Contemporary Sports Issues – Page 80

Addiction and the College Athlete: The Multiple Addictive Behaviors Questionnaire (MABQ) with College Athletes

INTRODUCTION

Addiction is a complex behavior and a major health problem in America (American Psychiatric Association, 2000). Schaef (1987) defines addiction as an insidious process that we are powerless to control, propelling us to act in ways contrary to our values and beliefs and may progress to obsession and maladaptive action. Persons with addictive behaviors are at high risk for affective disorders, criminal behavior, ethical misconduct, absenteeism, and problematic relationships (American Psychiatric Association, 2000; Weiss, 1999). Collegiate student-athletes are thought to be at an even higher risk for academic and socially problematic behaviors than their nonathletic peer cohort (FindLaw, 2002; National Collegiate Association Drug Education Committee, 2001).

Problematic behaviors such as alcohol abuse, steroid use, pathological gambling, weight control behavior, and exercise addition are common maladaptive behaviors within the athletic population at all ages and levels of sport. The media continues to highlight professional athletes who, as a result of maladaptive behaviors, have serious health conditions, relationship problems, or a decline in athletic performance. Ken Caminiti, 1996 MVP in baseball, career was cut short as a result of extensive steroid use; Pete Rose’s gambling problem; or the deaths of Korey Stringer and Rashida Wheeler after consuming ephedra are but a few examples. Sadly though, these athletes serve as role models for youths.

In the most recent NCAA study, 78.3% of the respondents reported using alcohol within the past year and that for most, the problem began in high school (2001). The American Psychiatric Association (2000) reports that 60% of males and 30% of females have had one or more negative event(s) in their lives as a result of alcohol use. The prevalence of eating disorders is significant among female athletes (Kirk, Singh & Getz, 2001). Although both men and women do not meet the diagnostic criteria for an eating disorder
as delineated in the DSM-IV-TR, there appears to be a large percentage of female athletes (Overdoff & Gill, 1994) and a growing number of males (Pope, Phillips, & Olivardia, 2000) with subclinical eating
problems. Studies report between 15% and 62% of college women engage in problematic weight control behaviors (Berry & Howe, 2000). The weight control methods used include: overuse of laxatives and diuretics, excessive exercise, and self-induced vomiting. (Pope, Phillips, & Olivardia,
2000).

Gambling in athletics is also a major concern. Sports wagering, beginning in high school and increasing in college is done by 50% of student-athletes (Engwall, Hunter, & Steinberg, 2003
showed evidence of pathological gambling behavior. Gambling activities in sport include: playing cards for money, wagering on sporting events, playing the lottery, and casino betting (Miller, Adams, Kraus, Clayton, Miller, Anderson, & Ogilvie, 2001).

Not all addictive behaviors involve ingesting a substance. Like gambling, excessive exercise is a process whereby the individual engages in excessive activity or series of actions or interactions (Schaef, 1987). Distance running is a common addiction sometimes referred to as a negative addiction (Hailey & Bailey, 1982). Process addictions, like gambling and exercise, meet the basic criteria of an addiction: powerlessness to stop at will, have harmful consequences, unmanageability in other areas of life, escalation of use, and withdrawal upon quitting (Kasl, 1989). In addition to the possibility of having multiple or cross addictions, many athletes meet the criteria for a dual diagnosis, that is, have a clinical depression along with a substance abuse or gambling addiction (Miller, Adams, Kraus, Clayton, Miller, Anderson, & Ogilvie, 2001).

The purpose of this study was to measure five addictive behaviors on two levels: problematic and clinically diagnostic. The addictive behaviors targeted for this study included: gambling, drug abuse, disordered eating, exercise addiction, and alcohol abuse. These five variables were chosen upon careful review of the literature as to which behaviors would be most associated with collegiate student-athletes.

METHODS

Subjects

The study consisted of ninety-nine male and eighty-six female Division III college athletes (N=185) between 18 and 23 years of age, primarily Caucasian (92.4%), middle class student-athletes from a mid-size New England college. Ninety-two percent of the participants lived on or near the campus. There was a fairly equal distribution of student by year: freshman (34.1%), sophomore (27.0%), junior (25.9%), and senior (23.0%).

Students reported the following distribution overall out of 4.00 G.P.A.: 2.0-2.49 (35.7%), 2.5-2.99 (33.5%). 3.0-3.49 (23.2%), and 3.5-4.0 (5.9%). The participants were selected from twelve teams: baseball, football, field hockey, lacrosse, softball, volleyball, men’s and women’s soccer, basketball, and swimming. Participation was voluntary with written consent. The Committee for Use of Human Subjects approved this study and informed consent was obtained from all participants.

Testing Procedure

A survey instrument, The Multiple Addictive Behaviors Questionnaire (MABQ) (Bacon & Lee, 1997) was developed to measure five addictive behaviors: gambling, substance abuse, disordered eating, exercise, and alcohol abuse. The MAGS-7 (Shaffer, LaBrie, ScanLan, & Cummings, 1994) was used in full to assess the student-athletes’ gambling behaviors. Benyo’s (1990) Exercise Addiction Questionnaire and Rudy and Estok’s (1989) Running Addiction Scale provided guidance for the development of questions for the exercise variable. All other questions were derived from the diagnostic criteria for the remaining variables (substance, alcohol, and eating) as outlined in the DSM IV-TR (American Psychiatric Association, 2000). The MABQ was designed to measure both problematic and clinically diagnostic levels for each of the five addictive behaviors as well as obtain demographic data. The instrument contained thirty-five questions having both forced choice and Likert-type scale questions which are cumulative for each of the five addictive behaviors measured: gambling, substance abuse, disordered eating, exercise, and alcohol abuse.

Results

The data revealed large numbers of athletes who self-reported as meeting the problematic or diagnostic criteria for one or more addictive behavior. Not surprisingly, the data in the problematic category shows that exercise addiction was the largest category and substance abuse the smallest. In the diagnostic category, the highest frequency was with gambling, with 15. 1 % of students reported pathological addiction to this activity.

The low incidence of substance use reported might be due in part to NCAA regulations that prohibit and penalize collegiate student-athletes who have been found to engage in recreational and/or controlled substances.

To assess the interrelationships among addictive behaviors patterns (i.e., multiple addictive behaviors) reported on The MABQ, a principle components factor analysis with a varimax rotation was done. The analysis revealed two factors (clusters) of addictive behaviors. The first factor accounted for 44.54 % of the variance and consisted of substance abuse, gambling and alcohol. The second factor accounted for 26.74% of the variance and consisted of eating and exercise. Five T-tests were performed to examine gender differences among the addictive behavior patterns (Table 3). Females reported a significantly higher (p=.00l) prevalence of disordered eating; males reported a significantly higher (p=.02) prevalence of substance abuse. Although males reported a higher level of gambling behaviors, this result only approached significance (p=.07) suggesting that problematic gambling with female college athletes is a notable concern. There were no significant gender differences on the other subscales.

DISCUSSION

These findings are consistent with other research studies (Shaffer, 1997; National Collegiate Association Drug Education Committee, 2001) where investigators have reported growing numbers of college athletes exhibiting addictive behaviors. When data were examined in light of gender differences, two patterns emerged: male athletes fell into the substance/gambling/alcohol cluster and female athletes fell into the eating/exercise cluster. The cluster patterns were similar to those suggested by Shaffer (1994). The increase in disordered eating with males is consistent with the findings of recent research investigating body image disorders with athletes and physically active males (Pope, Phillips, and Olivardia 2000).

Interestingly, earlier research shows gambling to be found primarily among male athletes. Gambling appears to be on the rise for female athletes – although a closer look at individual responses revealed women to be engaging in different gambling activities (e.g. scratch tickets). It is well documented in the literature that there is a high correlation between disordered eating and substance/alcohol abuse (Walsh, & Garner, 1997; Krahn, 1991). In this study, disordered eating correlated with excessive exercise, but not with drugs or alcohol, for female athletes. This brings into question the idea of volitional intent or choice. In one study, Martin (1998) found significantly less alcohol use in-season than out-of-season periods among NCAA Division I female basketball, softball, and volleyball players.

Collegiate student-athletes are unique and face different challenges than their non-athlete peers (Engwall, Hunter, & Steinberg, 2003; Weiss, 1999). The sport environment is complex with student-athletes having
to negotiate a unique set of challenges: succeeding at both academics and athletics, issues related to time management, stress related to the pressures of their sport, peer pressure regarding recreational activities
including drug and alcohol use, and having to cope with the traditional developmental tasks typical of their peer group (Etzel, Ferrante, & Pinkney, 1991). Athletic department staff and Counseling Center practitioners are faced with developing and implementing appropriate and successful intervention strategies to address the special needs of this population.
Collegiate athletes report lecture style education programs to be noneffective (Martin, 1998). Further study is needed to better understand addictive behaviors and to determine the most effective interventions for college athletes.

One limitation worth noting is the use of a newly developed instrument that is currently being tested for validity and reliability (Bacon & Russell, 2003). All study findings must be reviewed with caution. The
MAGS-7 (Shaffer, LaBrie, Scanlan & Cummings, 1994) has been found to be both valid and reliable; therefore, the gambling subscale, including the problematic and clinically diagnostic levels can be given the most credence. The MABQ (Bacon & Lee, 1994) is undergoing extensive field-testing to establish concurrent criterion related validity for all five variables and content validity for the subset of questions that address each behavior.

