Stroke is the second most common cause of death worldwide and a significant cause of chronic disability (Murray and Lopez 1997
). In a study conducted in Australia, it has been reported that within 12 months of a stroke, approximately 37% will die and 10% will experience a recurrent stroke (Thrift et al 2000
; Dewey et al 2001
). Of those who survive their stroke, approximately 51% are disabled in some activity of daily living, and 50% exhibit either cognitive impairment or dementia (Sturm et al 2002
; Srikanth et al 2004
). This represents a considerable burden to our community.
Despite the decline in mortality from stroke over recent years (Waters and Bennet 1995
), there is a looming epidemic of stroke. The increased proportion of the population in the older age groups that is predicted to occur in future years will contribute to this epidemic because of the strong association between age and stroke incidence. Using age- and sex-specific stroke attack rates obtained in a recent population-based study in Melbourne, Australia, and applying them to the Australian population (Thrift et al 2000
), it is estimated that approximately 42 200 strokes would have occurred during 1997. If we apply these same attack rates to the projected population of Australia 20 years later (2017) (Australian Bureau of Statistics 2003
), it is estimated that approximately 67 500 strokes will occur in that year. This resulting rise in the number of stroke cases in the elderly will significantly increase the burden of this disease and is also likely to overwhelm the resources currently available for stroke care.
There are two main ways in which we can reduce the burden of this disease. First, we can improve outcome after stroke by providing patients with proven therapies. These therapies include the use of intravenous tissue plasminogen activator (tPA) within 3 hours of ischemic stroke onset (Hacke et al 1999
; Wardlaw et al 2003
), aspirin within 48 hours (Chen et al 2000
), and treatment in a stroke care unit (Stroke Unit Trialists' Collaboration 2004
). For the first of these therapies, patients need to attend hospital within approximately 2 hours of stroke onset. Currently, only about 1%–2% of patients receive this treatment (Birbeck et al 2004
). The most common reasons that patients are not treated with tPA are that they do not attend hospital within the treatment time window (Kleindorfer et al 2004
), that there are insufficient trained staff, and that patients are ineligible for treatment. Although the proportion receiving therapy could be improved by increasing the number of centers in which this therapy could be administered, reducing the delay to hospitalization would also considerably improve access to this therapy.
The second way in which we can reduce the burden of stroke is to reduce the number of people experiencing a stroke. This could be undertaken by implementing good primary and secondary prevention measures at an individual and population level. The individual (or high-risk) approach involves identifying high-risk people and altering their risk factor profile by either reducing risky behaviors or introducing treatments. The population (or mass) approach involves either mass screening or education campaigns to reduce risky behaviors at the population level.
To reduce delays to hospitalization following stroke and to improve risk factor profiles of the population requires knowledge about stroke and its risk factors. In view of the importance of understanding the level of community awareness of stroke, we undertook a review of the literature in this area.
The aim of this review is to compile the findings of a number of groups that have investigated levels of knowledge of stroke signs, symptoms, and risk factors. Drawing these results together will provide readers with some insight into different communities' understanding of stroke, and thereby highlight areas where improvements can be made with targeted campaigns.
provides a summary of the publications discussed in this review. As can be seen from this table, there is a mix of both open-ended and closed-ended types of approaches to studying stroke knowledge. Although open-ended survey questions provide the researcher with the most “open and honest” assessment of the respondent's knowledge, the results are often difficult to compile and analyze. For the results of an open-ended survey to be reported, it is often necessary for the researcher to make a decision as to what the intention of a subject's response was and to group responses into similar categories. Because this coding process involves judgment decisions, it is always possible that the results may be biased by this decision process. Rowe et al (2001)
attempted to address this issue by coding responses using two individuals, and where a discrepancy was found, a third party was used to resolve the issue.
When knowledge of stroke symptoms is assessed using closed-ended questions, a different type of response is evoked, as the act of asking the question provides the respondent with some indication of what the answer could be. In the two studies in this review where respondents are asked to identify stroke symptoms from a provided list (Yoon et al 2001a
; Greenlund et al 2003
), there is a tendency for all suggested
symptoms of stroke (including those that are definitely not
stroke symptoms) to be identified as actual
symptoms – this may be a reflection of some of the inherent difficulties in using closed-ended questions. Positive responses identifying a particular stroke symptom appear to be more prevalent when using closed-ended rather than open-ended questions. For example, Rowe et al (2001)
utilized both approaches: for closed-ended questions, between 77% and 95% of respondents correctly identified different symptoms of stroke, while for open-ended questions, these values were between 7% and 24%.
In seven of the studies, telephone contact was used as the method of survey administration. Although this method is definitely more efficient and cost-effective than face-toface interviews, there is a small degree of selection bias whereby people without a telephone are excluded from the study, although this effect is likely to be small as these studies were all performed in areas where telephone access would be very high. For example, Pancioli et al (1998)
noted that 96% of all households in their survey area had reported having a telephone service. In one study, nonrespondents included a group that were not interviewed due to a communication barrier (Rowe et al 2001
). It is possible that this process may have reduced the generalizability of results, as people from non-English-speaking backgrounds and those with speech difficulties may have been excluded from the study group.
Sample size is an important issue in any study, particularly in population-based research, where large numbers of respondents are needed to provide adequate power. The largest study among the group reviewed here is that of Greenlund et al (2003)
, in which more than 61 000 individuals were surveyed across the USA. Although this study is extremely large, the response rate was relatively low – a median value of 53% was stated. Three of the studies in this review were conducted using very small (<200) samples (Kothari et al 1997
; Hux et al 2000
; Weltermann et al 2000
), and the results of these studies would therefore need to be interpreted with caution.
Ideally, response rates for community-based surveys should be 80% or more. When responses fall below this level, it is possible that those subjects who did not
respond to the survey may have been substantially different from those who did, thereby adversely affecting the result. Only two of the studies reviewed here had response rates greater than 80% (Kothari et al 1997
; Weltermann et al 2000
), while the remainder varied from 70% to as low as 45%.