Current status and future challenges in psychological research of sport injury prediction and prevention : a methodological perspective

The purpose of this critical review was to propose methodological developments in sport injury prediction and prevention research. Altogether, 24 studies (e.g., quantitative, qualitative, and prevention intervention studies) conducted from 2006 forward were analysed, related to the "stress-injury model." The injury prediction studies were mostly based on prospective designs, using regression analysis, and studied trait anxiety and life stress. The qualitative studies used mainly thematic analysis, and the intervention studies showed some promising effects, but also inconclusive results. We proposed five specific needs for future research: (a) focus on separate research cohorts, (b) variation in preventive intervention designs, including sound protocols conducting experimental studies, (c) focus on behaviours in relation to cognition, (d) application of repeated-measure designs, and (e) use of statistics that could test complex interactions and intraindividual differences. Future research attention should also be oriented towards the psychology of overuse injuries, biopsychosocial perspectives, and health economic evaluations. While progress has been made in research on psychological antecedents of sport injury, prevention, and intervention in the last 10-15 years, several methodological issues still remain to be further developed, as outlined in this article.El propósito de esta revisión crítica es proponer una serie de progresos metodológicos en la investigación sobre predicción y prevención de lesiones. Para ello, se analizaron conjuntamente 24 estudios (cuantitativos, cualitativos y de intervención preventiva) llevados a cabo desde el año 2006 en adelante relacionados con el "modelo de estrés-lesión". Los estudios de predicción de lesiones utilizaron mayoritariamente diseños prospectivos, utilizando el análisis de regresión y estudiando el rasgo ansiedad y los eventos vitales. Los estudios cualitativos utilizaron principalmente el análisis temático. Los estudios de intervención mostraron resultados promisorios, aunque todavía no definitivos. En este trabajo proponemos cinco necesidades específicas para la investigación futura: (a) centrarse en diferentes cohortes, (b) variar los diseños de intervención preventiva, incluyendo protocolos experimentales, (c) centrarse en las conductas relacionadas con las cogniciones, (d) utilización de diseños de medidas repetidas, y (e) utilización de estadísticos que puedan verificar las complejas interacciones y las diferencias individuales. El foco de la investigación futura también debe orientarse hacia la psicología de las lesiones por desgaste excesivo, las perspectivas biopsicosociales y las evaluaciones económicas del impacto en la salud. Si bien en los últimos 10-15 años se han conseguido importantes avances en la investigación sobre los antecedentes psicológicos de la lesión deportiva, la prevención y la intervención, algunas cuestiones metodológicas deben ser aún desarrolladas, tal y como se señala en este artículo.O objectivo desta revisão crítica é propor uma série de progressos metodológicos na investigação sobre a predição e prevenção de lesões. Para tal, analisaram-se conjuntamente 24 estudos (quantitativos, qualitativos e de intervenção preventiva), realizados a partir do ano de 2006, relacionados com o "modelo de stress-lesão". Os estudos de predição de lesões utilizaram maioritariamente delineamentos prospectivos, utilizando a análise de regressão e analisando o traço de ansiedade e os acontecimentos de vida. Os estudos qualitativos utilizaram principalmente a análise temática. Os estudos de intervenção revelaram resultados promissores, embora ainda não definitivos. Neste trabalho propomos cinco necessidades específicas para futuras investigações: (a) foco em diferentes grupos, (b) variar os delineamentos de intervenção preventiva, incluindo protocolos experimentais, (c) abordar os comportamentos relacionados com as cognições, (d) utilização de delineamentos de medidas repetidas, e (e) utilização de métodos estatísticos que permitam verificar as interacções complexas e as diferenças individuais. O foco da investigação futura também deve ser direccionado para a psicologia das lesões por desgaste excessivo, as perspectivas biopsicossociais e as avaliações económicas do impacto na saúde. Embora nos últimos 10-15 anos se tenham conseguido importantes progressos na investigação sobre os antecedentes psicológicos da lesão desportiva, a prevenção e a intervenção, algumas questões metodológicas necessitam ainda de ser desenvolvidas, tal como se assinala neste artigo

