unaf-
fected by level of bushfire impact for the writing,
spelling, and grammar domains. Conversely, the
predictive relationship between Year 3 and Year 5
NAPLAN scores is affected by level of bushfire
impact for the reading and numeracy domains. In
both sets of analysis there was a significant negative
relationship at Level 2 between the slope and
affected level, therefore as affected level increases the
slope decreases, or the slope becomes flatter between
Year 3 NAPLAN and Year 5 NAPLAN. That is, we
find a flattened developmental trajectory between
Year 3 and Year 5 NAPLAN scores (reading and
numeracy) for those individuals in schools that have
been more affected by the bushfires.
To investigate the differences in the slopes for
the reading and numeracy domains across the
levels of bushfire affectedness, subpopulation analy-
ses were run in Mplus using the Complex data
command to control for clustering effects when cal-
culating standard errors in the model. The differ-
ences in the slopes across bushfire affectedness
regions can be seen in Figure 1. This figure shows
the comparative standardized beta weights for Year
5 NAPLAN domain scores being predicted by Year
Table 1
Student Participants’Demographics
Measure M(SD)/proportion
Age
a
9.97 (0.42)
Gender (% female) 48.60%
ATSI (% yes) 1.60%
Home language English (% yes) 88.80%
Lives with both parents (% yes) 87.30%
Mother education (mode) Year 12 +(63.5%)
Father education (mode) Year 12 +(55.0%)
PEDS
High risk 6.80%
Moderate risk 16.60%
Low risk 8.20%
None 68.40%
Region impact
Low (n) 22,525 (91.4%)
Medium (n) 832 (3.4%)
High (n) 1,285 (5.2%)
NAPLAN
b
Grade 3 (2011)
Reading 435.17 (88.35)
Writing 424.04 (60.86)
Spelling 416.58 (74.96)
Numeracy 417.52 (74.17)
Grammar 436.96 (93.24)
NAPLAN Grade 5 (2013)
Reading 511.31 (65.47)
Writing 489.59 (60.78)
Spelling 498.02 (68.38)
Numeracy 496.81 (73.25)
Grammar 507.83 (71.21)
Note. ATSI =Aboriginal or Torres Strait Islander; PEDS =Par-
ents Evaluation of Developmental Status; NAPLAN =National
Assessment Program—Literacy and Numeracy.
a
Age at February 1, 2013 (Grade 3). The data were captured in
whole years and did not include months.
b
The range of possible
scores in each domain for each year level is 0–1,000 (Australian
Curriculum Assessment and Reporting Authority, 2013).
Disaster Impacts on Child Academic Performance 5
3 NAPLAN domain scores in each region sepa-
rately after controlling for demographics. As we
can see for the domains of reading and numeracy
there is a pattern of reduction in the slope values
with the increase in levels of bushfire affectedness.
Although the scores for numeracy plateau between
the “moderate”and “high”affected regions, they
are both sufficiently less than the slope for the
“low”region to find a significant result.
Discussion
This study analyzed primary students’academic
performance from 2 to 4 years after the Black Satur-
day bushfires, adjusting for demographic factors
collected 1 year before the bushfires. The analyses
examined the level of improvement in academic
scores from Year 3 to Year 5 across regions of
impact (i.e., were the changes in academic scores
over time the same for low-, moderate-, and high-
affected regions). The results showed that in read-
ing and numeracy the expected gains in academic
scores from Year 3 to Year 5 were reduced with
higher levels of bushfire impact. There were no sig-
nificant trends in academic scores for the writing,
spelling, and grammar domains of the academic
assessment, and no gender differences in any of the
scores.
