This article was downloaded by: [University of Western Ontario] On: 10 February 2015, At: 03:34 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Sports Sciences Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjsp20

Development of the children’s active play imagery questionnaire a

b

a

a

b

Lisa Cooke , Krista Munroe-Chandler , Craig Hall , Danielle Tobin & Michelle Guerrero a

School of Kinesiology, Western University, London, Ontario, Canada

b

Department of Kinesiology, University of Windsor, 401 Sunset avenue, Windsor, Ontario, N9B 3P4 Canada Published online: 10 Jan 2014.

Click for updates To cite this article: Lisa Cooke, Krista Munroe-Chandler, Craig Hall, Danielle Tobin & Michelle Guerrero (2014) Development of the children’s active play imagery questionnaire, Journal of Sports Sciences, 32:9, 860-869, DOI: 10.1080/02640414.2013.865250 To link to this article: http://dx.doi.org/10.1080/02640414.2013.865250

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

Journal of Sports Sciences, 2014 Vol. 32, No. 9, 860–869, http://dx.doi.org/10.1080/02640414.2013.865250

Development of the children’s active play imagery questionnaire

LISA COOKE1, KRISTA MUNROE-CHANDLER2, CRAIG HALL1, DANIELLE TOBIN1, & MICHELLE GUERRERO2 1

School of Kinesiology, Western University, London, Ontario, Canada, and 2Department of Kinesiology, University of Windsor, 401 Sunset avenue, Windsor, Ontario, N9B 3P4 Canada

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

(Accepted 10 November 2013)

Abstract The purpose of the current study was to develop an instrument, the Children’s Active Play Imagery Questionnaire (CAPIQ), to assess imagery use during children’s (7–14 years) active play. Phase 1 involved an assessment of content validity using experts (N = 7), while Phase 2 assessed the factorial validity of the CAPIQ using a sample of children (N = 302). Phase 3 contributed to the factorial validity of the CAPIQ by utilising confirmatory factor analysis among an independent sample of children (N = 252). The final version of the CAPIQ consists of 11 items across three factors: fun, social and capability. Further use of the CAPIQ will aid in identifying types of imagery used among children (7–14 years) in their active play, which may contribute to physical activity interventions. Keywords: imagery, measurement, children, active play

Introduction Imagery has been identified as a psychological skill contributing to changes in an individual’s behaviours, thoughts and beliefs (Hall, 2001). It has been examined extensively in physical activity, including sport and exercise. The reported benefits of imagery use in these domains include improved performance (e.g. Martin, Moritz, & Hall, 1999), enhanced concentration (e.g. White & Hardy, 1998), improved self-efficacy (e.g. MunroeChandler, Hall, & Fishburne, 2008), as well as the effective regulation of arousal levels (e.g. Giacobbi, Hausenblas, Fallon, & Hall, 2003). Moreover, imagery has been effective at improving positive feeling states (e.g. Cumming & Stanley, 2009) and motivation for physical activity behaviours (e.g. Hall, Mack, Paivio, & Hausenblas, 1998; Stanley, Cumming, Standage, & Duda, 2012). While various definitions of imagery have been proposed, the one forwarded by White and Hardy (1998) is often cited. Imagery is: an experience that mimics real experience. We can be aware of “seeing” an image, feeling movements as an image, or experiencing an image of smell, tastes or sounds without actually experiencing the real

thing…it differs from dreams in that we are awake and conscious when we form an image. (p. 389) Much of the sport imagery research has stemmed from Paivio’s (1985) conceptual framework, which posited that imagery serves both motivational and cognitive roles, at both general and specific levels. Cognitive specific imagery is the rehearsal of specific skills, while cognitive general imagery includes images of routines and strategies of play. The motivation functions of imagery consist of motivational specific imagery, which involves imagining specific goals or goal-orientated behaviour, and motivational general imagery, which involves images pertaining to affect and arousal levels. Further refinement of Paivio’s framework resulted in separating the motivational general function of imagery into motivational general-arousal (images associated with regulating arousal and stress) and motivational general-mastery (images associated with being in control, mentally tough, focused and confident) (Hall et al., 1998). The subsequent development of the Sport Imagery Questionnaire (Hall et al., 1998) enabled researchers to examine the use of the five imagery functions by athletes in various sport contexts (e.g. Munroe, Hall, Simms, & Weinberg, 1998)

Correspondence: Krista Munroe-Chandler, Department of Kinesiology, University of Windsor, 401 Sunset avenue, Windsor, Ontario, N9B 3P4 Canada. E-mail: [email protected] © 2013 Taylor & Francis

