The Cost of Autism Spectrum Disorders
Citation: Horlin C, Falkmer M, Parsons R, Albrecht MA, Falkmer T (
The Cost of Autism Spectrum Disorders
Chiara Horlin 0
Marita Falkmer 0
Richard Parsons 0
Matthew A. Albrecht 0
Torbjorn Falkmer 0
Jennifer Gladys Mulle, Emory University School Of Medicine, United States of America
0 1 School of Occupational Therapy & Social Work, CHIRI, Curtin University , Perth , Australia , 2 School of Education and Communication, CHILD Programme, Institute of Disability Research, J o nko ping University, Jo nko ping, Sweden, 3 School of Psychology, CHIRI, Curtin University , Perth , Australia , 4 Rehabilitation Medicine, Department of Medicine and Health Sciences (IMH), Faculty of Health Sciences, Linko ping University & Pain and Rehabilitation Centre, Linko ping, Sweden, 5 School of Occupational Therapy, La Trobe University , Melbourne, VIC , Australia
Objective: A diagnosis of an autism spectrum disorders is usually associated with substantial lifetime costs to an individual, their family and the community. However, there remains an elusive factor in any cost-benefit analysis of ASD diagnosis, namely the cost of not obtaining a diagnosis. Given the infeasibility of estimating the costs of a population that, by its nature, is inaccessible, the current study compares expenses between families whose children received a formal ASD diagnosis immediately upon suspecting developmental atypicality and seeking advice, with families that experienced a delay between first suspicion and formal diagnosis. Design: A register based questionnaire study covering all families with a child with ASD in Western Australia. Participants: Families with one or more children diagnosed with an ASD, totalling 521 children diagnosed with an ASD; 317 records were able to be included in the final analysis. Results: The median family cost of ASD was estimated to be AUD $34,900 per annum with almost 90% of the sum ($29,200) due to loss of income from employment. For each additional symptom reported, approximately $1,400 cost for the family per annum was added. While there was little direct influence on costs associated with a delay in the diagnosis, the delay was associated with a modest increase in the number of ASD symptoms, indirectly impacting the cost of ASD. Conclusions: A delay in diagnosis was associated with an indirect increased financial burden to families. Early and appropriate access to early intervention is known to improve a child's long-term outcomes and reduce lifetime costs to the individual, family and society. Consequently, a per symptom dollar value may assist in allocation of individualised funding amounts for interventions rather than a nominal amount allocated to all children below a certain age, regardless of symptom presentation, as is the case in Western Australia.
Competing Interests: The authors have declared that no competing interests exist.
A diagnosis of an Autism Spectrum Disorder (ASD) results in an
estimated annual national cost to Australia of $4.57.2 billion 
that is borne by the individuals themselves, their families, their
community, and by government. Costs of autism can peak during
the periods when a diagnosis is being assessed and when
treatments are being administered, but many costs are ultimately
on-going and constitute a life-long burden. The accurate
identification of ASDs necessarily relies on assessing observable
behaviours using timely, accurate, reliable and valid diagnostic
procedures. At present, the gold standard diagnosis of autism is
a lengthy and time consuming process that requires a suitably
qualified multi-disciplinary team (MDT) to assess behavioural,
historical and parental report information to determine a definitive
diagnosis . This is discouraging since failing to accurately
identify, or prolonging the identification of, children as having
ASD will delay access to apposite intervention and support services
[5,6]. This issue is compounded by the possible 25 fold increase in
the recent diagnosis rates of ASD in Australia , and resultant
pressing demand for delivery of diagnostic services and
It is possible that the delay in treatment and support for children
with ASD results in significant costs. Recently, the estimated
annual adjusted costs for an adult and a child with autism have
been calculated as follows (all dollar values are in AUD and
rounded to the nearest dollar):
where, P = production loss of the individual and family with an
ASD diagnosis, SP = support costs, S = school costs, mainly
addition and specialist staff, M = medical costs, and CMD =
missed diagnosis. It is important to note that several assumptions
are made regarding productivity costs that we do not feel fully
encompass the impact of a childs diagnosis on parent employment
resulting in what appears to be a very low estimate of the financial
impact (e.g., time taken out from current employment for
treatment visits is accounted for, but reduced employment of
parents so that they can care for a child with ASD is not taken into
account). Notably, estimates for the parameter CMD (missed
diagnosis) have not been made and, as a result, the true benefit of a
diagnosis of ASD could not be calculated. It seems plausible that
an early diagnosis of autism may reduce the cost of ASD because
diagnosis leads to early intervention, which results in better
outcomes [7,8], improved social behaviour [9,10], and less
reliance on specialised education support classes [7,9]. These
improvements may, in turn, have knock-on benefits to families and
society more broadly, as well as increased productivity for parents
and the individual themselves later in life. These gains are usually
accomplished when intervention is commenced very early,
between the ages of 2 and 4 [11,12].
