Free
Research Article  |   July 2012
Reliability and Validity of the McDonald Play Inventory
Author Affiliations
  • Ann E. McDonald, PhD, OTR/L, is Lead Occupational Therapist, Fullerton School District, Occupational Therapy Department, 2200 East Commonwealth Avenue, Fullerton, CA 92831; aemcdonald3@gmail.com
  • Cheryl Vigen, PhD, is Assistant Professor of Research, University of Southern California Division of Occupational Science and Occupational Therapy, Los Angeles
Article Information
Pediatric Evaluation and Intervention / Rehabilitation, Participation, and Disability / Children and Youth
Research Article   |   July 2012
Reliability and Validity of the McDonald Play Inventory
American Journal of Occupational Therapy, July/August 2012, Vol. 66, e52-e60. doi:10.5014/ajot.2012.002493
American Journal of Occupational Therapy, July/August 2012, Vol. 66, e52-e60. doi:10.5014/ajot.2012.002493
Abstract

OBJECTIVE. This study examined the ability of a two-part self-report instrument, the McDonald Play Inventory, to reliably and validly measure the play activities and play styles of 7- to 11-yr-old children and to discriminate between the play of neurotypical children and children with known learning and developmental disabilities.

METHOD. A total of 124 children ages 7–11 recruited from a sample of convenience and a subsample of 17 parents participated in this study.

RESULTS. Reliability estimates yielded moderate correlations for internal consistency, total test intercorrelations, and test–retest reliability. Validity estimates were established for content and construct validity.

CONCLUSION. The results suggest that a self-report instrument yields reliable and valid measures of a child’s perceived play performance and discriminates between the play of children with and without disabilities.

Play, as a central childhood occupation, has often been referred to as an important but elusive construct in occupational therapy and related disciplines (American Occupational Therapy Association, 2008; Herron & Sutton-Smith, 1971; Huizinga, 1950; King et al., 2004; Reilly, 1974). Occupational therapists often evaluate components of a child’s play performance using a variety of data, including observation, interviews, and related assessments (Parham & Fazio, 2008). A review of the play literature in occupational therapy, however, indicates a scarcity of reliable and valid play measures from the perspective of the child. Self-report assessments with adequate psychometric properties are needed to enable occupational therapy practitioners to develop meaningful goals with clients, document ongoing treatment effectiveness and client-reported outcomes, and contribute to evidence-based practice in our profession (Coster, 2008; Kramer, Kielhofner, & Smith, 2010).
Difficulty in play performance has been documented for children who have learning, developmental, emotional, and coordination difficulties (Cordier, Bundy, Hocking, & Einfeld, 2010; Muys, Rodger, & Bundy, 2006; Poulsen, Ziviani, Cuskelly, & Smith, 2007; Rogers, Cook, & Meryl, 2005). Specifically, Poulsen et al. (2007)  found that boys ages 10–13 yr with developmental coordination disorder (DCD) were reported to have higher rates of loneliness and lower participation rates in physical activities, whether structured or unstructured, than boys without DCD. Muys et al. (2006)  identified play differences in children with autism on two different assessments, and Cordier et al. (2010)  found that children with attention deficit hyperactivity disorder scored inconsistently on social play items related to empathy compared with typically developing peers. The need to provide reliable and valid measures of play for the child with learning and developmental disabilities has been supported by the writings of A. Jean Ayres (1980, 1982) and subsequent occupational therapy researchers (e.g., Parham & Fazio, 2008).
Understanding the nature of play for school-age children can also increase practitioners’ understanding of the importance of this occupation in children’s daily activities. Although diversity in the interpretation of play behavior exists historically (Erikson, 1950; Herron & Sutton-Smith, 1971; Reilly, 1974), the role of play in the school-age child’s acquisition of cognitive, physical, and psychosocial skills continues to be an area of interest in occupational therapy (Parham & Fazio, 2008). Knowledge regarding the child’s perceived play activities and play style would help practitioners understand the areas of play performance in which a child may be experiencing a sense of difficulty or of competence (Florey, 2005; McDonald, 1987). School-age children typically participate in play activities in a variety of settings (e.g., home, school, community), both alone and with peers. Consequently, primary caregivers may not always be aware of the activities in which the child actually engages or the child’s inner motivation and subjective experience during play (Miller & Kuhaneck, 2008). Person-centered data about the lived experience of children with and without disabilities can also contribute to the occupational science and occupational therapy knowledge base regarding the multifaceted elements of play from the child’s perspective.
In the occupational therapy field, published self-report play and leisure assessments often assess children’s play interests and participation levels (Henry, 2000; King et al., 2004; Rosenblum, Sachs, & Schreuer, 2010) but do not provide specific information about play quality, including peer acceptance, cooperation, social participation, and physical coordination. A review of play assessments from occupational therapy and related disciplines indicated that most measures for children rely primarily on observation and ratings of the child’s performance during spontaneous play (Kuhaneck, Spitzer, & Miller, 2010; Parham & Fazio, 2008). Although observation and interviews with caregivers and teachers often are necessary to validate and succinctly describe the play performance of children, self-report inventories can provide valuable insight into the child’s perceived style of play. School psychologists often use self-report inventories with sound psychometric properties to obtain information about peer relations and social competence (Ladd, 1999) and about experiences with bullying (Reynolds, 2003), although not necessarily within the context of play.
This article’s goal is to describe the instrument development process of the McDonald Play Inventory (MPI), a self-report play inventory, and to examine its internal reliability and validity among both neurotypical children and children with known disabilities. Specifically, the research questions guiding this study are as follows:
  1. 1.Can a self-report inventory reliably and validly measure the types and frequencies of play activities and play styles of 7- to 11-yr-old children?
  2. 2.Can the proposed inventory discriminate between the play of neurotypical children and children with known or suspected disabilities (i.e., learning disabilities [LD], autism spectrum disorder [ASD], mild intellectual impairment, Down syndrome)?
Method
Research Design
We used instrument development procedures outlined by Benson and Clark (1982)  and Thorndike and Thorndike-Christ (2010)  in this research. As part of the institutional review board approval process, the directors of each participating agency reviewed the research proposal. Site administrators gave written approval for the study, and letters of introduction describing the study, along with consent forms, were sent home to all eligible participants.
Instrument
The MPI is a two-part, self-report inventory developed by the principal investigator (Ann E. McDonald) and is a potentially useful clinical assessment that has demonstrated positive initial psychometric properties (McDonald, 1987, 1992). Initial research on the reliability and validity of the MPI demonstrated the instrument’s ability to discriminate between the play of neurotypical children and of children with known LDs (McDonald, 1987, 1992). The play domains or categories measured using this instrument were derived from the play literature and field studies.