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

Development of CAPIQ and at various competitive levels (e.g. ArvinenBarrow, Weigand, Hemmings, & Walley, 2008). More recently, there has been an interest in children’s use of imagery (e.g. Munroe-Chandler & Hall, 2005; Munroe-Chandler, Hall, Fishburne, Murphy, & Hall, 2012; Munroe-Chandler, Hall, Fishburne, & Strachan, 2007). However, the assessment of imagery use among youth athletes required the development of a new tool, the Sport Imagery Questionnaire for Children (Hall, MunroeChandler, Fishburne, & Hall, 2009). As suggested by Stadulis, MacCracken, Eidson, and Severance (2002), the direct application of an adult version (of a questionnaire) to a child population would be questionable, given the potential inability of the child to understand particular constructs. Additionally, researchers have noted that measurement tools should cater to the developmental stage of the population being assessed and be formatted (e.g. language, key concepts) appropriately for the sample (Whaley, 2007). As such, recent measurement tools in physical activity contexts have employed this rationale when developing age-appropriate questionnaires (e.g. Crocker, Bailey, Faulkner, Kowalski, & McGrath, 1997; Eys, Loughead, Bray, & Carron, 2009; Martin, Carron, Eys, & Loughead, 2012). Additionally, measurement tools have been developed to assess imagery functions in context-specific domains (e.g. Exercise Imagery Questionnaire; Hausenblas, Hall, Rodgers, & Munroe, 1999; Sport Imagery Questionnaire; Hall et al., 1998). Given the use of imagery in sport by both adults and children, and its use in exercise by adults, exploration of children’s imagery use in activities outside of sport was needed. Accordingly, Tobin, Nadalin, Munroe-Chandler, and Hall (2013) examined children’s use of imagery in their active play (i.e. unstructured leisure-time physical activity1) using a qualitative approach. Focus groups conducted with children aged 7–14 years found that they imagined activities that they enjoy and do often. They imagined playing with friends, family and others (e.g. professional athletes) and being very good (competent) at active play. These preliminarily results indicate that imagery use during active play among youth is evident and may therefore be a viable method to enhance motivation for physical activity, similar to what has been suggested in other activity contexts (e.g. Hall et al., 1998; Stanley et al., 2012). This is important since only 7% of Canadian children are meeting the required daily physical activity levels (Active Healthy Kids, 2010), and we need to identify new avenues to stimulate healthy behaviour. As such, further examination of active play, which is one form of unstructured physical activity, and in particular the role that imagery can have in this context, is warranted (Tobin et al., 2013).

861

Currently, there are no measures for assessing children’s imagery use during their active play. Although the Sport Imagery Questionnaire for Children is an age-appropriate tool for measuring imagery use in children, the context is sport and not active play. Given researchers contend that at least half of children’s physical activity is experienced in unstructured sessions of free play (Veitch, Salmon, & Ball, 2008) and active play imagery may serve different functions than those reported in the sport domain (Tobin et al., 2013), it is important to develop a context-specific measurement tool. Therefore, the purpose of the present study was to develop the Children’s Active Play Imagery Questionnaire (CAPIQ), which is an assessment tool measuring the use of imagery in active play among children (7–14 years). A three-phased approach was conducted, including item development, content validity and factorial validity. Phase 1: operational definition, item generation and item content validity In this phase, the operational definition of active play imagery was established, items were developed and their content was tested. Using terminology proposed by Godin, Anderson, Lambert, and Desharnais (2005), as well as Spink et al. (2006) regarding unstructured leisure-time physical activity among children, we proposed the following operational definition: Active play encompasses unstructured physical activity that takes place during a child’s (7–14 years) free time (Veitch et al., 2008). Some examples of active play activities include: going for a bike ride with friends, playing soccer in one’s backyard, or going skiing. As such, active play imagery involves picturing oneself engaging in unstructured play, such as seeing yourself running fast in tag or imagining how your legs move when bike-riding. Examination of existing literature identifying factors associated with participation in unstructured leisure-time physical activity contributed to the generation of an initial 32-item pool. More specifically, the developed items reflected imagery that would represent the most consistent correlates of children’s unstructured physical activity participation. As observed in previous literature (Sallis, Prochaska, & Taylor, 2000), children and youth (3–18 years) participate in physical activity for various reasons including: biological (e.g. coordination), emotional (e.g. enjoyment), psychological (e.g. achievement orientation) and social (e.g. interaction with peers). Similarly, Davies, Gregory, and White (1995) identified correlates of physical activity in unstructured settings, which included perceived physical competence, intentions, perceived barriers, parental

