Examining Differential Coaching Behaviors in Positive Coaches: a Mixed-Methods Perspective Guided by the Expectation Performance Process Megan Buning

Examining Differential Coaching Behaviors in Positive Coaches: A Mixed-Methods Perspective Guided by the Expectation Performance Process Megan Buning

Augusta University

The purpose of this concurrent triangulation mixed-methods study was to examine differences in perceptions of coach behaviors of athletes of varying performance abilities situated within a self-fulfilling prophecy. The mixed-methods approach allowed for a more holistic examination of softball athletes’ perspectives of head coaching behaviors. Division I softball athletes (n = 148) completed the CBAS-PBS providing perceptions of head coach (n =20) behavior. Coaches rated each athlete using the MERS providing a performance expectation score. Thirty-eight athletes provided supporting perspectives through individual interviews on perceptions of differential treatment based on expected performance level. Cluster analysis produced low, average, and high expectancy groups. MANOVA and DFA revealed two underlying functions that distinguished between groups. High expectancy athletes experienced less ‘detached’ coaching behaviors than low or average athletes. Qualitatively, athletes provided examples that support quantitative results that teammates perceive lower rated athletes are treated differently.

Key Words: self-fulfilling prophecy, female athletes, differential treatment

elf-fulfilling prophecies (SFP) are 2009). However, much of what we know evident in all types of environ- about SFP’s are created under experi- Sments from the classroom, work- mental conditions. Prophecies can have force, military, medical field, and the positive outcomes by enhancing receiver sports arena (Davidson & Eden, 2000; performance but can also have negative Inamori & Analoui, 2010; McNatt, 2000; outcomes resulting in weakened receiver Rowe & O’Brien, 2002; Wilkinson, performance (Davidson & Eden, 2000;

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 29 Rowe & O’Brien, 2002). Horn, Lox, and lationship (Jowett & Cramer, 2010) re- Labrador (1998) introduced the expecta- sulting in missed opportunities to make tion-performance process (EPP) detailing coaches aware of their behavior, influ- a SFP within sports. Years of personal ences, and prophecies. Situated within experience have exposed the reality of the context of a SFP, the purpose of this the EPP. However, both experience and study was to examine if collegiate soft- literature have revealed positive athlete ball athletes with a quantifiable coach-as- outcomes facilitated by educated coaches signed performance expectation score that either facilitate or terminate a SFP perceived various coaching behaviors within teams. Exceptional coaches learn differently. The mixed-methods approach how to approach athletes as individuals in of this study will enhance the literature terms of motivation and feedback, have about coach expectations and provide flexible expectations, and consistently additional understanding about the expec- communicate both individual and team tation performance process. Additionally, expectations despite performance expec- the goal is to provide further insight into tations (Becker & Wrisberg, 2008; Bloom, a how female softball athletes perceive Crumpton, & Anderson, 1999; Kahan, coaching behaviors in an effort to provide 1999). information to enhance coach training Coaches do form expectations about and education. athletes’ performance ability based on different types of cues (Solomon, 2008a; The Prophecies 2010), and do change behaviors based on The SFP was unintentionally discov- these expectations (Amorose & Wiess, ered in early experimental laboratory 1998; Horn et al., 1998; Solomon, DiMar- research (Clark, 1927; Merton, 1948; co, Ohlson, & Reece, 1998a; Solomon Rice, 1929), and has been used to explain & Rhea, 2008). If perceived negatively, a wide variety of social problems rang- behaviors can be harmful to the athlete’s ing from high-achiever performance to performance, continued enjoyment, managers’ influence on employee perfor- persistence, and overall motivation level mance to teachers’ impact on students to continuing playing (Amorose, 2003; (Gladwell, 2008; Jussim & Harber, 2005; Horn, Lox, & Labrador, 2006; Lyle, 1999; Jussim, Palumbo, Chatman, Madon, & Smith, Ntoumanis, & Duda, 2010). It is Smith, 2000; Nantanovich & Eden, 2008). startling that many coaches are unaware Popular definition of an SFP contends or unrealistic about the behavior they the cycle starts with an inaccurate or display toward their athletes (Smith et al., strong belief about a person or situa- 2010; Smith & Smoll, 2002). The focus tion, followed by actions that reflects the around coaching behavior has shifted belief, and results in the receiver chang- from the influence of behaviors to the ing behavior to reflect the belief (Mer- elements of a healthy coach-athlete re- ton, 1948; Salomon, 1981). An example

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 30 within the sport environment could be the coach’s camp, the coach treats the a coach expecting an athlete to be a top athlete indifferently (e.g., does not pay performer based on a skills video posted much attention to the athlete, does not online. In reality, the athlete may be an give the athlete challenging tasks) be- average-level athlete. When the athlete at- cause the coach formed an expectation tends the coach’s camp, the coach treats about the athlete’s performance based on the athlete as if he or she is the most the previously viewed skills video. The highly skilled athlete at the camp (e.g., athlete does not see the point in exert- gives the athlete the most challenging ing more effort and maintains the same tasks, uses the athlete as a demonstrator amount of effort during the camp result- for skill performance). As a result, the ing in average to below average perfor- athlete changes his or her approach to mance during the camp. Salomon (1981) drills during camp (e.g., gives more ef- details the existing behavior is what the fort, increases concentration) and emerg- person observed in the initial observa- es as the “best” athlete at camp. tion even if the behavior is not typical A self-sustaining prophecy works behavior. Researchers argue self-sus- slightly differently than a SFP. Self-sustaining prophecies occur more often taining prophecies begin similarly but and realistically than SFP’s in the natural progress differently. For a self-sustaining environment (Eden, 1990, 2016; Rowe & prophecy, once the person responds to O’Brein, 2002; Rudman & Glick, 2008; the receiver based off the initial expec- Salomon, 1981). tation, the person’s behavior then rein- Positive prophecies occur if the belief forces receiver behavior and causes the about the receiver is desirable resulting receiver to maintain, rather than alter, in a positive outcome, but prophecies existing behavior. Self-sustaining proph- tend to have a negative connotation. The ecies are much harder to detect because prophecy became of particular interest there is not a striking change in behav- with the submission of Rosenthal and ior. Using a similar example as above, a Jacobson’s (1968) landmark experimental coach finds a skill video posted online study of a SFP in the classroom (i.e., the of the athlete that is registered to attend Pygmalion effect) where they demonstrated an upcoming camp. The video shows the a SFP through positive student outcomes athlete performing skills on a day when connected to deception-induced higher the athlete was later diagnosed with the teacher expectations. However, this study flu resulting in average to below aver- also revealed what could have been con- age performance captured on the video. sidered a negative prophecy, the Golem However, when healthy, the athlete has effect. The Golem effect is characterized a reputation for being one of the most by low performance expectations from highly skilled athletes in the area. Later, the leader resulting in poor performance when the athlete (now healthy) attends from the receiver. Studies on the Golem

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 31 effect are scarce because of the nega- & Shani, 1982; McNatt, 2000) showing tive outcomes produced; however, Eden the same type of effect. The literature is (1990) presents the argument that natu- unclear as to how much of the effect is a rally occurring Golem effects occur more result of a self-fulfilling versus a self-sus- often than naturally occurring Pygmalion taining prophecy. Prophecies have the effects. Despite evidence of the SFP, power to increase the chance of a result many critics argued these types of exper- that would otherwise be a low-chance iments were unethical, controversial, did outcome stemming from the initial belief not show a large effect, and contained (Wilkinson, 2009). methodological flaws (Eden, 2002; Jus- Within athletics, no research was sim & Harber, 2005; White & Locke, found examining self-sustaining proph- 2000). A few researchers have attempted ecies in sports, and limited current re- to use a SFP to shape positive outcomes search was found on the SFP specifically (Chadha & Narula, 2016; Reynolds, (Siekanska, Blecharz, & Wojtowicz, 2013; 2007), but most of the Pygmalion re- Horn, Lox, & Labrador, 1998; Solomon, search and training has been implement- Golden, Ciapponi, & Martin, 1998b; ed in the management setting with leader Weaver, Moses, & Snyder, 2016). Sport behavior (Eden, 2002, 2016; Eden et al., researchers have pulled knowledge about 2000; Tierney & Farmer, 2004). Different prophecies primarily from early litera- effects are recognized to occur in sports ture pertaining to teacher expectations (Hancock, Adler, & Côté, 2013; Horn, (McNatt, 2000; Rowe & O’Brien, 2002; Lox, & Labrador, 2006), however, no Reynolds, 2007) and the management literature was found to show intention- field (Davidson & Eden, 2000; Eden, al training for sport coaches. McNatt’s 1990; Inamori & Analoui, 2010). Horn et (2000) review of the Pygmalion effect al.’s (1998) expectation performance pro- across a variety of settings indicates the cess is the most commonly used process effect can be strong and should be taken within athletics used to illustrate a SFP. into consideration for those in leadership positions. Expectation-performance process Research on SFP’s has continued with (EPP) teachers and students (Jussim & Harbor, One version of an SFP that has been 2005; Rist, 2000; Reynolds, 2007; Smith, adapted to fit sports to educate coaches Jussim, & Eccles, 1999), medical profes- on how they can affect an athlete’s de- sionals and patient outcomes (Christakis, velopment is the four-step cycle called 1999; Meyer et al., 2002; Wilkinson, the expectation-performance process 2009), managers and employees (David- (EPP, Horn et al., 1998). Step one, the son & Eden, 2000; Eden, 2002; McNatt, coach uses impression cues to develop 2000; Natanovich & Eden, 2008), and an expectation (accurate or inaccurate) military instructors and trainees (Eden for an athlete’s predicted athletic perfor-

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 32 mance and behavior (Horn et al., 2006; and amount of instruction is consistently Solomon, 2010). Flexible expectations do unequal. Although youth sport studies not create adversity (Becker & Wrisberg, have returned inconsistent results (Am- 2008; Wilson & Stephens, 2005), but orose & Weiss, 1998; Horn, 1984; Solo- inflexible, inaccurate expectations cause mon, 2008b; Solomon et al., 1998b), high issues (Horn et al., 1998). The coach may expectancy athletes have been observed not see the actual performance ability of receiving overall more and higher quali- the athlete, and the incorrect expectation ty feedback then their lower expectancy can alter the way the coach responds or counterparts in elite athletics (Sinclair & reacts to that particular athlete. If this Vealy, 1989), high school athletics (Solo- occurs, then coach and the athlete move mon et al., 1998b, 2008a), and in college into the second step of the cycle. athletics (Buning, 2016; Solomon, 2008a; Step two is the most researched step Solomon & Kosmitzki, 1996). Consistent in the EPP (Solomon, 2010). Step two of differential treatment that alters athletes’ the EPP outlines that a coach who differ- behaviors in ways that limit athletes’ entiates behavior changes the frequency abilities or opportunities to learn lead to and quality of interactions with the ath- damaged coach-athlete communication lete (Horn et al., 1998). Coaches develop and to the third step in the EPP cycle expectations about athletes’ potential (Horn et al., 1998). performance ability, and they group ath- Step three involves the coach’s ex- letes intentionally or subconsciously into pectancy-based treatment of the athlete high ability or low expectation groups. affecting the athlete’s performance and Athletes perceived to be low expectancy psychological growth. If a coach is con- athletes may receive less interpersonal sistently giving high expectancy athletes contact social or skill-related than high more and high-quality interactions (e.g., expectancy athletes, and high expectancy more time, feedback, instruction, and athletes may receive more interpersonal practice), then they should be able to contact and more approachable behav- capitalize on their situation toward the iors (for example smiling, personal con- advancement of their athletic perfor- tact). An even more hazardous behavior mance. Conversely, if low expectancy change could occur if the coach spends athletes repeatedly receive less, and poor- less time or provides poorer quality of er quality interactions, then they may not skill information or instruction to the show the same amount of skill improve- low expectancy athletes. The coach may ment as high expectancy athletes (Horn even reduce the amount of time low ex- et al., 1998). In this situation the coach pectancy athletes are allowed to practice attributes the skill differences between drills, and the coach may be less per- the two types of expectancy athletes as sistent in helping these athletes succeed natural, inherent differences rather than past a drill. As a result, practice quality differences brought about from differen-

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 33 tial treatment. The observable disparity or she is an accurate judge of talent and in the coach’s behavior toward the two may intensify the self-fulfilling prophecy types of athletes indicates the coach’s within the team. original expectations about the athletes’ The expectancy effect within athletics performance ability may not only predict is documented, but according to Horn but determine the level of success the and colleagues (2006), not all coaches or athletes’ will achieve (i.e., self-fulfilling athletes are susceptible to expectation prophecy). formation affects. A secondary issue is A coach’s biased feedback behavior the growing discourse between male and can create negative outcomes in skill de- female coaches crossing coaching gen- velopment, rate of learning, and achieve- der lines (e.g., males coaching females). ment level within expectancy groups, Male and female athletes have unique but differential behavior can have more characteristics across a variety of con- meaningful negative effects on psycho- structs (e.g., motivation to play (Duda, logical growth (Horn et al., 1998). Re- 1989), perceptions of athletic compe- search on differential coaching behavior tence (Hollembeak & Amorose, 2005), and the impact on athletes’ psycholog- and preference for coaching behaviors ical maturation have revealed causes or (Fasting & Pfister, 2000; Martin, Rocca, changes in athletes’ self-concept (Smith Cayanus, & Weber, 2009). Specific types & Smoll, 1990, 2002; Smith, Smoll, & of coaching behaviors needed to foster Barnett, 1995), perceived competence an environment for intrinsic growth for (Amorose & Horn, 2001; Black & Weiss, males and females should be considered 1992; Horn, 1987), and level of compet- independently. Female sports participa- itive trait anxiety (Kenow & Williams, tion is growing rapidly despite dropout 1992; Williams, Jerome, Kenow, Rogers, rates (Ohio University, 2017; Olympic & Sartain, 2003) through the course of Movement, 2014); however, the increase a season. As athletes receive information in female athletes does not translate to about their competence or ability via an increase in female coaches or the coaching feedback, the cycle progresses research examining same or different to the fourth step. The final stage in the gender coaches. EPP completes the self-fulfilling proph- Interest in college softball is on the ecy. The last step involves the athlete rise in the United States. The National changing behavior and performances to Collegiate Athletic Association (NCAA, conform to the coach’s original expecta- 2017) reports just within Division I tion. Once the athlete’s behavior changes, universities, institutions have added 42 the athlete confirms to the coach that teams and 1,448 softball athletes over the original expectations were accurate. The past 17 years. Over the course of four coach may develop a false sense of judg- years, ESPN has moved from covering ing ability and begin to believe that he 80 collegiate games (Volner, 2014) to

