Conformability Transferability Credibility

Trustworthiness of a Qualitative Study

According to Savin-Baden & Major (2013), a trustworthy qualitative study has qualities such as dependability, conformability, transferability, and credibility. Dependability entails the consistency of the research findings even if the same study was to be repeated by a different researcher. Hence, the dependability of a qualitative research involves the questioning of how the researcher has described the research process so clearly so it could be repeated to achieve the same results. Next, according to Ragin (2014), conformability of a qualitative research is concerned with the neutrality of the study, i.e. the extent to which the research findings are free of the researcher’s bias. It ensures that the researcher does not make any skewed/biased interpretations of the research findings (Palinks et al, 2015). On the other hand, transferability of a qualitative study questions the generalizability of the study results to a wider population (Ormston et al, 2014). It evaluates whether the findings can be applied to other contexts of practice. Lastly, a credible qualitative study is one that the researcher is confident in the accuracy of the results (Maxwell, 2012). It seeks to confirm whether the study results are a true depiction of what the data presented.


Research Rigor

According to Levis (2015), a rigorously done qualitative study is one whose results are reliable and valid. Nonetheless, Heaton (2008) acknowledge that determining the reliability of a qualitative study is difficult because, during the research process, the researcher’s subjectivity and creativity become part of the study. However, Gill et al (2008) opine that a reliable qualitative study can easily be replicated to obtain the same results. On the other hand, Elo & Kyngas (2008) and Creswell (2017) argue that the term ‘reliability’ in the context of a qualitative study may be misleading because such studies consider human behaviors and notions, constructs that are never static. Therefore, there is a need for a thorough evaluation of the research procedure before concluding that the study is reliable.

Contrastingly, there has been an unending debate over the concept of validity in the context of qualitative research. Part of the reason for such a controversy is that validity is based on mathematical data, evidence, and truth, yet these aspects are hard to come across in qualitative studies (Maxwell, 2012). Moreover, Ragin (2014) strongly believe that for data to be valid, it must be based on high-level accuracy. Interestingly though, Savin-Baden & Major (2013) asserts that there is no point in testing for validity in the qualitative study and instead, analysts should focus on authenticity and adequacy of the study. Nevertheless, Palinks et al (2015) point out that the validity can be applied in both qualitative and quantitative studies because it simply means investigating, theorizing and questioning the research findings – all these can be conducted both in qualitative and quantitative studies.

Part B: Sampling Methods

The researchers used convenient sampling to select head and neck cancer (HNC) patients as respondents to the study. The sampling method was explicitly and simply stated for any reader to understand. According to Barbour (2000), convenience sampling is a kind of non-probability sampling where a subset of the entire population under study is selected based on their availability and accessibility. A major advantage of convenience sampling is that participants can easily be accessed at a low cost and within a shorter period of time. However, it may lead to an underrepresentation of the population. When the population is underrepresented, the obtained results cannot be generalized to the entire population (Bowen, 2006).

Hendershot et al explicitly state that any HNC patient was eligible for interviews regardless of the status of their disease. This is a clear definition of the participants’ characteristics because any reader would know which kind of participants was involved. Also, if anyone wanted to repeat the same study, they would have a clear knowledge of the participant characteristics to be considered.

All the participants made an informed consent before participating in the interviews. According to Bentz & Shapiro (1998), informed consent enables the potential interviewee to have sufficient information about the research study before voluntarily agreeing to participate. Besides, other strengths of informed consent are that it informs the potential respondent of their discretion to withdraw from the study, potential risks, benefits of participating in the study, and any other relevant information that the respondent should have before participation (Heaton, 2008). However, some participants may not understand the research details, thus the researcher may have to spend much time explaining such details.
The researchers also gained a negotiated access to the samples, by applying for approval by the Institutional Review Board (IRB) of Emory University. According to Lacey et al (2016), such approvals improve the credibility of the study in the face of participants and helps in establishing the convenient time for the institution to allow patients participate in the study. Though, researchers may have to avail all the necessary documentation for such approvals to be made. This implies that much time will be spent organizing and availing all the necessary documents for scrutiny. However, once the documentation is all available, it will be easier to gain the approval. The study sought to investigate the attitudes and perceptions of HNC patients toward alternative cancer medicine (ACM). Therefore, as indicated in the study, HNC patients were the best source of the information sought by the researcher. HNC patients were at the best position to talk about their attitudes and experiences towards ACM.

Part C: Data Collection

The researchers have clearly stated that structured interview as their method of data collection. All the interviews were conducted by one interviewer and begun with open-ended questions then followed by probing. The researchers used semi-structured interviews as a method of data collection. According to Ridenour & Newman (2008), semi-structured interviews are developed in a manner that all the participants are asked to answer the same type of questions. These questions standardized nature of these questions enables the researcher to compare the responses thereby achieving effective data analysis (Rubin & Babbie, 2010). Besides, Suzanne (2016) points out that through semi-structured interviews, the researcher is always present to elaborate the questions so that the respondent to avoid misinterpretation of the research questions by the respondent.

However, even though interesting lines of information may emerge during the interview, an exploration of this information is limited because the respondent has to stick to the provided question (Tappen, 2010). An alternative could have been a less-structured in-depth interview, where the respondents are allowed to answer the questions by providing as many details as possible (Van Den Berg, 2017). However, according to Wiles et al (2016), lest structured interviews are only applicable in cases of few samples, because each session may take long hours to complete. The researchers indicate that the interviews were conducted in a private setting during routine appointments at the clinic. Conducting interviews in a private setting was appropriate as the participants could freely share their opinions anonymously (Denzin & Lincoln, 2005). They were at least assured of their privacy during the entire process. Moreover, the interview was conducted at a cancer treatment center (i.e. Winship Cancer Institute). This provided an opportunity for the researcher to encounter patients at different stages of HCN who have a variety of experience with alternative cancer medicine.

