Do the measures yield numbers that represent nominal-, ordinal-, or interval-level data?
Nursing care measure (Caring Behaviours Inventory) and patient satisfaction measure (Patient Satisfaction Scale) are Likert scales. Because the responses yield whole numbers representing the degree to which a participant agrees with a particular statement in an item, the measure generates ordinal-level data.
Which level of measurement is yielded by the Caring Behaviors Inventory Satisfaction Scale? Which information in the article leads you to this conclusion?
Based on the type of analysis (Pearson correlation analysis) used to examine the relationship between nursing care and patient satisfaction, it can be concluded that the level of measurement yielded by Caring Behaviours Inventory Satisfaction is interval. This is because for Pearson correlation analysis to be carried out in SPSS, the data must be in interval scale.
Which level of measurement is yielded by the Patient Satisfaction Scale? Which information in the article leads you to this conclusion?
To assess the factors affecting patient satisfaction, a stepwise multiple regression model was conducted in SPSS. This type of analysis can only be carried out in SPSS if the data is in interval level of measurement. Therefore, it can be concluded that the scale yielded interval level data.
Have the authors used the correct descriptive statistics for the level of measurement of the variables?
The authors did exemplary work in the use of descriptive statistics. The descriptive statistics reported are the mean, the standard deviation, and the minimum and maximum. These descriptives helped to present participants descriptions in the most understandable way.
Did the authors use the correct correlation analysis for these instrument scores?
One of the research questions was to find out the relationship between nursing care and patient satisfaction. The correct statistical analysis to use in SPSS in examining the relationship between two variables at the interval level of measurement is Pearson correlation analysis. Therefore, the authors used the correct correlation analysis.
Are the statistics represented in the most understandable way? Discuss the use of tables relative to the type of information being reported. Are there graphical representations that could simplify the report?
Even though the use of tables to present the various types of statistical analysis was perfect, some tables were omitted. For instance, the table showing the correlation between caring and satisfaction cannot be found. In addition, it could have been more helpful to the reader if the authors used graphical representations, in addition to tables, as they are easy to understand. For instance, in the correlational analysis, the authors ought to have used a scatter plot to display the correlation between variables under study. A pie chart showing participants descriptions (age, gender, and education) would have also been easier to interpret by the readers. For multiple regression, three-dimensional scatterplots could have been the simplest way of presenting the information graphically.
Do the authors provide the right descriptive numbers about the sample, measurement instruments, and results?
The authors provided the right descriptive numbers about the sample, measurement instruments, and results. The statistics provide the simple summaries of the sample and measures.
Do the authors interpret the data appropriatelythat is, they do not over interpret the results?
Generally, the data was interpreted appropriately. For instance, in correlational analysis, the authors provided both the r value and the p value and explained the direction of the relationship between the two variables as well as the statistical significance.
References
Palese, A., Tomietto, M., Suhonen, R., Efstathiou, G., Tsangari, H., Merkouris, A., ... & Balogh, Z. (2011). Surgical patient satisfaction as an outcome of nurses caring behaviors: a descriptive and correlational study in six European countries. Journal of Nursing Scholarship, 43(4), 341-350.
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