Influences of coaches, parents, and peers on the ...

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Scand J Med Sci Sports 2011 doi: 10.1111/j.1600-0838.2010.01277.x

& 2011 John Wiley & Sons A/S

Inﬂuences of coaches, parents, and peers on the motivational patterns of child and adolescent athletes D. K. Chan1, C. Lonsdale2, H. H. Fung3 1

Personality, Social Psychology, and Health Research Group, School of Psychology, University of Nottingham, Nottingham, UK, School of Biomedical and Health Sciences, University of Western Sydney, Penrith, New South Wales, Australia, 3Department of Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong 2

Corresponding author: C. Lonsdale, School of Biomedical and Health Sciences, University of Western Sydney, Locked Bag 1797, Penrith, New South Wales 2751, Australia. Tel: 161-2-9852-5403, E-mail: [email protected] Accepted for publication 22 November 2010

The purposes of this study were to assess the relative impact of social inﬂuences initiated by coach, parents, and peers on children and adolescent athletes’ motivational patterns, involving self-rated eﬀort, enjoyment, competence, and competitive trait anxiety. Questionnaire data were collected from 408 youth swimmers (aged 9–18 years). Results of multi-group structural equation modeling analyses generally showed that compared with athletes in the other age

group, the social inﬂuence from mother was stronger in childhood (mean age 5 10.87 years; SD 5 1.00), and that from peers was greater in adolescence (mean age 5 16.32 years; SD 5 1.15). The social inﬂuence from coach was more inﬂuential for athletes’ eﬀort and enjoyment in childhood, and competence in adolescence. We concluded that age appeared to moderate the impact of social inﬂuence from signiﬁcant others on young athletes’ sport experiences.

Millions of young people in developed nations participate in organized sport, and the quality of their experiences may have implications for their psychosocial development, as well as their attitudes toward physical activity in later life (Holt, 2007). Thus, it is important for researchers to investigate the factors that inﬂuence young people’s experiences in sport. In particular, sport psychology researchers have been independently exploring how coaches, parents, and peers can create environments that will foster adaptive and maladaptive motivational outcomes in young athletes (e.g., White et al., 2004; Vazou et al., 2006). However, ﬁndings about the role of signiﬁcant agents have been mixed across diﬀerent theories. We argue that the age of athletes may moderate the importance of these social agents to the motivational outcomes in sport. In this study, we investigated the relative inﬂuences of coaches, parents, and peers on the motivational patterns of children (aged 9–12 years) and adolescents (aged 15–18 years).

ents, are important social agents for consolidating children’s perceived competence, and aﬀect motivational orientation. However, the process of socialization and the cognitive maturation of children may inﬂuence the impact of signiﬁcant others (Harter, 1978, 1981). Findings from some studies based on EMM (Harter, 1978, 1981) provided initial evidence on how age moderated children’s perceived importance of competence feedback from signiﬁcant others. For instance, Horn and Hasbrook (1986) investigated players of three age groups (age 5 8–9, 10–11, and 12–14 years) in a youth soccer league. Compared with the two younger groups, the eldest group valued evaluative feedbacks from parents and spectators less, regarded the results of the competition in terms of winning or losing as less important, and relied more on peer comparison to judge their performance. Another study by Horn and Weiss (1991) examined the sources of competence feedback from 134 children from grade 3 to grade 7 who took part in a motor skill/sport training program. Results showed that, in comparison with the children under 10 (age 5 8–9 years), children aged between 10 and 13 years showed reduced preference for evaluative feedback from their parents. Moreover, they relied on feedback from peer comparison more than the children under 10. Nevertheless, no signiﬁcant difference between the two groups was found in the

Primary investigations One of the earliest theories to address the role of signiﬁcant others in sport was the eﬀectance motivation model (EMM; Harter, 1978, 1981). According to EMM, signiﬁcant socializing others, especially par-

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Chan et al. importance of coach/teacher feedback. Finally, similar age diﬀerences among 160 physical education (PE) students in late childhood and early adolescence were reported by McKiddie and Maynard (1997). Students in grade 10 (age 5 14–15 years) showed less reliance on the evaluations of their parents and PE teachers, but they displayed higher dependence on feedback from peer comparison than that of students in year 7 (age 5 11–12 years). Research on motivational climates Another line of research investigating the role of signiﬁcant others in youth sport has been based on the achievement goal theory (AGT; Nicholls, 1989), which also highlights the importance of childhood development and social factors in establishing adaptive motivations in achievement context (also see Ames, 1992). A number of AGT-based studies have shown that signiﬁcant others may exert social inﬂuences on individuals by emphasizing particular expectations, demands, and rewards. For example, White et al. (1998) assessed the perceived social inﬂuence initiated by coaches, PE teachers, and parents among school-aged athletes (age 5 10–14 years) who attended PE lessons in schools as well as training for sport teams. They found that athletes’ style of attributions and focus related to the sport outcomes (i.e., achievement goal orientation) were associated with the social inﬂuence initiated by coaches and parents, but not PE teachers. Vazou et al. (2006) preliminarily compared the relative impact of the social inﬂuence from peers in comparison with that from coaches among 493 teenage athletes (age 5 12–17 years). It was found that, among these young athletes, a positive social inﬂuence (i.e., environments emphasizing eﬀort and improvement) from coach predicted self-reported eﬀort, and that from peers predicted perceived competence, while a negative social inﬂuence (i.e., environments emphasizing social comparisons and mistake penalization) from coach predicted competitive trait anxiety. Moreover, compared with the positive social inﬂuence from coach, the positive social inﬂuence from peers appeared to be a stronger predictor of enjoyment. A recent study conducted by Papaioannou et al. (2008) examined the impact of perceived social inﬂuence initiated by coach, mother, and friends among 14-year-old and 11-year-old athletes. Although they did not compare the diﬀerence between the two age groups, the social inﬂuences initiated by these three important social agents explained a substantial amount of variance of the achievement goal orientations of the athletes. However, research using AGT has seldom examined the relative importance of diﬀerent social agents on diﬀerent age groups. As far as we know, only one