Acknowledgment

This study was funded by a grant from the Center for the Advancement of Research and Teaching at Bridgewater State College.

References

Ajar, B. (January 1999). New pieces filling in addiction puzzle.
American Psychological Association Monitor, 30(1), 1, 15.
American Psychiatric Association. (2000). Diagnostic and statistical
manual of mental disorders, (4th ed., TR) Washington, DC: Author.
Bacon, V.L. & Lee, K. (1997). The Multiple Addictive Behaviors Questionnaire
– (MABQ). Unpublished instrument.
Bacon, V.L. & Russell, P.J. (2003, Feb). Multiple Addictive Behaviors
Questionnaire (MABQ) Validation Bridgewater, MA.: Bridgewater State
College.
Benyo, R. (1990). The exercisers. Champaign, IL: Leisure Press.
Berry, T.R. & Howe, B.L. (2000, Sept). Risk factors for disordered
eating in female university athletes. Journal of Sport Behavior, 23(3),
207-219.
Engwall, D., Hunter, R., & Steinberg, M. (2003). Gambling and other
risky behaviors on university campuses. Retrieved on May 26, 2003 from
http://www.ncaa.org/ConnecticutGamblingStudy.pdf.
Estok, P. & Rudy, E. (1986). Physical, psychosocial, menstrual changes/risks
and addictions in female marathon and nonmarathon runners. Health Care
of Women International, 7, 187-202.
Etzel, E.F., Ferrante, A.P. & Pinkney, J.W. (Eds.). (1991). Counseling
college student-athletes: Issues and interventions. Morgantown, WV:
Fitness Information Technology Inc.
Fitch, T.J. & Robinson, C.R. (1998, Nov/Dec). Counseling and development
interventions with college athletes: A proposed model. Journal of College
Student Development, 39(6), 623-627.
FindLaw (2002). Drugs in sports. Retrieved April 11, 2003, from http://fndlaw.com/legalnews/sports/drugs/index.html.
Hailey, .J. & Bailey, L.A (1982). Negative addiction in runners: A
quantitative approach. Journal of Sport Behavior, 5, 150-154.
Joy, E., Clark, N., Ireland, M.L Martire, J., Nattiv, A., & Varechok,
S. (1997, April). Team management of the female triad. The Physician
and Sportsmedicine, 25(4), 55-69.
Kasl, C.D. (1989). Women, sex, and addiction. NY: Harper and Row Publishers.
Kirk, G., Singh, K., & Getz, H. (2001, Fall). Risk of eating disorders
among female college athletes and nonathletes Journal of College Counseling,
4(2), 122-133.
Krahn, D.D. (1991). The relationship of eating disorders and substance
abuse.
Journal of Substance Abuse, 3, 239-253.
Lesieur, H.R., (1991, Summer). Black and white college students equally
bitten by the gambling bug. Journal of Blacks in Higher Education, (8),
83.
Martin, M. (1998, April/June). The use of alcohol among NCAA Division
I female college basketballs softball and volleyball athletes. Journal
of Athletic Training, 33(2), 163-167.
Miller, Adams, Kraus, Clayton, Miller, Anderson, & Ogilvie (2001).
Gambling as an addictive disorder among athletes. Clinical Issues in
Sports Medicine, 31(3), 145-152.
National Collegiate Athletic Association. (2001). NCAA study of substance
use habits of college student-athletes. http://www.ncaa.org.
Overdorf, V.G. & Gill, K. S. (1994). Body image weight and eating
concerns, and use of weight control methods among high school female
athletes. Women in Sport and Physical Activity Journal, 3(2), 69-79.
Pope, H.G., Phillips, K.A., Olivardia, R. (2000). The Adonis complex..
How to identify, treat, and prevent body obsession in men and boys.
NY: Simon & Schuster.
Schaef A.W. (1987). When society becomes an addict. San Francisco,
CA: Harper and Row.
Shaffer, H.J., LaBrie, R. Scanlan, K.M. & Cummings, T.N. (1994, Winter).
Pathological gambling among adolescents: Massachusetts Gambling Screen
(MAGS).
Journal of Gambling Studies, 10(4), 339-362.
Walsh, B.T. & Garners D.M. (1997). Diagnostic issues. In D.M. Garner
and P.E.
Garfinkel, Handbook of treatment for eating disorders, 2nd ed, pp.
25-33. NY: The Guilford Press.
Weiss, S.M. (1999, May). A comparison of maladaptive behaviors of
athletes and nonathletes. Journal of Psychology, 133(3), 315-323.

U.S. Sports Academy2015-03-20T10:38:24-05:00March 1st, 2004|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|Comments Off

The Cross Country Program to Transform Your Team

Submitted by: Mike Spino

Scope and Purpose

Cross country runners will improve their performance, and coaches can experience the empowerment of their vocation when pinpointed physiological methods and competitive focusing techniques are bonded together in periodically based training schedules. This seasonal training guide contains a definitive coaching approach to the sport of cross-country and includes a mental awareness component that compliments the physical training. In many instances an unforgettable season can occur not because the coach wins every contest he enters but because the sport of cross-country itself is transformed into a new form of interaction—one in which the composite of the season’s experience is as important as the final team scores.

Our purpose is to promote the cross-country coach to be the teacher, motivator, and central figure for a group of young people attempting to glean the satisfactions and rewards from a challenging sport. This article asks the coach to make a commitment to a new perspective–to focus on the “whole runner’ whether addressing a star performer or any other team member. Both high school and college cross country coaches can benefit from this program that has embedded in its drills and techniques the embodiment of a mind/body training system which delivers measures of success mentally, physically, and even spiritually.

Mapping Out the Season

Cross-country training is a process that starts in the warm summer months and ends in the chill of late autumn. It is above all else an activity of cycles. It is a 13-16 week season during which time the coach and team are beginning with a new base of conditioning and a year ahead full of promise and ambition. This article provides instruction in the workouts, drills, and methods used for each segment of the cross-country season. The suggestions outline an ideal season of training although we will also speak about how to handle injury and setback, so you can learn how to regroup and peak during the championship part of the season. At the end of this article, a means for reviewing how to evaluate the most important elements of the training process is explained.

Planning the Pre-Season

The season’s initial set-up for the high school, college, university, and post-collegiate coach has some dissimilarity. It is recommended that the first pre-season workouts begin on a flat grass field. We hope this minimizes a workout we call “the long sad gray line” which refers to the practice of mostly high school coaches to have their team run for an indiscriminate time along the streets with the lead runner striding smoothly in front and everyone else straggling behind. Rather from the beginning, our method emphasizes selective group training. The coach’s objective is to figure out whom to train with whom, and what workouts, and what sequence of workouts will get the entire team at full throttle when it counts most- during the championship part of the season. The genius of all groupers was Hungarian born Mihlay Igloi who was coach to many star runners who used his method for vast improvement. His mastery could be observed in watching 30 to 40 runners in six or seven groups doing all manner of workouts in different directions and various speeds and finishing the workout together. The successful cross country coach does not have to be this precise, however, understanding the nuances of applying workouts that are physiologically accurate and diverse is at the heart of this program

Segments of the Year Long Program

The flat grass surface should be at least as large as the inside of a football field and if possible accessible to locations for long continuous running. As in all successful periodization training, each segment has a goal, methods, and techniques to achieve a particular result that naturally plateaus before it blends into the next phase of training. The coach teaches new techniques and terms in each phase of the training and the methods are broken down into the physical and mental aspects of the workout. Each new phase of the season will have the group return to the grass field to learn additional techniques that are then integrated into the whole program. The goal is for all aspects of the training and for each runner in the group to reach the zenith of peak performance during the championship phase of the season

Pre-Season Workouts

The initial phase of training is the pre-season that in the U.S. season lasts from July to the end of August. In the pre-season,the goal is to learn the initial techniques that are applied in the interval part of the training plan. Our aim in all phases is to keep all team members injury free as an aerobic base of conditioning is established. The unique training techniques are physical and mental as the team is training physically but also learning how to utilize lung and mental capacities to their maximum potential.

Gaits and Tempos of Running- Initial Drills for Teaching Gaits and Tempos

The pre-season begins with instruction in the application of gaits and tempos methodology. To accomplish this the coach can face the team directly on the grass field and lead or have a team member demonstrate the forms and speeds of running used in our interval training. We all know that effective training takes a sensibility of pace and an understanding of the best forms of running movement to achieve physiological efficiency. Using perhaps a straightaway of 100 meters, the coach explains that a gait is the form of movement during the run and that the tempo is the velocity at which you move. As the coach gives these gaits and tempos names, he is developing a language to communicate his training instructions and a means to carry out his training instructions. Igloi’s terminology works well in this regard as fresh swing tempo is assuming a gait and velocity to go up to about 60% effort. Good swing tempo approaches speeds from 60 to 80%, and hard swing tempo is between 80-95% effort.

During the entire season each training phase has at least one and usually two days of training on this grass field. The terminology however can be used on all surfaces and workouts during the entire season. One of the main reasons for using the gait and tempo with the whole group initially is to make sure each runner has time to “regroup,” so the workout retains group unity. The stopwatch should be used sparingly at the beginning of the season. When used properly, the stopwatch should determine the level of conditioning rather than be a means of setting up workouts to get in shape. In the pre-season, the team learns mid pace running, so as to maximally utilize the Exercise Heart Range (220-age and 60-85% of the target numbers) and avoid sprinting that places the runners’ physiology over the Anaerobic Threshold where it is shutting down its capacities because of the presence of lactic acid.

