Validation of the 8-item questionnaire for verifying stroke free status with and without pictograms in three West African languages

Background: The Questionnaire for Verifying Stroke-free Status (QVSFS) has been validated in Western populations as a method for verifying stroke-free status in participants of clinical, epidemiological and genetic studies. This instrument has not been validated in low-income settings where populati...

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Main Authors: Fred S. Sarfo, Mulugeta Gebregziabher, Bruce Ovbiagele, Rufus Akinyemi, Lukman Owolabi, Reginald Obiako, Kevin Armstrong, Oyedunni Arulogun, Albert Akpalu, Sylvia Melikam, Raelle Saulson, Carolyn Jenkins, Mayowa Owolabi
Format: Article
Language:English
Published: Elsevier 2016-06-01
Series:eNeurologicalSci
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Online Access:http://www.sciencedirect.com/science/article/pii/S2405650216300156
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Summary:Background: The Questionnaire for Verifying Stroke-free Status (QVSFS) has been validated in Western populations as a method for verifying stroke-free status in participants of clinical, epidemiological and genetic studies. This instrument has not been validated in low-income settings where populations have limited knowledge of stroke symptoms and literacy levels are low. Objective: To simultaneously validate the 8-item QVSFS in 3 languages spoken in West Africa (Yoruba, Hausa and Akan) for ascertainment of stroke-free status of control subjects in SIREN. Methods: Using a cross-sectional study design, 100 participants each from the 3 linguistic groups will be consecutively recruited from neurology and general medicine clinics of 5 tertiary referral hospitals in Nigeria and Ghana. Ascertainment of stroke status will be determined by neurologists using structured neurological examination, review of case records and neuro-imaging (Gold standard). The relative performance of QVSFS without and with pictures of stroke symptoms (pictograms) will be assessed using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Conclusion: The proposed study will provide valuable data on the performance of the QVSFS in resource-limited settings.
ISSN:2405-6502