Step 6: Design of a sampling plan

When focusing on the design of the sampling plan, the reference of Burns and Grove (2009:42,721) was utilised as an approach to the design of a sampling plan. Burns and Grove (2009:42,721) define a sample as “a selected group of people” identified to be included in a research study. The researcher used her interpretation to decide on the design of a sampling plan.

Sampling, according Burns and Grove (2009:721), is a process whereby the researcher decides on the exact group of people to be included in a study. Burns and Grove (2009:343) add that the sampling plan is the selection process that the researcher follows to include the identified population in a representative way. Polit and Beck (2010:307) posit that the representative sample for inclusion in a study group must fully reflect the characteristics of the population identified for the study, while Brink et al (2006:125) understand a representative sample to mean that it reflects similarities to the population in as many ways as possible. The viewpoints of these authors validate Burns and Grove’s (2009:724) claim that the target population, accessible population and the sample are alike in terms of characteristics, elements and setting.

Polit and Beck’s (2010:307) description of a sample as a “subset of population elements” recognises the opinion of Burns and Grove (2009:721) who view sampling as the process whereby the researcher selects the section of the population that will represent the whole population. The basic sampling unit or element identified for this study was child nurse practitioners, in other words, human beings or individuals.

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The sample frame, based on the explanation given by Brink et al (2006:124), consisted of sample elements in the target population which allowed every person conforming to the inclusive criteria the opportunity to be included in this study.

Figure 3.4 provides a summary of the sampling plan applied in this study.

Figure 3.4: Summary of the sampling plan (adopted from Polit & Beck 2010:308)

The inclusion criteria for respondents to access this study were child nurse practitioners who:

 were professional nurses registered with the SANC  worked in child nursing units in Gauteng

 consented to voluntary participate in this study.

Target population

Accessible population

Sampling frame

The sample

Child nurse practitioners

Child nurse practitioners in Gauteng

110 structured, self reported questionnaires distributed to child nurse practitioners working in public, private, military and district child nursing practices in Gauteng

82 respondents returned completed structured, self reported questionnaires

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After a decision on the target population had been made and the accessible population had been identified, the sample frame from the accessible population was listed to enable delineation of the sample. Table 3.4 summarises the sampling frame. The information was obtained through the Health Annals (Malambe 2009:126-136,145-162), telephone inquiries, and the researcher’s knowledge of the accessible population.

Table 3.4: The sampling frame

Health care facilities in Gauteng with associated child care practices that participated in the research

Sector Number of hospitals Number of child care units

Public sector 13 27

Private sector 45 51

Military 1 1

District 1 1

Total 60 80

Child nurse practitioners working in one of the public health care facilities refused to participate in the study. This particular public health care facility was therefore excluded from the study and no structured, self reported questionnaires were distributed to the child nurse practitioners. The particular health care facility is not included in Table 3.6.

A sampling plan was used to select the respondents for this study. The aim of the sampling plan, according to Burns and Grove (2009:34,721), is to increase representativeness. Polit and Beck (2010:309) and Burns and Grove (2009:721) propose two methods or types of sampling, namely, probability sampling and non-probability sampling. Burns and Grove (2009:715) describe probability sampling as the method which gives every element in the population the probability greater than zero to be selected for the study. Brink et al (2006:131) opine that a probability sample has the value of generalising the research findings to the target population.

Non-probability sampling can be described, according to Burns and Grove (2009:711) and Polit and Beck (2010:309), as a non-random method by which not every element in the population has the opportunity to be selected in the

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sample. Although these authors warn that non-probability sampling decreases representativeness, Brink et al (2006:131) argue that this method is convenient and economical in circumstances where it is impossible to reach all elements of the selected population.

Taking into account the limitations of purposive sampling, it was nevertheless decided by the researcher to use it as the method of data collection after a discussion between the researcher and the statistician had taken place. Considering the research question and recognising that the number of child nurse practitioners in Gauteng was limited, it was resolved that, for the purpose of this study, including a non-probability sampling method was justified. The two types or techniques of non-probability sampling applied in this study were convenience sampling and purposive sampling.

Convenience sampling refers to the sampling technique where the most conveniently available respondents are included in the study (Polit & Beck 2010:309). Burns and Grove (2009:687) regard convenience sampling as accidental, yet functional and commonly used in health care studies where it is difficult to find elements for a study. Brink et al (2006:132) also refer to this technique as “accidental”, but add that it is “availability sampling”. The sample in this study was based on a convenience approach due to the researcher’s access to the selected population as a child nurse educator during the data collection framework.

The snowball technique, a variation of convenience sampling, was also used when early respondents were requested to refer sample elements who met the inclusion criteria. According to Polit and Beck (2010:309) and Brink et al (2006:134), this technique can be used when it is difficult for the researcher to reach the entire population. The researcher used the first respondents to spread the message to the selected child health care facilities. Respondents were then considered by the researcher and those accepted were included in the study. Polit and Beck (2010:309) refer to this technique as “network sampling or chain sampling”.

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Snowballing, or network sampling, is a recognised method which can be utilised in quantitative studies to expand the sample size (Burns & Grove 2009:356). In this study the first respondents were included through the convenience sampling method. Through social networking other respondents who met the inclusion criteria were identified and contact was made with them (Burns & Grove 2009:356).

Purposive sampling or judgemental sampling, in the view of Polit and Beck (2010:312) and Brink et al (2006:133), is based on the personal judgement of the researcher when selecting the representative population. The purposive sampling technique was selected because of the researcher’s particular knowledge of the population.

A description of the process to identify the respondents is discussed in Section 3.3.2.3 of the empirical phase.

The final step in the sampling plan is the selection of an appropriate sample size. Polit and Beck (2010:316) postulate a sample size as the number of elements to be included in a sample for a specific study. Brink et al (2006:135) affirm this statement. Polit and Beck (2010:316) admit the fact that there is no clear equitation to follow in selecting an exact sample size, although they consider that a larger sample is more representative of the population. Brink et al (2006:137) remark that sampling is an important and integral part of the research process. Therefore, a sample should complement the purpose, research design and practical reality of the study. The sample size in this study is reflected in Table 3.5.

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Table 3.5: Sample size

Child health care facilities in Gauteng that participated in the research study