12
Behavioral sport psychology (BSP) is defined by the use of behavior analytic principles and techniques to enhance the performance of athletes, coaches, and others associated with sports (Martin & Tkachuk, 2000). The purpose of this chapter is to provide a brief history of the subspecialty known as BSP, to identify the main components of BSP, and to provide an overview of applications of BSP across a variety of domains. For a more detailed review of individual topics within BSP, readers may turn to Behavior Sport Psychology: Evidence-Based Approaches to Sports Performance (Luiselli & Reed, 2011). For a more thorough review of BSP applications, readers would benefit from the systematic review written by Schenk and Miltenberger (2019). Although physical fitness behaviors (e.g. exercise and nutrition) are important to sports performance, the analysis of this literature is outside of the scope of this chapter. A comprehensive review of existing literature for these topics within the context of behavior analysis is not currently available. However, a brief review of exercise assessment and intervention is available (Van Camp & Hayes, 2012).
History of Behavioral Sports Psychology
Sports psychology was established in the 1960s and was crystallized by the founding of several peer-reviewed journals, most notably the Journal of Sport Behavior and Journal of Sport Psychology. These journals centralized academic resources for clinicians interested in sports psychology. In 1972, Rushall and Siedentop published The Developmental and Control of Behavior in Sport and Physical Education. This book was written from a behavior analytic perspective and presented evidence-based teaching methods of sport-specific skills within an operant framework. Specifically, Rushall and Siedentop focused on behavioral strategies to optimize practice skills and generalize them to competitive settings. In 1974, McKenzie and Rushall published the first sport-specific article in the Journal for Applied Behavior Analysis, which demonstrated the efficacy of a self-monitoring package for improving practice performance of competitive swimmers. Many view this publication as the seminal article in BSP (Reed and Luiselli, 2015).
From the late 1970’s through early 1980’s, single-subject designs were incorporated into research targeting the improvement of athlete performance across a variety of sports including football, baseball, basketball, soccer, gymnastics, tennis, swimming, figure skating, and volleyball (Martin, Thompson, & Regehr, 2004). In addition to targeting athlete performance, BSP targeted improvements in coaching strategies (e.g., see Martin & Hrycaiko, 1983; Rushall & Smith, 1979; Smith, Smoll, & Curtis, 1979; Smoll, Smith, & Curtis, 1978). By changing the teaching strategies employed by coaches, researchers improved athlete behavior across the entire team rather than with individual athletes. Research was also expanded from contingency only applications to include cognitive–behavioral strategies for improving athletic performance (e.g., Desiderato & Miller, 1979; Gravel, Lemieux, & Ladouceur, 1980), while retaining the core features of BSP. The publication of BSP articles in sport journals increased from one article per year from 1974-1983 to 17 per year from 1994-2003, while the number of these articles published in behavioral journals remained between five and seven per year during that same timeframe (Martin et al., 2004). According to a recent review (Schenk & Miltenberger, 2019) a total of 101 articles have been published in BSP. Authors identified 23 intervention procedures across 21 different sports. This publication history demonstrates the growth of BSP as a discipline and also the acceptance of core BSP principles within more mainstream sports science.
Characteristics of Behavioral Sports Psychology
BSP contains five main characteristics, some of which overlap with traditional sports psychology, many of which are points of differentiation. Key features include; 1) the identification and operationalization of behaviors related to sports performance, 2) a focus on modifying antecedent and consequent variables, 3) contingency only and cognitive-behavioral applications, 4) reliance on single-subject design, and 5) socially validity (Reed and Luiselli, 2015). This section will define each of the five characteristics and provide examples of their importance to BSP.
Identification and Operationalization
The development of clear and concise operational definitions is essential to the study of any phenomenon (Skinner, 1945). Without clearly defined terminology, scientists are left to accept vague and ambiguous uses of the topic of interest. In the field of BSP, it is critical to identify target behaviors that will improve athlete and/or coach performance, to define those behaviors in a manner that allows reliable measurement, and to use changes in behavior as the primary indicator of success (Martin and Thomson, 2011). Sport-specific skills such as hitting a baseball or shooting a three-point shot are complex behavior repertoires that require operationalization to be appropriately assessed, to design effective interventions, and to track progress over time. Sports analytics represent one method of operationalizing and measuring such behaviors. The next sections will discuss the operationalization of sport-specific skills followed by an overview of sports analytics.
Defining Sport-Specific Skills
One way that behavior analysts understand a complex behavioral repertoire is by breaking it down to discrete observable components. This is known as a task analysis. Task analysis procedures are used to operationally define, measure, and teach a multi-step skill (Cooper et al., 2009). Once the task analysis is created, a chaining protocol is utilized to teach the discrete skills and link them together. Chaining refers to the procedure by which one learns to perform a series of behaviors in sequence following the presentation of a discriminative stimulus and ending with reinforcement (Alberto & Troutman, 2003). Completion of each behavior in the sequence (i.e., link in the chain) serves two functions: (a) as a discriminative stimulus for executing the next behavior in the chain and (b) as a conditioned reinforcer for executing the previous behavior in the chain. Several methods for teaching chained responses have been reported in the literature and include backward chaining (teach behaviors in reverse order from the terminal response), forward chaining (teach behaviors in sequence starting with the initial response), total task presentation (teach all behaviors each trial; Cooper et al., 2009). Task analysis and chaining procedures have a long history in behavior analysis and have been utilized to teach adaptive, social, and communicative skills. They have also been utilized to teach sport-specific skills.
In the context of BSP, a sport-specific skill can be broken down into smaller, teachable components. A relatively simple task such as throwing a baseball includes gripping the ball with the laces in particular orientation, separating the hand/ball from the glove hand, rotating the throwing arm to at or above shoulder level, extending the glove hand then tucking it into the hip, driving off the throwing side leg, planting the glove-side leg, rotating the hips, swinging the throwing arm through to the opposite side hip while releasing the ball on a desired plane, and following through with the throwing side leg. As exemplified by the pitching example, even a relatively straight-forward sport-specific skill requires chaining a set of discrete steps together to achieve optimal outcomes.
One example of the use of task analysis procedures to teach sport-specific skills to individuals with developmental disabilities (DD) was published by Luyben and colleagues (1986). First, the sport-specific skill, in this case a soccer pass, was broken down into a nine-step task analysis. Each component of the pass was operationally defined and taught using a forward chaining procedure. All three participants acquired this skill and maintained it with minimal reinstruction at follow up almost a year later. The next example highlights the use of task analysis and chaining procedures to teach shooting a basketball. Kladopoulos and McComas (2001) operationally defined five component skills required to shoot free throws with the appropriate form to three NCAA Division II women’s basketball players. Dependent variables included the percentage of shots made without touching the backboard and the percentage of shots executed with correct form. Following a chaining protocol, the percentage of shots taken with correct form and the percentage of shots made increased for all three participants. This provided evidence that a) component skills could be appropriately taught using the protocol outlined by the authors and b) that performing the component skills resulted in the desired outcome (i.e. increased shot accuracy). Task analysis and chaining procedures have also been implemented to teach martial arts skills. The studies discussed above demonstrate how complex sports-specific skills can be operationalized into smaller subskills, linked together, taught, and progress monitored to assess efficacy.
Sports Analytics
In Psychology as a Behaviorist Views It, Watson (1913) described the fundamental goals of behaviorism as prediction and control. Behaviorists must understand the behavior of interest to the extent that it could be explained, reproduced, and modulated with reliability. Sports analytics may be defined as operationally defined complex sport-specific skills used to measure athlete behavior, evaluate the effects of these behaviors on athlete performance, predict future behavior of the athlete or team, and to create environments that yield the greatest magnitude of reinforcement, in this case: winning. For example, at its most basic level a baseball manager may need to decide whether to keep a left-handed pitcher in the game to face a right-handed hitter. The manager knows in general, right-handed batters hit with a higher average (e.g. higher rates of reinforcement) against left-handed pitchers than right-handed pitchers. Thus, sports analytics enables the manager to make a data-based decision.
Several behavior analytic studies have analyzed sports performance through the concept of matching law. The generalized matching law describes the phenomenon in which response patterns match the reinforcer delivery when presented with concurrent behavioral options (Herrnstein, 1961; Baum, 1974). It has been conceptualized by behavioral scientists as the mechanism of choice. The generalized matching law explains variance in a wide variety of behaviors evaluated in applied settings including conversation (Borrero, et al., 2007), teen pregnancy (Bulow & Meller, 1998), and classroom conduct (Billington & DiTommaso, 2003). The increasingly analytic focus of sports has emphasized the importance of making data-based decisions, which has opened the door for the use of behavioral economic principles. Using an approach that quantifies athlete behavior with operant reinforcement offers advantages for those interested in analyzing and improving athletic performance.
