Clinimetric properties of lower limb neurological impairment tests for children and young people with a neurological condition: A systematic review

Ramona Clark; Melissa Locke; Bridget Hill; Cherie Wells; Andrea Bialocerkowski

doi:10.1371/journal.pone.0180031

Abstract

Background

Clinicians and researchers require sound neurological tests to measure changes in neurological impairments necessary for clinical decision-making. Little evidence-based guidance exists for selecting and interpreting an appropriate, paediatric-specific lower limb neurological test aimed at the impairment level.

Objective

To determine the clinimetric evidence underpinning neurological impairment tests currently used in paediatric rehabilitation to evaluate muscle strength, tactile sensitivity, and deep tendon reflexes of the lower limb in children and young people with a neurological condition.

Methods

Thirteen databases were systematically searched in two phases, from the date of database inception to 16 February 2017. Lower limb neurological impairment tests were first identified which evaluated muscle strength, tactile sensitivity or deep tendon reflexes in children or young people under 18 years of age with a neurological condition. Papers containing clinimetric evidence of these tests were then identified. The methodological quality of each paper was critically appraised using standardised tools and clinimetric evidence synthesised for each test.

Results

Thirteen papers were identified, which provided clinimetric evidence on six neurological tests. Muscle strength tests had the greatest volume of clinimetric evidence, however this evidence focused on reliability. Studies were variable in quality with inconsistent results. Clinimetric evidence for tactile sensitivity impairment tests was conflicting and difficult to extrapolate. No clinimetric evidence was found for impairment tests of deep tendon reflexes.

Conclusions

Limited high-quality clinimetric evidence exists for lower limb neurological impairment tests in children and young people with a neurological condition. Results of currently used neurological tests, therefore, should be interpreted with caution. Robust clinimetric evidence on these tests is required for clinicians and researchers to effectively select and evaluate rehabilitation interventions.

Citation: Clark R, Locke M, Hill B, Wells C, Bialocerkowski A (2017) Clinimetric properties of lower limb neurological impairment tests for children and young people with a neurological condition: A systematic review. PLoS ONE 12(7): e0180031. https://doi.org/10.1371/journal.pone.0180031

Editor: Christos Papadelis, Boston Children's Hospital / Harvard Medical School, UNITED STATES

Received: October 11, 2016; Accepted: June 8, 2017; Published: July 3, 2017

Copyright: © 2017 Clark et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Paediatric neurological examinations are a fundamental component for planning and adjusting rehabilitation interventions, monitoring the course of a neurological condition, and evaluating the effectiveness of an intervention, [1–3] in both clinical and research settings. Neurological examinations consist of a battery of neurological tests spanning multiple constructs of the International Classification of Function, Disability and Health: Children and Youth version (ICF-CY) framework. [4] Neurological impairment tests include those that evaluate muscle strength, tactile sensitivity, and deep tendon reflexes. These tests are frequently used to evaluate a child’s neural integrity [3,5,6] at the body functions and structures level of the ICF-CY [4] and may be used to aid in the selection of other tests including those in activity and participation domains. [3,5]

Clinicians may structure their physical assessment with an initial screen of neurological integrity in conjunction with the history, or subjective examination, providing information on activity limitations or participation restrictions from the child, young person or parent. Due to the increasing numbers of neurological impairment tests available, [3,6–11] selection of best available tests becomes difficult. There is no known “gold standard” for a neurological examination to aid in selecting tests [11–13] and/or “gold standards” for individual neurological impairment tests require expensive equipment that lack the clinical utility for daily practice, [14] such as the use of the isokinetic dynamometer for measuring muscle strength. Clinimetrics is a term that describes the psychometric properties of a test (reliability, validity, and responsiveness to change over time) and the test’s clinical utility (the clinical usefulness of the test) (Table 1). [7,10,14,15] Few paediatric tests have undergone comprehensive clinimetric evaluation. [5,12–15] Without specific clinimetric evidence, recommendations and clinical guidelines for using existing tests cannot be developed for use in children with a neurological condition.

Download:

Table 1. Clinimetric definitions for a lower limb neurological impairment test.

https://doi.org/10.1371/journal.pone.0180031.t001

Although adult neurological tests have frequently been modified for use in paediatric populations, the clinimetric properties of adult tests are not inherently transferrable to children and young people. [13,17] Adult tests tend to be modified for use in paediatric populations without a standardised protocol, [3,18] making it difficult to interpret the findings of these modified tests. Standardised protocols that increase a child’s comprehension and confidence to complete a task in a distraction-free environment are essential in reducing random errors, [16] particularly as a child grows and develops.

Clinimetric properties of tests for typically developing children are also not necessarily transferable to children with a lower limb neurological condition. [3,13,17–19] For example, children with neurological conditions may have intellectual disabilities that influence the child’s comprehension of the test requirements, and therefore their performance. Physical disabilities that also may influence a neurological test protocol and results include, but are not limited to, the presence of muscle contractures, spasticity or variations in tone, and previous orthopaedic surgery.

There is little evidence-based guidance on how to assist clinicians and researchers select and interpret an appropriate, paediatric-specific lower limb neurological test for children and young people with a neurological disorder. [12,20,21] While clinimetric evidence of activity and participation measures in children and young people with neurological diagnoses have been identified, [22] evidence of impairment measures remains limited. A recent systematic review found no conclusive clinimetric evidence to support the use of handheld dynamometry to measure muscle strength in children and young people with cerebral palsy, due to the poor methodological quality of primary papers. [23] Other systematic reviews have identified the lack of high quality clinimetric evidence for upper limb tests in children and young people with a neurological condition. [1,9] The clinimetric evidence for other lower limb neurological impairment tests for children and young people with cerebral palsy and other neurological conditions remains unknown. Therefore, the aims of this study were to:

Identify neurological impairment tests currently used to evaluate the lower limb neural integrity of muscle strength, tactile sensitivity, and deep tendon reflexes in children and young people with a neurological condition
Identify clinimetric evidence for neurological impairment tests used in children and young people with a wide range of neurological conditions
Critically appraise and synthesise the clinimetric evidence underpinning the lower limb neurological tests
Make recommendations regarding their use in clinical practice and research settings.

Method

This study was undertaken in two phases based on the works by Bialocerkowski and colleagues. [21,24] The first phase systematically identified lower limb neurological tests measuring muscle strength, tactile sensitivity or deep tendon reflexes, in children and young people. [25] The second phase systematically identified studies evaluating the clinimetric properties of these neurological tests specific to children and young people with a neurological condition.

Phase 1: Identification of neurological tests

Search terms, identifying lower limb neurological impairment tests for children (aged 2–18 years) with a neurological condition, were generated from previous search strategies. [26,27] Medical subject headings (MeSH) for ‘Lower Extremity’ AND (‘Neurological Examination’ OR ‘Physical Examination’) AND (‘Sensation’ OR ‘Reflex’ OR ‘Muscle Strength’) AND (‘Child’ OR ‘Adolescence’ OR ‘Child, Preschool’) were expanded to select relevant subcategories where possible. The search was simplified to ‘Sensation’, as results for ‘Touch Sense’ (the MeSH term for tactile sensitivity) were included within the broader search filter of ‘Sensation’. Neurological diagnoses were not individually searched in Phase 1 as not to limit neurological impairment tests to the number or type of diagnoses. Phase 1 therefore developed an extensive list of paediatric neurological impairment tests that could be used in Phase 2 of this study. A neurological condition included conditions classified under the International Statistical Classification of Diseases and Related Health Problems (ICD-10) codes. S1 Table displays the search strategy used for CINAHL. Thirteen health-related databases were systematically searched from January 1985 to 16 February 2017: CINAHL, Cochrane Library, EMBASE, Health Reference Center, Joanna Briggs Institute, Medline, PEDro, ProQuest Central, ProQuest Dissertations and Theses, ScienceDirect, Scopus, TRIP Database, Web of Science. Grey literature, including conference proceedings, theses and dissertations were included within database searches with no language limitations.

Study selection

Duplicates were removed from identified papers, before two researchers (RC and BH) independently evaluated them for the following inclusion criteria:

Paediatric participants had an average age greater than two years and less than 18 years, as the focus of the paper was on children and young people less than 18 years. [25,28–30]
Participants with a neurological condition affecting the lower limb. These conditions included diseases of the nervous system, musculoskeletal system and connective tissue, injuries to the head or unspecified part of trunk and certain other consequences of external causes, certain conditions originating in the perinatal period, congenital malformations, deformations and chromosomal abnormalities that effect the central or peripheral nervous system including the spinal cord, peripheral nerves, nerve roots, autonomic nervous system and muscles. [2]
Papers reported using a neurological impairment test that measured or evaluated muscle strength (b730), and/or tactile sensitivity (b270), and/or deep tendon reflexes (b750) at the “body functions and structures” level of the ICF-CY. [4]
Neurological impairment tests were suitable for use within the clinical setting, using equipment that was typically available, inexpensive and portable. [15,31]
Quantitative studies with a level of evidence rated I-IV [32] (including systematic reviews (I), randomised controlled studies (RCTs)(II) and, pseudo-RCTs (III), comparative studies (III2,3), and case series with pre/post studies (IV))
Full text or abstract papers published in a peer-reviewed journal, as listed in Ulrichsweb. [32]
Published in the English language between 1985 to February 2017, as papers published after the mid-1980s were considered to coincide with a period for the use of evidence-based practice (EBP) to optimise clinical care. [33]

Papers were excluded if:

The average age for participants could not be determined or the average age of participants was younger than 2 years of age or older than 18 years of age.
Participants were diagnosed with conditions limited to metabolic, orthopaedic or cardiovascular conditions (including, but not limited to systemic connective tissue disorders and other osteopathies, episodic and paroxysmal disorders and inflammatory diseases of the central nervous system).
Neurological tests were classified as activity or participation measures, as these measures represented a different ICF-CY construct. [4]
Papers reported only spasticity or primitive reflexes, as these were not the focus of this study. [28–30]
Neurological impairment tests with a low level of clinical utility due to expense or limited transportability of equipment (e.g. isokinetic dynamometer) or the specialised diagnostic nature of testing (e.g. electromyography or nerve conduction studies). [14]
Papers were editorials or opinion pieces, as they are not quantitative studies. [34]

If eligibility was unclear, the two researchers (RC and BH) undertook a review of the full text article. A third reviewer (AB) was consulted to reach consensus in cases of continued disagreement. Included papers were reviewed in full text and the names of all relevant neurological tests were extracted by the same two researchers (RC and BH) and compared for agreement. If required, the third reviewer (AB) determined consensus.

