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智能机械斑块控制的新型分类系统:一项聚类分析的横断面调查

A Novel Classification System of Smart Mechanical Plaque Control: A Cross-Sectional Survey with Cluster Analysis.

作者信息

Shukla Balraj R, Panda Anup K

机构信息

Department of Pediatrics and Preventive Dentistry, College of Dental Sciences and Research Centre, Gujarat University, Ahmedabad, Gujarat, India.

出版信息

Indian J Community Med. 2025 Jan-Feb;50(1):175-180. doi: 10.4103/ijcm.ijcm_439_23. Epub 2025 Jan 23.

Abstract

BACKGROUND

Recurring advances in the field of mechanical plaque control (MPC) devices have shown promise in improving the oral hygiene status of the community. However, little is known about the association between the knowledge of healthcare professionals regarding these advances, the manufacturers in understanding the demand of the community, and the community's willingness to switch to these "smarter" advances in MPC. This article puts forth a novel classification system of smart MPC to bridge this research gap.

MATERIALS AND METHODS

After a Delphi consensus and a sample pretesting, a customized questionnaire survey based on the knowledge, attitude, and practice model was filled by 618 participants. The participants were divided into two groups: Group I from the healthcare profession (n = 236) and Group II from other professions (n = 382). A Chi-square test was used to determine the significant variables. These variables went through K-means and cluster silhouette scoring for cluster analysis. A correlation coefficient using regression line was used to analyze the relation between related variables.

RESULTS

The Chi-square test revealed nine components with statistically significant associations ( < 0.05). K-means clustering of the nine parameters revealed six clusters (silhouette score >0.5) that guided in drawing a classification of smart MPC.

CONCLUSION

This study reveals the dearth of knowledge among the participants regarding advanced MPC and their negligence in following basic oral hygiene routines. The classification system derived through cluster analysis provides a basis for understanding the upgraded modes of MPC.

摘要

背景

机械菌斑控制(MPC)设备领域的不断进步已显示出改善社区口腔卫生状况的前景。然而,对于医疗保健专业人员对这些进展的了解、制造商对社区需求的理解以及社区转向这些MPC“智能”进展的意愿之间的关联,人们知之甚少。本文提出了一种智能MPC的新颖分类系统,以弥补这一研究空白。

材料与方法

经过德尔菲共识和样本预测试后,618名参与者填写了基于知识、态度和实践模型的定制问卷调查。参与者分为两组:第一组来自医疗保健行业(n = 236),第二组来自其他行业(n = 382)。采用卡方检验确定显著变量。这些变量经过K均值和聚类轮廓评分进行聚类分析。使用回归线的相关系数分析相关变量之间的关系。

结果

卡方检验揭示了九个具有统计学显著关联的成分(<0.05)。对这九个参数进行K均值聚类,得出六个聚类(轮廓评分>0.5),为智能MPC的分类提供了指导。

结论

本研究揭示了参与者对先进MPC知识的匮乏以及他们在遵循基本口腔卫生常规方面的疏忽。通过聚类分析得出的分类系统为理解MPC的升级模式提供了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/787d/11927868/f4666a242cee/IJCM-50-175-g001.jpg

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