Common demanding conditions among professional high-level military and sport leaders: a cross-contextual qualitative reflexive thematic analysis

Military and sport have attracted increased research interest separately as two distinctly demanding performance- and leadership-driven contexts. However, cross-contextual psychological research in leadership is lacking. Such research has potential to expose unique cross-fertilising insights into resemblances in leadership challenges among military and sport leaders, transferable to a broader range of contexts. Thus, the current study simultaneously explored high-level military and sport leaders’ real-life experiences of similarities in demanding conditions and their psychological manifestations. Sixteen participants - eight Swedish high-level military leaders and eight Swedish high-level sport leaders, participated in the study. Using a qualitative inductive cross-contextual design enabled in-depth knowledge and transferability. A reflexive thematic analysis (RTA) of sixteen interview transcripts generated four common themes of demanding conditions: (1) Developing organisations: Leading under an extensive workload and responsibility, (2) Managing destructive superiors and subordinates: Standing up for oneself, (3) Taking care of the minds and moods of others: Leading deliberated difficult conversations, and (4) Periods of extreme concentration: Leading critical coordination, decisions, and timing. The findings tie high-level military and sports leaders together into a high-stress and high-stakes leader role invoked to manoeuvre a complex buildup of demanding conditions. Implications are presented. Keywords: High-level leaders, military, sport, demanding conditions

Corrigendum: Increased Permeability of the Aquaporin SoPIP2;1 by Mercury and Mutations in Loop A

The publication of Andreas Cellarius\u27s Harmonia Macrocosmica in 1660 represented the completion of an ambitious cartographic project begun over twenty years earlier by the family of Johannes Jansonnius. Jansonnius had proposed to include in his multi-volume Novus Atlas a description of the whole world, that is \u27the Heavens and the Earth\u27. The series incorporated the famous Blaeu Atlas. Cellarius used elaborate illustrations to depict not only the Copernican \u27world system\u27 (model of the universe), but also the classical inheritance, Ptolemy\u27s geocentric model. The work became extremely popular and was frequently reprinted

Ambidexterity and Paradexterity: A typology of IT Governance contradictions

The theoretical construct of organizational ambidexterity addresses how organizations balance managerial contradictions such as exploitation and exploration or efficiency and flexibility. The underlying argument is that management should involve not a trade-off between two states, but simultaneous handling of contradictions. This paper expands the theory of organizational ambidexterity through introducing a typology of contradictions in the form of dichotomies and dualities within a particular management focus, i.e. IT Governance. The paper utilizes a previous study of IT Governance practice at two large, public universities to propose a typology and the concept of paradexterity. Through this, the paper seeks to add new knowledge to the fields of both organizational ambidexterity and IT Governance

Exploring psychosocial risk factors for dropout in adolescent female soccer

Objectives We examined the manner in which age, participation in other sports, socioeconomic status, perceived sport competence, achievement goal orientations, and perceived motivational climate may interact to predict the risk of dropout among adolescent female soccer players. Methods Self-reported data from 519 female soccer players between 10 and 19 years of age (M = 13.41, SD = 1.77) were analysed using a person-centred approach to uncover the interactions among risk factors and their relative predictability of dropout. Results Perceived motivational climate was identified as the main predictor, where relatively lower levels of mastery climate were associated with a higher dropout tendency (absolute risk reduction [ARR] = 12.2% ±6.1% [95% CL]). If combined with relatively lower levels of mastery climate, then relatively lower levels of perceived sport competence were related to higher dropout risks (ARR = 16.5% ±9.5%), whereas, in combination with relatively higher levels of mastery climate, then relatively lower levels of ego-orientated achievement goals were associated with higher dropout rates (ARR = 10.8% ±12.6%) Conclusions Our findings afford novel insights into the interactions between, and the relative importance of, various risk factors for dropout in adolescent female soccer. This knowledge may be useful for soccer associations, clubs, and coaches when developing guidelines and strategies that aim to foster young females’ sustained participation in organised soccer.publishedVersionPaid Open Acces