Phase 2: Identification of clinimetric properties of neurological tests

Neurological impairment tests identified in Phase 1 were systematically searched for their clinimetric properties from their date of inception to 16 February 2017 using four health databases, CINAHL, EMBASE, Medline, Scopus. [24] By translating the validated Terwee, Jansma, Riphagen, et al. [35] protocol for each specific database (S2 Table), the search strategy involved combining:

a neurological test search, to identify measures of muscle strength, or tactile sensitivity, or deep tendon reflexes limited to the lower limb;
a population search, including paediatric participants aged less than 18 years;
a neurological test search, derived from the neurological impairment test names identified in Phase 1 and;
filtering for measurement properties, as outlined by Terwee, et al. [35]

Papers were included if:

all paediatric participants were aged less than 18 years, as clinimetric properties are population specific. [17]
participants had a neurological condition affecting the lower limb. Neurological conditions were defined using the International Classification of Diseases (ICD-10) as per Phase 1.
papers contained clinimetric evidence on a lower limb neurological impairment test that evaluated muscle strength, tactile sensitivity and/or deep tendon reflexes in the lower limb as per the ICF-CY framework outlined in Phase 1.
quantitative studies with a level of evidence rated II-IV [34] (including randomised controlled studies (RCTs)(II) and, pseudo-RCTs (III), comparative studies (III2,3), and case series with pre/post studies (IV))
papers were published in full text in the English language and peer reviewed.

Consensus between two individual reviewers (RC and BH) was reached using the same method as Phase 1. Papers that contained additional evidence outside the scope of this paper were included only if data could be extrapolated that met the inclusion criteria. Systematic reviews (level I evidence) identified in this process were searched for primary papers that met the inclusion criteria through secondary searching. Additional primary papers that met the inclusion criteria were identified through secondary searching by hand through the reference lists of included papers and identified systematic reviews.

Quality assessment

The methodological quality of the included clinimetric papers was evaluated independently by two reviewers (RC and BH) using two critical appraisal tools: Brink and Louw critical appraisal tool [6] and the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). [8] These critical appraisal tools [6,8] have previously been used in a number of published systematic reviews on health-related outcome measures [21,36–39] to evaluate the aspects of the quality of psychometric evidence. Brink and Louw’s [6] tool assessed the impact of 13 items on the overall quality of the primary paper’s method, without calculating a composite score [6,21]. For each included primary paper, the percentages of “yes” responses for applicable items [6] was calculated by dividing the number of “yes” responses by the number of applicable items and converted into a percentage. [36,40] This provided an arbitrary evaluation of the overall methodological quality of each paper. Due to its wide use in health-related research the COSMIN was used to grade the methodological quality of included papers. [1,20,22,31,41] The COSMIN uses weighted items based on overall importance and a ‘worst score counts’ method. [42] Consensus for each item was gained through discussion and a third researcher (AB) was consulted if required. Kappa coefficients and 95% confidence intervals (CI) were calculated to assess the inter-reviewer reliability of the item response.

Data extraction

Additional data were extracted from each study, including the name of the authors, date of publication, name of the neurological test, type of clinimetric property evaluated, participant characteristics, rater characteristics, measurement characteristics, results of the clinimetric evaluation and information on the clinical utility of the test. Clinical utility was described based on information contained within the included papers on the portability, cost, and feasibility of using the equipment on children and young people with a neurological condition in a clinical setting. [14]

Best evidence synthesis

Evidence on each clinimetric property for each neurological test within primary papers was narratively synthesised and interpreted in combination with the methodological quality of the primary paper. Reliability correlation coefficients from the primary papers were interpreted using guidelines from Katz et al., [43] low = <0.40, moderate = 0.40–0.59, moderately high = 0.60–0.79 and very high = >0.80. The level of evidence for each neurological test was determined using guidelines from Terwee et al. [7] and Dobson et al., [31] which combined the quality of the paper for each neurological test with the consistency of the clinimetric evidence for that test (Table 2). [20,31,44]

Download:

Table 2. Levels of evidence synthesis for methodological quality of paper and consistency of clinimetric evidence of measurement property.^{^a}.

https://doi.org/10.1371/journal.pone.0180031.t002

Results

Search output

The Phase 1 search strategy identified 77 papers that met the inclusion criteria. Thirteen papers [45–57] met the Phase 2 selection criteria with clinimetric evidence of a neurological test (Fig 1). Twenty-one lower limb neurological tests were identified in total: ten evaluated muscle strength, six tactile sensitivity, one deep tendon reflexes, and four evaluated a combination of these constructs (S3 Table).

Download:

Fig 1. PRISMA flow diagram of systematic search strategy used to identify clinimetric papers.

https://doi.org/10.1371/journal.pone.0180031.g001

Methodological quality

There was high agreement (kappa = .98, 95% CI 0.96–1.01) between reviewers when scoring the methodological quality of included papers. The most prevalent quality limitations identified using the Brink and Louw critical appraisal tool [6] and COSMIN [8] were a lack of rater blinding, a lack in variation of examination order, not reporting the stability of the child’s condition and small samples of less than 30, with the exception of Florence et al. [56] (Table 3). Most primary papers rated “yes” for greater than 60% of Brink and Louw’s criteria (n = 11/13), [45–47,49–53,56] with a range from 38% “yes” statements [55] to 88% “yes” statements. [54] Thirteen [45–56] primary papers were rated as poor quality using the COSMIN criteria [8] (Table 4). This was mainly because primary papers had a sample size of less than 30 participants.

Download:

Table 3. Brink and Louw^{^a} critical appraisal summary of the methodological quality of the clinimetric papers.

(n = 15).

https://doi.org/10.1371/journal.pone.0180031.t003

Download:

Table 4. COSMIN^{^a} reliability critical appraisal summary of the methodological quality of the clinimetric papers.

(n = 15).

https://doi.org/10.1371/journal.pone.0180031.t004

Neurological tests and their clinimetric properties

The 13 primary papers provided clinimetric evidence for six neurological tests: American Spinal Impairment Association) ASIA impairment scale, [57] Charcot-Marie-Tooth Pediatric Scale, [45] Handheld Dynamometry (HHD), [46–54] Manual Muscle Test (MMT), [49,55,56] Richmond Quantitative Measurement System, [55] and Standing Heel Rise. [52] All tests evaluated lower limb muscle strength. The ASIA impairment scale and Charcot-Marie-Tooth Pediatric Scale evaluated tactile sensitivity and muscle strength in combination with other upper and lower limb tests to form a composite score. [45,57] No studies evaluated the clinimetric properties of lower limb deep tendon reflexes. All identified clinimetric evidence focused on the reliability of the test. No primary papers evaluated validity, responsiveness or clinical utility of the test. Reliability evidence was generated from participants with a range of neurological conditions, including six papers examining neurological tests in children and young people less than 18 years of age with cerebral palsy, [46,47,51–54] one with Charcot-Marie-Tooth, [45] one with spinal cord injury, [57] three with Duchenne’s muscular dystrophy [50,55,56] and two papers with children with spina bifida. [48,49] Children varied in age from 3 years 8 months [52] to 18 years. [51] Physiotherapists with over six years of experience performed neurological tests in all primary papers (S4 Table).

Clinimetric evidence

Hand held dynamometry.

Hand held dynamometry had the largest body of evidence, with nine papers [46–54] reporting evidence of reliability. (Table 5) The majority of clinimetric evidence was identified in six papers [46,47,51–54] for children with cerebral palsy. The remaining papers had evidence for children with spina bifida [48,49] and Duchenne’s muscular dystrophy. [50] Eight of the primary papers [46,47,49–54] evaluating hand held dynamometry had greater than 60% of “yes” items on methodological quality with a range of 56%-88% using the Brink and Louw [6] criteria (Table 3). Yet, all papers [46,47,49–54] had poor methodological quality according to the COSMIN checklist [8] due to the sample sizes being considered small (Table 4). Most papers reported moderately high to very high intra-rater reliability with ICCs ranging from 0.70 to 0.99. [46–48,51,52,54] Conversely, Crompton et al. [47] reported low reliability with ICCs as low as 0.26. Inter-rater reliability was more variable than intra-rater reliability across all papers with ICCs ranging from -0.04 to 0.97 [53,55] (Table 5). The “make” measurement method (Table 6) to evaluate strength had the largest body of evidence [45–54] (Table 5) with higher ICC values compared to the “break” method [53] (Fig 2). Manual or belt stabilisation of the proximal limb consistently had slightly higher intrarater reliability (Fig 2) compared with no stabilisation, particularly for the hip and knee extensors. [47] Variable confidence intervals were reported in the four papers [47,49,52,54] that calculated 95% CI (Fig 2). Protocols were not standardised across studies with different muscle groups tested, multiple body positions adopted (e.g. supine or sitting), variable placement of the dynamometer, different equipment used with numerous units of measurement, and disparate lengths of time between repeated tests (S4 Table). HHD had high portability, yet requires specialised equipment, reducing its clinical utility. [14] The cost of equipment was not reported and a requirement for additional training was inconsistently described. [46–54]

Download:

Fig 2. Forest plot of intra-rater and inter-rater reliability ICC with 95% CI and systematic error of measurement (SEM), where available, for muscle strength tests using different protocols.

https://doi.org/10.1371/journal.pone.0180031.g002

Download:

Table 5. The clinimetric properties of neurological tests for children and young people with a neurological condition.

https://doi.org/10.1371/journal.pone.0180031.t005

Download:

Table 6. Muscle groups with protocols for testing lower limb strength in children and young people with a neurological condition.

https://doi.org/10.1371/journal.pone.0180031.t006

Manual muscle testing.

There was a small body of evidence for assessing muscle strength with MMT (n = 3 papers) [49,55,56] for children and young people with Duchenne’s muscular dystrophy [55,56] and spina bifida. [49] The methodological quality of primary papers ranged from 38% [55] to 63% [55,56] of “yes” items using the Brink and Louw method (Table 3). [6] All papers using MMT [49,55,56] had a poor methodological quality according to the COSMIN checklist, [8] due to sample sizes being considered small ^[⁴⁹^,⁵⁵^] and a lack of reported patient stability between testing sessions (Table 4). [56] MMT intra-rater reliability (κ = 0.79–0.93) [56] was more consistent than inter-rater reliability (ICC = 0.37 to 0.75) [49] (Table 5). Escolar et al. [55] evaluated both MMT and RQMS neurological impairment tests. Inter-rater reliability for MMT (ICC = 0.87) was reported for Escolar et al., [55] however consisted of a composite score of the strength of upper and lower limb muscle groups. Muscle strength scale definitions varied between studies (Table 6). Body positions and measurement methods were comparable to those used with HHD with the addition of smaller muscle groups, such as the ankle invertors and evertors (Table 6). Body positions and measurement methods were comparable to those used with HHD with the addition of smaller muscle groups, such as the ankle invertors and evertors (Table 6). The MMT in primary papers [49,55,56] did not require any equipment; therefore it is also a portable test. [14]

Charcot marie-tooth paediatric scale.

The Charcot-Marie-Tooth Pediatric Scale (CMTPedS) was evaluated in one paper with children and young people with Charcot-Marie-Tooth (Table 3, Table 4). [45] The methodological quality of the reliability component of the paper on CMTPedS identified 75% of quality items using the Brink and Louw [6] criteria, (Table 3) yet was rated as poor using the COSMIN checklist [8] due to a sample size considered small (Table 4). The CMTPedS had very high reported inter-rater reliability (ICC = 0.95). [45] The CMTPedS score, however, was a composite score, including upper and lower limb test components with subsets of muscle strength and tactile sensitivity tests comprising 36% of items within the test. While this test has high portability, the need for other equipment, including HHD, [45] at an approximate cost of USD$2657 [45] in conjunction with the need for additional training reduces its overall clinical utility. [14]

ASIA impairment scale.

The International Standards for Neurological Classification of Spinal Cord Injury American Spinal Injury Association (ASIA) scale was evaluated in one paper with children and young people with spinal cord injury (Table 3, Table 4). [57] The methodological quality of the of the paper on the ASIA scale identified 50% of quality items using the Brink and Louw [6] criteria, (Table 3) and was rated as poor using the COSMIN checklist [8] due to methodological flaws considered major (Table 4). The ASIA scale reported high intra-rater reliability (ICC = 0.71 to 0.98), with wide variation in 95% CI (0.23 to 0.99). [57] The ASIA impairment scale, is a composite score, including upper and lower limb test components with subsets of motor scores and tactile sensitivity tests (including pinprick and light touch). This test has high portability, without the need for other equipment, although requires some training. [57]

Richmond quantitative measurement system.

Clinimetric evidence for the Richmond Quantitative Measurement System was identified in one paper in children and young people with cerebral palsy (Table 3, Table 4). [55] The methodological quality of the paper [55] identified 63% of items scored “yes” with the Brink and Louw critical appraisal tool, [6] but was rated as poor using the COSMIN checklist [8] (Table 3, Table 4). The Richmond Quantitative Measurement System had moderate to very high inter-rater reliability (ICC = 0.56 to 0.97) (Table 5). [55] This was determined in one study with poor methodological quality (Table 4). The Richmond quantitative measurement system requires equipment with specialised software and training requirements reducing its portability and clinical utility.

Standing heel rise.

One study provided evidence on the reliability of the Standing Heel Rise [52] in children and young people with cerebral palsy (Table 3, Table 4). The methodological quality of this paper [52] showed 75% of the Brink and Louw [6] items were rated as “yes”, however the overall paper [52] was rated poor using the COSMIN checklist, [8] due to a sample size considered small (Table 4). Intra-rater reliability was very high (ICC = 0.84–0.99), [52] using the protocol by Van Vulpen et al. [52] This protocol was portable, however it involved the additional use of infra-red beams connected to a receiver which detected the heels lifting 1.7cm off the ground. There was no detail regarding training requirements or equipment costs for the SHR.

Synthesis of evidence

A best evidence synthesis for each of the six neurological tests showed HHD had conflicting evidence on reliability for children with cerebral palsy, moderate inter-rater reliability for children with spina bifida and moderate intra-rater reliability for children with Duchenne’s muscular dystrophy (Table 7). MMT had conflicting evidence regarding intra-rater and inter-rater reliability in children with Duchenne’s muscular dystrophy and spina bifida respectively. Moderate evidence was found for the Charcot-Marie-Tooth Pediatric Scale [45] and the Standing Heel Rise. [52] These tests had consistent evidence across multiple studies and were published in papers higher in methodological quality, which resulted in greater evidence ratings despite small bodies of evidence (Table 7). Conflicting evidence on intra-rater reliability was found for both the motor and sensory constructs of the ASIA Impairment scale when used on children and young people with a SCI. The Richmond Quantitative Measurement Scale [55] had unknown evidence of inter-rater reliability due to the poor methodological quality of the published papers.

Download:

Table 7. Levels of evidence^{^a} of lower limb strength measurements based on Brink and Louw^{^b} methodological quality.

https://doi.org/10.1371/journal.pone.0180031.t007

Discussion

This is the first study to systematically identify clinimetric evidence on lower limb neurological impairment tests used on children and young people across a range of neurological disorders. Evidence of reliability was the only identified clinimetric property for six of the identified 21 neurological tests, demonstrating the paucity of evidence for neurological impairment testing. Clinimetric evidence for tactile sensitivity was identified in two primary papers [45,57] containing composite measures. However, tactile sensitivity evidence could only be extrapolated from one primary paper. [57] The limited to moderate body of evidence on reliability of lower limb muscle strength tests and composite tests including subsets of tactile sensitivity and muscle strength, highlights the lack of robust clinimetric evidence for neurological tests in a paediatric population with a lower limb neurological condition. This is further illustrated by no available clinimetric evidence for deep tendon reflex tests despite tests existing to evaluate this construct. Despite the limited and conflicting evidence, hand held dynamometry, manual muscle testing and the standing heel rise, may provide a starting point from which to develop high quality clinimetric studies that evaluate specific testing protocols for children and young people with a neurological condition.

Existing clinimetric evidence must be interpreted in conjunction with the methodological quality of the paper. [6,44] Ten of the 13 included papers in this study had greater than 60% of “yes” items for methodological quality using the Brink and Louw method, [6] compared with the COSMIN checklist grading 12 of 13 papers in this study with a ‘poor quality’ due to small sample sizes (less than 30). [8,44] The small sample size of children within primary papers has previously been highlighted as a potential limitation. [1,20] Benfer et al. [41] argued that smaller sample sizes are common in paediatrics, yet these studies may have adequate power to support their small sample. [49] Similar systematic reviews have used a ‘second-worst’ method with a modified COSMIN to combat this issue, however this technique has not been validated. [20,22,23,41,58]

The Brink and Louw [6] critical appraisal tool highlighted specific methodological flaws of included papers, the most prevalent being the lack of reported stability for a child’s condition across testing sessions. Ensuring the stability of a child’s condition means any identified differences are due to measurement error [16] and not changes in their condition. [59–62] The time between testing sessions should be considered relative to the underlying diagnosis to ensure there is no expected change or fatigue. The stability results for a participants neurological condition reported in five [45,49,50,52,54] of the six primary papers, [45,49,50,52,54,57] (Item 8, Table 3) should be interpreted with caution, as these papers did not state whether the time frame between sessions was appropriate for their population-group or if the child or carer believed there to be no change in the child’s status between testing sessions. Reliability cannot be inferred without measuring whether a child’s condition is stable across testing sessions. [16] Reliability coefficients in primary papers could therefore be lower than reported due to the absence of stability measures.

Clinimetric evidence was only identified for muscle strength tests, and was limited to evidence on reliability. Reliability has also been the primary identified clinimetric property in a similar review of upper limb tests of muscle strength in children with cerebral palsy. [20] The paucity of additional primary papers since Mulder-Brouwer et al’s [23] study also highlights the lack of an increase in the body of literature since 2013. The inconsistent reporting of evidence on reliability in the identified neurological tests makes interpretation and research translation difficult. Reliability was quantified using ICC or weighted kappa for 14 of the 15 primary papers, however the use of different measurement protocols made it difficult to draw conclusions and prevented a meta-analysis. Mahony et al. [49] calculated an ICC from ordinal data instead of the appropriate weighted kappa confounding the interpretation of their reliability values.

Reliability is defined as a measure that is consistent and free from random or systematic error (Table 1). [16,63] Additional statistics, such as the 95% CI and systematic error of measurement (SEM), aid in the interpretation of the test’s reliability. [59,63] Wide CIs in the few primary papers reporting 95% CI, indicated variation in this measurement property in children. [47,57] The SEM provides clinicians and researchers with information on the systematic and random error of a patient’s score that is not attributed to true change. [54,63] Reliability for neurological tests reported in the seven papers [45,48,50,51,55–57] that did not report SEM should therefore be interpreted with caution. Comparisons of SEM, where reported, could not be made between primary papers in this study due to different units of measurement, muscle groups tested and protocols used. A standardised measurement protocol would therefore provide the same units for SEM to aid in reporting random error [16] and assist in synthesising results from multiple primary studies.

Results of this study indicate that the same clinician should perform each neurological test due to consistently higher intra-rater reliability coefficients compared to inter-rater reliability coefficients (Fig 2). All clinicians who used the neurological tests in the included papers were reported to have six or more years of clinical experience. Without reporting the clinician’s experience in using the neurological test, or comparing to clinicians with less than six years of clinical experience, the effect clinician experience has on the outcome of neurological testing on children and young people with a neurological condition is unknown. [16] A recent reliability study of manual muscle testing in children and young people with spina bifida suggested experienced clinicians should assist in training novice clinicians to improve measurement reliability. Tan et al.’s 2016 (in press) [64] study reported an overall weighted kappa of 0.95 (CI 0.94–0.96) for MMT using the Daniel’s and Worthingham’s protocol, yet the methodological quality would have been graded as poor using the COSMIN checklist due to a small sample size. [8,64]

Manual muscle testing is typically recommended in weaker muscles, with equal or less than gravity strength, [54,64] yet this test becomes more variable when the clinician needs to apply increasing amounts of resistance. (i.e. grade IV to V) [65] Clinicians should use the make method when performing hand held dynamometry and manual muscle testing as the larger body of evidence and increased reliability (Fig 2) supports this method compared to the break test. Evaluation of the ankle plantarflexors was an exception to this finding. [53] The ankle plantarflexors are known to be a strong muscle group that acts upon a short lever arm, making it challenging for clinicians to apply sufficient manual resistance for muscle testing. [66–69] This often limits muscle testing of ankle plantarflexors group to the relative strength of the clinician performing the test. [70] However, clinician strength was not a reported variable in the primary papers. The moderate evidence for standing heel rise test may suggest using this as an alternative test for measuring plantarflexion muscle strength in ambulatory children.

