“I Think You Are Trustworthy, Need I Say More?” The Factor Structure and Practicalities of Trustworthiness Assessment

Abstract

Two popular models of trustworthiness have garnered support over the years. One has postulated three aspects of trustworthiness as state-based antecedents to trust. Another has been interpreted to comprise two aspects of trustworthiness. Empirical data shows support for both models, and debate remains as to the theoretical and practical reasons researchers may adopt one model over the other. The present research aimed to consider this debate by investigating the factor structure of trustworthiness. Taking items from two scales commonly employed to assess trustworthiness, we leveraged structural equation modeling to explore which theoretical model is supported by the data in an organizational trust context. We considered an array of first-order, second-order, and bifactor models. The best-fitting model was a bifactor model comprising one general trustworthiness factor and ability, benevolence, and integrity grouping factors. This model was determined to be essentially unidimensional, though this is qualified by the finding that the grouping variables accounted for significant variance with for several organizational outcome criteria. These results suggest that respondents typically employ a general factor when responding to items assessing trustworthiness, and researchers may be better served treating the construct as unidimensional or engaging in scale parceling of their models to reflect this response tendency more accurately. However, the substantial variance accounted by the grouping variables in hierarchical regression suggest there may be contexts in which it would be acceptable to consider the theoretical factors of ability, benevolence, and integrity independent of general trustworthiness.

Financial Capability as a Predictor of Financial Satisfaction among Catholic Higher Education Employees: A Sequential Explanatory Mixed Method Inquiry

“…Dependability. Dependability is essential for trustworthy research outcomes through consistency and replicability [21]. Detailed research information boosts credibility and robustness, improving overall trustworthiness [22].…”