Secondary Logo

Journal Logo


Interrelationships of Functional Status and Health Conditions in Children With Cerebral Palsy: A Descriptive Study

Bartlett, Doreen PT, PhD; Dyszuk, Emily MSc; Galuppi, Barbara BA; Gorter, Jan Willem MD, PhD

Author Information
doi: 10.1097/PEP.0000000000000469
  • Free


There are 2 commonly used systems for classifying children with cerebral palsy (CP): systems based on anatomy or physiology and systems based on function. Functional classification systems focus on what the child typically does instead of classifying based on impairments (such as distribution of involvement or type of movement disorder). The integration of the International Classification of Functioning, Disability and Health (ICF) framework1 into health care has helped emphasize children's functional abilities and their typical performance in day-to-day life, rather than impairments.2 These concepts have been incorporated and used in classification systems by researchers, clinicians, and families to describe performance in mobility, handling objects, and communication. The Gross Motor Function Classification System (GMFCS),3 the Manual Ability Classification System (MACS),4 and the Communication Function Classification System (CFCS)5 are 3 functional classification systems designed for children with CP to portray reliably their mobility habits, how they handle objects in daily life, and their communication skills with familiar and nonfamiliar partners, respectively. These classification systems can be accessed at the following sites:;; and

As there is no singular classification system for children with CP, combining various classifications encompassing functional components of a child's life is important.6 Hidecker and colleagues7 described functional profiles established from the 3 complementary classification systems (ie, the GMFCS, the MACS, and the CFCS). Although their study described a more comprehensive picture of children with CP than when classified using a single system, they did not concurrently describe impairments in body functions and associated health conditions, which are included in key components in the definition of CP.8

It is important to ascertain the frequency and impact of impairments in body functions and associated health conditions to provide a more complete picture of the functional profiles for children with CP. The primary purpose of this study was to replicate Hidecker's work7 to identify frequently occurring functional profiles for children with CP by examining the interrelationships among the GMFCS, the MACS, and the CFCS. We hypothesized that there would be a relatively small proportion of frequently occurring profiles in children with CP, as CP is a very heterogeneous condition. Secondarily, we explored the number and impact of impairments in body functions and associated health conditions in frequently occurring and additional selected functional profiles and differences among them.


This study is part of a 5-year prospective cohort study: Developmental Trajectories of Impairments, Associated Health Conditions, and Participation of Children with CP (the On-Track study).9 Ethical approval for this research was granted by the Health Science Research Ethics Board of Western University, as well as participating universities and sites in Canada and the United States. All ethical recommendations have been adhered to and written, informed consent for participation and publication was obtained from all legal guardians; assent was provided by children older than 7 years.


Children participating in the On-Track study who had been diagnosed with CP or were suspected to have CP at the time of recruitment and who were between the ages of 18 months and 12 years were eligible to participate in the larger study. Ongoing eligibility was maintained throughout the study so that the final data set for analysis represented children with CP. Therapist assessors provided detailed information for consideration of eligibility of 71 unique cases either before or after recruitment. A physiatrist (J.W.G.) reviewed and made recommendations to the team about queries relating to eligibility. As a result, 11 cases were excluded. Families were excluded from the On-Track study if they did not speak English, French, or Spanish. A convenience sampling approach was used to recruit participants for the study using various methods from clinical sites across Canada and the United States, including children from urban, rural, and suburban areas (see site descriptions at: Recruitment and the first data collection point took place between April 2013 and January 2015. Children in the original On-Track sample (n = 711) were excluded from this substudy if they were younger than 24 months at the first visit (n = 34) or if consensus information was not available for one or more of the classifications (n = 6). A total of 671 children were included in this descriptive substudy. Child and caregiver respondent characteristics are described in Table 1.

TABLE 1 - Child and Caregiver Respondent Characteristics
Characteristics Value
Child n = 671
Age, y
Mean 6.3
SD 2.6
Gender, n (%)
Boy 376 (56)
Girl 295 (44)
Limb distribution, n (%) n = 669
Unilateral 194 (29)
Monoplegia 5 (1)
Hemiplegia 189 (28)
Bilateral 475 (71)
Diplegia 179 (27)
Triplegia 37 (5)
Quadriplegia 259 (39)
Caregiver respondent n = 656
Age, y
Mean 38
SD 7.8
Relationship to child, n (%) n = 665
Mother/adoptive mother 585 (88)
Father/adoptive father/stepfather 48 (7)
Other (aunt, foster mother, grandmother, grandfather, nurse in LTC) 32 (5)
Abbreviations: LTC, long-term care; SD, standard deviation.


