ISSN: 1543-9518|Vol. 24

Maximizing Youth Sports Engagement on Social Media: How Visual Impact and Message Appeal Shape Consumer Responses Online

Authors: Wan S. Jung1, Won Yong Jang2, and Soo Rhee3

1Department of Professional Communications, Farmingdale State College, New York
2Department of Communication and Journalism, University of Wisconsin, Eau Claire, Wisconsin
3Department of Mass Communication, Towson University, Maryland

Corresponding Author:

Wan S. Jung, Ph.D
Knapp Hall 30
2350 Broadhollow Road, Farmingdale, NY 11735-1021
[email protected]
934-420-2276

Wan S. Jung, PhD is an Associate Professor of Professional Communications at Farmingdale State College, NY. His research interests focus on the credibility assessment process of digital information.

Won Yong Jang, PhD is a Professor at the University of Wisconsin, Eau Claire. He specializes in 1) international communication, 2) news media and society in East Asian countries, 3) climate change policy & communication, 4) public opinion on North Korea’s Nuclear Program, and 5) territorial disputes in the Asia-Pacific Region.

Soo Rhee, PhD is a Professor at Towson University, Maryland. Her research interests include luxury brand advertising, gender portrayals in advertising, dynamics of electronic word-of-mouth, cross-cultural studies in advertising and message strategies in health advertising.

ABSTRACT
An increasing number of people rely on the Internet as their primary information source and use it to share their opinions and thoughts with others. Generally, individuals adopt a systematic approach when processing sports information, evaluating its completeness and accuracy due to the serious consequences of incomplete or inaccurate information, such as monetary loss and negative impacts on child development. However, our study finds that the heuristics of online information, even with subtle changes in design features, generate more positive attitudinal and behavioral changes compared to central cues (i.e., informational posting). Our findings suggest a dissociation between involvement and the effects of heuristics. This study also provides an empirical framework for predicting how people process information in digital media environments. Additional findings and implications are discussed.

Key Words: youth sport communication, visual impact of social media posting, message appeal

INTRODUCTION
The youth sport market is a huge and fast-growing industry, ranging from organized sports leagues to recreational activities. The market for youth sports in the United States stood at 15.3 billion U.S. dollars in 2017 and grew to 19.2 billion U.S. dollars by 2019 (11). With a fast-growing trend (i.e., a growth rate of 25.4% from 2017 to 2019) with various options, parents became more active in searching for information. As social media are pervasive, rapidly evolving, and increasingly influencing parents’ daily life and their sport consumption, parents increasingly turn to the internet as a source of community, which helps them connect, communicate, and share information (18).

The rapid growth of online sports information production and dissemination through social media parenting communities (e.g., Facebook local groups and Nextdoor) raises important research questions about how individuals process online information provided by other consumers (i.e., experienced parents whose child(ren) have participated in your sport programs) in youth sport consumption decision making. Moreover, since sport consumers make decisions about whether or not to adopt online sports information based on their own judgement (e.g., attitudinal formation), how individuals evaluate online information is central to sports communication agendas.

Although the formation of attitudes toward information can be attributed to multiple aspects of that information (e.g., source credibility, information completeness), sport consumers using online resources are more reliant on how the information is presented than on the quality of the argument (10), and subtle graphical adjustments become relevant when online parenting community members share their own experiences with other members on social media platforms. In order to emphasize their own views, web users often create visual prominence using subtle design elements, such as capitalized subject lines, copy-and-paste text art (also called keyboard art, e.g., ≧◡≦), or bullet-point symbols. In addition to subtle design changes, the characteristics of the online posting can be varied based on the degree of informativeness (i.e., emotion-based versus information-based).

The purpose of the current study is twofold. First, it will explore the effect on attitudinal formation and behavioral intentions of the message appeals and subtle graphical adjustments of posts in online parenting communities in the youth sport consumption context. Second, the study will investigate whether the strength of the relationship between attitude and behavioral intentions varies based on message appeals. Overall, the study will seek to advance understanding of digital media by examining how small graphical changes and message appeals impact youth sport consumers’ attitudes and behaviors when searching for consumer-generated information (e.g., testimonials) in online communities.

LITERATURE REVIEW
Parent-to-Parent Online Information in Youth Sport Consumption
“It takes a village to raise a child” is a proverb to explain the role of and community support in parenting. As social aspect is one of the primary factors that drives parents and their children to be involved in sport program (1), the influence of other parents’ opinion and the role of parent community are even more prominent in youth sport consumer’s decision making process. Braunstein-Minkove & Metz (2019) noted in their research on the role of mothers in sport consumption that youth sport consumption might not always about the sport but the experience. Therefore, parents of youth rely on other parents’ opinion to obtain relevant and sufficient information and evaluate various youth sport program options available. In order to provide the best sporting and exercise experience for their children, parents of young children are willing to hear voices of other parents (i.e., testimonial) regarding the type of sports, sports programs, and sporting events their children would participate in.

With the modern technology and the advent of social media, the notion of the village (or supporting community) has been expanded from a physical village to a digital community. Social media platforms support a variety of user generated content to be disseminated to other users and allows users to participate in interactive discussions. Among the various types of social media platforms, Facebook have become the most prevalent web-based service in the world (21) and remaining the most popular site by far (12). Also, Facebook recently provides an option to mark the group type as parenting group, which gives parents new ways to discover and engage with their communities (5). Though the role of online community and the influence of information from other youth sport consumers (i.e., testimonials from other parents in such online community) in youth sport consumer’s decision-making process became more prominent, there is no previous research to explore the effects of the presentation of online information on consumers’ attitudinal and behavioral response in youth sport consumption context.

The Impact of Visual Prominence
Quick and low effort cognitive information processing has been investigated in the field of psychology since the 1970s (e.g., 9, 13), and the research indicates that impression formation is the result of the perceiver’s rapid response to selective or incomplete information. In other words, one’s appraisal of an event occurs without intention or conscious thought. Theories of impression formation in the context of digital communication have been developed by Fogg (2003) and Wathen and Burkell (2002), and their studies suggest that visual prominence—the visual salience that allows people to effortlessly notice the presence of graphic elements (e.g., bold vs. non-bold font)—is a primary driver of attitudinal formation, rather than information quality.

The impact of visual prominence can also be explained by individuals’ reliance, when making decisions, on transactive memory systems, which consist of two key elements: internal memory (e.g., personal experience) and external memory (e.g., another person’s expertise; 14). The presence of an external memory will activate a transactive memory system, and such a dependency on external memory increases efficiency and cognitive labor power (20). Thus, external sources of knowledge can have a significant impact on one’s perception of what to accept as true and how confidently to accept it.

The theoretical and empirical evidence for transactive memory systems is based on offline social interactions (e.g., interactions within family groups). However, recent studies suggest that online sources can also trigger transactive memory systems due to the similarity between the process of outsourcing cognitive tasks to other people and the process of outsourcing cognitive tasks to the Internet (6). This nonhuman transactive memory network is further fueled by the unique features of the Internet (e.g., accessibility, breadth, immediacy of information), but such features may distort one’s ability to calibrate personal knowledge because the boundary between internal and external memory becomes unclear. That is, individuals often mix up information obtained through the Internet with information stored in the brain, and this illusion inflates self-ratings of competence regarding personal knowledge and decision-making (17). Recent research on such illusions also suggests that people tend to believe they can solve problems even in unfamiliar domains and that their decision-making processes are often based on heuristics, such as visual prominence (7, 8); the impact of visual prominence would thus be greater in digital media environments.

Since online parenting community members can establish the visual prominence of their postings on social media platforms only with subtle graphical adjustments, the current study will investigate how subtle changes (e.g., capitalizing subject lines, use of text art) to posts in online youth sport communities influence individuals’ attitude formation and behavioral intentions. Given the exploratory nature of the topic of individual information judgment in digital media environments, the following hypotheses are proposed:
H1: Visually prominent postings in online youth sport communities form stronger attitudes than less prominent postings.
H2: Visually prominent postings in online youth sport communities form stronger behavioral intentions than less prominent postings.

The Impact of Involvement on Message Appeals
The persuasiveness and prevalence of various appeal types (e.g., emotional, informative) have been extensively examined in different contexts, such as brand familiarity (Rhee & Jung, 2019), cultural variability (Han & Shavitt, 1994), and involvement (Flora & Maibach, 1990). However, less is known about the differential effects of appeal types in the context of online youth sport communities, and the current study therefore presents an exploration of the question of which type of message appeal is most persuasive in such communities.
The elaboration likelihood model (ELM; 16) is one of the most prominent theoretical frameworks employed in the message appeal literature and is applied in various contexts, such as public health service announcements (Perse et al., 1996), crisis management (Lee & Atkinson, 2019), and advertising (Stafford & Day, 1995). Studies have also commonly found a moderating effect of involvement on message appeals, and according to the ELM, people tend to rely on argument quality (e.g., information completeness, comprehensiveness) when processing information under high involvement conditions, with persuasion less likely to occur through peripheral cues, such as peers’ emotional experiences. The converse is also true under low involvement conditions.

However, a recent study by Jung et al. (2017) found evidence that contradicts the prevailing literature on the role of involvement in digital media environments; the study claims that individuals often find it hard to motivate themselves to process information thoroughly, regardless of involvement levels, due to the nature of the Internet, which inundates them with massive amounts of non-verifiable information. Individuals therefore tend to compromise the accuracy of their decisions, which can require extensive cognitive effort, by relying on the heuristic aspects of information.

In addition, in the context of online youth sports communities, people tend to seek others’ prior experiences (e.g., a coach’s personality) and emotionally supportive messages because any objective information about a youth sports program (e.g., fees, coach’s experience, facilities) can be easily found through sources such as the program’s website. It can therefore be assumed that the moderating role of involvement in appeal types might be limited by the dominance of social media. Nevertheless, because there is still insufficient evidence for the limited role of involvement in the social media context, we propose the following research question:
RQ1: What effect does involvement have on the appeal types of posts in online youth sport communities?

The Moderating Impact of Involvement on the Attitude–Intention Relationship
Attitudes are among the most significant predictors of behavioral intentions in psychology. According to the theory of planned behavior (TPB), intention functions as an antecedent of behavior and is attributable to individual attitudes, together with subjective norms and perceived behavioral control (Ajzen, 1991). Although a number of studies have provided strong evidence for the relationship between intentions and the three causal variables of the TPB, a meta-analytic study by Cooke and Sheeran (2004) also noted that less than 42% of the variance in intentions can be explained by those variables.

Consequently, there have been numerous attempts to increase the predictive power of the TPB by exploring moderators of the relationship between intention and the TPB variables, such as attitudinal ambivalence (Armitage & Conner, 2000) and certainty (Bassili, 1996). In addition to these moderating variables, Petty et al. (1983) has offered theoretical and empirical evidence that the attitude–intention relationship is more consistent under high involvement conditions, because attitudes established by highly involved people are more stable than those of lowly involved people. Verplanken (1989) also examined whether involvement can explain additional variance in the attitude–intention relationship, although that study was in the context of nuclear energy.

Therefore, the current study will examine the moderating role of involvement in the attitude–intention relationship in the sport communication context.
H3: High involvement will be associated with greater attitude–intention consistency than low involvement.

METHOD
Subjects and Procedure
192 participants who had parenting experiences (male = 64%) from the United States between the ages of 20 and 55 completed the study through Amazon’s Mechanical Turk (MTurk). For participants’ ethnicity, the most common ethnicity was Caucasian (53.6%), followed by Asian (33.9%), African American (5.2%), Hispanic (3.6%), and other racial backgrounds (3.6%). To participate in the study, subjects were requested to provide electronic consent. And subjects were debriefed and compensated upon completion of the study.

Experimental Treatment Conditions
To investigate the effects of visual prominence (high vs. low prominence) and message appeals (emotional vs. informative message) on online youth sport program postings, four versions of online postings were created as stimuli, and the subjects were randomly assigned to one of the four experimental conditions: low prominence and emotional (n = 49), high prominence and emotional (n = 49), low prominence and informative (n = 49), and high prominence and informative (n = 45).

The postings contained an online community member-created message about a local youth soccer program. The community member-created posting consisted of either factual information about the soccer program (informative appeal) (i.e., up to 12 kids in one session with two coaches, all are CPR first aid and AED certified, and having an indoor field) or user experiences (emotional appeal) (i.e., it was such an amazing experience and my son loves his current coach). A youth soccer program was selected as the topic for this study because of popularity of the sport among young parents. The manipulation of visual prominence was carried out by differentiating graphic elements between high prominence and low prominence conditions. Since parent community members on social media platforms can emphasize their posting with subtle graphical alterations, the high prominence version was designed to help the study participants notice the key messages by capitalizing key words, using a bulleted list and line-breaks in order to increase readability, and using a text art. The low prominence version lacks those design features.

