Clinical trial NCT05627453: Arm-in-Arm Gait Training Trial
Official title: Helping Older People Recover Walking Abilities Through Arm-in-armg Gait Training: a Randomized Controlled Trial
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Healthy Aging
Keywords: fall risk
gait disorder
physical activity
complexity matching
Lead sponsor: Haute Ecole ARC Sante
Sponsor class: OTHER
Collaborators: name: Swiss National Science Foundation
First posted: 2022-11-25
Enrollment: 132
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: The AAGaTT study, is a monocentric, two-arm, open-label, randomized controlled trial. The superiority of arm-in-arm synchronized gait training will be assessed versus standard walking (i.e., walking side-by-side without gait synchronization).
Primary purpose: PREVENTION

Brief summary: The AAGaTT study, is a monocentric, two-arm, open-label, randomized controlled trial. The objective is to assess the efficacy of an arm-in-arm walking program for older people at risk of falling. Gait training imply that the older participants must walk while synchronizing steps with a younger partner.

Detailed description: A high level of physical activity is the cornerstone of healthy aging. Falls are a major issue in elderly population, and exercising can mitigate their occurrence. However, the type of exercise-and the optimal way to deliver it-that maximises efficacy is still unknown. The ideal-most efficient-exercise intervention should have the following characteristics: it should have a specific effect on fall risk mitigation, it should be of sufficient intensity to improve cardiovascular fitness and muscle strength, it should be safe, it should not induce high costs, and it should be sufficiently enjoyable and motivational to induce a high adherence and compliance. The present trial aims at testing an innovative exercise intervention that may exhibit all these advantages.

The intervention will consist in four weeks of 30min arm-in-arm synchronized gait training three times a week. Convincing evidence from the literature supports the use of rhythmic externals cues, either auditory or visual, to improve the efficacy of gait training for fall risk reduction in seniors. Synchronizing gait with a younger partner may bring further benefits.

We will focus on clinically relevant outcomes to highlight potential benefits of the intervention in term of gait quality, balance, fall risk mitigation, physical activity level, mood, and well-being.

Gait quality will be assessed through two inertial sensors attached to the low back and foot. Six gait assessement sessions are planned: at baseline (before randomization), at the end of each training week, and at week 7 (follow-up). Participants will walk at their preferred speed over 200m.

We will also include functional tests and self-filled questionnaires to evaluate participant's abilities and mood.

Falls occuring within 18 months after inclusion will be tracked via an online questionnaire every three months.

We will assess the superiority of arm-in-arm gait training compared to standard walking (without gait synchronisation) via a randomized-controlled design. The perception of the intervention by elderly participants will be explored via a qualitative analysis.

Eligibility criteria: Inclusion Criteria:

1. Older Participant

   * Older than 70 years old
   * Able to walk continuously during 15 minutes without walking aids.
   * Must have experienced a fall during the last year before the recruitment.
   * Health certificate that attests no contraindication to walking
   * No severe gait disorders from orthopedic or neurologic origins (such as lower-limb amputation or severe hemiparesis). Mild gait abnormalities (for example, mild limping due to knee arthritis, or slight gait asymmetry due to limited hemiparesis) will be tolerated.
2. Younger Participant

   * Older than 18 years old but younger than 40 years old.
   * No severe gait disorders from musculoskeletal or neurologic origin.

Exclusion Criteria:

* Inability to follow the procedures of the study, e.g., due to language problems, psychological disorders, dementia, etc.;
* Inability or contraindications to undergo the investigated intervention.
* Vulnerable persons, in sense of swiss Human Research Act art. 21-24.