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study based on AGT has directly tested the moderating eﬀect of age on the relative importance of signiﬁcant agents on students’ motivational patterns in PE. Carr et al. (1999) examined the relative impact of parents-, peers-, and teacher-initiated social inﬂuences on children (N 5 87; mean age 5 12.2) and adolescent (N 5 70; mean age 5 15.1) PE students. The results generally showed that parents were the most inﬂuential socializing agent for children; whereas, PE teacher and peers were the most inﬂuential socializing agents for adolescents. In particular, for children, the social inﬂuences from father and mother were associated with their eﬀort, enjoyment, and interest for PE. In contrast, for adolescents, the social inﬂuences initiated by PE teacher and peers were related to students’ eﬀort, enjoyment, and pressure/tension in PE. Nevertheless, Carr and colleagues’ study was conducted in the PE context, where participation is often mandatory. Our current investigation focused on youth sport, where participation is typically voluntary and, therefore, the inﬂuences of signiﬁcant others may be fundamentally diﬀerent from those in PE. The present investigation In sum, the social inﬂuences (e.g., evaluative feedback, motivational climate) initiated by coach, parents, and peers are all important to young athletes’ motivational patterns, but their relative impact on particular motivational outcome may not necessarily be consistent, and this inconsistency may plausibly be caused by the variation of participants’ age across diﬀerent studies. Although previous studies based on either EMM or AGT have addressed the potential moderating eﬀect of athletes’ age, they presented a number of limitations that hinder our full understanding of developmental diﬀerences in the role of signiﬁcant others on young athletes. First, previous studies based on Harter’s model only examined the role of signiﬁcant agents by asking athletes to rate the importance of each source of information they perceived (e.g., Horn & Weiss, 1991; Horn et al., 1993); however, ratings of importance might not directly represent the impact of signiﬁcant others on athletes’ motivation patterns in sport (e.g., enjoyment and eﬀort). Although some research examined the relationship between the perceived importance of sources of information and competence of young athletes, very little attention has been placed on other motivational outcomes (e.g., Horn & Hasbrook, 1986; Horn & Weiss, 1991). Rather than comparing the ratings on relative importance between the social agents (e.g., Horn & Hasbrook, 1986; Horn & Weiss, 1991), the present study aimed to test the strength of relationships between social inﬂuences and four motivational

Inﬂuences of coaches, parents, and peers on athletes outcomes in sport that were frequently used in previous studies: eﬀort, enjoyment, competence, and trait anxiety (e.g., Carr et al., 1999; Vazou et al., 2006). Second, the group ages between the comparative groups in previous studies were often too close to each other (e.g., Horn & Hasbrook, 1986; Horn & Weiss, 1991; Horn et al., 1993); thus, the eﬀects of age could be suppressed by the participants whose ages were at the upper or lower edges of the groups. In this study, the age gap of the participants between the child group and the adolescent group was at least 3 years in order to minimize this possibility. Third, previous research on the diﬀerential importance of the sources information considered the positive and negative social inﬂuences as a single dimension (e.g., Horn et al., 1993). However, diﬀerent feedback (i.e., punishment vs positive reinforcement) from various social agents may give rise to very diﬀerent results. To address this issue, the current study attempted to distinguish between positive reinforcement and punishment when measuring the inﬂuences of parents, coaches, and peers on young athletes. Finally, most research into the developmental diﬀerences did not formally compare the relative inﬂuences of signiﬁcant others between children and adolescents. For example, Carr et al. (1999) used two separate sets of multiple regressions, respectively, for the group of children and the group of adolescents. Although the prediction of perceived social inﬂuences initiated by father, mother, PE teacher, and peers to various outcome variables in the regression for children was somewhat diﬀerent from that for adolescents, one was not able to tell how diﬀerent they were, and whether the diﬀerences were signiﬁcant. Instead, this study used structural equation modeling (SEM) to directly test a moderation hypothesis in a more precise and powerful manner. SEM has several advantages over the traditional regression model. For example, SEM allows examination of relationships between latent (i.e., error-free) variables. In addition, by using a multigroup SEM (MG-SEM), we tested the invariance of the proposed relationships of the variables between two diﬀerent age groups.

