Population and sampling

Population and sample selection totally depend on the research design followed. A typical goal of quantitative research is to generalise findings to larger populations, achieving a high degree of reliability. To minimise sampling error, every case in a sampling frame must have an equal probability of selection (Patton 2001:185). The target population is, hence, the aggregate of cases about which the researcher would like to make generalisations. Sampling therefore involves selection of a number of units from a defined study population. The representative sample consists of subsets of the elements of a population; this allows for study results to be generalised (De Vos et al 2005:194; Polit & Beck 2004:290). The characteristics of the sample population are intended to be representative of the target population.

3.3.2.1.1 The study population

Population is defined as an entire aggregation or eligible group from which a sample can be drawn (Polit & Beck 2004:290). In their definition, Polit and Beck further explain that the accessible population is the aggregate of cases that conform to the designated criteria and that are accessible as a pool of subjects. The study population - an entire aggregation or eligible group from which a sample can be drawn (Polit & Beck 2004:290) − for this retrospective study are: 1) deceased mothers (all maternal death

cases of any age) − mothers who are died during pregnancy or 42 days after delivery during the study period − July 1st 2014-June 30th 2015 (N=142); and, 2) Deceased newborn (all newborn babies of neonatal & perinatal death) − within 28 weeks of gestational age and 28 days after delivery - within the study period (N=302). These are maternal mortality and newborn death cases of any nationality but are resident in the selected zones health catchment area.

3.3.2.1.2 Sampling methods

It is convincingly well explained in Bluman (2012:6-17) and numerous scholars in the area of sampling that in determining the sample size particular attention was given in getting adequate sample size that would ensure the generalisability of the study findings. The literature differentiates between two types of sampling: non-probability and probability. Non-probability sampling is used in large-scale surveys where the elements are not known and are thus non-random selection of subjects (Babbie 2005:188). Despite its inherent strength, the main disadvantage of non-probability sampling is that it is a less representative approach. The method used in this study was purposive sampling which is based on the researcher’s judgement regarding the respondents to be included in the study (Polit & Beck 2004:311; Babbie 2005:196).

Probability sampling is usually seen as the best way of selecting a sample that is representative of the population from which it is drawn. In probability sampling, every element has an equal chance of being selected for the sample. Probability sampling allows for the calculation of the desired sample size for the margin of error the researcher will agree to (De Vos et al 2005:198; Polit & Beck 2004:311; Wood & Ross-Kerr 2011:134). The method used for this study was a mix of two sampling methods, also known as stratified sampling (De Vos et al 2005:198; Polit & Beck 2004:311;

Babbie 2005:196; Wood & Ross-Kerr 2011:140).

A mix of two sampling methods promoted the completeness of the study. Stratified sampling was selected because it firstly allowed for the population to be divided into strata or groups, and all units have an equal chance to be included in the sample. Then, purposive sampling was relevant because the population under consideration is small and rare events of maternal mortality and newborn death cases, every cases in the specific study area were considered based on the researcher’s judgement.

3.3.2.1.3 Sampling criteria

Sampling criteria, which is also referred to as ‘eligibility criteria’, involves listing of attributes essential to the study. The sampling criteria also consist of inclusion criteria which are characteristics the subject should have to be included in the study. Also important are exclusion criteria that are characteristics that will exclude a subject from a study (Burns & Grove 2013:234). In this study, the study population for the retrospective study was women who were pregnant or had been recently pregnant or delivered in the last twelve months or delivered; and, newborn babies within 28 days. These are newborn babies and women of any age or nationality but are resident in these Regional States.

The cases eligible for inclusion of maternal and newborn were those which:

 Qualified to be classified as a maternal mortality and newborn death or suspected maternal mortality and newborn death according to the WHO ICD 10 definition.

 The deceased must be resident in the selected three regional states before death.

 The death must have occurred within the selected Hospitals and their catchment area; in other words, the death must have occurred in a health facility (hospital, health centre, health post), in the community or en route to a health facility.

 Death must have occurred between the time intervals of 1^stJuly 2014 to 30^th June 2015.

The exclusion criteria used:

 The death that does not meet the WHO definition of a maternal mortality and newborn death.

 Death occurred out of the study area – Oromia, Amhara and SNNPS Region.

 Death of women and newborn not a resident of the selected hospitals catchment area.

 Deaths of women and newborn not resident within the study area and the hospitals health catchment area will be excluded from the study mainly because including them will mean expanding the study area which would in turn demand extensive travelling for follow up. This will be labour intensive, costly and may make the study unmanageable.

3.3.2.1.4 Sample size

The size of the sample was determined by the fact that each hospitals on average have 10 maternal mortality and 60 newborn death in the previous year; and, projected to have similar or less maternal mortality and newborn death in the coming year. Based on the previous year review and the following year maternal mortality and newborn death projections of the selected hospitals, it was planned to include all expected 60 maternal mortalities and one third of 360 newborn death cases that were expected to take place in 12 months duration of the study period, in the selected six hospitals. Five districts from each zone were randomly selected and community workers were asked to identify maternal mortalities and newborn deaths which have occurred in the district between July 1, 2014, and June 30, 2015, and conducted verbal autopsies with families of the deceased maternal and newborn cases to capture factors and processes leading to the deaths. The 30 districts and the six hospitals were assumed to give us a total of 120 maternal mortality and 240 newborn deaths cases both from the six hospitals and the thirty randomly selected districts for the verbal autopsy. However, due to an overwhelming number of maternal mortality and newborn death cases recorded during the study period, in the study sites; instead a total of 142 maternal and 302 newborn cases were identified for the study. However, based on the inclusion criteria, only 133 maternal and 286 newborn cases were reviewed. All the maternal mortality and one-third of newborn deaths that occurred during the study period as well as in the study area and those cases met the inclusion criteria were included.

Table 3.3: Maternal and Newborn profile of the study area

Regiona l States

Selected

Zone Selected Hospital Total birth in the selected Maternal mortality in the selected

Newborn death in the selected

Districts Hospitals Total Districts Hospitals Total Districts Hospitals Total Oromiya East relevant questions and evaluate conclusions (Harris 2010:107-151; Sapsford & Jupp 2006:23-29). The data collection component of research is common to all fields of study. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The goal for all data collection is to capture quality evidence that then translates to rich data analysis and allows that building of a convincing and credible answer to questions that have been posed.

Literatures have shown that it is difficult to obtain comprehensive information about maternal mortality and newborn deaths (AbouZahr 2000:27-43; WHO 2007a:9-14).

Thus, it became clear that obtaining such information required the use of a variety of sources of information. Due to this reason a combination of approaches were used in this present study. In addition to the informal conversations and investigations; the two main approaches used were confidential enquiry and verbal autopsy as outlined in the WHO guidelines (WHO 2001:17-44; WHO 2007b:1-7; WHO 2012:7-22). In this section, the data collection method for quantitative aspects of verbal autopsy was discussed, and the qualitative aspects were discussed below.

The quantitative aspects of the verbal autopsy (VA) involved questionnaire in the community with family members, relatives (husband, co-wife, sister, in-laws, and parent), neighbours, TBA or HEW, and other people who were knowledgeable about the case). The researcher tried to interview as many people as possible among those