Lateral ankle sprains are consistently among the most common injuries observed in physically active populations, including high school and collegiate athletes, and the military.1–4 Although once considered a benign injury causing only a small loss of time from activity, the past several decades have established this injury as the first in a cascade that has the potential to contribute to decreased health-related quality of life.5,6 Most commonly described following ankle injury is the development of chronic ankle instability (CAI)—repeated sensations of “giving way” or “rolling” of the ankle, often associated with recurrent injury.7,8 Chronic ankle instability has been associated with several detrimental consequences that include decreased physical activity9 and the early onset of posttraumatic ankle osteoarthritis.10,11 Furthermore, the combination of recurrent injury and degenerative changes to the joint associated with CAI represents a significant financial burden on the health care system, estimated to cost 6.2 billion USD per year.5,12
The current standards of clinical practice rely on self-reported questionnaires in order for clinicians and researchers to determine whether patients or participants meet the criteria of having CAI.13 A wide variety of questionnaires are implemented, with questions ranging from asking individuals to estimate the number of giving-way episodes they experience, to rating any pain or difficulty in performing varying functional task related to sports or activities of daily living.14–17 Although these tools have proven useful, they have limitations related to their subjectivity and patient interpretation of questions (eg, individual understandings of giving way).16 The reliance on solely subjective measures of ankle function to diagnose individuals as having CAI is in stark contrast to similar models of knee instability that rely not only on subjective questionnaires, but also on a combination of special and functional tests to characterize sensations of giving way.18 For instance, various hop tests, including a triple-hop for distance, have been used to discriminate functional status for patients who have experienced a rupture of the knee's anterior cruciate ligament.19 However, a similar set of standardized tests have not been documented with regard to their efficacy in discriminating individuals with CAI.
An abundance of research has been conducted to determine functional deficits, such as strength,20 proprioception,21 balance,22 and functional kinematics23 between patients with CAI and healthy participants, as well as those who have successfully “coped” after injury.24 However, the majority of these tests require the use of advanced equipment including isokinetic dynamometers, force plates, and motion capture systems to differentiate these individuals. Clinical practitioners would benefit from noninstrumented clinical tests, such as functional performance tests (FPTs), to determine the functional ability of patients with suspected CAI. These FPTs have the advantage of being inexpensive, quick to administer, and accessible in clinical and field settings, with examples including single-leg heel and toe raises, noninstrumented balance tests, and hopping tasks. A simple outcome measurement that could include time in position or to completion of a task, distance moved, or number of repetitions in a given time allow for standardized measures that can be compared across patients and at numerous time points throughout a patient's rehabilitation.
To date, investigations into FPTs in chronically unstable ankles have largely consisted of hopping tests that require large degrees of lateral movement, as well as noninstrumented tests of balance, such as the Star Excursion Balance Test (SEBT). However, a large degree of differences in methodology, outcome measures, and results have served as a clear barrier toward the implementation of these potentially useful tests in clinical practice.25 A comprehensive summary of the findings in this area will allow health care providers to make evidence-based informed decisions related to functional performance testing to aid the diagnosis of—and track the rehabilitation for—patients with CAI. Therefore, the purpose of this systematic review with meta-analysis was to search the available literature to identify studies that implemented FPTs to differentiate patients with CAI from healthy controls and to perform a quantitative and qualitative appraisal of the methodology and findings reported throughout these investigations. These findings may, therefore, provide estimates regarding the effect sizes for varying FPTs for discriminating CAI, providing guidance to clinicians regarding which tests may best be implemented in practice.
