Abstract
Objective
To evaluate attitude and knowledge of stroke in a rural community in southern Thailand.
Design
A survey.
Setting
A community in southern Thailand.
Participants
All community members aged ≥18 years who were at home during the survey were invited to participate.
Primary and secondary outcome measures
Level of attitude and knowledge score towards stroke were assessed, and the associated factors were evaluated.
Methods
The questionnaire used in this survey was developed from a literature review, and the content validity and reliability were tested before use. Logistic and linear regression were used to determine factors associated with the level of attitude and knowledge score towards stroke.
Results
Among 247 participants, most were Muslim and the median age was 54.0 years. The median (Q1, Q3) score of stroke risk factors was 5 (2, 7) (full score: 9). Participants who knew about stroke, had an acquaintance diagnosed with stroke and had a high level of attitude had significantly higher scores. Two-thirds of the participants had a low-to-moderate level of attitude. Furthermore, most high-risk participants (99/113) had a low to no chance awareness of their risk to stroke. The median (Q1, Q3) score of stroke warning symptoms was 6 (3, 7) (full score: 10). The participants who had received education via the Face Arm Speech Time (FAST) campaign demonstrated a significantly higher proportion of correct answers to the symptoms mentioned in the FAST.
Conclusion
About half of the participants in this community did not know some of the risk factors and warning symptoms of stroke. Moreover, most participants had a low-to-moderate level of attitude and underestimated their risk to stroke even in the high cardiovascular risk participants. The FAST may help people memorise the typical warning symptoms of stroke.
Keywords: Stroke, EPIDEMIOLOGIC STUDIES, PUBLIC HEALTH
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study is one of few studies to evaluate stroke knowledge and attitude in a rural area.
This study used the Thai cardiovascular risk tool to categorise the participants according to their chance of having a stroke.
This study was done in only one community; therefore, the results cannot be extrapolated to other communities.
This study may have selection bias since the people surveyed were only those who stayed at home during the workdays.
Introduction
Stroke is the second-leading cause of death worldwide1 including Thailand. Moreover, stroke causes patient disability and caregiver and economic burdens. Nowadays, most hospitals have implemented the Stroke Fast Track protocol to diagnose patients as early as possible along with new treatment options in stroke. However, the mortality and morbidity rates of stroke are still high. The outcome of stroke treatment depends on the speed of receiving appropriate treatment, such as the time to receive intravenous thrombolysis or mechanical thrombectomy in ischaemic stroke.2 3 Delayed prehospital time is an important factor that influences treatment outcomes in stroke.4
Previous studies showed that various prehospital times in patients suspected of stroke were 33 min in the USA,5 39 min at two hospitals in Rochester, New York, USA,6 92–365 min in four countries in Europe and 372 min in Thailand.7 Prior knowledge towards stroke is one factor that can decrease prehospital delay in patients who had a stroke.7 The Face Arm Speech Time (FAST), which was established in 1999, is one of the widely used tools to educate people in the warning symptoms of stroke to ensure prompt management by going to a hospital as soon as possible. It can help people recognise the warning symptoms of stroke, increase the rate of thrombolytic therapy and emergency medical service8; however, it may miss 11.1%–14.1% of patients who had a stroke who do not have typical symptoms in FAST.9 10 Delayed detection of stroke symptoms was significantly associated with delayed prehospital time.4 Concerning attitude towards stroke, most populations recognise that stroke is a preventable disease that requires urgent treatment.11 However, if the severity of the disease is severe or treatment is delayed, a disability and economic burden may result.12
Previous studies on the knowledge towards stroke showed that knowledge of the risk factors and warning symptoms of stroke varies in each country.10 13–16 Factors associated with knowledge of stroke risk factors include being female, adults as opposed to the elderly, higher education and having a relative or an acquaintance who was diagnosed as stroke.11 16 17 Factors associated with high knowledge in stroke warning symptoms include being female, adults as opposed to the elderly, higher education and having underlying dyslipidaemia.13 17 18 The FAST campaign was found to increase knowledge towards stroke warning symptoms and planned response using emergency medical services; however, it did not improve knowledge on the risk factors of the disease.19 Similar to the data on attitude towards stroke, previous studies showed that the results depended on the study population.12 15 20
Few previous studies have assessed the topic of ‘knowledge and attitude towards stroke’ in Thailand, especially in people residing in rural areas. Koh Mak Subdistinct is an area with a mortality rate of stroke that is greater than the health indicator of the Ministry of Public Health of Thailand.21 In addition, most people living in this community follow Islam; therefore, having a particular religion may lead to different results. Therefore, this study was conducted in a rural community of Thailand to evaluate the attitude and knowledge towards stroke in both the risk factors and warning symptoms.
Methods
Study design
A cross-sectional survey was conducted from 16 May 2022 to 30 June 2022. The study settings were villages 6 and 8 of Koh Mak Subdistinct, Phatthalung Province, which is a rural area in southern Thailand.
Study sample and sampling
The inclusion criteria were participants aged ≥18 years old who lived in villages 6 and 8 of Koh Mak Subdistinct, Phatthalung Province for at least 6 months. The exclusion criterion was non-Thai citizens. We conducted a census in this community and used convenience sampling. All persons who met our eligibility criteria and stayed at home during the survey consented to be interviewed. The total sample size was 247 persons from the expected population in the registration data of 730 persons22 (response rate=33.8%).