However, the complication here is clear: those individuals
remaining undiagnosed are, for that very reason, inaccessible to
service providers and researchers alike. The next closest
approximation that can be made for parameter CMD is therefore the
difference in costs between those children identified and treated
early in their development and those not identified and/or treated
until later in childhood or even adolescence and adulthood. One
method of estimating this cost is to identify a subgroup of children
who receive a diagnosis of ASD shortly after their parents suspect
their childs development is atypical, and then compare costs for
these children with a subgroup of children who had their diagnosis
formally confirmed much later. However, one possible offset of the
cost of early diagnosis is the long-term accumulated cost of
interventions and special services. Therefore, the potential added
cost associated with a later diagnosis may not be substantially
higher than an earlier diagnosis.
Research into the impact of receiving an early diagnosis and on
a familys financial burden is limited . In Australia, state and
territory governments are primarily responsible for supporting
disability, including ASD, rather than the Commonwealth.
However, families with a child diagnosed with an ASD receive a
finite amount of Commonwealth funding up to the childs seventh
birthday (the so-called Helping Children with Autism -funding)
for the purposes of early intervention. From this point onwards,
ongoing therapies and services outside of school are largely
parentfunded on top of other medical and non-medical costs. Aside from
the obvious cost to families of missing this early opportunity for
government funding, the current study also seeks to determine
whether a delayed diagnosis results in inflated costs, reduced
incomes and increased financial stresses to families on a long-term
basis when compared to families of individuals with a more
immediate the immediate diagnosis. Thus it will be possible to
estimate an accessible proxy of the parameter CMD.
Participants and Procedures
With the assistance of the Disabilities Services Commission
(DSC) Western Australia, a questionnaire was distributed to
families with children registered as having an ASD on their client
register. Only families with diagnosed children currently under the
age of 18 years were included. This decision was made in line with
recommendations from the DSC based on the likelihood of
correct/valid information being extractable from the register. At
the time of the mail out, 3,965 children were registered with DSC
from 3,723 families. Of the packages mailed out, 3,494 were sent
to families with one child with ASD, 217 packages sent to families
with two diagnosed children, 11 packages sent to families with
three diagnosed children and one package sent to a family with
four children diagnosed with ASD. Families with more than one
child under 18 received one questionnaire for each child with
ASD. Of the 3,723 questionnaire packs (covering 3,965 children)
sent out by DSC, 192 were returned as address unknown. In
total, 521 questionnaires were returned, resulting in a response
rate of 15%.
Questionnaire Development. Development of the full
parent-report questionnaire was informed by anecdotal reports
from clinical experts and families, the current research literature
and insurance reports. Firstly, the general areas of interest were
listed and all financial aspects were itemised and categorised to
cover as many potential expenses that were a consequence of
having a child with ASD. The questionnaire also attempted to
gather and summarise information on all possible direct medical,
direct non-medical and indirect costs associated with having a
child with an ASD. The areas of expense addressed in the
questionnaire are listed in Table 1 and specific items relevant to
each area are presented in the final questionnaire in the Appendix
S1 in the provided Supporting Information.
