Telerehabilitation in Progressive Multiple Sclerosis

NCT ID: NCT06485115

Last Updated: 2024-07-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

78 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-06-30

Study Completion Date

2026-06-30

Brief Summary

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Multiple sclerosis (MS) is a highly disabling chronic, inflammatory, demyelinating disease of the Central Nervous System (CNS). Significant progress has been made during the past three decades in managing the relapsing-remitting phase of Multiple Sclerosis (RRMS). However, once patients have entered the progressive stage of MS (secondary progressive, SPMS), therapeutic options are limited to symptomatic treatments and rehabilitation. In addition, 10-20% of patients experience unremitting disease progression (primary progressive MS, or PPMS). The limited research focusing on Progressive MS (PMS) and the lack of ecological validity highlight the need for a bolder approach that combines more than one intervention intending to produce synergistic effects. The primary aim is to test the effectiveness of combining a home-based Digital Telerehabilitation program with in-hospital rehabilitation on mobility against in-hospital rehabilitation alone.

Detailed Description

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The literature emphasizes a striking dearth of studies devoted solely to people with SPMS or PPMS and the lack of ecological validity in assessing the results. This suggests that an additional effort is required, a bolder approach that combines more than one intervention intending to produce synergistic effects, an improvement in one area boosting the putative benefits of therapy in another, the overall outcome exceeding the sum of the individual treatments.

The primary aim will be to test the effectiveness of combining a home-based digital motor telerehabilitation program (experimental intervention) with in-hospital rehabilitation on mobility (primary outcome) against in-hospital rehabilitation without any additional therapy except for general instructions for self-management as usual care (conventional treatment) in patients with SPMS or PPMS.

The secondary aims will be to explore the effects on measures of motor and cognitive function; the patients reported outcomes on balance and upper extremity function, fatigue, pain, anxiety, and depressive symptoms; the self-perception of clinical change; and Health-Related Quality of Life. Furthermore, the investigators will explore the patient's perspective and experience with Digital Telerehabilitation post-treatment using quantitative-qualitative methods (EG intervention). An economic evaluation of the introduction of the digital telemedicine program will be carried out within the health technology assessment (HTA) framework, considering the perspective of the healthcare system and society as a whole.

This single-blind RCT with 2-parallel arms will compare the effects between the experimental group (EG) and control group (CG). After the screening, an administrator external to research groups (the principal investigator) will generate a block randomization list at each Unit to prevent selection bias using an automated randomization system (www.randomization.com) (allocation ratio 1:1) to assign eligible patients to either the EG or the CG. Patients will be stratified according to the EDSS (≥ 6 and \< 6). Group allocation will be kept concealed. All patients will receive an individualized ten sessions of an in-hospital rehabilitation program (1 hour/day, 3 days/week) by a qualified physiotherapist at each participating unit. Then, the EG will follow a 12-week individualized Digital Telerehabilitation program (1 hour/day, 3 days/week, EG) while the CG will not receive any additional therapy except for general instructions for self-management according to the allocation group. All the patients will undergo four clinical evaluations: before (T0) and after (T1) the in-hospital rehabilitation program, 12 weeks (T2), and 24 weeks (follow-up, T3) after it. One researcher assistant with experience in assessing primary and secondary outcomes blinded to group assignment will evaluate study participants at all time points in each Unit.

Conditions

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Progressive Multiple Sclerosis

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

SINGLE

Outcome Assessors

Study Groups

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Home-based Digital motor Telerehabilitation added to conventional therapy

All patients will receive an individualized ten sessions of an in-hospital rehabilitation program (1 hour/day, 3 days/week) by a qualified physiotherapist at each participating unit. Then, the EG will follow a 12-week individualized Digital Telerehabilitation program (1 hour/day, 3 days/week, EG).

Group Type EXPERIMENTAL

Digital Telerehabilitation (Euleria Home)

Intervention Type DEVICE

After the in-hospital rehabilitation treatment (1 h/day, 3 days/week), the EG patients will perform the Digital Telerehabilitation program at home. The three weekly sessions will be asynchronous (with the caregiver's supervision if necessary). At each Unit, the physiotherapist will develop the training sessions on the Home- based Digital Telerehabilitation program and monitor the training execution provided by the digital device to adapt the rehabilitation treatment to the patients' improvements/difficulties. The Digital Telerehabilitation device (Euleria Home, Euleria Health) will consist of one wearable sensor and an app on a tablet that guides the patient through the customized exercise-therapy path configured by the professional. The sensor is worn on different body segments to monitor movements and provides real-time feedback on angles, balance, and repetitions.