The first part of the MPI, the McDonald Play Activity Inventory (MPAI), measures the child’s perceived frequency of engagement in four mutually exclusive categories (10 activities in each). These categories form the four subscales of the MPAI: (1) Fine Motor (e.g., color pictures, make models, play with Legos®, make clay or dough projects), (2) Gross Motor (e.g., practice shooting basketballs, play catch with a ball, play four square, play kickball); (3) Social Group (e.g., play board games with friends, hang out with friends, go to the park with a friend, play pretend games with a friend or family member), and (4) Solitary (e.g., play a game alone, sing by yourself, play with dolls or action figures alone, daydream). The child is asked to read each item and rate how frequently he or she participates in the activity by circling one of five Likert-scale responses (never, about once or twice a year, about once or twice a month, about once or twice a week, or almost every day).
The second part of the MPI, the McDonald Play Style Inventory (MPSI), measures the types and frequencies of play behaviors in four domains: physical coordination, cooperation, peer acceptance, and social participation. The MPSI consists of 24 play behavior items (6 items in each category, with equal numbers of positively and negatively worded items), 12 neutral play activity items, and 4 “lie” or social desirability items. Sample play behavior items in the Physical Coordination subscale include “I can catch balls that are thrown to me” and “I have trouble kicking a ball or jumping rope”; in the Cooperation subscale, “I play by the rules of the game” and “I get into fights easily during a game”; in the Peer Acceptance subscale, “I make friends easily” and “I am teased by other children on the playground”; and in the Social Participation subscale, “I play over at a friend’s house” and “I play alone because I am afraid to ask other children to play with me.” The Neutral subscale play activities (e.g., “I play ball games”) and Lie subscale items (e.g., “I always have fun no matter what I am doing”) are included to deter respondents from using the same response set and to assess the influence of a social desirability factor in respondents’ responses. The same 5-point Likert scale is used for the response options (never, hardly ever, sometimes, a lot, always). All items for the MPAI and MPSI were written by the principal investigator on the basis of field studies, observation, 1-day diary records, and the relevant play literature. A panel of content experts (i.e., pediatric occupational therapists) placed the items in categories.
The MPAI was designed to yield factual information regarding frequency of participation in an activity, whereas the MPSI was designed to elicit how the child feels, or the affective component. Likert scales are generally selected for the development of affective instruments (Thorndike & Thorndike-Christ, 2010). The panel of 10 pediatric occupational therapists who served as content experts recommended item revisions reflecting the current types of play activities of children from middle- and upper-middle-class families residing in Southern California. After obtaining informed consent, the authors administered the MPI to 10 children with and without disabilities and made final revisions to the instrument.
Participant Selection
Children were recruited over the course of a year (2009–2010) from a sample of convenience drawn from a camp, an elementary school, and two private practice clinics in close geographic proximity. Participant criteria included age of 7 to 11 yr, socioeconomic background of middle and upper-middle class, and English as the child’s primary language. Children of any ethnicity were eligible to participate. The neurotypical children were identified as being without any known disability by the child’s teacher, parent, or camp counselor. Children with known or suspected disabilities (in the absence of a diagnosis) were identified by teacher, occupational therapist, or parent report as having LD according to the accepted definition (Handler & Fierson, 2011). Children with high-functioning ASD, Down syndrome, and mild intellectual disability (ID) were identified as such by the child’s teacher, parent, therapist, or camp counselor. Children with moderate to severe ID were not included in this study because of expected comprehension difficulties with items and response options, as observed during a previous pilot test of the instrument. Children and parents who agreed to be in the study, met participant criteria, and returned the signed consent forms were included in the study.
Data Collection
The two-part revised MPI was administered by the principal investigator (McDonald) at the camp and school sites. Typically, small groups of 2–4 children were administered the survey outdoors in a quiet location or in a classroom setting. Because of the large number of participants at the school site and limited time to collect data, group sizes of up to 40 children were seen during recess or a nonacademic period. Neurotypical children typically asked for assistance to clarify items by raising their hand. Any child who had a suspected or known LD was given extra support in reading test items and answering questions that arose during administration of the inventory. The average time to complete the inventory without assistance was 15 min; with assistance, it was approximately 20–30 min.
The clinic sites were the primary source of participants with known disabilities (ASD, LD, or mild ID). Occupational therapists who worked in each clinic received instruction on how to administer the inventory, and they provided parents of children who met the inclusion criteria with a letter from the principal investigator describing the study. The treating therapist administered the MPI to each child individually in the clinic setting, usually as part of the therapy session or over two consecutive sessions. Individual administration of the MPI allowed for more time to complete the inventory and read items as needed than did administration to groups of children. If a child had a question about a particular item, the therapist assisted in interpreting the item.
Finally, parents who participated in the study received the MPI (hand delivered or mailed home) after the principal investigator received the child’s completed survey. The parent version contained the same content as the child version and provided directions to answer the survey from the parents’ own perspective on their child’s frequency of play activities and style of play. Although it was not always possible to identify which parent completed the inventory, in most cases it was the mother of the participant. Inventories returned were scored in preparation for data analysis.
Data Analyses
Individual item scores were not normally distributed, and correlations were calculated using Spearman correlation. Subscale and total inventory scores, however, did not diverge materially from normal, and thus Pearson correlations and t tests were used in their analyses. Subscale total and subscale intercorrelations were calculated using Pearson correlation. Internal consistency was measured using Cronbach’s α. Test–retest reliability was measured using Pearson correlation. Parent–child agreement (concurrent validity) was measured using Pearson correlation, and parent–child differences were assessed using paired-sample t tests. All data were analyzed using SAS System for Windows (Version 9.2, SAS Institute, Cary, NC).
Results
Participants
The study sample consisted of 124 children, including 89 who were neurotypical and 35 who had disabilities (Table 1). Of the 35 children with disabilities, 17 had known or suspected LD, 13 had high-functioning ASD, 4 had Down syndrome (all of whom had mild ID, and 1 also had autism), and 1 child had a known mild ID. The ethnicity of the participants was approximately 50% White, 45% Asian-American, and 5% Latino. The majority of the children were from middle- and upper-middle-class socioeconomic backgrounds, as assessed by the director of each participating agency.
Table 1.
Participant Age and Gender
Participant Age and Gender×
Neurotypical Children
Children With Disabilitiesa
Age (yr)BoysGirlsBoysGirlsTotal
7885122
8998026
91195227
101184326
11884323
Total4742269124
Table Footer NoteaDisabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.
Disabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.×
Table 1.
Participant Age and Gender
Participant Age and Gender×
Neurotypical Children
Children With Disabilitiesa
Age (yr)BoysGirlsBoysGirlsTotal
7885122
8998026
91195227
101184326
11884323
Total4742269124
Table Footer NoteaDisabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.
Disabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.×
×
Item Analyses and Intercorrelations
The results of our analyses supported the inclusion of the items in each inventory; each item was moderately correlated (.27 to .75) with the respective subscale score. In addition, intercorrelations between the subscales on each inventory and between the total inventory or scale scores were obtained to determine the degree of relationship between the scales and subscales (Table 2). Moderate to strong correlations (.47 to .81) were found between each subscale and total scale score. The intercorrelations between the subscales ranged from low (<.25) to moderate (.50 to .71). The intercorrelation between the total inventory scores likewise fell in the moderate range (.49), suggesting that the two inventories were measuring related but different traits of play.
Table 2.
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)×
Range of Item CorrelationsGMFMSOCSLMPAI TotalPCCOPASPNLMPSI Total
GM.33–.66
FM.33–.75.32
SOC.32–.68.54.52
SL.27–.61.25.42.40
MPAI total.17–.64.69.77.81.72
PC.36–.70.47.03.22.04.24
CO.52–.66.05.00.07−.05.02.27
PA.38–.67.37−.01.27.04.21.39.28
SP.40–.64.21.06.28−.11.13.33.20.45
N.30–.62.46.43.48.28.55.11−.08.16.04
L.65–.71.53.27.41.21.47.36.30.52.34.35
MPSI total.02–.63.59.26.50.14.49.63.47.72.59.55.75
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table 2.
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)×
Range of Item CorrelationsGMFMSOCSLMPAI TotalPCCOPASPNLMPSI Total
GM.33–.66
FM.33–.75.32
SOC.32–.68.54.52
SL.27–.61.25.42.40
MPAI total.17–.64.69.77.81.72
PC.36–.70.47.03.22.04.24
CO.52–.66.05.00.07−.05.02.27
PA.38–.67.37−.01.27.04.21.39.28
SP.40–.64.21.06.28−.11.13.33.20.45
N.30–.62.46.43.48.28.55.11−.08.16.04
L.65–.71.53.27.41.21.47.36.30.52.34.35
MPSI total.02–.63.59.26.50.14.49.63.47.72.59.55.75
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
×
The moderate correlations between the subscales and between the scales demonstrated an expected association between the child’s perceived physical coordination and participation in gross motor play activities (.47); that is, children who reported greater participation in gross motor play activities (who were more likely to be boys than girls; data not shown) perceived themselves as more physically coordinated and accepted by peers (.39). Children who reported a preference for social participation versus social isolation also reported peer acceptance (.45).
Internal Consistency
The MPAI and MPSI each achieved acceptable internal consistency values of .84 and .79, respectively (Table 3). These findings are similar to those of the first pilot test (.87 and .83) and provide an estimate of how well the items on the scales and subscales measure the same content domain (McDonald, 1987).
Table 3.
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)×
Construct Validity (N = 124)
Unadjusted Values
Values Adjusted for Age and Genderd
Test–Retest Correlationb (n = 7)
M (SD)
Least Squares M
SubscaleM (SD)Internal Consistencya (N = 124)RpNeurotypical ChildrenChildren With DisabilitiespcNeurotypical ChildrenChildren With Disabilitiesp
GM24.42 (6.40).70.59.1624.87 (6.64)23.29 (5.69).2224.9023.21.20
FM26.49 (6.91).65.75.0526.25 (6.39)27.11 (8.15).5326.1727.32.40
SOC27.09 (5.98).60.47.2927.33 (5.58)26.49 (6.94).4827.2326.74.69
SL25.90 (7.18).71.94.00225.96 (6.92)25.74 (7.91).8825.9325.82.94
MPAI total103.90 (19.68).84.69.09104.39 (18.54)102.63 (22.55).65104.21103.09.78
PC23.50 (3.77).56.06.9124.13 (3.57)21.89 (3.84).00324.1521.85.002
CO24.84 (3.64).63.80.0325.36 (3.58)23.51 (3.49).0125.3223.62.02
PA22.60 (3.79).52.18.7023.27 (3.41)20.91 (4.20).00223.2820.89.002
SP22.10 (3.77).58.90.0122.73 (3.52)20.51 (3.96).00322.7220.55.004
N34.58 (6.17).72.02.9734.30 (5.68)35.29 (7.30).4334.2135.53.29
L13.58 (3.29).51.48.2813.93 (2.96)12.69 (3.90).0913.9512.65.05
MPSI total141.21 (14.88).79.82.02143.73 (13.23)134.80 (17.00).002143.62135.09.004
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table Footer NoteaCronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.
Cronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.×
Table 3.
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)×
Construct Validity (N = 124)
Unadjusted Values
Values Adjusted for Age and Genderd
Test–Retest Correlationb (n = 7)
M (SD)
Least Squares M
SubscaleM (SD)Internal Consistencya (N = 124)RpNeurotypical ChildrenChildren With DisabilitiespcNeurotypical ChildrenChildren With Disabilitiesp
GM24.42 (6.40).70.59.1624.87 (6.64)23.29 (5.69).2224.9023.21.20
FM26.49 (6.91).65.75.0526.25 (6.39)27.11 (8.15).5326.1727.32.40
SOC27.09 (5.98).60.47.2927.33 (5.58)26.49 (6.94).4827.2326.74.69
SL25.90 (7.18).71.94.00225.96 (6.92)25.74 (7.91).8825.9325.82.94
MPAI total103.90 (19.68).84.69.09104.39 (18.54)102.63 (22.55).65104.21103.09.78
PC23.50 (3.77).56.06.9124.13 (3.57)21.89 (3.84).00324.1521.85.002
CO24.84 (3.64).63.80.0325.36 (3.58)23.51 (3.49).0125.3223.62.02
PA22.60 (3.79).52.18.7023.27 (3.41)20.91 (4.20).00223.2820.89.002
SP22.10 (3.77).58.90.0122.73 (3.52)20.51 (3.96).00322.7220.55.004
N34.58 (6.17).72.02.9734.30 (5.68)35.29 (7.30).4334.2135.53.29
L13.58 (3.29).51.48.2813.93 (2.96)12.69 (3.90).0913.9512.65.05
MPSI total141.21 (14.88).79.82.02143.73 (13.23)134.80 (17.00).002143.62135.09.004
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table Footer NoteaCronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.
Cronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.×
×
Test–Retest Reliability
Test–retest reliability was obtained by administering the MPI to a subset of 7 children (5 neurotypical and 2 with learning disabilities) following a 3–4 wk interval (Table 3). The initial item, subscale, and total inventory scores were correlated with the retest item subscale and total inventory scores using Pearson correlation. The correlations were .69 for the MPAI and .82 for the MPSI, indicating that the results were consistent over a 1-mo period. Children were out of school during their summer vacation at the time of the test and retest, ensuring that changes in daily routine did not significantly affect the self-reported participation in play activities and play styles. Although the retest sample size is small, the results are consistent with the retest results for the original MPI in 1992 with a sample of 20 children (not part of the current sample), when moderate correlations were obtained for both inventories (MPAI = .82, MPSI = .78; McDonald, 1992). Taken together, these correlations suggest that the MPI is a fairly accurate measurement of the child’s reported play performance over a short period.
Construct Validity
No statistically significant differences were found by gender or presence of disability on the self-reported play activities of the MPAI total inventory or subscale scores (Table 4). It is possible that the determination of frequency of participation was too abstract a concept for some children with disabilities and that the children’s rating reflected desired versus actual performance. Alternatively, it is possible that the children with disabilities participated in categories of play similar to those of neurotypical children but that the qualitative aspects of their play style were different, as reported in the literature (Kuhaneck et al., 2010).
Table 4.
Concurrent Validity: Parent–Child Correlations
Concurrent Validity: Parent–Child Correlations×
Parent–Child Correlation
Children With Disabilities (n = 4)
Neurotypical Children (n = 13)
Parent–Child Correlations, Total Population (n = 17)
ItemRpRpp for Parent–Child Correlations Between Children With Disabilities and Neurotypical ChildrenRpMean Difference in p
GM.90.10.42.15.33.41.10.95
FM.41.59.30.32.90.32.21.11
SOC.24.76.40.18.87.33.19.17
SL−.83.17−.06.85.28−.16.53.00
MPAI total−.10.90.08.87.82.04.88.01
PC.97.03.54.06.16.62.01.57
CO−.08.92.63.02.44.64.01.75
PA.97.03.40.17.11.52.03.44
SP.60.40.21.49.65.20.45.17
N.42.58.43.14.99.38.13.60
L.90.10.18.55.22.47.06.19
MPSI total.96.04.28.36.11.49.05.70
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table 4.
Concurrent Validity: Parent–Child Correlations
Concurrent Validity: Parent–Child Correlations×
Parent–Child Correlation
Children With Disabilities (n = 4)
Neurotypical Children (n = 13)
Parent–Child Correlations, Total Population (n = 17)
ItemRpRpp for Parent–Child Correlations Between Children With Disabilities and Neurotypical ChildrenRpMean Difference in p
GM.90.10.42.15.33.41.10.95
FM.41.59.30.32.90.32.21.11
SOC.24.76.40.18.87.33.19.17
SL−.83.17−.06.85.28−.16.53.00
MPAI total−.10.90.08.87.82.04.88.01
PC.97.03.54.06.16.62.01.57
CO−.08.92.63.02.44.64.01.75
PA.97.03.40.17.11.52.03.44
SP.60.40.21.49.65.20.45.17
N.42.58.43.14.99.38.13.60
L.90.10.18.55.22.47.06.19
MPSI total.96.04.28.36.11.49.05.70
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
×
Qualitative differences were found in the performance of play activities as reported on the MPSI. Specifically, significantly lower scores were found for children with disabilities on the total inventory score of the MPSI (p = .002) and on the following subscale scores: Cooperation (p = .01), Peer Acceptance (p = .002), Social Participation (p = .003), and Physical Coordination (p = .003). These results are consistent with the literature noting that many children with LD and ASD have difficulty in social and physical interactions during play (Cordier et al., 2010; Muys et al., 2006; Rogers et al., 2005).
Additional analyses of the mean differences between 12 matched pairs of children with ASD and neurotypical children (data not shown) revealed a statistically significant difference (p = .02) only on the Social Participation subscale of the MPSI. That is, children with ASD were significantly more likely than neurotypical children to report playing alone; this finding is similar to the findings of Hilton, Crouch, and Israel (2008) . The matched mean scores were also higher for the neurotypical participants on the entire MPI, with the exception of the Fine Motor and Cooperation subscales, on which children with ASD had higher mean scores; no differences were evident between the two groups on the Lie subscale.
Age differences were identified on the MPAI fine motor subscale (p for trend = .005), with younger children engaging in more fine motor play activities than older children. On the MPSI, a significant age difference was found for overall play style for 11-yr-olds compared with 10-yr-olds (p = .04 after Bonferroni multiple-comparison adjustment), suggesting that older children rated themselves more often as being physically coordinated, socially engaged, and accepted by peers and as having a cooperative play style.
Concurrent Validity
Because a similar measure with which to compare the children’s self-ratings was not available, the parent ratings of the child’s performance were used as an estimate of concurrent validity (n = 17 parent–child pairs). A low correlation (r = .04) was found between the total parent–child responses on the MPAI, and a moderate correlation (r = .49) was found between the parent–child responses on the MPSI (Table 4). These findings are similar to the initial parent–child ratings (MPAI r = −.13; MPSI r = .33) from previous research with an earlier version of the MPI (McDonald, 1992). Additional separate analyses of the parent–child correlations for only the 3 children with learning disabilities and 1 child with mild ID indicated much stronger correlations for the MPSI (r = .96) and for the majority of the MPSI subscales, suggesting that parents whose child had a disability were, in general, more likely to agree with their child’s rating about perceived performance in play, with the exception of the Cooperation subscale (r = −.08). Caution is needed in the interpretation of these findings because of the small sample size (n = 4) of parent–child surveys in the LD–ID group.
For the total group, low to moderate parent–child correlations were found on the MPAI Gross Motor (r = .41), Fine Motor (r = .32), Social (r = .33), and Solitary (r = −0.16; Table 4) subscales. Parents reported significantly more solitary play activities than their children (parent mean score = 33.00, child mean score = 25.76; p = .0015). On the MPSI subscales for the total group, the following coefficients were found: Physical Coordination (r = .62), Cooperation (r = .64), Peer Acceptance (r = .52), Social Participation (r = .20), Neutral (r = .38), and Lie (r = .47). These data suggest that parents and their children were more likely to agree on perceived play style in physical coordination, cooperation, and peer acceptance than on frequency of participation in play activities. Interestingly, the lower correlation coefficient on the Social Participation subscale (.20) indicates that parents were again less likely to have the same responses as their child with respect to social engagement with peers.