Questions were then devised to gather the information
conveniently and efficiently, which would lead to clear and
relevant summary reports whilst taking into account the
heterogeneity of families with ASD. A pilot version of the questions and
response formats were sent for comments to a number of clinical
psychologists, neuropsychologists, developmental psychologists,
social workers, occupational therapists, and other clinicians and
A full version of the questionnaire was then piloted on three
families who have children with ASD. Based on their comments
and feedback the questionnaire was adjusted to its final version
(Appendix S1) and comprised a total of 73 items on demographic
information, the childs diagnosis, developmental history,
treatment history, education, child care and qualitative questions about
the child and families quality of life.
The final page of the questionnaire included a diagnostic
checklist of DSM-IV-TR/ICD-10 items . The checklist
consists of 20 symptom characteristics divided into 4 sections
addressing the traditional symptom domains of;
-Impairments in social interaction (five symptom characteristics),
-Impairments in communication (seven symptom characteristics),
-Restricted, repetitive and stereotyped patterns of behaviour,
interest or activities (seven symptom characteristics),
-The presence of impairments in at least one of the above before
the age of three (one characteristic).
Parents were asked to indicate whether any of these
characteristics currently previously applied to their child.
Data Collection. Questionnaire packs were prepared by the
authors before being delivered to the DSC. To maintain
confidentiality of the DSCs client register, all printing of cover
letters and addressing of envelopes was handled by the DSCs staff
and at no time did any of the researchers have access to this
register. As per the DSCs records, packs were sent to the primary
contact, the default for which was the diagnosed childs father.
Caregiver lost productivity
Family quality of life
Support services for other family members
The questionnaire pack included the questionnaire itself and a
reply paid return envelope. All questionnaires were de-identified
and asked for no identifying information.
After a period of one month, reminders to complete the
questionnaire were published online, in newspapers, DSC
newsletters and on community radio. Upon receiving deidentified
and completed questionnaires, a unique anonymous identifier was
allocated to each questionnaire. Responses were then entered into
a data file using IBM SPSS version 20 and analysed using the SAS
version 9.2 statistical software.
Treatment-related travel costs. Direct costs associated
with travel for medical, therapeutic and
complimentary/alternative treatments were calculated as a function of the reported
frequency of average visits per month (questions 19, 28 and 36
respectively) and distance from these services (questions 18, 27 and
35 respectively). Round trip costs were calculated based on
doubling the median kilometre distance from services and the
average per kilometre cost of running a small car (approximated at
$0.65AUD per kilometre by the most recent Royal Automobile
Individual cost estimates were calculated for medical visits
relating to a childs ASD diagnosis, therapeutic visits relating to an
ASD diagnosis and complimentary/alternative visits undertaken
as part of ASD treatment. These were summed to create a
monthly cumulative total, which was then adjusted to create an
annual estimate of treatment related travel costs according to the
Travel Cost ($AUD)~12|
X (0:65|(VMedical:DMedical zVTherapy:DTherapyzVComp:DComp))
where V equals the number of visits per month, D equals the
distance in km to the service. Medical, Therapy and Comp
refer to medical professional services, other therapeutic services
and complementary and alternative services respectively.
Out of pocket treatment costs. The reported annual
outof-pocket costs to families in relation to ASD- specific medical,
therapeutic and complimentary/alternative treatment services
(questions 22, 33 and 37) were summed to create a total direct
treatment cost variable. All three questions had seven potential
response options representing intervals of dollar amounts. These
options were then converted to the mid-point of each interval to
create a single dollar amount for analysis. These recoded variables
were then summed to create a cumulative total of the out of pocket
costs associated with ASD-specific medical, therapeutic and
Loss of income from employment reduction. The
productivity loss associated with having a child diagnosed with ASD
was calculated based on self-reported impact of their childs
diagnosis on the parent/caregiver ability to work (question 51)
and, if employment status was affected, the size of this reduction as
a function of hours in the average work week (question 52). Those
responding to question 51 by selecting options one, two or three,
as presented in Table 2, then indicated the reduction in hours in
question 52. This reduction was thereafter converted to a
proportion of full-time equivalent (FTE) employment. Those
indicating that either one or both parents could not work at all at
this time due to the needs of their ASD child were converted to an
FTE reduction of 1 or 2 units, respectively. Parents indicating that
their employment status was unaffected were coded as 0. This
variable was then multiplied with the median full-time income for
20102011 as reported by the Australian Taxation Office (the
latest figures made available), which was $48, 864.
Cumulative cost of having a child diagnosed with
ASD. To create a single estimate of direct and indirect expenses
to each family that were specifically related to having a child
diagnosed with ASD, the costs associated with treatment-related
travel, out-of-pocket treatment expenses and loss of income/
productivity were summed.
Immediate versus delayed diagnosis. A dichotomous
immediate versus delayed diagnosis variable was created based
on cross-tabulations between questions 10 (age at first suspicion of
something not being quite right) and 12 (age at which a formal
diagnosis was received). This variable was intended to capture the
chronological difference between those receiving early or more
immediate diagnosis (and presumably treatment and intervention)
and a later or delayed diagnosis (often after the optimal
developmental window for treatment and period at which early
intervention would take place). Those children with a zero or one
step chronological difference between questions 10 and 12 were
coded as immediate and those with a two or more step difference
between these questions were coded as delayed. A further,
stricter, division of immediate and delayed was also conducted
by retaining only those with a zero step difference between
questions 10 and 12 (immediate) and those with a three or more
step difference (delayed). These divisions are delineated in
Cumulative presence of ASD symptoms. The total
number of ASD symptoms was estimated by a cumulative total of the
positive indications from the presence of symptoms within the four
domains listed on the DSM-IV/TR-ICD-10 checklist. Positive
indications were coded as one and responses in domain one to
Question 51: How much has your childs diagnosis affected the employment status of your household?
Both parents must work less hours
One parent (of a two-parent household) must work less hours
Single parent must work less hours
One parent cannot work at this time
Both parents cannot work at this time
1 FTE reduction
2 FTE reduction
0 FTE reduction
0 FTE reduction
.2 FTE reduction
.4 FTE reduction
.6 FTE reduction
.8 FTE reduction
1 FTE reduction
three were summed to create a total for each child. The fourth
domain comprised one single developmental history question and
was excluded from this total, since this characteristic was regarded
as a prerequisite for receiving a diagnosis of ASD.
Analysis of non-respondents. Six months after the initial
mail-out, a random sample of 405 families registered with the
DSC were contacted for a telephone follow-up. Given the
confidentiality of the DSC register and the de-identified nature
of the returned questionnaires, it was not known which families on
the register had or had not completed the long-form questionnaire.
Thus, the random sample of 405 families would include those that
had completed and returned a questionnaire and those that had
not. Non-respondents were then asked to answer an abbreviated
form of the questionnaire over the phone. This short-form phone
questionnaire consisted of twenty questions taken from the original
questionnaire for the purposes of a later drop-out analysis. Those
questions included in the short-form are shown in italics in
Appendix S1. For the purposes of comparisons between those that
did and did not respond to the long-form questionnaire that was
sent out via mail, independent samples t-tests were used to
compare the ages of children, chi-square tests were used to
compare categorical demographic variables and Mann-Whitney U
tests were conducted to compare calculated cost variables. Due to
the shortened nature of the short-form questionnaire, only the out
of pocket treatment costs and the loss of income from employment
reduction variables could be calculated for both respondents and
non-respondents. The response categories of some demographic
variables (question 10 and 12 specifically) were collapsed to ensure
validity of the chi-square test.
Ethical approval was obtained from the Curtin University
Human Research Ethics Committee (HR 138/2012) and the
internal ethical review board of the DSC in Western Australia.
Questionnaire packs were sent to the DSCs clients with a cover
letter from the Director General of DSC explaining the nature and
purpose of the study as well as an information sheet inviting
families to complete and return the questionnaire. Completed and
returned questionnaires were taken as consent to participate in the
The characteristics of the included 521 children with ASD are
presented in Table 4. Descriptive statistics for all cumulative cost
estimates and the cumulative presence of ASD symptoms are
presented in Table 5. An additional total cost of ASD variable for
families with only one child diagnosed with ASD was calculated to
express the costs of ASD without the compounding effect of having
multiple children with ASD and the implications this may have to
Q12: How old was your child when she/he was formally diagnosed with an ASD?
Q10; How old
was your child
when you or
someone else noticed
something was different
or not quite right?
Numbers in bold indicate the stricter division of immediate (N = 116) versus delayed (N = 138).
Completed year 10
Completed year 12
Completed certificate at TAFE (or similar)
Some university education but did not complete
Completed university undergraduate degree
Completed university postgraduate degree
Two-parent plus extended
Single parent plus extended
Combined annual income
Only extended family (grandparents etc)
Percentage values are rounded to two decimal places where possible.
reductions in FTE employment. The cumulative Cost of ASD
variable predominantly consisted of loss of income of the parents
and caregivers (89%) with ASD-related travel costs (3%) and
treatment costs (8%) making smaller contributions.
The cost of ASD as a function of immediate versus
delayed diagnosis or frequency of ASD symptoms
A regression analysis was conducted with cost of ASD as the
dependent variable. Independent variables included: immediate
(coded as 1) versus delayed (coded as 2) diagnosis, ASD symptom
frequency (as continuous numeric), age of child in years, number
of siblings (0, 1, 2 or 3+), number of siblings with ASD (0, 1, or 2+),
combined income (in $AUD), age of diagnosis of child with autism
(1 = 012 months, 2 = 1224 months, 3 = 26 years, 4 = 612
years, 5 = 1218 years) and highest education of the mother and
father (1 = year 10, 2 = year 12, 3 = TAFE, 4 = Apprenticeship,
5 = some university, 6 = Bachelor degree, 7 = postgraduate
degree). The residuals from the regression analysis were plotted
(histogram and density plots) and followed a normal distribution.
The R2 values for the two models evaluating the different criteria
for immediate versus delayed diagnosis (i.e., loose and strict cut off)
below were 21% and 31%, respectively, as shown in Table 6.
Out of pocket treatment
Loss of income
Cost of ASD
Cost of ASD (1 ASD child per household)
Frequency of ASD symptoms
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Regardless of whether the strict or loose definition of the
immediate versus delayed diagnosis variable was used, neither
was found to be significantly associated with the of cost of ASD.
However, in both regression models, the number of ASD
symptoms present was a significant predictor. In both models,
costs were increased by approximately $1,400 per ASD symptom
reported for the loose and strict criteria models. Models with fewer
covariates were also fitted yielding similar estimates for the cost of
immediate versus delayed diagnosis and the cumulative presence
of ASD symptoms.
A delay in diagnosis and treatment may have an indirect effect
on costs associated with ASD by increasing the number of
symptoms present. In order to test this hypothesis, a mediation
analysis was conducted. Firstly, it was confirmed that a delay in
diagnosis was statistically significantly associated with an increased
number of symptoms (number of increased symptoms associated
with delay = 1.56, p = 0.001, 95% CI = 0.63, 2.49). Following this,
two models were constructed and contrasted: 1) total costs were
modelled as a function of delay in diagnosis alone, with the direct
effect of diagnostic delay denoted as c, and 2) total costs were
modelled as a function of delay in diagnosis and cumulative
symptom count, with the parameter estimate for delay in diagnosis
with the effect attributable to cumulative symptom count partialled
out denoted c9. The final mediated effect was calculated by
subtracting c9 from c (i.e., mediated effect = c c9). To produce
95% CIs around the mediated effect, 10,000 bootstrapped samples
were taken and the quantiles representing 2.5% and 97.5% of the
c - c9 distribution calculated. Bootstrapping the estimate of the
mediated effect has been recommended for mediation analysis
because the technique offers acceptable statistical power
properties, directly estimates the mediated effect, and does not rely on
many of the assumptions necessary for other tests [14,15].
