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| Journal of the New Zealand Medical Association,
21-January-2011, Vol 124 No 1328
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Choice of the channels for delivery of health information to
the public is a critical decision that faces agencies interested in improving
the health status of a population. Trust in different sources of information and
media through which the information is disseminated can be a major factor in
determining the effectiveness of any health
promotion.1,2
Research in recent years has focused on the use of the
Internet3 as a health information
source4 (HIS) and its acceptability as a medium
of communication.4–6 However, relatively
little attention has been paid to the wide variety of other sources individuals
can draw upon for information. Instead, research reinforces how the Internet is
preferred in use7 as a HIS but that it is not
highly trusted.8
Findings also are mixed regarding whether increased
frequency of use changes this.9,10 It is
recognised however, that trust toward a HIS can improve adherence to medical
advice provided.11 Therefore, it is important
to gain a comprehensive understanding of how people trust the wide variety of
sources that are used to deliver health information. In this paper we examine
the expressed trust that people have in a range of 24 different sources and
types of media. In terms of overall approach this research complements that
undertaken in the US by the Health Information National Trends Survey (HINTS).
HINTS focuses on how personal characteristics influence perceived information
needs and examines the consequent effects for choosing appropriate information
channels for health information.12
‘Trust’ is taken to mean the “message
received is true and reliable and that the communicator demonstrates competence
and honesty in conveying accurate objective, and complete
information”.13 Previous studies
demonstrate trust toward information sources influences both
usage14 and frequency of
searching.9 Research on trust in sources for
health information has also produced interesting links to personal
characteristics such as education, ethnicity and sex which can then be used to
assist in the selection of different media and potentially increase the
effectiveness of health communications.7
A key way in which this study differs from previous research
on trust in health information is the range of sources investigated. Firstly, we
have a comprehensive list of different types of health professionals, including
physiotherapists, nurses and alternative sources such as homeopaths.
Additionally our range includes different types of institutional sources,
including Government agencies and some charities, as well as media types and
friends and family. Many of these are consistently omitted from studies on
health information.7,15,16
MethodsThe data reported in this paper were collected during a
replication of the Maibach et al. American Healthstyles
study16 adapted for and conducted in New
Zealand and funded by Sport and Recreation New Zealand (SPARC) and the Cancer
Society.17 The questionnaire covered
comprehensive information regarding health status and beliefs as well as a data
on physical activity and fruit and vegetable intake. Measures of trust were
replicated from the Maibach survey with appropriate updates and adjustments for
the local context.
A total of 24 relevant sources and media were included
in the survey (see Table 2) and respondents were asked to indicate their level
of trust toward each source with respect to obtaining health information. This
level of trust was measured on a five point scale ranging from don’t
trust at all (1) through to trust a lot (5). While this approach
to measurement obviously cannot capture the variation that lies within any
particular category, for example a patient is likely to trust one doctor within
their general group practice more than another, it is still clear that people do
hold overall attitudes to different types of information sources and that
measurement at this global level allows the comparisons across the wide
assortment of sources and media that is intended in this paper.
The survey was mailed to a sample of New Zealanders
drawn from the electoral roll, achieving a 61% response rate and yielding a
total of 8,291 respondents for analysis. Those identifying themselves as
Māori were ‘oversampled’ by 26% in order to compensate for the
normally lower response rate from this group. Specifically, individuals were
required to self report themselves as Māori or of Māori descent to be
eligible for the Māori electoral roll, which was then used as a sampling
frame for this group.
A summary of the main demographic characteristics of
the sample is given in Table 1 which shows more female respondents than would be
expected. The categories for other variables in the table have been collapsed
for reporting purposes and are presented to show the main features of the
sample. Respondents were allowed to nominate more than one ethnic grouping, an
option chosen by 4.7% of the sample. People choosing more than one ethnicity
were removed from the analysis for comparisons on this variable. Different
Pacific Island groups (Cook Islands, Niuean, Samoan and Tongan) were recorded
separately in the survey but were subsequently amalgamated to one group as no
differences were identified between them in analysis on the trust ratings.