Dependent Measures
Attitude toward the online posting
The attitude toward the online youth program posting was measured using
three semantically differential items (i.e., good/bad, favorable/unfavorable, negative/positive) emerged from the literature on the scale (Lee & Hong, 2016). The scale was internally consistent (Cronbach’s  = .91, M = 4.70, SD = 1.81).

Behavioral Intentions
Subjects were also asked to answer their intentions to 1) recommend the youth soccer program on the posting you just read and 2) register for the soccer program in the future on 7-point Likert-type scales ranging from 1 (not at all) 7 (extremely). The items were averaged to create a behavioral intention scale (Cronbach’s  = .83, M = 4.33, SD = 1.73).

Independent Measure
Involvement
Involvement in sports activities may influence the attitudinal formation and behavioral intentions. Thus, this study measured personal involvement with sports activities by using three 7-point (1 = strongly disagree, 7 strongly agree) Likert-type scales, the participants reported on how much they agreed with the following three statements: “I enjoy playing sport,” “Sport plays a central role in my life,” and “Sport says a lot about who I am.” The three items were averaged to measure involvement (Cronbach’s  = .86, M = 5.38, SD = 1.35). This study used a median split to categorize high-involvement (N = 86) and low-involvement conditions (N = 83).

RESULTS
Manipulation Checks
The visual prominence manipulations were examined. Using two seven-point sematic differential items, the participants were asked to rate the extent to which they thought the format of the online posting they just read were “attractive/not attractive” and “likable/not likable” (Cronbach’s  = .83, M = 4.81, SD = 1.75). A t test between the two prominence conditions (low vs. high prominence) showed subjects felt that the youth sport program posting was more visually prominent when it included noticeable graphic elements (M = 5.60, SD = 1.23) than when it lacked the elements (M = 4.05, SD = 1.84), t (190) = 6.82, p < .001.

This study measured the degree of informativeness of online postings (emotional versus informative) by asking participants to rate the extent to which they though the posting they just read was “emotional” and “warmhearted” (Cronbach’s  = .80 M = 4.39, SD = 1.61). A t test between two message appeal conditions showed that the emotional appeal group (M = 4.94, SD = 1.27) perceived the posting to be significantly more emotional than the informative appeal group (M = 3.82, SD = 1.73), t (190) = 5.11, p < .001.
H1 and H2: Visual Prominence Main Effects

Multivariate analysis of variance (MANOVA) was conducted to determine the significant impacts of visual prominence, message appeal, and involvement on attitudes and behavioral intentions. H1 and H2 suggest that participants reading visually prominent postings would form stronger attitudes and behavioral intentions than did participants reading less prominent postings. Follow-up analysis of variance (ANOVA) tests were also performed the examine the effect of visual prominence for each of the dependent variables. Findings revealed that the effect of visual prominence was pronounced in relation to being able to determine consumers’ attitudes (M_High Prominence = 5.30, SD = 2.02 vs. M_Low Prominence = 4.14, SD = 1.38; F (1, 169) = 20.90, p < .001, partial η2 = .12) and behavioral intentions (M_High Prominence = 4.69, SD = 1.64 vs. M_Low Prominence = 4.01, SD = 1.73; F (1, 169) = 7.24, p < .01, partial η2 = .04). Thus, H1 and H2 were supported.



RQ1 and RQ2: Influence of Involvement on Visual Prominence and Message Appeals
The impact of consumers’ involvement on visual prominence and messages appeals were examined by 2 (visual prominence) X 2 (involvement) ANOVAs and 2 (message appeal) X 2 (involvement) ANOVAs with attitudes toward the online posting and behavioral intentions as dependent variables. The ANOVA results showed that that there were not significant interaction effects of the involvement-appeal relation and the involvement-visual prominence relation. The p values of the aforementioned relations were greater than .37. However, the impacts of visual prominence and message appeals were greater under both involvement conditions (see Figure 1 and 2).

H3: Moderating effect of involvement on the attitude-intention relation
This study anticipated that the attitude toward the online posting would form a stronger impact on the formation of behavioral intentions for high involvement conditions. Pearson’s correlation coefficient was used to examine whether involvement modifies the magnitude of the attitude-intention relation. Then, each correlation coefficient values for the high- and low-involvement conditions was converted into z scores by using Fisher’s r to z transformation. In order to compare the z scores for the two conditions, the following formula was implemented to determine the observed z score: Zobserved = (Z1−Z2) ∕ (square root of [1∕N1−3] + (1∕N2−3))

For the high involvement condition (n = 83), the correlation coefficient for the attitude-intention relation was .49 (p < .001). For the low involvement condition (n = 84), the correlation was .25 (p < .05). The test statistics, z = 1.78, p < .001 (one-tailed test), indicate that the correlation in the high involvement condition is significantly higher than it is in the low involvement condition. Therefore, Hypothesis 3 is supported.

DISCUSSION
Our findings suggest a lack of association between involvement and the effects of heuristics. The moderating role of involvement has been well established since the introduction of Petty et al.’s (1983) ELM and Chaiken’s (1987) heuristic-systematic model. According to those theories, involvement is a significant determinant in the selection of an information processing route (peripheral versus central). It is also commonly acknowledged in the sport communication field that individuals generally use a systematic mode (i.e., evaluating completeness/accuracy) when processing online sport information under high-involvement conditions in order to avoid the serious consequences of incomplete or inaccurate information (e.g., monetary loss, negative impacts on child development). However, our study found that the non-systematic mode is often activated for both high-involvement and low-involvement participants, and this finding thus contributes to the literature on individuals’ approaches to online information processing.

According to evidence-accumulation models (2), individuals reach a conclusion once there is enough evidence to support a particular case, but they can also alter the amount of evidence needed for coming to that decision. Although individuals generally want to make accurate decisions, Internet users often compromise the accuracy of their decisions by reducing the amount of evidence required to validate the information they are investigating. This tendency is attributable to online information overload, in which individuals experience difficulties in understanding the nature of a particular topic (Robin & Holmes, 2008). The tendency suggests a new general pattern of the speed–accuracy trade-off (SAT) in social media environments. In line with the SAT, there are two driving forces in the decision-making process (4); one emphasizes faster (or more efficient) decisions, while the other emphasizes higher accuracy. Although there are trade-offs between speed and accuracy, the two can be pursued independently, but they produce a wide spectrum of outcomes, from slower but more accurate decisions to quicker but less accurate decisions. In social media environments, individuals are motivated to engage in less-effortful information processing and are more likely to trade accuracy for speed in the decision-making process.

The current study also found another reason for further examining the role of involvement in social media environments. It has been assumed that persuasion is less likely to occur through emotional messages when an individual is highly involved in an issue because people tend to scrutinize issue-relevant information. However, our findings suggest that emotional messages can be more persuasive than informational messages regardless of the level of involvement, especially in the online youth sport community context, and these findings can be explained by the types of information individuals seek in online communities. Objective information about a youth program (e.g., fees, coaches’ experience, facilities) can be easily found through sources such as the youth program’s website, but people also tend to seek others’ prior experiences and emotionally supportive messages when joining online communities.
It is important to stress that the attitude–intention relationship varies with involvement levels. Our study shows that the attitudes of high-involvement participants are more predictive of the intention to perform a specific act (e.g., signing up a youth sport program) than the attitudes of low-involvement participants. Our findings regarding the attitude–intention relationship suggest that the moderating effect of involvement on that relationship is applicable to not only traditional media environments (e.g., Krosnick, 1988; Verplanken, 1989), but also to social media environments.

In addition to the theoretical implications of this study, understanding parents’ information processing in assessing youth sport program is an integral part of the sport communication landscape. With the growing importance of (local) parenting community groups on social media and the impact of user generated message, this study will help youth sport service providers understand the effective way of crafting online information. This study will shed lights on communication strategies for youth sport providers when they try to utilize a form of testimonial in introducing their services to the market. This study will also lead how social influencer marketing would be employed in delivering and disseminating the promotional messages to the consumers.

This study has some limitations. All its subjects were recruited through Amazon’s Mechanical Turk (MTurk). Although MTurk respondents tend to be more diverse than student samples in terms of demographic, psychographic, and geographic characteristics, some reliability issues (e.g., the work ethic of MTurk respondents) are unavoidable (3). Another limitation is that this study was conducted with samples of people who had parenting experiences because the study used a youth soccer program to develop the experimental stimuli, and the context of parenting might amplify reactions to emotional messages. We therefore recommend that future studies be conducted with more diverse samples and more popular sports topics (e.g., local sports events) in order to exclude the specific study topic and characteristics of the sample as potentially confounding factors.

REFERENCES

  1. Braunstein-Minkove, J. R., & Metz, J. L. (2019). Sport MOMsumers: A Modern Reexamination of the Role That Mothers Play in their Families’ Professional Sport Consumption. Journal of Applied Sport Management, 11(3), 7.
  2. Brown, S. D., & Heathcote, A. J. (2008). The simplest complete model of choice reaction time: Linear ballistic accumulation. Cognitive Psychology, 57, 153-178.
  3. Buhrmester, M. Kwang, T., & Gosling, S. (2011). Amazon’s mechanical turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6, 3-5.
  4. Donkin, C. Little, D. & Houpt, J. (2014). Assessing the speed-accuracy trade-off effect on the capacity of information processing. Journal of Experimental Psychology: Human Perception and Performance, 40(3), 1183.
  5. Facebook. (2020, June 16) Introducing a New Group Type for Parenting. Retrieved from https://www.facebook.com/community/whats-new/new-parenting-group-type/
  6. Fernbach, P. M., Rogers, T., Fox, C. R., & Sloman, S. A. (2013). Political extremism is supported by an illusion of understanding. Psychological Science, 24, 939-946.
  7. Fisher, M., Goddu, M. K., & Keil, F. C. (2015). Searching for explanation: How the Internet inflates estimates of internal knowledge, Journal of Experimental Psychology, 144 (3), 52-66.
  8. Fisher, M. & Keil, F. C. (2014). The illusion of argument justification. Journal of Experimental Psychology, 143, 425-433.
  9. Fiske, S. T. (1980). Attention and weight in person perception: The impact of negative and extreme behavior. Journal of Personality and Social Psychology, 38, 889-906.
  10. Fogg, B. J. (2003). Prominence-interpretation theory. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems CHI, 03, 722-723.
  11. Gough, C. (2021, March 1). Youth sports market size in the U.S. 2017-2019. Statista. https://www.statista.com/
  12. Greenwood, S., Perrin, A., & Duggan, M. (2016). Social media update 2016. Pew Research Center, 11(2), 1-18.
  13. Hamilton, D. L. & Zanna, M. (1972). Differential weighting of favorable and unfavorable attributes in impressions of personality. Journal of Experimental Research in Personality, 6, 204-212.
  14. Hollingshead, A. B. (2001). Cognitive interdependence and convergent expectations in transactive memory. Journal of Personality and Social Psychology, 81, 1080-1089.
  15. Jung, W. S., Chung, M., & Rhee, E. S. (2017). The effects of attractiveness and source expertise on online health site. Health Communication
  16. Petty, R., Cacioppo, J., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10, 135-146.
  17. Pronin, E. (2009). The introspection illusion. In M. P. Zanna (Ed.) Advances in experimental social psychology (pp. 1-67). Burlington, VT: Academic Press.
  18. Valtchanov, B. L., Parry, D. C., Glover, T. D., & Mulcahy, C. M. (2016). ‘A Whole New World’: Mothers’ Technologically Mediated Leisure. Leisure Sciences, 38(1), 50-67.
  19. Wathen, C., & Burkell, J. (2002). Believe it or not: Factors influencing credibility of the Web. Journal of the American Society for Information Science and Technology, 53, 134-144.
  20. Wegner, D. M. (1987). Transactive memory: A contemporary analysis of the group mind. In B. Mullen & G. R. Goethals (Eds.) Theories of group behavior (pp. 185-208). New York, NY: Springer-Verlag.
  21. Wittkower, D. E. (Ed.). (2010). Facebook and philosophy: what’s on your mind? (Vol. 50). Open Court.
2024-11-04T18:10:35-06:00November 22nd, 2024|Contemporary Sports Issues, General, Research, Sports Studies, Sports Studies and Sports Psychology|Comments Off on Maximizing Youth Sports Engagement on Social Media: How Visual Impact and Message Appeal Shape Consumer Responses Online
Read More

Perceptions of Former Collegiate Athletes on Career Transition Programs in the NCAA

Authors: Cameren Pryor1 and Lindsay Ross-Stewart2

1Department of Psychology, University of North Texas1

2Department of Applied Health, Southern Illinois University Edwardsville

Corresponding Author:
Dr. Lindsay Ross-Stewart
Campus Box 1126
Southern Illinois University Edwardsville
Edwardsville, IL, 62026
[email protected]
(618) 650-2410

Cameren Pryor: Cameren Pryor is a third-year doctoral student in Counseling Psychology with a concentration in Sport Psychology at the University of North Texas. Cameren’s research interests focus on athletic career transition/sport retirement, athletic transition psychoeducation/programming, and student athlete mental health.