The GMFCS,3,10 the MACS,4 and the CFCS5 were used to determine the appropriate levels of functional ability in the areas of gross motor, manual ability, and communication for each child with CP. The 3 systems have a similar parallel structure and design concept—examining children's performance in everyday life by placing them into 1 of 5 levels forming an ordinal scale from level I (most functional) to level V (least functional). The 3 classification systems were developed through the use of nominal group and the Delphi survey consensus methods. The GMFCS, the MACS, and the CFCS have evidence of reliability, validity, and stability.3–5,10–15 These properties are summarized in Table 2.

TABLE 2 - Summary of the Psychometric Properties of the Classification Systems
Classification System Reliability Validity Stability
GMFCS Interrater for children older than 2 y (κ = 0.75)10 Correlation with GMFM scores (r = −0.91)11 Yes12
MACS Interrater (ICC = 0.97)4 Content validity established13 Yes15
Test-retest (ICC = 0.97)4 Correlation with Functional Independence Measure for children (r = −0.78)14
CFCS Intrarater (κ = 0.82)5 Content validity5 Not at this point
Interrater (κ = 0.66) 5
Abbreviations: CFCS, Communication Function Classification System; GMFCS, Gross Motor Function Classification System; GMFM, Gross Motor Function Measure; ICC, intraclass correlation coefficient; κ, Kappa coefficient; MACS, Manual Ability Classification System.

The Child Health Conditions Questionnaire consists of 16 items pertaining to various impairments in body functions and health conditions of children with CP.16 Items were generated based on the international definition of CP8 and most were framed based on the body functions component of the ICF1 (eg, does your child have problems seeing, hearing, learning/understanding, speaking/communicating). Data can be reported on both number of health conditions and impact of health conditions on daily life (from 1 = not at all to 7 = to a very great extent) to describe the extent to which the conditions affect the child's daily activities. Test-retest reliability was established for number (intraclass correlation coefficient = 0.80) and the average impact (intraclass correlation coefficient = 0.85) of health conditions for children between 18 months and 5 years of age.16 This questionnaire is available at: Data obtained from the parent data collection booklets were used to describe the sample.


Data were collected at the first data collection point of the On-Track study during a 1-hour assessment completed by a trained therapist and completion of a separate booklet by the parent or caregiver. Both the assessing therapist and parent or caregiver classified the child's level of involvement, and consensus was reached on the level for each system. Decision algorithms and flow charts provided by the 3 systems3–5 were included in all study kits to aid with decisions on levels between therapists and the parent or caregiver if a consensus was not initially reached. In cases where consensus was not reached, we developed guidelines obtain final classifications.17 All completed data collection booklets were entered into a common database for analysis.

Statistical Analysis

Interrelationships among the GMFCS, the MACS, and the CFCS (reported in this order) were explored using nested cross-tabulations, producing 125 possible combinations of functional cells. The average number and average impact of each associated health condition were calculated in selected cell combinations. Differences among the selected cell combinations were determined using a 1-way analysis of variance and the Kruskal-Wallis k-independent samples test (and appropriate post hoc testing) for the average number and average impact of associated health conditions, respectively. Frequencies and proportions of each of the 16 health conditions were determined for the selected cells. A χ2 test was used to determine the significant difference in proportion of health conditions among the profiles. A P value was set at .05 for most inferential analyses, with Bonferroni's correction being used to compare differences in the 16 health conditions among the selected groups (P < .003).


The interrelationships among the GMFCS, the MACS, and the CFCS are shown in Table 3, representing the functional profiles. Of the possible 125 cell combinations available, 78 combinations were present among the children in this study, representing approximately 62% of all possible combinations. From Table 3, the frequency of the occurrence of the same level of classification in the 3 systems was determined. Of the 671 children, 157 (23%) were found to be the same level in the 3 classification systems. The most common same level classification was GMFCS level I, MACS level I, and CFCS level I (n = 71, 11%). Sequentially, all level IIs represent 4% (n = 26), all level IIIs 1% (n = 5), all level IVs 4% (n = 26), and all level Vs 4% (n = 29).

