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Updated: Dec 17, 2025

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
Published on: April 29, 2014
Are trust and satisfaction similar in dental care settings?
YoungHa Song1, Liana Luzzi1, Sergio Chrisopoulos1
1Australian Research Centre for Population Oral Health, Adelaide Dental School, The University of Adelaide, Adelaide, SA, Australia.
Objectives:
Trust and satisfaction in dental care settings are salient constructs to operationalize the concept of dentist-patient relationships (DPR). This study aimed to compare the similarity of both constructs with regard to factor structure and revise the scales for better psychometric properties.
Methods:
Data analysed in the study were collected in self-complete questionnaires from a random sample of 4011 adults living in South Australia. Trust and satisfaction were assessed using the Dentist Trust Scale and the Dental Care Satisfaction scale. Items in the scales were initially examined with a split-half sample in exploratory factor analysis and cluster analysis. Factor structures of different model designs were tested on the other half sample in confirmatory factor analysis. The final model was cross-validated on the first half sample for structural invariance.
Results:
Exploratory factor analysis revealed a three-factor structure consisting of 'trust', 'satisfaction' and 'distrust/dissatisfaction' (60.2% of the variance explained; Cronbach's α = 0.94, 0.81, 0.73, respectively). Cluster analysis supported the factor solution with the same three major clusters except for a single-item independent branch of the 'cost' domain from the satisfaction scale. The final model was designed with two correlated but distinct factors, 'trust' and 'satisfaction', with the modification of one inter-item covariance and deleting the least associated item (GFI = 0.96, CFI = 0.98, RMSEA = 0.06). The stability of the final model was achieved through cross-validation (P = .143, ∆CFI < 0.001).
Conclusions:
Trust and satisfaction in dental care settings are unidimensionally different yet highly correlated factors concurrently. Demonstrating the discriminant and complementary functions of both constructs can justify the rationale to apply them together in further studies for DPR.
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