This finding demonstrates the potential impact of
disaster exposure on academic performance. The
differential impact on subject performance was con-
sistent with another study of student academic per-
formance after a fire at a discotheque party in
Sweden in which 63 young people were killed and
213 physically injured (Broberg, Dyregrov, & Lilled,
2005). The authors attributed this to the different
levels of concentration required: “The most negative
influence on schoolwork was reported for subjects
demanding high concentration (e.g., mathematics,
Table 2
Multilevel Model Unstandardized Parameter Coefficients (B) and Significance Tests (p) at Level 1 and Level 2 for NAPLAN Domains Reading,
Writing, Spelling, Maths, and Grammar
Reading
(n=16,240)
Writing
(n=16,182)
Spelling
(n=16,254)
Maths
(n=16,147)
Grammar
(n=16,254)
BpBpBpBpBp
Level 1
Y3 NAPLAN
Both parent 9.214 .001 3.345 .037 0.594 .603 3.908 .021 2.834 .084
Home lang 6.225 .006 5.081 <.001 7.207 <.001 10.215 <.001 3.731 .006
ATSI 19.855 .002 6.841 .064 0.528 .847 4.760 .152 11.221 .005
Mother education 13.410 <.001 4.289 <.001 1.118 .001 2.569 <.001 4.513 <.001
Father education 13.030 <.001 4.391 <.001 1.956 <.001 3.108 <.001 3.961 <.001
Gender 13.577 <.001 12.639 <.001 3.192 <.001 7.467 <.001 2.862 <.001
PEDS8 5.911 <.001 1.775 <.001 0.453 .109 0.874 .028 2.743 <.001
Y5 NAPLAN
Both parent 1.692 .218 5.446 .004 5.822 .010 10.007 <.001 6.760 .017
Home lang 0.372 .751 5.410 <.001 14.159 <.001 2.472 .233 2.040 .396
ATSI 4.754 .130 13.396 .002 8.240 .161 16.062 .001 16.779 .031
Mother education 2.400 <.001 7.504 <.001 8.007 <.001 9.559 <.001 13.672 <.001
Father education 2.898 <.001 6.181 <.001 9.958 <.001 10.548 <.001 13.971 <.001
Gender 0.764 .263 19.927 <.001 12.709 <.001 14.837 <.001 18.932 <.001
PEDS8 1.984 <.001 4.590 <.001 5.059 <.001 4.601 <.001 6.177 <.001
Level 2
Slope
AFFLVL 0.038 <.001 0.005 .739 0.016 .101 0.051 <.001 0.675 .500
Y5NAPLAN
AFFLVL 1.508 .163 1.659 .170 1.096 .231 2.735 .045 3.014 .028
Y3NAPLAN
AFFLVL 4.862 .013 1.702 .241 4.853 .002 3.036 .127 4.646 .025
Reference category for gender =male. ATSI =Aboriginal or Torres Strait Islander; PEDS =Parents Evaluation of Developmental Status;
NAPLAN =National Assessment Program—Literacy and Numeracy.
6 Gibbs et al.
physics, and grammar) whereas subjects like reli-
gion, psychology, and arts were reported to have
become easier, more interesting or more important”
(pp. 1282–1283). This may reflect a shift in student
priorities and social and emotional responses to
subject content following their loss and trauma
experiences. Another explanation is that difficulties
with certain subjects are mediated through the dis-
ruption of neuro-maturational processes that under-
lie the development of cognitive, social, and
emotional building blocks necessary for academic
achievement (De Bellis & Zisk, 2014; Gabowitz
et al., 2008; McCrory et al., 2010).
Different types of cognitive deficits related to
working memory, speed of processing, visual -
verbal integration skills, rapid automatized naming,
and higher executive functioning may have greater
importance for particular types of learning. How-
ever, given that these same cognitive skills are
known to be impacted by early trauma experiences
and the development of PTSD, it is possible to
hypothesize that the deficits in reading and numer-
acy demonstrated by the children in this study may
be cognitively mediated (either directly or indirectly
though the development of PTSD), as was reported
in the Broberg et al. (2005) study. This is supported
by evidence that lower socioeconomic status and
proximity to disaster impact zone have been inde-
pendently associated with higher risk for delayed
development of these core neuropsychological skills
(Welsh et al., 2010) as well as development of PTSD
(Terasaka, Tachibana, Okuyama, & Igarashi, 2015).
Studies of children’s postdisaster recovery trajec-
tories have shown different groupings, reflecting
individual variation in response to a given experi-
ence. Some children show resistance to disaster
impacts, others show progressive recovery, and
others show ongoing or delayed impacts (Kronen-
berg et al., 2010; La Greca et al., 2013; Saigh,
Mroueh, & Bremner, 1997; Scott et al., 2014; Shan-
non, Lonigan, Finch, & Taylor, 1994). There are also
likely to be different contributing factors to poor
academic performance including persistent symp-
toms of PTSD and aggression (Scott et al., 2014),
impacting on school satisfaction (Sims, Boasso,
Burch, Naser, & Overstreet, 2015) and test anxiety
(Weems et al., 2013) School staff are often acutely
aware of the initial impacts of an emergency event
on students’academic performance (Dyregrov,
Dyregrov, Endsjø, & Idsoe, 2015). However, over
time, parents and schools may not recognize that
delayed impacts arise from the disaster experience,
and therefore children may not be offered appropri-
ate support programs (Gibbs et al., 2015; Grelland
Røkholt, Schultz, & Langballe, 2016; Smilde-van
den Doel et al., 2006).
The impact on reading results in this study may
also have arisen due to reduced supported reading
at home. Our previous work has shown that the
bushfires and subsequent life stressors markedly
0.650
0.660
0.670
0.680
0.690
0.700
0.710
0.720
0.730
0.740
0.750
Low Impact Medium Impact High Impact
Reading* Numeracy*
Figure 1. Standardized beta weights for Year 5 National Assessment Program—Literacy and Numeracy (NAPLAN) predicted by Year
3 NAPLAN across regions of bushfire affectedness.
Disaster Impacts on Child Academic Performance 7
affected the mental health of parents up to 5 years
later (Bryant et al., 2017), which could create a fam-
ily environment that could hinder children’s abili-
ties to study and learn. We also note that parents in
the high-affected region had lower education levels,
and it is possible that this factor may have con-
tributed to the poorer performance of children in
these communities. No other studies of children’s
postdisaster academic performance have identified
subject differences in impacts. However, a study of
prenatal exposure to disaster has shown a similar
association with lower third grade results in read-
ing and maths (Fuller, 2014). It was not possible in
this study to assess individual exposure to the dis-
aster from the available data, including psychologi-
cal or family factors that may moderate academic
performance. Instead, attendance at schools in dis-
aster impacted areas was used as a proxy for disas-
ter exposure. At primary school level, the vast
majority of students would be attending schools
close to their home, as compared to secondary
school for which many students travel longer dis-
tances.
