Effect of osteoarthritis on accuracy of continuous tracking leg movement.

Perceptual & Motor Skills: Motor Skills & Ergonomics 2014, 118, 1, 162-182. © Perceptual & Motor Skills 2014

EFFECT OF OSTEOARTHRITIS ON ACCURACY OF CONTINUOUS TRACKING LEG MOVEMENT1, 2 ELIZABETH MAE WILLIAMSON

PHILIP H. MARSHALL

Missouri State University Springfield, Missouri

Texas Tech University Lubbock, Texas

Summary.—The purpose of this study was to establish if osteoarthritis in older adults was associated with ability to accurately and continuously track leg movement in a model of therapy to improve age-related impairments of proprioception, kinesthesia, and coordination of muscles at the knee joint. 24 older adults without osteoarthritis and 24 older adults with osteoarthritis participated. Software generated a moving, on-screen sine wave and a vertically traveling disc. Participants attempted to keep the disc on the sine wave by bending and straightening the leg. Older adults without osteoarthritis performed better than older adults with osteoarthritis in one of two conditions. There was a relationship between osteoarthritis and reduced accuracy of leg movement. Further research will be required to specifically define this relationship and to establish if such interventions to improve accuracy of knee movement will positively affect functional capabilities of individuals with osteoarthritis.

Examination of motor control of the knee in individuals with osteoarthritis is of particular value since osteoarthritis of the knee is present in approximately 80% of the population over age 65 (Burckhardt, 1990). In 2002, 350,000 individuals with osteoarthritis underwent primary total knee replacement procedures, and 29,000 individuals underwent revision procedures due to end-stage osteoarthritis of the knee (Mahomed, Barrett, Katz, Baron, Wright, & Losina, 2005). As one of the most common orthopedic procedures performed in the United States, total knee replacements represent significant societal expense. In addition to surgical costs, in a study completed by a health delivery company, costs for medications were 102% greater for individuals with osteoarthritis than individuals without osteoarthritis (Mapel, Shainline, Paez, & Gunter, 2004). Sharma and Pai (1997) proposed that osteoarthritis is due, in part, to a series of events: (1) development of an age-related proprioceptive and kinesthetic impairments of the knee joint; (2) proprioceptive and kinesthetic Address correspondence to Elizabeth Williamson, Department of Physical Therapy, Missouri State University, 901 South National Ave., Springfield, MO 65897 or e-mail (ewilliamson@ missouristate.edu). 2 Software development was funded by the Dean of the School of Allied Health Services, Texas Tech University Health Science Center, Lubbock Campus and completed by Advanced Motion Measurement of Phoenix, Arizona. The study was supported by the Texas Society of Allied Health Professionals. No member of the above organizations contributed to the design of the study; the collection, analysis and interpretation of data; the writing of the manuscript; or the decision to submit the manuscript for publication. 1

DOI 10.2466/25.26.PMS.118k14w9

12-PMS_Williamson _140008.indd 162

ISSN 0031-5125

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impairments of the joint then leads to altered spatial and temporal activation of the muscles controlling the joint during movement; (3) altered spatial and temporal activation of the muscles around a joint reduces accuracy of movement; (4) reduced accuracy results in abnormal load distribution over the joint during functional activities; and (5) over time, these abnormal loading forces lead to arthritic changes within the joint. The first two events, altered proprioception and kinesthesia and coordinated movement of the knee, are supported in the literature. Knoop, Steultjens, van der Leeden, van der Esch, Thorstensson, Roorda, et al. (2011) reviewed studies relevant to the key words “knee,” “osteoarthritis,” and “proprioception.” In this review, proprioceptive impairment was defined as diminished position sense, in which participants were required to reproduce a perceived angle with the same or contralateral knee, or reduced motion sense, in which participants were required to detect the stop or start of passive knee movement. Diminished positional sense (proprioception) of the knees of individuals with osteoarthritis was noted in six studies, and diminished motion sense (kinesthesia) of the knees of individuals with osteoarthritis was noted in five studies. There were three studies in which no differences in proprioception or kinesthesia were found between participants with osteoarthritis and age-matched participants without osteoarthritis. Cammarata, Schnitzer, and Dhaher (2011) extended the kinesthesia findings reported in Knoop, et al. (2011) to include the frontal plane of movement, noting higher threshold to detection of passive movement among individuals with osteoarthritis of the knee in all directions (flexionextension and valgus-varum). In a later study, Cammarata and Dhaher (2012) found only a weak negative correlation between threshold to detection of passive movement (kinesthesia) and passive joint stiffness of the knee, concluding that neurophysiological factors such as decreased density of joint and muscle sensory receptors and changes in central sensory processing may contribute more significantly to kinesthesia acuity than joint mechanics. In addition to proprioceptive and kinesthetic sensory deficiency, Hortobagyi, Garry, Holbert, and Devita (2004) found a relationship between osteoarthritis and force accuracy of the quadriceps. Participants were asked to generate 50 and 100 N of force in the quadriceps during isometric, concentric, and eccentric contractions. There was no difference in force accuracy between groups in the isometric condition, but the osteoarthritis group performed significantly worse in both the concentric and eccentric conditions, indicating poorer motor control of the knee. These findings were also associated with slower walking speeds on level surfaces and stairs. De Luca, Gonzalez-Cuerto, Bonato, and Adam (2009) noted a relationship between the firing rate of recruited motor units and the density