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

862

L. Cooke et al.

support, support from significant others, programme/facility access, opportunities to be active and time in outdoors. Further examination of physical activity correlates revealed commonalities (Godin et al., 2005; Spink et al., 2006; Weiss & Williams, 2004) despite variations in methodology (e.g. longitudinal, cross-sectional). After identifying the common correlates of unstructured physical activity among children and youth, we acknowledged some broad themes: capability (e.g. perceptions of competence, self-efficacy, intention to be active and achievement orientation), fun (e.g. enjoyment and interest) and social (e.g. encouragement from significant others such as parents and peers, friend’s participation and social support). These themes correspond with the qualitative results reported by Tobin et al. (2013) for children’s use of active play imagery. Using these themes, in addition to evaluating the items for clarity of wording and sentence structure, the authors reduced the pool of items to 16, encapsulating the imagery commonly employed by children in active play settings. Method Each of the 16 items was rated using a Likert scale system which measured the frequency of imagery use (1 = not at all, 2 = a little bit, 3 = sometimes, 4 = often and 5 = very often). Consistent with previously validated questionnaires utilised with children (Sport Imagery Questionnaire for Children; Hall et al., 2009; Sport Friendship Quality Scale; Weiss & Smith, 1999; Competitive State Anxiety Inventory for Children; Stadulis et al., 2002) and in line with Pajares, Hartley, and Valinate’s (2001) suggestion, a short 5-point Likert scale was employed in the present study to reduce attention concerns. All components of Phases 1, 2 and 3 received ethical approval from the University’s research ethics board prior to any data collection procedures. Procedure and data analysis. In accordance with the guidelines provided by Crocker and Algina (1986), the assessment of item-content relevance was conducted by reviewers not involved in the original item development procedures. A preliminary version of the CAPIQ was distributed to expert raters (N = 7) for review. Experts, all of whom had a PhD, were selected for the review panel as a result of their proficiency in conducting physical activity research with children and/or imagery. Experts were asked to match each item in the questionnaire relative to the three broad categories of active play imagery (i.e. capability, fun, social) and then rate the item-content relevance on a 5-point Likert type scale (1 = poor match to 5 = excellent match) following guidelines outlined by Dunn, Bouffard, and Rogers (1999).

Additional comments were requested regarding age-appropriateness and word choice selection for the intended audience (7–14 years). Aiken’s (1985) item content-validity coefficient (V) calculations were conducted to assess the significance of expert’s rating for each item. As such, Aiken’s V was employed to statistically examine the congruency between each item and the judge’s response. For example, the statement “I picture myself having fun” which resulted in a score of V = 0.96, indicated a high match between the particular item and the intended subscale category, fun. Values (V) are expressed from 0 to 1, with values closer to 1 reflecting high scores on item-domain match (i.e. content validity; Dunn et al., 1999). Using the values obtained from our experts, comparison to Aiken’s right-tailed binominal probability table was conducted to establish the significance of V. In addition, further analyses were conducted on the expert rating using recommendations put forth by Penfield and Giacobbi (2004). A 90% confidence interval was calculated to improve the inference of the unknown population value of V (Vp) observed by Aiken’s statistic. Results Using the noted methodology, the critical value of Aiken’s V for testing the null hypothesis (Vp = 0.5) was 0.75 (under a Type I error rate of 0.05; Aiken, 1985). In an effort to further evaluate the criteria for item retention, we employed a null hypothesis of Vp = 0.5 against the alternative hypothesis that Vp > 0.5 when reviewing the 90% score confidence interval. Items for which the null hypothesis was rejected were retained and suggested a positive validation of that item (e.g. the mean rating in the population exceeds 3.0 on the 5-point Likert scale). Employment of noted criteria (i.e. Aiken’s values and the score confidence interval) highlighted six items requiring examination of their content (i.e. remove or revise), while the remaining items were retained (and further revised based on qualitative expert responses). Table I outlines the expert ratings, values of Aiken’s V and the 90% score confidence interval (upper and lower bounds) for all 16 original items of the CAPIQ. As noted, 10 of the original 16 item-domain matches were statistically significant, indicating that these items (as rated by content experts) were applicable to the constructs that they were intended to measure. Four original items were retained (statements: 1, 3, 4, 9 in final version) and five of the items were re-worded/modified (statements: 5–8, 11). In addition, three new items were added as a result of feedback received from the expert panel in conjunction with the statistical results (statements: 2, 10, 12). The experts identified comprehension concerns with some

Development of CAPIQ

863

Table I. Frequency and descriptive statistics for experts’ (N = 7) item content relevance rating, Aiken’s V, and score confidence interval of CAPIQ in Phase 1.

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

Items When thinking about playing … I picture myself laughing I imagine my body positions I imagine joining in with others I picture myself having fun I imagine myself doing the right movements* I see myself playing with my buddies I imagine doing fun physical activities* I imagine myself getting along with others** I imagine enjoying myself I imagine making the correct movements* I picture myself doing activities that have more than one person* I imagine my pals playing with me I imagine how my body moves I imagine myself being cheerful* I see myself with others I see myself being happy*

Poor match (1)

Fair match (2)

Good match (3)

Very good match (4)

Excellent match (5)

90% score confidence interval

M

Aiken’s V

0 0 0 0 1

0 0 0 0 0

2 2 2 0 3

1 2 4 1 3

4 3 2 6 0

5 4.14 4 4.85 3.14

0.82 0.79 0.75 0.96 0.53

0.67; 0.64; 0.60; 0.85; 0.38;

0 0

0 2

1 2

4 2

2 1

4.14 2.85

0.79 0.57

0.64; 0.89 0.42; 0.71

0

0

4

0

3

3.85

0.71

0.56; 0.83

0 0

0 0

0 3

4 1

3 3

4.42 4

0.86 0.58

0.72; 0.94 0.43; 0.72

0

1

2

2

2

3.71

0.68

0.52; 0.80

0 0 0 0 0

0 0 0 0 1

2 1 4 1 1

2 2 1 5 2

3 4 2 1 3

4.14 4.42 3.71 4 4

0.79 0.86 0.68 0.75 0.75

0.64; 0.72; 0.52; 0.60; 0.60;

