# Influence of a multicomponent exercise intervention on fear of falling and gait parameters in community-dwelling older adults: a prospective study

Aymeric Courtay-Breuil, Leo Delaire, Joannès Humblot, Thomas Gilbert, Mylène Aubertin-Leheudre, Marc Bonnefoy

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Aymeric Courtay-Breuil, Leo Delaire, Joannès Humblot, Thomas Gilbert, Mylène Aubertin-Leheudre, et al. Influence of a multicomponent exercise intervention on fear of falling and gait parameters in community-dwelling older adults: a prospective study. BMC Geriatrics, 2025, 25 (1), pp.668. 10.1186/s12877-025-06257-1. doi:10.1186/s12877-025-06257-1

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1 Influence of a multicomponent exercise intervention on fear of falling and gait parameters in community-dwelling older adults: a prospective study

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3 COURTAY-BREUIL Aymeric ¹,²,⁵, DELAIRE Leo ¹,⁴, HUMBLOT Joannès ¹, GILBERT Thomas ¹,⁵, AUBERTIN-LEHEUDRE Mylène ²,³*, BONNEFOY Marc ¹,⁴*.

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5 * equally senior author

6 ¹ Hospices Civils de Lyon, Hôpital Lyon Sud, Service de médecine du vieillissement, Pierre Bénite cedex F 69495, France.

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8 ² UQAM, Faculté des Sciences, Département des Sciences de l'Activité Physique, Montréal, Qc, Canada

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10 ³ Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal, Qc, Canada

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12 ⁴ Inserm 1060-CarMeN, Université Claude Bernard Lyon 1, 69100 Villeurbanne, France.

13 ⁵ RESHAPE Research on Healthcare Professionals and Performance, Inserm U1290, Université Claude Bernard Lyon 1, 69008 Lyon, France

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15 Corresponding author: Aymeric COURTAY-BREUIL; aymeric.courtay@chu-lyon.fr

16 5934 words

17 5 data elements, 63 references
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**Backgrounds:** The effects of exercise interventions on gait parameters and fear of falling (FOF) have been under-explored and the influence of FOF on exercise-induced adaptations of gait parameters is unclear. This interventional and comparative pilot study aimed to explore the influence of FOF status on gait parameters changes following a multicomponent exercise intervention in community-dwelling older adults at risk of mobility disability and implemented in routine care.

**Methods:** One-hundred five older adults (80.63 ± 5.80 years) completed a supervised group-based exercise (6-8 participants) intervention (10 weeks, 2x/week, 1h). Participants of this open cohort and prospective study were divided a-posteriori in 2 subgroups: with FOF subgroup (Falls Efficacy Scale-International (FES-I) > 23; n=64) or without FOF subgroup (FES-I ≤ 23; n=41). A two-way repeated measure ANOVA was performed to measure time, group and group*time interactions effects. Paired t-test were performed to measure changes within the subgroups. Correlations were performed between FOF delta's changes and gait parameters changes. Spatiotemporal gait parameters (i.e gait speed; stride variability, symmetry, length; swing, stance and double support phases; lift and strike angles; number of cycles at the turn; turning angle), perceived gait quality (i.e the "Locomotion" domain of the "SarQoL®" questionnaire), functional parameters (i.e Short Physical Performance Battery and its subtests; Timed Up and Go) and FOF were assessed.

**Results:** A time effect was observed for all spatial gait parameters (p < .05), all functional parameters (p < .001), perceived gait quality (p < .001) and FOF (p < .01) assessed after the intervention for the total cohort. A group effect was observed for FOF (p < .001), spatiotemporal gait parameters (p < .05) and perceived gait quality (p < .001). A group*time interaction was only observed for FOF (p < .001). Stride length, lift off angle, strike angle and turning angle (p < .05) improved in both subgroups. Stride variability (p < .05) and FOF (p < .001) improved
only in the FOF subgroup. Correlations between gait parameters changes and FOF changes
were only observed in FOF subgroup for double support phase (r =0.25, p < .05), swing phase
(r =-0.25, p < .05) and stance phase (r =0.25, p < .05). A moderate correlation was observed
between FOF changes and perceived gait quality changes (r =-0.49, p < .01) in no-FOF
subgroup. This correlation became weak for the total cohort (r =-0.25, p < .05).

Conclusions: Our results demonstrate that a multicomponent exercise intervention lead to significant changes in FOF, spatial gait parameters and perceived gait quality in older adults and more in those with FOF. Thus, this routine care intervention could be widely proposed to older adults at risk of falls, and particularly to those with a FOF. Finally, although FOF and gait parameters are related, their changes over time do not seem to be as related. This study confirmed that managing the FOF is complex, multifactorial and might be orientated to a holistic approach.

Trial Registration Number: NCT03667664 (registration date: 12/09/2018) and
NCT06659484 (registration date: 26/10/2024).

57 **Key words:** Gait, Fear of falling, Prevention, Mobility, Exercise, Real-life care setting
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Introduction

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Around 30% of older adults over 65 years old fall every year[1]. Falls may lead to serious injuries (such as fractures) but also to psychological issues notably fear of falling (FOF)[1,2]. FOF or concern about falling, defined as « a persistent feeling related to the risk of falling during one or more activities of daily living »[3], is a widespread and a complex syndrome in older adults[4]. FOF can be considered as protective response in order to avoid at-risk activities (walking on slippery or uneven surfaces, etc.)[5]. Nevertheless, FOF may lead to physical activity restriction and/or sedentary behavior that, in turn, cause a deconditioning vicious circle and consequently a decline in physical and postural function, social network, mental health and quality of life[4–6]. Moreover, FOF and physical inactivity are closely related to the development of geriatric syndromes such as frailty and sarcopenia, which ultimately lead to an increased risk of falling[3–6]. Thus, FOF should therefore be considered as a risk factor of fall and disabilities[5,7].

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FOF may also interfere with gait parameters and lead to gait disorders[8–12]. The decline of gait parameters, especially slowing of gait speed, could correspond to protective mechanisms in response to declining functional reserve and altered balance[8–10,12,13]. Functional reserve is defined as “the overall ability to compensate for the adverse effects of impairments, or recover from acute challenges to prevent functional loss in normal life”[14]. The functional reserve decline is associated with an alteration of various physiological system from whom the central nervous system which negatively impact the motor control system and could subsequently induce a decrease of dynamic balance control and thus gait parameters[15]. A decrease in gait speed is generally observed in physiological aging[16,17], but gait speed and associated spatiotemporal parameters (i.e. reduced stride length, increased double support time, increased stride variability, etc.) are even more affected in fallers and those with FOF[7,9,10,18,19]. As the increase of falls, fear and physical function (i.e. strength, gait
parameters, balance etc.) decline are all predictors of each other it is of the utmost importance
to grasp this spiraling effect in the context of falls prevention [20]. Therefore, improving older
adults' functional reserve in order to enhance mobility by better gait parameters and to reduce
FOF should be targeted through specific fall prevention programs [1,20-22].

It is now well established that multicomponent exercise interventions are highly effective
to improve several parameters such as gait and balance, and notably gait speed[19,23].
Nevertheless, changes in spatiotemporal gait parameters have been poorly explored and require
specific analysis[19]. Furthermore, the effectiveness of exercise on FOF remains unclear, with
a small-to-moderate level of evidence[24-26]. Optimizing exercise adaptations on gait
parameters, FOF and physical function and thus reduce fall risk is crucial. Therefore, it appears
necessary to explore changes in gait parameters following exercise interventions, and to
highlight influence of FOF status.

The main goal of this study was to explore the influence of FOF status on gait parameters
changes following the intervention in community-dwelling older adults at risk of mobility
disability. We also aimed to provide new data on specific gait parameters changes during an
exercise program and thereby contribute to filling the knowledge gap in this field. While we
expected to observe a moderate effect of the intervention on FOF, we hypothesized that older
adults with a FOF at baseline may improve their gait parameters to a greater extent than those
without FOF at baseline. Finally, we hypothesized that an improvement in gait parameters
would be associated with a decrease in FOF.

103 Methods

104 1. Study design, participants and setting

A monocentric prospective and comparative pilot study (phase 2 ORBIT) was conducted
on a cohort of adults aged 70 years or older to participate to the “well on my legs” exercise
intervention[27]. Participants were recruited between July 2020 and July 2023 and were included when they were diagnosed with a mobility disability risk. A mobility disability risk was defined as the presence of, at least, one of these criteria: short physical performance battery [SPPB] score < 10, presence of a dynapenia or a sarcopenia, reduced gait speed (≤0,8 m/s), reduced physical activity (reported by the Rapid Assessment of Physical Activity questionnaire[28] with a score < 6), exhaustion, FOF and at least one fall within the last 12 months [1,14,23,27,29,30]. This risk was assessed during a multidimensional consultation (medical, physical, and nutritional) with 3 professionals (geriatrician, dietician, and kinesiologist) in accordance with international recommendations for dynapenia, sarcopenia, physical activity, exhaustion, FOF and fall risk [1,23,29,30]. Participants with severe disability were not included in this current-care intervention and re-oriented to other specialized professionals. We considered as severe disability: SPPB score <5; high cardiovascular risk (non-stabilized coronary illness, decompensated heart failure, non-stabilized arrhythmia, severe and symptomatic aortic stenosis, uncontrolled arterial hypertension, aortic dissection, acute myocarditis, pericarditis or endocarditis, acute thromboembolic disease, severe pulmonary hypertension, Marfan syndrome, non-stabilized type 2 diabetes mellitus, non-stabilized orthostatic hypotension); heavy locomotive handicap (needs a wheelchair); high cognitive impairment, or dementia (previously diagnosed in specialized consultation or inability to follow a small-group session)[31]. Due to the nature of this study, neurological conditions, vestibular or orthopedic disorders were not considered as exclusion criteria as long as they were able to follow the program. To be included in these analyses, participants had to complete at least 15 collective exercise sessions (out of 20 sessions).

