Zur Bedeutung sportbezogener Verhaltensmuster in der Familie für die Sportpartizipation Jugendlicher

Einleitung: In der Sportpartizipation Jugendlicher und junger Erwachsener bestehen trotz vielfältiger Bemühungen der Sport- und Bewegungsförderung nach wie vor soziale Ungleichheiten und die Ausstiegsraten sind darüber hinaus relativ hoch (Nagel, 2003). Ein möglicher Erklärungsansatz für diese sozialen Ungleichheiten dürften aus einer sozialisationstheoretischen Perspektive die transgenerationale Vermittlung von sportbezogenen Wertvorstellungen und Verhaltensmuster in der Familie sein (Baur, 1989; Burrmann, 2005). Im Familienalltag wird den Aspekten Bewegung und Sport eine unterschiedliche Bedeutung zugesprochen, weshalb der Frage nachgegangen wird, inwiefern das Sportverhalten von Jugendlichen über sportbezogene Wertvorstellungen und Verhaltensmuster in der Familie beeinflusst wird. Methode: Mittels eines Online-Fragebogens wurden insgesamt 1909 Heranwachsende im Alter von 15 bis 20 Jahren (n = 1909; M = 17.3, SD = 1.7) zu ihrem aktuellen Sportverhalten sowie zu den sportbezogenen Verhaltensmustern in ihrer Familie befragt. Nebst dieser quantitativen Untersuchung wurden teilstrukturierte Interviews mit 13 Jugendlichen und jungen Erwachsenen im Alter zwischen 15 und 25 Jahren mit denselben Themenschwerpunkten geführt. Resultate: Die Ergebnisse der multiplen linearen Regression zeigen, dass wichtige Prädiktoren der Sportpartizipation von Jugendlichen die Kommunikation über Sport (β = .19, p < .001), die gegenseitige Unterstützung (β = .16, p < .001), die regelmässige Sportaktivität (β = .11, p < .01) sowie der Stellenwert des Sports in der Familie (β = .09, p < .05) darstellen. Die gemeinsame Sportaktivität in der Familie sowie das sportbezogene Gesundheitsbewusstsein im Familienalltag sind für die Sportbeteiligung Jugendlicher nicht relevant. Die signifikanten familiären Sportverhaltensmuster klären 16.8% der Varianz auf. Mithilfe der strukturierenden qualitativen Inhaltsanalyse nach Mayring (2002) lassen sich aus den Interviews vertiefende Aussagen zu den einzelnen Prädiktoren machen. Diskussion: Die quantitativen sowie qualitativen Ergebnisse zeigen die Relevanz des Stellenwerts des Sports sowie gewisser habitueller Sportverhaltensmuster in der Familie für die Sportbeteiligung der Jugendlichen auf. Die Sportförderung der jüngeren Generation über das familiäre Sportverhalten und deren sportbezogenen Wertvorstellungen scheint eine fruchtbare Strategie zu sein, um beim Nachwuchs aktive Sportverhaltensmuster zu entwickeln und dadurch die Sportpartizipation bis hin zum Jugend- und Erwachsenenalter aufrecht zu erhalten. Um zielgerichtet auf Familien zugeschnittene Sportförderprogramme schaffen zu können, sind jedoch weitere Untersuchungen zur transgenerationalen Vermittlung von sportbezogenen Wertvorstellungen und Verhaltensmuster in Familien notwendig. Literatur: Baur, J. (1989). Körper- und Bewegungskarrieren. Schorndorf: Hofmann. Burrmann, U. (2005). Zur Vermittlung und intergenerationalen "Vererbung" von Sport(vereins)engagements in der Herkunftsfamilie. Sport und Gesellschaft, 2, 125-154. Mayring, P. (2002). Einführung in die qualitative Sozialforschung: Eine Anleitung zu qualitativem Denken. Weinheim: Beltz. Nagel, M. (2003). Soziale Ungleichheiten im Sport. Aachen: Meyer & Meyer. 31