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 34 over 600 games (Balf, 2017). Addition- et al., 1998a, 1998b; Solomon, 2008a, ally, since 2015, the Women’s College 2008b; Weaver et al., 2016 ) with some World Series (WCWS) average viewership qualitative perspectives (Siekanska et al., across the final three-game champion- 2013; Solomon & Rhea, 2008), but only ship has increased by 535,000 viewers. capture one side of the problem. Con- For the first time since the WCWS first sidering these variables, the purpose of broadcast, the WCWS final series drew this study was to offer a mixed-methods an average of 440,000 more viewers than study to shed more light on how coach- the men’s baseball College World Series ing behaviors are perceived by softball (CWS) in the spring 2017 across major athletes with coach-assigned playing sport media outlets (Pucci, 2017; Vol- expectations This study focused on step ner, 2017). However, more than 31% of two of the EPP and offers a more holis- female collegiate teams are coached by tic examination from Division I female male coaches with close to 50% of Divi- softball athletes. The goal is to provide sion I softball coaches being male (The insight that could assist others in devel- Tucker Center for Research on Girls & oping training for coaches in awareness Women in Sport, 2014). Considering this and methods to harness the SFP. imbalance, it is important to examine how female athletes perceive coaching Methods behaviors and treatment. The sport of This mixed-methods study followed softball has a long history (Athnet, 2014), a concurrent triangulation design involv- consists of large numbers of female ing survey and interview data. This study athletes per team, is rapidly growing in aimed to answer the research question: popularity (Flynn, 1995), yet has not How do athletes with varying levels of been isolated for research. These ath- performance abilities differ in perception letes’ perspectives could provide insight of coaching behavior? Guided by EPP, it of this generation of athletes for coaches was hypothesized athletes rated as high of female athletes starting with the Divi- expectancy athletes would perceive more sion I level. SFP’s are understudied in the positive coaching behaviors than athletes athletic setting; yet, researchers in other rated lower. The intention of this study fields understand the need for training was to contribute to the existing litera- and using an SFP to produce positive ture on coaching behaviors, and to pro- results (Chadha & Narula, 2016; Eden, vide transferable results to participants in 2002, 2016; Eden et al., 2000; Reynolds, the target population. A mixed-methods 2007; Tierney & Farmer, 2004). Addi- design was employed to gather a holis- tionally, studies around the SFP in ath- tic perspective of participants’ views letics are mostly quantitative (Amorose on coaching behavior and treatment. & Weiss, 1998; Buning, 2016; Sinclair & Qualitative findings enhanced qualitative Vealy, 1989; Solomon, 2010; Solomon reports by providing context and further

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 35 insight through specific, real-life exam- years old and 25 to 34 years. Both male ples. and female coaches varied on lifetime collegiate coaching experience, yet the Participants majority had coached at their current Random cluster sampling was used to institution for less than 10 years. Coach select 20 Division I softball coaches and demographics are displayed in Table 2. teams from the population (N = 292) re- Athletes. For the quantitative analy- sulting in a sample that included teams (n sis, the majority of female softball ath- = 20) representing 15 of the 31 Division letes (n = 148) identified as White n( = I conferences recognized by the NCAA 144) followed by Latina (n = 20), Oth- in 2012 (Table 1). Teams were selected er (n = 6), and Black (n = 4). Athletes from a public website listing all NCAA ranged in age from 18 to 22 years old (M sanctioned Division 1 teams. = 19.43, SD = 1.17). Most athletes re- Coaches. Coaches (n = 20) ranged ported between 10 to14 years of lifetime between 25 to over 60 years old, but the softball playing experience (n = 147). The majority of coaches ranged between 35 majority (n = 141) had played for their to 44 years old followed by 50 to over 60 current head coach for 12 months or less

Table 1

Division I Softball Athletic Conference Representation Conference Name Number of Participant Institutions Atlantic 10 1 Atlantic Coast 1 Big East 2 Big Ten 1 Colonial Athletic 3 Conference USA 1 Horizon League 1 Mid-American Metro Atlantic 1 Missouri Valley 1 Northeast 1 Ohio Valley 2 Sunbelt 2 Southeastern 1 Southern 1 Patriot League 1 Note: Conferences presented for the year 2012-2013.

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 36 Table 2

Coach Participant Demographics n = 20 Frequency Race White 19 Other 1 Gender Male 6 Female 14 Age Range 25-29 1 30-34 3 35-39 8 40-44 2 50-54 4 55-59 1 60+ 1 Total Coaching Experience (years) 5-9 1 10-14 6 15-19 6 20+ 7 Total Coaching at Institution (years) Years >1 4 1-4 5 5-9 6 10-14 1 15-19 3 20+ 1

(Mmonths = 10.10, SD = 8.93) with others predominantly White (n = 33) with aver- having played 24 months (n = 24) and age age of 19.79 years (SD = 1.23), and 36 months (n = 9). The response rate for on average had played under the head athletes was 36%. coach for 10.74 months (SD = 10.23). Of these athletes, 38 responded to Interview athletes represented 18 of interview questions. Interviewees were the 20 teams selected for the study, and

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 37 11 of the 18 teams had more than one Solomon, 2008a). Solomon (2008a) athlete responding about the head coach. developed the MERS by modifying the Table 3 provides more information about Expectancy Rating Scale (ERS; Solo- interview athletes. mon, 1993) and the Solomon Expec- tancy Sources Scale (SESS; Solomon, Instruments 2008a). Instrument structure was tested Coach expectations. Coach expec- in Becker and Wrisberg (2008). For this tations were recorded through the Mod- study, Cronbach’s alpha was acceptable ified Expectancy Rating Scale (MERS; (α = .90). The MERS provided coaches

Table 3

Interview Athletes’ Demographics, Team Membership and Coach-assigned Expectancy Group Athlete Team Age Race Months Coach Assigned Self-Assigned (n = 38) Under Coach Exp Group Exp Group Tiffany 1 18 C 4 Average Average Elena* 1 21 L 4 High Average Hannah* 1 20 C 4 High High Bethany 1 18 C 4 Low Average Tara 1 20 C 4 Average Average Kayla 2 20 C 24 High High Melissa 3 18 C 4 Average Average Rosemary 4 21 C 24 High Average Jaclyn 4 20 C 24 High Average Teresa 4 21 C 36 High High Nesa 4 22 L 4 High High Tory 4 18 C 4 Average Average Brooke 5 20 C 24 High High Chloe 5 21 C 24 Average High Jackie 6 18 C 4 Average Average Jamie 7 18 C 4 Average Average Angela 8 20 C 4 Low Average Shawna 8 19 C 12 Low High Allison 9 20 C 36 Low High Jill 9 20 C 24 Low High Alicia 10 21 C 24 High High Peyton 10 21 C 12 Low Low Jessica 11 19 C 24 Low Low

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 38 Table 3 Continued

Melinda 12 22 C 12 High High Sadie 12 21 C 12 High High Sara 13 20 C 12 High High Christy 13 18 C 4 Average High Ashley* 14 20 C 4 Low Average Jane* 15 20 C 4 High High Brecken* 15 19 L 4 High High Alyssa* 15 21 C 4 Average Average Rylie* 15 20 C 4 High High Nicole* 15 19 C 4 Average High Kellie 16 18 C 4 High High Tracey 17 20 B 4 High High Ginny 17 21 L 12 Average High Sally 18 18 C 4 Low High Colleen 19 21 C 36 Low High Note: Athletes playing for new coaches are denoted by (*). Athlete race represented by Black (B). Caucasian (C), and Latina (L). All names are pseudonyms. with eight items assessing physical and score was calculated for each athlete by psychological attributes for each ath- first obtaining an average score for the lete. Coaches were asked to assess each initial eight MERS responses followed by athlete’s performance ability compared obtaining an average score for the final to similarly skilled athletes. An example eight responses, and finally by averag- question was “This athlete possesses ing the averaged initial and final MERS sound softball fundamentals.” Coaches scores to obtain the grand average. were asked to respond to the degree of Perceptions of coach behavior. truth for each statement using a 5-point Athletes completed the Coaching Be- Likert-type scale ranging from 1 =Not havior Assessment System Perceived True to 5 = Very True. Head coaches Behavior Scale (CBAS-PBS; Cumming, completed an electronic version of the Smith, & Smoll, 2006). The CBAS-PBS is MERS for each athlete on the roster a modified form of the Coaching Behav- prior to the fall practice season (initial) ior Assessment System (CBAS; Smith, and again after the fall practice season Smoll, & Curtis, 1979). The CBAS is a (final) allowing for three months between coach-report measure assessing coach assessments. A grand average expectation behaviors. The CBAS-PBS is a 12-item

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 39 measure to capture athletes’ perceptions behaviors toward athletes of different of their coach’s positive and negative performance expectation levels. The goal behaviors. The CBAS-PBS provides a of the interview was to capture a deeper definition and example in a description understanding of how participants per- of the original 12 behavioral categories ceived coach treatment. To contextualize from the CBAS from the athletes’ per- responses, one question did ask partici- spective. Athletes indicated how often pants to self-evaluate their performance the head coach behaved as described capability based on other members of using a 7-point Likert-type scale ranging the team by responding to the question, from 1 (Never) to 7 (Almost Always). The “Compared to your teammates, describe CBAS-PBS has not been used as fre- your softball playing abilities.” Three quently as the CBAS, but studies report experts in the field of sport psychology acceptable reliability (ICC = .83) (e.g., reviewed each interview questions to en- Lemonidis et al., 2014). The researcher hance content validity. Each expert had split the CBAS into positive behaviors a terminal degree in the field and held (n = 8) and negative behaviors (n = 4) extensive research agendas practicing based on behavioral categories. Posi- both qualitative and quantitative method- tive behaviors were identified as reward, ologies. Pilot interviews were conducted encouragement after mistakes, corrective using three female collegiate athletes instruction, keeping control, giving in- from non-participating institutions and structions, encouragement, organization, necessary clarifications to questions were and general communication. Negative made as needed. behaviors were identified as non-reward, punishment, corrective instruction with Procedures punishment, and ignoring mistakes. A Random cluster sampling was used grand average CBAS-PBS score was to select teams from the Division I soft- obtained similarly to the MERS calcula- ball population. During the fall practice tions. Internal consistency was acceptable season (August 2012), coaches were then for positive behaviors (Cronbach’s α = emailed an information sheet containing .78) and negative behaviors (α = .74). a link to an electronic survey requesting Interview protocol. Interviews con- demographic information and contained sisted of 12 semi-structured, open-ended an electronic version of the MERS. questions to add depth to the quantita- Coaches were emailed a second email tive data. The first question was a grand containing study information and a link tour question used to build rapport to the CBAS survey to forward to all ath- (Kvale & Brinkmann, 2009), and remain- letes on his or her. Athletes were asked to ing questions were designed by the re- provide a university issued-email address searcher to directly and indirectly assess for data-matching purposes. All partici- the athletes’ views of their head coaches’ pants were required to provide electronic

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 40 consent on the first page of initial survey. ing convergent and divergent codes then After the fall practice season (December responses were grouped according to 2012), coaches were emailed a second the question asked. Finally, over-arching link to the final MERS survey while major and minor themes were created. athletes were emailed directly a final Two external coders assisted to confirm CBAS-PBS survey. Athletes were asked validity of codes to themes. After themes to indicate on the initial survey interest in were assigned, a third party assessed a brief phone (n = 22) or email (n = 19) relating quotes and themes to assist with interview. The qualitative sample was the thematic validity (Patton, 2002). A the- result of an emergent sample (Patton, matic framework was developed as codes 2002). Interviews occurred during the emerged that guided the analysis. fall practice season. To enhance confi- dentiality, athletes were assigned a pseud- Results and Findings onym and identifying information was Quantitative Results removed. Data was examined both for univar- iate and multivariate outliers, and five Data Analysis cases were removed. Overall, coaches Quantitative data analysis. Fol- were perceived as mostly positive exhib- lowing procedures from Hair and Black iting positive behaviors “quite often” (M (2000) and Weiss and Amorose (2005), = 5.09, SD = .72) and negative behaviors two forms of cluster analyses were “seldom” (M = 2.81, SD = .87). Table used to establish expectancy groups 4 provides within group perceptions of using coached-assigned expectancy behavior frequencies. scores. Multivariate analysis of variance Expectancy group formation. (MANOVA) followed by discriminant Expectancy groups were formed using function analysis (DFA) was used to first Ward’s clustering method to deter- examine differences between expectancy mine how many groups may be present groups (independent variable) and per- in the data. Ward’s technique indicated ceptions of coach behavior (dependent three groupings based on MERS ratings variable). All assumptions for data analy- and was followed by k-means cluster- sis procedures were met. ing method using three pre-determined Qualitative data analysis. Inductive groups. The MERS descriptors were content analysis procedure was followed used to label cluster groups as a score for interview data. Transcripts were read of “1” indicated a low expectation, “3” multiple times in their entirety followed indicated an average expectation, and by an initial coding sheet to give the “5” a high expectation. Cluster analyses researcher a starting code framework. resulted in three distinct athlete expec- Codes were then refined, as necessary tancy groups: (a) high expectancy (HEx) through subsequent readings, by identify- (n = 64, M = 4.59), (b) average expectan-