This study was approved by the scientific and ethical committee of the Hospices Civils de Lyon (France) (NCT03667664, registration date: 12/09/2018 and NCT06659484,
registration date: 26/10/2024). This study complies with the Helsinki Declaration as after
receiving detailed information, all study participants signed on their informed consent form.

## 2. Exercise intervention

As described previously[27] the multicomponent exercise intervention is implemented
as a current-care intervention in real-life settings in the area of Lyon, France. This intervention
is in line with the current recommendations for older adults presenting frailty, mobility
disability and falls[1,23,31]. Briefly, during the intervention, the participants followed one hour
of supervised group-based sessions (6 to 8 participants) twice a week during 10 weeks (total of
20 sessions). Trained kinesiologists supervised the exercise sessions which included three
progressive phases to optimize physiological adaptations. Each session included a warm-up, a
combined resistance (i.e. using elastic band, dumbbells or at body-weight) and balance
exercises (i.e. unipodal or tandem balance), adapted physical activities (i.e. individual or in
teams, dribbling with a ball, passing between participants, shooting into a basket; passing over
a net with a racket and a balloon, etc.), gait retraining (i.e. walking with change pace, tandem
walking, heel-to-toe walking, obstacle-clearing exercises) and a cool-down phase with
stretching. Resistance exercises were mainly focused on quadriceps, hamstrings, iliopsoas,
gluteal, plantar and dorsi flexors muscles for lower limbs. The main muscle groups of the upper
body were mobilized, including the biceps and triceps brachii, pectoralis major, deltoids, rotator
cuff muscles, trapezius, rhomboid, dorsalis major, erector spinae and abdominal muscles. Each
exercise was performed over a range of 2 to 3 sets of 6 to 15 repetitions with a perceived effort
(using the Borg CR10 scale) ranging from light to moderate and moderate to vigorous
depending on the participant's physical capacities and medical conditions. To monitor
perception of effort, kinesiologists asked participants "how hard, heavy and strenuous the
previous exercise was to perform"[32]. At first, the targeted intensity was light to moderate.
According to planned progress, any potentials relative medical contraindications and when
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participants were performing correctly exercise without pain (during and after sessions), the
intensity was increase[31]. The Borg CR10 scale was used to assess difficulties to perform the
exercises in order to, adjust the number of repetitions, the range of motion, the task complexity
(i.e. adding or removing a weight and/or movement) and the rest time[27].

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3. **<u>Data collection</u>**

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Geriatricians and trained kinesiologists performed assessments and collected data
during baseline and reassessment visits as previously described[27]. They were not blinded as
it was performed in current care setting.

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i. <u>General characteristics:</u>

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In addition to age, weight and height, a self-reporting of falls in the last 12 months was
collected at baseline.

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ii. <u>Gait parameters:</u>

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Gait parameters were measured using two validated shoe-worn inertial sensors
"PhysiLog®5"ª during a fifty meters walking test[33]. The test was performed at usual speed
over a twenty-five meters round trip. The sensors were set on each shoe, under the malleolus.
All cycles, except the two initiation and termination cycles to rule out the acceleration and
deceleration phases, were included and analyzed[34]. Gait parameters were obtained using the
MindMaze© analysis packageᵇ and characterized through validated spatiotemporal (gait speed,
m/sec), temporal and spatial gait parameters.

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More specifically the analyzed temporal gait parameters include : 1) Stride variability
(coefficient of variation of cycle duration; in percent), 2) Stride symmetry (ratio of swing times
which compared the time in the air between both feet; in percent), 3) Swing phase (portion of
the cycle during which the foot was in the air and did not touch the ground; in percent), 4)
Stance phase (portion of the cycle during which a part of the foot touched the ground; in

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percent), 5) *Double support phase* was calculated as the portion of the cycle where both feet touched the ground, in percent. The *spatial gait parameters* include: 1) *Stride length* (distance, in meters, between two successive steps on the ground, from the heel of a foot to the heel of the same foot, one cycle after), 2) *Lift off angle* (angle between the foot and the ground at the end of the push phase, just before the start of swing phase), 3) *Strike angle* (angle between the foot and the ground at heel strike on a vertical plane), 4) *Turning angle* (angle between two consecutive foot-flat phases of the same foot on a horizontal plane, we selected the maximum value), and 5) *Number of cycles at the turn* (sum of cycles to complete the turn). To facilitate analyses, the mean value of the two feet was used for these variables: swing phase, stance phase, stride length, strike angle, lift off angle and turning angle. Lift off and strike angle were used to assess plantar roll.

As there are no minimal detectable changes for gait parameters in this population (except for gait speed: +0.1 m/s[35]), we cannot use reliable changes values. However, reference values were presented in a recent study of Dapp et al. (2022)[15].

### iii. Fear of falling (FOF):

The FOF was assessed using the Falls Efficacy Scale International (FES-I) questionnaire, which is the recommended tool to assess the “concern about falling” on community-dwelling older adults[1,3,36]. The FES-I is a self-report questionnaire with 16 items. Each item is graduated from 1 (not at all concerned) to 4 (very concerned) with sub scores of 2 (somewhat concerned) and 3 (fairly concerned). The sum of all the items provides a score ranging from a minimum of 16 to a maximum of 64[3,36]. Among the participants who completed the intervention and based on the validated FES cut point[3], participants with a FES score > 23 were included in the FOF subgroup (n= 64) whereas those with a FES score ≤ 23 were included in the no-FOF subgroup (n=41).
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There are no minimal detectable changes for FES-I score in this population, we cannot
use reliable changes values. However, we could use the effect size by referring a recent meta-
analysis of Feng et al. (2022) (i.e. effect size of -0.34)[26].

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### iii Physical performances and functional capacities:

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We assessed objectively physical performance and functional capacities through the
following validated tests: 1) *Short Physical Performance Battery (SPPB)*[37], 2) normal 6-
meters gait speed test[29], 3) 5 times sit-to-stand test (5-STS)[29], and 3) normal 3-meters
Timed Up and Go (TUG)[29]. We also assessed participant's perceived gait quality through the
"Locomotion" domain of the "SarQoL®" questionnaire[38]. This domain assesses the
limitation in waking time, walking speed, number of outings outdoor, steps length, the feeling
of fatigue when walking, difficulties to cross a road fast enough and difficulties to walk on
uneven grounds[38].

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## 4. Statistical analysis

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Participants were analyzed on a per protocol analysis. Variables were expressed as mean
plus or less standard deviation (SD) or count (percentage). Normality was checked with
Kolmogorov-Smirnov test or Shapiro-Wilk test for sample higher than 50 and lower than 50
respectively. Statistical difference was considered, for all variables, when *p* < .05. A two-way
repeated measures analysis of variance (ANOVA) was conducted to evaluate the time effect
(pre and post intervention, for the total cohort), the group effect (FOF vs no-FOF subgroup)
and the effect of time*group interaction. As the participant subgroups were different at baseline,
we needed to perform paired t-tests to study the pre/post differences for the two FOF subgroups
of participants. For variables that did not respect the ANOVA requirements (Mauchly or
Greenhouse-Geisser sphericity and Levene's homogeneity), we conducted non-parametric tests
(Mann-Whitney and Wilcoxon tests for inter and intra group differences respectively). For these
non-parametric variables, we assessed the group*time interaction by comparing the delta

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change (post-pre values) between FOF subgroups. To measure the effect size, we used the
Cohen's D (values of d = .20, d = .50, and d = .80 indicate small, medium, and large effect
sizes)[39]. Finally, Spearman and Pearson correlations, according to normality, between FES-
I score delta changes and gait parameters delta changes were conducted to explore potential
inter-relationship. A correlation was weak when r ≤ .30, moderate when .30 < r < .50 and strong
when r ≥ .50[40]. All data were analyzed using IBM SPSS Statistics version 21 (IBM Corp.,
Armonk, NY, USA)ᶜ.

236 **<u>Results</u>**

237 **1. <u>Baseline characteristics</u>**

As shown in Figure 1, among the 480 participants who completed an initial assessment, 42.1% were included in the group sessions, 24.8% had no risk factors, 12.1% were redirected to another intervention and only 10.2% refused to take part in the group sessions despite the medical indication to participate. When the study was carried out, among the 202 participants included in the collective sessions, 61.4% were reassessed, 31.7% were still participating in the collective sessions and have not completed all 20 sessions in the collective sessions (as data were obtain through a current-care program), and only 6.9% stopped attending before the end (mainly for health reasons, unrelated to the intervention). No significant difference was observed between participants who dropped out of the study and the subgroup with FOF. All these results are detailed in the additional table in the appendix.

Among the total cohort analyzed, 105 participants (79 women and 26 men, 80.63 ± 5.80 years old) met the inclusion criteria. The sample included 59.05% of non-fallers, 19.05% of single fallers and 21.90% of multiple fallers and reported an average FES-I score of 27.55 (±8.17).
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The subgroup of participants with FOF included 64 older adults (52 women and 12 men, 80.67 ± 5.77 years old). Among the FOF subgroup, 54.69% were defined as non-fallers, 17.19% as single fallers and 28.12% as multiple fallers. The average FES-I score in the FOF subgroup was 31.98 (±7.49).

