Forced retirement transition : a narrative case study of an elite Australian Rules football player

Retirement from elite sport is a complex and often-problematic process. The current study explores a negative case study of an athlete recently retired from a team sport (Australian Rules Football) in order to generate knowledge on how to improve the retirement process. Three semi-structured interviews were undertaken less than 5 years post retirement, and archival career records were gathered from online sources. Data were coded to construct a narrative account of the participant’s career and retirement. Narrative analysis also revealed that the retirement transition from elite sports for this athlete was problematic and caused considerable personal distress. We suggest that the means of improving retirement transition and reducing harm to players include fostering alternative life narratives and increasing self-complexity, utilising norm appropriate communication strategies, and recognising retirement as a potential grieving period for loss of community. © 2018, © 2018 International Society of Sport Psychology

Virtual burglary:exploring the potential of virtual reality to study burglary in action

Objectives: This article explores the potential of virtual reality (VR) to study burglary by measuring user responses on the subjective, physiological, and behavioral levels. Furthermore, it examines the influence of individual dispositions, such as sensation seeking and self-control, on behavior during a virtual burglary event. Methods: Participants, male university undergraduates (N ¼ 77), could freely move around a virtual neighborhood wearing a VR headset and using a game controller and were instructed to burgle one of the houses in the neighborhood. Participant movement, items stolen from the house, and heart rate (HR) were recorded throughout the burglary event. Individual dispositions were measured before, and subjective user responses were measured after, the event. Additionally, we experimentally varied whether there was an alarm sounding and participants’ beliefs about the chance of getting caught (deterrence). Results: Participants reacted subjectively to the burglary event by reporting high levels of presence in the virtual environment (VE) and physiologically by showing increased HRs. In terms of behavior, high deterrence resulted in fewer items being stolen and a shorter burglary. Furthermore, sensation seekers stole more valuable items, while participants high in conscientiousness stole fewer items. Conclusions: The results suggest that VEs have substantial potential for studying criminal behavior

Algorithms Aside: Recommendation as the Lens of Life

In this position paper, we take the experimental approach of putting algorithms aside, and reflect on what recommenders would be for people if they were not tied to technology. By looking at some of the shortcomings that current recommenders have fallen into and discussing their limitations from a human point of view, we ask the question: if freed from all limitations, what should, and what could, RecSys be? We then turn to the idea that life itself is the best recommender system, and that people themselves are the query. By looking at how life brings people in contact with options that suit their needs or match their preferences, we hope to shed further light on what current RecSys could be doing better. Finally, we look at the forms that RecSys could take in the future. By formulating our vision beyond the reach of usual considerations and current limitations, including business models, algorithms, data sets, and evaluation methodologies, we attempt to arrive at fresh conclusions that may inspire the next steps taken by the community of researchers working on RecSys

A quasi‐experimental investigation of differences between face‐to‐face and videoconference interviews in an actual selection process

Videoconference interviews are now integral to many selection processes. Theoretical arguments and empirical findings suggest that videoconference interviews may lead to different interview performance ratings in comparison to Face-to-Face (FTF) interviews. This has led to the question of the comparability of the psychometric properties of videoconferences and FTF interviews. However, evidence from actual selection processes stems from the beginning of the century, and recent findings predominantly stem from simulated interview contexts. We present insights from an actual selection process within a large European organization where we had the unique opportunity for a quasi-experimental investigation of differences between videoconference and FTF interviews. Initially, the organization conducted FTF interviews, and after the onset of the COVID-19 pandemic, the interviews were conducted via videoconference. We examine mean differences in applicant performance ratings and evidence for response format-related validity differences. There were only small, non-significant mean differences and no evidence for response format related validity differences. We discuss possible causes for discrepancies in our findings compared to previous research. Furthermore, we conclude that downstream consequences of differences between FTF and videoconference interviews may be lower than previously expected. We end with a call for research on the interaction between technology-design and selection-tool-design features

Exploring the Consistency, Quality and Challenges in Manual and Automated Coding of Free-text Diagnoses from Hospital Outpatient Letters

Coding of unstructured clinical free-text to produce interoperable structured data is essential to improve direct care, support clinical communication and to enable clinical research.However, manual clinical coding is difficult and time consuming, which motivates the development and use of natural language processing for automated coding. This work evaluates the quality and consistency of both manual and automated clinical coding of diagnoses from hospital outpatient letters. Using 100 randomly selected letters, two human clinicians performed coding of diagnosis lists to SNOMED CT. Automated coding was also performed using IMO's Concept Tagger. A gold standard was constructed by a panel of clinicians from a subset of the annotated diagnoses. This was used to evaluate the quality and consistency of both manual and automated coding via (1) a distance-based metric, treating SNOMED CT as a graph, and (2) a qualitative metric agreed upon by the panel of clinicians. Correlation between the two metrics was also evaluated. Comparing human and computer-generated codes to the gold standard, the results indicate that humans slightly out-performed automated coding, while both performed notably better when there was only a single diagnosis contained in the free-text description. Automated coding was considered acceptable by the panel of clinicians in approximately 90% of cases

Some Advice for Psychologists Who Want to Work With Computer Scientists on Big Data

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdisciplinary collaboration. This article aims to inform psychologists who are interested in working with computer scientists about the potentials of interdisciplinary collaboration, as well as the challenges such as differing terminologies, foci of interest, data quality standards, approaches to data analyses, and diverging publication practices. Finally, we provide recommendations preparing psychologists who want to engage in collaborations with computer scientists. We argue that psychologists should proactively approach computer scientists, learn computer scientific fundamentals, appreciate that research interests are likely to converge, and prepare novice psychologists for a data-oriented scientific future

Compositional landscape for glass formation in metal alloys

A high-resolution compositional map of glass-forming ability (GFA) in the Ni–Cr–Nb–P–B system is experimentally determined along various compositional planes. GFA is shown to be a piecewise continuous function formed by intersecting compositional subsurfaces, each associated with a nucleation pathway for a specific crystalline phase. Within each subsurface, GFA varies exponentially with composition, wheres exponential cusps in GFA are observed when crossing from one crystallization pathway to another. The overall GFA is shown to peak at multiple exponential hypercusps that are interconnected by ridges. At these compositions, quenching from the high-temperature melt yields glassy rods with diameters exceeding 1 cm, whereas for compositions far from these cusps the critical rod diameter drops precipitously and levels off to 1 to 2 mm. The compositional landscape of GFA is shown to arise primarily from an interplay between the thermodynamics and kinetics of crystal nucleation, or more precisely, from a competition between driving force for crystallization and liquid fragility

A model for determining cardiac mitochondrial substrate utilisation using stable 13 C-labelled metabolites

Abstract: Introduction: Relative oxidation of different metabolic substrates in the heart varies both physiologically and pathologically, in order to meet metabolic demands under different circumstances. 13C labelled substrates have become a key tool for studying substrate use—yet an accurate model is required to analyse the complex data produced as these substrates become incorporated into the Krebs cycle. Objectives: We aimed to generate a network model for the quantitative analysis of Krebs cycle intermediate isotopologue distributions measured by mass spectrometry, to determine the 13C labelled proportion of acetyl-CoA entering the Krebs cycle. Methods: A model was generated, and validated ex vivo using isotopic distributions measured from isolated hearts perfused with buffer containing 11 mM glucose in total, with varying fractions of universally labelled with 13C. The model was then employed to determine the relative oxidation of glucose and triacylglycerol by hearts perfused with 11 mM glucose and 0.4 mM equivalent Intralipid (a triacylglycerol mixture). Results: The contribution of glucose to Krebs cycle oxidation was measured to be 79.1 ± 0.9%, independent of the fraction of buffer glucose which was U-13C labelled, or of which Krebs cycle intermediate was assessed. In the presence of Intralipid, glucose and triglyceride were determined to contribute 58 ± 3.6% and 35.6 ± 0.8% of acetyl-CoA entering the Krebs cycle, respectively. Conclusion: These results demonstrate the accuracy of a functional model of Krebs cycle metabolism, which can allow quantitative determination of the effects of therapeutics and pathology on cardiac substrate metabolism

Some Advice for Psychologists Who Want to Work with Computer Scientists on Big Data

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdiscip