Negligible or low risk in research means that a risk of harm or any discomfort cannot be foreseen (Bryman & Bell 2015, pp. 240). Any risk that is foreseeable is no more than an inconvenience to those who participate.
When one fails to properly, consider ethical issues in ethical applications there is a risk that people, properties or environments can be harmed. An example is the Tuskegee Syphilis Study. Ethical considerations have to be made to that damage of any kind is avoided. Another harm that may occur is the use of deception to carry out studies. Lack of following ethical procedures may also lead to a breach of the confidentiality of the people who are participating. This may highly affect the study when participants feel violated hence the researchers may not be able to obtain results. Plagiarism may also occur where the work of others will be used without permission. It may also lead to the conclusions of the research being skewed, based on funding that may have been promised prior to the study (Bryman & Bell 2015, pp. 245). Scientific misconduct may also occur and this may have dire consequences.
The principle of respect for autonomy will apply to the research, as respect has to be there for people’s lives. Decisions made by adults should therefore not be interfered with, in any manner while carrying out the research. The principle of beneficence will also affect any research being done as when carrying out the study we have to ensure that all the actions carried out are intended to bring about good. The principle of non-maleficence applies to research as it ensures that we do not harm other people. The principle of justice will ensure that when we are doing the research we provide other people with what they deserve and treat all participants in a fair manner (Vanclay, Baines & Taylor 2013, pp.250). Any issues that do not follow these principles while doing research must immediately be corrected.
Mixed Methods Research
Sequential mixed methods refers to the use of both qualitative and quantitative methods in research. The quantitative methods will assist in finding out what happened while qualitative methods will be helpful in explaining how an incident occurred. These two methods are integrated within a study through triangulation so that validity and reliability of the study are increased. It helps researchers in maximising the knowledge yield of the research study. A sequential method is also called the combined approach. Various methods can be mixed in such a way that there are complementary strengths and no overlapping weaknesses. The sequential mixed methods are followed to obtain a convergence of study findings, elimination of plausible alternative explanations and eliminate divergent aspects of phenomenon (Buckley 2015, pp.5). The diagram below shows how the sequential method can be applied.
Triangulation enables a researcher to find an agreement of results by using different methods. Using different methods and coming up with similar results makes the researcher have more confidence that the results are a true reflection of what is happening. Triangulation also ensures that there is a good balance between qualitative and quantitative methods of research. The researcher is able to notice any trends and consistencies in the research. Triangulation enables two or more researchers are able to gather data hence protecting against researcher bias or different assumptions (Buckley 2015, pp.8).
Triangulation will enable the research to have greater understanding and corroboration while at the same time eliminating any weaknesses. It will also enable the research to be approached from different points while using different techniques. Unexpected findings will also be clarified in an easier manner (Hussein 2015, pp.1). The researcher will also be able to elaborate findings that have been drawn from other methods.
The aim of the research is to give a model for practice so that medical researchers can be connected with a useful means to increase quality of grounded theory research that is published in literature concerning medicine (Sbaraini et al 2013, pp.401).
The grounded theory method will enable medical researchers to better design and also justify the methods that they use in producing findings of better quality that will be further beneficial to patients, professionals and researchers (Sbaraini et al 2013, pp.403).
The elements of grounded theory that can be identified in this research are the questions, which are asked on what happens and how people interact. The research begins with open questions by asking participants how the MPP process worked and if they understood it. The aim of the research was to find out why instead of applying preventive care, dentists focus on drilling and filling in earlier stages (Sbaraini et al 2013, pp.405). The participants were asked the process of protocol implementation from the perspective of dentists and how the process varied.
A full-blooded approach to the grounded theory is that which includes as many qualitative and quantitative methods as possible. These methods are applied systematically until the researcher is satisfied with the study being carried out.
The limitations that were experienced in using this method in the research were that not all of the dentists, who were participating, trusted the evidence produced (Sbaraini et al 2013, pp.413). The results they saw in their patients, made them stand firm with specific dental treatment approaches.
