Effects of an online stroke education program on enhancing knowledge, awareness of stroke warning signs, and emergency medical services seeking among high-risk residents in Huanggang City, China

Abstract

BACKGROUND:

Stroke is the leading cause of disability and death in china. Raising public awareness of warning signs is critical for improving access to emergency services and treatment outcomes. Prehospital delay remains a significant challenge, especially among high-risk populations. This study therefore aims to determine the effects of an online stroke education program (osp) on the knowledge, awareness of stroke warning signs, and seeking of emergency medical services (ems) among high-risk residents.

MATERIALS AND METHODS:

A randomized controlled trial was conducted from September 2024 to April 2025. One hundred and six high-risk residents were randomly allocated to intervention and control groups (n = 53 each). The intervention group received the 6-week OSP program, while the control group received regular health education. Data were collected via an interview questionnaire and analyzed using the Chi-squared test, McNemar’s test, and multivariate regression.

RESULTS:

Postintervention, the experimental group exhibited significantly higher enhancement of stroke-related knowledge, awareness of warning signs, and EMS-seeking behavior compared to the control group (P < 0.05). The intervention effects were robust, showing significant improvements in awareness (adjusted OR = 3.78, 95% CI: 1.41–8.13), knowledge (adjusted OR = 3.68, 95% CI: 1.52–8.94), and EMS seeking (adjusted OR = 3.33, 95% CI: 1.44–7.69).

CONCLUSION:

The OSP significantly improved stroke recognition and EMS-seeking intentions. This scalable model supports stroke care management by integrating digital education into primary care, effectively reducing prehospital delays. Such integration is crucial for improving clinical outcomes in acute stroke management and achieving public health targets.

Introduction

Stroke is a global health burden, ranking as the third leading cause of death. In China, it is a primary cause of mortality and disability, with 17.8 million cases and 2.3 million deaths in 2020, imposing a heavy burden on society and healthcare systems.[1,2,3] Despite advances in management, prehospital delay remains a critical barrier to timely treatment, especially for ischemic stroke patients requiring thrombolysis or endovascular therapy within a narrow window.[4,5] In China, these delays are primarily driven by poor symptom recognition, low awareness of urgency, and underutilization of emergency medical services (EMS). Improving treatment access depends on reducing this prehospital delay.[5,6] Strategies focusing on enhancing stroke knowledge and awareness and promoting EMS use can help ensure early hospital arrival and better clinical outcomes.[3,7]

Raising stroke awareness, especially the recognition of symptoms and warning signs, is vital for timely healthcare-seeking behavior.[3,6] Higher awareness correlates with better knowledge and EMS activation, enabling faster hospital arrival for acute interventions.[5,8] However, awareness levels vary significantly across populations, influenced by cultural, geographical, socioeconomic, and medical resource access.[9,10] In China, despite nationwide “Stroke 1-2-0” campaigns, stroke awareness and EMS use remain low.[3,6,9] Evidence shows only 9.9–60.7% of people recognize symptoms, just 11.5–12.0% of patients reach hospitals within the critical three-hour window, and 13.7–15.5% utilize EMS.[9,11] Critically, one-third of high-risk individuals show limited symptom recognition and no greater tendency to call EMS than their low-risk counterparts.[6,12] Therefore, targeted education focusing on warning signs and urgent EMS utilization is essential for high-risk groups.[3,6]

Stroke education effectively increases knowledge, awareness of warning signs, and EMS intent. However, improved knowledge often fails to translate to timely action, resulting in limited behavioral impact.[13,14] Creating effective interventions requires knowledge of people’s beliefs about health.[14] The health belief model (HBM) predicts behavior based on individual perceptions; specifically, people only engage with EMS when they perceive stroke as serious and believe action benefits outweigh barriers.[13,14] Applying the HBM can help reshape risk perception and emergency response.[14] WeChat serves as a crucial and scalable platform for health communication in China.[15] WeChat-based interventions have proven effective in enhancing symptom recognition and EMS utilization intent.[16,17,18] Consequently, the platform offers a feasible and sustainable medium for stroke education.[18] However, effectiveness depends on accessibility, cultural relevance, and resources; culturally sensitive design is necessary to maximize impact in resource-limited settings.[13,17,18]

In 2024, Huanggang residents showed widely varying stroke symptom recognition (34.2–82.1%), with only 55% indicating willingness to call EMS.[8] Existing traditional education—lectures and brochures—suffers from limited reach and poor continuity. While HBM-based interventions have been studied, their application in online formats for high-risk groups, particularly within the context of WeChat-based delivery in a specific geographic region (Huanggang), is under-researched.[19] This study builds on previous baseline data[8] and combines HBM, a high-risk cohort, and WeChat delivery to address gaps in stroke education and EMS utilization in a region with particular demographic and healthcare challenges. This study evaluates the ability of an HBM-based online stroke education program (OSP) to improve knowledge, warning sign awareness, and EMS-seeking behavior among high-risk residents. We hypothesize that the OSP will enhance knowledge and awareness and increase EMS utilization, ultimately reducing prehospital delay and improving stroke outcomes.

Materials and Methods

Study design and setting

A randomized controlled trial was conducted among high-risk residents of Huanggang city who sought medical advice at the stroke clinic of Huanggang Central Hospital from September 2024 to April 2025.

Study participants and sampling

Participants were residents at high risk of stroke identified by the Stroke Screening and Prevention Engineering Committee.[20] Participants were classified as high risk if they had a history of ischemic stroke or transient ischemic attack, or if they presented with three or more of the following eight specific risk factors: (1) history of hypertension (≥140/90 mmHg) or prescribed antihypertensive drugs; (2) atrial fibrillation or valvular disease; (3) smoking; (4) dyslipidemia; (5) diabetes mellitus; (6) physical inactivity (<3 times a week, <30 min each time; or workers engaged in mild manual labor); (7) body mass index (BMI) ≥26 kg/m²; (8) family history of stroke. The sample size was calculated with the formula.[21]

. Prior research[22] suggests a 28.2% difference in awareness of stroke warning signs (experimental group (p1) =57.4%; control group (p2) =29.2%). This difference was used to calculate the required sample size with a 95% confidence interval (CI), 80% statistical power, and a 15% dropout rate. With a required sample of 106 (n = 53 per group), inclusion criteria were (1) community residents in Huanggang city; (2) absence of mental health problems; (3) ability to use a smartphone and having the WeChat app installed; and (4) willingness to participate. Participants were excluded if they had serious diseases, missed more than one OSP session, or provided incomplete interview responses.

Recruitment and randomization were conducted by a researcher independent of the intervention and outcome assessments. Of the 127 participants initially assessed for eligibility, 21 were excluded (10 failed inclusion criteria, and 11 declined), leaving 106 enrolled. These participants were allocated in a 1:1 ratio to the intervention or control group (n = 53 per group) using computer-generated random numbers [Figure 1].

Figure 1.

Overview of recruitment and group assignment

Data collection tool and technique

The primary outcomes were changes in awareness of stroke warning signs and EMS-seeking behavior; stroke-related knowledge was a secondary outcome. Data were collected by trained interviewers in a private setting, using a four-part questionnaire as outlined below.

Part 1: Baseline characteristics—including age, gender, education, personal yearly income, marital status, and residential areas—coded as dichotomous variables. History of vascular risk factors (e.g., smoking, alcohol use, hypertension, diabetes, dyslipidemia, coronary heart disease, atrial fibrillation, and sleep disorders)[23] was assessed and dichotomized based on the median value (3), giving two classifications of ≥3 and <3 factors. Previous stroke history was recorded as a dichotomous variable (Y/N) captured by the question, “Have you had strokes in the past?”[23] Stroke information sources used (e.g., internet, social media, radio/television, family/friends, and health professionals)[24] were assessed via a multiple-choice question. This scale was dichotomized based on the median value (3), giving two groups of ≥3 and <3 sources.

