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Published on: August 11, 2023
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Somatic awareness and symptom attribution in ischemic stroke patients
Summary
Patient awareness of stroke symptoms and how they interpret them did not influence seeking timely medical care in this pilot study. Further research is needed to understand factors influencing treatment-seeking behaviors for ischemic stroke.
Area of Science:
- Neurology
- Public Health
- Health Services Research
Background:
- Patient delay in seeking treatment for stroke symptoms significantly contributes to morbidity and mortality.
- A substantial percentage of stroke deaths occur before hospital arrival, highlighting the critical need to understand factors influencing timely care-seeking.
Purpose of the Study:
- To investigate the relationship between somatic awareness and symptom attribution and their impact on treatment-seeking behaviors among patients with ischemic stroke.
Main Methods:
- A descriptive, correlational pilot study was conducted across three tertiary-care hospitals.
- Twenty patients diagnosed with ischemic stroke were enrolled.
- Somatic awareness was measured using the Modified Somatic Perception Questionnaire, and symptom attribution was assessed with the Symptom Interpretation Questionnaire.
Main Results:
- No significant correlation was found between somatic awareness or symptom attribution and treatment-seeking behaviors.
- However, significant differences were observed in physical attribution scores based on insurance status (p = .038) and family history of stroke (p = .026).
- A significant positive correlation was identified between education level and both somatic awareness (r = .386) and symptom attribution (r = .433).
Conclusions:
- Somatic awareness and symptom attribution were not significantly associated with the time to seek care for ischemic stroke in this study.
- The findings suggest potential links between insurance status, family history of stroke, and education with how patients perceive and respond to stroke symptoms.
- Limitations include a small sample size and potential data inaccuracies due to recall bias, necessitating future research with refined methodologies.
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