Share this article on:

The Motor Learning Strategy Instrument: Interrater Reliability Within Usual and Virtual Reality Physical Therapy Interventions

Levac, Danielle PhD; Missiuna, Cheryl PhD; Wishart, Laurie PhD; DeMatteo, Carol MSc; Wright, Virginia PhD

doi: 10.1097/PEP.0b013e3182750c28
Research Article

Purpose: To evaluate and compare the interrater reliability of the Motor Learning Strategy Rating Instrument (MLSRI) within usual and virtual reality (VR) interventions for children with acquired brain injury.

Methods: Two intervention sessions for each of 11 children (total, 22) were videotaped; sessions were provided by 4 physical therapists. Videotapes were divided into usual and VR components and rated by 2 observers using the MLSRI. A generalizability theory approach was used to determine interrater reliability for each intervention.

Results: Interrater reliability for usual interventions was high for the MLSRI total score (g-coefficient, 0.81), whereas it was low for the VR total score (g-coefficient, 0.28); MLSRI category g-coefficients varied from 0.35 to 0.65 for usual and from 0.17 to 0.72 for VR interventions.

Conclusion: Adequate reliability was achieved within ratings of usual interventions; however, challenges related to MLSRI use to rate VR-based interventions require further evaluation.

The authors report that their instrument shows good interrater reliability when assessing usual interventions but was less reliable when assessing virtual reality based therapy.

School of Rehabilitation Science (Drs Levac, Missiuna, Wishart, and Wright and Ms DeMatteo) and CanChild Centre for Childhood Disability Research (Drs Missiuna and Wright and Ms DeMatteo), McMaster University, Hamilton, Ontario, Canada; Bloorview Research Institute (Dr Wright), Toronto, Ontario, Canada; Department of Physical Therapy (Dr Wright), University of Toronto, Toronto, Ontario, Canada.

Danielle Levac, PhD, School of Rehabilitation Science, Institute for Applied Health Science, Room 403, McMaster University, 1400 Main St W, Hamilton, Ontario, Canada, L8S 1C7 (

Grant Support: The first author was supported by a doctoral award from the Canadian Child Health Clinician Scientist Program, a strategic training initiative of the Canadian Institutes of Health Research, and the McMaster Child Health Research Institute. Dr Missiuna holds a Rehabilitation Scientist award from the Ontario Ministry of Health and Long-Term Care and the Ontario Neurotrauma Foundation. Funding for this study was provided by a grant from the Physiotherapy Foundation of Canada.

The authors declare no conflict of interest.

Back to Top | Article Outline


The physical and cognitive impairments arising from an acquired brain injury (ABI) may present a substantial burden for children and youth, leading to long-term functional limitations and participation restrictions.1 Children with moderate and severe ABI often receive physical therapy (PT) interventions within inpatient rehabilitation to regain gross motor, mobility, and balance skills and support reintegration in home, school, and community activities.2,3 Although studies have evaluated the effectiveness of various interventions at different stages of injury, no practice guidelines exist to support choices for physical therapists in the management of children and youth with ABI in early rehabilitation.25 Given that the learning occuring within rehabilitation interventions may influence neuroplastic mechanisms of recovery,6 the ability to describe intervention content is vital to develop, evaluate, and replicate effective treatments.

The complex nature of rehabilitation interventions implies that a specific focus be chosen when describing intervention content.7 Although interventions can be based in many theoretical frameworks, motor learning theory is a relevant focus for exploring the content of PT interventions for children and youth with ABI. This population must not only regain lost motor skills but also learn new motor skills as part of their continuing development.3,8 Motor learning is defined as the relatively permanent changes in motor skills, achieved with practice or experience, that can be retained, transferred, and/or generalized to new learning situations.9 Rather than simply improving motor performance during therapy sessions, the goal of PT sessions that are based in motor learning is for clients to retain skills so that they can use them in real-life activities and settings.10

