Introduction
Diabetes mellitus is an illness of significant importance to the global health care system. Estimates by the International Diabetes Federation (IDF) show that as of 2014, a whopping 371 million people globally had diabetes, with China, India, and the united states having the highest numbers at 92.3 million, 63 million, and 24.1 million, in that order (IDF, 2014). Diabetes is also a leading cause of death, accounting for 4.8 million deaths globally in 2014 (IDF, 2014). Type 2 diabetes tends to be more prevalent among adults with obesity and sedentary lifestyle being identified as the key risk factors. Considering that diabetes is a chronic illness, self-management is therefore a fundamental aspect in its management. However, it is important that health care professionals play a key role in facilitating diabetes education, especially on the importance of self-care. Accordingly, the current paper seeks to explore whether nurses are active participants in educating diabetic patients on self-care or whether this should be a collaborative effort involving nurses and patients. Towards this end, the paper reviews two studies on the topic: a qualitative study and a quantitative study with the aim of contrasting the two research designs.
Summary
Both qualitative and quantitative research approaches differ in terms of the nature of information one gains from reading them. In a qualitative study, the key goal is to gain the opinion, understanding, and views of the target population regarding a given phenomenon. With regard to the qualitative study under review, the purpose of the study was to augment insights and evidence into diabetic patients’ perspectives regarding care delivered by practice nurses. In others words, the author endeavored to gather the views and opinions of diabetic patients on the care that they receive form the practice nurse (Beresford 2011). The study further sought to assess diabetic patients’ level of involvement in decision making regarding the care received from health practitioners in their own words.
On the other hand, the quantitative study under review is in the form of a proposal to examine the relationship between cultural beliefs and illness, healthcare provider and family support, and the behavior of type 2 diabetes patients among middle-aged individuals in rural Pakistan (Ansari, Hosseinzadeh & Zwar 2016). A key defining feature between qualitative and quantitative studies is that whereas a qualitative study is concerned with the opinions and views of the target population on a given phenomenon, a quantitative study seeks to draw correlation between various variables. The goal is to establish if a correlation exists between the identified variables. This then bring out a second difference between a qualitative and quantitative study namely, the tools for data collection and analysis.
The qualitative study by Beresford (2011) used interview questionnaire as the tool of data collection. This is important because it enables the researchers to design the interview questions in such a way as to allow participants to give their opinions on questions posed. In contrast, the quantitative study by Ansari et al (2016) plans on using a survey questionnaire to collect data from study participants. Owing to the quantitative nature of the study, the researchers have to ensure that the design of the questionnaire is such that it facilitates in the collection of quantitative data. Unlike a qualitative study, a quantitative study may also have study hypothesis that the researchers need to accept or reject based on the research findings of the quantitative data analysis. The two studies also differed in terms of tool of data analysis, with Beresford (2011) utilizing content analysis while Ansari et al (2016) planning to use the STATA Software.
Advantages and disadvantages of the two research approaches featured in the articles
Qualitative research
Qualitative research is advantageous in the sense that it affords the researcher freedom to unfold naturally in the study. In other words, the researcher is not restricted by the study design. The researcher also gains rich and detailed data such as comprehensive written data from participants regarding their perceptions of a phenomenon (Johansson, Risberg & Hamberg, 2013). On the other hand, qualitative research entails heavy involvement of the researcher in the research process, and this could see the researcher adopt a subjective view of participants and the study. The researcher is also likely to assume a biased view to the study and this could inform his/her interpretation of the study research, thereby skewing data collected. Qualitative research is time consuming as well.
Quantitative research
Since quantitative research allows the researcher to measure and analyze data, he/she gains an objective view of research findings. Also, quantitative research uses statistics to measure data and can thus be used in testing research hypotheses (Balnaves & Caputi, 2001). Conversely, quantitative research tends to ignore the context of the experiment or study. Also, the method does not study phenomenon in their natural setting. The method also involves a very large sample size.
Qualitative Research is not Real Science
Since qualitative research is focused on social meaning and context, and its impact on individuals, it is thus beneficial in social sciences. On the other hand, quantitative research is based on statistical analysis (Devetak, Glažar & Vogrinc, 2011). This results in reliable study findings owing to their strict adherence to reproducible scientific methods and high controls. Qualitative research is not based on hypothesis, but instead seeks to examine a broad area of research.
General Insights to Researchers
Qualitative studies may be used in the early phases of a study if the researcher is not sure of what he/she wants to focus on. This is because there is no need for a strict design plan with qualitative research. Quantitative research is the most preferred choice in case the research wishes to study the likely relationship between variables because it uses statistics to test hypotheses.
References
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