Children with cerebral palsy (CP) can experience varying degrees of weakness.1,2 The early evidence in children with CP indicates their muscles may respond positively to resistive exercise. Concentric exercise training of the gastrocnemius muscle in children with CP increased muscle volume,3 increased muscle fascicle length, reduced pennation angle, decreased tendon length, and tendon stiffness.4 Eccentric training of biceps brachii in children with CP decreased cocontraction and improved torque.5
Despite improving muscle architecture and muscle function,3 conflicting evidence is found on the effectiveness of resistive exercise in improving gross motor ability and motor function in children with CP who are ambulatory.6,7 Franki et al6 found level II evidence in 2 studies of the effectiveness of strengthening on gait and gross motor function. However, Scianni et al7 reviewed 5 randomized controlled trials and found that muscle strengthening was not effective for improving Gross Motor Function Measure (GMFM) scores.7 Recently, Moreau et al8 reported an association between the ability of the muscle to generate force quickly and muscle architecture and motor function. These findings suggest that high-velocity exercise training may be beneficial for improving both muscle architecture and motor function. Strengthening interventions that incorporate high-velocity contraction could potentially improve gross motor ability in children with CP. Plyometric training is a type of resistive strengthening that provides dynamic, high-speed movements.
Verschuren et al9 compared intervention durations of 5 studies to the National Strength and Conditioning Association (NSCA) guidelines10 for children with typical development. None of the studies met the criteria for adequate duration. Because published protocols have not met the guidelines for resistive exercises in children with typical development, it seems likely that the duration of resistive training programs was insufficient to affect children with CP. Therefore, determining the optimal duration and effectiveness of a training program for improving the gross motor abilities of children with CP is an important clinical research question.
Plyometric exercise refers to a type of resistive strengthening where an eccentric contraction is followed by a rapid concentric contraction of the same muscle and typically includes high-velocity, high-impact activities such as hopping, jumping, bounding, and throwing.11 This type of exercise is specific to training muscle actions needed for gross motor function. Preliminary evidence has demonstrated the safety and efficacy of plyometric training for improving throwing and jumping skills in children with neurofibromatosis type 112 and for increasing bone mineral content13 and lean body mass14 in children with Down syndrome. Despite the potential benefits of plyometric exercise, there have been no studies published that evaluate the use of plyometric training programs in children with CP. The purposes of this study were to (a) evaluate the effects of plyometric training on gross motor abilities, (b) determine the optimal duration of a plyometric training program, and (c) determine whether gross motor abilities are maintained after training ends.
Participants and Setting
Participants were recruited from a children's orthopedic hospital. The inclusion criteria were a diagnosis of spastic, unilateral type CP as determined by their physician, Gross Motor Function Classification System (GMFCS)15 level I, a Manual Abilities Classification System (MACS)16 level I or II assigned by the researcher, and 7 to 11 years of age. Exclusion criteria were orthopedic surgery or neurosurgery within the past year, a botulinum toxin injection in the past 6 months, and inability to attend or participate in a twice a week, 10- to 15-week intervention. Institutional review board approval and consents/assents to participate were obtained for the study. Five children and their parents expressed interest in participating. The researcher reviewed the medical record of each prospective participant, met with the child and parent individually, and classified the child's gross motor function and manual ability using the GMFCS and MACS. One child decided she was not interested, and one parent decided she could not attend twice a week for 10 to 15 weeks. Table 1 describes the characteristics of the 3 participants.
The researcher assessed the participants in the motion analysis laboratory and delivered the intervention to each participant individually in the hospital gym or on the playground. A trained observer collected data for interobserver agreement of the outcome measures and treatment integrity (see procedures). The exercises were performed on grass, on a mat, or on the gym floor in an area that had sufficient room for jumping and throwing. The participants were encouraged to wear appropriate exercise apparel, bring water, and apply sunscreen.
