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ISSN: 1734-4948
Advances in Rehabilitation
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4/2024
vol. 38
 
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Original article

Cooperation between players with intellectual impairments and their partners in Special Olympics unified basketball – an observational study

Waldemar Skowroński
1
,
Bartosz Molik
1
,
Robert J. Szyman
2
,
Bogusław Słupczyński
1
,
Miguel Angel Gomez
3
,
Jolanta Marszalek
1

  1. Jozef Pilsudski University of Physical Education in Warsaw, Poland
  2. Faculty of Secondary Education, Professional Studies and Recreation, Chicago State University, Chicago, USA
  3. Technical University of Madrid, Universidad Politécnica de Madrid, Spain
Advances in Rehabilitation, 2024, 38(4), 45–56
Online publish date: 2024/11/19
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Introduction

One of the largest global sports movements, alongside the Deaflympics, Paralympics, and Olympic Games, is the Special Olympics (SO). Its efforts connect people with intellectual impairments via a range of special programs aimed at facilitating their physical activity development (II). The movement was developed in the early 1960s by Eunice Kennedy Shriver, and the first International SO Games were held in Chicago in 1968 [1]. Today, the SO includes people with II of all levels of physical activity, who take part in sport to improve their social life. These participants are able to practice individual and team sports in a similar manner as Olympians and Paralympians. The Games include both winter sports (e.g., alpine skiing) and summer sports (e.g., basketball, football, volleyball), with the World Winter and World Summer Special Olympics being the largest events; these are held every four years, like the Olympic and Paralympic Games [2].
An excellent opportunity for people both with and without II is SO Unified Sports [3]. Teams consist of athletes with II and people without impairment, known as partners. Both groups train and play together during competition. The unified sports are played in three models, viz. competitive, player development and recreational, which provide distinct types of experiences. The competitive model requires the athletes and partners to be of similar abilities and age, although in reality, they could significantly differ in age. The development and the recreation models do not provide any opportunity for advancement or higher levels of competition [4]. This three model structure of SO Unified Sports® is important for promoting understanding and acceptance for people with II in society, with both the team members and the general public benefitting. Research studies have confirmed that Unified Sports® have a positive social impact on individuals with and without II, as well as their communities [5-7].
One of the unified disciplines included in the SO World Summer Games is basketball [4], which is played by athletes of all ages and abilities. Young players learn to handle a ball, dribble, and protect it, while more experienced players, who understand strategies, learn how to play more challenging ball. Basketball itself consists of several events: speed dribble, individual skills competition, team skills competition, team competition (5-on-5), half-court competition (3-on-3), unified team competition (5-on-5), and unified half-court competition (3-on-3). Participation in each event is determined by a player’s functional and intellectual abilities. The ruleset of SO basketball differs slightly from the rules established by the Fédération Internationale de Basketball (FIBA); for example, a player may take two steps during a game but not double dribble [4]. Before competitions, the teams are divided into groups of similar ability based on their on-court physical basketball skills. For this purpose, players participate in Basketball Skills Assessment Tests (BSAT) and are observed during short, six-minute games [7].
However, it is unclear which factors determine team success in basketball during Unified Sports competitions. While available research has studied the performance of basketball [9-11] and wheelchair basketball players [12-18], no study has attempted to analyze the performance of international-level basketball players taking part in the Unified Sports® competition; furthermore, while determining the efficiency of players in unified basketball is an interesting topic, as in other sports, no data currently exists on the game performance of athletes and partners during competitions.
There is a need to develop unified basketball training protocols for athletes with II and the partners. Hence, it is necessary to understand the role of athletes with II in unified basketball, and which of the three models best represents this role. Armed with this knowledge, acquired from authentic game performance in Unified Sports, basketball coaches and administrators will be better equipped to lead teams to compete. Therefore, the aim of the current study is to compare the game performance of players with II with that of the partners in unified basketball. Our hypothesis is that players with II and their partners are equally active in unified basketball matches.

