Protection of human participants
In an empirical study carried out by Jayadevappa, Schwartz, Chhatre, Wein and Malkowicz (2010), a total of 201 participants were recruited to take part in the survey. These were patients who had already been diagnosed with prostate cancer. Prior to treatment, the subjects were supposed to fill a number of forms. Hence, one of the most profound benefits of the study to the participants was the availability of treatment after going through the study. This implied that the participants would cut down the cost of managing prostate cancer during the entire period of the quantitative study. In spite of the benefit, it is pertinent to mention that the patients had to wait for a very long time before concluding their participation in the study. A period of 24 months was extremely long especially for patients with advanced state of prostate cancer. It is unfortunate to mention that the researchers do not point out the negative effects to patients when they undergo such a long period of research. Besides, the authors fail to underscore the side effects of using the prescribed drugs. As much as post treatment utility appears to have a significant relationship with treatment, there are no clear pointers on the magnitude of risks posed to the participants.
The researchers identified eligible patients from reputable health facilities that manage prostate cancer. Study information was also sent to the participants in good time. Consent information and additional study materials were provided to the participants by the study research assistants. Before the process of data collection began, both the HIPPAA consent and written informed consents were given to the enrolled patients. Needless to say, the latter was one of the major strengths of the empirical study.
On the other hand, the follow-up surveys that were disseminated to the participants through personal e-mails were merely a retention plan in order to complete the 24 months of study exercise. It is evident that some participants were compelled to take part in the second portion of the research study bearing in mind that a number of them failed to respond. As a result, they had to be contacted by phone in order to complete the remaining sections. The team of researchers tried as much as possible to emphasize to the participants the importance of being active in the empirical study. Hence, voluntary participation was somewhat not in place. Worse still, there is no indication whether an institutional review board approval was obtained from the agency in which the study was conducted even though it was necessary (Fuhse & Mützel, 2011)
Data collection
Major variables have been identified and expounded in the research study. For instance, the HRQoL score log was the dependent variable during the process of collecting data. On the other hand, the model and treatment type were the independent variables of interests for the quantitative study. However, these variables have been scantly addressed at the data collection level. Besides, the variables were adjusted in order to be compatible with both the propensity score and the socio-demographic variables. Such an adjustment can easily complicate data analysis and thereafter generate wrong results. The authors should have applied the variables in their raw forms in order to obtain real outcomes.
In regards to data collection, information on income, living arrangement, marital status, education and ethnicity were self-reported by the participants through the guidance of research assistants. Information on comorbidity, TNM stage of cancer, Gleason score, prostate-specific antigen, treatment, health insurance and prostate cancer diagnosis were gathered using a structured medical chart review. All the self-administered surveys were completed by the participants. However, the authors do not explain the rationale behind choosing the above data collection method (Lach, 2014). The researchers have also not indicated the period taken to collect required data. It is usually necessary to give timelines in quantitative research studies of this magnitude (Allen & Austin, 2001).
The sequence of data collection for each of the participant entailed filling-up self assessment forms followed by questionnaires and finally a providing recovery data within a period of 12-24 months as part of the follow-up process by the researchers.
Data Management and Analysis
SAS 9.2 was used to analyze all the collected data. Variables were also analyzed descriptively. Each participating individual was assessed using repeated measurements through longitudinal data with the aim of obtaining consistent results. In addition, the researchers employed models with linear mixed effects. This would assist to create necessary adjustments in regards to observed patient correlations. Co-variances and variances were also adjusted in the same manner. Although the analysis process yielded reliable results, the authors did not discuss how the rigor of the process would be assured. No measures were taken to minimize the effects of researcher bias.
Findings/interpretation of Findings
All the findings were systematically, logically and coherently presented in a simplified tabular form. This makes it easy for the audience to follow up the quantitative study (Cameron, 2011). According to the researchers, the findings indicate that there is a close correlation between utility and treatment.
Conclusion
These findings indeed reflect reality on the ground. The authors have also pointed out a number of limitations of the study. These include the fact that the QWB-SA instrument is yet to be approved for cancer treatment, an observational study design was used and some findings were generalized. The nursing practice can indeed benefit from these findings especially in regards to the management of both acute and chronic prostate cancer patients. Finally, there are no recommendations made for further studies
References
Allen, M. T., & Austin, G. W. (2001). The role of formal survey research methods in the appraisal body of knowledge. The Appraisal Journal, 69(4), 394-399.
Cameron, R. (2011). Mixed methods research: The five ps framework. Electronic Journal of Business Research Methods, 9(2), 96-108.
Fuhse, J., & Mützel, S. (2011). Tackling connections, structure, and meaning in networks: Quantitative and qualitative methods in sociological network research. Quality and Quantity, 45(5), 1067-1089.
Jayadevappa, R., Schwartz, J. S., Chhatre, S., Wein, A. J., & Malkowicz, S.B. (2010). Association between utility and treatment among patients with prostate cancer. Quality of Life Research, 19(5), 711-720.
Lach, D. (2014). Challenges of interdisciplinary research: Reconciling qualitative and quantitative methods for understanding human-landscape systems. Environmental Management, 53(1), 88-93.