A multiple-baseline, multiple-probe, across-participants design17,18 was used to examine the effects of the plyometric training intervention on the gross motor abilities of children with unilateral spastic CP. Preintervention and postintervention measures were incorporated into this single-subject research design. This design is a variation of a multiple-baseline design that is often used when participants are likely to be in baseline for extended periods, creating problems of reactivity to measurement or issues related to practicality.17,18 In this study, conducting probes rather than twice-weekly assessments in baseline provided a series of performance measurements, decreased the likelihood that learning from repeated assessments would strengthen performance, and eased the burden on families from having to bring children into the clinic for twice-weekly measurements.
The assessment tools were chosen to measure the anticipated effects of plyometric training: gross motor ability, running speed, agility, and muscle power. Gross motor ability, running speed, and agility measures were pre/post measures. Muscle power measures were the primary measures used during the baseline and intervention phases to evaluate the response to intervention (plyometric training) and to determine the optimal duration (Table 2). The GMFM-66 was used to assess gross motor ability; the 10×5-m sprint was used to assess agility; the 20-m running-start timed sprint was used to assess running speed; and the basketball throw, broad jump, and vertical jump were used to assess power. Jumping tasks from the GMFM were not responsive enough to monitor session-to-session change in jump distance and height; therefore, task-specific tests to measure jumping and throwing with a ratio measurement scale were used to assess the expected outcomes. Minimal clinically important difference (MCID) scores have not been published for agility, running speed, or the power tests; therefore, psychometric properties were used to identify the primary outcome measure. The basketball throw test was chosen a priori as the primary measure for examining stability in baseline and for evaluating change during the intervention condition because the test had been found to have a high effect size19 (0.99) and was most responsive to change in children with typical development.20 The broad jump and vertical jump tests were secondary measures.
Gross Motor Ability Measure—GMFM-66
The GMFM-66 is a standardized test of gross motor function for children with CP.15 The interrater reliability (intraclass correlation coefficient [ICC] = 0.76-1.00) is high,21 and longitudinal responsiveness to change (effect size = 0.3-0.4) is fair.22 Dimensions D (standing) and E (walk, run, and jump) were administered before and after the intervention, and these 2 dimensions were used to calculate the GMFM-66 total score, and a percentile rank was computed at each of these sessions. Software accompanies the user's manual23 for entering test data. The program generates a score for each section, a percentile score for each section (number correct/number possible), and a total score (GMFM-66 score). A percentile rank was determined using tabulated reference percentiles24 to provide normative comparisons to function and age-matched peers with CP.
Agility Measure—the 10 × 5-m Sprint
This test was used to assess changes in agility. The participants run between 2 lines spaced 5 m apart, 10 times at maximum speed. Interobserver reliability and test-retest reliability have been shown to be high (ICC = 1.0, and 0.97, respectively) in children with CP.25 Construct validity was determined by evaluating the ability of the test to distinguish between GMFCS levels I and II (P = .006).25 Reference values are available to provide comparisons to severity-, height-, and weight-matched peers with CP.26
Running Speed Measure—the 20-m Running-Start Timed Sprint
This test was used to assess changes in running speed. It involves running a single maximum sprint over 20 m. Age- and sex-specific percentile values are provided and can be used to characterize performance relative to the reference population.27
Power Measures—Basketball Throw, Broad Jump, and Vertical Jump
These tests were chosen because they are specific to the type and speed of contraction, and to the movements being trained. Validity (0.82-0.99) and intrarater reliability (ICC = 0.99) of the tests have been shown to be high.19 Age- and sex-specific percentile values are provided and can be used to characterize performance relative to the reference population.19 The 3 power measures take a total of 5 minutes to administer, have standardized instructions, can be carried out in the clinic, have reference values on the basis of age and sex, and require a minimal amount of equipment.
The purpose of a self-selected gross motor skill goal was to motivate the children to attend and participate in the intervention sessions. Each participant selected a motor goal on which to work during the cool-down activity. The participants were asked about sport and physical activity interests and were assisted by the parent and researcher to select 1 motor task as a goal. The researcher defined the motor task and developed a measurement system to track the progress on the self-selected goal. At the end of the 5-minute cool-down activity, the child was given 2 opportunities to perform the motor task, and his/her performance from the better trial was recorded on the data sheet. Progress toward the self-selected goal was monitored. However, the results were not attributed to the plyometric training because the achievement of the goal may have resulted from practice, rather than from the intervention.
