Prognostic value of lymph node ratio and extramural vascular invasion on survival for patients undergoing curative colon cancer resection

There was no study funding. We are grateful to Tony Rafferty (Tailored Information for the People of Scotland, TIPs) for providing survival data.Peer reviewedPublisher PD

A prudent path forward for genomic engineering and germline gene modification

A framework for open discourse on the use of CRISPR-Cas9 technology to manipulate the human genome is urgently needed

Validation of the Short Version (TLS-15) of the Triangular Love Scale (TLS-45) Across 37 Languages

Love is a phenomenon that occurs across the world and affects many aspects of human life, including the choice of, and process of bonding with, a romantic partner. Thus, developing a reliable and valid measure of love experiences is crucial. One of the most popular tools to quantify love is Sternberg’s 45-item Triangular Love Scale (TLS-45), which measures three love components: intimacy, passion, and commitment. However, our literature review reveals that most studies (64%) use a broad variety of shortened versions of the TLS-45. Here, aiming to achieve scientific consensus and improve the reliability, comparability, and generalizability of results across studies, we developed a short version of the scale—the TLS-15—comprised of 15 items with 5-point, rather than 9-point, response scales. In Study 1 (N = 7,332), we re-analyzed secondary data from a large-scale multinational study that validated the original TLS-45 to establish whether the scale could be truncated. In Study 2 (N = 307), we provided evidence for the three-factor structure of the TLS-15 and its reliability. Study 3 (N = 413) confirmed convergent validity and test–retest stability of the TLS-15. Study 4 (N = 60,311) presented a large-scale validation across 37 linguistic versions of the TLS-15 on a cross-cultural sample spanning every continent of the globe. The overall results provide support for the reliability, validity, and cross-cultural invariance of the TLS-15, which can be used as a measure of love components—either separately or jointly as a three-factor measure

The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings