Data Quality

Construct validity, deals with concept operationalisation (i.e., defining a concept through a set of attributes or variable) in order to make the concept measurable through empirical observation. Construct validity can be caused by inadequate explication of constructs as well as mono-method bias. Moreover, Yin (2013) suggested that construct validity can be improved by using multiple data sources, conducting a member check on the case study report, and maintaining a chain of evidence. Based on these strategies, designing the case study to maintain the chain of evidence allows reviewers to trace from conclusions back to the initial research question, or from questions to the conclusions. Hence, having a member allow for correction, enhances the accuracy of the report and helps identify a range of competing perspectives.

In the case of internal validity, it is pronounced within the explanatory study, and not with the exploratory or descriptive study, to justify the causal relationship.

However, internal validity can be increased using methodological and data source triangulation. In addition, pattern matching could enhance internal validity by involving qualitative but logical deduction in which an empirically based pattern will be logically compared to a predicted pattern (Yin 2013). Similarly, external

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validity is concerned with determining whether the findings are generalizable to other cases. Threats to external validity include, the interaction of the causal relationship with units as well as context-dependent mediation. It has been argued that neither case is sufficient to reject or disprove propositions, and that several cases are more appropriate to demonstrate the accuracy of a theory (Yin 2013).

In other words, case studies are generalizable to theoretical propositions and not populations. With this view in mind, the researcher’s goal was to expand and provide analytical generalisation of the conceptual model within the rural context in South-East Nigeria, and not to suggest statistical generalisations by enumerating frequencies (Yin 2013, p.10). Reliability of this study, suggests that same results can be obtained by repeating the data collection procedure. In other words, other researchers in principle, can follow the same procedures and arrive at the same findings. Details of the reliability procedures are provided in the following section.

Data quality issues include the reliability, validity and generalisability of the data (Saunders et al. 2011).

4.5.1.1 Trustworthiness

When conducting research, trustworthiness and quality remain primary concerns.

The assumptions of interpretive inquiry propose some principles for enabling quality in such qualitative study. Such criteria were utilised in addressing the issue of trustworthiness in this research, according to Lincoln and Guba (1985) and Guba (1981).

4.5.1.2 Credibility

The researcher while upholding the truth value of the findings by using primary data and undertaking the study in its natural setting, accommodated the need to understand, in a holistic manner the complexity of the phenomenon under study.

In this study, the researcher carried out a member check by returning to rural communities in October 2015 and April 2016 to discuss with various individuals involved in the study in those rural communities. The process allowed the researcher to highlight emerging understanding, interpretations given to data, as well as show initial results to participants. These informal conversations occurred primarily at meetings, religious gatherings and whenever an appropriate

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opportunity presented itself. The gatekeepers, being crucial participants in the research facilitated a member check that was more formal than the former.

Likewise, the researcher's supervisory team reviewed the draft of the result as presented in Chapters 5 and 6, and the feedback that followed was instrumental in enhancing the quality of the research outcome and the revision of the CMIS model.

Several opportunities were utilised to share and present preliminary findings and conclusions at conferences (iDocQ 2014 in University of Glasgow, and iDocQ 2015, i3 Colloquium 2015 both in RGU) and article publication. The response to these attempts was positive and provided face validity (in the case of conferences) to the findings and conclusions by information science experts.

4.5.1.3 Transferability

The researcher addressed the applicability of the findings by conducting a case study research but acknowledged that the focus was not on statistical generalisation. The use of a small and unrepresented number of cases raises concern about the generalizability of qualitative research findings (Yin 2013). The reason lies in the fact that, the use of qualitative techniques is not enough to make statistical generalisations about the entire population where the sample was drawn because the sample is usually, small and unrepresentative of the cases especially in a single case design (Yin 2003). However, Bryman (1998) argues that within a case study, different variables, people and activities are examined, unlike the survey sample which is restricted to a locality. Saunders et al. (2011) added that a well-completed and rigorous case study is more likely to be useful in other contexts. This study uses some approaches to address the generalisability concern. One method relates to the adoption of a cross-sectional sampling style involving men with different demographic attributes, experiences and cultural orientations across the fifteen senatorial zones in South-East Nigeria to be examined.