Ground contact times during jumping were counted and repetitions and weight during throwing were recorded at each intervention session to prevent overtraining.28 Falls and events such as bumps, bruises, strains, sprains, and complaints of muscle soreness or unusual fatigue were counted in each session. The participants wore a Polar heart rate monitor (E600 ©Polar Electro 2012) during each session. The training heart rate was determined by using the formula (194 × 0.65 + resting heart rate).29 The training range was set using the guidelines accompanying the Polar heart rate monitor, and the participants were allowed to rest if their heart rate rose above the training zone.
Accuracy of the agility, running speed, and power measurements was checked by having the researcher and a trained observer independently record the best effort of each measure on their data sheets. Interobserver agreement was determined by comparing the data from the trained observer's checklist (Appendix A, available online as Supplemental Digital Content 1, at http://links.lww.com/PPT/A54) to the researcher's exercise log (Appendix B, available online as Supplemental Digital Content 2, at http://links.lww.com/PPT/A55). Interobserver agreement was calculated using the formula: percent agreement = (smaller number ÷ larger number) × 100.
The plyometric training intervention was developed using the NSCA guidelines10 and a review of plyometric training research.30 The block practice paradigm was used to vary the exercises and progress the exercise load.31 The intervention followed the protocol described in a previous paper.12 The intervention ended when the throw distance was stable (<10-cm difference) over a minimum of 3 consecutive sessions or at the end of 15 weeks.
All sessions began with a 5-minute warm-up consisting of dynamic stretching exercises (see the video, available online as Supplemental Digital Content 3, at http://links.lww.com/PPT/A56) followed by the power tests (basketball throw, broad jump, and vertical jump). Participants performed 3 sets of 5 repetitions of 8 plyometric exercises—4 jumping or hopping exercises (see the video, available online as Supplemental Digital Content 4, at http://links.lww.com/PPT/A57) and 4 throwing exercises (see the video, available online as Supplemental Digital Content 5, at http://links.lww.com/PPT/A58). The first exercise session of the week focused on developing horizontal power, and the second session of the week focused on developing vertical power. The exercise set was followed by a 5-minute cool-down during which the participant performed drills related to the self-selected goal. Testing of the self-selected goal occurred at the end of the cool-down period.
Treatment integrity was assessed to ensure that the intervention was delivered as described over the course of the study. The researcher developed a 14-item checklist describing the intervention procedures (Appendix A, available online as Supplemental Digital Content 1, at http://links.lww.com/PPT/A54). A prephysical therapy student was trained to evaluate treatment integrity. The training consisted of a description of the items on the checklist followed by watching a video of an exercise session. The trainee and researcher compared responses after watching the video. Discussion between the researcher and trainee continued until the trainee achieved consensus with the researcher over 3 videotaped intervention sessions. The trained observer watched the intervention from the sideline and recorded counts, distances/heights, times, and the presence or absence of the 14 items on the checklist. Treatment integrity was calculated by dividing the number of procedures observed by the trainee by 14 (the total number possible).
Descriptive statistics were used to describe changes in height and weight over the course of the study, safety, the preintervention, postintervention, and follow-up GMFM scores, agility, running speed, and power tests. Visual analysis and split-middle lines of trend estimation32 were used to evaluate the effectiveness of the intervention. Split-middle lines were calculated in baseline, and during each 5-week block of the intervention to depict trends in the data. The better performance of the 2 trials collected at each session of the power tests and self-selected goals were used for data analysis. Visual analysis was used to determine the optimal duration of the intervention by observing each participant's response over time in the ball throw test.
Interobserver Agreement and Treatment Integrity
Interobserver agreement was assessed during 78% of the assessments before and after the intervention and averaged 99% (98%-100%) for the 10×5-m sprint test, and 96% (95%-99%) for the 20-m running-start sprint. Interobserver agreement for the power tests was assessed during 33% of the sessions and averaged 98% (96%-99%) for the basketball throw, 98% (96%-100%) for the broad jump, and 99% (99%-100%) for the vertical jump.
