Validity in qualitative research

From traditional validity testing in quantitative research study, scholars have initiated determination of validity in qualitative studies as well (Golafshani 2003). However, according to Creswell & Miller (2000), the task of evaluating validity is challenging on many levels given the plethora of perspectives given by different authors at different time periods. For instance:

  • Maxwell’s (1992) five types,
  • Lather’s (1993) four frames and
  • Schwandt’s (1997) four positions.

Philosophical paradigms and validity in qualitative research

Taking all these varying perspective together validity in qualitative research can be defined as the accuracy in the account of the participants to their realities of the social phenomena and its credibility to them. Similarly, the procedures of establishing validity essentially depend on the philosophical paradigm of the study.  Some of the paradigms are summed up in the following table:

Paradigm assumptions/Lens Post-positivist or Systematic Paradigm Constructivist Paradigm Critical Paradigm
Lens of the Researcher Triangulation Disconfirming Evidence Researcher reflexivity
Lens of Study Participants Member checking Prolonged engagement in the field Collaboration
Lens of the People external to the study (Readers/Reviewers) The audit trail Thick, rich description Peer debriefing

Although, philosophical paradigm assumes utmost importance in determining the validity criteria and process within a qualitative research. However explaining each of them will make the article extensively and complicated to understand for a beginner. Furthermore, to make it easier to understand, it can be said that, unlike quantitative research where statistical or experimental methods are applied to ensure validity, qualitative studies are validated through ‘trustworthiness’ and ‘rigor’ (Lincoln & Guba 1982; Lincoln & Guba 1985; Nahid Golafshani 2003; Maxwell 2005; Leung 2015). This is dependent on truth value, consistency/neutrality and applicability (Noble & Smith 2015).

Strategies to test validity in qualitative research

The strategies considered to maintain this trustworthiness and rigor therefore ensuring quality and validity in qualitative research are presented in the following steps (Sandelowski (1993); Long & Johnson (2000); Lincoln & Guba (1985); Fraser & Greenhalgh (2001); Slevin (2002); Morse et al. (2002)):

  • Accounting for personal biases, so that the findings are not influenced.
  • Acknowledging biases in sampling and critical reflection of methods, ensuring sufficient depth and relevance of data collection and analysis.
  • Establishing a comparison to check the similarities and dissimilarities while recording varied perspectives.
  • Thorough record keeping, ensuring a clear decision trail and transparency in data interpretations.
  • Including rich and thick verbatim descriptions of participants’ accounts to support findings.
  • Clarity of thought process during data analysis and interpretations.
  • Validation through respondents, by inviting them to cross check the presentation of the transcripts along with the themes and concepts and adequately reflecting the issue investigated.
  • In addition engaging peers to reduce research bias.
  • Triangulation of data through various methods and perspectives thereby producing a comprehensive set of findings.

Hence, it can be opined that to validate the qualitative research there is no universally accepted path. However, the above strategies presented a summarised version, which can be pondered upon, while applying in practice and also while writing the process in final research document.


  • Creswell, J.W. & Miller, D.L., 2000. Determining Validity in Qualitative Inquiry. Theory Into Practice, 39(3), pp.124–130.
  • Drost, E.A., 2011. Validity and Reliability in Social Science Research. Education Research and Perspectives, 38(1), pp.115–123.
  • Fraser, S. & Greenhalgh, T., 2001. Coping with complexity: educating for capability. BMJ, 323, pp.799–803.
  • Glyn Winter, 2000. A Comparative Discussion of the Notion of “Validity” in Qualitative and Quantitative Research. The Qualitative Report, 4(4). Available at:
  • Kothari, C.R., 2012. Research Methodology: An introduction. In Research Methodology: Methods and Techniques. p. 418.
  • Leung, L., 2015. Validity, reliability, and generalizability in qualitative research. Journal of family medicine and primary care, 4(3), pp.324–7. Available at: [Accessed July 11, 2016].
  • Lincoln, Y.S. & Guba, E.G., 1982. ESTABLISHING. DEPENDABILITY AND tl:ONFIRMABILITY IN NATURALISTIC INQUIRY THROUGH AN AUDIT. In American Educational Research Association Annual Meeting, New York. New York: U.S. Department of Education, p. 31. Available at: [Accessed October 21, 2015].
  • Lincoln, Y.S. & Guba, E.G., 1985. Naturalistic Inquiry, Beverly Hills, CA: SAGE Publication.
  • Long, T. & Johnson, M., 2000. Rigour, reliability and validity in qualitative research. Clin Eff Nurs, 4, pp.30–37.
  • Maxwell, J.A., 2005. Qualitative Research Design: An Interactive Approach, SAGE Publications. Available at: [Accessed May 20, 2015].
  • Morse, J., Barrett, M. & Mayam, M., 2002. Verification strategies for establishing reliability validity in qualitative research. Int J Qual Res, 1, pp.1–19.
  • Nahid Golafshani, 2003. Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8(4), pp.597–607.
  • Noble, H. & Smith, J., 2015. Issues of validity and reliability in qualitative research. Evidence Based Nursing, 18(2), pp.34–35. Available at: [Accessed July 11, 2016].
  • Sandelowski, M., 1993. Rigor or rigor mortis: the problem of rigor in qualitative research revisited. Adv Nurs Sci, 16, pp.1–8.
  • Slevin, E., 2002. Enhancing the truthfulness, consistency, and transferability of a qualitative study: using a manifold of two approaches. Nurse Res, 7, pp.79–197.
  • Wainer, H. & Braun, H.I., 1988. Test validity, Hilldale, NJ: Lawrence Earlbaum Associates.
Measuring reliability of questionnaires
Determining validity while conducting a quantitative research

Priya Chetty

Partner at Project Guru
Priya is a master in business administration with majors in marketing and finance. She is fluent with data modelling, time series analysis, various regression models, forecasting and interpretation of the data. She has assisted data scientists, corporates, scholars in the field of finance, banking, economics and marketing.

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