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, 48 (3), 1018-38

Confirmatory Factor Analysis of the Pain Care Quality Surveys (PainCQ©)


Confirmatory Factor Analysis of the Pain Care Quality Surveys (PainCQ©)

Marjorie A Pett et al. Health Serv Res.


Objective: 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.

Study design: 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.

Principal findings: 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.

Conclusions: 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.


Figure 1
Figure 1
The Initial PainCQ-I (k = 11 Items Including the Shaded Items) and the Reduced PainCQ-I(k = 6 Items, with Shaded Items Removed)
Figure 2
Figure 2
The Initial PainCQ-N (k = 22 Items, Including the Shaded Items) and the Reduced PainCQ-N(k = 14 Items, Shaded Items Removed)

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