Trust in health care: an information perspective

Lars Höglund, Elena Macevičiūtė and T.D. Wilson

Swedish School for Library and Information
Science, University College, 501 90 Borås
Sweden

E-mail: lars.hoglund; elena.maceviciute; tom.wilson@hb.se



This article reports on an exploratory analysis of existing data obtained through a national survey carried out in Sweden. The survey questionnaire seeks information on a wide range of issues, including health care, library use and Internet use. The analysis presented here explores the relationship among these variables and the concept of trust in health care institutions. The results indicate that most of the correlations theoretically suggested were very small and that trust in health institutions in general is high but not strongly related to standard demographic variables found in a general survey of a large population. This exploratory study suggests that more specific indicators of health, experience from health institutions and health-related media exposure are needed to test, in greater depth, the relationships between information exposure, health and attitudes towards health institutions.

Introduction

Large-scale surveys of the general public are not uncommon in the developed world (for example, there are the British Household Panel Survey, the Polish General Social Survey, and the various Eurobarometer surveys in the European Union) and surveys of public health are relatively abundant (for example, the Medical Expenditure Panel Survey in the USA, the Commonwealth Fund 2001 International Health Policy Survey, and the National Survey on Health and Medical Care in France). However, it is rather uncommon for either of these kinds of surveys to include questions relating to access to and use of information services of any kind.

This article draws upon the national survey of the Swedish population, which has been implemented annually since 1986 by the SOM Institute of the University of Gothenburg. This survey includes questions proposed by various research organizations about politics, society, use of media, public service, the environment, risks, new media technology and people's leisure activities.

We have chosen to explore, in this article, as far as the data allow, the relationship between trust in health care in Sweden and a variety of demographic and informational variables.

Background

Public trust in health care

The issue of trust in health care institutions has become of critical importance as governments seek to justify expenditure on health care and as providers of health care and health insurance companies (particularly in countries with lower levels of public expenditure on health) seek to justify their charges [1]. Straten et al. [2] note that:

Public trust in health care could be defined as being confident that you will be adequately treated when you are in need of health care.

Straten et al. draw attention to Blendon's contention [3] that public trust in health care in America had declined in the 20 years prior to the publication of his article, and that this was the result of institutional changes in health care.

More recently, Orr [4] notes:

Recent evidence suggests that patients and physicians too often perceive the current health care system to be unfair or illegitimate because of the ways in which coverage decisions appear to be made. This perceived unfairness is disrupting trust in the health care system. Developing a framework that would promote trust in health care organizations by fostering and demonstrating fairness in coverage decisions would provide value to all participants in the health care system.

Trust is taken to be important because of its relation to other aspects of behaviour in relation to health. For example, there is a presumed relationship between trust and future behaviour, in that persons who do not have trust in the system may seek alternative therapies or have lower compliance with the therapies recommended by health care institutions [5]. How trust is composed, however, has at times been taken for granted, while other researchers have sought to identify the elements of which it is composed and some researchers have identified links to various aspects of information. Gray [5], for example, suggests that, with a decline in trust, patients will ask for a second opinion, and seek to identify the 'best physicians' or the 'best hospitals' - all of which require information for their satisfaction. Mechanic [6] identifies 'management of confidential information' and 'openness in providing and receiving information' as two of five dimensions of trust.

Straten et al. [2] carried out both qualitative and quantitative research towards the creation of an instrument to measure the dimensions of public trust in health care. One of the initial six factors, identified by analysis of interview data, was 'information supply and communication by care providers'. This dimension also appeared in the follow-up quantitative analysis, using factor analysis: it provided explanation for only a very small percentage of the variance (3.7 per cent) but nevertheless was a clearly identifiable factor which correlated significantly with the other factors, as well as with variables such as negative or positive experience of healthcare by the persons involved.

Hagström [7] explores among other topics the information media (namely, press) influence on healthcare and institutional policy. The study reflects to some extent the complex interaction between media and decision-makers' behaviour. It also suggests that public opinion and the general attitude of citizens towards health and medical care problems as formed by information sources are significant factors in these relationships. In Sweden, other studies have been conducted relating information provision to the health behaviour of different population groups [8, 9].

Although the study reported here cannot deal with the relationship between trust and these specific information variables, we believe there is sufficient evidence of an association to allow us to examine more general aspects of information behaviour, to discover whether variables such as library use and Internet access, in general, may be related to experience of healthcare and trust in healthcare institutions.