Part 2: Stroke-related knowledge was assessed using a 17-item true/false scale to evaluate participants’ understanding of warning signs, stroke risk factors, and prevention methods.[7,25,26] Correct responses earned one point, and the total score was summed across all items. Knowledge was dichotomized, based on the study mean[26] of 8, as good (≥8) or poor (<8). The scale was evaluated by three experts in neurology and health education; the index of item objective congruence (IOC) was 0.70–1.00, and Cronbach’s alpha was 0.76, indicating good internal consistency.

Part 3: Awareness of stroke warning signs was assessed using a 5-item scale—adapted from Yang et al.[27]—to measure early stroke warning sign recognition. The scale covered symptoms including (1) sudden confusion or trouble speaking; (2) sudden blurred vision in one or both eyes; (3) sudden intense headache without apparent cause; (4) sudden vertigo, difficulty walking, or loss of balance; and (5) sudden numbness or weakness on one side of the face and/or limb. Participants could respond with “yes,” “no,” or “do not know/not sure,” with correct answers earning one point. Total scores were dichotomized by the median value (3) into good (≥3) and poor (<3) awareness. The scale was evaluated by three experts in neurology and health education; the IOC was 0.80–1.00. Cronbach’s alpha was 0.72, indicating good internal consistency.

Part 4: EMS-seeking behavior was measured by assessing participants’ intention to call EMS with the question, “What should you do if a person around you suddenly has trouble speaking, a drooping face, or numbness or weakness of the arm or leg?”[27] Five options were available—(1) transport the patient to a hospital right away; (2) call a doctor for guidance; (3) call an ambulance right away; (4) call the patient’s relatives; or (5) take medication and/or wait and watch—with the correct action being “call an ambulance right away.”[27] The scale was evaluated by three experts in neurology and health education; the IOC was 0.80–1.00.

The online stroke education program

Theoretical framework

The HBM is a health-specific social cognition model that predicts behavioral change based on personal beliefs, including perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action.[28] Individuals adapt their behaviors according to perceived risks and benefits. Applying HBM to stroke education enhances symptom awareness and recognition, thereby altering actions and promoting healthy behaviors.[14,29]

The OSP program, developed via HBM-based literature review and expert consultation, was delivered to the intervention group through six weekly 60-min WeChat sessions. Participants were randomized into five groups (10–11 per group), each facilitated by a neurological specialist. Each session followed a three-step process: (1) Independent Learning (20 mins): researchers uploaded accessible texts and videos to the WeChat group; (2) Group Discussion (25 mins): participants and researchers discussed key topics within the group; and (3) Individual Follow-up (15 mins): the following day, researchers and assistants used WeChat calls to implement the teach-back method, clarifying information, ensuring comprehension, and motivating participants to maintain engagement. Intervention materials were designed as accessible texts, audio, and videos. Table 1 provides session details.

Table 1.