Inconsistent muscle strength testing methods between the primary papers confirms that a standardised test protocol for muscle strength testing does not exist. There is also wide variability in grading scales when using MMT, with four different scales reported in the three MMT papers [49,55,56] with clinimetric evidence and the motor subscale of the ASIA scale [57]. The conflicting evidence on reliability for hand held dynamometry found in papers of fair quality means additional high quality research, using a standardised measurement protocol, is required to make recommendations. Consensus between clinicians on a standard protocol is recommended prior to further clinimetric testing. Without clinimetric evidence, lower limb rehabilitation trials for children and young people are at risk of bias due to the use of neurological tests with unknown clinimetric properties. [71]

Reliability is only one of many clinimetric properties, which include validity, responsiveness and clinical utility, [7,14] The Charcot-Marie-Tooth Pediatric Scale (CMTPedS) [45] has clinimetric evidence of both reliability and validity, however the age range of participants differed between those who participated in the reliability and validity studies. The evidence on reliability, which was included in this study, was for children and young people aged 5–15 years. However, evidence on the validity of the CMTPedS was for children and young people aged 3–20 years. [45] Evidence of validity for the CMTPedS could not be included in this study due to the age ranges of participants exceeding 18 years of age, as per the exclusion criteria. Without clinimetric evidence presented for different age groups, it is unclear whether the validity evidence for the CMTPedS [45] is specific to the paediatric population. Clinimetric evidence for the ASIA scale [57] was included in this study by extrapolating data for children and young people aged 4–15, while the 16–21 year old age group data were not included in this study.

Currently there is no universally accepted definition of the upper age limits [25] for a paediatric population from other paediatric systematic reviews. [20,22,30,39,58] A definition of paediatrics as children less than 18 years was used in this study to align with previous systematic reviews with a paediatric population [1,20–22,39] and Medical Subject Headings definitions for a targeted search strategy. [27] The comprehensive search strategy used in this study [24,26,27] ensured the identification of lower limb impairment neurological tests that were specific to children and young people with a neurological condition. [42] Future studies may broaden the paediatric age range up to 22 years of age as suggested by Clark et al. [25] Until future research supports this upper age limit, papers should report evidence for different paediatric age ranges to allow for greater research translation. [25,72]

In contrast to previous reviews [9,20,23,30,31,41], this study covers a broad paediatric age range and multiple neurological conditions. Recommendations for a clinimetrically-sound neurological test require a standardised test protocol with population-specific evidence, as clinimetric properties from other populations are not inherently transferable. [13,14,42] The majority of papers identified in this review had clinimetric evidence of neurological impairment tests used on children with cerebral palsy, which likely reflects cerebral palsy as the most prevalent paediatric neurological condition with motor and sensory impairment. [73]

This study was limited to three components of a neurological examination at the ‘body function and structures’ level of the ICF-CY as other neurological impairment tests such as spasticity are dependent on the diagnosis of the child. [4] For a comprehensive neurological examination other components of a neurological examination should be included, such as measures from the ‘activity’ and ‘participation’ levels of the ICF-CY. [4,74] Selection of these neurological tests will be dependent on the diagnosis of the child. Limited evidence for clinimetrically-sound measures of ‘activity’ for children and young people with a neurological condition have been found, [22,58] demonstrating a similar shortage of high-quality studies in these constructs.

Synthesising best evidence, through combining a consistent body of clinimetric evidence with robust methodological qualities, can guide clinicians and researchers to select appropriate paediatric-specific lower limb neurological tests. [7,31] Guidance on best evidence of clinimetrically-sound measures cannot be made with reliability evidence alone. Without evidence of reliability, validity, responsiveness and clinical utility, recommendations to clinicians for neurological tests can only be made with caution until further clinimetric evaluation can be used to support best practice. [7,75]

Conclusion

There is a lack of robust clinimetric evidence on neurological impairment tests to use on children and young people with a lower limb neurological condition. Clinimetric evidence was only found on the reliability of neurological impairment tests evaluating muscle strength. Performing standardised testing protocols, such as the make method, with manual or belt stabilisation in a stable population-specific group, are recommended as a starting point for further clinimetric studies. In the absence of clinimetrically-sound neurological tests, clinicians should use the best available evidence. Without clinimetrically-sound neurological tests it is difficult for clinicians and researchers to select and perform a test in clinical practice, which becomes increasingly complex when requiring a combination of these tests for a thorough neurological examination. High quality, population-specific studies are required to provide a strong body of clinimetric evidence for clinicians and researchers to make future recommendations for use of a neurological examination in clinical practice and research.

Supporting information

S1 Table. CINAHL search terms used to identify lower limb neurological tests in children.

https://doi.org/10.1371/journal.pone.0180031.s001

(DOCX)

S2 Table. CINAHL search terms used to identify clinimetric properties for Achilles reflex in children.

https://doi.org/10.1371/journal.pone.0180031.s002

(DOCX)

S3 Table. Neurological test names for children and adolescents identified by the search strategies, and papers on their clinimetric properties.

https://doi.org/10.1371/journal.pone.0180031.s003

(DOCX)

S4 Table. Characteristics of included clinimetric papers for neurological tests used on children and young people with a neurological condition.

https://doi.org/10.1371/journal.pone.0180031.s004

(DOCX)

S5 Table. PRISMA checklist.

https://doi.org/10.1371/journal.pone.0180031.s005

(DOC)

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author Contributions

Conceptualization: RC ML AB.
Data curation: RC.
Formal analysis: RC BH.
Investigation: RC.
Methodology: RC ML AB CW.
Project administration: RC AB ML CW.
Software: RC.
Supervision: CW ML AB.
Validation: BH.
Visualization: RC.
Writing – original draft: RC.
Writing – review & editing: RC ML AB CW BH.

