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References
Matheson, H., Mathes, S., & Murray, M. (1997, August). The effect of winning and
losing on female interactive and coactive team cohesion. / Effet des
victoires et des defaites sur la cohesion d'equipes sportives feminines
interactives et coactives. Journal of Sport Behavior, 20(3), 284-298.
Retrieved March 23, 2008, from SPORTDiscus database.
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THE EFFECT OF WINNING AND LOSING ON FEMALE INTERACTIVE AND
COACTIVE TEAM COHESION
This study examined the influence of winning and losing on team cohesion of two coacting (swimming, gymnastics) and two interacting (lacrosse, basketball) female
intercollegiate athletic teams. Fifty-six of the original 70 subjects were administered
the Group Environment Questionnaire (GEQ) (Widmeyer, Brawley, & Carron, 1985)
three times during the playing season: preseason, after winning and after losing
contests. The GEQ measures four subscales of cohesion: Attraction to the GroupTask
(AGT), Attraction to the Group-Social (AGS), Group Integration-Task (GIT), Group
Integration-Social (GIS). A 2 X 2 ANCOVA examined the influence of type of team
(coacting, interacting) and outcome (win, loss) on the four subscale measures of
GEQ. Significant interaction effects (p<.05) were obtained on the AGT and GIT
subscales, with coacting teams in each instance scoring higher than interacting
teams in losing situations. Significant main effect (outcome) differences (p<.05)
were found between coacting and interacting teams on only the AGT subscale, with
coacting teams recording higher scores than interacting teams. Results were
discussed in terms of the effects of anticipated outcome of competition and divisional
level of competition.
Observers of sport often wonder how a team which has been so successful one year
could, with essentially the same personnel, fail to repeat that success the following
season. Conversely, how might a team whose members appear to be less talented,
defy logic and become league champions? What might explain such differing
outcomes? "Team cohesiveness" has been identified as a factor that may play a
critical role in the success or failure of teams (Widmeyer, 1994; Ziobro & Dziaasko,
1975). Many researchers (Brawley, Carron & Widmeyer, 1994; Carron & Chelladurai,
1981; Landers & Luschen, 1974; Martens & Peterson, 1971; Williams & Hacker,
1982) have postulated that cohesive teams, whose members are held together by
the force of a common goal (Carton, 1982), may be more successful.
Cohesion has been defined as, "the total field of forces which act on members to
remain in the group" (Festinger, Schachter, & Back, 1950). Cartwright (1968)
believes that attraction-to-the-group occurs due to four interacting variables: a)
motive base for attraction, which consists of needs such as affiliation and
recognition; b) group goals, such as the desire for prestige, and the positive
characteristics of the team that are vicariously reflected on individual members; c)
expectancy, or what benefits membership might afford; and d) comparison with
other groups regarding the outcomes of being a member. This view of cohesiveness
suggests that, if individual needs and goals are not being met within that group, and
the group does not change to meet individual needs, then attraction-to-the-group
declines.
Therefore, if a team member anticipated being on a successful team and the team
was not having a winning season the factor Cartwright (1968) defined as attractionto-the-group might diminish to such an extent that the athlete might drop off the
team unless other factors counterbalance the unmet goal.
Historically, much of the research in sport has focused on the cohesion of interacting
sports, which require the combined efforts of all members with specialized skills to
achieve group goals (Bird, 1977), and has found that interdependence contributes to
performance success (Bird, 1977; Carron, 1982). The few studies (Lenk, 1976;
McGrath, 1962; Meyers, 1962) which have analyzed coacting teams, where success
is based on individual performance which, when summed, results in total team
achievement and an overall score (Bird, 1977), have found that coacting team
members exhibit a lower level of cohesion than interacting team members due in
part to intragroup rivalry and within team competition (Carron, 1982, 1984; Carron
& Chelladurai, 1981; Donnelly, Carron, & Chelladurai, 1978; Gill, 1984).