Summary of the OSP

HBM constructs		Sessions		Topics		Objectives		Contents
Perceived susceptibility		1		OSP orientation and stroke risk identification		To develop the relationship between the researcher and participants, introduce the OSP program, and assist participants in identifying their own risk factors for stroke		• Developing the group relationship, introducing the OSP program • Presenting the natural history of stroke, symptoms, risk factors, and prevention strategies • Group discussion on the susceptible populations and prevention strategies • Encourages participants to assess their lifestyle and health history against identified risk factors
Perceived severity		2		Recognizing stroke severity and emergency response		To introduce the severity of stroke, its warning signs, and the appropriate emergency response		• Presenting stroke warning signs, emergency response, critical time windows for early therapy, and potential poststroke outcomes • Introducing and practicing the EMS call sequence focusing on communicating crucial details (e.g., location, stroke warning signs, time of onset) • Group discussion on poststroke outcomes, appropriate emergency response, and utilizing EMS • Encourage participants to recognize key stroke symptoms (e.g., stroke 120) and practice of immediate emergency action
Perceived benefits		3		Awareness of the benefit of stroke prevention		To introducing participants to the benefits of stroke prevention and healthy lifestyle modifications		• Introducing stroke prevention strategies and promoting a healthy lifestyle using the LE8 metrics to reduce stroke risk • Group discussion on modifying daily lifestyle and maintaining LE8 for stroke risk reduction • Encourage participants to make daily lifestyle changes to maintain LE8
Perceived barriers		4		Addressing barriers to stroke prevention and EMS seeking		To identify and mitigate barriers in stroke prevention and EMS utilization		• Identifying the barriers of stroke emergency care focuses on the “time is brain” concept and sharing problem-solving strategies • Group discussion on stroke symptom detection, timely treatment, addressing barriers to calling EMS (dialing 120), and case studies for problem-solving • Encourage participants to review stroke warning signs and build healthy habits through positive self-talk
Self-efficacy		5		Motivating to take timely emergency action		To motivate participants to recognize stroke emergencies and take appropriate action		• Motivate participants to recognize stroke symptoms and call EMS immediately if a stroke is suspected • Group discussion on participants’ experiences with stroke emergencies, seeking emergency assistance, and successful practice • Encourage participants to build confidence in their ability to recognize stroke signs and make a composed, timely call to EMS
Cues to action		6		Recognizing stroke symptom detection and healthy lifestyle		To encourage participants to recognize stroke symptoms and preventative healthy lifestyle behaviors		• Review stroke symptoms and prompt action, and promote healthy lifestyle behavior via the teach-back method • Stroke case discussion on contrasting outcomes from delayed versus immediate emergency response

LE8 metrics including healthy diet, physical activity, normal BMI, nonsmoking, sound sleep, and normal blood pressure, blood lipids, and blood glucose. BMI=Body mass index; HBM=Health belief model; EMS=Emergency medical services; LE8=Life’s Essential 8; OSP=Online stroke education program

Session 1: OSP orientation and stroke risk identification. This session introduced the OSP, built group relationships, and presented stroke symptoms, risks, and prevention. Participants were encouraged to identify personal risk factors and discuss their individual susceptibility to stroke.

Session 2: Recognizing stroke severity and emergency response. Participants were introduced to stroke warning signs, emergency protocols, treatment windows, and EMS call procedures. They were encouraged to take immediate emergency action upon recognizing key stroke symptoms.

Session 3: Awareness of the benefit of stroke prevention. This session introduced stroke prevention and healthy lifestyles based on Life’s Essential 8 (LE8) metrics. Participants were encouraged to discuss, modify, and maintain daily habits. This included diet, physical activity, sleep, stopping smoking, and managing weight, blood pressure, glucose, and lipids.

Session 4: Addressing barriers to stroke prevention and seeking EMS. This session addressed barriers to effective emergency stroke care, focusing on the “time is brain” concept and healthy lifestyle adoption. Participants discussed stroke symptom detection, timely treatment, and EMS utilization while promoting healthy habits via positive self-talk.

Session 5: Motivation to take timely emergency action. This session motivated participants to recognize stroke symptoms and call EMS immediately. Participants shared and discussed emergency experiences, assistance-seeking behaviors, and successful protocols.

Session 6: Recognizing stroke symptom detection and healthy lifestyles. Participants reviewed stroke symptoms and prevention through the teach-back method, discussing the consequences of immediate vs. delayed emergency response.

Control group

Participants in the control group did not receive any components of the OSP. Instead, they received regular health education, which included (1) health consultations with community health managers to address general health concerns, (2) stroke brochures covering risk factors and signs or symptoms, and (3) health lectures on general health topics, including hypertension and diabetes, which were provided by a health manager from the community health center. The researchers and assistants made weekly WeChat calls to clarify the study procedures and motivated participants to remain engaged.

Study procedure

After the baseline assessment, the intervention group received six weekly OSP sessions, while the control group had regular health education as described above. Outcomes were measured at three months postintervention. To prevent bias, outcome assessors and data analysts were blinded.

Ethical consideration

This study (project ID: 6809005) received ethical approval from the Ethics Committee for Research Involving Human Subjects, Mahasarakham University (Ref. No. 271-136/2024) and Huanggang Central Hospital (HGYY-KY-2023-008-1). All participants provided written informed consent after receiving the research information. Privacy was protected, and data was kept confidential.

