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Trial registered on ANZCTR

Registration number

ACTRN12616000023459

Ethics application status

Approved

Date submitted

4/01/2016

Date registered

14/01/2016

Date last updated

3/03/2017

Type of registration

Retrospectively registered

Titles & IDs

Public title

Effects of two neuromuscular training programs on running biomechanics with load carriage: a randomized controlled trial

Scientific title

In a cohort of healthy runners, does a biomechanically informed neuromuscular training program, do better than a generic strength training program, in improving self-determined load carriage running velocity and biomechanics, lower limb strength and power?

Secondary ID [1]

Nil Known

Universal Trial Number (UTN)

U1111-1176-6844

Trial acronym

CARNET = CArriage Running NEuromuscular Training

Linked study record

Health condition

Health condition(s) or problem(s) studied:

Running biomechanics

Lower limb strength and power

Condition category

Condition code

Musculoskeletal

Normal musculoskeletal and cartilage development and function

Neurological

Studies of the normal brain and nervous system

Intervention/exposure

Study type

Interventional

Description of intervention(s) / exposure

The principle of this training program is that key neuromuscular requirements of load carriage running are targeted by specific neuromuscular exercises. All training is administered in small group sessions by trained Exercise and Rehabilitation therapists. Two one hour training programs will be delivered to the therapists by the principal investigator to standardize the training program. This program will involve three training sessions per week for 6 weeks (total 18 sessions), and will involve single leg (SL) hopping (at 2.2 Hz), countermovement jumps (CMJ), and hip flexor cable pull. Each session will last approximately 45 minutes. For the plyometric component (hop and CMJ), intensity will be varied using a weighted vest. For the hopping, intensity will also be varied by increasing the hopping frequency to a maximal of 3.0Hz. Another key focus of this training group is that non-optimal lower limb alignment are corrected using a mixture of visual, auditory and verbal cues. In order to maintain peak power application for the CMJ and hip flexor pull, a cluster set method will be used. For the CMJ and SL hopping, a starting weight of 5% body weight will be used, with a 5% weight increment per week, until a maximum load of 20% body weight is achieved. A maximal mass of 20% BM will be added, as previous studies have demonstrated a reduction in peak power with heavier mass. For the hip flexor pull, a starting weight of ~80% of one repetition maximum (1RM) will be used at week 1 progressing to ~ 88% of 1RM at week 6. For the hip flexor pull, a 1RM load will be adjusted by a weekly increase of a factor of 2.5% to account for weekly increase in strength. The SL hopping will involve 2 to 4 sets of 20 second hopping. The CMJ and hip flexor pull will involve 5 to 10 sets of a cluster of 2 to 3 reps, to maintain peak power. Adherence to the exercises will be ensured by the onsite trainers, using patient record sheets.

Intervention code [1]

Other interventions

Comparator / control treatment

The principle governing this training program is that participants perform progressively heavy isotonic resistance training, at intensities from ~80% of 1RM at week 1 progressing to ~ 88% of 1RM at week 6. All training is administered in small group sessions by trained Exercise and Rehabilitation therapists. Two one hour training programs will be delivered to the therapists by the principal investigator to standardize the training program.This program will involve three training sessions per week for 6 weeks (total 18 sessions). Inter-set rest duration of three to five minutes will be provided. Each session will last approximately 45 minutes. Exercises will include isotonic unilateral leg press, unilateral calf press, and Russian lunge. These exercises were selected as they represented generic lower limb exercises used in current load carriage training studies. For all exercises, a 1RM load will be adjusted by a weekly increase of a factor of 2.5% to account for weekly increases in strength. All exercises will be sub-maximal in intensity (i.e. repetition failure will not occur). Adherence to the exercises will be ensured by the onsite trainers, using patient record sheets.

Control group

Active

Outcomes

Primary outcome [1]

Self selected overground running speed with a 20% body weight load, using a backpack filled with sandbags to achieve the target weight, across a biomechanics labaratory, via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Timepoint [1]

Baseline (pre intervention) and week 7 (post intervention)

Primary outcome [2]

Running biomechanics (Joint work of hip, knee, ankle) via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Composite measure

Timepoint [2]

Baseline (pre intervention) and week 7 (post intervention)

Primary outcome [3]

Running biomechanics (Joint power of hip,knee,ankle) via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .
Composite measure

Timepoint [3]

Baseline (pre intervention) and week 7 (post intervention)

Secondary outcome [1]

Countermovement jump peak power via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Timepoint [1]

Baseline (pre intervention)
Mid trial (3rd week)
Week 7 (post intervention)