Analyse und Schätzung von Mehrgruppen-Strukturgleichungsmodellen mittels SPSS und EQS: eine praxisnahe Anleitung

Diese SISS-Schrift erläutert die statistische Analyse von Mehrgruppen-Modellen sowie deren Schätzung und Interpretation als Strukturgleichungsmodelle mit latenten Variablen. Alle Analysen werden exemplarisch unter Verwendung eines empirischen Datensatzes durchgeführt. Dabei werden verschiedenste Probleme, die mit statistischen Mehrgruppenanalysen verbunden sind, aufgezeigt und Möglichkeiten für deren Lösung vorgestellt. Zusätzlich werden alle SPSS- und EQS-Inputfiles (Syntaxfiles), die für die Analyse (mittels „copy and paste“) benötigt werden, zur Verfügung gestellt.This SISS-paper describes the statistical analysis of multi-group models. It shows the estimation and interpretation of these models as structural equation models including latent variables. All analyses are presented in an exemplary way by using empirical data. Several problems that could arise in the course of multi-group analysis are discussed and recommendations on how to deal with the presented problems are given. Additionally, all the SPSS- and EQS-input files (syntax files) necessary for multi-group analysis are presented for download(by “copy and paste”)

Verfahren der Multiplen Imputation bei Schätzung von Strukturgleichungsmodellen mit latenten Variablen: ein systematischer Vergleich mittels Monte-Carlo-Simulationen