This systematic review and meta-analysis was completed in a manner in accordance with recommendations made in the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement (see Supplemental Digital Content 1, http://links.lww.com/JSM/A161).26
An electronic database search was initially conducted by 2 of the coauthors (J.K. and A.R.N.) on National Library of Medicine Catalog (MEDLINE/PubMed), the Cumulative Index for Nursing and Allied Health Literature (CINAHL), and the SPORTDiscus, from inception to June 2017. The initial key terms search consisted of exactly “Functional Performance Test*” OR “Dynamic Balance Test*” OR “Postural Stability Test*” OR “Star Excursion Balance Test*” OR “Hop Test*” AND “Ankle Instability” OR “Ankle Sprain.” Key terms searched were determined from our purpose and research question and confirmed by all investigators before conducting the search.
Inclusion and Exclusion Criteria
All articles included in the systematic review and meta-analysis met the following inclusion criteria: (1) written in the English language; (2) research conducted on human participants; (3) studies must use a FPT that involves hopping, landing, agility, and/or noninstrumented balance assessment; and (4) studies must include a group comparison between patients with CAI and healthy controls. Although studies would preferably adhere to identifying CAI individuals in accordance with standards put forward by the International Ankle Consortium,13 many articles were published before this criteria. Therefore, participants in the experimental group must have enrolled those with a history of at least 1 ankle sprain with subsequent complaints of rolling or giving way identified through self-reporting or use of a patient-reported outcomes, consistent with criteria related to functional or CAI.27 Research studies were excluded if they used the uninjured limb as a comparison, or if functional testing required instrumentation such as force platforms, electromyography, and other biomechanical data as primary outcome measures.
Data Extraction and Analysis
After the initial search was conducted using the aforementioned key terms, duplicates from across the databases were removed. The titles and abstracts were then inspected for relevance to the inclusion and exclusion criteria, followed by obtaining full-text manuscripts for those identified. Post–full-text retrieval manuscripts were further scrutinized for inclusion and exclusion criteria, and the reference lists of each were cross-checked for additional manuscripts. A consensus among all the authors was then sought for the final inclusion of manuscripts.
Manuscripts were then evaluated separately by 2 authors (A.B.R. and A.R.N.) for their methodological quality via the 22-item checklist for observational studies put forth by the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) statement.27 STROBE scores were averaged across all studies and assessed as a percentage. Studies were also assessed for their level of evidence based on the Oxford Centre for Evidence-Based Medicine's 2011 guidelines.28 Disagreements in scoring were resolved with a consensus between the 2 authors; if a situation arose where a consensus was not able to be achieved, the third author was consulted.
Numerical data extracted included the sample sizes and outcome measures for each FPT by group. A single investigator (A.B.R.) conducted all effect size calculations through Comprehensive Meta-Analysis (V3.3.070; Biostat, Inc, Englewood, New Jersey). Effect sizes were calculated using the standardized mean difference for each of the outcome measures adjusting for small sample bias (Hedges g).29 Because of the uncertainty of evaluating a homogenous population, a mean effect size ([INCREMENT]) was determined using a random effects model, if 3 or more studies evaluated a similar FPT.30 Further tests were calculated to determine whether heterogeneity existed by assessing the I2 and the Q-statistics. Finally, fail safe N was determined to evaluate the potential number of unpublished studies that would bring the value to a level of insignificance for each of the mean effect sizes.30
Figure 1 provides a flow chart of the article retrieval. Nine hundred ninety-six manuscripts were identified by the initial search terms across the databases and after duplicate removal, 479 remained. After title and abstract screening, 433 articles were excluded whereas 46 remained and their full texts were retrieved. Seven additional manuscripts were then identified by cross-checking the reference lists of the full-text manuscripts. Twenty-four of these articles were then excluded: 14 for assessing only instrumented or biomechanical data, 6 not comparing against a control group, 3 not having an experimental CAI group, and 1 being repetitive data from a previous study. Ultimately, 29 manuscripts were assessed, 7 were cross-sectional studies, 21 were case-control, and 1 was a randomized-control trial (Table 1). Correspondingly, the studies were deemed levels 2, 3, and 4 evidence, respectively. Only 4 disagreements in the STROBE scoring were needed to be resolved via a consensus and most often, disagreements occurred regarding whether the experimental design, participant demographics, or results were stated with enough detail. The average STROBE score across the evaluated studies was 17.3 ± 1.6 of a possible 22 (see Table, Supplemental Digital Content 2, http://links.lww.com/JSM/A162). In total, 97 individual effect sizes for FPTs' were calculated, as well as 11 overall mean effect sizes. Altogether, across the 29 studies, 1317 participants were surveyed, with 680 participants having CAI and 637 control participants.
Pooled effect sizes were calculated for the most common FPTs that included the single-limb timed-hopping tests (n = 9),31–39 the single-limb side-hop test (n = 7),32,34,36–40 all directions of the star-excursion balance test (n = 15),36,40–53 the single-limb hop test for distance (n = 3),34,37,39 the multiple-hop test (n = 3),54–56 and the foot-lift test (n = 3).36,40,57 Although some studies reported several different timed-hop tests, a single timed-hop test was chosen from each available study based on a similarity to limit the influence of individual studies on the mean effect. The figure-of-8 hopping test was the most common test (n = 6)32,34,36−39 included in the single timed-hopping tests mean effect, whereas the other 3 studies reported FPTs described as the single-limb hopping test,31 hopping test,33 and single-leg jump landing test,35 respectively.
The distribution for all unweighted effects calculated are shown in Figures 2–4 and see Figure, Supplemental Digital Content 3, http://links.lww.com/JSM/A163. Mean effect and their 95% confidence intervals, tests for homogeneity, and fail safe N calculations are shown in Table 2. The single-limb side-hop (g = −2.314, P = 0.001), timed single-limb hop tests (g = −1.056, P = 0.009), multiple-hop test (g = 1.399, P = 0.001), and foot-lift test (g = −0.761, P = 0.020) had large, significant mean effects across the included studies; whereas the SEBT-AM (g = 0.326, P = 0.022), SEBT-M (g = 0.369, P < 0.006), and SEBT-PM (g = 0.406, P < 0.001) directions demonstrated small to moderate, significant main effects. The single-hop (g = 0.033, P = 0.859), SEBT-A (g = 0.264, P = 0.051), SEBT-PL (g = 0.056, P = 0.599), SEBT-AL (g = 0.246, P = 0.116), SEBT-P (g = 0.232, P = 0.137), and SEBT-L (g = 0.253, P = 0.105) were not significant between groups. The timed hop and side-hop tests had relatively high Q, I2, and fail safe N values. Funnel plots for the single-limb hop, SEBT and foot-lifts tests are located in Supplemental Digital Content 4, 5, and 6 (Figures 5 and 6, see Figures, Supplemental Digital Content 4–6, http://links.lww.com/JSM/A164; http://links.lww.com/JSM/A165; http://links.lww.com/JSM/A166).
Other FPTs reported in the literature included the agility hop test (g = −0.039),58 Balance Error Scoring System (BESS) (g = −1.026; −0.696),36,59 co-contraction test (g = −0.235), Japan test (g = 0.670),35 shuttle run test (g = −0.114),58 single-limb hurdle test (g = −3.748; −0.168),31,37 6-m crossover hop test (g = −3.484),32 square hop test (g = −13.256; −3.416),32,37 time-in-balance test (g = 0.898; −0.362),36,40 triple-crossover hop (g = −0.256),39 and the up-down hop test (g = −0.609).34 Descriptions of individual FPTs are shown in Table 3.
The purpose of this systematic review with meta-analysis was to synthesize the literature to determine the relative effectiveness of various FPTs in differentiating between those with CAI and healthy individuals. The most effective FPTs to discriminate those with CAI, in descending order based on the magnitude of the pooled effect size, are the side-hop test, the multiple-hop test, timed-hop tests, foot-lift test, and the 3 directions of the SEBT, respectively. The single-hop test for distance seems to be an ineffective FPT in CAI populations, whereas a multitude of other FPTs lacked sufficient evidence to determine effectiveness although presented promising initial findings.
