Physical,cognitive and psychosocial effects of telerehabilitation-based motor imagery training in people with multiple sclerosis: A randomized controlled pilot trial

Abstract

Introduction

Motor imagery training delivered at home via telerehabilitation is a novel rehabilitation concept. The aim was to investigate the effects of telerehabilitation-based motor imaging training (Tele-MIT) on gait, balance and cognitive and psychosocial outcomes in people with multiple sclerosis (pwMS).

Methods

This randomized, controlled pilot trial included pwMS and healthy individuals. pwMS were randomly divided into two groups, intervention and control. The intervention group received Tele-MIT twice a week for 8 weeks. The control group was a wait-list group without any additional specific treatment. Healthy participants served as a baseline comparison. The Dynamic Gait Index, used to assess dynamic balance during walking, was the primary outcome. Secondary outcomes included assessments of walking speed, endurance and perceived ability, balance performance assessed by a computerized posturography device, balance confidence, cognitive functions, fatigue, anxiety, depression and quality of life.

Results

Baseline comparisons with healthy individuals revealed that motor imagery abilities were preserved in pwMS (p > 0.05). The intervention group exhibited significant improvements in dynamic balance during walking (p = 0.002), walking speed (p = 0.007), perceived walking ability (p = 0.008), balance confidence (p = 0.002), most cognitive functions (p = 0.001–0.008), fatigue (p = 0.001), anxiety (p = 0.001), depression (p = 0.005) and quality of life (p = 0.002). No significant changes were observed in the control group in any of the outcome measures (p > 0.05).

Discussion

Tele-MIT is a novel method that proved feasible and effective in improving dynamic balance during walking, walking speed and perceived walking ability, balance confidence, cognitive functions, fatigue, anxiety, depression and quality of life in pwMS.

Keywords

Multiple sclerosis telerehabilitation motor imagery walking cognition quality of life

Introduction

People with multiple sclerosis (pwMS) are confronted with a wide variety of serious symptoms. There are various pharmacological treatments and invasive procedures for the management of MS symptoms and one of the most commonly used treatment options is rehabilitation. Physical exercise training is one of the most beneficial rehabilitation strategies in pwMS.¹ However, this population typically engages in low levels of health-promoting physical activity compared to adults from the general population.¹ Due to a variety of challenges, physical exercise training may be problematic in some pwMS. To overcome these challenges, some promising new approaches to rehabilitation have been introduced, such as telerehabilitation and motor imagery training (MIT).

Motor imagery can be defined as a dynamic state in which the representation of a specific motor action is internally reactivated within working memory without any overt motor output, yet is governed by the principles of central motor control.² Motor imagery produces similar neurological and autonomic changes than executed movement and has been shown to be effective in many populations with neurological diseases such as stroke and Parkinson’s disease.^2–4 However, most studies have investigated the physical effects of MIT, while the cognitive and psychosocial effects remain to be investigated.^5,6 From the MS perspective, there is limited evidence suggesting MIT may be beneficial for walking, fatigue, and quality of life in pwMS.^7–9

pwMS have very diverse care needs, and long-term rehabilitation is recommended both in hospital and the community. Despite recent advances in MS management, pwMS are unable to achieve these improvements due to challenges such as travel costs, restricted mobility, fatigue, lack of motivation and various other symptoms.¹⁰ Additionally, it was reported that rehabilitation methods provided in the individuals’ natural environments are more effective than those provided in clinics.¹¹ A review concluded that due to the low methodological quality of previous telerehabilitation studies, there was pressing need for robust and methodologically sound studies evaluating the effectiveness of telerehabilitation intervention in pwMS.¹⁰ Furthermore, it has been emphasized that although most studies focused on physical outcome measures, psychosocial outcome measures should also be investigated.¹⁰

Telerehabilitation-based motor imaging training (Tele-MIT) is a novel rehabilitation concept. Only one case study reported that it was effective in improving gait and balance in a stroke patient.¹² The aim of the present study was to investigate the effects of Tele-MIT on gait, balance, and cognitive and psychosocial outcomes in pwMS. The research hypothesis was that in addition to gait and balance, cognitive and psychosocial improvements would be observed in pwMS who received Tele-MIT compared to those who did not receive the intervention.

