http://informahealthcare.com/pdr ISSN: 1751-8423 (print), 1751-8431 (electronic) Dev Neurorehabil, 2014; 17(6): 403–413 ! 2014 Informa UK Ltd. DOI: 10.3109/17518423.2014.897398
ORIGINAL ARTICLE
Determinants of self-care participation of young children with cerebral palsy Doreen J. Bartlett1, Lisa A. Chiarello2, Sarah Westcott McCoy3, Robert J. Palisano2, Lynn Jeffries4, Alyssa LaForme Fiss5, & Piotr Wilk6
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1
School of Physical Therapy, Western University, London, ON, Canada, 2Department of Physical Therapy and Rehabilitation Sciences, Drexel University, Philadelphia, PA, USA, 3Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA, 4Department of Rehabilitation Sciences, The University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA, 5Department of Physical Therapy, Mercer University, Atlanta, GA, USA, and 6Department of Epidemiology and Biostatistics, Western University, London, ON, Canada
Abstract
Keywords
Objective: To test a model of child, family and service determinants of self-care participation of children with cerebral palsy (CP), grouped by Gross Motor Function Classification System levels (I–II and III–V). Methods: Participants were a convenience sample of 429 children (242 males) with CP, aged 18–60 months. Data on impairments and gross motor function were collected by reliable therapists; parents provided information about children’s health conditions and adaptive behaviour. Seven months later parents reported on family life and services received. One year after study onset, parents documented children’s self-care participation. Data from two groups of children were analysed using structural equation modelling. Results: The model explained a significant proportion of the variance of self-care participation, with higher motor function, fewer health conditions and higher levels of adaptive behaviour being associated with greater self-care participation. Conclusion: Supporting children’s gross motor function, health and adaptive behaviour may optimize self-care participation.
Biopsychosocial approach, prospective cohort study, structural equation modelling
Introduction ‘‘Cerebral palsy (CP) describes a group of disorders of the development of movement and posture, causing activity limitation that are attributed to non-progressive disturbances that occurred in the developing foetal or infant brain. The motor disorders of cerebral palsy are often accompanied by disturbances of sensation, perception, cognition, communication, and behaviour, by epilepsy, and by secondary musculoskeletal problems’’ [1, p. 9]. Importantly, this international consensus definition of CP emphasizes the issues of activity limitation and participation restriction as well as the complexity of the condition with respect to associated health states and development of secondary conditions over time, all of which need to be considered in clinical decision-making. Along with others [2], we advocate for a holistic, biopsychosocial approach to assessment and intervention to ensure that all aspects of this complex health condition are considered. We have developed a multivariate model of determinants of activity and participation that incorporates primary and secondary impairments, associated health conditions, as well as personal and environmental components [3] involving
Correspondence: Doreen Bartlett, 1588 Elborn College, School of Physical Therapy, Western University, London, ON, N6G 1H1, Canada. Tel: +519 661 2111, extn 88953. E-mail: [email protected]
History Received 19 December 2013 Revised 30 January 2014 Accepted 19 February 2014 Published online 7 April 2014
children’s adaptive behaviour and aspects of families and services provided, aiming to provide a framework for decision-making for rehabilitation therapists and families of young children with CP [4]. The supplementary figure contains a reproduction of the conceptual model. One of the fundamental goals of early therapy for children with CP is to promote participation in daily life [4], including families’ priority of independence in self-care [5], which is the focus of the work reported here. A growing body of literature supports associations between multiple components of the International Classification of Functioning, Disability and Health (ICF) [3] and self-care in samples of children with CP. Among primary impairments, greater involvement of more limbs and parts of the body [2, 6, 7], problems with selective motor control [6] and atypical postures [8] have been identified to be associated with limitations in self-care function. Children with higher levels of gross motor function attain greater independence in self-care and daily living skills [2, 7, 9–14]; hand function has also been identified to be strongly associated with self-care abilities [13, 15]. The presence of learning problems and cognitive impairment has been found to be associated with lower self-care abilities [6, 7, 9, 12], as has the presence of pain [14]. In terms of services, functional approaches [16, 17], home-based consultations [18], and assistive devices and environmental modifications [19, 20] have all been found to contribute to improvements in self-care
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function. Recently, a more accessible physical environment in the home has been found to be associated with higher participation at mealtimes and with personal care [14]. All but three cohorts [6, 9, 10, 13] have exclusively studied schoolaged children and none focused solely on preschool-aged children. Because early childhood is a sensitive period for the development of many domains, including self-care [4], a study focusing on a younger age group is warranted. Furthermore, most investigations have focused on capability [6–8, 12, 13, 15], rather than performance, which is typically of greater interest to parents and caregivers. Although recent studies have gone beyond descriptive and bivariate analyses to use more sophisticated approaches including various forms of multiple regression [6–9, 11–13] and structural equation modelling [14] to examine multiple factors related to selfcare, none have incorporated all aspects suggested by both the international consensus definition of CP and the ICF. Specifically, the role of secondary impairments, personal aspects of children unrelated to a diagnosis of CP, and contextual factors associated with families have not yet been investigated. The purpose of this study, therefore, was to test a multivariate model of child, family and service determinants that together explain participation of self-care of preschoolaged children with CP (see Figure S1). Based on complementary theoretical frameworks, the research literature, clinical expertise and parent input [4] we hypothesized that: (1) the model would explain a greater proportion of variance of participation in self-care among children whose selfmobility is limited or who walk with assistive devices than among children with a good prognosis for independent ambulation, (2) children’s primary and secondary impairments and associated conditions would have an indirect effect on participation in self-care through the mediator of gross motor function, (3) children’s adaptive behaviour, family ecology and rehabilitation and community services would have a direct effect on participation in self-care and (4) rehabilitation and community services would be a mediator between family ecology and self-care. Knowledge of determinants of self-care participation will assist with decisions about what to assess and how to intervene to support optimal independence. Significant determinants that are amenable to change are targets for intervention, either directly or through environmental modifications. Determinants that are not amenable to change can assist with realistic goal-setting.