Dieser SISS-Beitrag fasst die Ergebnisse aus dem DFG-geförderten Projekt "Monte-Carlo-Simulationen zur Evaluation der Leistungsfähigkeit moderner Missing Data Techniken bei Schätzung von Strukturgleichungsmodellen mit latenten Variablen. Eine systematische Analyse verschiedener Varianten der Multiplen Imputation" zusammen. Im Projekt wurden mittels Monte-Carlo-Simulationstechniken (MC-Simulationstechniken) die Performanz verschiedener Varianten der Multiplen Imputation (MI) und MI-alternativer Verfahren zur Schätzung fehlender Werte im Kontext von Strukturgleichungsmodellierungen (SEM-Analyse) verglichen. Es wurden sechs Missing Data Techniken (MDTs) im Kontext von drei verschiedenen SEM-Populationsmodellen unter unterschiedlichen Simulationskonfigurationen getestet. Die variierten Konfigurationen ergaben sich aus: a) Datensätzen mit unterschiedlichen Fallzahlen, b) Datensätzen mit symmetrischen und (stark) asymmetrischen Variablenverteilungen, c) Datensätzen mit unterschiedlich hohen Anteilen an fehlenden Werten. Neben MI-Techniken mit strikten Annahmen zur Verteilung der Modellvariablen (multivariate Normalverteilung) wurden auch MI-Varianten getestet, welche dieser Annahme nicht unterliegen und kategoriale Variablen explizit im Verfahren berücksichtigen können. Zusätzlich zu den verschiedenen Varianten der Multiplen Imputation wurden zum Vergleich auch MI-alternative Verfahren eingesetzt (das "Direct Maximum Likelihood-Schätz-verfahren" sowie die "Expectation-Maximization-Methode"). Zur Bewertung der Performanz der verschiedenen MDTs wurden damit erreichbare SEM-Fit-Indices herangezogen (p-Wert der Chi²-Statistik, SRMR, RMSEA und CFI). Es wurden aber auch die Qualität der geschätzten SEM-Parameter und deren Standardfehler sowie die relative Effizienz der Parameterschätzungen untersucht. Auf diese Weise konnten unter den sechs getesteten MDTs zwei Verfahren identifiziert werden, die bei allen konfigurierten Modell- und Datenbedingungen sehr gute Ergebnisse erbringen. Das sind das "Direct Maximum Likelihood-Schätzverfahren" (Direct-ML-Verfahren) und eine Variante der MI, die bei der Imputation der fehlenden Werte die Modellstruktur des Analysemodells berücksichtigt: die H0-Technik. Beide erbringen neben sehr guten Ergebnissen bei den untersuchten SEM-Fit-Indices auch unverzerrte SEM-Parameterschätzungen und Standardfehler. Von den MI-Varianten kann somit allein dieH0-Technikuneingeschränkt für den praktischen Einsatz empfohlen werden. Zudem kann als Nicht-MI-Variante die Direct-ML-Methode empfohlen werden. Sie hat sogar den Vorteil, dass die fehlenden Werte direkt bei der Modellschätzung berücksichtigt werden (ohne die fehlenden Werte separat imputieren zu müssen). Alle anderen MDTs liefern zwar auch gute, unverzerrte SEM-Parameterschätzwerte und Standard-fehler, aber sie generieren häufig SEM-Fit-Werte, die zur fälschlichen Ablehnung von geschätzten Strukturgleichungsmodellen führen. Zwar ist bei kleinen Missinganteilen die Modellbewertung an-hand der Fit-Indices oftmals unproblematisch, aber bei höheren Anteilen (ab ca. 20%) kann nur ein einziger Fit-Index uneingeschränkt empfohlen werden: der SRMR-Index (Standardized Root Mean-Square Residual Index).This SISS-paper summarizes the results of the DFG-funded project "Monte Carlo simulations for evaluating the performance of modern missing data techniques in estimating structural equation models with latent variables. A systematic analysis of different variants of multiple imputation". In this project, Monte Carlo simulation (MC simulation) techniques were used to compare the performance of different variants of Multiple Imputation (MI) and other Non-Multiple Imputation methods for estimating missing values when analyzing structural equation models (SEM). In total, six missing data techniques (MDTs) applied to three different SEM-population models were investigated using various configurations for simulation. These configurations included a) data files with different numbers of cases, b) data files with symmetrical and (strong) asymmetrical value distributions, and c) data files with different proportions of missing data. Besides using MI techniques with strict assumptions of value distributions (multivariate normal distribution), we also tested MI variants which are not subject to these assumptions. For comparative reasons two Non-MI MDTs were applied (the "Direct Maximum Likelihood estimation" and the "Expectation-Maximization method"). For evaluating the performance of all six MDTs we focused on four different fit indices used most prominentlyin SEM analysis (p-value of the chi²-statistic, SRMR, RMSEA und CFI). We also analyzed the quality of all estimated SEM parameters and their standard errors as well as the relative efficiency of all estimated parameters. Among the six tested missing data techniques only two techniques could be identified that deliver very good results under all model-and data configurations. These are the "Direct Maximum Likelihood estimation" (Direct-ML-method) and a variant of MI that takes into account the model structure of the analyzed model when imputing the missing values: the H0-method. Both methods deliver high quality fit indices when applied to SEM estimation. They also deliver unbiased SEM parameter es-timations and standard errors. Thus, when looking particularly at the MI variants, just the H0-method can be recommended for practical usage. In addition, the Direct ML-method (a Non-MI technique) can be recommended. The Direct ML-method integrates the process of estimating missing values into model estimation so that there is no need for an initially separate process of missing value imputation. Although all the other MDTs deliver good and unbiased results when estimating SEM parameters and standard errors, they often generate SEM fit indices that lead to false rejections of SEMs. This is even more problematic when having data files with high proportions of missing values (≥ 20%). In situations like this, there is only one SEM fit index that can be fully recommended: the SRMR index (Standardized Root Mean-Square Residual index)