Methods

Study design

This randomized, controlled pilot trial was designed as an assessor-blinded trial with two parallel groups. All assessments were done before and after the 8-week intervention programme or waiting period. A healthy control group was also evaluated for baseline comparisons.

The study protocol followed the CONSORT statement,¹³ and was registered at ClinicalTrials.gov (Identifier: NCT02781142). The study protocol was approved by the Non-invasive Research Ethics Board of Dokuz Eylül University (Protocol Number: 2628-GOA, Approval Number: 2016/10-16) and written informed consent to participate was obtained from all participants.

Participants

pwMS included in this study were recruited from the MS outpatient clinic of the Neurology Department of Dokuz Eylül University Hospital in Izmir, Turkey. Healthy controls were recruited from among the hospital staff and friends and relatives of the research team.

During the study period, 78 people with a definite MS diagnosis were screened for the inclusion criteria upon routine clinical admission by the same neurologist. Inclusion criteria were age 18–65 years, Expanded Disability Status Scale (EDSS) score below 4.0, relapse-free status for the previous 3 months and having sufficient computer knowledge or someone to provide technical assistance, a personal computer and an active internet connection. pwMS who were pregnant, had physician-diagnosed severe hearing or cognitive impairment or had any serious musculoskeletal, cardiovascular, pulmonary, metabolic or neurological disease other than MS were not included. The healthy control group consisted of volunteers who were not pregnant and had no known chronic neurological, cardiovascular or orthopaedic disease.

Randomization and masking

pwMS were divided into two groups by block randomization with a 1:1 allocation using random block sizes of two prepared by an independent party using a computer-generated randomization list.¹⁴ The neurologist who investigated the inclusion and exclusion criteria, the physiotherapist assessor, and the psychologist were blinded to the size of each block and group allocation until study completion.

Study intervention

Participants in the intervention group received the Tele-MIT individually for 8 weeks, twice a week in 20–30 min sessions conducted by the same physiotherapist. Session appointments were scheduled according to mutual availability of participant and physiotherapist. If a participant was unable to participate in a scheduled session, another appointment was scheduled at the earliest opportunity. Telerehabilitation was provided via video-conferencing using Skype™ software (version 7.24, Microsoft Corp., Redmond, WA). The physiotherapist used the same standard notebook during the study (MacBook Pro, Model A1502, Apple Inc., Cupertino, CA). Participants used their personal computers; however, a webcam and standard headphones with a microphone were provided by the researchers. Standard broadband internet connection (download/upload speed: at least 3/1 Mbps) was used by both the physiotherapist and participants. The first session was held at the clinic.

The Physical, Environment, Task, Timing, Learning, Emotion, Perspective (PETTLEP) model was followed for MIT standardization.¹⁵ The PETTLEP model suggests seven motor imagery elements that should be considered to maximize functional equivalence.¹⁵ Functional equivalence is defined as the greatest possible stimulation of the same brain areas during motor imagery than during actual, and reinforcement of the memory trace of the corresponding motor task.¹⁵

Functional deficits of the participants were analysed in detail based on baseline assessments. Individualized MIT scripts were written for each participant and included task-oriented functional movements that could improve their functional deficits. The physiotherapist selected the majority of imaged functional activities, but different activities or environments were also included according to the participant's wishes.

Before sessions, participants were asked to inform other people in the house, to close the doors and windows of the room, and to have their phones in silent mode in order to minimize external distractions. During sessions, they were asked to sit on a comfortable chair in their preferred comfortable position and to keep their eyes closed. At the beginning of sessions, relaxation exercises were performed in order to maximize attention during MIT. These relaxation exercises lasted approximately 5 min and consisted of breath control, deep breathing, and awareness exercises.

After relaxation exercises, multisensory environmental information was provided using auditory, visual, tactile, and olfactory cues. For example, for a seaside environment, participants were asked to imagine seeing the blue colour of the sea, feeling the texture and warmth of the sand under their feet, smelling the sea salt in the air and hearing the sound of waves breaking on the shore.

During MIT, patients attempted to make their imaginations as similar to the actual executed movements as possible. Positive feedback and encouragement were provided about how well and easily the participant performed the movement. MIT was usually performed from a first-person perspective, but a third-person perspective was occasionally used.