Methods In this article, we report on one set of models tested in a multi-site prospective cohort study referred to as Move & PLAY (Movement and Participation in Life Activities of Young Children with cerebral palsy). In preliminary papers, we described the development of the conceptual [4] and measurement [21] models. Participants The participants of our study have been previously described [22]; this description is reproduced here with permission from Developmental Medicine and Child Neurology. Children were eligible to participate if they had a diagnosis of CP, or gross
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motor delay with impairments consistent with CP, and if their parents could speak English, French or Spanish. Children with a predominant dual diagnosis were excluded. Statistical estimation involving a sample of 200 typically results in stable estimates of various fit indices used to determine the degree of fit between the pattern of relationships in the data and proposed model [23, 24]. We initially aimed for equal numbers in each of the following GMFCS groups: Levels I and II, Level III, and Levels IV and V. Participants were a convenience sample of 429 children (242 males, 187 females) and their caregivers recruited from children’s rehabilitation centres in six provinces in Canada and four regions in the USA between July 2007 and February 2009. At the outset of the study, children ranged in age from 18 to 60 months (mean of 3 years, 2 months, SD 11 months). Children’s abilities varied across all five levels of the GMFCS [25] and across all distributions of involvement. Child and parent participant demographics are contained in Table I. This distribution is representative of GMFCS levels in populationbased studies around the world [26]. We were able to recruit a sufficient number of children in GMFCS Levels I and II (n ¼ 204) and Levels III, IV and V (n ¼ 226) to test the model on two groups of children. We retained 90% of the sample over the observation period of 1 year; data collection was completed in March 2010. Families who remained in the study had significantly higher incomes than families who withdrew or were lost to follow-up (however, the magnitude of this difference is not practically significant); no other child and family demographics differed between groups (Table I). Ethical approval was obtained from all academic and clinical sites; parents provided signed informed consent prior to data collection. Measures Outcome Children’s self-care participation was measured using the selfcare domain of the Child Engagement in Daily Life measure [27] which was developed in the context of the Move & PLAY study to be used to measure participation in family and recreational activities and self-care of young children with CP through parent report. The self-care domain contains 7 items about feeding, dressing, bathing and toileting which are measured using a 5-point Likert scale (i.e. ‘‘1’’ indicating ‘‘no help needed’’; ‘‘2’’, ‘‘no difficulty’’; ‘‘3’’, ‘‘a little difficulty’’; ‘‘4’’, ‘‘somewhat difficult’’ and ‘‘5’’, ‘‘very difficult’’). Construct validity is supported by the known groups method, with younger children obtaining lower scores than older children and children with more functional GMFCS levels obtaining higher scores than children in less functional levels [27]. Internal consistency, using Cronbach’s alpha, was 0.90 and test–retest reliability was high with an intra-class correlation coefficient of 0.96 (with 95% confidence interval of 0.91–0.98) for participation in self-care. Finally, using Rasch analysis, item stability was demonstrated to be excellent in distinct subsamples with a Pearson’s correlation of 0.99 for item calibrations and a Spearman rank correlation of 0.89 for item ranks. Item fit was acceptable, supporting the unidimensionality of the self-care domain. Although differential item functioning varied for children in
Determinants of self-care participation
DOI: 10.3109/17518423.2014.897398
Table I. Child and parent demographic characteristics (reproduced with permission).
Characteristics
Participants enrolled n ¼ 429 (%)
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Child GMFCS level I 154 (36) II 50 (11) III 53 (12) IV 75 (18) V 97 (23) Child distribution of involvement Monoplegia 10 (2) Hemiplegia 102 (24) Diplegia 100 (23) Triplegia 25 (6) Quadriplegia 190 (44)
Child ethnicity African–American Asian or Pacific Islander Hispanic/Latino Native American White Other Parent age, years:months Mean (SD) Parent relationship to child Mother Father Other Parent education High school or less Community College/ Associate’s Degree University Family incomea (CA$ or US$) $75 000 $60 000–74 999 $45 000–59 999 $30 000–44 999 $30 000
Family composition Adults (mean, SD) Children (mean, SD)
Participants retained over the year n ¼ 389 (%) 145 45 49 66 84
(37) (11) (13) (17) (22)
8 98 88 24 169
(2) (25) (23) (6) (44)
(n ¼ 427)
(n¼387)
32 19 18 11 299 50
25 17 16 9 272 50
(8) (4) (4) (3) (70) (11)
(7) (4) (4) (2) (70) (13)
34:4 (6.9)
34:6 (6.6)
393 (92) 21 (5) 15 (4)
364 (94) 21 (5) 4 (1)
134 (31) 114 (27)
115 (30) 101 (26)
181 (42)
173 (44)
164 49 59 54 88
157 48 52 45 74
(38) (11) (14) (13) (21)
(40) (12) (13) (12) (19)
(n ¼ 413)
(n ¼ 376)
2.2 (0.8) 2.2 (1.1)
2.2 (0.8) 2.2 (1.1)
a
Report based on the available information. GMFCS, Gross Motor Function Classification System Level; CA$, Canadian Dollars; US$, United States Dollars.
