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210 MJA •Volume 189 Number 4 •18 August 2008
MEDICINE IN THE COMMUNITY
The Medical Journal of Australia ISSN:
0025-729X 18 August 2008 189 4 210-
214
©The Medical Journal of Australia 2008
www.mja.com.au
Medicine in the Community
rust is crucial in medical settings,1 yet
recent reports describe a decline in
trust in Western health care systems2
and international health agencies.3 Waning
medical trust in the United Kingdom perme-
ates both public and private health sectors,4
while trust decrements in the United States
reflect a privatised health industry.5 Aus-
tralia’s health care system has evolved over
time to meet growing demands, and Austra-
lians have been increasingly encouraged to
use private insurance to subsidise the esca-
lating costs of public health care.6 It is not
clear if this change has eroded public trust,
because there are few published scientific
data on Australians’ trust in their health care
providers and institutions.
The Swinburne National Technology and
Science Monitor (SNTSM)7 has for several
years assessed public perceptions of trust in
various Australian institutions, including
hospitals. Over the years, average ratings for
hospitals have varied slightly, ranging from
3.3 to 3.6 out of 5, indicating moderately
high trust. In 2007, the SNTSM assessed
trust in medical specialists and family doc-
tors. Results showed that Australians had
strong trust in their family doctors (mean,
4.1). Trust in specialists (mean, 3.8) and
hospitals (mean, 3.6) was lower, but still
fairly strong.7
To obtain a more detailed picture of Aus-
tralians’ views on their health care providers,
institutions and systems, we conducted
another national survey in 2007. In addition
to assessing trust in family doctors, special-
ists, alternative practitioners, public and pri-
vate hospitals, private health insurers and
Medicare, we also measured attitudes
towards Australia’s current health care sys-
tem and the alternatives of a more universal
taxpayer-funded public system and a more
elite, user-pays private system.
METHODS
Survey design and sampling strategy
As part of a larger survey on the use of new
technologies to promote health and prevent
illness,8 800 Australian adults participated
in a computer-assisted telephone interview
(CATI) in August 2007. The sample size was
chosen to achieve an acceptable margin of
error (3.39%) and confidence intervals of
95%, assuming a 50% split on each ques-
tion.9 Telephone numbers were randomly
selected from the electronic white pages
across all states and territories. English-
speaking residents over 18 years of age were
eligible to participate.
Ethics approval
The Swinburne University Human Research
Ethics Committee approved this study.
Survey instrument
The survey included questions about the
respondents’ level of private health cover
(none, hospital, extras, both), subjective
health status (five-point rating: 1 = unwell,
to 5 = very healthy), frequency of visits to
health professionals (weekly, monthly, 3-
monthly, 6-monthly, yearly, less), health care
industry work experience (ever, never),
demographic information, and sets of trust
and attitude ratings.
Seven single-item trust ratings were used
to assess two health systems (Medicare and
private health insurance companies), two
types of hospitals (public and private) and
three types of health care professionals (the
participant’s own family doctor or general
practitioner, medical specialists, and altern-
ative practitioners [eg, naturopaths, acu-
puncturists]). Each target was rated on a six-
point scale (0= no trust at all, to 5 = a great
deal of trust).
Seven attitude items were rated on a six-
point scale (0 = strongly disagree, to 5 =
strongly agree). One item assessed level of
support for the current health care system or
status quo (“I’m happy with the way Aus-
tralia’s current health care system is funded by a
mix of public funds and private health insur-
ance”). The other six items assessed prefer-
ences for public and private health care
systems.
The sample was compared with the gen-
eral population using Australian Bureau of
Statistics (ABS) 2006 census data for all
demographic factors except private health
cover, which was compared with 2004 ABS
data.
Statistical analysis
Psychometric analysis of attitude ratings was
conducted with LISREL, version 8.54 (Sci-
entific Software International, Chicago, Ill,
USA). Sample weighting and descriptive and
comparative analyses, including χ2 analysis,
correlations, and within- and between-
Public perceptions of Australia’s doctors,
hospitals and health care systems
Elizabeth A Hardie and Christine R Critchley
ABSTRACT
Objective: To assess public perceptions of Australia’s doctors, hospitals and health
care systems.
Design and participants: A cross-sectional national telephone survey of a random
sample of 800 Australian adults in August 2007.
Main outcome measures: Ratings of subjective trust in health care providers, public
and private hospitals, private health insurers and Medicare; attitudinal ratings for the
current health care system, and public and private health care systems.
Results: Australians reported high trust in doctors (general practitioners more than
specialists), low trust in alternative practitioners, moderate trust in hospitals (private
more than public), and greater trust in Medicare than in private health insurers. Older
adults had the greatest trust in physicians, hospitals and Medicare, but all age groups
held similar attitudes toward public and private health care systems. Support for the
current health care system with its mix of public and private funding was moderately
strong, but all respondents reported weak pro-private attitudes and very strong
pro-public attitudes.
Conclusions: Public perceptions of Australian medical professionals, institutions and
systems are generally positive. This sample did not endorse an individual user-pays
private health system, but strongly favoured a universal public health system that is
MJA 2008; 189: 210–214
collectively funded by the public purse.
T
MJA •Volume 189 Number 4 •18 August 2008 211
MEDICINE IN THE COMMUNITY
groups analysis of variance and covariance,
were conducted using SPSS, version 15
(SPSS Inc, Chicago, Ill, USA).
RESULTS
CATI response rates were calculated accord-
ing to the American Association for Public
Opinion Research definitions.10 Of 7409
phone calls, 800 interviews were completed.
Taking known (eg, refusals, under 18 years
old) and unknown (eg, no answer, phone
line disconnected) eligibility into account,
the minimum response rate was 15.5%
(maximum, 20.5%) and the cooperation
rate was 29.6% (maximum, 31.8%). The
mean interview time was 13.7 minutes (SD,
3.9 minutes).
Psychometric properties of
attitude ratings
The factor structure of the six public and
private health care attitude items was
assessed using confirmatory factor analysis. A
two-factor model yielded a good fit, and all
factor loadings were significant (χ26= 29.64;
P< 0.001; comparative fit index, 0.96;
adjusted goodness-of-fit index, 0.95; root-
mean-square error of approximation, 0.08
[90% CI, 0.05–0.10]).
The “pro-private” factor included the
items: “Australia should adopt a private, user-
pays system like they have in the US” (= 0.69),
“I would be willing to pay higher private health
insurance premiums to improve my own health
care services” (=0.30), and “The very best
health care should be available only to those
who can afford it” (=0.62).
The “pro-public” factor included the
items: “I would be willing to pay higher taxes to
improve Australia’s health care services” (=
0.86), “Australia should adopt a collective
social health system supported by higher taxes
as is done in some Scandinavian countries” (=
0.57), and “There should always be a safety
net of basic health care available to disadvan-
taged people who cannot afford to pay for it”
(= 0.16). This latter item showed a nega-
tive cross-loading on the pro-private factor
(=−0.36, P< 0.05) and the model included
one significant correlated error variance
between the two items representing a will-
ingness to pay higher taxes and higher
insurance premiums (Pearson’s r =0.29).
Two composite total scores were com-
puted from each item’s factor score regres-
sion weight (FRW). Confirmatory
congeneric measurement models11 were cal-
culated to obtain separate FRWs for pro-
private and pro-public factors. Each item
was multiplied by its FRW, then proportion-
ally summed to obtain total scores. Internal
consistency (rc) coefficients11 showed
acceptable reliability for pro-private (0.65)
and pro-public (0.95) attitudes.
Demographic data
The sample was representative of the Austral-
ian population in terms of education and
health cover, but did not match the popula-
tion distribution on age, sex or state/territory
(all χ2 comparisons, P< 0.05). Respondents’
ages ranged from 18 to 91 years (mean [SD],
53.3 [16.7] years). Using four age groupings
(18–37, 38–57, 58–77, ⭓78 years), the
sample was representative of the 38–57-
years (n= 316) and ⭓78-years (n= 55) age
groups, but younger adults (18–37 years;
n= 138) were under-represented, and older
adults (58–77 years; n=269) were over-repre-
sented. Twelve respondents refused to give
their age.
There was an imbalance by sex, with
more women (63.25%) than men (36.75%)
in the sample compared with the population
ratio. When compared with state/territory
populations, New South Wales, Victoria and
Queensland were under-represented, while
Western Australia, South Australia, Tasma-
nia, the Australian Capital Territory and the
Northern Territory were over-represented.
To account for these sampling errors, the
data were weighted according to ABS propor-
tions for age groups, sex and location for all
further analyses. The weighted sample size
was 740, but numbers vary slightly between
analyses due to missing data for some ratings.
Trust and attitude ratings
Analyses of trust and attitude ratings are
based on weighted responses. Differences
between weighted and unweighted means
were negligible (range, 0.00–0.07).