Statistical analysis method

Descriptive statistics were used to analyze participant characteristics and outcomes. Baseline characteristics (categorical variables) were compared between the intervention and control groups using the Chi-squared test. Outcome measurements were compared between pre- and postintervention as follows: within-group comparisons used McNemar’s test, and between-group comparisons used the Chi-squared test. Intervention effects were analyzed using a multivariate regression model. All analyses were performed using SPSS version 23.0 (IBM Corp., Armonk, NY, USA), with P < 0.05 considered statistically significant.

Results

All 106 participants completed the intervention and were included in the analysis. The majority were male (57.5%), with a median age of 61 years. More than half had completed middle school or above (55.7%), resided in urban areas (52.8%), reported no previous stroke history (58.5%), and had more than three vascular risk factors (54.7%). Approximately 67.0% received stroke information from fewer than three sources. Baseline characteristics showed no significant differences between the intervention and control groups [Table 2].

Table 2.

Baseline characteristics of participants

Characteristics		Total (n=106)				Intervention n=53)				Control (n=53)				P #
		n		%		n		%		n		%
Age (year)
<61		47		44.3		24		45.3		23		43.4		0.845
≥61		59		55.7		29		54.7		30		56.6
Gender
Female		45		42.5		23		43.4		22		41.5		0.844
Male		61		57.5		30		56.6		31		58.5
Education
Primary school		47		44.3		23		43.4		24		45.3		0.845
Middle school or above		59		55.7		30		56.6		29		54.7
Personal yearly income (CNY)
<5000		23		21.7		11		20.8		12		22.6		0.814
≥5000		83		78.3		42		79.2		41		77.4
Marital status
Married		101		95.3		51		96.2		50		94.3		0.647
Others (unmarried, divorced, widowed)		5		4.7		2		3.8		3		5.7
Residential areas
Urban		56		52.8		27		50.9		29		54.7		0.697
Rural		50		47.2		26		49.1		24		45.3
Previous stroke history
No		62		58.5		30		56.6		32		60.4		0.693
Yes		44		41.5		23		43.4		21		39.6
Vascular risk factors history
<3		48		45.3		24		45.3		24		45.3		1.000
≥3		58		54.7		29		54.7		29		54.7
Sources of stroke information
<3		71		67.0		35		66.0		36		67.9		0.836
≥3		35		33.0		18		34.0		17		32.1

Values are presented as number (%); CNY, Chinese Yuan; ^#P-value for Chi-square test

Postintervention, the experimental group showed a significant increase in the proportion of participants with good awareness of stroke warning signs, stroke-related knowledge, and intention to seek EMS (all P < 0.05). No significant changes occurred in the control group. Postintervention, the experimental group had significantly higher proportions of enhanced awareness, knowledge, and willingness to seek EMS compared to the control group (all P < 0.05) [Table 3; Figure 2]. The intervention effect showed significant improvements in awareness (adjusted odds ratio (AOR) =3.78, 95% CI: 1.41–8.13), knowledge (AOR = 3.68, 95% CI: 1.52–8.94), and EMS seeking (AOR = 3.33, 95% CI: 1.44–7.69), controlling for baseline characteristics and baseline outcome values [Table 4].

Table 3.

Comparison of the outcome measurements between intervention and control groups at pre- and postintervention

Outcomes		Groups		Preintervention				Post-interventiona				P
				Number		Percentage		Number		Percentage
Good awareness of stroke warning signs (ref.: Poor)		Intervention		33		62.3		46		86.8		0.001*
		Control		31		58.5		33		62.3		0.687
		P		0.843†				0.007†*
Seeking EMS (ref.: No)		Intervention		26		49.1		40		75.5		<0.001*
		Control		23		43.4		25		47.2		0.754
		P		0.697†				0.005†*
Good stroke-related knowledge (ref.: Poor)		Intervention		28		52.8		43		81.1		<0.001*
		Control		26		49.1		28		52.8		0.727
		P		0.846†				0.004†*

Values are presented as number (%); EMS, Emergency medical services; P-value for McNemar’s test; ^†P-value for Chi-square test; ref, reference group; *Statistically significant (P<0.05); ^athree-month post intervention completion

Figure 2.