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The subgroup of participants without FOF (41 older adults: 27 women and 14 men, 80.56 ± 5.94 years old) included 65.85% of non-fallers, 21.95% of single fallers and 12.20% of multiple fallers. The average FES-I score in the no-FOF subgroup was 20.63 (±2.15). More details on Table 1.
<figure><img src="image_2.png" /><figcaption>Figure 1: Flow chart</figcaption></figure>
<table><caption>Table 1: Baseline characteristics of all participants and subgroups.</caption><thead><tr><th></th><th>Participants<br>(n=105)</th><th>Fear of Falling<br>subgroup<br>(n=64)</th><th>No-Fear of Falling<br>subgroup<br>(n=41)</th></tr></thead><tbody><tr><td>Age (y)</td><td>80.63 ± 5.8</td><td>80.67 ± 5.77</td><td>80.56 ± 5.94</td></tr><tr><td>Sex (n. %)</td><td>♀: 79 (75.24%)<br>♂: 26 (24.76%)</td><td>♀: 52 (81.25%)<br>♂: 12 (18.75%)</td><td>♀: 27 (65.85%)<br>♂: 14 (34.15%)</td></tr><tr><td>Weight (kg)</td><td>69.03 ± 16.3</td><td>69.05 ± 15.55</td><td>68.99 ± 14.35</td></tr><tr><td>Height (cm)</td><td>160.21 ± 9.14</td><td>159.23 ± 8.63</td><td>161.74 ± 9.81</td></tr><tr><td>BMI (kg/m²)<sup>a</sup></td><td>26.82 ± 5.42</td><td>27.10 ± 5.84</td><td>26.34 ± 4.76</td></tr><tr><td>Falls/pers (n)<sup>b</sup></td><td>1.02 ± 2.63</td><td>1.29 ± 3.23</td><td>0.63 ± 1.22</td></tr><tr><td>Non-fallers (n, %)</td><td>62 (59.05%)</td><td>35 (54.69%)</td><td>27 (65.85%)</td></tr><tr><td>Single fallers (n, %)</td><td>20 (19.05%)</td><td>11 (17.19%)</td><td>9 (21.95%)</td></tr><tr><td>Multiple Fallers (n, %)</td><td>23 (21.90%)</td><td>18 (28.12%)</td><td>5 (12.20%)</td></tr><tr><td>FES-I (/64)<sup>c</sup></td><td>27.55 ± 8.17</td><td>31.98 ± 7.49</td><td>20.63 ± 2.15</td></tr></tbody></table>

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## 2. Changes after the intervention for the total cohort

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### i. Changes in gait parameters and gait quality perception

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First, we observed a time effect for the locomotion SarQoL score ($p < .001$) and for all spatial parameters that improved significantly after the multicomponent exercise intervention ($p < .05$). No time effect was observed for the temporal gait parameters. Nevertheless, we observed a tendency towards improved stride variability ($p = .065$) (Table 2). Moreover, the locomotion SarQoL score exceed the smallest detectable change for group of 0.85 point (+4.56 points)[41].

<footnote><sup>a</sup>BMI: Body mass index. <sup>b</sup>Number of self-reported falls during the last 12 months per person. When participants reported only one fall, they were considered as "single fallers". When they reported two or more falls, they were considered as "multiple fallers". <sup>c</sup>FES-I: Falls Efficacy Scale International questionnaire. "Fear of Falling subgroup": participants with FES-I baseline score >23/64. "No-Fear of Falling subgroup": Participants with FES-I baseline score ≤ 23/64. Quantitative variables are expressed as mean ± standard deviation, qualitative variables are expressed as count (percentage).</footnote>
## ii. Changes in FES-I score and physical function

As shown in Table 2, a time effect was observed for the FES-I score that significantly decrease ($p < .01$) after the multicomponent exercise intervention. There is no minimal detectable change or minimal important change for FES-I score, however we found an effect size of -0.22 that is lower to the one found in a recent meta-analysis (effect size of -0.34)[26]. A time effect was also observed for all physical and functional parameters (SPPB score, 5-STS time, 6-m gait speed, TUG time, and 50-m gait speed) that improved significantly ($p < .001$). Moreover, SPPB score and 5-STS time reached a clinical meaningful difference (+1.18 points and -3.05 second respectively)[35,37]. Finally, 6-meters gait speed was close to reach the clinical threshold of +0.1 m/s (+0.09 m/s)[35].

## INSERT TABLE 2

### 3. Changes after the intervention per subgroups of FOF

#### i. Changes in gait parameters and gait quality perception

A group effect was observed for the locomotion SarQoL score ($p < .001$), all spatial and temporal gait parameters ($p < .05$) except for the stride symmetry ($p = .297$). Gait quality perception ($p < .01$), all spatial gait parameters ($p < .05$) and stride variability ($p < .05$) were significantly improved in the FOF subgroup. Gait quality perception ($p < .05$) and all spatial gait parameters ($p < .05$), except for the number of cycles at the turn ($p = .144$), were significantly improved for the no-FOF subgroup. Nevertheless, no time*group interaction was observed for gait parameters and gait quality perception (a FES-I: Falls Efficacy Scale International questionnaire. $^b$SPPB: Short Physical Performance Battery. $^c$5-STS: 5 times sit-to-stand test. $^d$TUG: Timed Up and Go test. "Fear of Falling subgroup": participants with FES-I baseline score $>23/64$. "No-Fear of Falling subgroup": Participants with FES-I baseline score $\le 23/64$. p Values are significant at values $< .05$. Significant values are highlighted in bold. d: d of Cohen's effect size.
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Moreover, the locomotion SarQol score exceed the smallest detectable change for group of 0.85 point for the FOF and the no-FOF subgroup (+5.45 and +3.12 points respectively)[41].

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## ii. Changes in FES-I score and physical function

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A group and a time\*group interaction effects were only observed for the FES-I score ($p < .001$). The FES-I score was only decreased for the FOF subgroup ($p < .001$; a FES-I: Falls Efficacy Scale International questionnaire. $^b$SPPB: Short Physical Performance Battery. $^c$5-STS: 5 times sit-to-stand test. $^d$TUG: Timed Up and Go test. "Fear of Falling subgroup": participants with FES-I baseline score >23/64. "No-Fear of Falling subgroup": Participants with FES-I baseline score $\le 23/64$. $p$ Values are significant at values $< .05$. Significant values are highlighted in bold. $d$: $d$ of Cohen's effect size.

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SPPB score, 5-STS and TUG were improved in both FOF subgroups ($p < .05$; Table 3).

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In FOF subgroups, SPPB score and 5-STS time reached a clinical meaningful difference (+1.32 points and -3.3 second respectively)[35]. The FES-I effect size was -0.39 for the FOF subgroup that is higher to the one found in a recent meta-analysis (effect size of -0.34)[26]. In no-FOF subgroup, 5-STS time reached a clinical meaningful difference (-2.28 second) and SPPB score was close to reach the clinical threshold of +1 (+0.95 points)[35,37].

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## INSERT TABLE 3

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## 4. Correlation between FES-I score deltas and gait parameters deltas

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Significant correlation, albeit weak, were observed between the FES-I score delta change and the double support phase delta ($r =0.25, p < .05$), the swing phase delta change ($r =-0.25, p < .05$) and the stance phase delta ($r =0.25, p < .05$) in FOF subgroup only. No other significant correlation was observed in objectives gait parameters. Nevertheless, a moderate and significant correlation was observed between the FES-I score delta and the locomotion

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SarQol score delta ($r=-0.49, p < .01$) in no-FOF subgroup. This correlation became weak for the total cohort ($r=-0.25, p < .05$) (Table 4).

# INSERT TABLE 4

## Discussion

The main goal of this study was to explore the influence of FOF status on gait parameters changes following the intervention in community-dwelling older adults at risk of mobility disability. We also aim to provide new data on specific gait parameters changes during an exercise program and thereby contribute to filling the knowledge gap in this field. The main result of this study is the absence of robust associations between spatiotemporal gait parameters changes and FES-I changes following the exercise intervention. In addition, this study shows that, while perceived gait quality, spatial gait parameters and functional capacity were improved for all participants after the exercise intervention, FES-I score was only reduced in the FOF subgroup.

### 1. Changes of gait parameters after the exercise intervention

First, it is interesting to notice that spatial parameters, gait speed and gait quality perception increased significantly after the intervention for the total cohort. This suggests that spatial gait parameters and gait speed may exert a greater influence on older adults' perception of their gait quality than temporal gait parameters. Perception of improvement in gait quality could be a good lever to support involvement to this type of intervention[42].

Considering the association between quadriceps strength (i.e. 5-STS)[43] and some gait parameters, such as speed and stride length[44], it is therefore consistent to observe an improvement in these parameters after the intervention[45]. The effectiveness of exercise interventions in improving gait speed is now widely established and our results are in line to those observed in other studies[19,35]. In a recent systematic review, only one study
investigated the effect of resistance training on specific spatiotemporal gait parameters and
observed a greater positive difference on stride length than in our study[19,46]. This study
proposed a 16-weeks exercise intervention with three exercises sessions (one supervised
collective session and two home sessions per weeks). Participants had to complete thirteen
exercises during a session. They used elastic band with a progressive increase of intensity and
volume as we did. The difference in results with our study observed could be explained by a
higher duration and volume of training. Another recent study, also observed a positive effect
on several gait parameters including stride length on hospitalized older adults with a “Square-
Stepping Exercise” protocol[47]. The intervention was performed five times a week (30-
minutes) during 3-weeks with three specific session of square-stepping at body weight.
Participants of this study performed a higher volume of training per week but in a shorter
duration. Moreover, participants were hospitalized. Nevertheless, these studies showed that gait
improvement could be achieved using different protocols and provided that the exercise was
progressive, adapted and of sufficient volume. However, it is noteworthy that devices used (i.e.
GAITRite) and the test condition were different (i.e. straight walking) that could change the
results[48]. Using a 50-m distance with a half-turn could induce more tiredness than a 10-m
distance in a straight-line for older adults at risk of mobility disability.

