Biases Are Factors Which Affects The True Results Of Any Research Study

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Biases are factors which affects the true results of any research study. Ellis (2010) suggests a carefully designed study should be free of bias but are inevitable in reality. Firstly, in Chilver’s et al’s (2001) paper, patients were allowed to complete the data collection questionnaires at home which could result to bias. This is because there is no guarantee that patients completed the forms themselves (barns and groove 2003) Furthermore, there is a potential for sampling bias as some of the participants were allowed to choose the treatment they received. Bowling (2009) argue that self selection by participants in any research sampling process will invariably constitute a bias. Sampling bias is also evident in the unequal size of the…show more content…
Contrary to Johnson & Wakefield’s (2004) claims that any good study should be independent of its researcher, the design strategy and recruitment in this study, is targeted at this expert group for obvious reasons; however, one could argue by virtue of their educational and professional alliance, that assumptions and preferences could have been made which could also have influenced the true nature of their data and the overall study outcome (Holloway 2008). 150 words ======================================================================= 2c An extensive body of literature on research methodology clearly indicates an inconclusive debate about the relative merits of qualitative and quantitative research strategies with the majority contending that both have advantages and drawbacks Fineout-Overholt & Melnyk (2011). Quantitative research is by its very nature deductive. It uses scientific methods to uncover the processes by which both physical and human events occur (Ellis 2010). It reduces complex behaviour to a simple set of variables that offer the possibility of identifying cause- and- effect relationship (Sim & Comerasamy 2013). Quantitative research according to Gournay (2001) takes a higher position in the hierarchy of evidence. A typical example is the Randomised control trial (RCT).However, in healthcare, quantitative research is sometimes indicted for being rigid and devoid of human
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