Football play calling offers a convenient evaluation of the matching law. During a football game, the offense has up to four plays (i.e., downs) to advance the ball 10 or more yards. If this criteria is met, the offense is allotted an additional set of four downs to advance 10 additional yards, to advance the ball down the field towards the opposing team’s end zone. If the ball crosses the plane of the end zone, the offense is awarded six points. To advance the ball, the offense has two options: (1) pass the ball by throwing it to a receiving player or (2) rush the ball by handing it to a player who runs towards the opponent’s end zone. Given this simple two-choice arrangement, as well as the clear identification and quantification of reinforcement (i.e., yards gained), the matching law offers a lens through which play selection can be analyzed.
Three studies have been published that analyze play calling in football games through the lens of the matching law. The selection of rush or pass plays by coaches in the National Football League (NFL) was examined for sensitivity to reinforcement, bias, and variance across different game situations (Stilling & Critchfield, 2010). Generally speaking, their analyses indicate that sensitivity to reinforcement remains stable across downs, yards to the goal line, and score (i.e., whether winning, losing, or tied). However, their analyses revealed that teams became more sensitive to reinforcement as the end of the half approached and decreased as the number of yards needed for a first down decreased. Reed and colleagues (2015) examined the offensive play calling of elite football teams to determine if the relative proportion of passing to rushing plays approximated the relative proportion of yards gained passing to yards gained rushing. Indeed, these researchers found that the matching law did an excellent job in explaining offensive play calling across numerous elite football leagues (e.g., National Football League [NFL], Arena Football League, National Women’s Football Association [NWFA], several large NCAA conferences, etc. Additionally, data indicated that the degree to which NFL teams conformed to the matching law was significantly correlated with winning percentage –that is, teams that “matched” relatively better according to the matching law won more games than teams that did not.
Similar analyses have also been used to evaluate shot selection in basketball games. Vollmer and Bourret (2000) analyzed the allocation of two-and three-point shots by 13 male and 13 female National Collegiate Athletic Association (NCAA) Division I basketball players. In NCAA basketball, an arc designated with a painted line extends from the center of the hoop with a radius of 6.02 m (19 ft 9 in). When a player makes a shot from beyond this line that the player’s team is awarded three points. Shots (not counting free throws) made within the line are rewarded only with two points. Thus, at any given point during gameplay, a player with the ball has the choice to take a three-point shot, or advance closer to the basket for a two-point shot. Researchers examined the proportion of two-and three-point shots and compared this against the proportion of the number of points obtained for each shot type using the matching law. As predicted, the proportion of shots taken nearly perfectly matched the proportion of reinforcement the players obtained for making those shots. In addition to simply capturing molar shot selection–reinforcement relations (that is, summarizing large amounts of data collectively, rather than looking at game-to game performance), Vollmer and Bourret (2000) also sought to determine whether they could predict future shot selections. Toward this end, Vollmer and Bourret calculated the running aggregate allocation of shots from all previous games following each game to make a prediction about the allocation of shots for the next game. These researchers found their predictions became more and more accurate across the course of the season. Thus, not only does analyzing data at the molar level (i.e., analyzing data at the end of the season) within a matching framework describe shot selection as an operant behavior, but this analytic approach may also be translated to game-by-game data to predict future behaviors.
In a major extension of matching theory to understand factors affecting shot selection in basketball, Alferink and colleagues (2009) sought to determine the extent to which matching law accounted for the variance in 320 Division I college basketball teams. From these results, Alferink et al. demonstrated that their large sample resembled shot selection patterns similar to those reported by previous researchers (e.g. Vollmer and Bourret, 2000), further suggesting that matching theory is a robust phenomenon in basketball. Alferink and colleagues then investigated the difference in matching between Division I, II, and III teams. Their research indicated that more elite teams (i.e., Division I or II) conformed to matching theory to a greater extent than less elite teams (i.e., Division III). Moreover, Alferink and colleagues then compared regulars and substitutes from these teams, and found that regulars better conformed to matching theory than did substitutes. In these examples, Alferink et al. demonstrate that a relationship between matching and success exists –that is, there appears to be advantages to conforming to matching expectations. Nevertheless, it remains unclear whether better teams select players who conform to matching, or whether matching itself makes a team successful.
Antecedent and Consequent Interventions
The second characteristic of behavioral sports psychology is the identification of antecedent and consequent variables that impact sports performance and the modification of these variables to improve performance. This section will discuss the impact of antecedent and consequent manipulations on important sports performance variables.
Antecedent Interventions
Antecedent-based interventions are defined as a behavior change strategy that manipulates contingency-independent stimuli (Cooper et al., 2009). In BSP, antecedent procedures include any manipulation that occurs prior to the onset of the targeted sport specific behavior. Examples of antecedent interventions used to improve sports performance include instruction, goal setting, modeling (expert, video, etc.), and prompting. Antecedent interventions in BSP often include multiple components (e.g. instruction and modeling) and may include both antecedent and consequence-based interventions (e.g. goal setting plus reinforcement contingent on goal attainment). Examples of each are highlighted below.
Instruction
Verbal instruction is a form of rule governed behavior in which the instructor takes the place of the speaker and the performer takes the place of the listener. Specifically, the instructor provides a set of verbal rules that specify (explicitly or implicitly) contingencies for target behavior. In the context of BSP, the instructor (often the coach) provides a set of verbal rules regarding sport specific targets and specifies the contingency that achieving these targets will lead to increased access to reinforcement in the form of improved sports performance. A total 22 BSP studies implemented an instruction procedure (Schenk & Miltenberger, 2019). For example, Anderson and Kirkpatrick (2002) implemented a treatment package consisting of instruction, TAGteaching, and graphical feedback with four speed skaters. Results demonstrated that this treatment package increased skaters form but results were not maintained following a six month follow up.
Goal Setting
The concept of goal setting can also be described as rule governed. A behavior analytic account of goal setting includes two functionally separate but related events: the verbal behavior (overt or covert) of setting the goal and goal directed behavior. Talking about goals is one functional class of behavior, and behavior under the influence of such talking is another functional class. It is thus a behavior–behavior relationship (Hayes & Brownstein, 1986). If a person states a goal and then acts to achieve it, he or she is interacting with his or her own behavior in the moment, not with a future object. Lerner and colleagues (1996) implemented an intervention consisting of either goal setting (n=4), imagery training (n=4), or both (n=4) on free throw shooting performance with female collegiate basketball players. Three participants in the goal setting group improved free throw performance. Additionally, a strong positive correlation was identified between the goal and actual number of free throws made during the session.
Modeling
Video modeling is defined by the review of performance through digital medium. Boyer, and colleagues (2009) examined the effects of combining video modeling by experts with video feedback in the performance of gymnastic skills by female youth gymnasts. Following skill performance, the gymnast viewed a video segment showing an expert gymnast performing the same skill and then viewed a video replay of her own performance of the skill. Each gymnast was told to try to match her performance to the expert performance. The gymnast then returned to practice. The intervention was successful for all four gymnasts in the study.
Prompting
Stimulus prompting has been used to improve hitting performance with college baseball players. Osborne, Rudrud, and Zezoney (1990) studied curveball hitting proficiency of five college baseball players under baseline and two intervention conditions in an alternating treatment design (ATD). Before intervention, the players practiced hitting against a pitching machine that was adjusted to simulate a curveball thrown at a standard speed. The interventions consisted of marking the seams of baseballs with either 1/4 inch or 1/8 inch orange stripes. Each of these marked-ball conditions was compared to the unmarked-baseball condition during two batting practice sessions each day. The ATD showed that curveball hitting proficiency improved with the marked-ball intervention.
Consequence-based Interventions
A reinforcement procedure is any programmed consequence delivered or removed contingent on behavior intended to increase the likelihood of that behavior occurring (Cooper et al., 2009). BSP procedures were categorized as consequence procedures when some stimulus was introduced contingent on performance and was clearly described to function as reinforcement or punishment. Authors identified four separate procedures as consequence interventions: positive or negative reinforcement, auditory feedback, token reinforcement, and chaining.
