Computer-assisted instruction before colonoscopy is as effective as nurse counselling, a clinical pilot trial.

ENDOSCOPY INTERNATIONAL OPEN(2017)

引用 10|浏览1
暂无评分
摘要
Background and study aims Better patient education prior to colonoscopy improves adherence to instructions for bowel preparation and leads to cleaner colons. We reasoned that computer assisted instruction (CAI) using video and 3D animations followed by nurse contact maximizes the effectiveness of nurse counselling, increases proportion of clean colons and improves patient experience. Patients and methods Adults referred for colonoscopy in a high-volume endoscopy unit in the Netherlands were included. Exclusion criteria were illiteracy in Dutch and audiovisual handicaps. Patients were prospectively divided into 2 groups, 1 group received nurse counselling and 1 group received CAI and a nurse contact before colonoscopy. The main outcome, cleanliness of the colon during examination, was measured with Ottawa Bowel Preparation Scale (OBPS) and Boston Bowel Preparation Scale (BBPS). We assessed patient comfort and anxiety at 3 different time points. Results We included 385 patients: 197 received traditional nurse counselling and 188 received CAI. Overall patient response rates were 99%, 76.4% and 69.9% respectively. Endoscopists scored cleanliness in 60.8%. Comparative analysis of the 39.2% of patients with missing scores showed no significant difference on age, gender or educational level. Baseline characteristics were evenly distributed over the groups. Bowel cleanliness was satisfactory and did not differ amongst groups: nurse vs. CAI group scores in BBPS: (6.54 +/- 1.69 vs. 6.42 +/- 1.62); OBPS: (6.07 +/- 2.53 vs. 5.80 +/- 2.90). Patient comfort scores were significantly higher (4.29 +/- 0.62 vs. 4.42 +/- 0.68) in the CAI group shortly before colonoscopy. Anxiety and knowledge scores were similar. Conclusion CAI is a safe and practical tool to instruct patients before colonoscopy. We recommend the combination of CAI with a short nurse contact for daily practice.
更多
查看译文
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