What are the various types of research bias in qualitative research? Give a solution to overcome these bias

In-Brief:

• In research, bias take place when regular or common errors introduced in selecting sampling or testing by supporting particular results or out come.
• Selection of samples occur when the presence of observations in the sample depends on the value of the variable of interest.
• Qualitative research is an descriptive scientific method of study to collect non-numeric data.

Introduction:

If it is the situation then samples are no longer randomly drawn from the population being studied, and any inferences or conclusions about that population are based on the samples selected will be biased. It involves characteristics, meanings and description of  particular object or study.  Most of the case researcher should handled objective type then it is difficult to separate from the complete data, means that maintaining the objectivity and avoid bias. Therefore qualitative research and Data analysis facing criticisms due to lack of transparency. There are many potential causes of bias in research. As a result vague results and wrong statements and conclusions are identified which leads to major damage especially in clinical and social researches. Basically, there are three types of bias such as information bias, selection bias and confounding bias.

Information bias:

Information bias may happed in the Data collection, observational, recall, recording and data handing which includes missing data also. It may also occur due to wrong classification.  Observational and missing data are more impact particularly those relying on self-reports and retrospective data collection. To over come these problem by taking care of using multiple source of data collection, use standard measurements to collect information like questionnaire automatic instruments for recording measurements.  Maintain similarities between the groups to collect information. Use study design tools for gathering information. An important element to minimize information bias is to ensure that blinding of intervention status (or exposure status in observational studies) is maintained while outcomes are measured and recorded.

Selection bias:

It occurs when comparison is made between competed study with the targeted population. it compares an association between coverage population and outcome of the population.  Some case it also involves risk factor such as health outcome differs in dropouts compared with study participants. In some situation its magnitude and direction of effect is very hard to determine.  To assess the degree of selection biases the researcher should consider random techniques when selecting the sub groups. Because any thing happened after randomization is due to chance cause. Baseline comparison between  intervention or exposure groups. Define exactly what procedure was followed to prevent prediction of future allocation based on the knowledge of previous allocation. It is more clear that selected subgroups are equivalent to the large population characteristics. Handled the missing data in a systematic way may leads to reduce bias.

Confounding bias:

Confounding bias occurs when experimental variables affects the control variables being studied therefore the results may not reflect the actual relationship exists between independent and dependent variables. That means exposure and outcome are influencing the an additional variable called confounder. Simply saying that when the person wants to prove a predetermined assumption.  These kind of biases mostly arises in epidemiology studies. This can be avoided by implementing randomization, study design, data analysis, restriction and matching etc.

Most of the cases the researcher is having the Questionnaire hypothesis that he should prefer particular outcome or expectations then he should trying to carryout his work to get the expected results which leads to the entire research process is bias. When the experiment or qualitative research is considering population point of view then he should be impartial so that the results are very significant. If it is quantitative research numerical values may not change until the researcher purposively adjust the results.

Ways to reduce the risk of bias:

In order to reduce the risk of bias the researcher should focus on human errors appeared in the process of research. Beside of the above three biases there are few other biases exists in the qualitative research such as channeling bias, interviewer bias, culture bias, chronology bias, performance bias, citation bias etc., once if you recognize and identify the various biases then it is easier to make measures to avoid the biases.

However, a complete unbiased is not possible, but can be reduced  to some extent. In research if the study is completely unbiased then it will be the ultimate qualitative research. But it can not be possible in all cases. Bias may occur at any stage of research. Most importantly the researcher should consider and outline all kinds possible biases will probably may occur in the experiment or study. in qualitative studies the researcher should maintain the records of every step of his research work.  He should be more concentrated on study plan, Sampling design in qualitative research methodology, sample size, qualitative data collection, questionnaire and surveys to avoid bias. A complete elimination or minimizing bias provide benefits to business, community and society. Publishing false statements can leads more harm than good to the people and organizations. Some times lack of resources and time may drives researchers to neglect these unfair practices.

Finally, the researcher should pay attention to objective, transparency, selecting participants, qualitative questioning, analysis ,reporting and writing manuscripts to minimize biases in the complete research process.  Qualitative research analysis more depends on researcher experience and judgment. Also he is trying to collect data for subjective point of view it may be unique to persons  or situation. Hence it is very difficult for the researcher to handle or avoid bias comparatively quantitative research. As there in quantitative research numerical values may not same in every situation. Therefore its always better to identify the bias exists in the research and try to predict what kind of bias is that having in our study and try to avoid the bias as much as possible. There are few general solutions to avoid bias is that take third person view, through understanding is required on the subject as well as study when comparison takes place, better to use people first language in questionnaire preparation, so that they can understand in proper way, be specific when writing about people etc.,

References:

• Collier, D., & Mahoney, J. (1996). Insights and pitfalls: Selection bias in qualitative research. World Politics, 49(1), 56-91.
• Novick, G. (2008). Is there a bias against telephone interviews in qualitative research?. Research in nursing & health, 31(4), 391-398.
• Buetow, S. (2019). Apophenia, unconscious bias and reflexivity in nursing qualitative research. International journal of nursing studies, 89, 8-13.