Conventional therapy

Intervention Type OTHER

After the in-hospital rehabilitation treatment (1 h/day, 3 days/week), the CG patients will be advised to perform the Self-management activities learned during the in-hospital rehabilitation training without home-based Digital Telerehabilitation devices.

Conventional therapy alone

All patients will receive an individualized ten sessions of an in-hospital rehabilitation program (1 hour/day, 3 days/week) by a qualified physiotherapist at each participating unit. Then, the CG will not receive any additional therapy except for general instructions for self- management according to the allocation group.

Group Type OTHER

Conventional therapy

Intervention Type OTHER

After the in-hospital rehabilitation treatment (1 h/day, 3 days/week), the CG patients will be advised to perform the Self-management activities learned during the in-hospital rehabilitation training without home-based Digital Telerehabilitation devices.

Interventions

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Digital Telerehabilitation (Euleria Home)

After the in-hospital rehabilitation treatment (1 h/day, 3 days/week), the EG patients will perform the Digital Telerehabilitation program at home. The three weekly sessions will be asynchronous (with the caregiver's supervision if necessary). At each Unit, the physiotherapist will develop the training sessions on the Home- based Digital Telerehabilitation program and monitor the training execution provided by the digital device to adapt the rehabilitation treatment to the patients' improvements/difficulties. The Digital Telerehabilitation device (Euleria Home, Euleria Health) will consist of one wearable sensor and an app on a tablet that guides the patient through the customized exercise-therapy path configured by the professional. The sensor is worn on different body segments to monitor movements and provides real-time feedback on angles, balance, and repetitions.

Intervention Type DEVICE

Conventional therapy

After the in-hospital rehabilitation treatment (1 h/day, 3 days/week), the CG patients will be advised to perform the Self-management activities learned during the in-hospital rehabilitation training without home-based Digital Telerehabilitation devices.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Age 18-75;
* Diagnosis of MS (primary or secondary progressive);
* Mild to moderate balance impairments with increased fall risk, defined as TUG \> 8.4s;
* A disability rate, as calculated using the Kurtzke Expanded Disability Status Scale (EDSS) lower than 7;
* Acceptable level of digital skills;
* The presence of the caregiver.



* The absence of metallic implants in the brain;
* No history of brain surgery;
* No use of medications that alter cortical excitability or are presumed to affect brain plasticity;
* Right-handed dominance.

Exclusion Criteria

* Other conditions that may affect motor function;
* Impaired cognitive functioning (Mini-Mental Status Examination \<24/30);
* Severe visual deficits (daltonism and visual acuity deficit);
* Unable or refused to attend the rehabilitation treatment.
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Università degli Studi di Ferrara

OTHER

Sponsor Role collaborator

Universita di Verona

OTHER

Sponsor Role lead

Responsible Party

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Marialuisa Gandolfi

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Marialuisa Gandolfi

Role: PRINCIPAL_INVESTIGATOR

Universita di Verona

Locations

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Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona

Verona, , Italy

Site Status

Countries

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Italy

Central Contacts

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Marialuisa Gandolfi, PhD

Role: CONTACT

+390458124943

Marialuisa Gandolfi

Role: CONTACT

3491656108

References

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Lassmann H, Bruck W, Lucchinetti CF. The immunopathology of multiple sclerosis: an overview. Brain Pathol. 2007 Apr;17(2):210-8. doi: 10.1111/j.1750-3639.2007.00064.x.

Reference Type BACKGROUND
PMID: 17388952 (View on PubMed)

Lublin FD, Reingold SC. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology. 1996 Apr;46(4):907-11. doi: 10.1212/wnl.46.4.907.

Reference Type BACKGROUND
PMID: 8780061 (View on PubMed)

Lassmann H, van Horssen J, Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. Nat Rev Neurol. 2012 Nov 5;8(11):647-56. doi: 10.1038/nrneurol.2012.168. Epub 2012 Sep 25.

Reference Type BACKGROUND
PMID: 23007702 (View on PubMed)

Feinstein A, Freeman J, Lo AC. Treatment of progressive multiple sclerosis: what works, what does not, and what is needed. Lancet Neurol. 2015 Feb;14(2):194-207. doi: 10.1016/S1474-4422(14)70231-5.