Several researchers have indicated attraction-to-the-group is greater when members
are cooperatively interdependent, rather than competitive (Bird, 1977; Gasparec,
1984; Landers & Luschen, 1974; Martens & Peterson, 1971; Segrave, 1972; Williams
& Hacker, 1982). Higher levels of cohesion have, therefore, been found in sports
such as field hockey (interactive), than in coacting sports such as track. On
interactive teams, characterized by the sport slogan "there is no '1' in team,"
athletes might be called upon to suppress individual goals for the sake of team goals.
If, however, such personal goals are sacrificed for the team there is a risk that
athletes may become frustrated and lose their desire to be part of the team. In
contrast, on coacting teams such frustration is less likely to occur, because individual
task goals are more often met through individual participation. In addition, athletes
are often motivated by intrateam rivalry and competition (Landers & Luschen, 1974).
Besides the interdependence or independence of team members, it appears that
another intervening variable that influences cohesion is contest outcome (Widmeyer,
1994). Attraction to the group is enhanced by success of the team (Davids & Nutter,
1988; Klein & Christiansen, 1969; Martens & Peterson, 1971; Spink, 1990;
Widmeyer & Martens, 1978; Yukelson, Weinberg, & Jackson, 1984).
Research has primarily focused on the relationship between cohesion and win/loss
record at the end of the season. The influence of wins and losses on cohesion within
a season has only partially been investigated. At the end of a competitive season
Evans (1980) found that high school basketball and wrestling teams, exhibited
greater levels of cohesion after a win than a loss. Gray (1975) and Martens and
Peterson (1971) studying cohesion among winning and losing basketball teams
composed of athletes at ages that ranged from elementary to university intramural
players, found no differences at the end of the season. Ruder and Gill (1982) using
collegiate volleyball players found that winning teams exhibited higher levels of
cohesion than losing teams prior to a game. This level of cohesion was even greater
after the game. Baltzer (1977), however, studying female basketball players found
that the most cohesive teams were those that had moderate amounts of wins and
losses versus those that were experiencing a season of mainly wins or mainly losses.
It may be that being on a team that is clearly going to win or lose reduces
dependence on one another because the outcome is predictable and the level of
cooperation and motivation between team members may be reduced or considered
of lesser importance. Being on a team, where the outcome is uncertain, however,
may promote interdependence in order to promote success.
In spite of the fact that contest outcome appears to be a significant factor influencing
cohesion, this has been studied primarily with interacting male teams and focused on
team records at the end of the season. Thus, it may be important to identify what
factors are important within the multidimensional concepts of cohesion. The Group
Environment Questionnaire (Widmeyer, Carron, & Brawley, 1985) was designed to
differentiate between the reasons and goals individuals might have prior to joining a
team and the factors that may influence them to remain with that team. The
purposes of this study, therefore, were to determine whether interacting (basketball,
lacrosse) teams recorded a higher level of perceived cohesion than coacting
(gymnastics, swimming) teams, and if cohesion was greater following a winning or a
losing competitive experience.
Methods
Instrument
The Group Environment Questionnaire (Widmeyer et al., 1985) was selected for use
in the study because it is a sport specific measure of cohesion, which distinguishes
between task oriented and socially oriented concerns both for the individual and the
group. This measure is designed to be scored as a general rather than a situationally
specific measure of cohesion in sport teams, since the questionnaire may be
administered to teams competing in different sports without requiring modification.
The GEQ measures four components of cohesion: a) a member's Attraction to the
Group-Task (AGT, 4 items); b) a member's Attraction to the Group-Social (AGS, 5
items); c) a member's Integration into the Group-Task (GIT, 5 items); and d) a
member's Integration into the Group-Social (GIS, 4 items). Table 1 shows sample
items from the subscales. The 18 items on the questionnaire are scored on a
continuous scale from 1-9 (9=strongly agree, 1=strongly disagree). The obtained
summed scores for each scale are derived independently with scores potentially
ranging from 4-45, with four indicating a low and 45 a high level of cohesion. For
women the norms vary by subscale and type of team (Widmeyer et al., 1985, p.5664). Team sport norms at the 50 percentile (AGT = 27; AGS = 30; GIT = 33; GIS =
21) are different than those reported for individual sport participants (AGT = 33;
AGS = 33; GIT = 30; GIS = 26).
Reliability measures ranging from .64 to .76 have previously been established for
each of the four subscales (Widmeyer et al., 1985). Validity also has been previously
determined through interviews with athletes, expert opinion and factor analysis.
Concurrent validation of the GEQ with the Sport Cohesiveness Questionnaire
(Martens, Landers, & Loy, 1972) has produced intercorrelations of .41 and .47 for
the task subscales, and .47 and .62 for the social subscales.
Subjects
The original subject pool was a convenience sample of 70 female Division III athletes
from four teams: 16 lacrosse players, 13 basketball players, 18 gymnasts, and 22
swimmers. They ranged in age from 18 to 21 years and attended a small eastern
college (enrollment=2700). Only those athletes who completed all questionnaires
during the season were included in the analysis, which resulted in a final sample of
56 athletes (14 lacrosse; 12 basketball; 11 gymnasts; 15 swimmers).
Procedures
In order to determine the influence of winning and losing on cohesion a preseason
GEQ baseline measure was recorded to be utilized for later comparisons. The
questionnaire was again administered by the researcher on two subsequent
occasions (after the first win, and after the first loss). Collection of this data varied
by sport. The basketball team lost their first contest four days after the baseline data
collection and recorded their first win (seventh game) five weeks later. The lacrosse
team lost a match six days after baseline measures were recorded and earned their
first win (second game) 10 days later. The swimmers won their first contest five days
after baseline measures were obtained and did not lose until four weeks later (third
meet). The gymnastics team recorded a win after four days and a loss after 10 days
(third competition).
As can be seen, the data collection for the lacrosse and gymnastics teams was
completed early in the season, while for swimming and basketball, the process
extended over several weeks. The first administration lasted approximately 20
minutes and further testing took 6-8 minutes. Athletes completed the questionnaire
as they arrived at the training venue for the start of practice, the day after their first
intercollegiate win and the day after their first loss. The questionnaires were
administered by the researcher in a group setting.
Results
The purposes of the study were to determine whether 1) interacting teams
(basketball, lacrosse) recorded higher levels of cohesion than coacting teams
(gymnastics, swimming); 2) perceived cohesion was greater following a winning
situation than a losing situation. The results were analyzed utilizing a 2 x 2
(coacting/interacting x win/loss) ANCOVA with the preseason measure the covariate.
A review of the data (Table 2) showed that cohesion levels of coacting teams were
higher than interacting teams on the AGT, GIT, and GIS subscales, for preseason,
after winning and after losing. Interacting team members' scored higher than
coacting teams on the AGS scale only during the preseason and winning. Coacting
team members scored higher following a loss, rather than a win, on all cohesion
scales. In contrast, interacting team members scored higher on all scales, after a
win, than a loss.
The analysis of covariance by sport yielded a significant interaction effect on two of
the subscales. Members of coacting teams scored significantly higher (F1,50=5.25,
p<.05; F1,50=6.90, p<.01) than interacting teams on AGT (Figure 1) and GIT
(Figure 2) subscales in a losing condition. No interaction effects were found on AGT
or GIT in a winning situation, or on AGS, or GIS scales in winning or losing
conditions.
A significant main effect (outcome) difference (F1,49=6.28, p<.05) was obtained on
the AGT scale with coacting team members recording higher levels of cohesion than
interacting team members.
The calculation of effect size for all four subscales showed large effect size for AGT
following a loss and medium effect size following a win. Medium effect size results
also were obtained for the AGS, GIT, and GIS scales after a loss, and on GIS after a
win (Table 3).
Discussion
It was expected, based on previous research, that interacting teams would obtain
higher cohesion scores than coacting teams on all measures and that perceived
levels of cohesion would increase after a winning situation and decrease after a
losing situation. It was found, however, that coacting teams obtained significantly
higher scores than interacting teams after a loss on the AGT and GIT subscales.