The three weeks of pre-season will contain two kinds of workouts- intervals and long continuous runs. Interval workouts have a particular sequence of warm-up, stretching, the body of the workout, and a recovery method.

For the warm-up during pre-season, the coach can instruct with the following information.

Warm-Up During Pre-Season- After the team jogs together for about 5 minutes; finish the warm-up with a few easy stretches and a technique called the shake-up.

The following stretches are good for starters.

Fully Body Swing: Feet shoulder width apart, raise your arms and extend to the sides swinging your entire body from right to left.
Grape Picker: Slowly stretch both hands overhead, then stretch your right hand as high as possible, and repeat on the left side as if your were picking grapes
Lateral Stretch: Raise right arm straight overhead, palms up as you place your left hand on your left hip. Bend as far as possible to the left while reaching over and down to the left with your right arm. Repeat on the other side.
Wall Stretch: Leaning on a wall or tree moves your right foot back about two feet and place your heel down, toes straight, lean into the wall bending the left foot forward and allow your right leg to stretch. Do on the other side.
Skip and Shake-Up: On the grass field take a distance of maybe 60 meters begin by skipping as a child skips, only raising your knees a bit higher. Shake up by letting your muscles hand like a rag doll, and every so often throw your hands over your head and to the sides but stay mainly on your toes to loosen up our body and elevate your heartbeat to get ready for the workout. Up and down the 60 meters about 4 times is usually good to complete the warm-up.

Begin the first workout by teaching the difference between fresh, good and hard swing. Have your team run at the various tempos and they will naturally assume the gait that accomplishes the objective. The coach will do perhaps three or four 100-meter intervals with a rest period between each so the group can regather together after each segment.

Introduction of the breathing drills

Breathing Drills- Our Breath is our Awareness

The breathing techniques are taught on the grass field using the concept of the acceleration point. Usually accomplished just once at the point of acceleration, the technique known as tidal breathing propels the runner into a faster tempo half way into the interval. The coach can explain the following breathing principles to his team while standing in front of them on the grass field.

The coach can tell the team to remember that:

the exhale is the starting point of all breathing techniques. The sound of the exhale should reverberate like the sound of a hollow log.
when you use the full capacity of your lungs, your breathing begins in the diaphragm and rises to the top of your chest filling up like a balloon.
stored breath released properly can help accelerate you forward.
relaxing your lungs when stationary in between parts of the workout accelerates physical recovery.

The technique of tidal breathing teaches the runner to fill his lungs to capacity, store it for a moment, and then spring forward into a faster gait thereby increasing speed and achieving a higher heart rate without greater exertion. On the grass field, the coach can stand in front of his team and give the following instructions. “Exhale all the air out of your lungs somewhat forcefully, and then bring your arms up the sides of your body to your chest. Store the oxygen for a split moment as you imagine the fullness to the top of your throat, then turn your palms over, exhale and drive your body forward.”

Teach tidal breathing by having the group begins running at a fresh swing and at the acceleration point doing a tidal breath, which accelerates them into a good swing tempo. Tidal breathing drills have the extra capacity to allow the runners to become more aware of their lung capacity and training aid potential

The Surge Technique

Using the same location of the grass field, another technique used in the training and applied in racing to accelerate is the surge. Again on the grass field the surge allows the runners to propel forward by pressing your thumb and first finger together like a gas pedal on a car making the sound of ‘ping’ in your throat and flying forward. This technique always gets a laugh, as the coach can explain it is like pouncing forward like a tiger. Of course physiologically, your heartbeat goes to the top of the exercise heart range when you surge.

Workout Recovery

How the runners finish a workout is as or more important than how one starts. This recovery sets the day for the next workout and is part of the entire sequence of a training segment. The technique called the Full Body Recovery lets the runners “check out” their physicality, and because they are relaxed at the end of the session, it provides the coach an opportunity to begin introducing ‘positive suggestions’ that can be built later in the season into a mental exercise that prepares the team for the championships. By tightening and relaxing each part of the runner’s body beginning in the feet and rising all the way up to the runners head, a physical awareness of each section of the body becomes apparent. For instance, while the group is mingling after the training, have them stand in a semi circle and close their eyes and begin by saying, “imagine a color. A cool refreshing color. It might be gold, green, or soft blue or any color that you identify with becoming refreshed. As you are thinking of this color, press your toes, then your heels to the ground, and squinch up your feet. Imagine the color leaving from your toes when you relax.”

At the end of the recovery, as their eyes are closed, you might have the runners begin to imagine themselves “running with perfect form, and feeling strong, fluid, and in control.”

Typical Pre-Season Workout

Following the day of instruction in which you introduced the gaits, tempos, and other techniques, the pre-season conditioning for 3-4 weeks can include variations of the following:

Long continuous distance from 30 to 50 minutes (usually in fresh swing)
One longer run that will be 1½ times as far as the regular continuous run
On the grass field measure out distances from 60 meters to 400 meters in combinations such as 110, 150, 220, 260, 300, and 400 meters. The short intervals in sets program can have the following elements:

10 minutes of jogging.
Stretches.
Skip/Shake-ups.
Interval Segment from 80 to 400 meters using the interval language with sections that express workouts like:

6 times 100 (50 fresh/50 good swing with tidal breath at junction).
Finish with full body recovery.

Typical Pre-Season Week

Three days of continuous running from 30-one hour a day (a collegiate runner may run twice a day, etc)
One day of 1 ½ times longest run (For top runner this can be as long as two hours)
Two days of short intervals in sets (high school workout should be about 30 minutes, top runners can have interval workouts as long in duration as 1 hour and twenty minutes
One day of active rest or a very short easy run.

Techniques for the pre-season include: gaits and tempos, acceleration point, tidal breathing, stretches, skips shake-ups, surging, full body recovery. Optimum use of the exercise heart range and avoiding the anaerobic threshold.

Early Competition phase- Late August to the End of September

Proper running locations are necessary for maximizing results. For the early competition phase, the coach should add:

A loop of a mile or so of grass if possible that is relatively flat.
A trail that is about 30 minutes of undulating surfaces that contain some but not many hills.
Keep the grass field.
Have your continuous run trail that leaves from your front door.

The grass field introductory methods of this phase introduce the mental aspects of the training program. The thing to remember when tapping into the imagination of your team’s mental capacities to make practice more fun and enjoyable and transfers to all kinds of situations. Using your mental capacities is like training your body. It takes time and persistence, and your runners improve in increments.

The Mental Training Workout

The coach has introduced mental training techniques during the full body recovery. The team has closed their eyes and placed their mind’s eye inside their body to review their condition after the workout. On the grass field, the group has had at least six workouts of using short intervals in sets, and now we will add a few new mental awareness applications to the workouts.

The technique used in mental training on the grass field is called active visualization, and it uses the methods of soft eyes and the principles of push and pull imagery to attain the desired results. To teach the soft eyes technique, have the team stand still with their eyes closed and in their mind’s eye visualize a bird flying over a mountain- notice the smoothness of his feathers, every detail of his flight movement. Next, have the team open their eyes slightly, so they can see out and at the same time keep the image of the bird in their mind. When the team applies this to an interval run,remember this technique should only be done in a safe environment and never on a street where there are cars present or you can trip over a curb.

The Hand Push Drill. Have your team stand in front of you on the grass field, and after placing them in soft eyes mode, have them visualize a hand coming out of the sky. Tell them that the hand is round them and supports your whole body. Tell the runners to lean back into the hand and feel its support. Feel it all the way up your body with the top of your hand supporting your neck. Lean back into the hand for support, so that when you begin running at fresh or good swing, the hand is doing most of the work, and you are just being carried along. Feel the hand guide you up the field. This active visualization can help you when you are struggling during a race or hard practice. Moreover, you will find that the techniques effectiveness is increased using a cue to signify the end of a particular segment. To do this uses the wipe away technique by brushing your fingertips across your eyes to return to normal viewing.

Rope Pull Forward. On the same grass field, the coach will have the team close their eyes and face up the field towards a goal or soccer goal, tree, or any non-movable object. Face the post with soft eyes and imagine there is a harness around your body from your waist up to your chest. Actually go through the motion of throwing a harness around the post while you are in soft eyes mode and have it be connected directly to your body. Actually feel the tug of the rope as it wants to pull you towards it. Have the runners raise their hands, and when they drop it, have it signify that they are being pulled towards the post. Run towards the post at fresh or good swing, and when the run is complete, use the wipe away technique to condense and finish the segment of the workout.

Speed Play Drills

One the one-mile grass loop or the undulating trail the following two techniques can add camaraderie and structure to the workouts. The manner of speed play, going at various tempos at your own discretion, is an excellent way to reach diverse physiological goals. The following are two-speed play drills. They are called energy transfer and the 24-step formula. The first utilizes the concept of natural body heat or energy into a partner games, and the second has a duo or individual increase the heart beat into higher aspects of the exercise heart range.

Energy Transfer Drill. Have your team learn the energy transfer drill going up and down the flat grass field, and then they can transfer it to the one-mile grass oval or undulating trail. Begin the game of ‘energy transfer’ by facing each other, possibly with soft eyes. Rub your hands together and then place them over each other, noticing how far apart each hand must be from the other while still maintaining contact signified by the heat generated between your hands. Speed play is put into effect when one partner drops his/her hands and faces up the field while the other takes the energy into his/her own hands and places it into the other person’s. As the runner goes behind the partner to a designated spot or distance, one partner stops and faces the other maintaining the “heat” by the rubbing together of two hands and when “recharged” runs back to the starting point or next spot on the trail. This is a fun way to get your heartbeat into the top of your exercise heart range. Sometimes if you have a boys and girls team you can let them match up, and it is a little like going to the dance.