Reference Type BACKGROUND
PMID: 25772898 (View on PubMed)

Morgen K, Kadom N, Sawaki L, Tessitore A, Ohayon J, McFarland H, Frank J, Martin R, Cohen LG. Training-dependent plasticity in patients with multiple sclerosis. Brain. 2004 Nov;127(Pt 11):2506-17. doi: 10.1093/brain/awh266. Epub 2004 Sep 29.

Reference Type BACKGROUND
PMID: 15456705 (View on PubMed)

Tomassini V, Matthews PM, Thompson AJ, Fuglo D, Geurts JJ, Johansen-Berg H, Jones DK, Rocca MA, Wise RG, Barkhof F, Palace J. Neuroplasticity and functional recovery in multiple sclerosis. Nat Rev Neurol. 2012 Nov 5;8(11):635-46. doi: 10.1038/nrneurol.2012.179.

Reference Type BACKGROUND
PMID: 22986429 (View on PubMed)

Tieri G, Morone G, Paolucci S, Iosa M. Virtual reality in cognitive and motor rehabilitation: facts, fiction and fallacies. Expert Rev Med Devices. 2018 Feb;15(2):107-117. doi: 10.1080/17434440.2018.1425613. Epub 2018 Jan 10.

Reference Type BACKGROUND
PMID: 29313388 (View on PubMed)

Peran P, Nemmi F, Dutilleul C, Finamore L, Falletta Caravasso C, Troisi E, Iosa M, Sabatini U, Grazia Grasso M. Neuroplasticity and brain reorganization associated with positive outcomes of multidisciplinary rehabilitation in progressive multiple sclerosis: A fMRI study. Mult Scler Relat Disord. 2020 Jul;42:102127. doi: 10.1016/j.msard.2020.102127. Epub 2020 May 6.

Reference Type BACKGROUND
PMID: 32438326 (View on PubMed)

Lotze M, Ladda AM, Stephan KM. Cerebral plasticity as the basis for upper limb recovery following brain damage. Neurosci Biobehav Rev. 2019 Apr;99:49-58. doi: 10.1016/j.neubiorev.2019.01.027. Epub 2019 Jan 30.

Reference Type BACKGROUND
PMID: 30710580 (View on PubMed)

Schmidt R, Lee T, Winstein C, et al. Motor control and learning: a behavioral emphasis. 2018. cited Sep. 17, 2022.,36

Reference Type BACKGROUND

Gandolfi M, Mazzoleni S, Morone G, Iosa M, Galletti F, Smania N. The role of feedback in the robotic-assisted upper limb rehabilitation in people with multiple sclerosis: a systematic review. Expert Rev Med Devices. 2023 Jan;20(1):35-44. doi: 10.1080/17434440.2023.2169129. Epub 2023 Jan 29.

Reference Type BACKGROUND
PMID: 36649574 (View on PubMed)

Dehem S, Montedoro V, Edwards MG, Detrembleur C, Stoquart G, Renders A, Heins S, Bruno D, Lejeune T. Development of a robotic upper limb assessment to configure a serious game. NeuroRehabilitation. 2019;44(2):263-274. doi: 10.3233/NRE-182525.

Reference Type BACKGROUND
PMID: 31006692 (View on PubMed)

Maier M, Rubio Ballester B, Duff A, Duarte Oller E, Verschure PFMJ. Effect of Specific Over Nonspecific VR-Based Rehabilitation on Poststroke Motor Recovery: A Systematic Meta-analysis. Neurorehabil Neural Repair. 2019 Feb;33(2):112-129. doi: 10.1177/1545968318820169. Epub 2019 Jan 30.

Reference Type BACKGROUND
PMID: 30700224 (View on PubMed)

Shaw MT, Best P, Frontario A, Charvet LE. Telerehabilitation benefits patients with multiple sclerosis in an urban setting. J Telemed Telecare. 2021 Jan;27(1):39-45. doi: 10.1177/1357633X19861830. Epub 2019 Jul 15.

Reference Type BACKGROUND
PMID: 31307269 (View on PubMed)

Thompson AJ. Neurorehabilitation in multiple sclerosis: foundations, facts and fiction. Curr Opin Neurol. 2005 Jun;18(3):267-71. doi: 10.1097/01.wco.0000169743.37159.a0.

Reference Type BACKGROUND
PMID: 15891410 (View on PubMed)

Freeman J, Hendrie W, Jarrett L, Hawton A, Barton A, Dennett R, Jones B, Zajicek J, Creanor S. Assessment of a home-based standing frame programme in people with progressive multiple sclerosis (SUMS): a pragmatic, multi-centre, randomised, controlled trial and cost-effectiveness analysis. Lancet Neurol. 2019 Aug;18(8):736-747. doi: 10.1016/S1474-4422(19)30190-5.

