Meta-analysis of quasi-experimental research: are systematic narrative reviews indicated?
BACKGROUND
Meta-analyses are commonly performed on quasi-experimental studies in medical education and other applied field settings, with little or no apparent concern for biases and confounds present in the studies synthesised. The implicit assumption is that the biases and confounds are randomly distributed across the studies and are averaged or cancelled out by the synthesis.


OBJECTIVE
We set out to consider the possibility that the results and conclusions of meta-analyses in medical education are subject to biases and confounds and to illustrate this possibility with a re-examination of the studies synthesised in an important, recently published meta-analysis of problem-based learning.


METHODS
We carefully re-examined the studies in the meta-analysis. Our aims were to identify obvious biases and confounds that provided plausible alternative explanations of each study's results and to determine whether these threats to validity were considered and convincingly ruled out as plausible rival hypotheses.


RESULTS
Ten of the 11 studies in the meta-analysis used quasi-experimental designs; all 10 were subject to constant biases and confounds that favoured the intervention condition. Threats to validity were not ruled out in the individual studies, nor in the meta-analysis itself.


CONCLUSIONS
Our re-examination of the results and conclusions of the meta-analysis illustrates our concerns about the validity of meta-analyses based primarily on quasi-experimental studies. Our tentative conclusion is that the field of medical education might be better served in most instances by systematic narrative reviews that describe and critically evaluate individual studies and their results in light of threats to their validity.
Colliver
Jerry A
JA
Statistics and Research Consulting, Southern Illinois University School of Medicine, Springfield, Illinois 62794-9623, USA. jcolliver@siumed.edu
Kucera
Kathryn
K
Verhulst
Steven J
SJ
D015982:Bias; D015201:Meta-Analysis as Topic; D033262:Narration; D018794:Problem-Based Learning; D012107:Research Design; D012196:Review Literature as Topic