Lindsay Ross-Stewart: Dr. Ross-Stewart is an Associate Professor in the Department of Applied Health at Southern Illinois University Edwardsville. Dr. Ross-Stewart’s research is grounded in Bandura’s concept of self- efficacy and its role in behavior change. Dr. Ross-Stewart is an Association for Applied Sport Psychology Certified Mental Performance Consultant (CMPC®) and a Canadian Sport Psychology Association Mental Performance Consultant (MPC).

Perceptions of Former Collegiate Athletes on Career Transition Programs in the NCAA

ABSTRACT

Many student athletes experience feelings of grief, sadness, loss of motivation, and depressive symptoms due to improperly preparing for sport retirement (1). Past literature encourages practitioners to incorporate psychoeducational programming into NCAA athletic programs that better prepare athletes for transition. However, it has been found that there is a lack of consensus on when and what is being advised to student athletes about the transition process (2). Additionally, little research has investigated the overall effectiveness of NCAA collegiate career transitioning programs through the perceptions of student athletes. The purpose of this study was to investigate if current career transition programs in NCAA Athletic Departments were using best practices, as defined by the current research in the field, based on former collegiate athlete’s perceptions of their experience with career transition programming. A secondary and equally important purpose was to investigate the overall impact athletic career transition had on former collegiate athletes’ current lives. Former collegiate student athletes completed semi – structured interviews via Zoom to assess their experience with career transition programming during their time as an athlete and the level of effectiveness they felt the program offered. The findings of this study suggest that NCAA athletic departments need to implement effective athletic career transition programming that better prepares student athletes to transition from collegiate sport.

Keywords: career transition, qualitative research, sport psychology

College student athletes dedicate approximately 70 hours per week to athletic and academic demands (3). With less than two percent of National Collegiate Athletics Association (NCAA) student athletes competing on the professional level (4), most student athletes will transition out of athletics when they graduate from university. This transition time led to increased feelings of grief, sadness, loss of motivation, and depressive symptoms for some athletes (1). To prevent these negative experiences, career transition researchers have encouraged athletic departments to implement psychoeducational programming that better prepares student athletes for the psychological, behavioral, and social outcomes of sport retirement (5). However, it has been found that there is a lack of consensus on when and what is being advised to student athletes about the transition process (2). Additionally, little research has investigated the overall effectiveness of NCAA collegiate career transitioning programs through the perceptions of student athletes.

A recent literature review of career transition research (6) found there were very few studies conducted in the United States concerning athletic transition, with the limited findings highlighting retirement planning, identity loss, coping skills and support systems as the core areas that have been investigated. They reiterated the importance of psychoeducational interventions; however, they acknowledged that more research is needed to better understand the transition process and how to effectively implement career transition programing.

Past research has also highlighted the findings that career transitions appear through social, developmental, and psychological factors (5) and the importance of starting career transition education at the earliest stages of sports participation. The importance of social support has been supported by the work of Adams et al. (7) who found participants experienced a more positive transition if they felt cared for by the people that they believed understood them and what they were going through. Thus, a sense of closeness and trust between the recipient and the person providing support appeared to be crucial for support during career transitions. Of importance was the finding that athletes perceived coaches to provide more social support than parents and teammates indicating coaches should be a central part of career transition programming. Cummins and O’Boyle (8) found that athletes perceived their universities as unable to support them during the transition process with support, career advice and information on the professional role and guidance from past student athletes. Thus, the lack of career control was shown by all participants. Cummins and O’Boyle (8) recommended implementing mentoring into university programs from former student athletes to current student athletes on the transition process and potential career opportunities.

Along with social support, one’s athletic identity has been highlighted as impacting an athlete’s experience with career transition. Specifically, the more an athlete identifies with their athletic role, the less likely they are to have a well-defined career plan (9) and therefore struggle during career transition. Furthering this finding, researchers found that athletic identity was positively correlated to retirement outcomes and negatively correlated with decreased self-esteem, feelings of uncontrollability and ‘vagueness’ about the future (10). It has also been shown that athletes who retired due to injury have greater adjustment difficulties (10). Furthermore, researchers found that the strength and exclusivity of the athletic role during sport participation increased an athlete’s potential vulnerability to psychiatric distress after leaving sport (11), and higher levels of emotional adjustment difficulties (12). In contrast to these negative connections to athletic identity, Cabrita et. al, (13) found that athletes with higher athletic identity have higher levels of career decision making self- efficacy. They suggested this may be due to the efficacy they gain from sport transferring to their career decision making efficacy. Further research is needed to better understand these potentially conflicting findings on the relationship between athletic identity and career transition.

Menke and Germany (14), identified consistent themes athletes identified when discussing their feelings and thoughts related to coping with transition out of sport including the positive of gains or strength of transferable skills as well as the negative experiences of a loss of identity, feelings of loss, sadness, anxiety, loss of motivation and depressive symptoms. It has been shown that global self-esteem and physical self-perceptions decreased during the transition out of elite sport (15). Additionally, it was found that retired athletes that experience difficulties with their bodies have decreased feelings of pride, satisfaction, happiness, and confidence regarding their physical selves. These experiences can contribute to stressful reactions to retiring out of sport. Of extra importance is the finding that sport individuals that experience bodily changes accompanied with high athletic identity can experience increased psychiatric distress and self-esteem issues when transitioning (15).

Taken together, the above information highlights the need for career transition programming and combining a plan for post-sport retirement with talking about the emotions experienced during the transition process. Past researchers have suggested that sport psychology practitioners and mental health professionals work with athletic teams to encourage the development of the student athlete by consistently speaking to them about career related topics and encouraging student athletes to explore and engage in expanding their interests outside of sport as well as supporting the use of health care resources for former high-level athletes (16).

During sport retirement, many athletes cognitively make the decision to grieve the loss of their sport by participating in healthy and unhealthy coping behaviors for extra support. Acceptance, account making, positive reinterpretation, planning, active coping, mental disengagement and seeking social support for emotional reasons are all strategies that have been reported (12). Account-making (the construction of a story about a traumatic event (i.e., it’s nature, what happened, how one feel’s about it, and what it means for the future; citation) and confiding (portions of one’s account, are revealed to others) has also been shown to be an effective tool as it helps athletes to understand their retirement experience, understand their emotions and to acknowledge an identity that is outside of sport.

Recent literature reviews have encouraged viewing transition from a lifespan perspective involving pre-career, post-career, and other domains of an athlete’s life (17), and preparing for retirement before it happens, creating a strong alliance with trust (client and counselor), exploring the emotions accompanied with the transition, interventions, and knowledge of transferable skills, addressing athlete’s overall competency of transferable skills, developing a support network, and evaluating the effectiveness of the athletes transitions out of sport and the effectiveness of counseling interventions. Based on the literature review, the researchers recommended that counselors may be effective in assisting athletes to plan for life after sport by helping them understand and realize that the skills they have acquired through sport can help them be successful in other areas of life (18).  

Furthering our understanding of best practice, researchers have recommended empathy and attentive listening need to be utilized to help athletes make sense of their experiences and it has been recommended that programming should look at the development of interventions from different psychological perspectives for athletes in transition (5). Overall, researchers suggest the need to examine the effectiveness of these models and devote attention to interventions from different psychological perspectives. Lastly, they highlight the finding that helping athletes become aware of the transferrable skills can help facilitate successful career planning. 

Researchers have continuously suggested the need for psychoeducational interventions that address the psychological, behavioral, social effects and the loss of athletic identity has on a sport individual when transitioning from sport and the need to start this programming early in an athlete’s college career (e.g., 5). Being that there is a lack of consensus on when and how to speak to athletes about career transition, and a lack of connection between research suggested guidelines and applied programming at the college level, further understanding of this area is needed. Thus, the primary purpose of this study was to investigate former NCAA athlete’s perceptions of current career transition programs in NCAA Athletic Departments. A secondary purpose was to investigate former collegiate athlete’s perceptions of their experience transitioning from sport and how these experiences affected their current lives.

Materials and Methods
Methods
Setting, Recruiting, Sampling, and Consent

            All participants were recruited via social media. Posts were made on both researchers’ Instagram, Facebook, and Twitter pages, as well as shared on their program social media sites. People were encouraged to share the posts with people they may have known who would be interested. Potential participants were instructed on how to reach the primary researcher if they were interested in participation. The primary researcher then spoke with each potential participant to make sure they were a former NCAA athlete who finished their career within the last five years but did not suffer a career ending injury or quit their college career (which were the exclusion criteria). Those that qualified were interviewed over zoom for this study. Zoom was chosen as it allowed for participants from across the United States and increased the accessibility of the study to participants. Prior to the interview the participants were sent the informed consent form and gave consent to participate. They then gave verbal consent on zoom while the session was being recorded. Participants were also given the opportunity to ask any clarification questions about the study they may have had after reading the informed consent.

 Participants

The participants of this study were six retired collegiate student athletes who previously competed in NCAA athletic programs and completed their athletic careers in the five years. The participants were two males and four females. Participants were represented from various sports consisting of basketball, track & field, softball, baseball, and golf. The athletes were from Division I (n=four), Division II (n=one), and Division III (n=one).

Data Collection Tools

Career Transition Interview

As there is a lack of set tools for assessing the psychological impact of career transition for college athletes, and to hear the voices of those who have experiences career transition, – semi structured, questions (some open and some closed based on need) were developed for this study. The goal was to allow the participants to reflect on their personal experiences with career transition programming at the universities they competed in and their overall transition experience. The important themes recognized in previous athletic career transition literature were used to develop questions for the interviews focused on their career transition program experience and their experiences post-tradition career. A specific focus was made to keep the questions neutral in language so as not to lead the participants in any direction. During the interviews, based on the participant’s comments, follow up questions were asked, and discussion was encouraged with the athlete to gain their views outside of the predetermined questions, as needed the closed questions were aimed at understanding the organization of any career transition programing they may have had during their athletic career (e.g., “Did your university have an athletic career transition program or workshop? And “How often did this program occur at your university?”) as well as understanding their demographics (e.g., “What is your age” “What sport did you play”).  year were you when you participated in this program?). To better understand their experiences and truly give the participants a chance to process their experiences in their own words, open-ended questions were used. Example questions included “What was your athletic career transition experience like?,” “How did transitioning from sport make you feel?” and “During your transition experience, what did you do/not do to cope?

Procedures

Data Analyses

 A six phase Reflexive thematic approach was used with the essentialist/realist method for qualitative data (19-22). This method is used to identify, analyze, and report patterns (themes) within a given data set. Additionally, it is used to describe and interpret the meaning and importance of the patterns (themes) found. The Essentialist/Realist method is used to report experiences, meanings, and the reality of participants (19), which was used to analyze the perceptions and personalized experiences from former collegiate athletes. Of importance for this approach is to acknowledge that we all perceive the environment and impact it through those perceptions. Therefore, giving as much room for the exact voice of the participants is needed to minimize the participants experiences being reported through the researcher’s lens alone. Therefore, this paper gives significant space to each participant’s voice, which is possible due to the sample size of six people. Utilizing the ‘top-down approach’ also known as deductive approach (23), this study analyzed semantic themes that are suggested within previous career transition literature to implement into athletic career transition programming for student athletes However, ideas that emerged that did not fit within current literature were also noted and coded to add to the already existing literature. In qualitative research, the researchers and coders must assess their biases and perceptions as it relates to the research topic. In this study, the data was coded by two coders, the primary researcher, a former collegiate athlete whose career ended two years before data analysis recognized that her own experiences were a potential bias to the study. Therefore, several methods of checking trustworthiness were used (See Trustworthiness section below). The second coder was not involved in the study at all and was not a former collegiate athlete, nor were they familiar with the literature in the area.

Following the guidelines of Braun and Clarke (19-23) both coders followed a six-step process. Prior to coding all interviews were electronically transcribed using zoom transcription services, and all transcriptions were checked for accuracy against the recorded interviews. To start the coding process both coders familiarized themselves with the data by reading all the transcripts. The coders then independently recorded points of interest in the transcripts as they began to generate the initial codes, making sure to code each piece of data available. Data could be an individual word (e.g., the answer “yes” to a closed question) or as long as a few sentences (e.g., “Even though I did not struggle a lot, I think it still would have been nice to have a transition program in those later years of college just to learn how to be an adult on your own without sports ruling your life”). Focusing on the context of a comment opposed to the length when deciding on a code was done in line with the recommendations of past researchers (e.g., 20). Next, coders began to develop themes with past research in career transition in mind. Again, this deductive approach did not mean discarding data that did not fit in a prior identified theme, but instead recognized past information while new themes that emerged were also identified and titled with this new information being an addition to our current understanding of the career transition experience in the field. The coders then compared their codes and themes and when in disagreement engaged in thoughtful discourse explaining their rationale for their coding choice, while being cognizant of their potential biases. This process led to agreement between the coders in the few places where there was initial disagreement. Finally, the overall themes and codes are explained in detail in this manuscript as is noted as an important step in thematic analysis.

Trustworthiness

Trustworthiness was assessed in multiple ways to increase the credibility, transferability, dependability, and confirmability of the study (19-22;24, 25). In addition to an acknowledgement of the researcher’s viewpoint and the reality that all researcher’s perspective’s impact their analysis, both coders of the data assessed their own views and were systematic in assessing the impact of these views throughout the research. Furthermore, as the lead researcher of this study was a former NCAA athlete, and as such recognized that this may have led to potential biases peer debriefing was used to increase credibility. Furthermore, a third coder, who was familiar with the research in the field but did not conduct the interviews or participate in the original data analysis was brought in to engaged in negative case analysis to assess any divergent data and discuss these findings to make sure they were appropriately accounted for in the data coding. Internal auditing was also done by two researchers who were not a part of this study, nor familiar with the research on career transition in sport, to highlight and address any potentially biased interpretations of the data. The detailed documentation of the procedures used for this study at each stage following the guidelines of the APA Journal Article Reporting Standards for Qualitative Research (2018), along with using thick description in this manuscript was done to increase dependability and transferability.
Results
The major themes that emerged throughout the data were lack of athletic career transition programming, high athletic identity, lack of psychological support, social support, coping mechanisms and the Covid-19 pandemic. Note that participants’ names have been changed to maintain confidentiality. Pseudonyms given are representative of names that match the self- reported gender and race of each participant.

Lack of Athletic Career Transition Programming

It was found that four out of six participants experienced a positive overall career transition from athletics and described their experience as ‘easy’ and ‘smooth sailing.’ However, two of the participants in this study experienced a negative overall career transition from athletics. When it came to access to career transition programming, only two of the participants had access to transition programs from their universities. Example comments related to this are included Leah commenting, ‘I don’t even know where to begin, I felt so unprepared to go out into the world.’ and Andrea stating, ‘My transition experience was a little rocky and it had an effect on how I was mentally.’ Mary said, ‘Even though I did not struggle a lot, I think it still would have been nice to have a transition program in those later years of college just to learn how to be an adult on your own without sports ruling your life.’ Two participants recalled their athletic departments referring them to their on-campus career center for career assistance. For example, Kelly noted, ‘The programs that were available to me via the career center were focused on interviewing skills, portfolio/resume building and career fairs; none of these events catered to my athletic experience.’ Andrea who did have access to career transition programming, indicated that their school had the NCAA Life Skills Program (NCAA, 1994). She stated, ‘I definitely found this program to be helpful and I felt as though I needed those skills to be able to transition from college into the outside world.’ Although Andrea spoke highly of the Life skill program at her previous university, she still reported a negative transition due to the COVID-19 pandemic. Chance recalled his previous athletic department hosting optional career transition programming that he did not attend due to the programs conflicting with his schedule. ‘I felt like it would have been helpful, I just did not feel like I had the time to do it with athletics and my class schedule.’ When looking at the differences between programming across the three different division levels present in this study, both Andrea and Chance were in Division I programs. Chelsea, who participated within Division III stated, ‘We weren’t provided with a lot of resources being the lower level and I think it had to do with finances as well as compliance.’

When asked what participants would value within athletic career transition programming, participants noted the importance of programming on financial topics (budgeting, taxes, financing vehicles and homes), programs for juniors and seniors on resources for transition. For example, Chelsea stated, I think a big topic that needs to be talked about in depth is financials because as an athlete, you spend a lot of your time on the road, and you don’t necessarily go out all of the time to spend money because you are giving per- diem and gear etc. When you are not an athlete, you are not provided with those things anymore.

As well as making programming more accessible,

 I think it would be helpful to make the programs more available for everybody else. I wasn’t able to attend some of the programs because I had night classes during the times, they had the events. ‘I also think having programs that teach athletes about finances could be helpful; specifically on financing things, insurance and buying a home. (Chance)

Implementing mentorship programming was noted by the athletes with this quote by Kelly being a good representation of the athletes’ comments ‘I think having talks that help athletes learn how to speak about their skills and how to speak about that when interviewing for jobs.’ ‘I also think it would be great to bring back sport alumni and have them speak to current athletes about their careers.’ Additionally, it was also recommended that athletic departments speak to athletes about degrees and course choices that suit that athletes’ interests. Leah noted ‘I wish my academic advisor helped me more with what I could do with my degree after I graduated.’ ‘I feel like the focus was for me to get classes that worked around my practice schedule mostly.’

High athletic identity

             With years devoted to excelling within sport, many athletes find themselves identifying as an athletic individual even when their sport career ends (9). This finding was supported by the reflections from the participants in this study. Five out of six participants indicated they still identify as an athlete and considered themselves athletic. Chelsea noted, ‘I still try to live an athletic style similar to how I was when I was a competitive athlete’, while Chance noted ‘I still identify as a former athlete who still does athletic things.’ – and Leah said, ‘I still resemble as an athlete just because I’m still in shape and I’m still basically active.’ Of note, half of the participants in this study transitioned out of sport and into a career within or surrounding athletics. These participants openly discussed how this allowed them to stay identified within sport culture. For example, Kelly said ‘I now identify as a coach, which gives me sport identity; making it easier to take away the athlete part of me, but that identity is still very much part of who I am.’ Chelsea commented ‘I work within an athletic department and am still around sport every day. I enjoy that part of my job’ and Mary said,

After college I became a graduate assistant for an athletic department and it’s nice to still being in the sports world because I am still constantly around athletics.’ ‘The best thing about being a college athlete is you definitely have like a foot up; I feel like in a lot of the career world.

Two participants discussed the transferability of the skills they learned as athletes, and how these gave them an advantage throughout the job search process. For example, Chance said ‘Just from my experience playing in college athletics, it helped me in terms of interviews and getting in the position to get a job.’ When asked what skills from sport helped him get his current position, he discussed leadership, communication, teamwork/collaboration, and confidence. He commented, ‘Leadership and communication; these were big for coming out of college athletes. I think it helped. As well as just like you get the confidence for like playing in front of people, so that helped with confidence and interviews and everything like that.’ ‘Being able to do team work as well; a lot of jobs like that as you obviously have to work in teams and collaborate with other people within your company.’

Lack of Psychological support

Although the strength and exclusivity of the athletic role during sport participation may increase an athlete’s potential vulnerability to psychiatric distress after leaving sport (11), none of the participants reported experiencing athletic career transition programming that addressed the psychological effects that a transition can have on a sport individual. Although only one participant expressed experiencing mental health difficulties during her transition, five out of six participants spoke on the need for mental health to be addressed in athletic career transition programming. For example, Kelly noted,

“I think having a mental health professional to provide tools and be real with athletes, like hey it is not going to be a smooth sailing process once you finally hang up the cleats, here are some tools to help you cope with this process better.”

 Leah on the other hand focused on the importance of wellness checks, ‘I do believe that for athletes who will transition, psychologists should come in and do a wellness check or just be an ear for somebody would be an amazing thing because college athletics is a mental trip.’

Coping

Coping strategies are used to help student athletes better adjust to sport retirement. Participants in this study reported that they coped with their transition out of sport by finding ways to get their mind off this process. Chelsea said, ‘I definitely did try to find ways to get my mind off of the fact that I’m not going to practice.’ Mary noted, ‘You try and find outlets you know, to still be competitive and find other ways to use your talents but it takes a little bit of time to find those things’ while Andrea stated, ‘I exercised to relieve the stress I had and that helped a lot.’ Although some of the participants found positive ways to cope with their transition, one participant utilized negative ways to cope with their transition. Leah said, ‘I was being real nonchalant. I was trying to like mask it with everything will work out fine, but I was panicking.’ During this time, she mentioned that she participated in drinking alcohol and smoking. She said, ‘another way that I coped truthfully during that time in all honesty; was drinking and smoking. I was like a spiral, like I did not know what to do.’ None of the participants indicated experiencing programming that spoke on positive ways to cope with transitioning out of athletics. By implementing this in programming, negative coping mechanisms during transitions can be prevented.

Social Support

             During athletic transitions, the participants utilized social support and informal information given to them about the transition process before and during their journey. It was found that the participants recalled receiving support from coaches, athletic advisors, family, and friends. Although the participants in the study did not receive as much support within their athletic departments, it was noted that they all utilized their social networks as support systems during their transitions. Andrea said, ‘I definitely needed some social support and I talked to my coach. He would hit me and just ask me if I was doing okay and stuff like that.’ Kelly stated, ‘I connected with my coaches a lot about the transition process as a player and my plans to pursue coaching as a career’ and ‘My coaches had a good grasp on what transitioning was like especially when they have played sport for so long.’ Kelly also noted the importance of friends and family, ‘My friends and family were also a good support system.’ The role of professors was also noted, ‘The professors I interacted with were very helpful to prepare me for what comes next, and I had an older sibling that played college sports, so I definitely relied on help from him.’

Covid-19 Pandemic

             The final theme that emerged from the data and affected two out of six participants in the year 2020 was the Covid-19 pandemic. The pandemic for the year 2020 ended college sports prematurely causing more athletes to experience a traumatic end to their athletic season and for some, a traumatic end to their athletic careers. The participants in this study who experienced this expressed not being supported by their athletic departments which increased their feelings of not being prepared for what was next for them. For example, Leah stated, ‘We were told that we weren’t going to get our season and that was it; our season was stripped away.’ When asked if there were any resources or emotional support provided for her, she said she could not recall any. She did reflect on being offered an extra season, which would grant her a fifth year of eligibility. She said she declined this opportunity in hopes of being able to put more time towards starting her career. Andrea, whose transition experience was also affected by the pandemic described her athletic career as ending suddenly, which took a toll on her mental health. She stated, ‘I never had anybody to talk to about how to move forward or continue on with the degree I earned.’ ‘I just remember thinking, what am I going to do next?’ ‘We never had a good closing statement.’ When asked if there were any resources or emotional support available to her, she recalled her athletic advisor reaching out to her via email and text message but decided to not respond due to feeling overwhelmed.

Discussion

             This study examined athletic career transition programming within the NCAA through the perceptions of former student athletes. Additionally, the impact of an athletic career transition was further explored. The results from this study provide evidence that athletic departments may not be using best practices to better support student athletes in their transition out of collegiate athletics (2). From these findings, participants received little to no programming specific to how retiring from sport affects an individual psychologically, emotionally, behaviorally, and socially as well as how it affects their overall identity (5,7,8,9). The data further shows that athletic departments may not be listening to what the research says (5) should be implemented into programming; thus, demonstrating that athletic departments may not be prioritizing the overall well-being of student athletes. Past literature has continuously encouraged practitioners within athletic departments to include programming to provide student athletes the tools to adjust to sport retirement (4) and with the lack thereof, student athletes can potentially experience more negative reactions to retiring from collegiate sport (1,11,12).

 The findings of this study were consistent with previous research with there still being a lack of consensus of what is told to student athletes about the transition process (2) shown throughout the perceptions of the former student athletes in this study. The themes (i.e., athletic career transition programming, athletic identity, psychological impact, and coping) from past research re-emerged when the participants were asked to reflect on their overall transition experience. Two additional themes that emerged were social support and the Covid-19 pandemic. Social support was not surprising as past literature has suggested it to be a positive coping mechanism for athletes in transition (7). However, the Covid-19 pandemic was a unique theme that has not often been discussed regarding athletic retirement. This provides a unique perspective to the overall findings. The perceptions of participants personal athletic transition experiences from collegiate sport were also consistent with previous literature in that most participants still resonated with the athletic role (athletic identity) (e.g., 9, 11,12), experienced mixed feelings about transitioning support and would have appreciated psychological support (8,12); utilizing positive and negative coping mechanisms and used social support networks that were available to them (7,8). With the difficulties and challenges of the unprecedented pandemic, this may have further exacerbated the lack of proper resources for student athletes transitioning from collegiate sport. This further provides evidence that proper exit strategies must be implemented within athletic departments for collegiate student athletes (5).

Limitations & Future Research

There were limitations to this study that should be discussed. The findings were derived from a participant sample consisting primarily of women or individuals that competed within the Division I level. The lack of participants from other divisions did not allow for comparison across divisions. Furthermore, although interviewing only six participants led to the ability to give each participant a voice in this paper, it was a small sample making it impossible to make set inferences on this data alone. Instead, these results should be seen as an additional piece of information, along with past research findings, that can be used for best practice in career transition. With the structured interviews conducted primarily over zoom, this may have impacted the participants openness to disclose sensitive information due to the interview format. This was demonstrated by one participant disclosing confidential information related to their mental health after the interview process was completed, and the recording of the zoom appointment stopped. Future research should consider replicating this study with an in-person structured interview, with a more diverse and larger participant sample. Future studies should consider looking at the differences in athletic career transition programming implemented within all division levels of the NCAA qualitatively.

Conclusions Implications for Practice

The purpose of this present study was to investigate if current career transition programs in NCAA Athletic Departments are using best practices, as defined by the current research in the field, based on former collegiate athlete’s perceptions of their experience with career transition programming. A secondary and equally important purpose was to investigate the overall impact athletic career transition has on former collegiate athletes’ lives. The findings of this study provided evidence on the overall impact transitioning from collegiate sport has on an athletic individual and along with past research highlight the lack of athletic career transition programming implementation into athletic departments. These findings add to the evidence that suggests that professionals should be creating programs and psychoeducational interventions that include how the transition affects an athlete psychologically, socially, emotionally, behaviorally, and how it affects their overall athletic identity, per previous athletic career transition literature. Furthermore, professionals should implement psychological support for athletic career transitions from qualified staff, programming that gives student athletes tools on mental health resources, programming on positive coping mechanisms, programming to student athletes on financial topics (e.g., budgeting, financing, housing, taxes) and implementing mentorship programs that feature student athlete alumni. Additionally, these findings support the recommendation that practitioners should consider making programming accessible to all student athletes with various schedules by having programming for student athletes in person and virtually if possible. Lastly, practitioners within athletic departments should consider receiving feedback from former student athletes like this study, to ensure that the programming implemented is using best practices to better support student athletes. It is with hope that the findings of this study encourage practitioners within NCAA athletic departments to implement effective athletic career transition programming that will provide student athletes the tools to properly prepare for the transition out of collegiate athletics.

References

  1. Weigand, S., Cohen, J., & Merenstein, D. (2013). Susceptibility for depression in current and retired student athletes. Sports Health: A Multidisciplinary Approach, 5(3), 263–266. https://doi.org/10.1177/1941738113480464
  2. Leonard, J. & Schimmel, C. (2016). Theory of Work Adjustment and Student Athlete Transition out of Sport. Journal of Issues in Intercollegiate Athletics, 9, 62-85.
  3. Hansen, A., Perry, J., Ross, M., & Montgomery, T. (2018). Facilitating a successful transition out of sport: Introduction of a collegiate student-athlete workshop. Journal of Sport Psychology in Action, 10(1), 1–9. https://doi.org/10.1080/21520704.2018.1463329
  4. National Collegiate Athletics Association. (2022). Research. Retrieved from https://www.ncaa. org/research
  5. Lavallee, D., Park, S., & Taylor, J. (2014). Career transition among athletes: Is there life after sports? In J. M. Williams, & V. Krane (Eds.), Applied sport psychology: personal growth to peak performance (7 ed., pp. 490-509)
  6. Miller, L., & Buttell, F. P. (2018). Are NCAA Division I athletes prepared for end-of-athletic-career transition? A literature review. Journal of Evidence-Informed Social Work, 15(1), 52–70. https://doi.org/10.1080/23761407.2017.1411305
  7. Adams C, Coffee P, & Lavallee D (2015) Athletes’ perceptions about the availability of social support during within-career transitions. Sport and Exercise Psychology Review, 11(2), pp. 37-48.
  8. Cummins, P., & O’Boyle, I. (2014). Psychosocial factors involved in transitions from college to post-college careers for male NCAA Division-1 basketball players. Journal of Career Development, 42(1), 33–47. https://doi.org/10.1177/0894845314532713
  9. Lally, P. S., & Kerr, G. A. (2005). The career planning, athletic identity, and student role identity of intercollegiate student athletes. Research Quarterly for Exercise and Sport, 76(3), 275–285. https://doi.org/10.1080/02701367.2005.10599299
  10. Webb, W. M., Nasco, S. A., Riley, S., & Headrick, B. (1998). Athlete identity and reactions to retirement from sports. Journal of Sport Behaviour, 21(3), 338–362.
  11. Giannone ZA, Haney CJ, Kealy D, Ogrodniczuk JS. (2017). Athletic identity and psychiatric symptoms following retirement from varsity sports. International Journal Social Psychiatry, 63(7):598-601. https://doi:org/10.1177/0020764017724184.
  12. Grove, J. R., Lavallee, D., Gordon, S., & Harvey, J. H. (1998). Account-making: A model for understanding and resolving distressful reactions to retirement from sport. The Sport Psychologist, 12(1), 52–67. https://doi.org/10.1123/tsp.12.1.52
  13. Cabrita, T. M., Rosado, A. B., Leite, T. O., Serpa, S. O., & Sousa, P. M. (2014). The relationship between athletic identity and career decisions in athletes. Journal of Applied Sport Psychology, 26(4), 471–481. https://doi.org/10.1080/10413200.2014.931312
  14. Menke, D. J., & Germany, M.L. (2018). Reconstructing athletic identity: College athletes and sport retirement. Journal of Loss and Trauma, 24(1), 17–30. https://doi.org/10.1080/15325024.2018.1522475
  15. Stephan, Y., Torregrosa, M., & Sanchez, X. (2007). The body matters: Psychophysical impact of retiring from elite sport. Psychology of Sport and Exercise, 8(1), 73–83. https://doi.org/10.1016/j.psychsport.2006.01.006
  16. Kerr, Z. Y., DeFreese, J. D., & Marshall, S. W. (2014). Current Physical and Mental Health of Former Collegiate Athletes. Orthopedic Journal of Sports Medicine, 2(8), 232596711454410. https://doi.org/10.1177/2325967114544107
  17. Wylleman, P., Alfermann, D., & Lavallee, D. (2004). Career transitions in sport: European perspectives. Psychology of Sport and Exercise, 5(1), 7–20. https://doi.org/10.1016/s1469-0292(02)00049-3
  18. McKnight, K. M., Bernes, K. B., Gunn, T., Chorney, D., Orr, D. T., & Bardick, A. D. (2009). Life after sport: Athletic career transition and transferable skills. Journal of Excellence, 13, 63-77.                     
  19. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  20. Braun, V., Clarke, V., & Weate, P. (2016). Using thematic analysis in sport and exercise research. In B. Smith & A. Sparkes (Eds.), Routledge handbook of qualitative research methods in sport and exercise (pp. 191–205). London: Routledge. 
  21. Braun, V., & Clarke, V. (2012). Thematic analysis. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D.  Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology, Vol. 2. Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 57–71). American Psychological Association. Doi.org/10.1037/13620-004 
  22. Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589-597, doi; 10.1080/2159676X.2019.1628806 
  23. Boyatzis, R. E. (1998). Transforming qualitative information: Thematic analysis and code development.
  24. Lincoln, YS. & Guba, EG. (1985). Naturalistic Inquiry. Newbury Park, CA: Sage Publications. 
  25. Nowell, L.S., Norris, J.M., White, D.E., Moules, N.J. (2018). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16, 1609406917733847. https://doi.org/10.1177/1609406917733847
2024-08-23T10:19:26-05:00August 16th, 2024|Research, Sport Education, Sports Studies and Sports Psychology|Comments Off on Perceptions of Former Collegiate Athletes on Career Transition Programs in the NCAA
Read More

Navigating Darkness: College Athlete Suicide, Support Systems, and Shadows of Depression

Authors: Matt Moore, Ph. D, MSW 1, Anne M. W. Kelly, Ph. D 2, Lana Loken, Ed. D. ATC 2, Mastano N. Dzimbiri, MS 1, Payton Bennett, student

Corresponding Author:

Matt Moore, Ph. D, MSW
Chair and Faculty, Family Science and Social Work Department
Miami University
501 E. High Street
Email: [email protected]

Coaches’ Perspectives of the Influence of Safe Sport-Related Education 

ABSTRACT

Purpose: An increase in mental health concerns and suicide among young adults led to a sharpened research focus on suicide and college athletes. In this study, we investigated the relationship between college athletes’ risk of depression, suicidality, and their support system and whether preventing suicide deaths requires identification of commonly cited risk factors. Methods: Voluntary college athletes aged 18-years-old or older and attending an NAIA member institution participated in the study (n = 361). They completed a web-based instrument that consisted of the following: (1) demographic questionnaire, (2) Patient Health Questionnaire (PHQ-9), (3) Berlin Social Support Scale, and (4) Columbia Suicide Severity Rating Scale. Results: Between 5-18% of college athletes responded affirmatively to one of the questions asking about suicidality. There was a significant moderate negative correlation between the suicide predictor and the PHQ-9 score and significant weak positive correlations between the suicide predictor and perceived emotional support and between the suicide predictor and perceived instrumental support. Conclusion: This study identified findings that might be useful to practitioners and opened new lines for future research. Applications in Sport: College athletic programs and university counseling centers are poised to enhance our understanding of student-athletes’ suicidal distress and how to respond by making use of qualitative research methods. We strongly recommend adopting this strategy to address depression and suicidal ideation.


Keywords: prevention, student-athletes, mental health, risk factors

Introduction
Despite growing openness about mental health struggles, a disparity still exists between physical and mental health (Gorczynski et al., 2023; Moore et al., 2022), fostering stigma and hindering help-seeking behavior (Moore, 2017), particularly among college students (Centers for Disease Control and Prevention [CDC], 2021). While mental health diagnoses in the college student population is a longstanding challenge, the COVID-19 pandemic increased stressors placed on the college student population leading to increased risks (Gupta & Agrawal, 2021; MacDonald & Neville, 2023).


According to the CDC (2021), mental health concerns and suicidal thoughts are increasing for youth and young adults. Forty percent of those surveyed showed signs and symptoms of depression and 20% said they had thoughts of suicide. These trends are similar to studies on college student mental health and suicidality (Barclay et al., 2023; Schmiedehaus et al., 2023). According to the Substance Abuse and Mental Health Services Administration (SAMHSA, 2017) individuals aged 18-25 reported a 3% increase in major depressive episodes from 2015-2017. Additionally,18.9% of individuals 18 and above reported experiencing a mental illness in the past year, with 7.5% reporting a serious mental health illness (SAMHSA, 2017). A second SAMHSA (2021) study found 33.7% of individuals aged 18-25 reported a mental illness and 11.4% reported a serious mental illness.
In addition to concerns about serious mental health illness, SAMHSA (2021) found an increase in rates of suicidal behavior. Specifically, 10.5% reported having serious thoughts of suicide, 3.7% created a suicide plan, and 1.9% attempted suicide. Research by Rosenthal et al. (2023) found higher rates with 13.7% of college students reporting suicide ideation, 7.6% making a suicide plan, and 3.2% reporting at least one suicide attempt. In 2021 suicide became the leading cause of death for those aged 20-24 (CDC, 2023).
One subset of the college student population is college athletes. Recently, discussion of their mental health increased. Researchers attempted to explore the intersectional identity of student athletes and the effect that this role strain may have on mental health (Gorczynski et al., 2023; Moore et al., 2022). Quantifying mental health and suicide risk in this group is challenging, with conflicting results on the link between depression, support systems, and suicide. Many researchers see sport participation as a protective factor for mental health risk due to the social support provided by the team (Hui et al., 2023; Sullivan et al., 2020). But additional pressures like failure to successfully compete or live up to expectations, loss of social structure due to injury or retirement from sport, or time demands of the sport in addition to being a college student can increase the risk (Moore, 2017; Moore et al., 2022). This study builds upon existing research by looking more closely at the relationship between a college athletes’ risk of depression, suicidality, and their support system.


