Meadows noted that:
without a well-defined and specific research question or hypothesis, even if the research is carried out to the end, it is unlikely to provide much information. (Meadows, 2003, p. 397)
Hence, this is acknowledged to be a crucial phase of any research study. Providing sufficient detail and focus at this stage guides the researcher to make robust decisions about how relevant data will be gathered and analysed.
Hypotheses are generally declarative statements which predict the outcome of a research study (Cormack, 2000). Pawson and Tilley clearly outline how this applies within realist research:
programme theories are tested for the purpose of refining them. The basic question asked, and hopefully answered, is thus multi-faceted. Realist evaluation asks not, ‘ӧhat works?’ or, ‘Does this program work?’ but asks instead, ‘ӧhat works for whom in what circumstances and in what respects, and how?’ (Pawson and Tilley, 2004, p. 2)
So, the scientific discourse of the natural sciences, such as the ‘null hypothesis’, and the ‘intervention’ do not fit with the purpose of this study. The intervention is ‘the mechanisms within the programme’, and the hypothesis was developed around exploring what it was about the programme that worked, or not. As Pawson and Tilley (1997, p. 77) note, ‘evaluators will always construct their explanations around three crucial ingredients of any initiative: context (C), mechanism (M) and outcome (O)’. They acknowledge the likelihood of variation in the effectiveness of mechanisms, and the outcomes, depending upon the context in which they are introduced. This is expected within research conducted within a higher stratum of reality, as in this study. Pawson and Tilley (1997, p. 58) called this ‘generative causation’, accepting that there will be ‘interplay between mechanisms operating in a particular context’ (Powell, et al., 2010, p. 6). This is summarised in figure 1.3.
35
Context (C)
Mechanism (M)
An actionis causal only if…
Outcome (O) …its outcome is triggered by a mechanism acting in context
Figure 1.3 Generative causation (Pawson and Tilley, 1997, p. 58).
This could be considered congruent with the realist view of causation already discussed, on page 27. So, it is necessary to articulate how these three elements might come together, to address the main aim of the study, and to make clear in what configuration they are being employed. Hence, data were collected to test the following research hypothesis:
The mechanisms within an educational programme (M1 - M16), delivered in
the clinical learning environment (C) will improve the attitudes of nursing students toward caring for ill older people (O).
The mechanisms referred to in this hypothesis (M1 - M16), are identified and
expanded upon in chapter three, along with the identification of the context for programme delivery.
A number of secondary questions related to this hypothesis were identified, related to whether or not a programme effect of any type would be demonstrated, as follows:
If an effect is demonstrated within the context of the clinical learning environment, what was it about the programme that worked, and who did it ‘work’ for?
36 If no effect is demonstrated within the context of the clinical learning
environment, what mechanisms within this context made it inhospitable to the operation of programme mechanisms?
In order to address the hypothesis and secondary questions, the study was designed as follows: the attitudes of two separate groups of nursing students toward working with ill older people were measured, using McLafferty’s Attitude Scoring Tool (MAST - McLafferty, 2001), over a period of twenty months, at identical points in time; the groups were studying at different Universities, and both had just commenced their two-year ‘adult’ field of practice programme. There were five-week intervals between these measurements being made, which was decided following pre-testing. The PG attended the educational programme related to the nursing care of ill older people, whilst on clinical placement, and supplementary to pre-registration education. The CG did not know about, or attend the educational programme, but completed MAST at the same intervals, or data points, as the PG. Both groups of students were in the ‘adult’ field of practice of their particular pre-registration nurse education programme, so each group was likely to encounter ill older people throughout the course of their clinical placements (NMC, 2010). The attitudinal measurements for the PG were ‘interrupted’ after the seventh measurement by the educational programme.
The ‘care of older people’ is a theme which is integrated throughout the curriculum being studied by the PG. This means that the ‘older person’, and ‘ageing’ as concepts were not explicitly examined in modular format, by the PG, but rather were studied as a theme throughout the two-year ‘adult’ field of practice programme. The CG, on the other hand, studied a module on the care of older people, upon commencement of their ‘adult’ field of practice programme. Despite these two groups having had exposure to different educational programmes, this can be accounted for to some extent, during the visual inspection of the time-series, once
37 created. A sustained difference in attitude scores between both groups might be seen, if this difference in the content of their pre-registration programmes were having an effect upon attitudinal scores. The baseline measures made at the start of the study would also allow a judgement to be made about whether there were marked differences in attitude scores for each group. Additionally, any effect of the educational programme employed in this study, if realised, would still be apparent in the PG scores, when assessed alongside CG scores. The level of scores across the time series may be different for each group, but a programme effect would still be clearly seen (Ramsay, et al., 2003).
A further eight measures of the attitudes of both groups were made after the programme had been delivered. Repeated measures analysis was used to look for significant effects, both immediately after the programme, and at the end of the study, ten months after programme delivery (Pallant, 2007)1.
1:7 Populations and Samples
As Parahoo (2006) notes, when designing research, a central task is to make a decision about who will be invited to participate, and in what numbers. The ‘theoretical population’, which is made up of ‘all the units of a population’, is the one from which a sample can be drawn for the purposes of research (Parahoo, 2006, p. 257). In this study, this was governed by the size of the individual cohorts of students approached at each University, and the PG and CG were recruited through the process of gaining informed consent.
1
Study timelines, as applied to each group, are included as appendices, referenced within chapter three.
38 Probability sampling is a technique whereby ‘the chance of selection for each unit is known in advance’ (Parahoo, 2006, p. 259). This approach was used to select a sub-sample of ten students from each consented sample, at each data point, through a process of simple random sampling. This sub-sampling technique was used as a means of generating sufficient data to measure attitudes, whilst also trying to keep potential respondents in their respective groups, in order that the PG and CG remained comparable, by making sure that respondents were not over- burdened by repeated testing (Jaegar, 1997). This is discussed more fully in chapter three.