Preliminary comparisons found no signif-
icant differences in mean trust or attitude
ratings based on state/territory, sex, or
health care industry experience, with two
exceptions. Significant differences (P<0.05)
with negligible effect sizes (2<0.02) were
found for two targets based on sex, or health
care industry experience: women reported
higher trust in alternative practitioners than
did men; and respondents who had worked
in the health care industry reported less
trust in private hospitals than those who had
not (Box 1).
Apart from pro-private attitudes, and trust
in alternative practitioners in the ⭓78-years
age group, all means were well above the
scale mid-point of 2.5 (Box 2).The sample
reported high trust in their GPs and in
specialists, and moderately high trust in
private hospitals, public hospitals and Medi-
care. Moderately low trust was reported for
private health insurers and alternative prac-
titioners. Attitudes toward Australia’s cur-
rent health care system were moderately
positive; pro-public attitudes were high and
pro-private attitudes were very low.
A within-subject analysis of variance
showed that trust ratings were significantly
different across the seven types of practition-
ers and health systems (P<0.05, 2=0.22).
Contrasts showed that all medical doctors
were trusted more than alternative practition-
ers (GPs: 2= 0.46; specialists: 2= 0.34), but
there was greater trust in GPs than specialists
(2= 0.08). Medicare was trusted more than
private health insurers (2= 0.07), and pri-
vate hospitals were trusted more than public
hospitals (2= 0.11).
Within-subject comparisons of the three
attitude scores showed significant differences
(P< 0.05, 2=0.48). Contrasts revealed that
pro-public attitudes were favoured more than
the status quo (2= 0.01), but the status quo
was greatly favoured over pro-private atti-
tudes (2= 0.61). There was very strong
endorsement of pro-public over pro-private
attitudes (2= 0.62).
Age differences in trust and
attitude ratings
Significant age effects were found for trust in
all practitioners and institutions, apart from
private health insurers (Box 2). Polynomial
contrasts revealed linear effects for trust in
GPs, public hospitals, Medicare, and alter-
native health practitioners. Older Austra-
lians reported greater trust in GPs, public
hospitals and Medicare, but lower trust in
alternative health practitioners. While there
was not a significant linear effect for trust in
medical specialists, post-hoc comparisons
suggested that the older 58–77-years age
group reported greater trust in specialists
than did the 18–37-years age group.
Older age was associated with poorer self-
reported health status (Spearman’s rho [ρ]=
−0.18, P< 0.05) and more frequent health
care visits (ρ=0.10, P< 0.05), while fre-
quent health visits were associated with
greater trust in private hospitals (r=0.10,
P< 0.05). After controlling for the effects of
health status and health visits, the pattern of
age differences in trust and attitude ratings
remained. The one exception was that trust
in private hospitals did not differ by age
group when the covariates were included
(P>0.05, 2= 0.01), suggesting that older
212 MJA •Volume 189 Number 4 •18 August 2008
MEDICINE IN THE COMMUNITY
respondents’ higher trust in private hospitals
could be due to their greater need for and
use of health care.
Older and younger Australians did not
differ in attitudes to public or private health
care systems. However, there was a slight age
effect for attitudes toward the status quo (2=
0.01). Older Australians were more favour-
able towards the current system (Box 2), but
neither contrasts nor post-hoc comparisons
reached statistical significance.
Education differences in trust and
attitude ratings
Education level was not associated with
trust in health practitioners or systems,
with one exception. There was a signifi-
cant linear trend for trust in GPs, whereby
those with secondary school education
reported higher trust than did those with
advanced diplomas or university degrees
(P< 0.05, 2= 0.02) (Box 1). Similarly,
groups based on education level did not
differ in attitudes towards the current
health system or pro-public attitudes;
however, stronger pro-private attitudes
were reported by those with secondary
qualifications than the advanced diploma
group and the university-educated
(P< 0.05, 2= 0.03) (Box 1).
Private health cover differences in trust
and attitude ratings
Comparisons of those with no private
health insurance, hospital-only, extras-only
and full cover (hospital and extras) showed
that level of health cover was not associated
with trust in GPs, alternative practitioners,
public hospitals or Medicare. Differences
were found for trust in specialists (2=
0.04) and private hospitals (2= 0.07)
(Box 1). Those with hospital-only cover
reported greater trust in specialists than did
those with no private insurance. Those
with hospital-only or full cover were more
likely than those with no private insurance
to trust private hospitals. Trust in private
health insurers was highest among those
with full cover and hospital-only cover,
followed by those with extras-only and no
cover. No health cover effects were found
for pro-public attitudes or support for the
current system; however, significant differ-
ences were evident for pro-private attitudes
(2= 0.02). Those with full private cover
had stronger pro-private attitudes than
those with no private cover (Box 1).
