Dental Hygienists' Job Attractiveness and Satisfaction

Cross-tabulation was performed on age group and the items of job attractiveness, and the factors dental hygienists feel would improve the work environment. Correspondence analysis was performed with this cross-tabulation. To visualize the relationships, the results were illustrated graphically as biplots [13 (link)]. A three-parameter logistic model with item response theory (IRT) analysis was applied to calculate item discrimination, item difficulties, and item guesses for job attractiveness and satisfaction [1 (link),13 (link),14 (link)]. Item response and information curves are graphically illustrated. The analyses were carried out using R software version 3.50 (Institute for Statistics and Mathematics, Wien, Australia) with the LTR and irtoys packages using the following formula: $P_i\left(\theta \right)=\frac{\left(1-c_i\right)}{1+e^{-D{a}_i\left(\theta -b_i\right)}}$
where a_i: discrimination, b_i: difficulty and c_i: guessing.
Factor analysis with varimax rotation was performed to determine the latent variables for structural equation modelling (SEM). The structural relationship between job attractiveness and job satisfaction was calculated using AMOS software (24.0, IBM, Tokyo, Japan).