The observed improvements of the plantar roll after the intervention seem consistent
with the increase in stride length[49]. It is assumed that this change may be due to an increase
in the strength of the plantar flexors and extensors[50] and/or an improvement in the distal
proprioceptive capacity of the lower limbs[51]. The practice of exercises to stand on tiptoe,
heel-to-toe walking, changing walking pace, tandem walking, obstacle-clearing exercises,
might also have been useful. Half-turn quality (ie. the number of cycles required to make a half-
turn and half-turn angle) was also one of the spatial parameters that changed positively after the
intervention. In our study, the improvement in half-turn quality may consequently results into
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better TUG performances following the exercise intervention together with the increase of gait speed and 5-STS.

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Surprisingly, temporal gait parameters remained unchanged after the exercise intervention. Regarding stride variability, this result was unexpected, as stride variability is regularly used to characterize gait parameters in older adults[52]. Given that stride variability is associated with quadriceps power[53], we could expect to obtain improvements in stride variability as 5-STS increased in the total cohort and in both subgroups[54]. Yet, only a tendency was observed for this parameter. It seems that the effects of exercise on stride variability may differ from study to study, due to different training modalities (duration, intensity, volume)[45,55-57]. It is also worth noting the difference in the populations studied, which are all younger and more robust than our own[45,55-57]. Moreover, a supervised exercise intervention, conducted on autonomous older adults during 12-weeks with 3 sessions of 1 hour per week and with progressive intensity, observed a significant improvement of stride variability; but failed to show an improvement, at an intermediate assessment at 8 weeks[45]. As our intervention lasted 10 weeks (with 2 weekly 1-hour sessions), the absence of improvement might be explained by an insufficient volume or duration of training to induce significant changes[45] for the overall cohort.

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The other temporal parameters (double-support phase, support phase, swing phase and step asymmetry) did not change after the exercise intervention. Considering the association of double-support phase with gait speed and FOF[8], it is surprising to not observe changes of double-support phase after the intervention, while gait speed and FOF were improved. One study using the specific "Square-Stepping Exercise" protocol, observed significant improvement of double-support phase[47]. Thus, it might be possible that this protocol could be more effective to improve this parameter. With regards to stride symmetry, baseline data were relatively preserved, that mainly explain the absence of change after the intervention[58].

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The positive changes after the intervention on spatial gait parameters observed did not seem to be followed by improvements in temporal gait parameters.

Overall, gait improvement could be achieved using different exercise protocols, if the exercise was progressive, adapted and of sufficient intensity (at least moderate) and volume (at least 2 sessions per week). Exercises should be performed using bodyweight or small equipment (such as elastic bands), in 2 to 3 sets of 6 to 12 repetitions. Exercises should be transposable to functional movements and target the muscles recruited during gait (hip, knee and ankle flexors and extensors muscles; postural upper body muscles and arms muscles).

## 2. Influence of FOF in exercise adaptations: comparison between FOF subgroups

First, FOF significantly decreased after the multicomponent exercise intervention but with a small effect in the overall cohort. These results are in agreement with previous studies[24-26]. More specifically, the population most likely to experience changes following an intervention are those with a higher level of FOF or with a higher level of frailty according to previous study of Delbaere et al[3]. It is worth noting that FES-I scale has a floor effect, especially for older adults without FOF, but remains limited [59]. Thus, this could partly explain the absence of FOF decrease in the no-FOF subgroup. In the context of falls prevention, these results are encouraging. Nevertheless, although the FOF is a major factor in the risk of falling, management of fall prevention cannot be limited to this factor alone. It needs to be considered in a global approach with the history of falls, physical functions and activity restrictions [1,20-22]. Indeed, there is a "spiraling effect of increasing falls, fear and functional decline", since they are all predictors of each other[20].

However, we did not observe a time*group interaction in gait parameters and in physical function (SPPB score, 5-STS and TUG), indicating that the presence of FOF may not be
422 responsible of different spatial gait parameters and physical function changes. In addition, as
423 stride variability and number of cycles at the turn were only improved in FOF-subgroup, there
424 seems to be a ceiling effect for the no-FOF subgroup. Indeed, participants in the FOF-subgroup
425 had lower gait parameters at baseline than those in the no-FOF subgroup. This was even more
426 marked for temporal parameters, since the differences between the subgroups were no longer
427 present after the multicomponent exercise intervention. Nevertheless, the spatial parameters of
428 participants with FOF seemed to be too impaired at baseline to attain gait parameters
429 comparable to those of participants without FOF. To our knowledge, this is the first study to
430 compared differences in gait parameters adaptations according to FOF. However, considering
431 the difference of physical function between the subgroup participants at baseline, this difference
432 of exercise-induced adaptations could also be explained by the training load (volume and
433 intensity) that may be insufficient for the more robust no-FOF group [45]. As no-FOF
434 participants showed better fitness, the training load might not be sufficient for them to achieve
435 a gain, as previously discussed[45]. In addition, analysis of the participants who dropped out of
436 the study (for health reasons unrelated to the intervention) indicated that their profiles were
437 similar to those of the subgroup with FOF.

438 Furthermore, although the intervention adaptation in gait parameters was slightly
439 different between the subgroups of FOF, the improvements in perceived gait quality was
440 equally marked in both subgroups. This finding is particularly interesting for mobility loss
441 prevention, since it has been shown that the perception of difficulty in walking is strongly
442 associated with social isolation and the risk of developing sarcopenia[60,61]. Thus, decrease
443 FOF and improve perceived gait quality can therefore help participants to be more involved to
444 develop social activities and reduce sedentary time. Secondly, an improvement in perceived
445 gait quality is encouraging, considering the predictive value of self-perception of mobility on
446

occurrence of adverse events in older adults, especially when the FOF and its related consequences are added[3-6,62,63].

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### 3. Correlations between FOF and gait parameters changes

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Considering that literature showed significant associations between FOF and gait parameters[8-12], we should have expected a synergic changes between them after the intervention. Surprisingly, no robust correlation between delta changes were observed. We only found weak correlations in FOF subgroup for some temporal parameters. From a clinical point of view, participants who exhibit a decrease in FOF will reduce their stance time and logically increase their swing time. These results seem consistent with the literature, which indicates that stance time increases with FOF[8]. Moreover, as we observed a group effect on these parameters, these results suggest that it might be relevant to target older adults with prolonged stance phase and double support phase for this type of multicomponent exercise intervention. A recent observational study which was carried out on fallers and non-fallers older adults[7], reported that after 6 months without intervention, the gait speed of both groups remained stable but FOF remained stable only in the fallers' group[7]. Non-fallers, conversely, reduced their FOF. Thus, although FOF and gait parameters are related, their changes over time do not seem to be as related. Nevertheless, perceived gait quality changes were correlated with FOF changes, particularly in no-FOF subgroup. Surprisingly, no significant correlation was observed for the subgroup with the greatest changes in FOF. These results reinforce the idea that FOF is complex and multifactorial[1]. Thus, changes of FOF cannot easily be associated with changes of objective and subjective gait parameters.

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Identifying factors that appear to be most related to FOF reduction would be a relevant approach to optimize the efficiency of the multicomponent exercise interventions. We assumed that the reduction of FOF might be induced by psychological factors changes such as a better stress management and self-efficacy. Focusing exercise interventions towards gait retraining
471 (e.g. with gait paths) and psycho-affective factors for the most frail and fearful of falls older
472 adults could be worth testing further. Finally, these results reinforce the importance of
473 integrating older adults with a FOF into these types of interventions. For older adults without
474 FOF, targeting exercise interventions on FOF might not be a priority on physical function
475 improvement and social isolation decrease. In clinical setting, an assessment of FOF in the first
476 multidimensional assessment could be used to allocate participants in specific exercise
477 interventions.

478 Limitations

479 This study had some limitations. While this study provides clinical knowledge closer to
480 real-life care interventions and a population representative of patient profiles encountered in
481 usual care practice, the effect of the exercise intervention needs to be interpreted with caution.
482 Based on the real-life care setting and for obvious ethical reasons, this study was not blinded
483 and a control group could not be constituted in this context. Thus, the superiority effect of the
484 intervention on the studied parameters cannot be affirmed. Despite we have not carried out an
485 intention-to-treat analysis to assess all participants included in the intervention, we performed,
486 to limit bias, a comparative analysis of participants at baseline that allow us to maintain our
487 analysis design (per-protocol) and conclusion. As our study was an exploratory pilot study
488 (phase II ORBIT framework) and a pragmatic feasibility intervention (usual care), we had not
489 calculated a prior sample size. Several results are based on self-administrated questionnaires,
490 however therapists involved with the study had to ensure that patients completed them in their
491 entirety. Nevertheless, this study had also some strengths: it is the first to investigate the
492 changes and the influence of FOF status on spatiotemporal gait parameters after a multimodal
493 exercise intervention implemented in the community with older adults at risk of mobility
494 disability. In addition, this study also contributes to fill the gap on specific gait parameters, such
495

as half-turn and to promote the interest of current-care intervention in real-life settings in
mobility disability prevention.