Materials and methods

Participants
This investigation of game-related statistics was approved by the local Institutional Review Board (IRB; 001-48-1/2008) and the Special Olympics (SO). The competition organizer and the teams agreed to participate in this research. All athletes and partners signed Form C3 - Athlete/Unified Partner Release Form, which is the SO consent form.
Data were collected during SO European Summer Games in Warsaw (Poland) in 2010, as part of the 5-on-5 Unified Team Competition. Sixteen male teams competed, with every team playing every other team in its level. The teams consisted of a maximum of 10 players: six players with II and four partners without II. The competition was played in accordance with SO rules outlined in the Official Special Olympics Summer Sports Rules, Revised Edition (January 2010) and the official regulations of the FIBA. The rules were revised in 2020 [19], but the competition adaptations, basketball protocols and etiquette have not been changed.
In total, 150 male basketball athletes participated in this study. The participants were divided into two main groups: partners (n = 54; mean age 22.3 ± 6.7 years, 15-47 years) and players (n = 96; mean age 21.2 ± 5.2 years, 15-38 years). They were also divided according to four skill levels (groups) by experts and classifiers based on observations during at least two basketball games of six minutes each, with a one-minute intermission between games.
During these games there was a running clock, free substitution i.e., without the referee’s permission, and no timeouts. Each team member was required to play in each of the observed games, and each team had to start the observed game with its strongest line-up. All players were obliged to perform to the maximum of their abilities during observed games, and the team coach was responsible for making sure that each player had the opportunity to do so. During the observed games, three athletes and two partners were required to always be on the court. International classifiers assessed the players during preliminary round games played during the first day of competition. The players at level 1 presented the highest level of basketball skill during this competition.
Procedures
All 25 male unified basketball games were recorded with a video camera (Panasonic VDR-D310). The camera was placed strategically in the bleachers to see half of the court from the halfway line and follow the game. Three basketball experts scored game performance variables. Each game was analyzed independently by at least two observers. They could repeat selected actions. The total time spent in analyzing each match was approximately three hours. High inter-observer and an intra-observer reliability between observers were achieved for each variable (Spearman’s rank correlation coefficients varying between r = .95 - 1.00). Additionally, all observations were verified with official score sheets and game statistics provided by tournament organizers immediately after each game.
A total of 42 variables related to critical game elements were evaluated: total points scored, 2-point field goals scored (outside of the restricted area), missed 2-point field goal attempts (outside of the restricted area), 2-point field goal attempts (outside of the restricted area), 2-point field goals scored (inside the restricted area), 2-point field goals missed (inside the restricted area), 2-point field goal attempts (in the restricted area), 2-point field goals made, 2-point field goals missed, 2-point field goal attempts, 3-point field goals scored, 3-point field goals missed, 3-point field goal attempts, free throws scored, free throws missed, free throw attempts, scored points after a fast break, scored points after a restart of the game, steals, assists, blocked shots, offensive rebounds, defensive rebounds, turnovers, complete pass, errant pass, all passes, passes caught, passes dropped, all catches, successful passes off the dribble, tries for a field goal of the dribble, dribbling successfully around an opponent, all dribbling. Additional efficiency (percentage) of 2-point field goals (out of the restricted area), 2-point field goals (inside the restricted area), total 2-point field goals, 3-point field goals, free throws, passes, catches, and dribbling were calculated.
These parameters were chosen by experts coaching people in unified basketball with the aim of evaluating the performance of individual basketball athletes on the court. As the present study is one of the first such game analyses in unified basketball, very few, if any, references are available for comparison.
Statistical Analysis
The amount of playing time was documented for each player and partner. For each parameter, the mean scores for a 24-minute unified basketball game were extrapolated based on the actual minutes played by the athletes.
Firstly, all game indicators were assessed for normality with the Kolmogorov-Smirnov test. Since none of the variables were normally distributed, the non-parametric test Mann-Whitney U-test was used to analyze the differences between partners and players for all game performance indicators. Following this, the effect size (ES) was calculated to determine the influence of the level of competition (levels 1 to 4); each level was analyzed separately when comparing partners and athletes. The ES was calculated using the r test, with the formula for the Mann-Whitney U test being r = Z/n. The results were interpreted based on the following criteria: 0.10 = small effect, 0.30 = medium effect, and 0.50 = large effect [20].
Statistical analyses were performed using SPSS 29 for Windows (IBM computers, US). The statistical significance was set to p < 0.05.