Demographic characteristics and health information behaviour

The literature relating to health information behaviour reveals a number of associations with demographic characteristics. Connell and Crawford [10] found that the amount of health information received by urban residents from all sources declined with age, but that older rural women received a great deal of information from a variety of sources and that the amount declined only slightly with age. Older men received far less information than younger men. On the other hand, MacHaffie [11] suggests that persons with severe and persistent mental illness living in more rural areas with fewer resources are likely to experience less exposure to health promotion information from all sources. Research has also shown that men were more likely to perceive lack of knowledge as a barrier to seeking preventive healthcare in the rural Appalachian region of the USA, whereas older and less educated persons were more likely to identify cost as a barrier [12].

Slevin et al. [13], in a study of a national cancer information service (BACUP), found that use of the service was mainly (80 per cent) by women (although men are marginally more at risk), both in the 30-49 years age group (52 per cent of enquirers) and in those over 60 years of age (17 per cent of enquirers). More than 85 per cent of enquirers were in non-manual occupations and 97 per cent were white (1.2 per cent came from the Indian subcontinent, compared with 3.6 per cent in the population as a whole). The authors commented that 'lower social classes make much less use of community health and preventive services', although again there is a slightly higher incidence of cancer in the lower socio-economic groups.

Connell and Crawford [10] found women reported receiving more health information than men from all sources and attributed this to women's traditional role as caregivers and 'lay healthcare providers'.

The use of the Internet by various groups has also become a subject of research in recent years and various relationships with some demographic variables have been found. Gordon et al. [14] in a survey of patients attending a rheumatology clinic found that 43 per cent had access to the Internet (27 per cent at home) and that 27 per cent had searched for medical information. Age was shown to be a factor: those who searched for information had a median age of 48, while those who did not had a median age of 62. The patients in this study were predominantly female, but studies of Internet use in general (at least in the UK) suggest that it is now as likely to be used by women as by men [15].

US surveys also show that health information on the Internet is an age-related activity [16]. More children (65 percent of those aged 10-13) and teenagers (75 percent of those aged 14-17) use the Internet than other age groups. But health information seekers tend to be ages 30-64 [17]. The latter survey of Americans also shows that finding health information on the Internet affects how people manage their health. Almost half (48 percent) of users who have gone online for health information say it improved the way they take care of themselves.

The research company Datamonitor [18] surveyed over 4500 adults in France, Germany, Italy, Spain, the UK and the US, and found that 57 percent of respondents had consulted Internet sources when looking for health information. This compares with 76 percent who consulted their physician, 73 percent who looked for information via television, books and magazines, and 53 percent who sought advice from family and friends. The study indicates that between 32 and 34 percent of adults aged 18 to 54 went online to look for health information during the past 12 months. However, that number falls to 27 percent for adults in the 55-64 age group and to 14 percent for those aged 65 and over. Datamonitor's research shows that general health sites and sites run by governments or institutions are considered more credible than those run by pharmaceutical firms, because they are seen to be more objective.

Harris Interactive [19] has been tracking the people who search information on health topics ('cyberchondriacs') in the US, France, Germany and Japan for 4 years. Their number has doubled during this time (54 million in 1998, 110 million in 2002). The survey summarizes the types of websites visited by cyberchondriacs (Table 1). Most people say that they look for information on their own, but rely on it only if their doctor confirms the quality (60 per cent in the US and 47 per cent in Japan). Another group tends to judge the information without consulting doctors (37 per cent in Japan, 46 per cent in Germany). Only in some cases (particularly in Japan) do people look for information only if their doctor tells them to do this.

Table 1 Websites visited by 'cyberchondriacs' [19]
Web site categoryUS France Germany Japan
% % % %
Medical journals 45 45 33 27
Commercial health pages 44 52 40 32
Academic or research institutions 43 50 50 33
Pharmaceutical companies 34 18 27 23
Medical societies 34 2145 35
Patient support or advocacy group for specific diseases 29 30 42 46
News media 29 28 40 33
Government sites 25 29 24 34
Hospitals 16 21 14 36
Individual doctors 11 10 15 25

A Swedish survey in East Götland found that higher credibility is attributed to health information from healthcare staff and family than to the same information on the net [20]. The Riks-SOM survey includes questions relating to many of the factors discussed here, including the main demographic factors, and there is the potential, therefore, to explore the data from the perspective of both information use and health factors.