MIT progressed as participants learned their imagined movements or as their proficiency in the corresponding actualized movement increased. For example, if a participant reported that he/she was now able to walk more comfortably, the imagined walking surface was changed (e.g. unstable, uneven or uphill) or speed was increased.

Fatigue levels before and after each session were evaluated using a 0–10 numerical rating scale. In case of marked difference in fatigue levels, adjustments were made for the following sessions. After each session, the technical quality of the Tele-MIT session was assessed using a 0–10 numerical rating scale, with scores of 7–10 considered good. Participants were also asked whether there were any interruptions, such as disconnections, noise, etc., and to what extent they affected the quality.

Study protocol

Intervention-blinded assessors evaluated the pwMS. Adequate rest periods were provided between the tests, especially before the motor imagery and cognitive assessments. The pre-intervention assessment was performed within one week before the day of the first session, and the post-intervention assessment within one week after the last intervention session at 8 weeks. The MS control group was a wait-list group with no specific intervention. These participants were evaluated twice at an interval of 8 weeks. The healthy participants were evaluated only once.

Motor imagery abilities were assessed using a questionnaire and mental chronometry. The Kinesthetic and Visual Imagery Questionnaire (KVIQ)-short version was used to determine the extent to which individuals were able to visualize and feel imagined movements.¹⁶ KVIQ is a valid and reliable measure for pwMS.¹⁷ Mental chronometry assessments were performed for 2, 5 and 10 m walks and the Timed Up and Go (TUG) test. Temporal congruence between actual and imagined movement was calculated as delta time.¹⁸

Primary outcome measure

Because the objective was to determine the effects of Tele-MIT on gait and balance compared to conventional MS treatments, the Dynamic Gait Index (DGI) was chosen as the primary outcome measure. The DGI assesses dynamic balance and gait ability and has adequate psychometric properties in pwMS.^19,20

Secondary outcome measures

Walking speed and endurance were assessed using the Timed 25-Foot Walk (T25FW) and 2-Minute Walk Test (2MWT), respectively.^21–23 Perceived walking ability was assessed by the Turkish version of 12-Item MS Walking Scale (MSWS-12), which has been shown to be valid and reliable.²⁴

Balance and balance confidence were assessed with commonly used outcome measures in MS including TUG,¹⁸ the Turkish version of the Activities-specific Balance Confidence (ABC) Scale,^25,26 and a computerized posturography device. Postural Stability Test (PST) and Limits of Stability (LOS) test were used to assess postural control and balance using the Balance System™ SD (Model: 115 VAC, Biodex Medical Systems, Inc., New York). PST emphasizes an individual’s ability to maintain their centre of balance. Lower scores reflect less motion during the test, indicating poor postural balance control. The LOS test challenges individuals to move and control their centre of gravity within their base of support. Lower scores or increased times to complete the LOS test indicate decreased dynamic balance control performance.

Cognitive functions were assessed by the Symbol Digit Modalities Test (SDMT),²⁷ Selective Reminding Test (SRT),²⁸ and 10/36 Spatial Recall Test (10/36SRT).²⁹ Psychosocial domains including fatigue, anxiety, depression, and quality of life were evaluated using valid and reliable measures for pwMS. Psychosocial assessments included the Modified Fatigue Impact Scale (MFIS),^30,31 Hospital Anxiety and Depression Scale (HADS),^32,33 and Multiple Sclerosis International Quality of Life questionnaire (MusiQoL).³⁴

A record sheet was prepared for possible adverse events during the tests and intervention. It included information about seriousness, expectedness, severity, causality, time, duration of the event and clinical action taken.

Statistical analysis

A priori sample size was calculated as 21 participants in each group for a power of 0.80, alpha error probability of 0.05 and effect size of 0.80 according to the primary outcome measure. Therefore, it was decided to recruit at least 25 participants in each group to account for possible dropouts.

Statistical analyses were performed using IBM SPSS Statistics (version 23.0, IBM Corp., Armonk, NY). Normal distribution of variables was assessed using Shapiro-Wilk test, histogram and probability plots. Nonparametric test statistics were conducted because the data were not normally distributed. Continuous variables are expressed by median (interquartile range), while categorical variables are shown as frequency and percentage. Kruskal–Wallis H test was used to assess the significance of differences between groups for continuous variables. Post hoc analyses of groups with significant differences were performed using the Mann–Whitney U test with Bonferroni correction. For categorical variables, significance of differences between groups was assessed using chi-square test. Statistical significance of changes in primary and secondary outcome measures from before to after the intervention was assessed using the Wilcoxon signed-rank test. Effect sizes were calculated as Cohen's d coefficients; d values above 0.8 were interpreted as large. Post hoc power analysis was calculated using the effect size of the primary outcome measure. A priori sample size and post hoc power analysis were calculated G-Power software (Version 3.1.9.2, Düsseldorf University, Germany). Statistical significance level was set at p < 0.05.

Results

Seventy-eight pwMS and 20 healthy individuals were screened. Fifty pwMS were randomly divided into two groups: intervention (n = 25) and control (n = 25). Five participants from the intervention group and 10 participants from the control group dropped out of the study for various reasons. Twenty participants completed the 8-week Tele-MIT; however, one did not complete the post-intervention assessment due to a change in employment (Figure 1). Participants showed no adverse effects related to the Tele-MIT or testing protocols. Tele-MIT compliance was very high, with no missed sessions.

Figure 1.

Flow chart of study.

No statistically significant difference was found in demographic characteristics between the intervention, MS control and healthy groups (p > 0.05). In addition, there was no significant difference in participants’ clinical characteristics (EDSS and disease duration) or motor imagery abilities between the intervention and MS control groups (p > 0.05) (Table 1).

Table 1.

Comparison of demographic and clinical characteristics and motor imagery abilities of the participants in the intervention, control and healthy control groups.

Variables	Intervention group (n = 20)	Control group (n = 15)	Healthy controls (n = 20)	p
Age (years)^†	34.5 (30–38.75)	36 (28–45)	31 (27–45.5)	0.717
Gender
Female/male	16 (80%)/4 (20%)	14 (93.3%)/1 (6.7%)	14 (93.3%)/6 (6.7%)	0.233^§
Body mass index (kg/m²)^†	22.61 (20.06–25.03)	22.48 (21.20–24.61)	22.63 (19.54–25.74)	0.970
Education level
Primary school	0	1 (6.7%)	0	0.279^§
Secondary school	0	0	1 (5%)
High school	6 (30%)	1 (6.7%)	3 (15%)
University	14 (70%)	13 (86.7%)	16 (80%)
Employment status
Employee	11 (55%)	10 (66.7%)	15 (75%)	0.733^§
Non-employee	5 (25%)	3 (20%)	2 (10%)
Retired	2 (10%)	2 (13.3%)	2 (10%)
Student	2 (10%)	0 (%0)	1 (5%)
Marital status
Married	13 (65%)	9 (60%)	10 (50%)	0.595^§
Single	6 (30%)	5 (33.3%)	10 (50%)
Other	1 (5%)	1 (6.7%)	0
Disease duration (years)^†	4 (1.5–8)	4 (6.2–5.3)	–	0.705
EDSS (0–10)^†	1 (0–1.75)	2 (0–2.5)	–	0.259
KVIQ – visual^†	20 (17.25, 25.0)	21 (19, 25)	20.5 (19, 24.75)	0.791
KVIQ – kinaesthetic^†	19 (16.25, 24.0)	20 (10, 25)	20.5 (15.5, 24)	0.910
Delta 2 m walk^†	−17.84 (−43.74, 4.76)	−31.09 (−37.18, 0)	−14.24 (−34.04, 13.03)	0.599
Delta 5 m walk^†	7.77 (−12.05, 22.87)	−1.04 (−19.13, 21.87)	2.25 (−41.41, 27.95)	0.809
Delta 10 m walk^†	18.83 (−6.22, 39.22)	13.90 (−6.36, 22.31)	3.89 (−32.91, 12.50)	0.238
Delta TUG test^†	27.89 (9.99, 60.41)	30.14 (21.73, 40.59)	34.06 (13.68, 52.20)	0.885

^†Variables are presented as median (interquartile range), ^§Chi-squared test.

EDSS, Expanded Disability Status Scale; KVIQ, Kinesthetic and Visual Imagery Questionnaire; TUG, Timed Up and Go.