Results

The means and standard deviations for each game indicator, for all of basketball players, are presented in Table 1. The results of the Mann-Whitney U-test indicate that partners obtained significantly better values than players in 31 out of 42 parameters, indicated in Table 1 (p < 0.05). Seven out of the 42 analyzed parameters demonstrated large ES (ES ≥ 0.05) (Table 1).
  Tab. 1. Descriptive statistics and univariate differences (Mann-Whitney U-test) between partners and players from all levels
Table 2 and Table 3 show the descriptive statistics for partners and players at each level of competition, for shooting and activity with the ball. The players from level 1 demonstrated the highest level of basketball skills. Significant differences between players and partners were observed for 2-point field goals achieved (in the restricted area), 2-point field goal percentage (in the restricted area), 2-point field goals made, and efficiency of dribbling, but only at level 1. At level 2, significant differences in 2-point field-goal attempts (in the restricted area) were found between the two groups. At level 3, thew two groups were differentiated by the percentage of free-throws made, field goals achieved after a fast break or after a restart, and offensive rebounds. Finally, completed 3-point field-goals differentiated players at level 4.
In summary, 21 out of 42 game performance variables significantly differentiated players and partners at level 1 (eight with large ES; ES ≥ 0.05), 18 out of 42 at level 2 (nine with large ES; ES ≥ 0.05) and level 3 (seven had large ES; ES ≥ 0.05), and 17 out of 42 at level 4 (11 with large ES; ES ≥ 0.05). Tab. 2. Descriptive statistics and univariate differences (Mann-Whitney U test) between partners and players in shooting   Tab. 3. Descriptive statistics and univariate differences (Mann-Whitney U test) between partners and players in activity with the ball