Patient and public involvement
This research arose from cooperation with the stakeholders and public health volunteers to improve the health of the population in Koh Mak Subdistinct. We started with empathising health problems among public health volunteers and the surrogates to find problems that the community wanted to be solved. The results found many new cases of stroke that the population did not know how it happened and did not know the preventive measures against stroke. This concern corresponded with the official mortality rate due to stroke in this community, and the occurrence of stroke was greater than the health indicator of the Ministry of Public Health of Thailand. Therefore, this research was developed by surveying the knowledge and attitude towards stroke in the population. After the survey was completed, we used the results to create a strategy to educate the population on identifying stroke and increase the health literacy in the community by emphasising community engagement.
Variables
The dependent variables consisted of three parts. Part 1 was knowledge towards stroke risk factors that consisted of nine questions with possible answers of yes/no/unsure. Part 2 was attitude towards stroke that was modified from previous studies15 20 and consisted of two sections. The first section asked this question ‘Do you think you have a chance of having a stroke?’ The possible answers were no chance/low chance/high chance. The second section was the attitude towards stroke disease, which consisted of eight questions with 5-point Likert scale answers from strongly agree to strongly disagree. The scores were summed and categorised into three levels of attitude according to Best’s criteria.23 Part 3 was knowledge towards stroke warning symptoms that consisted of 10 questions in which 7 of the questions had the correct symptom indicated by yes/no/unsure. The independent variables consisted of sex, age, education, marital status, occupation, income, underlying disease, smoking and alcohol drinking status. In Thailand, the elderly are defined as persons ≥60 years of age. Therefore, the age cut-point in this study to define the elderly was ≥60 years old. Levels of education in this study were defined as ‘primary school and lower’ and ‘higher than primary school’ according to Thailand’s compulsory education standards. Cardiovascular (CV) risk was calculated based on the 10-year CV risk tools developed by Mahidol University, Thailand.24 The results were classified into low (10-year CV risk <10%) and high CV risk.
The questionnaire was tested for its content validity by two family physicians and one neurologist. The Item Objective Congruence Index (IOC) was calculated for each question and three questions had an IOC of less than 0.5.25 The questions were then modified based on the suggestions of a specialist and the validity of the questionnaire was tested again. The cut-off IOC for all questions was then greater than 0.5. The reliability of this instrument was assessed in terms of internal consistency measured by Cronbach’s alpha coefficients, which were 0.71, 0.90 and 0.72 for knowledge towards the risk factors, warning symptoms of stroke and attitude towards stroke, respectively. (The English-translated version of the four-part questionnaire used in this study is included in online supplemental file 1).
bmjopen-2023-080269supp001.pdf (111KB, pdf)
Data collection
All participants aged ≥18 years who stayed at home during the survey were asked to sit for an interview that included measurements of blood pressure, body weight and waist circumference. The data were recorded in Kobo Toolbox. Before collecting the data, all data collectors were trained in the meaning of each question and the correct way to perform a physical examination.
Data management and analysis
The data were exported to Excel and analysed using the R program (R Core Team 2021, Vienna, Austria). We used descriptive analysis to analyse the baseline characteristics, number of correct answers of knowledge, and level of attitude. Categorical data are presented in terms of number and percentage, and continuous data were presented in median (Q1, Q3) when normal distribution assumption was not met. The association between categorical variables was tested by the χ2 or Fisher’s exact test, while rank sum or Kruskal-Wallis test was used to test differences of continuous variables between the groups. Factors associated with the knowledge score of stroke risk factors and warning symptoms were analysed using linear regression, while logistic regression was used to analyse factors associated with the level of attitude towards stroke. Ordinal logistic regression was used to analyse factors associated with participant awareness of possibly having a stroke. We included independent variables with p values <0.2 from the univariable analysis into the initial model and used backward stepwise elimination for the final model. The multicollinearity of independent variables in the final model was tested using the variance inflation factor (VIF) method, and the results of all models had VIF values <10. Statistical significance was considered at p values<0.05.
Results
The baseline participant characteristics are shown in table 1. Two-thirds of the participants were female and the median age was 54.0 years. Nearly half of the participants were agriculturists and most were Muslim and non-drinkers of alcohol. More than half of the participants claimed to know about the disease called ‘stroke’ before participation (58.2%); however, the proportion of high CV risk participants who knew about stroke was significantly less than the low CV risk group. Approximately half of the participants were educated in a primary school and lower (52.5%). High CV risk participants were more significantly likely to be elderly, married, educated at the primary school level and lower, and had underlying hypertension or dyslipidaemia.
Table 1.