Discussion
Although the children with disabilities in this study reported engaging in play activities with the same frequency as their nondisabled peers, they reported differences in perceived overall style of play. These findings reinforce the known difficulties children with disabilities may have on the playground and after school in the community. The current study revealed, as expected, that children with various types of disabilities reported having difficulties with physical coordination (p = .003), peer acceptance (p = .002), social participation (p = .003), and cooperation (p = .01). Interestingly, when the mean Cooperation subscale scores for children with LD and children with ASD were further analyzed, the scores of children with LD accounted for the majority of the difference, whereas children with ASD received a higher mean score in perceived cooperation than neurotypical peers (data not shown). This finding is consistent with other research on ASD and may indicate decreased awareness of social nuances with peers during playtime (Williams White, Keonig, & Scahill, 2007).
Parents from both groups did not concur with their children’s responses regarding the frequency of participation across the majority of the play activities, with the exception of the gross motor play activities. This finding may be attributable to the fact that many play activities during middle childhood occur in many different settings at home, at school, and in the community, resulting in differing perspectives on the amount of time spent in play. Although the two groups of parents did not differ significantly in terms of parent–child ratings, parents of children with disabilities were slightly more likely to be in agreement with their child’s perceived style than were parents of children without disabilities. The lack of statistical significance may be related to the smaller number of parent–child pairs in the sample with disabilities.
In related research, Ziviani et al. (2006)  reported that the negative effects of perceived peer rejection and lower self-confidence in physical competence for neurotypical children contributed to a general decrease in physical activity, suggesting that the play style categories of the MPSI are important factors to consider for children with and without disabilities. Identifying a child’s perceived barriers to engagement in physical activity may assist occupational therapy practitioners and educators in facilitating appropriate playground and after-school interventions for all children.
Although no gender differences by subscale were found as previously reported (McDonald, 1987), significant item differences were identified in certain play activities and play styles (data not shown). That is, boys were more likely to engage in play with Legos (p = .0001) and play video games (p = .07) than girls, whereas girls engaged in painting (p = .01) and coloring or drawing (p = .03) more than boys. Both boys and girls reported feeling physically coordinated and cooperative with peers. These findings are partially supported by other studies (Eyler, Nanney, Brownson, Lohman, & Haire-Joshu, 2006; King et al., 2004; Ziviani, Macdonald, Ward, Jenkins, & Rodger, 2008).
Implications for Occupational Therapy Practice
The results of this study have the following implications for occupational therapy practice:
  • The MPI is a valid and reliable tool for clinicians who evaluate the perceived performance in play during middle childhood for children from middle- and upper-middle-class families.

  • The domains of play activities and play styles assessed by the MPI provide another key facet of information contributing to the multidimensional assessment of play for children with a suspected play deficit.

  • Occupational therapists who work with children from similar backgrounds and locales in school district or other after-school programs could use data yielded from the MPI to guide intervention programs.

  • Data regarding perceived play performance contributes to a greater understanding of the personal meaning of the child’s sense of mastery or challenges during play across many different settings.

Limitations and Future Research
Limitations of this research include the lack of generalization to children from lower socioeconomic backgrounds and other geographic areas. Possible differences in play styles between White and Asian-American children are unknown because we did not analyze these data. Other areas of play not assessed by the MPI include play interests unique to a specific child; this information may be obtained through additional interviewing. Further research is needed to gather normative data on children from diverse backgrounds and age ranges to detect similarities and differences in MPI scores among a wider age range of children and their parents. Additional data from playground observations, teacher interviews, and assessments that identify specific motoric and sensory deficits would also assist practitioners in determining the etiology of a child’s perceived play deficit and additional concurrent validity.
Acknowledgments
Thanks are extended to the pediatric occupational therapists and occupational therapy students who participated in the pilot testing of the MPI and to the participating agencies: Camp Anderson of the Rose Bowl Aquatic Center, Rosemary Johnson and Associates, the Center for Developing Kids, and the Anaheim and San Marino School Districts. Acknowledgments are extended to Ann McDonald’s master’s research committee at the University of Southern California—Florence Clark, Elizabeth Yerxa, Janice Burke, and Wendy Mack—and to the California Foundation for Occupational Therapy, which provided a research grant to assist in making this study possible. This study could not have been completed without the most important players—the participating children and parents. This study was presented at the 2011 AOTA Annual Conference & Expo in Philadelphia.
References
American Occupational Therapy Association. (2008). AOTA’s societal statement on play. American Journal of Occupational Therapy, 62, 707–708. http://dx.doi.org/10.5014/ajot.62.6.707 [Article] [PubMed]
American Occupational Therapy Association. (2008). AOTA’s societal statement on play. American Journal of Occupational Therapy, 62, 707–708. http://dx.doi.org/10.5014/ajot.62.6.707 [Article] [PubMed]×
Ayres, A. J. (1980). Sensory integration and learning disorders. Los Angeles: Western Psychological Services.
Ayres, A. J. (1980). Sensory integration and learning disorders. Los Angeles: Western Psychological Services.×
Ayres, A. J. (1982). Sensory integration and the child. Los Angeles: Western Psychological Services.
Ayres, A. J. (1982). Sensory integration and the child. Los Angeles: Western Psychological Services.×
Benson, J., & Clark, F. A. (1982). A guide for instrument development and validation. American Journal of Occupational Therapy, 36, 789–800. http://dx.doi.org/10.5014/ajot.36.12.789 [Article] [PubMed]
Benson, J., & Clark, F. A. (1982). A guide for instrument development and validation. American Journal of Occupational Therapy, 36, 789–800. http://dx.doi.org/10.5014/ajot.36.12.789 [Article] [PubMed]×
Cordier, R., Bundy, A., Hocking, C., & Einfeld, S. (2010). Empathy in the play of children with attention deficit hyperactivity disorder. OTJR: Occupation, Participation and Health, 30, 122–132. [Article]
Cordier, R., Bundy, A., Hocking, C., & Einfeld, S. (2010). Empathy in the play of children with attention deficit hyperactivity disorder. OTJR: Occupation, Participation and Health, 30, 122–132. [Article] ×
Coster, W. J. (2008). Embracing ambiguity: Facing the challenge of measurement (Eleanor Clarke Slagle Lecture). American Journal of Occupational Therapy, 62, 743–752. http://dx.doi.org/10.5014/ajot.62.6.743 [Article] [PubMed]
Coster, W. J. (2008). Embracing ambiguity: Facing the challenge of measurement (Eleanor Clarke Slagle Lecture). American Journal of Occupational Therapy, 62, 743–752. http://dx.doi.org/10.5014/ajot.62.6.743 [Article] [PubMed]×
Erikson, E. H. (1950). Childhood and society. New York: Norton.
