Secondary Research Article

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Q1 Study Selection

 

Verloo et al. (2017) conducted a systematic literature search to assess nursing interventions to improve medication adherence among discharged older adults. With the help of a medical librarian, the team was able to find articles using predefined search terms, search themes and several mash terms to conduct a stringent criterion of the study with specific dates. Two members of the research team also did a search by hand of articles that were relevant but were unpublished. Any discrepancies among the authors they would bring everyone in and agree or disagree on the study. The selected studies included controlled clinical trials and randomized clinical trials to elevate the effects of the nursing interventions of patients who were 65 years or older. The takeaway from this is that the criteria and inclusion and exclusion matched the intended purpose of the study. The strengths were the collection of articles by using a skilled librarian and the two individual members finding articles that were unpublished. I believe the weaknesses of the study is that the population is too narrow to determine if the results represents the population.

References

Verloo, H., Chiolero, A., Kiszio, B., Kampel, T., & Santschi, V. (2017). Nurse interventions to improve medication adherence among discharged older adults: A systematic review. Age & Ageing, 46(5), 747–754. https://doi.org/10.1093/ageing/afx076

 

 

 

 

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Question 2: Risk of Bias and data Extraction

Strengths of Data Extraction

The researchers employed a standardized data extraction technique. Standardization is essential in the manipulation and transformation of data in a consistent manner.  As such, the research articles used in the extraction of information contained author names, country, year of publication, participants’ characteristics, sample sizes, and follow-up durations. Standardization comes with several benefits. For instance, it enables the researcher to fish for more data that share the same concept that addresses the study problem. Nonetheless, it immensely reduces data variation that relates to the topic of concern. Through standardization, data extraction methods have been adopted to guide comparative and useful literature reviews.

Weaknesses of Data Extraction

Data extraction in this study is done separately. One major of this technique is that disagreements and conflicts often arise based on source findings.  Such often complicate literature review and analysis processes. This is because irrelevant or inaccurate data is added to vital data, a barrier to accurate information. Errors that arise and are not corrected by researchers often lead the study astray, giving out misleading conclusions of reviews. Whenever such errors go, undetected invalidity is almost inevitable. That said, data extraction needs to be more precise.  Data extraction techniques should give concrete in-depth evidence on related fields of study.

The Risk of Bias

Several factors increased the risk of biasness. One of such factors included the inability to conduct an official risk of bias assessment trial. The assessment test would have been performed using a checklist. The other factor that increased the risk of biasness was the lack of specific bias approaches for medical research. More so, false referencing formats used in the studies ascertains the risk of bias. Drawing conclusions to the research findings is unclear, therefore tricky.

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