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of muscle spindles. Amplitude of maxima of the instantaneous cross-correlation function (the relationship between amplitude of newly recruited motor units and already active motor units) decreases with increased spindle density—that is, there was less variability in the force generated. The reduced accuracy of force generation of the quadriceps among individuals with osteoarthritis as noted by Hortobagyi, et al. (2004) may be due to a lower density of muscle spindles within the muscles. Using electromyography (EMG), a later study found that individuals with osteoarthritis demonstrated significantly higher levels of co-activation between the hamstrings and quadriceps as compared to individuals without osteoarthritis (Hortobagyi, Westerkamp, Beam, Moody, Garry, Holbert, et al., 2005). These EMG findings confirm the assumption of an altered muscle activation pattern (co-activation rather than triphasic activation of agonist and antagonist) among individuals with knee osteoarthritis. Another study found that the combination of poor kinesthesia and muscle weakness were associated with greater functional limitations than poor kinesthesia or muscle weakness alone (Van der Esch, Steultjens, Harlaar, Knol, Lems, & Dekker, 2007). In a longitudinal study, Segal, Glass, Felson, Hurley, Yang, Nevitt, et al. (2010) also noted a relationship between poor proprioception and muscle weakness of the quadriceps and that greater strength of the quadriceps was related to decreased reported symptoms but was unrelated to radiographic progression of knee osteoarthritis. Thus, evidence supports Sharma and Pai's (1997) first two suppositions that individuals with osteoarthritis develop proprioceptive and kinesthetic impairments of the knee joint, and these impairments of the joint are related to spatial and temporal activation of the muscles controlling the joint during movement. However, only indirect evidence supports their third supposition, that altered spatial and temporal activation of the muscles around a joint reduces accuracy of movement. Sharma and Pai admitted the evidence was limited to the phenomenon of arthrogenous muscle inhibition, believed to result from damage to sensory receptors. There is apparently no published research that measured accuracy of leg movement, such as movement during a continuous tracking task, consistent with the reciprocal pattern of knee flexion and extension essential for functional activities such as walking, in individuals with osteoarthritis. Although there is a relationship between altered spatial and temporal activation of the muscles (co-activation rather than triphasic activation of agonist and antagonist) and osteoarthritis during functional activities as noted by Hortobagyi, et al. (2005), these EMG changes do not necessarily predict changes in accuracy of leg movement. Co-activation of hamstrings and quadriceps may alter the firing pattern of muscle fibers without altering the accuracy of the movement. In fact, older adults can improve accu-


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racy of movement by adopting a co-activation strategy in which concentric activation of the antagonist cancels the force-generation error of the agonist (Patten & Kamen, 2000). Hortobagyi, et al. (2004) also found a relationship between force accuracy of the quadriceps and walking speeds, but there have been no studies that measured the effect of speed of leg on accuracy of movement. The inability to modulate temporal activation of muscles controlling the joint during movement may explain why individuals with osteoarthritis preferred walking speeds slower than individuals without osteoarthritis (Zeni & Higginson, 2009). Although poor proprioception and muscle weakness are associated with functional limitations, other factors may contribute to these functional limitations, particularly in a complex environment or in completing dual tasks. Individuals with osteoarthritis may have difficulty adjusting to conflicting task requirements as noted by Dohrenbusch, Buchanan, Lipka, and Ott (2008). Using a process-dissociation paradigm, Dohrenbusch, et al. noted that participants with osteoarthritis of the hip demonstrated lower conscious processing and preconscious inhibition than did sameage participants with somatoform chronic pain or without chronic pain. They speculated that higher pain in participants with osteoarthritis led to cognitive exhaustion and reduced ability to selectively inhibit irrelevant motor patterns. The present study investigated differences in accuracy of leg movement between older individuals with and without knee osteoarthritis and whether accuracy of motor performance was related to either speed of movement or stimulus-response congruency. The data presented in this report were collected in a larger study that examined accuracy of motor performance among three groups (young adults without osteoarthritis, older adults without osteoarthritis, and older adults with osteoarthritis).3 A previous publication discussed findings related to younger and older participants without osteoarthritis who completed the continuous tracking task in a compatible stimulus-response (the leg moved in-phase to the stimulus) and an incompatible stimulus-response (the leg moved anti-phase to the stimulus) condition at two different stimuli speeds (Williamson & Marshall, 2012). Age-related findings of an earlier publication relevant to this article included an interaction between age and stimulus-response, and age, stimulus-response, and movement time segment (Williamson & Marshall, 2012). Although younger participants performed better in both compatible stimulus-response and incompatible stimulus-response conditions, the average magnitude of error between conditions was 3.7 mm for younger particiThe data analyzed for the Non-osteoarthritis group reported in this manuscript were the same data analyzed in an earlier article examining differences in motor performance between younger and older participants without osteoarthritis (Williamson & Marshall, 2012). 3


