Clean language interviewing

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Clean language interviewing (CLI), sometimes shortened to clean interviewing, aims to maximise the reliability that information collected during an interview derives from the interviewee. CLI seeks to address some of the "threats to validity and reliability" [1] that can occur during an interview and to increase the "trustworthiness" of the data collected. [2] It does this by employing a technique that minimises the unintended introduction of interviewer content, assumption, leading question structure, presupposition, framing, priming, tacit metaphor and nonverbal aspects such as paralanguage and gesture that may compromise the authenticity of the data collected. [3]

Contents

At the same time clean language interviewing seeks to minimise common interviewee biases, such as the consistency effect, acquiescence bias and the friendliness effect which may mean an interviewee (unconsciously) looks for cues from the interviewer about how to answer. [4]

Furthermore, a systematic application of a 'cleanness rating' protocol provides a quantitive measure of adherence to interview guidelines and by extension the "confirmability" of the data collected. [5] [6]

CLI can be considered a phenomenologically-based interview method, similar in intent to neuro- and micro-phenomenology, [7] psycho-phenomenology, [8] phenomenography, [9] and Interpersonal Process Recall. [10] Clean interviewing can be seen as a method of operationalising the phenomenological aim of bracketing (epoché). [3]

CLI has the flexibility to be applied at four progressive levels of practice and principles: [11] :10
    A questioning technique
    A method of eliciting interviewee-generated metaphors
    A method of studying how people do things
    A coherent research strategy based on ‘clean’ principles.

CLI is also an integral part of a new action research methodology, Modelling Shared Reality which suggests that by paying careful attention to the language they use, qualitative researchers can reduce undesired influence and unintended bias during all stages of research—design, data gathering, analysis and reporting. [12]

History

Clean interviewing derived from clean language, the language model of therapeutic processes devised by David Grove [13] which has since found application in education, business, organisational change, health and academic research. [14]

Grove devised the principles of clean language in the 1980s and continued to develop a specific question set until his death in 2008. Although Owen first suggested applying clean language to phenomenological research in 1996, [15] it was not until 2010 that the first systematic research into the veracity of the method was conducted and published in the British Journal of Management. [16]

Another milestone is the publication of Clean Language Interviewing: Principles and Applications for Researchers and Practitioners. [17] It consists of four chapters introducing the method and eleven chapters detailing the application of CLI to fields such as: journalism in Malaysia; the experience of neurodifferent job applicants in the UK; parents of children diagnosed with encephalopathy in France; modelling an excellent case manager of neurodiverse offenders in the UK; conflict resolution with gang leaders in Haiti; management systems auditing in Japan; serious injury or fatality investigations in the US, among others.

Features

The features of clean interviewing include: the specificity of the technique; minimising unintended influence; data collection from the perspective of the interviewee; its applicability to in-depth interviews; elicitation of autogenic metaphors; investigating tacit knowledge; modelling mental models; and the verifiability of the adherence to the method. [16] [18] [19] [20]

CLI seeks to address the issues raised by research that demonstrates responses can materially be affected by: question construction; [21] [22] framing; [23] changing a single word; [24] [25] introduced metaphors; [26] [27] presupposition; [28] and the nonverbal behaviour of the interviewer such as paralanguage [29] and gesture. [30] Furthermore, in these studies, not only did the subjects show little or no awareness of being subtly and systematically influenced, many reported their answers with a high degree of confidence. [31]

The amount of training required to become a proficient interviewer is commonly underestimated [32] [33] and because of the rigour of the CLI technique, training and practice are required to become a competent clean language interviewer. [20] [16]

Cleanness rating

Roulston maintains "researchers must demonstrate the quality of their work in ways that are commensurate with their assumptions about their use of interviews" [34] :193 yet systematic methods for assessing the reliability and validity of the data collected during an interview are noticeably absent from published research. [35]

A "cleanness rating" can be used to measure the proportion of 'clean' to 'leading' interviewer interventions and hence the authenticity or trustworthiness of the data collected (i.e. how much is sourced in the interviewee's lexicon and logic). “The principal benefit of the rating is to enhance reflexivity” and contribute to “methodological transparency by enabling researchers to report on confirmability”. [36] :19

The rating was created in 2011 [16] and subsequently extended and formalised. An independent examination of interview transcripts allocates one of six categories (Classically clean; Clean repeat; Contextually clean; Mildly leading; Strongly leading; Other) to every question or statement made by the interviewer. The tabulated results are used to arrive at a summary assessment for each interview. [36]

Interviewers experienced in CLI can consistently achieve over 85% of 'clean' interventions. [18] [5] Whereas as many as two-thirds of the questions asked by an untrained interviewer may be 'leading'. [20] An inter-rater reliability analysis of 19 interviews from five research studies demonstrated substantial agreement among raters with an average intraclass correlation coefficient of 0.72 (95% CI). [5]

