ObjectiveBecause of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers.ParticipantsTwenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention.EvidenceWe conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods.Consensus ProcessFrom the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed.ConclusionsThe proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.

A meta-analysis examined data from 36 studies linking physical activity to well-being in older adults without clinical disorders. The weighted mean-change effect size for treatment groups (d(C). = 0.24) was almost 3 times the mean for control groups (d(C). = 0.09). Aerobic training was most beneficial (d(C). = 0.29), and moderate intensity activity was the most beneficial activity level (d(C). = 0.34). Longer exercise duration was less beneficial for several types of well-being, though findings are inconclusive. Physical activity had the strongest effects on self-efficacy (d(C).= 0.38), and improvements in cardiovascular status, strength, and functional capacity were linked to well-being improvement overall. Social-cognitive theory is used to explain the effect of physical activity on well-being.

The multidimensional approach to the study of anxiety (Martens, Vealey, & Burton, 1990a) considers subcomponents of anxiety, specifically cognitive anxiety, somatic anxiety, and self-confidence. Much of the research based on this theory has utilized the Competitive State Anxiety Inventory (CSAI-2) (Martens, Burton, Vealey, Bump, & Smith, 1990b). Findings have been inconsistent, with some research suggesting that the three subcomponents have separate relationships with performance and other studies failing to find any relationship between the anxiety subcomponents and performance. This meta-analysis examined the effect of state anxiety as measured by the CSAI-2 (i.e., cognitive anxiety, somatic anxiety, and self-confidence) on athletic performance. Studies were coded for characteristics that could potentially moderate the effects of anxiety on performance (i.e., features of design, subjects, sport). Interdependency between the three subscales was examined using multivariate meta-analytic techniques (Becker & Schram, 1994). Relationships among cognitive anxiety, somatic anxiety, self-confidence, and performance appeared weak. Exploratory modeling showed that self-confidence displayed the strongest and most consistent relationship with performance.

Research on methods of meta-analysis (the synthesis of related study results) has dealt with many simple study indices, but less attention has been paid to the issue of summarizing regression slopes. In part this is because of the many complications that arise when real sets of regression models are accumulated. We outline the complexities involved in synthesizing slopes, describe existing methods of analysis and present a multivariate generalized least squares approach to the synthesis of regression slopes.