Erikson, E. H. (1950). Childhood and society. New York: Norton.×
Eyler, A., Nanney, M. S., Brownson, R. C., Lohman, D., & Haire-Joshu, D. (2006). Correlates of after-school activity preference in children ages 5–12: The PARADE study. American Journal of Health Education, 37, 69–74. [Article]
Eyler, A., Nanney, M. S., Brownson, R. C., Lohman, D., & Haire-Joshu, D. (2006). Correlates of after-school activity preference in children ages 5–12: The PARADE study. American Journal of Health Education, 37, 69–74. [Article] ×
Florey, L. L. (2005). A second grader with oppositional defiant disorder. In S. E.Ryan, & K.Sladyk (Eds.), Ryan’s occupational therapy assistant: Principles, practice issues and techniques (pp. 172–183). Thorofare, NJ: Slack.
Florey, L. L. (2005). A second grader with oppositional defiant disorder. In S. E.Ryan, & K.Sladyk (Eds.), Ryan’s occupational therapy assistant: Principles, practice issues and techniques (pp. 172–183). Thorofare, NJ: Slack.×
Handler, S. M., & Fierson, W. F. (2011). Joint technical report—Learning disabilities, dyslexia, and vision. Journal of Pediatrics. Retrieved from http://pediatrics.aappublications.org/content/early/2011/02/28/peds.2010-3670
Handler, S. M., & Fierson, W. F. (2011). Joint technical report—Learning disabilities, dyslexia, and vision. Journal of Pediatrics. Retrieved from http://pediatrics.aappublications.org/content/early/2011/02/28/peds.2010-3670×
Henry, A. (2000). Pediatric Interest Profiles: Surveys of play for children and adolescents. San Antonio, TX: Therapy Skill Builders.
Henry, A. (2000). Pediatric Interest Profiles: Surveys of play for children and adolescents. San Antonio, TX: Therapy Skill Builders.×
Herron, R. E., & Sutton-Smith, B. (1971). Child’s play. New York: Wiley.
Herron, R. E., & Sutton-Smith, B. (1971). Child’s play. New York: Wiley.×
Hilton, C. L., Crouch, M. C., & Israel, H. (2008). Out-of-school participation patterns in children with high-functioning autism spectrum disorders. American Journal of Occupational Therapy, 62, 554–563. http://dx.doi.org/10.5014/ajot.62.5.554 [Article] [PubMed]
Hilton, C. L., Crouch, M. C., & Israel, H. (2008). Out-of-school participation patterns in children with high-functioning autism spectrum disorders. American Journal of Occupational Therapy, 62, 554–563. http://dx.doi.org/10.5014/ajot.62.5.554 [Article] [PubMed]×
Huizinga, J. (1950). Homo ludens: A study of the play element in culture. Boston: Beacon Press.
Huizinga, J. (1950). Homo ludens: A study of the play element in culture. Boston: Beacon Press.×
King, G., King, S., Rosenbaum, P., Kertoy, M., Law, M., Hurley, P., et al. (2004). Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC). San Antonio, TX: Harcourt Assessment.
King, G., King, S., Rosenbaum, P., Kertoy, M., Law, M., Hurley, P., et al. (2004). Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC). San Antonio, TX: Harcourt Assessment.×
Kramer, J. M., Kielhofner, G., & Smith, E. V., Jr. (2010). Validity evidence for the Child Occupational Self Assessment. American Journal of Occupational Therapy, 64, 621–632. http://dx.doi.org/10.5014/ajot.2010.08142 [Article] [PubMed]
Kramer, J. M., Kielhofner, G., & Smith, E. V., Jr. (2010). Validity evidence for the Child Occupational Self Assessment. American Journal of Occupational Therapy, 64, 621–632. http://dx.doi.org/10.5014/ajot.2010.08142 [Article] [PubMed]×
Kuhaneck, H. M., Spitzer, S. L., & Miller, E. (2010). Activity analysis, creativity and playfulness in pediatric occupational therapy: Making play just right. Sudbury, MA: Jones & Bartlett.
Kuhaneck, H. M., Spitzer, S. L., & Miller, E. (2010). Activity analysis, creativity and playfulness in pediatric occupational therapy: Making play just right. Sudbury, MA: Jones & Bartlett.×
Ladd, G. W. (1999). Peer relationships and social competence during early and middle childhood. Annual Review of Psychology, 50, 333–359. http://dx.doi.org/10.1146/annurev.psych.50.1.333 [Article] [PubMed]
Ladd, G. W. (1999). Peer relationships and social competence during early and middle childhood. Annual Review of Psychology, 50, 333–359. http://dx.doi.org/10.1146/annurev.psych.50.1.333 [Article] [PubMed]×
McDonald, A. E. (1987). The construction of a self-report instrument to measure play activities and play styles in 7 to 11 year old children. Unpublished master’s thesis, University of Southern California, Los Angeles.
McDonald, A. E. (1987). The construction of a self-report instrument to measure play activities and play styles in 7 to 11 year old children. Unpublished master’s thesis, University of Southern California, Los Angeles.×
McDonald, A. E. (1992). [Test–retest data for child and parent McDonald Play Inventory]. Unpublished raw data.
McDonald, A. E. (1992). [Test–retest data for child and parent McDonald Play Inventory]. Unpublished raw data.×
Miller, E., & Kuhaneck, H. (2008). Children’s perceptions of play experiences and play preferences: A qualitative study. American Journal of Occupational Therapy, 62, 407–415. http://dx.doi.org/10.5014/ajot.62.4.407 [Article] [PubMed]
Miller, E., & Kuhaneck, H. (2008). Children’s perceptions of play experiences and play preferences: A qualitative study. American Journal of Occupational Therapy, 62, 407–415. http://dx.doi.org/10.5014/ajot.62.4.407 [Article] [PubMed]×
Muys, V., Rodger, S., & Bundy, A. C. (2006). Assessment of play in children with autistic disorder: A comparison of the Children’s Playfulness Scale and the Test of Playfulness. OTJR: Occupation, Participation and Health, 26, 159–171.