Positive or Negative Reinforcement
BSP studies met criteria for using positive or negative reinforcement if they explicitly stated that programmed reinforcement was a component of the intervention, or if praise, positive feedback, or specific social positive statements (e.g., “great job,” “well done,” etc.) were provided by the behavior change agent contingent on a correct target response. Twenty‐three studies implemented a positive or negative reinforcement procedure (Schenk & Miltenberger, 2019). For example, Heward (1978) provided monetary reinforcement to professional baseball players contingent on successful at bats. At the end of each week, the three players with the highest efficiency average were given monetary reinforcement, resulting in efficiency averages increasing for most of the participants.
Auditory Feedback
One procedure that uses auditory feedback is referred to as Teaching with Acoustical Guidance (TAGteach; Quinn, Miltenberger, & Fogel, 2015). This procedure involves providing auditory feedback (e.g. a click from a clicker) when a subject correctly performs a step in a specific behavioral sequence. The auditory feedback has been shown to function as a form of reinforcement as it increases correct performance of multiple skills (Quinn, Miltenberger, James, & Abreu, 2016). Seven studies implemented an auditory feedback procedure. For example, Quinn et al. (2015) used TAGteach to enhance the performance of competitive dancers. Each time a student engaged in correct performance of a step in a dance move, the dance teacher provided auditory feedback with a click from a clicker.
Token Reinforcement
Token economies are generalized conditioned reinforcement systems in which tokens (e.g. stickers, poker chips, tally marks) are provided contingent on the demonstration of target behaviors. Over the past 50 years, token reinforcement systems have been utilized to increase myriad target behaviors including academic (Jenkins and Goraffa, 1974; Mattson and Pinkleman, 2020), social (Abrams et al. 1974; Sleiman et al. 2020), and adaptive skills (Atthowe, 1972). Token reinforcement has also been utilized in the context of sports performance. For example, a token reinforcement procedure was used by Reitman et al. (2001) and was shown to be more effective than medication at decreasing disruptive behavior and increasing attentive behavior for students playing kickball.
Chaining
Chaining is a method used to teach a complex behavior by breaking it into a number of steps and teaching the steps one at a time (through prompting, fading, and reinforcement) starting with the last step or with the first step and proceeding sequentially until the entire sequence of behaviors occurs together. For example, O’Brien and Simek (1983) used a backward chaining procedure with mastery criteria to improve shot accuracy of golfers. Once each golfer mastered the easiest and closest shot, shot difficulty and distance were increased until the golfers reached all mastery criteria.
Second and Third Wave Applications
Cognitive Behavioral Therapy (CBT) and Mindfulness and Acceptance approaches are both behavior-based therapies, but they differ primarily in the view they take around thoughts. Whereas CBT works by helping participants identify and change negative or destructive thoughts, mindfulness and acceptance approaches are founded on the belief that pain and discomfort are a necessary part of life. This therapeutic approach relies on the recognition of such thoughts while creating the space to act in service with one’s values (Hayes et al., 1999).
Cognitive-Behavioral Approaches
Second wave applications of behavioral strategies are exemplified by cognitive-behavioral approaches. Martin and Pear (2011) suggested that emotions have three important characteristics relevant to sports performance: 1) the internal autonomic reaction that an athlete experiences, which is influenced by respondent conditioning, 2) the way that one learns to express an emotion overtly (such as swearing and throwing things when angry), which is influenced by operant conditioning, 3) the way that one becomes aware of and tacts one’s emotions (e.g., “I’m a little excited,” as opposed to “I’m really nervous”), which is also influenced by operant conditioning. Intervention targets focus on teaching athletes strategies to decrease excessive nervousness or fear that negatively affects athletic performance.
Strategies that have been applied by behavioral sport psychologists to help athletes cope with excessive nervousness or fear include teaching athletes to recognize and change negative thinking that might cause the fear or nervousness, restructure the environment to “tune out” and prompt relaxing thoughts, practice a relaxing breathing technique called deep center breathing, practice progressive muscle relaxation by alternatively tensing and relaxing various muscle groups and paying close attention to how the muscles feel when they are relaxed, teaching athletes strategies to overcome excessive anger and aggression. Such studies commonly follow a four-step strategy including helping the athlete to identify anger-causing situations, teaching the athlete to perform substitute behaviors to compete with the anger, prompting the athlete to practice the substitute behaviors using imagery and/or simulations and/or role-playing, encouraging the athlete to use the coping skills in competitive situations and to receive feedback. A related area of research has examined the relationship between physiological arousal and athletic performance.
Using self-talk and/or imagery to maximize athletic performance is another area that has been utilized by behavioral sports psychologists. Applied behavior analysts consider private behavior to include saying things to oneself (i.e., self-talk) and imagining (e.g., visualizing a clear blue sky), and assume that behavioral principles and procedures apply to private as well public behavior. Regarding self-talk, research has indicated that athletes can use self-talk to improve performance in a variety of areas, including controlling their emotions and/or mood, stopping negative thoughts, improving their focusing or concentration skills, problem solving or planning, and improving skill acquisition and performance (Zinsser et al., 2006). Maximizing confidence and concentration for peak performance during competitions. Questionnaire studies with athletes have reported that the factor that most consistently distinguishes highly successful athletes from less successful ones is “confidence” (Weinberg & Gould, 2007; Zinsser et al., 2006). The ability to concentrate effectively has also been identified as a key ingredient of peak athletic performance (Nideffer & Sagal, 2006). A behavioral interpretation of the term concentration suggests that two behavioral processes are involved (Martin, 2011). First, concentration includes behavior commonly referred to as observational, orienting, attending, or focusing behavior that puts the individual in contact with important cues for further responding. For example, a batter in baseball who is “concentrating” is likely to focus on the pitcher, rather than attending to the first baseman. Second, following appropriate attending or focusing behavior, concentration refers to the extent to which particular cues exert effective stimulus control over skilled performance. Strategies to improve confidence, concentration, and peak performance include teaching athletes to orient to proper cues (Nideffer & Sagal, 2006), influencing athletes to perform well in simulations of competitive cues (Weinberg & Gould, 2007), using imagery to relive best performances (Orlick & Partington, 1988), encouraging athletes to focus on realistic goals for execution rather than worrying about outcome (Ward & Carnes, 2002), using facts and reasons to build a case against negative thinking (called countering; Bell, 1983), and encouraging athletes to prepare and follow specific competition plans (Rushall, 1979, 1992).
Mindfulness and Acceptance Approaches
Where cognitive-behavioral interventions attempt to deliberately change the content of thoughts and feelings, mindfulness and acceptance approaches help athletes sustain task-focused attention, in this case by training open, non-reactive, present moment awareness (Birrer et al., 2012). Mindfulness and acceptance interventions aim to promote a modified relationship with internal experiences (i.e. cognitions, emotions, and physiological sensations), rather than seeking to change their form or frequency (Gardner & Moore, 2012). They often emphasise the acceptance of internal processes as a typical part of the athletic experience, and focus on the present moment regardless of those internal processes (Baltzell et al., 2014; Birrer et al., 2012; Gardner & Moore, 2012). These interventions have largely drawn from psychotherapeutic approaches like mindfulness meditation (Kabat-Zinn et al., 1992), acceptance and commitment therapy (ACT; Hayes, Strosahl, & Wilson, 1999), and self-compassion interventions (Gilbert, 2009). Meta-analyses in the clinical domain have found these approaches to have a positive effect for various psychological conditions (e.g. depression, chronic pain, tinnitus; Brown, Glendenning, Hoon, & John, 2016; Khoury et al., 2013; Ost, 2014). More generally, meditative approaches have been shown to reduce anxiety, stress, and neurobiological markers such as cortisol, epinephrine, and norepinephrine (Chen et al., 2012; Chiesa & Serretti, 2010).
Authors have argued that application of mindfulness and commitment based approaches to sports performance, including focusing on the present moment with acceptance, facilitates the automatic execution of performance (Gardner & Moore, 2006, 2007, 2012). Birrer et al. (2012) suggested that athletes perform at their peak when executing skills with automaticity, and with open awareness to the context so they can make goal-directed adjustments. Some studies have found large effect sizes for mindfulness and acceptance interventions for promoting present-moment awareness and improving performance. While there are a number of studies showing positive effects for mindfulness and acceptance-based interventions for athletes, this systematic review indicates that the evidence is, at present, of low quality. A recent meta-analysis indicated that improvements in study design are critical to adequate evaluation of mindfulness and acceptance approaches on sports performance (Noetel et al., 2017).