Baseline characteristics of the participants
| Characteristics | Total (N=247) |
10-year CV risk§ | P value | |
| High risk (n=113) |
Low risk (n=131) |
|||
| Sex: female | 152 (62.3) | 64 (56.6) | 88 (67.2) | 0.118* |
| Elderly: age ≥60 years old | 97 (39.8) | 87 (77) | 10 (7.6) | <0.001* |
| Marital status | 0.006* | |||
| Single/widow | 67 (27.5) | 21 (18.6) | 46 (35.1) | |
| Married | 177 (72.5) | 92 (81.4) | 85 (64.9) | |
| Religion | 0.226* | |||
| Buddhism | 45 (18.4) | 25 (22.1) | 20 (15.3) | |
| Islam | 199 (81.6) | 88 (77.9) | 111 (84.7) | |
| Education | <0.001* | |||
| Primary school and lower | 128 (52.5) | 84 (74.3) | 44 (33.6) | |
| High school education and higher | 116 (47.5) | 29 (25.7) | 87 (66.4) | |
| Occupation | 0.879* | |||
| None | 67 (27.5) | 30 (26.5) | 37 (28.2) | |
| Yes | 177 (72.5) | 83 (73.5) | 94 (71.8) | |
| Agriculturist | 103 (42.2) | 52 (46.0) | 51 (38.9) | |
| Personal business | 40 (16.4) | 15 (13.3) | 25 (19.1) | |
| Employee | 23 (9.4) | 9 (8.0) | 14 (10.7) | |
| Government official | 11 (4.5) | 7 (6.2) | 4 (3.1) | |
| Income, median (Q1, Q3) | 6000 (1225, 10 000) |
5000 (1200, 9000) |
6000 (2550, 12 000) |
0.129† |
| Having underlying disease | 91 (37.3) | 68 (60.2) | 23 (17.6) | <0.001* |
| Hypertension | 45 (18.4) | 39 (34.5) | 6 (4.6) | <0.001* |
| Dyslipidaemia | 59 (24.2) | 48 (42.5) | 11 (8.4) | <0.001* |
| Diabetes mellitus | 23 (9.4) | – | – | |
| Coronary artery disease | 11 (4.5) | – | – | |
| Old cerebrovascular accident | 5 (2.0) | – | – | |
| Current smoking | 36 (14.8) | 21 (18.6) | 15 (11.5) | 0.166* |
| Alcohol drinking | 9 (3.7) | 3 (2.7) | 6 (4.6) | 0.511‡ |
| Knowing stroke before participation¶ | 142 (58.2) | 53 (46.9) | 89 (67.9) | 0.001* |
| Having acquaintance diagnosed stroke** | 103 (42.2) | 49 (43.4) | 54 (41.2) | 0.835* |
Data are presented as n (%) unless otherwise indicated.
*χ2.
†Rank sum test.
‡Fisher’s exact test.
§Ten-year CV risk data are available for 244 patients.
¶Source of knowledge received (can answer more than 1 choice): from a close person 76 persons (53.1%), health professional 48 persons (33.6%), advertising media 42 persons (29.4%).
**Acquaintance who has been diagnosed with stroke: father/mother 21 persons (20.4%), sibling 16 persons (15.5%), couple 5 persons (4.9%), child 2 persons (1.9%), other relatives 41 persons (39.8%), friend 24 persons (23.3%).
CV, cardiovascular.
The results of the level of attitude and knowledge towards stroke are shown in table 2. The median (Q1, Q3) of the knowledge score towards stroke risk factors was 5 (2, 7) (full score: 9). Approximately 42.5% of participants knew fewer than half of the risk factors for stroke (n=105/247). More than half of the participants knew that older age (53.4%), overweight/obesity (51.8%), smoking (55.9%), hypertension (58.3%) and dyslipidaemia (59.5%) were risk factors of stroke. However, only 39.3% of the participants answered that diabetes mellitus was a risk factor of stroke. Adult participants, married status, still working, non-smokers, knowledge of stroke before participation and having an acquaintance diagnosed with stroke had significantly higher knowledge scores on stroke risk factors. Approximately two-thirds of the participants had low-to-moderate levels of attitude. Participants who were female, had knowledge of stroke before participation or had underlying dyslipidaemia had a significantly higher level of attitude compared with males who had no knowledge of stroke before participation and were not diagnosed with dyslipidaemia. The details of each question that explored attitude towards stroke are shown in table 3. Approximately three-quarters (75.7%) of the participants agreed that having a stroke would influence the family economy, and 71.7% agreed that stroke is a preventable disease. However, approximately one-third (40.9%) of the participants mistakenly believed that younger adults have no chance of having a stroke, 31.2% believed that herbal medicines could help decrease the chance of a stroke and 35.6% believed that temporarily stopping medication for the treatment of diabetes mellitus, hypertension or dyslipidaemia would not increase the chance of a stroke.
Table 2.