There was no significant difference in DGI scores between the intervention and MS control groups (p = 0.483). On the other hand, healthy controls had significantly higher DGI score compared to both MS groups (p < 0.05) (Table 2). No significant difference was observed in the study outcome measures between the intervention and MS control groups (p > 0.05) with the exception of SDMT score (p = 0.014) (Table 2). The intervention and MS control groups showed significantly decreased performance in most of the study outcome measures compared to the healthy controls (Table 2).

Table 2.

Comparison of the baseline primary and secondary outcome measure results of the participants in the intervention, control and healthy control groups.

Variables	Intervention group (n = 20)	Control group (n = 15)	Healthy controls (n = 20)	p	Post hoc analysis
Variables	Intervention group (n = 20)	Control group (n = 15)	Healthy controls (n = 20)	p	p ^†	p ^‡	p ^§
DGI	22.5 (19.25, 24)	24 (17, 24)	24 (24, 24)	<0.001*	0.483	<0.001**	0.002**
T25FW test (s)	4.46 (4.08, 5.23)	4.65 (3.84, 5.0)	3.57 (3.36, 3.94)	<0.001*	0.641	<0.001**	0.003**
2MWT (m)	182 (161.25, 190.25)	158 (145, 191)	198 (193, 221)	0.001*	0.151	0.003**	0.001**
MSWS-12	15 (12, 22)	15 (12, 23)	–	0.760	–	–	–
TUG test (s)	6.57 (5.43, 7.07)	6.45 (5.31, 7.0)	5.39 (4.97, 5.89)	0.014*	0.653	0.006**	0.037
ABC scale	91.25 (81.10, 97.82)	92.5 (58.75, 96.90)	96.57 (91.60, 98.80)	0.112	–	–	–
LOS – time (s)	40 (36, 46)	44 (38.5, 52.75)	40 (36, 50)	0.405	–	–	–
LOS – total	56 (43, 60)	52.5 (42.25, 57)	63 (48, 65)	0.150	–	–	–
PST	0.4 (0.22, 0.47)	0.3 (0.3, 0.65)	0.2 (0.2, 0.4)	0.027*	0.766	0.019	0.027
SDMT	57 (49.25, 62.5)	46 (34, 52)	58 (49.25, 63.75)	0.012*	0.014**	0.655	0.007**
SRT – short term	9 (7.47, 9.25)	9.2 (8.2, 9.8)	9.99 (8.83, 10.95)	0.024*	0.301	0.011**	0.074
SRT – long term	8 (7, 10)	9 (8, 10)	10 (9, 12)	0.005*	0.170	0.002**	0.060
10/36SRT – short term	6.3 (4.62, 7.52)	6.7 (5.3, 8.7)	9.85 (8.74, 10)	<0.001*	0.193	<0.001**	0.001**
10/36SRT – long term	6 (5.25, 8)	9 (4, 10)	10 (8, 10)	0.001*	0.381	<0.001**	0.021
MFIS – physical	18 (4.5, 21)	7 (3, 18)	2.5 (1, 10.5)	0.005*	0.256	0.002**	0.034
MFIS – cognitive	12 (6, 23.25)	5 (2, 8)	3 (0.25, 10.5)	0.012*	0.020	0.008**	0.556
MFIS – psychosocial	2.5 (0.25, 4)	3 (1, 6)	0 (0, 3.75)	0.155	–	–	–
MFIS – total	32 (13.25, 45.25)	14 (7, 29)	9 (3.25, 26.75)	0.014*	0.147	0.005**	0.151
HADS –anxiety	7.5 (5, 9)	4 (2, 9)	3.5 (1, 6.75)	0.016*	0.185	0.003**	0.306
HADS – depression	3 (2, 7.5)	2 (0, 5)	1 (1, 2.75)	0.025*	0.163	0.004**	0.561
MusiQoL	78.22 (70.36, 84.07)	78.22 (72.58, 84.67)	–	0.868	–	–	–

Variables are presented as median (interquartile range).

*p < 0.05, **p < 0.01.

^†Intervention vs. control group.

^‡Intervention vs. healthy controls groups.

^§Control vs. healthy controls groups.

