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Development of a contact Lens risk survey
Contact Lens & Anterior Eye ( IF 3.2 ) Pub Date : 2020-12-03 , DOI: 10.1016/j.clae.2020.11.003
G Lynn Mitchell 1 , Kathryn Richdale 2 , Dawn Lam 3 , Heidi Wagner 1 , Beth T Kinoshita 4 , Aaron B Zimmerman 1 , Luigina Sorbara 5 , Bernard Rosner 6
Affiliation  

Purpose

To describe the development and report psychometric properties of the Contact Lens Risk Survey (CLRS) to identify patients at risk for soft contact lens-related complications.

Methods

Psychometric properties of the CLRS, a web-based survey with branching logic, were determined using data from 5 multi-site fieldings (n = 1059), including re-fielding to sub groups. Responses from participants with and without an active red eye were used to identify risk factors of a red eye event and calculate an overall risk score. A 6th fielding of the CLRS (n = 171) was used to assess discriminate validity.

Results

Participants needed 11−12 min to complete the survey with a negligible difference by age. Internal consistency was excellent (Cronbach’s α ≥ 0.70) for 3 of the 5 constructs identified by factor analysis. Twelve of the 17 survey items exhibited excellent within-subject repeatability (Kappa ≥ 0.61). Between-subject agreement, assessed in 18−25 year olds, was high for the majority of items, suggesting good generalizability across different populations of SCL wearers. The ability of the model using individual items of the CLRS to discriminate Controls and participants with a red eye was good with an area under the curve of 0.779.

Conclusion

The CLRS tool is a repeatable and valid instrument to standardize documentation of demographic, behavior, and exposure factors which appear to drive the greatest risk of a contact lens related red eye event.



中文翻译:

隐形眼镜风险调查的发展

目的

描述隐形眼镜风险调查 (CLRS) 的发展和报告心理测量特性,以识别有软性隐形眼镜相关并发症风险的患者。

方法

CLRS 的心理测量特性是一项具有分支逻辑的基于网络的调查,使用来自 5 个多站点部署 (n = 1059) 的数据确定,包括重新部署到子组。来自有和没有活动性红眼的参与者的反应被用于识别红眼事件的风险因素并计算总体风险评分。CLRS 的第 6 次部署(n = 171)用于评估区分效度。

结果

参与者需要 11-12 分钟才能完成调查,年龄差异可以忽略不计。通过因子分析确定的 5 种结构中的 3 种内部一致性非常好(Cronbach α ≥ 0.70)。17 项调查项目中有 12 项表现出优异的受试者内重复性(Kappa ≥ 0.61)。在 18-25 岁人群中评估的受试者之间的一致性对于大多数项目来说都很高,这表明在不同的 SCL 佩戴者人群中具有良好的普遍性。使用 CLRS 的单个项目的模型区分对照组和红眼参与者的能力很好,曲线下面积为 0.779。

结论

CLRS 工具是一种可重复且有效的工具,用于标准化人口统计、行为和暴露因素的文档,这些因素似乎导致与隐形眼镜相关的红眼事件的最大风险。

更新日期:2020-12-03
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