Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial

References

• Giunti G, Kool J, Rivera Romero O, et al. Exploring the specific needs of persons with multiple sclerosis for mHealth solutions for physical activity: mixed-methods study. JMIR Mhealth Uhealth. 2018;6(2):e37.
   PubMed Web of Science ®Google Scholar
• Agnihothri S, Cui L, Delasay M, et al. The value of mHealth for managing chronic conditions. Health Care Manag Sci. 2020;23(2):185–202.
   PubMed Web of Science ®Google Scholar
• Marrie RA, Leung S, Tyry T, et al. Use of eHealth and mHealth technology by persons with multiple sclerosis. Mult Scler Relat Disord. 2019;27:13–19.
   PubMedGoogle Scholar
• Thompson AJ, Baranzini SE, Geurts J, et al. Multiple sclerosis. Lancet. 2018;391(10130):1622–1636.
   PubMed Web of Science ®Google Scholar
• Multiple Sclerosis International Federation. Atlas of MS. 3rd ed. Multiple Sclerosis International Federation; 2020. p. 1–37.
   Google Scholar
• Månsson E, Lexell J. Performance of activities of daily living in multiple sclerosis. Disabil Rehabil. 2004;26(10):576–585.
   PubMed Web of Science ®Google Scholar
• Spooren AIF, Timmermans AAA, Seelen HAM. Motor training programs of arm and hand in patients with MS according to different levels of the ICF: a systematic review. BMC Neurol. 2012;12:49.
   PubMed Web of Science ®Google Scholar
• Boesen N, Trénel R, Petersen L, et al. Longer term effectiveness of inpatient multidisciplinary rehabilitation on health-related quality of life in MS patients: a pragmatic randomized controlled trial – the Danish MS Hospitals Rehabilitation Study. Mult Scler. 2018;24(3):340–349.
   PubMed Web of Science ®Google Scholar
• Bevens W, Weiland T, Gray K, et al. Attrition within digital health interventions for people with multiple sclerosis: systematic review and meta-analysis. J Med Internet Res. 2022;24(2):e27735.
   PubMed Web of Science ®Google Scholar
• Winberg C, Kylberg M, Pettersson C, et al. The use of apps for health in persons with multiple sclerosis, Parkinson’s disease and stroke – barriers and facilitators. Stud Health Technol Inform. 2017;242:638–641.
   PubMedGoogle Scholar
• Gromisch ES, Turner AP, Haselkorn JK, et al. Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review. JAMIA Open. 2021;4(10).
   Google Scholar
• Bevens W, Gray K, Neate SL, et al. Characteristics of mHealth app use in an international sample of people with multiple sclerosis. Mult Scler Relat Disord. 2021;54:52–54.
   Google Scholar
• Plow M, Golding M. Using mHealth technology in a self-management intervention to promote physical activity among adults with chronic disabling conditions: randomized controlled trial. JMIR Mhealth Uhealth. 2017;5(12):e185.
   PubMed Web of Science ®Google Scholar
• Montalban X, Graves J, Midaglia L, et al. A smartphone sensor-based digital outcome assessment of multiple sclerosis. Mult Scler. 2022;28(4):654–664.
   PubMed Web of Science ®Google Scholar
• Midaglia L, Mulero P, Montalban X, et al. Adherence and satisfaction of smartphone- and smartwatch-based remote active testing and passive monitoring in people with multiple sclerosis: nonrandomized interventional feasibility study. J Med Internet Res. 2019;21(8):e14863.
   PubMed Web of Science ®Google Scholar
• Park G, Balcer MJ, Hasanaj L, et al. The MICK (mobile integrated cognitive kit) app: digital rapid automatized naming for visual assessment across the spectrum of neurological disorders. J Neurol Sci. 2022;434:120150.
   PubMed Web of Science ®Google Scholar
• Pratap A, Grant D, Vegesna A, et al. Evaluating the utility of smartphone-based sensor assessments in persons with multiple sclerosis in the real-world using an app (elevateMS): observational, prospective pilot digital health study. JMIR Mhealth Uhealth. 2020;8(10):e22108.
