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Selection of Methodologies

Write an essay on Research Methodology.

It covers essential parts of the research work focusing on the selection and application of specific tools and techniques that are suitable for the study. As data collection becomes the crucial part of a study for evaluation and analysing information that are relevant to the research topic, appropriate methods are applied. In addition, amongst different methodologies available they are selected based on the type of data required and assumed outcomes. Thus, for executing this study, and developing enormous knowledge from the collected data on Polycystic ovarian syndromes seen in adolescents in context of Maldives being the location of choice, has been fulfilled by selecting suitable methodologies.

Amongst four types of philosophies, Interpretivism, realism, post-positivism and positivism, post-positivism has been selected to analyse data in logical manner. Selection of post-positivism is also due to its nature of top-bottom approach of evaluating data (Tooze et al. 2010). In addition, it has been selected due to its incorporation of real facts in the study that is analysed in scientific manner. Presence of deductive and inductive approach for research studies require selecting any one of it based on the nature of the research (Thabane et al. 2010).

Thus, as this study is based on acquiring existing data without the need of developing new theories, deductive approach has been suitable. Unlike inductive approach, deductive approach does not require analysing observed data for framing theories for the study. On the other hand, descriptive design has been selected to carry out this piece of work due to its positive impact of providing relationship related data amongst research variables and collected data (McGaghie et al. 2010).

In gaining knowledge on the background of polycystic ovarian syndrome and its occurrence amongst adolescents, research design is the important criteria in progressing with the study. According to Creswell (2013), three distinct types of research designs are available from exploratory to explanatory and descriptive. Based on the type of data required in executing the study, necessary research design is selected by a researcher (Hakim, 2012). In exploratory design, it helps in providing basic knowledge regarding the research topic, which is not in-depth study. It aims to explore the topic rather than following a structured way of providing information.

As supported by Brewer et al. (2011), it only gives detailed information on the topic of research and identifies data related to the identified problem but it defines data in very reluctant manner. Thus, to acquire detailed information that is critically analysed for better research outcome, descriptive design has been selected. It not only provided detailed information on the topic, but also helped to structure the research study by providing basic concepts on the disease and its impact on adolescents. In addition, statistical information was also acquired due to incorporation of descriptive design.

In case of explanatory design, it focuses mainly on explaining the acquired data related to the research topic (Zhang et al. 2010). It also provides relationship information between variables that are linked with the present study. For example, it can provide information based on relationship by explaining the factors related to polycystic ovarian syndrome and the reasons for which it is prevalent amongst adolescents of Maldives. However, both the research designs fail to provide in-depth knowledge from background information on polycystic ovarian syndrome to linking the causes and its incidence amongst adolescents particularly in Maldives.

Research Design

In order to conduct a research study, it is necessary to select few participants for deriving necessary information that are required to gain in-depth knowledge on the study topic. Therefore, based on the viewpoints of Elo et al. (2014), population is referred to as the total number of participants agreeing to participate in the study to provide relevant information. As viewpoints of participants form the core to a research work outcome that provides basic experiences is effective part of a research. Thus, in this study, adolescents from Maldives are selected as the population. In addition, adolescents within the age of 15 to 35 years have been selected for the study.

Thus, the sample size related to population has been 203 adolescent girls from Maldives between the age group of 15 to 35 years. On the other hand, Roger (2011) criticised that only taking perceptions of patients with a diseased state is not sufficient to develop understanding about the disease or to understand the gaps in medical assistance to the patients. Therefore, respecting this view, few participants were selected being the doctors providing assistance and guidance to adolescent patients of polycystic ovarian syndrome. About 7 doctors from different hospitals such as ADK and IGMH in Maldives were incorporated in the population for the present study. Data were also collected from a hospital in Maldives related to adolescents with polycystic ovarian syndrome within 2 years.

The sample size selected for the study has been 203 adolescent girls with the diseased condition, following 7 doctors from the same field. In the assertions made by Peffers et al. (2007), it is understood that sampling technique forms the necessary mechanism through which samples are selected from the population. Sampling technique helps to understand the categories of participants for the study and the information that can be obtained from their viewpoints (Concato et al. 2000). For example, adolescent girls can provide information regarding the consequences of polycystic ovarian syndrome based on their experiences and the daily problems faced by them due to the disease following healthcare services given to them.

On the other hand, doctors selected through specific sampling technique are helpful to acquire information on interventions for the disease and the support provided to adolescents in Maldives to rescue them from this disease. In addition, strong information related to disease incidence, healthcare services available for them and the problems faced by them while providing treatment to these patients can be acquired. Thus, for selecting adolescents, simple random probability sampling technique has been implemented. However, for sampling doctors from different hospitals, incorporation of non-probability sampling technique has been applied.

Population and Sampling and sampling technique

In assessing the collected data, requirement of specific research instruments forms the basic part of data gathering. As per the comment of Schulz et al. (2010), instrument for collecting data are of different types from questionnaires to surveys, interviews, focus groups based on the type of information required. Thus, for achieving viewpoints of adolescents with the diseased state, questionnaire have been used that comprised of several relevant questions about 23 in numbers based on polycystic ovarian syndrome and their experiences. On the contrary, as doctors are available to provide enhanced information on this subject matter, therefore, they were asked for participating in the interview.

Online survey was carried out for the quantitative research, which involves adolescents as participants. However, for qualitative information interview was conducted amongst the 7 doctors. As criticised by Harriss and Atkinson (2013), gathering information not only requires specific instruments, but instruments for data analysis and documentation are also necessary. Thus, implementation of MS Excel and SPSS tool has been used for documenting gathered information from respondents and analysing those data to acquire assumed results respectively.

 

Information for carrying out a research work is acquired from either primary sources or secondary sources, based on the requirement. Primary sources allow gaining practical information on the study topic that involves participants (Johnson and Onwuegbuzie, 2004). As suggested by Bernard (2013), secondary sources are helpful for acquiring information from books, journals, news articles, and blogs and websites articles.
Thus, in this study application of both the sources has been helpful to arrive at a solution of gaining practical knowledge from participants and in-depth information from secondary sources. Online library has also been incorporated for collecting secondary data. Thus, quantitative technique was applied by framing the questionnaire that was based on PICO format and they have been surveyed. For qualitative technique, interview was the form of data collection from doctors based on few structured questions based on which quantitative questionnaire was framed.
Ethical considerations were maintained while primary data collection was conducted. This comprised of non-application of gathered information for commercial reasons and maintaining accuracy of collected data. In addition, maintaining anonymity of participants’ identity was followed to avoid ethical issues. Their participation was voluntary and they were not forced for participation.

SPSS software has been selected for the purpose of primary data analysis. This has been helpful to obtain numerical data from qualitative approach whereas, through quantitative approach details aspect of data was acquired by linking concepts and theories. As per Maxwell (2012), SPSS software allows to conduct data analysis in the best manner without facing extensive errors that makes the outcome more relevant as assumed. This study involves a mixed approach involving quantitative and qualitative technique of data collection.

Research Instruments

The researcher had faced some challenges of restricted time that hindered in analysing larger data within the stipulated time. This became the barrier in achieving quality results that would have been possible if more was available. In addition, bias in reliability of healthcare organisation authorities has been an issue in the study. This reduced scope for the current research study.

Introduction
The study aims to explore the incidence, cause and symptoms of Polycystic Ovarian Syndrome (PCOS) which is one of the common reproductive disorders of Woman in Maldives and across the world. Having identified the lack of research on the same in Maldives, the present study has been designed to bring out a clear picture of this acute syndrome. With the help of a suitable questionnaire, survey sessions have been conducted on adolescents of the age of 15 to 35 who were diagnosed with PCOS. Also, interview sessions were conducted with the doctor of Maldives. According to the data was sorted and analyzed in SPSS, exploratory factor analysis has been carried out to throw some insights on the nature of this acute syndrome in Maldives.

Data and information were collected in two parts, the first related to the interview sessions which were conducted with the doctors in different hospitals in Maldives while the second part dealt with the primary survey with the questionnaire as the prime instrument.
The hospitals were selected at random and face to face interviews were conducted with seven (7) doctors who had experience in dealing with the PCOS. Three questions were asked to each of the doctor's, and the responses were recorded (questions appended at the end). Parallelly, a note was taken on the number of registered cases of PCOS over a period of twenty-four (24) months.

Also, a questionnaire was designed to impute the determinants, causes, and symptoms of PCOS. The intended population for this research was adolescents’ girls of the age of 15 to 35, the questionnaire comprised of 23 questions pinpointed at drawing quality insights at the ground level. The respondents have presented the survey and responses were asked in yes/no (yes coded as 1, and no coded as 2) except for question no 1 and question no 20 where the responses were coded as per convenience.