Levac et al11 have described a clinical decision-making process that outlines how therapists can use motor learning strategies in practice (Figure 1). Motor learning strategies (MLSs) are observable therapeutic actions involving the selection, manipulation, and application of a motor learning variable according to client- and task-specific factors and with consideration of motor learning principles. Motor learning variables, based in motor learning theories and empirical evidence, require physical therapists to make choices about their frequency, type, duration, intensity, or schedule (eg, organization of practice: whole versus part; random versus blocked, or amount of practice: more versus less).11 Examples of MLSs include providing verbal feedback about task performance or structuring the order of tasks or activities within the practice session. Although some evidence for the method and extent of MLS application exists in other pediatric populations, little is known about how therapists use MLSs in their interventions for children and youth with ABI, where children's cognitive, memory, or behavioral impairments12 may be factors that influence intervention content.

Physical therapy interventions for children with ABI can include new technologies such as the interactive virtual reality (VR) video games Nintendo Wii/WiiFit that are gaining popularity within pediatric rehabilitation.13 Currently, few reports exist to provide evidence or direction for therapists interested in integrating VR technology within clinical practice. These VR games may have an effect on the extent and manner of therapist use of MLSs as compared with usual interventions, given their inherent features of abundant feedback and opportunities for consistent repetition of tasks.13,14 Exploring the link with MLS use is an important step in designing and evaluating VR interventions.

In recognition of the need to quantify the use of MLSs, our research group used a systematic development process (incorporating face and content validity analysis) to create the Motor Learning Strategy Rating Instrument (MLSRI).11 This is a 33-item observer-rated scale designed to rate the extent of MLS use within a videotaped PT intervention session.11 Initial evaluation of inter- and intrarater reliability was completed.15 The MLSRI demonstrated excellent total score intrarater reliability (intraclass correlation coefficient [ICC], 0.86; 95% confidence interval [CI], 0.66-0.94). However, total score interrater reliability was found to be inadequate (ICC, 0.50; 95% CI, 0.08-0.78]), and we proposed that a key issue may have been lack of consistency between raters' interpretations of item definitions.15 Further development of item definitions and rater training materials was undertaken and the revised instrument was used in this study. To compare the use of MLSs within VR-based interventions with their use in other types of interventions, a reliability evaluation of the MLSRI specific to VR-based interventions was required. The purpose of this study was to further evaluate and compare the interrater reliability and feasibility of the revised MLSRI between usual and VR interventions.

Back to Top | Article Outline



This study used a repeated-measures observational design in which participants received both usual and VR interventions in each of the 2 therapy sessions (Figure 2). Two sessions per child, provided a minimum 2 weeks apart, were included to capture potential changes in MLS use at different points in the child's recovery. The extent of MLS use within usual and VR interventions was separately rated in each of these sessions. Ethical approval was received from the McMaster University Research Ethics Board and the ethics board of the Holland Bloorview Kids Rehabilitation Hospital.

Back to Top | Article Outline

Setting and Participants

The study took place at the inpatient brain injury rehabilitation unit of a large children's rehabilitation center in Toronto, Ontario, Canada. To avoid influencing the content of videotaped intervention sessions, the study focus on the use of MLSs was not revealed to the therapists during the recruitment and data-collection processes. Therapists were informed that the study purpose was to evaluate an instrument measuring frequency and nature of their intervention activities. Physical therapists identified eligible children and youth among their clients and a research assistant (RA) provided more information about the study and obtained informed consent. Inclusion criteria for children and youth were that they be diagnosed with an ABI; ambulatory (independent or with a walking aid); receiving inpatient PT services; aged 7 to 18 years; and that the VR be a key component of the therapist's existing intervention plan geared toward improving motor skills. Given the inclusion of the VR in their interventions, we anticipated that therapists would not identify children who demonstrated significant cognitive limitations. The only exclusion criterion was a history of seizure(s), as Nintendo lists this as a warning for the use of their product. The physical therapist inclusion criterion was a willingness to be videotaped while delivering interventions. Written informed consent/assent was obtained from physical therapists, children/youth, and their parents as appropriate.

