Is Infidelity Predictable? Using Explainable Machine Learning to Identify the Most Important Predictors of Infidelity.

Infidelity can be a disruptive event in a romantic relationship with a devastating impact on both partners' well-being. Thus, there are benefits to identifying factors that can explain or predict infidelity, but prior research has not utilized methods that would provide the relative importance of each predictor. We used a machine learning algorithm, random forest (a type of interpretable highly non-linear decision tree), to predict in-person and online infidelity across two studies (one individual and one dyadic, N = 1,295). We also used a game theoretic explanation technique, Shapley values, which allowed us to estimate the effect size of each predictor variable on infidelity. The present study showed that infidelity was somewhat predictable overall and interpersonal factors such as relationship satisfaction, love, desire, and relationship length were the most predictive of online and in person infidelity. The results suggest that addressing relationship difficulties early in the relationship may help prevent infidelity

Understanding Stress In The Operating Room: A Step Toward Improving The Work Environment

Job-related stress is an important factor predicting staff satisfaction and position turnover among nursing staff, particularly in the operating room. The purpose of this study was to examine the perceived amount of stress elicited by events in the perioperative environment, the frequency of those events, and the impact of those events on the perceived stress of operating room nurses (ORNs) and operating room technologists (ORTs). The Survey on Stress in the OR instrument, which was used to query the subjects, exhibited high internal consistency of all items. The findings indicated that the ORNs and the ORTs exhibited remarkable similarities between stressful events perceived as high and low impact. The two groups agreed that the highest impact stressful event was pressure to work more quickly. Using the results of this study, OR administrators may be able to redesign the OR environment to minimize the impact of stressful events and thereby improve job satisfaction and minimize nursing staff turnover

Natural History Of Syphilitic Aortitis

No large studies of cardiovascular syphilis at necropsy have been reported since 1964. We examined at necropsy 90 patients who had characteristic morphologic findings of syphilitic aortitis. None had ever undergone cardiovascular surgery. With the exception of 2 cases seen more recently, the hearts and aortas of the 90 patients were examined and categorized by one of us (W.C.R.) from 1966 to 1990. All 90 had extensive involvement of the tubular portion of the ascending aorta by the syphilitic process, which spared the sinuses of Valsalva in all but 4 patients. The aortic arch was also involved in 49 (91%) of 54 patients and the descending thoracic aorta in 47 (90%) of 52 patients. Syphilis was the cause of death in 23 (26%) of the 90 patients. It was secondary to rupture of the ascending or descending thoracic aorta in 12, severe aortic regurgitation leading to heart failure in 10, and severe narrowing of the aortic ostium of the right coronary artery in 1 patient. Of the 40 patients who had undergone serologic testing for syphilis, 28 (70%) had a positive (reactive) finding. Those patients with a negative or nonreactive test or who did not undergo a serologic test for syphilis had morphologic and histologic findings in the aorta at necropsy similar to the findings of those patients who had had a positive serologic test for syphilis. In conclusion, cardiovascular syphilis has not disappeared. In patients with dilated ascending aortas, with or without aortic regurgitation, a serologic test for syphilis is recommended. If the findings are positive or if characteristic morphologic features of cardiovascular syphilis are suspected, irrespective of the results of the serologic tests, antibiotic therapy appears desirable. (C) 2009 Elsevier Inc. All rights reserved. (Am J Cardiol 2009;104:1578-1587)Integrative Biolog

Identifying the strongest self-report predictors of sexual satisfaction using machine learning

Sexual satisfaction has been robustly associated with relationship and individual well-being. Previous studies have found several individual (e.g., gender, self-esteem, and attachment) and relational (e.g., relationship satisfaction, relationship length, and sexual desire) factors that predict sexual satisfaction. The aim of the present study was to identify which variables are the strongest, and the least strong, predictors of sexual satisfaction using modern machine learning. Previous research has relied primarily on traditional statistical models which are limited in their ability to estimate a large number of predictors, non-linear associations, and complex interactions. Through a machine learning algorithm, random forest (a potentially more flexible extension of decision trees), we predicted sexual satisfaction across two samples (total N = 1846; includes 754 individuals forming 377 couples). We also used a game theoretic interpretation technique, Shapley values, which allowed us to estimate the size and direction of the effect of each predictor variable on the model outcome. Findings showed that sexual satisfaction is highly predictable (48–62% of variance explained) with relationship variables (relationship satisfaction, importance of sex in relationship, romantic love, and dyadic desire) explaining the most variance in sexual satisfaction. The study highlighted important factors to focus on in future research and interventions