in sport. We further predicted that punishment from these social agents would be negatively associated with athletes’ eﬀort, enjoyment, and competence, and positively related to athletes’ trait anxiety in sport. Based on the age diﬀerences in social interaction patterns in sports found in previous studies (e.g., Horn & Hasbrook, 1986; Horn & Weiss, 1991; Carr et al., 1999), we hypothesized that the impact of social inﬂuences (including positive social reinforcement and punishment) initiated by parent and peer would be diﬀerent between children and adolescents. In childhood, the social inﬂuence from parents was expected to be more predictive of outcomes than that of peers. In adolescence, the social inﬂuence from peers was predicted to be more predictive of outcomes than that of parents. Finally, we preliminarily investigated the social inﬂuence from coaches relative to those from parents and peers in childhood and adolescence. However, we oﬀered no ﬁrm hypotheses with respect to this line of inquiry. Method Participants and procedure Swimming is one of the most popular sports in Hong Kong (Sit et al., 2006). It is an activity whose training is generally considered to be suitable and safe for both children and adolescents. Although swimming is often categorized as an individual sport, swimmers usually have their trainings and competitions (e.g., relays) in a team, so they experience as many social interactions with their teammates as they do with parents and coaches. Therefore, swimmers were chosen to be our target sampling population. After obtaining approval from a university Research Ethics Committee, we collected 408 questionnaires from young swimmers (mean age 5 12.48 years, SD 5 2.96 years, range 5 9–18 years) who had received regular training in swimming clubs or school teams for 1–5 years (M 5 3.36 years, SD 5 2.53 years). Participants were Hong Kong Chinese whose native language was Cantonese. All participants in this study and their parents or guardians provided informed consent. In particular, they were informed of the voluntary nature of the study, the rights of withdrawal, and the conﬁdentiality of the data. The questionnaire took approximately 15 min to complete. The subsample of youths from single-parent families was not large enough (N 5 30) to conduct separate analyses, and we therefore removed these data.

Measures

Hypothesis Both EMM (Harter, 1978) and AGT (Nicholls, 1989; Ames, 1992) suggest that signiﬁcant others may create social environments that are adaptive or maladaptive to the motivational patterns of young athletes. We hypothesized that coach, father, mother, and peer’s positive reinforcements (i.e., positive feedback, and reward for improvement) would be positively associated with eﬀort, enjoyment, and competence, and negatively related with trait anxiety

Perceived social influences In order to identify potential item content that would have meaning for all three types of social inﬂuences (i.e., coaches, parents, and peers), we ﬁrst examined the subscales and items from existing scales intended to assess positive reinforcements and punishment of signiﬁcant others in sport, including Sources of Competence Information Scale (Horn & Amorose, 1998), Perceived Motivational Climate in Sport Questionnaire-2 (PMCSQ-2; Newton et al., 2000), Parent-Initiated Motivational Climate Questionnaire-2 (White & Duda, 1993), and Peer Motivational Climate in Youth Sport (Ntou-

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Chan et al. manis & Vazou, 2005). From them, we extracted eight items for positive social reinforcement, four of which were related to positive reinforcement for eﬀort and four of which were related to positive reinforcement for improvement. We then extracted another four items representing punishment for mistake (Horn & Weiss, 1991; White et al., 1998; Vazou et al., 2006). For each item, we deleted nouns that speciﬁed a particular social agent. For example, an item from the PMCSQ-2, ‘‘On this team, the coach gets mad when a player makes a mistake’’ was modiﬁed to ‘‘_______ gets angry when I make a mistake.’’ At the end of this process, we had created 12 items for which ‘‘coach,’’ ‘‘mother,’’ ‘‘father,’’ or ‘‘teammates’’ could be the subject. These items are displayed in Table 1. Participants responded to 48 items (i.e., 12 for each social inﬂuence) using seven-point Likert scales ranging from 1 (not true at all for me) and 7 (very true for me). As participants might have had numerous coaches or groups of teammates, they were instructed to rate the coach or group of teammates from the swimming team they perceived as the most important.

Chinese version of questionnaire A team of three bilingual individuals with training in psychology translated the measures into Chinese (the native language of the participants). The items were then back-translated by an independent group. The resultant Chinese questionnaire was pilot-tested by 10 children (age 5 8–12 years) and 10 adolescents (age 5 14–19 years). These individuals’ written and verbal feedback indicated that the questionnaire was comprehensible both by children and adolescents.

Analyses We screened the data to ensure that all values were within the possible range, examined the univariate and multivariate normality statistics, and checked for the presence of multivariate outliers (Mahalanobis distances). We also examined the pattern of missing data and replaced missing values using an Expectation Maximization algorithm. Statistical power of each SEM analysis was computed according to the algorithm of MacCallum et al. (1996); a value of 0.80 or higher revealed adequate statistical sensitivity to estimate the parameters in the model.

Motivational outcomes We assessed four motivational outcomes, including eﬀort, enjoyment, competence, and competitive trait anxiety. The measure of eﬀort (four items), competence (six items), and enjoyment (ﬁve items) were adapted, respectively, from the Eﬀort Subscale of the Intrinsic Motivation Inventory (McAuley et al., 1989), the Physical Self-Perception Proﬁle (Fox, 1990), and the enjoyment items of a previous study concerning motivation and enjoyment in schoolwork and sport (Duda & Nicholls, 1992). The corresponding items of eﬀort, competence, and enjoyment were slightly modiﬁed to ﬁt the context of swimming. The trait anxiety measure (21 items) was adopted from the Sport Anxiety Scale (Smith et al., 1990). Seven-point Likert scales ranged from ‘‘strongly agree’’ (7) to ‘‘strongly disagree’’ (1) were used for all items. The internal reliabilities of the eﬀort (a 5 0.82), enjoyment (a 5 0.94), competence (a 5 0.91), and anxiety (a 5 0.93) measures were satisfactory. Finally, participants were asked to provide various biographical data including sex, age, ethnicity, family status (e.g., single- vs two-parent household), and the number of years spent in training. Table 1. Core items for the perceived social influences in sport scale

