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The less obvious effect of hosting the Olympics on sporting performance.

ABSTRACT: Hosting the Olympics has long been claimed to bring a financial return on investment. When this cannot clearly demonstrated, the medal surplus associated with host status is usually highlighted. We investigate the magnitude of having a home advantage at the recent Summer Olympic Games (1996-2021) separately for each organising country and by gender. Beside the host effect, the ex-ante and post impact on the medal surplus is also investigated in the same way. We analyse this effect using three models at the level of total medals, and medals won by men, and by women. Because of the number of zero observation in the response variable, we employ a zero-inflated negative binomial estimator. Our results cast some doubt on the claim of a host effect of the Olympics: when we control for socioeconomic variables in the models, the host effect fades away. Any host effect is clearer for medals won by men. Ex-ante and post effects on host countries are detectable in some cases but also fade with the inclusion of control variables. Based on our results, the medal surplus associated with the hosting of the Olympics is less evident than reported in literature or public discourse.

SUBMITTER: Csurilla G

PROVIDER: S-EPMC9895060 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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The less obvious effect of hosting the Olympics on sporting performance.

Csurilla Gergely G Fertő Imre I

Scientific reports 20230202 1

Hosting the Olympics has long been claimed to bring a financial return on investment. When this cannot clearly demonstrated, the medal surplus associated with host status is usually highlighted. We investigate the magnitude of having a home advantage at the recent Summer Olympic Games (1996-2021) separately for each organising country and by gender. Beside the host effect, the ex-ante and post impact on the medal surplus is also investigated in the same way. We analyse this effect using three mo ...[more]

PMID: 36732572

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Project description:BackgroundTo investigate the influence of artificial intelligence (AI) based on deep learning on the diagnostic performance and consistency of inexperienced cardiovascular radiologists.MethodsWe enrolled 196 patents who had undergone both coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) within 6 months. Four readers with less cardiovascular experience (Reader 1-Reader 4) and two cardiovascular radiologists (level II, Reader 5 and Reader 6) evaluated all images for ≥ 50% coronary artery stenosis, with ICA as the gold standard. Reader 3 and Reader 4 interpreted with AI system assistance, and the other four readers interpreted without the AI system. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (area under the receiver operating characteristic curve (AUC)) of the six readers were calculated at the patient and vessel levels. Additionally, we evaluated the interobserver consistency between Reader 1 and Reader 2, Reader 3 and Reader 4, and Reader 5 and Reader 6.ResultsThe AI system had 94% and 78% sensitivity at the patient and vessel levels, respectively, which were higher than that of Reader 5 and Reader 6. AI-assisted Reader 3 and Reader 4 had higher sensitivity (range + 7.2-+ 16.6% and + 5.9-+ 16.1%, respectively) and NPVs (range + 3.7-+ 13.4% and + 2.7-+ 4.2%, respectively) than Reader 1 and Reader 2 without AI. Good interobserver consistency was found between Reader 3 and Reader 4 in interpreting ≥ 50% stenosis (Kappa value = 0.75 and 0.80 at the patient and vessel levels, respectively). Only Reader 1 and Reader 2 showed poor interobserver consistency (Kappa value = 0.25 and 0.37). Reader 5 and Reader 6 showed moderate agreement (Kappa value = 0.55 and 0.61).ConclusionsOur study showed that using AI could effectively increase the sensitivity of inexperienced readers and significantly improve the consistency of coronary stenosis diagnosis via CCTA. Trial registration Clinical trial registration number: ChiCTR1900021867. Name of registry: Diagnostic performance of artificial intelligence-assisted coronary computed tomography angiography for the assessment of coronary atherosclerotic stenosis.

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The less obvious effect of hosting the Olympics on sporting performance.

Publications

The less obvious effect of hosting the Olympics on sporting performance.

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