However, adopting cross-sectional sampling across multiple cases might be one way to provide case heterogeneity (mixed characteristics) from the cases, and provide a good representation of the population across the setting. One advantage of having a diversity of opinions is the amount of information it provides. Another

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benefit is the enhanced robustness of the findings of participants’ perceptions, culture and direct experiences with the phenomenon. The non-probability sampling technique used in this study allowed for in-depth examination of the situation across the cases (i.e. their information behaviour, cultural orientation and experience with health information around prostate cancer). The interrelatedness of the study to the existing theoretical model (i.e. the Johnson's (1997) CMIS), demonstrates that the findings have a broader theoretical significance (Marshall and Rossman 1999). The applicability of the CMIS model was examined by the researcher in the context of this study to establish its appropriateness, and where it is not all-encompassing, the researcher suggested possible modifications allowing theoretical propositions to be advanced in a manner that can be tested in others similar contexts.

4.5.1.4 Dependability

The researcher ensured that the methods and methodological choices employed in the research design were accurately and appropriately documented. To produce quality, reliable and robust study, the researcher employed several processes.

These processes include systematic research design; use of appropriate data collection techniques; theory-based data analysis (e.g. using thematic analysis about the CMIS framework); and communicating findings (e.g. publications, thesis) (Creswell 2007).

Therefore, to ensure and improve the reliability and validity of the data in this current study, a culturally acceptable native language was adopted for this research. The researcher demonstrated knowledge of the research topic and the context of the study. Before beginning the data collection process, eligible participants were briefed about the aim of the study, and their consent to participate in the study was sought as well as an explanation of the various data handling measures adopted to ensure data protection and confidentiality. For example, the participants were made aware that their responses were recorded and stored in secured devices accessible to only the researcher. Assurance of anonymity was given that whatever the participant said would not be linked directly to their identities.

The participants were assured that any confidential information of the participants

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was not the focus of this study as well as the anonymity assurance increased the level of confidence and trustworthiness of the researcher and reduced the possibility of response bias. The location for the data collection process was examined for its appropriateness against interference and comfortability as these factors could influence the quality of the data (Saunders et al. 2011). The safety, comfort and quietness of the location were crucial to the choice of the place to preserve the quality of the recordings. Additionally, the researcher appeared in acceptable but casual clothing that aligns with the style of dress of those in rural communities (Robson 2002). The use of open-ended questions also helped to reduce bias (Easterby-Smith, Thorpe and Jackson 2008).

4.5.1.5 Confirmity (or Neutrality)

The researcher ensured absolute neutrality by conducting the study without any preconceived idea to allow for findings that emanated solely from the data, and not from bias, motivation, interest or the perspective of the researcher.

4.5.1.6 Procedure Adopted to Ensure Data Quality:

High-quality data presents the bedrock for building a holistic knowledge of the subject area, and this remained one of the top priorities of the researcher.

Therefore, the researcher considered several procedures to assist in collecting appropriate and high-quality data. The researcher applied systemic processes for the collection of data from high-quality sources. The following processes were put in place for managing the huge amount of data that was being gathered:

• Prolonged engagement: The researcher regularly attended cultural gatherings (e.g. meetings, festivals and court) as a non-active participant (i.e., participant observer) who simply observed how the events unfolded.

Through regular attendance to these gathering, the level of familiarity between the researcher and the participants increased, thus reducing any possible effect on the process and giving the researcher the opportunity to collect and analyse data from these gatherings. By prolonged engagement, the researcher could develop an understanding of the essential modes or pattern of interaction.

• Interview Recording and Transcription: Using recording equipment to capture the interview sessions provided the researcher with the opportunity

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to access the exact words and verbal expressions of the participants without limit. Furthermore, the recorded interview provided reliable data rather than depending solely on post-interview notes which may not capture some essential details. Recording the interview meant that the researcher could listen to the interview over and over whenever necessary throughout the research process especially during the data analysis process to keep a check on the appropriateness of the researcher's interpretation.

• Use of Primary data source and Purposeful sampling: The researcher used primary data (rural men) instead of secondary data. The data used in this study came directly from the men in rural South-East Nigeria in each of the selected rural communities. Adopting the participant's observation method further provided the researcher with the opportunity to experience and observe the interaction of this population with the phenomenon under study. Another procedure used to ensure high-quality data was collected involving the use of purposeful sampling to select primary data sources who are information-rich experts in the context of interest. These key subjects and sources helped in ensuring that the data gathered was fit for purpose.

• Collection of detailed contextual information: A primary concern was to develop a detailed description of the context in which the phenomenon occurred. Providing the contextual detail was particularly important because of the CMIS model that directed the researcher to look at the background factors (e.g. demography) as part of the context for understanding how these influencing factors inform the health information behaviour of rural men. The researcher collected these contextual details through the interviews, observations and focus group discussion.