Research framework

The possible relationships between the variables of interest to us, that is, health status, contact with health institutions, library use, Internet use, and trust in health institutions, are numerous. Consequently, a theoretical model is needed to guide our analysis. Our initial model of the relationships among these variables is shown in Figure 1. The model suggests the following theoretical propositions:

fig1

P1 Health status will be related to demographic variables such as age, sex and occupation. Thus, elderly people are more likely than young persons to have a lower health status, and manual workers more likely than professional workers.

P2 Contact with healthcare institutions will be related to both health status and demographic factors. Thus, persons in good health are unlikely to seek contact with healthcare institutions, and demographic variables such as age, occupation and rural or urban dwelling are likely to have an impact. Men are also less likely to visit general practitioners, for example, than are women.

P3 The informational variables are likely to be affected by both health status and demographic variables and, in turn, are likely to have an impact on contact with healthcare institutions and on trust in healthcare institutions, in that those who show most use of information resources are likely to have higher trust in health institutions.

Given the general nature of the data available, it is not possible for us to identify information use (i.e., library use and Internet use) specifically for the purposes of seeking health information, since this use was not specifically identified in the Riks-SOM survey. However, it is possible to identify general associations that may be explored through more detailed questioning in relation to healthcare in future surveys.

Methodology

Riks-SOM, as noted earlier, incorporates questions proposed (and paid for) by a variety of research organizations. This article, therefore, draws upon questions that have been proposed for a variety of reasons. However, questions on library and information use were proposed by the senior author, and these are related to questions proposed by others. In totality, therefore, the survey was not designed specifically to test the model, but is a post facto analysis of available data.

The survey is mailed by the Institute to a randomly selected sample of 6,000 persons between the ages of 15 and 85. In 2001 the response rate was 60.63 per cent, giving data on 3,638 persons.

The questions on library and information use used in the analysis were:

  1. How often in the past 12 months have you visited the library?
  2. How often do you do the following in the library: . . . use a computer to look for information on the Internet?
  3. Do you have Internet access (at home, at work, or elsewhere)?
  4. Do you, or does anyone in your household, subscribe to any daily newspaper?

The questions on healthcare used in the study were:

  1. How large is your trust in the way the following institutions do their work?
  2. How large is your trust in the staff within the following institutions?
  3. Estimate your present health condition from 1 (my worst possible health condition) to 10 (my best possible).
  4. How is your current health condition compared with the situation 12 month ago?

Finally, the demographic characteristics used were: age, sex, educational level attained, residence in rural or urban area, and family income.

Results

Demographics

The survey is highly representative of the Swedish population: 49.5 per cent of the respondents were male, and 50.5 per cent were female. This is very close to the official population figures in December 2002, which gave values of 49.52 per cent for men and 50.48 per cent for women [21].

The age distribution of the respondents is close to that of the population at large, but slightly under-represents the age groups 15-39 and 75-85 and over-represents the group 40-75 (Table 2).

Table 2 Age distributions of Swedish population and Riks-SOM respondents
Swedish populationSOM respondents
Age groupNo.%Age groupNo.%
15-19532,2267.4415-192346.44
20-24517,0047.2320-242015.53
25-29568,7487.9525-292577.07
30-391,276,52917.8430-3958916.20
40-491,172,82416.3940-4961516.91
50-591,249,95817.4750-5974320.43
60-751,285,29017.9660-7573720.27
76-85552,8977.7376-852607.15
Totals7,155,476100.00 3,636100.00

The sex and age distributions of the Riks-SOM respondents, therefore, can give us confidence that the survey data closely represent the Swedish population in general.

Health status

Health status was measured on a scale from 1 (poor) to 11 (excellent). The results (Figure 2) show a generally high level of health.

fig2

Health status was redefined as low (1-5), medium (6-8) and high (9-11) and a modest but highly significant correlation between perceived health and age was found (Table 3).