0.91 0.89 0.86 0.99 0.68

0.89 0.94 0.80 0.86 0.86

Note: *denotes removed items; **denotes revised items.

items in capability imagery. For example, an original capability item “I imagine doing the right movements” resulted in a poor content relevance rating (V = 0.53) as experts commented on a lack of association between correct movements within active play activities. Subsequently, new items were developed to replace all of the original capability items to reflect more appropriate descriptions of movements involved in active play. An example of a revised capability item is, “I imagine the movements that my body makes”. Modification of items reflected slight adjustment in age-appropriate terminology as suggested by experts. Additionally, the stem “When thinking about active play” was added to each item to further strengthen the association with the specific context. Discussion The purpose of Phase 1 was to develop a preliminary measurement tool suitable for assessing the use of imagery in active play among children (7–14 years). The results highlighted inconsistencies in item wording and clarity as indicated by the expert panel and content relevance output, which were subsequently addressed prior to Phase 2. The expert panel evaluated items using a matching task protocol to pair each item with its respective construct and qualitatively elaborated on individual items for further clarification. Given researchers have suggested a

minimum of three items are needed for each construct (DeVellis, 2011; Loewenthal, 2001; Marsh, 2007), the CAPIQ aimed to retain as many items as possible for Phase 2 analysis. As such, a preliminary version of the CAPIQ consisted of 12 items rated on a 5-point Likert scale (1 = not at all to 5 = very often), which was subjected to further examination using a large and representative sample in Phase 2.

Phase 2: principal component analyses The purpose of Phase 2 was to assess factorial structure of the 12-item questionnaire derived from Phase 1 using exploratory techniques. As suggested by Stevens (2002), application of a principal component analysis (PCA) allows investigated variables (e.g. items) to freely associate with each other and effectively establish the number of underlying components. Although three broad themes served to guide the development of the items, the factor structure had yet to be examined. Criteria outlined by Stevens were employed for the current phase, given the psychometric rigidity of PCA.

Method Participants. Youth participants (N = 302) aged 7–14 years (x– = 9.96, s = 2.17) were recruited from

864

L. Cooke et al.

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

various physical activity events (e.g. public swimming, public skating) in southwestern and eastern Ontario. Both males (n = 145) and females (n = 157) voluntarily participated in the study. Instrument and procedures. Participants completed the CAPIQ developed in Phase 1, which consisted of 12 items rated on a 5-point Likert scale from 1 (not at all) to 5 (very often). Facility operators offering various unstructured physical activities were contacted and were requested to grant permission for research to be conducted at their venue. Parental permission and consent, in addition to participant assent, were obtained prior to questionnaire distribution. Participants completed the CAPIQ, which took on average about 7 min,2 with variations in time due to participants’ ages. All participants were informed of their right to withdraw at any point, without consequence, and anonymity of responses was assured. The investigator remained on site until all questionnaires were completed and inquiries were answered. Results The data were subjected to PCA followed by direct oblimin transformation (δ = –1) (Tabachick & Fidell, 2007) to examine the factor structure of the CAPIQ. An examination of both the scree plot (Cattell, 1978) and Kaiser–Guttman’s (λ ≥ 1) stopping rules (Guttman, 1954) suggested the presence of three latent factors. Furthermore, an examination of the face validity of the items comprising the factors also suggested that a three-factor solution was tenable. Thurstone’s (1947) notion of simple structure was used primarily for determining factor interpretation. Consistent with the recommendations of Gorsuch (1983), factor pattern loading of |.30| served as the lower bound of “item meaningfulness” for each factor in the CAPIQ. The results of the PCA suggested that one item (“When thinking about playing, I picture myself laughing”) was factorially complex (i.e. cross-loaded on more than one factor), and indicated that the solution accounted for 57.9% (before transformation) of the CAPIQ item variance. Consequently, another three-factor PCA was pursued following the removal of this troublesome item. The results of this analysis (Table II) resulted in the retention of 11 items defining a three-factor solution. Factor 1 contained four items and was labelled as capability imagery. Factor 2 contained four items and was labelled as social imagery. Factor 3 contained three items and was labelled as fun imagery. The final three-factor solution accounted for 61.4% of the variance in the remaining 11 items. The inter-factor correlations were low to moderate (r1.2 = 0.23; r1.3 = 0.30; r2.3 = 0.44). Two of the three factors

Table II. Factor loadings – PCA;(direct oblimin) solutions for three-factor CAPIQ in Phase 2. Items

Factor 1 Factor 2 Factor 3

When thinking about active play … I imagine the moves that are needed I imagine the positions of my body I imagine the movements that my body makes I imagine how my body moves I imagine joining in with others I see myself playing with my friends I picture myself doing physical activities in a group I imagine my friends playing with me I picture myself having fun I imagine the fun I have doing the physical activities I imagine enjoying myself

