CHAPTER 3 RESEARCH METHODOLOGY
3.6 SAMPLING
Sampling is a process of selecting a segment of the population which is an entire aggregate of cases (Polit and Beck, 2012). For the researcher to understand a much larger set of cases and learn from them, selection of cases for detailed examination is done when sampling. The main use of sampling in quantitative studies is to produce a representative sample and generalise the findings to the entire population. Whereas, in qualitative studies the selection of participants is determined by their relevance to the research topic rather than their representativeness (Neuman, 2011). Sampling includes selecting groups of people, events, behaviours or other elements with which to conduct a study (Burns and Grove, 2005). In view of the pragmatic paradigm which allowed mixed methods, both quantitative and qualitative samples were drawn. However purposive sampling was used for participants in the study based on the researcher’s knowledge of the population (Polit and Beck 2012). The prospective participants were recruited (after obtaining permission from the facility) and their cooperation was requested.
3.6.1 Sampling Frame
A list of all the districts and hospitals in KwaZulu-Natal was obtained from the KZN health Intranet website. A list of all ANMs and NMs from the selected sites and nurse leaders at the district health offices was accessed from the PERSAL control system. It was used to estimate the number of potential respondents.
3.6.2 . Quantitative Sampling
A multi-stage sampling was applied. Multistage sampling is a complex form of cluster sampling in which two or more levels of units are rooted one in the other. It involves the repeat of two main steps, which are listing and sampling. Typically, at each stage the cluster gets smaller in size and in the end, subject sampling is done (Wahyuni, 2012). The initial sample was selecting districts that had the regional and tertiary hospitals. The study was conducted in five health districts namely, Amajuba, eThekwini, ILembe, uGu, and uThukela districts. Eleven hospitals participated in the study. Table 3.1 illustrates the facilities and participants that were available for the study.
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Table: 3.1: Participants in the respective institutions
Facility Total
number of ANMs
Total number of nurse managers
Total
responded to questionnaire
Nurse managers
ANMs
EThekwini District
R K Khan 9 1 8 1 7
Addington 8 Nil (acting ANM) 5 5
Prince Mshiyeni 10 1 7 7
Inkosi Albert Luthuli 12 Nil (acting ANM) 10 10
King Dinuzulu 14 1 11 11
King Edward (KEH) 10 1 10 10
ILembe District
Stanger 8 1 5 1 4
Amajuba District
Madadeni 9 1 6 6
Newcastle 6 1 1 1 0
UGu District
Port Shepstone 10 1 9 1 8
UThukela District
Lady Smith 8 1 9 1 8
TOTAL 104 9 81 5 76
The nurse leaders consisted of nurse managers and assistant nurse managers. Five nurse managers participated in the quantitative study. One nurse manager was recruited from each participating health district. The total number of assistant nurse managers (ANM) that was available was 104 in the five districts. Seventy six ANMs out of the 104 were enrolled for the study. In two facilities namely KEH and Ladysmith, all ANMs participated in the study, making up at total of 18. In the remaining institutions, a simple random sampling was conducted.
The overarching aim of the study was to determine participation of nurse leaders in the four broad stages of policy development, namely: problem identification and agenda
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setting; policy formulation; policy implementation and policy evaluation. The purpose was to identify and analyse the gap in their participation.
3.6.3 .1Analysis of variance (ANOVA)
An ANOVA test had the potential to determine differences in involvement of participants at different stages of policy development. The null hypothesis (basic assumption) was that there was no statistically significant difference in participation of nurse leaders in policy development from one stage to the other. The ANOVA would either accept or reject the null hypothesis. Therefore if the P value of the ANOVA is < 0.05, it means there is a statistical significance. If the P value is > 0.05 ANOVA accepts the null hypotheses.
Rejection of the null hypothesis would result in the use of a post-hoc test to ascertain at which level participants involve themselves most.
A statistical tool called G-power was used to calculate the number of participants in the study. G-power was used to calculate the number of ANMs. The following parameters were used:
a) Effect size of 0.39 (large effect size)
The effect size is a standardised index that is independent of the sample size and quantifies the magnitude of the difference between populations or the relationship between explanatory (independent) and responsive (dependent) variables. In the interest of analysis of variance, the effect size can be viewed as the population standard deviation.
b) Type 1 error (Alpha error) = 0.05 (5%) (Recommended for a medical study).
c) Type 2 error (Beta error) = 0.02 (20%) (Recommended for a medical study).
Statistical power = 1β. 1 - 0.2 = 0.8 (80%).
d) Critical F value (value at which F should be to get a significant result) = 2.73
On the basis of the above parameters the researcher and statistician arrived at the sample size of 76 ANMs and 5 nurse managers, 76+5= 81 participants. Therefore the quantitative sample for the study consisted of 81 participants. According to Polit and Beck (2010), the quantitative researchers should select the largest sample possible so that it is representative of the population.
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3.6.4 Qualitative sampling Purposive non probability
Purposive sampling refers to the sample being selected purposefully and is subject to the researcher’s judgment, in line with the aim of the study, regarding whom he/she considers to be typical of the population and is particularly knowledgeable about the issues being studied (Polit and Beck, 2008; Keeney et al, 2010). Sampling was purposive because the intention was to include participants who were knowledgeable about the phenomenon under study. In searching for meaning, the researcher was looking for the sample that could best provide the required data. Participants were selected who were likely to have a genuine interest in the topic, or who were part of, or should be part of, the health policy development process (Keeney et al., 2010). According to Neuman (2011), for clarity, insight and understanding about issues or relationships in the social world, few participants must be selected. The aim of sampling is to uncover new theoretical understandings, show characteristics of people and the social environment, or expand knowledge of complex conditions or events.
The sample size in qualitative approach is usually small. The qualitative sample consisted of eight participants. This is in line with the guidelines for sample sizes in qualitative research which according to Short (2008), should be at least six. According to Byrne (2012), the researcher could consider sample sizes used in previous published studies, the scope of his or her study and the resources available to him or her. No similar study was found using action research or mixed methods. Sampling was done until data saturation occurred. Saturation of data occurs when additional interviews provide no information to identify themes and subthemes (Burns and Grove, 2005). Purposive sampling was adopted because of the small population of nurse leaders in a hospital.
Furthermore, the number was reduced when people were on vacation or sick leave or working shifts.
3.6.5 Sample inclusion and exclusion criteria
The inclusion criterion for participating in both the first and second phase of the study was being an ANM or Nurse Manager working in the selected regional and tertiary hospitals in the KwaZulu-Natal Province, and senior nurses in leadership positions working at provincial and national level. The second phase of the study expanded the inclusion and allowed the nurse educators to be included in the sample. This was done to strengthen partnerships between the nurse leaders from practice and the nurse educators to help
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realize improvements. The researcher appreciates that they need to speak the language of policy and work cohesively as a profession. Nursing leaders must translate new research findings to the practice environment and into nursing education and from nursing education into practice and policy. Participation in the study was voluntary. Nurses, who were not in managerial positions in the selected hospitals, were excluded. The district and specialised hospitals were also excluded from the study.