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Health, Medicine, Nursing
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Qualitative Research Analysis – Diabetes and Personal Habits

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Module 4 SLP assignment is to write a 3-page essay in which the following are addressed:
Identify an applicable data analysis technique that will be used to analyze the qualitative data. Include one of the following techniques in the discussion: open and/or axial coding, cross-case analysis, member checking, or other strategy (Refer to Module 4 Homepage and Background literature references for helpful content information.)
Develop a rationale and justification for the data analysis strategy selected. (Present a logical sequence of ideas to explain)
Analyze the qualitative data (be sure to include the two steps below, as well as other procedures as identified within the data analysis strategy):
Code the qualitative data and organize and present it in a Microsoft Excel sheet.
Create a matrix that categorizes the data.
As a culmination of data analysis, identify any patterns and themes that may exist among the data collected. Describe the findings. Do the findings answer the qualitative research question(s)?
Demonstrate understanding of context and purpose of the assignment by bringing all required elements (described above) to the discussion.
IMPORTANT NOTE: For samples of coding and matrices please review:
Qualitative Data Analysis
Schneider, D. (2005). Qualitative data analysis. TECFA: University of Geneva. Retrieved August 25, 2019 from
http://tecfa(dot)unige(dot)ch/guides/methodo/edu-tech/slides/analysis-quali.pdf
Analyzing Qualitative Data
Taylor-Powell, E. & Renner, M. (2003). Analyzing qualitative data. Program Development and Evaluation, 1-12. Retrieved August 25, 2019 from https://cdn(dot)shopify(dot)com/s/files/1/0145/8808/4272/files/G3658-12.pdf
These documents can be accessed through the Presentation Folder.
Dunn, P. J., Margaritis, V., & Anderson, C. L. (2017). Use of grounded theory in cardiovascular research. The Qualitative Report, 22(1), 197-212.
Mundt, S., & Briggs, S. (2016). HIV-related stigma and discrimination in the New Zealand healthcare setting: A mixed-methods study. Sexual Health (Online), 13(6), 582. https://doi(dot)org/10.1071/SH16063

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Qualitative Research Analysis – Diabetes and Personal Habits
Your Name
Subject and Section
Professor’s Name
March 14, 2023
Based on the information provided, open coding is the most applicable data analysis technique for this study. Open coding is a qualitative data analysis technique that involves the breaking down of qualitative data into smaller segments, known as codes. This technique is appropriate for analyzing data from different sources and allows for the discovery of new themes and concepts that may emerge from the data. Open coding is suitable for analyzing data from individuals who may have diverse experiences with a particular phenomenon, such as diabetes.
Rationale and Justification
The open coding technique is suitable for this study because it allows for the identification of new themes and concepts that may emerge from the data. Additionally, open coding is a flexible technique that can be used to analyze data from different sources, including interview transcripts and written responses (Deterding & Waters, 2021). Diabetes is a complex disease that affects people differently, and using open coding will allow for a more in-depth analysis of the participants' experiences and perceptions (Ritholz et al., 2022).
Analysis of Qualitative Data
The qualitative data from the participants were coded and organized in a Microsoft Excel sheet. The data were categorized into themes and sub-themes. The themes that emerged from the data include (1) Diabetes Management Strategies, (2) Challenges in Diabetes Management, (3) Social Support, and (4) Access to Healthcare.
Diabetes Management Strategies
All participants reported using a combination of medication and dietary changes to manage their diabetes. Some participants reported following a low-carb, high-protein, or high-fiber diet. In contrast, others reported needing help to maintain a healthy diet due to the nature of their job or lack of access to healthy food options. Some participants reported engaging in regular exercise, while others reported finding it challenging to incorporate exercise into their daily routines.
Challenges in Diabetes Management
Participants reported various challenges in managing their diabetes, including feeling overwhelmed with the constant monitoring and self-management of blood sugar levels, stigmatized and judged by others for their condition, and struggling to make healthy lifestyle changes due to the lack of support and resources available in their community (Seo & Song, 2021).
Social Support
Participants reported receiving varying levels of social support from their family, friends, and healthcare providers. Some participants reported receiving adequate support, while others reported feeling isolated and unsupported in their diabetes management journey.
Access to Healthcare
Participants reported varying levels of access to healthcare, with some reporting access to affordable healthcare and others reporting challenges due to financial constraints or geographic location.
Findings
The qualitative data analysis findings suggest that diabetes management is a complex and multifaceted issue that affects individuals differently. Participants reported using a combination of medicatio...
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