Correction to: Establishing Trustworthiness Through Algorithmic Approaches to Qualitative Research (original) (raw)
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Establishing Trustworthiness Through Algorithmic Approaches to Qualitative Research
International Conference on Quantitative Ethnography, 2021
Establishing trustworthiness is a fundamental component of qualitative research. In the following paper, we document how combining natural language processing (NLP), with human analysis by researchers, can help analysts develop insights from qualitative data and establish trustworthiness for the analysis process. We document the affordances of such an approach to strengthen three specific aspects of trustworthiness in qualitative research: credibility, dependability, and confirmability. We illustrate this workflow and shed light on its implications for trustworthiness from our own, recent research study of educators' experiences with the 2020 COVID-19 pandemic; a context that compelled our research team to analyze our data efficiently to best aid the community, but also establish rigor and trustworthiness of our process.
Establishing trustworthiness in qualitative research
As the use of qualitative inquiry increases within the field of social work, researchers must consider the issue of establishing rigor in qualitative research. This article presents research procedures used in a study of autoethnographies that were written regarding the experience of being Jewish. In this project, the researchers utilized reflexivity, audit trail, triangulation by observer, peer debriefing, member check and prolonged engagement in order to manage the threats to trustworthiness as discussed by Padgett (1998). Implications of the project suggest that research procedures utilized by qualitative researchers to establish rigor are an important way to increase our confidence that the voice of the participants is heard, therefore fitting the mission of the social work profession.
The Pillars of Trustworthiness in Qualitative Research
Journal of Medicine, Surgery, and Public Health, 2024
The global medical and nursing research community has increasingly embraced qualitative research approaches, recognizing the additional benefits they provide to the investigation process. Qualitative research explores the intricate details of human behavior, attitudes, and experiences, emphasizing the exploration of nuances and context. Ensuring trustworthiness is crucial in establishing the credibility and reliability of qualitative findings. This includes elements such as credibility, transferability, dependability, and confirmability. Several papers have discussed concerns regarding the rigor of qualitative health services research and have provided guidelines and checklists for publishing and conducting qualitative research. The key criteria for ensuring the quality of qualitative research include credibility, achieved through extended involvement, persistent observation, and triangulation; transferability, achieved through comprehensive and detailed explanations; dependability, achieved through rigorous documentation and the creation of an audit trail; and confirmability, achieved through peer debriefing, member checking, and reflexive journaling. Establishing reliability in qualitative research is crucial for influencing future research paths and advancing cumulative knowledge. Trustworthy qualitative research findings are also important for informing policy decisions and improving the provision of services in various fields. While qualitative research has limitations, such as subjectivity and resource constraints, the methodical application of measures to ensure trustworthiness greatly enhances the precision and reliability of qualitative research. These measures also encourage transparency and critical evaluation by the scholarly community.
Journal of Organizational Change Management, 2021
Abstract: The implicit epistemic vice of ‘confirmation bias’ is widely regarded as undermining the trustworthiness of professional research endeavours, political discourse, policy formulation and implementation, and everyday reasoning. But from a variety of perspectives there is also an extensive literature which denies that this bias exists or that it is problematic. Focusing on qualitative analysis of causality, Part 1 first describes the major features and manifestations of confirmation bias and the threats to trustworthiness attributed to it. Secondly, it illustrates the adverse consequences of the bias through an analyses three confirmation biased based studies. Part 2 (under review) describes and critiques three ways in which the threats from that bias have been dismissed.
Organizational Research Methods, 2019
Many scholars have called for qualitative research to demonstrate transparency and trustworthiness in the data analysis process. Yet these processes, particularly within inductive research, often remain shrouded in mystery. We suggest that computer-aided/assisted qualitative data analysis software (CAQDAS) can support qualitative researchers in their efforts to present their analysis and findings in a transparent way, thus enhancing trustworthiness. To this end, we propose, describe, and illustrate working examples of six CAQDAS building blocks, three combined CAQDAS techniques, and two coder consistency checks. We argue that these techniques give researchers the language to write about their methods and findings in a transparent manner and that their appropriate use enhances a research project’s trustworthiness. Specific CAQDAS techniques are rarely discussed across an array of inductive research processes. Thus, we see this article as the beginning of a conversation about the util...
Trustworthiness in evaluation practice: An emphasis on the relational
Evaluation and Program Planning, 2007
As canons for trustworthiness developed explicitly in the discourse of qualitative inquiry, the emphasis was on procedural matters rather than fundamentally relational ones. A nod was made to the relational in such strategies as ''member checks'' but the issues of how the evaluator actually relates to participants and to the larger communities of practice and discourse-matters subsumed under moral principles and ethical standards-were often marginalized. This chapter posits that the first consideration in designing and conducting rigorous evaluation inquiry, and in critiquing the results of any research, should be the study's trustworthiness. Judging a study's trustworthiness, however, should focus on much more than procedural matters; it should also rely on moral principles and ethical standards which specifically address how we relate to an evaluation's participants. Central to these considerations are cross-cultural sensibilities about the nuanced meanings associated with any principles and standards. The chapter provides a theoretical framework for this position and offers two illustrative examples in the form of dialogues. r
Journal of Organizational Change Management, 2021
Part 1 described the major features and manifestations of confirmation bias and the threats to trustworthiness attributed to it. Part 2 describes and critiques three ways in which the threats from that bias have been dismissed. The dismissals considered-but rejected-are: (i) radical scepticism: the concept of 'bias' presupposes the possibility of validity/truth-a possibility scorned by radical sceptics, including in some versions of 'post-modernism'; (ii) consequentialism: explicitly partisan enquiry is advocated-desired research impact trumps commitment to evidence gathering and/or analysis impartiality; and (iii) denial: confirmation bias is not a problem, at least for field-based research, as such research is said to have a built-in immunity against the bias.
BMC Medical Education
Following publication of the original article [1], the authors identified an error in the #2 affiliation. The correct affiliation has been updated above. Also, they would like to correct the Methods section. The updated section is given below and the changes have been highlighted in bold typeface. Trustworthiness We applied four criteria proposed by Lincoln and Guba to evaluate trustworthiness, including credibility, dependability, conformability, and transferability [22]. Triangulation in the data collection and analysis, prolonged engagement (6 months), and maximum variance in sampling was performed to increase the data's credibility. Moreover, member checking was considered by giving some of the developed codes to the participants to assess the degree of consensus on the codes among the researchers and the participants. Parts of the transcripts, along with the extracted codes and categories, were sent to two external examiners to assess the data analysis process and provide dependability. Transferability was achieved through providing rich descriptions [22, 24]. The original article [1] has been corrected.
What Makes Research/Researchers Trustworthy? A workshop report
On 11th September 2011, the Public Engagement and Information Governance work streams of the Scottish Health Informatics Programme (SHIP) held a workshop to explore researchers’ perceptions of the role, relevance and functions of trust (or trustworthiness) in relation to research practices. This report summarises the discussion of this workshop.