The 24 Step Formula is another speed play workout in prescribed “mix” of segments of 24 steps in cadence of light, moderate, and brisk tempos of walking, jogging, or running. The term 24 steps refer to the number of steps taken in each cycle of the workout. The method has nine perambulations:

Walk: light, moderate, brisk
Jog: light, moderate, brisk
Run: light, moderate, brisk

If one were to move through a complete sequence, there would be eight changes of pace within 216 strides. The 24 steps refer to the cadence when the 24 Step formulas come into play. Count from one to twelve on each strike of the left or right foot. At twelve, announce the cycle such as light, moderate, or brisk to yourself. There may be a few steps of adjustment when going from a brisk back to a light cycle.

You can have your team utilize the 24 step formula method as a speed play workout or with a partner. It can be the second part of a continuous workout or as a speed play through the wooded trails.

Workouts in the Early Season

Continuous runs from the house from 30-50 minutes.
One or two days on the grass field utilizing gaits, tempos, breathing techniques, surging, and active visualization.
On the one-mile grass loop, you can do energy transfers with a partner or 24 steps. Also another good speed play is a few minutes of fresh or good swing with a break like 3 minutes fresh swing, one-minute jog or walk.
Sunday run should be 1½ times farthest run.
Continuous runs on the trails.

Your team will have run probably two or three tune-up races, and you may have a person or two hurt or at least somewhat injured at this juncture in the season.

What To Do With Your Injured

There are many forms of therapy from chiropractic care, massage, physical therapy, orthotics, and acupuncture. All and any can be helpful to your hurt or injured athlete. However, the best advise for the coach trying to keep his cross country team in tact without a big gap in the score is to separate out your injured and put them on their own program. It may sound simplistic, but the best advise to give a coach being driven mad with injury is to have your runner do the same workout every day while injured and at a location where he can stop whenever the pain is getting worse rather than better. Whether it is jogging on the one mile grass or doing fresh swing tempos back and forth, the runner knows how the injury is progressing in its healing process if his body knows exactly what to do each day and can gauge to go further or less. When the runner is improving, slowly integrate him or her back into the group but not too quickly or in a competitive situation.

THE MID RACING SEASON—4 weeks

During the racing season you can continue to meet on the grass field once a week for the short interval in sets workouts using all the gaits, tempos, and other techniques at your disposal. You can add two new workouts.

Continuous workouts remain the same, and you can lighten up to fresh swing on any to recover for the more difficult or precise.
On the grass or dirt one mile loop, measure out about 2/3 of the way around and have your team run at about 80% good swing anywhere from 3 to 6 times. You might want to break the team into two or three smaller groups. Time the run but also pay attention to the rest period and keep it to a jog if you can.
Let your long run remain 1½ times the continuous and let it be bit slower than before.
Two or three times during the 4 week period, have your team run up a gradual hill and find a flat space at the top or on an adjacent field and do about 4 times 100 meters at good swing.
Rest easy for meets and try to do them only every two weeks, so that you can alternative a 14-day cycle with two days of rest on either side of a 10-day period.

Tips: Continue to keep the full body recovery after at least 50% of the workouts and begin expanding the suggestions in the end phase by saying statements such as: you are feeling better and better with each race, or notice how you are rounding into shape so nicely.

The Championship Part of the Season

In the championship part of the season, you can return to the grass field and go back into a training pattern resembling the pre-season. Over the last 10 days, we will introduce a mental training for the event.

Add the following workouts

On the grass field, add a set of fast 60 to 80 meter hard swings with long rest walk back runs.
For one of the continuous workouts, have the whole group run together in a “pack” to gain team spirit
Cease hill climbing and do one workout of only 2 or 3 times the 1000 meter run with a long rest and no pressure on the group for time (but they will run fast anyway)

Event Rehearsal

10 days before the championship, bring the team together and talk about the championship course. Ask them to write down the flowing or challenging parts of the course or have the coach write down the responses. Have the coach strategize how to break the course down into three parts- the start, mid, and finish of the race. Write down a script that covers all the aspects of the race. Some tips are to have the runners “feel strong and fluid”, “get into a bubble at the beginning of the start to get a perfect run out,” “notice the time they would like to achieve and see it on the scoreboard, finishing strong and under control.” Do the event rehearsal at least three times in the last ten days and the night before the race. It is best to do it the last time before you go to the course. If you go to stay over night before the big race, that is the perfect time for the last event rehearsal

Summary and final review

In my fifteen years of coaching, I have found various approaches and methods that insure success, both from a personal as well as professional perspective. These approaches can be separated into two distinct and wholly dissimilar philosophies that represent the likelihood of success or failure. These two cycles are the cornerstones for success or failure. They are: The Cycle of Imminent Defeat and the Cycles of Impending Success. The coach is responsible for which of these cycles he chooses.

The coach will invite a greater likelihood of failure if the:

team does not participate in pre-season conditioning.
practice does not start on time and tardiness by the team is acceptable
coach does not address emotional and psychological distractions.
coach fails to plan workouts and to provide training schedules to all participants.
coach loses sight of the overall purpose of the season.
coach does not keep the overall health and well being of his team paramount.

Conclusion

By studying the above cornerstones of success in review, it does well to look at the elements of the program and realize how paying attention to each segment almost guarantees success. If you start the season with an overall well conditioned team and create a program that leaves room for them to grow personally and psychologically within the context of the planned schedule, you are on the right track. When you provide every avenue for making good decisions with the welfare of each runner in mind, success will surely come your way. Watch the athletes as they mature in the program and listen closely to how they are responding and what they are saying and being successful at team cross country is one of the most rewarding experiences in all sport.

U.S. Sports Academy2016-04-01T09:47:25-05:00January 9th, 2004|Contemporary Sports Issues, Sports Coaching, Sports Exercise Science, Sports Management|Comments Off

The Changing Role of Local Television Sports

Submitted by: Dr. Brad Schultz & Mary Lou Sheffer

Abstract

A study was conducted to assess how the sports segment within the local television newscast is changing. Literature suggests that many stations are eliminating or otherwise revising the sports segment in response to industry conditions.

Results indicated changes but more in terms of style and presentation than in time allotment. The sports segment is emphasizing more localism and appealing to casual fans. Major factors for change were audience ratings and competition from all-sports networks. The implication of these changes for the broadcast industry and journalism education were discussed.

Introduction

If there has been a constant throughout the history of television in the U.S., it has been local news. Almost from the time stations first signed on the air, they began delivering local news in which sports has always had an integral role. Lacking a consistent source of programming in these early days, many stations turned to sports to fill their broadcasting schedule. WNBT television in New York signed on the air in July 1941, and its very first telecast was a professional baseball game (“NBC history,” 2003). In developing local newscasts to suit their audiences, these stations usually included sports and weather. In 1961, for example, WKMG started the first full-time news department in Orlando. The newscast included a sports report by Frank Vaught (“The history of,” 2003).

Sports maintained an unchallenged position in the local newscast for several years, but recent trends within the industry have called this position into question. Fragmenting audiences, changing demographics, and declining news profitability have caused stations to reexamine their local sports segment. “Sports is one of the last areas of TV where people do things the way they’ve always done them,” says television executive Elliott Wiser. “(Today) you have to have a new approach” (Deggans, 2000).

The Problem for Local TV News

Several factors have combined to threaten the supremacy of television as the main provider of news for Americans. According to a study conducted by the Project for Excellence in Journalism (2002), television newscasts are losing viewers. In 1998, two-thirds of stations reported a decline in viewership for their local newscasts. By 2002, that number had risen to 76%. Even in the aftermath of the terrorist attacks in September 2001, local news viewership fell seven percent.

The emergence of media sources such as the Internet, cable channels, and home satellite has given viewers a news alternative. According to research from the Radio and Television News Director’s Association (“Changing channels,” 1996), a “significant portion of the public tunes into a variety of other sources on a regular basis.”

As more and more stations become controlled by larger media companies, local television news has also become more bottom-line oriented. In the first few weeks of 2002, for example, three station groups decided to completely eliminate local news at their subsidiary stations (Trigoboff, 2002). “I think there’s going to be a shakeout,” said television news consultant Jim Willi. “Do we really need to have four or five newscasts in the same market at the same time?” (Trigoboff, 2002).

The Problem for Local TV Sports

None of this is good news for the local television sports segment which has come under increasing scrutiny from station executives. Despite its traditional presence within the local newscast, sports has long been considered a “tune out” factor. A survey by the Radio and Television News Directors Foundation indicated that only 31% of viewers said they were ‘very interested’ in the sports segment while 32% said they were ‘somewhat interested’ (“Journalism and ethics,” 1998). This compared to 72% who expressed an interest in the weather. “Sports is extremely polarizing,” said television news consultant Brent Magid. “The majority can either take it or leave it, or despise it” (Greppi, 2002).

Research suggests that women have much less interest in the sports segment compared to men (Gantz and Wenner, 1991, Perse, 1992), and many stations have acted accordingly. In 2000, WTSP in Tampa dropped sports from both of its early evening newscasts. According to station news director Jim Church, “Telling a story when nobody’s listening is not a good use of air time” (Deggans, 2000).