Reference Type BACKGROUND
PMID: 31301748 (View on PubMed)

Gandolfi M, Munari D, Geroin C, Gajofatto A, Benedetti MD, Midiri A, Carla F, Picelli A, Waldner A, Smania N. Sensory integration balance training in patients with multiple sclerosis: A randomized, controlled trial. Mult Scler. 2015 Oct;21(11):1453-62. doi: 10.1177/1352458514562438. Epub 2015 Jan 12.

Reference Type BACKGROUND
PMID: 25583852 (View on PubMed)

Straudi S, Tramontano M, Russo EF, et al. Robot-assisted upper limb training for patients with multiple sclerosis: an evidence-based review of clinical applications and effectiveness. Appl Sci. 2021 Dec;12(1):2222.

Reference Type BACKGROUND

Munari D, Fonte C, Varalta V, Battistuzzi E, Cassini S, Montagnoli AP, Gandolfi M, Modenese A, Filippetti M, Smania N, Picelli A. Effects of robot-assisted gait training combined with virtual reality on motor and cognitive functions in patients with multiple sclerosis: A pilot, single-blind, randomized controlled trial. Restor Neurol Neurosci. 2020;38(2):151-164. doi: 10.3233/RNN-190974.

Reference Type BACKGROUND
PMID: 32333564 (View on PubMed)

Gandolfi M, Vale N, Dimitrova EK, Mazzoleni S, Battini E, Benedetti MD, Gajofatto A, Ferraro F, Castelli M, Camin M, Filippetti M, De Paoli C, Chemello E, Picelli A, Corradi J, Waldner A, Saltuari L, Smania N. Effects of High-intensity Robot-assisted Hand Training on Upper Limb Recovery and Muscle Activity in Individuals With Multiple Sclerosis: A Randomized, Controlled, Single-Blinded Trial. Front Neurol. 2018 Oct 24;9:905. doi: 10.3389/fneur.2018.00905. eCollection 2018.

Reference Type BACKGROUND
PMID: 30405526 (View on PubMed)

Vale N, Gandolfi M, Mazzoleni S, Battini E, Dimitrova EK, Gajofatto A, Ferraro F, Castelli M, Camin M, Filippetti M, De Paoli C, Picelli A, Corradi J, Chemello E, Waldner A, Saltuari L, Smania N. Characterization of Upper Limb Impairments at Body Function, Activity, and Participation in Persons With Multiple Sclerosis by Behavioral and EMG Assessment: A Cross-Sectional Study. Front Neurol. 2020 Feb 14;10:1395. doi: 10.3389/fneur.2019.01395. eCollection 2019.

Reference Type BACKGROUND
PMID: 32116983 (View on PubMed)

Gandolfi M, Geroin C, Picelli A, Munari D, Waldner A, Tamburin S, Marchioretto F, Smania N. Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial. Front Hum Neurosci. 2014 May 22;8:318. doi: 10.3389/fnhum.2014.00318. eCollection 2014.

Reference Type BACKGROUND
PMID: 24904361 (View on PubMed)

Baroni A, Fregna G, Milani G, Severini G, Zani G, Basaglia N, Straudi S. Video game therapy on mobility and dual tasking in multiple sclerosis: study protocol for a randomised controlled trial. BMJ Open. 2021 Oct 21;11(10):e052005. doi: 10.1136/bmjopen-2021-052005.

Reference Type BACKGROUND
PMID: 34675018 (View on PubMed)

Straudi S, De Marco G, Martinuzzi C, Baroni A, Lamberti N, Brondi L, Da Roit M, Pizzongolo LDM, Basaglia N, Manfredini F. Combining a supervised and home-based task-oriented circuit training improves walking endurance in patients with multiple sclerosis. The MS_TOCT randomized-controlled trial. Mult Scler Relat Disord. 2022 Apr;60:103721. doi: 10.1016/j.msard.2022.103721. Epub 2022 Mar 5.

Reference Type BACKGROUND
PMID: 35276451 (View on PubMed)

Kalron A, Dolev M, Givon U. Further construct validity of the Timed Up-and-Go Test as a measure of ambulation in multiple sclerosis patients. Eur J Phys Rehabil Med. 2017 Dec;53(6):841-847. doi: 10.23736/S1973-9087.17.04599-3. Epub 2017 Mar 13.