College Athletes and Depression
According to the American Psychological Association (2020), depression is one of the most common mental health disorders in the United States. Depression might include emotional, cognitive, physical, and/or behavioral symptoms and is best understood on a continuum of severity, rather than either present or not present. Findings amongst college athletes demonstrate that depression rates align with rates of the general population of college students (hovering around 25%) (Prinz et al., 2016; Wolanin et al., 2016), and some revealed that athletes have higher rates of depression (over 30%) than the general population (Cox, 2015). While many studies find similar rates between college athletes and their non-athlete peers, others show participation in college athletics can decrease one’s risk for depression (Banu, 2019; Salehioan et al., 2012).
Although some research shows athletic participation may protect against mental illness, there is still reason for concern for college athletes. A current study by the National Collegiate Athletic Association (NCAA, 2022) surveyed almost 10,000 NCAA athletes from all three competitive division levels. Results showed athletes of all competition levels demonstrated elevated levels of mental exhaustion, anxiety, and depression. These levels were nearly two times higher than pre-pandemic levels. The top three factors negatively affecting mental health were academic worries (44%), planning for the future (37%), and financial worries (26%). Only 50% of college athletes believed mental health was a priority for their athletic department, 33% of college athletes did not know where to go to seek mental health services, and as many as 17% of college athletes reported feeling hopeless.


College Athletes and Suicide
Suicide risk in athletes is difficult to determine due to underreporting and misclassification of many sudden deaths. Over the past two decades the NCAA attempted to determine the risk of suicide specific to college athletes. Rao et al. (2015) reported that 7.3% of all athlete deaths were suicides, making suicide the fourth leading cause of death for college athletes. Previously, Miller and Hoffman (2009) found approximately 5% of student-athletes contemplated suicide. Much like research on college athlete depression, some research demonstrates sport protects against suicidality (Maron et al., 2014). This study’s findings highlight the importance of promoting participation in diverse sporting activities among college students given that engaging in such activities safeguards against depression and suicidal ideation by nurturing self-esteem and bolstering social support.


College Athletes and Social Support
The discrepancy in the literature may be accounted for by the supports that are available to college athletes and their willingness to seek such supports (Sullivan et al., 2020). One of the most discussed supports is the team environment. Sullivan et al. (2020) analyzed the effects of social supports on depressive symptoms in college athletes. They found emotional support from teammates, family, and friends was correlated with a decrease in depressive symptoms. Other more formal or instrumental supports that reduced depression included the availability of tutoring and health services, including mental health providers with specialization with athletes.
Social support has not been as extensively studied in the college athlete population. Studies show links between social support and burnout as well as social support and overall wellbeing in college athletes (Defreese & Smith, 2014). Research identified social support as an important component in allowing athletes to balance school and athletics (Carter-Francique, 2015). Many college athletes have strong social support networks naturally, such as relationships with teammates, coaches, medical staff, and other resources provided by the athletic department (Armstrong & Oomen-Early, 2009). They also have supportive relationships, such as family and friends, outside of athletics.
Despite knowledge of these available supports and benefits they offer college athletes, exploring the utilization of built-in athletic supports and personal supports unique to an individual athlete remains understudied. Much of the research tends to oversimplify social support. Due to its dynamic and complex nature, social support among college athletes merits further investigation. Research has not examined the differences in the type of perceived social support in collegiate athletics as it relates to levels of depressive symptoms and suicidality.

Present Study
Overall, the research on mental health issues, including depression and suicide in collegiate athletes is inconclusive. More research is needed to determine what factors put athletes at risk for severe mental health concerns and suicide. The purpose of this study was to investigate whether there is a relationship between levels of depression and suicide risk and levels of social support among National Association of Intercollegiate Athletics (NAIA) college athletes. The NAIA does not have data available on connectedness between depression, social support, and suicide.

Methods

Procedures

Research Design
The current exploratory study utilized a cross-sectional, web-based survey design to gather data from NAIA college athletes. Considering the size of the NAIA student-athlete population, confidence level, confidence intervals, statistical test, and statistical power, the minimum sample for this study was 47 college athletes (Faul et al., 2007). Researchers identified athletic trainers through the NAIA database to establish contact information. Athletic trainers provided survey information to their assigned college athletes. This approach was successful in other NAIA research efforts (Moore & Abbe, 2021).


Sampling
The exploratory study utilized a stratified random sampling procedure to identify college athlete participants. Researchers divided the NAIA college athlete population into subgroups, or strata, based on sports available throughout the NAIA. This included a stratum for each of the 17 sports with separate stratum for each gender that participates in a sport. Next, researchers identified NAIA member institutions that participated in each of the 17 sports. Each institution participating in a sport received a random number. Researchers selected random numbers to identify the member institutions that would participate in the survey from each sport. This approach ensured all member institutions participating in various sports had an equal opportunity for inclusion.


Participants
Voluntary college athletes aged 18-years-old or older and attending an NAIA member institution participated in the study (n = 361). Most participants were 18-21 years old (53.5%, 46.5% indicated being over the age of 21). Survey participants were primarily juniors (30.7%, 23.8% sophomores, 23.1% first years, 22.1% seniors of graduate students). More women completed the survey (59.8%, 40.2% men). Most participants who reported race/ethnicity were White/Caucasian (55.4%, 21.9% Hispanic or Latino, 14.9% Black or African American, 6.6% multiracial, 1.2% from other groups).

Table 1.

NAIA Institutional Demographic Information

University Demographic%
Private20.2%
Public79.8%
Suburban33.3%
Urban33.9%
Rural32.8%
Faith Based62.9%
Non-Faith Based37.1%


Participants recorded which NAIA athletic team they were primarily affiliated with (20.2% baseball, 19.9% soccer, 12.5% track volleyball, 8.0% softball, 6.4% cross country, 6.1% basketball, with all other sports being under 5% each [e.g., football, bowling, cheer, dance, track and field, swimming and diving, golf, tennis, and lacrosse]). Participants were further examined regarding NAIA college/university demographics (See Table 1). Participants also responded to whether or not they receiving mental health training from their college of university before participating in sport. The largest majority (n = 229, 63.7%) indicated they did not receive such training. The other 36.3% (n= 132) indicated they did receive some form of training.
[Insert Table One]

Measures and Instruments

College athletes completed a web-based instrument that consisted of the following: (1) demographic questionnaire (see above demographics), (2) Patient Health Questionnaire (PHQ-9; Kroenke et al., 1999), (3) Berlin Social Support Scale (BSSS; Shulz & Schwarzer, 2003), and (4) the Columbia Suicide Severity Rating Scale (C-SSRS; Posner et al., 2011).

Patient Health Questionnaire (PHQ-9)
The PHQ-9 is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders (Kroenke et al., 2001). It is used to make criteria-based diagnoses of depressive and other mental disorders commonly encountered in primary care. This is a 9-item depression module upon which the diagnosis of Diagnostic and Statistical Manual (DSM) depressive disorders is based. Reliability and validity of the tool have indicated it has sound psychometric properties. Internal consistency of the PHQ-9 has been shown to be high (American Psychological Association, 2020). There is precedent for using the PHQ-9 in research with college athletes (DaCosta et al., 2020; LoGalbo et al., 2022).

Berlin Social Support Scale (BSSS)
The researchers measured the degree of emotional and tangible support using the BSSS (Schulz & Schwarzer, 2003). This scale measured perceived emotional and instrumental supports, need for support, and support seeking. There are 17 items on the BSSS that are answered using a five-point Likert scale with endpoints “1 = Strongly Disagree” and “4 = Strongly Agree.” The researchers used a mean score for each of the subscales (perceived emotional support, perceived instrumental support, need for support, and support seeking). The scale has a Cronbach’s alpha of 0.83 for perceived social support, 0.63 for need for support, and 0.83 for support seeking (DiMillo et al., 2017). The scale has a prior history of use within college athletics (Sullivan et al., 2020)


Columbia Suicide Severity Rating Scale (C-SSRS)
The C-SSRS was developed by researchers from Columbia, Pennsylvania, and Pittsburgh Universities to evaluate suicidal ideation and behavior (Posner et al., 2011). The scale provides a brief assessment of severity and intensity of suicidal ideation, suicidal behavior, and lethality (Syndergaard et al., 2023). The screener version used in this study consisted of six “yes” or “no” questions. Based on participant responses to the six questions, participants were considered low, moderate, or high risk. The C-SSRS has excellent internal consistency (α = 0.95). Principal components analysis revealed a two-factor solution, accounting for 65.3% of the variance across items (Madan et al., 2016). There is limited research on the use of the C-SSRS with the athlete population (Costanza et al., 2021).


Data Collection
Researchers contacted the athletic training staff at all sampled NAIA member institutions. Athletic training staff received the list of teams from their institution for inclusion in data collection. Researchers provided athletic training staff detailed instructions for data collection and a copy of the informed consent. Athletic training staff distributed the electronic survey to their college athletes. College athletes were able to opt-out of the survey at any time. The survey took approximately 15-20 minutes to complete. Researchers recorded survey results into a statistical software program (SPSS 28) on a secure, private platform.

Data Analysis
Researchers utilized descriptive statistics to provide details about the sample and overall survey results. Researchers used inferential statistics to infer information from the sample data to the overall NAIA student-athlete population.

To investigate the first research objective, an initial correlation analysis was conducted to examine whether having any safe sport training was related to increases in coaching outcomes. The safe sport training variable was transformed so that coaches who answered “yes” to completing any of the safe sport training courses were coded as 1 and coaches who had answered “no” to completing all the safe sport training courses were coded as 0 (i.e., no SS training=0, any SS training=1). This variable was included in a correlation analysis with all coaching outcomes: knowledge & confidence, safe sport stress, stress over athlete well-being, and efficacy to support others. To investigate the second research objective, four separate linear regression models were constructed with the sum of completed safe sport training courses (range =1-12) as the independent variable, and the following coaching outcomes as respective dependent variables: knowledge & confidence, safe sport stress, stress about athlete well-being, and efficacy to support others. In all four models, the coaching context, whether training was required (0=no, 1=yes), and whether training was free (0=no, 1=yes) were included as covariates. To address the third research objective, ANOVAs were conducted with individual safe sport courses as independent variables, and the following coaching outcomes as dependent variables: knowledge & confidence, efficacy to support others, safe sport stress, stress about athlete well-being and efficacy to support others. All analyses were conducted using IBM SPSS Statistics (Version 28) (20).

Results

Results
Descriptive Statistics
College athletes answered each item from the C-SSRS. Descriptive findings from this scale indicated that 18.3% of participants wished to be dead, 18,3% had non-specific active suicidal thoughts, 13.6% had active suicidal ideation without intent to act, 6.1% had active suicidal ideation with some intent to act, and 5.0% had active suicidal ideation with a specific plan and intent to act. Of the 361 college athlete respondents, 25.8% answers “yes” to at least one of the questions on the scale.

College athletes completed the PHQ-9 as a brief screening tool for potential depressive symptoms. Results of the PHQ-9 and the percent of athletes at risk of depression for each item can be found in Table 2.

Table 2. PHQ-9 Scores for NAIA College Athletes

QuestionMean (SD) (% At Risk)
Little interest or pleasure in doing things?1.81 (0.91) (22.1%)
Feeling down, depressed, or hopeless?1.68 (0.81) (14.1%)
Trouble falling asleep or sleeping too much?2.06 (1.05) (30.2%)
Feeling tired or having little energy?2.17 (0.92) (29.1%)
Poor appetite or overeating?1.81 (0.96) (21.3%)
Feeling bad about yourself?1.75 (0.93) (18.6%)
Trouble concentrating on things?1.69 (0.96) (17.2%)
Moving or speaking so slowly that people could have notice? Or more fidgety and restless than usual?1.34 (0.69) (7.8%)
Thoughts that you would be better off dead?1.21 (0.53) (4.1%)

Evaluation of Assumptions

College athletes also completed the BSSS. Results of the BSSS and the percent of athletes at risk of limited social support in various areas can be found in Table 3. These are only the scale items where there were significant concerns about perceived emotional support, perceived instrumental support, need for support, and support seeking.

