Pre-hospital delay intention and its associated factors in the high-risk population of stroke: a latent profile analysis.

Aims: To explore the possible latent classifications of pre-hospital delayed intention at high risk of stroke and to analyse the characteristics of different profiles.

Methods and results: A cross-sectional study was conducted in one community in Shanghai, China. Four hundred and seventy individuals at high risk of stroke were recruited, and self-reported questionnaires (including socio-demographic, stroke knowledge, health belief, and pre-hospital delay behaviour intention scale) were distributed between April and June 2023. A latent profile analysis was employed to identify the delay intention clusters, and multinomial logistic regression was utilized to ascertain the factors influencing the latent classes of delay intention. Four hundred and fifty-seven high-risk populations with a response rate of 97.23% were finally enrolled in this study. Four distinct classes were identified: high warning signs-low delay intention (26.3%), low warning signs-low delay intention (17.7%), moderate level of delay intention (37.3%), and high level of delay intention (18.7%). The influencing factors included stroke knowledge, health belief, age, education background, the nearest distance to the medical institution, and household income.

Conclusion: The pre-hospital delay intention among high-risk populations of stroke was classified into four distinct classes. It is crucial for individuals at high risk to remain vigilant towards stroke symptoms and to take prompt action. Health promotion education may be explored as a strategy to bridge the gap between the recognition of stroke symptoms and the low pre-hospital delay intention.