ISQ Factor Analysis: Assessing Suitability and Interrelatedness

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Although the ISQ was not originally designed as a multi-factor questionnaire, exploratory factor analysis (EFA) was conducted to explore potential meaningful factors and evaluate the relevance of individual items. The data for EFA was first analyzed for interrelatedness using the Kaiser-Meyer-Olkin (KMO) measure and the Bartlett test of sphericity (Table 4). KMO values greater than 0.9 indicated a high degree of sampling adequacy, indicating that the data was suitable for factor analysis. The significant results of the Bartlett test of sphericity also indicated that the items in the ISQ were not independent, further confirming the suitability of factor analysis.