Pysch Article
Measurement in Physical Education and Exercise Science, 16: 254–267, 2012 Copyright © Taylor & Francis Group, LLC ISSN: 1091-367X print / 1532-7841 online DOI: 10.1080/1091367X.2012.693371
Assessing College Student-Athletes’ Life Stress: Initial Measurement Development and Validation
Frank Jing-Horng Lu and Ya-Wen Hsu
Graduate Institute of Physical Education, National Taiwan Sport University, Taiwan
Yuan-Shuo Chan, Jang-Rong Cheen, and Kuei-Tsu Kao
Department of Adapted Physical Education, National Taiwan Sport University, Taiwan
College student-athletes have unique life stress that warrants close attention. The purpose of this study was to develop a reliable and valid measurement assessing college student-athletes’ life stress. In Study 1, a focus group discussion and Delphi method produced a questionnaire draft, termed the College Student-Athletes’ Life Stress Scale. In Study 2 and Study 3, the properties of the items and the underlying structure of the College Student-Athletes’ Life Stress Scale were confirmed through item analysis, factor analysis, and reliability examination. A 24-item College Student-Athletes’ Life Stress Scale with eight factors was established. In addition, examining concurrent and discriminant validity via correlations among College Student-Athletes’ Life Stress Scale, positive state of mind, and burnout experiences provided further evidences of criterion validity. Across these phases, results showed adequate factorial structure, criterion validity, and reliability of the College Student-Athletes’ Life Stress Scale. The investigators suggest that College Student-Athletes’ Life Stress Scale could be used as a tool for researchers and practitioners to assess college student-athletes’ life stress. Key words: Delphi method, concurrent and discriminant validity, athletes’ positive state of mind, burnout
INTRODUCTION College student-athletes are a unique group on campus who may face a variety of stressors and challenges compared to their non-athlete counterparts because of their social environments (Etzel, 2009; Yusko, Buckman, White, & Pandina, 2008). College student-athletes are developing young adults, and like their non-athlete peers, they must try to find ways to deal with a variety of academic events and challenges in daily life. However, in athletic settings, they face harsh and weighty demands, such as repetitive and exhausting training, frequent travels and competitions, injuries, pressures to win and avoid losses, internal competitions between teammates, media pressures, and sometimes burnout (Etzel, 2009; Johnson & Ivarsson, 2011; Steffen, Pensgaard, & Bahr, 2009). These added burdens of sports participation make college student-athletes’ life stress an extremely important issue (Loughran & Etzel, 2008). Moreover, stress can be either
Correspondence should be sent to Ya-Wen Hsu, Graduate Institute of Physical Education, National Taiwan Sport University, # 250, Wen-Hua First Rd., Kweishan, Taoyuan, Taiwan. E-mail: tgieva@gmail.com
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“eustress” or “distress” (Selye, 1974), and when it becomes damaging or unpleasant stress (i.e., distress), it could endanger not only their sports performance but also their physical and mental health (Kleinert, 2007; Yusko et al., 2008). In such cases, understanding and identifying distress that student-athletes encounter in their daily life would be an essential starting point to provide them with proper support. In terms of stressors in daily life, researchers assess life stress using various well-developed measurements. For example, the Social Readjustment Rating Scale (SRRS: Holmes & Rahe, 1967) is a measurement that lists 43 life events to evaluate one’s total values of experienced life stressors. The Life Experiences Survey (LES: Sarason, Johnson, & Siegel, 1978) has been used frequently to measure life stressors. However, some items of these measures may be improper and irrelevant to college students, such as “death of a spouse or divorce.” To overcome these issues, Lustman and colleagues (Lustman, Sowa, & O’Hara, 1984) developed Psychological Distress Inventory (PDI) to assess four aspects of life stress among college students, including depression, anxiety, somatic discomfort, and stress. In addition, Baker and Siryk (1984) developed Adjustment Measures (AM), which assesses college students’ life adjustment, including academic, social, personal-emotional, and general adjustment. Although PDI and AM are suitable for college population, a lack of sport-specific focus may cause them to be inappropriate in terms of validity and reliability when assessing student-athletes’ life stress. In sports settings, several measurements had been used to assess athletes’ stress. For instance, Rushall (1990) proposed the Daily Analysis of Life Demands for Athletes (DALDA) to measure athletes’ perceived environment stimuli and their responses. DALDA contains nine items related to the sources of stress (e.g., diet, health, and sleep: Nicholls, Backhouse, Polman, & McKenna, 2009; Rushall, 1990). Similarly, the Perceived Stress Scale-10 (PSS-10: Cohen, Kamarck, & Mermelstein, 1983; Galambos, Terry, Moyle, & Locke, 2005) is a 10-item scale assessing the degree to which situations in an athlete’s life are appraised as stressful. However, similar to PDI and AM, these measurements only focus on athletes’ daily life stressors without considering sports-related stressors such as competitions and trainings; besides, using a single-item to represent each stressor in both DALDA and PSS-10 may lead to questionable reliability (Oshagbemi, 1999). Later, the Life Event Scale for Collegiate Athletes (LESCA: Petrie, 1992) was developed to measure an athlete’s life history stressors. The LESCA contains 69 items, and the score can be divided into three categories: negative life event stress, positive life event stress, and total life event stress. Although the LESCA has been used in recent literature (Johnson & Ivarsson, 2011; Steffen et al., 2009) with appropriate reliability in a sports setting, still no category of the LESCA reflects the sports-specific stressors that college student-athletes encounter such as academic, training, competition, and interpersonal. Moreover, using the general composited scores (summing three categories) in LESCA is not sufficient for those working with athletes to probe different types of stress faced by different athletes. The usability of these previous measurements is therefore questionable. As previously stated, college student-athletes have unique life experiences compared to their non-athlete counterparts. According to the literature, student-athletes expressed concerns with life-related problems, such as substance abuse, academic skill difficulties, emotional adjustments, interpersonal relationships, and athletic retirement or career searching (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009). In addition, student-athletes were confronted with sports-related issues, such as competitive performance demands, injury stressors, including repetitive injury or worry about recovery, coach-athlete relationship, training issues, and others (Anshel & Wells, 2000; Fletcher, & Hanton, 2003; Gould,
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Udry, Bridges, & Beck, 1997; Noblet & Gifford, 2002; Poczwardoswski, Barott, & Henschen, 2002). These stressors were confirmed to have potential negative impacts on student-athletes’ affects and behaviors (Etzel, 2009). Given that a general life stress scale in assessing college student-athletes for research is inappropriate, a sport-specific tool with sound validity and reliability is warranted for ongoing studies. Built on previous research, the purposes of the present study were two-fold: (a) to develop a preliminary measurement to assess college student-athletes’ life stress and (b) to validate this preliminary measurement in terms of structure and construct validity. Study 1 determined a measurement draft by athletes and experts; Study 2 and Study 3 examined the factorial structures and criterion validity. STUDY 1 The purpose of Study 1 was to construct an initial questionnaire for assessing college studentathletes’ life stress. To complete this task, the investigators followed the guidelines suggested by the Standards for Educational Psychological Testing (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999). Particularly, the researchers used the Delphi method (Okoli & Pawlowski, 2004; Schmidt, 1997) to produce meaningful items for the initial questionnaire. Methods Participants A focus group was conducted with the aim of providing a preliminary description about college student-athletes’ life stress. After gaining permission from the coaches and administrators, 30 Taiwanese college student-athletes from different individual and team sports voluntarily participated in a focus group discussion as three subgroups. The context of the discussions was utilized as item pool resources in the Delphi method analysis. Thereafter, 15 experts who are familiar with college-student athletes and their lives took part in a Delphi panel board. The panel board members include sports psychologists (n = 4), coaches (n = 5), psychological consultants (n = 2), and administrators (n = 4). Measurements & Procedure First, prior to data collection, the researchers gained an approval for the series of investigations, including Study 1 through Study 3; this was approved by the Institutional Review Board of a university ethical committee. Then, researchers contacted targeted athletes through the permissions of coaches and administrators. On the appointed date, researchers briefly informed participants of the purpose of the research and of the confidentiality and anonymity of their participation. Those who committed to join the discussion signed informed consent and were divided randomly into three subgroups (each group n = 10). Participants were asked to discuss the life distress that they had experienced during their student-athlete career, especially those experiences that had negative impacts on their affects and behaviors. During the discussion, participants were free
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to propose and discuss their challenges, stress, or life events. The discussions were hosted by the first and second authors and lasted about 60 min. All of the discussions were tape-recorded and transcribed. The transcription was sent to experts in the Delphi method as a content validity reference. The Delphi method is a useful approach for identifying important issues of interest and qualitatively assessing them by inviting a group of experts to provide opinions about the issue and, finally, achieving a consensus about the topic through a series of stages or rounds (Okoli & Pawlowski, 2004; Schmidt, 1997). The analysis process was conducted following the guidelines and analysis method proposed by Schmidt; all of the documents and questionnaires across three rounds were administered using e-mail and post-mail. In the first round of the Delphi method (brainstorming for important factors), the experts were asked to list important factors regarding college student-athletes’ life stressors. To address the focus of research, they were also asked to provide their recommendations in reference to the focus group discussion data and previous measurements used in sports settings, such as DALDA, PSS-10, and LESCA. It took 7 days to collect all experts’ responses. Based on the first round’s answers, an opinion list consisting of 70 descriptions was made by first and second authors. In the second round (narrowing down the original list to the most important ones), experts were asked to revise the list in order to validate the consolidated lists of factors. It took another seven days to collect experts’ responses and arrange them. Finally, the focus of the third round was to trim the final list of selected items. Experts independently rated each item’s importance according to their expertise and experiences. The rating scale ranged from 1 (not important at all) to 5 (very important). The authors tallied each item’s priority by averaging scores from all experts and ranked the item scores from high to low. The scores of items ranged from 2.60 to 4.80. Based on this ranking, the authors chose 40 items (with scores higher than 3.73) as a questionnaire draft. Results By using focus group’s discussion and three rounds of the Delphi survey, the researchers identified 40 items that represent the most frequently reported life stressors experienced by college student-athletes. An initial questionnaire was established and entitled “College Student-Athletes’ Life Stress Scale” (CSALSS). STUDY 2 The purpose of Study 2 was to test the underlying structure of the initial questionnaire and to trim the inappropriate items using item analysis and Exploratory Factor Analysis (EFA). Methods Participants & procedure After data screening, 333 college student-athletes (males = 211; females = 112) were recruited as participants (M age = 19.36 yrs, SD = 1.43). The participants were recruited at three
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sport-colleges and two universities in Taiwan. At the time of data collection, participants were all in their regular training seasons and had been participating in a variety of individual and team sports, such as gymnastics, track and field, golf, weight-lifting, basketball, volleyball, soccer, and baseball for 8.17 ± 2.69 years. A small session of briefly reporting the purpose of the study and the process to complete questionnaires was conducted before the data collection. To prevent social desirability effects, the researchers informed participants that this was a study to explore athletes’ life experiences, and there were no right or wrong answers. Additionally, the investigators instructed them to answer the questions as truthfully as possible; all responses would be confidential. After the briefing, participants who were interested in this study then signed a consent form and completed the demographic questionnaire and 40-item CSALSS. It took about 15 min to complete the questionnaires. Measurements Demographic Information The demographic questionnaire was designed to gather information about participants’ age, gender, types of sports, and years of athletic experiences. College Student-Athletes’ Life Stress Scale (CSALSS). The 40-item CSALSS developed in the first study was used. The items of CSALSS described situations that participants encountered in their daily life, and sports and were considered as major stressors in their lives. Participants indicated the frequency of the event on a six-point Likert scale which ranged from 1 (never) to 6 (always). The questionnaire asked questions such as “I am annoyed with my coach’s bias against me.” Results Statistical Package for the Social Sciences version 17.0 (SPSS 17.0) was used for data screening and statistical analyses in Study 2. The item discrimination was processed before further EFA. The authors examined each item by comparing the item that participants scored higher than one SD of the mean with item that participants scored lower than one SD of the mean. An independent t-test demonstrated that all 40 items exceeded the critical value of three, indicating that all 40 items with significant item discrimination. Also, a preliminary check for skewness, kurtosis, Bartlett’s test of sphericity, Kaiser–Meyer–Olkin value, and zero-order correlation showed that data were normally distributed and were acceptable for factor analysis. An EFA then was conducted with the principle-axis factor method and orthogonal rotation to examine the underlying structure of the initial questionnaire (Tabachnick & Fidell, 2007). EFA yielded an eight-factor solution with 29 items, accounting for 54.86% of variance. Item-total correlation was acceptable for each item. In consideration of the length of time needed for participants to complete the questionnaire and to maintain parsimony, the researchers selected three items with the highest rotated loadings on each of eight factors. Using an extraction with the fixed eight factors, the
COLLEGE STUDENT-ATHLETES’ LIFE STRESS SCALE TABLE 1 Questionnaire Items and Factor Loadings from EFA (Study 2) Item I am bothered by a lack of motivation for academic learning. I am annoyed when preparing for exams. I worry about my academic skills because I do not know how to learn efficiently. I am annoyed by my injury because it has still not yet fully recovered. I worry about being frequently injured. I am bothered by the slow recovery of my injury. I am annoyed by my disappointing relationship with my coach. I am annoyed by my coach’s preference for some teammates. I am annoyed by my coach’s bias against me. I am annoyed by my parents’ high expectations. I am bothered by difficult situations in my family. I am annoyed with communicating with my family. I am annoyed with not finding time to encounter romantic partners. I am annoyed with being too shy to express myself when I encounter someone I love. I am annoyed with not getting along with my romantic partner. I am bothered by poor social skills in handling interpersonal relationships. I am annoyed with being friendless. I am annoyed by my social skills because it seems like nobody likes me. I worry about my unstable competitive performance. I worry about dragging my team down. I am afraid of being eliminated from competition because of poor performance. I am annoyed with the training program now. I worry that my training is not beneficial to my performance. I am annoyed by my training load because it is too much for me. Eigenvalues % of Variance Cumulative % AR SI CR — — — FR — — — — RR — — — — — — — — — — — — .72 IR — — — — — — — — — — — — — PD — — — — — — — — — — — — — —
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TA — — — — — — — — — — — — — — — — — —
.70 — .64 — .63 — — — — — — — — — — — — — — — — — — — — — —
.93 —
.87 — — .67 — — — .77 — — — — — — — — — — — — — — — — — — .73 — .48 — — .87 — .58 — .58 — — — — — — — — — — — — — — — — — — — — — — — —
.68 —
— — —
.60 — — .71 — .57 — .53 — — — — — — —
— — — — — —
.75 — .63 — .51 — — — — .80 .65 .60
6.47 2.34 1.92 1.61 1.45 1.23 1.17 1.02 25.20 8.25 6.30 4.93 4.27 3.26 3.09 2.01 25.20 33.45 39.75 44.68 48.96 52.21 55.30 57.31
Note: AR = academic requirements; SI = sports injury; CR = coach relationships; FR = family relationships; RR = romantic relationships; IR = interpersonal relationships; PD = performance demand; and TA = training adaptation.
shortened version of 24-item CSALSS was able to explain a comparable proportion of variance (57.31%). These eight factors were: (a) sports injury, (b) performance demand, (c) coach relationships, (d) training adaptation, (e) interpersonal relationships, (f) romantic relationships, (g) family relationships, and (h) academic requirements. Cronbach’s α of these factors ranged from .72 to .86, and the reliability for all items was .88, indicating that the result was reliable (See Table 1 for the result of EFA).
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STUDY 3 The purpose of Study 3 was to confirm the factorial stability of the 24-item and 8-factor CSALSS developed for Study 2. Furthermore, in Study 3 the researchers also aimed to present evidence on the initial criterion validity, which is the concurrent and discriminant validity, via correlational analyses surrounding the relationships among CSALSS subscales, positive state of mind, and burnout experiences. Methods Participants & procedure A new sample of the targeted population was recruited during the National Intercollegiate Athletic Games in Taiwan. Valid data of 334 student-athletes from 11 different universities were collected (males = 221, females = 113, M age =19.26 yrs, SD = 1.42). The recruiting procedure was similar to Study 2. Measurements The measurements included the Demographic Questionnaire and the revised 24-item CSALSS. In addition, the researchers administered the following measures for examining concurrent and discriminant validity. Athlete Burnout Questionnaire. The Athlete Burnout Questionnaire (ABQ: Raedeke & Smith, 2001) is a self-reported inventory that assesses athletes’ burnout experiences. The initial factor analyses by Raedeke and Smith revealed that ABQ has three subscales including (a) reduced sense of athletic accomplishment (RA), (b) perceived emotional and physical exhaustion (E), and (c) devaluation of sports participation (D). The Chinese version of ABQ with 11 items and three factors was revised by Lu, Chen, and Cho (2006) through item analysis, EFA, confirmatory factor analysis (CFA), criterion-related validity examination, and test–retest reliability. Participants identified their athletic burnout experiences using a 6-point Likert scale that ranged from 1 (never) to 6 (always). In the present study, the result of CFA confirmed that the factorial structure was suitable for the data. The Cronbach’s α for the three subscales ranged from .80 to .88, and the reliability for all items was .87. These three burnout subscales should be positively correlated with the CSALSS, because athletes’ stress has been identified as leading factor of maladaptive outcomes (Galambos et al., 2005; Johnson & Ivarsson, 2011; Lewis, 1991; Nicholls et al., 2009). Athletic Positive State of Mind Scale (APSMS.). The Athletic Positive State of Mind Scale (APSMS: Chang & Lu, 2002) was adapted from Horowitz and colleagues’ (Horowitz, Adler, & Kegeles, 1988) Positive States of Mind (PSOM), which is regarded as the key variable in measuring stress response. Chang and Lu adapted the original six items of PSOM by replacing the statement of the item’s stem into sports-specific questions and providing preliminary reliability and validity through item analysis, EFA and CFA. These six major elements include: attentional focus, productivity, maintaining responsibility, restful repose, and sensual pleasure. Data in the
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present study supported the single factor structure, and the Cronbach’s α was .86. Given that APSMS represents an individual’s positive state of mind, subscales of CSALSS were expected to have negative or no correlations with APSMS. Statistical Analyses To examine the factor structure of the revised 24-item CSALSS, maximum likelihood CFA using AMOS 17.0 (Arbuckle, 2008) was performed, and the researchers reported the following absolute and incremental fit indices to determine if the 8-factors measurement model fit the data well: (a) the χ 2 /DF ratio; (b) the root mean square error of approximation (RMSEA); (c) the standardized root mean square residual (SRMR); (d) the Goodness of Fit Index (GFI); (e) the Comparative Fit Index (CFI); and (f) the Non-Normed Fit Index (NNFI). The recommendations for good fit are the following: χ 2 /DF ratios between one and three, values for RMSEA values less than .08 along with SRMR values less than .05, and GFI/CFI/NNFI values greater than .90 (Hu & Bentler, 1999; McDonald & Ho, 2002). To examine the internal consistency of the factors, Cronbach’s α coefficient was used as an index. Additionally, the composite reliability (CR > .7: Fornell & Larcker, 1981) and average variance extracted (VE > .5: Kline, 1998) were calculated to examine the fit of internal structure. Finally, using SPSS 17.0, the investigators examined the concurrent and discriminant validity by examining the correlations among CSALSS, APSMS, and ABQ. Results The 8-factor measurement model of the 24-item CSALSS indicated a good fit of the instrument according to the fit indices (RMSEA = .056, SRMR = .049, χ 2 /DF = 2.06, CFI = .925, NNFI = .907, GFI = .926). The factor loadings for the 24 items range from .62 to .92 (Figure 1). Cronbach’s α coefficients were higher than .70, except for the coefficient for the “family relationship” subscale, which was .66. The composite reliability (Fornell & Larcker, 1981) for each subscale was calculated: sports injury (.88), performance demand (.79), coach relationships (.80), training adaptation (.83), interpersonal relationships (.76), romantic relationships (.75), family relationships (.83), and academic requirements (.76), indicating that each was above the .70 standard. The average variance extracted was also calculated: sports injury (.70), performance demand (.55), coach relationships (.57), training adaptation (.62), interpersonal relationships (.52), romantic relationships (.50), family relationships (.62), and academic requirements (.51), which were all above the acceptable standard (.50). As for concurrent and discriminant validity, the Pearson correlations indicated that all of the eight subscales of CSALSS negatively correlated with APSMS. Moreover, most subscales of 24-item CSALSS had low to moderate positive association with the three subscales of ABQ (Refer to Table 2 for the reliability coefficients and correlations of the CSALSS, the APSMS, and the ABQ). GENERAL DISCUSSION Although there are many measurements assessing life stress, very few studies attempted to develop a sports-specific life stress measurement for college student-athletes. The present study
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FIGURE 1 Factor structure of the CSALSS (Study 3).
developed a preliminary self-report questionnaire for such population. The results demonstrate that a 24-item CSALSS containing eight factors is an acceptable tool for measuring college student-athletes’ life stress (see Appendix A). Across these phases, evidence showed adequate factorial structure, concurrent and discriminant validity, and reliability of the instrument.
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TABLE 2 Means, SDs, Reliability Coefficients, and Bivariate Correlations of the CSALSS, the APSMS, and the ABQ (Study 3) 1 1. Sports injury 2. Performance demand 3. Coach relationships 4. Training adaption 5. Interpersonal relationships 6. Romantic relationships 7. Family relationships 8. Academic requirements 9. APSMS 10. ABQ–E 11. ABQ–D 12. ABQ–RA Mean SD .87 — — — — — — — — — — — 3.37 1.31 2 .78 — — — — — — — — — — 3.93 1.17 .23∗ 3 .24∗ .21∗ .78 — — — — — — — — — 2.72 1.06 4 .35∗ .60∗ .46∗ .83 — — — — — — — — 3.67 .97 5 .20∗ .30∗ .35∗ .41∗ .76 — — — — — — — 2.38 .90 6 .09∗ .36∗ .24∗ .38∗ .49∗ .75 — — — — — — 3.25 1.18 7 .12∗ .25∗ .21∗ .26∗ .34∗ .30∗ .66 — — — — — 3.07 .94 8 .23∗ .41∗ .28∗ .47∗ .42∗ 9 −.16∗ −.27∗ −.21∗ −.38∗ −.29∗ 10 .26∗ .20∗ .24∗ .45∗ .26∗ 11 .19∗ .14∗ .31∗ .42∗ .24∗ 12 .16∗ .32∗ .22∗ .41∗ .35∗ .31∗ .23∗ .33∗ −.34∗ .52∗ .52∗ .88 3.16 .95
.33∗ −.25∗ .22∗ .23∗ .27∗ −.14∗ .13∗ .10∗ .76 −.22∗ .28∗ .22∗ — .86 −.10∗ −.24∗ — — .80 .69∗ — — — .84 — — — — 3.66 1.07 3.84 .81 3.42 .96 3.34 1.07
Note: ∗ p < .05; Cronbach’s α is presented on the diagonal as bold font; ABQ–E: perceived emotional and physical exhaustion; ABQ–D: devaluation of sports participation; ABQ–RA: reduced sense of athletic accomplishment.
In the production of CSALSS, the researchers first focused on face validity to confirm the content of the construct. The inclusion of college student-athletes enabled us to collect the substantial stressors that they experienced in their prolonged athletic career. In addition, rather than producing as many similar items as possible, the researchers utilized the Delphi method to eliminate redundant items. It is paramount in the early stage of measurement development that each item, even those that have not yet undergone quantitative statistical examination, is meaningful for respondents. After confirming adequacy of content relevance and representativeness of the items, the CSALSS draft (40 items) was produced and examined through item analysis, EFA, and the evaluation of internal reliability in Study 2. In Study 3, the CFA, the concurrent and discriminant validity testing yield a 24-item CSALSS with eight factors. The newly developed 24-CSALSS contains four factors representing daily life stressors that have been identified by previous life stress scales. These four factors mostly focused on the interpersonal relationship issues and academic difficulties (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009). Furthermore, another four factors with 12 items representing sports-specific stressors were included. Unlike the DALDA, PSS-10, or LESCA, these factors clearly and robustly portrayed athletes’ stress experiences in sports settings (Anshel & Wells, 2000; Fletcher, & Hanton, 2003; Gould et al., 1997; Noblet & Gifford, 2002; Poczwardoswski et al., 2002). After being examined by factor analysis, CSALSS demonstrated proper factorial structure and cumulatively explained variance. Although the 24-item CSALSS demonstrates initial validity and reliability, it is worth noting that Cronbach’s α within the subscale “family relationship” was lower (α = .66). Literature
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indicates that Cronbach’s α changes as a function of the number of items (Nunnally, 1978); precisely, the fewer the items, the lower the internal consistency will be. This means that fewer items in the “family relationship” subscale may be the reason for lower Cronbach’s α. However, the composite reliability of “family relationship” was .83, achieving a “very good” level proposed by Kline (1998). Thus, the researchers supposed that the internal consistency was still acceptable and suggested that supplementary items for the “family relationship” factor would be needed in future study. In terms of discriminant validity, the eight subscales of CSALSS were all negatively associated with APSMS; it is reasonable that athletes with higher stress in both daily life and in a sports setting were less likely to have positive state of mind (Etzel, 2009; Loughran & Etzel, 2008) and instead, negative effects might arise (Nicholls et al., 2009). The result is supported by previous literature; however, one should notice that data in this study revealed the negative relationship between life stress and positive state of mind was not very strong (r = –.14 ∼ –.38). Future study is still needed to examine whether various factors, such as coping skills, sport experiences, or resilient personality, might interact with life stress (Steffen et al., 2009). The results of present study may provide an insight for future investigations. In terms of concurrent validity, the researchers chose a measurement of burnout experiences as a criterion, which has a conceptual overlap with student-athletes’ stress. It has been shown that athletes’ stress leads to many possible maladapted outcomes, such as injury occurrence and decline in performance and emotional exhaustion, which were highly correlated with burnout experiences (Galambos et al., 2005; Johnson & Ivarsson, 2011; Lewis, 1991; Nicholls et al., 2009). In such cases, three subscales of burnout were expected to positively correlate with stress, and the results were consistent with the prediction. Athletes with higher levels of stresses from daily life and sports events had a reduced sense of athletic performance and more perceived emotional and physical exhaustion and devaluation of sports participation. In particular, the researchers also found that “Training Adaption” had the highest correlation with all categories of burnout experiences. A possible explanation is related to college student-athletes’ unsuccessful adjustment to college and athletics (Etzel, 2009; Loughran & Etzel, 2008). Those who provide professional support for student-athletes, such as sports counselors, coaches, and faculty, must be aware of the unique life stress of college student-athletes, and supportive programs offered to these athletes must take all these aforementioned life-related and sports-specific stressors into account (Etzel, 2009). Though results in the present study support that the CSALSS is tenable, there are several limitations worthy of further examination. First, the present study found eight factors considered to constitute college student-athletes’ life stress. However, athletes in the present study were mostly at a higher competitive level. The training system for elite student-athletes in Taiwan may lead to omitting some factors that are important for other athletes. Future research may extend the CSALSS and include diverse samples, such as student-athletes with different ages, competitive levels, genders, and training experiences to comprehensively measure student-athletes’ life stress. Future studies may also examine CSALSS in different cultures. Furthermore, while examining the psychometric properties of the CSALSS, this study provided only a preliminary reliability and validity evaluation. More evidence is needed for the ongoing validation process. Finally, future research that focuses on diverse groups of student-athletes who may confront more specific challenges is warranted. These athletes may have not only visible differences, such as gender and ethnicity, but also less visible differences, such as socioeconomic status, injury or
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disability, career transition stages, and sexual orientation (Etzel, 2009; Loughran & Etzel, 2008). This exploration will be more useful for practical use. To conclude, this article presents a chronology of three empirical studies that produced a new measurement tool with 24 items and identified eight factors that are potential stressors to college student-athletes. The results, coupled with a review of the relevant literature (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009), help us understand college student-athletes’ life stress. REFERENCES
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational psychological testing. Washington, DC: Author. Anshel, M. H., & Wells, B. (2000). Sources of acute stress and coping styles in competitive sport. Anxiety, Stress, & Coping, 13, 1–26. Arbuckle, J. L. (2008). Amos 17.0 [Computer software]. Chicago, IL: Small Walters. Baker, R. W., & Siryk, B. (1984). Measuring adjustment to college. Journal of Counseling Psychology, 31, 179–189. Chang, Y. C., & Lu, F. J. H. (2002). The development of Athletic Positive States of Mind Scale (APSMS): Reliability and validity (in Chinese). Bulletin of Sport and Exercise Psychology of Taiwan, 1, 71–80. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 386–396. Etzel, E. F. (2009). Counseling Student Athletes: Issues and interventions. Morgantown, WV: Fitness Information Inc. Fletcher, D., & Hanton, S. (2003). Sources of organizational stress in elite sports performers. The Sport Psychologist, 17, 175–195. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. Galambos, S. A., Terry, P. C., Moyle, G. M., & Locke, S. A. (2005). Psychological predictors of injury among elite athletes. British Journal of Sports Medicine, 39, 351–354. Gould, D., Udry, E., Bridges, D., & Beck, L. (1997). Stress sources encountered when rehabilitating from season-ending ski injures. The Sport Psychologist, 11, 361–378. Holmes, T. H., & Rahe, R. H. (1967). The Social Readjustment Rating Scale. Journal of Psychosomatic Research, 11, 213–218. Horowitz, M., Alder, N., & Kegeles S. (1988). A scale for measuring the occurrence of positive states of mind: A preliminary report. Psychosomatic Medicine, 50, 477–483. Hu, L., & Bentler, P. M. (1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. Johnson, U., & Ivarsson, A. (2011). Psychological predictors of sport injuries among junior soccer players. Scandinavian Journal of Medicine and Science in Sports, 21, 129–136. Kleinert, J. (2007). Mood states and perceived physical states as short-term predictors of sport injuries: Two prospective studies. International Journal of Sport & Exercise Psychology, 5, 340–351. Kline, R. B. (1998). Principles and practice of structural equation modeling. New York, NY: Guilford Press. Lewis, M. (1991). Athletes in college: Differencing role and conflicting expectations. College Student Journal, 10, 195–200 Loughran, M. J., & Etzel, E. F. (2008). Ethical practice in a diverse world: The challenges of working with differences in the psychological treatment of college student-athletes. Athletic Insight, 10. Retrieved from http://athleticinsight. com/Vol10Iss4/Ethical.htm. Lu, F. J. H., Chen, L. H., & Cho, K. H. (2006). Revision of Raedeke and Smith’s Athlete Burnout Questionnaire (ABQ): Analyses of validity and reliability of Chinese version (in Chinese). Physical Education Journal, 39, 83–94. Lustman, P. J., Sowa, C. J., & O’Hara, D. J. (1984). Factors influencing college student health: Development of the psychological distress inventory. Journal of Counseling Psychology, 31, 28–35. McDonald, R. P., & Ho, M. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Method, 7, 64–82.
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Nicholls, A. R., Backhouse, S. H., Polman, R. C. J., & McKenna, J. (2009). Stressors and affective states among professional rugby union players. Scandinavian Journal of Medicine and Science in Sports, 19, 121–128. Noblet, A. J., & Gifford, S. M. (2002). The sources of stress experienced by Australian professional footballers. Journal of Applied Sport Psychology, 14, 1–13. Nunnally, J. (1978). Psychometric theory. New York, NY: McGraw-Hill. Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: An example, design considerations and applications. Information & Management, 42, 15–29. Oshagbemi, T. (1999). Overall job satisfaction: How good are single versus multiple-item measures? Journal of Managerial Psychology, 14, 388–403. Petrie, T. A. (1992). Psychosocial antecedents of athletic injury: The effects of life stress and social support on female collegiate gymnasts. Behavioral Medicine, 18, 127–138. Poczwardoswski, A., Barott, J. E., & Henschen, K. P. (2002). The athlete and coach: Their relationship and its meaning. International Journal of Sport Psychology, 33, 116–140. Raedeke, T. D., & Smith, A. L. (2001). Development and preliminary validation of an athlete burnout measure. Journal of Sport and Exercise Psychology, 23, 281–306. Rushall, B. R. (1990). A tool for measuring stress tolerance in elite athletes. Journal of Applied Sport Psychology, 2, 51–66. Sarason, I. G., Johnson, J. H., & Siegel, J. M. (1978). Assessing the impact of life changes: Development of Life Experiences Survey. Journal of Consulting & Clinical Psychology, 46, 932–946. Schmidt, R. C. (1997). Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences, 28, 763–774. Selye, H. (1974). Stress without distress. Philadelphia, PA: Lippincott. Steffen, K., Pensgaard, A. M., & Bahr, R. (2009). Self-reported psychological characteristics as risk factors for injuries in female youth football. Scandinavian Journal of Medicine and Science in Sports, 19, 442–451. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (4th ed.). Boston, MA: Allyn & Bacon. Yusko, D. A., Buckman, J. F., White, H. R., Pandina, R. J. (2008). Risk for excessive alcohol use and drinking-related problems in college student athletes. Addictive Behaviors, 33, 1546–1556.
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APPENDIX A COLLEGE STUDENT-ATHLETES’ LIFE STRESS SCALE
Directions: Below are 24 statements that describe something that annoys/bothers you or makes you uncomfortable in your daily life as a college student-athlete. Please read each one carefully and circle the number that indicates how often you experience it. Your answers are absolutely confidential. 1 I am annoyed by my injury because it has still not yet fully recovered. 2 I worry about my unstable competitive performance. 3 I am annoyed by my disappointing relationship with my coach. 4 I am annoyed with the training program now. 5 I am bothered by poor social skills in handling interpersonal relationships. 6 I am annoyed with not finding time to encounter romantic partners. 7 I am annoyed by my parents’ high expectations. 8 I am bothered by a lack of motivation for academic learning. 9 I worry about being frequently injured. 10 I worry about dragging my team down. 11 I am annoyed by my coach’s preference for some teammates. 12 I worry that my training is not beneficial to my performance. 13 I am annoyed with being friendless. 14 I am annoyed with being too shy to express myself when I encounter someone I love. 15 I am bothered by difficult situations in my family. 16 I am annoyed when preparing for exams. 17 I am bothered by the slow recovery of my injury. 18 I am afraid of being eliminated from competition because of poor performance. 19 I am annoyed by my coach’s bias against me. 20 I am annoyed by my training load because it is too much for me. 21 I am annoyed by my social skills because it seems like nobody likes me. 22 I am annoyed with not getting along with my romantic partner. 23 I am annoyed with communicating with my family. 24 I worry about my academic skills because I do not know how to learn efficiently.