My coach/father/mother/teammates Positive reinforcement

Punishment

1 Encourages me to improve my skills by working on my weaknesses* 2 Encourages me to improve* 3 Praises me when I develop new skills 4 Praises me when I improve the skills I do not do well. 5 Emphasizes always trying my best* 6 Encourages me to try my hardest* 7 Praises me when I try hard* 8 Encourages me to keep trying after I make a mistake* 9 Criticizes me when I make a mistake* 10 Makes negative comments when I play poorly* 11 Gets angry when I make a mistake* 12 Criticizes me when I play poorly*

*The item was retained in the final model.

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Factor analyses of the perceived social influences in sport scale We used exploratory factor analysis (EFA) to examine the factor structure of the 12 items from the scale measuring perceived social inﬂuences in sport. We used principal-axis factoring with an oblimin rotation to conduct four EFAs; one each for the coach-, father-, mother-, and peer-related datasets. Data for these analyses were obtained from a subsample of 97 participants (mean age 5 13.29, SD 5 0.76, range 13–14 years; 54.5% male), whose data were not used in any subsequent analyses. We then divided the rest of the data into two groups. The child group (n 5 184; mean age 5 10.87 years; SD 5 1.00; 62.8% male) ranged from 9 to 12 years old, and the adolescent group (n 5 97; mean age 5 16.32 years; SD 5 1.15; 66.3% male) ranged from 15 to 18 years old. Conﬁrmatory factor analysis (CFA) was used to test if the factor structure of the Perceived Social Inﬂuences in Sport Scale yielded from the EFA was psychometrically reliable across the two age groups.

SEM The overall goals of our SEM were (a) to test the relative inﬂuence of coach, parent, and peer on four motivationrelated outcome variables: enjoyment, eﬀort, competence, and anxiety, and (b) to examine the invariance of these relationships across child and adolescent samples. EQS version 6.1 (Bentler, 2004) was the statistical package used to run all the SEM analyses. We tested four models in the children’s data and four models in the adolescents’ data. Each model had eight latent predictor variables (one positive reinforcement and one punishment variable for coach, father, mother, and peers) and one latent outcome variable (eﬀort, enjoyment, competence, or anxiety). We decided not to include all four outcome variables within the same model in order to avoid an excessively large parameters-to-participants ratio and to ease interpretation. In these single-group analyses, we ﬁrst tested the ﬁt of the measurement model (essentially a CFA) and then tested the full structural model (Anderson & Gerbing, 1988). We assessed model ﬁt by examining two absolute (RMSEA and SRMR) and two incremental (TLI and CFI) ﬁt index. We adopted the traditional criteria (TLI and CFI ^ 0.90; SRMR

Inﬂuences of coaches, parents, and peers on athletes Table 2. Cronbach’s a, correlations, means, and standard deviations for the study variables of all participants (N 5 378)w

Variables

1

1. Coach-positive reinforcement 1 2. Coach punishment 0.08 3. Father-positive reinforcement 0.48** 4. Father punishment 0.06 5. Mother-positive reinforcement 0.44** 6. Mother punishment 0.06 7. Peer-positive reinforcement 0.32** 8. Peer punishment 0.12* 9. Effort 0.43** 10. Enjoyment 0.42** 11. Competence 0.18** 12. Anxiety 0.12* Cronbach’s a 0.84 Mean 5.52 Standard deviation 1.00

2

3

– – 1 – 0.03 1 0.45** 0.27** 0.11* 0.57** 0.46** 0.11* 0.00 0.36** 0.23** 0.04 0.11* 0.36** 0.04 0.37** 0.08 0.25** 0.22** 0.12* 0.81 0.85 4.69 5.47 1.35 1.06

4

5

6

7

8

9

10

11

12

– – – 1 0.15** 0.52** 0.00 0.35** 0.11* 0.10* 0.20** 0.16** 0.82 4.51 1.47

– – – – 1 0.28** 0.37** 0.03 0.43** 0.36** 0.26** 0.191 0.87 5.46 1.15

– – – – – 1 0.10* 0.39** 0.12* 0.04 0.17** 0.27** 0.84 4.52 1.47

– – – – – – 1 0.23** 0.36** 0.29** 0.22** 0.06 0.89 4.87 1.31

– – – – – – – 1 0.01 0.01 0.15** 0.21** 0.88 3.78 1.54

– – – – – – – – 1 0.63** 0.47** 0.16** 0.82 5.51 1.17

– – – – – – – – – 1 0.44** 0.07 0.94 5.65 1.25

– – – – – – – – – – 1 0.13* 0.91 4.78 1.26

– – – – – – – – – – – 1 0.93 4.52 1.16

**Correlation is significant at the 0.01 level (two-tailed), *Correlation is significant at the 0.05 level (two-tailed). w After omitting the data from athletes of single-parent home (n 5 30), the total sample size of this study was 378, including the participants from the child group (n 5 184; aged 9–12 years), adolescent group (n 5 97; aged 15–18 years), and the subsample used only in the exploratory factor analysis (n 5 97; aged 13–14 years).

and RMSEA scores % 0.08) as indicators of an adequate ﬁt, with Hu and Bentler’s (1999) criteria (TLI and CFI40.95, RMSEAo0.06, SRMRo0.08) as evidence of a good ﬁt. Finally, we conducted MG-SEM. For each model, we ﬁrst tested the invariance of the measurement model by ﬁtting progressively more constrained models (loadings, errors, variances, and covariances). When DCFI40.01, we concluded that the parameter was not invariant across the child and adolescent samples (Cheung & Rensvold, 2002). Finally, we tested the invariance of the structural model across the two samples by systematically constraining the paths from each predictor to the outcome variable. When Dw2 between the original and the constrained model was signiﬁcant (Po0.05), we considered the strength of the relationship to be diﬀerent across the samples (Steiger et al., 1985).