Back to Top | Article Outline


Demographic information about children and therapists was obtained. For each child participant, 2 PT intervention sessions taking place at least 2 weeks apart were videotaped by the RA. The RA positioned herself so as to optimize the video views and audio capture while avoiding intruding into the session. She attempted to capture full frontal or side views of both child and therapist throughout the session.

Intervention content was not dictated by the study other than the eligibility requirement that the therapists use VR as a component of their intervention sessions. All interventions were geared toward improving motor skills. “Usual” (ie, non-VR) interventions targeted gait training, strengthening, balance (static or dynamic), endurance, or coordination. Therapists used traditional therapy tools such as a treadmill, bicycle, balance boards, and balls and other toys, and provided interventions in a therapy gym, hallway, or stairwell.

For VR interventions, requirements for Wii programs and usage times were not specified. The Wii uses motion-sensing technology to detect acceleration and orientation, allowing the child to control games by means of movement and posture.13 The Wii remote control uses accelerometers that enable the detection of movements in 3 dimensions. A range from miniscule movements of the controller to whole body movements can be used to play the games. An onscreen avatar (a visual representation of the self) mimics movements of the child. Therapists primarily used the Wii sports games and the Wii Fit balance games. A description of the 5 Wii Sports games can be found in Deutsch et al.13 The Wii Fit is a pressure-sensitive balance board in which weight shifting and changes in body posture control 12 different balance games. VR interventions took place in a small therapy room. Children stood approximately 3' from a flat-screen television on which the VR was displayed. Therapists often integrated additional therapy equipment such as balance boards and weights into their VR interventions. They chose whether or not to participate in VR game play to provide competition for the child.

The RA transformed usual and VR components of each videotaped session into separate mpeg movie format files to facilitate separate independent rating. Two PT student raters, who were part of the initial reliability study, had undergone an extensive training and review process (see Kamath et al15 for details) to learn to use the MLSRI in usual interventions. Subsequent training was undertaken with the revised item definitions and with VR interventions. These raters independently rated the usual and VR components of the videotapes in a randomized order, with a minimum of 2 days between ratings of the same child. For the feasibility evaluation, raters recorded the time taken to rate each video and used 10-cm visual analog scales to indicate their confidence and difficulty with rating each session.

Back to Top | Article Outline

Measurement Tool


The MLSRI11 contains 33 items divided into 6 categories: therapist provision of verbal instructions, feedback, or cues (therapist verbalizations: 10 items); child verbalizations related to learning (child verbalizations: 3 items); organization of practice (practice: 6 items); therapist techniques (guidance: 3 items); observations about therapist and child behavior in the session as a whole (conduct: 6 items); and use of VR (the Wii) (VR: 3 items). Table 1 provides examples of items in each category; Appendix 1 provides an example of the instrument layout. All items are rated on a 5-point ordinal scale that rates the extent to which (from “not at all” to “very great”) a specific MLS occurred within the observed treatment session. Higher total and category scores indicate greater extent of MLS use.

The MLSRI also contains 2 items comprising the category of carryover of practice rated on a categorical scale (yes, no, unable to rate). These items reflect whether the therapist recommends practice of specific tasks outside therapy time, and whether the therapist provides training to support this practice directly to a caregiver. These items are not included in the total score but are evaluated on their own to indicate the presence or absence of these MLSs.

A worksheet was used to track rater impressions while they watched the videotaped session and to document the frequency at which specific MLSs were observed (see Appendix 2 for an example of the worksheet layout). Immediately after observation of the video, the rater used the information from the worksheet as a guide to complete the MLSRI.