Muys, V., Rodger, S., & Bundy, A. C. (2006). Assessment of play in children with autistic disorder: A comparison of the Children’s Playfulness Scale and the Test of Playfulness. OTJR: Occupation, Participation and Health, 26, 159–171.×
Parham, L. D., & Fazio, L. S. (2008). Play in occupational therapy for children (2nd ed.). St. Louis, MO: C. V. Mosby.
Parham, L. D., & Fazio, L. S. (2008). Play in occupational therapy for children (2nd ed.). St. Louis, MO: C. V. Mosby.×
Poulsen, A. A., Ziviani, J. M., Cuskelly, M., & Smith, R. (2007). Boys with developmental coordination disorder: Loneliness and team sports participation. American Journal of Occupational Therapy, 61, 451–462. http://dx.doi.org/10.5014/ajot.61.4.451 [Article] [PubMed]
Poulsen, A. A., Ziviani, J. M., Cuskelly, M., & Smith, R. (2007). Boys with developmental coordination disorder: Loneliness and team sports participation. American Journal of Occupational Therapy, 61, 451–462. http://dx.doi.org/10.5014/ajot.61.4.451 [Article] [PubMed]×
Reilly, M. (1974). Play as exploratory learning: Studies of curiosity behavior. London: Sage.
Reilly, M. (1974). Play as exploratory learning: Studies of curiosity behavior. London: Sage.×
Reynolds, W. (2003). Reynolds Bullying Victimization Scales for Schools. San Antonio, TX: Pearson.
Reynolds, W. (2003). Reynolds Bullying Victimization Scales for Schools. San Antonio, TX: Pearson.×
Rogers, S. J., Cook, I., & Meryl, A. (2005). Imitation and play in autism. In F. R.Volkmar, R.Paul, A.Kiln, & D. J.Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Vol. 1. Diagnosis, development, neurobiology, and behavior (pp. 382–405). Hoboken, NJ: Wiley.
Rogers, S. J., Cook, I., & Meryl, A. (2005). Imitation and play in autism. In F. R.Volkmar, R.Paul, A.Kiln, & D. J.Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Vol. 1. Diagnosis, development, neurobiology, and behavior (pp. 382–405). Hoboken, NJ: Wiley.×
Rosenblum, S., Sachs, D., & Schreuer, N. (2010). Reliability and validity of the Children’s Leisure Assessment Scale. American Journal of Occupational Therapy, 64, 633–641. http://dx.doi.org/10.5014/ajot.2010.08173 [Article] [PubMed]
Rosenblum, S., Sachs, D., & Schreuer, N. (2010). Reliability and validity of the Children’s Leisure Assessment Scale. American Journal of Occupational Therapy, 64, 633–641. http://dx.doi.org/10.5014/ajot.2010.08173 [Article] [PubMed]×
Thorndike, R., & Thorndike-Christ, T. (2010). Measurement and evaluation in psychology and education (8th ed.). Englewood Cliffs, NJ: Prentice Hall.
Thorndike, R., & Thorndike-Christ, T. (2010). Measurement and evaluation in psychology and education (8th ed.). Englewood Cliffs, NJ: Prentice Hall.×
Williams White, S., Keonig, K., & Scahill, L. (2007). Social skills development in children with autism spectrum disorders: A review of the intervention research. Journal of Autism and Developmental Disorders, 37, 1858–1868. http://dx.doi.org/10.1007/s10803-006-0320-x [Article] [PubMed]
Williams White, S., Keonig, K., & Scahill, L. (2007). Social skills development in children with autism spectrum disorders: A review of the intervention research. Journal of Autism and Developmental Disorders, 37, 1858–1868. http://dx.doi.org/10.1007/s10803-006-0320-x [Article] [PubMed]×
Ziviani, J., Macdonald, D., Jenkins, D., Rodger, S., Batch, J., & Cerin, E. (2006). Physical activity of young children. OTJR: Occupation, Participation and Health, 26, 4–14.
Ziviani, J., Macdonald, D., Jenkins, D., Rodger, S., Batch, J., & Cerin, E. (2006). Physical activity of young children. OTJR: Occupation, Participation and Health, 26, 4–14.×
Ziviani, J., Macdonald, D., Ward, H., Jenkins, D., & Rodger, S. (2008). Physical activity of young children: A two-year follow-up. Physical and Occupational Therapy in Pediatrics, 28, 25–39. http://dx.doi.org/10.1300/J006v28n01_03 [Article] [PubMed]
Ziviani, J., Macdonald, D., Ward, H., Jenkins, D., & Rodger, S. (2008). Physical activity of young children: A two-year follow-up. Physical and Occupational Therapy in Pediatrics, 28, 25–39. http://dx.doi.org/10.1300/J006v28n01_03 [Article] [PubMed]×
Table 1.
Participant Age and Gender
Participant Age and Gender×
Neurotypical Children
Children With Disabilitiesa
Age (yr)BoysGirlsBoysGirlsTotal
7885122
8998026
91195227
101184326
11884323
Total4742269124
Table Footer NoteaDisabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.
Disabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.×
Table 1.
Participant Age and Gender
Participant Age and Gender×
Neurotypical Children
Children With Disabilitiesa
Age (yr)BoysGirlsBoysGirlsTotal
7885122
8998026
91195227
101184326
11884323
Total4742269124
Table Footer NoteaDisabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.
Disabilities include learning disorders, autism spectrum disorders, Down syndrome, and mild intellectual disability.×
×
Table 2.
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)×
Range of Item CorrelationsGMFMSOCSLMPAI TotalPCCOPASPNLMPSI Total
GM.33–.66
FM.33–.75.32
SOC.32–.68.54.52
SL.27–.61.25.42.40
MPAI total.17–.64.69.77.81.72
PC.36–.70.47.03.22.04.24
CO.52–.66.05.00.07−.05.02.27
PA.38–.67.37−.01.27.04.21.39.28
SP.40–.64.21.06.28−.11.13.33.20.45
N.30–.62.46.43.48.28.55.11−.08.16.04
L.65–.71.53.27.41.21.47.36.30.52.34.35
MPSI total.02–.63.59.26.50.14.49.63.47.72.59.55.75
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table 2.
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)
Intercorrelations (Pearson Correlation Coefficients) and Ranges for Item Correlations (N = 124)×
Range of Item CorrelationsGMFMSOCSLMPAI TotalPCCOPASPNLMPSI Total
GM.33–.66
FM.33–.75.32
SOC.32–.68.54.52
SL.27–.61.25.42.40
MPAI total.17–.64.69.77.81.72
PC.36–.70.47.03.22.04.24
CO.52–.66.05.00.07−.05.02.27
PA.38–.67.37−.01.27.04.21.39.28
SP.40–.64.21.06.28−.11.13.33.20.45
N.30–.62.46.43.48.28.55.11−.08.16.04
L.65–.71.53.27.41.21.47.36.30.52.34.35
MPSI total.02–.63.59.26.50.14.49.63.47.72.59.55.75
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
×
Table 3.