Comparison of the outcome between intervention and control groups

Table 4.

The intervention effects on outcomes at the three-month postintervention completion

Outcomes		AORb		95%CI		P
Primary outcome
Awareness of stroke warning signs		3.78		1.41–8.13		0.008*
EMS-seeking behavior		3.33		1.44–7.69		0.005*
Secondary outcome
Stroke-related knowledge		3.68		1.52–8.94		0.004*

^bMultivariate logistics regression model, ^bAdjusted for gender, age, education, personal yearly income, marital status, resident sites, sources of stroke information, vascular risk factors history, previous stroke history, and baseline outcome measures. AOR=adjusted odds ratio; CI=confidence interval. *Statistically significant (P<0.05)

Discussion

Effects of the online stroke education program on awareness of stroke warning signs

This study demonstrates that the HBM-based OSP effectively improved stroke warning sign awareness. The results support our hypothesis that OSP would significantly enhance awareness of stroke warning signs, consistent with previous research[16,30] in which HBM-guided interventions increased symptom recognition. This effectiveness stems from addressing core beliefs—perceived susceptibility, severity, benefits, barriers, cues to action, and self-efficacy—which enhance an individual’s motivation and readiness to act.[14,16,30,31] Evidence indicates that awareness increases when individuals perceive themselves or their relatives as susceptible to stroke, recognize its severity, and understand the benefits of prompt care.[30,32] Additionally, the program utilizes the “Stroke 1-2-0” mnemonic, where “1” represents an asymmetrical face, “2” denotes arm weakness, and “0” signifies slurred speech, with each sign triggering a call to 1-2-0 after spotting a potential stroke.[7] This framework empowers participants to rapidly identify warning signs and differentiate them from nonemergencies. The activity effectively heightens stroke action awareness by streamlining symptom recognition, ensuring an immediate transition from detection to calling EMS.[7,33] Accordingly, this study suggests that when individuals possess high symptom-specific awareness, they demonstrate a significantly better understanding of necessary emergency actions and the critical benefits of prompt medical care.[5,7] Moreover, group discussions on risk factors, warning signs, and prevention allowed participants to share personal risk factors and early symptom detection experiences, further enhancing symptom recognition and proactive health-positive behavior.[29,30,32] Our results suggest that HBM provides an effective framework for motivating at-risk individuals to adopt preventive behaviors. Healthcare providers should therefore prioritize educating high-risk groups on risk identification, early symptom detection, and appropriate emergency actions.

Effects of the online stroke education program on emergency medical services-seeking behavior

The HBM-based OSP significantly enhanced participants’ intention to call EMS, supporting our hypothesis that the OSP would encourage EMS-seeking behavior. This finding aligns with existing research showing that HBM-based interventions effectively predict proactive health-seeking behaviors, including EMS utilization.[30,34] The program’s effectiveness stems from its focus on perceived severity and emergency response. By facilitating discussions on warning sign detection, poststroke outcomes, and EMS protocols, the OSP enhances awareness and emergency action, which are critical for timely action.[3,6,7] Evidence shows that recognition of early stroke symptoms is crucial for timely healthcare-seeking. Enhancing the public’s ability to identify these signs improves their understanding of the situation’s urgency and increases their readiness to call EMS.[6,8,32] Our findings suggest that raising stroke awareness can contribute to improving emergency response times and optimizing patient outcomes. The program additionally highlights the “Time is Brain” concept, emphasizing early symptom recognition and prompt intervention. By highlighting timely treatment and barriers to emergency care, the program helps participants recognize the benefits of rapid therapy and provides strategies for overcoming obstacles to EMS utilization.[35,36] Evidence suggests that public recognition of stroke symptoms and the perceived benefits of early action—such as promptly calling EMS—are crucial to prompt reactions.[35,37] Individuals typically engage with EMS when they perceive stroke as a serious threat and believe the benefits of immediate action outweigh potential barriers.[35] To enhance behavioral maintenance, educational strategies should focus on positive reinforcement and highlight the expected benefits of early treatment to ultimately lead to the desired health-seeking behaviors.[35,36,37] Meanwhile, healthcare providers should design community education programs targeting symptom recognition and EMS activation to encourage immediate response and reduce prehospital delays.