different GMFCS levels, scaled (Rasched) total scores did not differ among GMFCS level groupings, so there is little practical significance to this finding [27]. Independent variables/determinants The list of measures representing the determinants of self-care is contained in Table II; a description of the psychometric properties of these measures follows. Determinants are categorized into gross motor function (activity), primary impairments (i.e. impairments of body functions related to the movement disorder of CP present at the outset of a diagnosis), secondary impairments (i.e. impairments of body functions related to the movement disorder of CP that develop over time), associated health conditions (as conceptualized in the international consensus definition of CP and measured using
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body functions terminology, where possible), child adaptive behaviour (a personal factor that is unrelated to the diagnosis of CP), and family ecology and services provided (environmental factors). Four primary impairments were measured: spasticity, quality of movement, balance and distribution of involvement. Three secondary impairments included strength, range of motion and endurance for activity. Motor function was measured using the basal and ceiling approach of the Gross Motor Function Measure (GMFM66-B&C) [28], which requires administration of a minimum of 15 items from the original GMFM-66 [37], ranked in order of difficulty. The 15 items must start with a basal level of three consecutive scores of 3 (‘‘completes’’ item as described) up to a ceiling level of three consecutive scores of 0 (‘‘does not initiate’’). GMFM-66 scores are then calculated using the Gross Motor Ability Estimator (GMAE) [37], now available in an updated second version (GMAE-2; www.canchild.ca). GMFM-66 scores range from 0 to 100. Concurrent validity between the GMFM-66-B&C and the full GMFM-66 and test–retest reliability were estimated using the intraclass correlation coefficient (ICC); both were 0.99 [28]. Spasticity was measured using the Modified Ashworth Scale [29]. Three estimates of each of bilateral elbow flexors and hamstrings using a 6-point ordinal scale were recorded. Inter-rater reliability has been established with an ICC value of 0.79 [38]. Evidence for construct validity was provided with significant correlations with the Tardieu Scale and scores taken with a myotonometer and isokinetic dynamometer [38]. Selected items from the ‘‘coordination’’ and ‘‘dissociation’’ subscales of the Gross Motor Performance Measure (GMPM) [30] were used to obtain an estimate of quality of movement. For each child, an attempt was made to obtain two estimates of each of these subscales based on performance of the relevant GMFM item within the child’s current motor repertoire. Each item is scored using a 4-point Likert scale (0–3); estimates for each subscale were averaged and the two subscales summed for a total possible score between 0 and 6. Inter-, intra- and test–retest reliabilities had ICCs in the range of 0.92–0.96; known groups validity was established with differences in GMPM scores for children at different functional ability levels [30]. A new measure of postural stability developed through the Move & PLAY study is the Early Clinical Assessment of Balance (ECAB) [31], which is appropriate for children in all GMFCS levels. Items are scored on 4- and 5-point ordinal scales in Parts 1 and 2, respectively. Possible total scores on the ECAB range from 0 to 100. Validity of the ECAB is supported by significant differences across GMFCS levels and significant associations with age and GMFM-66-B&C scores. Test–retest reliability is very strong with an intra-class correlation coefficient (ICC) of 0.98 [39]. Distribution of involvement was scored from 1 to 5 based on the following classification: monoplegia, hemiplegia, diplegia, triplegia or quadriplegia. Stability of classification over a 1-year period in the Move & PLAY study was strong, with a kappa value of 0.79 (p50.001). For muscle strength, a global estimate was obtained on the following groups of muscles: neck and trunk flexors and extensors, hip and knee extensors, and shoulder flexors.
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Table II. List of measures used to test the model of self-care participation.
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Construct
Indictor
Motor function
Gross motor function
Primary impairments Primary impairments
Spasticity Quality of movement
Primary impairments Primary impairment
Balance Distribution of involvement
Secondary impairment Secondary impairment
Strength Range of motion
Secondary impairment Associated health conditions and comorbidities Child adaptive behaviour
Endurance Associated conditions
Family ecology Family ecology Rehabilitation and community services
Sensorimotor organization Self-initiated behaviours Reactive behaviours Family relationships Social integration Expectations Intensity of therapy Family-centred services Number of community programs Services meeting needs
Each muscle group was rated on a 5-point ordinal scale, using standard physical therapy manual muscle testing approaches. The psychometric properties of this measure were established through the Move & PLAY study. Internal consistency among the groups of muscles (Cronbach’s alpha ¼ 0.93), test–retest reliability (ICC ¼ 0.97) and known groups validity (significant differences among all GMFCS levels except II and III) were supported. The Spinal Alignment and Range of Motion Measure (SAROMM) [32] was used to provide an overall estimate of the extent of limitations in spinal alignment and range of motion. It comprises 26 items, each scored on a 5-point Likert scale. Each item is scored based on observation of postural alignment or passive movement of the extremities, using standard manual techniques. Internal consistency (Cronbach’s alpha ¼ 0.95), inter-rater and test–retest reliability (ICC40.80) and known groups validity (significant differences among all GMFCS levels) have all been established [32]. Endurance for activity was measured using the Early Activity Scale for Endurance, which was developed in the context of the Move & PLAY study [33]. Although it started out as a 10-item, parent-completed measure scored on a 5-point Likert scale, confirmatory factor analysis was used to pare it down to 4 items. Internal consistency (Cronbach’s alpha ¼ 0.83), test–retest reliability (ICC ¼ 0.95) and known groups validity (significant differences among all GMFCS levels except between II and III and between III and IV) were supported [33]. We designed the parent-completed Health Conditions Questionnaire [26] to measure the number and impact of health conditions experienced by children with CP. Each parent first responds ‘‘yes’’ or ‘‘no’’ to 16 questions asking ‘‘does your child have problemsð.’’ about a range of health manifestations (i.e. seeing, hearing, learning and understanding, speaking or communicating, controlling emotions or
Measure Gross Motor Function Measure (basal and ceiling approach) [28] Modified Ashworth Scale [29] 4 items from the Gross Motor Performance Measure [30] Early Clinical Assessment of Balance [31] Monoplegia, hemiplegia, diplegia, triplegia, quadriplegia Functional Strength Assessment Spinal Alignment and Range of Motion Measure [32] Early Activity Scale for Endurance [33] Health Conditions Questionnaire [26]
Respondent Assessor; 15 min Assessor; 5 min Assessor; 10 min Assessor; 10–15 min Assessor; 5 min Assessor; 10 min Assessor; 15 min Parent; 5 min Parent; 5 min
Early Coping Inventory [34]
Parent; 10 min
Part of the Family Environment Scale [35] Family’s Expectations of Child (developed by team, in collaboration with parents) Services Questionnaire [36]
Parent; 30 min Parent; 5 min Parent; 10 min
behaviour, seizures or epilepsy, the mouth, teeth and gums, digestion, growth, sleeping, repeated infections, breathing, skin, heart and pain). If the response is ‘‘yes’’, they were also asked to rate ‘‘to what extent does this problem affect your child’s daily activities?’’ using a 7-point Likert scale. Content validity was supported through use of the international consensus definition of CP [1] in combination with the ICF [3]. Test–retest reliability (ICC ¼ 0.80 – number; 0.85–impact) and known groups validity (significant differences among all GMFCS levels) have been established [26]. The Early Coping Inventory [34], a 48-item parent-report measure, was used to provide an estimate of children’s adaptive behaviour. For each item, parents rate the effectiveness of their children’s behaviour from 1 (not effective) to 5 (consistently effective across situations). Inter-rater reliability has been established with the total score inter rater reliability coefficient of r ¼ 0.91. Known groups’ validity has been demonstrated through determination that scores differentiate children with developmental disabilities from those without disabilities [40]. The construct of family ecology was estimated using two parent-completed measures. The Family Environment Scale [35] contains 90 items representing statements with respect to three dimensions of relationships, personal growth and system maintenance. Each item is scored dichotomously as ‘‘true’’ or ‘‘false’’ and subscale and dimension scores can be obtained. Internal consistency across dimensions (Cronbach’s alphas 0.61–0.78), test–retest reliability (0.54–0.91) and concurrent validity have been established [35]. A measure of Family’s Expectations of Child was developed collaboratively with parents of young children with CP for the Move & PLAY study, providing some evidence of content validity. It contains 5 questions, each rated on a 7-point scale. Test–retest reliability is supported by non-significant differences when repeated over a 2-week interval.