While some stations have eliminated sports, others have reduced the time allotted for it. Depending on the day of the week (weekends get more sports time), sports segments have traditionally received anywhere from three to five minutes of the local newscast. Now that number has dropped to as little as a minute. In 2002, KDKA in Pittsburgh reduced its time commitment to only three and a half minutes of sports for its three hours of news. Others in the industry have implemented new approaches such as sports stories that focus more on people than scores, or that cater to more of a news audience. “What we’re trying to do now is treat sports more as news,” says KDKA news director Al Blinke. “We want to do the stuff that transcends sports” (Finder, 2002).

Research Questions and Methodology

These conditions prompted the following research questions:

RQ1: Is local television sports changing, and if so, how?

RQ2: What factors are most responsible for causing this change?

RQ3: Where does local television sports appear headed in the future?

These questions were investigated with a national stratified sample of 340 news directors. News directors were chosen because they are the ones with direct control over placement, time allotment and presentation style of the local sports. In total, 163 valid responses were collected for a response rate of 49%.

Results

Most stations (84%) reported that the local sports segment within their major evening newscast gets three to four minutes, and the time for sports is declining slightly. In addition, not many stations (70%) were willing to completely eliminate the sports segment from their newscasts.

While time did not appear to be a factor, stations are considering changes to style, presentation, and content. The overwhelming response was more emphasis on local sports coverage and less coverage of national sports (62%), followed by more feature-oriented stories (14%).

The results of a correlation indicated that audience perception of the sports segment (r=.45, r² = .20, p < 0.01) and ratings (r = .43, r²= .18, p < 0.01) were the most influential factors for stations that changed the time allotted for sports. The higher the audience ratings and perception of the sports segment, the more time the station devoted to sports. Stations that viewed other all-sports networks as detrimental (r = -.40, r²= .16, p < 0.01) were much more likely to reduce the time allotted to sports. A multiple regression indicated that after controlling for financial stability and audience perception, audience ratings (b = -.11, p = .04) and all-sports networks (b = -.29, p < .001) were significant predictive factors.

The majority of news directors (63%) believed that the sports segment will decline in importance and time allotment in the future. Another 27% said that no significant changes will take place, while only 2% said that sports would increase in time and importance.

Discussion

The changes taking place in the sports segment have more to do with content, style, and presentation than time allotment. Perhaps in an effort to offer viewers a contrast to all-sports networks, local television sports is focusing more on local stories, athletes, and events and making its coverage more feature-oriented and viewer friendly for the casual sports fan. Typical of the responses was the news director in the Midwest who commented, “We want sports to be interesting to non-sports fans. Here, sports is news, is community. Give the viewer local as opposed to anything the many cable sports channels offer. Only we can go local. They can’t.”

As for the future of local television sports, news directors were more pessimistic which suggests two distinct time frames for this study-now and in the near future, and while local television sports seems safe, news directors have it on a very short leash. One news director noted, “I considered eliminating the sports department and reallocating those resources to put more news gatherers on the street. I am reluctant to do so now, but may in the future.”

Implications

Changes in local sports may be a reflection of the tremendous upheaval going on throughout broadcast news. If the sports segment is no longer safe, what does that say for other news elements? “[All of this] forces us to reexamine the [news] model,” said CBS Group News Vice President Joel Cheatwood (Trigoboff, 2002).

On a more immediate level, changes in the local sports segment directly affect thousands of aspiring sportscasters. Stations that are reducing their commitment to sports are also reducing their sports staffing levels which has an impact on the job market. “[Sports in the newscast] is dying,” said another news director. “We have gone from two full time sports people to one full time and one who works news three days a week, and keeping that position has been a fight.”

Just as important, the change in the way sports is presented requires would-be sports broadcasters to learn new methods. No longer can sportscasters focus on scores; they must make their presentation more engaging for the casual fan. This is also important for journalism schools around the country which must take note of what stations want in a sports segment and update their teaching curricula.

Will these changes work or even last? Commenting on KDKA’s changes, sportswriter Chuck Finder (2002) noted, “Let’s reserve final judgment until September, when the Steelers, college and high school football seasons fully get underway. We’ll see then if the station . errs in clock management.”

References

Changing channels: Young adults, Internet surfers and the future of the news audience. (1996). Radio and Television News Directors Association. Retrieved November 15, 2002, from:http://www.rtnda.org/resources/channels/chsum.html

Deggans, Eric. (2000, April 27). Local TV eliminating some sports reports. St. Petersburg Times. Retrieved December 11, 2000, from: http://www.sptimes.com/News/ 042700/Sports/Local_TV_eliminating_.shtml

Finder, Chuck. (2002, July 18). The big picture: KDKA-TV alters sports approach. Pittsburgh Post-Gazette. Retrieved November 20, 2002, from: http://www.post-gazette.com/sports/columnists/20020718thebig5.asp

Gantz, Walter and Wenner, Lawrence. (1991). Men, women and sports: audience experiences and effects. Journal of Broadcasting and Electronic Media. 35, (2), 233-243.

Greppi, Michelle. (2002, August 19). Time out for sports? Local stations debate how much coverage viewers really want. New Orleans Times-Picayune, p. 9.

Journalism and ethics integrity project. (1998). Radio and Television News Directors Foundation. Retrieved January 13, 1999, from: http://www.rtnda.org/research/judg.shtml

Local TV news project. (2002). The Project for Excellence in Journalism. Retrieved November 15, 2002, from: http://www.journalism.org.resources.research/reports/localTV/2002/disappearing.asp

NBC history. (2003). WNBC television. Retrieved January 9, 2003, from: http://www.wnbc.com/wnbc/1169359/detail.html

Newsroom profitability survey. (2001). Radio and Television News Directors Association. Retrieved March 18, 2003, from: http://www.rtnda.org/research/money.shtml

Perse, Elizabeth. (1992). Predicting attention to local television news: need for cognition and motives for viewing. Communication Reports. 5, (1), 40-49.

The history of WKMG-TV. (2003). WKMG Television. Retrieved January 9, 2003, from: http://www.local6.com/orlpn/insidewkmg/stories/insidewkmg-20000911-122225.html

Trigoboff, Dan. (2002, February 11). Live at 11? Maybe not for long. Broadcasting & Cable, p. 3.

U.S. Sports Academy2016-04-01T09:46:52-05:00January 7th, 2004|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|Comments Off

Evolution of Scholars’ Approach to Studying Consumer Loyalty in Recreational Sport and Fitness Businesses

Submitted by: Tian-Shiang Kuo, Chia-Ming Chang, and Kuei-Mei Cheng

Abstract

Customer loyalty is of great value to recreational sport agencies in terms of their effectiveness and success. In recent decades, students in the field of recreation and leisure have paid growing attention to the phenomenon of customer loyalty. This paper reviews how exploration of consumer loyalty began, especially in the field of recreation and leisure. There have been three stages of evolution: the one-dimensional approach, two-dimensional approach, and multidimensional approach. The latter two developed out of critiques of an established approach. The authors find the multidimensional approach to be the most comprehensive, and thus the most promising, perspective for future research on consumer loyalty in the field of recreation and leisure.

Evolution of Scholars’ Approach to Studying Consumer Loyalty in Recreational Sport and Fitness Businesses

Because it is much cheaper to serve loyal customers and easier to maintain their support, customer loyalty is of great value to organizations (Seybold, 2001). Rosenberg and Czepiel, whom Park and Kim cite (2000), claim that attracting a new customer costs 6 times more than retaining an existing customer. To a great extent, the success of a recreational sport and fitness business depends on how the business manages customers’ loyalty (Backman & Crompton, 1991a, 1991b). As Park and Kim note, consumer loyalty is embodied not only in economic transactions with a business but more broadly in general support for the organization (Park & Kim, 2000).

Glimpsing the importance of consumer loyalty to sport-related businesses, in recent decades scholars in the field of recreation and leisure have paid growing attention to the phenomenon of customer loyalty (Gahwiler & Havitz, 1995; Howard, Edginton, & Selin, 1988; Park & Kim, 2000). What has been the result of this increased focus? For one thing, a gradual evolution in how researchers approach the phenomenon of customer loyalty has resulted. Three stages can be roughly identified. In the very beginning, most investigators focused on only one dimension of consumer loyalty, either the behavioral or attitudinal dimension. Next, as a result of criticism of this initial research model, models that approached both behavioral and attitudinal dimensions of customer loyalty were developed. Finally, the latest studies of customer loyalty incorporate multiple attitudinal or psychological facets. This has led to a deeper, better-integrated understanding of loyalty. The following describes in more detail each evolutionary stage of the historical development of customer loyalty research.

]One-Dimensional Approaches to Studying Consumer Loyalty[

Behavioral Approaches

The majority of early studies of consumer loyalty looked only at its behavioral dimension. A customer was viewed as loyal to a product or service if he or she demonstrated “consistent purchase of one brand over time” (Backman & Crompton, 1991b). According to Prichard and colleagues, one-dimensional behavioral approaches were classified in four groups by Jacoby and Chestnut (Prichard, Howard, & Havitz, 1992, pp.156–157). The first group comprises researchers who located loyalty in the customer’s purchasing sequence, for example George N. Brown. The second group comprises researchers such as Ross M. Cunningham who defined loyalty on the basis of the proportion of the customer’s purchases that featured the brand in question. Jacoby and Chestnut’s third group includes the scholars who applied probability models to analyze consumers’ purchasing behavior. To this group belongs Ronald E. Frank, who in the early 1960s investigated repeat-purchase probabilities using a simple chance model. The fourth and last of Jacoby and Chestnut’s groups integrated several behavioral variables to generate its definition of customer loyalty (Prichard et al., 1992). Burford, Enis, and Paul (1971), as an example, put forward an index combining three behavioral measures of customer loyalty: proportion of resources spent on brand or store, amount allocated to switching, and the number of alternative brands or stores.