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 41 Table 4

Expectancy Group Means and DA Coefficients for Coaching Behavior Variables LEx AEx Hex DA Function: DA Function: n = 17 n = 59 n = 70 Detached Engaged CBAS Subscale M M M Function Coef Function Coef (SD) (SD) (SD) (Structure) (Structure)

Non-Reward(n) 3.85 2.97 2.89 .88 -.48 (0.28) (0.13) (0.12) (.53) (-.35) Encouragement 3.97 4.34 4.24 .54 .27

After Mistakes(p) (0.30) (0.16) (0.14 (-.12) (.22) Corrective 4.71 5.44 5.38 -.59 .12

Instruction(p) (.027) (0.15) (0.12 (-.33) (.37)

Ignore Mistakes(n) 2.97 2.80 2.94 -.47 .14 (0.31) (0.14) (0.14) (-.01) (-.17) General

Communication(p) 4.76 5.41 5.50 -.42 -.05 (0.24) (0.13) (0.12) (-.43) (.21)

Organization(p) 5.85 6.21 5.83 .54 .65 (0.20) (0.11) (0.12) (.09) (.59)

Punishment(n) 3.26 3.03 2.80 .40 .49 (0.28) (0.14) (0.14) (.27) (.13) Corrective Inst. & 2.29 2.43 2.34 -.28 .44

Punishment(n) (0.31) (0.15) (0.15) (.00) (.19)

Reward(p) 4.18 4.75 4.86 -.14 -.39 (0.26) (0.14) (0.12) (-.39) (.14)

Keeping Control(p) 4.50 4.39 4.53 .02 -.36 (0.25) (0.16) (0.12) (-.05) (-.23)

Instructions(p) 5.21 5.63 5.30 .26 .25 (0.24) (0.14) (0.14) (.01) (.49)

Encouragement(p) 4.68 5.32 5.22 -.02 .22 (0.22) (0.14) (0.13) (-.27) (.35) Positive Behaviors 4.73 5.17 5.11 (0.15) (0.09) (0.09) Negative Behaviors 3.10 2.81 2.74 (0.20) (0.12) (0.10) Note: Subscripts denote inclusion in positive(p) or negative(n) behavior group. CBAS response selections ranged from 1 (never), 2 (hardly ever), 3 (seldom), 4 (sometimes), 5 (quite often), 6 (very often), and 7 (almost always). Standardized function coefficients reported.

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 42 cy (AEx) (n = 66, M = 3.73), and (c) low quent general communication (r = -.43), expectancy (LEx) (n = 18, M = 2.60). and infrequent rewarding behavior (r = Considering the limitations of clus- -.39). This function was labeled detached ter analysis (Tan, Steinbach, & Kumar, as the most strongly correlated behaviors 2013), a one-way analysis of variance represented a coach that did not engage confirmed a significant difference -be with the athletes. The second function, tween expectancy group MERS scores, labeled engaged, most strongly correlated Welch’s F(2, 44.10) = 281.20, p = .00, with coaching behaviors of organization ω2 = .79, and a Games-Howell post hoc (r = .59), instructions (r = .49), corrective analysis confirmed LEx MERS scores instruction (r = .37), and encouragement were significantly lower than HEx and (r = .35). The DFA plot (see Figure 1) AEx scores, p = .00, and HEx scores showed the detached function discrimi- were significantly higher than LEx and nated LEx and AEx athletes from HEx AEx scores, p = .00. athletes as HEx athletes perceived less Expectancy group differences. A detached behaviors. The second func- one-way MANOVA followed by DFA tion discriminated the AEx athletes as was used to examine differences in per- perceiving more engaged behaviors than ceptions of coaching behavior by ex- both LEx and AEx athletes. Table 4 pectancy group. Pillai’s trace revealed a displays function and structure coeffi- significant effect of expectancy group cients for each function. Overall, DFA membership on perceptions of coaching suggested the differences in perception behavior with observed power = .70, of coaching behavior by expectancy V = .30, F(24, 266) = 1.98, p = .01, η2 group was best explained by one underly- = .15, and DFA revealed two discrimi- ing dimension, that being perceptions of nant functions. The first accounted for detached coaching behavior. The second 70.3% of the variance, canonical R2 = dimension, perceptions of engaging .21, whereas the second accounted for behavior, influenced this primary under- 29.7%, canonical R2 = .10. In combina- lying dimension, but did not necessarily tion, these functions significantly dif- change by expectancy group membership ferentiated the groups, λ = .72, χ2(24) = by itself. 45.69, p = .01. Removing the first function indicated the second function did Qualitative Findings not significantly differentiate between Of the 20 teams recruited for the groups, λ = .90, χ2(11) = 14.82, p = .22. study, 18 teams were represented for the Using structure matrix coefficients, cor- qualitative portion. Two teams had first relations between functions and behav- year head coaches and responses about iors revealed the first function was most new (to the athletes) head coaches ac- strongly correlated with more frequent counted for 26% of interview responses. non-rewarding behavior (r = .53), infre- Three teams had five athletes per team

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 43 Figure 1: Expectancy Group Centroid Position by Function participate and account for 39.5% of the Two major themes emerged pertaining to total responses. The remaining 15 teams distinct coaching differences: (a) Stronger combined provided 60.5% of the total athletes get more, and (b) weaker athletes participation. Athletes were first asked to are different. Themes were considered self-rate their performance expectation major themes if at least 60% of partic- group (i.e., high, low, average), and com- ipants contributed to the theme. Both parisons of coaching behavior toward major themes contained minor themes. other types of athletes were used in ref- Minor themes were retained if at least erence to the athlete’s self-identification 30% of participants contributed to the (see Table 2). theme. Seventy-six percent (n = 29) of in- Stronger athletes get more (Ma- terviewed athletes reported noticeable jor 1). This major theme was defined as differences in coach behavior direct- specific behaviors issued by the coach ed toward the “better” players versus perceived to occur because the receiving “weaker” players on respective teams. athletes were considered to be stron-