Discussion

The aim of the current study was to compare the game performance of players with II and their partners in unified basketball. Our analysis, performed during Special Olympics European Summer Games, Warsaw 201, indicates that 31 out of 42 studied factors differentiated athletes with II (players) from partners. These included 2-point field-goals in the restricted area, and 3-point field-goals, as well as free throws, rebounds, turnovers, dribbling, and passes.
No significant differences were observed between partners and players with regard to 2-point field-goal shots taken; however, the partners took more shots in the restricted area and scored more points than the players, and the players took shots from outside the restricted area significantly more often than the partners. This may indicate a lack of good technical or tactical preparation by the players e.g., poor shot mechanics, not being able to recognize an opportunity to attack the basket and shoot from within the restricted area, or a lack of 1-on-1 offensive tactical skill. Since attempts in the restricted area are statistically the most successful in basketball, coaches should plan more time to teach players with II to attempt more shots inside the restricted area.
The next most important parameter in the analysis was free throws. The data indicates that the partners attempted and completed more free throws than the players; however, it is unclear which group committed more fouls. It is possible that players with II may have lower defensive skills and that they committed more personal fouls, because more partners attempted more free throws. Even so, the effect size of this difference was medium.
There were quite a few attempts in the 3-point zone for both partners and players, with the partners attempting 3-point shots more often than players. Since a 3-point attempt is technically and physically more difficult than a 2-point attempt, the partners were not very successful and players with II did not appear to be comfortable with attempting 3-point shots. Generally, while coaches should work to improve shooting accuracy from all positions on the court for both partners and players, they should pay special attention to the players to improve their shooting percentage.
In many instances, passes, rebounds, turnovers, and dribbling during games are not analyzed in detail for either able-bodied players or wheelchair athletes. In this study, because of the unique nature of unified basketball, it was necessary for the observers to consider more variables than those typically considered in running and wheelchair basketball. The list of observed parameters was chosen by expert unified basketball coaches; no such lists currently exist in the literature as this is the first such analysis of unified basketball.
The players threw significantly fewer completed passes than partners, but the two groups demonstrated similar passing efficiency. Even so the players threw nearly seven times fewer successful passes off the dribble, and nearly four times fewer successful field-goals off the dribble, and three times fewer turnovers while dribbling compared to the partners. This indicates that the partners spent more time dribbling the ball than players. This is supported by the large ES observed for differences in all dribbling factors between players and partners. Similarly, the players were not as active as the partners in steals, blocks, and assists.
Sampaio et al. (2015) found that certain game performance factors, viz. scoring, passing, defensive and all-round duties, differentiate all-star players from non-all-star players. They suggest that their findings may help optimize preparation for individual player groupings and improve the game performance of players and teams [11]. These findings emphasize the potential value of player-centered coaching in the Special Olympics.
In the 2010 Special Olympics European Summer Games, the partners appear to have played the dominant role in the unified game. Although this may appear obvious, as some studies have found people with II to have a lower level of physical fitness than their peers, both players and partners in unified basketball should have equal physical fitness. However, at the foundation stage of training, coaches focus on motor development and the fundamentals of sports skills, with the aim of building a foundation of health, fitness and nutrition habits: the rule of Unified Sports®. Therefore, it is unclear why there should be so many differences between players and partners. It is possible that the players with II may be very easily stressed, not ready in terms of mental preparation for training and competition; they may also be adversely influenced by the unusual setting, such as a game taking place in a nearby court, and by the special atmosphere of sports events or competition.
Secondly, developing the relations between players and partners requires many training sessions together and many shared drills with players with partners. Such training should also improve the individual skills of players at the “learning to train” stage aimed at taking players to the next level by focusing on specific sports training with partners. It is evident that similar levels of sport skills cannot always be achieved among players and partners. Even players have emphasized that the training program has the most significant positive influence on their social self-concept, or at least on the physical self-concept [21]. Castagno (2001) report that an eight-week training program improved social relations and self-esteem of participants with II as much as their basketball skills [22]. However, future partnerships, such as cooperation between the SO and European league, may offer improvements in the technical and tactical aspects of the game, along with the social nature of the unified basketball program [23].
Thirdly, the significant differences in game performance noted between players and partners could be due to differences in anthropometric parameters. Cavedon, Zancanaro, and Milanese (2015) compared four different groups (sports ability class) of young wheelchair basketball players with their game parameters and anthropometric parameters. Their findings indicate that the sitting height and sport classification of the players especially correlated positively with performance outcomes, but not with game experience or skinfolds [24]. Also, Apostolidis and Emmanouil (2015) confirmed relationships between anthropometric parameters, technical skills and handgrip strength in young basketball players; they suggest that coaches should consider anthropometric parameters, technical skills and handgrip strength when recruiting players to their teams [25]. We would also recommend such an approach for coaches in unified basketball.