Primary outcomes:
measure: Walking speed
timeFrame: Week 4
Secondary outcomes:
measure: Walking speed
timeFrame: Baseline
measure: Walking speed
timeFrame: Week 1
measure: Walking speed
timeFrame: Week 2
measure: Walking speed
timeFrame: Week 3
measure: Walking speed
timeFrame: Week 7 (follow-up)
measure: Average step frequency
timeFrame: Baseline
measure: Step frequency
timeFrame: Week 1
measure: Step frequency
timeFrame: Week 2
measure: Step frequency
timeFrame: Week 3
measure: Step frequency
timeFrame: Week 4
measure: Step frequency
timeFrame: Week 7 (follow-up)
measure: Step length
timeFrame: Baseline
measure: Step length
timeFrame: Week 1
measure: Step length
timeFrame: Week 2
measure: Step length
timeFrame: Week 3
measure: Step length
timeFrame: Week 4
measure: Step length
timeFrame: Week 7 (follow-up)
measure: Step symmetry
timeFrame: Baseline
measure: Step symmetry
timeFrame: Week 1
measure: Step symmetry
timeFrame: Week 2
measure: Step symmetry
timeFrame: Week 3
measure: Step symmetry
timeFrame: Week 4
measure: Step symmetry
timeFrame: Week 7 (follow-up)
measure: Stride regularity
timeFrame: Baseline
measure: Stride regularity
timeFrame: Week 1
measure: Stride regularity
timeFrame: Week 2
measure: Stride regularity
timeFrame: Week 3
measure: Stride regularity
timeFrame: Week 4
measure: Stride regularity
timeFrame: Week 7 (follow-up)
measure: Gait Stability
timeFrame: Baseline
measure: Gait Stability
timeFrame: Week 1
measure: Gait Stability
timeFrame: Week 2
measure: Gait Stability
timeFrame: Week 3
measure: Gait Stability
timeFrame: Week 4
measure: Gait Stability
timeFrame: Week 7 (follow-up)
measure: Gait attentional demand
timeFrame: Baseline
measure: Gait attentional demand
timeFrame: Week 1
measure: Gait attentional demand
timeFrame: Week 2
measure: Gait attentional demand
timeFrame: Week 3
measure: Gait attentional demand
timeFrame: Week 4
measure: Gait attentional demand
timeFrame: Week 7 (follow-up)
measure: Fractal index
timeFrame: Baseline
measure: Fractal index
timeFrame: Week 1
measure: Fractal index
timeFrame: Week 2
measure: Fractal index
timeFrame: Week 3
measure: Fractal index
timeFrame: Week 4
measure: Fractal index
timeFrame: Week 7 (follow-up)
measure: Stride time variability
timeFrame: Baseline
measure: Stride time variability
timeFrame: Week 1
measure: Stride time variability
timeFrame: Week 2
measure: Stride time variability
timeFrame: Week 3
measure: Stride time variability
timeFrame: Week 4
measure: Stride time variability
timeFrame: Week 7 (follow-up)
measure: Time to perform Timed up-and-go (TUG) test.
timeFrame: Baseline
measure: Time to perform Timed up-and-go (TUG) test.
timeFrame: Week 1
measure: Time to perform Timed up-and-go (TUG) test.
timeFrame: Week 2
measure: Time to perform Timed up-and-go (TUG) test.
timeFrame: Week 3
measure: Time to perform the Timed up-and-go (TUG) test.
timeFrame: Week 4
measure: Time to perform the Timed up-and-go (TUG) test.
timeFrame: Week 7 (follow-up)
measure: Average time held on a leg obtained following the Unipedal stance test
timeFrame: Baseline
measure: Average time held on a leg obtained following the Unipedal stance test
timeFrame: Week 1
measure: Average time held on a leg obtained following the Unipedal stance test
timeFrame: Week 2
measure: Average time held on a leg obtained following the Unipedal stance test
timeFrame: Week 3
measure: Average time held on a leg obtained following the Unipedal stance test
timeFrame: Week 4
measure: Average time held on a leg obtained accordion to the Unipedal stance test
timeFrame: Week 7 (follow-up)
measure: Score at the Geriatric Depression Scale (GDS)
timeFrame: Baseline
