Is What We See What We Get? Rethinking Prototypical Leadership

The COVID-19 pandemic disrupted traditional workplace channels by restricting social interaction. This disruption exposed the vulnerability of boundary roles and forced leaders to confront extraordinary challenges under unfavorable conditions. The global crisis enriched organizational leadership scholarship and practice by challenging long-standing assumptions about leadership traits and behavior. We examine contemporary leadership theories using an integrative literature review. We synthesize diverse concepts of leader effectiveness through the lens of Implicit Leader Theories (ILTs), which depend upon the organizational culture and context, and present our findings as a conceptual model for use as a heuristic tool by scholar-practitioners. Our research identified a reciprocal relationship between ILTs and leadership traits. ILTs form through a three-step sensemaking process that shapes individual values, attitudes, work intentions, and behaviors. Such implicit leadership theories guide the collective evaluation of leader effectiveness by informing the archetypes of how a leader should behave and what a leader should be. When actual leader traits manifest, the sensemaking process evaluates effectiveness to rationalize such behaviors, thereby refining the collective ILT. Our research extends scholarly understanding of leadership theories by integrating multiple streams into a unified, contingency-oriented conceptual model for scholar-practitioners

(Semi)automated approaches to data extraction for systematic reviews and meta-analyses in social sciences: A living review protocol

Background: An abundance of rapidly accumulating scientific evidence presents novel opportunities for researchers and practitioners alike, yet such advantages are often overshadowed by resource demands associated with finding and aggregating a continually expanding body of scientific information. Across social science disciplines, the use of automation technologies for timely and accurate knowledge synthesis can enhance research translation value, better inform key policy development, and expand the current understanding of human interactions, organizations, and systems. Ongoing developments surrounding automation are highly concentrated in research for evidence-based medicine with limited evidence surrounding tools and techniques applied outside of the clinical research community. Our objective is to conduct a living systematic review of automated data extraction techniques supporting systematic reviews and meta-analyses in the social sciences. The aim of this study is to extend the automation knowledge base by synthesizing current trends in the application of extraction technologies of key data elements of interest for social scientists. Methods: The proposed study is a living systematic review employing a partial replication framework based on extant literature surrounding automation of data extraction for systematic reviews and meta-analyses. Protocol development, base review, and updates follow PRISMA standards for reporting systematic reviews. This protocol is preregistered in OSF: (Semi)Automated Approaches to Data Extraction for Systematic Reviews and Meta-Analyses in Social Sciences: A Living Review Protocol on August 14, 2022. Conclusions: Anticipated outcomes of this study include: (a) generate insights supporting advancement in transferring existing reliable methods to social science research; (b) provide a foundation for protocol development leading to enhancement of comparability and benchmarking standards across disciplines; and (c) uncover exigencies that spur continued value-adding innovation and interdisciplinary collaboration for the benefit of the collective systematic review community

Significance of Thymosin β4 and Implication of PINCH-1-ILK-α-Parvin (PIP) Complex in Human Dilated Cardiomyopathy

Myocardial remodeling is a major contributor in the development of heart failure (HF) after myocardial infarction (MI). Integrin-linked kinase (ILK), LIM-only adaptor PINCH-1, and α-parvin are essential components of focal adhesions (FAs), which are highly expressed in the heart. ILK binds tightly to PINCH-1 and α-parvin, which regulates FA assembly and promotes cell survival via the activation of the kinase Akt. Mice lacking ILK, PINCH or α-parvin have been shown to develop severe defects in the heart, suggesting that these proteins play a critical role in heart function. Utilizing failing human heart tissues (dilated cardiomyopathy, DCM), we found a 2.27-fold (p<0.001) enhanced expression of PINCH, 4 fold for α-parvin, and 10.5 fold (p<0.001) for ILK as compared to non-failing (NF) counterparts. No significant enhancements were found for the PINCH isoform PINCH-2 and parvin isoform β-parvin. Using a co-immunoprecipitation method, we also found that the PINCH-1-ILK-α-parvin (PIP) complex and Akt activation were significantly up-regulated. These observations were further corroborated with the mouse myocardial infarction (MI) and transaortic constriction (TAC) model. Thymosin beta4 (Tβ4), an effective cell penetrating peptide for treating MI, was found to further enhance the level of PIP components and Akt activation, while substantially suppressing NF-κB activation and collagen expression—the hallmarks of cardiac fibrosis. In the presence of an Akt inhibitor, wortmannin, we show that Tβ4 had a decreased effect in protecting the heart from MI. These data suggest that the PIP complex and activation of Akt play critical roles in HF development. Tβ4 treatment likely improves cardiac function by enhancing PIP mediated Akt activation and suppressing NF-κB activation and collagen-mediated fibrosis. These data provide significant insight into the role of the PIP-Akt pathway and its regulation by Tβ4 treatment in post-MI