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)×
Construct Validity (N = 124)
Unadjusted Values
Values Adjusted for Age and Genderd
Test–Retest Correlationb (n = 7)
M (SD)
Least Squares M
SubscaleM (SD)Internal Consistencya (N = 124)RpNeurotypical ChildrenChildren With DisabilitiespcNeurotypical ChildrenChildren With Disabilitiesp
GM24.42 (6.40).70.59.1624.87 (6.64)23.29 (5.69).2224.9023.21.20
FM26.49 (6.91).65.75.0526.25 (6.39)27.11 (8.15).5326.1727.32.40
SOC27.09 (5.98).60.47.2927.33 (5.58)26.49 (6.94).4827.2326.74.69
SL25.90 (7.18).71.94.00225.96 (6.92)25.74 (7.91).8825.9325.82.94
MPAI total103.90 (19.68).84.69.09104.39 (18.54)102.63 (22.55).65104.21103.09.78
PC23.50 (3.77).56.06.9124.13 (3.57)21.89 (3.84).00324.1521.85.002
CO24.84 (3.64).63.80.0325.36 (3.58)23.51 (3.49).0125.3223.62.02
PA22.60 (3.79).52.18.7023.27 (3.41)20.91 (4.20).00223.2820.89.002
SP22.10 (3.77).58.90.0122.73 (3.52)20.51 (3.96).00322.7220.55.004
N34.58 (6.17).72.02.9734.30 (5.68)35.29 (7.30).4334.2135.53.29
L13.58 (3.29).51.48.2813.93 (2.96)12.69 (3.90).0913.9512.65.05
MPSI total141.21 (14.88).79.82.02143.73 (13.23)134.80 (17.00).002143.62135.09.004
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table Footer NoteaCronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.
Cronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.×
Table 3.
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)
Internal Consistency, Test–Retest Reliability, and Construct Validity (Unadjusted and Adjusted)×
Construct Validity (N = 124)
Unadjusted Values
Values Adjusted for Age and Genderd
Test–Retest Correlationb (n = 7)
M (SD)
Least Squares M
SubscaleM (SD)Internal Consistencya (N = 124)RpNeurotypical ChildrenChildren With DisabilitiespcNeurotypical ChildrenChildren With Disabilitiesp
GM24.42 (6.40).70.59.1624.87 (6.64)23.29 (5.69).2224.9023.21.20
FM26.49 (6.91).65.75.0526.25 (6.39)27.11 (8.15).5326.1727.32.40
SOC27.09 (5.98).60.47.2927.33 (5.58)26.49 (6.94).4827.2326.74.69
SL25.90 (7.18).71.94.00225.96 (6.92)25.74 (7.91).8825.9325.82.94
MPAI total103.90 (19.68).84.69.09104.39 (18.54)102.63 (22.55).65104.21103.09.78
PC23.50 (3.77).56.06.9124.13 (3.57)21.89 (3.84).00324.1521.85.002
CO24.84 (3.64).63.80.0325.36 (3.58)23.51 (3.49).0125.3223.62.02
PA22.60 (3.79).52.18.7023.27 (3.41)20.91 (4.20).00223.2820.89.002
SP22.10 (3.77).58.90.0122.73 (3.52)20.51 (3.96).00322.7220.55.004
N34.58 (6.17).72.02.9734.30 (5.68)35.29 (7.30).4334.2135.53.29
L13.58 (3.29).51.48.2813.93 (2.96)12.69 (3.90).0913.9512.65.05
MPSI total141.21 (14.88).79.82.02143.73 (13.23)134.80 (17.00).002143.62135.09.004
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SD = standard deviation; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table Footer NoteaCronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.
Cronbach’s α with subscale deleted. bPearson correlation. cIndependent sample t test. dGeneral linear models, p values for difference between children with and without disabilities, adjusted for age and gender.×
×
Table 4.
Concurrent Validity: Parent–Child Correlations
Concurrent Validity: Parent–Child Correlations×
Parent–Child Correlation
Children With Disabilities (n = 4)
Neurotypical Children (n = 13)
Parent–Child Correlations, Total Population (n = 17)
ItemRpRpp for Parent–Child Correlations Between Children With Disabilities and Neurotypical ChildrenRpMean Difference in p
GM.90.10.42.15.33.41.10.95
FM.41.59.30.32.90.32.21.11
SOC.24.76.40.18.87.33.19.17
SL−.83.17−.06.85.28−.16.53.00
MPAI total−.10.90.08.87.82.04.88.01
PC.97.03.54.06.16.62.01.57
CO−.08.92.63.02.44.64.01.75
PA.97.03.40.17.11.52.03.44
SP.60.40.21.49.65.20.45.17
N.42.58.43.14.99.38.13.60
L.90.10.18.55.22.47.06.19
MPSI total.96.04.28.36.11.49.05.70
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
Table 4.
Concurrent Validity: Parent–Child Correlations
Concurrent Validity: Parent–Child Correlations×
Parent–Child Correlation
Children With Disabilities (n = 4)
Neurotypical Children (n = 13)
Parent–Child Correlations, Total Population (n = 17)
ItemRpRpp for Parent–Child Correlations Between Children With Disabilities and Neurotypical ChildrenRpMean Difference in p
GM.90.10.42.15.33.41.10.95
FM.41.59.30.32.90.32.21.11
SOC.24.76.40.18.87.33.19.17
SL−.83.17−.06.85.28−.16.53.00
MPAI total−.10.90.08.87.82.04.88.01
PC.97.03.54.06.16.62.01.57
CO−.08.92.63.02.44.64.01.75
PA.97.03.40.17.11.52.03.44
SP.60.40.21.49.65.20.45.17
N.42.58.43.14.99.38.13.60
L.90.10.18.55.22.47.06.19
MPSI total.96.04.28.36.11.49.05.70
Table Footer NoteNote. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.
Note. CO = Cooperation; FM = Fine Motor; GM = Gross Motor; L = Lie; MPAI = McDonald Play Activity Inventory; MPSI = McDonald Play Style Inventory; N = Neutral; PA = Peer Acceptance; PC = Physical Coordination; SL = Solitary; SOC = Social Group; SP = Social Participation.×
×