Levels of attitude and knowledge towards stroke according to baseline characteristics
| Characteristic | Knowledge score of stroke risk factors (full score=9) (median (Q1, Q3)) |
P value | Level of attitude towards stroke n (%) |
P value | Awareness of having a stroke n (%) |
P value | Knowledge score of stroke warning symptoms (full score=10) (median (Q1, Q3)) |
P value | |||
| Low to moderate | High | No chance | Low chance | High chance | |||||||
| Total | 5 (2, 7) | 155 (62.8) | 92 (37.2) | 115 (46.6) | 110 (44.5) | 22 (8.9) | 6 (3, 7) | ||||
| Sex | 0.115* | 0.021‡ | 0.164‡ | 0.037* | |||||||
| Male | 5 (2, 6) | 68 (72.3) | 26 (27.7) | 51 (54.3) | 36 (38.3) | 7 (7.4) | 5 (3, 7) | ||||
| Female | 5 (2, 7) | 87 (56.9) | 66 (43.1) | 64 (41.8) | 74 (48.4) | 15 (9.8) | 6 (4, 7) | ||||
| Age | 0.037* | 0.328‡ | 0.675‡ | 0.016* | |||||||
| Adult | 5 (3, 7) | 90 (60.0) | 60 (40.0) | 64 (42.7) | 75 (50.0) | 11 (7.3) | 7 (4, 7) | ||||
| Elderly: age ≥60 years | 5 (2, 6) | 65 (67.0) | 32 (33.0) | 51 (52.6) | 35 (36.1) | 11 (11.3) | 5 (3, 7) | ||||
| Education | 0.05† | 0.441‡ | 0.934‡ | 0.237† | |||||||
| Primary school and lower | 5 (2, 6) | 85 (65.4) | 45 (34.6) | 64 (49.2) | 55 (42.3) | 11 (8.5) | 6 (3, 7) | ||||
| High school education and higher | 6 (3, 7) | 70 (59.8) | 47 (40.2) | 51 (43.6) | 55 (47.0) | 11 (9.4) | 6 (4,7) | ||||
| Marital status | 0.024* | 0.182‡ | 0.161‡ | 0.005* | |||||||
| Single/widow | 4 (2, 6) | 49 (70.0) | 21 (30.0) | 76 (42.9) | 83 (46.9) | 18 (10.2) | 4.5 (3, 7) | ||||
| Married | 5 (2, 7) | 106 (59.9) | 71 (40.1) | 39 (55.7) | 27 (38.6) | 4 (5.7) | 7 (3, 7) | ||||
| Occupation | 0.034* | 0.901‡ | 0.594§ | 0.168‡ | |||||||
| Yes | 5 (2, 7) | 112 (63.3) | 65 (36.7) | 86 (48.6) | 76 (42.9) | 15 (8.5) | 6 (4, 7) | ||||
| No | 4 (2, 6) | 43 (61.4) | 27 (38.6) | 29 (41.4) | 34 (48.6) | 7 (10.0) | 5 (3, 7) | ||||
| Having underlying disease | 0.608* | 0.154‡ | 0.016‡ | 0.382* | |||||||
| Yes | 5 (2, 7) | 52 (56.5) | 40 (43.5) | 36 (39.1) | 42 (45.7) | 14 (15.2) | 6 (3, 7) | ||||
| No | 5 (2, 7) | 103 (66.5) | 52 (33.5) | 79 (51.0) | 68 (43.9) | 8 (5.2) | 6 (3.5, 7) | ||||
| Having hypertension | 0.29* | 1‡ | 0.219‡ | 0.23* | |||||||
| Yes | 5 (2, 7) | 28 (62.2) | 17 (37.8) | 20 (44.4) | 18 (40.0) | 7 (15.6) | 5 (3, 7) | ||||
| No | 5 (2, 7) | 127 (62.9) | 75 (37.1) | 95 (47.0) | 92 (45.5) | 15 (7.4) | 6 (3, 7) | ||||
| Having dyslipidaemia | 0.247* | 0.044‡ | 0.037‡ | 0.412* | |||||||
| Yes | 6 (2.5, 7) | 30 (50.8) | 29 (49.2) | 23 (39.0) | 26 (44.1) | 10 (16.9) | 7 (3, 7) | ||||
| No | 5 (2, 6.2) | 125 (66.5) | 63 (33.5) | 92 (48.9) | 84 (44.7) | 12 (6.4) | 6 (3, 7) | ||||
| Having diabetes mellitus | 0.389* | 0.673‡ | 0.076‡ | 0.865* | |||||||
| Yes | 6 (2, 7) | 13 (56.5) | 10 (43.5) | 6 (26.1) | 13 (56.5) | 4 (17.4) | 6 (3, 7) | ||||
| No | 5 (2, 7) | 142 (63.4) | 82 (36.6) | 109 (48.7) | 97 (43.3) | 18 (8.0) | 6 (3, 7) | ||||
| Having coronary artery disease | 0.609* | 0.751§ | 0.719§ | 0.034* | |||||||
| Yes | 6 (2, 7) | 8 (72.7) | 3 (27.3) | 5 (45.5) | 6 (54.5) | 0 (0) | 4 (3, 5) | ||||
| No | 5 (2, 7) | 147 (62.3) | 89 (37.7) | 110 (46.6) | 104 (44.1) | 22 (9.3) | 6 (3, 7) | ||||
| Having old cerebrovascular accident | 0.432* | 0.364§ | <0.001§ | 0.764* | |||||||
| Yes | 4 (2, 6) | 2 (40) | 3 (60) | 0 (0) | 1 (20.0) | 4 (80.0) | 7 (4, 7) | ||||
| No | 5 (2, 7) | 153 (63.2) | 89 (36.8) | 115 (47.5) | 109 (45) | 18 (7.4) | 6 (3, 7) | ||||
| Current smoker | 0.04* | 0.278‡ | 0.727‡ | 0.036* | |||||||
| Yes | 4 (2, 6) | 26 (72.2) | 10 (27.8) | 18 (50.0) | 14 (38.9) | 4 (11.1) | 5 (3, 6.2) | ||||
| No | 5 (2, 7) | 129 (61.1) | 82 (38.9) | 97 (46.0) | 96 (45.5) | 18 (8.5) | 6 (3, 7) | ||||
| Alcohol drinking | 0.841* | 0.748§ | one§ | 0.794* | |||||||
| Yes | 5.5 (2.2,6) | 7 (70.0) | 3 (30.0) | 5 (50.0) | 4 (40.0) | 1 (10.0) | 5 (3, 8) | ||||
| No | 5 (2, 7) | 148 (62.4) | 89 (37.6) | 110 (46.4) | 106 (44.7) | 21 (8.9) | 6 (3, 7) | ||||
| CV risk¶ | 0.483* | 0.277‡ | 0.212‡ | 0.024* | |||||||
| High risk (n=113) | 5 (2, 7) | 75 (66.4) | 38 (33.6) | 52 (46.0) | 47 (41.6) | 14 (12.4) | 5 (3, 7) | ||||
| Low risk (n=131) | 5 (2.5, 7) | 77 (58.8) | 54 (41.2) | 61 (46.6) | 62 (47.3) | 8 (6.1) | 6 (4, 7) | ||||
| Having acquaintance diagnosed stroke | <0.001* | 0.839‡ | 0.249‡ | <0.001* | |||||||
| Yes | 6 (5, 7) | 64 (61.5) | 40 (38.5) | 42 (40.4) | 52 (50.0) | 10 (9.6) | 7 (5.8, 8) | ||||
| No | 4 (2, 6) | 91 (63.6) | 52 (36.4) | 73 (51.0) | 58 (40.6) | 12 (8.4) | 4 (3, 7) | ||||
| Knowledge of stroke before participation | <0.001* | 0.006‡ | 0.247‡ | <0.001* | |||||||
| Yes | 6 (5, 7) | 79 (55.2) | 64 (44.8) | 62 (43.4) | 65 (45.5) | 16 (11.2) | 7 (5, 8) | ||||
| No | 2 (2, 5) | 76 (73.1) | 28 (26.9) | 53 (51.0) | 45 (43.3) | 6 (5.8) | 3 (3, 6.2) | ||||
*Rank sum test.