DGI, Dynamic Gait Index; T25FW, Timed 25-Foot Walk; 2MWT, 2-Minute Walk Test; MSWS-12, 12-Item Multiple Sclerosis Walking Scale; TUG, Timed Up and Go; ABC, Activities-specific Balance Confidence; LOS, Limits of Stability; PST, Postural Stability Test; SDMT, Symbol Digit Modalities Test; SRT, Selective Reminding Test; 10/36SRT, 10/36 Spatial Recall Test; MFIS, Modified Fatigue Impact Scale; HADS, Hospital Anxiety and Depression Scale; MusiQoL, Multiple Sclerosis International Quality of Life questionnaire.

The healthy participants had significantly higher 2MWT, SRT short- and long-term and 10/36SRT short- and long-term scores compared to the intervention group (p < 0.05). T25FW, TUG test, MFIS (physical, cognitive and total) and HADS anxiety and depression scores were significantly lower in the healthy controls compared with the intervention group (p < 0.05). T25FW, 2MWT, SDMT and 10/36SRT short-term scores differed significantly between the MS control and healthy control groups (p < 0.05), but no other significant differences were observed (p > 0.05).

DGI scores significantly improved in the intervention group (p = 0.002) after the intervention, while no significant improvement was observed in the control group following the waiting period (p = 0.999) (Figure 2). The T25FW, MSWS-12, ABC scale, PST, SDMT, SRT short- and long-term, 10/36SRT short-term, MFIS physical, psychosocial and total, HADS anxiety and depression and MusiQoL scores were significantly improved from baseline at 8 weeks in the intervention group, represented by large effect sizes (p < 0.05, d > 0.80). No significant differences in secondary study outcome measures were observed from baseline at 8 weeks in the MS control group (p > 0.05) (Table 3).

Figure 2.

Changes in the primary outcome measure score in the intervention and control groups from baseline at 8 weeks.

Table 3.

Changes in the study outcome measures of the participants in the intervention and control groups from baseline at 8 weeks.

	Intervention group				Control group
Variables	At 8 weeks	Change from baseline	p	d	At 8 weeks	Change from baseline	p	d
DGI	24 (24, 24)	1 (0, 4)	0.002 ^*	1.887^†	24 (20, 24)	0 (0, 0)	0.999	0.001
T25FW test (s)	4.15 (3.98, 4.57)	−0.33 (−0.68, −0.09)	0.007 ^*	1.530^†	4.55 (3.75, 4.97)	−0.07 (−0.20, 0.34)	0.975	0.016
2MWT (m)	177 (168, 202)	3 (−7, 14)	0.227	0.561	173.5 (140, 189)	−2.5 (−11.3, 9.3)	0.824	0.115
MSWS-12	12 (12, 13)	−1 (−7, 0)	0.008 ^*	1.456^†	13.5 (12, 21.25)	0 (−2.5, 2.0)	0.721	0.185
TUG test (s)	6.16 (5.65, 7.03)	0.25 (−0.94, 0.44)	0.629	0.217	5.95 (5.28, 7.66)	0.23 (−0.21, 0.93)	0.184	0.730
ABC scale	96.88 (91.88, 99.37)	1.88 (0.63, 9.38)	0.002 ^*	1.944^†	91.90 (73.90, 98.28)	0 (−1.87, 2.81)	0.449	0.398
LOS – time (s)	40 (34, 43)	−2 (−4, 14)	0.147	0.686	42 (35, 52.25)	0 (−6.8, 5.6)	0.959	0.026
LOS – total	56 (50, 65)	4 (−4, 14)	0.067	0.899^†	55.5 (49.5, 63.5)	3.5 (−3.5, 12.3)	0.153	0.794
PST	0.3 (0.2, 0.4)	−0.1 (−0.1, 0)	0.008 ^*	1.478^†	0.3 (0.2, 0.5)	0 (−0.2, 0.1)	0.491	0.362
SDMT	58 (48, 68)	4 (0, 5)	0.008 ^*	1.468^†	45 (37, 52.5)	2 (−1, 5)	0.082	1.007^†
SRT – short term	10.5 (9.2, 11.2)	1.5 (0.5, 2.7)	0.001 ^*	2.083^†	9.1 (8.45, 10.87)	−0.2 (−0.7, 1.2)	0.906	0.061
SRT – long term	11 (10, 12)	2 (0, 4)	0.001 ^*	2.300^†	9.5 (9, 10.25)	0.5 (−1, 1.3)	0.496	0.357
10/36SRT – short term	8 (6.3, 9.3)	2 (0.4, 2.7)	0.005 ^*	1.625^†	8.18 (5, 9.16)	0.3 (−0.1, 1)	0.068	1.068^†
10/36SRT – long term	8 (6, 10)	1 (0, 2)	0.064	0.909^†	9 (7, 10)	0 (−1, 2.3)	0.291	0.567
MFIS – physical	5 (3, 8)	−9 (−16, 0)	0.001 ^*	2.210^†	6.5 (3, 18)	−0.5 (−4.5, 4.3)	0.937	0.041
MFIS – cognitive	5 (2, 12)	−5 (−14, 0)	0.802	1.903^†	0.5 (0, 6.5)	0 (−4.5, 0.8)	0.514	0.342
MFIS – psychosocial	0 (0, 1)	−2 (−3, 0)	0.018 ^*	1.245^†	6.5 (0, 14)	2 (−2, 6.8)	0.115	0.890^†
MFIS – total	10 (7, 17)	−15 (−30, −2)	0.001 ^*	2.181^†	17.5 (4, 39.75)	−1.5 (−9.5, 11.8)	0.826	0.114
HADS – anxiety	5 (2, 7)	−2 (−4, −1)	0.001 ^*	2.060^†	4 (2, 9)	0.5 (−1.3, 2.0)	0.812	0.123
HADS – depression	2 (2, 4)	−1 (−4, 0)	0.005 ^*	1.586^†	2.5 (0, 6.25)	0.5 (−1.3, 3.0)	0.608	0.267
MusiQoL	86.29 (82.25, 94.35)	8.87 (0, 20.16)	0.002 ^*	1.916^†	79.03 (66.73, 90.92)	−1.21 (−7.66, 7.46)	0.802	0.130

