Answer

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  Article Evaluation

  Singh, T., Kaur, M., Verma, M. & Kumar, R. (2019). Job satisfaction among health care providers: A cross-sectional study in public health facilities in Punjab, India. Journal of Family Medicine and Primary Care, 8(10),3268-3275.

               Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857391/?report=printable

  Overview

  This article details a study in which Singh et al. (2019) sought to “measure job satisfaction among different categories of healthcare providers from Punjab government health services and to determine the factors that affect job satisfaction most” (p. 3268).  They conducted the research against the backdrop of comprehension and appreciation of the significance of job satisfaction in the context of organizational functioning. As the authors report, job satisfaction affects workers, hence their performance and ultimately organizational performance.  The study setting was Punjab state in India, which has 176 health institutions providing curative, promotive, and curative services.

  The researchers’ target population was the healthcare providers (including lab technicians, pharmacists, doctors, nurses) working in the state’s various health institutions. They selected a sample of 457 participants through multi-stage random sampling. They conducted a survey using the Job Satisfaction Scale (JSS), a standard validated instrument that focuses on various factors relating to work, workplace outcomes and related job satisfaction (or lack of it). They found a significant association between satisfaction levels and marital status and educational degree as well as no transfer in the previous 5 years. Factors like age, city of present posting, and stay with family in the same town were found to be only partially significant. They also found out that job satisfaction flowed directly from motivation. The authors conclude by emphasizing the significance of job satisfaction and making a call to policymakers to pay attention to it. They call for interventions geared towards improving the various faces that increase job satisfaction.

  Sampling Strategy/Method

  Having chosen their target population as the various healthcare providers working at different health institutions spread across the state of Punjab, the researchers set to come up with a convenient sample size. Using the online sample size calculator, open epi (Version 3.01), they estimated their sample size to be 457.

  They used the multi-stage random sampling technique to select their participants. The first stage entailed randomly selecting nine districts of the state using a random number table from a total of 22. Next, from each of the selected district, 50 participants were randomly approached via telephone from a list they had prepared after an appointment. None of those telephonically approached refused to participate. However, 12 participants initially missed the calls but later called back and were included in the study. The sample comprised of 462 participants, a figure that was about the estimate, hence a convenient one for the study.

  Of interest presently is the sampling method used. According to Sedgwick (2015), “multistage sampling entails two or more stages of random sampling based on the hierarchical structure of natural clusters within the population” (p.1).  Indeed, the method was effective since the population being studied was geographically diverse. Had a simple random method been used, all healthcare providers in Punjab would have had the same chances of being selected. As Sedgwick (2015) explains, “it would have been impractical and too expensive to survey such a sample” (p.2), since Punjab is a big state and the study’s target population was geographically diverse. Additionally, using this method ensured study efforts and resources were concentrated only on certain districts (nine in total), as opposed to all districts in the state. Therefore, multistage random sampling was convenient and effective for the detailed study.