0.56 0.81 0.82 0.77 0.63 0.65 0.51 0.67 0.52 0.53 0.56

Table III. Phase 2 descriptive statistics for entire sample (N = 302) on CAPIQ subscales. Subscale Capability Social Fun

x–

s

α

3.18 4.07 4.35

1.02 0.72 0.67

0.82 0.71 0.65

demonstrated acceptable levels of internal consistency (α’s > 0.70) (Nunnally & Bernstein, 1994), however, factor 3 exhibited less than adequate internal consistency (α = 0.65) (Table III). As noted by Tavakol and Dennick (2011), reliance on the use of alpha can lead to situations in which a scale is discarded prematurely. Given Factor 3 was approaching the recommended alpha value (i.e. α > 0.70; Nunnally & Bernstein, 1994) and the resultant alpha value is reflective of measurement scores from each independent sample (Tavakol & Dennick, 2011), it was decided to retain this factor for further psychometric testing. Discussion The results of Phase 2 lend support to a three-factor solution (i.e. capability, fun, social) to assess imagery use among children during their active play. Overall, participants reported using fun imagery most frequently, potentially highlighting that children strongly associate active play with enjoyment. Phase 3: confirmatory factor analyses The purpose of Phase 3 was to conduct a confirmatory factor analysis on the CAPIQ (i.e. 11 items, three factors) using IBM SPSS Amos 20 (2011).

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

Development of CAPIQ

865

The confirmatory factor analysis was completed to assess the fit between the three-factor model observed from the exploratory analysis in Phase 2 and a new sample of independent data. In addition, differences in children’s active play imagery use was examined for both age and gender.

Participants completed the CAPIQ and returned it to the researcher. All participants were informed of their right to withdraw at any point, without consequence, and anonymity of responses was assured.

Methods

The descriptive statistics for examined items are presented in Table IV and a confirmatory factor analysis model is presented in Figure 1. A variety of indices were employed to assess the fit between the suggested three-factor model and participant data. Specifically, the comparative fit index (Bentler, 1990), the normative fit index (Bentler & Bonett, 1980), the Tucker–Lewis Index (Tucker & Lewis, 1973), the root-mean-square error of Approximation (Browne & Cudeck, 1993) and the standardised root-mean-square residual (RMSEA; Bentler, 1995) were utilised. Cut-off values for the comparative fit index, normative fit index and the Tucker–Lewis Index are adequate when values are

Participants. Youth participants (N = 252) aged 7–14 years (x– = 10.4 years, s = 2.3) were recruited from summer activity camp programmes in southwestern Ontario. Both males (n = 118) and females (n = 134) voluntarily participated in the study and represented two distinct age cohorts: 7–10 (n = 134) and 11–14 (n = 118). Thomas, Gallagher, and Thomas (2001) suggest narrow and distinct groupings should be used when studying children as they move from early through middle and late childhood to adolescence. Measure. Participants completed the CAPIQ resulting from Phase 2, which consisted of 11 items rated on a 5-point Likert scale from 1 (not at all) to 5 (very often).

Results

Table IV. Phase 3 descriptive statistics for entire sample (N = 252) on CAPIQ subscales. Subscale

Procedure. Participants were recruited from permissible summer activity programmes. Parental permission and consent, in addition to participant assent, were obtained prior to questionnaire distribution.

Figure 1. Path diagram of three-factor model (standardised).

Capability Social Fun

x–

s

α

3.30 3.76 4.27

1.02 0.81 0.82

0.82 0.73 0.82

866

L. Cooke et al.

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

Table V. Phase 3 descriptive statistics for gender and age cohorts. Capability

Social

Fun

M (s)

M (s)

M (s)

Age 7–10 (n = 134) 11–14 (n = 118)

3.3 (1.1) 3.2 (0.96)

3.8 (0.80) 3.7 (0.82)

4.4 (0.80) 4.2 (0.85)

Gender Male (n = 118) Female (n = 134)

3.2 (1.1) 3.4 (0.92)

3.7 (0.90) 3.8 (0.70)

4.2 (0.91) 4.3 (0.72)

