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The Use of Factor Analysis for Questionnaire Development: Lessons Learned and Takeaways

By: Published: 2020 | Product: SAGE Research Methods Cases: Medicine and Health
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Chronic pelvic pain (CPP) is associated with significantly negative consequences on health and wellbeing and can have a detrimental effect on everyday functioning. A new measure assessing the impact of CPP, the Impact of Female Chronic Pelvic Pain Questionnaire (IF-CPPQ), was developed because a measure that targeted domains that women with CPP deemed important was missing. This involved preliminary studies including a study using in-depth semi-structured interviews and a think aloud study with women with CPP. Findings from these studies informed the development of the initial questionnaire items. This was followed by a large-scale cross-sectional study that assessed the IF-CPPQ’s reliability, validity, and psychometric structure. Data analysis involved both exploratory and confirmatory factor analysis. Reliability was assessed using Cronbach’s alpha. Many decisions and considerations had to be made during factor analyses (both exploratory and confirmatory factor analyses). For instance, sample size requirements for factor analyses are somewhat arbitrary, though the majority agree the greater the sample size, the better. Although guidelines exist, there are no hard-and-fast rules and it is important to understand the data and ensure it makes sense.

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Confirmatory factor analysis

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