1 Demographic details of the sample, with weighted means (SDs) for trust and attitude ratings
* Number of respondents in each demographic group in the weighted sample (N= 740). Total numbers for demographic groups differ due to missing data.
† Five health ratings were collapsed into three categories. ‡ Six frequency ratings were collapsed into three categories. ◆
Trust Attitude
No.*
General
practitioner
Medical
specialists
Alternative
practitioners
Public
hospitals
Private
hospitals Medicare
Private
insurers Status quo Pro-public Pro-private
Sex
Women 405 4.13 (1.02) 3.88 (0.88) 2.94 (1.23) 3.12 (1.20) 3.57 (0.99) 3.15 (1.22) 2.84 (1.30) 3.00 (1.41) 3.15 (1.46) 0.93 (0.93)
Men 335 4.16 (0.91) 3.79 (1.06) 2.66 (1.19) 3.25 (1.23) 3.61 (1.05) 3.29 (1.23) 2.68 (1.32) 2.92 (1.44) 3.27 (1.51) 0.96 (0.94)
Health care industry
Ever worked in 134 4.09 (1.02) 3.81 (0.92) 2.90 (1.24) 3.11 (1.24) 3.37 (1.13) 3.11 (1.14) 2.70 (1.32) 2.90 (1.46) 3.16 (1.39) 0.87 (0.89)
Never worked in 606 4.15 (0.96) 3.85 (0.98) 2.79 (1.21) 3.19 (1.21) 3.64 (0.98) 3.24 (1.25) 2.78 (1.31) 2.98 (1.42) 3.21 (1.50) 0.96 (0.95)
Education
Secondary school 352 4.27 (0.94) 3.88 (1.03) 2.79 (1.29) 3.19 (1.26) 3.64 (1.05) 3.22 (1.32) 2.74 (1.34) 2.95 (1.44) 3.17 (1.51) 1.10 (1.01)
Advanced
diploma
147 4.02 (0.96) 3.80 (0.95) 2.86 (1.22) 3.22 (1.18) 3.53 (1.02) 3.30 (1.21) 2.72 (1.38) 3.03 (1.50) 3.22 (1.44) 0.73 (0.87)
University degree 238 4.03 (1.00) 3.81 (0.87) 2.81 (1.11) 3.15 (1.16) 3.56 (0.97) 3.17 (1.10) 2.83 (1.23) 2.93 (1.37) 3.25 (1.48) 0.84 (0.82)
Private insurance
None 303 4.11 (1.06) 3.66 (1.15) 2.82 (1.23) 3.29 (1.29) 3.33 (1.12) 3.29 (1.32) 2.21 (1.32) 3.10 (1.42) 3.28 (1.45) 0.86 (0.94)
Hospital-only 85 4.29 (0.95) 4.05 (0.73) 2.54 (1.30) 3.22 (1.22) 3.79 (0.96) 3.00 (1.23) 2.88 (1.35) 2.78 (1.36) 3.26 (1.50) 0.84 (0.90)
Extras-only 30 3.85 (0.83) 3.64 (0.91) 3.06 (1.02) 3.03 (1.00) 3.41 (0.92) 3.11 (1.23) 2.58 (1.09) 2.96 (1.48) 2.97 (1.71) 1.22 (1.19)
Full cover 317 4.16 (0.89) 3.99 (0.80) 2.84 (1.20) 3.08 (1.16) 3.79 (0.89) 3.21 (1.14) 3.24 (1.11) 2.91 (1.43) 3.13 (1.49) 1.04 (0.91)
Self-reported health†
Not healthy 58 4.16 (0.98) 3.67 (1.32) 2.60 (1.16) 3.06 (1.31) 3.62 (1.22) 3.40 (1.42) 2.79 (1.47) 3.05 (1.50) 3.16 (1.75) 0.76 (0.82)
Moderately
healthy
431 4.09 (0.99) 3.81 (0.95) 2.77 (1.22) 3.13 (1.24) 3.57 (0.95) 3.18 (1.22) 2.72 (1.32) 2.93 (1.44) 3.20 (1.47) 0.95 (0.96)
Very healthy 251 4.22 (0.92) 3.93 (0.90) 2.92 (1.22) 3.30 (1.15) 3.61 (1.08) 3.24 (1.19) 2.84 (1.25) 3.01 (1.39) 3.21 (1.45) 0.98 (0.91)
Frequency of health professional visits‡
Weekly to
monthly
177 4.24 (0.93) 3.87 (0.99) 2.89 (1.25) 3.20 (1.19) 3.66 (1.09) 3.28 (1.27) 2.70 (1.36) 3.04 (1.52) 3.31 (1.49) 0.87 (0.97)
3–6-monthly 394 4.17 (0.97) 3.86 (0.96) 2.80 (1.20) 3.17 (1.23) 3.62 (0.96) 3.22 (1.26) 2.80 (1.33) 2.94 (1.40) 3.16 (1.46) 0.98 (0.91)
Yearly or less 169 3.97 (0.98) 3.75 (0.95) 2.75 (1.23) 3.17 (1.20) 3.46 (1.07) 3.13 (1.11) 2.76 (1.20) 2.95 (1.38) 3.20 (1.54) 0.94 (0.96)
MJA •Volume 189 Number 4 •18 August 2008 213
MEDICINE IN THE COMMUNITY
DISCUSSION
This sample of Australians reported fairly
high levels of trust in their health care
providers, hospitals and systems, confirm-
ing that there is a good deal of public
confidence in Australian health care.
Few studies have assessed public trust in
health care providers and systems. Two
notable exceptions are the 2007 SNTSM7