≥0.95 (Hu & Bentler, 1999). Cut-off values for the RMSEA are adequate if the values are below 0.10 (Browne & Cudeck, 1993) and RMSEA is below 0.08 (Hu & Bentler, 1999). The initial factor analysis resulted in an acceptable model fit, with the comparative fit index = 0.95, normative fit index = 0.92, Tucker–Lewis Index = 0.93, RMSEA = 0.07 and RMSEA = 0.06, having met or closely approaching noted cut-offs. Observed results supported a threefactor model, represented by three imagery functions (i.e. fun, social and capability) from the conducted confirmatory factor analysis. Several analyses of variance (ANOVA) (Bonferroni adjustment utilised) were conducted to examine differences among age (7–10 and 11–14) and gender (male, female) for each type of imagery employed. The results indicated that regardless of age or gender, participants reported using fun imagery most frequently, followed by social, and capability imagery. No significant effects were noted between age cohorts (7–10 and 11–14) for any of the imagery functions. However, a significant main effect for gender was found for capability imagery, F (1, 250) = 3.88, P = 0.052, with females reporting more use of this imagery function (Table V). General discussion Previous literature has documented the use of imagery in an active play setting (Tobin et al., 2013). Specifically, qualitative results with children (aged 7–14 years) revealed that they imagined activities that bring enjoyment and partake in frequently. Moreover, they imagined playing with peers, family and others (e.g. professional athletes) and were (competent) at active play. In order to further advance active play research, the aim of the current study was to develop a measurement tool assessing imagery use during active play in children 7–14 years old. By employing a three-phased approach, which involved expert assessment of developed items, preliminary evaluation of the inventory with a sample of children and confirmatory analyses with an independent sample, the final CAPIQ consisted of 11 items

(four capability, four social and three fun), rated on a 5-point Likert scale (1 = not at all to 5 = very often) (see Appendix A). Results from the current study indicate that children engage in images pertaining to the fun they experience, the competence they have for doing the activity and the social relationships they engage in while in active play settings. Findings revealed that female participants used significantly more capability imagery than their male counterparts. Previous researchers found that female youth report having lower self-esteem, which contributes to an overall lack of exercise behaviour (Garcia et al., 1995). Therefore, based on the results presented, girls may employ capability imagery more readily as a tool to increase their confidence for active play in comparison to boys. Individuals with high motivation towards physical activity are characterised by high perceived competence (Wang, Chatzisarantis, Spray, & Biddle, 2002). As such, it is likely that individuals who are more inexperienced (e.g. younger females) may have a greater need for employing capability imagery to improve competence and indirectly increase their physical activity. As previously noted, imagery provides an effective means for changing individuals’ behaviours, thoughts and/or beliefs (Hall, 2001). By identifying the correlates of imagery with active play, future interventions aimed at improving activity levels among children and youth can be established, particularly among those who are highly sedentary. This is especially important given that Canadian children are unable to meet the guidelines which recommend 60 min a day of moderate to vigorous physical activity, and that at least half of their physical activity accumulation should be in active play (unstructured leisure-time physical activity) (Active Healthy Kids Canada, 2010). Future studies should aim to further establish the psychometric properties of the CAPIQ. More specifically, convergent validity is needed to determine if measured imagery constructs on the CAPIQ are theoretically related to other constructs among children (e.g. Organismic Integration Theory; Deci & Ryan, 1985), a direction we aim to pursue in future research. In addition, it is suggested further studies employ the CAPIQ among more diverse populations to highlight the applicability of the instrument.

Acknowledgements Krista Munroe-Chandler and Craig Hall would like to thank the Social Science and Humanities Research Council (SSHRC) for funding support.

Development of CAPIQ Notes

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

1.

2.

Active play can be distinguished from deliberate play. Deliberate play involves early developmental physical activities which can be intrinsically motivating and provide enjoyment. Although active play and deliberate play may encompass similar outcomes, the distinction between the two contexts is that of sport. Specifically, deliberate play is suggested to be a form of sporting activity. Individuals engage in activities (e.g. street ice hockey, backyard soccer) which involve adapting rules from standardised sports, while active play encompasses all forms of unstructured physical activity that takes place during a child’s free time (e.g. jumping on a trampoline, playing tag, backyard soccer). Additionally, deliberate play lends to an athlete’s skill development, while active play may not. Younger-aged participants (7–8 years) required additional time and explanation of the items being asked. Researchers provided standardised elaboration on any item requiring more clarification. Researchers provided additional examples to younger participants of active play situations to enhance their comprehension of the items.

References Active Healthy Kids Canada. (2010). Healthy attitudes start earlier than you think. The Active Healthy Kids Canada report card on physical activity for children and youth. Toronto, ON: Author. Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45, 131–142. Arvinen-Barrow, M., Weigand, D. A., Hemmings, B., & Walley, M. (2008). The use of imagery across competitive levels and time of season: A cross sectional study among synchronized skaters in Finland. European Journal of Sport Science, 8, 135–142. Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238–246. Bentler, P. M. (1995). EQS structural equation programs manual. Enchino, CA: Multivariate Software. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and the goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage. Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York, NY: Plenum Press. Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. New York, NY: Holt, Rinehart, & Winston. Crocker, P. R., Bailey, D. A., Faulkner, R. A., Kowalski, K. C., & McGrath, R. O. (1997). Measuring general levels of physical activity: Preliminary evidence for the physical activity questionnaire for older children. Medicine and Science in Sports and Exercise, 29, 1344–1349. Cumming, J., & Stanley, D. M. (2009). Are images of exercising related to feeling states? Journal of Imagery Research in Sport and Physical Activity, 4(1), 1–23. Davies, P. S., Gregory, J., & White, A. (1995). Physical activity and body fatness in pre-school children. International Journal of Obesity and Related Metabolic Disorders, 19, 6–10. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and selfdetermination in human behaviour. New York, NY: Plenum.

