Miscellaneous Statistics, Public Health, Sociology

“However noble the goal, research findings should be reported accurately. Distortion of results often occurs not in the data presented but . . . in the abstract, discussion, secondary literature and press releases. Such distortion can lead to unsupported beliefs about what works for obesity treatment and prevention. Such unsupported beliefs may in turn adversely affect future research efforts and the decisions of lawmakers, clinicians and public health leaders.”

FavoriteLoadingAdd to favorites

David Allison points us to this article by Bryan McComb, Alexis Frazier-Wood, John Dawson, and himself, “Drawing conclusions from within-group comparisons and selected subsets of data leads to unsubstantiated conclusions.” It’s a letter to the editor for the Australian and New Zealand Journal of Public Health, and it begins: [In the paper, “School-based systems change for obesity prevention in adolescents: Outcomes of the Australian Capital Territory ‘It’s Your Move!’”] Malakellis et al. conducted an ambitious quasi-experimental evaluation of “multiple initiatives at [the] individual, community, and school policy level to support healthier nutrition and physical activity” among children.1 In the Abstract they concluded, “There was some evidence of effectiveness of the systems approach to preventing obesity among adolescents” and cited implications for public health as follows: “These findings demonstrate that the use of systems methods can be effective on a small…
Original Post: “However noble the goal, research findings should be reported accurately. Distortion of results often occurs not in the data presented but . . . in the abstract, discussion, secondary literature and press releases. Such distortion can lead to unsupported beliefs about what works for obesity treatment and prevention. Such unsupported beliefs may in turn adversely affect future research efforts and the decisions of lawmakers, clinicians and public health leaders.”