References

1. Gerber CN, Labruyère R, van Hedel HJA. Reliability and Responsiveness of Upper Limb Motor Assessments for Children With Central Neuromotor Disorders: A Systematic Review. Neurorehabil Neural Repair. 2016;30(1):19–39. pmid:25921350
- View Article
- PubMed/NCBI
- Google Scholar
2. Who, ebrary I, World Health O. Neurological disorders: public health challenges. Geneva: World Health Organization; 2006.
3. Wright V, Majnemer A, Maltais DB, Burtner PA, Sanders H. Motor measures: A moving target? Semin Pediatr Neurol. 2013;20:84–99. pmid:23948683
- View Article
- PubMed/NCBI
- Google Scholar
4. WHO. International classification of functioning, disability, and health: children & youth version: ICF-CY. Geneva: World Health Organization; 2007.
5. Petty NJ. Neuromusculoskeletal Examination and Assessment: A Handbook for Therapists. Elsevier Health Sciences UK; 2011.
6. Brink Y, Louw QA. Clinical instruments: reliability and validity critical appraisal. J Eval Clin Pract. 2012;18(6):1126–1132. pmid:21689217
- View Article
- PubMed/NCBI
- Google Scholar
7. Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42. pmid:17161752
- View Article
- PubMed/NCBI
- Google Scholar
8. Mokkink L, Terwee C, Knol D, Stratford P, Alonso J, Patrick D, et al. Protocol of the COSMIN study: COnsensus-based Standards for the selection of health Measurement INstruments. BMC Med Res Methodol. 2006;6(1):2. pmid:16433905
- View Article
- PubMed/NCBI
- Google Scholar
9. Auld ML, Boyd RN, Moseley GL, Johnston LM. Tactile assessment in children with Cerebral Palsy: A Clinimetric Review. Phys Occup Ther Pediatr. 2011;31(4):413–439. pmid:21599569
- View Article
- PubMed/NCBI
- Google Scholar
10. Hobart JC, Cano SJ, Zajicek JP, Thompson AJ. Rating scales as outcome measures for clinical trials in neurology: problems, solutions, and recommendations. Lancet Neurol. 2007;6(12):1094–1105. pmid:18031706
- View Article
- PubMed/NCBI
- Google Scholar
11. Tyson S, Watson A, Moss S, Troop H, Dean-Lofthouse G, Jorritsma S, et al. Development of a framework for the evidence-based choice of outcome measures in neurological physiotherapy. Disabil Rehabil. 2008;30(2):142–149. pmid:17852285
- View Article
- PubMed/NCBI
- Google Scholar
12. Majnemer A, Limperopoulos C. Importance of outcome determination in paediatric rehabilitation. Dev Med Child Neurol. 2002;44(11):773–777. pmid:12418619
- View Article
- PubMed/NCBI
- Google Scholar
13. Jerosch-Herold C. An evidence-based approach to choosing outcome measures: a checklist for the critical appraisal of validity, reliability and responsiveness studies. Br J Occup Ther. 2005;68(8):347–353.
- View Article
- Google Scholar
14. Smart A. A multi-dimensional model of clinical utility. Int J Qual Health Care. 2006;18(5):377–382. pmid:16951425
- View Article
- PubMed/NCBI
- Google Scholar
15. de Vet HC, Terwee CB, Bouter LM. Current challenges in clinimetrics. J Clin Epidemiol. 2003;56:1137–1141. pmid:14680660
- View Article
- PubMed/NCBI
- Google Scholar
16. Bialocerkowski AE, Bragge P. Measurement error and reliability testing: Application to rehabilitation. Int J Ther Rehabil. 2008;15(10):422–427.
- View Article
- Google Scholar
17. Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. Pearson/Prentice Hall; 2009.
18. Van den Beld W, Van der Sanden G, Sengers R, Verbeek A, Gabreels F. Validity and reproducibility of hand-held dynamometry in children aged 4–11 years. J Rehabil Med. 2006.38:57–64. pmid:16548089
- View Article
- PubMed/NCBI
- Google Scholar
19. Damiano DL, Abel MF. Functional outcomes of strength training in spastic cerebral palsy. Arch Phys Med Rehabil. 1998;79(2):119–125. pmid:9473991
- View Article
- PubMed/NCBI
- Google Scholar
20. Dekkers KJFM, Rameckers EAA, Smeets RJEM, Janssen-Potten YJM. Upper extremity strength measurement for children with cerebral palsy: a systematic review of available instruments. Phys Ther. 2014;94(5):609–622. pmid:24415772
- View Article
- PubMed/NCBI
- Google Scholar
21. Bialocerkowski A, O'Shea K, Pin TW. Psychometric properties of outcome measures for children and adolescents with brachial plexus birth palsy: a systematic review. Dev Med Child Neurol. 2013;55(12):1075–1088. pmid:23808952
- View Article
- PubMed/NCBI
- Google Scholar
22. Ammann-Reiffer C, Bastiaenen CH, de Bie RA, van Hedel HJ. Measurement properties of gait-related outcomes in youth with neuromuscular diagnoses: a systematic review. Phys Ther. 2014;94(8):1067. pmid:24786947
- View Article
- PubMed/NCBI
- Google Scholar
23. Mulder-Brouwer AN, Rameckers EAA, Bastiaenen CH. Lower Extremity Handheld Dynamometry Strength Measurement in Children With Cerebral Palsy. Pediat Phys Ther. 2016;28:136–153. pmid:26744991
- View Article
- PubMed/NCBI
- Google Scholar
24. Hill BE, Williams G, Bialocerkowski AE. Clinimetric evaluation of questionnaires used to assess activity after traumatic brachial plexus injury in adults: a systematic review. Arch Phys Med Rehabil. 2011;92(12):2082–2089. pmid:22133257
- View Article
- PubMed/NCBI
- Google Scholar
25. Clark R, Locke M, Bialocerkowski A. Paediatric terminology in the Australian health and health‐education context: a systematic review. Dev Med Child Neurol. 2015;57(11):1011–1018. pmid:25963398
- View Article
- PubMed/NCBI
- Google Scholar
26. Kastner M, Wilczynski NL, Walker-Dilks C, McKibbon K, Haynes B. Age-specific search strategies for Medline. J Med Internet Res. 2006;8(4):e25. pmid:17213044
- View Article
- PubMed/NCBI
- Google Scholar
27. Boluyt N, Tjosvold L, Lefebvre C, Klassen TP, Offringa M. Usefulness of systematic review search strategies in finding child health systematic reviews in MEDLINE. Arch Pediatr Adolesc Med. 2008;162(2):111–116. pmid:18250233
- View Article
- PubMed/NCBI
- Google Scholar
28. Fily A, Truffert P, Ego A, Depoortere M, Haquin C, Pierrat V.Neurological assessment at five years of age in infants born preterm. Acta Paediatr. 2003;92(12):1433–1437. pmid:14971795
- View Article
- PubMed/NCBI
- Google Scholar
29. Majnemer A, Mazer B. Neurologic evaluation of the newborn infant: definition and psychometric properties. Dev Med Child Neurol. 1998;40(10):708–715. pmid:9851241
- View Article
- PubMed/NCBI
- Google Scholar
30. Spittle AJ, Doyle LW, Boyd RN. A systematic review of the clinimetric properties of neuromotor assessments for preterm infants during the first year of life. Dev Med Child Neurol. 2008;50(4):254–266. pmid:18190538
- View Article
- PubMed/NCBI
- Google Scholar
31. Dobson F, Hinman R, Hall M, Terwee C, Ross E, Bennell K. Measurement properties of performance-based measures to assess physical function in hip and knee osteoarthritis: a systematic review. Osteoarthritis Cartilage. 2012;20(12):1548–1562. pmid:22944525
- View Article
- PubMed/NCBI
- Google Scholar
32. R.R. Bowker Company, and Serials Solutions. Ulrichsweb: global serials directory. New Providence, N.J.: R.R. Bowker. 2001. http://ulrichsweb.serialssolutions.com/ [accessed Jan 2016]
33. Sackett DL, Rosenberg WMC, Gray JAM, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn't. BMJ. 1996; 312:71–72. pmid:8555924
- View Article
- PubMed/NCBI
- Google Scholar
34. Evans D. Hierarchy of evidence: a framework for ranking evidence evaluating healthcare interventions. J Clin Nurs. 2003;12:77–84. pmid:12519253
- View Article
- PubMed/NCBI
- Google Scholar
35. Terwee CB, Jansma EP, Riphagen II, de Vet HC. Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Qual Life Res. 2009;18(8):1115–1123. http://dx.doi.org/10.1007/s11136-009-9528-5. pmid:19711195
- View Article
- PubMed/NCBI
- Google Scholar
36. Bellet RN, Adams L, Morris NR. The 6-minute walk test in outpatient cardiac rehabilitation: validity, reliability and responsiveness—a systematic review. Physiotherapy. 2012;98(4):277–286. pmid:23122432
- View Article
- PubMed/NCBI
- Google Scholar
37. Schrama PP, Stenneberg MS, Lucas C, van Trijffel E. Intraexaminer Reliability of Hand-Held Dynamometry in the Upper Extremity: A Systematic Review. Arch Phys Med Rehabil. 2014;95(12):2444–2469. pmid:24909587
- View Article
- PubMed/NCBI
- Google Scholar
38. Barrett E, McCreesh K, Lewis J. Reliability and validity of non-radiographic methods of thoracic kyphosis measurement: a systematic review. Man Ther. 2014;19(1):10–17. pmid:24246907
- View Article
- PubMed/NCBI
- Google Scholar
39. Rathinam C, Bateman A, Peirson J, Skinner J. Observational gait assessment tools in paediatrics–a systematic review. Gait Posture. 2014;40(2):279–285. pmid:24798609
- View Article
- PubMed/NCBI
- Google Scholar
40. May S, Chance-Larsen K, Littlewood C, Lomas D, Saad M. Reliability of physical examination tests used in the assessment of patients with shoulder problems: a systematic review. Physiotherapy. 2010;96(3):179–190. pmid:20674649
- View Article
- PubMed/NCBI
- Google Scholar
41. Benfer KA, Weir KA, Boyd RN. Clinimetrics of measures of oropharyngeal dysphagia for preschool children with cerebral palsy and neurodevelopmental disabilities: a systematic review. Dev Med Child Neurol. 2012;54(9):784–795. pmid:22582745
- View Article
- PubMed/NCBI
- Google Scholar
42. Terwee CB, Prinsen CAC, Ricci Garotti MG, Suman A, de Vet HCW, Mokkink LB. The quality of systematic reviews of health-related outcome measurement instruments. Qual Life Res. 2015;25:767–779. pmid:26346986
- View Article
- PubMed/NCBI
- Google Scholar
43. Katz JN, Larson MG, Phillips CB, Fossel AH, Liang MH. Comparative Measurement Sensitivity of Short and Longer Health Status Instruments. Med Care. 1992;30:917–925. pmid:1405797
- View Article
- PubMed/NCBI
- Google Scholar
44. Terwee CB, Mokkink LB, Knol DL, Ostelo RW, Bouter LM, de Vet HCW. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual Life Res. 2012;21(4):651–657. pmid:21732199
- View Article
- PubMed/NCBI
- Google Scholar
45. Burns J, Ouvrier R, Estilow T, Shy R, Laura M, Pallant JF, et al. Validation of the Charcot-Marie-Tooth disease pediatric scale as an outcome measure of disability. Ann Neurol. 2012;71(5):642–652. pmid:22522479
- View Article
- PubMed/NCBI
- Google Scholar
46. Berry ET. Intrasession and intersession reliability of handheld dynamometry in children with cerebral palsy. Pediatr Phys Ther. 2004;16(4):191–198. pmid:17057548
- View Article
- PubMed/NCBI
- Google Scholar
47. Crompton J, Galea MP, Phillips B. Hand-held dynamometry for muscle strength measurement in children with cerebral palsy. Dev Med Child Neurol. 2007;49(2):106–111. pmid:17253996
- View Article
- PubMed/NCBI
- Google Scholar
48. Effgen SK, Brown DA. Long-term stability of hand-held dynamometric measurements in children who have myelomeningocele. Phys Ther. 1992;72(6):458–465. pmid:1589465
- View Article
- PubMed/NCBI
- Google Scholar
49. Mahony K, Hunt A, Daley D, Sims S, Adams R. Inter-tester reliability and precision of manual muscle testing and hand-held dynamometry in lower limb muscles of children with spina bifida. Physical & Occupational Therapy In Paediatrics. 2009;29(1):44–59. pmid:19197758
- View Article
- PubMed/NCBI
- Google Scholar
50. Stuberg WA, Metcalf WK. Reliability of quantitative muscle testing in healthy children and in children with Duchenne muscular dystrophy using a hand-held dynamometer. Phys Ther. 1988;68(6):977–982. pmid:3375322
- View Article
- PubMed/NCBI
- Google Scholar
51. Taylor NF, Dodd KJ, Graham HK. Test-retest reliability of hand-held dynamometric strength testing in young people with cerebral palsy. Arch Phys Med Rehabil. 2004;85(1):77–80. pmid:14970972
- View Article
- PubMed/NCBI
- Google Scholar
52. Van Vulpen LF, De Groot S, Becher JG, De Wolf GS, Dallmeijer AJ. Feasibility and test-retest reliability of measuring lower-limb strength in young children with cerebral palsy. Eur J Phys Rehab Med. 2013;49(6):803–813.
- View Article
- Google Scholar
53. Verschuren O, Ketelaar M, Takken T, Van Brussel M, Helders PJM, Gorter JW. Reliability of hand-held dynamometry and functional strength tests for the lower extremity in children with Cerebral Palsy. Disabil Rehabil. 2008;30(18):1358–1366. pmid:18850351
- View Article
- PubMed/NCBI
- Google Scholar
54. Willemse L, Brehm MA, Scholtes VA, Jansen L, Woudenberg-Vos H, Dallmeijer AJ. Reliability of isometric lower-extremity muscle strength measurements in children with cerebral palsy: implications for measurement design. Phys Ther. 2013;93:935–941. pmid:23538586
- View Article
- PubMed/NCBI
- Google Scholar
55. Escolar D, Henricson E, Mayhew J, Florence J, Leshner R, Patel K, et al. Clinical evaluator reliability for quantitative and manual muscle testing measures of strength in children. Muscle Nerve. 2001;24(6):787–793. pmid:11360262
- View Article
- PubMed/NCBI
- Google Scholar
56. Florence JM, Pandya S, King WM, Robison JD, Baty J, Miller JP, et al. Intrarater reliability of manual muscle test (Medical Research Council scale) grades in Duchenne's muscular dystrophy. Phys Ther. 1992;72(2):115–122. pmid:1549632
- View Article
- PubMed/NCBI
- Google Scholar
57. Mulcahey M, Gaughan J, Betz R, Johansen K. The International Standards for Neurological Classification of Spinal Cord Injury: reliability of data when applied to children and youths. Spinal Cord. 2007;45:452–459. pmid:17016490
- View Article
- PubMed/NCBI
- Google Scholar
58. Oftedal S, Bell KL, Mitchell LE, Davies PSW, Ware RS, Boyd RN. A Systematic Review of the Clinimetric Properties of Habitual Physical Activity Measures in Young Children with a Motor Disability. Int J Pediatr. 2012;2012:12. pmid:22927865
- View Article
- PubMed/NCBI
- Google Scholar
59. de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006;4(1):54.
- View Article
- Google Scholar
60. Guyatt GH, Kirshner B, Jaeschke R. A methodologic framework for health status measures: Clarity or oversimplification? J Clin Epidemiol. 1992;45(12):1353–1355. pmid:1460472
- View Article
- PubMed/NCBI
- Google Scholar
61. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Normman GR. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77:371–383. pmid:11936935
- View Article
- PubMed/NCBI
- Google Scholar
62. Hobart JC, Lamping DL, Thompson AJ. Evaluating neurological outcome measures: the bare essentials. J Neurol Neurosurg Psychiatry [Editorial]. 1996;60(2):127–130.
- View Article
- Google Scholar
63. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231–240. pmid:15705040
- View Article
- PubMed/NCBI
- Google Scholar
64. Tan JL, Thomas NM, Johnston LM. Reproducibility of Muscle Strength Testing for Children with Spina Bifida. Phys Occup Ther Pediatr [Article in Press]. 2016:1–12. pmid:28026982
- View Article
- PubMed/NCBI
- Google Scholar
65. Bohannon RW. Manual muscle testing: does it meet the standards of an adequate screening test? Clin Rehabil. 2005;19(6):662–667. pmid:16180603
- View Article
- PubMed/NCBI
- Google Scholar
66. Yocum A, McCoy SW, Bjornson KF, Mullens P, Burton GN. Reliability and validity of the standing heel-rise test. Phys Occup Ther Pediatr. 2010;30(3):190–204. pmid:20608857
- View Article
- PubMed/NCBI
- Google Scholar
67. Harris-Love MO, Shrader JA, Davenport TE, Joe G, Rakocevic G, McElroy B, et al. Are repeated single-limb heel raises and manual muscle testing associated with peak plantar-flexor force in people with inclusion body myositis? Phys Ther. 2014;94(4):543. pmid:24309617
- View Article
- PubMed/NCBI
- Google Scholar
68. Lunsford BR, Perry J. The standing heel-rise test for ankle plantar flexion: criterion for normal. Phys Ther. 1995;75(8):694–698. pmid:7644573
- View Article
- PubMed/NCBI
- Google Scholar
69. Hébert-Losier K, Newsham-West RJ, Schneiders AG, Sullivan SJ. Raising the standards of the calf-raise test: a systematic review. J Sci Med Sport. 2009;12(6):594–602. pmid:19231286
- View Article
- PubMed/NCBI
- Google Scholar
70. Wikholm JB, Bohannon RW. Hand-held dynamometer measurements: tester strength makes a difference. J Orthop Sports Phys Ther. 1991;13(4):191–198. pmid:18796845
- View Article
- PubMed/NCBI
- Google Scholar
71. Pannucci CJ, Wilkins EG. Identifying and Avoiding Bias in Research. Plast Reconstr Surg. 2010;126:619–625. pmid:20679844
- View Article
- PubMed/NCBI
- Google Scholar
72. Kahn MG, Bailey LC, Forrest CB, Padula MA, Hirschfeld S. Building a common pediatric research terminology for accelerating child health research. Pediatrics. 2014 Mar;133(3):516–525. pmid:24534404
- View Article
- PubMed/NCBI
- Google Scholar
73. Hirtz D, Thurman D, Gwinn-Hardy K, Mohamed M, Chaudhuri A, Zalutsky R. How common are the “common” neurologic disorders? Neurology. 2007;68(5):326–337. pmid:17261678
- View Article
- PubMed/NCBI
- Google Scholar
74. Kim WH, Park EY. Causal relation between spasticity, strength, gross motor function, and functional outcome in children with cerebral palsy: A path analysis. Dev Med Child Neurol. 2011;53(1):68–73. pmid:21126242
- View Article
- PubMed/NCBI
- Google Scholar
75. Guyatt GH, Kirshner B, Jaeschke R. Measuring health status: What are the necessary measurement properties? J Clin Epidemiol. 1992;45:1341–1345. pmid:1460470
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Gerber CN, Labruyère R, van Hedel HJA. Reliability and Responsiveness of Upper Limb Motor Assessments for Children With Central Neuromotor Disorders: A Systematic Review. Neurorehabil Neural Repair. 2016;30(1):19–39. pmid:25921350
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Who, ebrary I, World Health O. Neurological disorders: public health challenges. Geneva: World Health Organization; 2006.