867

DeVellis, R. F. (2011). Scale development: Theory and applications (3rd ed.). Los Angeles, CA: Sage. Dunn, J. G. H., Bouffard, M., & Rogers, W. T. (1999). Assessing item content relevance in sport psychology scale construction research: Issues and recommendations. Measurement in Physical Education and Exercise Science, 3, 15–36. Eys, M., Loughead, T., Bray, S. R., & Carron, A. V. (2009). Development of a cohesion questionnaire for youth: The Youth Sport Environment Questionnaire. Journal of Sport and Exercise Psychology, 31, 390–408. Garcia, A. W., Broda, M. A., Frenn, M., Coviak, C., Pender, N., & Ronis, D. (1995). Gender and developmental differences in exercise beliefs among youth and prediction of their exercise behavior. Journal of School Health, 65, 213–217. Giacobbi Jr., P. R., Hausenblas, H. A., Fallon, E. A., & Hall, C. A. (2003). Even more about exercise imagery: A grounded theory of exercise imagery. Journal of Applied Sport Psychology, 15, 160–175. Godin, G., Anderson, D., Lambert, L., & Desharnais, R. (2005). Identifying factors associated with regular physical activity in leisure time among Canadian adolescents. American Journal of Health Promotion, 20, 20–27. Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Erlbaum. Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrica, 19, 149–161. Hall, C. R. (2001). Imagery in sport and exercise. In R. N. Singer, H. A. Hausenblas, & C. M. Janelle (Eds.), Handbook of sport psychology (2nd ed., pp. 529–549). New York, NY: John Wiley & Sons. Hall, C. R., Mack, D. E., Paivio, A., & Hausenblas, H. A. (1998). Imagery use by athletes: Development of the sport imagery questionnaire. In D. Smith & M. Bar-Eli (Eds.), Essential readings in sport and exercise psychology (pp. 258–264). Champaign, IL: Human Kinetics. Hall, C. R., Munroe-Chandler, K. J., Fishburne, G. J., & Hall, N. D. (2009). The Sport Imagery Questionnaire for Children (SIQ-C). Measurement in Physical Education and Exercise Science, 13, 93–107. Hausenblas, H. A., Hall, C. R., Rodgers, W. M., & Munroe, K. J. (1999). Exercise imagery: Its nature and measurement. Journal of Applied Sport Psychology, 11, 171–180. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. IBM Corp. Released, 2011. IBM SPSS statistics for Windows, version 20.0. Armonk, NY: Author. Loewenthal, K. M. (2001). An introduction to psychological tests and scales. Philadelphia, PA: Taylor & Francis. Marsh, H. W. (2007). Application of confirmatory factor analysis and structural equation modeling in sport and exercise psychology. In G. Tenenbaum & R. C. Eklund (Eds.), Handbook of sport psychology (3rd ed., pp. 774–798). Hoboken, NJ: John Wylie and Sons. Martin, L. J., Carron, A. V., Eys, M. A., & Loughead, T. M. (2012). Development of a cohesion inventory for children’s sport teams. Group Dynamics: Theory, Research, and Practice, 16(1), 68. Martin, K. A., Moritz, S. E., & Hall, C. R. (1999). Imagery use in sport: A literature review and applied model. The Sport Psychologist, 13, 245–268. Munroe, K., Hall, C., Simms, S., & Weinberg, R. (1998). The influence of type of sport and time of season on athletes’ use of imagery. The Sport Psychologist, 12, 440–449. Munroe-Chandler, K. J., & Hall, C. R. (2005). Enhancing the collective efficacy of a soccer team through motivational general-mastery imagery. Imagination, Cognition, and Personality, 24, 51–67.