Treatment integrity was assessed during 29% of the sessions and averaged 97% (95%-99%). The safety events were recorded in each session (Table 3). The length of the session and training heart rates were consistent with those described in a systematic review of plyometric training.30 Participants began with a low number of repetitions at the onset of the intervention and increased repetitions gradually each week. Participant 2's (P2's) initial number of repetitions was high because the exercises were too easy for him and the difficulty was adjusted during the second session.
Height and weight were measured, and body mass index (BMI) percentile was calculated for each assessment33 (Table 4). BMI percentile indicates an individual child's position relative to children of the same age and sex. Participant 1 (P1) and participant 3 (P3) were in the Centers for Disease Control and Prevention underweight category, and P2 was in the obese category. Because the participants were not in the healthy weight category, the hospital nutritionist was consulted. P1 and P3 were at risk of losing weight from increasing physical activity level, and their parents were counseled to increase their caloric intake during the intervention. P2's parent was counseled to eliminate sugary drinks, switch to low-fat dairy products, and limit fast foods. P1 and P2 grew during the intervention condition; P1 grew 1.5 cm in 8 weeks, and P2 grew 3 cm in 14 weeks. P1 increased his BMI 1%, P2 decreased his BMI 1%, and P3 increased his BMI 2% during the intervention.
Gross Motor Ability (Table 5), Agility—10 × 5-m Sprint (Table 6), and Running Speed—20-m Running-Start Sprint (Table 6)
All 3 participants improved GMFM dimension E scores, the GMFM-66 scores, the GMFM percentile rank, and the 10×5-m sprint times from pretest to posttest. Only P1 and P2 improved in running speed times from pretest to posttest.
Power—Basketball Throw (Figure 1)
P1 had stable data in throw distance during baseline, indicating that without treatment his motor performance did not change. The intervention was begun for P1, whereas additional baseline measures were collected for P2 and P3. The longer baseline sessions for P2 and P3 replicated the finding of no change without treatment. Throw distance increased for all 3 participants when the intervention was begun, although P3's increase was small. All 3 participants continued to increase throw distance during the second 5-week block. Intervention ended when 3 consecutive measures were within 10 cm of each other.
Power—Broad Jump (Figure 2)
P3 had stable data in broad jump distance in baseline and then made gains through the first and second 5-week blocks, reflecting improvement in lower extremity power. Intervention was begun for P1 and P2 despite variable baseline data because the throw data were selected as the primary measure for determining the response to the intervention. P1 and P2 took longer to achieve a stable response in broad jump distance. P1's data reflect improvement in intersession variability; however, only P2 increased broad jump distance during the second 5-week block of the intervention.
Power—Vertical Jump (Figure 3)
Similar responses were seen for vertical jump power. P3 had stable data in vertical jump distance in baseline and then made gains through the first and second 5-week blocks, reflecting improvement in lower extremity power. P1 and P2 took longer to reach a stable response. P1 and P2 both achieved a stable response by the end of the second block. P2 increased vertical jump distance in the third block, reflecting improvement in vertical jump distance. However, P1 decreased vertical jump distance in the second block of treatment, reflecting a decline in vertical jump distance.
Self-Selected Goal (Figure 4)
P1 and P3 both chose to improve soccer dribbling. They were timed while dribbling a soccer ball with both feet through a set of 6 cones, placed 6 steps apart. Decreasing times indicate improvement. P1's dribbling times decreased quickly during the first 2 weeks of treatment and then plateaued. P3's dribbling times decreased and became more consistent between the first and second 5-week blocks.
P2 chose to learn Tae Kwon Do. He was taught basic kicks, punches, blocks, and stances and performed a series of techniques that increased in difficulty over the duration of intervention. He was judged on a 3-point scale developed by the researcher on stance, punch, block, kick, and body position (15 points total) during the technique drills. Increasing scores or stable scores with more difficult moves indicate improvement. His score improved between the first and second 5-week blocks, and became more consistent during the third block. Improvement in the self-selected goal was not attributed to plyometric training and was used to motivate the child to participate.
P1 made consistent increases in throw distance in the first and second 5-week blocks of the intervention, and reached stability by the 16th session (8 weeks). P2 made consistent increases in throw distance in the first, second, and third 5-week blocks of the intervention and reached stability by the 23rd session (14 weeks). P2 missed 5 sessions because of personal reasons in the second 5-week block. P3 made consistent, though much smaller increases in throwing distance during the first and second 5-week blocks of the intervention and reached stability by the 19th session (week 9.5) (Figure 1).