TABLE 3 - Interrelationships of All 3 Functional Classifications (N = 671)
GMFCS Level Row Totals
GMFCS level I (n = 213)
CFCS level
MACS level I 71 13 3 1 1 89
II 65 26 16 6 0 113
III 1 4 2 2 0 9
IV 0 0 1 1 0 2
V 0 0 0 0 0 0
Column totals 137 43 22 10 1 213
GMFCS level II (n = 155)
CFCS level
MACS level I 20 8 2 2 0 32
II 37 26 18 10 0 91
III 5 7 6 6 0 24
IV 1 1 1 4 1 8
V 0 0 0 0 0 0
Column totals 63 42 27 22 1 155
GMFCS level III (n = 76)
CFCS level
MACS level I 10 1 0 0 0 11
II 16 11 9 2 0 38
III 7 4 5 3 1 20
IV 1 0 2 3 0 6
V 0 0 0 0 1 1
Column totals 34 16 16 8 2 76
GMFCS level IV (n = 123)
CFCS level
MACS level I 3 0 1 0 0 4
II 8 5 4 4 0 21
III 7 9 13 12 3 44
IV 0 2 16 26 4 48
V 1 0 0 3 2 6
Column totals 19 16 34 45 9 123
GMFCS level V (n = 104)
CFCS level
MACS level I 0 0 0 0 0 0
II 0 0 1 1 0 2
III 1 0 2 0 0 3
IV 1 1 13 23 10 48
V 1 0 7 14 29 51
Column totals 3 1 23 38 39 104
Abbreviations: CFCS, Communication Function Classification System; GMFCS, Gross Motor Function Classification System; MACS, Manual Ability Classification System.

The most frequent functional profiles were those that represented 5% or more of the 671 participants and accounted for 27% of the total sample. The most frequent functional cell combinations were (I, I, I) representing 11% (n = 71) of the total sample, followed by (I, II, I) representing 10% (n = 65), and (II, II, I) representing 6% (n = 37). To round out the exploratory portion of this substudy, we selected 2 additional groups: all level IV and all level V, each representing about 4% of the sample. We selected the additional lower functioning groups as a complement to allow for greater variability in number and impact of health conditions to be described and interpreted.

The average number and average impact of associated health conditions were described for both frequent and selected (hereafter referred to as selected) functional profiles (Table 4). A significant difference in the number of associated health conditions was determined among the 5 groups (F = 81.32, df = 4, P < .001). There were significant differences between (I, I, I) and (II, II, I) (P = .008); (I, I, I) and both (IV, IV, IV) and (V, V, V) (P < .001); between (I, II I) and both (IV, IV, IV) and (V, V, V) (P < .001); between (II, II, I) and both (IV, IV, IV) and (V, V, V) (P < .001); and between (IV, IV, IV) and (V, V, V) (P = .001). Differences for the average number of health conditions exceeded the minimal detectable difference at the 95% confidence interval (MDC95) of 3.4 (calculated from Wong et al16) between the 3 most frequent profiles and each of the 2 additional selected profiles. Significant differences in the average impact were determined among groups (χ2 = 117.29, df = 4, P < .001). Post hoc testing using the Mann-Whitney U test and a Bonferroni correction of 0.01, established differences between (I, I, I) and (II, II, I), (IV, IV, IV) and (V, V, V) (all P < .001); between (I, II, I) and (II, II, I) (P = .001), as well as for (IV, IV, IV) and (V, V, V) (both P < .001); between (II, II, I) and (IV, IV, IV) and (V, V, V) (both P < .001); and finally between (IV, IV, IV) and (V, V, V) (P < .001). Again, differences for average impact of health conditions exceeded the MDC95 of 0.8 (also calculated from Wong et al16) among the 3 most frequent profiles and each of the 2 additional selected profiles.