Reference Type BACKGROUND
PMID: 28290192 (View on PubMed)

Fischer JS, Rudick RA, Cutter GR, Reingold SC. The Multiple Sclerosis Functional Composite Measure (MSFC): an integrated approach to MS clinical outcome assessment. National MS Society Clinical Outcomes Assessment Task Force. Mult Scler. 1999 Aug;5(4):244-50. doi: 10.1177/135245859900500409.

Reference Type BACKGROUND
PMID: 10467383 (View on PubMed)

Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Phys Ther. 2000 Sep;80(9):896-903.

Reference Type BACKGROUND
PMID: 10960937 (View on PubMed)

Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983 Jun;67(6):361-70. doi: 10.1111/j.1600-0447.1983.tb09716.x.

Reference Type BACKGROUND
PMID: 6880820 (View on PubMed)

Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989 Oct;46(10):1121-3. doi: 10.1001/archneur.1989.00520460115022.

Reference Type BACKGROUND
PMID: 2803071 (View on PubMed)

Powell LE, Myers AM. The Activities-specific Balance Confidence (ABC) Scale. J Gerontol A Biol Sci Med Sci. 1995 Jan;50A(1):M28-34. doi: 10.1093/gerona/50a.1.m28.

Reference Type BACKGROUND
PMID: 7814786 (View on PubMed)

Solaro C, Di Giovanni R, Grange E, Brichetto G, Mueller M, Tacchino A, Bertoni R, Patti F, Pappalardo A, Prosperini L, Castelli L, Rosato R, Cattaneo D, Marengo D. Italian translation and psychometric validation of the Manual Ability Measure-36 (MAM-36) and its correlation with an objective measure of upper limb function in patients with multiple sclerosis. Neurol Sci. 2020 Jun;41(6):1539-1546. doi: 10.1007/s10072-020-04263-2. Epub 2020 Jan 23.

Reference Type BACKGROUND
PMID: 31974795 (View on PubMed)

Caraceni A, Mendoza TR, Mencaglia E, Baratella C, Edwards K, Forjaz MJ, Martini C, Serlin RC, de Conno F, Cleeland CS. A validation study of an Italian version of the Brief Pain Inventory (Breve Questionario per la Valutazione del Dolore). Pain. 1996 Apr;65(1):87-92. doi: 10.1016/0304-3959(95)00156-5.

Reference Type BACKGROUND
PMID: 8826494 (View on PubMed)

Vickrey BG, Hays RD, Harooni R, Myers LW, Ellison GW. A health-related quality of life measure for multiple sclerosis. Qual Life Res. 1995 Jun;4(3):187-206. doi: 10.1007/BF02260859.

Reference Type BACKGROUND
PMID: 7613530 (View on PubMed)

Guy W. (1976). Clinical global impression scale. The ECDEU Assessment Manual for Psychopharmacology, Revised. US Department of Health, Education, and Welfare Publication (ADM), 76(338), 218-222. Rockville, MD: National Institute of Mental Health

Reference Type BACKGROUND

Buchholz I, Janssen MF, Kohlmann T, Feng YS. A Systematic Review of Studies Comparing the Measurement Properties of the Three-Level and Five-Level Versions of the EQ-5D. Pharmacoeconomics. 2018 Jun;36(6):645-661. doi: 10.1007/s40273-018-0642-5.

Reference Type BACKGROUND
PMID: 29572719 (View on PubMed)

Donisi V, Gajofatto A, Mazzi MA, Gobbin F, Busch IM, Ghellere A, Klonova A, Rudi D, Vitali F, Schena F, Del Piccolo L, Rimondini M. A Bio-Psycho-Social Co-created Intervention for Young Adults With Multiple Sclerosis (ESPRIMO): Rationale and Study Protocol for a Feasibility Study. Front Psychol. 2021 Feb 23;12:598726. doi: 10.3389/fpsyg.2021.598726. eCollection 2021.

Reference Type BACKGROUND
PMID: 33708157 (View on PubMed)

Donisi V, Poli S, Mazzi MA, Gobbin F, Schena F, Del Piccolo L, Bigardi V, Gajofatto A, Rimondini M. Promoting participatory research in chronicity: The ESPRIMO biopsychosocial intervention for young adults with multiple sclerosis. Front Psychol. 2022 Nov 3;13:1042234. doi: 10.3389/fpsyg.2022.1042234. eCollection 2022.

Reference Type BACKGROUND
PMID: 36405126 (View on PubMed)

Broadbent E, Petrie KJ, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res. 2006 Jun;60(6):631-7. doi: 10.1016/j.jpsychores.2005.10.020.