Back to Top | Article Outline

Data Analysis

Descriptive statistics were calculated for child and therapist demographic data. To standardize the scoring of the MLSRI, total and category scores were converted to percentages. To determine interrater reliability of the MLSRI for usual and VR interventions in this repeated-measures design, a generalizability theory16 approach was used. Generalizability theory allows researchers to estimate the variance per source,17 thus permitting the use of all data from both sessions for each child. A random-effects analysis of variance was used to estimate sources of variance and create g-coefficients (varying from 0.0 to 1.0) for each source of interest.18 G-coefficients are similar to ICCs,17 and can be compared with traditional benchmark values of 0.40 or below as low, 0.40 to 0.75 as moderate to good, and 0.75 and higher as excellent reliability.19 Confidence intervals, however, cannot be calculated. Because of nonparametric assumptions regarding independence of observations, κ values were calculated per session for interrater agreement for the MLSRI's 2 categorical items. Absolute reliability was evaluated by the standard error of measurement at the 95% confidence level and the Bland-Altman method to evaluate measurement bias for each intervention (usual and VR). A repeated-measures analysis of variance was used to determine main effects and interactions between raters, interventions, and occasions (ie, sessions 1 or 2) for all feasibility outcomes (ie, confidence, difficulty, and time to rate). SPSS version 17.0 was used for all analyses.

Back to Top | Article Outline


Participant Demographics

Eleven children and youth (7 male and 4 female) with ABI participated in the study. Children were between 8 and 18 years of age (mean [SD], 12.4 [3.4]). Ten had sustained a nontraumatic ABI (3 had a brain tumor, 7 had other etiologies). The average time since ABI was 12.18 months (SD, 3.92). One participant had a previously diagnosed ABI, 1 had a developmental disability, and 2 had learning disabilities. The Gross Motor Function Measure total mean score on admission to the center was 68.4% (SD, 34.4%). Four physical therapists participated in the study; each enrolled between 1 and 4 children. Therapists had a mean of 19.5 years (SD, 10.8) of experience of which a mean of 15 years (SD, 8.6) involved working with children and youth with ABI at this center. Each had 6- to 12-month experience using the Wii system.

Back to Top | Article Outline

MLSRI Data for Each Rater

Table 2 presents the mean scores for each rater within each intervention, and Table 3 presents the differences in these mean scores between raters for each intervention. The VR category demonstrated the greatest difference between raters' mean scores.

Back to Top | Article Outline

Interrater Reliability

G-coefficients for interrater reliability of the MLSRI total score were 0.81 for the usual interventions and 0.28 for the VR interventions. Standard error of measurement was 2.8% for usual interventions and 4.7 % for VR. Bland-Altman graphs suggest no systematic biases between raters in MLSRI scores for either intervention. G-coefficients, shown in Table 4 for the 6 categories of the MLSRI, varied from 0.36 to 0.65 for usual interventions and from 0.17 to 0.72 for VR interventions.

Back to Top | Article Outline

Feasibility of MLSRI Rating

Table 5 provides descriptive results of the feasibility outcomes summarized by rater and intervention. The repeated-measures analysis of variance showed no significant differences by rater, intervention, or occasions in difficulty completing the MLSRI. Rater 1 was more confident than rater 2 in completing the MLSRI (P = .05), and this effect was dependent on the intervention, such that it occurred with the VR ratings (P = .036). There was a significant main effect for difference between raters for time to complete the MLSRI, with rater 2 taking more time than rater 1 (P < .001), and also for the difference between interventions with VR taking less time to rate than usual interventions (P = .003). Usual interventions were an average of 34.5 minutes (SD, 7.5) long, whereas the length of VR interventions was an average of 14.5 minutes (SD, 5.6).

Back to Top | Article Outline


Comparison of the use of MLSs between usual and VR-based interventions requires a reliable and valid measurement instrument. This study builds upon initial intra- and interrater reliability investigations15 of the newly developed MLSRI, and evaluates and compares the interrater reliability and feasibility of the revised MLSRI between usual and VR-based interventions.