All 3 participants were able to maintain the improvements made in throw and jump distance at the 6-week follow-up by demonstrating increases or minimal decreases (Figure 1). Running speed times were slower for all 3 participants. GMFM-66 scores (Table 5) and agility times (Table 6) declined for P1 at the 6-week follow-up.
This study evaluated the effects of plyometric training on gross motor ability, agility, running speed, and power in three 9- to 10-year-old boys with right unilateral spastic CP. All 3 participants improved upper extremity power. Gross motor ability, agility, and performance on their self-selected goal also improved. The effects of plyometric training on running speed and lower extremity power were inconsistent.
The greatest amount of information about the effect of the plyometric training program was gathered from monitoring the participants’ behaviors in the power tests. The single-subject design allowed flexibility to extend the intervention until throw distance plateaued, described the trajectory of change in the dependent variables that cannot be observed in before/after snapshots, and revealed the intra- and inter-individual differences. The ball throw test was the most responsive test for detecting change, similar to the responsiveness of the test reported in research on children who are typically developing. P3 had very stable responses during baseline. Intersession variability increased during treatment and may indicate that he went from a very rigid performance to having more variability and adaptability. P3 had a more severe MACS and may not have had the same capacity as P1 and P2 for making gains in throw distance.
The effect on lower extremity power was inconsistent. Because upper extremity power was chosen as the primary outcome, the intervention was begun before stability in baseline occurred in lower extremity power. Lower extremity power is significantly less in obese and overweight boys19 and may have taken longer to stabilize because of the need to move body mass for P2. When extreme variability was present in baseline, beginning the intervention resulted in participants becoming more consistent in achieving their best baseline performance. A similar pattern of improving throwing and jumping consistency was seen during a plyometric training program for children with neurofibromatosis type 1,30 where gains in consistency preceded gains in distance. The participants may have benefited from instruction and practice to optimize variability by either reducing highly variable responses or increasing variability of rigid or stereotypical responses during the resistive exercise intervention.35 The changes in running speed, which required lower extremity power, were inconsistent and similar to the responses seen in the lower extremity power tests.
Plyometric training resulted in medium to large changes in gross motor ability reflected in GMFM-66 score increases. The changes for 2 participants met the MCID scores for a large effect size of 2.7.34 The changes for the other participant met the MCID score for a medium effect size of 1.7. Improvements in the GMFM-66 score were attributed to dimension E because not all participants improved in dimension D. Two of the participants scored 100% on dimension E on the posttest, indicating a possible ceiling effect on the test. All 3 participants improved compared to age and severity-matched peers with CP by increasing their percentile points: 13.56% for P1, 64.67% for P2, and 16.26% for P3. P2's percentile point change was larger than 20%, indicating that the change was greater than that made by 80% of his peers with CP between 2 assessments.24 The test items on which P2 improved were vertical jump, balance on right leg, and walking downstairs.
P1, P2, and P3 also demonstrated changes in agility with improvement in times of 9.6%, 9.3%, and 9.1%, respectively. Verschuren et al26 published figures representing percentile curves for children with CP by severity, sex, and height for the 10×5-m sprint. P1 and P3's agility scores fell between the 75th and 97th percentile, and P2's between the 50th and 75th percentile at the pre- and postintervention assessment. However, because Verschuren et al26 did not report actual values, it is not possible to determine improvement in percentile point change. Meylan and Malatesta36 found a statistically significant improvement of 9.6% in an agility test in a group of typically developing 13-year-old boys who participated in an 8-week plyometric training program. The improvement in agility test times for the participants in this study (9.6%, 9.3%, and 9.1%) was similar to those reported in children with typical development.
