In this section, the population, sampling, and sampling methods will be introduced.
1.4.1 Population
The term “population” can be defined as the group or collection that a researcher is interested in generalising about (Rubin & Babbie 2013:372). According to Carey (2012:247), population is the total group or collection of people from which a sample is drawn. Likewise, Jupp (2006:265) refers to a population as a group of people or unit of analysis which is the focus of the study and which the researcher aims to understand or draw conclusions from. Additionally, Williams (2015:126) suggests that a population involves research with people who belong to a particular place, or data collection about large groups of people. Therefore, a population is a group of people which the researcher intends to understand, generalise about, and draw conclusions from.
The population for this study was defined as follows:
All social workers in the Gauteng Province of South Africa, employed in the private sector, at NGOs, at government departments, and/or in private practice, who are registered with the South African Council for Social Service Professions.
All divorced persons (men and women) residing in the Gauteng Province of South Africa.
From this population the researcher intended to draw a sample, since the entire population could not be included in the study.
1.4.2 Sampling
A sample is a smaller subgroup drawn from a larger population (Wilson & Maclean 2011:317). The sampling process begins when the researcher chooses the subset of the population that he or she intends to engage with and decides on how he or she will locate and involve them (Thorne 2016:96). In sampling, the researcher explicitly selects participants who are likely to generate appropriate and useful data (Green &
Thorogood 2009:118). The necessity of sampling is based on the fact that the nature of the research problem in which the researcher is interested does not always permit access to all entities that constitute the population (Strydom 2011:224). Without sampling, the qualitative research study would be flawed. In qualitative research, a sample must be drawn from the population in such a way that it would provide appropriate and adequate insight into people’s experiences of the world (Nicholls 2009:639). Furthermore, sufficiency needs to be achieved in qualitative research sampling (Nicholls 2009:639). Sufficiency means that participants represent the range of population members in terms of whatever social categories are considered relevant, for example ethnicity, class, gender, or region (Waller, Farquharson & Dempsey 2016:70).
The sampling for this study initially proposed to focus on two groups of participants, namely social workers who provide social work services to divorced persons, and divorced persons who received or sought social work services. With the inclusion of social workers, the researcher was able to gain an in-depth understanding of the nature of the social work services they provide to divorced persons, whereas the divorced persons were able to share their first-hand knowledge about their needs and experiences related to social work services to divorced persons. Eventually, the researcher developed guidelines that would inform social welfare policies and social work practice, and they are included in Chapter Six, section 6.4, of this research report.
1.4.3 Sampling Methods
Sampling methods or plans refer to designs for how researchers specifically choose sources for their data (Tracy 2013:134). The most commonly used sampling method in qualitative research is non-probability sampling (Waller et al 2016:66; Chambliss &
Schutt 2013:97). Non-probability sampling comprises the following sampling methods:
convenience sampling, snowball sampling, purposive sampling, theoretical sampling, and quota sampling (Chambliss & Schutt 2013:97; Waller et al 2016:66). For this study, the researcher found the purposive sampling and snowball sampling methods to be more appropriate in adequately addressing the research goal and objectives.
According to Tracy (2013:135), good qualitative researchers, at the very least, engage in purposeful sampling, which means that they purposefully choose data that fit the parameters of the project’s research questions, goals and purposes. These views
resonate with Hesse-Biber and Leavy’s (2011:45) notion that qualitative researchers are often interested in selecting a purposive or judgement sample.
Purposive sampling is a somewhat more representative sampling technique in which the settings and specific individuals within them are recruited by virtue of some angle of the experience related to the topic under study that might help the researcher to understand the topic better (Thorne 2016:99). The aim of purposive sampling is to select interviewees who are likely to generate appropriate and useful data (Green &
Thorogood 2009:118). It is worth noting that the type of purposive sample chosen in qualitative research is often based on the particular research question, as well as in consideration of the resources available to the researcher (Hesse-Biber & Leavy 2011:45). In other words, purposive sampling is based on the assumption that the researcher aims to discover and gain understanding into a certain phenomenon and therefore he or she would select a sample from which the most can be learned.
Another method for reaching difficult-to-access or hidden populations is snowball sampling (Tracy 2013:136). Snowball sampling is a common sampling technique used in qualitative research, especially when the researcher does not have access to a population from which to draw a sample, or if the nature of the research population makes it impossible (Hesse-Biber & Leavy 2011:47). This is a sampling method in which sample elements are selected as successive informants or interviewees identify them (Chambliss & Schutt 2013:97). Likewise, Waller et al (2016:66) state that with snowball sampling, participants are asked to suggest other participants. In this regard, snowball sampling is used to identify participants when appropriate candidates for a study are difficult to locate (Hesse-Biber & Leavy 2011:47).
The researcher planned to use the following criteria for the inclusion of the first group of participants (social workers) into the sample:
The participants must be working as social workers either in the private sector, at an NGO, at a government department, or in private practice.
The participants must have at least two years’ working experience as social workers.
The participants must have provided social work services to divorced persons since they started working as social workers.
The participants must have received intake cases of divorced persons seeking social work services.
The participants must be based in the Gauteng Province, South Africa.
The participants must be willing and available to participate in the study.
The following criteria were planned for the inclusion of the second group of participants (divorced persons) into the sample:
The participants must have been legally divorced from their partners.
The participants must have received or sought social work services from a social worker employed either in the private sector, at an NGO, at a government department, or in private practice.
The participants must reside in the Gauteng Province, South Africa.
The participants must be willing and available to participate in the study.
The researcher was cognisant of the fact that size is not the priority in most qualitative research projects, but rather the quality of data collected and analysed remain the core objective (Carey 2012:41). However, it should be noted that 10 social workers and 10 divorced persons were interviewed for this study and that data saturation was reached.
Saturation or redundancy of data implies that the researcher will continue to compile data to a point where the data becomes recurring and a broad insight into the phenomena is achieved (Lincoln & Guba, in Merriam 2009:48). Therefore, data saturation can be reached when the researcher can no longer derive new information (Willig 2009:39). In other words, data saturation occurs when the participants no longer share new information. The determination of the sample size is further expounded in Chapter Three, sub-section 3.5.5.4.
The next section focuses on the method of data collection, data analysis, and data verification.