Angle Orthod. 2021 May 1;91(3):371-376. doi: 10.2319/051820-448.1.
(1) To assess the effectiveness of the Orthognathic Quality of Life Questionnaire (OQLQ) and the Child Oral Health Impact Profile (COHIP) to detect differences in Oral Health-Related Quality of Life (OHRQoL) between pediatric patients with dentofacial deformities and controls. (2) To assess for correlations between scores from the OQLQ and COHIP domains with the type and severity of the skeletal mal-relationship. (3) To assess if the COHIP and OQLQ were identifying unique or overlapping OHRQoL concerns.
Subjects were under age 18, presented with a dentofacial deformity, and completed both surveys. Matched controls completed the same. Severity for conditions was recorded via overjet, overbite, and ANB values and subjects were classified as skeletal Class I, II, or III.
Enrollment yielded 30 subjects and 31 controls. For the OQLQ, significant differences between subjects and controls were found for the Facial Esthetics domain, Oral Function domain, and total score. For the COHIP, significant differences were found for the Social/Emotional Well-Being and Self-Image domains plus total score. There were no significant correlations between the severity of the condition as measured by overjet and reported OHRQoL for any domains.
The OQLQ and COHIP are effective at detecting significant OHRQoL differences between pediatric patients with dentofacial deformities and controls. Although there is some overlap in the results, the instruments appear to identify different OHRQoL concerns.
(1)评估正颌质量问卷(OQLQ)和儿童口腔健康影响概况(COHIP)在检测牙颌面畸形儿童患者与对照组之间口腔健康相关生活质量(OHRQoL)差异方面的有效性。(2)评估 OQLQ 和 COHIP 各领域的评分与骨骼错合关系的类型和严重程度之间的相关性。(3)评估 COHIP 和 OQLQ 是否识别出独特或重叠的 OHRQoL 关注点。
受试者年龄在 18 岁以下,存在牙颌面畸形,并完成了这两项调查。匹配的对照组也完成了相同的调查。通过覆盖深度、覆颌深度和 ANB 值记录条件的严重程度,将受试者分为骨骼 I 类、II 类或 III 类。
入组得到 30 名受试者和 31 名对照组。对于 OQLQ,在面部美学、口腔功能和总分方面,患者组与对照组之间存在显著差异。对于 COHIP,在社交/情绪健康和自我形象领域以及总分方面,存在显著差异。在任何领域,条件严重程度(以覆盖深度衡量)与报告的 OHRQoL 之间均无显著相关性。
OQLQ 和 COHIP 可有效检测出牙颌面畸形儿童患者与对照组之间 OHRQoL 的显著差异。尽管结果有一些重叠,但这些工具似乎可以识别不同的 OHRQoL 关注点。