DQ: In your own words, describe personal and research bias and explain why bias is one of the main reasons for poor validity in research outcomes

 

 

Melnyk, B. M., & Fineout-Overholt, E. (2018). Evidence-based practice in nursing & healthcare: A guide to best practice. LWW.

Bias is when there is undue favor for or against a particular thing, person or group in an unfair way while discounting the obvious truth of the others or by distorting the truth or discarding the facts as presented either personally or in academic research (Oxford Dictionary, 2019). In any research, bias can happen at any time. This is when there is an error in the systematic way used to conduct the research. Such as in the study design, data collection, sampling, interventions, experiments and controls, as well as in analyzing and the reporting of results (Enago Academy, 2021). Bias is one of the reasons that research is not valid, it reduces the credibility and accuracy of the researcher. Some researchers include their personal beliefs which influences their methods hence they become impartial (Enago Academy, 2021). Most qualitative research is prone to emotional biases especially in the social, political, religious and psychological fields as compared to the scientific fields that deals with numbers and statistics (Enago Academy, 2021). There are different types of Biases starting with the design bias, data collection with selecting of samples and participants, analyzing the data, process bias and publication bias (Enago Academy, 2021). There are also other types of biases in research such as race bias, social class bias and gender bias (Alcalde-Rubio, Hernández-Aguado, Parker, Bueno-Vergara, & Chilet-Rosell, 2020). So, to reduce the possibility of bias in research, the researcher should be aware of themselves totally, widen their range of possibilities and sample participants, and be careful of choice of vocabulary (Enago Academy, 2021). There is also the observation bias known as the Hawthorne effect-when participants know that they are being observed by the researcher, they change their answers or behavior, confirmation bias- the researcher looks only for information or patterns to confirm their ideas while recall bias is when participants recall events which may be recalled in a distorted form (MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. (n.d.).

A quality improvement DPI project could be affected if they do not meet the comprehensive standard for inclusion in the research. Some DPI projects did not state a clear evidence gap and may involve so many different settings participants from different age ranges and then they end up not fully describing the implementation process or the implementation is not appropriate for all the age groups. Some did not fully describe their methods, intensity of activities of the participants or the implementers or the involvement of the site all that can lead to bias of the research. The credibility of the site will be affected and they may lose their accreditations and licenses. Also, patients may not want to go to that site any longer (Wells, Tamir, Gray, Naidoo, Bekhit, & Goldmann, 2018).

The article, Association between gender and stoke recurrence in ischemic stroke patients with high-grade carotid artery stenosis by Chen, Weng, Wu, & Huang, (2021) illustrates some of the biases that can discredit any research. In this article, a total of 372 participants were used of which 273 were males and only 99 were females. I feel that the ratio of males to females is a gender bias for the researcher to conclude that the male gender had a higher rate of increased risk for stroke recurrence compared to the female gender.  It the number for both was comparable then the readers may be willing to accept this research. Also, the article points out that some gender differences that was conducted in other research was pointed out but the article still remained confusing. Another bias is the sample size is small to conclude that the prevalence of stroke recurrence is higher in males-which may be caused by smoking in males-than females. Also, they had some unmeasured confounders that may have influenced their conclusions. This bias has led them to propose the need for aggressive treatments for males and females may be treated casually which may lead to serious injuries for the females. I believe that this bias has affected the validity of the research because the sample size is not representative of the entire groups of males or females. It could still be viable research for my DPI project because I will look at what worked or not and attempt to improve on it (Chen, Weng, Wu, & Huang, 2019).

 

References:

 

Alcalde-Rubio, L., Hernández-Aguado, I., Parker, L. A., Bueno-Vergara, E., & Chilet-Rosell, E. (2020). Gender disparities in clinical practice: Are there any solutions? Sc

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