Single Subject Design
Reliance on single-subject research design (SSD) provides a focus on individual athletic performance across several practices and/or competitions; acceptability by athletes and coaches because no control group is needed, few participants are needed, and sooner or later all participants receive the intervention, easy adaptability to assess a variety of interventions in practices and/or competitions; and effectiveness assessed through direct measures of sport-specific behaviors (e.g., jumps landed by figure skaters) or outcomes of behaviors. Single-case evaluation of behavioral coaching interventions are desirable because they (a) concentrate on the individual athlete, (b) include direct measurement of performance, (c) are intended to isolate the most effective procedures, and (d) can be implemented in a relatively brief period of time (Luiselli, 2011). Thus, the designs are compatible with best practices in applied sport psychology intervention and consultation (Martin, 2011). The following sections provide examples of the implementation of variations of SSD in BSP.
Multiple Baseline Design
The multiple baseline design (MBD) is defined as an experimental design that begins with the concurrent measurement of two or more behaviors in a baseline condition, followed by the application of the treatment variable to one of the behaviors while baseline conditions remain in effect for the other behavior(s). After maximum change has been noted in the first behavior, the treatment variable is applied in sequential fashion to each of the other behaviors in the design (Cooper et al., 2009). The MBD is the most commonly implemented SSD in BSP with a total of 53 articles published using the experimental framework (Schenk & Miltenberger, 2019). For example, Harding and colleagues (2004) conducted a MBD across behaviors with two adults (ages 33 and 40 years) participating in martial arts training. The intervention target was to improve their punching and kicking techniques during drill and sparring sessions. Differential reinforcement of technique execution was implemented first for punching, followed by kicking, and was effective with both adults. Stokes and colleagues (2010) designed a study that evaluated three behavioral coaching interventions within a MBD across individuals. The participants were five offensive linemen (ages 15–17 years) on a varsity high school football team. The offensive line coach recorded the percentage of steps the players executed correctly according to a 10-step, task analyzed blocking sequence. a) descriptive (nonverbal) feedback, (b) descriptive and verbal feedback, and (c) teaching with acoustical guidance. The results revealed that the players responded similarly to the intervention procedures, that in-game performance improved following intervention, and that the intervention procedures had to be reinstated to support performance during a second season.
Reversal Design
The reversal design is characterized by at lest three distinct phases: 1) baseline 2) treatment 3) baseline with preference for a fourth, return to treatment phase. The reversal design has been utilized to demonstrate the effects of multiple intervention components in sports performance. According to the review published by Schenk and Miltenberger (2019), a total of eight studies implemented reversal designs in BSP. For example, Smith and Ward (2006) evaluated several coaching procedures using an A-B-A-C-A-B+C design. The performance measures were the percentage of blocks, pass routes, and releases from the line of scrimmage, each wide receiver executed correctly during practices and games. In baseline (A), the coach reviewed expectations with the players, gave them verbal feedback, and corrected errors. The three intervention phases were public posting of performance (B), goal setting (C), and public posting of performance with goal setting (B+C). The three coaching interventions were equally effective with the players and better than baseline. Reversal designs are not appropriate when the behavioral target is the learning of a new skill, due to irreversibility effects. Since over 70% of BSP studies targeted the improvement of sport-specific skills, the applicability of reversal designs in BSP studies is limited.
Multielement Design
The multielement design or alternating treatment design is defined by the concurrent measurement of two or more behaviors in a baseline condition, followed by the application of the treatment variable to one of the behaviors while baseline conditions remain in effect for the other behavior(s). After maximum change has been noted in the first behavior, the treatment variable is applied in sequential fashion to each of the other behaviors in the design (Cooper et al., 2009). Osborne and colleagues (1990) studied curveball hitting proficiency of five college baseball players (ages not specified) under baseline and two intervention conditions in an ATD. Before intervention, the players practiced hitting against a pitching machine that was adjusted to simulate a curveball thrown at a standard speed. The interventions consisted of marking the seams of baseballs with either 1/4 inch or 1/8 inch orange stripes. Each of these marked-ball conditions was compared to the unmarked-baseball condition during two batting practice sessions each day. The ATD showed that curveball hitting proficiency improved with the marked-ball interventions.
Social Validity
Baer, Wolf, and Risley (1968; 91-92) defined the application of behavior analysis as “a self-examining, self-evaluating, discovery-oriented research procedure for studying behavior… constrained to examining those which are socially important.” But how do behavior analysts define social importance? Social importance must be defined by the context/community in which it occurs. Financial impact represents one way in which level of social importance may be objectively evaluated and quantified. According to the National Collegiate Athletic Association (NCAA; 2019), the total revenue generated by college athletic programs in 2018 was $10.8 billion. In an effort to gain or maintain competitive advantages in a landscape in which athletes cannot be financially compensated for participation, universities invest in lavish athletics facilities. The Washington Post (2015) reported that the 48 universities in the five largest athletic conferences spent a total of $772 million on athletic facilities in 2014. In 2018, Northwestern University opened a $270 million athletic complex. In addition to state-of-the-art football fields, basketball courts, and weight rooms, these facilities include saunas, movie theaters, barber shops, bowling alleys, and miniature golf courses. In addition to building modern palaces for athletes, universities spend top dollar on coaches for revenue generating sports. ESPN (2019) reported that the highest paid public employee was an NCAA football coach in 29 of 50 states and that no NCAA Division I basketball coach earned a salary of less than $1 million. The financial impact of collegiate athletics demonstrates its high social significance in the United States.
Social validity is defined as increasing participant access to reinforcers across three criteria; the 1) selection of goals that participants deem important, 2) procedures used to achieve these goals are acceptable to participants, and 3) results are satisfactory (Wolf, 1978). This definition was intended for behavior analysis as a broader discipline, but it is also explicitly stated as a primary characteristic of BSP. In a 30 year review of BSP, Martin and colleagues (2004) reported that 26 of 40 total studies utilized a social validity questionnaire as part of their study. Participants in these 26 studies provided overwhelmingly positive responses to the three criteria outlined above. A more recent review (Page & Thelwell, 2013) offered suggestions for BSP practitioners to improve collection of social significance data. Recommendations included the comparison of different types of questions within the BSP social validity process, methods used to assess social validity (e.g. interviews, surveys), and how to analyze the social validity data that is collected in BSP research.
Applications of Behavioral Sports Psychology
Applications of BSP include the development of user-friendly behavioral assessments targeting sports performance, teaching of sports-specific skills, decreasing persistent errors, and reducing problem behaviors in sports contexts (Martin, 2004). By applying the principles of behavior analysis to the areas outlined above, behavioral sports psychologists improve sports performance to a meaningful degree. Although physical fitness is defined by behavioral repertoires (e.g. exercise and nutrition) that impact sports performance, the purpose of this chapter is to review response classes that more directly fit the criteria of BSP. For a review of behavioral applications targeting exercise see Hayes and Van Camp (2012).
Assessment
The development of user-friendly behavioral assessment tools for athletes is essential for understanding appropriate performance targets. Behavioral assessment has been defined as the collection and analysis of information and data in order to identify and describe target behaviors, identify possible causes of the behavior, guide the selection of appropriate behavioral treatment, and evaluate treatment outcome (Martin & Pear, 2011). Behavioral assessment in BSP typically begins with a behavioral interview to help the athlete identify major problem areas, select one or two such areas for initial treatment, identify specific behavioral deficits or excesses within the targeted problem areas, attempt to identify controlling variables of the problem behavior, and identify some specific target behaviors for initial treatment (Tkachuk, Leslie-Toogood, & Martin, 2003). One method that has demonstrated clinical efficacy is the across-sport behavioral checklist. Examples include the Post-Competition Evaluation Form (Orlick, 1986), the Psychological Skills Inventory for Sport (Mahoney, Gabriel, & Perkins, 1987), and the Athletic Coping Skills Inventory-28 (Smith, Schutz, Smoll, & Ptacek, 1995). Another method of evaluation is the within-sport behavioral checklist. Such checklists contain behavioral descriptors and situational examples with terminology specific to a given sport. Martin, Toogood, and Tkachuk (1997) described within-sport behavioral checklists for 21 different sports. The within-sport checklists were positively reviewed and research on the checklists for basketball, swimming, running, volleyball, and figure skating has found them to demonstrate both external validity and test–retest reliability (Tkachuck et al, , 2003; Lines, Schwartzman, Tkachuk, Leslie-Toogood, & Martin, 1999; Martin & Toogood, 1997). However, there was little agreement between volleyball coaches and the athletes that they coached, and between track coaches and the athletes that they coached, concerning the mental-skills strengths and weaknesses of those athletes.