Never Rarely Sometimes 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
Quite often 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
Very often 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
Always 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
Note: (a) items1, 9, 17 represent “sports injury;” (b) items 2, 10, 18 represent “performance demand;” (c) items 3, 11, 19 represent ”coach relationships;” (d) items 4, 12, 20 represent “training adaptation;” (e) items 5, 13, 21 represent “interpersonal relationships;” (f) items 6, 14, 22 represent “romantic relationships;” (g) items 7, 15, 23 represent “family relationships;” and (h) items 8, 16, 24 represent “academic requirements”
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Assessing College Student-Athletes’ Life Stress: Initial Measurement Development and Validation
Frank Jing-Horng Lu and Ya-Wen Hsu
Graduate Institute of Physical Education, National Taiwan Sport University, Taiwan
Yuan-Shuo Chan, Jang-Rong Cheen, and Kuei-Tsu Kao
Department of Adapted Physical Education, National Taiwan Sport University, Taiwan
College student-athletes have unique life stress that warrants close attention. The purpose of this study was to develop a reliable and valid measurement assessing college student-athletes’ life stress. In Study 1, a focus group discussion and Delphi method produced a questionnaire draft, termed the College Student-Athletes’ Life Stress Scale. In Study 2 and Study 3, the properties of the items and the underlying structure of the College Student-Athletes’ Life Stress Scale were confirmed through item analysis, factor analysis, and reliability examination. A 24-item College Student-Athletes’ Life Stress Scale with eight factors was established. In addition, examining concurrent and discriminant validity via correlations among College Student-Athletes’ Life Stress Scale, positive state of mind, and burnout experiences provided further evidences of criterion validity. Across these phases, results showed adequate factorial structure, criterion validity, and reliability of the College Student-Athletes’ Life Stress Scale. The investigators suggest that College Student-Athletes’ Life Stress Scale could be used as a tool for researchers and practitioners to assess college student-athletes’ life stress. Key words: Delphi method, concurrent and discriminant validity, athletes’ positive state of mind, burnout
INTRODUCTION College student-athletes are a unique group on campus who may face a variety of stressors and challenges compared to their non-athlete counterparts because of their social environments (Etzel, 2009; Yusko, Buckman, White, & Pandina, 2008). College student-athletes are developing young adults, and like their non-athlete peers, they must try to find ways to deal with a variety of academic events and challenges in daily life. However, in athletic settings, they face harsh and weighty demands, such as repetitive and exhausting training, frequent travels and competitions, injuries, pressures to win and avoid losses, internal competitions between teammates, media pressures, and sometimes burnout (Etzel, 2009; Johnson & Ivarsson, 2011; Steffen, Pensgaard, & Bahr, 2009). These added burdens of sports participation make college student-athletes’ life stress an extremely important issue (Loughran & Etzel, 2008). Moreover, stress can be either
Correspondence should be sent to Ya-Wen Hsu, Graduate Institute of Physical Education, National Taiwan Sport University, # 250, Wen-Hua First Rd., Kweishan, Taoyuan, Taiwan. E-mail: tgieva@gmail.com
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“eustress” or “distress” (Selye, 1974), and when it becomes damaging or unpleasant stress (i.e., distress), it could endanger not only their sports performance but also their physical and mental health (Kleinert, 2007; Yusko et al., 2008). In such cases, understanding and identifying distress that student-athletes encounter in their daily life would be an essential starting point to provide them with proper support. In terms of stressors in daily life, researchers assess life stress using various well-developed measurements. For example, the Social Readjustment Rating Scale (SRRS: Holmes & Rahe, 1967) is a measurement that lists 43 life events to evaluate one’s total values of experienced life stressors. The Life Experiences Survey (LES: Sarason, Johnson, & Siegel, 1978) has been used frequently to measure life stressors. However, some items of these measures may be improper and irrelevant to college students, such as “death of a spouse or divorce.” To overcome these issues, Lustman and colleagues (Lustman, Sowa, & O’Hara, 1984) developed Psychological Distress Inventory (PDI) to assess four aspects of life stress among college students, including depression, anxiety, somatic discomfort, and stress. In addition, Baker and Siryk (1984) developed Adjustment Measures (AM), which assesses college students’ life adjustment, including academic, social, personal-emotional, and general adjustment. Although PDI and AM are suitable for college population, a lack of sport-specific focus may cause them to be inappropriate in terms of validity and reliability when assessing student-athletes’ life stress. In sports settings, several measurements had been used to assess athletes’ stress. For instance, Rushall (1990) proposed the Daily Analysis of Life Demands for Athletes (DALDA) to measure athletes’ perceived environment stimuli and their responses. DALDA contains nine items related to the sources of stress (e.g., diet, health, and sleep: Nicholls, Backhouse, Polman, & McKenna, 2009; Rushall, 1990). Similarly, the Perceived Stress Scale-10 (PSS-10: Cohen, Kamarck, & Mermelstein, 1983; Galambos, Terry, Moyle, & Locke, 2005) is a 10-item scale assessing the degree to which situations in an athlete’s life are appraised as stressful. However, similar to PDI and AM, these measurements only focus on athletes’ daily life stressors without considering sports-related stressors such as competitions and trainings; besides, using a single-item to represent each stressor in both DALDA and PSS-10 may lead to questionable reliability (Oshagbemi, 1999). Later, the Life Event Scale for Collegiate Athletes (LESCA: Petrie, 1992) was developed to measure an athlete’s life history stressors. The LESCA contains 69 items, and the score can be divided into three categories: negative life event stress, positive life event stress, and total life event stress. Although the LESCA has been used in recent literature (Johnson & Ivarsson, 2011; Steffen et al., 2009) with appropriate reliability in a sports setting, still no category of the LESCA reflects the sports-specific stressors that college student-athletes encounter such as academic, training, competition, and interpersonal. Moreover, using the general composited scores (summing three categories) in LESCA is not sufficient for those working with athletes to probe different types of stress faced by different athletes. The usability of these previous measurements is therefore questionable. As previously stated, college student-athletes have unique life experiences compared to their non-athlete counterparts. According to the literature, student-athletes expressed concerns with life-related problems, such as substance abuse, academic skill difficulties, emotional adjustments, interpersonal relationships, and athletic retirement or career searching (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009). In addition, student-athletes were confronted with sports-related issues, such as competitive performance demands, injury stressors, including repetitive injury or worry about recovery, coach-athlete relationship, training issues, and others (Anshel & Wells, 2000; Fletcher, & Hanton, 2003; Gould,
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Udry, Bridges, & Beck, 1997; Noblet & Gifford, 2002; Poczwardoswski, Barott, & Henschen, 2002). These stressors were confirmed to have potential negative impacts on student-athletes’ affects and behaviors (Etzel, 2009). Given that a general life stress scale in assessing college student-athletes for research is inappropriate, a sport-specific tool with sound validity and reliability is warranted for ongoing studies. Built on previous research, the purposes of the present study were two-fold: (a) to develop a preliminary measurement to assess college student-athletes’ life stress and (b) to validate this preliminary measurement in terms of structure and construct validity. Study 1 determined a measurement draft by athletes and experts; Study 2 and Study 3 examined the factorial structures and criterion validity. STUDY 1 The purpose of Study 1 was to construct an initial questionnaire for assessing college studentathletes’ life stress. To complete this task, the investigators followed the guidelines suggested by the Standards for Educational Psychological Testing (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999). Particularly, the researchers used the Delphi method (Okoli & Pawlowski, 2004; Schmidt, 1997) to produce meaningful items for the initial questionnaire. Methods Participants A focus group was conducted with the aim of providing a preliminary description about college student-athletes’ life stress. After gaining permission from the coaches and administrators, 30 Taiwanese college student-athletes from different individual and team sports voluntarily participated in a focus group discussion as three subgroups. The context of the discussions was utilized as item pool resources in the Delphi method analysis. Thereafter, 15 experts who are familiar with college-student athletes and their lives took part in a Delphi panel board. The panel board members include sports psychologists (n = 4), coaches (n = 5), psychological consultants (n = 2), and administrators (n = 4). Measurements & Procedure First, prior to data collection, the researchers gained an approval for the series of investigations, including Study 1 through Study 3; this was approved by the Institutional Review Board of a university ethical committee. Then, researchers contacted targeted athletes through the permissions of coaches and administrators. On the appointed date, researchers briefly informed participants of the purpose of the research and of the confidentiality and anonymity of their participation. Those who committed to join the discussion signed informed consent and were divided randomly into three subgroups (each group n = 10). Participants were asked to discuss the life distress that they had experienced during their student-athlete career, especially those experiences that had negative impacts on their affects and behaviors. During the discussion, participants were free
