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Patient Satisfaction And Nursing

¶ … size is an important step in the sample selection process. In Negarandeh, Bahabadi & Mamaghani's (2014) study, the procedure used to determine the sample size is clearly described. Following a pilot study, using the sample size formula, and based on the population of the hospital in which the trial was carried out, the authors estimated the sample size at 100 participants (50 participants in each group). Revealing how the sample size was determined enables readers to ascertain the extent to which the sample selected is representative of the larger population (Thomas, 2009). In quantitative research, a representative sample is important for improving the generalizability of findings (Bryman, 2008). In this case, the sample was quite representative of the study population. The study setting was a 530-bed hospital. The trial was specifically conducted in the medical surgical ward, which had 40 active beds, meaning the findings can readily be generalized to the study population. The next step in the sampling process entails recruiting participants, which may involve random or non-random sampling techniques. In this case, subjects were recruited through convenience sampling. As convenience sampling is a form of non-random sampling, some bias may have occurred (Kothari, 2004). Negarandeh, Bahabadi & Mamaghani's (2014) article provided valuable insights about sample selection. This knowledge will be important for my future DNP scholarly projects. For me to generate credible findings in my future DNP projects, I must know how to determine the right sample size and the appropriate technique to use in locating the sample. Also, by reading the article, I was able to connect my previous knowledge with a real-world example. This increased my understanding of sample size determination and selection. Furthermore, the article demonstrated the importance of documenting sample size determination and sample selection procedures. In my future DNP projects, I must pay attention to disclosing these elements.

Part II

The aim of Negarandeh, Bahabadi & Mamaghani's (2014) study was to examine the impact of

The study specifically focused on two variables: patient satisfaction (the dependent variable) and regular nursing rounds (the independent variable). Patient satisfaction was measured using the Patient Satisfaction with Nursing Care Quality Questionnaire (PSNCQQ). A number of studies have confirmed the validity and reliability of the tool (e.g. Ksykiewicz-Dorota et al., 2011; Al-Abri & Al-Balushi, 2014). In Ksykiewicz-Dorota et al.'s (2011) study, for instance, the internal consistency of the tool was 0.96 on Cronbach's alpha, with predictive validity ranging from 0.57-0.84. This shows that the tool was appropriate for measuring the variables of interest. The data collection process involved administering the PSNCQQ tool on the second and fifth days of hospitalisation. To ensure effective data collection, the nurses involved were first taken through a twenty-minute training session. The length of the training session may seem short, but I believe it was adequate given the nature of the study.
One thing that stood out for me is the training of data collectors prior to embarking on the process of data collection. For me, this was new knowledge. Often, clinical researchers rely on hospital personnel to collect data. As demonstrated in Negarandeh, Bahabadi & Mamaghani's (2014) study, training data collectors is crucial for ensuring the required data is collected as desired. This will be a major point of consideration in my future DNP projects. Training data collectors, however, does not necessarily mean that the researcher leaves everything to them. The researcher must closely supervise the data collectors to ensure they comply with the provided guidelines throughout the study period. Nevertheless, too much researcher supervision may result in a Hawthorne effect (Negarandeh, Bahabadi & Mamaghani, 2014). The data collection part of the article was also an opportunity for me to connect previous knowledge with a real-world study.

Part III

It is not clear in Negarandeh, Bahabadi &…

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References

Al-Abri, R., & Al-Balushi, A. (2014). Patient satisfaction survey as a tool towards quality improvement. Oman Medical Journal, 29(1), 3-7.

Broeck, J., Cunningham, S., Eeckels, R., & Herbest, K. (2005). Data cleaning: detecting, diagnosing, and editing data abnormalities. PLoS, 2(10), e267.

Bryman, A. (2008). Social research methods. 3rd ed. Buckingham: Open University Press.

Creswell, J. (2014). Research design: qualitative, quantitative, and mixed methods approaches. 4th ed. London: SAGE.
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