Back to Top | Article Outline

Usual Interventions

The excellent interrater reliability for usual sessions for the total score demonstrates that it is possible for different raters to consistently use the MLSRI to differentiate between observed MLS use within videotaped intervention sessions. The interrater reliability for the total score (g-coefficient, 0.81) is improved from previous testing with the original MLSRI with this population in which the ICC was 0.50.15 This improvement may be due to greater clarity in item definitions and/or more rater experience with the instrument. High total score reliability may support MLSRI use in research studies in which the goal is to understand differences in MLS application between different therapists, intervention approaches, or children. However, category score interrater reliability g-coefficients were only adequate, although they were improved in 3 of the 5 categories (instructions, practice, and conduct) as compared with the ICCs achieved in the previous investigation.15

The 2 categorical items demonstrated varying degrees of agreement across sessions. It was not always possible for the raters to identify whether a person in the videotape was a caregiver (item 30), and the nature of recommendations for task practice outside of therapy (item 31) may not have been defined clearly enough within the rater training materials. This latter item represents the motor learning variables of amount of practice and transfer/generalization to real-world tasks. In addition to revisiting rater training materials for these items, it will be important to consider whether they could be changed to the 5-point scale, as opposed to capturing presence or absence with a categorical “yes or no” response.

Back to Top | Article Outline

VR-Based Interventions

In comparison with usual interventions, interrater reliability for the VR intervention total score was poor. Because the VR intervention videotapes were of shorter duration than the usual components, there was less time for raters to observe therapists interacting with clients, undertaking different tasks, or demonstrating any of the actions or verbalizations relevant to the MLSRI. This difference in intervention length meant that raters had to make decisions based on fewer data points than were available for usual interventions. If VR was used in similar ways with all children at both time points, this would reduce both the intrasubject and the intersubject variance and contribute to the poor reliability findings. Understanding whether these data points themselves were homogeneous as compared with usual interventions requires an additional task analysis through review of the intervention videotapes.

A systematic pattern of differences was found between raters for VR interventions (ie, the mean scores demonstrate that rater 1 consistently awarded lower scores than did rater 2, except for the “guidance” category for both interventions). Differences between raters' mean scores (Table 3) illustrate that the most problematic categories of the MLSRI for VR interventions were “practice,” “conduct,” and “VR.” Despite the provision of VR-specific instructions with respect to item rating, several items on the MLSRI may be more challenging to rate for VR than usual interventions. For example, items within the “practice” category including “repetitive,” “whole (rather than part),” “variable (rather than constant),” and “progressive” may have been more difficult to rate when raters did not have a good understanding of which game was being played, when games were changed or when difficulty levels were progressed, or whether different games were of differing challenge levels. Videotapes only captured the child and therapist, not the television screen. The question of whether a single trial of a VR game could in itself represent variable practice (given the potential for needing to react in different ways to unexpected and changing stimuli) was not addressed during rater training. Items within the conduct category may also have been more challenging to rate for VR interventions where differences in games were difficult to capture or where fewer environmental resources may have been used.

The 3 “VR” category items are among the most subjective on the instrument, requiring raters to judge both child and therapist intent behind observed verbalizations, actions, or facial expressions. These are the only items that endeavor to capture how the therapist capitalizes on the purported motor learning attributes of the Wii system itself (ie, its visual or auditory information and the motivation that it provides). Although capturing whether or not the Wii features may be offering motor learning benefits is important, the results demonstrate that these items require clarification.

Back to Top | Article Outline

Implications for Clinical and Research Use of the MLSRI

Ultimately, with further refinements, the clinical potential of the MLSRI is in description and measurement of the motor learning content of interventions for children and youth with ABI and comparison of MLS use between different types of interventions. This can enhance our understanding of clinical practice in this area and allow exploration of whether using MLSs can influence the motor learning outcomes important to physical therapists, such as retention and transfer of skills learned in therapy to daily life activities.