Single-Limb Hop Tests
The single-limb side-hop and timed-hop tests provided the best clinical utility to identify those with CAI demonstrating large effect sizes. Although both tests are timed, the side-hop demonstrated greater utility than other single-limb timed-hopping tests such as the figure-of-8. It may be hypothesized that hopping tests that challenge an individual directly in the frontal plane would provide an additional challenge for patients with CAI, than challenging individuals directly in the sagittal plane The side-hop test is performed by completing 10 medial–lateral single-limb hops for a total of 20 jumps as quickly as possible, a movement occurring directly in the frontal plane. By comparison, the timed-hop tests are typically through a course such as the figure-of-8 that incorporates both sagittal and frontal plane aspects. Perhaps, the medial–lateral stress placed on the joint is more effective to disrupt those with CAI compared with frontal plane tasks. Although no studies have quantified the direct stress on the lateral ligament complex during these tasks, it has been revealed that the side hop requires a significant amount of peroneus longus activation, of which patients with CAI may be deficient. Nonetheless, both seem to be effective at discriminating those with CAI.60,61
However, of some concern pertaining to the side-hop and timed-hop tests is the funnel plots (Figures 5 and 6, see Figures, Supplemental Digital Content 4–6, http://links.lww.com/JSM/A164; http://links.lww.com/JSM/A165; http://links.lww.com/JSM/A166), and the heterogeneity statistics analyses indicate there may be some variations among the included studies. Driving these values was a study by Sharma et al,37 which had a significant influence on the mean effect size. Although this study substantially influenced the effect sizes, when removing this particular outlier, the mean effect sizes for both tests remain moderate-large and significant (side-hop: g = −1.444, P = 0.022; timed-hop: g = −0.446, P = 0.027). It is difficult to ascertain why this study in particular had such a massive individual effect size; however, one possible explanation is that the authors dichotomized their instability group by those with CAI who reported giving way during the test and those who did not.37 The group reporting giving way was used for the meta-analysis, and perhaps this drove the large effect sizes. Thus, using FPTs in those with CAI with those who report feeling unstable during their performance may be much more likely to identify those with CAI compared with their healthy counterparts or those who self-report CAI yet fail to report instability during the FPT.
Several other hopping tests may also provide adequate discriminative ability yet have only been reported by 1 or 2 studies. The single-limb hurdle test, 6-m crossover hop test, square hop test, and up-down hop test also demonstrated moderate-large individual effect sizes. Each of these tests are similar to the timed-hop tests, as they each require the participants to perform a task or course as fast as they can on a single limb. The greatest differences exist regarding the amount of vertical, lateral, or forward movement across tasks. However, the relative effectiveness of these tasks, although less studied than the single-limb side-hop or figure-of-8, suggests that tests that require components of speed, power, and agility in a combination of planes will serve to differentiate patients with CAI. These findings are consistent with several theories behind CAI that suggests a multifaceted problem affecting multiple functional abilities.61,62 Thus, including a timed-hop test such as the side-hop or figure-of-8 test during evaluation of individuals with CAI is valid and appropriate.
Interestingly, based on the results of the meta-analysis, the single-hop jump for distance does not differentiate those with CAI from healthy controls. The single-hop jump is much different than the timed-hop and side-hop jump testing because of the fact that it assesses and requires greater muscular strength and power rather than speed and agility. Although interesting, this negative result is rather unsurprising because of the evidence that the role of ankle strength in CAI is widely disputed and equivocal.63–68 Furthermore, this test stresses the joint primarily in the sagittal plane, rather than the frontal and transverse planes that would be more difficult for patients with CAI. Similarly, another primarily uniplanar test that was studied by only 1 group, the triple-crossover hop test demonstrated a small effect size. The triple-crossover hop test such as the single-limb hop for distance requires participants to jump as far as possible, but in this test it is the maximum distance after 3 jumps across a 15-cm line. Although the incorporation of a crossover adds a lateral component, the test outcome is primarily the distance advanced in the forward direction. Therefore, using FPTs in those with CAI that require muscular power within the sagittal plane seems to be ineffective compared with agility-based hopping tests.