Determinants of self-care participation
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DOI: 10.3109/17518423.2014.897398
Finally, we developed a Services Questionnaire for the Move & PLAY study, which parents completed [36]. Although we collected many aspects of services, for final model testing, we used the following dimensions: intensity of therapy (total time of physical and occupational therapy over 1 year), family-centredness (18 items measured on a 5-point Likert scale, including parents’ perceptions of the family centredness of therapists and coordination of care among all care providers), number of community programs, and three items that tapped into parents’ perceptions of services meeting their children’s needs in terms of supporting motor function, self-care participation and participation in family and recreational activities. Many of these measures (and scoring tables for the full Child Engagement in Daily Life measure) are available on the Move & PLAY section of the CanChild Centre for Childhood Disability Research website (http://www.canchild.ca/en/ourresearch/moveplay.asp). Procedures Assessors trained in administration of the measures and who met criteria for reliability collected the following data at the onset of the study in either a home or clinic setting: spasticity, quality of movement, balance, distribution of involvement, strength, range of motion, gross motor function and motor classification using the GMFCS. At the same time, parents provided information about their children’s endurance, health conditions and adaptive behaviour, in addition to completing a family demographic form. An average of 7 months later, through a telephone interview, parents provided information about their families and services their children received. Approximately 1 year after the first data collection point, parents provided information about their children’s self-care participation. Statistical analyses Data management and statistical analyses for the series of model testing projects have been described elsewhere [22], and are reproduced here with permission from Developmental Medicine and Child Neurology. Our interest is in testing the conceptual model, with latent constructs measured by underlying indicators. Accordingly, we simplified the measurement model such that the measures of a given construct (single item questions and subscales) were combined to produce a single indicator. Table S2 (online supporting information of reference 22) contains details of how the measures were used in this analysis. For body structures and functions (i.e. primary impairments), all scores were adjusted to be aligned with the ECAB scores (i.e. higher scores reflect ‘‘better’’ structures and functions). All scores were scaled to the same metric (0– 10) and averaged to produce one indicator. Confirmatory Factor Analysis (CFA) provides evidence that balance (factor loading of 0.95), distribution of involvement (0.82), quality of movement (0.77) and spasticity (0.68) contribute to the construct of primary impairments. For secondary impairments, all scores were adjusted to the metric of the SAROMM (i.e. higher scores reflect more impairment and scaled 0–4 and averaged to produce one indicator). Again, CFA confirms that impairments in strength (0.95), range of motion (0.74)
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and endurance (0.66) contribute to the construct of secondary impairments, as evidenced by their factor loadings. The indices for health conditions and child adaptive behaviour were simply the mean scores of scale components. The indicator for family ecology involved combining three components based on factor loadings (family relationships, social integration and families’ expectations of child); the final score was scaled from 0–1. Four service measures (intensity of therapy, family-centred services, number of community programs and services meeting needs) were each treated as separate indicators in the model, and scaled as in the original data collection (note that a full description of the services received by the participants has been described [36]). When using structural equation modelling, the data input is the variance–covariance matrix representing relationships among the latent constructs. Person-level means were used to impute missing values on each scale. Full information maximum likelihood was used to estimate the models when some of the indicators had missing values. Full information maximum likelihood produces unbiased estimates under ‘‘missing at random’’ assumptions, an assumption that is supported by no clinically significant differences between those recruited and retained. The model was tested simultaneously for children in GMFCS Levels I and II (Group 1) and children in GMFCS Levels III–V (Group 2) with multi-group structural equation modelling using the software MPLUS 5; (Muthe´n & Muthe´n, Los Angeles, CA), permitting testing of the proposed hypotheses. We examined: (1) overall model fit, (2) proportion of variance in the outcome variable explained by the model for each group and (3) the standardized coefficients of the significant pathways, followed by testing of differences between groups. The fit of the data to the model for both groups was examined using 2 (p50.05), the comparative fit index (CFI, 0.95), the Tucker–Lewis Index (TLI, approximating 0.95) and the Root Mean Square Error of Approximation (RMSEA,50.05). For details of these terms, please see Palisano et al. [41] Meeting minimum criteria indicates adequacy of the model fit. The criterion for whether the hypothesized paths were significant was a standardized path coefficient ( ) with an alpha level of 0.05. Differences in the magnitude of path coefficients between the groups (i.e. GMFCS groupings) were tested using the likelihood ratio test with an alpha level of 0.05.
Results The structural models for Groups 1 and 2 are contained in Figures 1 and 2, respectively. Fit statistics indicated a good fit between the data and the models ( 2 ¼ 52.73, df ¼ 36, p ¼ 0.036; CFI ¼ 0.988; TLI ¼ 0.968 and RMSEA ¼ 0.047). These models explained 65.2 and 74.5% of the variance in self-care participation for children in Groups 1 and 2. Standardized beta coefficients were significant (p50.05) for direct paths between gross motor function (0.41, 0.44), health conditions ( 0.30, 0.18) and adaptive behaviour (0.20, 0.12) and self-care participation, for both groups. Although health conditions were significant in both groups, the association was significantly stronger in Group 1. For Group 1, the perception that services were meeting children’s
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Dev Neurorehabil, 2014; 17(6): 403–413
−0.52***
Secondary Impairments
−0.25***
0.56***
Body Structure and Function
GMFM-66 Time 3
Health Conditions
0.41*** −0.30***
Adaptive Behavior
Self-Care
0.20***
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−.29***
R2(p) 65.2% (0001)
Family Ecology 0.19** Intensity of Therapy 0.17*
0.19**
Family-Centred Services
0.27***
# Community Programs Services Meeting Needs
Figure 1. Determinants of self-care participation for children in Gross Motor Function Classification System levels I and II (solid lines indicate significant effects; dashed lines are non-significant). Note: *p50.5; **p50.01; ***p50.001.