Teaching Sports Specific Skills
In a review of 30 years of research using single-subject designs in sport psychology, 72% of the studies focused on improving sport-specific skills of athletes in a variety of sports (Martin et al., 2004). Behavioral sports psychology interventions have been implemented to improve skills across 21 different sports including basketball (e.g. Kladopoulos & McComas, 2001), football (e.g. Allison & Ayllon, 1980), baseball (e.g. Osborne et al, 1990), soccer (Brobst & Ward, 2002), golf (e.g. Simek & O’Brien, 1981), swimming (e.g. Hazen, Johnstone, Martin, & Skrikameswaran, 1990), tennis (e.g. Buzas & Ayllon, 1981), figure skating (e.g. Ming & Martin, 1996), pole vaulting (e.g. Scott et al. 1997), speed skating (e.g. Anderson & Kirkpatrick, 2002), and more. Examples of sports that have received the most attention in BSP literature will be highlighted below.
Basketball
According to Schenk and Miltenberger (2019), a total of 11 interventions to improve football performance have been implemented in BSP. For example, a total of five interventions targeted free throw shooting performance using interventions such as relaxation training, self‐imagery, video modeling (Hall & Erffmeyer, 1983), relaxation techniques and self‐talk (Hamilton & Fremouw, 1985), relaxation techniques and self‐imagery (Kearns & Crossman, 1992), goal setting and self‐imagery (Lerner, Ostrow, Yura, & Etzel, 1996), and verbal feedback, instruction, and social positive reinforcement (Kladopoulos & McComas, 2001). Additional targets included improvements to shot form (Aiken, Fairbrother, and Post, 2012), field goal percentage (Templin & Vernacchia, 1995), and defensive performance (Kendall, Hrycaiko, Martin, & Kendall, 1990).
Football
According to Schenk and Miltenberger (2019), a total of 11 interventions to improve football performance have been implemented in BSP. For example, Smith and Ward (2006) evaluated the effects of several coaching procedures to increase the percentage of correct blocks and percentage of correct routes run by wide receivers on a collegiate football team. Offensive blocking was also improved in athletes participating in youth football (Allison & Ayllon, 1980). Improving positioning and tackling of linebackers in college football was a focus of a behaviorally-based intervention (Ward & Carnes, 2002). Additionally, Stokes, and colleagues (2010) designed a study that evaluated three behavioral coaching interventions within a MBD across individuals. The participants were five offensive linemen (ages 15–17 years) on a varsity high school football team. Using a 10-step, task analyzed blocking sequence plus an intervention composed of a) descriptive (nonverbal) feedback (DF), (b) descriptive and verbal feedback (DF+VF), and (c) teaching with acoustical guidance (TAG), players improved in-game performance. The team reinstated this teaching approach during the next season.
Golf
A total of 8 interventions have been implemented to target golf performance according to Schenck and Miltenberger (2019). Interventions have targeted essential characteristics of swing form using video and expert modeling as well as various forms and feedback (Bertram, Marteniuk, & Guadagnoli, 2007; Guadagnoli, Holcomb, & Davis, 2002). Interventions have also included chaining procedures to improve shot quality (Simek, O’Brien, & Figlerski, 1994) and to decrease the number of shots required to finish a round (O’Brien & Simek, 1981).
Swimming
A total of 11 articles have been published using BSP interventions to improve swimming performance (Schenck & Miltenberger, 2019). Interventions have targeted stroke technique using instruction plus physical prompting (Rogers, Hemmeter, & Wolery, 2010), video feedback (Dowrick & Dove, 1980), and expert modeling, physical prompting, punishment, verbal feedback, and social positive reinforcement (Koop & Martin, 1983). Additional targets have included increasing number of laps swam (Schonwetter, Miltenberger, & Oliver, 2014; Critchfield & Vargas, 1991; Rushall & Pettinger, 1969), increasing practice attendance (McKenzie & Rushall, 1974), and coaching strategies (Rushall & Smith, 1979).
Tennis and Table Tennis
A total of 15 articles hae been published in the BSP structure which improve tennis and table tennis skills (Schenck & Miltenberger, 2019). Intervention targets have included improving serve execution using instruction and video modeling (Bouchard & Singer, 1998), instruction, expert modeling, video modeling, and video feedback (Emmen, Wesseling, Bootsma, Whiting, & Van Wieringen, 1985), and instruction and video feedback (Rikli & Smith, 1980; Van Wieringen, Emmen, Bootsma, Hoogesteger, & Whiting, 1989). Additional targets have included improving service returns and/or volleys (Hebert & Landin, 1994; Todorov, Shadmehr, & Bizzi, 1997; Allison & Ayllon, 1980; Buzas & Ayllon, 1981; Scott et al., 1998; Haskins, 1965; Ziegler, 1987) and the strategic placement of forehands and backhands (Landin & Hebert, 1999).
Decreasing Persistent Errors in Sports Skills
Persistent errors in sport-specific skills negatively impact sports performance. For example, errors in shooting form likely cause shot accuracy to decrease in basketball skills. Improvement in form has demonstrated efficacy in improving accuracy (Aiken, Fairbrother, & Post, 2012). Martin (2004) proposed potential sources for errors in sport-specific skills. Errors made by beginning athletes might be due to imitation of other young athletes who are making the same errors, due to misidentification of appropriate antecedent cues, as a strategy to obtain attention from the coach, lack of reinforcement for correct performance, or adventitious reinforcement of an error in skill demonstration. Regarding the last point, when a skill results in early success for a young athlete, all of the components of that skill are strengthened, even if one of the components is flawed. For example, an instance of swinging a baseball bat and contacting the baseball may reinforce all components of this swing even if many of them are incorrect. Examples include reducing errors in swimming strokes (Koop & Martin, 1983), Play execution of the offensive backfield of a youth football team to reduce incorrect activity (Komaki & Barnett, 1977) reducing errors of gymnastic skills with young gymnasts (Allison & Ayllon, 1980), reducing errors in the execution of throw-ins and goal kicks in youth soccer (Rush & Ayllon, 1984), performance of volleyball skills by college players (Landin & Hebert, 1999).
Decreasing Problem Behaviors of Athletes in Sports Environments
Behavior analysts often work to reduce interfering behavior in individuals with whom they work. A variety of disruptive behaviors that occur within the sports setting are likely to interfere with athletic performance including excessive socializing during athletic drills, temper tantrums, and disruptive behaviors that occur while the coach is talking to the team. Behavioral sports psychologists may work with individuals to reduce behaviors that interfere with athletic performance and to promote more effective replacement skills. For example, Galvan and Ward (1998) used public posting to effectively reduce unsportsmanlike behavior during tennis matches by male and female collegiate tennis players. In their study they reported that coaches were concerned with inappropriate behaviors such as disrespectful physical gestures, swearing publicly, and throwing and striking objects during tennis matches (e.g., tennis balls and racquets). The intervention consisted of presenting the data to the tennis players individually on the frequency of inappropriate behaviors collected during baseline and establishing an expectation in the form of a goal that these behaviors would be reduced from game to game. The data from games were publicly posted in training sessions for all players to see. While the behaviors were not eliminated for any of the players, the overall reductions were from means of 14 per game in baseline to 2–4 occurrences per game during the intervention. Interventions that have focused on teaching appropriate alternatives have also demonstrated positive outcomes. For example, self-monitoring and charting was shown to increase desirable alternative practice behaviors and decrease interfering behaviors in freestyle figure skating participants (Hume et al., 1985). Using group music in a differential reinforcement for desirable alternative behaviors has also been effective in reducing interfering behaviors and increasing more productive behavior in swimming participants (Hume & Crossman, 1992).
Conclusion
Behavioral sport psychology (BSP) is defined by the use of behavior analytic principles and techniques to enhance the performance of athletes, coaches, and others associated with sports (Martin & Tkachuk, 2000). The purpose of this chapter was to provide a brief history of the subspecialty known as BSP, to identify the main components of BSP, and to provide an overview of applications of BSP across a variety of domains. Starting with the seminal works published in BSP in the early 1970’s (Rushall & Siedentop, 1972; McKenzie & Rushall, 1974) through 2018, a total of 101 articles have been published in BSP across 21 sports which utilize 23 different intervention strategies. BSP research has been implemented to develop user-friendly behavioral assessments targeting sports performance, teaching of sports-specific skills, decreasing persistent errors, and reducing problem behaviors in sports contexts (Martin, 2004). BSP research has been published in behavior analytic journals as well as mainstream sports science journal, with strategies gaining acceptance from applied scientists across fields. Although this research base provides impressive precision and scope, opportunities exist to incorporate behavior analytic techniques more thoroughly in sports sciences.
