Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/10740
Title: | Self-Management Recommendations for Sickle Cell Disease: A Content Analysis of Websites |
Authors: | DRUYE, A. Andrews NELSON, Katherine ROBINSON, , Brian |
Keywords: | Content Analysis Chronic Disease Sickle Cell Disease Self-Management Websites Recommendations |
Issue Date: | 2018 |
Publisher: | National Library of Medicine |
Abstract: | This paper reports on the findings of a study designed to establish website-based self-management recommendations for sickle cell disease. Google and Yahoo search engines were used to search the World-Wide-Web. Purposive sampling was utilized to select 28 websites that met the inclusion criteria. Data were manually collected from health education materials and subjected to qualitative content analysis. Self-management was conceptualized as actions involving preventive health, self-monitoring, self-diagnosing, and self-treatment. The results show that the websites recommend more self-management actions for preventive health and self-treatment than for self-monitoring and self-diagnosis. Frequent oral fluid intake, limitation of overactivity, eating a healthy diet, avoiding extreme temperatures, and infections were the commonest preventive health recommendations. Daily pain monitoring and general bodily inspections were the most frequent sel-fmonitoring recommendations. Commonly cited self-diagnostic indicators were fever, persistent pain, enlarged spleen, and leg ulcers. The use of analgesics and nonpharmacological measures were regularly cited for self-treatment. Most recommendations were assessed as clinically safe as they align with standards for sickle cell management. Nurses and other professionals should teach patients how to assess the credibility of websites. |
URI: | http://hdl.handle.net/123456789/10740 |
Appears in Collections: | School of Nursing & Midwifery |
Files in This Item:
File | Description | Size | Format | |
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Self-management recommendations for sickle cell disease- A content analysis of websites.pdf | MAIN ARTICLE | 1.62 MB | Adobe PDF | View/Open |
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