TABLE 4 - Average Number and Average Impact of Selected Associated Health Conditions
(GMFCS, MACS, CFCS) Levels Number of Associated Health Conditions Impact of Associated Health Conditions
Mean (SD) Median (Range) Mean (SD) Median (Range)
(I, I, I) (n = 70)a 2.0 (2.0) 2 (0-8) 0.4 (0.4) 0.3 (0.0-1.9)
(I, II, I) (n = 65) 2.5 (2.3) 2 (0-11) 0.4 (0.4) (n = 63)a 0.3 (0.0-1.8)
(II, II, I) (n = 37) 3.7 (2.3) 4 (0-10) 0.7 (0.6) (n = 35)a 0.7 (0.0-2.6)
(IV, IV, IV) (n = 26) 7.5 (2.9) 7 (3-14) 2.1 (1.1) 1.9 (0.3-5.5)
(V, V, V) (n = 29) 10.0 (2.8) 10 (3-14) 3.1 (1.1) (n = 27)a 3.2 (0.8-4.7)
Abbreviations: CFCS, Communication Function Classification System; GMFCS, Gross Motor Function Classification System; MACS, Manual Ability Classification System; SD, standard deviation.
aNumbers are not the same as in Table 1 as some of the health condition data were missing.

The number and proportion of individual associated health conditions in each of the selected functional profiles are recorded in Table 5. Using a Bonferroni correction of 0.003, the χ2 tests show differences among the 5 groups for problems seeing, hearing, learning, speaking, the mouth, the teeth and gums, digestion, growth, sleeping, repeated infections, breathing, and with seizures.

TABLE 5 - Frequency and Proportion of Each Associated Health Condition in the Selected Groups
Health (I, I, I) (n = 70) (I, II, I) (n = 65) (II, II, I) (n = 37) (IV, IV, IV) (n = 26) (V, V, V) (n = 29) P Value
Condition n (%) n (%) n (%) n (%) n (%) 2 Test)
Seeing 16 (23) 20 (31) 12 (32) 9 (35) 26 (90) <.001a
Hearing 2 (3) 3 (5) 1 (3) 5 (19) 17 (59) <.001
Learning/understanding 15 (21) 21 (32) 11 (30) 22 (85) 28 (97) <.001
Speaking/communicating 3 (4) 9 (14) 1 (3) 24 (92) 29 (100) <.001
Emotions/behavior 26 (37) 24 (37) 20 (54) 18 (69) 11 (39) (n = 28) .03
Seizures/epilepsy 1 (1) 10 (15) 8 (22) 13 (50) 22 (76) <.001
Mouth 1 (1) 8 (12) 9 (24) 24 (92) 27 (96) (n = 28) <.001
Teeth/gums 0 (0) 3 (5) 4 (11) 6 (23) 14 (50) (n = 28) <.001
Digestion 12 (17) 14 (22) 15 (41) 20 (77) 28 (97) <.001
Growth 7 (10) 7 (11) (n = 64) 7 (29) 11 (42) 15 (54) <.001
Sleeping 12 (17) 7 (11) 6 (16) 15 (58) 20 (68) <.001
Repeated infections 2 (3) 4 (6) 7 (19) 3 (12) 13 (45) <.001
Breathing problems 9 (13) 6 (9) 12 (32) 7 (27) 17 (59) <.001
Skin problems 15 (21) 11 (17) 5 (14) 6 (23) 6 (21) .83
Heart problems 5 (7) 5 (8) 2 (5) 3 (12) 4 (14) .73
Pain 17 (24) 10 (15) 15 (41) 9 (35) 13 (45) .01
aBonferroni-corrected P value italicized if significant (ie, <.003).


Alone, there is no single classification system to describe all aspects of a child's life with CP. On their own the GMFCS,3,10 the MACS,4 and the CFCS5 are reliable and valid classification systems that describe a child's body movement, hand function, and communication abilities in everyday life, respectively. When these 3 classification systems are reported together, they provide a more comprehensive picture of a child with CP than with a single classification. Functional profiles of the 3 systems were observed in another study. Hidecker and colleagues7 also observed that the most common profile was children in all level I, representing 10% their total sample, a value that is similar to ours (11%). The Hidecker group also found profile (II, II, I) to be a common profile representing 5% of the sample, which is also similar to our results (6%). Hidecker's study was not as diverse as our study, as their study filled 50% of the possible cell combinations in comparison to 62% in our study. Nonetheless, considering the distribution of involvement in various samples, we did not expect to see all 125 possible combinations as some are functionally unlikely.18 The fact that 73% of the sample was in cells with fewer than 5% of the children highlights the heterogeneity of cerebral palsy.