†Kruskal-Wallis test.
‡χ2 test.
§Fisher’s exact test.
¶High CV risk= (1) Diagnosed with diabetes mellitus, old cerebrovascular accident or coronary artery disease, (2) calculated 10-year CV risk≥10%.
CV, cardiovascular.
Table 3.
Details of answers on attitude towards stroke
| Attitude towards stroke | Answers n (%) | ||
| Agree | Neutral | Disagree | |
| Stroke is not a serious disease* | 109 (44.1) | 33 (13.4) | 105 (42.5) |
| Diagnosis of stroke has an influence on the family economy | 187 (75.7) | 31 (12.6) | 29 (11.7) |
| Younger people have no chance to be diagnosed with stroke* | 101 (40.9) | 56 (22.7) | 90 (36.4) |
| Exercise can help decrease the chance of a stroke | 182 (73.7) | 52 (21.1) | 13 (5.3) |
| Avoiding fatty, salty or sweet food can help decrease the chance of a stroke | 186 (75.3) | 47 (19.0) | 14 (5.7) |
| Stroke is a preventable disease | 177 (71.7) | 51 (20.6) | 19 (7.7) |
| Taking herbal medicine can help decrease the chance of a stroke* | 77 (31.2) | 83 (33.6) | 87 (35.2) |
| Temporarily stopping medication for treatment of diabetes mellitus, hypertension or dyslipidaemia does not increase the chance of a stroke* | 88 (35.6) | 82 (33.2) | 77 (31.2) |
*In negative questions, the appropriate answer should be disagreement.
Table 2 shows that up to 87.6% of high-risk participants (99/113) had only a low to no chance awareness of their risk to stroke. However, having underlying disease, especially dyslipidaemia or previous stroke, was significantly associated with increasing their awareness of stroke. The median (Q1, Q3) of the knowledge score for warning symptoms of stroke was 6 (3, 7) (full score: 10). Being adult, female, married, having knowledge of stroke before participation or having an acquaintance diagnosed with stroke demonstrated higher scores on the warning symptoms of stroke. On the other hand, current smokers, those previously diagnosed with coronary artery disease and participants with a high CV risk had significantly lower knowledge of the stroke warning symptoms. Table 4 shows the details of the correct answers on the warning symptoms of stroke. More than half of the participants correctly answered the questions regarding the eight stroke warning symptoms. However, 54.3% of them did not know that sudden confusion can be a warning symptom and 55.1% did not know that sudden numbness of both the hand and foot was not a warning symptom of stroke. Only 13.4% of participants (33/247) had received education via the FAST campaign. Participants who had received the FAST education had higher percentages of correct answers in symptoms mentioned in the FAST along with ‘sudden loss of vision in one or both eyes’. However, a significantly lower proportion of participants who had received the FAST education gave correct answers in the symptoms of ‘sudden trouble walking or loss of balance’ and misunderstand that ‘sudden chest pain’ and ‘sudden numbness of both hand and foot’ were warning symptoms of stroke.
Table 4.
Numbers of participants who had correct knowledge of stroke warning symptoms compared with participants who received or did not receive education according to the FAST
| Stroke warning symptoms | Total | Received education on FAST | P value* | |
| Yes (n=33) | No (n=214) | |||
| Correct answers | ||||
| Sudden trouble speaking† | 148 (59.9) | 27 (81.8) | 121 (56.5) | 0.01 |
| Sudden trouble walking or loss of balance | 143 (57.9) | 118 (55.1) | 25 (75.8) | 0.041 |
| Sudden weakness of unilateral face, arm, leg† | 141 (57.1) | 26 (78.8) | 115 (53.7) | 0.012 |
| Sudden numbness of unilateral face, arm, leg† | 140 (56.7) | 25 (75.8) | 115 (53.7) | 0.029 |
| Sudden, severe headache with unknown cause | 139 (56.3) | 22 (66.7) | 117 (54.7) | 0.269 |
| Sudden vision loss in one or both eyes | 124 (50.2) | 23 (69.7) | 101 (47.2) | 0.026 |
| Sudden confusion | 113 (45.7) | 20 (60.6) | 93 (43.5) | 0.098 |
| Incorrect answers | ||||
| Sudden chest pain | 168 (68.0) | 13 (39.4) | 155 (72.4) | <0.001 |
| Sudden muscle pain of both arm and leg | 158 (64.0) | 17 (51.5) | 141 (65.9) | 0.16 |
| Sudden numbness of both hand and foot | 111 (44.9) | 8 (24.2) | 103 (48.1) | 0.017 |
Data are presented as n (%).