Interestingly, HBM-based interventions promoting self-efficacy—an individual’s confidence to execute preventive or management actions—can effectively enhance stroke prevention and emergency response.[38,39] In this study, OSP activities motivated participants to recognize symptoms and take prompt action. By sharing experiences regarding stroke emergencies and help-seeking behaviors, participants improved both their symptom recognition and confidence in EMS engagement.[34,38] Furthermore, incorporating “cues to action” through simulated stroke scenarios helped participants build the confidence necessary for immediate responses.[34,38,39] Evidence identifies self-efficacy as a key predictor of health behavior adherence; thus, the observed enhanced confidence suggests a potential for actual behavioral change, including EMS utilization.[29,34,38] Individuals who are confident in recognizing stroke symptoms are more likely to respond appropriately, initiate EMS calls, and adhere to protocols, all critical steps in reducing prehospital delays.[36,38,39] Consequently, healthcare providers should prioritize building self-efficacy in community stroke education. This approach would bolster the competence and confidence necessary for decisive, life-saving emergency responses.

Effects of the online stroke education program on stroke-related knowledge

The HBM-based OSP significantly enhanced stroke-related knowledge, thereby supporting our hypothesis that the program would enhance participants’ understanding of stroke. This result is consistent with prior studies, suggesting that HBM-guided interventions can effectively improve participants’ knowledge of stroke risk factors, warning signs, and preventive behaviors.[34,40] This effectiveness stems from HBM’s focus on perceived susceptibility and severity. By linking chronic conditions (such as hypertension and diabetes) to severe consequences like disability, the program heightens personal risk awareness and cognitive readiness; this enhances participants’ ability to learn and recall warning signs, leading to superior knowledge retention regarding risk factors and preventive behaviors.[29,30,34,41] Delivered via WeChat, the intervention enhanced participants’ learning through accessible, engaging videos that simplified complex health concepts.[15,18] The platform’s features—anytime access, self-paced learning, and repetition—can enhance memory retention and provide ongoing reminders that improve the accessibility of culturally relevant stroke education.[6,17,18,34] Through six educational sessions, WeChat facilitated interactive and effective communication between researchers and participants. Concurrently, health information was tailored to and delivered through mediums based on participants’ preferences—including text, articles, audio, and video—to directly address their educational needs. This intervention not only enhanced participants’ knowledge, awareness, and disease management skills but also fostered understanding of their conditions, potentially leading to improved health outcomes.[17,18,34] Expert facilitation by a neurological specialist ensured accurate stroke education, significantly enhancing participant engagement and knowledge acquisition.[6,42] For those with limited health literacy, the “teach-back” method was used during follow-up calls, reinforcing comprehension and empowering participants to acquire stroke-related knowledge and adopt preventive behaviors.[43] These findings suggest that healthcare providers should leverage online platforms to implement flexible, specialist-led education to build trust and foster long-term engagement in high-risk populations.

Limitation and recommendation

Our study demonstrated that the implemented HBM-based OSP is a feasible intervention that can significantly improve stroke knowledge, awareness, and emergency response among high-risk residents. This study provides a theoretical foundation for stroke education. Health providers should integrate this OSP into community health promotion to enhance symptom recognition and timely health-seeking behaviors in this population. The OSP should be adopted as a scalable digital education tool in primary care settings to optimize stroke care management. This integration supports a reduction in prehospital delay by streamlining EMS activation, which could lead to a reduction in the burden of stroke-related disabilities.