−0.68***
Secondary Impairments
−0.28***
0.56***
Body Structure and Function
GMFM-66 Time 3
0.21**
Health Conditions
0.44*** 0.25*** −0.18**
Adaptive Behavior
0.12*
Self-Care
0.09* −.14*
R2(p) 74.5% (
ORIGINAL ARTICLE
Determinants of self-care participation of young children with cerebral palsy Doreen J. Bartlett1, Lisa A. Chiarello2, Sarah Westcott McCoy3, Robert J. Palisano2, Lynn Jeffries4, Alyssa LaForme Fiss5, & Piotr Wilk6
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1
School of Physical Therapy, Western University, London, ON, Canada, 2Department of Physical Therapy and Rehabilitation Sciences, Drexel University, Philadelphia, PA, USA, 3Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA, 4Department of Rehabilitation Sciences, The University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA, 5Department of Physical Therapy, Mercer University, Atlanta, GA, USA, and 6Department of Epidemiology and Biostatistics, Western University, London, ON, Canada
Abstract
Keywords
Objective: To test a model of child, family and service determinants of self-care participation of children with cerebral palsy (CP), grouped by Gross Motor Function Classification System levels (I–II and III–V). Methods: Participants were a convenience sample of 429 children (242 males) with CP, aged 18–60 months. Data on impairments and gross motor function were collected by reliable therapists; parents provided information about children’s health conditions and adaptive behaviour. Seven months later parents reported on family life and services received. One year after study onset, parents documented children’s self-care participation. Data from two groups of children were analysed using structural equation modelling. Results: The model explained a significant proportion of the variance of self-care participation, with higher motor function, fewer health conditions and higher levels of adaptive behaviour being associated with greater self-care participation. Conclusion: Supporting children’s gross motor function, health and adaptive behaviour may optimize self-care participation.
Biopsychosocial approach, prospective cohort study, structural equation modelling
Introduction ‘‘Cerebral palsy (CP) describes a group of disorders of the development of movement and posture, causing activity limitation that are attributed to non-progressive disturbances that occurred in the developing foetal or infant brain. The motor disorders of cerebral palsy are often accompanied by disturbances of sensation, perception, cognition, communication, and behaviour, by epilepsy, and by secondary musculoskeletal problems’’ [1, p. 9]. Importantly, this international consensus definition of CP emphasizes the issues of activity limitation and participation restriction as well as the complexity of the condition with respect to associated health states and development of secondary conditions over time, all of which need to be considered in clinical decision-making. Along with others [2], we advocate for a holistic, biopsychosocial approach to assessment and intervention to ensure that all aspects of this complex health condition are considered. We have developed a multivariate model of determinants of activity and participation that incorporates primary and secondary impairments, associated health conditions, as well as personal and environmental components [3] involving
Correspondence: Doreen Bartlett, 1588 Elborn College, School of Physical Therapy, Western University, London, ON, N6G 1H1, Canada. Tel: +519 661 2111, extn 88953. E-mail: [email protected]
History Received 19 December 2013 Revised 30 January 2014 Accepted 19 February 2014 Published online 7 April 2014
children’s adaptive behaviour and aspects of families and services provided, aiming to provide a framework for decision-making for rehabilitation therapists and families of young children with CP [4]. The supplementary figure contains a reproduction of the conceptual model. One of the fundamental goals of early therapy for children with CP is to promote participation in daily life [4], including families’ priority of independence in self-care [5], which is the focus of the work reported here. A growing body of literature supports associations between multiple components of the International Classification of Functioning, Disability and Health (ICF) [3] and self-care in samples of children with CP. Among primary impairments, greater involvement of more limbs and parts of the body [2, 6, 7], problems with selective motor control [6] and atypical postures [8] have been identified to be associated with limitations in self-care function. Children with higher levels of gross motor function attain greater independence in self-care and daily living skills [2, 7, 9–14]; hand function has also been identified to be strongly associated with self-care abilities [13, 15]. The presence of learning problems and cognitive impairment has been found to be associated with lower self-care abilities [6, 7, 9, 12], as has the presence of pain [14]. In terms of services, functional approaches [16, 17], home-based consultations [18], and assistive devices and environmental modifications [19, 20] have all been found to contribute to improvements in self-care
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function. Recently, a more accessible physical environment in the home has been found to be associated with higher participation at mealtimes and with personal care [14]. All but three cohorts [6, 9, 10, 13] have exclusively studied schoolaged children and none focused solely on preschool-aged children. Because early childhood is a sensitive period for the development of many domains, including self-care [4], a study focusing on a younger age group is warranted. Furthermore, most investigations have focused on capability [6–8, 12, 13, 15], rather than performance, which is typically of greater interest to parents and caregivers. Although recent studies have gone beyond descriptive and bivariate analyses to use more sophisticated approaches including various forms of multiple regression [6–9, 11–13] and structural equation modelling [14] to examine multiple factors related to selfcare, none have incorporated all aspects suggested by both the international consensus definition of CP and the ICF. Specifically, the role of secondary impairments, personal aspects of children unrelated to a diagnosis of CP, and contextual factors associated with families have not yet been investigated. The purpose of this study, therefore, was to test a multivariate model of child, family and service determinants that together explain participation of self-care of preschoolaged children with CP (see Figure S1). Based on complementary theoretical frameworks, the research literature, clinical expertise and parent input [4] we hypothesized that: (1) the model would explain a greater proportion of variance of participation in self-care among children whose selfmobility is limited or who walk with assistive devices than among children with a good prognosis for independent ambulation, (2) children’s primary and secondary impairments and associated conditions would have an indirect effect on participation in self-care through the mediator of gross motor function, (3) children’s adaptive behaviour, family ecology and rehabilitation and community services would have a direct effect on participation in self-care and (4) rehabilitation and community services would be a mediator between family ecology and self-care. Knowledge of determinants of self-care participation will assist with decisions about what to assess and how to intervene to support optimal independence. Significant determinants that are amenable to change are targets for intervention, either directly or through environmental modifications. Determinants that are not amenable to change can assist with realistic goal-setting.