*χ2.
†Warning symptoms in the FAST.
FAST, Face Arm Speech Time.
Table 5 shows the multivariable analysis of factors associated with stroke knowledge and attitude. The participants with knowledge of stroke before participation, or had an acquaintance diagnosed with stroke, or possessed a high level of attitude compared with low to moderate level had higher knowledge scores in stroke risk factors: beta=1.54 (95% CI 0.99 to 2.08), beta=0.91 (95% CI 0.37 to 1.44) and beta=1.01 (95% CI 0.52 to 1.49), respectively. The participants who had higher knowledge scores of stroke risk factors or warning symptoms had higher odds to have high levels of attitude: adjusted OR 1.24 (95% CI 1.07 to 1.44) and adjusted OR 1.17 (95% CI 1.01 to 1.37), respectively. The participants who had underlying disease or had higher knowledge scores of stroke risk factors had higher ORs of increasing awareness of having a stroke: adjusted ordinal OR 1.95 (95% CI 1.16 to 3.30) and adjusted ordinal OR 1.30 (95% CI 1.15 to 1.47), respectively. Married participants, who had knowledge of stroke, or had an acquaintance diagnosed with stroke, or who had a high level of attitude compared with low-to-moderate level, had significantly higher knowledge scores of stroke warning symptoms: beta=0.51 (95% CI 0.02 to 1.01), beta=1.42 (95% CI 0.90 to 1.94), beta=0.73 (95% CI 0.21 to 1.24) and beta=0.77 (95% CI 0.31 to 1.23), respectively.
Table 5.
Multivariable analysis of factors associated with knowledge and attitude towards stroke
| Factors | Knowledge score of stroke risk factors | Level of attitude towards stroke (high level compares with low-to-moderate level) | Awareness of being stroke | Knowledge score of stroke warning symptoms | ||||
| Beta (95% CI) | P value | Adjusted OR (95% CI) |
P value (Wald’s test) |
Adjusted ordinal OR (95% CI) |
P value | Beta (95% CI) | P value | |
| Sex: female | – | 1.65 (0.92 to 2.98) | 0.094 | – | – | |||
| Status: married | – | – | 0.51 (0.02 to 1.01) | 0.042 | ||||
| Having underlying disease | – | 1.61 (0.91 to 2.86) | 0.105 | 1.95 (1.16 to 3.30) | 0.013 | – | ||
| Knowing stroke before participation | 1.54 (0.99 to 2.08) | <0.001 | – | – | 1.42 (0.90 to 1.94) | <0.001 | ||
| Having acquaintance diagnosed with stroke | 0.91 (0.37 to 1.44) | <0.001 | – | – | 0.73 (0.21 to 1.24) | 0.006 | ||
| Knowledge scores of stroke risk factors | – | 1.24 (1.07 to 1.44) | 0.004 | 1.30 (1.15 to 1.47) | <0.001 | – | ||
| Knowledge scores of stroke warning symptoms | – | 1.17 (1.01 to 1.37) | 0.049 | – | – | |||
| Level of attitude towards stroke (high vs low moderate) |
1.01 (0.52 to 1.49) | <0.001 | – | 1.49 (0.87 to 2.55) | 0.145 | 0.77 (0.31 to 1.23) | 0.001 | |
Discussion
Only half of the participants in this rural community knew each risk factor and warning symptoms of stroke even though more than half claimed they recognised stroke as a disease. In addition, most participants had a low-to-moderate level of attitude and underestimated the risk of a stroke even in the high CV risk participants. The FAST may be effective as an education tool to improve the knowledge of the typical warning symptoms of stroke; however, it does not improve awareness, attitude or knowledge of the risk factors of stroke. Participants who had a high attitude towards stroke were significantly associated with a higher knowledge of the stroke risk factors and warning symptoms.
The baseline characteristics of the participants, in which more than half were female and adult, were the same as previous studies.11 15–17 The highlight of this community, which differed from a previous community survey, was that most participants were Muslim. The proportion of participants who knew each of the stroke risk factors was higher than a community survey in Brazil.15 16 This occurred possibly because this study used yes/no answers to the questions, while the previous study used open-ended questions. Therefore, the correct answers in this study possibly occurred by guessing; however, in our questionnaire the choice of ‘not sure’ was included to reduce this problem. Having an acquaintance diagnosed with stroke produced higher knowledge towards the stroke risk factors, which possibly was the result of learning about the risk factors from the acquaintance for application to themselves. The results of the survey showed significantly higher odds of knowledge of stroke before participation in participants who had an acquaintance diagnosed with stroke compared with participants who had no acquaintance diagnosed with stroke (OR 10.92; 95% CI 5.66 to 21.07), which was the same as a previous study in Morocco.11 Most participants had a low attitude towards stroke and most thought that stroke influenced the family economy and was preventable, which was the same as previous studies.11 15 20 21 Nearly half of the participants thought that stroke usually occurred in elderly persons, which was the same as a previous study.20 Moreover, one-third of the participants misunderstood that herbal medicines can reduce the risk of stroke, which was also the same as a previous study.20 In Thailand, herbal medicines are perceived as a science that is widely accepted, inexpensive and available. Most participants estimated a lower CV risk than the calculated 10-year CV risk prediction. Participants who had one or more underlying medical conditions had higher awareness of stroke, which was possibly the result of health education they received during follow-up of their underlying disease.