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution.C.L. was supported by the Vienna Science and Technology Fund (WWTF VRG13-007); L.M.D. was supported by ERC 647910 (KINSHIP); D.I.B. and N.I. received funding from CONICET, Argentina; L.K., F.K. and Á. Putz were supported by the European Social Fund (EFOP-3.6.1.-16-2016-00004; ‘Comprehensive Development for Implementing Smart Specialization Strategies at the University of Pécs’). K.U. and E. Vergauwe were supported by a grant from the Swiss National Science Foundation (PZ00P1_154911 to E. Vergauwe). T.G. is supported by the Social Sciences and Humanities Research Council of Canada (SSHRC). M.A.V. was supported by grants 2016-T1/SOC-1395 (Comunidad de Madrid) and PSI2017-85159-P (AEI/FEDER UE). K.B. was supported by a grant from the National Science Centre, Poland (number 2015/19/D/HS6/00641). J. Bonick and J.W.L. were supported by the Joep Lange Institute. G.B. was supported by the Slovak Research and Development Agency (APVV-17-0418). H.I.J. and E.S. were supported by a French National Research Agency ‘Investissements d’Avenir’ programme grant (ANR-15-IDEX-02). T.D.G. was supported by an Australian Government Research Training Program Scholarship. The Raipur Group is thankful to: (1) the University Grants Commission, New Delhi, India for the research grants received through its SAP-DRS (Phase-III) scheme sanctioned to the School of Studies in Life Science; and (2) the Center for Translational Chronobiology at the School of Studies in Life Science, PRSU, Raipur, India for providing logistical support. K. Ask was supported by a small grant from the Department of Psychology, University of Gothenburg. Y.Q. was supported by grants from the Beijing Natural Science Foundation (5184035) and CAS Key Laboratory of Behavioral Science, Institute of Psychology. N.A.C. was supported by the National Science Foundation Graduate Research Fellowship (R010138018). We acknowledge the following research assistants: J. Muriithi and J. Ngugi (United States International University Africa); E. Adamo, D. Cafaro, V. Ciambrone, F. Dolce and E. Tolomeo (Magna Græcia University of Catanzaro); E. De Stefano (University of Padova); S. A. Escobar Abadia (University of Lincoln); L. E. Grimstad (Norwegian School of Economics (NHH)); L. C. Zamora (Franklin and Marshall College); R. E. Liang and R. C. Lo (Universiti Tunku Abdul Rahman); A. Short and L. Allen (Massey University, New Zealand), A. Ateş, E. Güneş and S. Can Özdemir (Boğaziçi University); I. Pedersen and T. Roos (Åbo Akademi University); N. Paetz (Escuela de Comunicación Mónica Herrera); J. Green (University of Gothenburg); M. Krainz (University of Vienna, Austria); and B. Todorova (University of Vienna, Austria). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.https://www.nature.com/nathumbehav/am2023BiochemistryGeneticsMicrobiology and Plant Patholog

To which world regions does the valence–dominance model of social perception apply?

Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov’s methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov’s original analysis strategy, the valence–dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence–dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world

Updated Supplemental Files: (Semi)Automated Approaches to Data Extraction for Systematic Reviews and Meta-Analyses in Social Sciences: A Living Review Protocol

Background: An abundance of rapidly accumulating scientific evidence presents novel opportunities for researchers and practitioners alike, yet such advantages are often overshadowed by resource demands associated with finding and aggregating a continually expanding body of scientific information. Across social science disciplines, the use of automation technologies for timely and accurate knowledge synthesis can enhance research translation value, better inform key policy development, and expand the current understanding of human interactions, organizations, and systems. Ongoing developments surrounding automation are highly concentrated in research for evidence-based medicine with limited evidence surrounding tools and techniques applied outside of the clinical research community. Objective: Our objective is to conduct a living systematic review of automated data extraction techniques supporting systematic reviews and meta-analyses in the social sciences. The aim of this study is to extend the automation knowledge base by synthesizing current trends in the application of extraction technologies of key data elements of interest for social scientists. Methods: The proposed study is a living systematic review employing a partial replication framework based on extant literature surrounding automation of data extraction for systematic reviews and meta-analyses. Protocol development, base review, and updates follow PRISMA standards for reporting systematic reviews. Conclusions: Anticipated outcomes of this study include: (a) generate insights supporting advancement in transferring existing reliable methods to social science research; (b) provide a foundation for protocol development leading to enhancement of comparability and benchmarking standards across disciplines; and (c) uncover exigencies that spur continued value-adding innovation and interdisciplinary collaboration for the benefit of the collective systematic review community

(Semi)Automated Approaches to Data Extraction for Systematic Reviews and Meta-Analyses in Social Sciences: A Living Review Protocol

Keywords: Automated Data Extraction, Systematic Review, Meta-Analysis, Evidence Synthesis, Social Science Research, APA JAR