Purpose: The 2 × 2 model of perfectionism (Gaudreau and Thompson in Personal Individ Diff 48:532-537, 2010) represents an important addition to the perfectionism literature, but so far has not been studied in relation with disordered eating.
Method: Using the 2 × 2 model as analytic framework, this study examined responses from a convenience sample of 716 participants aged 19-68 years (71% female) investigating how self-oriented perfectionism (SOP) and socially prescribed perfectionism (SPP) predicted individual differences in eating disorder symptoms, additionally controlling for body mass index, gender, and age.
Results: Results showed a significant SOP × SPP interaction indicating that the combination of high SOP and high SPP-called "mixed perfectionism"-was associated with the highest levels of eating disorder symptoms.
Conclusions: The findings demonstrate the utility of the 2 × 2 model of perfectionism as an analytic framework for examining perfectionism and disordered eating. Moreover, they suggest that mixed perfectionism is the most maladaptive form of perfectionism when it comes to disordered eating, such that having high levels of SPP combined with high levels of SOP represents the most maladaptive combination of perfectionism in terms of risk of eating disorder.
Level Of Evidence: Level V, cross-sectional descriptive study.
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http://dx.doi.org/10.1007/s40519-017-0438-1 | DOI Listing |
Angew Chem Int Ed Engl
January 2025
Ritsumeikan University: Ritsumeikan Daigaku, Applied Chemistry, B805 Biolink, 1-1-1 Nojihigashi, 525-8577, Kusatsu, JAPAN.
Inorganic photochromic materials offer several advantages over organic compounds, including relatively inexpensive and higher thermal stability. However, tuning their color with the same component has remained a significant challenge. In this study, we demonstrate that the photochromic color of Cu-doped ZnS nanocrystals (NCs), which is initially pale yellow before light irradiation, can be tuned from gray to brown by adjusting the surface stoichiometry of Zn and S, which is controlled through the use of thiol and non-thiol ligands.
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Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
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Department of General Surgery.
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Department of Cardiovascular Surgery, Xijing Hospital, Xi'an, Shaanxi, China.
Background: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study was to evaluate the AA morphology of patients who had TF-TAVR using an artificial intelligence algorithm and then to evaluate its predictive value for clinical outcomes.
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Background: Detecting kidney trauma on CT scans can be challenging and is sometimes overlooked. While deep learning (DL) has shown promise in medical imaging, its application to kidney injuries remains underexplored. This study aims to develop and validate a DL algorithm for detecting kidney trauma, using institutional trauma data and the Radiological Society of North America (RSNA) dataset for external validation.
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