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Exploring job satisfaction among pharmacy professionals in the Arab world: a multi-country study
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Abstract<sec> <title>Objectives

The study objectives were to (1) describe the characteristics of the pharmacy professionals and (2) explore the association between job satisfaction and factors, such as work control, work stress, workload and organization and professional commitments.

Methods

This study was a cross-sectional design. The survey items were mainly adapted from the US National Pharmacist Workforce Survey. An electronic (Qualtrics) questionnaire was posted on pharmacist social media in several Arab countries. The survey link was posted from 22 March 2021 to 1 May 2021. The multiple linear regression measured the association between 12 independent variables and pharmacist job satisfaction.

Key findings

A total of 2137 usable surveys were received from pharmacists (54.7% female) working in 18 Arabic countries. The job satisfaction rate varied among countries in the Arab world. The fields with the highest satisfaction average included pharmaceutical marketing, academia and the pharmaceutical industry. At the same time, pharmacists working in community pharmacy and Ministry of Health/administrative positions had the lowest satisfaction rates. Overall, pharmacist satisfaction was average (3.1 out of 5). The pharmacists had the lowest satisfaction averages with income and job expectations. The pharmacists with bachelor’s degrees had significantly lower satisfaction than pharmacists with postgraduate degrees. Male pharmacists had significantly higher job satisfaction compared with female pharmacists. Workload and the feelings of organization and professional commitments had significant positive associations with job satisfaction.

Conclusions

The pharmacy profession in Arabic countries faced several challenges that negatively impacted job satisfaction. Improving work environment, professional management, income and organization loyalty is necessary to enhance pharmacist job satisfaction.

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Fri Jun 01 2018
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Sun May 22 2022
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Publication Date
Tue Jan 01 2019
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Multi -Focus Image Fusion Based on Stationary Wavelet Transform and PCA on YCBCR Color Space
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