The higher attraction to the group task (AGT) after a loss by coacting, rather than
interacting, teams may be a function of perceived personal control and assumption
of responsibility. On coacting teams athletes compete autonomously, except for
relays, in specified events. These athletes, therefore, may be more likely than those
on interactive teams to feel that the amount of time they compete, opportunities for
improvement, style of performance and team desire to win are self determined and
under their control. A losing situation, rather than undermining feelings of control
and responsibility, might increase them. A gymnast, who performs a routine poorly
or swimmer with a slow time, typically assesses with the coach the reasons for such
performance problems and then sets appropriate performance goals. On interacting
teams control and responsibility is shared and the contribution of the individual
athlete to team failure may be less clear. Coaches often tend to control playing time,
style of play, and even opportunities to improve personal performance. The
individual's level of desire to win, therefore, as part of a collective may be more
problematic on interactive teams, since success depends not just on themselves, but
teammates. In losing, athletes on interactive teams may feel less input and control
over factors that impact on future team success and subsequently care less about
the group task. Feelings of responsibility for the loss may be lower, not only because
of the team nature of the task, but also because of the control the coach has over
the situation.
Higher scores achieved by coacting than interacting teams after losing on the group
integration task subscale (GIT) also may be a function of clearer identified
responsibility, as the GIT construct is a measure of the individual team members'
perception of the task-oriented, similarity, closeness and bonding within the team as
a whole (Widmeyer et al., 1985). Items on this subscale measure shared goals for
performance, responsibility for losing or poor performance, shared team aspirations,
concern for those who experience performance problems and communication about
responsibilities during competition and practice. Brawley, Carron, and Widmeyer
(1985,1987) indicate that greater levels of perceived cohesion enable team members
to resist the negative impacts of disruptive events (such as poor performance) and
have an increased ability to share responsibility for failure.
The finding that coacting and interacting teams did not differ in the social domain of
individual attraction to the group (AGS) or group integration (GIS) in winning or
losing situations may be due to the gender of the sample. Apparently, for the
athletes in this study, being part of the teams' social activities, having teammates as
best friends, viewing the team as a primary social group and spending time together
off-season is not significantly influenced by success or failure or the type of team
upon which an athlete participates. Preseason AGS scores of all teams were higher
than AGT scores. Mean scores across the season placed coacting teams AGS scores
on the reported norms at the 60 percentile and interacting teams at the 80
percentile. This greater importance of the social versus task dimension of the team
may be related to gender and is supported by the theories of Gilligan (1982). For
women, striving to succeed on an independent task and even competing against
teammates for positions, does not necessarily have to reduce cohesion, but may
even increase it. Martina Navratilova explains that she was coached by a former
basketball player to hate her opponents in order to succeed. She never understood
this and instead believed that her opponents success took nothing away from her
skills and that she could beat them and still go out to dinner with them afterwards
(Nelson, 1991). Nelson (1991) suggests that even on independent sport tasks,
women are drawn to partnership models of competition in which they support one
another's quest to master the task rather than to beat a rival. Here teammates,
coaches and even opponents, Nelson theorizes, view each other as comrades rather
than enemies and see competition as its Latin root suggests to seek together. The
suggestion is that, regardless of the type of team or outcome, women athletes social
attraction and integration remain salient and relatively stable.
Finally, these findings also may have been due to the frequency and timing of data
collection. Data were only collected after the first success and loss. This varied by
team as reported on page 288. The loss of a competition early in the season may
have had a more detrimental effect on cohesion scores than a later loss, since
feelings of "wellness" may not have yet developed within the team. It seems
reasonable that the longer a team is together, the greater the possibility shared
goals and feelings of closeness may develop. It might have been more effective to
collect data after each contest and plot season records, rather than only first wins
and losses.
Summary and Conclusions
In contrast to previous research, this study found that coacting teams scored
significantly higher than interacting teams on the AGT and GIT cohesion subscales.
This was attributed to: a) athletes perceptions of control and responsibility; b) the
gender of the sample; c) the timing and frequency of data collection. The value of
employing a preseason measure as covariate to assist in the control of initial levels
of cohesion with teams was also identified as useful.