[ref3] 3. Wright V, Majnemer A, Maltais DB, Burtner PA, Sanders H. Motor measures: A moving target? Semin Pediatr Neurol. 2013;20:84–99. pmid:23948683
View Article
PubMed/NCBI
Google Scholar

[7] View Article

[8] PubMed/NCBI

[9] Google Scholar

[ref4] 4. WHO. International classification of functioning, disability, and health: children & youth version: ICF-CY. Geneva: World Health Organization; 2007.

[ref5] 5. Petty NJ. Neuromusculoskeletal Examination and Assessment: A Handbook for Therapists. Elsevier Health Sciences UK; 2011.

[ref6] 6. Brink Y, Louw QA. Clinical instruments: reliability and validity critical appraisal. J Eval Clin Pract. 2012;18(6):1126–1132. pmid:21689217
View Article
PubMed/NCBI
Google Scholar

[13] View Article

[14] PubMed/NCBI

[15] Google Scholar

[ref7] 7. Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42. pmid:17161752
View Article
PubMed/NCBI
Google Scholar

[17] View Article

[18] PubMed/NCBI

[19] Google Scholar

[ref8] 8. Mokkink L, Terwee C, Knol D, Stratford P, Alonso J, Patrick D, et al. Protocol of the COSMIN study: COnsensus-based Standards for the selection of health Measurement INstruments. BMC Med Res Methodol. 2006;6(1):2. pmid:16433905
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref9] 9. Auld ML, Boyd RN, Moseley GL, Johnston LM. Tactile assessment in children with Cerebral Palsy: A Clinimetric Review. Phys Occup Ther Pediatr. 2011;31(4):413–439. pmid:21599569
View Article
PubMed/NCBI
Google Scholar

[25] View Article

[26] PubMed/NCBI

[27] Google Scholar

[ref10] 10. Hobart JC, Cano SJ, Zajicek JP, Thompson AJ. Rating scales as outcome measures for clinical trials in neurology: problems, solutions, and recommendations. Lancet Neurol. 2007;6(12):1094–1105. pmid:18031706
View Article
PubMed/NCBI
Google Scholar

[29] View Article

[30] PubMed/NCBI

[31] Google Scholar

[ref11] 11. Tyson S, Watson A, Moss S, Troop H, Dean-Lofthouse G, Jorritsma S, et al. Development of a framework for the evidence-based choice of outcome measures in neurological physiotherapy. Disabil Rehabil. 2008;30(2):142–149. pmid:17852285
View Article
PubMed/NCBI
Google Scholar

[33] View Article

[34] PubMed/NCBI

[35] Google Scholar

[ref12] 12. Majnemer A, Limperopoulos C. Importance of outcome determination in paediatric rehabilitation. Dev Med Child Neurol. 2002;44(11):773–777. pmid:12418619
View Article
PubMed/NCBI
Google Scholar

[37] View Article

[38] PubMed/NCBI

[39] Google Scholar

[ref13] 13. Jerosch-Herold C. An evidence-based approach to choosing outcome measures: a checklist for the critical appraisal of validity, reliability and responsiveness studies. Br J Occup Ther. 2005;68(8):347–353.
View Article
Google Scholar

[41] View Article

[42] Google Scholar

[ref14] 14. Smart A. A multi-dimensional model of clinical utility. Int J Qual Health Care. 2006;18(5):377–382. pmid:16951425
View Article
PubMed/NCBI
Google Scholar

[44] View Article

[45] PubMed/NCBI

[46] Google Scholar

[ref15] 15. de Vet HC, Terwee CB, Bouter LM. Current challenges in clinimetrics. J Clin Epidemiol. 2003;56:1137–1141. pmid:14680660
View Article
PubMed/NCBI
Google Scholar

[48] View Article

[49] PubMed/NCBI

[50] Google Scholar

[ref16] 16. Bialocerkowski AE, Bragge P. Measurement error and reliability testing: Application to rehabilitation. Int J Ther Rehabil. 2008;15(10):422–427.
View Article
Google Scholar

[52] View Article

[53] Google Scholar

[ref17] 17. Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. Pearson/Prentice Hall; 2009.