Co-occurring impairments in body functions and health conditions were also reported in this study, as they are included in the definition of CP.8 Overall, among the selected functional profiles, we found that as the levels increased (ie, function decreased) in one or more of the classification systems the average number and average impact of associated health conditions also increased. A report on preschool children with CP found similar results regarding the number and impact of associated health conditions. Wong and colleagues16 reported a slightly lower frequency and average impact compared with this study, which might be explained by the younger age of the participants and the age in which associated health conditions become apparent.

Additional efforts to group children with CP more comprehensively than with the 3 classification systems and health conditions alone involved using measures of spasticity, balance, distribution of involvement, strength, range of motion, endurance, and impact of health conditions.19 Five “profiles” of functioning were established using both a summative, quintile approach and cluster analysis. Although average function decreased from the most to least functional groups, similar to the observations reported in this article, there was significant variability in scores on individual measures within each of the 5 groups, with considerable overlap between groups, a finding that has been observed by others investigating measurement scores among children at different GMFCS levels.20 We suggest that aiming for a single comprehensive classification is not useful as this oversimplifies the complexity of health issues. Instead, we advocate for routine assessment with a “suite” of measures or classification systems being interpreted separately, and in combination with each other, to understand individual children's functional and health profiles with their relative strengths and limitations, and then to plan interventions based on collaborative decisions with families (see

Among the functional profiles selected for this study, children with all level V on the GMFCS, the MACS, and the CFCS had the highest proportion of problems seeing, hearing, with teeth, and gums, as well as with repeated infections and breathing. Children in classifications (IV, IV, IV) or (V, V, V) had a greater likelihood of problems with learning, speaking, with the mouth, with digestion, and sleeping, as well as epilepsy, than children in the 3 more functional profiles. These results are not surprising, as it is known that virtually all children with CP with good motor abilities survive into adulthood while the risk of death is highest in children with limited motor function.21 Nonetheless, our findings do suggest that comprehensive care coordination and additional services may be required for children with CP and medical complexity to manage their many (and often impactful) associated impairments and health conditions.22 Children at GMFCS level I have been observed to have a greater number of health conditions with greater impact on their lives than children without CP16; therefore, all children with CP could potentially benefit from having the Child Health Conditions Questionnaire completed on a routine basis, at least annually.

Several areas of health are worth highlighting. Problems with the mouth, teeth, and gums occur more frequently, as functional profiles are more limited. Given that children with CP are at an increased risk for tooth decay,23 early oral hygiene care from appropriately trained professionals is required. Problems with digestion, growth, and sleep also increase as functional profiles decrease. We agree with colleagues who have suggested that all care providers working with children with CP should comprehensively assess and manage physical activity, nutrition, and sleep to promote health across the lifespan, suggested to be particularly important for children with lower functional abilities.24 A comprehensive review and analysis of sleep disturbances in children with CP, including guidelines for assessment and management, is a valuable resource for frontline clinicians.25

The most commonly occurring health condition in the 3 most functional profiles, with no significant difference among the 5 selected profiles, was controlling emotions and behavior. Controlling emotions and behavior has been recognized as an unmet health need in children with CP compared with children developing typically.26,27 This health condition has previously received attention as having an effect on children's lives.28–30 As others have found,31 the frequency and impact of pain do not differ by functional ability. Accordingly, all children with CP warrant early detection and prevention of chronic pain, where possible. Guidelines are available for assessment32 and management ( of pain in children with CP.

The increase in research on CP makes it more challenging for health care practitioners to stay up to date on appropriate assessment and intervention across the spectrum of needs for children with CP. Recognition of unmet health needs can lead to changes in how health care practitioners are caring for children with CP. Although physical therapists are not responsible for management across the range of impairments in body functions and health conditions reported here, we suggest routine use of the Child Health Conditions Questionnaire. It is psychometrically sound and readily completed with parents in 5 minutes. Integration of this questionnaire in examinations can lead to appropriate referral, monitoring, and care for early intervention and health promotion.33 Completion of this questionnaire with parents indicates that therapists are interested in the whole child and his or her overall health and well-being.

It is important to note that while the functional aspects of the child's life are portrayed using the 3 classification systems, functional aspects of associated health conditions also impact the lives of children with CP. The additional information on the associated health conditions can help health care practitioners and families to better estimate what to expect and how to better deal and plan for these associated health conditions. Together, the combination of functional profiles and associated health conditions gives a more comprehensive profile for children with CP, than with the classification systems alone.

