Jared Richardson and Dr. Benjamin Ogles, Psychology Department
Introduction
Goal setting provides multiple benefits in the realm of athletics. These include overcoming fear of failure (Wikman, Stelter, Melzer, Hauge, & Elbe, 2014), performing at a higher level in both training and competition (Filby, Maynard, & Graydon, 1999), and increasing motivation (Sullivan & Strode, 2010). Marathon runners and halfmarathon runners are included among the benefactors of goal setting.
In this study, runners in the Utah Valley Marathon filled out a pre-race survey, which included their expected time for the race and their goal time. We noted that there was often a difference between the two. We hypothesized that this difference, which we called goal specificity, would predict finish time and goal achievement. We operationally defined goal achievement as the difference between runners’ goal time and actual time. We also hypothesized that experience (number of previous marathons, training miles per week, and longest training run), confidence, motivation for running (competition and/or personal goal achievement) would predict goal specificity, finish time, and goal achievement.
Methods
286 participants between 18 and 78 years of age who had registered to compete in the Utah Valley Marathon were invited to participate in the study through an email containing a link to a pre-race web survey. Of the 286 participants involved in the study, 148 were registered to compete in the marathon and 138 in the half-marathon. Included in the study were those who completed both the pre-race and post-race surveys in their entirety.
We conducted 3 hierarchical regression analyses predicting goal specificity, goal achievement, and finish time for marathoners and half-marathoners, respectively. To predict goal specificity, independent variables included the experience variables in Step 1, confidence in Step 2, and the motivation variables in Step 3. We used the same independent variables to predict goal achievement and finish time, but also added goal specificity in Step 4.
Results
We found that goal specificity predicted finish time and goal achievement for both marathon and half-marathon runners, with one exception. It did not predict finish time for marathon runners, though it was very close to predictive. None of the other variables predicted goal achievement. Experience predicted goal specificity in halfmarathon runners. Experience and motivation for running predicted finish time in both marathon and half-marathon runners.
Discussion
Some of the results of the study were not surprising. We fully expected that experience and motivation for running would predict finish time. The fact that confidence did not add any significance was surprising. Also surprising was the finding that none of our variables predicted goal achievement except goal specificity.
Another finding was that experience predicted goal specificity for half-marathon runners, but not for marathon runners. The reason for this could be because there is a wider variety of experience in the half-marathon group, both beginners and more experienced runners. In contrast, most marathoners are more experienced.
Conclusion
The most relevant finding to us was that goal specificity predicted finish time for halfmarathon runners. It was close enough to predictive of finish time for marathon runners that it deserves attention. Runners can apply this by setting a finish time goal that is close to what their expected finish time is. Setting a goal that is just a little beyond what they expect to get could push them to run faster. However, these findings are preliminary. Further research should be done in order to determine how specific goals should be. Is it better for the expected time and goal time to be the same time or is it better to set a goal that is just a little faster or slower than the expected time? Are there other variable that should be considered? The answers to these questions could help runners better prepare for races.