[ref18] 18. Van den Beld W, Van der Sanden G, Sengers R, Verbeek A, Gabreels F. Validity and reproducibility of hand-held dynamometry in children aged 4–11 years. J Rehabil Med. 2006.38:57–64. pmid:16548089
View Article
PubMed/NCBI
Google Scholar

[56] View Article

[57] PubMed/NCBI

[58] Google Scholar

[ref19] 19. Damiano DL, Abel MF. Functional outcomes of strength training in spastic cerebral palsy. Arch Phys Med Rehabil. 1998;79(2):119–125. pmid:9473991
View Article
PubMed/NCBI
Google Scholar

[60] View Article

[61] PubMed/NCBI

[62] Google Scholar

[ref20] 20. Dekkers KJFM, Rameckers EAA, Smeets RJEM, Janssen-Potten YJM. Upper extremity strength measurement for children with cerebral palsy: a systematic review of available instruments. Phys Ther. 2014;94(5):609–622. pmid:24415772
View Article
PubMed/NCBI
Google Scholar

[64] View Article

[65] PubMed/NCBI

[66] Google Scholar

[ref21] 21. Bialocerkowski A, O'Shea K, Pin TW. Psychometric properties of outcome measures for children and adolescents with brachial plexus birth palsy: a systematic review. Dev Med Child Neurol. 2013;55(12):1075–1088. pmid:23808952
View Article
PubMed/NCBI
Google Scholar

[68] View Article

[69] PubMed/NCBI

[70] Google Scholar

[ref22] 22. Ammann-Reiffer C, Bastiaenen CH, de Bie RA, van Hedel HJ. Measurement properties of gait-related outcomes in youth with neuromuscular diagnoses: a systematic review. Phys Ther. 2014;94(8):1067. pmid:24786947
View Article
PubMed/NCBI
Google Scholar

[72] View Article

[73] PubMed/NCBI

[74] Google Scholar

[ref23] 23. Mulder-Brouwer AN, Rameckers EAA, Bastiaenen CH. Lower Extremity Handheld Dynamometry Strength Measurement in Children With Cerebral Palsy. Pediat Phys Ther. 2016;28:136–153. pmid:26744991
View Article
PubMed/NCBI
Google Scholar

[76] View Article

[77] PubMed/NCBI

[78] Google Scholar

[ref24] 24. Hill BE, Williams G, Bialocerkowski AE. Clinimetric evaluation of questionnaires used to assess activity after traumatic brachial plexus injury in adults: a systematic review. Arch Phys Med Rehabil. 2011;92(12):2082–2089. pmid:22133257
View Article
PubMed/NCBI
Google Scholar

[80] View Article

[81] PubMed/NCBI

[82] Google Scholar

[ref25] 25. Clark R, Locke M, Bialocerkowski A. Paediatric terminology in the Australian health and health‐education context: a systematic review. Dev Med Child Neurol. 2015;57(11):1011–1018. pmid:25963398
View Article
PubMed/NCBI
Google Scholar

[84] View Article

[85] PubMed/NCBI

[86] Google Scholar

[ref26] 26. Kastner M, Wilczynski NL, Walker-Dilks C, McKibbon K, Haynes B. Age-specific search strategies for Medline. J Med Internet Res. 2006;8(4):e25. pmid:17213044
View Article
PubMed/NCBI
Google Scholar

[88] View Article

[89] PubMed/NCBI

[90] Google Scholar

[ref27] 27. Boluyt N, Tjosvold L, Lefebvre C, Klassen TP, Offringa M. Usefulness of systematic review search strategies in finding child health systematic reviews in MEDLINE. Arch Pediatr Adolesc Med. 2008;162(2):111–116. pmid:18250233
View Article
PubMed/NCBI
Google Scholar

[92] View Article

[93] PubMed/NCBI

[94] Google Scholar

[ref28] 28. Fily A, Truffert P, Ego A, Depoortere M, Haquin C, Pierrat V.Neurological assessment at five years of age in infants born preterm. Acta Paediatr. 2003;92(12):1433–1437. pmid:14971795
View Article
PubMed/NCBI
Google Scholar

[96] View Article

[97] PubMed/NCBI

[98] Google Scholar

[ref29] 29. Majnemer A, Mazer B. Neurologic evaluation of the newborn infant: definition and psychometric properties. Dev Med Child Neurol. 1998;40(10):708–715. pmid:9851241
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref30] 30. Spittle AJ, Doyle LW, Boyd RN. A systematic review of the clinimetric properties of neuromotor assessments for preterm infants during the first year of life. Dev Med Child Neurol. 2008;50(4):254–266. pmid:18190538
View Article
PubMed/NCBI
Google Scholar

[104] View Article

[105] PubMed/NCBI

[106] Google Scholar

[ref31] 31. Dobson F, Hinman R, Hall M, Terwee C, Ross E, Bennell K. Measurement properties of performance-based measures to assess physical function in hip and knee osteoarthritis: a systematic review. Osteoarthritis Cartilage. 2012;20(12):1548–1562. pmid:22944525
View Article
PubMed/NCBI
Google Scholar

[108] View Article

[109] PubMed/NCBI

[110] Google Scholar

[ref32] 32. R.R. Bowker Company, and Serials Solutions. Ulrichsweb: global serials directory. New Providence, N.J.: R.R. Bowker. 2001. http://ulrichsweb.serialssolutions.com/ [accessed Jan 2016]

[ref33] 33. Sackett DL, Rosenberg WMC, Gray JAM, Haynes RB, Richardson WS. Evidence based medicine: what it is and what it isn't. BMJ. 1996; 312:71–72. pmid:8555924
View Article
PubMed/NCBI
Google Scholar

[113] View Article

[114] PubMed/NCBI

[115] Google Scholar

[ref34] 34. Evans D. Hierarchy of evidence: a framework for ranking evidence evaluating healthcare interventions. J Clin Nurs. 2003;12:77–84. pmid:12519253
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref35] 35. Terwee CB, Jansma EP, Riphagen II, de Vet HC. Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Qual Life Res. 2009;18(8):1115–1123. http://dx.doi.org/10.1007/s11136-009-9528-5. pmid:19711195
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

[ref36] 36. Bellet RN, Adams L, Morris NR. The 6-minute walk test in outpatient cardiac rehabilitation: validity, reliability and responsiveness—a systematic review. Physiotherapy. 2012;98(4):277–286. pmid:23122432
View Article
PubMed/NCBI
Google Scholar

[125] View Article

[126] PubMed/NCBI

[127] Google Scholar

[ref37] 37. Schrama PP, Stenneberg MS, Lucas C, van Trijffel E. Intraexaminer Reliability of Hand-Held Dynamometry in the Upper Extremity: A Systematic Review. Arch Phys Med Rehabil. 2014;95(12):2444–2469. pmid:24909587
View Article
PubMed/NCBI
Google Scholar

[129] View Article

[130] PubMed/NCBI

[131] Google Scholar

[ref38] 38. Barrett E, McCreesh K, Lewis J. Reliability and validity of non-radiographic methods of thoracic kyphosis measurement: a systematic review. Man Ther. 2014;19(1):10–17. pmid:24246907
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref39] 39. Rathinam C, Bateman A, Peirson J, Skinner J. Observational gait assessment tools in paediatrics–a systematic review. Gait Posture. 2014;40(2):279–285. pmid:24798609
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref40] 40. May S, Chance-Larsen K, Littlewood C, Lomas D, Saad M. Reliability of physical examination tests used in the assessment of patients with shoulder problems: a systematic review. Physiotherapy. 2010;96(3):179–190. pmid:20674649
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref41] 41. Benfer KA, Weir KA, Boyd RN. Clinimetrics of measures of oropharyngeal dysphagia for preschool children with cerebral palsy and neurodevelopmental disabilities: a systematic review. Dev Med Child Neurol. 2012;54(9):784–795. pmid:22582745
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

[ref42] 42. Terwee CB, Prinsen CAC, Ricci Garotti MG, Suman A, de Vet HCW, Mokkink LB. The quality of systematic reviews of health-related outcome measurement instruments. Qual Life Res. 2015;25:767–779. pmid:26346986
View Article
PubMed/NCBI
Google Scholar

[149] View Article

[150] PubMed/NCBI

[151] Google Scholar

[ref43] 43. Katz JN, Larson MG, Phillips CB, Fossel AH, Liang MH. Comparative Measurement Sensitivity of Short and Longer Health Status Instruments. Med Care. 1992;30:917–925. pmid:1405797
View Article
PubMed/NCBI
Google Scholar

[153] View Article

[154] PubMed/NCBI

[155] Google Scholar

[ref44] 44. Terwee CB, Mokkink LB, Knol DL, Ostelo RW, Bouter LM, de Vet HCW. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual Life Res. 2012;21(4):651–657. pmid:21732199
View Article
PubMed/NCBI
Google Scholar

[157] View Article

[158] PubMed/NCBI

[159] Google Scholar

[ref45] 45. Burns J, Ouvrier R, Estilow T, Shy R, Laura M, Pallant JF, et al. Validation of the Charcot-Marie-Tooth disease pediatric scale as an outcome measure of disability. Ann Neurol. 2012;71(5):642–652. pmid:22522479
View Article
PubMed/NCBI
Google Scholar

[161] View Article

[162] PubMed/NCBI

[163] Google Scholar

[ref46] 46. Berry ET. Intrasession and intersession reliability of handheld dynamometry in children with cerebral palsy. Pediatr Phys Ther. 2004;16(4):191–198. pmid:17057548
View Article
PubMed/NCBI
Google Scholar

[165] View Article

[166] PubMed/NCBI

[167] Google Scholar

[ref47] 47. Crompton J, Galea MP, Phillips B. Hand-held dynamometry for muscle strength measurement in children with cerebral palsy. Dev Med Child Neurol. 2007;49(2):106–111. pmid:17253996
View Article
PubMed/NCBI
Google Scholar

[169] View Article

[170] PubMed/NCBI

[171] Google Scholar

[ref48] 48. Effgen SK, Brown DA. Long-term stability of hand-held dynamometric measurements in children who have myelomeningocele. Phys Ther. 1992;72(6):458–465. pmid:1589465
View Article
PubMed/NCBI
Google Scholar

[173] View Article

[174] PubMed/NCBI

[175] Google Scholar

[ref49] 49. Mahony K, Hunt A, Daley D, Sims S, Adams R. Inter-tester reliability and precision of manual muscle testing and hand-held dynamometry in lower limb muscles of children with spina bifida. Physical & Occupational Therapy In Paediatrics. 2009;29(1):44–59. pmid:19197758
View Article
PubMed/NCBI
Google Scholar