Reduced foveal vision enhances peripheral monitoring and peripheral event detection

Introduction: Although it seems plausible that sports performance relies on high-acuity foveal vision, it could be empirically shown that myoptic blur (up to +2 diopters) does not harm performance in sport tasks that require foveal information pick-up like golf putting (Bulson, Ciuffreda, & Hung, 2008). How myoptic blur affects peripheral performance is yet unknown. Attention might be less needed for processing visual cues foveally and lead to better performance because peripheral cues are better processed as a function of reduced foveal vision, which will be tested in the current experiment. Methods: 18 sport science students with self-reported myopia volunteered as participants, all of them regularly wearing contact lenses. Exclusion criteria comprised visual correction other than myopic, correction of astigmatism and use of contact lenses out of Swiss delivery area. For each of the participants, three pairs of additional contact lenses (besides their regular lenses; used in the “plano” condition) were manufactured with an individual overcorrection to a retinal defocus of +1 to +3 diopters (referred to as “+1.00 D”, “+2.00 D”, and “+3.00 D” condition, respectively). Gaze data were acquired while participants had to perform a multiple object tracking (MOT) task that required to track 4 out of 10 moving stimuli. In addition, in 66.7 % of all trials, one of the 4 targets suddenly stopped during the motion phase for a period of 0.5 s. Stimuli moved in front of a picture of a sports hall to allow for foveal processing. Due to the directional hypotheses, the level of significance for one-tailed tests on differences was set at α = .05 and posteriori effect sizes were computed as partial eta squares (ηρ2). Results: Due to problems with the gaze-data collection, 3 participants had to be excluded from further analyses. The expectation of a centroid strategy was confirmed because gaze was closer to the centroid than the target (all p < .01). In comparison to the plano baseline, participants more often recalled all 4 targets under defocus conditions, F(1,14) = 26.13, p < .01, ηρ2 = .65. The three defocus conditions differed significantly, F(2,28) = 2.56, p = .05, ηρ2 = .16, with a higher accuracy as a function of a defocus increase and significant contrasts between conditions +1.00 D and +2.00 D (p = .03) and +1.00 D and +3.00 D (p = .03). For stop trials, significant differences could neither be found between plano baseline and defocus conditions, F(1,14) = .19, p = .67, ηρ2 = .01, nor between the three defocus conditions, F(2,28) = 1.09, p = .18, ηρ2 = .07. Participants reacted faster in “4 correct+button” trials under defocus than under plano-baseline conditions, F(1,14) = 10.77, p < .01, ηρ2 = .44. The defocus conditions differed significantly, F(2,28) = 6.16, p < .01, ηρ2 = .31, with shorter response times as a function of a defocus increase and significant contrasts between +1.00 D and +2.00 D (p = .01) and +1.00 D and +3.00 D (p < .01). Discussion: The results show that gaze behaviour in MOT is not affected to a relevant degree by a visual overcorrection up to +3 diopters. Hence, it can be taken for granted that peripheral event detection was investigated in the present study. This overcorrection, however, does not harm the capability to peripherally track objects. Moreover, if an event has to be detected peripherally, neither response accuracy nor response time is negatively affected. Findings could claim considerable relevance for all sport situations in which peripheral vision is required which now needs applied studies on this topic. References: Bulson, R. C., Ciuffreda, K. J., & Hung, G. K. (2008). The effect of retinal defocus on golf putting. Ophthalmic and Physiological Optics, 28, 334-344.