It is also possible that academic performance
was impaired because of substantial damage to
infrastructure and social disruption in schools,
which directly limited the accessibility of teaching
facilities for children. Focusing on school-level
impacts is helpful in highlighting the demands on
school staff and resources (Alisic, Bus, Dulack, Pen-
nings, & Splinter, 2012; Casserly, 2006), and the
importance of a planned comprehensive program of
postdisaster support for children. It has been sug-
gested that school-level programs and high stan-
dards of academic achievement at students’new
schools may mitigate the disruption and academic
decline experienced by relocation (Barrett et al.,
2012; Pane et al., 2008; Peek & Richardson, 2010).
However, this is mostly based on research arising
from Hurricane Katrina where the children moved
away from schools that have been described as
among the most poorly performing schools in the
USA to schools with higher academic standards
and expectations of students (Casserly, 2006; Peek
& Richardson, 2010; Reich & Wadsworth, 2008). A
combination of sensitive support from teachers, tar-
geted academic support, and encouragement to
engage in extracurricular activities have been indi-
cated but not yet proven as factors likely to enable
students to adjust to the school changes and thus to
realize their academic potential (Barrett et al., 2012;
Grelland Røkholt et al., 2016; Pane et al., 2008;
Smilde-van den Doel et al., 2006). This provision of
a positive supportive environment has been
recognized more broadly as an important element
in child and youth resilience (Durlak et al., 2011;
Ungar, 2011), and mental health promotion (Weare
& Nind, 2011). Further research would be helpful
to identify the content and dose of school-level
interventions most likely to support positive post-
disaster outcomes. Additional examination of regio-
nal differences would also provide insights into the
influence on student resilience of wider factors such
as levels of available resources, local recovery pro-
cesses, and social connectedness.
In the data sets utilized for this study, it was not
possible to track students who moved to different
schools during their primary school years. This
means that the final sample only included students
who attended the same school in Prep, Grade 3, and
Grade 5. It is possible that some students temporar-
ily relocated and then returned between the study
measures. However, children who permanently relo-
cated were not included in the sample because of
the difficulties in linking the data. This is a limitation
of the study. Families who relocated following the
Black Saturday bushfires were most likely to have
been significantly affected in terms of property loss
(Gibbs et al., 2016). Other postdisaster studies have
also shown that children who relocated to new areas
and schools were most at risk initially of poor aca-
demic outcomes (Pane et al., 2008; Peek & Richard-
son, 2010; Sacerdote, 2008). Therefore, the results in
this study may represent an underestimation of the
disaster impacts on academic achievement. In fact,
high mobility in school years is generally considered
a risk factor for academic achievement (Obradovic
et al., 2009) particularly if it occurs for “negative”
reasons, but the effect may be a proxy for a range of
other high-risk factors such as low income,
marginalized social groups, and non-nuclear fami-
lies (Pane et al., 2008). As previously noted, in a
postdisaster context, it appears that the initial nega-
tive consequences of shifting to a new school in a
new area may be offset by a positive school culture
(Barrett et al., 2012; Peek & Richardson, 2010).
Conclusion
This study contributes new findings about delayed
impacts on academic achievements for children living
in postdisaster communities. It extends the existing
evidence base by examining the period up to 4 years
after the event and identifies a subject-specificdepres-
sion in academic achievements over time for reading
and numeracy that clearly differentiates between dif-
ferent levels of bushfire affectedness at the school
8 Gibbs et al.
level. Given the apparent delayed impact, previous
findings in the literature of no impact within a 3-year
period of the disaster event should be reviewed.
Although it is positive to find no difference in those
early years after the event, the risk is that subsequent
impacts on academic performance are overlooked
and, without targeted interventions, children’sfuture
academic trajectories, and life opportunities may be
compromised. There is emerging evidence that the
early neurodevelopmental impacts of trauma may
only be observed at later stages of development
when key abilities are due to emerge, for example,
the development of executive skills through adoles-
cence. Without early intervention, these adverse
developmental trajectories have the potential to
impact educational and functional outcomes many
years down the track. It is promising that the wider
evidence base indicates there are opportunities to
mitigate negative impacts on child academic achieve-
ments through positive multilevel school strategies.
This provides direction for research, policy, and
school-level planning and response to disaster events.
This study may also be used to guide future research
studies into the developmental factors likely to be
underlying the delayed impacts on academic achieve-
ment specifically relating to reading and numeracy.
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