A limitation to the On-Track study is the method in which the sample was obtained. Although not a population-based sample of children with CP, the distribution of the GMFCS in this large prospective cohort sample of 671 participants is comparable to incidence data reported in the literature. Reid and colleagues34 reported mean proportions (SD) in each GMFCS level in 9 international CP registries: GMFCS I, 34.2% (13.1); GMFCS II, 25.6% (11.6); GMFCS III, 11.5% (2.5); GMFCS IV, 13.6% (4.3); and GMFCS V, 15.6% (4.3). The proportion of children in each GMFCS level in our sample is as follows: GMFCS I, 31.7%; GMFCS II, 23.1%; GMFCS III, 11.3; GMFCS IV, 18.3%; and GMFCS V, 15.5%. Another limitation to the study is that although this study determined differences among 5 selected functional classifications systems and the associated health conditions, there is so much more that contributes to each individual child with CP. As alluded to earlier,19 clinical practice needs to incorporate all of the heterogeneous features of children with CP. Finally, the Child Health Conditions Questionnaire has been validated for use with parents of preschool children with CP and not with parents of older children. We do not know whether the psychometric properties would differ significantly when parents use it with their school-aged children.


This study demonstrates that functional profiles can be established for children with CP by observing their GMFCS, MACS, and CFCS levels and providing a more comprehensive profile by considering impairments in body functions and associated health conditions (both number and impact on daily life). This research represents a more comprehensive picture of children with CP; however, it is important to remember that CP is a heterogeneous condition and more developmental domains should be taken into consideration when planning intervention to optimize outcomes within each child's prognostic potential.


We thank additional members of the On-Track team Sarah Westcott McCoy, Lisa Chiarello, Robert Palisano, Lynn Jefferies, Alyssa LaForme-Fiss, and Steve Hanna for access to the data from the On-Track study.


