Original ArticlesMeta-analysis of studies assessing the efficacy of projective techniques in discriminating child sexual abuse
Introduction
HOW WELL PROJECTIVE instruments discriminate between sexually abused and nonabused children is evaluated by this author through the application of meta-analytic strategies Cohen 1988, Howell 1992, Hunter and Schmidt 1990, Rosenthal 1987, Rosenthal and Rosnow 1991, Wolfe 1986. Meta-analysis is concerned with drawing inferences about an area of research from the results of many different studies. Meta-analysis has become associated with one set of diverse techniques, largely due to a seminal paper by Glass (1976), who categorized three levels of analysis:
- 1.
Primary analysis: the original analysis of data from a research study.
- 2.
Secondary analysis: the re-analysis of the data from a research study.
- 3.
Meta-analysis: the statistical analysis of results from a large number of individual research studies so as to integrate their findings (pp. 3–8).
The statistical techniques incorporated by meta-analysis vary in complexity. In the most commonly used meta-analytic techniques, the common statistic selected is an effect-size measure, an index of how large or strong the relationship is between the variables. There are six stages (as cited in Brakewell, Hammond, & Fife-Shaw, 1995) involved in the Glass meta-analytic procedure (item 3 above):
- 1.
Select the independent and dependent variables of interest.
- 2.
Identify, locate and obtain all relevant and usable studies containing information of interest.
- 3.
Code each study for characteristics which might be a predictor of study outcomes, that is, might relate to the size of effects obtained.
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Calculate estimates of the effect-size (ES) for the variable pairs (independent-dependent) of interest.
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Calculate estimates of the effect-size across studies.
- 6.
Examine those study characteristics identified in (3) above which correlate with study effects (p. 391).
The analysis that follows applies the steps of the Glass (as cited in Brakewell et al., 1995) procedure with modification and the addition of recommendations by Hunter and Schmidt (1990) in order to assess the relationship between various projective instruments and identification of childhood sexual abuse (CSA). The modification is the restriction of sources from selected data bases (PsychLit, Eric, Psych Abstracts, and Medline). This decision extends the complication of the “File drawer problem” (Hunter & Schmidt, 1990, p. 506), which refers to the fact that journals tend to include studies that contain Type I errors and exclude the studies that contain Type II errors. Using Orwin’s (1983) formula for calculating the number of studies that would be needed to lower the ES to a small effect, it was determined that 38 studies with small or insignificant findings would be needed to over-turn the present ES. In addition, studies included in this analysis have been selected from a specific ten-year period, which further biases the sample. The restriction of databases and time period prohibits this analysis from being identified as a comprehensive meta-analytic review. It is, rather, a demonstration of applying selected statistical strategies to generate a minimum effect size which can then be used to examine the efficacy of certain projectives in assessing child sexual abuse. It can also be useful in a prospective power analysis of particular projectives in discriminating sexually abused children from nonsexually abused children.
Section snippets
Procedure
The data base sample of 16 studies employed 9 projective instruments. Twelve of these studies used projective instruments to assess sexually abused children, and four studies used projectives with physically abused children. All included two or more groups and were published between 1986 and 1996. The data reported in all of these studies are appropriate for calculation of effect size. The Rorschach Inkblot Test (Rorschach, 1921) was used in three of the studies and the TAT (Murray, 1943) in
Review of studies
Six of the studies on sexual abuse were designed to include a clinic group of psychiatric or distressed subjects who were not sexually abused. Most assessment instruments seem to be able to discriminate between child sexual abuse subjects and a normal group of subjects. However, all that can be inferred in this case is that the instrument is able to detect some type of distress from nondistress. The inclusion of a clinical group with no history of sexual abuse is important because it creates
Discussion
All of the 16 studies reached a common conclusion: projective techniques can identify children who have been sexually or physically abused from nondistressed children. The 12 studies of sexual abuse assessment in children that have been reviewed here all showed medium to large effect sizes with an average d = .81, a large ES (Table 4). This offers data about the ability of the various projective techniques to significantly discriminate between children with a known history of sexual abuse and
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