It is, however, important to underline that competitive, player development and recreation models exist in Unified Sports [8]. In the competitive model, most athletes have similar sports skills and all participate in regular training sessions, while in the development and recreational models, the partners have significantly better sports skills and only assist the players; likewise, in the latter two, regular training sessions are not a key aspect [26].
However it is unclear which Unified Sports Model is represented in the current study. Although Unified Sports favors a homogeneous model, represented by the competitive model [8], the results of the game analyses suggest that rather the development model (player development) or the training model (recreational) were observed. The partners played a dominant role in the games, performing more actions on the court, and remaining more active than the players. Therefore, to build a more competitive approach among the players, it is recommended to practice more small-sided games with the same intensity as in the competition and to train without partners or with their minimized participation i.e. player-centered coaching.
Regarding the models of the analysed competition, 42 indicators of game performance were recorded for each of the four sports groups, with the highest performance demonstrated by level 1. Statistically significant differences were observed between players and partners for 21 out of 42 performance indicators at level 1, compared to 17 out of 42 performance indicators at the lowest level (level 4). In level 2 and 3, significant differences were observed in 18 out of 42 indicators. It is intriguing that partners playing at level 1 had worse results in the game parameters than partners playing at level 2, and that partners at level 2 had worse results than partners at level 3.
Interestingly, large or close to large effect sizes were observed between levels for all dribbling parameters. The best dribbling efficiency was observed among partners at level 1, indicating that partners at levels 2, 3, and 4 were more active at dribbling but made many mistakes and they were not as effective. Significant differences were noted between partners and players in dribbling and passing at all four levels. Those are very important technical skills in basketball and require good skill from athletes. It may be the case that the players had difficulties with such technical skills. To address this, it is recommended to devote more practice time to throws and ball dribbling to create a basketball team ready for competition.
This was particularly evident with assists, where significant differences were noted between players and partners. Assists in basketball require technical and tactical skills from athletes, which are difficult for both players and partners. Partners on level 1 were more effective at 2-point field-goal percentage (inside in the restricted area), 2-point field-goal percentage (out of the restricted area), 3-point field-goal percentage, and free throw percentage than other partners at levels 2, 3, and 4; however, all players had similar efficiency results, regardless of level.
Nevertheless, the true role of athletes with II (players) in unified basketball remains uncertain. It seems that partners played the primary role on the court at all levels because they attempted more game elements. However, partners still have a significant role when playing basketball with people with II and their participation in training programs, and this cannot be lightly dismissed. Their participation is very beneficial as it provides people with II with both the positive and negative aspects of social inclusion, together with the opportunity to improve their sporting skills [21,22,27]. It could be possible to reduce the number of partners on the court during a unified basketball game e.g., one partner and four players, so that players have greater roles during the game, but this requires future research.
Limitations of the study and recommendations for further research
One limitation of the study was the difference in age between the players with II and their partners, because people of similar ages tend to have similar interests and needs. In addition, it only considers the psychomotor aspects of Unified Sports basketball, as well as some cognitive factors. Also, the study does not compare player / partner performance in the initial games with later ones; the resulting data would have provided an insight into whether the coaches, experts and classifiers correctly assessed the levels of the players and partners.
Future research could compare the anthropometrical parameters of the players and partners with game performance, and game performance in Unified Sports during different events. It could also compare the performance of the basketball players with the final results. The obtained data could be used to review the 2011 SO Unified Sports rules regarding the ratio of players to partners on the court. It might also be advisable to allow all participants to complete without division by skill level, to confirm the effect of dividing players into levels. Research should also examine the social and affective aspects of sport.

Conclusions

Our analyses indicate that the partners play a dominant role in unified basketball and are more active on the court, thus rejecting our hypothesis. The system of matching partners and players should be more focused on choosing partners who have the same level of physical fitness as players with II, to meet the rules of Unified Sports.
Further studies should examine the game performance of participants in unified basketball during different tournaments. The findings may support the validity of using the current ratio of players and partners on the court, or as the basis for suggesting other combinations of players and partners.

Acknowledgements

The authors would like to thank the organizers of the Special Olympics European Summer Games in 2010 in Warsaw (Poland) for providing the opportunity to conduct this research and supporting the researchers’ efforts.

Funding

The publication is a result of the International Scientific Conference Occupational Therapy Evidence-Based Practice project funded by the Ministry of Science and Higher Education under the program Excellent Science II.

Conflicts of interest

The authors declare no conflict of interest.

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