Australian survey and recent European
research comparing medical trust in the UK,
the Netherlands and Germany.12 That
research found that UK respondents had
greater trust in family doctors and specialists
than did Dutch or German respondents, but
all reported strong trust in doctors, followed
by moderately strong trust in hospitals. Our
results mirrored the European12 findings
and were consistent with the earlier
SNTSM7 findings.
In our study, respondents’ GPs were
deemed more trustworthy than specialists or
hospitals, but all medical practitioners and
hospitals were trusted more than alternative
practitioners. The sample as a whole had
fairly low trust in these non-traditional prac-
titioners, but they were trusted more by
women than men. Others have shown that
those who use alternative medicine are more
likely to be women,13-15 people who suffer
from chronic physical and psychological
conditions,14,16 and those with a positive
approach to preventive health care.13,14
We found that older age was associated
with poorer self-reported health and more
frequent health care visits, as well as
stronger trust in doctors, hospitals and
Medicare. It could be surmised that older
adults were more trusting because of their
health problems and dependence on health
care providers. However, when health status
and health visits were controlled for, age
differences remained for all trust ratings
except trust in private hospitals. This sug-
gests that older Australians’ greater need for
health services may partly account for their
greater trust in private hospitals, but did not
influence their strong trust in doctors, pub-
lic hospitals or Medicare. Unlike recent Brit-
ish research,17 which found that poorer
health was associated with less trust in the
health care system, older Australians with
health problems seemed to maintain their
trust in the public health system.
The sample had greater trust in private
compared with public hospitals, but greater
trust in public (Medicare) than private
(health insurers) systems. This may reflect
Australians’ historical support for a public
health care system,18 combined with an
awareness of the long waiting lists and
strained resources currently experienced by
Australia’s public hospitals. This pattern was
evident even for respondents with private
health cover, although they did show
slightly greater trust in the private system
than those without cover.
This Australian sample strongly endorsed
the current health system, and had fairly
weak pro-private attitudes and strong pro-
public attitudes. Individuals with full-cover
private insurance held the strongest pro-
private attitudes. Attitudes were not influ-
enced by age, but education played a role,
with the least-educated holding the strong-
est pro-private attitudes. Differences
between a positive attitude to the status quo,
strong pro-public attitudes and weak pro-
private attitudes were accompanied by par-
ticularly strong effect sizes (2>0.60).
These findings demonstrate a striking pref-
erence for public over private health care,
with the sample clearly favouring an
improved public health care system sup-
ported by the public purse. Although the
current system with its mix of public funds
and private insurance was endorsed, this
group of Australians was more likely to
favour a collective, socially responsive
health care system. A US-style user-pays
private system was clearly not supported.
