Gender, Social Networks, and Stroke Preparedness in the Stroke Warning Information and Faster Treatment Study

Factors affecting stroke pre-hospital delay behavioral intention among community residents: A path analysis

BACKGROUND

Pre-hospital delay is the major cause of stroke treatment delay, and behavioral intention is considered to be the most direct predictor of behavior. Therefore, to effectively reduce stroke pre-hospital delay, it is essential to further understand the relationship between stroke pre-hospital delay intention (SPDBI) and its social-psychological influencing factors, namely personality traits, social support and coping style.

AIM

This study aims at examining the relationships among personality traits, coping style, social support, and SPDBI.

METHODS

A cross-sectional, self-administered questionnaire was distributed to 845 residents. The content of the questionnaire included demographic information, the knowledge of "Stroke 120", Ten-Item Personality Inventory-Chinese version, Simplified Coping Style Questionnaire, Perceived Social Support Scale and SPDBI Scale. Path analysis was used to investigate the relationship among SPDBI and its psychosocial influencing factors.

RESULTS

The final path model showed a good fit to the data (χ2/df = 2.981, RMSEA = 0.048, GFI = 0.936, CFI = 0.941). Extroversion (β = 0.106), positive coping (β = -0.110), negative coping (β = 0.150) and the knowledge of "Stroke 120" (β = -0.152) had only direct effects on SPDBI. While agreeableness (β = 0.113), openness (β = -0.121) and social support (β = -0.118) had direct effects on SPDBI, they also had indirect effects (β = -0.009; -0.022; -0.049) on SPDBI though positive coping.

CONCLUSIONS

Adequate social support and positive coping of health threat may reduce residents' SPDBI. Meanwhile, the interventions to reduce SPDBI should take personality differences into consideration.

Transfer behaviors in stroke and dementia development associated with environmental risks

AIM

Chronic diseases are influential components of stroke, one of the dominant reasons for dementia and premature mortality. Environmental risks are risk factors for transitioning from stroke to dementia. This study addresses the transition behaviors in stroke and dementia development associated with chronic diseases and environmental risks.

METHODS

This study is an integrated survey of medical and environmental informatics concerning stroke patients' quality of life. A total of 10 627 stroke patients diagnosed in Taiwan were surveyed in this study. A covariate model and subgroup analysis were used to evaluate the influence of chronic diseases and environmental risk factors (i.e., divorce rate, unemployment rate, solitariness rate, temperature, and air pollution rate) on stroke and the corresponding dementia transition behaviors.

RESULTS

This study constructed a total of 98 covariate analysis models, consisting of 14 transition types [10 transitions from chronic diseases to stroke (5 metabolic risk states × 2 stroke states) and 4 transitions from stroke to dementia (2 stroke states × 2 dementia states)] by 7 covariates (i.e., sex, age, divorce rate, unemployment rate, temperature, air pollution, and solitariness rate). Among the 98 transitions, 26 were statistically significant.

CONCLUSIONS

Sex, age, divorce rate, unemployment rate, temperature, and air pollution rate exerted a partially significant influence on the transition from chronic diseases to stroke. Sex, age, unemployment rate, and temperature partially influenced the transition from stroke to dementia. This study also considered high-risk sub-populations of stroke patients, particularly males aged 65 years and below. Geriatr Gerontol Int 2024; 24: 766-772.

Decision Delay Is a Significant Contributor to Prehospital Delay for Stroke Symptoms

Prehospital delay after stroke symptom onset is a primary barrier to eligibility for reperfusion therapies. Decision delay is an understudied contributor to prehospital delay. We aimed to explore decision delay as a component of prehospital delay. For this correlational study, 170 Thai acute stroke patients were interviewed to explore their treatment-seeking decision factors: prior stroke knowledge, onset context, and cognitive, emotional, and behavioral factors. Participants' mean age was 61.2 years, and 46% were women. Median decision delay and prehospital delay times were 120 and 372 minutes. Decision delay represented 49% of prehospital delays. Factors shortening decision delay were atrial fibrillation, prior stroke knowledge, perceived cause of symptoms as stroke, perceived severity of symptoms, and advice from bystanders to seek treatment. In contrast, seeking support from others and self-treatment affected prolonged decision delay. Shortening decision delay, often under the patient or bystander control, can reduce overall prehospital delay.