Secondary outcome [2]

Isokinetic strength test (60 degree/second) of Knee extensors (90 degree flexion to 0 degree) using HUMAC NORM dynamometer (Computer Sports Medicine Inc., Stoughton, MA)

Timepoint [2]

Baseline (pre intervention) and week 7 (post intervention)

Secondary outcome [3]

Running biomechanics (Joint angle of hip,knee,ankle) via via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .
Composite measure

Timepoint [3]

Baseline (pre intervention) and week 7 (post intervention)

Secondary outcome [4]

Isokinetic strength test (60 degree/second) of ankles extensors (5 degre dorsiflexion to 30 degree plantarflexion) using HUMAC NORM dynamometer (Computer Sports Medicine Inc., Stoughton, MA)

Timepoint [4]

Baseline (pre intervention) and week 7 (post intervention)

Secondary outcome [5]

Squat jump peak power via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Timepoint [5]

Baseline (pre intervention)
Mid trial (3rd week)
Week 7 (post intervention)

Secondary outcome [6]

Hopping leg stiffness via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Timepoint [6]

Baseline (pre intervention)
Mid trial (3rd week)
Week 7 (post intervention)

Secondary outcome [7]

Self selected overground running speed with no external load, across a biomechanics labaratory, via three dimensional motion analysis using force plates (AMTI, Watertown, MA) and 18 camera motion capture system (Vicon T-series, Oxford Metrics, UK) .

Timepoint [7]

Baseline (pre intervention) and week 7 (post intervention)

Eligibility

Key inclusion criteria

Participants between 18 and 60 years old who are in good general health, and are currently running or participating in running-related sports with an accumulated total distance of 45 minutes/week, will be recruited.

Minimum age

18 Years

Maximum age

60 Years

Sex

Both males and females

Can healthy volunteers participate?

Yes

Key exclusion criteria

1. Presence of any disorders that could affect their gait and load carrying ability.
2. Medical conditions that preclude heavy resistance training and strenuous running.
3. Presence of a training-loss running related injury within the last 3 months.
4. Current running related pain (except blisters or muscle soreness)}
5. Lower limb surgery within the past 12 months.
6. Females who are pregnant.

Study design

Purpose of the study

Prevention

Allocation to intervention

Randomised controlled trial

Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)

Sealed opaque envelopes

Methods used to generate the sequence in which subjects will be randomised (sequence generation)

Permuted stratified block randomization using computer generated sequence.

Masking / blinding

Blinded (masking used)

Who is / are masked / blinded?

The people assessing the outcomes

Intervention assignment

Parallel

Other design features

Phase

Not Applicable

Type of endpoint/s

Efficacy

Statistical methods / analysis

This study was powered on the effects of a core stability program on changes to hopping leg stiffness. Sample size was planned based on a two way, repeated measures ANOVA, using the Hotelling-Lawley Trace to test for an intervention by time interaction. Previous studies on leg stiffness reported a standard deviation of 3600 N/m, and a correlation between repeated measures of 0.80. For a desired power of 0.80, and a Type 1 error rate of 0.05, we need to enrol 24 participants to detect a between group mean difference of 3000N/m. In order to account for a 20% dropout over the 6 weeks intervention period, we will enrol 30 participants. All statistical analysis will be performed in R software within RStudio (Version 0.98.1062, RStudio, Inc.). Descriptive statistics (mean and standard deviation) will be calculated for baseline demographics of participants. Between groups difference in baseline demographics will be calculated using t-test or non-parametric test where appropriate. Analysis will be based on an intention-to-treat (ITT) using the multiple imputation method. A repeated measures linear mixed model with time, group, and their interaction as fixed effects, and participants clustered within groups as random effects will be used to analyse our discrete dependent variables. For the linear mixed model, significance will be set at a = 0.05. Statistical testing between group and within group mechanical wave form data (kinematics, kinetics) will be analysed using Statistical Parametric Mapping (SPM). Statistical significance will be inferred using Random Field Theory (RFT), with appropriate Bonferroni correction applied to retain a family-wise error rate of a = 0.05. SPM will be performed using spm1d package (v0.3) (www.spm1d.org), installed in Python 2.7, and implemented in Enthought Canopy 1.5.4 (Enthought Inc., Austin, USA).