A third class of hopping tests observed in this review were those requiring individuals to hop across a pattern, scoring individuals on “errors” rather than a measure of time or distance. The multiple-hop test across 3 studies demonstrated a large pooled effect with the rest demonstrating conflicting results according to effect size calculations. Although similarly requiring the functional ability of muscle strength, power, and agility to perform hops, an additional component of postural stability is added by scoring individuals on their ability to “stick” a landing. Although intriguing, this does require a degree of subjectivity for the assessor that may serve to bias results. Similar measures exist throughout the CAI literature using instrumented measures derived from force plates. Moderate evidence exists establishing diminished postural control during hopping as quantified through the dynamic Postural Stability Index.69–72 However, this measure relies on precise force calculations with differences between uninjured and injured individuals often not grossly visual to an assessor. As conflicting results exist using noninstrumented measures, additional studies are necessary to determine the ability of FPTs using error systems during hop landing to discriminate between healthy and CAI individuals.
The SEBT, depending on the direction, also provides adequate discriminative ability between those with without CAI. The anteromedial, medial, and posteromedial directions each demonstrated moderate mean-effect sizes; however, the anterior and posterolateral directions were small and considered unimportant. Based on these results, those with shorter anteromedial, medial, and posteromedial reach distances are more likely to have CAI. This could potentially be explained by considering the shifts in the center of gravity occurring through reaches in medial direction, causing tensile forces to be applied on the lateral ankle. A previous systematic review has also been completed on the SEBT73; however, the authors chose not only CAI, but other pathologies such as ACL injuries. In addition, studies were included that assessed the injured compared with uninjured limbs as well as CAI compared with controls. Although the authors similarly concluded that the SEBT was an effective FPT in those with CAI, their study did not resynthesize data to determine mean effects, nor was their main purpose to identify the differences in the SEBT across CAI populations. Based on the current results, not all directions of the SEBT have similar prognostic ability as the anteromedial, medial, and posteromedial directions provided the best clinical utility. Although this is not a particularly new finding, some previous studies have attempted to address this by simplifying the SEBT to the Y Balance Test, which includes only the anterior, posteromedial, and posterolateral directions.74,75 However, it seems that the anterior direction may not be as sensitive enough to differentiate between controls, and CAI and clinicians should consider the anteromedial, medial, and posteromedial directions specifically for individuals with CAI.
Balance and postural control deficits are often described in those with CAI, which could potentially contribute to functional performance deficits observed during the SEBT.50,70,72,76,77 Although the SEBT is considered a dynamic postural control task, requiring movement of the body over a stationary base of support, additional clinical tests are used to assess static postural control. The foot-lift test (counting the number of times a part of the foot lifts off the ground) seems to be an adequate discriminating test, whereas the time-in balance36 also demonstrated large effects in a single study. The BESS—an error system identifying gross instability during 3 to 6 stance conditions—was reported in 2 studies36,59 and demonstrated a moderate-large effect size between CAI and control participants. These findings suggest that FPTs requiring an individual to maintain static postural control are able to yield similar results as seen in studies using advanced equipment such as force plates.