Variables are presented as median (interquartile range).

*p < 0.05.

^†Large effect size.

IQR, Interquartile range; DGI, Dynamic Gait Index; T25FW, Timed 25-Foot Walk; 2MWT, 2-Minute Walk Test; MSWS-12, 12-Item Multiple Sclerosis Walking Scale; TUG, Timed Up and Go; ABC, Activities-specific Balance Confidence; LOS, Limits of Stability; PST, Postural Stability Test; SDMT, Symbol Digit Modalities Test; SRT, Selective Reminding Test; 10/36SRT, 10/36 Spatial Recall Test; MFIS, Modified Fatigue Impact Scale; HADS, Hospital Anxiety and Depression Scale; MusiQoL, Multiple Sclerosis International Quality of Life questionnaire.

Discussion

To the best of our knowledge, this is the first randomized controlled trial investigating the effects of Tele-MIT in pwMS. The results have shown that Tele-MIT improves dynamic balance during walking, walking speed and perceived walking ability, balance confidence, cognitive functions, fatigue, anxiety, depression and quality of life.

Cognitive and motor dysfunction may be associated with deterioration in motor imagery abilities, which may raise doubt concerning the applicability and effectiveness of motor imaging training in people with neurological disease. For example, it has been shown that motor imagery abilities are affected in 40% of people after stroke.³⁵ It is important to understand the possible factors affecting motor imagery abilities because they may be related to the benefits of MIT; however, there is limited evidence regarding these factors in pwMS. Heremans et al. examined motor imagery abilities in pwMS with severe motor and cognitive dysfunction and showed that image clarity is preserved even in pwMS with high EDSS levels,³⁶ whereas temporal congruence is impaired. Because different cognitive and motor disorders are associated with different subtypes of MS, variation in the nature and degree of change in motor imagery abilities is expected among pwMS with different clinical features. In this context, Tabrizi et al. examined motor imagery abilities in pwMS with low disability levels,³⁷ such as those in our study, and demonstrated no significant differences in image clarity or intensity of kinaesthetic sensations between pwMS and healthy controls. Based on evidence from previous studies and our findings that motor imagery abilities are mostly preserved in pwMS, MIT seems to be an applicable method in this population.