Methods In this article, we report on one set of models tested in a multi-site prospective cohort study referred to as Move & PLAY (Movement and Participation in Life Activities of Young Children with cerebral palsy). In preliminary papers, we described the development of the conceptual [4] and measurement [21] models. Participants The participants of our study have been previously described [22]; this description is reproduced here with permission from Developmental Medicine and Child Neurology. Children were eligible to participate if they had a diagnosis of CP, or gross
Dev Neurorehabil, 2014; 17(6): 403–413
motor delay with impairments consistent with CP, and if their parents could speak English, French or Spanish. Children with a predominant dual diagnosis were excluded. Statistical estimation involving a sample of 200 typically results in stable estimates of various fit indices used to determine the degree of fit between the pattern of relationships in the data and proposed model [23, 24]. We initially aimed for equal numbers in each of the following GMFCS groups: Levels I and II, Level III, and Levels IV and V. Participants were a convenience sample of 429 children (242 males, 187 females) and their caregivers recruited from children’s rehabilitation centres in six provinces in Canada and four regions in the USA between July 2007 and February 2009. At the outset of the study, children ranged in age from 18 to 60 months (mean of 3 years, 2 months, SD 11 months). Children’s abilities varied across all five levels of the GMFCS [25] and across all distributions of involvement. Child and parent participant demographics are contained in Table I. This distribution is representative of GMFCS levels in populationbased studies around the world [26]. We were able to recruit a sufficient number of children in GMFCS Levels I and II (n ¼ 204) and Levels III, IV and V (n ¼ 226) to test the model on two groups of children. We retained 90% of the sample over the observation period of 1 year; data collection was completed in March 2010. Families who remained in the study had significantly higher incomes than families who withdrew or were lost to follow-up (however, the magnitude of this difference is not practically significant); no other child and family demographics differed between groups (Table I). Ethical approval was obtained from all academic and clinical sites; parents provided signed informed consent prior to data collection. Measures Outcome Children’s self-care participation was measured using the selfcare domain of the Child Engagement in Daily Life measure [27] which was developed in the context of the Move & PLAY study to be used to measure participation in family and recreational activities and self-care of young children with CP through parent report. The self-care domain contains 7 items about feeding, dressing, bathing and toileting which are measured using a 5-point Likert scale (i.e. ‘‘1’’ indicating ‘‘no help needed’’; ‘‘2’’, ‘‘no difficulty’’; ‘‘3’’, ‘‘a little difficulty’’; ‘‘4’’, ‘‘somewhat difficult’’ and ‘‘5’’, ‘‘very difficult’’). Construct validity is supported by the known groups method, with younger children obtaining lower scores than older children and children with more functional GMFCS levels obtaining higher scores than children in less functional levels [27]. Internal consistency, using Cronbach’s alpha, was 0.90 and test–retest reliability was high with an intra-class correlation coefficient of 0.96 (with 95% confidence interval of 0.91–0.98) for participation in self-care. Finally, using Rasch analysis, item stability was demonstrated to be excellent in distinct subsamples with a Pearson’s correlation of 0.99 for item calibrations and a Spearman rank correlation of 0.89 for item ranks. Item fit was acceptable, supporting the unidimensionality of the self-care domain. Although differential item functioning varied for children in
Determinants of self-care participation
DOI: 10.3109/17518423.2014.897398
Table I. Child and parent demographic characteristics (reproduced with permission).
Characteristics
Participants enrolled n ¼ 429 (%)
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Child GMFCS level I 154 (36) II 50 (11) III 53 (12) IV 75 (18) V 97 (23) Child distribution of involvement Monoplegia 10 (2) Hemiplegia 102 (24) Diplegia 100 (23) Triplegia 25 (6) Quadriplegia 190 (44)
Child ethnicity African–American Asian or Pacific Islander Hispanic/Latino Native American White Other Parent age, years:months Mean (SD) Parent relationship to child Mother Father Other Parent education High school or less Community College/ Associate’s Degree University Family incomea (CA$ or US$) $75 000 $60 000–74 999 $45 000–59 999 $30 000–44 999 $30 000
Family composition Adults (mean, SD) Children (mean, SD)
Participants retained over the year n ¼ 389 (%) 145 45 49 66 84
(37) (11) (13) (17) (22)
8 98 88 24 169
(2) (25) (23) (6) (44)
(n ¼ 427)
(n¼387)
32 19 18 11 299 50
25 17 16 9 272 50
(8) (4) (4) (3) (70) (11)
(7) (4) (4) (2) (70) (13)
34:4 (6.9)
34:6 (6.6)
393 (92) 21 (5) 15 (4)
364 (94) 21 (5) 4 (1)
134 (31) 114 (27)
115 (30) 101 (26)
181 (42)
173 (44)
164 49 59 54 88
157 48 52 45 74
(38) (11) (14) (13) (21)
(40) (12) (13) (12) (19)
(n ¼ 413)
(n ¼ 376)
2.2 (0.8) 2.2 (1.1)
2.2 (0.8) 2.2 (1.1)
a
Report based on the available information. GMFCS, Gross Motor Function Classification System Level; CA$, Canadian Dollars; US$, United States Dollars.