BSSS Scores for NAIA College Athletes

QuestionMean (SD) (% At Risk)
Whenever I am not feeling well, other people show me that they are fond of me? 3.14 (0.82) (17.2%)
When everything becomes too much for me to handle, others are there to help me?3.21 (0.83) (18.3%)
I get along best without any outside help?2.48 (0.81) (48.7%)
In critical situations, I prefer to ask others for their advice?3.00 (0.79) (23.0%)
Whenever I am down, I look for someone to cheer me up again?2.51 (0.89) (49.6%)
When I am worried, I reach out to someone to talk to?2.69 (0.93) (38.2%)
Whenever I need help, I ask for it.2.70 (0.96) (39%)


Researchers used correlation analysis to assess the relationship between a college student-athletes predictor of suicide with their score on the PHQ-9, perceived emotional support, perceived instrumental support, level of needed support, level of support sought, and mental health training.

Prior to conducting the analysis, researchers generated several statistics and graphs to examine the tests of assumption, including level of measurement, related pairs, absence of outliers, and linearity.


Results of the Correlational Analysis
Researchers computed a Pearson product-moment correlation coefficient to assess the relationship between a college student-athletes suicide predictor and their PHQ-9 score, perceived emotional support, perceived instrumental support, level of needed support, and level of support sought. There was a significant (p < 0.001) moderate negative correlation, r = -.462, N = 361 between the suicide predictor and score on the PHQ-9. There was a significant (p < 0.001) weak positive correlation, r = .236, N = 361 between the suicide predictor and perceived emotional support. A similar significant (p < 0.001) weak positive correlation, r = .255, N = 361 between suicide predictor and perceived instrumental support. A college student-athlete’s exposure to mental health training, perceived level of needed support, and level of support sought did not appear to be suicide predictors.

Discussion

In this study, we investigated whether preventing suicide deaths requires the identification of factors that are associated with people’s risk of suicidal behavior. Commonly cited risk factors for suicidal thoughts and behaviors are depression and inadequate support. Association between major depressive disorder (MDD) and suicide attempts or ideation has been well-documented. Accordingly, depression has been considered a necessary or sufficient cause of suicidal thoughts. But much is unknown about the characteristics that increase suicide risk among people living with depression (Bradvik, 2018). Many mechanisms could play a role in suicidal behavior among people with MDD, and, although suicidal behavior occurs among people with major depressive disorder, depression is not necessarily a useful tool for understanding the complexity of suicide (Orsolini et al., 2020).


Most people with depression do not attempt suicide. Diagnosis of MDD requires a simultaneous presentation of several specific symptoms. Approximately, 17 million American adults will have symptoms of MDD each year, but only around 45,000-50,000 Americans will die by suicide during that same time. Considered independently of other risk factors, MDD may put one at greater risk, meaning that those with this disorder are more likely than those without it to die by suicide. But still very few of those with MDD will go on to die by suicide; reliance on depression to predict suicidality is inadvisable. This is supported by Ribeiro et al. (2018), who reviewed existing literature on the subject and showed that although depressive symptoms were reported to confer risk of suicidality, the effects were weaker than expected.

Melhem et al. (2019) demonstrated that the most severe depressive symptoms and variability over time were the only predictors of suicide attempt in young adults, especially when combined with other factors (e.g., childhood abuse, history of attempt, substance use disorder, and parental attempt). But prediction was marginally better than chance, perhaps because suicidal risk varies during a psychiatric illness and may be linked to other factors that appear during depressive episodes. Orsolini et al. (2020) showed that anxiety disorders co-occurring with MDD are among the main predictors of attempts. Several factors interact and contribute to suicidal behavior and death by suicide. These may include major depressive disorder, but interactions with other factors, such as genetic vulnerability, stress, psychiatric comorbidities, and social aspects need to be evaluated to improve prevention (Orsolini et al., 2020).
Results from our research showed a moderate negative correlation between the suicide predictor and score on the PHQ-9, challenging the assumption that depression is a necessary or sufficient cause of suicidal thoughts. This lends support to the idea that traditional risk factors can be problematic and that their predictive value has not improved over the past 50 years (Franklin et al., 2017; Fortune & Hetrick, 2022).

Bradvik (2018) also acknowledged that depression is related to suicidal ideation and attempt but is not a good predictor. Bradvik (2018) pointed to results from the Australian Rural Mental Health Study in which only 364 out of 1051 respondents reported life-time depression. Of those 364 respondents, 48% reported life-time suicidal ideation and 16% reported a suicide attempt. Gender, age of depression onset, and possibly psychiatric comorbidities were somewhat predictive of suicide behavior, but no other predictive factors were revealed. These results were echoed by Melhem et al. (2019).

The limits of risk factors to accurately predict suicide is further strengthened by our finding that an increase in emotional social support was weakly associated with an increase in suicide risk, contradicting earlier research that showed suicidal distress was worse when emotional social support was low (Ayub, 2015; Otsuki et al., 2019). Similarly, instrumental social support (i.e., support that helps people with practical tasks) was weakly associated with suicide risk, contradicting findings from Otsuki et al. (2019).
After a concussion, athletes experience a range of psychological symptoms, with depression and anxiety being among the most reported (Kontos et al., 2012). Symptoms can include loss of interest in activities that were once enjoyable, persistent sadness, physical and mental fatigue, and changes in sleep patterns. These negative outcomes may be more pronounced in athletes who attach a great degree of importance to the athlete’s role in relation to other activities (Brewer et al., 1993; Raedeke & Smith, 2001) and can be made worse by changes in lifestyle, the loss of social support that team members provided, and even personality traits. One such trait is maladaptive perfectionism.
Maladaptive perfectionists are overly critical of mistakes. They strive for excessively high and ultimately unobtainable goals. This usually results in failure, which can be painful, especially for athletes with maladaptive perfectionism, who may lack resilience to bounce back from stressful experiences. This unhealthy perfectionism is associated with higher levels of depressive symptoms (Egan et al., 2011; Olmedilla et al., 2022). Additionally, perfectionists can struggle with time management, not setting realistic timelines for getting things done or because they are paralyzed by the prospect of failure. Time management is one of the most difficult aspects of participating in college sports (Rothschild-Checroune et al., 2013).

Taken together, injury and concussion, personality traits (e.g., maladaptive perfectionism), and external factors (e.g., time constraints) can contribute to negative mental health outcomes among student-athletes and may increase suicidal distress. College athletic programs and university counseling centers are poised to improve our understanding of the nature of suicidal distress among student-athletes face and how to respond by making use of qualitative research methods, which we recommend. We urge university administrators to dedicate more resources to building and integrating academic and co-curricular resilience programs into their campuses and rely less on risk assessment that focuses on commonly cited factors (e.g., depression) to predict suicide.

Study Limitations
While efforts were made to decrease discomfort with the survey, it is possible college athletes felt pressure to respond in particular ways out of personal and/or athletic concerns. This study also relied upon self-reported data. Without having the ability to verify participant responses, there was no way of knowing the legitimacy or honesty of participants’ responses. The study was unable to control the multiple covariates or confounding variables that influence a college suicidality and mental health. Finally, our study lacked a detailed exploration of how specific socio-demographic characteristics, such as race, gender, and class status, might influence suicidal ideation and other risk behaviors among college athletes.

Future Research
The complex interplay between core risk factors in individuals and heightened suicide risk among athletes necessitates further exploration. Future research should focus on understanding the repercussions of escalated demands on athletes’ mental well-being, particularly the impact of significant situational factors such as career-ending injuries on their mental health and suicide vulnerability. Additionally, there is a need to delve into the connection between suicide rates, race, and gender among collegiate students for a more comprehensive understanding of these dynamics.

Conclusion
This study examined the relationship between college athletes’ risk of depression, suicidality, and their support system and whether preventing suicide deaths requires identification of commonly cited risk factor. The results are quite different from previous research findings, revealing a moderate negative correlation between the suicide predictor and scores on the PHQ-9, adding nuance to the presumption that depression is either a necessary or sufficient factor for the emergence of suicidal thoughts. College athletic programs and university counseling centers are poised to enhance our understanding of student-athletes’ suicidal distress and how to respond by making use of qualitative research methods. We strongly recommend adopting this strategy to address depression and suicidal ideation.

Applications in Sport
Studying suicide in college sports has practical applications that can help improve the well-being and safety of college athletes. By examining the factors that contribute to suicidal ideation and behavior in college sports, researchers and practitioners can develop targeted interventions and support systems to address mental health challenges. For instance, such studies may lead to the creation of tailored mental health resources for student-athletes, including counseling services and peer support networks. Furthermore, understanding the unique stressors faced by student-athletes, such as performance pressure and balancing academics with athletics, can inform the design of preventative measures such as stress management and resilience training programs. Additionally, awareness campaigns can be created to destigmatize mental health struggles in sports, encouraging athletes to seek help when needed. Overall, studying suicide in college sports can lead to a safer and more supportive environment for student-athletes, promoting their overall health and success.