This program represents a novel approach to health education, integrating the HBM for a high-risk group with structured delivery via WeChat. WeChat is an effective tool for stroke care management, offering a user-friendly platform for multifaceted health education via group chats. Its diverse supported formats—including text, images, and voice messages—enable convenient, self-paced learning.[17,34] WeChat enhances communication between providers and patients by offering tailored instructions and facilitating real-time interactions. It serves as a cost-effective alternative to traditional face-to-face education and is easily integrated into daily routines.[18,34] Our findings indicate that WeChat is a practical and effective approach for delivering stroke education to high-risk populations.

However, our study also had several limitations. Firstly, focusing exclusively on high-stroke-risk residents may limit the generalizability of our results, as the awareness and beliefs of this population may differ from those of the general public. Therefore, the findings should be interpreted within the context of high-risk populations. Nevertheless, enhancing public awareness improves general emergency responses;[8,12] future research should expand interventions to broader groups, including community residents and family members. Secondly, this study used WeChat to deliver the intervention; this may restrict the study’s generalizability to populations without access to such platforms. Further studies should explore the use of diverse digital platforms to enhance generalizability across different demographics. Thirdly, the sample was restricted to Huanggang, Hubei, and the results may reflect specific regional characteristics. Future studies should recruit from more diverse settings to ensure broader applicability. Fourthly, due to the nature of the OSP as an educational intervention, it was impossible to blind participants to their group allocation. The results may therefore have been impacted by social desirability bias and responses to subjective outcome measures. Blinding participants in behavioral health interventions is often impractical due to the active nature of the intervention. However, it remains feasible to blind outcome assessors and data analysts to ensure unbiased results. Meanwhile, attention control groups—offering similar time and interaction without specific educational content—can help standardize participant expectations.[44,45] This study implemented blinding for outcome assessors and data analysts to reduce potential bias. In addition, an attention control group was established, in which participants received regular health education and weekly WeChat calls to clarify procedures and sustain engagement. Fifthly, outcomes were measured only before intervention and at three months after the intervention was complete; the long-term effects were not monitored. The study focused on proximal outcomes, including stroke awareness, knowledge, and intention to seek EMS; public health targets, such as prehospital delay and clinical outcomes (e.g., thrombolysis rates or mortality) were not recorded. Future research should therefore employ longitudinal designs with extended follow-up periods to evaluate the sustained impact of the OSP. Additionally, research should incorporate real-time clinical data, such as actual prehospital arrival times and EMS arrival rates, to validate the program’s direct impact on stroke survival.

Although this study lacked a follow-up period, there were no dropouts in either the intervention or control groups. This high retention rate was likely due in part to weekly WeChat calls from the researchers and trained assistants, which helped clarify the procedures and motivated participants to remain engaged. Upon completion, all participants received a small token of appreciation ($10 USD). Evidence suggests that a WeChat-based follow-up approach could improve healthcare provider–client relationships, allowing the offering of personalized advice and enhancing user engagement.[16,17] Proactive digital engagement via WeChat, combined with modest incentives, can maintain participant commitment and prevent attrition in stroke education.

Conclusion

This study advances the HBM by integrating it with a digital OSP. Its novelty lies in leveraging WeChat to overcome traditional barriers—such as geographical constraints—providing high-risk residents with continuous, culturally tailored education. By facilitating real-time reinforcement, this intervention effectively enhanced stroke awareness, knowledge, and EMS-seeking behavior. Integrating this program into primary care could help bridge the gap between clinical education and daily routines, ultimately mitigating prehospital delays and stroke-related morbidity.

AI policy statement

The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

Abbreviations

An online stroke education program (OSP), Emergency medical services (EMS), Health belief model (HBM), Item objective congruence (IOC), Life’s Essential 8 (LE8), Chinese Yuan (CNY), Odds ratio (OR), Adjusted odds ratio (AOR), Confidence interval (CI).

Author’s contributions

WX Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review & editing. WT Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Software, Supervision, Writing–original draft, Writing–review & editing. FF Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing–original draft, Writing–review & editing, and SY Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing–original draft, Writing–review & editing.

Data availability statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Conflict of interest

There are no conflicts of interest.

Use of artificial intelligence tools declaration

The authors declare they have not used artificial intelligence tools in the creation of this article.

Funding Statement

This research project was financially supported by Mahasarakham University.