Factors influencing alertness to premonitory symptoms in stroke patients with pre-hospital delay

OBJECTIVE

The purpose was to explore the alertness of premonitory symptoms in stroke patients with prehospital delay, and to analyze the influencing factors.

DESIGN AND SAMPLE

A cross-sectional study using the convenience sampling method was conducted in the neurology department of a general hospital between November 2018 and July 2019. A total of 352 stroke patients were participated in the survey.

MEASURES

A hierarchical multiple regression was performed to analyze the factors related to the alertness of premonitory symptoms (0-9 scores) in stroke patients with prehospital delay.

RESULTS

The alertness score was 6.53 ± 2.377. The lowest score of 0.55 ± 0.498 was for "Continuous yawning occurs continuously despite no tiredness or lack of sleep is okay, and need not be treated." The hierarchical regression results revealed that symptom onset, symptom change before admission, knowledge, social support were the influencing factors delaying the alertness of premonitory symptoms. Knowledge and support from friends could improve the alertness, while support from family and other support had a notable negative impact.

CONCLUSIONS

Stroke patients need to be more alert toward premonitory symptoms. This alertness is related to stroke knowledge and social support. Nurses should formulate interventions and advise stroke patients to improve their stroke knowledge and expand their social network.

Call Characteristics of Patients Suspected of Transient Ischemic Attack (TIA) or Stroke During Out-of-Hours Service: A Comparison Between Men and Women

Background: In the Netherlands, a digital decision support system for telephone triage at out-of-hours services in primary care (OHS-PC) is used. Differences in help-seeking behavior between men and women when transient ischemic attack (TIA) or stroke is suspected could potentially affect telephone triage and allocation of urgency.

Aim: To assess patient and call characteristics and allocated urgencies between women and men who contacted OHS-PC with suspected TIA/stroke.

Methods: A cross-sectional study of 1,266 telephone triage recordings of subjects with suspected neurological symptoms calling the OHS-PC between 2014 and 2016. The allocated urgencies were derived from the electronic medical records of the OHS-PC and the final diagnosis from the patient's own general practitioner, including diagnoses based on hospital specialist letters.

Results: Five hundred forty-six men (mean age = 67.3 ± 17.1) and 720 women (mean age = 69.6 ± 19.5) were included. TIA/stroke was diagnosed in 294 men (54%) (mean age = 72.3 ± 13.6) and 366 women (51%) (mean age = 78.0 ± 13.8). In both genders, FAST (face-arm-speech test) symptoms were common in TIA/stroke (men 78%, women 82%) but also in no TIA/stroke (men 63%, women 62%). Men with TIA/stroke had shorter call durations than men without TIA/stroke (7.10 vs. 8.20 min, p = 0.001), whereas in women this difference was smaller and not significant (7.41 vs. 7.56 min, p = 0.41). Both genders were allocated high urgency in 75% of the final TIA/stroke cases.

Conclusion: Overall, patient and call characteristics are mostly comparable between men and women, and these only modestly assist in identifying TIA/stroke. There were no gender differences in allocated urgencies after telephone triage in patients with TIA/stroke.

Relationship between social support status and mortality in a community-based population: a prospective observational study (Yamagata study)

Background

Social support, defined as the exchange of support in social relationships, plays a vital role in maintaining healthy behavior and mitigating the effects of stressors. This study investigated whether functional aspect of social support is related to 5-year mortality in health checkup participants.

Methods

This study recruited 16,651 subjects (6797 males, 9854 females). Social support was evaluated using five-component questions: Do you have someone 1) whom you can consult when you are in trouble? 2) whom you can consult when your physical condition is not good? 3) who can help you with daily homework? 4) who can take you to hospital when you don’t feel well? and 5) who can take care of you when you are ill in bed? The association between the component of social support and all-cause and cardiovascular mortality was examined using Cox proportional hazard analysis.

