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Brain Sciences
  • Brief Report
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19 August 2022

Update on an Observational, Clinically Useful Gait Coordination Measure: The Gait Assessment and Intervention Tool (G.A.I.T.)

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1
Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, FL 32608, USA
2
Department of Physical Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32608, USA
3
Department of Neurology, School of Medicine, Case Western Reserve University, Cleveland, OH 44108, USA
4
Brain Plasticity and NeuroRecovery Laboratory, Cleveland VA Medical Center, Cleveland, OH 44106, USA
This article belongs to the Special Issue Underlying Mechanisms and Neurorehabilitation of Gait after Stroke

Abstract

With discoveries of brain and spinal cord mechanisms that control gait, and disrupt gait coordination after disease or injury, and that respond to motor training for those with neurological disease or injury, there is greater ability to construct more efficacious gait coordination training paradigms. Therefore, it is critical in these contemporary times, to use the most precise, sensitive, homogeneous (i.e., domain-specific), and comprehensive measures available to assess gait coordination, dyscoordination, and changes in response to treatment. Gait coordination is defined as the simultaneous performance of the spatial and temporal components of gait. While kinematic gait measures are considered the gold standard, the equipment and analysis cost and time preclude their use in most clinics. At the same time, observational gait coordination scales can be considered. Two independent groups identified the Gait Assessment and Intervention Tool (G.A.I.T.) as the most suitable scale for both research and clinical practice, compared to other observational gait scales, since it has been proven to be valid, reliable, sensitive to change, homogeneous, and comprehensive. The G.A.I.T. has shown strong reliability, validity, and sensitive precision for those with stroke or multiple sclerosis (MS). The G.A.I.T. has been translated into four languages (English, Spanish, Taiwanese, and Portuguese (translation is complete, but not yet published)), and is in use in at least 10 countries. As a contribution to the field, and in view of the evidence for continued usefulness and international use for the G.A.I.T. measure, we have provided this update, as well as an open access copy of the measure for use in clinical practice and research, as well as directions for administering the G.A.I.T.

1. Gait Coordination Importance and Definition

There have been important discoveries of brain and spinal cord mechanisms controlling gait coordination (e.g., [1,2,3,4,5,6,7]). Additionally, there is growing evidence identifying the neural pathologies and resulting impairments underlying gait dyscoordination after stroke and other neurological diagnoses, and their response to treatment (e.g., [8,9,10,11,12]). For stroke, these include description not only of the disruption of neural control, but its manifestation in terms of gait dyscoordination, for example, abnormal co-contractions [13] and interference with the normal coordinated interactions of the mechanical energetics of the lower limbs [14].
Based on the available discoveries, there is a greater ability to construct more efficacious gait coordination training paradigms for those with neurological injury or disease. With new interventions targeted at improving the neural drive of gait coordination, it is critical in these contemporary times to use the most precise, sensitive, homogeneous (i.e., domain-specific [15]), and comprehensive measures available [16,17] to assess both gait coordination itself, as well as its underlying domains of strength, limb joint coordinated movement, coordination of muscle co-contractions, proprioception, and balance [18,19,20]. Indeed, others have called for and suggested a standardized set of assessment measures [21], but pertaining to gait coordination, this most recent suggestion was limited to only an incomplete gait measure [16,17].
Gait coordination is defined well by Krasovsky and Levin [22], page 213, as follows:
“Locomotor coordination is a context-dependent property of the motor system, having both spatial and temporal components. Spatial coordination is the relationship between the position of different body segments or joints, whereas temporal coordination is the relative timing between segment or joint positions throughout the task. These components are never mutually exclusive……”
Therefore, an example of a gait coordination measure is ‘knee flexion angle at toe-off’. In this example, the spatial component is knee flexion angle and the temporal component is the gait event time of toe-off. Without both the spatial and temporal components simultaneously being performed, there is no measure of coordination. The technology-based gold standard of gait coordination measurement and force production includes gait kinematics and gait kinetics, customarily measured using motion capture and force plate systems in well-equipped gait research laboratories [23]. Studies have shown that gait kinematics is an important quantitative measure of gait coordination and is associated with observed abnormal co-contractions after stroke, causing gait dyscoordination [24].

2. Observational Gait Coordination Scale with Precision, Sensitivity, Reliability, Validity, Homogeneity, and Comprehensiveness

In clinical practice and in some gait research settings, there is no access to such technology. Furthermore, the time constraints of clinical practice make it impractical to utilize this instrumented technology in its current form due to the labor-intensive process of collecting and analyzing the data. However, observational gait coordination measures can be used in that case. The ideal observational gait coordination measure would be constructed according to the following characteristics:
Homogenous, that is, all items measuring gait coordination/dyscoordination, according to the above definition of coordination, and no items assessing compensatory strategies.
As comprehensive as possible, that is, measuring as many coordination joint movements and other gait components as possible.
Numerical scoring scheme overall, and per item, with score numbers within an item assigned across levels of dyscoordination.
Good psychometrics (e.g., reliability, validity).
Good sensitivity in measuring the recovery of gait coordination, both endogenous and in response to treatment.
Practical, with a reasonable scoring time and the use of equipment available in most clinical settings.
Two separate research groups conducted a review of observational gait measures [16,17]. They concluded that the Gait Assessment and Intervention Tool (G.A.I.T.) was the most suitable scale for both research and clinical practice compared to other observational gait scales, since it has been proven to be valid, reliable, sensitive to change, homogeneous, and comprehensive (Table 1 and Table 2). Since that time, the developers of the G.A.I.T. have received requests and notices indicating that clinicians and researchers are using the G.A.I.T. in the following countries: Turkey, Slovenia, Italy (three separate users), Korea, India (two separate users), Australia (two separate users), Columbia, Spain, Thailand, and the U.S. Additionally, the G.A.I.T. has been translated into the following languages: Spanish [25], Taiwanese [26], and Portuguese (translation is complete, but not yet published).
Table 1. Gait Assessment and Intervention Tool (G.A.I.T.)
Table 2. Directions for Administration of the Gait Assessment and Intervention Tool (G.A.I.T.).

