kohler effect
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2021 ◽  
pp. 92-93
Author(s):  
Edward Watson ◽  
Bradley Busch
Keyword(s):  

Author(s):  
Christopher R Hill ◽  
Stephen Samendinger ◽  
Amanda M Rymal

Abstract Background Practitioners and researchers may not always be able to adequately evaluate the evidential value of findings from a series of independent studies. This is partially due to the possibility of inflated effect size estimates for these findings as a result of researcher manipulation or selective reporting of analyses (i.e., p-hacking). In light of the possible overestimation of effect sizes in the literature, the p-curve analysis has been proposed as a worthwhile tool that may help identify bias across a series of studies focused on a single effect. The p-curve analysis provides a measure of the evidential value in the published literature and might highlight p-hacking practices. Purpose Therefore, the purpose of this paper is to introduce the mechanics of the p-curve analysis to individuals researching phenomena in the psychosocial aspects of behavior and provide a substantive example of a p-curve analysis using findings from a series of studies examining a group dynamic motivation gain paradigm. Methods We performed a p-curve analysis on a sample of 13 studies that examined the Köhler motivation gain effect in exercise settings as a means to instruct readers how to conduct such an analysis on their own. Results The p-curve for studies examining the Köhler effect demonstrated evidential value and that this motivation effect is likely not a byproduct of p-hacking. The p-curve analysis is explained, as well as potential limitations of the analysis, interpretation of the results, and other uses where a p-curve analysis could be implemented.


2020 ◽  
pp. 372-390
Author(s):  
Deborah L. Feltz ◽  
Christopher Hill

Author(s):  
Tayo Moss ◽  
Stephen Samendinger ◽  
Norbert L. Kerr ◽  
Joseph Cesario ◽  
Alan L. Smith ◽  
...  

The authors describe two research experiments exploring the influence of race on the Köhler motivation gain effect with exercise tasks. Experiment 1 tested whether partner racial dissimilarity affects individual performance. Experiment 2 created a team identity recategorization intervention to potentially counter the influence on performance observed in Experiment 1. White male participants were partnered with either a Black or Asian partner (Experiment 1) or with a Black partner utilizing team names and shirt colors as a team identity recategorization strategy (Experiment 2). Racially dissimilar dyads completed two sets of abdominal plank exercises with a Köhler conjunctive task paradigm (stronger partner; team performance outcome dependent upon the weaker-ability participant’s performance). The results of Experiment 1 suggest attenuation of the previously successful group motivation gain effect in the racially dissimilar condition. The simple recategorization strategy utilized in Experiment 2 appeared to reverse motivation losses under conjunctive-task conditions in racially dissimilar exercise dyads.


2019 ◽  
Vol 41 (5) ◽  
pp. 90-95
Author(s):  
Christopher R. Hill
Keyword(s):  

2019 ◽  
pp. 92-93
Author(s):  
Bradley Busch ◽  
Edward Watson
Keyword(s):  

2018 ◽  
Vol 7 (4) ◽  
pp. 240-245 ◽  
Author(s):  
Tayo Moss ◽  
Deborah L. Feltz ◽  
Norbert L. Kerr ◽  
Alan L. Smith ◽  
Brian Winn ◽  
...  

2018 ◽  
Vol 49 (5) ◽  
pp. 538-552 ◽  
Author(s):  
Seungmin Lee ◽  
Nicholas D. Myers ◽  
Taiwoo Park ◽  
Christopher R. Hill ◽  
Deborah L. Feltz

Background. One way to motivate people to exercise is to create a motivating social context, such as group exercise, due to social comparison opportunities. However, typical group exercise is not always easy for those who have problems in scheduling or social physique anxiety. Software-generated partners (SGPs) could offer a solution because they have advantages over human partners. Aim. This exploratory study examined the psychological state of flow under Köhler paradigm over a 24-week exergame with different types of SGPs: Individual Control (IC), Always Superior Partner (AWS), and Not Always Superior Partner (NAS). Method. The experiment was a 3 (Type of the partner) × 3 (Time blocks) factorial design. Fifteen participants engaged in the experiment. A multivariate multiple regression with type of SGPs predicting flow state at the second and third block was conducted. Results. Participants with an NAS partner had significantly higher flow state, as compared to participants under IC, at both blocks. Participants with an AWS partner had approximately equal flow state, as compared to participants under IC, at both blocks. Conclusions. Possible reasons for flow perceptions with different types of SGPs over time were discussed in terms of programming SGPs and flow theory.


2017 ◽  
Vol 32 ◽  
pp. 131-137 ◽  
Author(s):  
Stephen Samendinger ◽  
Samuel T. Forlenza ◽  
Brian Winn ◽  
Emery J. Max ◽  
Norbert L. Kerr ◽  
...  
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