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pants and 12.30 mm for older participants. These findings suggested older participants had greater difficulty inhibiting the more automatic, synchronized, stimulus-response compatible movement pattern in order to complete the less automatic, non-synchronized, stimulus-response incompatible movement pattern. A particularly intriguing finding was the interaction between age, stimulus-response compatibility, and time segment (movement trials were divided into time segments). Older participants performed worse in the last segment than the first segment in all trials in the incompatible stimulus-response condition, indicating performance deteriorated over a relatively short period of 40 sec. If Dohrenbusch, et al.'s (2008) speculations—that individuals with osteoarthritis suffer from cognitive exhaustion and have reduced ability to selectively inhibit irrelevant motor patterns—are correct, then older individuals with osteoarthritis will perform even worse during the incompatible stimulus-response condition than older individuals without osteoarthritis. It may be possible to observe this effect within a single trial of 40 sec. Thus, the current research examined differences in fine motor control between older individuals with and without osteoarthritis when completing a continuous tracking task of the leg. Consistent with Sharma and Pai's (1997) supposition: Hypothesis 1. Performance of older individuals with osteoarthritis on a continuous tracking task would be less accurate in comparison with individuals without osteoarthritis. Also, consistent with Sharma and Pai's (1997) suppositions that proprioceptive and kinesthetic impairments of the joint lead to altered spatial and temporal activation of the muscles controlling the joint during movement: Hypothesis 2. Differences between groups will persist even when differences in pain ratings are statistically controlled. Hypothesis 3. Differences will be greater at the fast versus slow tracking speeds. Due to cognitive exhaustion and reduced ability to selectively inhibit irrelevant motor patterns among older individuals with osteoarthritis (Dohrenbusch, et al., 2008): Hypothesis 4. Differences in motor performance between individuals with and individuals without osteoarthritis will be greater during the incompatible stimulus-response condition (leg moves out of phase with the movement of the disc on the computer screen) than during the compatible stimulus-response condition (leg moves in-phase with the movement of the disc on the computer screen).


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Hypothesis 5. Accuracy among participants with osteoarthritis will deteriorate at a greater rate within each trial (across segments) and across trials compared with participants without osteoarthritis in the incompatible stimulus-response condition. This would be expected if proposed cognitive fatigue has greater impact on the ability to selectively inhibit irrelevant motor patterns during the stimulus-response incompatible condition for individuals with osteoarthritis (Dohrenbusch, et al., 2008). METHOD Participants Participants were 24 older adults without a self-reported medical diagnosis of osteoarthritis (M age = 72.5 yr., SD = 5.0, range = 65–82) and 24 older adults with a self-reported medical diagnosis of osteoarthritis of the right knee (M age = 74.2 yr., SD = 5.1, range = 65–82), recruited by contacting churches and senior citizens' organizations. Recruitment continued until 12 men and 12 women were identified who met the inclusion criteria for each group. Groups were fairly equal in age and gender (Table 3). Selection of 24 participants was based on the power analysis of a previous study (Williamson & Marshall, 2009). A medical history questionnaire addressed inclusion and exclusion criteria, and a demographic survey collected data on education, weight, and height of each participant. Individuals with a self-reported history of major knee surgery; recent surgeries to the neck, back, hips, or ankles; corrected vision less than 20/30; or medical history of peripheral vascular disease, diabetes, or neurological disorder were excluded from the study. Since participants' medical records were unavailable to the researchers, older participants who reported a medical diagnosis of osteoarthritis and consistent use of anti-inflammatory medication (used within the last week) for knee pain were included in the Osteoarthritis group. Older participants who reported no medical diagnosis of osteoarthritis and no consistent use of anti-inflammatory medication for knee pain were included in the Non-osteoarthritis group. Morvan, Roux, Fautrel, Rat, Euller-Ziegler, Loeuille, et al. (2009) noted sensitivity of 0.85, specificity of 0.75, positive likelihood ratio of 3.51, and negative likelihood ratio of 0.19 for the specific question, “Do you have knee osteoarthritis?” These ratios are consistent with the American College of Rheumatology clinical criteria, which have a sensitivity of 0.95 and a specificity of 0.69 (Altman, Asch, Bloch, Bole, Borenstein, Brandt, et al., 1986). Therefore, it is likely participants in the self-reported Osteoarthritis group did have osteoarthritis, and participants in the Non-osteoarthritis group did not have osteoarthritis. Neither of the questionnaires of Morvan, et al. or Altman, et al. specifically categorized the severity of osteoarthritis.


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Measures In addition to reading and signing approved consent forms, participants completed a self-reported medical history questionnaire, a demographic survey, the Mini-Mental Status Examination (Folstein, Folstein, & McHugh, 1975), the Functional Status Questionnaire (Jette, Davies, Cleary, Calkins, Rubenstein, Fink, et al., 1986), and the Center for Epidemiologic Studies Depressed Mood Scale (Corcoran & Fisher, 1987). The Mini-Mental Status Examination and the Center for Epidemiologic Studies Depressed Mood Scale were used to exclude individuals at risk for dementia or clinical depression. Information derived from the demographic survey (highest level of education, weekly exercise activities, and individual weight and height) and the Functional Status Questionnaire established that groups were fairly comparable (see Table 3). Dementia screen.—The Mini-Mental Status Examination is the most commonly used screening of cognitive function (see Table 1 for example items). A meta-analysis of 39 studies found a pooled sensitivity of .80, a specificity of .81, a positive predictive value of .86, and a negative predictive value of .76 (Mitchell, 2009). Although the Mini-Mental Status Examination's internal consistency varies across studies with a range of .77 to .32 among community samples (Folstein, Folstein, & Fanjiang, 2001), Mitchell concluded that it is moderately accurate for the purpose of ruling out diagnoses of dementia in community populations. One potential participant was excluded when the Mini-Mental Status Examination identified him as possibly being cognitively impaired. Depression screen.—Depression may affect psychomotor performance (Caligiuri & Ellwanger, 2000), so the Center for Epidemiologic Studies Depressed Mood Scale was also completed by all participants. The Center for Epidemiologic Studies Depressed Mood Scale is a screen for possible depression in the general population. Internal consistency of the Center for Epidemiologic Studies Depressed Mood Scale is strong with Cronbach's coefficient α of .85 (Radloff, 1977). It has moderate concurrent correlation with other depression and mood scales such as the Negative Affect Scale (.60) of the Bradburn Scale of Psychological Well-Being, Lubin Depression Adjective Checklist (.51), Langner Symptom Survey for College Students (.54), and Cantril Life Satisfaction Ladder (.43). Activity.—Consistent moderate exercise is associated with improved cognitive function (see meta-analysis by McMorris & Hale, 2012, and systematic review by Smith, Blumenthal, Benson, Hoffman, Cooper, Strauman, et al., 2010) and motor performance of older adults (Sari, 2011). Therefore, participants reported how many days of the week they participated in aerobic, strengthening, and balance activities. Each individual's Body Mass Index (BMI) was calculated using height and weight data (Centers


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OSTEOARTHRITIS AND LEG MOVEMENT TABLE 1 EXAMPLE OF MINI-MENTAL STATUS EXAMINATION QUESTIONS Instructions: Words in boldface type should be read aloud clearly and slowly to the examinee. Item substitutions appear in parentheses. Administration should be conducted privately and in the examinee’s primary language. Circle 0 if the response is incorrect or 1 if the response is correct. Begin by asking the following two questions: Do you have any trouble with your memory? May I ask you some questions about your memory? Response

Score

Orientation to Time What is the . . . year?

0

1

season?

0

1

month of the year?

0

1

day of the week?

0

1

date?

0

1

Attention and Calculations Now I'd like you to subtract 7 from 100. Then keep subtracting 7 from each answer until I tell you to stop. What is 100 take away 7?

[93]

0

1

[If needed, say:] Keep going.

[86]

0

1


[79]

0

1


[72]

0

1


[65]

0

1

Naming What is this? [Point to a pencil or pen]

0

1

What is this? [Point to a watch]

0

1

Comprehension Listen carefully because I am going to ask you to do something. Take this paper in your right hand [pause], fold it in half [pause], and put it on the floor (or table). Take in right hand

0

Fold in half

0

1 1

Put on floor (or table)

0

1

for Disease Control and Prevention, 2009) since high BMI measurements have been associated with diminished performances in executive function, manual dexterity, and motor speed (Waldstein & Katzel, 2006). Function.—The Functional Status Questionnaire assessed each participant's perceived ability to complete daily activities, ability to participate in social activities, overall well-being, and quality of social interactions (Yarnold, Stille, & Martin, 1995). Its subscales demonstrated superior to moderate internal consistency with alpha coefficients of .84 for basic activities of daily living, .82 for intermediate activities of daily living, .83 for


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social activity, and .77 for sense of well-being (Yarnold, et al., 1995). Crosssectional analysis revealed a strong discriminant predictor for the physical limitation measures of basic and intermediate activities of daily living (R2 = .40) for a geriatric sample (Yarnold, Bryant, Repasy, & Martin, 1991). Apparatus An IBM compatible PC, a 19-in. monitor, InertiaCube2 Sensor™ hardware (InterSense, Billerica, MA), and Advanced Motion Measurement (AMM, Phoenix, AZ) Sine Wave Tracker® (Beta Version) software were used for all performance trials. An InertiaCube2 sensor which controlled an on-screen disc was placed on a participant's anterior leg between the malleoli. The participant attempted to keep a disc on the center of a moving on-screen sinusoidal wave (Fig. 1). Wave parameters included thickness of 2 mm, wavelength of 125 mm, and amplitude of 85 mm. The onscreen sinusoidal wave moved at a frequency of .35 Hz at a velocity of 57.0 mm/sec. or .47 Hz at a velocity of 79.0 mm/sec. These frequencies were selected based on a pilot study of young adults in which the velocity parameters of 57 and 79 mm/sec. in both compatible stimulus-response and incompatible stimulus-response conditions appeared demanding enough to produce significant differences between speeds (Williamson, 2006). AMM Tracker software created the visual stimuli and measured the accuracy of the leg movement (Cheetham, 2004). Absolute average deviation from the wave target (in mm) defined accuracy of motor performance. In order to match the movement of the on-screen stimuli with movement of the leg, the sinusoidal wave was scaled according to 60° of knee range of motion for each individual. Each degree of angular motion of the leg represented approximately 1.5 mm of disc movement on the screen. The reliability of the AMM Tracker software was assessed previously by comparing data from two groups of 18- to 25-yr.-old participants (12 men and 12 women in each group) using a mixed analysis of variance (ANOVA). There was no significant difference between the two groups (F1, 60 = 0.12, p = .73; Williamson, 2006). Reliability of the AMM Tracker software for this study was assessed by calculating a split-half measure of reliability of all tracking data for participants with and without osteoarthritis. There was no significant difference between the two halves, with a reliability coefficient of .96. Participants sat upright on an N-K™ Exercise Table (Lake Elsinore, CA), which has two adjustable radial arms that may be adjusted to a specific angle. Angles were selected by having each participant actively flex the leg against a physical stop, which extended from the right radial arm of the table, set at 80° of knee flexion. A goniometric measurement of the knee angle using the greater trochanter, the lateral condyle, and the lateral malleolus as landmarks for alignment was completed, and necessary ad-


