Assessing change in quality of life using the Oral Health Impact Profile.
Assessing change in quality of life using the Oral Health Impact Profile.
复制标题
使用口腔健康影响概况评估生活质量的变化。
DOI：
10.1111/j.1600-0528.1998.tb02084.x
复制
发表时间：
1998
影响因子：
2.3
通讯作者：
Slade,GD
中科院分区：
文献类型：
--
作者：
Slade,GD
传统的口腔健康纵向研究仅测量疾病进展，忽略了健康状况的改善。Objectives：本研究探讨了口腔健康相关生活质量（OHRQOL）变化的纵向评估中出现的方法学问题。Methods：基线和2年随访数据来自一项观察性纵向研究，该研究纳入了498名年龄在60岁或60岁以上的人，居住在南澳。口腔健康相关的生活质量使用口腔健康影响概况（OHIP）进行测量。三个假设的风险预测因素（牙齿脱落，基于问题的牙科就诊和经济困难）被选中来检查四种测量变化的方法的效果：改善，恶化和净变化的分类措施，以及OHIP评分净变化的定量措施。所有三个高风险组的OHRQOL恶化率约为相应低风险组的两倍。令人惊讶的是，高危人群的改善率也更高。当分类测量时，这些影响并没有相互抵消，表明OHRQOL的改善和恶化可以同时发生。然而，定量分析导致改善和恶化取消，平均OHIP评分的分析产生了一个虚假的印象，即OHRQOL的变化没有不同的牙科访问组。此外，平均OHIP评分的变化被掩盖的回归mean.Conclusions：口腔健康相关的生活质量的措施捕捉改善和恶化的健康状况，创造新的复杂性概念化和分析变化的纵向研究。
Traditionally longitudinal studies of oral health have measured only disease progression and ignored improvements in health.Objectives: This study examines methodological issues that arise in longitudinal assessment of change in oral health‐related quality of life (OHRQOL).Methods: Baseline and 2‐year follow‐up data were used from an observational longitudinal study of 498 people aged 60 years or more living in South Australia. Oral health‐related quality of life was measured using the Oral Health Impact Profile (OHIP). Three hypothesized risk predictors (tooth loss, problem‐based dental visits and financial hardship) were selected to examine the effects of four methods of measuring change: categorical measures of improvement, deterioration and net change, and a quantitative measure of net change in OHIP scores.Results: Some 31.7% of people experienced some improvement and 32.7% experienced some deterioration in OHRQOL. All three high‐risk groups had approximately twice the rate of deterioration in OHRQOL compared with their corresponding low‐risk groups. Surprisingly, high‐risk groups also had higher rates of improvement. When measured categorically, these effects did not cancel one another, indicating that improvement and deterioration in OHRQOL can be experienced simultaneously. However, quantitative analyses cause improvements and deteriorations to cancel, and analysis of mean OHIP scores created a spurious impression that change in OHRQOL did not differ between dental visit groups. Furthermore, changes in mean OHIP scores were masked by regression to the mean.Conclusions: Oral health‐related quality of life measures capture both improvement and deterioration in health status, creating new complexities for conceptualizing and analyzing change in longitudinal studies.