Assess Validity Threats of Qualitative Research Designs Essay

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A Chart to Defend a Qualitative Research Design.

Validity Threats	How you will defend these threats	Sources cited
What are the plausible alternative interpretations and validity threats to your conclusions you might have about your topic?	Interpretations are based on participants’ subjectivity, a variety of experiences, and human senses. For example, one homeless young person shares information about his or her childhood and the conditions under which such results have been achieved. Another participant does not focus on the details and gives direct answers to the questions. In this case, alternative interpretations depend on how well the participants give explanations. There is no absolute truth in qualitative studies, and obtained data is a product of various situational factors, knowledge, and understanding of the problem. Validity threats in this case are researcher’s bias (knowledge and assumptions), reactivity (results of observations), and participant’s bias (honesty).	Kriukow (2018) Leung (2015) Roller and Lavrakas (2015)
How will you successfully defend against the plausible alternative interpretations?	Trustworthiness and credibility are the major means to avoid alternative interpretations in the study. Trustworthiness includes a procedural description of research goals, data collection, and analysis so the reader can follow the progression of the ideas. Credibility evaluates the truth value when the results correspond with the already established goals. The researcher explains that the same methods and qualitative data may be effective in other projects.	Hammarberg, Kirkman, and de Lacey (2016)
How will you successfully defend against validity threats to your conclusions?	Internal and external validity threats can be removed with the help of such credibility practices as triangulation, reflexivity, and verbatim quotations. Applicability is another instrument in terms of which the evaluation of validity is possible outside the current study. Consistency is the method the researcher may use to prove that the same results have already been achieved in other investigations.	Hammarberg et al. (2016)
In what ways can the data you have, or that you can potentially collect, challenge your ideas about your topic?	In a qualitative study, data collection may be challenged in several ways. First, people are free to rely on their own expectations regarding to their personal world, norms, and knowledge. Therefore, it is recommended to rely on the theoretical standpoint. Second, the researcher is not able to predict the behaviors of homeless youth as the major participants of the study. As a result, such challenges as the unwillingness to participate in communication, the lack of solid background knowledge, and the use of non-standard language can be identified in a working process.	Sutton and Austin (2015)
Why should the research community believe your results?	The research community must believe in the trustworthiness of the results because of the intentions to follow all of the standards, a properly developed structure of the study, and clearly explained goals and expectations. Qualitative research will include an appropriate design and instruments to gather and analyze the data. Definitions of new terms and real-life examples will be mutually developed in the study to prove their theoretical and practical appropriateness. Finally, direct communication with homeless youth should help discover some new experiences and mental health problems.	Sutton and Austin (2015)

Summary

The topic of the project is mental problems among homeless young people. The expected conclusions include the list of the most frequent and dangerous mental health concerns in the chosen population. Regarding the fact that a qualitative research design is applied to gather and analyze personal data, a researcher has to answer the question about how to defend against plausible alternative interpretations and validity threats can be developed. Interpretations in qualitative research are closely tied with human senses, experiences, and subjectivity (Leung, 2015). The researcher is not able to predict what kind of information participants want to share. It is necessary to deal with subjective opinions and various life experiences that prevent the development of absolute truth (Roller & Lavrakas, 2015). Validity threats are based on three major factors that may challenge the project development. They include researcher’s bias or the inability to avoid personal knowledge and experiences, reactivity or the intention to interpret observations, and participant’s bias or the way of how participants accept the reality (Kriukow, 2018). The task of the researcher is to make sure that the results do not contradict the goals and research questions.

There are many ways to improve the quality of the study under analysis. Communication with participants and the use of theoretical models are useful tools to achieve good results. However, to defend against validity threats and alternative interpretations, the researcher must use such instruments as trustworthiness, credibility, applicability, and consistency (Hammarberg, Kirkman, & de Lacey, 2016). These methods help to explain why the offered research goals and questions have meaning and need to be discussed. In addition, the chosen methods of data collection and analysis are effective, and the obtained results can be used in the future. Sutton and Austin (2015) underline that human experiences and interpretations may challenge the study, but the researcher’s confidence, decision-making, and critical thinking verify the results. When the time to defend the validity of the study comes, personal biases and background knowledge should be called into question to have enough time and space to focus on participants’ opinions and credible theories.

References

Hammarberg, K., Kirkman, M., & de Lacey, S. (2016). Qualitative research methods: When to use them and how to judge them. Human Reproduction, 31(3), 498-501.

Kriukow, J. (2018). Validity and reliability in qualitative research. Web.

Leung, L. (2015). Validity, reliability, and generalizability in qualitative research. Journal of Family Medicine and Primary Care, 4(3), 324-327.

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach. New York, NY: Guilford Publications.

Sutton, J., & Austin, Z. (2015). Qualitative research: Data collection, analysis, and management. The Canadian Journal of Hospital Pharmacy, 68(3), 226-231.

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