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justments were made to the radial arm to ensure active knee flexion was limited to 80° of flexion. A second goniometric measurement of the knee angle using the same anatomical landmarks was completed with the leg actively extended against a physical stop, which extended from the left radial arm of the table, set at approximately 20° of knee flexion, with similar adjustments to ensure active knee extension was limited to 20° of flexion. Procedure When sitting upright on the NK Exercise Table, hips were at 90° in relation to the trunk, and the lateral condyle of the right4 leg was aligned with the hub of the right radial arm of the table. Using a velcro strap, the InertiaCube2 Sensor was placed on the anterior surface of the right leg between the medial and lateral malleoli. In order to calibrate the devices, participants sat with hands folded in their laps and moved the leg several times from a start position of 80° of knee flexion to an ending position of 20° of knee flexion, as defined by physical stops at the starting and ending positions. This range of motion was selected because it was felt that mid-range movement potentially would be the least painful for individuals with osteoarthritis (Bennett, Hanratty, Thompson, & Beverland, 2009). Also, although functional range of motion of the knee during walking varies across individuals, during each stride the knee experiences two waves of knee flexion; on average, the first peaks at 20° in stance and the second peaks at 60° in swing (Perry & Burnfield, 2010). Once calibration was completed, the physical stops were removed to allow free movement of the leg in flexion and extension. In this study, participants attempted to keep a disc (located in the middle of the screen and which only moved up and down) on the center of a moving on-screen sinusoidal wave under four different conditions (Table 2 and Fig. 1). In the slow, stimulus-response compatible condition, the sinusoidal wave moved across the screen at 57 mm/sec., and moveTABLE 2 EXPERIMENTAL CONDITIONS Stimulus-response

Speed of Stimulus Slow

Fast

Compatible (in-phase)

57 mm/sec. Computer disc ↑ Leg ↑

79 mm/sec. Computer disc ↑ Leg ↑

Incompatible (anti-phase)

57 mm/sec. Computer disc ↑ Leg ↓

79 mm/sec. Computer disc ↑ Leg ↓

Due to the arrangement of the NK Exercise Table, only the right leg could be tested. Leg preference was established by asking participants to kick a small ball, and for the record, of the 48 total participants, only 3 were left-footed. All individuals in the Osteoarthritis group reported osteoarthritis of the right leg. 4


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E. M. WILLIAMSON & P. H. MARSHALL Compatible Stimulus-response Wave Movement

Incompatible Stimulus-response Wave Movement

FIG. 1. Illustration of movement of the stimulus disc on the computer screen and leg movement in compatible and incompatible conditions. The red arrow shows the required direction of vertical leg movement to keep the disc on the curve.

ment of the disc was in-phase with movement of the leg (extension of the knee moved the disc upward, and flexion of the knee moved the disc downward). In the fast, compatible stimulus-response condition, the sinusoidal wave moved across the screen at 79 mm/sec., and movement of the disc was in-phase with leg movement. In the slow, stimulus-response incompatible condition, the sinusoidal wave moved across the screen at 57 mm/sec., and movement of the disc was anti-phase with the movement of the leg (extension of the knee moved the disc downward, and flexion of the knee moved the disc upward). In the fast, incompatible condition, the sinusoidal wave moved across the screen at 79 mm/sec., and movement of the disc was anti-phase with the movement of the leg. Prior to the initiation of the first trial, participants were informed of the characteristics of each condition, and during the inter-trial interval, each participant received on-screen feedback in the form of the percentage of time-on-target


