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Exploring professional identity and its predictors in health profession students and healthcare practitioners in Saudi Arabia.

Walaa Abdullah MumenaBandar A AlsharifAbdulaziz M BakhshWaleed H Mahallawi
Published in: PloS one (2024)
The government of Saudi Arabia is making significant efforts to improve the quality of health education and healthcare services. Professional identity has been linked to the quality of healthcare services provided by practitioners, however, data concerning the professional identity of health profession students (HPS) and healthcare practitioners (HCP) are still lacking in Saudi Arabia. The current study aimed to assess the level of professional identity in HPS and HCP in Saudi Arabia and to investigate its predictors. Cross-sectional data were collected from 185 HPS and 219 HCP in Saudi Arabia using river sampling technique. Data related to the sample characteristics were collected; an adapted version of the Macleod Clark Professional Identity Scale was utilized to collect data about the level of professional identity. Total score of professional identity was later calculated for each participant. Median professional identity scores for HPS and HCP were 38.0 (34.0-41.0) and 41.0 (37.0-43.0), respectively, out of 45. Significantly higher median professional identity score was found among HCP as compared to HPS (p <0.001). Data obtained from the multiple linear regression analysis, using the backward elimination method technique indicated that only working status (HPS vs. HCP) significantly predicted the professional identity score in all models performed. In conclusion, high levels of professional identity were reported among HCP and HPS in Saudi Arabia. Changes related to professional identity should be monitored in public and private educational and healthcare organizations to enhance the quality of healthcare services provided in the country.
Keyphrases
  • healthcare
  • primary care
  • mental health
  • electronic health record
  • public health
  • health information
  • saudi arabia
  • cross sectional
  • risk assessment
  • deep learning
  • health insurance
  • general practice