According to Terre Blanche, Durrheim and Painter (2006, p. 133) population is the main focus of a study, which in most cases is larger than its sample. They state that, ‘theoretically speaking, the population encompasses all the elements that make up our unit of analysis’. Terre Blanche et al.
82 (2006) argue that the population for data collection has to be carefully identified to maintain the significance of the study and avoid violation of the researcher’s interest. The phenomenon identified for this study was all HIV infected and affected individuals in Botha-Bothe. There are various reasons that can prevent the researcher from reaching out to the whole population of the study. Amongst the reasons are time to attend to the entire population, costs that one could incur and the accessibility of the large population. Simons (2009) stipulates that this smaller group or subset is the sample and it is therefore advisable to use a smaller group representative of the whole population. The population from which my data emanated was the infected and affected people who attend HIV monthly services, either directly because they live with the virus, or affected because they accompany close relatives to access services in this particular hospital. In this case the sample for this study had to form a good representation for the entire population.
4.7.1 The sampling process
According to Walliman (2015), sample refers to the manner in which a small portion of the entire population is used as a representative of its larger group. The sample has to have exactly the same characteristics as its larger population to allow responses to have the same value and same context even though responses are sourced from the smaller representation. Babbie (2004) sees sampling as the action of giving the researcher a manageable number as representation of a bigger group but relying on the responses of the smaller and manageable group to provide precise responses one expects from the bigger group. The smaller group provides information that could be obtained from the larger group. As a result, the significance of the smaller group is the same as the significance of the larger group (Mason as cited in Silverman, 2004). Blaikie (2010), Babbie (2004) and Silverman (2004) argue that the selection criteria of the representative population must not be biased against nor be in favour of the researcher because the intention is to obtain information from the generalised population of the study.
Silverman (2004) argues that generalisation in qualitative research can be addressed in part through sampling. Generalisation is concerned with the representatives of the research sample and also the degree to which one can then make inferences to other contexts or populations.
Baxter and Jack (2008) share the point that in quantitative research designs, generalisability is achieved through statistical sampling procedures because data is quantified to indicate its
83 implications and direct the researcher to the meaningful action to be taken in response to the implication. In qualitative research, participants are not selected randomly and the size of the sample is usually quite small to allow the researcher to work on the manageable data responses.
It is befitting at this juncture to indicate that purposive sampling was used in this study.
Silverman (2004) designates that purposive sampling as the name implies (from purpose) is based on the need of the researcher to decide on the respondents that reflect the researcher’s interest or those identified by the researcher to have the knowledge and responses that would help answer the research questions.
The researcher is at liberty to classify the type of respondents that can best fit the criteria.
Simons (2009) highlights that purposive sampling is used in order to access knowledgeable people; that is those who have in-depth knowledge about particular issues. The power of purposive sampling emanates from the perfect selection of respondents to the study based on knowledge of the matter understudied. For instance: seeking responses on the impact of studying PhD in cohorts can best be responded to by learners who have been in a PhD cohort. This implies that the responses gathered from a population that best experienced the cohort method can best suit the needs of the researcher (Patton, 1990). The selection should take account of cost effectiveness, ease of access and manageable procedural demands which are the pre-requisites for selecting a good sample for a project (Neuman, 2000). As the researcher in this study I had to consider the financial constraints under which the study was conducted because I had no permanent job to finance myself. The support groups were therefore purposively chosen and therefore became representative samples of all HIV/AIDS infected and affected people in Botha- Bothe. But the case study design meant that they also constituted the whole population of each of the support groups (subject to attendance at any particular meeting) since I observed the support group meetings in their entirety.
The total population for my study was people who are infected and affected by HIV/AIDS. The sampled population was the members of three support groups.
Each support group consisted of between 12 and 27 people who attended one or more of the groups’ meetings during the period of observation. In addition, guest speakers such as youth
84 leaders, nurses or other medical staff who attended the meetings also became part of the observed sample.
Each support group members’ composition increased as time went on because members encouraged less reliable members to attend because they realised the impact that was made by shared and collective learning to the support groups and to the community.
Table 1 below indicates the attendance of people observed at the beginning (February), in the middle (May) and during the last meeting (August) per support group as an example of attendance rates. It also indicates visitors as subject specialists per meeting. The table shows that the total observed number of participants in the research across all three support groups could range from 43 to 66 per month.
Table 1: Indicators of attendance rates across the support groups
Dates Support Group Topic Discussed Attendance 08 / 02 / 2013 Fathers-to=Fathers
(F2F) New committee
elected, confirm the use of voice recorder in next meeting.
12 Males 1 Nurse 1 Counsellor
07 / 05 / 2013 F 2 F Defaulting and
treatment failure 16 Males 1 Nurse 1 Counsellor 16 / 08 / 2013 F 2 F Preparing for a trip to
Mafeteng 17 Males
1 Nurse
1 Administrator to assist with logistics.
08 / 02 / 2013 Mothers-In-Law Post mortem of
previous meeting 13 Females 1 Nurse 1 Counsellor 07 / 05 / 2013 Mothers-in-Law Nutrition and HIV 14 Females
1 Nurse 1 Nutritionist 1 Counsellor 16 / 08 / 2013 Mothers-in-Law MCSP reduction 15 Females
1 Nurse 1 Counsellor 13 / 03 / 2013 Mixed Support Group
(Thusanang Bakuli) Basic HIV and AIDS, Transmission, rules and regulations disclosure
18 Females 1 Nurse 1 Counsellor
85 08 / 05 / 2013 Mixed Support Group MCSP Reduction and
sexual partner infection
24 Females 1 Nurse 1 Counsellor 28 / 05 / 2013 Mixed Support Group Cleanliness and
living exemplary life 27 Females 1 Nurse 1 Counsellor