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for the each completed trial. For each condition, ten 40-sec. trials with 15sec. inter-trial intervals were completed with a 5-min. break between conditions. It took 50 min. to complete all trials and conditions. The order of presentation of the conditions was counter-balanced across participants. Since pain could affect movement accuracy (Bellamy, Southern, Campbell, & Buchanan, 2002), prior to beginning the motor task, and after completing each condition, all participants completed a visual analog pain scale (VAS). This consisted of a 100-mm horizontal line with end points defined as “no pain” and the “worst pain ever imagined.” Participants were asked to draw a vertical line at the point on the scale that represented their current knee pain. Pain VAS measurements are sensitive to interventionrelated changes and correlated moderately (.57) with category pain scales (Bradley, 1993). Bradley also reported test-retest reliability coefficient of .90–.96 among literate and illiterate patients with rheumatoid arthritis. The research protocol was reviewed and approved by the Texas Tech University and Texas Tech University Health Science Center Institutional Review Boards. Informed consent was acquired from all participants. Analysis All statistical analyses were completed using STATISTICA ‘98 Edition (StatSoft, Inc., Tulsa, OK). Lacking a sufficient sample size to complete a multiple analysis of variance on all possible characteristics or life experiences that may affect motor performance, Osteoarthritis and Non-osteoarthritis groups were selected to be comparable on these characteristics and life experiences. Thus, a series of Kruskal-Wallis ANOVAs were run to compare group differences on education, BMI, weekly exercise activities, perceived ability to complete basic and intermediate activities of daily living and to participate in social activities, and overall sense of well-being. In the Non-Osteoarthritis group, pain data were missing for one participant for the first and second ratings, and for two participants for the third and fifth ratings. In the Osteoarthritis group, pain ratings were missing for three participants for the second rating. Rather than replacing these participants, it was decided to analyze available data. All available pain ratings for each participant were averaged. Accuracy of movement was analyzed using a mixed within-subjects factorial design 2 × 2 × 2 × 10 × 4 analysis of covariance5 (ANCOVA) with One of the assumptions of a mixed within-subjects factorial design is sphericity, that is, “the homogeneity of variances within treatment conditions and the homogeneity of correlations between pairs of treatment conditions” (Keppel, 1991, pp. 377-378). An additional assumption of the mixed within-subjects factorial design is that the nature of the variances and correlations are the same across the levels of the non-repeated factors (Keppel, 1991). Assuming violation of these assumptions, a multivariate approach to repeated-measures analysis was used. With the use of the multivariate criteria, multiple contrasts do not need to be independent of each other when testing the statistical significance of two or more repeated measures contrasts (STATISTICA, 1995). 5


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pain as the covariate. Independent variables included group (individuals without osteoarthritis and individuals with osteoarthritis as the betweensubjects factor), cognitive demand (compatible and incompatible stimulus-response), speed of stimulus (57 mm/sec., 79 mm/sec.), trial (1–10), and intra-trial time segment6 (2–5) as the within-subjects factors. Absolute average deviation from target was the dependent variable. Further analyses were completed as dictated by initial findings and are noted below. Only interactions specifically related to Osteoarthritis and Non-osteoarthritis group differences are discussed. RESULTS Group Similarities and Differences Participants with and without osteoarthritis were similar in age; educational level; BMI; and frequency of aerobic, strengthening, and balance activities (Table 3). The Functional Status Questionnaire assessed each participant's perceived ability to complete daily activities, sense of wellbeing, and social activity (the lower the rating on a series of 5-point Likerttype scales, the greater perceived disability). As noted in Table 3, participants in the Osteoarthritis group reported significantly greater difficulties with basic activities of daily living and intermediate activities of daily living than participants without osteoarthritis. Social activity and perceived sense of well-being were similar between groups. Motor Performance Significant differences were found for all main effects except group (Tables 4 and 5). The Tukey HSD confirmed that overall, participants performed worse during the first trial than any other trial (p = .001) and performed better in the second segment than the fourth (p < .001) and fifth (p = .001) segments. Although a group main effect was not found, there was a four-way interaction between group, cognitive load, speed of stimuli, and trial (F9, 414 = 2.06, p = .03, η2 = 0.01). To help make sense of this interaction, separate mixed-design 2 × 2 × 10 × 4 ANCOVAs were completed for the compatible and incompatible stimulus-response conditions. Pain was a covariate in both analyses. Analysis of the compatible stimulus-response trials indicated a significant difference in performance between Non-osteoarthritis and Osteoarthritis groups (F1, 45 = 4.06, p = .05, η2 = 0.80). Non-osteoarthritis group leg movements were more accurate than the Osteoarthritis group (Fig. 2). 6 The first time segment (the first 8 sec.) of each trial was eliminated from analysis since it dealt with the initial acquisition movement toward the moving sinusoidal wave and not with tracking performance, per se.


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OSTEOARTHRITIS AND LEG MOVEMENT TABLE 3 PARTICIPANTS' CHARACTERISTICS Non-osteoarthritis

Characteristic Age

M

BMI

M

95%CI

Statistic

p

72, 76

F1, 45 = 1.22

.28

3.92

3.61, 4.23

3.79

3.67, 3.91

H1, 48 = 0.20

.66

73

Education

Osteoarthritis

95%CI 68, 78

74

27.47

25.90, 29.04

27.63

27.00, 28.26

H1, 47 = 0.03

.88

Aerobic activities

2.71

2.49, 2.93

2.21

2.22, 2.30

H1, 48 = 3.64

.06

Strengthening activities

1.88

1.50, 2.26

1.78

1.63, 1.93

H1, 47 = 0.10

.75

Balance activities

1.33

1.03, 1.63

1.25

1.13, 137

H1, 48 = 0.02

.90

BADL

198

195.75, 200.25

187

176.98, 197.77

H1, 48 = 7.51

.006

IADL

153

149.40, 156.60

133

124.28, 141.72

H1, 48 = 14.50 .001

Social activities

192

184.14, 199.86

183

169.60, 196.40

H1, 48 = 1.73

.19

Well-being

133

127.26, 138.74

128

121.77, 134.23

H1, 48 = 1.51

.28

Note.—BADL = basic activities of daily living; IADL = intermediate activities of daily living; BMI = Body Mass Index.