It should be noted that this study and
recent European studies12,17 share a meth-
odological limitation, in that trust was meas-
ured with single-item ratings. Such
measures can be criticised because their
validity and reliability are not readily evalu-
ated.19 Nonetheless, single-item ratings are
widely used in social surveys and seem to
adequately capture general levels of trust
that can be compared across targets and
populations.7,12
This national survey confirmed that public
trust in Australian health care is quite robust.
There was strong trust in medical practition-
ers and mixed views on hospitals, with pri-
vate hospitals currently trusted over public
hospitals. Australians endorse the current
2 Weighted means (95% CIs) for trust and attitude ratings across total sample and age groups
* Trust and attitude means are listed in rank order in total sample column. N= 730 due to sample weighting and missing data. † Post-hoc Scheffé comparisons
show significant differences (P< 0.05) from 18–37-years, 38–57-years and 58–77-years age groups. ‡ Indicates a significant difference (P<0.05) from means listed above.
§ Post-hoc Scheffé comparisons show significant differences (P< 0.05) from 18–37-years age group. ¶ Indicates comparisons that neared significance (P< 0.06).
** Post-hoc Scheffé comparisons show significant differences (P< 0.05) from 38–57-years age group. ◆
Total sample (N= 730)* 18–37 years (n=228) 38–57 years (n= 292) 58–77 years (n= 168) ⭓78 years (n=42)
Tru s t
General practitioner 4.13 (4.06–4.20) 4.13 (4.01–4.25) 4.00 (3.87–4.12) 4.24 (4.11–4.38) 4.64† (4.44–4.84)
Medical specialists 3.83‡ (3.76–3.91) 3.75 (3.62–3.87) 3.78 (3.66–3.90) 4.03§ (3.90–4.16) 3.89 (3.54–4.24)
Private hospitals 3.58‡ (3.51–3.66) 3.72 (3.60–3.84) 3.44§¶ (3.31–3.57) 3.58 (3.40–3.75) 3.88**¶ (3.61–4.16)
Public hospitals 3.18‡ (3.09–3.27) 3.23 (3.08–3.38) 3.06 (2.91–3.21) 3.19 (2.99–3.39) 3.72** (3.46–3.99)
Medicare 3.20 (3.11–3.30) 3.20 (3.05–3.36) 3.08 (2.94–3.23) 3.26 (3.06–3.46) 3.83** (3.55–4.11)
Private insurers 2.76‡ (2.66–2.86) 2.68 (2.52–2.83) 2.66 (2.49–2.82) 2.98 (2.77–3.19) 3.09 (2.64–3.54)
Alternative practitioners 2.81 (2.72–2.90) 2.94 (2.79–3.09) 2.86 (2.73–3.00) 2.66 (2.45–2.87) 2.26§ (1.72–2.79)
Attitude
Pro-public 3.18 (3.07–3.29) 3.14 (2.95–3.33) 3.14 (2.96–3.33) 3.25 (3.03–3.47) 3.41 (3.00–3.82)
Status quo 2.96‡ (2.85–3.06) 3.04 (2.86–3.22) 2.75 (2.58–2.92) 3.10 (2.87–3.32) 3.34 (2.94–3.74)
Pro-private 0.94‡ (0.87–1.01) 0.97 (0.86–1.09) 0.92 (0.80–1.03) 0.85 (0.71–0.99) 1.35 (0.96–1.75)
214 MJA •Volume 189 Number 4 •18 August 2008
MEDICINE IN THE COMMUNITY
Medicare system, but overwhelmingly favour
a more socially responsive public health
system, funded by the public purse, to pro-
vide quality care for all. These findings sup-
port a mandate for a more socially equitable
health care system in Australia.
ACKNOWLEDGEMENTS
This research was supported by a Swinburne Uni-
versity Research Development Grant to Elizabeth
Hardie for a research project on social trust. The
university had no role in the study design, analysis,
interpretation or writing of this article. We would like
to thank the Australian Centre for Emerging Tech-
nologies and Society for access to the 2007 SNTSM
data. We would also like to thank Peter Groene-
wegen of the Netherlands Institute for Health Serv-
ices Research for providing us with the mean
medical trust scores for their European samples.
COMPETING INTERESTS
None identified.
AUTHOR DETAILS
Elizabeth A Hardie, BA, PhD, Senior Lecturer in
Psychology
Christine R Critchley, BA, PhD, Senior Lecturer
in Psychology
Faculty of Life and Social Sciences, Swinburne
University of Technology, Melbourne, VIC.
Correspondence: ehardie@swin.edu.au
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(Received 13 Dec 2007, accepted 20 Mar 2008) ❏