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to propose and discuss their challenges, stress, or life events. The discussions were hosted by the first and second authors and lasted about 60 min. All of the discussions were tape-recorded and transcribed. The transcription was sent to experts in the Delphi method as a content validity reference. The Delphi method is a useful approach for identifying important issues of interest and qualitatively assessing them by inviting a group of experts to provide opinions about the issue and, finally, achieving a consensus about the topic through a series of stages or rounds (Okoli & Pawlowski, 2004; Schmidt, 1997). The analysis process was conducted following the guidelines and analysis method proposed by Schmidt; all of the documents and questionnaires across three rounds were administered using e-mail and post-mail. In the first round of the Delphi method (brainstorming for important factors), the experts were asked to list important factors regarding college student-athletes’ life stressors. To address the focus of research, they were also asked to provide their recommendations in reference to the focus group discussion data and previous measurements used in sports settings, such as DALDA, PSS-10, and LESCA. It took 7 days to collect all experts’ responses. Based on the first round’s answers, an opinion list consisting of 70 descriptions was made by first and second authors. In the second round (narrowing down the original list to the most important ones), experts were asked to revise the list in order to validate the consolidated lists of factors. It took another seven days to collect experts’ responses and arrange them. Finally, the focus of the third round was to trim the final list of selected items. Experts independently rated each item’s importance according to their expertise and experiences. The rating scale ranged from 1 (not important at all) to 5 (very important). The authors tallied each item’s priority by averaging scores from all experts and ranked the item scores from high to low. The scores of items ranged from 2.60 to 4.80. Based on this ranking, the authors chose 40 items (with scores higher than 3.73) as a questionnaire draft. Results By using focus group’s discussion and three rounds of the Delphi survey, the researchers identified 40 items that represent the most frequently reported life stressors experienced by college student-athletes. An initial questionnaire was established and entitled “College Student-Athletes’ Life Stress Scale” (CSALSS). STUDY 2 The purpose of Study 2 was to test the underlying structure of the initial questionnaire and to trim the inappropriate items using item analysis and Exploratory Factor Analysis (EFA). Methods Participants & procedure After data screening, 333 college student-athletes (males = 211; females = 112) were recruited as participants (M age = 19.36 yrs, SD = 1.43). The participants were recruited at three
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sport-colleges and two universities in Taiwan. At the time of data collection, participants were all in their regular training seasons and had been participating in a variety of individual and team sports, such as gymnastics, track and field, golf, weight-lifting, basketball, volleyball, soccer, and baseball for 8.17 ± 2.69 years. A small session of briefly reporting the purpose of the study and the process to complete questionnaires was conducted before the data collection. To prevent social desirability effects, the researchers informed participants that this was a study to explore athletes’ life experiences, and there were no right or wrong answers. Additionally, the investigators instructed them to answer the questions as truthfully as possible; all responses would be confidential. After the briefing, participants who were interested in this study then signed a consent form and completed the demographic questionnaire and 40-item CSALSS. It took about 15 min to complete the questionnaires. Measurements Demographic Information The demographic questionnaire was designed to gather information about participants’ age, gender, types of sports, and years of athletic experiences. College Student-Athletes’ Life Stress Scale (CSALSS). The 40-item CSALSS developed in the first study was used. The items of CSALSS described situations that participants encountered in their daily life, and sports and were considered as major stressors in their lives. Participants indicated the frequency of the event on a six-point Likert scale which ranged from 1 (never) to 6 (always). The questionnaire asked questions such as “I am annoyed with my coach’s bias against me.” Results Statistical Package for the Social Sciences version 17.0 (SPSS 17.0) was used for data screening and statistical analyses in Study 2. The item discrimination was processed before further EFA. The authors examined each item by comparing the item that participants scored higher than one SD of the mean with item that participants scored lower than one SD of the mean. An independent t-test demonstrated that all 40 items exceeded the critical value of three, indicating that all 40 items with significant item discrimination. Also, a preliminary check for skewness, kurtosis, Bartlett’s test of sphericity, Kaiser–Meyer–Olkin value, and zero-order correlation showed that data were normally distributed and were acceptable for factor analysis. An EFA then was conducted with the principle-axis factor method and orthogonal rotation to examine the underlying structure of the initial questionnaire (Tabachnick & Fidell, 2007). EFA yielded an eight-factor solution with 29 items, accounting for 54.86% of variance. Item-total correlation was acceptable for each item. In consideration of the length of time needed for participants to complete the questionnaire and to maintain parsimony, the researchers selected three items with the highest rotated loadings on each of eight factors. Using an extraction with the fixed eight factors, the
COLLEGE STUDENT-ATHLETES’ LIFE STRESS SCALE TABLE 1 Questionnaire Items and Factor Loadings from EFA (Study 2) Item I am bothered by a lack of motivation for academic learning. I am annoyed when preparing for exams. I worry about my academic skills because I do not know how to learn efficiently. I am annoyed by my injury because it has still not yet fully recovered. I worry about being frequently injured. I am bothered by the slow recovery of my injury. I am annoyed by my disappointing relationship with my coach. I am annoyed by my coach’s preference for some teammates. I am annoyed by my coach’s bias against me. I am annoyed by my parents’ high expectations. I am bothered by difficult situations in my family. I am annoyed with communicating with my family. I am annoyed with not finding time to encounter romantic partners. I am annoyed with being too shy to express myself when I encounter someone I love. I am annoyed with not getting along with my romantic partner. I am bothered by poor social skills in handling interpersonal relationships. I am annoyed with being friendless. I am annoyed by my social skills because it seems like nobody likes me. I worry about my unstable competitive performance. I worry about dragging my team down. I am afraid of being eliminated from competition because of poor performance. I am annoyed with the training program now. I worry that my training is not beneficial to my performance. I am annoyed by my training load because it is too much for me. Eigenvalues % of Variance Cumulative % AR SI CR — — — FR — — — — RR — — — — — — — — — — — — .72 IR — — — — — — — — — — — — — PD — — — — — — — — — — — — — —
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TA — — — — — — — — — — — — — — — — — —
.70 — .64 — .63 — — — — — — — — — — — — — — — — — — — — — —
.93 —
.87 — — .67 — — — .77 — — — — — — — — — — — — — — — — — — .73 — .48 — — .87 — .58 — .58 — — — — — — — — — — — — — — — — — — — — — — — —
.68 —
— — —
.60 — — .71 — .57 — .53 — — — — — — —
— — — — — —
.75 — .63 — .51 — — — — .80 .65 .60
6.47 2.34 1.92 1.61 1.45 1.23 1.17 1.02 25.20 8.25 6.30 4.93 4.27 3.26 3.09 2.01 25.20 33.45 39.75 44.68 48.96 52.21 55.30 57.31
Note: AR = academic requirements; SI = sports injury; CR = coach relationships; FR = family relationships; RR = romantic relationships; IR = interpersonal relationships; PD = performance demand; and TA = training adaptation.
shortened version of 24-item CSALSS was able to explain a comparable proportion of variance (57.31%). These eight factors were: (a) sports injury, (b) performance demand, (c) coach relationships, (d) training adaptation, (e) interpersonal relationships, (f) romantic relationships, (g) family relationships, and (h) academic requirements. Cronbach’s α of these factors ranged from .72 to .86, and the reliability for all items was .88, indicating that the result was reliable (See Table 1 for the result of EFA).