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 44 ger athletes on the team and was men- tive, but they knew those athletes were tioned by 81.6% of athletes (n = 31). held to a generally higher standard than Two minor themes indicated stronger the rest. athletes benefited from (i) Higher standards: More attention and “pushing,” or Ashley’s perspective was shared by most (ii) received more instruction, praise, or athletes under this theme, patience. I guess you can tell if you do Higher standards: Attention and something that another players push (Minor 1i). Stronger athletes were does with ease, and you it’s some- perceived to receive more attention, or thing that you do every now and more pushing to perform, than oth- then, and you’re praised for that. I er athletes and were held to an overall guess you can kind of assume that higher standard. Athletes (n = 19) no- your expectations are lower than ticed coaches providing attention only the expectations that your coach to the athletes that played starting roles. might have for that other player. Peyton explained, “I think [coach] just cares if the starters get better. At practice Several athletes perceived stronger she only pays attention to starters and athletes were placed in more prestigious only works on starters.” Other athletes team roles (e.g., mentors, performance simply noticed the coach paying more exemplars, leaders) or had “better” re- attention to the athletes who served in a lationships with the coach. Brooke, a starting role. Hannah revealed why she stronger athlete, believed her coach thought stronger athletes were pushed “has confidence in everyone, but she more when she explained, “Sometimes expects us [stronger athletes] to be lead- [coach] will push players harder, verbally. ers and role models.” Christy, a weaker I think she feels like the better players athlete, confirmed Brooke’s perceptions can handle it and will benefit from it by explaining her coach “uses [stronger more.” Melinda agreed with Hannah and athletes] as examples all the time.” Jessica exemplified what other athletes perceived thought her coach was “more friendly” about stronger athletes when she com- towards stronger athletes. Hannah, a mented that her coach “pushes them to strong athlete, added, “I feel like Coach make better plays” while Jackie noted values our opinions of the team and stronger players are “different in the comes to us individually for insight to fact that [coaches] test and are harder on the team. A lot of the players on the those they expect more out of.” team that are very good will see coach Some athletes were not able to de- off the field more to talk about aspects scribe exactly why they thought stronger of the team outside of playing, such as athletes received different behaviors, and team chemistry and leadership.” Tiffany, they did not think the coach was nega- an average athlete, noticed, “In regards

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 45 to casual conversation, the coaches talk because you know we’re not good to the best players on the team like they enough to play against a [lower are on their level. When I get spoken to, division] college. I feel very inferior and low on the totem pole.” In general, athletes believed the praise Instruction, praise, and patience was abundant for stronger athletes as (Minor 1ii). Athletes (n = 12) shared they seemed to receive praise “pretty their perceptions of stronger athletes much every time they make not even that receiving more instruction time, more good of a play.” praise feedback, and more patience. Col- Weaker athletes are different (Ma- leen, a self-rated strong athlete, provided jor 2). This theme was defined as specific one example when she commented on behaviors issued by the coach perceived the use of individual coaching and video to occur because the receiving athletes instruction, “I mean the starters will get were considered to be weaker athletes on video reviews from the game. So yeah, the team and was mentioned by 63.2% I guess there is a little more coaching of athletes (n = 24). Two minor themes directed to the people who play more… indicated weaker athletes experienced there’s more one-on-one time.” Other (i) lower expectations: more frustration, athletes remarked on the coach’s pa- ignoring of mistakes, or general negativ- tience level with stronger athletes when ity from the coach, or (ii) received more mistakes were made on the field. Tiffany instruction or encouragement. (average athlete) noticed, “When the best Instruction or encouragement people on the team mess up, the coach (Minor 2i). Athletes (n = 15) contrib- lets it go.” Ginny considered herself to uting to this major theme perceived the be a strong athlete and consented, “He is coach to provide more skill instruction harder on us, but he also lets us get away or encouraging feedback to weaker ath- with a little more sometimes.” While athletes; however, the consensus was weaker letes noticed stronger athletes received athletes needed the additional instruc- remarks in the form of “good job” or tion and feedback. Kayla and Bethany’s “positive affirmation,” Peyton provided remarks captured the essence of this insight from a self-rated weaker athlete, theme. Kayla, a self-rated stronger ath- Basically when we were playing lete, provided an example of this theme, [a lower division college] [Coach] “I mean if you’re not the best and you said that after the game we won need a lot of work he’ll like maybe be on by a lot and she [coach] was like, you more to get things right.” Bethany, ‘Thankfully the starters got us up a self-rated weaker athlete, provided the ahead enough so that we could explanation for increased instruction be- put everybody else in.’ which just cause weaker athletes “might need a little makes people feel like garbage more attention in some areas.”

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 46 Lower expectations: Negativity, different skill levels, and coaches treated frustration, and ignoring (Minor 2ii). above average and below average ath- Athletes (n = 9) contributing to this ma- letes differently. Stronger athletes were jor theme perceived the coach to exhibit perceived to be held to an overall higher negative behavior including frustration expectation level involving more pushing and ignoring of mistakes toward weaker and testing of skill limits, and received athletes on the team. Alicia, a self-rated more practice time, attention, and praise stronger athlete, noticed, “Coach tends than lower skilled athletes. Below average to not pay as much attention to the weak- athletes’ performances, presence, or mis- er players than to the stronger ones.” Me- takes were ignored more often, and lesser linda agreed when she stated, “Most of skilled athletes were held to an overall the time [our coach] just ignores them.” lower expectation. Ashley, a weaker athlete, noticed her coach reached a point of frustration with Discussion other weaker athletes including her more This mixed-methods study sought quickly. After not performing a skill to explore how athletes of different correctly after instruction, Ashley’s coach expected performance levels perceived yelled, “Why aren’t you just doing what head coach behavior to understand more we just told you to do?” Other athletes about a self-fulfilling prophecy within made remarks about lower expectancy sports. Using coach-assigned perfor- athletes during games, “If you’re on the mance expectation ratings, quantitative bench she doesn’t always acknowledge data showed low and average expectan- what you’re doing to help the team.” cy athletes perceived more behaviors Some perceived weaker athletes were reflecting a detached coach than high treated as having a lower performance expectancy athletes thus supporting the expectation in general. Athletes were null hypothesis. Despite coaches receiv- unclear why they perceived this treatment ing positive behavior ratings, qualitative but knew there was something different findings enhanced quantitative data that about the coach’s behaviors. Chloe pro- athletes of differing skill levels experi- vided an example when she noticed one enced disparate behaviors. The results teammate “can’t keep up with the rest are discussed in relation to an expectancy of us” and her coach would correct her effect. infrequently because the coach “doesn’t Research on coach expectations, really waster her time to get on her.” although inconsistent, has shown high In summary, inductive examination expectancy athletes can receive more of interview data revealed two major instruction, praise, and encouragement themes: (a) stronger athletes get more, than low expectancy athletes (Amorose and (b) weaker athletes are different. & Weiss, 1998; Krane, Eklund, & Mc- Athletes perceived teammates to have Dermott, 1991; Solomon, 2008a; Sol-

