College of Nursing, University of Utah, Salt Lake City, UT 84112, USA.
Health Serv Res. 2013 Jun;48(3):1018-38. doi: 10.1111/1475-6773.12014. Epub 2012 Dec 3.
To examine the reliability and validity and to decrease the battery of items in the Pain Care Quality (PainCQ(©) ) Surveys.
DATA SOURCES/STUDY SETTING: Patient-reported data were collected prospectively from 337 hospitalized adult patients with pain on medical/surgical oncology units in four hospitals in three states.
This methodological study used a cross-sectional survey design. Each consenting patient completed two PainCQ(©) Surveys, the Brief Pain Inventory-Short Form, and demographic questions. Clinical data were extracted from the medical record.
DATA COLLECTION/EXTRACTION METHODS: All data were double entered into a Microsoft Access database, cleaned, and then extracted into SPSS, AMOS, and Mplus for analysis.
Confirmatory factor analysis using Structural Equation Modeling supported the initial factor structure. Modification indices guided decisions that resulted in a superior, parsimonious model for the PainCQ-Interdisciplinary Care Survey (six items, two subscales) and the PainCQ-Nursing Care Survey (14 items, three subscales). Cronbach's alpha coefficients all exceeded .80.
Cumulative evidence supports the reliability and validity of the companion PainCQ(©) Surveys in hospitalized patients with pain in the oncology setting. The tools may be relevant in both clinical research and quality improvement. Future research is recommended in other populations, settings, and with more diverse groups.
检验疼痛护理质量(PainCQ(©) )调查问卷的可靠性和有效性,并精简其项目组合。
资料来源/研究场所:前瞻性收集了来自四个州的四家医院的医学/肿瘤外科住院成年疼痛患者 337 人的患者报告数据。
这是一项使用横断面调查设计的方法学研究。每位同意参与的患者均完成两份 PainCQ(©) 调查问卷、简短疼痛量表-简表以及人口统计学问题。临床数据从病历中提取。
资料收集/提取方法:所有数据均经双录入进入 Microsoft Access 数据库,进行清理后再导入 SPSS、AMOS 和 Mplus 进行分析。
结构方程模型的验证性因子分析支持初始因子结构。修正指数指导决策,最终得出疼痛跨学科护理调查问卷(六项目、两个分量表)和疼痛护理调查问卷(14 项目、三个分量表)的更优简约模型。克朗巴赫 α 系数均大于.80。
累积证据支持疼痛护理质量调查问卷在肿瘤学环境下住院疼痛患者中的可靠性和有效性。这些工具在临床研究和质量改进中可能都具有相关性。建议在其他人群、环境和更多样化的群体中开展进一步研究。