different GMFCS levels, scaled (Rasched) total scores did not differ among GMFCS level groupings, so there is little practical significance to this finding [27]. Independent variables/determinants The list of measures representing the determinants of self-care is contained in Table II; a description of the psychometric properties of these measures follows. Determinants are categorized into gross motor function (activity), primary impairments (i.e. impairments of body functions related to the movement disorder of CP present at the outset of a diagnosis), secondary impairments (i.e. impairments of body functions related to the movement disorder of CP that develop over time), associated health conditions (as conceptualized in the international consensus definition of CP and measured using
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body functions terminology, where possible), child adaptive behaviour (a personal factor that is unrelated to the diagnosis of CP), and family ecology and services provided (environmental factors). Four primary impairments were measured: spasticity, quality of movement, balance and distribution of involvement. Three secondary impairments included strength, range of motion and endurance for activity. Motor function was measured using the basal and ceiling approach of the Gross Motor Function Measure (GMFM66-B&C) [28], which requires administration of a minimum of 15 items from the original GMFM-66 [37], ranked in order of difficulty. The 15 items must start with a basal level of three consecutive scores of 3 (‘‘completes’’ item as described) up to a ceiling level of three consecutive scores of 0 (‘‘does not initiate’’). GMFM-66 scores are then calculated using the Gross Motor Ability Estimator (GMAE) [37], now available in an updated second version (GMAE-2; www.canchild.ca). GMFM-66 scores range from 0 to 100. Concurrent validity between the GMFM-66-B&C and the full GMFM-66 and test–retest reliability were estimated using the intraclass correlation coefficient (ICC); both were 0.99 [28]. Spasticity was measured using the Modified Ashworth Scale [29]. Three estimates of each of bilateral elbow flexors and hamstrings using a 6-point ordinal scale were recorded. Inter-rater reliability has been established with an ICC value of 0.79 [38]. Evidence for construct validity was provided with significant correlations with the Tardieu Scale and scores taken with a myotonometer and isokinetic dynamometer [38]. Selected items from the ‘‘coordination’’ and ‘‘dissociation’’ subscales of the Gross Motor Performance Measure (GMPM) [30] were used to obtain an estimate of quality of movement. For each child, an attempt was made to obtain two estimates of each of these subscales based on performance of the relevant GMFM item within the child’s current motor repertoire. Each item is scored using a 4-point Likert scale (0–3); estimates for each subscale were averaged and the two subscales summed for a total possible score between 0 and 6. Inter-, intra- and test–retest reliabilities had ICCs in the range of 0.92–0.96; known groups validity was established with differences in GMPM scores for children at different functional ability levels [30]. A new measure of postural stability developed through the Move & PLAY study is the Early Clinical Assessment of Balance (ECAB) [31], which is appropriate for children in all GMFCS levels. Items are scored on 4- and 5-point ordinal scales in Parts 1 and 2, respectively. Possible total scores on the ECAB range from 0 to 100. Validity of the ECAB is supported by significant differences across GMFCS levels and significant associations with age and GMFM-66-B&C scores. Test–retest reliability is very strong with an intra-class correlation coefficient (ICC) of 0.98 [39]. Distribution of involvement was scored from 1 to 5 based on the following classification: monoplegia, hemiplegia, diplegia, triplegia or quadriplegia. Stability of classification over a 1-year period in the Move & PLAY study was strong, with a kappa value of 0.79 (p50.001). For muscle strength, a global estimate was obtained on the following groups of muscles: neck and trunk flexors and extensors, hip and knee extensors, and shoulder flexors.
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Table II. List of measures used to test the model of self-care participation.
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Construct
Indictor
Motor function
Gross motor function
Primary impairments Primary impairments
Spasticity Quality of movement
Primary impairments Primary impairment
Balance Distribution of involvement
Secondary impairment Secondary impairment
Strength Range of motion
Secondary impairment Associated health conditions and comorbidities Child adaptive behaviour
Endurance Associated conditions
Family ecology Family ecology Rehabilitation and community services
Sensorimotor organization Self-initiated behaviours Reactive behaviours Family relationships Social integration Expectations Intensity of therapy Family-centred services Number of community programs Services meeting needs
Each muscle group was rated on a 5-point ordinal scale, using standard physical therapy manual muscle testing approaches. The psychometric properties of this measure were established through the Move & PLAY study. Internal consistency among the groups of muscles (Cronbach’s alpha ¼ 0.93), test–retest reliability (ICC ¼ 0.97) and known groups validity (significant differences among all GMFCS levels except II and III) were supported. The Spinal Alignment and Range of Motion Measure (SAROMM) [32] was used to provide an overall estimate of the extent of limitations in spinal alignment and range of motion. It comprises 26 items, each scored on a 5-point Likert scale. Each item is scored based on observation of postural alignment or passive movement of the extremities, using standard manual techniques. Internal consistency (Cronbach’s alpha ¼ 0.95), inter-rater and test–retest reliability (ICC40.80) and known groups validity (significant differences among all GMFCS levels) have all been established [32]. Endurance for activity was measured using the Early Activity Scale for Endurance, which was developed in the context of the Move & PLAY study [33]. Although it started out as a 10-item, parent-completed measure scored on a 5-point Likert scale, confirmatory factor analysis was used to pare it down to 4 items. Internal consistency (Cronbach’s alpha ¼ 0.83), test–retest reliability (ICC ¼ 0.95) and known groups validity (significant differences among all GMFCS levels except between II and III and between III and IV) were supported [33]. We designed the parent-completed Health Conditions Questionnaire [26] to measure the number and impact of health conditions experienced by children with CP. Each parent first responds ‘‘yes’’ or ‘‘no’’ to 16 questions asking ‘‘does your child have problemsð.’’ about a range of health manifestations (i.e. seeing, hearing, learning and understanding, speaking or communicating, controlling emotions or
Measure Gross Motor Function Measure (basal and ceiling approach) [28] Modified Ashworth Scale [29] 4 items from the Gross Motor Performance Measure [30] Early Clinical Assessment of Balance [31] Monoplegia, hemiplegia, diplegia, triplegia, quadriplegia Functional Strength Assessment Spinal Alignment and Range of Motion Measure [32] Early Activity Scale for Endurance [33] Health Conditions Questionnaire [26]
Respondent Assessor; 15 min Assessor; 5 min Assessor; 10 min Assessor; 10–15 min Assessor; 5 min Assessor; 10 min Assessor; 15 min Parent; 5 min Parent; 5 min
Early Coping Inventory [34]
Parent; 10 min
Part of the Family Environment Scale [35] Family’s Expectations of Child (developed by team, in collaboration with parents) Services Questionnaire [36]
Parent; 30 min Parent; 5 min Parent; 10 min
behaviour, seizures or epilepsy, the mouth, teeth and gums, digestion, growth, sleeping, repeated infections, breathing, skin, heart and pain). If the response is ‘‘yes’’, they were also asked to rate ‘‘to what extent does this problem affect your child’s daily activities?’’ using a 7-point Likert scale. Content validity was supported through use of the international consensus definition of CP [1] in combination with the ICF [3]. Test–retest reliability (ICC ¼ 0.80 – number; 0.85–impact) and known groups validity (significant differences among all GMFCS levels) have been established [26]. The Early Coping Inventory [34], a 48-item parent-report measure, was used to provide an estimate of children’s adaptive behaviour. For each item, parents rate the effectiveness of their children’s behaviour from 1 (not effective) to 5 (consistently effective across situations). Inter-rater reliability has been established with the total score inter rater reliability coefficient of r ¼ 0.91. Known groups’ validity has been demonstrated through determination that scores differentiate children with developmental disabilities from those without disabilities [40]. The construct of family ecology was estimated using two parent-completed measures. The Family Environment Scale [35] contains 90 items representing statements with respect to three dimensions of relationships, personal growth and system maintenance. Each item is scored dichotomously as ‘‘true’’ or ‘‘false’’ and subscale and dimension scores can be obtained. Internal consistency across dimensions (Cronbach’s alphas 0.61–0.78), test–retest reliability (0.54–0.91) and concurrent validity have been established [35]. A measure of Family’s Expectations of Child was developed collaboratively with parents of young children with CP for the Move & PLAY study, providing some evidence of content validity. It contains 5 questions, each rated on a 7-point scale. Test–retest reliability is supported by non-significant differences when repeated over a 2-week interval.