The mediation analysis was supportive of this hypothesis. A
statistically significant reduction in the effect associated with
diagnostic delay of $2,110 (95% CI = 820, 3700) was observed
when symptom count was included in the model. This was despite
the delay in diagnosis not being statistically significantly associated
with total cost directly (see above). The mediation analysis was
repeated with all covariates included in the original model (age of
child, number of siblings, number of siblings with ASD, combined
income, age of ASD diagnosis, and highest education of mother
and father) and a similar effect was found (mediated effect
cc9 = $1,770, 95% CI = 360, 3340).
Analysis of non-respondents
Contact was established with 267 of the 405 families who did
not return a completed questionnaire, and, of these, 148 agreed to
complete the short-form questionnaire. Sixty-four families had
already completed the long-form questionnaire. Fifty-two families
(13%) declined to participate in the phone questionnaire. Incorrect
phone numbers and no answer were the main reasons for failures
to contact. A complete breakdown of the telephone sample is
shown in Figure 1. Two of the 148 families that agreed to
participate did not have a child with ASD. From the 146 families
with children with ASD that agreed to complete the short- form
questionnaire, data were collated for 171 individual children.
As shown in Table 7, there were few noteworthy differences
between respondents and non- respondents. Demographically,
respondents were slightly more likely to have a male child and to
have noticed developmental atypicality earlier. Respondents also
received a formal diagnosis of ASD earlier than non-respondents.
Respondents reported higher treatment costs than
non-respondents. However, there were no differences in reported income loss.
ASD-related costs were strongly associated with the cumulative
presence of the childs symptoms. This builds upon previous
research that has found that having a child with ASD is associated
with significant financial strain . The association between
increased costs and ASD symptom severity suggests that effective
and early interventions that result in the reduction of expressed
symptoms may have a significant impact on improving a familys
productivity and their resultant financial situation.
Contrary to expectations, there was no statistically significant
differences in costs related to receiving the diagnosis of ASD
whether soon or late after suspicion. We suggest two possible
reasons for this. Firstly, given the above finding that increasing
symptomatology is directly related to the cost of ASD, the more
immediate identification of ASD may create a situation where
improvement in outcomes and the effect on associated
symptomatology measures dwarfs the influence of delay to diagnosis on the
final cost of ASD. This interpretation appears to be consistent with
the mediation analysis, whereby an indirect effect of diagnostic
delay on costs appeared to be mediated by an association between
increased symptomatology and increased diagnostic delay.
Secondly, families with a child with ASD may adapt their work-family
balance regardless of whether the child has a diagnosis or not. This
is reflected by the finding that the largest cost reported by parents
was a loss of income from reduced working hours. This is
consistent with a previous report stating that a loss of
approximately 14% of family income is often the consequence of having a
child with ASD , equalling $7,200 (based on the median
income and average exchange rate of 2008). The results from the
present study suggest a substantially higher (29%) loss of combined
From a family and societal perspective, support that allows
family members to work may more effectively assist families with
children with ASD by lessening the financial burden and
improving well-being of all family members. Furthermore, the
long-term consequence of high costs associated with having a child
who has a diagnosis of ASD is not well researched. A study
reporting on the distribution of societal costs of ASD distributed
throughout the lifespan estimated that fathers of children with
moderate to severe autism were unemployed 20% of a full time
equivalent , whereas 60% of mothers were unemployed and
30% worked part time of a full time equivalent . If these
estimates are indeed accurate, the family income may therefore be
severely impacted through the lifespan as a result of having a child
with ASD . The largest direct life time cost is to provide care
for adults with ASD [20,21]. Consequently, parents of adults with
ASD may face an even larger financial strain when having to
provide services for their adult children whilst having had less
opportunity to save or accumulate superannuation funds due to
reduced possibilities to work full time .
There are several limitations to the cost analysis presented here:
1) The return rate of 15% observed in the present study is quite
poor in comparison to similar studies. This may be because client
details registered with the DSC are maintained sporadically and a
number of records contained incomplete or inaccurate entries.