Moreover, the researchers noted the interview responses in the interview tool rather than recording them. According to Lacey et al (2016), a major advantage of note taking over tape recording is that the researcher is able to easily identify the main points and key information provided during the interview. Noteworthy, notes are more reliable because they are continuously taken during the interview session – as and when the interviewee gives answers to the questions asked. Also, according to Bentz & Shapiro (1998), note taking organizes and emphasizes information so that the researcher can easily transfer them for analysis. Besides, the researcher is able to indicate supporting points and easily relate them to the interview questions. But, transcribing recorded data may be time-consuming.

The researchers have also discussed, in detail, the concept of saturation of data. According to Ragin (2014), saturation refers to a point in the research process where no additional information is gained from further enquiry. In the present study, saturation was used to define the sample population and to mark the end of interview sessions. Hence, based on the concept of saturation, respondents were interviewed until no more new information was gathered. Specifically, it is mentioned that the interviews were conducted until there was a saturation of pre-defined codes such as interaction with HNC physician and attitudes towards alternative cancer medicine According to Barbour (2000), saturation indicates a point where any further information or data gathered becomes counter-productive. It is meant to save the interviewer’s and interviewee’s time because ideally, the interview would stop when no further useful information is obtained from additional interviews (Bowen, 2006). Here, the researchers also used the saturation point to determine their sample size (12). This indicates the flexibility of convenient sampling because the researchers were able to determine their sample size only after collecting enough data. But, according to Lacey et al (2016), it is often difficult to determine the saturation point of an interview process because there is always new information emerging from each interviewee. Part D: Data Analysis and Presentation
The researchers used both qualitative and quantitative methods to analyze data. These two methodologies are clearly and separately described in the study. For instance, it is mentioned that quantitative methods were used to calculate the frequency of use of alternative cancer medicine frequency of participant consultation with a physician over alternative cancer medicine, and the frequency of participant’s reported comfort with alternative cancer medicine. On the other hand, it is explicitly indicated that qualitative methods were used in developing a codebook for the analysis of participants’ attitude towards alternative cancer medicine. Lacey et al (2016) acknowledge that a clear description of data analysis procedure not only promoted the reliability of the study but also enables other researchers to duplicate the same research process and receive the similar outcome. It enables an easier use of the research information and interpretation of the research findings by other researchers or readers (Bowen, 2006).

It is also described that after the creation of a codebook, two investigators coded the interview data and combined similar codes into three major themes that described a separate type of attitude (i.e. positive or negative) towards CAM. This exemplifies a step-by-step description of the data analysis procedure, which can easily be followed by any reader. One advantage of codebooks is that it helps in the development of various data categories for easier analysis (Palinks et al, 2015). However, according to Ragin (2014), codebooks create a set of combined codes that make it difficult to corroborate themes. In this regard, Bentz & Shapiro (1998) point out that a proper description of data analysis promotes the reliability and transferability of the study. This is because users of the research information are interested in knowing how the study made particular conclusions and whether such conclusions can be achieved if a similar research study is conducted (Denzin & Lincoln, 2005).

Hendershot et al (2014) used themes to present their results. There is a clear description of how these themes were derived and one can follow from the first step of codebook creation, followed by coding of all the interviews, and then grouping the codes into three major themes. Consequently, any user of the research information has a clear understanding of how the themes were derived, thereby promoting research transparency (Denzin & Lincoln, 2005). In this regard, according to Levis (2015), a major strength of themes is that the researcher is able to easily identify specific and important chunks of data from a large data set thereby easily evaluating this data to answer the research questions. Though, the use of themes requires the researcher to have high skills of interpretation because themes to not occur within a theoretical framework (Ormston et al, 2014).

At some stage during the data analysis process, the researchers included an additional researcher to help in dispute resolution during the coding process. Often, researchers may differ on how to select and classify codes, and therefore to create a consensus, a third researcher is always invited. Based on Barbour (2000), inviting a third researcher to resolve disputes help in saving time and promoting the reliability of the final results by enhancing the accuracy of the coding process. The coding process could have been time-consuming especially due to the fact that the data have to be grouped before specific codes are developed (Maxwell, 2012). Similarly, inviting an additional researcher may mean additional costs incurred during the research process. Nonetheless, codes make easier to develop themes for further interpretation.

The researchers have also used extracts of the interview data to support their discussion. For instance, quotes from the interviews have been used to reinforce the arguments presented while discussing both negative and positive attitudes of the respondents towards alternative cancer medicine. Moreover, the researchers have used a combination of numbers and letters (for example, m5, f6, m11 and m10) to denote the source of each quote used in the results and discussion section. This enables the readers to identify the specific respondent who gave specific responses referred to in the text. Consequently, the study becomes more verifiable and reliable because readers can see that only the information collected from the respondents are used to make conclusions (Newell & Burnard, 2011). There is no mismatch between the quotes and the numbers. Every number identifies the exact quite within the study discussion, revealing the accuracy with which the researcher numbered them. In this regard, Levis (2015) suggest that when using numbers to represent quotes, each number should accurately match the intended quote because any slight difference would affect the accuracy of the findings. This has negative implications on the trustworthiness of the study. Therefore, in this case, it is important to avoid any confusion or mismatch between the quotes and the numbers.

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