The subject of quality in qualitative research has received much attention from academics, who have tried to develop best practice in this area (Creswell, 2007; Denzin & Lincoln, 2005). Seale (1999) believes that “research is a craft skill”; for researchers to produce valuable research, they have to learn how to select criteria suitable to their research by looking at different cases and conducting them at different times. Tracy (2010) suggests that a researcher should combine various paths and crafts to suit each study and its context. This researcher looked at the research criteria of “validity” and “reliability”, and considered the quality criteria for a field study approach.
3.7.1 Validity and reliability (credibility) in qualitative research
Schwandt (1997) defines validity as how accurately research reflects the reality of the social phenomena it studies and how acceptable it is to the groups it studies. Procedures to ensure
105
validity include strategies used by researchers to gain credibility for their studies and conclusions drawn from the gathered data (Hammersley & Atkinson, 1983). Tracy (2010) lists many criteria for research quality: catalytic validity (Lather, 1986); empathetic validity (Dadds, 2008);
crystallisation (Richardson, 2000); tacit knowledge (Altheide & Johnson, 1994); and transferability (Lincoln & Guba, 1985). Several scholars have also created models of validity, such as Maxwell’s five types (1992); Lather’s four frames (1993); and Schwandt’s four positions (1997) (Creswell & Miller, 2000, p. 124).
This research used the “Eight Big-Tent” criteria and “validity procedures within a qualitative lens and paradigm assumptions” to build research trustworthiness and enable investigation of correspondences between the research questions, literature, data collection procedures, and analysis (Morse et al., 2002). The reason for using these criteria was the need for a specific set of relevant quality criteria when using a particular paradigm (Tracy, 2010, p. 837). To emphasise validity procedures, Creswell and Miller (2000) stress “the lens the researchers choose to validate their studies” and how it illustrates the “researchers’ paradigm assumptions”. A two-dimensional framework makes it simpler for researchers to identify relevant criteria and evaluate what makes qualitative research effective in the sense of its validity.
3.7.2 Quality criteria
This research applied rich rigour and credibility, including thick description and triangulation methods adapted from Tracy (2010), who proposes eight criteria for high research quality. For
“validity procedures within a qualitative lens and paradigm assumptions”, Creswell and Miller (2000) suggest a number of validity procedures, three of which were appropriate to this study:
triangulation, prolonged engagement, and thick or rich description.
3.7.3 Strategies to establish quality
Accuracy, credibility and trustworthiness were achieved in this research through archiving material, being rigorous, and using triangulation of methods; prolonged engagement in the field;
and the use of thick, rich description (Creswell & Miller, 2000; Tracy, 2010). In terms of rigour, this research was rechecked for accuracy, relevance and level of detail. Triangulation, the use of different sources for data collections, theories and methods to ensure that they give the same conclusions (Denzin, 1978), was used to examine different views and therefore check the validity of the research. Another criterion, prolonged engagement in the field, was used to generate a better understanding of the cultural context by using participant observation and interviews.
Finally, thick, rich description was used to generate abundant detail in order to explore, interpret and analyse the data in a way that served to answer the research questions as fully as possible.
106 3.7.3.1 Ri ch ri gour
Quality is essential in qualitative research, and accuracy is central to quantitative research (Winter, 2000). Weick (2007, p. 16) defines “requisite variety” as the generation of sufficient richness of description and explanation in the research process in terms of abundance, sampling, and context. Rigour also supports richness in validity (Golafshani, 2003). To confirm the need for rigour in research, Tracy (2010, p. 841) raises four questions about the sufficiency of data:
“Are there enough data to support significant claims?”; “Did the researcher spend enough time gathering interesting and significant data?; “Is the context or sample appropriate, given the goals of the study?”; and “Did the researcher use appropriate procedures in terms of field note style, interview practices, and analysis procedures?”
Richness is an important element for supporting the quality of the research but it does not necessarily involve abundant data, if data are rare or unique. Generating a small amount of data can be qualitatively valid in particular circumstances (Scarduzio & Geist-Martin, 2008). In this research, rigour was applied to data collection and analysis. In fieldwork, researchers should take notes, as far as is possible, and rigour is evaluated by the number of observations and pages of notes collected. It helps the researcher understand the participants. In the interviews, rigour was judged by the number and breadth of the questions. In the analytical process, the number of pages of transcription was considered in terms of the accuracy of detail.
3.7.3.2 Credibilit y
For credibility, there are three strategies (Tracy, 2010): triangulation; thick description; and prolonged engagement in the field.
i) Triangulation
Triangulation is used in qualitative research as a way of ensuring data reliability. In this research, different data collection techniques were used and revealed the same conclusions (Denzin, 1970;
Creswell & Miller, 2000). The use of a triangulation process increases the validity of the data through cross-checking (Bloor, 1997).
ii) Thick description
This method establishes credibility by describing the setting, participants and themes of the study in rich detail (Creswell & Miller, 2000). Thick description involves rich cultural data which expand previously established meanings (Geertz, 1973). Complex data, including particular and surrounding data, should be provided (Geertz, 1973). This research achieved data complexity by providing enough detail about PLM value, management, and community participation to be able to draw a full set of conclusions. Moreover, the researcher encouraged interviewees to expand on
107
their responses by giving examples or referring to specific events to make the data more distinct and precise. These processes are called thick description (Geertz, 1973).
iii) Engagement in the field
The longer the observation period, the more likely it is that participants will trust the researcher.
This creates reliability and establishes rapport, enabling the willing sharing of information (Creswell & Miller, 2000). To achieve credibility, normally a researcher will stay in the field for three to six months in order to gather sufficient rich information (Creswell & Miller, 2000).
However, here, due to the specific context, one in which only three events involving PLMs took place, it was not appropriate to spend such a long period in the field, since little relevant data could be collected at other times. Although the time spent in the field was less than recommended for a typical study, the period spent collecting data during these events generated significant amounts of rich data in an intensive environment, which were recorded extensively (see Sections 3.4.2.2-3.4.2.3 & 3.4.3.1-3.4.3.2). Thus, although time in the field was limited, the strategies adopted for collecting and collating data give the study credibility in terms of the amount and quality of data collected.