 

The first research question was targeted at assessing the most common age for PCOD. To examine this, question 1 was set up in the questionnaire; the question asked to impute 1 in the box if the age lies between 25-34 years, impute two if the age lies in the range of 18-24 years and impute three if the age is less than 17 years. The data was loaded in SPSS and accordingly a frequency table was formulated to assess the maximum frequency of the age of the respondents. As per the sample, the most common age group for the presence of PCOS is group 1 which comprised of the age group 25-34. The maximum frequency in the observed sample has been found for the first group; this gives the answer to the first research question. The result seems to be similar to what was revealed from the interviews conducted with the doctors. The results show that 130 of the 203 sampled individuals were of the age group 25-34 which is a whopping 64% of the sample. The pictographic representation of the same has been plotted on the bar diagram in 

To understand and identify the most common symptoms and the risk factors of PCOD an exploratory factor analysis has been conducted using the data set on SPSS, the outcome of which is presented below. The factors were extracted based on the Eigen value criteria (Eigen value >1), also weak factor loadings that are loadings less than 0.4 were dropped. The correlation matrix was formulated, and the necessary steps have been followed in carrying out the exploratory factor analysis.

The Kaiser-Meyer-Olkin Measure of Sampling Adequacy reads the value of 0.742 which gives the clear indication that there are adequate samples to go for the factor analysis. The Bartlett’s Test reveals a statistically significant value (less than 0.05).

The communalities table give us the values of extractions, which tells us about the proportions of variation in each variable that can be explained by the factors. The extraction values are moderately high and have a significant role to play in the factor extraction procedure.

We can clearly see that SPSS extracted eight factors or components based on the Eigen value criterion (Eigen value>1). These eight factors together explain 59% of the total variance.

The scree plot next says that there were eight factors with Eigen value greater than 1 and were extracted, while the rest with Eigen value less than one were not extracted.

A total of 7 factors has been extracted based on the factor analysis. The rotated component matrix is used to identify the components of the factors. The matrix says that Q21, Q17, Q19, and Q13 are together, that is, the incidence of obesity in childhood, the presence of diabetes, gestational diabetes, and incidence of depression/ anxiousness go together. Further, the second factor reveals that Q22, Q6, Q8, and Q4 are together, i.e. presence history of Polycystic Ovarian Syndrome in the family, irregular menstrual cycle, excess hair growth, and feeling bloated go along.

The third factor reveals that Q20, Q11, and Q7 goes along which implies that whether a person exercises or not, the presence of skin tags (lumps of skin sometimes as large as a raisin) and unsuccessful attempts to conceive (in the past six months or more) go together. The fourth factor incorporates Q12, Q3, and Q23, the i.e. incidence of discoloured skin, and impact of weight gain around the middle and impact of other hormonal diseases go together. The fifth factor comprises of Q15, Q14 and Q18 go along which implies that incidence of uncontrolled craving, feeling tired and weird and, the impact of diabetes in the family go together.

The sixth factor reveals that Q2 and Q16 are suitable, i.e. struggling with weight and incidence of 1st-trimester abortion goes along. The seventh and the eighth factor has one component each, the sixth and the seventh factor has a very high factor loading of around 0.9; and the components are taking birth control pills to bring period and presence of acne respectively.

The study reveals clearly that the most common age group showing the presence of PCOS is the age group 25-34 years, as revealed from analyzing the frequency table; this fulfills the first research objective.

It was possible to draw conclusions about the second and the third research question using factor analysis. The aim is to identify the most common symptoms of PCOD and to determine the risk factors of PCOD. Menstrual irregularities, weight gain, skin darkening; irregular hair growth, acne and obesity are the most common symptoms of PCOD. According to our factor analysis, factor 2, factor 4 and factor 8 encompass these aspects; apart from these symptoms and therefore it can be said that apart from the symptoms described by the doctors is clearly verified by the sample. Increased BMI, sedentary lifestyle, family history, infertility, junk foods and obesity are the risk factors of PCOD as per doctors in Maldives. Factor 1, factor 3 and factor 5 captures these risk factors; and the results from the factor analysis go hand in hand with the comments of the doctors.

It must be noted that apart from the factors specified by the doctors, there are other factors which affect the incidence of PCOD as revealed by the factor analysis. The ground reality seems more diversified than that told by the Doctors in the interview.

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