References

References
1. American Psychological Association. (2020). Patient Health Questionnaire. https://www.apa.org/pi/about/publications/caregivers/practice-settings/assessment/tools/patienthealth#:~:text=PHQ%2D9%20scores%20%3E%2010%20had,been%20shown%20to%20be%2high.
2. Armstrong, S., & Oomen-Early, J. (2009). Social connectedness, self-esteem, and depression symptomatology among collegiate athletes versus non-athletes. Journal of American College Health, 57(5), 521-526.
3. Ayub, N. (2015). Predicting suicide ideation through intrapersonal and interpersonal factors: The interplay of Big-Five personality traits and social support. Personality and Mental Health, 9(4), 308-318.
4. Banu, P. R. (2019). Depression among athletes and non-athletes university students. International Journal of Social Sciences, 7(5-III), 1565-1569.
5. Barclay, N., Kelley, K. A., Brausch, A. M., Muehlenkam, J. J., & Nadorff, M. R. (2023). Changes in the suicide risk behaviors of American college students over time: An analysis of three universities. Suicide & Life-Threatening Behavior, 53(5), 764-775.
6. Bradvik, L. (2018). Suicide risk and mental disorders. International Journal of Environmental Research and Public Health, 15(9), 2028.
7. Brewer, B. W., Van Raalte, J. L., & Linder, D. E. (1993). Athletic identity: Hercules’ muscles or Achilles heel? International Journal of Sport Psychology, 24(2), 237–254.
8. Carter-Francique, A. (2015). Examining the value of social capital and social support for Black student-athletes’ academic success. Journal of African American Studies, 19(2), 157-177.
9. Centers for Disease Control and Prevention. (2023). Youth risk behavior survey: Data summary and trends report. https://www.cdc.gov/healthyyouth/data/yrbs/pdf/YRBS_Data-Summary-Trends_Report2023_508.pdf.
10. Centers for Disease Control and Prevention (2021). Suicide data and statistics. https://www.cdc.gov/suicide/suicide-data-statistics.html.
11. Costanza, A., Radomska, M., Zenga, F., Amerio, A., Aguglia, A., Serafini, G., Amore, M., Beradelli, I., Ojio, Y., & Nguyen, K. (2021). Severe suicidality in athletes with chronic traumatic encephalopathy: A case series and overview on putative etiopathogenetic mechanisms. International Journal of Environmental Research and Public Health, 18(3), 876.
12. DaCosta, A., Grueninger, K., Hurt, S., Crane, A., Webbe, F. M., & LoGalbo, A. (2020). A-11 comparison of the PHQ-9 and ImPACT affective symptom cluster scores in measuring depression at baseline among college athletes. Archives of Clinical Neuropsychology, 35(5), 607.
13. Defreese, J., & Smith, A. (2014). Athlete social support, negative social interactions, and psychological health across a competitive sport season. Journal of Sports Sciences, 32(15), 1454-1464.
14. DiMillo, J., Hall, N. C., Ezer, H., Schwarzer, R., & Körner, A. (2017). The Berlin Social Support Scales: Validation of the Received Support Scale in a Canadian sample of patients affected by melanoma. Journal of Health Psychology, 24(13), 1785-1795.
15. Egan, S. J., Wade, T. D., & Shafran, R. (2011). Perfectionism as a transdiagnostic process: A clinical review. Clinical Psychology Review, 31, 203-212.
16. Faul, F., Erdfelder, E., Lang, A.G., & Buchner, A. G. (2007). *Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical Sciences. Behavior Research Methods, 39(2), 175-191.
17. Fortune, S., & Hetrick, S. (2022). Suicide risk assessments: Why are we still relying on these a decade after the evidence showed they perform poorly? Australian & New Zealand Journal of Psychiatry, 56(12), 1529-1534.
18. Franklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., …Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological Bulletin, 143(2), 187-232
19. Gorczynski, P., Miller-Aron, C., Moore, M. A., & Reardon, C. (2024). The epidemiology of mental health symptoms and disorders amongst elite athletes and the evolution of mental health literacy. Mental Health Considerations in Athletes, 43(1), 1-11.
20. Gupta, R., Agrawal, R. (2021). Are the concerns destroying mental health of college athletes? A Qualitative analysis portraying experiences amidst COVID-19 ambiguities. Analyses of Social Issues & Public Policy, 21(1), 621-639.
21. Hui, Z., Guo, K., Huang, W. B., Wu, J., Ma, X., Jia, S., & Xing, Z. (2023). Relationships between college students’ exercise motivation and mental health: Chain mediating effect of perceived social support and resilience. Social Behavior & Personality, 51(8), 1-10.
22. Kontos, A. P., Covassin, T., Elbin, R. J., & Parker, T. (2012). Depression and neurocognitive performance after concussion among male and female high school and collegiate athletes. Archives of Physical Medicine and Rehabilitation, 93(10), 1751-1756.
23. Kroenke, K., Spitzer, R. L., & Williams, J. B. (2011). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606-613.
24. LoGalbo, A., DaCosta, A., & Webbe, F. (2022). Comparison of the PHQ-9 and ImPAC symptom cluster scores in measuring depression among college athletes. Applied Neuropsychology: Adult, 29(4), 703-709.
25. MacDonald, H., & Neville, T. (2023). Promoting college students’ mindfulness, mental health, and self-compassion in the time of COVID-19: Feasibility and efficacy of an online, interactive mindfulness-based stress reduction randomized trial. Journal of College Student Psychotherapy, 37(3), 260-278.
26. Madan, A., Frueh, C. B., Allen, J. G., Eillis, T. E., Rufino, K. A., Oldham, J. M., & Fowler, C. (2016). Psychometric reevaluation of the Columbia – Suicide Severity Rating Scale: Findings from a prospective inpatient cohort of severely mentally ill adult. Journal of Clinical Psychiatry, 77(7), 867-873.
27. Maron, B. J., Haas, T. S., Murphy, C. J., Ahluwalia, A., & Rutten-Ramos, S. (2014). Incidence and causes of sudden death in the U.S. college athletes. Journal of American College of Cardiology, 63(16), 1636-1643.
28. Melhem, N. M., Porta, G., Oquendo, M. A., Zelazny, J., Keilp, J. G., Iyengar, S., … Brent, D. A. (2019). Severity and variability of depression symptoms predicting suicide attempt in high-risk individuals, JAMAPsychiatry, 76(6), 603-613.
29. Miller, K. E., & Hoffman, J. H. (2009). Mental well-being and sport-related identities in college students. Sociology of Sport Journal, 26(2), 335-356.
30. Moore, M. A. (2017). Stepping outside of their comfort zone: Perceptions of seeking psychosocial services amongst college athletes. Journal of Issues in Intercollegiate Athletics, Special Issue, 130-144.
31. Moore, M. A., & Abbe, A. (2021). The National Association of Intercollegiate Athletics substance use and abuse survey. Journal of Issues in Intercollegiate Athletics, 14, 95-114.
32. Moore, M. A., Gorczynski, P., & Miller-Aron, C. (2022). Mental health literacy in sport: The role of the social work profession. Social Work, 67(3), online. National Collegiate Athletic Association. (2022). NCAA student-athlete well-being study. https://www.ncaa.org/sports/2020/5/22/ncaa-student-athlete-well-being-study.aspx.
33. Olmedilla, A., Aguilar, J. M., Ramos, L. M., Trigueros, R., & Cantón, E. (2022). Perfectionism, mental health, and injuries in women footballers. Journal of Sport Psychology, 31(1), 49-56.
34. Orsolini, L., Latini, R., Pompili, M., Serafini, C., Volpe, U., Vellante, F. … De Bearardis, D. (2020). Understanding the complex of suicide in depression: From research to clinics. Psychiatry Investigation, 17(3), 207-2021.
35. Otsuki, T., Tomata, Y., Zhang, S., Tanji, F., Sugawara, Y., & Tsuji, I. (2019). The association between emotional and instrumental social support and risk of suicide death: A population-based cohort study. Journal of Psychiatric Research, 114, 141-146.
36. Posner, K., Brown, G. K., Stanley, B., Brent, D. A., Yershova, K. V., Oquendo, M. A., Currier, G. W., Melvin, G. A., Greenhill, L., Shen, S., & Mann, J. J. (2011). The Columbia – Suicide Severity Rating Scale: Initial validity and internal consistency findings from three multisite studies with adolescents and adults. The American Journal of Psychiatry, 168(12), 1266-1277.
37. Prinz, B., Dvořák, J., & Junge, A. (2016). Symptoms and risk factors of depression during and after the football career of elite female players. British Journal of Medicine and Sport: Open Sport & Exercise Medicine, 2(1), e000124.
38. Raedeke, T. D., & Smith, A. L. (2001). Coping with stressors in sport: A conceptual model. Journal of Sport & Exercise Psychology, 23, 528-541.
39. Rao, A. L., Asif, I. M., Drezner, J. A., Toresdahl, B. G., & Harmon, K. G. (2015). Suicide in National Collegiate Athletic Association (NCAA) athletes. Sports Health, 7(5), 452-457.
40. Ribeiro, J. D., Huang, X., Fox, K. R., & Franklin, J. C. (2018). Depression and hopelessness as risk factors for suicide ideation, attempts and death: Meta-analysis of longitudinal studies. British Journal of Psychiatry, 212(5), 279-286.
41. Rosenthal, S. R., Noel, J. K., Edwards, Z. C., Sammartino, C. J., & Swanberg, J. E. (2023). Risk factors for suicide ideation among Rhode Island college students. Rhode Island Medical Journal, 106(3), 42-47.
42. Rothschild-Checroune, E., Gravelle, F., Dawson, D., & Karlis, G. (2013). Balancing academic and athletic time management: A qualitative exploration of first year student athletes’ university football experiences. Society and Leisure, 35(2), 243-261.
43. Salehian, M. H., Gursoy, R., Aftabi, G. R., Sardarudi, M. T., & Ancari, Z. D. (2012). Comparison of depression between university athletes and non-athletes. European Journal of Experimental Biology, 2(4), 1008-1011.
44. Schmiedehaus, E., Snyder, E., Perrotte, J., Deason, R., Howard, K., & Cordaro, M. (2023). The ongoing mental health plight of depressed college students: Clinical recommendations and the importance of early screening and detection. Issues in Mental Health Nursing, 44(6), 562-570.
45. Schulz, U., & Schwarzer, R. (2004). Long-term effects of spousal support on coping with cancer after surgery. Journal of Social and Clinical Psychology, 23(5), 716-732.
Substance Abuse and Mental Health Services Administration. (2017). National Survey of Drug Use and Health Survey. https://www.samhsa.gov/data/data-we-collect/nsduh-national-survey-drug-use-and-health.
46. Substance Abuse and Mental Health Services Administration. (2021). National Survey of Drug Use and Health Survey. https://www.samhsa.gov/data/sites/default/files/reports/rpt39443/2021_NNR_figure_slides.pdf.
47. Sullivan, M., Moore, M., Blom, L. C., & Slater, G. (2020). Relationship between social support and depressive symptoms in collegiate student athletes. Journal for the Study of Sports and Athletes in Education, 14(3), 192-209.
48. Syndergaard, S., Borger, J., Klenzak, S., Grello, A., & Adams, A. (2023). Implementation of Columbia – Suicide Severity Rating Scale (C-SSRS) as a universal suicide risk screening tool in high volume emergency department. Archives of Suicide Research, 27(2), 769-779.
49. Wolanin, A., Hong, E., Marks, D., Panchoo, K., & Gross, M. (2016). Prevalence of clinically elevated depressive symptoms in college athletes and differences by gender and sport.
British Journal of Sports Medicine, 50(3), 167–171.

2024-07-03T13:38:41-05:00July 5th, 2024|General, Research, Sport Education, Sports Studies and Sports Psychology|Comments Off on Navigating Darkness: College Athlete Suicide, Support Systems, and Shadows of Depression
Read More

Restructuring NFL Ownership, A New Way Forward

Authors: R. Matthew Hedges1, David Hughes2

1School of Continuing Studies, Sports Industry Management, Georgetown University, Washington D.C., USA
2School of Continuing Studies, Sports Industry Management, Georgetown University, Washington D.C., USA

Corresponding Author:

R. Matthew Hedges, MPS
295 Durham St.
Unit F
Lake Oswego, Oregon 97034
[email protected]
541-727-1008

1R. Matthew Hedges, MPS, is a graduate of Georgetown University’s School of Continuing Studies and studied Sports Industry Management. In light of the current sports franchise ownership market and the lack of diversity thereof, Hedges’ interest includes finding a pathway to a more inclusive sports ownership structure.

2David C. Hughes, Ph.D., M.Ed., is an adjunct professor at Georgetown University’s School of Continuing Studies. His specialties include esports, diversity, equity, and inclusion within sports management, and sports technology.

Restructuring NFL Ownership, A New Way Forward

ABSTRACT

Racial discrimination still exists in the NFL today. What has been referred to as a modern-day plantation, NFL franchises have insufficient diversity at the ownership level as well as in the top front office positions. NFL franchise owners have illimitable power and are averse to a 21st-century progressive society. The league is a multi-billion-dollar enterprise that is owned and operated by 32 franchise owners. Although the NFL is the behemoth of the sports industry, there are ingrained systemic issues. Instead of putting a band-aid on a bullet wound, the NFL must address the diversity concerns with strategic initiatives to overcome the deficiencies. A comprehensive top-down structural reformation is required to alter the ownership level. With the introduction of private equity funds, amending the Rooney Rule to include limited partners, and modifying the relationship between NFL franchises and their respective local governments, diversity within senior executives will advance. While the 32 owners have tightly held the reins of the league, a revolution must transpire.

Key Words: NFL Ownership, Diversity in the Workplace, Social Reform, Private Equity, Rooney Rule, Equal Opportunity

(more…)
2023-04-27T16:37:15-05:00April 28th, 2023|Contemporary Sports Issues, Sports Studies and Sports Psychology|Comments Off on Restructuring NFL Ownership, A New Way Forward
Read More

Environmental Sustainability Practices in Minor League Sports [EARTH DAY PUBLICATION]

Authors: Mark Mitchell1, Melissa Clark1, and Sara Nimmo2

1Wall College of Business, Coastal Carolina University, Conway, South Carolina, USA

2University of North Carolina, Charlotte, North Carolina, USA

Corresponding Author:

Professor of Marketing
Associate Dean, Wall College of Business
NCAA Faculty Athletics Representative (FAR)
Coastal Carolina University
P. O. Box 261954
Conway, SC 29528
[email protected]
(843) 349-2392

Mark Mitchell, DBA is Professor of Marketing at Coastal Carolina University in Conway, SC.

Melissa Clark, PhD isProfessor of Marketing at Coastal Carolina University in Conway, SC.

Sara Nimmo is a 2022 Honors Graduate of Coastal Carolina University. Nimmo currently works in Sports Marketing at the University of North Carolina at Charlotte, and  previously served as a Fan Engagement Assistant with MiLB’s Myrtle Beach Pelicans.

Environmental Sustainability Practices in Minor League Sports

ABSTRACT

Recently, there has been heightened attention on what businesses are doing to sustain the environment. This trend has also impacted minor league sports. Many teams have developed and implemented strategies to lessen the environmental impact of their operations. Consultation with officials of a local minor league baseball team, in addition to extensive information search, identified the strategies used by teams and leagues to improve the environmental sustainability of their part of the sports industry. A cluster analysis was then performed to classify the strategies identified into categories of similar topics. To date, the main areas where minor league sport teams have focused their efforts on environmental sustainability are: (1) facility-related matters (i.e., sustainable certificates, renewable energy, and changes in water and fertilizer usage); and (2) waste reduction (i.e., recycling, paperless ticketing, digital publications). Many of these sustainability initiatives were introduced during the COVID global pandemic as teams and leagues sought to play games while concurrently lower costs and limiting contact among fans and staff. Since their introduction, many of these practices, particularly those dealing with waste reduction, have become standard operating procedures. As fans become more aware of the need to reduce the environmental impact of business operations, they will apply those expectations to minor league sports teams and leagues. Teams and leagues are responding driven by the concurrent desire to sustain their business and to lower the environmental impact of their operations.

Key words: minor league sports, environmental sustainability, facilities, waste reduction

(more…)
2023-04-20T15:01:13-05:00April 21st, 2023|Research, Sports Facilities, Sports Studies and Sports Psychology|Comments Off on Environmental Sustainability Practices in Minor League Sports [EARTH DAY PUBLICATION]
Read More
Go to Top