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**Conclusion**

498

Our results demonstrate that a multicomponent exercise intervention lead to significant
changes in FOF, spatial gait parameters and perceived gait quality in older adults and more
especially in those with FOF. Although FOF and gait parameters are related, their changes over
time do not seem to be as related. This study confirmed that managing the FOF is complex,
multifactorial and might be orientated to a holistic approach. Further comparative studies are
necessary to better determine which factors are most related to changes in gait parameters and
FOF. Finally, this study shows that multicomponent exercise interventions appear to influence
not only physical parameters, but also spatiotemporal gait parameters and FOF. Consequently,
these interventions should be proposed more widely to older adults at risk of falls, and
particularly to those with a FOF.

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**Abbreviations**

509

5-STS: 5 Times Sit-to-Stand test

510

FES-I: Falls Efficacy Scale International

511

FOF: Fear Of Falling

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SPPB: Short Physical Performance Battery

513

TUG: Timed Up and Go test

514

**Acknowledgment**

515

The authors would like to thank all professionals of the “Well on my legs” intervention
from Hôpital Lyon Sud, Hospices Civils de Lyon, for their involvement, their participation in
assessments and their help to collect data. Authors also acknowledge participants who agreed

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to be integrated in this study. Authors acknowledge municipalities of Métropole de Lyon for their collaboration to propose the care path.

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## Author contributions

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A.C.B, T.G, M.A.L and M.B designed and conceptualized the study. A.C wrote the manuscript and analyzed the data. T.G, M.A.L and M.B. supervised the research project. All authors had access to all of the data, contributed to the interpretation of findings, revised and approved the final manuscript.

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## Funding

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The authors received a grant funding from the "Conférence des Financeurs de la métropole de Lyon" to implement this intervention in the area.

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## Availability of data and materials

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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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## Declarations

532

## Ethics approval and consent to participate

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This study was approved by the scientific and ethical committee of the Hospices Civils de Lyon (France) (NCT03667664, registration date: 12/09/2018 and NCT06659484, registration date: 26/10/2024). This study complies with the Helsinki Declaration as after receiving detailed information, all study participants gave their informed consent.

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## Consent for publication

538

Not applicable

539

## Competing interest
540

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References

542

1. Montero-Odasso M, Van Der Velde N, Martin FC, Petrovic M, Tan MP, Ryg J, et al. World guidelines for falls prevention and management for older adults: a global initiative. Ageing. 2022 Sep 2;51(9):afac205.

543

544

545

2. Meyer M, Constancias F, Vogel T, Kaltenbach G, Schmitt E. Gait Disorder among Elderly People, Psychomotor Disadaptation Syndrome: Post-Fall Syndrome, Risk Factors and Follow-Up - A Cohort Study of 70 Patients. Gerontology. 2021;67(1):17-24.

546

547

548

3. Delbaere K, Close JCT, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The Falls Efficacy Scale International (FES-I). A comprehensive longitudinal validation study. Ageing. 2010 Mar 1;39(2):210-6.

549

550

551

4. Merchant RA, Chen MZ, Wong BLL, Ng SE, Shirooka H, Lim JY, et al. Relationship Between Fear of Falling, Fear-Related Activity Restriction, Frailty, and Sarcopenia. J Am Geriatr Soc. 2020 Nov;68(11):2602-8.

552

553

554

5. Souza LF, Canever JB, Moreira B de S, Danielewicz AL, de Avelar NCP. Association Between Fear of Falling and Frailty in Community-Dwelling Older Adults: A Systematic Review. Clin Interv Aging. 2022;17:129-40.

555

556

557

6. Mo C, Peng W, Luo Y, Tang S, Liu M. Bidirectional relationship between fear of falling and frailty among community-dwelling older adults: A longitudinal study. Geriatr Nur (Lond). 2023 May;51:286-92.

558

559
560

7. Park C, Atique MMU, Mishra R, Najafi B. Association between Fall History and Gait, Balance, Physical Activity, Depression, Fear of Falling, and Motor Capacity: A 6-Month Follow-Up Study. Int J Environ Res Public Health. 2022 Aug 30;19(17):10785.

561

562

563

8. Chamberlin ME, Fulwider BD, Sanders SL, Medeiros JM. Does Fear of Falling Influence Spatial and Temporal Gait Parameters in Elderly Persons Beyond Changes Associated With Normal Aging? J Gerontol Ser A. 2005 Sep 1;60(9):1163-7.

564

565

566

9. Rochat S, Büla CJ, Martin E, Seematter-Bagnoud L, Karmaniola A, Aminian K, et al. What is the Relationship Between Fear of Falling and Gait in Well-Functioning Older Persons Aged 65 to 70 Years? Arch Phys Med Rehabil. 2010 Jun;91(6):879-84.

567

568

569

10. Wang C, Patriquin M, Vaziri A, Najafi B. Mobility Performance in Community-Dwelling Older Adults: Potential Digital Biomarkers of Concern about Falling. Gerontology. 2021;67(3):365-73.

570

571

572

11. Jahn K, Heinze C, Selge C, Heßelbarth K, Schniepp R. Gait disorders in geriatric patients. Classification and therapy. Nervenarzt. 2015 Apr;86(4):431-9.

573

574

12. Orihuela-Espejo A, Álvarez-Salvago F, Martínez-Amat A, Boquete-Pumar C, De Diego-Moreno M, García-Sillero M, et al. Associations between Muscle Strength, Physical Performance and Cognitive Impairment with Fear of Falling among Older Adults Aged ≥ 60 Years: A Cross-Sectional Study. Int J Environ Res Public Health. 2022 Aug 23;19(17):10504.

575

576

577

578

579

13. Reelick MF, Van Iersel MB, Kessels RPC, Rikkert MGMO. The influence of fear of falling on gait and balance in older people. Age Ageing. 2009 Jul 1;38(4):435-40.

580
581

14. Ferrucci L, Cooper R, Shardell M, Simonsick EM, Schrack JA, Kuh D. Age-Related Change in Mobility: Perspectives From Life Course Epidemiology and Geroscience. J Gerontol A Biol Sci Med Sci. 2016 Sep;71(9):1184-94.

582

583

584

15. Dapp U, Vinyard D, Golgert S, Krumpoch S, Freiberger E. Reference values of gait characteristics in community-dwelling older persons with different physical functional levels. BMC Geriatr. 2022 Aug 29;22(1):713.

585

586

587

16. Bohannon RW. Comfortable and maximum walking speed of adults aged 20-79 years: reference values and determinants. Age Ageing. 1997;26(1):15-9.

588

589

17. Mayhew AJ, So HY, Ma J, Beauchamp MK, Griffith LE, Kuspinar A, et al. Normative values for grip strength, gait speed, timed up and go, single leg balance, and chair rise derived from the Canadian longitudinal study on ageing. Age Ageing. 2023 Apr 1;52(4):afad054.

590

591

592

593

18. Ayoubi F, Launay CP, Kabeshova A, Fantino B, Annweiler C, Beauchet O. The influence of fear of falling on gait variability: results from a large elderly population-based cross-sectional study. J NeuroEngineering Rehabil. 2014 Dec;11(1):128.

594

595

596

19. Keating CJ, Cabrera-Linares JC, Párraga-Montilla JA, Latorre-Román PA, Del Castillo RM, García-Pinillos F. Influence of Resistance Training on Gait & Balance Parameters in Older Adults: A Systematic Review. Int J Environ Res Public Health. 2021 Feb 11;18(4):1759.

597

598

599

600

20. Friedman SM, Munoz B, West SK, Rubin GS, Fried LP. Falls and fear of falling: which comes first? A longitudinal prediction model suggests strategies for primary and secondary prevention. J Am Geriatr Soc. 2002 Aug;50(8):1329-35.

601

602
603

21. Deshpande N, Metter EJ, Lauretani F, Bandinelli S, Ferrucci L. Interpreting Fear of Falling in the Elderly: What Do We Need to Consider? J Geriatr Phys Ther 2001. 2009;32(3):91-6.

604

605

606

22. Wapp C, Mittaz Hager AG, Hilfiker R, Zysset P. History of falls and fear of falling are predictive of future falls: Outcome of a fall rate model applied to the Swiss CHEF Trial cohort. Front Aging. 2022 Dec 14;3:1056779.

607

608

609

23. Izquierdo M, Merchant RA, Morley JE, Anker SD, Aprahamian I, Arai H, et al. International Exercise Recommendations in Older Adults (ICFSR): Expert Consensus Guidelines. J Nutr Health Aging. 2021 Jul;25(7):824-53.

610

611

612

24. Kumar A, Delbaere K, Zijlstra G a. R, Carpenter H, Iliffe S, Masud T, et al. Exercise for reducing fear of falling in older people living in the community: Cochrane systematic review and meta-analysis. Age Ageing. 2016 May;45(3):345-52.

613

614

615

25. Kruisbrink M, Delbaere K, Kempen GIJM, Crutzen R, Ambergen T, Cheung KL, et al. Intervention Characteristics Associated With a Reduction in Fear of Falling Among Community-Dwelling Older People: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Heyn PC, editor. The Gerontologist. 2021 Aug 13;61(6):e269-82.

616

617

618

619

620

26. Feng C, Adebero T, DePaul VG, Vafaei A, Norman KE, Auais M. A Systematic Review and Meta-Analysis of Exercise Interventions and Use of Exercise Principles to Reduce Fear of Falling in Community-Dwelling Older Adults. Phys Ther. 2022 Jan 1;102(1):pzab236.