Results Preliminary analyses Data were univariately normally distributed and there were no multivariate outliers (Po0.001); however, Mardia’s normalized kurtosis coeﬃcient of 22.23 was higher than the cutoﬀ point (i.e., 5) recommended by Byrne (2006), which indicated multivariate non-normality. As a result, we used robust maximum likelihood methods to protect the analyses against violations of any assumptions regarding normality when conducting the SEM analyses and the chi-square diﬀerence tests of invariance for the MG-SEMs (Satorra & Bentler, 2001). There was no apparent pattern to the missing data, and we replaced these values using an Expectation Maximization algorithm. Statistical power of all SEM analyses were higher than 0.83, revealing that the sample sizes of both the child and the adolescent samples were large enough to exclude the likelihood of type II error. The mean, standard deviation, and Cronbach’s

a of all variables in the study, and their correlations are shown in Table 2.

Psychometric properties of the perceived social influences in sport scale In EFAs, two factors emerged for each of coach-, father-, mother-, and peer-initiated social inﬂuence. Full details regarding factor loadings are available from the ﬁrst author. Two items from the positivereinforcement subscale had strong loadings on both factors and were eliminated (see Table 1). The remaining positive-reinforcement items loaded strongly on the ﬁrst factor (mean 5 0.75, SD 5 0.12), with relatively low loadings on the second factor (mean 5 0.25, SD 5 0.12). Items intended to represent punishment loaded strongly on the second factor (mean 5 0.74, SD 5 0.14), but only weakly on the ﬁrst factor (mean 5 0.26, SD 5 0.13). In summary, once the two items were deleted, the EFAs showed a relatively clear and simple structure across all four EFAs, with the two factors accounting for between 62.60% (social inﬂuence from coach) and 66.76% (social inﬂuence from peers) of the total variance. CFA also revealed that the two-factor model of the Perceived Social Inﬂuences in Sport Scale ﬁt the data of the child group and the adolescent group satisfactorily (df 5 34; CFI ^ 0.90, RMSEA % 0.08, SRMRo0.08), apart from peerinitiated social inﬂuence in the adolescent group that displayed marginally acceptable ﬁt indices (df 5 34; CFI 5 0.91, RMSEA 5 0.09, SRMR 5 0.09). However, the overall pattern of the CFAs supported the psychometric properties of the scale (Table 3).

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Chan et al. SEM For single-group CFA of the measurement models and SEM of the full structural models, the data ﬁtted the models well in both the child and the adolescent samples. Table 4 showed the ﬁt indices of the structural models. The ﬁt indices of the measurement models were identical to the structural model because both types of model identiﬁed and included estimations of all possible paths between latent factors; hence the ﬁt statistics of the measurement models were not presented separately. In the children’s data, social inﬂuence predictors accounted for 57.0% of the variance in eﬀort, as well as substantial portions of variance in enjoyment (43.1%), competence (24.9%), and anxiety (35.1%). Social inﬂuence predictors also accounted for moderate-to-large amounts of variance in the adolescent sample (eﬀort 5 46%, enjoyment 5 33%, competence 5 36%, anxiety 5 13%). Path estimates from

Table 3. Confirmatory factor analysis results for the perceived social influences in sport scale

Power w2

df TLI CFI SRMR RMSEA RMSEA 90% CI

Age 9–12 years Coach 0.95 55.78 34 0.93 0.95 0.07 Father 0.99 106.00 34 0.88 0.91 0.08 Mother 0.83 35.01 34 0.99 0.99 0.04 Peers 0.86 114.69 34 0.90 0.92 0.07 Age 15–18 years Coach 0.95 49.72 34 0.88 0.91 0.08 Father 0.94 63.57 34 0.87 0.90 0.09 Mother 0.95 54.34 34 0.87 0.90 0.08 Peers 0.94 62.73 34 0.87 0.91 0.09

0.06 0.08 0.01 0.08

0.03–0.09 0.07–0.11 0.00–0.06 0.07–0.11

0.07 0.08 0.08 0.09

0.02–0.11 0.06–0.13 0.04–0.11 0.06–0.13

All w2 statistics were significant at Po0.05. Power, statistical power; w2, Satorra–Bentler scaled chi-square; df, degree of freedom; TLI, Tucker–Lewis index; CFI, comparative fit index; SRMR, root mean square residual; RMSEA, root mean square error of approximation; CI, confidence interval.