THE APPLICATION OF SPECTRAL AND CROSS-SPECTRAL ANALYSIS TO SOCIAL SCIENCES DATA

The primary goal of this paper is to demonstrate the application of a relatively esoteric and interdisciplinary technique, called spectral analysis, to dyadic social sciences data. Spectral analysis is an analytical and statistical technique, commonly used in engineering, that allows times series data to be analyzed for the presence of significant regular/periodic fluctuations/oscillations. These periodic fluctuations are reflected in the frequency domain as amplitude or energy peaks at certain frequencies. Furthermore, a Magnitude Squared Coherence analysis may be used to interrogate more than one time series concurrently in order to establish the degree of frequency domain correlation between the two series, as well to establish the phase (lead/lag) relationship between the coherent frequency components. In order to demonstrate the application of spectral analysis, the current study utilizes a secondary dyadic dataset comprising 30 daily reports of perceived sexual desire for 65 couples. The secondary goal of this paper is to establish a) whether there is significant periodic fluctuation in perceived levels of sexual desire for men and/or women, and at which specific frequencies, and b) how much correlation or `cross-spectral coherence\u27 there is between partners\u27 sexual desire within the dyads, and c) what the phase lead-lag relationship is between the partners at any of the identified frequency components. Sexual desire was found to have significant periodic components for both men and women, with a fluctuation of once per month being the most common frequency component across the groups of individuals under analysis. Mathematical models are presented in order to describe and illustrate these principal fluctuations. Partners in couples, on average, were found to fluctuate together at a number of identified frequencies, and the phase lead/lag relationships of these frequencies are presented

ETHICS BUILT IN: A DIALOGIC APPROACH TO MANAGEMENT INFORMATION SYSTEMS ETHICS EDUCATION

The study of ethics is unarguably a key component of Management Information Systems (MIS) education. From the early days of the discipline, concerns abounded that computing and information were fraught with the possibility of misuse, leading the profession to determine that it had an obligation to do its utmost to encourage ingrained ethical practice. I propose a new approach to ethics teaching in Management Information Systems, one that addresses the need to inculcate habits of ethical thought as an integral part of the design, deployment and use of Management Information Systems. Students would learn the necessity of including ethical analysis at the beginning rather than at the end of MIS initiatives because ethics would be presented as “built in”, an essential organic element of major MIS topics. The habits of ethical thought would be supported by introducing students to models and frameworks using a dialogic approach

Anthropology Display Case

Assembling of display case in classroom that creatively depicts evolutionary species and historical timeline of central Illinois history

Information Systems Implementation Consequences: Ethical Treatment of End Users

For decades, end users have been studied from a multitude of aspects, attitudes, and perspectives in an attempt to better understand end-user resistance to new technology and to find ways to increase the likelihood of implementation success. Ethical considerations are beginning to emerge in the literature; we propose to build on this work by applying it to information systems implementation. This requires drawing on well-established works in ethics as well as work in the field of end-user satisfaction. This research proposes an ethical foundation validating that leadership and information implementation teams should consider how their decisions might affect end-users with respect to the concept of harm, and so an explicit motivation in implementing information systems should be to do no harm. The Ethical Treatment Index is proposed as a tool to empirically measure end-user harm or lack thereof relating to information systems implementation factors

A Strategic Case for RFID: An Examination of Wal-Mart and its Supply-Chain

Although Radio Frequency Identification (RFID) implementation faces a host of challenges, Wal-Mart perseveres in its drive for RFID adoption throughout its supply chain. By being such early adopters of RFID, Wal-Mart’s suppliers suffer increased costs which put pressure to bear on their profitability. In the face of the additional costs of RFID, why has Wal-Mart chosen to mandate the use of RFID tagging in its supply chain and insisted on such a short implementation period? This paper reviews Wal-Mart’s relationship with its supply chain, describes Wal-Mart’s RFID initiative, and proposes a possible unexpressed motivation underlying Wal-Mart’s drive to go to RFID. Early results are indicating incremental improvements at Wal-Mart due to RFID implementation; however, the argument can be made that Wal-Mart’s ultimate goal is an innovative improvement on a Schumpeterian scale – the desire to radically improve an important supply chain metric, the cash-to-cash cycle. This reasoning supports fertile areas for future research in the relationship between RFID and the Cash-to-Cash Cycle