Compared to the evidence regarding MIT in stroke and Parkinson’s disease, there is little information concerning pwMS. In a recent randomized controlled study, Seebacher et al. investigated the effects of MIT in pwMS and showed that there were significant improvements in walking speed, walking endurance, perceived walking ability, fatigue and quality of life.⁷ We also observed significant improvements in the same outcomes, except walking endurance. One possible reason for this discrepancy in walking endurance may be the use of different outcomes (2MWT vs. 6-minute walk test). Although 2MWT is considered a good alternative to the 6-minute walk test in pwMS, its use is recommended in shorter routine visits.²² However, considering the numerous outcome measures in our study, we decided to use the 2MWT as a less time-consuming alternative to the 6-minute walk test. Nevertheless, 2MWT may be insufficient to assess the efficacy of the treatment. In addition, the pwMS included in Seebacher et al.’s study had higher EDSS scores than our participants. It may be expected that pwMS with a greater walking impairment would show a larger response to treatment. Lastly, Seebacher et al. used a rhythmic MIT (cued by music or metronome) with verbal cues that are different from our method.⁷ Therefore, the greater gains observed in their study could be related to the positive effects of music on walking performance. Further research is needed to investigate the possible additional benefits of music in MIT.

The results of another pilot study also revealed that MIT had positive effects on walking, fatigue, and quality of life in pwMS.⁸ The authors of the study reported 100% retention, no adverse events, good compliance, high acceptability of the interventions, and no worsening of fatigue, similar to our findings. In our study, Tele-MIT compliance was very high, with no missed therapy sessions. Our study suggests that Tele-MIT is feasible and applicable in pwMS. However, dropout rates were high before the intervention. A structured introductory programme for the Tele-MIT would be a preferable option that must be investigated in future studies.

Catalan et al. investigated the efficacy of 5-week MIT in 20 pwMS and reported significant improvements in fatigue and quality of life.⁹ They also showed that the improvements in fatigue and physical subscale of quality of life persisted at 6-month follow-up. As there was no long-term follow-up in our study, we do not know whether achieved gains returned to baseline after cessation of Tele-MIT. Future Tele-MIT trials with longer follow-up are needed to better evaluate the long-term effects of MIT in pwMS.

Although our programme focused mainly on motor tasks, we hypothesized that it would also improve cognitive functions because it is known that physical exercise enhances cognitive function due to an increase of brain activity. As MIT and physical exercise share similar pathways, MIT also has the potential to boost cognitive functions. In addition, during our programme, many multisensory stimuli were used. A recent near-infrared spectroscopy study in healthy adults suggested that MIT improves the behavioural performance of working memory and enhances prefrontal cortex activity induced by the working memory task.³⁸ In addition, recent studies have also suggested that MIT can improve cognitive functions in people with stroke and Parkinson’s disease.^39,40 Our study has provided novel evidence on the efficacy of a Tele-MIT programme on cognitive functions in pwMS. Future studies with a larger sample size and cognitive function as a primary outcome measure are warranted.

Our study has certain limitations. First, the participants were mostly young and had low EDSS scores. Indeed, participants were not recruited a priori based on the presence of a specific problem that is being studied as a primary outcome, which has been identified as a major limitation. This limits the external validity and applicability to pwMS with a more severe disability. Moreover, since most of the participants’ DGI scores were maximal, as shown in Figure 2, the issue of a possible ceiling effect in the primary study outcome measure arises. Secondly, there was no long-term follow-up. Third, the calculated sample size could not be achieved due to the high dropout rate, which mostly occurred before the first assessment. However, post hoc power analysis revealed that the study power was high. In addition, we used a block size of two for the randomization to obtain more balanced groups over time. However, this small block size could increase the risk of the allocation process being predictable. To reduce selection bias, the investigators (assessor neurologist, physiotherapist, and psychotherapist) were blind to the size of each block. Finally, although the outcome measures used in our study are reliable, valid, and commonly used, studies including magnetic resonance imaging, electroencephalography and/or transcranial magnetic stimulation measurements would be beneficial in demonstrating possible neuroplasticity changes provided by MIT.

In conclusion, this study suggests that an 8-week Tele-MIT programme was feasible and effective in improving dynamic balance during walking, walking speed and perceived walking ability, balance confidence, cognitive functions, fatigue, anxiety, depression, and quality of life in pwMS.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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