Qualitative Data Quality and Trustworthiness Research Paper

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When it comes to qualitative research, scientists should draw specific attention to achieving the trustworthiness of data. This phenomenon is essential because it ensures that the study’s findings have scientific significance. That is why this checklist is created to provide individuals with the guideline to evaluate the data. The proposed list consists of four criteria, and each of them will offer three options to check data quality.

Credibility is the first criterion that this paper will cover. According to Amankwaa (2016), this phenomenon ensures that the study’s findings are valid. There exist multiple techniques to make research meet high credibility standards. They are:

  • prolonged engagement (researchers spend much time with respondents in their natural environment);
  • referential adequacy (portions of data are archived);
  • peer debriefing (independent peers offer their views on the data) (Forero et al., 2018).

Transferability is the second phenomenon that comprises the given checklist. This criterion ensures that the findings can be applied in other environments (Amankwaa, 2016). Researchers have three options to check their data for transferability. They are as follows:

  • thick description (shows to what extent the conclusions can be applied to other contexts);
  • data saturation (the data do not offer any new information);
  • purposive sampling (Forero et al., 2018).

Dependability is another element that is significant for checking the data’s trustworthiness. Amankwaa (2016) argues that this phenomenon ensures that it is possible to repeat the findings. Multiple procedures make it possible to assess the data dependability. They include:

  • inquiry audit (an external researcher examines the study);
  • an exhaustive description of the study protocol (all steps are outlined exhaustively);
  • inter-coder agreement (controls the coding accuracy) (Forero et al., 2018).

Confirmability is the final element that is included in the given checklist. Amankwaa (2016) explains that this criterion shows the extent to which the findings are free from researchers’ bias and motivation. Possible checks include:

  • triangulation (ensures that an account is rich and comprehensive (Amankwaa, 2016);
  • reflexivity (demonstrates researchers’ and participants’ thoughts about the study);
  • an audit trail (it is the detailed description of research steps taken).

References

Amankwaa, L. (2016). Creating protocols for trustworthiness in qualitative research. Journal of Cultural Diversity, 23(3), 121-127.

Forero, R., Nahidi, S., De Costa, J., Mohsin, M., Fitzgerald, G., Gibson, N., McCarty, S., & Aboagye-Sarfo, P. (2018). Application of four-dimension criteria to assess rigor of qualitative research in emergency medicine. BMC Health Services Research, 18. Web.

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IvyPanda. (2022, September 24). Qualitative Data Quality and Trustworthiness. https://ivypanda.com/essays/qualitative-data-quality-and-trustworthiness/

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"Qualitative Data Quality and Trustworthiness." IvyPanda, 24 Sept. 2022, ivypanda.com/essays/qualitative-data-quality-and-trustworthiness/.

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IvyPanda. (2022) 'Qualitative Data Quality and Trustworthiness'. 24 September.

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IvyPanda. 2022. "Qualitative Data Quality and Trustworthiness." September 24, 2022. https://ivypanda.com/essays/qualitative-data-quality-and-trustworthiness/.

1. IvyPanda. "Qualitative Data Quality and Trustworthiness." September 24, 2022. https://ivypanda.com/essays/qualitative-data-quality-and-trustworthiness/.


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IvyPanda. "Qualitative Data Quality and Trustworthiness." September 24, 2022. https://ivypanda.com/essays/qualitative-data-quality-and-trustworthiness/.

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