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STUDY 3 The purpose of Study 3 was to confirm the factorial stability of the 24-item and 8-factor CSALSS developed for Study 2. Furthermore, in Study 3 the researchers also aimed to present evidence on the initial criterion validity, which is the concurrent and discriminant validity, via correlational analyses surrounding the relationships among CSALSS subscales, positive state of mind, and burnout experiences. Methods Participants & procedure A new sample of the targeted population was recruited during the National Intercollegiate Athletic Games in Taiwan. Valid data of 334 student-athletes from 11 different universities were collected (males = 221, females = 113, M age =19.26 yrs, SD = 1.42). The recruiting procedure was similar to Study 2. Measurements The measurements included the Demographic Questionnaire and the revised 24-item CSALSS. In addition, the researchers administered the following measures for examining concurrent and discriminant validity. Athlete Burnout Questionnaire. The Athlete Burnout Questionnaire (ABQ: Raedeke & Smith, 2001) is a self-reported inventory that assesses athletes’ burnout experiences. The initial factor analyses by Raedeke and Smith revealed that ABQ has three subscales including (a) reduced sense of athletic accomplishment (RA), (b) perceived emotional and physical exhaustion (E), and (c) devaluation of sports participation (D). The Chinese version of ABQ with 11 items and three factors was revised by Lu, Chen, and Cho (2006) through item analysis, EFA, confirmatory factor analysis (CFA), criterion-related validity examination, and test–retest reliability. Participants identified their athletic burnout experiences using a 6-point Likert scale that ranged from 1 (never) to 6 (always). In the present study, the result of CFA confirmed that the factorial structure was suitable for the data. The Cronbach’s α for the three subscales ranged from .80 to .88, and the reliability for all items was .87. These three burnout subscales should be positively correlated with the CSALSS, because athletes’ stress has been identified as leading factor of maladaptive outcomes (Galambos et al., 2005; Johnson & Ivarsson, 2011; Lewis, 1991; Nicholls et al., 2009). Athletic Positive State of Mind Scale (APSMS.). The Athletic Positive State of Mind Scale (APSMS: Chang & Lu, 2002) was adapted from Horowitz and colleagues’ (Horowitz, Adler, & Kegeles, 1988) Positive States of Mind (PSOM), which is regarded as the key variable in measuring stress response. Chang and Lu adapted the original six items of PSOM by replacing the statement of the item’s stem into sports-specific questions and providing preliminary reliability and validity through item analysis, EFA and CFA. These six major elements include: attentional focus, productivity, maintaining responsibility, restful repose, and sensual pleasure. Data in the
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present study supported the single factor structure, and the Cronbach’s α was .86. Given that APSMS represents an individual’s positive state of mind, subscales of CSALSS were expected to have negative or no correlations with APSMS. Statistical Analyses To examine the factor structure of the revised 24-item CSALSS, maximum likelihood CFA using AMOS 17.0 (Arbuckle, 2008) was performed, and the researchers reported the following absolute and incremental fit indices to determine if the 8-factors measurement model fit the data well: (a) the χ 2 /DF ratio; (b) the root mean square error of approximation (RMSEA); (c) the standardized root mean square residual (SRMR); (d) the Goodness of Fit Index (GFI); (e) the Comparative Fit Index (CFI); and (f) the Non-Normed Fit Index (NNFI). The recommendations for good fit are the following: χ 2 /DF ratios between one and three, values for RMSEA values less than .08 along with SRMR values less than .05, and GFI/CFI/NNFI values greater than .90 (Hu & Bentler, 1999; McDonald & Ho, 2002). To examine the internal consistency of the factors, Cronbach’s α coefficient was used as an index. Additionally, the composite reliability (CR > .7: Fornell & Larcker, 1981) and average variance extracted (VE > .5: Kline, 1998) were calculated to examine the fit of internal structure. Finally, using SPSS 17.0, the investigators examined the concurrent and discriminant validity by examining the correlations among CSALSS, APSMS, and ABQ. Results The 8-factor measurement model of the 24-item CSALSS indicated a good fit of the instrument according to the fit indices (RMSEA = .056, SRMR = .049, χ 2 /DF = 2.06, CFI = .925, NNFI = .907, GFI = .926). The factor loadings for the 24 items range from .62 to .92 (Figure 1). Cronbach’s α coefficients were higher than .70, except for the coefficient for the “family relationship” subscale, which was .66. The composite reliability (Fornell & Larcker, 1981) for each subscale was calculated: sports injury (.88), performance demand (.79), coach relationships (.80), training adaptation (.83), interpersonal relationships (.76), romantic relationships (.75), family relationships (.83), and academic requirements (.76), indicating that each was above the .70 standard. The average variance extracted was also calculated: sports injury (.70), performance demand (.55), coach relationships (.57), training adaptation (.62), interpersonal relationships (.52), romantic relationships (.50), family relationships (.62), and academic requirements (.51), which were all above the acceptable standard (.50). As for concurrent and discriminant validity, the Pearson correlations indicated that all of the eight subscales of CSALSS negatively correlated with APSMS. Moreover, most subscales of 24-item CSALSS had low to moderate positive association with the three subscales of ABQ (Refer to Table 2 for the reliability coefficients and correlations of the CSALSS, the APSMS, and the ABQ). GENERAL DISCUSSION Although there are many measurements assessing life stress, very few studies attempted to develop a sports-specific life stress measurement for college student-athletes. The present study
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FIGURE 1 Factor structure of the CSALSS (Study 3).
developed a preliminary self-report questionnaire for such population. The results demonstrate that a 24-item CSALSS containing eight factors is an acceptable tool for measuring college student-athletes’ life stress (see Appendix A). Across these phases, evidence showed adequate factorial structure, concurrent and discriminant validity, and reliability of the instrument.
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TABLE 2 Means, SDs, Reliability Coefficients, and Bivariate Correlations of the CSALSS, the APSMS, and the ABQ (Study 3) 1 1. Sports injury 2. Performance demand 3. Coach relationships 4. Training adaption 5. Interpersonal relationships 6. Romantic relationships 7. Family relationships 8. Academic requirements 9. APSMS 10. ABQ–E 11. ABQ–D 12. ABQ–RA Mean SD .87 — — — — — — — — — — — 3.37 1.31 2 .78 — — — — — — — — — — 3.93 1.17 .23∗ 3 .24∗ .21∗ .78 — — — — — — — — — 2.72 1.06 4 .35∗ .60∗ .46∗ .83 — — — — — — — — 3.67 .97 5 .20∗ .30∗ .35∗ .41∗ .76 — — — — — — — 2.38 .90 6 .09∗ .36∗ .24∗ .38∗ .49∗ .75 — — — — — — 3.25 1.18 7 .12∗ .25∗ .21∗ .26∗ .34∗ .30∗ .66 — — — — — 3.07 .94 8 .23∗ .41∗ .28∗ .47∗ .42∗ 9 −.16∗ −.27∗ −.21∗ −.38∗ −.29∗ 10 .26∗ .20∗ .24∗ .45∗ .26∗ 11 .19∗ .14∗ .31∗ .42∗ .24∗ 12 .16∗ .32∗ .22∗ .41∗ .35∗ .31∗ .23∗ .33∗ −.34∗ .52∗ .52∗ .88 3.16 .95
.33∗ −.25∗ .22∗ .23∗ .27∗ −.14∗ .13∗ .10∗ .76 −.22∗ .28∗ .22∗ — .86 −.10∗ −.24∗ — — .80 .69∗ — — — .84 — — — — 3.66 1.07 3.84 .81 3.42 .96 3.34 1.07
Note: ∗ p < .05; Cronbach’s α is presented on the diagonal as bold font; ABQ–E: perceived emotional and physical exhaustion; ABQ–D: devaluation of sports participation; ABQ–RA: reduced sense of athletic accomplishment.
In the production of CSALSS, the researchers first focused on face validity to confirm the content of the construct. The inclusion of college student-athletes enabled us to collect the substantial stressors that they experienced in their prolonged athletic career. In addition, rather than producing as many similar items as possible, the researchers utilized the Delphi method to eliminate redundant items. It is paramount in the early stage of measurement development that each item, even those that have not yet undergone quantitative statistical examination, is meaningful for respondents. After confirming adequacy of content relevance and representativeness of the items, the CSALSS draft (40 items) was produced and examined through item analysis, EFA, and the evaluation of internal reliability in Study 2. In Study 3, the CFA, the concurrent and discriminant validity testing yield a 24-item CSALSS with eight factors. The newly developed 24-CSALSS contains four factors representing daily life stressors that have been identified by previous life stress scales. These four factors mostly focused on the interpersonal relationship issues and academic difficulties (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009). Furthermore, another four factors with 12 items representing sports-specific stressors were included. Unlike the DALDA, PSS-10, or LESCA, these factors clearly and robustly portrayed athletes’ stress experiences in sports settings (Anshel & Wells, 2000; Fletcher, & Hanton, 2003; Gould et al., 1997; Noblet & Gifford, 2002; Poczwardoswski et al., 2002). After being examined by factor analysis, CSALSS demonstrated proper factorial structure and cumulatively explained variance. Although the 24-item CSALSS demonstrates initial validity and reliability, it is worth noting that Cronbach’s α within the subscale “family relationship” was lower (α = .66). Literature
