Dietary app for patients with kidney disease: Qualitative evaluation of a prototype.

Louise Birk Suder,Per Ivarsen, Lisbeth Førrisdahl, Mette R Christensen, Lise Streubel-Kristensen, Anni Sørensen,Jeanette Finderup

Journal of renal care(2023)

引用 0|浏览1
暂无评分
摘要
BACKGROUND:Individual dietary recommendations change as loss of kidney function progresses. Adopting these recommendations in everyday life poses major challenges for patients. Individualising dietary counselling is crucial to easy accessibility. AIM:To investigate patients' needs with regard to a dietary app for patients with chronic kidney disease, patients', and health professionals' immediate responses to such a dietary app and suggestions for improvement and further development of a prototype. DESIGN:A prototype of the dietary app has been developed and demonstrates how all information it provides can be tailored to the individual patient according to stage of disease, anthropometrics, and phosphate and potassium levels. A qualitative evaluation of the prototype was conducted using the Consolidated Criteria for Reporting Qualitative Research checklist for reporting. APPROACH:Seven individual interviews and four focus groups were analysed using interpretive description. PARTICIPANTS:Individual interviews with seven patients who have stage 4 or 5 chronic kidney disease and are not on dialysis, and four focus groups: one with participants from the individual interviews, one with six patients on haemodialysis, one with 13 kidney dieticians and one with seven health professionals. FINDINGS:Both patients and healthcare professionals were positive about the app. Individualisation is necessary for the app to work in practice. The patients reported access to a diet diary and recipes as important elements. CONCLUSION:There is a need to improve the tools we use today to enhance patient adherence to dietary recommendations. The development of an app for individual dietary counselling could be a useful solution.
更多
查看译文
关键词
chronic kidney disease, dietary app, self-management
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要