Payesh (Jun 2023)

Factors affecting management of dental anxiety among dental students: A structural equation modelling

  • Fatemeh Babadi,
  • Yosra Abdolhossein,
  • Hossein Malekzadeh,
  • Marzieh Araban

Journal volume & issue
Vol. 22, no. 3
pp. 323 – 333

Abstract

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Objective: The aim of the present study was to assess factors affecting behavioural management of dental anxiety among dental students. Methods: The present study was conducted on 218 dental students of Ahvaz Jundishapur University of Medical Sciences, Ahvaz (AJUMS), school of dentistry, Iran during 1 to 21 November 2020. The data collection tool included a self-designed questionnaire containing a number of questions for assessing students’ anxiety reduction guidelines, and behavioural-medication anxiety control methods, as well as measuring key components of the Theory of Planned Behaviour (TPB). The layout of the questionnaire and all its questions/items were designed on the website https://survey.porsline.ir. Data were analysed using SPSS, version 23. The structural equation modelling (SEM) was performed using AMOS software version 26.0. Results: A total of 246 dentistry students were invited to participate in the study. Out of 246 students enrolled, 218 (88%) students completed and sent the questionnaire. The results revealed that behavioural intention had a direct impact on the implementation of distinguished instructions. Likewise, subjective norms and perceived behavioural control directly influenced the behavioural intention. The fit indices indicated that the measurement might have an acceptable performance (GFI = 0.86, CFI=0.81 RMSEA = 0.07, x2/df >3); R2=0.37. Perceive behavioral control and intention were the most important factors in explaining dental anxiety control behaviour. Conclusion: The findings suggest that the constructs of the theory of planned behaviour might have a preliminary acceptable fit for determining the factors related to the beliefs and behaviours of dental anxiety control. Further studies are needed to improve model fit indices. The future studies should determine which educational methods could better manipulate the predictive factors.

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