One example cited by researchers is the importance of incorporating social validity measures more consistently in BSP research as well as developing more sophisticated approaches to assessing it. Another area ripe for behavior analysis is within sports analytics. With continued technological advances, measurement of athlete behavior has become increasingly precise. Behavior analysts could embed themselves within sports analytics programs in order to help design effective measurement procedures, help to intervene when necessary, and to track progress over time. A third area of research that deserves more future attention is the use of contextual behavior science to improve sports performance. Strategies such as stimulus equivalence have demonstrated efficacy as efficient teaching approaches but have not been applied to sports behaviors. Mindfulness and acceptance based approaches have demonstrated promise as sports performance interventions but have not been adequately assessed. Future research should continue to analyze these approaches under tightly controlled experiments. Continued incorporation of behavior analytic principles to sports settings offers a bright future for the synthesis of BSP.
Reference
Abrams, L., Hines, D., Pollack, D., Ross, M., Stubbs, D. A., & Polyot, C. J. (1974). Transferable Tokens: Increasing Social Interaction in Token Economies. Psychological Reports, 35(1), 447–452. https://doi.org/10.2466/pr0.1974.35.1.447
Aiken, C. A., Fairbrother, J. T., & Post, P. G. (2012). The effects of self-controlled video feedback on the learning of the basketball set shot. Frontiers in Psychology, 3, 338.
Alferink, L. A., Critchfield, T. S., Hitt, J. L., & Higgins, W. J. (2009). Generality of the matching law as a descriptor of shot selection in basketball. Journal of Applied Behavior Analysis, 42(3), 595–608. https://doi.org/10.1901/jaba.2009.42-595
Allison, M. G., & Ayllon, T. (1980). Behavioral coaching in the development of skills in football, gymnastics, and tennis. Journal of Applied Behavior Analysis, 13(2), 297–314. https://doi.org/10.1901/jaba.1980.13-297
Anderson, G., & Kirkpatrick, M. A. (2002). Variable effects of a behavioral treatment package on the performance of inline roller speed skaters. Journal of Applied Behavior Analysis, 35(2), 195–198. https://doi.org/10.1901/jaba.2002.35-195
Atthowe, J. M. (1972). Controlling nocturnal enuresis in severely disabled and chronic patients. Behavior Therapy, 3(2), 232–239. https://doi.org/10.1016/S0005-7894(72)80083-2
Ayres, K. M., Maguire, A., & McClimon, D. (2009). Acquisition and Generalization of Chained Tasks Taught with Computer Based Video Instruction to Children with Autism. Education and Training in Developmental Disabilities, 44(4), 493–508. JSTOR.
Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97. https://doi.org/10.1901/jaba.1968.1-91
Baltzell, A., Caraballo, N., Chipman, K., & Hayden, L. (2014). A Qualitative Study of the Mindfulness Meditation Training for Sport: Division I Female Soccer Players’ Experience. Journal of Clinical Sport Psychology, 8(3), 221–244. https://doi.org/10.1123/jcsp.2014-0030
Baum, W. M. (1974). On two types of deviation from the matching law: Bias and undermatching. Journal of the Experimental Analysis of Behavior, 22(1), 231–242. https://doi.org/10.1901/jeab.1974.22-231
Bertram, C. P., Marteniuk, R. G., & Guadagnoli, M. A. (2007). On the Use and Misuse of Video Analysis. International Journal of Sports Science & Coaching, 2(1_suppl), 37–46. https://doi.org/10.1260/174795407789705406
Billington, E., & DiTommaso, N. M. (2003). Demonstrations and Applications of the Matching Law in Education. Journal of Behavioral Education, 12(2), 91–104. https://doi.org/10.1023/A:1023881502494
Birrer, D., Röthlin, P., & Morgan, G. (2012). Mindfulness to Enhance Athletic Performance: Theoretical Considerations and Possible Impact Mechanisms. Mindfulness, 3(3), 235–246. https://doi.org/10.1007/s12671-012-0109-2
Borrero, J. C., Crisolo, S. S., Tu, Q., Rieland, W. A., Ross, N. A., Francisco, M. T., & Yamamoto, K. Y. (2007). An Application of the Matching Law to Social Dynamics. Journal of Applied Behavior Analysis, 40(4), 589–601. https://doi.org/10.1901/jaba.2007.589-601
Boyer, E., Miltenberger, R. G., Batsche, C., & Fogel, V. (2009). Video moedling by experts with video feedback to enhance gymnastics skills. Journal of Applied Behavior Analysis, 42(4), 855–860. https://doi.org/10.1901/jaba.2009.42-855
Brobst, B., & Ward, P. (2002). Effects of public posting, goal setting, and oral feedback on the skills of female soccer players. Journal of Applied Behavior Analysis, 35(3), 247–257. https://doi.org/10.1901/jaba.2002.35-247
Brown, M., Glendenning, A. C., Hoon, A. E., & John, A. (2016). Effectiveness of web-delivered acceptance and commitment therapy in relation to mental health and well-being: a systematic review and meta-analysis. Journal of Medical Internet Research, 18(8), 221.
Bouchard, L. J., & Singer, R. N. (1998). Effects of the five-step strategy with videotape modeling on performance of the tennis serve. Perceptual and motor skills, 86(3), 739-746.
Bulow, P. J., & Meller, P. J. (1998). Predicting teenage girls’ sexual activity and contraception use: An application of Matching Law. Journal of Community Psychology, 26(6), 581–596. https://doi.org/10.1002/(SICI)1520-6629(199811)26:6<581::AID-JCOP5>3.0.CO;2-Y
Buzas, H. P., & Ayllon, T. (1981). Differential reinforcement in coaching tennis skills. Behavior Modification, 5(3), 372-385.
Carrion, T. J., Miltenberger, R. G., & Quinn, M. (2019). Using Auditory Feedback to Improve Dance Movements of Children with Disabilities. Journal of Developmental and Physical Disabilities, 31(2), 151–160. https://doi.org/10.1007/s10882-018-9630-0
Chen, K. W., Berger, C. C., Manheimer, E., Forde, D., Magidson, J., Dachman, L., & Lejuez, C. W. (2012). Meditative Therapies for Reducing Anxiety: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Depression and Anxiety, 29(7), 545–562. https://doi.org/10.1002/da.21964
Chiesa, A., & Serretti, A. (2010). A systematic review of neurobiological and clinical features of mindfulness meditations. Psychological Medicine, 40, 1239−1252
Cooper J.O, Heron T.E, Heward W.L. Applied behavior analysis (2nd ed.) Upper Saddle River, NJ: Pearson; 2007. [Google Scholar]
Critchfield, T. S., & Stilling, S. T. (20150601). A matching law analysis of risk tolerance and gain–loss framing in football play selection. Behavior Analysis: Research and Practice, 15(2), 112. https://doi.org/10.1037/bar0000011
Desiderato, O., & Miller, I. B. (1979). Improving tennis performance by cognitive behavior modification techniques. The Behavior Therapist, 2(4), 19–19.
Dowrick, P. W., & Dove, C. (1980). The use of self-modeling to improve the swimming performance of spina bifida children. Journal of Applied Behavior Analysis, 13(1), 51–56. https://doi.org/10.1901/jaba.1980.13-51
Emmen, H. H., Wesseling, L. G., Bootsma, R. J., Whiting, H. T. A., & van Wieringen, P. C. W. (1985). The effect of video‐modelling and video‐feedback on the learning of the tennis service by novices. Journal of Sports Sciences, 3(2), 127–138. https://doi.org/10.1080/0264041
Gardner, F. L., & Moore, Z. E. (2007). Using a case formulation approach in sport psychology consulting. The Sport Psychologist, 19, 430–445.
Gilbert, P. (2009). Introducing compassion-focused therapy. Advances in Psychiatric Treatment, 15(3), 199–208. https://doi.org/10.1192/apt.bp.107.005264
Gravel, R., Lemieux, G., & Ladouceur, R. (1980). Effectiveness of a cognitive behavioral treatment package for cross-country ski racers. Cognitive Therapy and Research, 4(1), 83–89. https://doi.org/10.1007/BF01173357
Guadagnoli, M., Holcomb, W., & Davis, M. (2002). The efficacy of video feedback for learning the golf swing. Journal of Sports Sciences, 20(8), 615–622. https://doi.org/10.1080/026404102320183176
Hall, E. G., & Erffmeyer, E. S. (1983). The effect of visuo-motor behavior rehearsal with videotaped modeling on free throw accuracy of intercollegiate female basketball players. Journal of Sport and Exercise Psychology, 5(3), 343-346.
