Anna Lisa Ward and Ben Ogles, Department of
One debate found in the psychological field is one of nature vs. nurture. Those agreeing with the nature side of this argument would state that we, as individuals, come into the world knowing everything we will ever know. We are ‘born’ with the genes, brain structures, etc. that will make us who they are, while those on the nurture side of the argument would say we come into the as a blank slate and our environment determines who we are. Through research and scientific discovery the consensus has been reached that both nature and nurture influence who we are, we come into the world with specific attributes but our environment is able to mold us and impact us in many ways (Keating, 2011). One of the purposes of this project was to see if behavior could be predicted depending upon which of the sides (nature or nurture) individuals tended to believe more for athletic ability. In other words, if one thought that athleticism was talent based as opposed to a product of hard work would that influence their behavior when faced with adversity?
We looked at fixed and growth mindset, which can be related to the terms of nature and nurture. A fixed mindset states that what you have is what you got and you can’t really improve from there; while a growth mindset would say that what you have is changeable and through hard work you can improve in various skills and abilities (Dweck 2006). Another element we wanted to look at, similar to growth mindset, was resilience. Resilience is the ability to respond positively when difficulty or adversity arises (Galli & Gonzalez, 2015). We hypothesized that mindset and resilience would be correlated with each other.
We further hypothesized that having a growth mindset would be positively related to higher resilience scores, that those holding a growth mindset would respond with greater persistence to experimentally induced adversity, as opposed to those with a fixed mindset. We further hypothesized that those who score high on the resilience scale, indicating they have high levels of resilience, will respond with greater persistence to experimentally induced adversity, as opposed to those scoring low on the resilience scale.
Method
We went to a high school cross-country practice and invited high school cross-country runners to participate in our study. We sent home a packet of information and surveys to those interested in participating. This packet included consent forms for the participants and their guardians, selfreport surveys measuring mindset and resilience, and questionnaires gathering training and demographic data.
We ended up with sixty-nine high school cross-country athletes in our study. Five participants had incomplete data, and were not included in our analysis. This left us with sixty-four participants with complete data (mean age=15.88 years). There were 41 males and 19 females. Average fastest mile time for males was 5 minutes and 12 seconds and average fastest mile time for females was 6 minutes and 14 seconds.
Upon receiving completed packets from each runner we were ready to begin the study. We attended a practice of the participants’ where they were to run an interval workout. The beginning of this workout included two 400-meter runs. During the first 400 meter run we had coaches tell each athlete they ran 3 seconds slower than they had actually run, this was our experimentally induced adversity (if they had run 70 seconds, they were told the ran 73 seconds, etc.). Following this first interval we had an in-between survey for each participant to fill out. Responses from this survey allowed us to come to the conclusion that our false feedback was believable. The second 400-meters they ran, the coaches gave accurate times. Following this second 400-meter an in-between survey was again completed and then athletes were debriefed.
Results
We have completed some analyses on this project, but have yet to come up with a model that tells the story we anticipate to tell with this data. One regression model we found with mindset and resilience was significant in predicting time difference, but only when a variable representing some form of talent was involved, in this case we used participants personal record, best time, for the mile. We are continuing to work on computing different regression models with the data we have collected.
Discussion
From the results we have found it appears that mindset and resilience are somewhat important when predicting responses to experimentally induced adversity, but only when other variables are also included in the model. We hope to either find research to back-up having a regression model with other variables or find a model that fits our initial hypothesis.
Conclusion
It appears, from this project, that mindset and resilience do play an important role in bouncing back from experimentally induced hard times but only when other variables are included; specifically variables indicative of talent. We will continue to look at the data and work towards finding an interesting and accurate model of our data.
References
Dweck, C. S. (2006). Mindset: The new psychology of success. New York, NY, US: Random
House.
Galli, N., & Gonzalez, S. P. (2015). Psychological resilience in sport: A review of the literature
and implications for research and practice. International Journal of Sport and Exercise
Psychology, 13(3), 243-257. Doi:10.1080/1612197X.2014.9496947
Keating, D. P. (2011). Nature and nurture in early child development. New York, NY, US:
Cambridge University.