Reference Type BACKGROUND
PMID: 16731240 (View on PubMed)

Rolffs JL, Rogge RD, Wilson KG. Disentangling Components of Flexibility via the Hexaflex Model: Development and Validation of the Multidimensional Psychological Flexibility Inventory (MPFI). Assessment. 2018 Jun;25(4):458-482. doi: 10.1177/1073191116645905. Epub 2016 May 5.

Reference Type BACKGROUND
PMID: 27152011 (View on PubMed)

Bonino, S., Graziano, F., Borghi, M., Marengo, D., Molinengo, G., Calandri, E. (2018). The self-efficacy in Multiple Sclerosis (SEMS) Scale: development and validation with Rasch analysis. European Journal of Psychological Assessment, 34 (5), 352-360. DOI: 10.1027/1015-5759/a000350

Reference Type BACKGROUND

Emilia Ambrosini, Simona Ferrante, Mauro Rossini, Franco Molteni, Margit Gföhler, Werner Reichenfelser, Alexander Duschau-Wicke, Giancarlo Ferrigno and Alessandra Pedrocchi (2014). Functional and usability assessment of a robotic exoskeleton arm to support activities of daily life. Robotica, 32, pp 1213-1224 Doi:10.1017/S0263574714001891.

Reference Type BACKGROUND

Carpinella I, Cattaneo D, Bonora G, Bowman T, Martina L, Montesano A, Ferrarin M. Wearable Sensor-Based Biofeedback Training for Balance and Gait in Parkinson Disease: A Pilot Randomized Controlled Trial. Arch Phys Med Rehabil. 2017 Apr;98(4):622-630.e3. doi: 10.1016/j.apmr.2016.11.003. Epub 2016 Dec 10.

Reference Type BACKGROUND
PMID: 27965005 (View on PubMed)

Kim YK, Park E, Lee A, Im CH, Kim YH. Changes in network connectivity during motor imagery and execution. PLoS One. 2018 Jan 11;13(1):e0190715. doi: 10.1371/journal.pone.0190715. eCollection 2018.

Reference Type BACKGROUND
PMID: 29324886 (View on PubMed)

Ness NH, Haase R, Kern R, Schriefer D, Ettle B, Cornelissen C, Akguen K, Ziemssen T. The Multiple Sclerosis Health Resource Utilization Survey (MS-HRS): Development and Validation Study. J Med Internet Res. 2020 Mar 17;22(3):e17921. doi: 10.2196/17921.

Reference Type BACKGROUND
PMID: 32181745 (View on PubMed)

Marques E, Johnson EC, Gooberman-Hill R, Blom AW, Noble S. Using resource use logs to reduce the amount of missing data in economic evaluations alongside trials. Value Health. 2013 Jan-Feb;16(1):195-201. doi: 10.1016/j.jval.2012.09.008.

Reference Type BACKGROUND
PMID: 23337231 (View on PubMed)

www.imta.nl iMTA Productivity and Health Research Group. Manual iMTA Medical Cost Questionnaire (iMCQ). Rotterdam: iMTA, Erasmus University Rotterdam, 2018

Reference Type BACKGROUND

Bouwmans C, Krol M, Severens H, Koopmanschap M, Brouwer W, Hakkaart-van Roijen L. The iMTA Productivity Cost Questionnaire: A Standardized Instrument for Measuring and Valuing Health-Related Productivity Losses. Value Health. 2015 Sep;18(6):753-8. doi: 10.1016/j.jval.2015.05.009. Epub 2015 Aug 20.

Reference Type BACKGROUND
PMID: 26409601 (View on PubMed)

Sciaraffa N, Di Flumeri G, Germano D, Giorgi A, Di Florio A, Borghini G, Vozzi A, Ronca V, Babiloni F, Arico P. Evaluation of a New Lightweight EEG Technology for Translational Applications of Passive Brain-Computer Interfaces. Front Hum Neurosci. 2022 Jul 14;16:901387. doi: 10.3389/fnhum.2022.901387. eCollection 2022.

Reference Type BACKGROUND
PMID: 35911603 (View on PubMed)

Wiendl H, Hohlfeld R. Multiple sclerosis therapeutics: unexpected outcomes clouding undisputed successes. Neurology. 2009 Mar 17;72(11):1008-15. doi: 10.1212/01.wnl.0000344417.42972.54.

Reference Type BACKGROUND
PMID: 19289741 (View on PubMed)

Other Identifiers

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2023/R-Multi/010

Identifier Type: -

Identifier Source: org_study_id

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