Furthermore, distributed questionnaires were addressed only to
the fathers of the registered child for some families due to a DSC
database error. Given reports of higher than normal divorce rates
in families with children with ASD , this may be another
reason for a lower than usual return rate reflected by the higher
than expected number of respondents reporting being in
twoparent households compared to non-respondents. 2) There are
multiple reasons why a child might not be diagnosed until later in
development, giving rise to a number of caveats with respect to the
delayed diagnostic group. For example, some of those diagnosed
later in development may present with symptomatology that is
either more complex or reduced in severity compared to those
children with evident and more severe symptoms from an early
age. However, this influence appeared to be relatively small as the
effect of the variable Age of diagnosis was not a statistically
significant contributor to cost, or may be reflected more by the
cumulative presence of ASD symptomatology measure. 3)
Requesting estimates of current costs may not be representative
of historical costs as current expenses are dependent on the childs
stage of development, time since diagnosis, and current stage of
treatment or intervention. However, one aspect for which our
estimates are robust is their specification of only ASD-related
expenses for medical, behavioural or complimentary/alternative
therapies. 4) In contrast to most parents that had reduced their
hours due to the needs of their child with ASD, a small number of
parents were seeking more work due to the expenses of having a
child with ASD. This is not often considered when calculating the
costs and productivity losses associated with a diagnosis of ASD. 5)
A number of parents reported low treatment costs because they
had exhausted all funded avenues and could not afford to
independently fund treatment for their children. 5) Lastly, the
present study does not address all aspects of how an immediate or
delayed diagnosis may impact families and their financial situation.
The processes that parents undergo in order to access a proficient
diagnosis are reported as being extremely stressful  and may
result in health related consequences difficult to estimate in any
cost benefit analysis . Consequently, health related
consequences and costs for family members and society in relation to
early/late diagnosis may warrant further scrutinising.
The median family cost of ASD was estimated to be AUD
$34,900 per annum (IQR $20,700 - $51,700; based on median
income from wages), with almost 90% of the sum ($29,200) due to
loss of income from employment. While there was no statistically
significant direct effect on the cost depending on the timeliness of
the diagnosis (immediate versus delayed) the cumulative presence
of ASD symptoms had a significant impact on the costs and a
delay in diagnosis could indirectly increase costs by neglecting
symptoms that may respond to more immediate intervention. For
each additional symptom reported, a $1,400 cost for the family per
annum was added. These findings take on a great deal of
significance when considered within a regional context as funding
amounts vary across states and countries. The financial burden of
families of children with ASD is correlated with the existing
societal financial safety net . In an Australian context, families
may miss out on the most widely available financial support for
early intervention if the diagnosis is received after the age of six
. If the family is expected to carry a substantial share of the
cost needed to support the development of children with ASD, this
may have detrimental consequences for the wellbeing of the child
Respondents (N = 521)
Categorical demographic variables are presented as proportions due to missing data in some variables.
* These variables have been collapsed across categories for the purposes of chi-square analyses.
with ASD, as well as for other family members, especially for low
income families that may not seek services at all for financial
Appendix S1 The complete questionnaire. Those
questions included in the short form are shown in italics.
Aoife McNally, Kirsty Oehlers, Mandy Richards, Geoff Cole, Susan
Peden, staff at Disabilities Services Commission, Caitlin Axford, Fiona
Choi, Helen Weldergergish, Rachel Owens, Rex Parsons, Stephen Lawrie,
Gal Rose, Tim Parkin and the AIM employment AAWA.
Authorship statement& transparency declaration
The final manuscript has been seen and approved by all authors and
they have taken due care to ensure the integrity of the work. The work is
original and has not been published elsewhere and is currently not under
consideration by another journal. All authors have had full access to the
data, analysis and writing and editing has jointly been done.
The lead author affirms that this manuscript is an honest, accurate, and
transparent account of the study being reported; that no important aspects
of the study have been omitted; and that any discrepancies from the study
as planned (and, if relevant, registered) have been explained.
Conceived and designed the experiments: CH MF MA TF. Performed the
experiments: CH MF. Analyzed the data: CH RP MA TF. Wrote the
paper: CH MF RP MA TF.
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