Hamilton, S. A., & Fremouw, W. J. (1985). Cognitive-behavioral training for college basketball free-throw performance. Cognitive Therapy and Research, 9(4), 479–483. https://doi.org/10.1007/BF01173095
Harding, J. W., Wacker, D. P., Berg, W. K., Rick, G., & Lee, J. F. (2004). Promoting response variability and stimulus generalization in martial arts training. Journal of Applied Behavior Analysis, 37(2), 185–195. https://doi.org/10.1901/jaba.2004.37-185
Hayes, S. C., Brownstein, A. J., Zettle, R. D., Rosenfarb, I., & Korn, Z. (1986). Rule-governed behavior and sensitivity to changing consequences of responding. Journal of the Experimental Analysis of Behavior, 45(3), 237–256. https://doi.org/10.1901/jeab.1986.45-237
Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2003). Acceptance and Commitment Therapy: An Experiential Approach to Behavior Change (First Edition). The Guilford Press.
Hazen, A., Johnstone, C., Martin, G. L., & Srikameswaran, S. (1990). A Videotaping Feedback Package for Improving Skills of Youth Competitive Swimmers. The Sport Psychologist, 4(3), 213–227. https://doi.org/10.1123/tsp.4.3.213
Hebert, E. P., & Landin, D. (1994). Effects of a learning model and augmented feedback on tennis skill acquisition. Research quarterly for exercise and sport, 65(3), 250-257.
Herrnstein, R. J. (1961). Relative and absolute strength of response as a function of frequency of reinforcement,. Journal of the Experimental Analysis of Behavior, 4(3), 267–272. https://doi.org/10.1901/jeab.1961.4-267
Heward, W. L. (1978). Operant Conditioning of a .300 Hitter?: The effects of reinforcement on the offensive efficiency of a barnstorming baseball team. Behavior Modification, 2(1), 25–40. https://doi.org/10.1177/014544557821002
Hobson, W., & Rich, S. (2015, November 30). Why students foot the bill for college sports, and how some are fighting back. Washington Post. Retrieved from: https://www.washingtonpost.com/sports/why-students-foot-the-bill-for-college-sports-and-how-some-are-fighting-back/2015/11/30/7ca47476-8d3e-11e5-ae1f-af46b7df8483_story.html
Hume, K. M., & Crossman, J. (1992). Musical reinforcement of practice behaviors among competitive swimmers. Journal of Applied Behavior Analysis, 25(3), 665–670. https://doi.org/10.1901/jaba.1992.25-665
Hume, K. M., Martin, G. L., Gonzalez, P., Cracklen, C., & Genthon, S. (1985). A Self-Monitoring Feedback Package for Improving Freestyle Figure Skating Practice. Journal of Sport and Exercise Psychology, 7(4), 333–345. https://doi.org/10.1123/jsp.7.4.333
Jenkins, J. R., & Gorrafa, S. (1974). Academic performance of mentally handicapped children as a function of token economies and contingency contracts. Education and Training of the Mentally Retarded, 9(4), 183–186. JSTOR.
Kabat-Zinn, J., Massion, A. O., Kristeller, J., Peterson, L. G., Fletcher, K. E., Pbert, L., Lenderking, W. R., & Santorelli, S. F. (1992). Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders. The American Journal of Psychiatry, 149(7), 936–943. https://doi.org/10.1176/ajp.149.7.936
Kearns, D. W., & Crossman, J. (1992). Effects of a cognitive intervention package on the free-throw performance of varsity basketball players during practice and competition. Perceptual and motor skills, 75(3_suppl), 1243-1253.
Khoury, B., Lecomte, T., Fortin, G., Masse, M., Therien, P., Bouchard, V., Chapleau, M. A., Paquin, K., & Hofmann, S. G. (2013). Mindfulness-based therapy: A comprehensive meta-analysis. In Database of Abstracts of Reviews of Effects (DARE): Quality-assessed Reviews [Internet]. Centre for Reviews and Dissemination (UK). https://www.ncbi.nlm.nih.gov/books/NBK153338/
Kladopoulos, C. N., & McComas, J. J. (2001). The effects of form training on foul-shooting performance in members of a women’s college basketball team. Journal of Applied Behavior Analysis, 34(3), 329–332. https://doi.org/10.1901/jaba.2001.34-329
Komaki, J., & Barnett, F. T. (1977). A behavioral approach to coaching football: Improving the play execution of the offensive backfield on a youth football team. Journal of Applied Behavior Analysis, 10(4), 657–664. https://doi.org/10.1901/jaba.1977.10-657
Koop, S., & Martin, G. L. (1983). Evaluation of a coaching strategy to reduce swimming stroke errors with beginning age-group swimmers. Journal of Applied Behavior Analysis, 16(4), 447–460. https://doi.org/10.1901/jaba.1983.16-447
Landin, D., & Hebert, E. P. (1999). The influence of self-talk on the performance of skilled female tennis players. Journal of Applied Sport Psychology, 11(2), 263–282. https://doi.org/10.1080/10413209908404204
Lerner, B. S., Ostrow, A. C., Yura, M. T., & Etzel, E. F. (1996). The Effects of Goal-Setting and Imagery Training Programs on the Free-Throw Performance of Female Collegiate Basketball Players. The Sport Psychologist, 10(4), 382–397. https://doi.org/10.1123/tsp.10.4.382
Lines, J. B., Schwartzman, L., Tkachuk, G. A., Leslie-Toogood, S. A., & Martin, G. L. (1999). Behavioral assessment in sport psychology consulting: Applications to swimming and basketball. Journal of Sport Behavior, 22(4), 558.
Luiselli, J. K., & Reed, D. D. (2015). Applied behavior analysis and sports performance. In Clinical and organizational applications of applied behavior analysis (pp. 523–553). Elsevier Academic Press. https://doi.org/10.1016/B978-0-12-420249-8.00021-6
Luyben, P. D., Funk, D. M., Morgan, J. K., Clark, K. A., & Delulio, D. W. (1986). Team sports for the severely retarded: Training a side-of-the-foot soccer pass using a maximum-to-minimum prompt reduction strategy. Journal of Applied Behavior Analysis, 19(4), 431–436. https://doi.org/10.1901/jaba.1986.19-431
Mahoney, M. J., Gabriel, T. J., & Perkins, T. S. (1987). Psychological skills and exceptional athletic performance. The Sport Psychologist, 1(3), 181-199.
Martin G. and Hrycaiko D. (1983) Effective behavioral coaching: What’s it all about. Journal of Sport and Exercise Psychology 5, 8–20. [Google Scholar]
Martin, G. L., Thompson, K., & Regehr, K. (2004). Studies using single-subject designs in sport psychology: 30 years of research. The Behavior Analyst, 27(2), 263–280.
Martin, G. L., & Thomson, K. (2011). Overview of Behavioral Sport Psychology. In J. K. Luiselli & D. D. Reed (Eds.), Behavioral Sport Psychology: Evidence-Based Approaches to Performance Enhancement (pp. 3–21). Springer. https://doi.org/10.1007/978-1-4614-0070-7_1
Martin, G. L., & Tkachuk, G. A. (2000). Behavioral sport psychology. In Handbook of applied behavior analysis (pp. 399–422). Context Press/New Harbinger Publications.