Table 1. Characteristics of study
participants
Exploratory factor analysis, using principal axis factoring
and direct oblimin rotation, was conducted on the trust ratings for the 24
different HISs in order to identify underlying patterns in the ratings of
different information sources. Polychoric correlations estimated in LISREL were
used as inputs for the factor analysis and all other analysis was conducted
using PASW v18.0 software. Summary variables were generated to represent the
factors by computing an average score for all the variables that loaded with an
absolute value greater than 0.6. A multivariate general linear model was used to
compare these trust variables across categories of age, gender, education,
income, ethnic background and occupational status.
ResultsBefore exploring the results of the factor analysis it is
useful to briefly consider the median trust ratings and ranges for each of the
information sources (see Table 2). Medians are reported as opposed to means
because four of the rating scales deviate significantly from a normal
distribution.
Table 2: Median trust scores for each health
information source
Range = 1–5:
“don’t trust at all” (1) to “trust a lot” (5); n =
6,541. SPARC: Sports and Recreation New Zealand.
Overall the pattern of responses for these average trust
scores looks reasonable and consistent with expectations from previous research.
For example, similar to the HINTS survey,12
personal professional sources, in particular the person’s own general
practitioner, but also their nurse and trained dieticians are seen as very
trustworthy sources of health information.
The three other HIS that are rated especially highly are the
three major national charities that were included in the list: The Heart
Foundation, Cancer Society and Diabetes New Zealand. Amongst these the rating
for the Heart Foundation is significantly higher than the other two. This is
possibly a reflection of its high public profile and the repeated exposure that
it achieves through schemes like the product endorsements that it offers to
‘healthy foods’. The Heart Foundation mark of approval is a
recognized symbol on many food products and offers continuous reinforcement of
its name as a supplier of health-related information.
While the remaining sources all have a median of 3, the mean
scores suggest that they fall into three broad groups. The highest rated of
these three is a mixed range of sources including official public health bodies,
professional in health-related occupations including pharmacists and
gym/personal trainers. Friends and family are rated next and the lowest set of
ratings are those offered to the mass media sources, though the idea of books
and journals contains more credibility with the sample than do the other
sources.
Table 3 gives the main results of the exploratory factor
analysis. For ease of interpretation only loadings above 0.4 are displayed. Five
factors had an eigenvalue of over 1 with a sixth factor having an eigenvalue of
.989. The scree plot showed a marked drop after that with the next eigenvalue at
.667. The 5-factor solution essentially combined Factors 3 and 4 in table 3 but
the resulting factor was also highly correlated (.645) with Factor 2, with many
sources cross-loading. The 6-factor solution presented below is much more
interpretable with more face validity.
Parallel analysis was also conducted following the procedure
published by O’Connor.18 This also
produced an ambiguous result with the sixth factor failing to meet the
equivalence criteria by 0.06. Ideally future work in this area would test both
five and six factor structures on a different sample using confirmatory factor
analysis. In total the factors explained 77.6% of the variance. The lowest
communality for any single variable was 0.408 (trust in naturopaths).
The distribution of factor loadings in Table 3 has
considerable face validity. There are a few items that cross-load between
factors, especially three and five, but most sources only load on one factor and
those (such as dieticians and SPARC) which are more distributed are
understandable. Factor 1 was identified as grouping mass media together as
sources for health information.
The variables that load most heavily on Factor 2 are the
three major New Zealand health charities that were included in the list. SPARC
and Regional sports trusts also contribute to this factor. These are the two
organisations that cross into more than one factor which would seem appropriate
since, while they have overlaps with charities and other official bodies they
also fall outside the official ‘health industry’ sources. Both can
act as a source of funding to support local community physical activity
initiatives.
Factor 3 is plainly related to official health sources and,
apart from the small cross-loading by pharmacists on this factor all the other
contributing variables are official health bodies who could contact people
outside a normal primary care situation. Conversely Factor 4 is centred on the
primary personal professional health contacts experienced by most people:
doctors and doctor’s nurses. Pharmacists, and local hospitals also
contribute to this factor.