Analysis of the incompatible stimulus-response trials revealed no difference in performance between the Non-osteoarthritis group (M = 11.24, SD = 5.79) and the Osteoarthritis group (M = 11.12, SD = 4.78; F1, 46 = 0.01, p = .93, η2 = 0.001) or significant group interactions. TABLE 4 MAIN EFFECTS OF CONTINUOUS TRACKING TASK DURING ALL CONDITIONS: ANALYSIS OF VARIANCE Main Effect

df

MS

F

p

η2

.61

0.21

Group

1

493.5

0.26

Load

1

109,914.7

115.69

.001

0.99

Speed

1

7,557.1

26.25

.001

0.93

Trial

9

317.0

11.76

.001

0.92

Segment

3

140.2

8.48

.001

0.89

DISCUSSION The results were partially consistent with Sharma and Pai's (1997) supposition that there is a relationship between osteoarthritis and accuracy of movement and with Hypothesis 1, that the performance of older individuals with osteoarthritis on a continuous tracking task would be less accurate compared to individuals without osteoarthritis. In the compati-


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176

E. M. WILLIAMSON & P. H. MARSHALL TABLE 5 MEANS AND CONFIDENCE INTERVALS (CI) FOR ALL MAIN EFFECTS Main Effect

M (mm)

95%CI

Group Non-osteoarthritis

7.14

5.11, 9.17

Osteoarthritis

7.65

5.95, 9.35

Load Compatible

3.61

3.42, 3.80

11.18

10.53, 11.83

57 mm/sec.

6.40

5.48, 7.32

79 mm/sec.

8.39

6.82, 9.96

1

9.11

6.98, 11.24

2

7.59

5.75, 9.43

3

6.95

5.07, 8.83

4

7.10

5.18, 9.02

5

6.99

5.08, 8.90

6

6.82

4.97, 8.67

7

7.43

5.29, 9.57

8

7.43

5.37, 9.49

9

7.34

5.26, 9.42

10

7.36

5.38, 9.34

2

7.05

5.16, 8.94

3

7.37

3.80, 10.62

4

7.46

3.38, 11.54

5

7.70

2.27, 13.13

Incompatible Speed

Trial

Time Segment

ble stimulus-response condition, the Non-osteoarthritis group performed significantly better than the Osteoarthritis group. This difference persisted during all 10 trials. Also, as hypothesized (Hypothesis 2), this group difference occurred even though the analysis controlled for differences in pain between groups. Other findings were not consistent with the hypotheses. Differences between groups were not greater at the fast (79 mm/sec.) than the slow (57 mm/sec.) stimuli speeds as predicted by Hypothesis 3. Apparently, the inability to selectively inhibit irrelevant motor patterns among older individuals with osteoarthritis was no greater than that of older individuals without osteoarthritis (Dohrenbusch, et al., 2008) since there was no difference in motor performance between individuals with


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177

Absolute Average Deviation from Target (mm)

7 6 5 4 3 2 1 0

Groups

FIG. 2. Absolute average deviation from target (mm) for Non-osteoarthritis and Osteoarthritis groups in stimulus-compatible cognitive load conditions of all trials.

and individuals without osteoarthritis during the incompatible stimulus conditions (Hypothesis 4). Further, accuracy among participants with osteoarthritis did not deteriorate at a greater rate across intra-trial time segments or across trials compared with individuals without osteoarthritis in any condition. Thus, there was no evidence of greater cognitive fatigue for individuals with osteoarthritis (Hypothesis 5). The finding that leg movements of individuals in the Osteoarthritis group were less accurate than the leg movements of individuals in the Non-osteoarthritis group in the compatible stimulus-response condition supports Sharma and Pai's (1997) supposition that accuracy of movement is affected by osteoarthritis. Group differences in performance on the continuous tracking task were consistent across trials, suggesting that the poorer performance of the Osteoarthritis group may be unrelated to fatigue. The lack of significant differences between slow and fast tracking speeds suggests that spatial control was affected more than temporal control. If timing of movement were the major factor, a difference between slow and fast tracking speeds would be observed. However, since only two speeds were used in this study, further research that examines a greater number or range of speeds will be required before a definitive conclusion can be drawn. The present study extends the findings of Hortobagyi, et al. (2004), which noted an increased percentage of error among individuals with osteoarthritis when completing a force accuracy task with the quadriceps, to include control of the quadriceps and hamstrings over a longer period of time. Since this study did not directly measure proprioceptive and kines-