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DOI: 10.3109/17518423.2014.897398
Finally, we developed a Services Questionnaire for the Move & PLAY study, which parents completed [36]. Although we collected many aspects of services, for final model testing, we used the following dimensions: intensity of therapy (total time of physical and occupational therapy over 1 year), family-centredness (18 items measured on a 5-point Likert scale, including parents’ perceptions of the family centredness of therapists and coordination of care among all care providers), number of community programs, and three items that tapped into parents’ perceptions of services meeting their children’s needs in terms of supporting motor function, self-care participation and participation in family and recreational activities. Many of these measures (and scoring tables for the full Child Engagement in Daily Life measure) are available on the Move & PLAY section of the CanChild Centre for Childhood Disability Research website (http://www.canchild.ca/en/ourresearch/moveplay.asp). Procedures Assessors trained in administration of the measures and who met criteria for reliability collected the following data at the onset of the study in either a home or clinic setting: spasticity, quality of movement, balance, distribution of involvement, strength, range of motion, gross motor function and motor classification using the GMFCS. At the same time, parents provided information about their children’s endurance, health conditions and adaptive behaviour, in addition to completing a family demographic form. An average of 7 months later, through a telephone interview, parents provided information about their families and services their children received. Approximately 1 year after the first data collection point, parents provided information about their children’s self-care participation. Statistical analyses Data management and statistical analyses for the series of model testing projects have been described elsewhere [22], and are reproduced here with permission from Developmental Medicine and Child Neurology. Our interest is in testing the conceptual model, with latent constructs measured by underlying indicators. Accordingly, we simplified the measurement model such that the measures of a given construct (single item questions and subscales) were combined to produce a single indicator. Table S2 (online supporting information of reference 22) contains details of how the measures were used in this analysis. For body structures and functions (i.e. primary impairments), all scores were adjusted to be aligned with the ECAB scores (i.e. higher scores reflect ‘‘better’’ structures and functions). All scores were scaled to the same metric (0– 10) and averaged to produce one indicator. Confirmatory Factor Analysis (CFA) provides evidence that balance (factor loading of 0.95), distribution of involvement (0.82), quality of movement (0.77) and spasticity (0.68) contribute to the construct of primary impairments. For secondary impairments, all scores were adjusted to the metric of the SAROMM (i.e. higher scores reflect more impairment and scaled 0–4 and averaged to produce one indicator). Again, CFA confirms that impairments in strength (0.95), range of motion (0.74)
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and endurance (0.66) contribute to the construct of secondary impairments, as evidenced by their factor loadings. The indices for health conditions and child adaptive behaviour were simply the mean scores of scale components. The indicator for family ecology involved combining three components based on factor loadings (family relationships, social integration and families’ expectations of child); the final score was scaled from 0–1. Four service measures (intensity of therapy, family-centred services, number of community programs and services meeting needs) were each treated as separate indicators in the model, and scaled as in the original data collection (note that a full description of the services received by the participants has been described [36]). When using structural equation modelling, the data input is the variance–covariance matrix representing relationships among the latent constructs. Person-level means were used to impute missing values on each scale. Full information maximum likelihood was used to estimate the models when some of the indicators had missing values. Full information maximum likelihood produces unbiased estimates under ‘‘missing at random’’ assumptions, an assumption that is supported by no clinically significant differences between those recruited and retained. The model was tested simultaneously for children in GMFCS Levels I and II (Group 1) and children in GMFCS Levels III–V (Group 2) with multi-group structural equation modelling using the software MPLUS 5; (Muthe´n & Muthe´n, Los Angeles, CA), permitting testing of the proposed hypotheses. We examined: (1) overall model fit, (2) proportion of variance in the outcome variable explained by the model for each group and (3) the standardized coefficients of the significant pathways, followed by testing of differences between groups. The fit of the data to the model for both groups was examined using 2 (p50.05), the comparative fit index (CFI, 0.95), the Tucker–Lewis Index (TLI, approximating 0.95) and the Root Mean Square Error of Approximation (RMSEA,50.05). For details of these terms, please see Palisano et al. [41] Meeting minimum criteria indicates adequacy of the model fit. The criterion for whether the hypothesized paths were significant was a standardized path coefficient ( ) with an alpha level of 0.05. Differences in the magnitude of path coefficients between the groups (i.e. GMFCS groupings) were tested using the likelihood ratio test with an alpha level of 0.05.
Results The structural models for Groups 1 and 2 are contained in Figures 1 and 2, respectively. Fit statistics indicated a good fit between the data and the models ( 2 ¼ 52.73, df ¼ 36, p ¼ 0.036; CFI ¼ 0.988; TLI ¼ 0.968 and RMSEA ¼ 0.047). These models explained 65.2 and 74.5% of the variance in self-care participation for children in Groups 1 and 2. Standardized beta coefficients were significant (p50.05) for direct paths between gross motor function (0.41, 0.44), health conditions ( 0.30, 0.18) and adaptive behaviour (0.20, 0.12) and self-care participation, for both groups. Although health conditions were significant in both groups, the association was significantly stronger in Group 1. For Group 1, the perception that services were meeting children’s
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−0.52***
Secondary Impairments
−0.25***
0.56***
Body Structure and Function
GMFM-66 Time 3
Health Conditions
0.41*** −0.30***
Adaptive Behavior
Self-Care
0.20***
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−.29***
R2(p) 65.2% (0001)
Family Ecology 0.19** Intensity of Therapy 0.17*
0.19**
Family-Centred Services
0.27***
# Community Programs Services Meeting Needs
Figure 1. Determinants of self-care participation for children in Gross Motor Function Classification System levels I and II (solid lines indicate significant effects; dashed lines are non-significant). Note: *p50.5; **p50.01; ***p50.001.
−0.68***
Secondary Impairments
−0.28***
0.56***
Body Structure and Function
GMFM-66 Time 3
0.21**
Health Conditions
0.44*** 0.25*** −0.18**
Adaptive Behavior
0.12*
Self-Care
0.09* −.14*
R2(p) 74.5% (