3. Use of G.A.I.T. for Those with Stroke

The G.A.I.T. psychometrics were originally tested in stroke survivors. The G.A.I.T. was constructed with items measuring the spatial coordinated movement components of gait (movement excursion), that occur at specified temporal events of stance and swing phases of the gait cycle. Within each item of the measure, deviation from normal coordination is scored at multiple levels of dyscoordination. Psychometrics were studied and found to be good, according to intra-rater reliability (intraclass correlation (ICC) = 0.98; p = 0.0001; 95% confidence interval (CI)= 0.95–0.99), and inter-rater reliability (ICC = 0.83; p = 0.007; 95% CI = 0.32–0.96), including between an experienced and an inexperienced clinician (ICC = 0.996; p = 0.0001; 95% CI = 0.986–0.999) [27]. The G.A.I.T. showed measurement sensitivity in identifying a difference between two treatment groups in the recovery of gait coordination from pre- to post-treatment (that is, the G.A.I.T. showed that group 1 had a significant additive effect (parameter statistic = 1.10, p = 0.045, 95% CI= 0.023–2.18)) [28].

4. MCID

Very recently, two independent groups have estimated the minimal clinically important difference (MCID) for the G.A.I.T. in stroke survivors [29,30]. In a group of subacute patients (mean time since stroke was 45 days), a change in the G.A.I.T. score between 1.5 and 4 points was deemed the MCID value [29]. In a study of chronic stroke, the G.A.I.T. scores were well correlated to the Functional Ambulation Category (FAC) measure (r = 0.73; [30]. In that study, the G.A.I.T. was studied for MCID according to two anchors, the FAC and the speed-based functional categories of household, limited community, or full community ambulation [31]. They proposed the following G.A.I.T. MCID value: 11.8 points related to FAC (Functional Ambulation Category) level 3 or household ambulator gait classification; and 5.19 points related to FAC levels 4 and 5, or limited community ambulator, or full community ambulator classification [30]. In this particular study [30], the G.A.I.T. was scored bilaterally and averaged, which is a novel approach to the utilization of the measure; this procedure may have influenced the value of the MCID by diluting (averaging out) any improvement in the paretic limb and thus resulting in a higher calculated MCID. Given its advantageous characteristics [16,17], additional analyses to interpret the MCID value levels for meaningful change according to the G.A.I.T. are warranted; at the same time, these current studies are an important contribution to the field.

5. Use of the G.A.I.T. for Those with MS

Recently, the G.A.I.T. psychometrics were studied for those with multiple sclerosis (MS). Construct validity was tested [32]. The results showed a high construct validity, with correlations between the G.A.I.T. and the Rivermeade Gait Assessment (RVGA) at r > 0.90, and ranging in correlation with the Tinetti Gait Scale (TGS) from −0.62 to −0.59. We should note, in this regard, that in prior work, the authors of [17] compared the G.A.I.T. versus other gait measures such as the RVGA and TGS, and found the G.A.I.T. to be the most suitable scale for stroke survivors for both research and clinical practice compared to the other observational gait scales, since it has been proven to be valid, reliable, sensitive to change, homogeneous, and comprehensive. Further, for the MS population, they found that correlations were lower for scales that included speed, such as the Timed Up and Go Test. Reliability of the G.A.I.T. was high for use with those with MS (intraclass correlation coefficient for the intra-rater reliability, e.g., r = 0.91; 95% CI 0.85–0.95 for the right side; and inter-rater reliability, e.g., r = 0.91 (95% CI 0.85–0.95) for the right side) [33].

6. Contribution to the Field

In view of the evidence for the continued usefulness and international use for the G.A.I.T. measure, we have provided this update, as well as an open access copy of the measure for use in clinical practice and research (Table 1). We are also providing the prior published directions for administering the G.A.I.T., enhanced with additional information obtained from its continued use (Table 2).

Author Contributions

J.J.D.: literature review, interpretation, writing first draft, editing last draft. J.P.M.: literature review, interpretation, draft editing; M.D.G.-G.-F.: editing; and J.C.N.: review, editing, and leader of the original measure construction. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Veterans Health Association (VHA), National Research and Development (ORD), and the Office of Rehabilitation Research and Development (RR&D), Grants: B2226R; A3102R; B2261S.

Institutional Review Board Statement

No subjects were studied for this report.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors have no conflict of interest.

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