No studies provided a direct comparison between abilities of hopping tests and balancing tests in discriminating CAI. As previously stated, these assess different components of ankle function with the former addressing muscular strength, power, and agility and the latter assessing proprioception and neuromuscular control. Given these different components, it may be recommended that both hopping- and balance-based measures be included in the assessment of patients with CAI. Although these would combine yield very high effect sizes and a strong ability to predict functional instability in these patients, there are additional components that should be considered. Dorsiflexion deficits are consistently observed in those with CAI.78–80 To some extent, this may be assessed through the anterior reach of the SEBT, as a recent study found that dorsiflexion range of motion, eversion strength, and time-to-boundary contributed most to SEBT reach distances.77 However, further studies assessing dorsiflexion range-of-motion through simple tests such as the weight-bearing lunge should be considered.79
The included studies in the systematic review were case–control and cross-sectional studies, described as level IV and III evidence, respectively, indicating limited methodological quality. In addition, the average STROBE score indicates relative consistency in the methodological quality of the evidence. With a maximum of 22, the average score as a percentage was 78.6% ± 7.3%. The 2 most common faults were no indication of addressing sources of bias, including blinding procedures as well as providing a sample size justification. Other notable sources of demerits included providing information related to distributive statistics, funding sources, and indications of study design early in the manuscript. Improving methodological quality and study design stands to greatly improve FPT evidence. Because of these differences in reporting only pooled effect sizes were able to be calculated as opposed to cutoff scores for individual tests. Future studies may want to better identify and address systematic ways to improve the quality of manuscripts to elevate the literature.
Across the studies, there was also inconsistent reporting of inclusion and exclusion criteria making comparisons difficult. In 2013, recommendations put forth by the International Ankle Consortium established guidelines for reporting populations of individuals with CAI; however, many of these studies predated these recommendations and therefore did not provide information necessary to understand these populations. One notable point of caution that should be added is that most of the studies included in the analysis were conducted on relatively physically active individuals. This is because most of the research on CAI is conducted by sports medicine specialists. Whether these results apply to more sedentary populations is unknown. Thus, additional CAI research may want to focus on nonphysically active populations. It remains possible that different measures may better apply to different populations.
Other limitations include the sample size of both the included studies and the total number of studies included in this meta-analysis. The sample sizes of the studies themselves limit their statistical power and generalizability of the effects found. Larger samples would provide superior evidence for the use of FPTs in those with CAI. The total number of studies also limits the effects of this meta-analysis. As reported, many of the FPTs have only been assessed in 1 or 2 limiting the ability to perform a meta-analysis on those individual tests. In addition, pertaining to the SEBT anteromedial and posteromedial directions, the estimates for the fail-safe N calculations indicate that publication bias may be present with 4 additional publications necessary to negate the present results.81 Although this is concerning for the SEBT, the fail-safe N calculations for the timed-hop and side-hop calculations are very high, indicating strong, stable effect sizes. This provides evidence that more studies with larger samples need to be conducted to properly evaluate the alterations in muscle activation strategies during jump landing activities in those with CAI.
Level B evidence exists suggesting that the side-hop, timed-hopping, multiple-hop tests, and foot-lift test are able to discriminate between those with CAI and healthy individuals. Level B evidence also exists suggesting that the medial, anteromedial, and posteromedial components of the SEBT are similarly able to differentiate. Although a multitude of additional tests exist presenting a wide range of effect sizes, it seems that those tests that include timed measures of lateral hopping and those quantifying balance may have clinical utility. Recent evidence suggests that combining the results of multiple FPTs has greater clinical utility than singular tests.40 Specifically, a combination of a version of the side-hop test and SEBT displayed the greatest clinical utility. However, limited research is available to corroborate additional tests, and a more comprehensive assessment of FPTs may be necessary to determine the best combination of FPTs to assess CAI.
These tests present an advantage to clinicians aiming to address functional deficits in patients with CAI as they are cheap, effective alternatives compared with instrumented measures. However, further research is necessary to aid in the full implementation of these tests clinically. Greater sample sizes and study volume would improve on evaluation methods and decrease publication bias to more appropriately determine clinical measures to assess those with CAI. Furthermore, consistency in test implementation must be encouraged to calculate precise protocols and cutoff scores that may improve clinical utility. Last, it remains largely unknown in which ways the current treatment methods may serve to modify these values, affecting the implementation of these measures through patient rehabilitation.
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