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

868

L. Cooke et al.

Munroe-Chandler, K. J., Hall, C. R., & Fishburne, G. (2008). Playing with confidence: The relationship between imagery use and self-confidence and self-efficacy in youth soccer players. Journal of Sport Sciences, 26, 1539–1546. Munroe-Chandler, K. J., Hall, C. R., Fishburne, G. J., Murphy, L., & Hall, N. D. (2012). Effects of a cognitive specific imagery intervention on the soccer skill performance of young athletes: Age group comparisons. Psychology of Sport and Exercise, 13(3), 324–331. Munroe-Chandler, K. J., Hall, C. R., Fishburne, G. J., & Strachan, L. (2007). Where, when, and why young athletes use imagery: An examination of developmental differences. Research Quarterly for Exercise and Sport, 78(2), 103–116. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY: McGraw-Hill. Paivio, A. (1985). Cognitive and motivational functions of imagery in human performance. Canadian Journal of Applied Sport Sciences, 10(4), 22–28. Pajares, F., Hartley, J., & Valiante, G. (2001). Response format in writing self-efficacy assessments: Greater discrimination increases prediction. Measurement and Evaluations in Counseling and Development, 33, 214–221. Penfield, R. D., & Giacobbi Jr., P. R. (2004). Applying a score confidence interval to Aiken’s item content-relevance index. Measurement in Physical Education and Exercise Science, 8(4), 213–225. Sallis, J. F., Prochaska, J. J., & Taylor, W. C. (2000). A review of correlates of physical activity of children and adolescents. Medicine & Science in Sports & Exercise, 32, 963–975. Spink, K. S., Shields, C. A., Chad, K., Odnokon, P., Muhajarine, N., & Humbert, L. (2006). Correlates of structured and unstructured activity among sufficiently active youth and adolescents: A new approach to understanding physical activity. Pediatric Exercise Science, 18, 203–215. Stadulis, R. E., MacCracken, M. J., Eidson, T. A., & Severance, C. (2002). A children’s form of the competitive state anxiety inventory: The CSAI-2C. Measurement in Physical Education and Exercise, 6, 147–165. Stanley, D. M., Cumming, J., Standage, M., & Duda, J. L. (2012). Images of exercising: Exploring the links between exercise imagery use, autonomous and controlled motivation to exercise, and exercise intention and behavior. Psychology of Sport and Exercise, 13(2), 133–141. Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (5th ed.). New York, NY: Routledge. Tabachick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston, MA: Allyn and Bacon. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. Thomas, K. T., Gallagher, J. D., & Thomas, J. R. (2001). Motor development and skill acquisition during childhood and adolescence. In R. N. Singer, H. A. Hausenblas, & C. M. Janelle (Eds.), Handbook of sport psychology (2nd ed., pp. 20– 52). New York, NY: Wiley. Thurstone, L. L. (1947). Multiple-factor analysis. Chicago, IL: University of Chicago Press. Tobin, D., Nadalin, E. J., Munroe-Chandler, K. J., & Hall, C. R. (2013). Children’s active play imagery. Journal of Sport and Exercise Psychology, 14, 371–378. Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1–10. Veitch, J., Salmon, J., & Ball, K. (2008). Children’s active free play in local neighbourhoods: A behavioral mapping study. Health Education Research, 23, 870–879.

Wang, J. C. K., Chatzisarantis, N. L. D., Spray, C. M., & Biddle, S. J. H. (2002). Achievement goal profiles in school physical education: Differences in self-determination, sport ability beliefs, and physical activity. British Journal of Educational Psychology, 72, 433–445. Weiss, M. R., & Smith, A. L. (1999). Quality of youth sport friendships: Measurement development and validation. Journal of Sport and Exercise Psychology, 21, 145–166. Weiss, M. R., & Williams, L. (2004). The why of youth sport involvement: A developmental perspective on motivation processes. In M. R. Weiss (Ed.), Developmental sport and exercise psychology: A lifespan perspective (pp. 223–268). Morgantown, WV: Fitness Information Technology. Whaley, D. E. (2007). A life span developmental approach to studying sport and exercise behavior. In G. Tenenbaum & R. C. Eklund (Eds.), Handbook of sport psychology (3rd ed., pp. 645–661). Hoboken, NJ: John Wylie and Sons. White, A., & Hardy, L. (1998). An in-depth analysis of the uses of imagery by high-level slalom canoeists and artistic gymnasts. The Sport Psychologist, 12, 387–403.

Appendix Children’s active play imagery questionnaire Age: ______

Gender: Boy _____

Girl ______

Directions When you picture things in your mind, this is called IMAGERY – like picturing your bedroom or where your desk is in your classroom. You can even use imagery to picture things when playing – like seeing yourself running fast in tag or imagining how your legs move when bike-riding. If you get your body moving and start to sweat when playing, this is called active play. Try to picture yourself doing active play – like going skating with your friends, playing soccer in your backyard, swimming, or going skiing. Remember, active play does not mean organised sport like playing on a hockey team or competing for a gymnastic club. These questions ask how you use imagery (make pictures in your mind) when doing active play. Any question that sounds like something you do a lot should get a high number (5) or if it sounds like something you never do, it should get a low number (1). Remember the questions have to do with your active play – play that gets your body moving – but not organised sport. After you read the question, circle a number that works for you. You can use a number more than once and there is no right or wrong answer.

Development of CAPIQ

Statement

Downloaded by [University of Western Ontario] at 03:34 10 February 2015

(1) When thinking about active play, I imagine the moves that are needed (2) When thinking about active play, I imagine joining in with others (3) When thinking about active play, I picture myself having fun (4) When thinking about active play, I imagine the positions of my body (5) When thinking about active play, I see myself with my friends (6) When thinking about active play, I imagine the fun I have (7) When thinking about active play, I picture myself doing it in a group (8) When thinking about active play, I imagine enjoying myself (9) When thinking about active play, I imagine the movements that my body makes (10) When thinking about active play, I imagine my friends with me (11) When thinking about active play, I imagine how my body moves

869

Not at all A little bit Sometimes Often Very often 1 1 1 1 1 1 1 1 1 1 1

2 2 2 2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4 4 4 4

5 5 5 5 5 5 5 5 5 5 5