1. World Health Organization. International Classification of Functioning, Disability and Health. Geneva, Switzerland: World Health Organization; 2001.
2. Rosenbaum P, Gorter JW. The “F-words” in childhood disability. I swear this is how we should think. Child Care Health Dev. 2012;38:457–463.
3. Palisano R, Rosenbaum P, Bartlett D, Livingston M. Content validity of the expanded and revised Gross Motor Function Classification System. Dev Med Child Neurol. 2008;50:744–750.
4. Eliasson A, Krumlinde-Sundholm L, Rosblad B, et al. The Manual Ability Classification System (MACS) for children with cerebral palsy. Scale development and evidence of validity and reliability. Dev Med Child Neurol. 2006;48:549–554.
5. Hidecker M, Paneth N, Rosenbaum P, et al. Developing and validating the Communication Function Classification System (CFCS) for individuals with cerebral palsy. Dev Med Child Neurol. 2011;53:704–710.
6. Rosenbaum P, Eliasson AC, Hidecker MJ, Palisano RJ. Classification in child disability: focusing on function in the 21st century. J Child Neurol. 2014;29:1036–1045.
7. Hidecker M, Ho N, Dodge N, et al. Inter-relationships of functional status in cerebral palsy: analyzing gross motor function, manual ability, and communication function classification systems in children. Dev Med Child Neurol. 2012;54:737–742.
8. Rosenbaum P, Paneth N, Leviton A, Goldstein M, Bax M. A report: the definition and classification of cerebral palsy. April 2006. Dev Med Child Neurol. 2007;49(suppl 109):8–14.
9. Westcott McCoy S, Bartlett D, Smersh M, Galuppi B, Hanna S. Monitoring development of children with cerebral palsy: the on-track study. Protocol of a longitudinal study of development and services. Under review.
10. Palisano R, Rosenbaum P, Walter S, Wood E, Galuppi B. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997;39:214–223.
11. Palisano RJ, Hanna SE, Rosenbaum PL, et al. Validation of a model of gross motor function for children with cerebral palsy. Phys Ther. 2000;80:974–985.
12. Palisano RJ, Cameron D, Rosenbaum PL, Walter SD, Russell D. Stability of the Gross Motor Function Classification System. Dev Med Child Neurol. 2006;48:424–428.
13. Őhrvall AM, Eliasson AC. Parents' and therapists' perceptions of the content of the Manual Ability Classification System, MACS. Scand J Occup Ther. 2010;17:209–216.
14. Gunel MK, Mutlu A, Tarsuslu T, Livanelioglu A. Relationship among the Manual Ability Classification System (MACS), the Gross Motor Function Classification System (GMFCS), and the function status (WeeFim) in children with spastic cerebral palsy. Eur J Pediatr. 2009;168:477–485.
15. Ohrvall AM, Krumlinde-Sundholm L, Eliasson AC. The stability of the Manual Ability Classification System over time. Dev Med Child Neurol. 2014;56:185–189.
16. Wong C, Bartlett D, Chiarello L, Chang HJ, Stoskopf B. Comparison of the prevalence and impact of health problems of preschool children with and without cerebral palsy. Child Care Health Dev. 2011;38:128–138.
17. Bartlett D, Galuppi B, Palisano R, Westcott McCoy S. Consensus classifications of gross motor, manual ability, and communication function classification systems between therapists and parents of children with cerebral palsy. Letter to the Editor. Dev Med Child Neurol. 2016;58:96–99.
18. Cans C. Description of children with cerebral palsy. Steps for the future. Dev Med Child Neurol. 2012;54:679.
19. Jeevanantham D, Bartlett D. Subgrouping children with cerebral palsy from a broader perspective using two methods. Physiother Theory Pract. In Press.
20. Oeffinger D, Gorton G, Bagley A, et al. Outcome assessments in children with cerebral palsy, part 1: descriptive characteristics of GMFCS levels I to III. Dev Med Child Neurol. 2007;49:172–180.
21. Westbom L, Bergstrand L, Wagner P, Nordmark E. Survival at 19 years of age in a total population of children and young people with cerebral palsy. Dev Med Child Neurol. 2011;53:808–814.
22. Dewan T, Cohen E. Children with medical complexity in Canada. Paediatr Child Health. 2013;18:518–522.
23. Rodrigues dos Santos B, Teresa M, Novo D, Ferrerira N, Lorenzetti S. Oral conditions in children with cerebral palsy. Am Acad Pediatr Dent. 2003;70:40–46.
24. Verschuren O, McPhee P, Rosenbaum P, Gorter JW. The formula for health and well-being in individuals with cerebral palsy: physical activity, sleep and nutrition. Dev Med Child Neurol. 2016;58:989–990.
25. Verschuren O, Gorter JW, Pritchard-Wiart L. Sleep: an underemphasized aspect of health and development in Neurorehabilitation [published online ahead of print July 12, 2017]. Early Human Dev. doi:10.1016/j.earlhumdev.2017.07.006.
26. Goodman R, Graham P. Psychiatric problems in children with hemiplegia: cross-sectional epidemiological survey. Br Med J. 1996;7038:1065–1069.
27. Parkes J, White-Koning M, Dickinson H, Thyen U, Arnaud C, Beckung E. Psychological problems in children with cerebral palsy: a cross sectional European study. J Child Psychol Psychiatry. 2008;49:405–413.
28. Bjorgaas H, Elgen I, Boe T, Hysing M. Mental health in children with cerebral palsy: does screening capture the complexity? Sci World J. 2013;2013:468402.
29. Brossard-Racine M, Hall N, Majnemer A, et al. Behavioural problems in school-aged children with cerebral palsy. Eur J Pediatr Neurol. 2012;16:35–41.
30. McDermott S, Coker A, Mani S, et al. A population-based analysis of behavior problems in children with cerebral palsy. J Pediatr Psychol. 1996;21:447–463.
31. Doralp S, Bartlett DJ. The prevalence, distribution, and impact of pain among adolescents with cerebral palsy. Pediatr Phys Ther. 2010;22:26–33.
32. Kingsnorth S, Orava T, Provvidenza C. Chronic pain assessment tools for cerebral palsy: a systematic review. Pediatrics. 2015;136;e947.
33. Novak I. Evidence-based diagnosis, health care, and rehabilitation for children with cerebral palsy. J Child Neurol. 2014;29:1141–1156.
34. Reid SM, Carlin JB, Reddihough DS. Using the Gross Motor Function Classification System to describe patterns of motor severity in cerebral palsy. Dev Med Child Neurol. 2011;53:1007–1012.

associated impairments; cerebral palsy; functional classifications; health conditions

© 2018 Academy of Pediatric Physical Therapy of the American Physical Therapy Association