While operationalizing such behavioral approaches is easy enough, at the same time they may exhibit fatal weaknesses as theoretical frameworks upon which to hang studies of consumer loyalty. Beginning in the late 1960s, some consumer loyalty researchers began to criticize behavioral approaches to their task (Howard et al., 1988, p. 42). They pointed out, for example, that because the associated measures relied on overt, observable behaviors, behavioral conceptualizations of consumer loyalty were doomed to such error as the classification of particular consumers as loyal in one study and nonloyal in the next (Backman & Crompton, 1991b, p. 206). Moreover, failure to identify relations between loyalties measured by different patterns of use brought many researchers to the conclusion that “brand loyalty encompassed more than repeat use” (Backman & Crompton, 1991b, p. 206).

Attitudinal Approaches

Conceptually, behavioral models could not, Day noted (1969), discriminate between true or intentional loyalty and spurious loyalty (Backman & Crompton, 1991b; Prichard et al., 1992). Day (1969) and Jacoby (1971) proposed an attitudinal conceptualization of customer loyalty in order to better understand it. According to Jacoby (as cited in Prichard et al., 1992), a customer who shows brand loyalty by implication “repeat[s] purchase based on cognitive, affective, evaluative and predispositional factors: the classical primary components of an attitude” (1971, p. 26). Prichard et al. (1992) also briefly review those early researchers who looked at psychological aspects of consumer loyalty as well as behavioral. Guest, Monroe, and Guiltinan; Bennett and Kassarijia; and Jain, Pinson, and Malhotra all made an effort to study consumers’ attitudes or intentions.

Just like approaches focused one-dimensionally on consumer behavior, however, approaches focused one-dimensionally on attitudinal loyalty had limitations. According to Prichard et al., the early studies of the attitudinal components in consumer loyalty, when they were reviewed by loyalty theorists, were often found to lack adequate theoretical conceptualization. A result of this was a multitude of measures that confounded research. Examination of the theoretical and empirical rigor underlying the development of various attitudinal measures raised certain questions about construct validity (Prichard et al., 1992).

Overall, then, early definitions of customer loyalty as solely a behavioral construct or solely an attitudinal construct could be accused not only of superficiality but also of insufficiency. In time, a two-dimensional approach would replace these flawed perspectives.

]Consumer Loyalty as a Two-Dimensional Construct[

As noted by Jacoby and Chestnut, neither behaviors nor psychological attachments alone could well explain customer loyalty (Backman & Crompton, 1991a, p. 2). Criticism of the old models (which was most vigorous against the one-dimensional behavioral models) informed the development of a new model integrating behavioral and attitudinal dimensions. Day’s (1969) new two-dimensional definition of consumer loyalty (cited in Selin, Howard, Udd, & Cable, 1988, p. 220) provides an example of the advances at the research’s next evolutionary stage. Day’s results showed his consumer loyalty index combining behavioral and attitudinal dimensions to have twice the predictive power of the behavioral approach.

Olson and Jacoby’s (1971) six-point definition of loyalty followed Day in supporting with empirical evidence the idea that loyalty’s “cognitive” and “behavioral” parts were separate and identifiable (Backman & Crompton, 1991b, p. 207). Olson and Jacoby defined loyalty as “a biased, behavioral response, expressed over time, by some decision making unit, with respect to one or more alternative brands out of a set of such brands, and [moreover] . . . a function of psychological processes” (Prichard et al., 1992, p.159). The definition came to be “widely accepted as the conceptual basis for loyalty research” (Backman & Crompton, 1991b, p. 207).

After Day (1969) and Jacoby (1971), a consensus developed in the field that loyalty should be treated as a two-dimensional construct, a concept including both behavioral and attitudinal facets. As Backman urged, “to measure loyalty necessitates assessing both affective attachment to an activity as well as measuring behavioral use of the activity” (1991, p. 335).

According to Selin et al. (1988, p. 219), the two-dimensional model offered by Day and Jacoby was improved on in a study Jacoby reported with Kyner (1973). They used a two-dimensional definition of loyalty weighing both repeat purchase and consumers’ attitudes, and their definition became the next “definitive” standard for the measures used in loyalty studies.

Once the two-dimensional model was available, many researchers applied it in investigations of consumer loyalty. Most representative is Backman and Crompton’s operationalization of this approach in loyalty research (1991a), following their review of the conceptualization of loyalty proposed by such earlier researchers such as Pessemier, Day, Olsen and Jacoby, and Howard, Edginton, and Selin. Backman and Crompton studied golf and tennis participants and used attitudinal and behavioral scores to segment the respondents in their study. A semantic differential scale with 13 items was used to measure participants’ “general feelings” about golf and tennis (1991a, p.208); a two-dimensional matrix next was used to distinguish four discrete levels of loyalty. The resulting four-quadrant matrix served to group participants according to their weak versus strong attitudes and their high versus low “behavioral consistency” (Mahoney & Howard, 2000, p. 16).

Backman and Crompton (1991a) divided studied consumers into four groups having different levels of loyalty: low loyalty (weak psychological attachments and weak behavioral consistency); latent loyalty (strong psychological attachment but weak behavioral consistency); spurious loyalty (weak psychological attachment but strong behavioral consistency); and high loyalty (strong psychological attachment and strong behavioral consistency). Mahony and Howard (2000, p. 17) judged Backman and Crompton’s research to offer an improved grasp of consumer loyalty in a context of sport and leisure, because their two-dimensional operationalization “reaffirmed and extended Day’s claim” about loyalty and also “provided important insights into the complexity of the construct” (Mahony, Madrigal, & Howard, 2000).

The two-dimensional approach combining behavioral and psychological facets of consumer loyalty advanced the literature on loyalty by overcoming weaknesses of earlier, one-dimensional approaches. As it turned out, however, most two-dimensional studies of consumer loyalty were themselves deficient, in that it proved very difficult to measure consumers’ psychological attachment to brands. In the end, even the operationalization of Backman and Crompton’s attitudinal loyalty was far from sufficient (Mahony et al., 2000, p.17). In recent years, the further exploration of the attitudinal dimension has led to the conceptualization of consumer loyalty as a dynamic process.

Beyond the Two-Dimensional Model

The complexity of the attitudinal dimension, in particular, has drawn the attention of many recent researchers to the multifacetedness of the concept of consumer loyalty. Park and Kim’s analysis (2000) of attitudinal loyalty within the recreational sport industry indicates three components of attitudinal loyalty: normative loyalty, based on “social expectation or normal pressure”; affective loyalty, based on “affective attachment”; and investment loyalty, based on “accumulation of investments.” Park and Kim further suggest that all of these dimensions are distinct and should be simultaneously taken into consideration to explain attitudinal loyalty.

Prichard et al. (1992) note that in past decades, commitment as a component of attitudinal loyalty attracted much attention from loyalty researchers. They further describe how multidimensional models of commitment based on Buchanan’s work (1985) paralleled the studies of composite loyalty. (Buchanan had defined commitment using three dimensions: behavioral consistency, affective engagement, and degree of investment.) They also argued for Crosby and Taylor’s conceptualization of commitment (1983) as the one to “provide a sound theoretical basis for operationalizing the attitudinal dimension of recreation loyalty.” Crosby and Taylor used both “cognitive consistency” and “position involvement” when conceptualizing commitment.

Acknowledging that consumer loyalty was multidimensional, some scholars went a step farther and began to investigate the relationships between dimensions of loyalty. Applying hierarchical multiple regression analyses, Park (1996) studied the relationships between involvement and attitudinal loyalty constructs in a fitness program, reporting the two constructs to be “highly intercorrelated” though independent. According to Park, both involvement and attitudinal loyalty are multidimensional.

Gahwiler and Havitz (1995) also sought to understand these relationships. Dissatisfied with how earlier research had investigated in isolation from one another such factors as social subworld, involvement, psychological commitment, and behavioral loyalty, Gahwiler and Havitz studied the four simultaneously (p. 3). Analyzing data from a study of YMCA patrons, they found that a relatively high level of consumer loyalty was positively related to each of the following: relatively greater social-world integration, relatively greater position involvement, and relatively greater psychological commitment (p. 1).

Iwasaki and Havitz (1998) proposed a path analytic model of the relationships among loyalty’s dimensions (involvement, psychological commitment, and loyalty). They criticized studies by Park (1996) and by Kim, Scott, and Crompton (1997), arguing that the development of consumer loyalty really was a dynamic process. Iwasaki and Havitz outlined the progressive stages consumers went through enroute to becoming loyal customers; these sequential psychological processes included (a) formation of high levels of involvement in an activity, (b) development of psychological commitment to a brand, and (c) maintenance of strong resistance to any change of brand preference (p. 256). In addition, Iwasaki and Havitz believed that variables such as personality and social status “moderate the developmental process” (1998, p. 256).

These relational studies involving multiple dimensions of consumer loyalty facilitated understanding of the loyalty concept and are more comprehensive than the one- and two-dimensional approaches had been. The path analytic model, especially, in representing a dynamic process, advanced an investigation of the mechanism by which an individual develops consumer loyalty. The model may be less parsimonious than previous models, but it provides an insightful theoretical framework for further study of consumer loyalty.