The proportion of people who gave correct answers on the knowledge of stroke warning symptoms was nearly the same as in hypertensive patients in Thailand15 but was lower than a national survey in the USA.10 14 Since the FAST is in English, it may be less effective in countries, such as Thailand, where English is not the primary language. However, we found that participants who reportedly received the FAST campaign education had significantly higher scores of knowledge of the stroke warning symptoms than those who had not received the FAST campaign education. Therefore, the FAST campaign can help people memorise the warning symptoms of stroke mentioned in the FAST, which was the same as previous studies.10 14 The interesting finding was that approximately half of the participants gave correct answers on stroke warning symptoms which are not mentioned in the FAST, especially in participants who were previously aware of the FAST campaign. This result is inconsistent with a previous study that found that symptoms related to posterior circulation stroke (PCS) were often more difficult for lay people to recognise.26 This inconsistency might be explained by the methodological differences. Our study used closed-ended questions, whereas the previous study used open-ended questions. So, the greater proportion of correct answers in this study was possibly due to guessing. Even though the FAST does not mention the symptoms of PCS, awareness of the FAST possibly improves recognition of stroke including the symptoms of PCS. The BEFAST, which adds balance and vision-related symptoms, may be considered a better health education tool because the BEFAST has better performance in improving knowledge on stroke warning symptoms related to PCS.27
This study has some strengths. First, this study is one of few studies to evaluate stroke knowledge and attitude in a rural area, especially an area that has a high mortality rate of stroke. Second, this study used the Thai CV risk tool to categorise the participants according to their chance of having a stroke. However, this study has some limitations. First, this study was done in only one community. Therefore, the results cannot be extrapolated to other communities. For example, most participants in this community adhered to Islam, which impacts certain health behaviours that include no alcohol drinking. Second, even though the population in this community cooperated well with the researchers, the collection method surveyed only people at home during the workdays. Therefore, the adults who worked during the week were not interviewed. The low response rate possibly caused selection bias; therefore, the outcomes may be different in a population with a higher response rate. For example, the baseline characteristics of population may have a higher proportion of males and adults and a lower proportion of having underling disease and lower 10-year CV risk. The knowledge score towards stroke, as the primary outcome of this study, may increase in a larger adult population that is able to retain information better with better access to medical knowledge and information from various media. However, the knowledge score and level of attitude towards stroke may be lower in younger adults since they assess themselves as having a lower chance of stroke when in fact the risk may not be low. In any case, many young people lack interest in stroke disease.
This study suggested that the FAST campaign is an effective tool in helping people memorise the typical warning symptoms of stroke, which should decrease prehospital time and improve the treatment outcomes of stroke.4 However, the FAST may miss some patients who had a stroke who present with atypical symptoms; therefore, healthcare providers should educate the public on the warning symptoms in addition to the FAST in the high CV risk population. Furthermore, healthcare providers should create an additional protocol to educate the public to increase the awareness of stroke and gain knowledge of the stroke risk factors to prevent a stroke. Moreover, each community should translate the FAST into the local language to make it easier to remember. We suggest further research in other communities and add other topics such as a planned response to a stroke to decrease prehospital delay in patients who had a stroke.
Conclusion
About half of the participants in this community did not know some of the risk factors and warning symptoms of stroke. Furthermore, most participants had a low-to-moderate level of attitude towards stroke and underestimated their risk to stroke, which included the high CV risk participants. Therefore, governments and medical agencies need to increase public awareness through FAST campaigns of the warning symptoms of stroke, and urge the public to seek prompt treatment in the event of stroke. In addition to the FAST campaigns, other public interventions need to be implemented to inform the public on the important stroke risk factors for the prevention of stroke.
Supplementary Material
Acknowledgments
We greatly appreciate the assistance of the third-year medical students for the data collection.
Footnotes
Contributors: WW, TA and NB contributed substantially to the concept and design of this article. TA and KC analysed the data. All authors interpreted the results. WW and TA contributed to drafting the manuscript. All authors approved the final version submitted for publication and took responsibility for statements made in the published article. TA is the guarantor.
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available at coresponding author up reasonable request.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants and was approved by Office of Human Research Ethics Committee (HREC), Prince of Songkla University (REC 64-167-9-2). Participants gave informed consent to participate in the study before taking part.