The high interrater reliability for usual interventions suggests that the MLSRI could be used by trained PT raters in clinical practice. However, the raters in this study required a time-intensive training process, which may limit clinical feasibility and uptake. Whether or not therapists would require the same extent of training as the student raters used in this study, needs to be determined. In research, the instrument could be used to compare use of MLSs between different rehabilitation settings or between therapists. Regardless of context, the MLSRI requires responsiveness evaluation if it is to be used to measure change over time, for example, before or after a therapist takes part in a knowledge translation initiative about MLS use.

Issues with the reliability for rating VR interventions limit recommendations for use in this area. Further work with the instrument for these interventions is needed to address whether these issues relate to rater training or experience with VR, issues with the instrument, logistical issues with the videotapes, or the ways in which the therapists used the VR in this study.

Back to Top | Article Outline


Although the 2 raters had each achieved excellent intrarater reliability in a previous study,15 they were PT students who did not have a great deal of experience either providing or observing therapy sessions. Although a lack of preconceived opinions may have been a positive in terms of augmenting the influence of rater training, the lack of experience may have affected their ability to recognize some MLSs and to judge therapeutic intent of observed interventions if they were more subtle, perhaps causing them to question their judgment and leading to more variable ratings.

It is not possible to estimate reliability confidence intervals when using g-coefficients, and this prevents interpretation of precision of the reliability estimates.

The study's small sample size likely limited variance in the use of MLSs between therapists and between videotapes, which was compounded for VR interventions by their decreased duration. Capturing each client at 2 occasions during their rehabilitation was a strategy to address this, but it may be that therapists adopt a particular approach or style with an individual child or it may be that they have a particular approach or style in general that is invariant, regardless of the child. It is also possible that the time between the 2 occasions may not have been long enough to capture any changes in the child that would cause the therapists to use MLSs differently.

Finally, as new commercially available VR video games are developed and integrated into practice, it will be important to understand whether the VR-specific items are relevant to these new technologies.

Back to Top | Article Outline

Future Directions

To enhance rater training materials, results from this study will be used to revise item wording and definitions, and the study videotapes will provide additional examples illustrating range of MLS application of each item. Subsequent reliability investigations require larger sample sizes and greater diversity in therapists and practice settings. With further evidence of its psychometric properties, the MLSRI may be used to determine if MLS application within usual interventions is related to intervention outcomes or to child characteristics. Using the MLSRI to determine which MLSs are used most frequently in practice may inform research to specifically evaluate the effectiveness of those MLSs. As described earlier, further instrument refinement and evaluation will be undertaken for subsequent reliability investigations relating to MLSRI use to rate VR-based interventions. In general, little is known about how using VR influences therapist behavior and decision making. A greater understanding of this, including qualitative description of therapists' perspectives on VR use in practice,20 will contribute to refining the VR-specific items.

Back to Top | Article Outline


Exploring the use of MLSs is an important perspective to describe PT interventions for children and youth with ABI. The MLSRI, a newly developed instrument to quantify the use of MLSs in practice, demonstrated excellent reliability for usual interventions. Issues with rater training, instrument item relevance to VR interventions, and characteristics of the videotaped sessions had an effect on the reliability of the MLSRI to rate VR-based interventions. With further development of rater training materials and ongoing psychometric property testing, the MLSRI could be a useful tool to measure the MLS content of usual and VR-based interventions for children and youth with ABI.

Back to Top | Article Outline


The authors thank the therapists and children for participation and the 2 physiotherapy student raters, Priyanka Banerjee-Guenette and Megan Pfeiffer, for assistance. The authors also thank Susan Cohen (research assistant) and Dr Steven Hanna and Professor Paul Stratford for their assistance with data analysis.