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 47 omon et al., 1998a, 1998b; Solomon & treatment. The most alarming difference Rhea, 2008), and is demonstrated most was how coaches were perceived to ig- distinctly in the second step of the EPP. nore below average athletes’ performance Despite an overall group of positive or behavior more often than others. coaches involved in this study, HEx ath- Horn et al. (2006) argued a SFP could letes experienced less “detached” behav- occur if coaches consistently portrayed ior, and interview responses supported certain behaviors toward athletes over an this finding with 65% of participants extended length of time, and if feedback indicating athletes perceived differen- or behaviors were negative (i.e., a Golem tial treatment toward different levels of effect), athletes could experience harmful athletes based solely on performance psychological effects. Qualitative find- ability. Specifically, LEx and AEx athletes ings revealed athletes perceived below perceived coaches ignored effort and average teammates experienced ignoring good performances more often (non-re- behaviors the most by the coach ignoring ward), engaged in less general commu- physical presence, mistakes, or perfor- nication, and provided less reward and mance attempts. Coaches were perceived corrective instruction than with HEx to avoid interaction with these athletes athletes. These findings support literature including spending less practice time that low expectancy athletes receive less with this group. A Golem effect could overall feedback (Siekanska et al., 2013; be in motion with this sample as coaches Solomon, 1998, 2008). Some difference who ignore athletes’ performances or in behavior was seemingly positive in that physical presence may hinder the ath- coaches were perceived in some cases to letes’ psychological and performance offer more instruction or praise to be- growth (Horn et al., 2006). Responses low average athletes. However, as Horn in this study indicate ignoring behaviors (1984) demonstrated, even this type of directed at below average teammates differentiated treatment can lead to neg- influenced not just the targeted athlete ative athlete outcomes. What is not clear but also their teammates. The literature is if these coaches started a self-fulfill- is clear that negative coaching behaviors, ing or a self-sustaining prophecy. Many primarily ignoring behaviors, alters the of these athletes had been recruited by perception of team climate (e.g., task ver- head coaches and invited to play for the sus ego) and in turn can lead to changes current team, so an assumption could be in athletes’ self-determined motivation, coaches had an inaccurate initial belief performance, and persistence (Horn they did not change, or athletes had since et al., 2006; Ryan & Deci, 2000; Smith, conformed to the coaches’ initial behav- Fry, Ethington, & Li, 2005). Addition- ior. What is unsettling is despite coaches ally, ignoring behavior and excluding an being rated as positive behavior coaches, athlete from the team (or not engaging) athletes still perceived a difference in is a form of social ostracism (Williams,

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 48 2007). Social ostracism can lead to neg- of the negative perceptions. However, ative physiological reactions (e.g., higher of the 38 athletes included in the quali- stress levels and increased blood pres- tative portion of the study, three athletes sure) (Stroud, Tanofsky-Kraff, Wilfley, & self-rated lower than the coach and 12 Salovey, 2000). More importantly, social self-rated higher than their coach’s rat- ostracism leads to a host of negative psy- ing of their performance. Of those 12 chological responses including increased athletes, five athletes thought they were sense of loneliness, helplessness, frus- above average, yet their coach rated them tration, anxiety, depression (Williams & below average. Overall, the qualitative Sommer, 1997; Williams & Zadro, 2001), sample appeared to be a group of pre- and can lead the ignored to self-evaluate dominantly self-assured athletes as only negatively (Williams, Bernieri, Faulkner, two athletes self-rated as below average Gada-Jain, & Grahe, 2000). Ultimately, athletes. Interestingly, little research could if coaches ignored those athletes rated be found addressing the consequences lower, a Golem effect could be set into of coach perceptions not aligned with motion with the risk of those athletes athlete perceptions. Of the few studies, not meeting their optimal performance misalignment may be more common level, quitting the sport, or suffering than exposed in the literature and should more intense side effects associated with be considered for intervention strategies ostracism (Williams, Jerome, Kenow, aimed at enhancing the coach-athlete Rogers, & Sartain, 2000). This genera- relationship (Boyce, Gano-Overway, & tion of athletes have made it clear that Campbell, 2009; Møllerløkken, Lorås, & acknowledgement of physical presence Pedersen, 2017). The question arises as and performance through either verbal to how, if at all, the misaligned expecta- or nonverbal cues is not only needed tion beliefs contribute to a SFP. but desired for improved motivation, It is known that athletes can interpret confidence, and ultimately, performance coaching behaviors differently within (Buning, 2016; Fasting & Pfister, 2000; the same team particularly based on Horn, Bloom, Berglund, & Packard, the current success of the team (Smith, 2011; Norman & French, 2013). Shoda, Cumming, & Smoll, 2009), and Particularly among females, ath- team success was not a factor in this letes who already have a lower sense study. Additionally, coach leadership style of self-confidence tend to perceive the was not accounted for in this study. It actions of the coach more negatively is well-documented that coaches with a compared to teammates with higher more democratic approach and emphasis self-confidence (Konter, 2009; Siekanska on task-mastery are perceived to empha- et al, 2013). The lower rated athletes in size more positive behaviors (Amorose this study may already have self-confi- & Horn, 2000; Hollembeak & Amorose, dence issues, and this could explain some 2005; Smith et al., 2010). Similarly, what

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 49 was not measured, but deserves mention, idence that AEx athletes may perceive is the motivation and teaching efficacy of behaviors similarly to LEx athletes yet the head coaches. Coaches who are high- not as positively as HEx athletes (Bun- ly motivated and report feeling confident ing, 2016). in their teaching ability tend to give more positive feedback and instruction (Sulli- Conclusion van & Kent, 2003). In turn, athletes who This study provided evidence that play for high-efficacy coaches perceive despite coaches being rated as exhibiting their coaches more favorably resulting predominately positive coaching behav- in higher win percentages (Myers, Var- ior, there were observed differences in gas-Tonsing, & Feltz, 2005). More spe- behavior across expectancy groups leav- cifically, when athletes perceive a coach ing open the possibility of both a Pyg- to be effective in teaching technique, malion and Golem effect in action. The athletes’ self-efficacy can be raised pro- consequences of poor coaching behav- ducing better performance (Feltz, Chase, iors can be detrimental to psychological Moritz, & Sullivan, 1999). Coaches in well-being (Gearity & Murray, 2010) and this study may vary in various elements performance (Gould et al., 1999). In of coaching efficacy, and coach behavior addition to the undesirable products of (and initial belief) could be dictated by a negative team environment, coaches the coach’s coaching efficacy orienta- should be concerned that athletes still tion rather than the athlete’s actions. In perceived differential behaviors between experimental studies, self-efficacy has athletes even though coaches were given been shown to be a mediating variable to high scores for positive behaviors overall. the Pygmalion effect (Eden 1990; 1996) Athletes’ perceptions of an experience and could be a mediator for coaches as are vitally important to their motiva- well. More needs to be studied about tional drive (Amorose & Horn, 2000; the intersection between coach efficacy Pensgaard & Roberts, 2002), perceived and prophecies. Coaches may have good motivational climate (Smith et al., 2005), intentions to behave and create desirable achievement strategies and behavior climates, but lack of teaching skills or ef- (Treasure, 1997), and continued sport ficacy could dictate how athletes perceive participation (Ryan & Deci, 2000). reality (Smith, Quested, Appleton, & Implications. To truly support Duda, 2016a; Werthner & Trudel, 2006). coaches in their quest to create optimal Finally, this study took into consider- environments, and minimize opportu- ation average-rated athletes (AEx). Many nities for negative consequences (e.g., studies are limited to the examination of Golem effects), there needs to be a more only high versus low expectancy athletes; holistic and comprehensive examination however, average athletes comprise the of the existing environment rather than a majority of a team. There is some ev- narrow focus (e.g., athlete-only) (Smith et