References
- 1.GBD . Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol 2021;20:795–820. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Prabhakaran S, Ruff I, Bernstein RA. Acute stroke intervention: a systematic review. JAMA 2015;313:1451–62. 10.1001/jama.2015.3058 [DOI] [PubMed] [Google Scholar]
- 3.Hacke W, Donnan G, Fieschi C, et al. Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials. Lancet 2004;363:768–74. 10.1016/S0140-6736(04)15692-4 [DOI] [PubMed] [Google Scholar]
- 4.Heemskerk JL, Domingo RA, Tawk RG, et al. Time is Brain: prehospital emergency medical services response times for suspected stroke and effects of prehospital interventions. Mayo Clin Proc 2021;96:1446–57. 10.1016/j.mayocp.2020.08.050 [DOI] [PubMed] [Google Scholar]
- 5.Li T, Cushman JT, Shah MN, et al. Prehospital time intervals and management of ischemic stroke patients. Am J Emerg Med 2021;42:127–31. 10.1016/j.ajem.2020.02.006 [DOI] [PubMed] [Google Scholar]
- 6.Potisopha W, Vuckovic KM, DeVon HA, et al. Decision Delay Is a Significant Contributor to Prehospital Delay for Stroke Symptoms. West J Nurs Res 2023;45:55–66. 10.1177/01939459221105827 [DOI] [PubMed] [Google Scholar]
- 7.Gordon C, Bell R, Ranta A. Impact of the national public “FAST” campaigns. N Z Med J 2019;132:48–56. [PubMed] [Google Scholar]
- 8.Aroor S, Singh R, Goldstein LB. BE-FAST (Balance, Eyes, Face, Arm, Speech, Time). Stroke 2017;48:479–81. 10.1161/STROKEAHA.116.015169 [DOI] [PubMed] [Google Scholar]
- 9.Kleindorfer DO, Miller R, Moomaw CJ, et al. Designing a message for public education regarding stroke: does FAST capture enough stroke? Stroke 2007;38:2864–8. 10.1161/STROKEAHA.107.484329 [DOI] [PubMed] [Google Scholar]
- 10.Awareness of stroke warning signs--17 states and the U.S. Virgin Islands, 2001. MMWR Morb Mortal Wkly Rep 2004;53:359–62. [PubMed] [Google Scholar]
- 11.Kharbach A, Obtel M, Achbani A, et al. Level of knowledge on stroke and associated factors: a cross-sectional study at primary health care centers in Morocco. Ann Glob Health 2020;86:83. 10.5334/aogh.2885 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tharisara C. Knowledge attitude and stroke risk behaviors among young university lecturer with risk factors. J Kasetsart Educ Rev;2021:184–200. [Google Scholar]
- 13.Centers for Disease Control and Prevention . Awareness of stroke warning symptoms --- 13 States and the District of Columbia. 2005. Available: https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5718a2.htm [PubMed]
- 14.KOMPILO N. Knowledge, attitude and risk behaviors of stroke among people with hypertension in Maeta hospital Maeta district. Lampang, [Google Scholar]
- 15.Pontes-Neto OM, Silva GS, Feitosa MR, et al. Stroke awareness in Brazil: alarming results in a community-based study. Stroke 2008;39:292–6. 10.1161/STROKEAHA.107.493908 [DOI] [PubMed] [Google Scholar]
- 16.de Mélo Silva Júnior ML, Menezes N de S, Vilanova M de S. Recognition, reaction, risk factors and adequate knowledge of stroke: a Brazilian populational survey. J Stroke Cerebrovasc Dis 2023;32:107228. 10.1016/j.jstrokecerebrovasdis.2023.107228 [DOI] [PubMed] [Google Scholar]
- 17.Blades LL, Oser CS, Dietrich DW, et al. Rural community knowledge of stroke warning signs and risk factors. Prev Chronic Dis 2005;2:A14. [PMC free article] [PubMed] [Google Scholar]
- 18.Pratt CA, Ha L, Levine SR, et al. Stroke Knowledge and Barriers to Stroke Prevention Among African Americans: Implications for Health Communication. Journal of Health Communication 2003;8:369–81. 10.1080/10810730305725 [DOI] [PubMed] [Google Scholar]
- 19.Hickey A, Mellon L, Williams D, et al. Does stroke health promotion increase awareness of appropriate behavioural response? Impact of the face, arm, speech and time (FAST) campaign on population knowledge of stroke risk factors, warning signs and emergency response. Eur Stroke J 2018;3:117–25. 10.1177/2396987317753453 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Roongprasert K. The production of motion Graphics to knowledge and attitudes toward stroke prevention. Bangkok, Rajamangala University of Technology, 2018 [Google Scholar]
- 21.Health Data . Mortality rate from cerebrovascular disease. 2023. Available: https://plg.hdc.moph.go.th/hdc/reports/report.php?&cat_id=6a1fdf282fd28180eed7d1cfe0155e11&id=9bf46fa15f85178a05b665ae986bd467
- 22.Sukthawee S, Boongerd S. Java Health Center Information System. JHCIS Dis Control J 2017;43:96–110. Available: https://he01.tci-thaijo.org/index.php/DCJ/article/view/149499 [Google Scholar]
- 23.Best JW. Research in education. 3rd ed. Englewood Cliffs, NJ: Prentice-Hall, 1977: 403. [Google Scholar]
- 24.Mahidol University . Thai CV risk score. 2023. Available: https://www.rama.mahidol.ac.th/cardio_vascular_risk/thai_cv_risk_score/
- 25.Ongiem A, Vichitvejpaisal P. Validation of the Tests. Thai J Anesthesiol 2018;44:36–42. [Google Scholar]
- 26.de Mélo Silva Júnior ML, Oliveira AGC, Gois WM, et al. Different words for stroke: the same concept? an analysis of associated symptoms and intended reaction in Brazil. BMC Neurol 2023;23:273. 10.1186/s12883-023-03327-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Chen X, Zhao X, Xu F, et al. A systematic review and meta-analysis comparing FAST and BEFAST in acute stroke patients. Front Neurol 2021;12:765069. 10.3389/fneur.2021.765069 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
bmjopen-2023-080269supp001.pdf (111KB, pdf)
Data Availability Statement
Data are available at coresponding author up reasonable request.