Question

Discuss sources of bias for both quantitative and qualitative research. For quantitative research, be sure to address both random and systematic bias. You may use examples from the articles you selected as illustrations of bias and/or preventing bias.

Answer 1

The main aim of a researcher is to eliminate or reduce bias and during the research study a bias is a force that can cause fault in the outcome. The integrity of the study was ensured through bias elimination. Bias is a systematic deviation and it can influence, whether intentional or unintentional, that misrepresents the evidence and prevents unprejudiced consideration of a question and therefore affects the validity and integrity of the study.

In qualitative studies, management of bias is a major challenge secondary to the variables associated with the interviewer and the interviewee. Reviewing the different types of bias and being mindful of the characteristics in quantitative and qualitative research can help to ensure the level of bias is at best kept to a minimum. The types identified include attrition, measurement, performance, and publication and selection biases. No study or researcher even at their best effort can avoid all bias from surfacing in their studies. Methods to help decrease the degree of bias entertain including withdrawn participants and being transparent with the results. Double blinding of the investigator, the participants and outcome assessors in a study will aid in decreasing “Measurement” bias. Standardization of “care protocols” along with blinding will protect against “Performance” bias. The inclusion of unpublished works and foreign language studies will limit the likelihood of “Publication” bias. Concealment of patients’ allocation to a particular group and randomization of a large sample size will decrease “Selection” biases.

Random bias is an error that has equal probability of being too high or too low. Almost all measurements have some degree of random bias. Random bias can, with enough trials, average itself out. Essentially all quantitative studies have some degree of random bias entangled in the fabric. However by repeating the research several times one can reach a mean standard deviation.

Systematic bias is an error that tends towards being too high or too low. Systematic bias does average out with repeated trials. These types of errors can be studied through inter-comparisons, calibrations, and error propagation but the “truth” is difficult to ascertain.

Both random and systematic biases can threaten the study’s end product validity and researchers credibility. However, by determining random errors by utilizing statistical analysis the researcher can be astute to the challenges. Systematic biases can arise from innumerable complex human factors and are difficult to determine.

References:

Krishna, R., Maithreyi, R., & Surapaneni, K. (2010).Journal of Clinical and Diagnostic Research. Research Bias: A Review for Medical Students. Retrieved from http://www.jcdr.net/articles/PDF/677/565-815_E(C)_F(P)_R(P)_PF_P.pdf

Polit, D., & Tetano-Beck, C. (2012). Nursing Research: Generating and Assessing Evidence for Nursing Practice (Tenth ed.). Philadelphia, PA: Wolters Kluwer.