Characteristics Associated With the Method of Each Article

The methodologies of the articles were unique and fit well with the participants’ and study objectives. Cheng et al. (2018) used questionnaires distributed among the study participants before and after the intervention. Questionnaires involved 26 items, which were meant to collect information on patient outcomes after incorporating home visit services. This method was perfect for the study because the participants knew how to answer questionnaire questions. In the second article by Gilad et al. (2020), Semi-structured, in-depth interviews were used. The researchers settled for this method because the sample was conveniently available in Hadassah Medical Hospital. This method was applicable in getting quality data from the participants, thus leading to a deeper understanding of Chronic Drug Treatment Among Hemodialysis Patients. Zimmerman et al. (2020) also incorporated an appropriate methodology for accurate results. The study was divided into two phases. In the first phase, the researchers used an anonymous, paper-based, validated questionnaire, while the second phase incorporated semi-structured interviews. Questionnaires were used to gain data on hand washing among nursing students and involved items to measure the factors influencing these attitudes, including cultural and environmental factors. The research methodologies used depended on the sample sizes and type of data being collected.

Characteristics Associated with the Design of Each Article

Similarly, study designs depended on the data being collected and the chosen methodologies. Cheng et al. (2018) used quasi-experimental quantitative design. This experimental design is effective in finding a cause-effect relationship. Therefore, through this design, the researchers managed to analyze the effects of home care for patients with mental health issues such as schizophrenia compared to the health outcomes of those who were hospitalized. A qualitative research design was used in the article by Gilad et al. (2020). This design does not apply to numerical data. Since an in-depth analysis was needed to elaborate on the impacts of chronic drug treatment among hemodialysis patients, this design was best applicable. It opened an avenue for open-ended interview questions. Lastly, Zimmerman et al. (2020) used a mixed-method design. Paper-based validated questionnaires and semi-structured interviews were incorporated. The design guided the selection of the two methods, each incorporated independently. This design is best applicable when dealing with a large sample size, as in this case, where the n was 930. Further, this method incorporated qualitative and quantitative methods, facilitating the design. It is therefore recommended that researchers pay close attention to the study aims and objectives, as well as the size of the study population, to determine the best applicable research designs.

Statistical Analysis Associated with The Method and Design of Each Article

Statistical analysis is vital for drawing conclusions from both the raw and unstructured data. Cheng et al., 2018 used Statistical Package for the Social Sciences (SPSS), a software package offering efficient and organized ways to manage extensive, complex data. Therefore, information from the questionnaires was collected and analyzed to narrow down conclusions on the effects and outcomes of caring for mentally ill patients from the comfort of their homes. This software package was the best pick since large data sets were applied in this study. Gilad et al. (2020) did not use specific software to analyze data collected through the interviews. Due to the open-ended interview questions, the researchers collectively reviewed participant responses, manually gauging them according to uniqueness. The sample population was small; therefore, analysis of the data and responses through interviews was simplified. Again, extensive data is better analyzed through software packages such as (SPSS), so Zimmerman et al. (2020) used it to analyze data from the 930 study respondents. Each response was categorized into specific groups, and the conclusions were drawn from the data accumulated on the software.

Reliability and Validity Issues Associated with Each Methodology and Design

Reliability and validity in research are essential to ensure the collected data is replicable and the results are undoubtedly accurate. The proof of validity and reliability of every research design and methodology are necessary to guarantee the integrity and quality of the instruments used. Therefore, Cheng et al. (2018) used Cronbach’s Alpha measure to assess scale reliability. Participants answered the study items using the Likert scale, ranging from one to five, with one being the lowest. Researchers ensured the instrument was valid by measuring the item-level and scale-level content validity indexes. Gilad et al. (2020) analyzed interviews to establish major categories and themes to ensure the reliability and validity of the designs and methodologies used and, thus, the findings. The open-ended interviews eradicated ambiguity and minimized subjectivity, thus maximizing reliability.

Further, there was a one-to-one correspondence involving interview items and interviewer competency, which was the case and thus assured validity. Lastly, although there were no evident reliability tests in the study by Zimmerman et al. (2020), mixed methods often allow various data collection methods, thus improving reliability and validity. The diversity in analysis, as well as data collection and interpretation, eradicates the possibility of reliability and validity concerns. However, the instrument’s validity was guaranteed because the standard English language is also used in Australia. If a study is not replicable, the results cannot be trusted since they cannot be used as a frame of reference in a similar research. The designs and methods used in the three articles were reliable; thus, no concerns were found. Further, the study designs and methods answered the three articles’ different research questions without bias, leaving no room for validity concerns.

Summary Comparing the Different Methods and Designs Used in the Studies

Although different studies use different methods and designs that are all valid and reliable, some methodologies are better than others; however, this does not affect study outcomes as long as they are implemented effectively. According to Wasti et al. (2022), the mixed methods method has become quite popular today for quantitative and qualitative methodologies, thus providing a stronger inference. Unfortunately, using this research method in all studies would be impossible since factors such as the sample size are crucial in determining the methodology and design to be applied. Quantitative and qualitative research designs are not badly off. However, Tenny et al. (2022) propose that qualitative research is less reliable than quantitative design for various reasons. For example, researcher skills are highly regarded, and personal biases may hinder results. However, this does not guarantee that quantitative research methods are the best per se. Savela (2018) mentions that participants under the quantitative design may not give quality responses due to a lack of options. It is risky to complete research yet have inaccurate answers or outcomes. Therefore, researchers should be keen on their chosen study designs and methodologies to avoid errors in data and outcomes.

References

Cheng, J., Huang, X., Lin, M., Wang, Y., & Yeh, T. (2018). A Mental Health Home Visit Service Partnership Intervention on Improving Patients’ Satisfaction. Archives of Psychiatric Nursing, 32(4), 610-616. https://doi.org/10.1016/j.apnu.2018.03.010

Gilad, L., Haviv, Y. S., Cohen-Glickman, I., Chinitz, D., & Cohen, M. J. (2020). Chronic Drug Treatment Among Hemodialysis Patients: A Qualitative Study of Patients, Nursing and Medical Staff Attitudes and Approaches. BMC Nephrology, 21(1). https://doi.org/10.1186/s12882-020-01900-y

Savela, T. (2018). The Advantages and Disadvantages of Quantitative Methods in Schoolscape Research. Linguistics and Education, 44, 31-44. https://doi.org/10.1016/j.linged.2017.09.004

Tenny, S., Brannan, J. M., & Brannan, G. D. (2022). Qualitative Study. National Library of Medicine. https://www.ncbi.nlm.nih.gov/books/NBK470395/

Wasti, S. P., Simkhada, P., Van Teijlingen, E., Sathian, B., & Banerjee, I. (2022). The Growing Importance of Mixed-Methods Research in Health. Nepal Journal of Epidemiology, 12(1), 1175-1178. https://doi.org/10.3126/nje.v12i1.43633

Zimmerman, P. P., Sladdin, I., Shaban, R. Z., Gilbert, J., & Brown, L. (2020). Factors Influencing Hand Hygiene Practice of Nursing Students: A Descriptive, Mixed-Methods Study. Nurse Education in Practice, 44, 102746. https://doi.org/10.1016/j.nepr.2020.102746

Appendix

Comparison Table of Methods and Designs