Martin, G. L., & Toogood, A. (1997). Cognitive and behavioral components of a seasonal psychological skills training program for competitive figure skaters. Cognitive and Behavioral Practice, 4(2), 383–404. https://doi.org/10.1016/S1077-7229(97)80008-9
Mattson, S. L., & Pinkelman, S. E. (2019). Improving on-task behavior in middle school students with disabilities using activity schedules. Behavior Analysis in Practice, 13(1), 104–113. https://doi.org/10.1007/s40617-019-00373-2
McKenzie, T. L., & Rushall, B. S. (1974). Effects of self-recording on attendance and performance in a competitive swimming training environment. Journal of Applied Behavior Analysis, 7(2), 199–206. https://doi.org/10.1901/jaba.1974.7-199
Ming, S., & Martin, G. L. (1996). Single-subject evaluation of a self-talk package for improving figure skating performance. The Sport Psychologist, 10(3), 227–238. https://doi.org/10.1123/tsp.10.3.227
Noetel, M., Ciarrochi, J., Van Zanden, B., & Lonsdale, C. (2019). Mindfulness and acceptance approaches to sporting performance enhancement: A systematic review. International Review of Sport and Exercise Psychology, 12(1), 139–175. https://doi.org/10.1080/1750984X.2017.1387803
Orlick, T., & Partington, J. (1988). Mental Links to Excellence. The Sport Psychologist, 2(2), 105–130. https://doi.org/10.1123/tsp.2.2.105
Osborne, K., Rudrud, E., & Zezoney, F. (1990). Improved curveball hitting through the enhancement of visual cues. Journal of Applied Behavior Analysis, 23(3), 371–377. https://doi.org/10.1901/jaba.1990.23-371
Öst, L. G. (2014). The efficacy of Acceptance and Commitment Therapy: An updated systematic review and meta-analysis. Behaviour Research and Therapy, 61, 105–121. https://doi.org/10.1016/j.brat.2014.07.018
Page, J., & Thelwell, R. (2013). The Value of Social Validation in Single-Case Methods in Sport and Exercise Psychology. Journal of Applied Sport Psychology, 25(1), 61–71. https://doi.org/10.1080/10413200.2012.663859
Poling, A., Lotfizadeh, A., & Edwards, T. L. (2017). Predicting reinforcement: Utility of the motivating operations concept. The Behavior Analyst, 40(1), 49–56. https://doi.org/10.1007/s40614-017-0091-z
Quinn, M. J., Miltenberger, R. G., & Fogel, V. A. (2015). Using tagteach to improve the proficiency of dance movements. Journal of Applied Behavior Analysis, 48(1), 11–24. https://doi.org/10.1002/jaba.191
Quinn, M., Miltenberger, R., Abreu, A., & Narozanick, T. (2017). An Intervention Featuring Public Posting and Graphical Feedback to Enhance the Performance of Competitive Dancers. Behavior Analysis in Practice, 10(1), 1–11. https://doi.org/10.1007/s40617-016-0164-6
Ramnerö, J., & Törneke, N. (2015). On having a goal: Goals as representations of behavior. The Psychological Record, 65, 89–99. https://doi.org/10.1007/s40732-014-0093-0
Reitman, D., Hupp, S. D., O’Callaghan, P. M., Gulley, V., & Northup, J. (2001). The influence of a token economy and methylphenidate on attentive and disruptive behavior during sports with ADHD-diagnosed children. Behavior Modification, 25(2), 305-323.
Rikli, R., & Smith, G. (1980). Videotape feedback effects on tennis serving form. Perceptual and Motor Skills, 50(3, Pt 1), 895–901. https://doi.org/10.2466/pms.1980.50.3.895
Rush, D. B., & Ayllon, T. (1984). Peer behavioral coaching: Soccer. Journal of Sport and Exercise Psychology, 6(3), 325-334.
Rushall, B. S., & Smith, K. C. (1979). The modification of the quality and quantity of behavior categories in a swimming coach. Journal of Sport and Exercise Psychology, 1(2), 138–150. https://doi.org/10.1123/jsp.1.2.138
Rogers, L., Hemmeter, M. L., & Wolery, M. (2010). Using a constant time delay procedure to teach foundational swimming skills to children with autism. Topics in Early Childhood Special Education, 30(2), 102-111. https://doi.org/10.1177/0271121410369708
Rushall, B. S., & Siedentop, D. (1972). The Development and Control of Behavior in Sport and Physical Education. Lea & Febiger.
Schenk, M., & Miltenberger, R. (2019). A review of behavioral interventions to enhance sports performance. Behavioral Interventions, 34(2), 248–279. https://doi.org/10.1002/bin.1659
Schonwetter, S. W., Miltenberger, R., & Oliver, J. R. (2014). An evaluation of self-monitoring to improve swimming performance. Behavioral Interventions, 29(3), 213–224. https://doi.org/10.1002/bin.1387
Scott, D., Scott, L., & Goldwater, B. (1997). A performance improvement program for an international-level track and field athlete. Journal of Applied Behavior Analysis, 30(3), 573–575. https://doi.org/10.1901/jaba.1997.30-573
Simek, T. C., & O’Brien, R. M. (1981). Total Golf: A Behavioral Approach to Lowering Your Score and Getting More Out of Your Game (1st Edition). Doubleday.
Simek, T. C., O’Brien, R. M., & Figlerski, L. B. (1994). Contracting and Chaining to Improve the Performance of a College Golf Team: Improvement and Deterioration. Perceptual and Motor Skills, 78, 1099–1105. https://doi.org/10.2466/pms.1994.78.3c.1099
Skinner, B. F. (1945). The operational analysis of psychological terms. Psychological Review, 52(5), 270–277. https://doi.org/10.1037/h0062535
Sleiman, A. A., Betz, A. M., Rey, C. N., & Blackman, A. L. (2020). Effects of token manipulation on responding within a token economy implemented with children with autism. Education and Treatment of Children. https://doi.org/10.1007/s43494-020-00014-2
Smith, R. E., Schutz, R. W., Smoll, F. L., & Ptacek, J. T. (1995). Development and validation of a multidimensional measure of sport-specific psychological skills: The Athletic coping skills inventory-28. Journal of Sport and Exercise Psychology, 17(4), 379–398. https://doi.org/10.1123/jsep.17.4.379
Smith, R. E., Smoll, F. L., & Curtis, B. (1979). Coach effectiveness training: A cognitive-behavioral approach to enhancing relationship skills in youth sport coaches. Journal of Sport and Exercise Psychology, 1(1), 59-75.
Smith, S. L., & Ward, P. (2006). Behavioral interventions to improve performance in collegiate football. Journal of Applied Behavior Analysis, 39(3), 385–391. https://doi.org/10.1901/jaba.2006.5-06
Stilling, S. T., & Critchfield, T. S. (2010). The Matching relation and situation-specific bias modulation in professional football play selection. Journal of the Experimental Analysis of Behavior, 93(3), 435–454. https://doi.org/10.1901/jeab.2010.93-435
Stokes, J. V., Luiselli, J. K., Reed, D. D., & Fleming, R. K. (2010). Behavioral coaching to improve offensive line pass-blocking skills of high school football athletes. Journal of Applied Behavior Analysis, 43(3), 463–472. https://doi.org/10.1901/jaba.2010.43-463
Templin, D. P., & Vernacchia, R. A. (1995). The effect of highlight music videotapes upon the game performance of intercollegiate basketball players. The Sport Psychologist, 9(1), 41–50. https://doi.org/10.1123/tsp.9.1.41
Tkachuk, G., Leslie-Toogood, A., & Martin, G. L. (2003). Behavioral assessment in sport psychology. The Sport Psychologist, 17(1), 104–117. https://doi.org/10.1123/tsp.17.1.104
Todorov, E., Shadmehr, R., & Bizzi, E. (1997). Augmented feedback presented in a virtual environment accelerates learning of a difficult motor task. Journal of Motor Behavior, 29(2), 147–158. https://doi.org/10.1080/00222899709600829
Van Camp, C. M., & Hayes, L. B. (2012b). Assessing and increasing physical activity. Journal of Applied Behavior Analysis, 45(4), 871–875. https://doi.org/10.1901/jaba.2012.45-871
Van Wieringen, P. C. W., Emmen, H. H., Bootsma, R. J., Hoogesteger, M., & Whiting, H. T. A. (1989). The effect of video‐feedback on the learning of the tennis service by intermediate players. Journal of Sports Sciences, 7(2), 153-162.
Vollmer, T. R., & Bourret, J. (2000). An application of the matching law to evaluate the allocation of two- and three-point shots by college basketball players. Journal of Applied Behavior Analysis, 33(2), 137–150. https://doi.org/10.1901/jaba.2000.33-137
Ward, P., & Carnes, M. (2002). Effects of posting self-set goals on collegiate football players’ skill execution during practice and games. Journal of Applied Behavior Analysis, 35(1), 1–12. https://doi.org/10.1901/jaba.2002.35-1
Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review, 20(2), 158–177. https://doi.org/10.1037/h0074428
Weinberg, R., & Gould, D. (1999). Foundations of sport and exercise psychology (No. Ed. 2). Human Kinetics Publishers (UK) Ltd.
Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis, 11(2), 203–214. https://doi.org/10.1901/jaba.1978.11-203