Results

The percentage of subjects without social support components was 7.7–15.0%. They were more likely to be male, non-elderly, and living alone. During the follow-up period, there were 166 all-cause and 38 cardiovascular deaths. Cox proportional analysis adjusted for confounders showed that only the lack of support for transportation to hospital was significantly associated with all-cause (hazard ratio [HR] 2.01, 95% confidence interval [CI] 1.26–3.05) and cardiovascular mortality (HR 3.30, 95% CI 1.41–6.87). These associations were stronger in males than females.

Conclusion

This study showed that the lack of social support for transportation to the hospital was independently associated with all-cause and cardiovascular mortality in a community-based population.

Sex Differences in Prehospital Delay in Patients With Acute Stroke: A Systematic Review

BACKGROUND

In 2009, the window from symptom onset to administration of tissue plasminogen activator for acute ischemic stroke was extended from 3 to 4.5 hours. Yet no systematic review has addressed prehospital delay by sex for stroke symptoms since this change.

PURPOSE

We aimed to (1) compare prehospital delay times-the time from symptom onset to hospital arrival-between women and men with acute stroke or transient ischemic attack and (2) summarize factors influencing prehospital delay by sex.

METHODS

The CINAHL, MEDLINE, PubMed, Scopus, and PsycINFO databases were searched using PRISMA guidelines. Inclusion criteria were as follows: (1) quantitative research articles published between May 2008 and April 2019, (2) investigation of prehospital delay among women and men 15 years or older who were given a diagnosis of acute stroke or transient ischemic attack, and (3) English-language publications. The Crowe Critical Appraisal Tool was used to evaluate the quality of studies.

RESULTS

Fifteen publications (n = 162 856) met inclusion criteria. Most studies (n = 11) showed no sex differences in prehospital delay. Four studies from Asian-Pacific countries and the United States showed that women had significantly longer prehospital delay compared with men. Older age, minority race/ethnicity (black and Mexican American), and underuse of emergency medical services were associated with prolonged prehospital delay in women.

CONCLUSIONS

Most study authors found no differences in prehospital delay between women and men; however, women delayed longer in some Asian-Pacific and American studies. Findings of sex differences were inconclusive.

Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model

BACKGROUND

Most stroke cases lead to serious mental and physical disabilities, such as dementia and sensory impairment. Chronic diseases are contributory risk factors for stroke. However, few studies considered the transition behaviors of stroke to dementia associated with chronic diseases and environmental risks.

OBJECTIVE

This study aims to develop a prognosis model to address the issue of stroke transitioning to dementia associated with environmental risks.

DESIGN

This cohort study used the data from the National Health Insurance Research Database in Taiwan.

SETTING

Healthcare data were obtained from more than 25 million enrollees and covered over 99% of Taiwan's entire population.

PARTICIPANTS

In this study, 10,627 stroke patients diagnosed from 2000 to 2010 in Taiwan were surveyed.

METHODS

A Cox regression model and corresponding semi-Markov process were constructed to evaluate the influence of risk factors on stroke, corresponding dementia, and their transition behaviors.

MAIN OUTCOME MEASURE

Relative risk and sojourn time were the main outcome measure.

RESULTS

Multivariate analysis showed that certain environmental risks, medication, and rehabilitation factors highly influenced the transition of stroke from a chronic disease to dementia. This study also highlighted the high-risk populations of stroke patients against the environmental risk factors; the males below 65 years old were the most sensitive population.

CONCLUSION

Experiments showed that the proposed semi-Markovian model outperformed other benchmark diagnosis algorithms (i.e., linear regression, decision tree, random forest, and support vector machine), with a high R² of 90%. The proposed model also facilitated an accurate prognosis on the transition time of stroke from chronic diseases to dementias against environmental risks and rehabilitation factors.