the four structural models of each sample can be seen in Table 4. Next, we tested the invariance of the measurement models across the child and adolescent samples. We tested a baseline measurement model with no constraints, which ﬁtted the data well according to most indices (CFI40.93, RMSEAo0.05, SRMRo0.06), regardless of the outcome variable that was used. Testing progressively more constrained models (loadings, errors, variances, and covariances) did not result in DCFI40.01, thereby indicating that the measurement models were invariant across the two groups. (Complete results are available from the ﬁrst author.) In the ﬁnal stages of our analyses, we tested the invariance of the structural models. The baseline model with no constraints ﬁtted the data well in all four models, according to most indices (CFI40.93, RMSEAo0.05, SRMRo0.06). By systematically constraining the individual path coeﬃcients, we were able to ascertain which relationships between reinforcements and outcome variables were signiﬁcantly diﬀerent (i.e., Dw2 signiﬁcant at Po0.05) across the child and the adolescent samples. Similar patterns emerged in relation to the eﬀort and enjoyment outcome variables, with peer-positive reinforcement and coach-positive reinforcement acting as stronger positive predictors in the adolescent group than in the child group, and mother-positive reinforcement acting as a stronger predictor in the child group than in the adolescent group. The mother-punishment was also a stronger negative predictor of eﬀort in the child group than in the adolescent group. With respect to the competence outcome variable, signiﬁcant group diﬀerences were observed in the coeﬃcients associated with the coach-punishment, mother-positive reinforcement, and peer-punishment predictors. Coach-punishment was a stronger negative predictor in the adolescent group than in the

Table 4. Single-group structural model fit statistics

Age 9–12 years Effort Enjoyment Competence Anxiety Age 15–18 years Effort Enjoyment Competence Anxiety

Power

w2

df

TLI

CFI

SRMR

RMSEA

RMSEA 90% CI

R2

0.94 0.95 0.95 0.94

189.13 223.68 322.41 202.90

116 134 173 116

0.94 0.94 0.91 0.94

0.96 0.96 0.93 0.96

0.04 0.05 0.06 0.05

0.06 0.06 0.07 0.06

0.04–0.07 0.05–0.07 0.06–0.08 0.05–0.08

0.57 0.43 0.25 0.35

0.94 0.89 0.95 0.95

157.52 186.47 252.90 175.41

116 134 173 116

0.91 0.92 0.92 0.92

0.94 0.94 0.92 0.92

0.08 0.07 0.07 0.07

0.06 0.06 0.07 0.07

0.03–0.08 0.04–0.08 0.05–0.09 0.05–0.09

0.46 0.33 0.36 0.13

R2 column indicates the percentage of variance explained for the dependent variables in the structural model. All w2 statistics were significant at Po0.05. Power, statistical power; w2, Satorra–Bentler scaled chi-square; df, degree of freedom; TLI, Tucker–Lewis index; CFI, comparative fit index; SRMR, root mean square residual; RMSEA, root mean square error of approximation; CI, confidence interval.

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Inﬂuences of coaches, parents, and peers on athletes Table 5. SEM results

Endogenous variable

TLI

CFI

RMSEA (90% CI)

SRMR

Statistical powerw

Effort

0.93

0.95

0.04 (0.03–0.05)

0.06

0.94

Enjoyment

0.93

0.95

0.04 (0.04–0.05)

0.06

0.95

Competence

0.91

0.92

0.05 (0.04–0.05)

0.07

0.95

Anxiety

0.91

0.93

0.05 (0.04–0.06)

0.06

0.95

Exogenous variables Chi-square test of age difference, Po0.05* Coach pos* Coach pun Father pos Father pun Mother pos* Mother pun* Peer pos* Peer pun Coach pos* Coach pun Father pos Father pun Mother pos* Mother pun Peer pos* Peer pun Coach pos Coach pun* Father pos Father pun Mother pos* Mother pun Peer pos Peer pun* Coach pos Coach pun Father pos Father pun Mother pos* Mother pun* Peer pos Peer pun

Path estimatesz Po0.05* Children

Adolescents

0.40* 0.13 0.18 0.28 0.53* 0.41* 0.14 0.04 0.32* 0.13 0.01 0.16 0.35* 0.35* 0.12 0.04 0.12 0.01 0.00 0.31 0.33* 0.17 0.04 0.07 0.20 0.24 0.30 0.28 0.09 0.38* 0.26* 0.38*

0.08 0.24 0.15 0.37* 0.09 0.01 0.63* 0.10 0.18 0.15 0.03 0.49* 0.02 0.37 0.44* 0.14 0.40* 0.53* 0.20 0.13 0.49* 0.08 0.31* 0.43* 0.20 0.22 0.13 0.03 0.41* 0.18 0.03 0.17

*significant difference at Po0 .05. w

The indices were taken from multi-group structural equation models. The path estimates were taken from single-group structural equation models. TLI, Tucker–Lewis index; CFI, comparative fit index; RMSEA, root mean square error of approximation; CI, confidence interval; SRMR, root mean square residual; pos, positive reinforcement; pun, punishment; SEM, structural equation modeling. z

child group. Mother-positive reinforcement was a positive predictor in the child group, but a negative predictor in the adolescent group. Peer-punishment was a stronger positive predictor in the adolescent group than in the child group. Finally, signiﬁcant group diﬀerences were observed in relation to mother-initiated social inﬂuence predicting competitive trait anxiety. Mother-positive reinforcement in the adolescent group and motherpunishment in the child group formed positive associations with anxiety, but the associations were not signiﬁcant in the other group. (See Table 5 for details.) Discussion In this study, we hypothesized that the relative impact of coach, parents, and peer-initiated social inﬂuences diﬀered according to the athletes’ age. As

expected, analyses revealed that the social inﬂuences from mothers was more important for children than for adolescents. Also, in line with hypotheses, the social inﬂuence from peers was important for adolescents, but was less important for children. Finally, the social inﬂuence from coaches was complex, appearing more important for athletes’ enjoyment and eﬀort in childhood, but more important for athletes’ competence in adolescence.