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178


thetic loss, one cannot conclude that difference in accuracy of knee movement between groups was due to diminished position or motion sense of the knees, as noted in the review of Knoop, et al. (2011). Age-related findings in an earlier publication revealed older participants had greater difficulty inhibiting the more automatic, synchronized, stimulus-response compatible movement pattern to complete the less automatic, non-synchronized, stimulus-response incompatible movement pattern (Williamson & Marshall, 2012). In this study, with two elderly samples, there was no significant difference between the Non-osteoarthritis group and the Osteoarthritis group in the incompatible stimulus-response condition, indicating that the inability to selectively inhibit irrelevant motor patterns was similar for both groups. Participants with osteoarthritis of the hip in Dohrenbusch, et al. (2008) had lower conscious processing and preconscious inhibition than participants with somatoform chronic pain or participants without chronic pain. However, participants with osteoarthritis in that study reported greater joint pain than participants without osteoarthritis or with somatoform chronic pain. In contrast, an ANCOVA controlled for pain ratings in the present study, therefore, participants' pain experiences may explain the difference between current findings and Dohrenbusch, et al. (2008). The finding that there was no difference between groups in the incompatible condition was unexpected, since one would have expected a consistent difference between groups in the compatible and incompatible conditions when the order of conditions was counter-balanced across participants and pain was statistically controlled in both analyses. The findings of no difference between Osteoarthritis and Non-osteoarthritis groups may simply be a cellar effect, that is, all participants experienced the same difficulty in performing the task. Roerdink, Peper, and Beek (2005) found that under difficult high-speed, manual pursuit tracking conditions, the visual components of participants' tracking strategies changed from one of smooth pursuit to one of gaze fixation. It is possible that a similar less effective strategy change may have occurred in the more difficult incompatible conditions of the present study, rendering any differences between the Osteoarthritis and Non-osteoarthritis groups harder to detect. Therefore, the present study does not completely rule out a relation between poor motor performances and increased cognitive load among individuals with osteoarthritis in the absence of pain, since all participants performed poorly in the incompatible stimulus-response condition. Limitations Although medical records were not obtained, the finding of a significant group effect in the compatible condition confirmed a difference between those who self-reported having osteoarthritis and those who


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self-reported no osteoarthritis. This difference cannot be explained by differences in age, education, BMI, or self-reported frequencies of aerobic, strengthening, and balance activities. In addition to a self-reported medical diagnosis of osteoarthritis, the Osteoarthritis group differed in perceived ability to complete basic and intermediate activities of daily living. However, since a direct relationship between accuracy of performance and functional capabilities was not found, the findings should be interpreted and applied to future clinical interventions with caution. Further, since recruitment of muscle fibers was not specifically examined, there was no direct link between Sharma and Pai's (1997) supposition that altered spatial and temporal activation of the muscles around a joint reduced accuracy of movement. Although both groups reported the same frequency of physical activities (aerobic, strength, and balance), it cannot be assumed the intensity of the activities were similar. It is possible that individuals in the Non-osteoarthritis group were stronger and had greater muscle endurance. A possible cellar effect may explain why there was no group difference in the incompatible stimulus-response condition. Slower speeds or a different paradigm may be required to resolve the inconsistency between the compatible and incompatible conditions. Future Research Future studies may benefit from osteoarthritis being detected and quantified through radiographs and for control of fatigue and strength of the knee musculature. Through gait analysis, the relationship between inaccurate movement of the knee, abnormal load distribution over the joint, and arthritic changes of the knee could also be examined. Assuming there is a relationship between abnormal loading of the knee during walking and inaccuracy of leg movement for individuals with osteoarthritis, specific rehabilitative treatment protocols that include activities which improve accuracy of movement could be examined, determining whether spatial and temporal control of knee musculature reduces pain, improves functional capabilities, and delays surgical interventions. Older adults with self-reported osteoarthritis appeared to have no greater difficulty adjusting to high cognitive load than older adults without self-reported osteoarthritis in this study. This may not be the case with severe osteoarthritis, or perhaps the incompatibility in this study was so high that both groups performed too poorly to observe any differences. A study which uses a different cognitive load paradigm may provide valuable information regarding osteoarthritis changes and performance under increased cognitive load.


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In conclusion, this initial study has established that there is a relation between osteoarthritis and reduced accuracy of leg movement. Further research will be required to clarify this relation and to establish whether interventions to improve accuracy of movement would positively affect functional capabilities of individuals with osteoarthritis. REFERENCES

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Immediate Effect of Positioning Devices on Infant Leg Movement Characteristics.

The effect of accuracy constraints on three-dimensional movement kinematics.

The Effect of Physical Activity on Passive Leg Movement-Induced Vasodilation with Age.

The effect of action video game playing on sensorimotor learning: Evidence from a movement tracking task.

Effect of Continuous Glucose Monitoring Accuracy on Clinicians' Retrospective Decision Making in Diabetes: A Pilot Study.

Relationship between Leg Mass, Leg Composition and Foot Velocity on Kicking Accuracy in Australian Football.

Pelvic movement strategies and leg extension power in patients with end-stage medial compartment knee osteoarthritis: a cross-sectional study.

Movement features and H-reflex modulation. II. Passive rotation, movement velocity and single leg movement.

The Effect of an Acute Bout of Moderate-Intensity Aerobic Exercise on Motor Learning of a Continuous Tracking Task.

Haptic perception accuracy depending on self-produced movement.

Empirical Study on Designing of Gaze Tracking Camera Based on the Information of User's Head Movement.

Effect of age on transvascular fluid movement.

Design and validation of a periodic leg movement detector.

Correction: Design and Validation of a Periodic Leg Movement Detector.

Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement.

Illusory motion reversals and feature tracking analyses of movement.

Effect of straight leg raising on blood pressure.

Effects of training and simulated combat stress on leg tourniquet application accuracy, time, and effectiveness.

Translocation as continuous movement through the ribosome.

Standardized accuracy assessment of the calypso wireless transponder tracking system.

Diagnostic Accuracy on Magnetic Resonance Imaging for the Diagnosis of Osteoarthritis of the Temporomandibular Joint.

What mechanisms coordinate leg movement in walking arthropods?

Continuous discourse tracking: an analysis of the procedure.

Effect of Glucosamine Sulfate on Osteoarthritis in the Cruciate-Deficient Canine Model of Osteoarthritis.