Table 3 Health status 1-3 . ålder4 cross-tabulation
Health status  Ålder4 age groupsTotal
15-3031-6061-85
1 Count 91 260 134 485
% within Ålder4 12.6 13.8 15.1 13.9
2 Count 205 576 345 1126
% within Ålder4 28.4 30.5 38.9 32.2
3 Count 426 1052 408 1886
% within Ålder4 59.0 55.7 46.0 53.9
Total Count 722 1888 887 3497
% within Ålder4 100.0 100.0 100.0 100.0

Trust in healthcare

Trust in health institutions was measured on a five-point scale (very strong trust to very weak trust) and the results showed a generally high level of trust, with 58.4 per cent choosing the top two trust levels, compared with only 15.6 per cent choosing the bottom two levels. The results are shown in Figure 3.

fig3

As can be seen from Table 4, the differences in trust related to contact with healthcare institutions as well as to different social and demographic variables seem to be small. In fact all the variables tested showed a very small impact on trust in health institutions and a somewhat greater impact for trust in staff.

Table 4 Trust in healthcare and selected variables: % with high trust (n = 3382)
% with high trust in staff% with high trust in health institutions
Contact with health care institutions: no 68 (709) 58 (744)
Contact with health care institutions: yes 73 (2673) 60 (2642)
Household income: 1 (low) 71 (251) 59 (252)
    2 69 (568) 60 (573)
    3 67 (670) 56 (671)
    4 73 (620) 62 (628)
    5 76 (485) 62 (487)
    6 73 (270) 57 (271)
    7 (high) 82 (128) 68 (128)
Education: 1 (low) 69 (1551) 57 (1553)
    2 71 (777) 59 (794)
    3 (high) 76 (977) 65 (984)

Media exposure might affect trust, but in this case the more general indicators showed small correlations with trust. This was also tested in a series of regression analyses: the results are shown in Table 5.

Table 5 Summary of exploratory regression analysis
Dependent variable: trust in healthcare institutions, stepwise regression
Variables entered ΣR ΣR2 Adj.R2 Beta Sig.
1 Trust in staff 0.700 0.490 0.489 0.701 0.000
2 Age 0.701 0.492 0.491 0.043 0.000
Excluded (all other variables): Internet availability, education, subscription to daily newspaper, library visits, contact with health care, present health condition, household income and sex.
Dependent variable: trust in staff within health institutions, stepwise regression
Variables entered ΣR ΣR2 Adj.R2 Beta Sig.
1 Subscription to daily newspaper 0.146 0.021 0.021 0.144 0.000
2 Present health condition 0.202 0.041 0.040 0.130 0.000
3 Sex 0.052 0.049 0.046 0.093 0.001
4 Education 0.231 0.053 0.050 0.069 0.011

Discussion and conclusions

The results do not support the proposed theoretical model. Nor do they seem to support some earlier findings from more limited populations in other countries. There may be several reasons for this. First of all, trust in health service institutions in Sweden is high at this very general level. Among a number of institutions studied for a number of years, healthcare is normally at the top, along with the universities, the police, the King, and radio and TV. During the 1990s the trend has been somewhat downwards, indicating a general decrease in trust for social institutions. Some theories of trust suggest that trustworthiness, quality, interest and perceived importance together with values and opinions should explain the level of trust for a specific institution [22]. It does not appear to be possible to trace the complex relationships between different media, their content and the consequences for individual opinion with these survey data. However, long-term changes in opinion can be related to media, but this is normally very difficult to show. Many years of research and debate about the effects of violence in various media illustrate this point.

A further conclusion relates to the need for caution in accepting the results of smallscale research as representative of populations in general - a point to which we have already alluded. There is today a fashion for qualitative research in many fields, not excepting the healthcare arena, and the largely self-selected groups of persons studied are very unlikely to represent the generality of the population. Where the results of such research are used to guide public policy, therefore, the results may be other than expected. Where public resources are to be used to bring about changes in healthcare, it is important that the research should represent the population at large as well as can be obtained with current social survey methods. Collaboration with large-scale surveys may be more appropriate than totally independent but small-scale studies - no matter how much insight into individual problems is obtained.

Research that does not confirm a proposed theoretical model frequently goes unpublished. In this case the study results imply that further research and more specific indicators should be used before the model can be more firmly rejected. However, in spite of this, the study has shown that existing databanks can be used for explorative research and model testing to a much larger degree than is normally undertaken. The general quality and the methodological possibilities with large surveys are normally good. In this case the survey was not intended to be used for this kind of health-related research. It is suggested that more and better health indicators should be added in the forthcoming annual Riks-SOM surveys, as well as more appropriate indicators relating to information and media use for health-related purposes. We hope to be in a position to influence this situation for the next survey.

Notes

1 The questions on trust in institutions are part of research by Holmberg and Weibull, who are also the editors of the main report from the 2001 Riks-SOM survey [22].