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 50 al., 2016b). This approach should extend itations can be addressed, a few specific to include assisting coaches in their de- limitations to consider pertaining to this velopment and understanding of athlete study are as follows: This study was part issues surrounding the coach-athlete rela- of a dissertation study and was delimited tionship. Coaches need assistance to un- to Division I collegiate softball athletes in derstand the value of athlete perceptions, an attempt to get a better understanding and programming should continue to of how this population functions. Results help coaches understand the disconnect for the low expectancy group should be between how they think they are behav- interpreted with caution as this group ing and how athletes perceive behavior consisted of only 18 athletes although (Krane et al., 1991). Horn et al. (2006) findings were consistent with literature provides an outline of behaviors that (Amorose & Weiss, 1998; Solomon, may be considered “Pygmalion prone” 2008a; Solomon & Rhea, 2008). The data coaches verses “non-Pygmalion-prone,” is five years old, and time should be con- (p. 99), but the Pygmalion effect is a sidered for interpretation. The researcher positive cycle that may be used for good. altered the scoring of the CBAS-PBS by The Golem effect is the concern for grouping and assigning a positive and coaches. Additionally, the idea that some negative behavior score, and although coaches may be “Pygmalion prone,” or methods were strategically considered “non-Pygmalion-prone,” may have flaws and researched, this may have affected as ultimately the assessment of coach scale reliability and validity. Additional behaviors relies on how athletes perceive studies using the same technique are war- the coach at the moment. Coaches must ranted to truly determine the influence first be made aware of their behaviors of this decision. Although the researcher and be open to evaluation and change. intentionally studied one subset of fe- To encourage a Pygmalion effect, coach- male sports (Division I softball), findings es need to raise their own expectations may not represent other female sports or first. Support professionals (e.g., sport other competition levels (e.g., Division psychologists, mental performance II). Finally, interview athletes responded coaches, counselors) can help coaches through two different modes (phone vs. self-evaluate and receive consultation and email). Although both modes are consid- training to assist with the development ered acceptable for data collection (Gais- of coaching efficacy (Boardley, Kavussa- er & Schreiner, 2009), data may have nu, & Ring, 2008). been more consistent using one mode and collecting data from participants on Limitations and Future Research. more than one occasion. More research As with all research studies, there are needs to be conducted to determine if many limitations to consider when in- the expectancy effect works consistently terpreting results. Although not all lim- on both males and females (Kierein &

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Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 58 ketball coaches. Journal of Sport Behav- affective response. Journal of Sport and ior, 19, 163-177. Exercise Psychology, 19, 278-290. Solomon, G. B., & Rhea, D. J. (2008). Volner, D. (2014, January 28). ESPN rolls Sources of expectancy information out unprecedented college softball schedule. among college coaches: A quali- ESPN MediaZone. Retrieved from tative test of expectancy theory. http://www.espnmediazone.com. International Journal of Sports Sci- Volner, D. (2017, June 8). Sooners’ second ence and Coaching, 3, 251-268. doi: consecutive National Championship: Most- 10.1260/174795408785100725 watched Women’s College World Series fi- Stroud, L. R., Tanofsky-Kraff, M., Wil- nals sweep ever. ESPN MediaZone. fley, D. E., & Salovey, P. (2000). The Retrieved from http://www.espnme- Yale Interpersonal Stressor (YPS): diazone.com. Affective, physiological, and behav- Weaver, j. Moses, J. F., & Snyder, M. ioral responses to novel interpersonal (2016). Self-fulfilling prophecies rejection paradigm. Annals of Behavior- in ability settings. The Journal of So- al Medicine, 22(3), 201-213. cial Psychology, 156, 179-189. doi: Sullivan, P. J., & Kent, A. (2003). Coach- 10.1080/00224545.2015.1076761 ing efficacy as a predictor of leader- Weiss, M. R., & Amorose, A. J. (2005). ship style in intercollegiate athletics. Children’s self-perceptions in the phys- Journal of Applied Sport Psychology, 15, ical domain: Between- and within-age 1-11. doi: 10.1080/10413200305404 variability in level, accuracy, and sourc- Tan, P. N., Steinbach, M., & Kumar, V. es of perceived competence. Journal of (2013). Data mining cluster analysis: Sport & Exercise Psychology, 27, 226-244. Basic concepts and algorithms: Intro- doi: 10.1123/jseop.27.2.226 duction to data mining (pp. 487-559). Werthner, P., & Trudel, P. (2006). A new Boston, MA: Addison-Wesley. theoretical perspective for under- The Tucker Center for Research on Girls standing how coaches learn to coach. & Women in Sport. (2014, January). Sport Psychology, 20, 198-212. doi: Head coaches of women’s collegiate teams: 10.1123/tsp.20.2.198 A report on select NCAA Division-I FBS Wilkinson, D. (2009). The self-fulfilling institutions, 2013-14. Minneapolis, MN: prophecy in intensive care. Theoretical LaVoi, N. M.. Medicine and Bioethics, 30(6), 401-410. Tierney, P., & Farmer, S. M. 2004. The Williams, K. D. (2007). Ostracism. Annu- Pygmalion process and employee cre- al Review of Psychology, 58, 425-452. ativity. Journal of Management, 30(3), Williams, K. D., Bernieri, F. J., Faulkner, S. 413-432. J., Gada-Jain, N., & Grahe, J. E. (2000). Treasure, D. C. (1997). Perceptions of The Scarlet Letter study: Five days the motivational climate and elemen- of social ostracism. Journal of Person- tary school children’s cognitive and

Journal of Amateur Sport Volume Four, Issue Three Buning, 2018 59 al and Interpersonal Loss, 5, 19-63. doi: and rejected. In M. Leary (Ed.), Inter- 10.1080/10811440008407846 personal rejection (p. 21-54). New York: Williams, J. M., Jerome, G. J., Kenow, L., Oxford Press. Rogers, T., & Sartain, T. A. (2003). Wilson, M. A., & Stephens, D. E. (2005). Factor structure of the coaching Great expectations: How do athletes behavior questionnaire and its rela- of different expectancies attribute tionship to athlete variables. The Sport their perception of personal athletic Psychologist, 17, 16-34. doi: 10.1123/ performance? Journal of Sport Behav- tsp.17.1.16 ior, 28(4), 392. Williams, K. D., & Sommer, K. L. (1997). White, S. S., & Locke, E. A. (2000). Social ostracism by coworkers: Does Problems with the Pygmalion affect rejection lead to social loafing or and some proposed solutions. Lead- compensation. Personality & Social ership Quarterly, 11(3), 389-415. doi: Psychology Bulletin, 23, 693-706. doi: 10.1016/S1048-9843(00)00046-1 10.1177/0146167297237003 Williams, K. D., & Zadro, L. (2001). Os- tracisim: On being ignored, excluded,

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