Comportamiento rural, respecto a la violencia familiar

The design of a study refers to the procedure for collecting, analysing and reporting the research. Four factors are important in determining the type of design for a mixed-methods study (Table 3.3) (Creswell et al 2003). These four factors are variable, as shown in column two, and are closely associated with the purpose of the study. They are each discussed in detail below.

Table 3.3 - Factors to help decide the Design for a Mixed-Methods Study

3.6.1 Implementation of data collection

The implementation of the quantitative and qualitative data collection in a mixed-methods study can either be concurrent or sequential. Data that are collected concurrently are analysed to see the degree to which the quantitative and qualitative findings converge (i.e. triangulation). If collected sequentially, the objectives of the study will determine which data type are collected first (Creswell et al 2003). If quantitative data are collected first using a large sample, qualitative methods are then used to explore aspects in more depth

Factors in Mixed-Methods Designs

Options

Implementation of data collection Concurrent - No sequence Sequential - Qualitative first Sequential – Quantitative first Priority given to each data

collection method

Equal Qualitative Quantitative Stage of Integration At data collection

At data analysis At data interpretation With some combination Theoretical perspective Explicit

Implicit Adapted from Creswell et al (2003), p171.

3.6.2 Priority given to data collection method

The priority given to each type of data also needs to be decided, with options being to give equal priority to quantitative and qualitative data, emphasise quantitative more or emphasise qualitative more (Creswell et al 2003). A decision about priority needs to be explicit at all stages of the research, although this can be problematic. Several factors can help decide on the emphasis including the need to understand data from one method before proceeding and practical constraints with data collection, but it is recognised that the ‘comfort level of the researcher’ with the data types may have the greatest influence (Creswell et al 2003).

3.6.3 Stage of Integration

It is desirable to be explicit at the outset of a mixed-methods study about the timing (i.e. during data collection, analysis and/or interpretation) and nature of the integration of the qualitative and quantitative methods (Creswell et al 2003).

The degree of integration of quantitative and qualitative data varies between studies. A review of 57 ‘early’ mixed-methods studies showed that 25(44%) studies showed no integration at analysis or interpretation; 18(31%) studies analysed qualitative and quantitative data separately, with some integration during interpretation; 5(9%) studies showed integration at both analysis and interpretation; and 9(16%) studies did not report details of their analysis (Greene et al 1989). The total lack of integration was particularly the case when ‘expansion’ was the purpose. They concluded that mixed-methods research is being hindered by a tendency for quantitative and qualitative findings not to be integrated or only integrated to a limited degree (Greene et al 1989).

More recently, Bryman (2006) also observed that of the 232 mixed-methods studies that he analysed only 42 (18%) had genuinely integrated the qualitative and quantitative findings, indicating that this problem remains. Instead, the majority of articles still present parallel accounts of the quantitative and qualitative findings. There have been calls for greater attention to the writing of mixed-method articles in order to ‘genuinely integrate’ quantitative and qualitative findings (Bryman 2007), and to do this across the analysis, interpretation and reporting stages (Caracelli and Greene 1993).

However, there may be situations in which integration at the analysis stage is not appropriate. Caracelli and Greene (1993) have developed this argument in relation to the five purposes of mixed-methods evaluation outlined earlier (Greene et al 1989). In mixed-methods studies involving triangulation, research questions are addressed using different methods to see the extent to which the results agree. Thus, the theory behind triangulation requires an independence of analysis and interpretation of the different data sources, and it would not be appropriate to integrate. This is also the case for mixed-methods studies which have a complementarity purpose where different methods address different aspects within the study, thus making integration at the analysis stage less useful. However, when the purpose of the mixed-methods study is development, initiation or expansion, analysis strategies which integrate the qualitative and quantitative data are desirable and appropriate (Caracelli and Greene 1993). This indicates that decisions about the stage when the data should be integrated depends on the purpose for using mixed-methods.

With regards to the nature of the integration of qualitative and quantitative data, four strategies are available (Caracelli and Greene 1993). First, data transformation involves transforming one type of data into the other type to permit analyses of the data types together. For example, qualitative data is coded into numeric data, which is then used in the analysis alongside quantitative data. This is referred to as ‘quantitising’. Or transformation of quantitative data to qualitative data is referred to as ‘qualitising’ (Sandelowski 2003). Second, typology development involves the analysis of one type of data which places individuals into categories (typologies) which are then used in the analysis of the other data type. Third, extreme case analysis identifies ‘extreme cases’ from one data type which are then analysed further using the other data type, in order to scrutinise the initial explanation for the extreme cases. For example, individuals who dropped out of a study could be interviewed to assess if they differ from those who did not drop out. Fourth, data consolidation or merging involves the review of both data types and then the creation of new variables for use in further analyses. These strategies help in identifying how integration of the analysis of qualitative and quantitative data can be done.

3.6.4 Theoretical perspective

The fourth factor which researchers need to consider when designing mixed- methods research is whether the research is driven by theoretical perspectives held by the researcher (Creswell et al 2003). Deeply held perspectives might include, for example, class, race and gender perspectives such as feminist theory. Some mixed-methods research employs transformative designs in which the goal of the research is to advocate for change either at the individual level or to influence policy at the political level. If a transformative model is used

then it is important that the ‘theoretical lens’ is made explicit in the study. Others feel that all research is influenced by the researchers’ theoretical perspectives (personal communication, M Thorogood).

3.6.5 Six Mixed-Methods Study Designs

The four criteria described above (sections 3.6.1 to 3.6.4) has led Creswell (2003) to identify six mixed-methods study designs (Table 3.4). Three employ sequential implementation of data collection, and three employ concurrent data collection. Thereafter the order and priority of the data collection, the stage of integration and the theoretical perspective describe six distinct study designs.

Table 3.4 - Types of Mixed-Methods Study Designs Design Type Implementation

Sequence Priority Stage of Integration Theoretical perspective Sequential explanatory

Quant - Qual Quant (usual); can be Qual or equal Interpretation May be present Sequential exploratory

Qual - Quant Qual (usual); can be Quant or equal Interpretation May be present Sequential transformative Either:- Quant – Qual or Qual - Quant Quant, Qual or equal Interpretation Definitely present Concurrent triangulation Concurrent collection of Quant & Qual

Equal (preferably); can be Quant or Qual Interpretation or Analysis May be present Concurrent nested Concurrent collection of Quant & Qual

Quant or Qual Analysis May be present Concurrent

transformative

Concurrent collection of Quant & Qual

Quant, Qual or equal Analysis (usual); can be during interpretation Definitely present

SECTION II – Evaluating Interventions for the Treatment of Childhood