Effort and enjoyment In relation to the eﬀort and enjoyment outcomes, results supported our hypotheses that the role of parents was more important in childhood than in adolescence, but only with respect to mothers. This result diﬀered somewhat from that of Carr et al. (1999), who found that the climates created by both parents were important. However, our ﬁndings are in

7

Chan et al. line with the evidence that, compared with fathers, mothers may exert a greater inﬂuence on their children’s physical activity experiences (Bois et al., 2005). This heightened maternal inﬂuence may be due to the fact that mothers usually spend more time with their children than do fathers, as childcare is traditionally regarded as women’s responsibility (Sayer et al., 2004). In line with our hypothesis, the role of peers appeared to be more important in adolescence than in childhood. Thus, ﬁndings from our study provide additional evidence regarding the importance of peers in relation to the enjoyment of adolescent athletes in sport (Horn & Hasbrook, 1986; Horn & Weiss, 1991; Carr et al., 1999). In contrast, coachpositive reinforcement formed positive associations with children’s eﬀort and enjoyment in sport, but the associations were not signiﬁcant in the adolescent sample. Similarly, Vazou et al. (2006), found that, compared with peer-positive reinforcement, coachpositive reinforcement was a weaker predictor of enjoyment in adolescents (age 5 12–17 years). However, Vazou and colleagues also observed that positive reinforcement of eﬀort and improvement initiated by coaches and peers were associated with coach-rated eﬀort in adolescent athletes, while we found that peers’ positive reinforcement, but not coach-positive reinforcement, predicted self-rated eﬀort. Perhaps, when coaches reinforce hard work in the team (i.e., the task climate in Vazou and colleagues’s study), they are more likely to perceive athletes as putting forth more eﬀort. Another explanation can be drawn from the fact that the age of our adolescent sample (15–18 years) was slightly higher than that of the adolescent sample of Vazou and colleagues. For these older adolescents, the inﬂuence of coaches may be reduced and the impact of peers may be heightened, compared with the relationships observed in somewhat younger adolescents. However, it is important to discuss why fathers’ punishment showed positive relationships with eﬀort and enjoyment in our adolescent sample, a result that was contrary to our predictions. The eﬀects of punishment may plausibly depend on the cognitive maturation of young athletes and the social agent who deliver the reinforcement. Jodl et al. (2001) examined how parental belief inﬂuenced early adolescent’s (seventh grader) career aspirations in sport. It was found that the parental belief about children’s talent and ability in sport was associated with children’s desire to pursue a career in sport, but this association was partially mediated by the instrumental support oﬀered by father. In that sense, to enhance the value adolescents assign to sport, parents’ positive appraisals for sport involvement may not be adequately helpful. Behavioral engagement and instrumental support from father, such as constructive criticism, could be an

8

essential element. Alternatively, cultural diﬀerences may play a role. The adaptive role of father-punishment observed within our sample of Chinese athletes was in contrast to typical ﬁndings from the Western countries (e.g., White & Duda, 1993; White et al., 2004). This might reﬂect the cultural diﬀerences in social interactions and inter-personal relationship. For instance, the principles of Confucianism (a Chinese traditional belief system) are suggested to play a role in Hong Kong young people’s motives in sport participation (Ha et al., 2010). Under the belief system of Confucianism, children are expected to show complete obedience and submissiveness to their parents, particularly to their fathers (Ha et al., 2010), and such beliefs may then inﬂuence how children understand negative feedbacks from parents. Indeed, future studies should investigate if adolescent athletes are more likely to view punishment as more constructive than child athletes do, and whether this phenomenon is more likely to occur for a particular social agent (i.e., father) in a speciﬁc culture. Competence and anxiety Consistent with our hypothesis, mother-positive reinforcement and mother-punishment were important positive predictors of children’s competence and anxiety, respectively. These ﬁndings again underscore the impact of parents on children’s adaptive motivations in sport (e.g., Bois et al., 2005). However, motherpositive reinforcement surprisingly formed a negative association with adolescents’ competence (i.e., in the direction opposite to that observed with children). Similarly, mother-positive reinforcement had a positive relationship with anxiety in the adolescent group. These results are in contrast with typical ﬁndings concerning the adaptive inﬂuences of positive reinforcement (i.e., task-involving climates; Vazou et al., 2006; Harwood et al., 2008). A comparison of these results and those concerning eﬀort and enjoyment outcomes suggest that the positive reinforcement initiated by mother is usually important and adaptive to children’s motivation in sport, but it might be less helpful or even detrimental to adolescents’ sport experiences. This somewhat surprising possibility may be explained by the decreased quality of the mother–child relationship from childhood to adolescence (Larson & Richards, 1991). These worsening relationships may negate the potential beneﬁts of positive reinforcement. On the contrary, the positive reinforcement and the punishment initiated by peers were strongly related to adolescents’ competence ratings. Again, these ﬁndings underscore the important role of peers in adolescent athletes, which is in line with the ﬁndings in previous literature (Horn & Hasbrook, 1986; Horn & Weiss, 1991; McKiddie & Maynard,