This study also investigated the optimal duration of training. The ball throw distance plateaued at 8 weeks for P1, 14 weeks for P2, and 9 weeks for P3. Improvement was made in the first block of intervention, sometimes as early as 2.5 weeks. Some benefit was seen from extending intervention by adding the second and third blocks if gains had not occurred or if performance approached stability in the first block (P1, P2, and P3's throw, P2 and P3's broad jump, P2 and P3's vertical jump). The NSCA guidelines for resistive exercise in children recommend training for a minimum of 8 weeks. Our results suggest that participants must first gain consistency in skill performance before training for a minimum of 8 weeks. A longer duration may be necessary for participants to learn and perform the motor skill proficiently before gains in distance or height of jumping and throwing are observed. Additional time may also be necessary if personal or environmental factors prohibit training.
Finally, this study evaluated whether participants maintained the benefits after training was discontinued. The participants’ running speed declined at the 6-week follow-up, suggesting speed requires ongoing training to be maintained. Response rates were varied between and within participants and measures. Their performance may have been within the variability observed during intervention, rather than true change. However, more posttest measurements would be necessary to determine if the variability observed at follow-up was similar to the variability observed during treatment.
To some extent the gains in agility, running speed, and power may be appropriately attributed to growth. Philippaerts et al37 reported a relationship between growth and change in motor ability and fitness. These researchers followed a group of 10- to 13-year-old soccer players over a 5-year period and reported that peak height and weight velocity (rapid growth) occurred at the same time as peaks in balance, running speed, agility, strength, power, and anaerobic capacity. Because 2 of the participants grew during the intervention, height and weight gain may have contributed to their improved performance. González-Agüero et al13,14 reported increased bone mass and lean body mass in youth with Down syndrome. Gains in lean body mass and bone density may have contributed to the improvements we saw in BMI percentile; however, we did not measure these parameters. The homogeneity of the participants in this study limits generalizability of the results to children of different sex, ages, or disabilities. The capacity of the children, their response to treatment, and the outcome measures chosen would likely influence the results. The lack of improvement in lower extremity power may have been due to starting the intervention before stability in jump performance was observed. Both the upper and lower extremity power tests could have been used as primary measures by beginning the upper extremity exercises when stability had been observed in throwing, then adding the lower extremity exercises when stability in jumping had been achieved. There was a ceiling effect on the GMFM dimension E for 2 participants. Thus, different measures of high-level gross motor ability may need to be considered for children in GMFCS level I. The MCID values used to interpret change scores for the GMFM were reported for group differences and may differ on the basis of an individual's age.
Implications for Research
This research should be extended by evaluating the effectiveness of plyometric training in children with different classifications and severity of CP, different diagnosis, different ages, and in females. It is important to evaluate the use of more specific and sensitive measures for detecting change in jumping ability such as force plates, for high functioning children because of a potential ceiling effect on the GMFM. In addition, measures such as the Canadian Occupational Performance Measure or the Goal Attainment Scale could be used to measure self-selected goals.
Plyometric training resulted in improvements in upper extremity power, gross motor ability, and agility for all 3 participants. The effect on lower extremity power and running speed was inconsistent and may be attributed to the lack of stability in baseline before the intervention was begun, because the throw was chosen as the primary measure of stability. The influence of growth may have contributed to the changes in BMI percentile and should be considered when interpreting outcomes in children.
Optimal duration of training is likely dependent on the capacity of the child, restrictions that limit training, and the outcome instrument chosen. A pattern of improving consistency before making gains in distance or height was observed, suggesting that instruction and skill practice may be necessary before an 8-week plyometric exercise intervention. In sum, it is our recommendation that duration of the intervention should be determined individually by monitoring an individual's performance until consistency is achieved and then providing a minimum of 8 weeks of training.
Running speed declined at follow–up, suggesting that continuous training is required to maintain speed. Intra- and inter-participant differences were seen at the 6-week follow-up in gross motor ability, agility, and the power tests. The declines in performance may have been due to the lack of stability in the measurements rather than to a true change. More data points may be necessary to make a judgment about maintenance of motor performance after training has ended.
We thank Emily Sackett, Mark Lange, and Soffe Lowell for assistance with data collection. We also thank the participants and their families.
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activities of daily living; agility; cerebral palsy/hemiplegia; child; exercise physiology; humans; male; motor activity/physiology; motor skills/physiology; muscle strength/physiology; plyometric training; treatment outcome