References

  1. Anders G. Health against Wealth: HMOs and the Breakdown of Medical Trust. New York: Houghton Mifflin, 1996.
  2. Straten G F M, Friele R D, Groenewegen P P. Public trust in Dutch health care. Social Science & Medicine 2002; 55; 227-34.
  3. Blendon R. The public's view of the future of health care. Journal of the American Medical Association 1988; 259; 3587-93.
  4. Orr A S. Consensus towards trust: improving fairness in health care coverage decisions. Abstract of a paper presented at the 130th Annual Meeting of APHA, Philadelphia, 2002. In Proceedings 9-13. November 2002. http://apha.confex.com, March 2003.
  5. Gray B. Trust and trustworthy care in the managed care era. Health Affairs 1997; 16; 34-49.
  6. Mechanic D. Changing medical organization and the erosion of trust. The Milbank Quarterly 1996; 74 (2); 171-89.
  7. Hagström B. Svensk sjukvård i och under press: pressens raportering om svensk hälso- och sjukvård. Lund: Studentlitteratur, 2002.
  8. Jarlbro G, Jönsson A, Windamt S. Aids Ett drama i flera akter: en innehållsanalys av svensk press. Lund: Studentlitteratur, 1992.
  9. Persson E, Sandstrom B, Jarlbro G. Sources of information, experiences and opinions on sexuality, contraception and STD protection among young Swedish students. Advances in Contraception 1992; 8 (1); 41-49.
  10. Connell C M, Crawford C O. How people obtain their health information: a survey in two Pennsylvania counties. Public Health Reports 1988; 103; 189-95.
  11. MacHaffie S. Health promotion information: sources and significance for those with serious and persistent mental illness. Archives of Psychiatric Nursing 2002; 16 (6); 263-74.
  12. Elnicki D M, Morris D K, Shockcor W T. Patient-perceived barriers to preventive health-care among indigent, rural Appalachian patients. Archives of Internal Medicine 1995; 155 (4); 421-4.
  13. Slevin M L, Terry Y, Hallett N, Jefferies S, Launder S, Plant R, Wax H, McElwain T. BACUP: the first two years. Evaluation of a national cancer information service. British Medical Journal 1988; 297; 669-72.
  14. Gordon M M, Capell, H A, Madhok R. The use of the Internet as a resource for health information among patients attending a rheumatology clinic. Rheumatology 2002; 41 (12); 1402-5.
  15. Eysenbach G, Sa E, Diepgen T. Shopping around the Internet today and tomorrow: towards the millennium of cybermedicine. British Medical Journal 1999; 319; 1294.
  16. US National Telecommunications and Information Administration. A nation online: how Americans are expanding their use of the Internet. 2002. http://www.ntia.doc.gov, March 2002.
  17. Fox S, Rainie L, Horrigan J, Lenhart A, Spooner T, Burke M, Lewis O, Carter C. The online health care revolution: how the web helps Americans take better care of themselves. Pew Internet & American Life Project, 2000. http://www.pewinternet.org, March 2003.
  18. Datamonitor. Growth in numbers seeking health info online. NUA surveys, 2002. http://www.nua.com, March 2002.
  19. Harris Interactive. Four-nations survey shows widespread but different levels of Internet use for health purposes. Health Care News 2002; 2 (11). http://www.harrisinteractive.com, March 2003.
  20. Garbenby P, Husberg M. Stort intresse för mer hälsoinformation. Läkartidningen 2001; 23; 2814-2816.
  21. Statistika centralbyrån. Swedish population on 31 December 2002. Stockholm, 2003. http://www.scb.se/statistik, March 2003.
  22. Holmberg S, Weibull L. Det våras för politiken. Trettiotvå artiklar om politik, medier och samhälle: SOM-undersökningen 2001. SOM-rapport no. 30, 2002. Göteborg: SOM-institutet, Goteborg universitet.

This paper was presented at the iSHIMR meeting, Borås, Sweden in 2003. It is scheduled for publication in Health Informatics Journal.


How to cite this paper

Hölund, L., Macevičiūtė, E. & Wilson, T.D. Trust in health care: an information perspective. Health Informatics Journal, 10(1), 2004. 37-48 [Available at http://informationr.net/tdw/publ/papers/2003iSHIMR.html]


counter
Web Counter

Valid XHTML 1.0!