Impairments of peripheral motion change detection during smooth pursuit eye movements

Introduction: In team sports the ability to use peripheral vision is essential to track a number of players and the ball. By using eye-tracking devices it was found that players either use fixations and saccades to process information on the pitch or use smooth pursuit eye movements (SPEM) to keep track of single objects (Schütz, Braun, & Gegenfurtner, 2011). However, it is assumed that peripheral vision can be used best when the gaze is stable while it is unknown whether motion changes can be equally well detected when SPEM are used especially because contrast sensitivity is reduced during SPEM (Schütz, Delipetkose, Braun, Kerzel, & Gegenfurtner, 2007). Therefore, peripheral motion change detection will be examined by contrasting a fixation condition with a SPEM condition. Methods: 13 participants (7 male, 6 female) were presented with a visual display consisting of 15 white and 1 red square. Participants were instructed to follow the red square with their eyes and press a button as soon as a white square begins to move. White square movements occurred either when the red square was still (fixation condition) or moving in a circular manner with 6 °/s (pursuit condition). The to-be-detected white square movements varied in eccentricity (4 °, 8 °, 16 °) and speed (1 °/s, 2 °/s, 4 °/s) while movement time of white squares was constant at 500 ms. 180 events should be detected in total. A Vicon-integrated eye-tracking system and a button press (1000 Hz) was used to control for eye-movements and measure detection rates and response times. Response times (ms) and missed detections (%) were measured as dependent variables and analysed with a 2 (manipulation) x 3 (eccentricity) x 3 (speed) ANOVA with repeated measures on all factors. Results: Significant response time effects were found for manipulation, F(1,12) = 224.31, p < .01, ηp2 = .95, eccentricity, F(2,24) = 56.43; p < .01, ηp2 = .83, and the interaction between the two factors, F(2,24) = 64.43; p < .01, ηp2 = .84. Response times increased as a function of eccentricity for SPEM only and were overall higher than in the fixation condition. Results further showed missed events effects for manipulation, F(1,12) = 37.14; p < .01, ηp2 = .76, eccentricity, F(2,24) = 44.90; p < .01, ηp2 = .79, the interaction between the two factors, F(2,24) = 39.52; p < .01, ηp2 = .77 and the three-way interaction manipulation x eccentricity x speed, F(2,24) = 3.01; p = .03, ηp2 = .20. While less than 2% of events were missed on average in the fixation condition as well as at 4° and 8° eccentricity in the SPEM condition, missed events increased for SPEM at 16 ° eccentricity with significantly more missed events in the 4 °/s speed condition (1 °/s: M = 34.69, SD = 20.52; 2 °/s: M = 33.34, SD = 19.40; 4 °/s: M = 39.67, SD = 19.40). Discussion: It could be shown that using SPEM impairs the ability to detect peripheral motion changes at the far periphery and that fixations not only help to detect these motion changes but also to respond faster. Due to high temporal constraints especially in team sports like soccer or basketball, fast reaction are necessary for successful anticipation and decision making. Thus, it is advised to anchor gaze at a specific location if peripheral changes (e.g. movements of other players) that require a motor response have to be detected. In contrast, SPEM should only be used if a single object, like the ball in cricket or baseball, is necessary for a successful motor response. References: Schütz, A. C., Braun, D. I., & Gegenfurtner, K. R. (2011). Eye movements and perception: A selective review. Journal of Vision, 11, 1-30. Schütz, A. C., Delipetkose, E., Braun, D. I., Kerzel, D., & Gegenfurtner, K. R. (2007). Temporal contrast sensitivity during smooth pursuit eye movements. Journal of Vision, 7, 1-15.

Fokusgruppen zur Weiterentwicklung von Studiengängen nutzen

Im Weiterbildungsbereich wird oft einzig auf die standardisierte schriftliche Befragung als Evaluationsmethode zurückgegriffen, ohne dass anfänglich eine Auseinandersetzung mit Evaluationszweck und Fragestellungen erfolgt ist. Der folgende Beitrag zeigt am Beispiel einer formativen Evaluation eines betriebswirtschaftlichen Studiengangs auf, wie die Fokusgruppenmethode in der Weiterbildungsevaluation eingesetzt wird und nützliche Informationen zur Weiterentwicklung von Studiengängen liefern kann.