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indicates that Cronbach’s α changes as a function of the number of items (Nunnally, 1978); precisely, the fewer the items, the lower the internal consistency will be. This means that fewer items in the “family relationship” subscale may be the reason for lower Cronbach’s α. However, the composite reliability of “family relationship” was .83, achieving a “very good” level proposed by Kline (1998). Thus, the researchers supposed that the internal consistency was still acceptable and suggested that supplementary items for the “family relationship” factor would be needed in future study. In terms of discriminant validity, the eight subscales of CSALSS were all negatively associated with APSMS; it is reasonable that athletes with higher stress in both daily life and in a sports setting were less likely to have positive state of mind (Etzel, 2009; Loughran & Etzel, 2008) and instead, negative effects might arise (Nicholls et al., 2009). The result is supported by previous literature; however, one should notice that data in this study revealed the negative relationship between life stress and positive state of mind was not very strong (r = –.14 ∼ –.38). Future study is still needed to examine whether various factors, such as coping skills, sport experiences, or resilient personality, might interact with life stress (Steffen et al., 2009). The results of present study may provide an insight for future investigations. In terms of concurrent validity, the researchers chose a measurement of burnout experiences as a criterion, which has a conceptual overlap with student-athletes’ stress. It has been shown that athletes’ stress leads to many possible maladapted outcomes, such as injury occurrence and decline in performance and emotional exhaustion, which were highly correlated with burnout experiences (Galambos et al., 2005; Johnson & Ivarsson, 2011; Lewis, 1991; Nicholls et al., 2009). In such cases, three subscales of burnout were expected to positively correlate with stress, and the results were consistent with the prediction. Athletes with higher levels of stresses from daily life and sports events had a reduced sense of athletic performance and more perceived emotional and physical exhaustion and devaluation of sports participation. In particular, the researchers also found that “Training Adaption” had the highest correlation with all categories of burnout experiences. A possible explanation is related to college student-athletes’ unsuccessful adjustment to college and athletics (Etzel, 2009; Loughran & Etzel, 2008). Those who provide professional support for student-athletes, such as sports counselors, coaches, and faculty, must be aware of the unique life stress of college student-athletes, and supportive programs offered to these athletes must take all these aforementioned life-related and sports-specific stressors into account (Etzel, 2009). Though results in the present study support that the CSALSS is tenable, there are several limitations worthy of further examination. First, the present study found eight factors considered to constitute college student-athletes’ life stress. However, athletes in the present study were mostly at a higher competitive level. The training system for elite student-athletes in Taiwan may lead to omitting some factors that are important for other athletes. Future research may extend the CSALSS and include diverse samples, such as student-athletes with different ages, competitive levels, genders, and training experiences to comprehensively measure student-athletes’ life stress. Future studies may also examine CSALSS in different cultures. Furthermore, while examining the psychometric properties of the CSALSS, this study provided only a preliminary reliability and validity evaluation. More evidence is needed for the ongoing validation process. Finally, future research that focuses on diverse groups of student-athletes who may confront more specific challenges is warranted. These athletes may have not only visible differences, such as gender and ethnicity, but also less visible differences, such as socioeconomic status, injury or
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disability, career transition stages, and sexual orientation (Etzel, 2009; Loughran & Etzel, 2008). This exploration will be more useful for practical use. To conclude, this article presents a chronology of three empirical studies that produced a new measurement tool with 24 items and identified eight factors that are potential stressors to college student-athletes. The results, coupled with a review of the relevant literature (Etzel, 2009; Galambos et al., 2005; Johnson & Ivarsson, 2011; Loughran & Etzel, 2008; Nicholls et al., 2009), help us understand college student-athletes’ life stress. REFERENCES
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (1999). Standards for educational psychological testing. Washington, DC: Author. Anshel, M. H., & Wells, B. (2000). Sources of acute stress and coping styles in competitive sport. Anxiety, Stress, & Coping, 13, 1–26. Arbuckle, J. L. (2008). Amos 17.0 [Computer software]. Chicago, IL: Small Walters. Baker, R. W., & Siryk, B. (1984). Measuring adjustment to college. Journal of Counseling Psychology, 31, 179–189. Chang, Y. C., & Lu, F. J. H. (2002). The development of Athletic Positive States of Mind Scale (APSMS): Reliability and validity (in Chinese). Bulletin of Sport and Exercise Psychology of Taiwan, 1, 71–80. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 386–396. Etzel, E. F. (2009). Counseling Student Athletes: Issues and interventions. Morgantown, WV: Fitness Information Inc. Fletcher, D., & Hanton, S. (2003). Sources of organizational stress in elite sports performers. The Sport Psychologist, 17, 175–195. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. Galambos, S. A., Terry, P. C., Moyle, G. M., & Locke, S. A. (2005). Psychological predictors of injury among elite athletes. British Journal of Sports Medicine, 39, 351–354. Gould, D., Udry, E., Bridges, D., & Beck, L. (1997). Stress sources encountered when rehabilitating from season-ending ski injures. The Sport Psychologist, 11, 361–378. Holmes, T. H., & Rahe, R. H. (1967). The Social Readjustment Rating Scale. Journal of Psychosomatic Research, 11, 213–218. Horowitz, M., Alder, N., & Kegeles S. (1988). A scale for measuring the occurrence of positive states of mind: A preliminary report. Psychosomatic Medicine, 50, 477–483. Hu, L., & Bentler, P. M. (1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. Johnson, U., & Ivarsson, A. (2011). Psychological predictors of sport injuries among junior soccer players. Scandinavian Journal of Medicine and Science in Sports, 21, 129–136. Kleinert, J. (2007). Mood states and perceived physical states as short-term predictors of sport injuries: Two prospective studies. International Journal of Sport & Exercise Psychology, 5, 340–351. Kline, R. B. (1998). Principles and practice of structural equation modeling. New York, NY: Guilford Press. Lewis, M. (1991). Athletes in college: Differencing role and conflicting expectations. College Student Journal, 10, 195–200 Loughran, M. J., & Etzel, E. F. (2008). Ethical practice in a diverse world: The challenges of working with differences in the psychological treatment of college student-athletes. Athletic Insight, 10. Retrieved from http://athleticinsight. com/Vol10Iss4/Ethical.htm. Lu, F. J. H., Chen, L. H., & Cho, K. H. (2006). Revision of Raedeke and Smith’s Athlete Burnout Questionnaire (ABQ): Analyses of validity and reliability of Chinese version (in Chinese). Physical Education Journal, 39, 83–94. Lustman, P. J., Sowa, C. J., & O’Hara, D. J. (1984). Factors influencing college student health: Development of the psychological distress inventory. Journal of Counseling Psychology, 31, 28–35. McDonald, R. P., & Ho, M. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Method, 7, 64–82.
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Nicholls, A. R., Backhouse, S. H., Polman, R. C. J., & McKenna, J. (2009). Stressors and affective states among professional rugby union players. Scandinavian Journal of Medicine and Science in Sports, 19, 121–128. Noblet, A. J., & Gifford, S. M. (2002). The sources of stress experienced by Australian professional footballers. Journal of Applied Sport Psychology, 14, 1–13. Nunnally, J. (1978). Psychometric theory. New York, NY: McGraw-Hill. Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: An example, design considerations and applications. Information & Management, 42, 15–29. Oshagbemi, T. (1999). Overall job satisfaction: How good are single versus multiple-item measures? Journal of Managerial Psychology, 14, 388–403. Petrie, T. A. (1992). Psychosocial antecedents of athletic injury: The effects of life stress and social support on female collegiate gymnasts. Behavioral Medicine, 18, 127–138. Poczwardoswski, A., Barott, J. E., & Henschen, K. P. (2002). The athlete and coach: Their relationship and its meaning. International Journal of Sport Psychology, 33, 116–140. Raedeke, T. D., & Smith, A. L. (2001). Development and preliminary validation of an athlete burnout measure. Journal of Sport and Exercise Psychology, 23, 281–306. Rushall, B. R. (1990). A tool for measuring stress tolerance in elite athletes. Journal of Applied Sport Psychology, 2, 51–66. Sarason, I. G., Johnson, J. H., & Siegel, J. M. (1978). Assessing the impact of life changes: Development of Life Experiences Survey. Journal of Consulting & Clinical Psychology, 46, 932–946. Schmidt, R. C. (1997). Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences, 28, 763–774. Selye, H. (1974). Stress without distress. Philadelphia, PA: Lippincott. Steffen, K., Pensgaard, A. M., & Bahr, R. (2009). Self-reported psychological characteristics as risk factors for injuries in female youth football. Scandinavian Journal of Medicine and Science in Sports, 19, 442–451. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (4th ed.). Boston, MA: Allyn & Bacon. Yusko, D. A., Buckman, J. F., White, H. R., Pandina, R. J. (2008). Risk for excessive alcohol use and drinking-related problems in college student athletes. Addictive Behaviors, 33, 1546–1556.
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APPENDIX A COLLEGE STUDENT-ATHLETES’ LIFE STRESS SCALE
Directions: Below are 24 statements that describe something that annoys/bothers you or makes you uncomfortable in your daily life as a college student-athlete. Please read each one carefully and circle the number that indicates how often you experience it. Your answers are absolutely confidential. 1 I am annoyed by my injury because it has still not yet fully recovered. 2 I worry about my unstable competitive performance. 3 I am annoyed by my disappointing relationship with my coach. 4 I am annoyed with the training program now. 5 I am bothered by poor social skills in handling interpersonal relationships. 6 I am annoyed with not finding time to encounter romantic partners. 7 I am annoyed by my parents’ high expectations. 8 I am bothered by a lack of motivation for academic learning. 9 I worry about being frequently injured. 10 I worry about dragging my team down. 11 I am annoyed by my coach’s preference for some teammates. 12 I worry that my training is not beneficial to my performance. 13 I am annoyed with being friendless. 14 I am annoyed with being too shy to express myself when I encounter someone I love. 15 I am bothered by difficult situations in my family. 16 I am annoyed when preparing for exams. 17 I am bothered by the slow recovery of my injury. 18 I am afraid of being eliminated from competition because of poor performance. 19 I am annoyed by my coach’s bias against me. 20 I am annoyed by my training load because it is too much for me. 21 I am annoyed by my social skills because it seems like nobody likes me. 22 I am annoyed with not getting along with my romantic partner. 23 I am annoyed with communicating with my family. 24 I worry about my academic skills because I do not know how to learn efficiently.
Never Rarely Sometimes 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
Quite often 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
Very often 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
Always 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
Note: (a) items1, 9, 17 represent “sports injury;” (b) items 2, 10, 18 represent “performance demand;” (c) items 3, 11, 19 represent ”coach relationships;” (d) items 4, 12, 20 represent “training adaptation;” (e) items 5, 13, 21 represent “interpersonal relationships;” (f) items 6, 14, 22 represent “romantic relationships;” (g) items 7, 15, 23 represent “family relationships;” and (h) items 8, 16, 24 represent “academic requirements”
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