Critique

The assumption that interviewers can minimise their influence on the collection of data has been questioned for several decades [37] and the social constructivist school claims all knowledge is co-constructed. [38] Practitioners of CLI do not claim it does not influence nor that it is "non-directive". [39] They acknowledge that the interviewer's role is to set the overall purpose and direct the general flow of the interview [1] and they emphasise that all questions, including clean questions, set frames, contain presuppositions and invite the interviewee to attend to certain aspects of his or her experience. [14] Clean questions aim to stay within the lexicon and inherent logic expressed by the interviewee and leave them maximally free to answer from within his or her frames of reference. Tosey maintains that, "accounts are co-constructed through the process of selecting and asking questions. At the same time, Clean Language [Interviewing] aims to minimise the co-construction of the content." [3] :205

In inexperienced hands the questions may “feel scripted, mechanical and inappropriately therapeutic” [40] and the "guidelines may be quite hard to follow, and rub up against a tension between sustaining neutrality and developing rapport” yet still “invite interviewees to talk about their inner world in their own way which could ideally create openness”. [41]

As yet there has been no comprehensive test of the premise that interviews with a high cleanness rating result in higher quality data. Rather, an interview with a low cleanness rating may raise questions about compliance with research protocols and doubts about the authorship of the data collected.

Other forms of interviewing would be more appropriate where the researcher intentionally aims for the 'co-construction of meaning' or to challenge and change the understandings of participants, as in 'transformative interviews'. [34]

Some critics have maintained that the metaphor 'clean' is pejorative to other methods. Grove settled on the metaphor after discovering how others – including Carl Rogers the originator of "non-directive therapy" [42] – (unwittingly) 'contaminate' another person's perceptions with introduced content and presupposition

Applications

While clean interviewing is ideally suited to research, it has also been used by police interviewers, critical incident investigators and in commercial projects such as requirements gathering, market research and organisational change. There is scope for it to be applied in fields such as cognitive task analysis [43] and Naturalistic decision-making.

Examples of published research include:

In addition clean interviewing has been used in a range of PhD research topics:

Notes

  1. 1 2 Seidman, 2006
  2. Lincoln & Guba, 1985
  3. 1 2 3 Tosey, 2015
  4. Podsakoff et al., 2003
  5. 1 2 3 Nehyba & Lawley, 2020
  6. Jensen, 2008
  7. Petitmengin, 2017
  8. Mathison & Tosey, 2010
  9. Reid & Solomonides, 2007
  10. Larson et al., 2008
  11. Tosey, Cairns-Lee & Lawley, 2022
  12. 1 2 van Helsdingen & Lawley, 2012
  13. Grove & Panzer, 1989
  14. 1 2 Lawley & Tompkins, 2000
  15. Owen, 1996
  16. 1 2 3 4 5 Tosey, Lawley & Meese, 2014
  17. Cairns-Lee, Lawley & Tosey, 2022
  18. 1 2 Lawley, 2017
  19. 1 2 Linder-Pelz & Lawley, 2015
  20. 1 2 3 4 Nehyba & Svojanovsky, 2017
  21. Loftus & Palmer, 1974
  22. Harris, 1973
  23. Tversky & Kahneman, 1981
  24. Loftus & Zanni, 1975
  25. Heritage et al., 2007
  26. Thibodeau & Boroditsky, 2011
  27. Thibideau & Boroditsky, 2013
  28. Loftus, 1975
  29. Duncan et al., 1969
  30. Gurney et al., 2013
  31. Loftus & Hoffman, 1989
  32. Cho, 2014
  33. Kvale & Brinkmann, 2014
  34. 1 2 Roulston, 2010
  35. Mann, 2010
  36. 1 2 Cairns-Lee, Lawley & Tosey, 2021
  37. Mishler, 1986
  38. Silverman, 2006
  39. Rogers, 1945
  40. Buetow, 2013, p.53
  41. Langley & Meziani, 2020, p.11
  42. Tompkins & Lawley, 1996
  43. Clark et al., 2007
  44. Cáscová, 2015
  45. Lawley & Linder-Pelz, 2016
  46. Cairns-Lee, 2015
  47. Janssen et al., 2014
  48. Akbari, 2013
  49. Nixon & Walker, 2009
  50. Snoddon, 2005
  51. Sanders et al., 2018
  52. van Schuppen, 2021
  53. Conway, 2019
  54. Sinclair, 2019
  55. Walker, 2021
  56. Philmon, 2019
  57. Calderwood, 2017
  58. Hanley, 2018
  59. Cairns-Lee, 2017
  60. Munsoor, 2018
  61. Pickerden, 2013
  62. Vanson, 2011

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