From the KidZ Health Castle, UZ Brussel, Brussels, Vrije Universiteit Brussel, Brussels, Belgium.
the Danone Nutricia Research, Precision Nutrition D-lab, Biopolis, Singapore.
J Pediatr Gastroenterol Nutr. 2022 Nov 1;75(5):584-588. doi: 10.1097/MPG.0000000000003586. Epub 2022 Aug 4.
The Brussels Infants and Toddlers Stool Scale (BITSS) was developed for the assessment of stool consistency in non-toilet-trained children. This study aimed to (1) investigate the intra-rater reliability of the BITSS among health care professionals (HCPs) and caregivers (CGs); (2) study a potential learning curve; (3) explore the impact of photo quality on intra-rater reliability.
Photos of diapers containing stool were assessed twice by 4 HCP (2432 photos) and 8 CGs (492 photos) using the BITTS. Intra-rater reliability was calculated by the percentage of exact agreement and a κ-value. A learning effect and the impact of photo quality was explored using mixed linear model and generalized estimating equations.
HCPs generated 24,320 stool consistency ratings: 12.1% were scored as watery, 31.0% loose, 29.4% formed, and 27.6% hard. CGs performed 7872 ratings: 9.2% classified as watery, 34.6% loose, 28.9% formed, and 27.3% hard. Intra-rater reliability (κ) for HCPs ranged from 0.64 [95% confidence interval (CI) = 0.61-0.66] to 0.78 (95% CI = 0.76-0.80) and from 0.68 (95% CI = 0.63-0.73) to 0.94 (95% CI = 0.91-0.97) in the CG group. Both groups had <1% improvement in the odds of identical classification per 50 photos. The percentage of absolute agreement was higher in photos rated as good quality than those that were not (HCPs: 80.3% vs 69.5%, P < 0.001; CGs: 90.4% vs 86.3%, P < 0.001).
The BITSS has an excellent intra-rater reliability for the stool consistency scoring of photographs of stools in diapers, but can be influenced by photo quality. A clinically meaningless learning effect was found.
布鲁塞尔婴幼儿粪便量表（BITSS）是为评估未接受如厕训练的儿童粪便稠度而开发的。本研究旨在：（1）调查健康照护专业人员（HCP）和照护者（CG）对 BITSS 的内部评估者可靠性；（2）研究潜在的学习曲线；（3）探讨照片质量对内部评估者可靠性的影响。
4 名 HCP（2432 张照片）和 8 名 CG（492 张照片）两次使用 BITTS 评估含有粪便的尿布照片。通过百分比完全一致和κ 值计算内部评估者可靠性。使用混合线性模型和广义估计方程探索学习效果和照片质量的影响。
HCP 生成了 24320 个粪便稠度评分：12.1%被评为水样便，31.0%为稀便，29.4%为成形便，27.6%为硬便。CG 完成了 7872 次评分：9.2%被评为水样便，34.6%为稀便，28.9%为成形便，27.3%为硬便。HCP 的内部评估者可靠性（κ）范围为 0.64（95%置信区间（CI）=0.61-0.66）至 0.78（95%CI=0.76-0.80），CG 组为 0.68（95%CI=0.63-0.73）至 0.94（95%CI=0.91-0.97）。两组每增加 50 张照片，相同分类的几率仅提高了<1%。照片质量好的照片，其完全一致的百分比高于照片质量差的照片（HCP：80.3%比 69.5%，P<0.001；CG：90.4%比 86.3%，P<0.001）。
BITSS 对尿布中粪便照片的粪便稠度评分具有极好的内部评估者可靠性，但可能受到照片质量的影响。发现了一个无临床意义的学习效应。
