Co Action Effects On Motor Performance Psychology Essay

The aim of our study was to see whether a person would perform better in a co-actor conditioned race than in a solitary conditioned race. We conducted this to see whether there was any effects and whether the social facilitation theory had anything do with the results. We had 27 participants, 23 males and four females, age 18±5 years. We measured this by putting the 27 participants under two conditions, an individual conditioned race and a co-actor conditioned race. We made them run a 200 meter sprint, and recorded both times for each condition. We found that the majority of people ran better under the co-actor conditioned race than in the solitary conditioned race. We could say this could be due to social facilitation, co-actor and audience effect.

Studies on Social facilitation show that a degree of individual’s performance and behaviour is influenced and affected by the indirect presence, competition or imagination of others.

Lab studies such as N.Triplett (1898) noted cyclist whom were against other peers performed faster times against the clock than when they were cycling as an individual. He then tried to back this up by duplicating another lab test, by using fishing reels and children; he gave them the reels and gave them the task to reel in the fishing line. This test was done under two conditions, first test had the children reeling in the fishing reel alone, and then the second test he had the children doing the exact same test, but in pairs, but working alone, against one another. This test showed that children alone reeled in the fishing line slower when they were alone and faster when they were partnered up against someone, who was doing the exact same task.

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There are two type of social facilitation. One type is Co-action effect; this is where the participant performs better working in a competitive situation, for example a 100 meter sprint against someone. The co-action effect would suggest that you will see the participant performing to a higher standard than if they were running on their own. The other type is audience effect, this is when the individual whom is being watched by spectators has an increase in arousal levels, and this can then positively increase the individual’s performance due to the audience watching. For example long jump, where the audience is presents the individuals arousal levels will peak and according to the Drive Theory the individual should perform better due to being aroused. However the audience effect could also hinder the individual as this could lead to them to become over aroused, anxious, and nervous, but also if the individuals skill ability, and confidence is low, than the idea of having an audience can lead to them to become, over aroused, anxious, and nervous, and this could have a negative effect on their performance.

N.Triplett (1898) showed that the co-action effect, a singularity which shows that when and individual is in the mere presence of another who is doing the same task as them, their performance is influenced and/or changed, increasing performance.

Although Triplett focused on social facilitation as a whole, his main focus was on co-action effect and competitive situations. Due to this, further experiment’s into audience effect was carried out by other Theorist’s such as Zajonc (1965, 1980) which anticipated social facilitation as an overall theory, and applying it to both audience effect and co-action effect.

Zajonc (1965, 1980) considered the theory that the company of other people will increase the arousal levels of the individual (drive theory) and therefore increasing an individual’s reaction response. In addition to this, the company of other people would increase the individual’s likelihood of having a prevailing response, leading to the individual performance to increase.

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Fig.1. the Zajonc Model (1965)

Having looked at Triplets’s, Zajonc’s and other researches social facilitation theories we, as Sports Psychology students conducted our own lab test. In our test we had a Sport Science year one group, and we set the task of two 200 meter sprints, one as an individual and one as a co-actor.

As research has shown that social facilitation has an effect upon people’s performance we predicted that people would run quicker in the co-action condition, than they would to the solitary condition.

Method:

Design:

The experimental design of this test was ‘within’ as it was the same group for both experiments, but there were two different conditions. One factor was running as an individual, solitary, and the other factor was running as a co-actor, running as a group. The test was ‘within’ because it was within the same group that the experiment was testing, and the group was tested under the conditions, solitary and co-actor.

Participants:

In this experiment there were 27 participants who took part. There were 4 females, and 23 males. The age 18 ± 5 years, the mean age was 18.81. The participants for this experiment were from the first year sport science course, and it was a requirement for them to take part in the practical experiment. However there was a consent form given around at the briefing, this where people ticked their name and this gave consent from them and gave them a participant number. This helped randomly select the participants so they could be put into the condition groups. From this, the first 14 numbers were selected to run individually first and the co-actor second. Similarly to this, the last 13 numbers out of 27 were to run the co-actor race first and then the individual run. In this experiment both males and females participated although, there was a significantly greater amount of males that participated in comparison to females.

Materials:

The experiment was held at the UCLan Sport Arena, and was held on the 400 meter athletic track. The participants were asked to wear appropriate sports performance clothing. Participants were also asked to wear trainers but this lead to some people wearing sport performance trainers and others wearing more fashionable shoes. This could have affected the individual’s performance depending on their footwear. To measure the time of each participant we used stopwatches, there was more than one stopwatch to record the time so that we could take down the most accurate time. We used a clipboard and a sheet of paper which had a table on with the participant numbers, and the condition categories, individual and co-actor. This is where we recorded the results of the performers.

Procedure:

The experiment took place at the UCLan Sport Arena in Preston. It was held on the 400 meter athletics track. The experiment was conducted by the whole first year sport science class. The instructions which were given for this experiment was to meet at the UCLan sport arena for 9, making sure that everyone was dressed in correct sports practical kit. Once everyone met, we all went into a classroom where we had a briefing of what the experiment was and how it was going to run. A register and consent sheet was sent around the class, this is where you ticked your name off and got a participant number. Once the briefing was over the class was split up into a group of 14 and a group of 13, this depended on your numbers. The first group of 14 were to run individually first and the last group of 13 were to run co-actor first.