Inﬂuences of coaches, parents, and peers on athletes 1997). However, peer-punishment was unexpectedly related positively to perceived competence of adolescent athlete. Consonant with the results regarding eﬀort and enjoyment, punishment again displayed an adaptive role on the motivational outcomes of adolescent athletes, but its positive inﬂuence on competence was only initiated by peers, instead of by fathers. In addition, the association between peerpunishment and anxiety observed in the child sample was not signiﬁcant in the adolescent sample. Although the strength of this association was not signiﬁcantly diﬀerent between child athletes and adolescent athlete, this pattern of results once again suggest that adolescent athletes, who have more inter-personal experience in sport than do children, may be more likely to perceive punishments as constructive, or at least less maladaptive. Apart from peers’ inﬂuences, coaches also appeared to be important agents in determining adolescents’ sport competence perceptions. Unlike the prediction of enjoyment, positive reinforcement initiated by coaches predicted adolescents’ competence, but not children’s competence. We speculate that this result may be due to age diﬀerences in sport participation motives. A number of studies have suggested that enjoyment is a dominant motive for children’s participation in sport (e.g., Woods et al., 2007), and thus coach may inﬂuence this outcome variable at this age. Later on, during adolescence, when physical competence is perceived to be more important (Weiss & Williams, 2004), coach’s feedback may have a larger inﬂuence on competence perceptions. Unexpectedly, the social inﬂuence initiated by coaches predicted competitive trait anxiety in neither age group. This result is in contrast to Vazou et al.’s (2006) ﬁnding that the negative social inﬂuence (i.e., emphasis of mistake penalization and comparison) initiated by coaches predicted anxiety in adolescent athletes, even when the variance explained by that of peers was taken into account. In contrast to Vazou and colleagues, our study included parents’ social inﬂuence as predictors of anxiety. These additional predictors may have attenuated the apparent social inﬂuence of coaches. Further research should investigate possible reasons for the discrepancy between our ﬁndings and those of Vazou and colleagues, including possible cultural variations in the coachreinforcement–anxiety relationship. Limitations In line with Duda’s (2001) suggestion, we developed a scale that allowed assessment of psychosocial environment to be standardized across socializing agents. Results from EFA, CFA, and path estimates supported the reliability, factorial validity, discriminant validity, and concurrent validity of these items.

However, it should not be assumed that our questionnaire assessed all aspects of perceived social inﬂuence in sport. First, the scale was only developed and tested among swimmers; thus, its applicability to athletes in other sports remains uncertain. Second, there may be aspects that are unique to a particular socializing agent, such as peers’ relatedness support (Keegan et al., 2010), and parents’ role modeling (Dorsch et al., 2009), which were not covered in the scale. Thus, this preliminary measure of perceived social inﬂuences in sport would require further development, reﬁnement, and testing in future studies. In addition, the age groups in this study were formed based only on the age of the participants, which could be confounded by gender diﬀerences in maturation. Nevertheless, according to Tanner’s (1986) classiﬁcation system, the vast majority of our adolescent group was likely in Stage 4 or 5. Thus, gender diﬀerences in puberty pattern were unlikely to be a confounding variable of our age categorization. Moreover, female on average enters Tanner’s Stage 3 or 4 from Stage 2, respectively, at 13 or 14 years (Tanner, 1986), so the female participants in the child group in general should still be in Stage 2 or below as the male participants did. Indeed, the early maturation pattern of female and the presence of early-maturers may aﬀect the homogeneity of participants’ stage of development in the child group, so further studies should use sexual maturation as an index of participants’ stages of development, and test if gender interacts with the eﬀect of age on the inﬂuences of signiﬁcant others. Furthermore, we cannot exclude the possibility that the age diﬀerences found in this study were the result of diﬀerences in overall skill levels between junior players and senior players (Horn et al., 1993; Weiss & Amorose, 2005). Finally, in the current study, we only compared the relative inﬂuence of socializing agents across two age groups within the context of swimming, and we did not include a longitudinal design to observe the change of social inﬂuences, so the results may be inﬂuenced by cohort eﬀects. Further studies with improved designed should examine the developmental changes in the relative inﬂuence of social agents among athletes of the same cohort over the period of childhood and adolescence, and also test the eﬀects of some other potential moderators of signiﬁcant others’ inﬂuence, such as sport types (e.g., individual sport vs team sport), parents’ sport background, coach–athlete relationship, and peer-friendship quality.

Perspectives Findings from this study suggest that age appears to moderate the impact of signiﬁcant others on young athletes’ sport experiences. In particular, the mother

9

Chan et al. seems to play a more important role in children, peers tend to exert greater inﬂuence on adolescents, and coaches are likely to have greater impact on children’s eﬀort and enjoyment and adolescents’ competence. The pattern of results implies that interventions that foster athletes’ adaptive involvement in sport, such as the mastery approach to

coaching (Smith et al., 2007), might be the most eﬀective if they target certain socializing agents according to the age of the athletes involved.

Key words: age, anxiety.

sport,

competence,

enjoyment,

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Concussion Information for Parents, Coaches, and Referees.pdf ...