measure: Score at the Geriatric Depression Scale (GDS)
timeFrame: Week 4
measure: Score at the Geriatric Depression Scale (GDS)
timeFrame: Week 7 (follow-up)
measure: Score at the Falls Efficacy Scale International (FES-I)
timeFrame: Baseline
measure: Score at the Falls Efficacy Scale International (FES-I)
timeFrame: Week 4
measure: Score at the Falls Efficacy Scale International (FES-I)
timeFrame: Week 7 (follow-up)
measure: Level of physical activity over the last seven days
timeFrame: Baseline
measure: Level of physical activity over the last seven days
timeFrame: Week 4
measure: Level of physical activity over the last seven days
timeFrame: Week 7 (follow-up)
measure: Measure of the quality of life and well-being
timeFrame: Baseline
measure: Measure of the quality of life and well-being
timeFrame: Week 4
measure: Number of falls over the past year
timeFrame: Baseline
measure: Number of falls over three months
timeFrame: Between 0 and 3 months after the end of the training program (week 4).
measure: Number of falls over three month
timeFrame: Between 3 and 6 months after the end of the training program (week 4).
measure: Number of falls over three months
timeFrame: Between 6 and 9 months after the end of the training program (week 4).
measure: Number of falls over three months
timeFrame: Between 9 and 12 months after the end of the training program (week 4).
measure: Number of falls over three months
timeFrame: Between 12 and 15 months after the end of the training program (week 4).
measure: Number of falls over three months
timeFrame: Between 12 and 18 months after the end of the training program (week 4).
measure: Perception of the training program
timeFrame: Week 4
measure: Number of participants withdrawing from the study
timeFrame: Week 7 (follow-up)
Other outcomes:
Locations:
city: Neuchâtel
country: Switzerland
facility: Haute-Ecole Arc Santé
Study officials:
affiliation: Haute-Ecole Arc
name: Philippe Terrier, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Ghai S, Ghai I, Effenberg AO. Effect of Rhythmic Auditory Cueing on Aging Gait: A Systematic Review and Meta-Analysis. Aging Dis. 2018 Oct 1;9(5):901-923. doi: 10.14336/AD.2017.1031. eCollection 2018 Oct.
citation: Van Abbema R, De Greef M, Craje C, Krijnen W, Hobbelen H, Van Der Schans C. What type, or combination of exercise can improve preferred gait speed in older adults? A meta-analysis. BMC Geriatr. 2015 Jul 1;15:72. doi: 10.1186/s12877-015-0061-9.
citation: Sherrington C, Fairhall NJ, Wallbank GK, Tiedemann A, Michaleff ZA, Howard K, Clemson L, Hopewell S, Lamb SE. Exercise for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2019 Jan 31;1(1):CD012424. doi: 10.1002/14651858.CD012424.pub2.
citation: Almurad ZMH, Roume C, Blain H, Delignieres D. Complexity Matching: Restoring the Complexity of Locomotion in Older People Through Arm-in-Arm Walking. Front Physiol. 2018 Dec 4;9:1766. doi: 10.3389/fphys.2018.01766. eCollection 2018.
citation: Terrier P, Le Carre J, Connaissa ML, Leger B, Luthi F. Monitoring of Gait Quality in Patients With Chronic Pain of Lower Limbs. IEEE Trans Neural Syst Rehabil Eng. 2017 Oct;25(10):1843-1852. doi: 10.1109/TNSRE.2017.2688485. Epub 2017 Mar 28.
citation: Terrier P, Reynard F. Maximum Lyapunov exponent revisited: Long-term attractor divergence of gait dynamics is highly sensitive to the noise structure of stride intervals. Gait Posture. 2018 Oct;66:236-241. doi: 10.1016/j.gaitpost.2018.08.010. Epub 2018 Aug 14.
citation: Bohannon RW, Williams Andrews A. Normal walking speed: a descriptive meta-analysis. Physiotherapy. 2011 Sep;97(3):182-9. doi: 10.1016/j.physio.2010.12.004. Epub 2011 May 11.