Recruitment

Recruitment status

Completed

Date of first participant enrolment

Anticipated

18/01/2016

Actual

1/12/2015

Date of last participant enrolment

Anticipated

31/03/2016

Actual

24/03/2016

Date of last data collection

Anticipated

Actual

12/05/2016

Sample size

Target

Accrual to date

Final

Recruitment in Australia

Recruitment state(s)

Funding & Sponsors

Funding source category [1]

University

Name [1]

Curtin University Internal funding

Address [1]

Kent Street, Bentley, WA 6102

Country [1]

Australia

Primary sponsor type

Individual

Name

A/Prof Kevin Netto

Address

Curtin University, Kent Street, Bentley, WA 6102

Country

Australia

Secondary sponsor category [1]

None

Name [1]

Address [1]

Country [1]

Ethics approval

Ethics application status

Approved

Ethics committee name [1]

Curtin University Human Research Ethics Committee

Ethics committee address [1]

Kent street, Bentley, WA 6102

Ethics committee country [1]

Australia

Date submitted for ethics approval [1]

29/10/2014

Approval date [1]

30/07/2015

Ethics approval number [1]

RD-41-14

Summary

Brief summary

Background: Ultra-endurance and adventure racing are increasingly becoming popular with recreational and elite athletes. These athletes routinely carry some form of external loads, to transport various equipment for survival, navigation and sustenance. It has been well reported that load carriage impairs gait performance, with subsequent training studies conducted to identify if gait performance improved. However, most of these training studies were not of a randomized, controlled trials design, and they were largely conducted within the military setting. More importantly, exercise selections within current studies have not been based on known neuromuscular demands involved in load carriage gait patterns. Previous studies on load carriage in running have identified potential adaptive and mal-adaptive biomechanical alterations when load is imposed on running. Adaptive mechanical alterations are changes whose functions are to needed to sustain running speed, enhance postural control, support an increased weight and absorb shock. Mal-adaptive alterations are changes which could heighten the risk of incurring injuries, and reduce gait performance. It is hypothesized that a neuromuscular training that is targeted to known neuromuscular demands of load carriage running would compare better than a generic strength training program in improving load carriage running mechanics.
Methods: This study will be a two-arm, parallel randomized controlled trial with single assessor blinding. 30 healthy runners, aged 18 to 60 years, will be enrolled. The total duration of this study is 8 weeks, broken up into two phases. In the first phase, participants will undergo a common two weeks familiarization training sessions. They will undergo a pre and post biomechanics and strength testing assessment. A permuted block randomization procedure will be used as participants will be stratified based on gender (male/female). Allocation will be concealed using sealed-opaque envelopes. After baseline assessments, participants will be randomized into either a targeted or a general neuromuscular training program. Both programs will involve three supervised sessions per week for six weeks. A mid assessment will be conducted during the 3rd week with regards to maximal jumps and hops.
Statistical analysis: Baseline demographic variables will be compared using parametric and non-parametric tests, where appropriate. Descriptive statistics (mean and standard deviation) will be calculated. A linear mixed model will be used to identify between group and within group by time changes in discrete dependent variables. Statistical Parametric Mapping will be used to identify between and within group by time changes in time-continuous dependent variables. Statistical inference will be made at a family wise error rate of a = 0.05.

Trial website

Trial related presentations / publications

Submissions are pending and will be filled up when accepted

Public notes

Contacts

Principal investigator

Name

Mr Bernard Liew

Address

School of Physiotherapy and Exercise Sciences, Curtin University, GPO Box U1987, Perth, WA 6845

Country

Australia

Phone

+618 9266 3689

Fax

+618 9266 3699

b.liew@postgrad.curtin.edu.au

Contact person for public queries

Name

Kevin Netto

Address

School of Physiotherapy and Exercise Sciences, Curtin University, GPO Box U1987, Perth, WA 6845

Country

Australia

Phone

+618 9266 3689

Fax

+618 9266 3699

Kevin.Netto@curtin.edu.au

Contact person for scientific queries

Name

Kevin Netto

Address

School of Physiotherapy and Exercise Sciences, Curtin University, GPO Box U1987, Perth, WA 6845

Country

Australia

Phone

+618 9266 3689

Fax

+618 9266 3699

Kevin.Netto@curtin.edu.au

No information has been provided regarding IPD availability

What supporting documents are/will be available?

No Supporting Document Provided

Results publications and other study-related documents

Documents added manually

No documents have been uploaded by study researchers.

Documents added automatically

Source	Title	Year of Publication	DOI
Embase	Effects of two neuromuscular training programs on running biomechanics with load carriage: a study protocol for a randomised controlled trial.	2016	https://dx.doi.org/10.1186/s12891-016-1271-9

N.B. These documents automatically identified may not have been verified by the study sponsor.

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