621

622

623

27. Delaire L, Courtay A, Fauvernier M, Humblot J, Bonnefoy M. Integrating a Prevention Care Path into the Daily Life of Older Adults with Mobility Disability Risk: Introducing a Predictive Response Model to Exercise. Clin Interv Aging. 2021 Sep;Volume 16:1617-29.

624

625
626

627

28. Topolski TD, LoGerfo J, Patrick DL, Williams B, Patrick MMB. The Rapid Assessment of Physical Activity (RAPA) Among Older Adults. 2006;3(4).

628

629

630

29. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019 Jan 1;48(1):16–31.

631

632

633

30. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-156.

634

635

636

637

31. Delaire L, Courtay A, Humblot J, Aubertin-Leheudre M, Mourey F, Racine AN, et al. Implementation and Core Components of a Multimodal Program including Exercise and Nutrition in Prevention and Treatment of Frailty in Community-Dwelling Older Adults: A Narrative Review. Nutrients. 2023 Sep 22;15(19):4100.

638

639

32. Marcora SM. Perception of. In: Encyclopedia of Perception. SAGE Publications: Thousand Oaks. usa: EB Goldstein; 2010. p. 380.

640

641

642

33. Dadashi F, Mariani B, Rochat S, Büla CJ, Santos-Eggimann B, Aminian K. Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults. Sensors. 2013 Dec 27;14(1):443–57.

643

644

34. Jian Y, Winter D, Ishac M, Gilchrist L. Trajectory of the body COG and COP during initiation and termination of gait. Gait Posture. 1993 Mar 1;1(1):9–22.

645

646

647

35. Shen Y, Shi Q, Nong K, Li S, Yue J, Huang J, et al. Exercise for sarcopenia in older people: A systematic review and network meta-analysis. J Cachexia Sarcopenia Muscle. 2023 Jun;14(3):1199–211.
648

36. Dewan N, MacDermid JC. Fall Efficacy Scale - International (FES-I). J Physiother. 2014

649

Mar;60(1):60.

650

37. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short

651

physical performance battery assessing lower extremity function: association with self-

652

reported disability and prediction of mortality and nursing home admission. J Gerontol.

653

1994 Mar;49(2):M85-94.

654

38. Geerinck A, Locquet M, Bruyère O, Reginster J, Beaudart C. Evaluating quality of life in

655

frailty: applicability and clinimetric properties of the SarQoL® questionnaire. J Cachexia

656

Sarcopenia Muscle. 2021 Apr;12(2):319-30.

657

39. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, N.J: L.

658

Erlbaum Associates; 1988. 567 p.

659

40. Akoglu H. User's guide to correlation coefficients. Turk J Emerg Med. 2018 Sep;18(3):91-

660

3.

661

41. Geerinck A, Alekna V, Beaudart C, Bautmans I, Cooper C, De Souza Orlandi F, et al.

662

Standard error of measurement and smallest detectable change of the Sarcopenia Quality

663

of Life (SarQoL) questionnaire: An analysis of subjects from 9 validation studies. PLoS

664

ONE. 2019 Apr 29;14(4):e0216065.

665

42. Collado-Mateo D, Lavín-Pérez AM, Peñacoba C, Del Coso J, Leyton-Román M, Luque-

666

Casado A, et al. Key Factors Associated with Adherence to Physical Exercise in Patients

667

with Chronic Diseases and Older Adults: An Umbrella Review. Int J Environ Res Public

668

Health. 2021 Feb 19;18(4):2023.
669

43. Porto JM, Peres-Ueno MJ, de Matos Brunelli Braghin R, Scudilio GM, de Abreu DCC.

670

Diagnostic accuracy of the five times stand-to-sit test for the screening of global muscle

671

weakness in community-dwelling older women. Exp Gerontol. 2023 Jan;171:112027.

672

44. Callisaya ML, Blizzard L, Schmidt MD, McGinley JL, Srikanth VK. Ageing and gait

673

variability--a population-based study of older people. Age Ageing. 2010 Mar;39(2):191-7.

674

45. Wang RY, Wang YL, Cheng FY, Chao YH, Chen CL, Yang YR. Effects of combined

675

exercise on gait variability in community-dwelling older adults. AGE. 2015 Jun;37(3):40.

676

46. Fahlman MM, McNevin N, Boardley D, Morgan A, Topp R. Effects of Resistance Training

677

on Functional Ability in Elderly Individuals. Am J Health Promot. 2011 Mar;25(4):237-

678

43.

679

47. Fränzel K, Koschate J, Freiberger E, Shigematsu R, Zieschang T, Tietgen S. Square-

680

stepping exercise in older inpatients in early geriatric rehabilitation. A randomized

681

controlled pilot study. BMC Geriatr. 2024 Apr 10;24(1):326.

682

48. Najafi B, Helbostad JL, Moe-Nilssen R, Zijlstra W, Aminian K. Does walking strategy in

683

older people change as a function of walking distance? Gait Posture. 2009 Feb;29(2):261-

684

6.

685

49. Segal AD, Shofer J, Hahn ME, Orendurff MS, Ledoux WR, Sangeorzan BJ. Functional

686

Limitations Associated with End-Stage Ankle Arthritis. J Bone Jt Surg. 2012 May

687

2;94(9):777-83.

688

50. Anderson DE, Madigan ML. Healthy older adults have insufficient hip range of motion and

689

plantar flexor strength to walk like healthy young adults. J Biomech. 2014 Mar;47(5):1104-

690

9.
691 51. Pirker W, Katzenschlager R. Gait disorders in adults and the elderly: A clinical guide. Wien
692 Klin Wochenschr. 2017 Feb;129(3-4):81-95.

693 52. Montero-Odasso M, Muir SW, Hall M, Doherty TJ, Kloseck M, Beauchet O, et al. Gait
694 Variability Is Associated With Frailty in Community-dwelling Older Adults. J Gerontol A
695 Biol Sci Med Sci. 2011 May 1;66A(5):568-76.

696 53. Martinikorena I, Martínez-Ramírez A, Gómez M, Lecumberri P, Casas-Herrero A, Cadore
697 EL, et al. Gait Variability Related to Muscle Quality and Muscle Power Output in Frail
698 Nonagenarian Older Adults. J Am Med Dir Assoc. 2016 Feb;17(2):162-7.

699 54. Alcazar J. The sit-to-stand muscle power test_ An easy, inexpensive and portable procedure
700 to assess muscle power in older people. Exp Gerontol. 2018;

701 55. Granacher U, Muehlbauer T, Bridenbaugh SA, Wolf M, Roth R, Gschwind Y, et al. Effects
702 of a salsa dance training on balance and strength performance in older adults. Gerontology.
703 2012;58(4):305-12.

704 56. Granacher U, Muehlbauer T, Bridenbaugh S, Bleiker E, Wehrle A, Kressig RW. Balance
705 training and multi-task performance in seniors. Int J Sports Med. 2010 May;31(5):353-8.

706 57. Newell D, Shead V, Sloane L. Changes in gait and balance parameters in elderly subjects
707 attending an 8-week supervised Pilates programme. J Bodyw Mov Ther. 2012
708 Oct;16(4):549-54.

709 58. Auvinet B, Berrut G, Touzard C, Moutel L, Collet N, Chaleil D, et al. Reference data for
710 normal subjects obtained with an accelerometric device. Gait Posture. 2002 Oct;16(2):124-
711 34.
712

713

714

59. Hauer KA, Kempen GIJM, Schwenk M, Yardley L, Beyer N, Todd C, et al. Validity and sensitivity to change of the falls efficacy scales international to assess fear of falling in older adults with and without cognitive impairment. Gerontology. 2011;57(5):462-72.

715

716

717

60. Kuang K, Huisingh-Scheetz M, Miller MJ, Waite L, Kotwal AA. The association of gait speed and self-reported difficulty walking with social isolation: A nationally-representative study. J Am Geriatr Soc. 2023 Aug;71(8):2549-56.

718

719

720

721

61. Guillamón-Escudero C, Diago-Galmés A, Zuazua Rico D, Maestro-González A, Tenías-Burillo JM, Soriano JM, et al. SarQoL Questionnaire in Community-Dwelling Older Adults under EWGSOP2 Sarcopenia Diagnosis Algorithm: A New Screening Method? Int J Environ Res Public Health. 2022 Jul 11;19(14):8473.

722

723

724

62. Rejeski WJ, Rushing J, Guralnik JM, Ip EH, King AC, Manini TM, et al. The MAT-sf: Identifying Risk for Major Mobility Disability. J Gerontol A Biol Sci Med Sci. 2015 May;70(5):641-6.

725

726

727

63. Callahan KE, Lovato L, Miller ME, Marsh AP, Fielding RA, Gill TM, et al. Self-Reported Physical Function As a Predictor of Hospitalization in the Lifestyle Interventions and Independence for Elders Study. J Am Geriatr Soc. 2018 Oct;66(10):1927-33.

728
<caption>Table 2: Time effect for all participants after the multicomponent exercise intervention (n=105).</caption>

732

<table><thead><tr><th>Variable</th><th>Pre (Mean ± SD)</th><th>Post (Mean ± SD)</th><th>p*</th><th>d</th></tr></thead><tbody><tr><td colspan="5">Questionnaires</td></tr><tr><td>FES-I (/64)<sup>a</sup></td><td>27.55 ± 8.17</td><td>26.25 ± 8.04</td><td><strong>&lt;.01</strong></td><td>-0.22</td></tr><tr><td>Locomotion SarQoL score (/100)</td><td>48.79 ± 14.59</td><td>53.35 ± 15.59</td><td><strong>&lt;.001</strong></td><td>0.41</td></tr><tr><td colspan="5">Physical function</td></tr><tr><td>SPPB (/12)<sup>b</sup></td><td>9.38 ± 1.85</td><td>10.56 ± 1.59</td><td><strong>&lt;.001</strong></td><td>0.83</td></tr><tr><td>5-STS (s)<sup>c</sup></td><td>14.78 ± 5.89</td><td>11.73 ± 3.96</td><td><strong>&lt;.001</strong></td><td>-0.71</td></tr><tr><td>6-meters gait speed (m/s)</td><td>0.83 ± 0.19</td><td>0.92 ± 0.21</td><td><strong>&lt;.001</strong></td><td>0.63</td></tr><tr><td>Static balance (SPPB item /4)</td><td>3.40 ± 0.80</td><td>3.74 ± 0.50</td><td><strong>&lt;.001</strong></td><td>0.46</td></tr><tr><td>50-meters gait speed (m/s)</td><td>0.99 ± 0.20</td><td>1.04 ± 0.22</td><td><strong>&lt;.001</strong></td><td>0.47</td></tr><tr><td>TUG (s)<sup>d</sup></td><td>12.65 ± 3.21</td><td>11.48 ± 3.10</td><td><strong>&lt;.001</strong></td><td>-0.47</td></tr><tr><td colspan="5">Temporal gait parameters</td></tr><tr><td>Stride variability (%)</td><td>4.54 ± 2.13</td><td>4.25 ± 1.45</td><td>0.065</td><td>-0.16</td></tr><tr><td>Stride symmetry (%)</td><td>5.50 ± 5.86</td><td>5.07 ± 4.77</td><td>0.566</td><td>-0.07</td></tr><tr><td>Double support phase (%)</td><td>21.28 ± 5.58</td><td>20.65 ± 5.86</td><td>0.264</td><td>-0.12</td></tr><tr><td>Swing phase (%)</td><td>39.53 ± 2.79</td><td>39.67 ± 2.93</td><td>0.266</td><td>0.12</td></tr><tr><td>Stance phase (%)</td><td>60.65 ± 2.79</td><td>60.33 ± 2.93</td><td>0.264</td><td>-0.12</td></tr><tr><td colspan="5">Spatial gait parameters</td></tr><tr><td>Stride length (m)</td><td>1.06 ± 0.17</td><td>1.09 ± 0.18</td><td><strong>&lt;.001</strong></td><td>0.41</td></tr><tr><td>Lift off angle (°)</td><td>54.74 ± 7.79</td><td>56.31 ± 8.02</td><td><strong>&lt;.01</strong></td><td>0.29</td></tr><tr><td>Strike angle (°)</td><td>21.39 ± 5.06</td><td>22.33 ± 5.36</td><td><strong>&lt;.05</strong></td><td>0.27</td></tr><tr><td>Turning angle (°)</td><td>87.92 ± 16.27</td><td>92.85 ± 16.29</td><td><strong>&lt;.01</strong></td><td>0.36</td></tr><tr><td>The number of cycles at the turn (n)</td><td>3.37 ± 0.65</td><td>3.17 ± 0.58</td><td><strong>&lt;.01</strong></td><td>-0.26</td></tr></tbody></table>

<footnote><sup>a</sup>FES-I: Falls Efficacy Scale International questionnaire. <sup>b</sup>SPPB: Short Physical Performance Battery. <sup>c</sup>5-STS: 5 times sit-to-stand test. <sup>d</sup>TUG: Timed Up and Go test. <sup>p</sup>Values are significant at values < .05. Significant values are highlighted in bold. <sup>d</sup>of Cohen's effect size.</footnote>
733 Table 3: Group and group*time interaction effects for subgroups of participants after the

734 <u>multicomponent exercise intervention.</u>

735
<table><thead><tr><th rowspan="2">Variables</th><th rowspan="2">Group (G) p<br>G * Time (T) p</th><th colspan="3">Fear of Falling Subgroup (n=64)</th><th colspan="3">No-Fear of Falling Subgroup (n=41)</th><th colspan="3">Fear of Falling Subgroup vs<br>No-Fear of Falling Subgroup</th></tr><tr><th>Pre (Mean ± SD)</th><th>Post (Mean ± SD)</th><th>p<br>(d)</th><th>Pre (Mean ± SD)</th><th>Post (Mean ± SD)</th><th>p<br>(d)</th><th>Pre p<br>(d)</th><th>Post p<br>(d)</th></tr></thead><tbody><tr><td rowspan="2">FES-I (/64)<sup>a</sup></td><td>G = &lt;.001</td><td rowspan="2">31.98 ± 7.49</td><td rowspan="2">29.34 ± 8.40</td><td rowspan="2">&lt;.001<br>(-.39)</td><td rowspan="2">20.68 ± 2.07</td><td rowspan="2">21.37 ± 4.16</td><td>0.543<br>(.16)</td><td>&lt;.001<br>(1.87)</td><td>&lt;.001<br>(1.13)</td></tr><tr><td>G * T = &lt;.001</td><td>&lt;.001<br>(.42)</td><td>&lt;.001<br>(.38)</td><td>&lt;.001<br>(-.96)</td><td>&lt;.001<br>(-.70)</td></tr><tr><td rowspan="2">Locomotion SarQoL<br>score (/100)</td><td>G = &lt;.001</td><td rowspan="2">43.84 ± 13.34</td><td rowspan="2">49.29 ± 15.50</td><td rowspan="2">&lt;.001<br>(.62)</td><td rowspan="2">56.60 ± 13.10</td><td rowspan="2">59.72 ± 13.62</td><td>&lt;.001<br>(.66)</td><td>&lt;.01<br>(-.61)</td><td>&lt;.05<br>(-.49)</td></tr><tr><td>G * T = 0.727</td><td>&lt;.001<br>(.43)</td><td>&lt;.001<br>(.53)</td><td>&lt;.001<br>(-.75)</td><td>&lt;.001<br>(-.77)</td></tr><tr><td rowspan="2">6-meters gait speed<br>(m/s)</td><td>G = &lt;.01</td><td rowspan="2">0.79 ± 0.19</td><td rowspan="2">0.88 ± 0.22</td><td rowspan="2">&lt;.001<br>(.62)</td><td rowspan="2">0.90 ± 0.16</td><td rowspan="2">0.98 ± 0.17</td><td>&lt;.001<br>(.66)</td><td>&lt;.01<br>(-.61)</td><td>&lt;.05<br>(-.49)</td></tr><tr><td>G * T = 0.556</td><td>&lt;.001<br>(.43)</td><td>&lt;.001<br>(.53)</td><td>&lt;.001<br>(-.75)</td><td>&lt;.001<br>(-.77)</td></tr><tr><td rowspan="2">50-meters gait speed<br>(m/s)</td><td>G = &lt;.001</td><td rowspan="2">0.93 ± 0.21</td><td rowspan="2">0.98 ± 0.23</td><td rowspan="2">&lt;.001<br>(.43)</td><td rowspan="2">1.07 ± 0.14</td><td rowspan="2">1.14 ± 0.17</td><td>&lt;.01<br>(.53)</td><td>&lt;.001<br>(-.75)</td><td>&lt;.001<br>(-.77)</td></tr><tr><td>G * T = 0.560</td><td>&lt;.001<br>(.61)</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(-.93)</td><td>&lt;.001<br>(-.81)</td></tr><tr><td rowspan="2">SPPB (/12)<sup>b</sup></td><td>G = &lt;.001</td><td rowspan="2">8.77 ± 1.88</td><td rowspan="2">10.09 ± 1.74</td><td rowspan="2">&lt;.001<br>(.90)</td><td rowspan="2">10.34 ± 1.33</td><td rowspan="2">11.29 ± 0.96</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(-.93)</td><td>&lt;.001<br>(-.81)</td></tr><tr><td>G * T = .146</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(.74)</td><td>&lt;.001<br>(.42)</td><td>&lt;.001<br>(-.81)</td></tr><tr><td rowspan="2">5-STS (s)<sup>c</sup></td><td>G = &lt;.01</td><td rowspan="2">15.62 ± 6.70</td><td rowspan="2">12.32 ± 4.59</td><td rowspan="2">&lt;.001<br>(-.71)</td><td rowspan="2">13.11 ± 4.49</td><td rowspan="2">10.83 ± 2.53</td><td>&lt;.05<br>(-.74)</td><td>&lt;.05<br>(.42)</td><td>0.093<br>(.38)</td></tr><tr><td>G * T = 0.434</td><td>&lt;.001<br>(-.71)</td><td>&lt;.001<br>(-.51)</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(.60)</td></tr><tr><td rowspan="2">TUG (s)<sup>d</sup></td><td>G = &lt;.001</td><td rowspan="2">13.51 ± 3.57</td><td rowspan="2">12.18 ± 3.56</td><td rowspan="2">&lt;.001<br>(.61)</td><td rowspan="2">11.31 ± 19.2</td><td rowspan="2">10.39 ± 1.78</td><td>&lt;.001<br>(-.51)</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(.60)</td></tr><tr><td>G * T = &lt;.425</td><td>&lt;.001<br>(.61)</td><td>&lt;.001<br>(-.51)</td><td>&lt;.001<br>(.72)</td><td>&lt;.001<br>(.60)</td></tr><tr><td colspan="10" style="text-align: left; font-weight: bold;">Temporal gait parameters</td></tr><tr><td rowspan="2">Stride variability (%)</td><td>G = &lt;.05</td><td rowspan="2">4.96 ± 2.52</td><td rowspan="2">4.42 ± 1.57</td><td rowspan="2">&lt;.05<br>(-.31)</td><td rowspan="2">3.88 ± 1.00</td><td rowspan="2">3.99 ± 1.21</td><td>0.856<br>(.07)</td><td>&lt;.05<br>(.52)</td><td>0.199<br>(.30)</td></tr><tr><td>G * T = 0.108</td><td>0.532<br>(-.10)</td><td>0.989<br>(-.03)</td><td>0.315<br>(.35)</td><td>0.657<br>(.26)</td></tr><tr><td rowspan="2">Stride symmetry (%)</td><td>G = 0.297</td><td rowspan="2">6.30 ± 6.88</td><td rowspan="2">5.66 ± 5.59</td><td rowspan="2">&lt;.001<br>(-.71)</td><td rowspan="2">4.25 ± 3.48</td><td rowspan="2">4.14 ± 2.97</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(.36)</td></tr><tr><td>G * T = 0.669</td><td>0.327<br>(-.12)</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td rowspan="2">Double support phase<br>(%)</td><td>G = &lt;.05</td><td rowspan="2">22.21 ± 6.09</td><td rowspan="2">21.46 ± 5.92</td><td rowspan="2">&lt;.001<br>(-.71)</td><td rowspan="2">19.85 ± 4.37</td><td rowspan="2">19.38 ± 5.59</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td>G * T = 0.800</td><td>0.331<br>(.12)</td><td>0.297<br>(.11)</td><td>&lt;.05<br>(-.43)</td><td>0.075<br>(-.36)</td></tr><tr><td rowspan="2">Swing phase (%)</td><td>G = &lt;.05</td><td rowspan="2">38.89 ± 3.04</td><td rowspan="2">39.26 ± 2.96</td><td rowspan="2">&lt;.001<br>(-.71)</td><td rowspan="2">40.07 ± 2.18</td><td rowspan="2">40.31 ± 2.80</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td>G * T = 0.804</td><td>0.327<br>(-.12)</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td rowspan="2">Stance phase (%)</td><td>G = &lt;.05</td><td rowspan="2">61.10 ± 3.04</td><td rowspan="2">60.73 ± 2.96</td><td rowspan="2">&lt;.001<br>(-.71)</td><td rowspan="2">59.93 ± 2.18</td><td rowspan="2">59.69 ± 2.79</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td>G * T = 0.800</td><td>0.327<br>(-.12)</td><td>0.297<br>(-.11)</td><td>&lt;.05<br>(.43)</td><td>0.075<br>(-.36)</td></tr><tr><td colspan="10" style="text-align: left; font-weight: bold;">Spatial gait parameters</td></tr><tr><td rowspan="2">Stride length (m)</td><td>G = &lt;.001</td><td rowspan="2">1.01 ± 0.17</td><td rowspan="2">1.04 ± 0.18</td><td rowspan="2">&lt;.01<br>(.41)</td><td rowspan="2">1.14 ± 0.14</td><td rowspan="2">1.17 ± 0.16</td><td>&lt;.05<br>(.40)</td><td>&lt;.001<br>(-.82)</td><td>&lt;.001<br>(-.75)</td></tr><tr><td>G * T = 0.926</td><td>&lt;.001<br>(.41)</td><td>&lt;.001<br>(-.82)</td><td>&lt;.001<br>(-.75)</td><td>&lt;.001<br>(-.56)</td></tr><tr><td rowspan="2">Lift off angle (°)</td><td>G = &lt;.01</td><td rowspan="2">52.88 ± 8.17</td><td rowspan="2">54.61 ± 8.22</td><td rowspan="2">&lt;.001<br>(.33)</td><td rowspan="2">57.63 ± 6.21</td><td rowspan="2">58.95 ± 7.02</td><td>&lt;.05<br>(.24)</td><td>&lt;.01<br>(-.64)</td><td>&lt;.01<br>(-.56)</td></tr><tr><td>G * T = 0.701</td><td>&lt;.001<br>(.33)</td><td>&lt;.001<br>(-.64)</td><td>&lt;.01<br>(-.56)</td><td>&lt;.001<br>(-.56)</td></tr></tbody></table>
<table><tr><td>Strike angle (°)</td><td>G = &lt; .05<br>G * T = 0.445</td><td>20.31 ± 5.07</td><td>21.46 ± 5.38</td><td>&lt; .05<br>(.32)</td><td>23.06 ± 4.61</td><td>23.68 ± 5.12</td><td>&lt; .05<br>(.20)</td><td>&lt; .01<br>(-.56)</td><td>&lt; .05<br>(-.42)</td></tr><tr><td>Turning angle (°)</td><td>G = &lt; .05<br>G * T = 0.521</td><td>84.62 ± 16.40</td><td>90.50 ± 16.24</td><td>&lt; .05<br>(.39)</td><td>93.08 ± 14.83</td><td>96.41 ± 15.90</td><td>&lt; .05<br>(.30)</td><td>&lt; .01<br>(-.54)</td><td>0.071<br>(-.37)</td></tr><tr><td>The number of cycles<br>at the turn (n)</td><td>G = &lt; .01<br>G * T = 0.714</td><td>3.5 ± 0.71</td><td>3.26 ± 0.63</td><td>&lt; .05<br>(.28)</td><td>3.17 ± 0.50</td><td>3.02 ± 0.47</td><td>0.144<br>(.24)</td><td>&lt; .05<br>(.52)</td><td>&lt; .05<br>(.42)</td></tr></table>