After the briefing everyone was taken out to the athletics track, where they had to warm up. The warm up consisted of; two laps around the athletics track and then into static stretches of the gastrocnemius, quadriceps, hamstrings, glutes and personal stretches.

Once everyone was warmed up the group was split into the individual runners and the co-actor runners. The time keepers stood at the finish line so they could see once the runner had crossed the line. There was someone on the starting line which started the race by dropping their arm and saying ‘go’, this conducted the time keepers on the finish line to start the stopwatches.

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Once all the individual runners ran and the times were recorded, the co-actors ran. The race had three to four people in at a time this to make sure it was a co-actor race. The same applied for the starting of the race but each time keeper had a lane and a runner to time the whole race in case someone did not get an accurate record.

After the co-actors ran, the first group who ran individually first ran the co-actors race and then vice versa, the group who ran co-actors first ran individually.

We made sure we put participants into two separate groups, as we wanted to counterbalance the onset of fatigue, so we made the individuals run first, and they rested while the co-actors ran vice versa.

All the results were recorded down and then put into an excel sheet, this highlighted the sex, age, individual race and the co-actor race for each participant.

On the day the lecturer made sure that there was enough time to conduct the experiment as they booked out the track for 3 hours but the experiment did not take this long.

Results:

The data that was collected was put down into an excel spread sheet, with sex, age, individual and co-actor. Having looked at the raw data (refer to appendix 1) you can see that there are considerably more males to females, 24 males and four females. As well, the raw data (refer to appendix 1) shows that one male did not participate in the individual race but did in the co-actor race. This means that only 26 ran the individual race and 27 ran the co-actor race, this was shown in the results as there is an anomaly and the time that is counted for the person who did not participate in the individual race reads zero.

The raw data (refer to appendix 1) also shows that not everyone performed better in the co-actor race, which was the prediction of the experiment but in fact got a quicker time in the individual race, 10 out of 27 people have a slower time in the co-actor race then they have in the individual race.

The raw data (refer to appendix 1) shows that the first group, one to 14, who ran individual first only four of the runners had a quicker time on the co-actor race than their individual race time. But in comparison the last group from 15 to 27, all bar one, had a faster co-actor race time than their individual race time.

With the raw data (refer to appendix 1) we put it into SPSS and conducted a Paired sample t-test (refer to appendix 2), as we used the same group for the experiment and everyone was tested under both conditions. After putting the raw data into SPSS and conducting a Paired sample t-test we can see that the test we conducted was significant (t (25) =2.488, p<0.05). This indicates that there is significance between the individual conditions and the co-actor condition, the co-actor condition shows that it has a faster time compared to the individual condition race time.

Discussion:

We hypothesised that people would run quicker in the co-action condition, than they would to the solitary condition. The results show this is the case, as there was significant difference between the individual condition and the co-actor condition, the majority of people ran faster in the co-actor condition than in the solitary condition. This could be due to the social facilitation theory which states “The tendency for people who are being watched or observed to perform better than they would alone on simple tasks (or tasks they know how to do very well due to repetition)” (Gillian Fournier.(2009). Social Facilitation.

Available://psychcentral.com/encyclopedia/2009/social-facilitation/. Last accessed 25th November 2012.).

However looking at the raw data (refer to appendix 1) we could see that there was an anomaly, as one participant did not run under the solitary condition but did run in the co-actor condition, this could have a dramatic change of results if the participant did run both races, as if they performed better in the individual conditioned race and not as well in the co-actor conditioned race, this could affect the end results.

Also looking at the raw data (refer to appendix 1) we could see that the first group who ran the individual conditioned race first, the majority of the participants had a slower co-actor time, only four out of the first 14 showed an improvement in their time, then looking at the second group participants between 15 to 27 who ran the co-actor conditioned race first all bar one had improved times. This may link into the fact that when it came down to the second group to run, not only had they seen what was expected but also they were put into a co-actor condition. This could have led to them to perform better, as there was competition and also an audience present. You could also say this has a relationship with the drive theory, as the performer could have been aroused by the audience and the competitive situation.

However, when I noted that the first group performed worse in the second race which was the co-actor, I also noticed that the second group performed worse in their second race this was their individual run. Although there are many different reasons behind why the performances could have decreased second time round, it could be mainly linked to fatigue as; even though the groups were split to try and counterbalance the onset of fatigue it seems it has occurred. This is because both groups performed weaker second time round suggesting they had worked harder in the first race in comparison to their second race.

Although, this might not be the case as it could also be down to the group getting split up and it could have happened that the first group were not as quick as the second group at running. These slower times could have been down to skill ability as if, the performer is not great at the task given; they may not work to their full potential. Similarly to this it could be down to anxiety, as the first group were first to run and due to the audience effect, this could have impaired the participants performance.

In addition to this, Social inhibition could be another reason that is linked to the participants who did not perform better in the co-actor condition. Social inhibition theory says that being in a competitive situation or having an audience present can weaken a performance. I believe this could have had an effect on some individuals as not everyone performed better in the co-actor. This would be a valid reason not to, as every individual handles a situation differently.

Looking at my results, you could put them into real life sporting scenarios, such as a boxer who, due to having an audience watching, also in a competitive situation, they will either thrive an perform better, social facilitation, or their performance will be effected, as the presence of others is too much, this could be due to social inhibition.

In conclusion looking at the results we could say that are hypothesis was correct, a person who runs in a co-actor conditioned race will perform a quicker time than they would if they were in a solitary condition.


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