• Data management controls: The researcher implemented data management procedures such as storing the data in a secured location (e.g.

a personal computer with password), attaching the transcribed interviews with all the details in the NVivo software and maintaining a regular backup throughout the research process. This data management controls assisted in preserving the data and safeguarding the quality of the data collected by assuring rigour in the data collection, management and processing as well as, providing systematic access to the data.

175 4.5.2 Researcher's Experience

The researcher began this study with substantial experience of living in rural communities. The pre-existing knowledge and previous experience were useful in improving the study.

Specifically, the researcher's nationality enabled the researcher to communicate with the participants in their local language, thus bridging possible language barriers (e.g. dependent on interpreter) that might have been created. This attribute provided the basis for understanding and observing cultural aspects relevant to the phenomenon under study that might otherwise have gone unnoticed.

The researcher's previous contact with friends on social media had helped to meet many gatekeepers from the selected states and communities. Knowledge and keeping regular contact (through phone calls) with some of these gatekeepers assisted the researcher in identifying hard-to-reach communities and participants for this study. In addition, the participant's knowledge of these gatekeepers built their trust in the researcher and improved the researcher's credibility among the rural communities thus resulting in increased expressions of interest and access to participants, and willingness to participate in this study.

However, the researcher's previous experience also posed threats to this study.

However, this challenge was mitigated by bracketing off previous experience during the research process (Tufford and Newman 2012). In qualitative research, the researcher should begin the study without any preconceived ideas.

Preconceived ideas or assumptions can blind the researcher and act as a filter that inhibits them from seeing important and salient details in the phenomenon. The presence of preconceived ideas leads to researcher bias (Saunders et al. 2011) which threatens the credibility of the data and the overall trustworthiness of the research. Naturalistic (i.e. Interpretivist) research assumes that the researcher constructs findings inductively based on an in-depth interaction with the research subjects.

In this study, the researcher attempted to accommodate the stance of neutrality by bracketing off previous experience or pre-existing knowledge. Patton (1990, p.473) further suggests that other factors have the potential to distort the findings

176 of a research study. These factors include:

4.5.2.1 Influence of the researcher on what is studied

In the case of the influence of the researcher on what is studied, the previous experience of the researcher assisted to minimise this effect. The researcher had lived in rural communities for over a decade and had observed how men in rural South-East Nigeria interact with health information. The researcher's prolonged engagement (e.g. residing in the community) reduced the possibility of the researcher having a direct effect, for example, on the actual modality of conducting the various cultural gatherings the researcher attended during the participant’s observation process. In the case of the individual interviews and focus group discussions, the effect of the researcher on what or how the respondent responded was less controllable since the interviewee responded to the research questions as a respondent in a research study (i.e. choosing the manner deemed appropriate by the respondent). Furthermore, the researcher employed accepted interviewing practices such as asking non-leading questions, using the interview guide and requesting the respondents to speak from personal experience to minimise the effects of the researcher.

4.5.2.2 Influence of what is studied on the researcher

Qualitative research assumes that the researcher will be affected by what is being studied. The iterative and interactive nature of the research design implied that the researcher continually traversed between the process and activities (e.g. data collection, analysis) learning and understanding more about the phenomenon. The researcher being the primary instrument for data collection and analysis, should change over the course of the research. In this study, the researcher identified gaps in the data or new leads to follow based on the data collected. The researcher's evolving knowledge over the course of the study enabled the researcher to purposefully select participants to collect needed information for this study. The engagement of the researcher in many of the cultural gatherings allowed the researcher to maintain sensitivity with a broader range of activities and behaviours of rural men. However, the researcher was unduly affected by these gatherings to the detriment of data collection and analysis.

177 4.5.2.3 Researcher's competence

The final factor listed by Patton (1990), researcher competence, was addressed in several ways. Firstly, the researcher designed a systematic research study that included specific procedures for data collection, data management and data analysis. Adhering to the rigour of the study, enhanced the quality of the research findings. Secondly, the researcher had knowledge of and experience with the data collection activities used in this research. Thirdly, the researcher's nationality and origin, and experience within this context provided the foundation for dealing with the complex phenomenon and that were essential for the interviews, participant observation and understanding the primary source of data (rural men). Finally, the researcher had attended NVivo software training, seminars on qualitative research and conducted pilot study before this study.

In addition to these, the researcher presented the issues encountered in the research process and the methodological challenges which include, the scope of the study, the complexity of the phenomenon, and the data available for analysis and interpretation.