<table><caption>Table 4: Correlation between changes of FES-I score and gait parameters for the total cohort and subgroups</caption><thead><tr><th rowspan="2">Variables</th><th colspan="3">Correlations with gait speed r (p*)</th><th colspan="3">Correlations with temporal gait parameters r (p*)</th><th colspan="3">Correlations with spatial gait parameters r (p*)</th><th colspan="2">Correlations with perceived gait quality r (p*)</th></tr><tr><th>Δ 6-m gait speed</th><th>Δ 50-m gait speed</th><th>Δ Stride variability</th><th>Δ Stride symmetry</th><th>Δ Double support phase</th><th>Δ Swing phase</th><th>Δ Stance phase</th><th>Δ Stride length</th><th>Δ Lift off angle</th><th>Δ Strike angle</th><th>Δ Turning angle</th><th>Δ The number of cycles at the turn</th><th>Δ Locomotion SarQoL score</th></tr></thead><tbody><tr><td>Δ FES-I<sup>a</sup><br>Total Cohort</td><td>-0.15<br>(0.136)</td><td>-0.03<br>(0.728)</td><td>0.10<br>(0.306)</td><td>-0.1<br>(0.335)</td><td>0.17<br>(0.076)</td><td>0.17<br>(0.077)</td><td>0.17<br>(0.077)</td><td>-0.80<br>(0.416)</td><td>-0.06<br>(0.530)</td><td>-0.05<br>(0.613)</td><td>0.05<br>(0.650)</td><td>0.004<br>(0.970)</td><td><strong>-0.252</strong><br>(&lt; .05)</td></tr><tr><td>Δ FES-I<br>Fear of Falling Subgroup</td><td>0.09<br>(0.465)</td><td>-0.11<br>(0.393)</td><td>0.05<br>(0.072)</td><td>-0.14<br>(0.269)</td><td><strong>0.25</strong><br>(&lt; .05)</td><td><strong>-0.25</strong><br>(&lt; .05)</td><td><strong>0.25</strong><br>(&lt; .05)</td><td>-0.07<br>(0.570)</td><td>-0.03<br>(0.845)</td><td>-0.08<br>(0.549)</td><td>0.56<br>(0.668)</td><td>0.01<br>(0.930)</td><td>-0.154<br>(0.233)</td></tr><tr><td>Δ FES-I<br>No-Fear of Falling Subgroup</td><td>-0.24<br>(0.125)</td><td>-0.18<br>(0.270)</td><td>0.03<br>(0.870)</td><td>-0.13<br>(0.429)</td><td>0.12<br>(0.474)</td><td>0.12<br>(0.474)</td><td>0.12<br>(0.474)</td><td>-0.20<br>(0.206)</td><td>-0.10<br>(0.527)</td><td>0.06<br>(0.715)</td><td>-0.001<br>(0.995)</td><td>-0.03<br>(0.862)</td><td><strong>-0.486</strong><br>(&lt; .01)</td></tr></tbody></table>

<footnote>ªFES-I: Falls Efficacy Scale International questionnaire. ᵇSPPB: Short Physical Performance Battery. ᶜ5-STS: 5 times sit-to-stand test. ᵈTUG: Timed Up and Go test. “Fear of Falling subgroup”: participants with FES-I baseline score >23/64. “No-Fear of Falling subgroup”: Participants with FES-I baseline score ≤ 23/64. p Values are significant at values < .05. Significant values are highlighted in bold. d: d of Cohen's effect size.</footnote>

<footnote>ª FES-I: Falls Efficacy Scale International questionnaire. “Fear of Falling subgroup”: participants with FES-I baseline score >23/64. “No-Fear of Falling subgroup”: Participants with FES-I baseline score ≤ 23/64. r = Pearson or Spearman correlation results. Δ: Delta = post-pre values. p Values are significant at values < .05. Significant values are highlighted in bold.</footnote>
## Suppliers

a Physilog5, Gait Up, Switzerland.

b MindMaze © gait analysis package.

c IBM SPSS Statistics version 21 (IBM Corp., Armonk, NY, USA).

Additional table 1 (.txt): Baseline comparison between participants drop-out and participants included in the analysis.