[177] View Article

[178] PubMed/NCBI

[179] Google Scholar

[ref50] 50. Stuberg WA, Metcalf WK. Reliability of quantitative muscle testing in healthy children and in children with Duchenne muscular dystrophy using a hand-held dynamometer. Phys Ther. 1988;68(6):977–982. pmid:3375322
View Article
PubMed/NCBI
Google Scholar

[181] View Article

[182] PubMed/NCBI

[183] Google Scholar

[ref51] 51. Taylor NF, Dodd KJ, Graham HK. Test-retest reliability of hand-held dynamometric strength testing in young people with cerebral palsy. Arch Phys Med Rehabil. 2004;85(1):77–80. pmid:14970972
View Article
PubMed/NCBI
Google Scholar

[185] View Article

[186] PubMed/NCBI

[187] Google Scholar

[ref52] 52. Van Vulpen LF, De Groot S, Becher JG, De Wolf GS, Dallmeijer AJ. Feasibility and test-retest reliability of measuring lower-limb strength in young children with cerebral palsy. Eur J Phys Rehab Med. 2013;49(6):803–813.
View Article
Google Scholar

[189] View Article

[190] Google Scholar

[ref53] 53. Verschuren O, Ketelaar M, Takken T, Van Brussel M, Helders PJM, Gorter JW. Reliability of hand-held dynamometry and functional strength tests for the lower extremity in children with Cerebral Palsy. Disabil Rehabil. 2008;30(18):1358–1366. pmid:18850351
View Article
PubMed/NCBI
Google Scholar

[192] View Article

[193] PubMed/NCBI

[194] Google Scholar

[ref54] 54. Willemse L, Brehm MA, Scholtes VA, Jansen L, Woudenberg-Vos H, Dallmeijer AJ. Reliability of isometric lower-extremity muscle strength measurements in children with cerebral palsy: implications for measurement design. Phys Ther. 2013;93:935–941. pmid:23538586
View Article
PubMed/NCBI
Google Scholar

[196] View Article

[197] PubMed/NCBI

[198] Google Scholar

[ref55] 55. Escolar D, Henricson E, Mayhew J, Florence J, Leshner R, Patel K, et al. Clinical evaluator reliability for quantitative and manual muscle testing measures of strength in children. Muscle Nerve. 2001;24(6):787–793. pmid:11360262
View Article
PubMed/NCBI
Google Scholar

[200] View Article

[201] PubMed/NCBI

[202] Google Scholar

[ref56] 56. Florence JM, Pandya S, King WM, Robison JD, Baty J, Miller JP, et al. Intrarater reliability of manual muscle test (Medical Research Council scale) grades in Duchenne's muscular dystrophy. Phys Ther. 1992;72(2):115–122. pmid:1549632
View Article
PubMed/NCBI
Google Scholar

[204] View Article

[205] PubMed/NCBI

[206] Google Scholar

[ref57] 57. Mulcahey M, Gaughan J, Betz R, Johansen K. The International Standards for Neurological Classification of Spinal Cord Injury: reliability of data when applied to children and youths. Spinal Cord. 2007;45:452–459. pmid:17016490
View Article
PubMed/NCBI
Google Scholar

[208] View Article

[209] PubMed/NCBI

[210] Google Scholar

[ref58] 58. Oftedal S, Bell KL, Mitchell LE, Davies PSW, Ware RS, Boyd RN. A Systematic Review of the Clinimetric Properties of Habitual Physical Activity Measures in Young Children with a Motor Disability. Int J Pediatr. 2012;2012:12. pmid:22927865
View Article
PubMed/NCBI
Google Scholar

[212] View Article

[213] PubMed/NCBI

[214] Google Scholar

[ref59] 59. de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006;4(1):54.
View Article
Google Scholar

[216] View Article

[217] Google Scholar

[ref60] 60. Guyatt GH, Kirshner B, Jaeschke R. A methodologic framework for health status measures: Clarity or oversimplification? J Clin Epidemiol. 1992;45(12):1353–1355. pmid:1460472
View Article
PubMed/NCBI
Google Scholar

[219] View Article

[220] PubMed/NCBI

[221] Google Scholar

[ref61] 61. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Normman GR. Methods to explain the clinical significance of health status measures. Mayo Clin Proc. 2002;77:371–383. pmid:11936935
View Article
PubMed/NCBI
Google Scholar

[223] View Article

[224] PubMed/NCBI

[225] Google Scholar

[ref62] 62. Hobart JC, Lamping DL, Thompson AJ. Evaluating neurological outcome measures: the bare essentials. J Neurol Neurosurg Psychiatry [Editorial]. 1996;60(2):127–130.
View Article
Google Scholar

[227] View Article

[228] Google Scholar

[ref63] 63. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231–240. pmid:15705040
View Article
PubMed/NCBI
Google Scholar

[230] View Article

[231] PubMed/NCBI

[232] Google Scholar

[ref64] 64. Tan JL, Thomas NM, Johnston LM. Reproducibility of Muscle Strength Testing for Children with Spina Bifida. Phys Occup Ther Pediatr [Article in Press]. 2016:1–12. pmid:28026982
View Article
PubMed/NCBI
Google Scholar

[234] View Article

[235] PubMed/NCBI

[236] Google Scholar

[ref65] 65. Bohannon RW. Manual muscle testing: does it meet the standards of an adequate screening test? Clin Rehabil. 2005;19(6):662–667. pmid:16180603
View Article
PubMed/NCBI
Google Scholar

[238] View Article

[239] PubMed/NCBI

[240] Google Scholar

[ref66] 66. Yocum A, McCoy SW, Bjornson KF, Mullens P, Burton GN. Reliability and validity of the standing heel-rise test. Phys Occup Ther Pediatr. 2010;30(3):190–204. pmid:20608857
View Article
PubMed/NCBI
Google Scholar

[242] View Article

[243] PubMed/NCBI

[244] Google Scholar

[ref67] 67. Harris-Love MO, Shrader JA, Davenport TE, Joe G, Rakocevic G, McElroy B, et al. Are repeated single-limb heel raises and manual muscle testing associated with peak plantar-flexor force in people with inclusion body myositis? Phys Ther. 2014;94(4):543. pmid:24309617
View Article
PubMed/NCBI
Google Scholar

[246] View Article

[247] PubMed/NCBI

[248] Google Scholar

[ref68] 68. Lunsford BR, Perry J. The standing heel-rise test for ankle plantar flexion: criterion for normal. Phys Ther. 1995;75(8):694–698. pmid:7644573
View Article
PubMed/NCBI
Google Scholar

[250] View Article

[251] PubMed/NCBI

[252] Google Scholar

[ref69] 69. Hébert-Losier K, Newsham-West RJ, Schneiders AG, Sullivan SJ. Raising the standards of the calf-raise test: a systematic review. J Sci Med Sport. 2009;12(6):594–602. pmid:19231286
View Article
PubMed/NCBI
Google Scholar

[254] View Article

[255] PubMed/NCBI

[256] Google Scholar

[ref70] 70. Wikholm JB, Bohannon RW. Hand-held dynamometer measurements: tester strength makes a difference. J Orthop Sports Phys Ther. 1991;13(4):191–198. pmid:18796845
View Article
PubMed/NCBI
Google Scholar

[258] View Article

[259] PubMed/NCBI

[260] Google Scholar

[ref71] 71. Pannucci CJ, Wilkins EG. Identifying and Avoiding Bias in Research. Plast Reconstr Surg. 2010;126:619–625. pmid:20679844
View Article
PubMed/NCBI
Google Scholar

[262] View Article

[263] PubMed/NCBI

[264] Google Scholar

[ref72] 72. Kahn MG, Bailey LC, Forrest CB, Padula MA, Hirschfeld S. Building a common pediatric research terminology for accelerating child health research. Pediatrics. 2014 Mar;133(3):516–525. pmid:24534404
View Article
PubMed/NCBI
Google Scholar

[266] View Article

[267] PubMed/NCBI

[268] Google Scholar

[ref73] 73. Hirtz D, Thurman D, Gwinn-Hardy K, Mohamed M, Chaudhuri A, Zalutsky R. How common are the “common” neurologic disorders? Neurology. 2007;68(5):326–337. pmid:17261678
View Article
PubMed/NCBI
Google Scholar

[270] View Article

[271] PubMed/NCBI

[272] Google Scholar

[ref74] 74. Kim WH, Park EY. Causal relation between spasticity, strength, gross motor function, and functional outcome in children with cerebral palsy: A path analysis. Dev Med Child Neurol. 2011;53(1):68–73. pmid:21126242
View Article
PubMed/NCBI
Google Scholar

[274] View Article

[275] PubMed/NCBI

[276] Google Scholar

[ref75] 75. Guyatt GH, Kirshner B, Jaeschke R. Measuring health status: What are the necessary measurement properties? J Clin Epidemiol. 1992;45:1341–1345. pmid:1460470
View Article
PubMed/NCBI
Google Scholar

[278] View Article

[279] PubMed/NCBI

[280] Google Scholar

Figures

Abstract

Background

Objective

Methods

Results

Conclusions

Introduction

Method

Phase 1: Identification of neurological tests

Study selection

Phase 2: Identification of clinimetric properties of neurological tests

Quality assessment

Data extraction

Best evidence synthesis

Results

Search output

Methodological quality

Neurological tests and their clinimetric properties

Clinimetric evidence

Hand held dynamometry.

Manual muscle testing.

Charcot marie-tooth paediatric scale.

ASIA impairment scale.

Richmond quantitative measurement system.

Standing heel rise.

Synthesis of evidence

Discussion

Conclusion

Supporting information

S1 Table. CINAHL search terms used to identify lower limb neurological tests in children.

S2 Table. CINAHL search terms used to identify clinimetric properties for Achilles reflex in children.

S3 Table. Neurological test names for children and adolescents identified by the search strategies, and papers on their clinimetric properties.

S4 Table. Characteristics of included clinimetric papers for neurological tests used on children and young people with a neurological condition.

S5 Table. PRISMA checklist.

Acknowledgments

Author Contributions

References