Dataset Information

Stroke literacy in Central Harlem: a high-risk stroke population.

ABSTRACT:

Background

Awareness of stroke warning symptoms and risk factors (stroke literacy), as well as knowledge of available treatment options, may be poor in high-risk populations. We sought to evaluate stroke literacy among residents of Central Harlem, a predominantly African American population, in a cross-sectional study.

Methods

Ten community-based sites in Central Harlem were identified between 2005 and 2006 for administration of a stroke knowledge survey. Trained volunteers administered in-person closed-ended questionnaires focused on stroke symptoms and risk factors.

Results

A total of 1,023 respondents completed the survey. African Americans comprised 65.7% (n = 672) of the survey cohort. The brain was correctly identified as the site where a stroke occurs by 53.7% of respondents, whereas the heart was incorrectly identified by 20.8%. Chest pain was identified as a symptom of stroke by 39.7%. In multivariable analyses, African Americans (odds ratio [OR] 2.20, 95% confidence interval [CI] 1.09-4.45) and Hispanics (OR 5.27, 95% CI 2.46-11.30) were less likely to identify the brain as the damaged organ in stroke. Hispanics were more likely to incorrectly identify chest pain as a stroke symptom, compared with whites (OR 3.40, 95% CI 1.49-7.77). No associations were found between calling 911 and race/ethnicity and stroke knowledge, although women were more likely than men to call 911 (OR 0.50, 95% CI 0.30-0.80).

Conclusion

Significant deficiencies in stroke literacy exist in this high-risk population, especially when compared with national means. Culturally tailored and sustainable educational campaigns should be tested in high-risk populations as part of stroke public health initiatives.

SUBMITTER: Willey JZ

PROVIDER: S-EPMC2790229 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Stroke literacy in Central Harlem: a high-risk stroke population.

Willey Joshua Z JZ Williams Olajide O Boden-Albala Bernadette B

Neurology 20091104 23

<h4>Background</h4>Awareness of stroke warning symptoms and risk factors (stroke literacy), as well as knowledge of available treatment options, may be poor in high-risk populations. We sought to evaluate stroke literacy among residents of Central Harlem, a predominantly African American population, in a cross-sectional study.<h4>Methods</h4>Ten community-based sites in Central Harlem were identified between 2005 and 2006 for administration of a stroke knowledge survey. Trained volunteers admini ...[more]

PMID: 19890071

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Project description:IntroductionElectronic health (eHealth) strategies are evolving making it important to have valid scales to assess eHealth and health literacy. Item response theory methods, such as the Rasch measurement model, are increasingly used for the psychometric evaluation of scales. This paper aims to examine the internal construct validity of an eHealth and health literacy scale using Rasch analysis in a population with moderate to high cardiovascular disease risk.MethodsThe first 397 participants of the CONNECT study completed the electronic health Literacy Scale (eHEALS) and the Health Literacy Questionnaire (HLQ). Overall Rasch model fit as well as five key psychometric properties were analysed: unidimensionality, response thresholds, targeting, differential item functioning and internal consistency.ResultsThe eHEALS had good overall model fit (?2 = 54.8, p = 0.06), ordered response thresholds, reasonable targeting and good internal consistency (person separation index (PSI) 0.90). It did, however, appear to measure two constructs of eHealth literacy. The HLQ subscales (except subscale 5) did not fit the Rasch model (?2: 18.18-60.60, p: 0.00-0.58) and had suboptimal targeting for most subscales. Subscales 6 to 9 displayed disordered thresholds indicating participants had difficulty distinguishing between response options. All subscales did, nonetheless, demonstrate moderate to good internal consistency (PSI: 0.62-0.82).ConclusionRasch analyses demonstrated that the eHEALS has good measures of internal construct validity although it appears to capture different aspects of eHealth literacy (e.g. using eHealth and understanding eHealth). Whilst further studies are required to confirm this finding, it may be necessary for these constructs of the eHEALS to be scored separately. The nine HLQ subscales were shown to measure a single construct of health literacy. However, participants' scores may not represent their actual level of ability, as distinction between response categories was unclear for the last four subscales. Reducing the response categories of these subscales may improve the ability of the HLQ to distinguish between different levels of health literacy.

Project description:BACKGROUND:Several models have been developed to predict asymptomatic carotid stenosis (ACS), however these models did not pay much attention to people with lower level of stenosis (<50% or carotid plaques, especially instable carotid plaques) who might benefit from early interventions. Here, we developed a new model to predict unstable carotid plaques through systematic screening in population with high risk of stroke. METHODS:Community residents who participated the China National Stroke Screening and Prevention Project (CNSSPP) were screened for their stroke risks. A total of 2841 individuals with high risk of stroke were enrolled in this study, 266 (9.4%) of them were found unstable carotid plaques. A total of 19 risk factors were included in this study. Subjects were randomly distributed into Derivation Set group or Validation Set group. According to their carotid ultrasonography records, subjects in derivation set group were further categorized into unstable plaque group or stable plaque group. RESULTS:174 cases and 1720 cases from Derivation Set group were categorized into unstable plaque group and stable plaque group respectively. The independent risk factors for carotid unstable plaque were: male (OR 1.966, 95%CI 1.406-2.749), older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;?70, OR 31.267, 95%CI 7.472-130.83), married(OR 1.780, 95%CI 1.186-2.672), LDL-C(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was generated, ranging from 0 to 10. The cut-off value of this predictive scoring system is 6.5. The AUC value for derivation and validation set group were 0.738 and 0.737 respectively. CONCLUSIONS:For those individuals with high risk of stroke, we developed a new model which could identify those who have a higher chance to have unstable carotid plaques. When an individual's predictive model score exceeds 6.5, the probability of having carotid unstable plaques is high, and carotid ultrasonography should be conducted accordingly. This model could be helpful in the primary prevention of stroke.

Dataset Information

Stroke literacy in Central Harlem: a high-risk stroke population.

Background

Methods

Results

Conclusion

Publications

Stroke literacy in Central Harlem: a high-risk stroke population.

Similar Datasets

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