a b s t r a c t a r t i c l e i n f oAfter an unbroken series of positive, but underpowered studies seemed to demonstrate Type D personality predicting mortality in cardiovascular disease patients, initial claims now appear at least exaggerated and probably false. Larger studies with consistently null findings are accumulating. Conceptual, methodological, and statistical issues can be raised concerning the construction of Type D personality as a categorical variable, whether Type D is sufficiently distinct from other negative affect variables, and if it could be plausibly assumed to predict mortality independent of depressive symptoms and known biomedical factors, including disease severity. The existing literature concerning negative affect and health suggests a low likelihood of discovering a new negative affect variable that independently predicts mortality better than its many rivals. The apparent decline effect in the Type D literature is discussed in terms of the need to reduce the persistence of false positive findings in the psychosomatic medicine literature, even while preserving a context allowing risk-taking and discovery. Recommendations include greater transparency concerning research design and analytic strategy; insistence on replication with larger samples before accepting "discoveries" from small samples; reduced confirmatory bias; and availability of all relevant data. Such changes would take time to implement, face practical difficulties, and run counter to established practices. An interim solution is for readers to maintain a sense of pre-discovery probabilities, to be sensitized to the pervasiveness of the decline effect, and to be skeptical of claims based on findings reaching significance in small-scale studies that have not been independently replicated.© 2012 Elsevier Inc. All rights reserved.
IntroductionMany "discoveries" turn out to be exaggerated or simply false across diverse research areas and disciplines. John Ioannidis [1] provoked concern with his demonstration that of the 49 most cited clinical research studies in major journals, replications of 34 had been attempted, and 41% of key findings had been refuted or shown to be substantially diminished. In a subsequent paper [2] he offered evidence that "most claimed research findings are false" and he and others [3-6] have since identified some mechanisms by which discoveries appear in the literature and then undergo a decline or refutation. Claims of breakthrough discoveries frequently arise in small positive studies that would seem to be too underpowered to detect an effect, and the inadequate sample size makes findings all the more attention grabbing.Yet, portrayals in the literature of such "discoveries" ignore the larger context of a strong confirmatory bias in published research papers, with unknown numbers of negative findings not being published and findings being declared discoveries simply because of having achieved an arbitrary level of significance. Moreover, statistically significant findings in small studies are nece...