A Methodological Design For Research Into Child Sex Abuse (CSA): Utilising Secondary Data and the Application of Theoretical Perspectives

A Methodological Design For Research Into Child Sex Abuse (CSA): Utilising Secondary Data and the Application of Theoretical Perspectives

1 Introduction

This paper shall briefly outline one possible methodological design for research into child sex abuse (CSA), by utilising secondary data and applying suitable theoretical perspectives. The approach to be explored is that of a meta-analysis of existing studies, with thematic analysis and grounded theory also drawn upon. Moreover, any ethical considerations in this area will also be considered, before outlining a structural-functionalist and rational choice theory approach, as lenses to be applied to this analysis.

2 Choosing a Research Design

2.1 Understanding the Meta-Analyses Approach

In cases where time and resources are limited, primary data often cannot be collected. Therefore, a meta-analysis of primary data in existing studies seems to be one of the most pragmatic and sensible ways forwards in creating a contributory piece of research in this field. Wampold (2000) explains that meta-analysis refers to a class of statistical methods that combine results from a series of studies that all address the same (or a similar) research question. Thus, by using this method, a hypothesis can be tested that cannot be answered clearly with one study; while it also eliminates any ambiguity that can result from narrative reviews, or from counting the number of studies that support a particular conclusion (Wampold, 2000). This then, is a technique that can be used to reach firm and confident conclusions through a vast cumulative sample.

In addition, Borenstein, Hedges, Higgins & Rothstein (2011) also look at why researchers perform meta-analyses, and what the advantages are of it as a methodology, and go on to say that it is important to understand whether a set of results in a research study is consistent across the body of data available, or whether it varies substantially from study to study. Thus: “we want to quantify the extent of the variance and consider the implications” (Borenstein, Hedges, Higgins & Rothstein, 2011, n.p.). Furthermore, what a meta-analysis also does is to move beyond questions of statistical significance (with statistically insignificant results often being the result of small sample sizes), and to address questions that are much more interesting and relevant (Borenstein, Hedges, Higgins & Rothstein, 2011). Moreover, by synthesising results from a wide range of studies, and looking at the cumulative samples and results, it is possible to gain statistically significant results from what are individually small sample sizes in a number of studies that have little value when viewed in isolation. Furthermore, on the subject of meta-analyses, Schulze (2004, p. 3) also says that as research in the social sciences is growing at such a rapid pace, it is virtually impossible for a researcher to keep track of all relevant published articles, and so there is a strong need for summaries of recent theoretical and empirical results. A ‘meta-analysis’ then, can be seen as a systematic review of studies done in a particular area (Pigott, 2012, p. 2), from which the results can then be synthesised to weed out any errors or deficiencies in individual studies, and to come to an overall conclusion based upon these cumulative studies.

2.2 Thematic Analysis and Grounded Theory

However, in addition to carrying out a meta-analysis, the use of thematic analysis (Guest, MacQueen & Namey, 2012) can also be used for any qualitative studies, which is one of the most common forms of analysis in qualitative research in the social sciences, as it identifies patterns within datasets, which can then be used to comment on a particular research question or overall hypothesis when looking at various studies. However, this method does rely on some degree of interpretation from the researcher, and so any researcher bias has to be carefully guarded against (Guest, MacQueen & Namey, 2012). In addition, Guest, MacQueen & Namey (2012) also state that:

“Thematic analyses move beyond counting explicit words or phrases and focus on identifying and describing both implicit and explicit ideas within the data, that is, themes. Codes are then typically developed to represent the identified themes and applied or lined to raw data as summary markers for later analysis… Generally speaking, reliability is of greater concern with thematic analysis than with word-based analyses because more interpretation goes into defining the data items” (p. 11).

As such, a good deal of reflection is needed to ensure that these themes and the research do not amount to a self-fulfilled prophecy of sorts, and the researcher essentially fitting the data into a preconceived idea about what the results will be (either consciously, or unconsciously). However, by using this approach in conjunction with a meta-an