Table 3. Rotated factor loadings from the
exploratory factor analysis
Factor 5 is linked to alternative or
‘non-medical’ personal HISs and the final factor constitutes family
and friends as an independent grouping. Thus the factor analysis suggests that,
in terms of trust, the New Zealand public perceive six major groupings of
sources for health information.
In Table 4 below we report associations between these trust
factors and a number of demographic characteristics. All the results reported
below are statistically significant at p ≤0.001 though, based on partial
eta squared, effect sizes would all be regarded as small.
Table 4: Variations in trust factors by
demographics
The variations across demographics reveal some interesting
patterns though immediate explanations for all the relationships are not
obvious. Why females exhibit more trust than males is not absolutely understood
although it has been recorded in other contexts such as the internet and trust
games in experimental economics20,21. The links
with work status are the weakest of all those examined and possibly the least
useful from a policy perspective. A possible explanation for lower trust in
alternative health professionals by those identifying themselves as sick or
invalid may simply be lower levels of contact with some of these sources –
for example sports organisations and gym trainers.
The two sources that retired people rate more highly than
other work status groups are both personal sources as opposed to other the
factors that contain at least some impersonal items. The associations with age,
income and education all follow the same pattern with media and alternative
sources being less trusted as all three increase. Intuitively this seems
sensible and as would be expected. Ethnicity is rather more complex. Two of the
groupings in the survey are composite
groups—‘British/European’ and ‘other Asian’ but
both still show some significant variations across the factors. Overall the
biggest differences are found between the different Asian groups and the rest of
the sample.
While these groups still trust personal health professionals
such as doctors and nurses more than other sources for HIS they do express more
trust in the media and alternative health professionals. Arguably the latter may
be a feature of a wider view of medicine that is sometimes attributed to Asian
countries. An interesting finding is the difference in trust accorded to friends
and family.
In New Zealand recognition and involvement of whānau
(extended family) has been a significant issue in relation to Māori in
recent years. Our data suggest that this is not just a feature of Māori but
more a difference between those of European heritage and all other ethnic
groupings. It is possible that the latter groupings reflect cultures that pay
more attention to the extended family and are less individualistic in their
value systems than European, especially Anglo-Saxon, cultures.
ConclusionsThe purpose of this paper is to investigate how the source
of information used to about health might affect the trust that people have in
the information. As such it differs from most of the work in trust and health
information that manipulates an individual message and identifies the effects
and interactions of the different message components. Trust was assessed by
single statements that asked people to judge sources at a general level. While
this approach does not capture variation that exists within any of the
categories—for example some radio programs on science may be more trusted
than information coming from a radio talkback show—it does allow for
comparisons across a wide variety of media types and the results of the factor
analysis suggest that the data is capturing systematic variations in a reliable
way.
While some cross-loading is evident, the factor solution is
quite clear and each factor has a distinctive set of sources. Not surprisingly,
health professionals with whom people have personal contact are the most trusted
sources across the whole spectrum. But clearly not all information can be
delivered through these channels.
For many of the population their contact with these health
professionals is sporadic and usually motivated by some specific need which may
be far removed from an information message that policy makers or higher level
planners want to put across to the population. Therefore it becomes important to
understand the mix of media that might be required in order to effectively
communicate trustworthy health information and it is clear that the optimum mix
varies across the population. Choice of channels could well be as important as
the message itself.
Competing interests: None.
Author information: Rob Lawson, Professor,
Department of Marketing, School of Business, University of Otago, Dunedin; Sarah
Forbes, PhD Candidate, Department of Marketing, School of Business, University
of Otago, Dunedin; John Williams, Lecturer, Department of Marketing, School of
Business, University of Otago, Dunedin
Correspondence: Professor Rob Lawson,
Department of Marketing, School of Business, University of Otago, PO Box 56,
Dunedin, New Zealand. Email: rob.lawson@otago.ac.nz
References:
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