]Conclusion[

Reviewing the evolution of the consumer loyalty concept, looking at several decades’ worth of loyalty research, suggests that the concept’s complexity was not adequately acknowledged by the behavioral approach, attitudinal approach, or even composite approach to its study. Only recent multidimensional modeling of consumer loyalty that incorporates relational analyses of loyalty’s dimensions and a path analytic model, as Iwasaki and Havitz did (1998), is dynamic enough in its approach to psychological processes to offer a useful direction for future research.

]References[

Backman, S. J. (1991). An investigation of the relationship between activity loyalty and perceived constraints. Journal of Leisure Research, 23(4), 332–344.

Backman, S. J., & Crompton, J. L. (1991a). Differentiating between high, spurious, latent, and low loyalty participants in two leisure activities. Journal of Park and Recreation Administration, 9(2), 1–17.

Backman, S. J., & Crompton, J. L. (1991b). The usefulness of selected variables for predicting activity loyalty. Leisure Sciences, 13, 205–220.

Buchanan, T. (1985). Commitment and leisure behavior: A theoretical perspective. Leisure Sciences, 7(4), 401–420.

Burford, R. L., Enis, B. M., & Paul, G. W. (1971). Functional and behavioral application: An index for the measurement of consumer loyalty. Decision Science, 2, 17–24.

Crosby, L. A., & Taylor, J. R. (1983). Psychological commitment and its effects on post decision evaluation and preference stability among voters. Journal of Consumer Research, 9, 413–431.

Day, G. S. (1969). A two-dimensional concept of brand loyalty. Journal of Advertising Research, 9, 29–35.

Frank, R. E. (1962). Brand choice as a probability process. The Journal of Business, 35, 43–56.

Gahwiler, P., & Havitz, M. (1995). Toward a relational understanding of leisure social worlds, involvement, psychological commitment, and behavioral loyalty. Journal of Park and Recreation Administration, 13(2), 1–23.

Howard, D. R., Edginton, C. R., & Selin, S. W. (1988). Determinants of program loyalty. Journal of Park and Recreation Administration, 6(4), 41–51.

Iwasaki, Y., & Havitz, M. E. (1998). A path analytic model of the relationship between involvement, psychological commitment, and loyalty. Journal of Leisure Research, 30(2), 256–280.

Jacoby, J. (1971). A model of multi-brand loyalty. Journal of Advertising Research, 11, 25–30.

Jacoby, J., & Kyner, D. (1973). Brand loyalty vs. repeat purchasing behavior. Journal of Marketing Research, 10(2), 1–9.

Kim, S. S., Scott, D., & Crompton, J. L. (1997). An exploration of the relationships among social psychological involvement, behavioral involvement, commitment, and future intentions in the context of birdwatching. Journal of Leisure Research, 29, 320–341.

Mahony, D. F., Madrigal, R., & Howard, D. (2000). Use the Psychological Commitment to Team (PCT) Scale to segment sport consumers based on loyalty. Sport Marketing Quarterly, 9(1), 15–25.

Olson, J. C., & Jacoby, J. (1971). A construct validation study of brand loyalty. Proceedings of the American Psychological Association, 6, 657–658.

Park, S. H. (1996). Relationships between involvement and attitudinal loyalty constructs in adult fitness programs. Journal of Leisure Research, 28(4), 233–250.

Park, S. H., & Kim, Y. M. (2000). Conceptualizing and measuring the attitudinal loyalty construct in recreational sport contexts. Journal of Sport Management, 14, 197–207.

Prichard, M. P., Howard, D. R., & Havitz, M. E. (1992). Loyalty measurement: A critical examination and theoretical extension. Leisure Sciences, 14, 155–164.

Selin, S. W., Howard, D. R., Udd, E., & Cable, T. T. (1988). An analysis of consumer loyalty to municipal recreation program. Leisure Sciences, 10, 217–223.

Seybold, P. (2001). Loyalty incentives. Executive Excellence, 18, 15.

Author Note

Tian-Shiang Kuo; Chia-Ming Chang, D. S. M.; & Kuei-Mei Cheng, D. S. M.

U.S. Sports Academy2015-03-20T08:55:06-05:00January 4th, 2004|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|Comments Off

NCAA Tennis Coaches’ Views on Recruiting with a Team Website

Submitted by: Jonathan Casper and Peter S. Finley

Abstract

At most universities today, the athletic program maintains an Internet website to provide information about its particular teams and put into athletes’ hands a form for prospective team members that can be submitted directly to coaches for appraisal of the athletes’ academic and athletic information. To date no research has sought insight into how and to what extent websites are used by coaches as recruiting tools. The present study surveyed NCAA tennis coaches (N = 232) about this topic. According to its results, most coaches find the website to be useful in the recruiting process. Comparison of coaches in three NCAA divisions showed that the lower division coaches use and value this recruiting tool significantly more (p < .003) than do Division I coaches.

NCAA Tennis Coaches’ Views on Recruiting with a Team Website

It is clear that athlete recruitment represents an important component of collegiate athletics. For students, the would-be recruits, “selecting a college is a time-consuming and difficult process” (Kirk & Kirk, 1993, p. 55). This process, at least for student-athletes, involves the consideration of several factors, including but not limited to a school’s geographic location, its urban or rural setting, the size of its student population, the reputations of its academic and athletic programs, and its graduation rates (Kirk & Kirk, 1993).

The recruiting process, of course, is intended to shape student-athletes’ selection of a college. Despite the increasing importance of recruiting across all division levels of the NCAA (Klenosky, Templin, & Troutman, 2001), the process has received little scholarly attention. The use of unique team websites to carry out via the Internet the important coaching duty of recruiting has been nearly ignored. One examination, however, of the websites maintained by NCAA women’s cross country teams found they are being used as tools in the recruiting process (Finley & Finley, 2003). Supporting the study’s claim was the presence on websites of such content as letters to prospective athletes, NCAA clearinghouse information, and electronically transferred personal information forms. It was noted, as well, that most school websites could do far more to maximize their potential in the recruiting process, for example by supplying more of the kind of information expected to be of interest to recruits, such as coach’s philosophy, review of athletic facilities, and images of teams.

A 1998 report from the Commerce Department said that Internet usage doubles every 100 days, with more than 100 million people now online in the United States (Caskey & Delpy, 1999). Worldwide usage estimates from September 2002 furthermore suggest at least 605 million people use the Internet (NUA Internet Surveys, 2003). The Internet clearly has “evolved into a mainstream communications medium for Americans, as well as users in other countries around the world” (Caskey & Delpy, 1999, p .13).

Given the sport’s international nature, using the World Wide Web to reach prospective athletes may be of especial significance to collegiate tennis. According to Casey Angle, director of communications for the Intercollegiate Tennis Association, in the 2002–03 academic year 17% of NCAA tennis players were international students, with nearly one third of Division I players being foreign born (personal communication, June 5, 2003). Recruiting players who live overseas may be accomplished more readily with a complete and compelling website than by more traditional means. Particularly at the Division III level, for example, tennis programs have limited recruiting budgets. As Walsh (1997) describes it, “Coaches at the second tier schools recruit just as actively as the larger universities. But their recruiting budgets are smaller, and they often must play a waiting game” (p. 135). In fact, a Division III tennis program has an average annual recruiting budget of a paltry $300 (Fulks, 2000). The Internet can offer an inexpensive means of bringing coaches together with players too far away to visit. Walsh notes (1997) that, “In the non-revenue producing sports with limited recruiting budgets, coaches may be more eager for information” (p. 89).

In addition to disseminating information to prospective student-athletes, websites have come to be used for information gathering, delivering initial forms for completion by the prospect. Such a form elicit descriptions of a prospect’s playing experience, academic performance, and contact information; it is returned directly to a coach’s e-mail. Finley & Finley (2003) noted that such forms are present on over half (51.9%) of those websites maintained by NCAA women’s cross country teams, with 72% of Division III programs utilizing them.

The present study sought to better understand contemporary approaches to recruitment of NCAA tennis players by surveying their prospective coaches. The researchers were guided by three research goals: (a) to determine the extent to which NCAA tennis coaches view websites as meaningful aids in recruitment; (b) to determine the the extent to which the coaches value electronic prospective student-athlete forms; and (c) to observe any significant differences among the responses of Division I, II, and III coaches, as well as between the responses of coaches using prospective student-athlete forms and coaches not using them.

]Method[

Participants and Instrument

The sample consisted of 232 head tennis coaches (109 from NCAA Division I schools, 50 from Division II schools, and 73 from Division III schools) who where current members of the Intercollegiate Tennis Association (ITA). The ITA serves as the governing association of college tennis and also prepares rankings throughout the competitive season. The researchers contacted by e-mail all head coaches having an e-mail address published in the 2002–03 ITA membership directory, inviting their participation in the study; approval to use the directory was granted by the ITA.

The study comprised an original exploratory study in this subject area. It employed a survey containing 13 questions for coaches whose team website included a prospective student-athlete (PSA) form, and 9 questions for coaches whose website did not include a PSA form. The first 2 questions (for both groups) established which NCAA division (I, II, or III) a coach belonged to and whether the coach used a PSA form featuring electronic submission. Remaining questions solicited coaches’ perceptions of the value of websites and PSA forms to recruitment, using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Table 1 and Table 2 present the survey questions, response means, and standard deviations.