The appropriate sample size was determined by using a sample of 500 donors who were in the annual giving program between 1993 and 2003. They recorded each individual’s characteristics and how they donated up until 2012.
The random sample was generated by looking at a sample of 1200 alumni who graduated with degrees from the focal business school (Khodakarami, Petersen & Venkatesan 2015, pp.79). These were either undergraduate, MBA or PHD degrees. They had made at least one donation in 2012.
The researchers took stratified donor samples that fell into one of four groups. The first group was of donors who had donated to the business school in the past, the second group was donors who had funded multiple initiatives including the business group and the third group was donors who had funded other past initiatives that did not include the business school (Khodakarami, Petersen & Venkatesan 2015, pp.80). The final group was made up of those who funded multiple initiatives that did not include the business school.
The model development that the authors did included having model free evidence of how variety of donations can be linked to the value of donors. The researchers used s sample of 5,500 donors for this study. The model development also lent to quantification of the benefits of donation variety through control of a number of factors. The researchers came up with an econometric model to identify the consequences of having donation variety. The researchers empirically tested hypotheses by controlling marketing efforts, as non-profits do not solicit for funds randomly (Khodakarami, Petersen & Venkatesan 2015, and pp.87). Instrumental variable models were used for personal and impersonal methods of marketing.
The field study that was carried out in the research led to strong causal evidence being provided and it can lead to non-profit organizations motivating donors to increase donation variety. It also led to a general framework, which can be used by other non-profit organizations in motivating their donors to increase donation variety. The researchers used direct mail and email to motivate single initiative donors in turning to multiple initiatives (Khodakarami, Petersen & Venkatesan 2015, pp.90). Those already providing multiple initiatives were encouraged to take up further initiatives.
Target population is important to any study, as it will determine the type of results. The researcher has to ensure that the correct sampling approach is used in determining sample size. Taking a sample size that is inaccurate can lead to inadequate results and inconclusive research (Marshall et al 2015, pp.15). A sample size that is too large may lead to difficulty in analysing data.
Non-sampling errors are mostly caused by human errors. They may include factors such as wording of questionnaires, which may in turn lead to wrong data being collected (Altman 2014, pp.1). Data from studies may also be entered incorrectly hence producing results, which are inaccurate. Non-sampling errors can also occur when decisions are biased.
Focus Group Participation
Participating in a focus group is interesting as it enables many perceptions about a certain topic to be enlisted. It is collective and it allowed the group members to interact with one another during the discussion( Ritchie et al 2013,pp. 70). Many ideas and considerations were given. Bias was reduced to this and the session was interactive.
The positive aspect of the focus group experience was the fact that very useful data was obtained because of the number of people that were engaged. It was also easier hence led to saving of time and money as many people were talked to at once. It also led to reduction of any bias that might have been there initially (Ritchie et al 2013, pp. 66). A lot of information, which was broader, was gathered due to the number of people who participated in the focus group.
The negative aspect I experienced in the focus group was that sometimes there were disagreements, which led to distractions from the main topic. It was also hard for some analysis to be done (Silverman 2016, pp. 45). Getting people to participate was also hard and some people felt intimidated. The thing that could have been managed differently is having a smaller group for easier management.
Differences between Leximancer and NVIVO
The use of Leximancer leads to automated analysis wile NVIVO requires data to be handled manually in some phases. NVIVO has tools that enable the researcher to classify, sort and arrange information in a certain manner. The researcher codes data and develops certain themes to be used. It therefore enables a researcher to engage in an analysis process that is more meaningful (Sotiriadou, Brouwers, & Le 2014, pp.180). Leximancer produces results without requiring the researcher to manually intervene. It identifies different relationships occurring in data without need for intervention
Leximancer has over the years grown in popularity as it enables a researcher to handle large amounts of qualitative data (Birosack et al 2017 2014, pp.1). The method is therefore suitable for use in analysing qualitative data especially when a very large population is being studied.
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