In summary, although the results from this study are limited in generalizability due
to the sample size, a unique finding was that coacting team members recorded
higher cohesion scores on all subscales than interacting team participants after a
loss, rather than after a win. This suggests that future studies should examine
whether coacting teams do, in fact, have different perceptions of success and
satisfaction than interacting teams due to the nature of the activity and performance
success and failure. More frequent collection of data following wins and losses
throughout the season might provide clearer indications of factors affecting levels of
cohesion, particularly if closeness of the competition and the strength or weakness of
the opposition also are recorded at the time of the data collection. Finally, it appears
that perception of cohesion on women's teams in general and after winning and
losing in particular may differ from males. The mean AGS scores for women were
higher than AGT scores and higher than 50% of norms previously reported for both
men and women (Widmeyer et al., 1985). These scores remained relatively stable
across the season regardless of winning and losing. Previous research on men has
indicated that AGT scores for coacting teams are higher than AGS scores. This was
not true for the women's teams studied here. Theories and models of cohesion need
to examine whether in sport as well as other aspects of life, women speak in a
different voice.
Table 1 Sample questions from The Group Environment Questionnaire
Attraction to Group-Task (AGT)
1 I am not happy with the amount of playing time I
get.
2 1 am unhappy with my team's level of desire to win.
3 I do not like the style of play on this team.
Attraction to Group-Social (AGS)
1 I am not going to miss the members of this team when
the
season ends.
2 For me this team is one of the most important social
groups to which I belong.
3 Some of my best friends are on this team.
Integration Into Group-Task (GIT)
1 Our team is united in trying to reach its goals for
performance.
2 We all take responsibilities for any loss or poor
performance by our team.
3 Our team members have conflicting aspirations for
the
team's performance.
Integration Into Group-Social (GIS)
1 Our team would like to spend time together in the
off-season.
2 Our team members rarely party together.
3 Members of our team do not stick together outside of
practice and games.
Table 2 Means and Standard Deviations for Coacting and Interacting Teams
on Scales of the Group Environment Questionnaire[*] According to Time of
Season Collected
Legend for Chart:
A
B
C
D
E
-
Subscale
Team: Coacting(N=26); M
Team: Coacting(N=26); SD
Team: Interacting(N=26); M
Team: Interacting(N=26); SD
A
E
B
C
D
AGTpre-season
6.09
winning
5.57
losing
6.98
MEAN
6.21
31.85
4.14
28.54
31.05
4.66
28.54
32.62
3.41
26.46
31.99
4.07
27.85
AGSpre-season
6.87
winning
6.40
losing
6.60
MEAN
6.62
35.27
7.42
36.58
35.31
9.01
36.12
36.96
7.15
34.92
35.85
7.86
35.87
GITpre-season
7.05
winning
6.91
losing
7.52
MEAN
35.73
6.64
33.65
36.15
8.50
35.46
37.77
8.30
32.96
36.55
7.81
34.02
7.16
GISpre-season
6.50
winning
7.23
losing
7.71
MEAN
7.15
26.69
5.15
23.00
26.85
7.52
23.35
27.46
5.41
22.85
27.00
6.03
23.07
* Scores for all subscales range from a low of 4 to a high of 45
Table 3 Obtained Effect Size Scores for All Subscales of the Group
Environment Questionnaire+ Following Outcome Using Pooled Standard
Deviations
Subscales
AGT
Win
0.47[**]
0.57[**]
Loss
0.69[**]
1.12[***]
AGS
-0.10[*]
0.41[**]
GIT
GIS
0.09[*]
0.61[**]
* small (<0.41)
** medium (0.41 D 0.70)
*** large (>0.70) +Widmeyer et al. (1985)
Figure 1. Adjusted post-test mean scores between coacting and interacting teams for
Attraction to Group -Task scale measured the outcome.
Figure 2. Adjusted post-test mean scores between coacting and interacting teams for
Group Integration-Task measured after outcome.
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~~~~~~~~
By Hilary Matheson, University of Wales College, Newport and Sharon Mathes, Iowa
State University and Mimi Murray, Springfield College
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Source: Journal of Sport Behavior, 19970801, Vol. 20 Issue 3, p284, 15p
Item: SPH455520
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