Procedures

A specialist in statistical research methods assessed the survey instrument’s face validity prior to pilot testing of the instrument. A college sports information director responsible for managing an athletic program website featuring a PSA form also reviewed the instrument. Recommendations from the two led to the omission or revision of some of the survey questions. A pilot study with 7 coaches from various sports was then conducted to ensure that all survey items were clear and relevant to the research goals. Feedback from the pilot study participants enabled the researchers to enhance the items’ clarity with further wording changes.

An e-mail to NCAA head tennis coaches invited them to complete the survey online by following a web link. The e-mail informed the prospective respondents that the study intended to describe tennis coaches’ attitudes toward team websites and PSA forms. The prospective respondents were told (a) that participation was voluntary, (b) that no personal information would be solicited, (c) that no more than 3 min would be needed to complete the survey, and (d) that respondent identity would be kept confidential. The link to the survey remained active for 3 weeks after the initial invitation was sent. A follow-up e-mail reminder was sent 2 weeks after the initial invitation to coaches who had not returned the survey. The web link was designed to prevent submission of multiple surveys by a single respondent and could be accessed only by coaches who had been sent the initial e-mail invitation.

Descriptive statistics were calculated using the competitive division variables (I, II, III) and use-of-PSA-form variable. A series of univariate ANOVAs using the Bonferroni adjustment was then conducted with each of the remaining questions, to examine the relationships of competitive division (independent variable) to coach perceptions of the website and PSA form in the recruiting process (dependent variables). Student-Newman-Keuls (SNK) post hoc tests were employed to differentiate the NCAA divisions on the variables. The responses of coaches using a PSA form and those not using such a form were differentiated with t tests.

]Results[

The means and standard deviations for each question are presented in Table 1. In specific terms of their athletic program websites, the surveyed coaches all perceived the website to be an important recruiting tool, whether they served Division I, II, or III institutions. Most of the coaches indicated a belief that prospective student-athletes do use websites to select a school and that maintaining a quality website is important. Coaches who used a PSA form perceived it as a useful tool for recruiting and information gathering, but gave more neutral answers when asked if such forms gave them a recruiting advantage over programs not using PSA forms. Similarly, coaches not using PSA forms gave relatively neutral answers when asked if they perceived themselves as disadvantaged by lack of a PSA form. In general the coaches not using forms agreed that the technology would improve their chances to recruit better players.

Post hoc analysis of those questions generating significant differences during ANOVA revealed certain NCAA division–based trends in recruiting. Relative to coaches in the other two divisions, Division I coaches did not feel the PSA form effectively identified and recruited athletes or gathered information. Division I coaches who used a PSA form also perceived a relatively small recruiting advantage in that form, compared to Division II and Division III coaches who used the form. In addition, compared to the lower division coaches, Division I coaches reported less likelihood of responding to a prospective athlete who had contacted the coach via a PSA form. Coaches in the top NCAA division reported that players completing PSA forms had little chance of making a roster, as compared to the coaches in Division II and Division III. Division I coaches not using a PSA form also indicated a lesser tendency than Division II and Division III coaches to respond to players who contact them about their program.

Table 2 shows the means and standard deviations for the comparisons of the responses from coaches using PSA forms and coaches not using them. ANOVAs were also conducted to detect significant differences between the two groups’ attitudes. The analysis indicated only one significant difference, which was that coaches not using PSA forms agreed more strongly that an athletic program website is an important recruiting tool.

]Conclusions[

Although the study found some significant differences, among NCAA head tennis coaches the general trend is a perception that an athletic program website and PSA form are valuable tools in the recruiting process and that students are likely making choices based on information such websites present. Division II and Division III coaches value websites and PSA forms, for identification of potential recruits, to a greater extent than Division I coaches do. These study findings suggest how useful Internet recruiting technologies may prove for NCAA Division II and Division III athletic programs, as a low-cost means to locate and recruit prospects. Further research will need to examine how prospective student-athletes use the Internet to gather information affecting college choice as well as which website elements influence prospects most.

Table 1

Survey Items’ Descriptive Statistics, by NCAA Division, Employing 7-Point Likert Scale of 1 (Strongly Disagree) to 7 (Strongly Agree)

Question	Division	N	Mean	SD
The website is an important tool in the recruiting process.
	1	108	5.92	1.23
	2	50	5.58	1.62
	3	73	5.56	1.17
	Total	231	5.73	1.31
A quality website will help attract prospective student-athletes.
	1	108	5.97	1.06
	2	48	5.83	1.36
	3	73	5.90	1.08
	Total	229	5.92	1.13
I believe student-athletes are using information from team websites to assist in making their college choice.
	1	107	5.90	1.15
	2	49	5.76	1.11
	3	73	5.44	1.12
	Total	229	5.72	1.14
My team’s website is updated frequently to provide information that may be of interest to prospective student-athletes.
	1	108	5.22	1.38
	2	49	4.65	1.87
	3	73	5.16	1.51
	Total	230	5.08	1.54
In identifying and recruiting prospective student-athletes, the prospective student-athlete forms contribute very little to the process (respondent uses PSA).^a
	1	53	4.51	1.61
	2	20	3.60	1.39
	3	53	3.21	1.49
	Total	126	3.82	1.63
The prospective student-athlete form is an important information gathering tool (respondent uses PSA).^b
	1	53	4.60	1.47
	2	20	5.35	1.35
	3	53	5.53	1.12
	Total	126	5.11	1.38
Having the prospective student-athlete form gives me a recruiting advantage over schools that do not have this technology available (respondent uses PSA).
	1	53	4.25	1.30
	2	20	4.80	1.61
	3	52	5.04	1.43
	Total	125	4.66	1.44
Most players who complete the prospective student-athlete form have little chance of making the roster (respondent uses PSA).^a
	1	53	4.77	1.34
	2	20	4.05	1.73
	3	53	3.40	1.39
	Total	126	4.08	1.55
I respond to players who fill out the prospective student-athlete form (respondent uses PSA).^b	1	53	5.57	1.20
	2	20	6.00	.97
	3	53	6.21	.86
	Total	126	5.90	1.07
The prospective student-athlete form begins a dialogue through which I inform players about my program (respondent uses PSA).
	1	52	5.27	1.40
	2	20	5.50	1.64
	3	53	5.85	1.15
	Total	125	5.55	1.36
Not having the prospective student-athlete form puts me at a recruiting disadvantage compared to schools that have this technology (respondent does not use PSA).
	1	55	4.56	1.85
	2	29	4.72	1.53
	3	20	4.80	1.24
	Total	104	4.65	1.65
I respond to players who contact me about my program (respondent does not use PSA).
	1	55	6.38	.89
	2	29	6.31	.54
	3	19	6.89	.32
	Total	103	6.46	.75
Having a prospective student-athlete form on my team’s website would improve my ability to identify and recruit quality players (respondent does not use PSA).
	1	54	5.09	1.65
	2	29	5.24	1.15
	3	19	5.53	1.07
	Total	102	5.22	1.43

^aDivision I differs significantly from Divisions II and III (p < .003). ^bDivision I and Division III differ significantly (p < .003).

Table 2

Descriptive Statistics for 4 Survey Items, by Respondent’s Use of PSA Form

Question	PSA	N	Mean	SD
The website is an important tool in the recruiting process.*
	PSA	126	5.51	1.43
	No PSA	105	6.00	1.10
	Total	231	5.73	1.31
A quality website will help attract prospective student-athletes.
	PSA	125	5.82	1.23
	No PSA	104	6.05	1.00
	Total	229	5.92	1.13
I believe student-athletes are using information from team websites to assist in making their college choice.
	PSA	125	5.62	1.13
	No PSA	104	5.85	1.16
	Total	229	5.72	1.14
My team’s website is updated frequently to provide information that may be of interest to prospective student-athletes.
	PSA	126	5.14	1.44
	No PSA	104	5.01	1.67
	Total	230	5.08	1.54

* p < .01

References

Caskey, R., & Delpy, L. (1999). An examination of sport web sites and the opinion of employees toward the use and viability of the world wide web as a profitable sports marketing tool. Sport Marketing Quarterly, 8(2), 13–24.

Finley, P. S., & Finley, L. L. (2003). An analysis of women’s cross country web sites at NCAA schools as aids in the recruiting process. The Sport Journal, 6(2). Retrieved October 3, 2003, from www.thesportjournal.org/2003Journal/Vol6 No2/websites.htm

Fulks, D. L. (2000). Revenues and expenses of Division III intercollegiate athletics programs: Financial trends and relationships–1999. Indianapolis, IN: National Collegiate Athletic Association.

NUA Internet Surveys. (2003). How many online? Retrieved October 3, 2003, from http://www.nua.com/surveys/how_many_online/index.html

Kirk, W., & Kirk, S. (Eds.). (1993). Student athletes: Shattering the myths and sharing the realities. Alexandria, VA: American Counseling Association.

Klenosky, D., Templin, T., & Troutman, J. (2001). Recruiting student athletes: A means-end investigation of school-choice decision making. Journal of Sport Management, 15, 96–106.

Walsh, J. (1997). Everything you need to know about college sports recruiting. Kansas City, MO: Andrews and McNeel.

U.S. Sports Academy2015-03-20T08:52:11-05:00January 2nd, 2004|Contemporary Sports Issues, Sports Facilities, Sports Management, Sports Studies and Sports Psychology|Comments Off