Back to Top | Article Outline


1. Taylor HG. Research on outcomes of pediatric traumatic brain injury: current advances and future directions. Dev Neuropsych. 2004;25(1–2):199–225.
2. Dumas HM, Haley SM, Carey TM, Shen NP. The relationship between functional mobility and the intensity of physical therapy intervention in children with traumatic brain injury. Pediatr Phys Ther. 2004;16:157–164.
3. Haley SM, Baryza MJ, Webster HC. Pediatric rehabilitation and recovery of children with traumatic brain injuries. Pediatr Phys Ther. 1992;4:24–30.
4. Beaulieu CL. Rehabilitation and outcome following pediatric traumatic brain injury. Surg Clin North Am. 2002;82(2):393–408.
5. Teplicky R, Law M, Rosenbaum P, Stewart D, DeMatteo C, Rumney P. Effective rehabilitation for children and adolescents with brain injury: evaluating and disseminating the evidence. Arch Phys Med Rehabil. 2005;86(5):924–931.
6. Nudo RJ, Plautz EJ, Frost SB. Role of adaptive plasticity in recovery of function after damage to motor cortex. Muscle Nerve. 2001;24(8):1000–1019.
7. Whyte J, Hart H. It's more than a black box; It's a Russian doll: defining rehabilitation treatments. Am J Phys Med Rehabil. 2003;82(8):639.
8. Giza CC, Kolb B, Harris NG, Asarnow RF, Prins ML. Hitting a moving target: basic mechanisms of recovery from acquired developmental brain injury. Dev Neurorehabil. 2009;12(5):255–268.
9. Schmidt RA, Lee TD. Motor Control and Learning: A Behavioral Emphasis. 4th ed. Champaign, IL: Human Kinetics; 2005.
10. Schmidt RA. Motor learning principles for physical therapy. In: Lister MJ, ed. Contemporary Management of Motor Control Problems: Proceedings of the II-Step Conference. Fredericksberg, VA: Foundation for Physical Therapy; 1991:49–62
11. Levac D, Missiuna C, Wishart L, DeMatteo C, Wright V. Documenting the content of physical therapy for children with acquired brain injury: development and validation of the Motor Learning Strategy Rating Instrument. Phys Ther. 2011;91(5):689–699.
12. Babikian T, Asarnow R. Neurocognitive outcomes and recovery after pediatric TBI: meta-analytic review of the literature. Neuropsychol. 2009;23(3):283–296.
13. Deutsch JE, Borbely M, Filler J, Huhn K, Guarrera-Bowlby P. Use of a low-cost, commercially available gaming console (Wii) for rehabilitation of an adolescent with cerebral palsy. Phys Ther. 2008;88(10):1–12.
14. Saposnik G, Mamdani M, Bayley M, et al. Effectiveness of virtual reality exercises in stroke rehabilitation (EVREST): rationale, design and protocol of a pilot randomized controlled trial assessing the Wii gaming system. Int J Stroke. 2010;5:47–51.
15. Kamath T, Pfeifer M, Banerjee-Guenette P, et al. Reliability of the motor learning strategy rating instrument (MLSRI) for children and youth with acquired brain injury (ABI). Phys Occup Ther Pediatr. 2012;32(3):288–305.
16. Cronbach LJ, Nanda H, Rajaratnam N. The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. New York, NY: Wiley; 1972.
17. Mushquash C, O'Connor BP. SPSS and SAS programs for generalizability theory analyses. Behav Res Meth. 2006;38(3):542–547.
18. Boodoo GM, O'Sullivan P. Obtaining generalizability coefficients for clinical evaluations. Eval Health Prof. 1982;5:345–358.
19. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–174.
20. Levac D, Miller P, Missiuna C. Usual and virtual reality video game–based physiotherapy interventions for children and youth with acquired brain injuries. Phys Occup Ther Pediatr. 2012;32(2):180–195; doi: 10.3109/01942638.2011.616266.

adolescent; brain injuries/rehabilitation; child; clinical decision making; disabled children/rehabilitation; motor skills; physical therapy modalities; psychomotor performance; reproducibility of results; sensory feedback; therapy/computer assisted methods

© 2013 Lippincott Williams & Wilkins, Inc.