   PubMed Web of Science ®Google Scholar
• De Angelis M, Lavorgna L, Carotenuto A, et al. Digital technology in clinical trials for multiple sclerosis: systematic review. J Clin Med. 2021;10(11):2328.
   PubMed Web of Science ®Google Scholar
• Ghadiri F, Naser Moghadasi A, Sahraian MA. Telemedicine as a strategic intervention for cognitive rehabilitation in MS patients during COVID-19. Acta Neurol Belg. 2022;122(1):23–29.
   PubMed Web of Science ®Google Scholar
• Abou L, Wong E, Peters J, et al. Smartphone applications to assess gait and postural control in people with multiple sclerosis: a systematic review. Mult Scler Relat Disord. 2021;51:102943.
   PubMed Web of Science ®Google Scholar
• Pedullà L, Brichetto G, Tacchino A, et al. Adaptive vs. non-adaptive cognitive training by means of a personalized app: a randomized trial in people with multiple sclerosis. J Neuroeng Rehabil. 2016;13(1):1–10.
   PubMedGoogle Scholar
• Tacchino A, Veldkamp R, Coninx K, et al. Design, development, and testing of an app for dual-task assessment and training regarding cognitive-motor interference (CMI-APP) in people with multiple sclerosis: multicenter pilot study. JMIR Mhealth Uhealth. 2020;8(4):e15344.
   PubMed Web of Science ®Google Scholar
• Bove RM, Rush G, Zhao C, et al. A videogame-based digital therapeutic to improve processing speed in people with multiple sclerosis: a feasibility study. Neurol Ther. 2019;8(1):135–145.
   PubMed Web of Science ®Google Scholar
• Goodwin RA, Lincoln NB, das Nair R, et al. Evaluation of NeuroPage as a memory aid for people with multiple sclerosis: a randomised controlled trial. Neuropsychol Rehabil. 2020;30(1):15–31.
   PubMed Web of Science ®Google Scholar
• Tacchino A, Pedullà L, Bonzano L, et al. A new app for at-home cognitive training: description and pilot testing on patients with multiple sclerosis. JMIR Mhealth Uhealth. 2015;3(3):e85.
   PubMed Web of Science ®Google Scholar
• Hsieh K, Fanning J, Frechette M, et al. Usability of a fall risk mHealth app for people with multiple sclerosis: mixed methods study. JMIR Hum Factors. 2021;8(1):e25604.
   PubMedGoogle Scholar
• Stephens S, Schneiderman JE, Finlayson M, et al. Feasibility of a theory-informed mobile app for changing physical activity in youth with multiple sclerosis. Mult Scler Relat Disord. 2022;58:103467.
   PubMed Web of Science ®Google Scholar
• Paul L, Coulter EH, Miller L, et al. Web-based physiotherapy for people moderately affected with multiple sclerosis; quantitative and qualitative data from a randomized, controlled pilot study. Clin Rehabil. 2014;28(9):924–935.
   PubMed Web of Science ®Google Scholar
• Paul L, Renfrew L, Freeman J, et al. Web-based physiotherapy for people affected by multiple sclerosis: a single blind, randomized controlled feasibility study. Clin Rehabil. 2019;33(3):473–484.
   PubMed Web of Science ®Google Scholar
• Donkers SJ, Nickel D, Paul L, et al. Adherence to physiotherapy-guided web-based exercise for persons with moderate-to-severe multiple sclerosis a randomized controlled pilot study. Int J MS Care. 2020;22(5):208–214.
   PubMedGoogle Scholar
• Wingo BC, Rinker JR, Goss AM, et al. Feasibility of improving dietary quality using a telehealth lifestyle intervention for adults with multiple sclerosis. Mult Scler Relat Disord. 2020;46:102504.
   PubMed Web of Science ®Google Scholar
• Kayes NM, McPherson KM, Schluter P, et al. Exploring the facilitators and barriers to engagement in physical activity for people with multiple sclerosis. Disabil Rehabil. 2011;33(12):1043–1053.
   PubMed Web of Science ®Google Scholar
• Johansson S, Ytterberg C, Claesson IM, et al. High concurrent presence of disability in multiple sclerosis: associations with perceived health. J Neurol. 2007;254(6):767–773.
   PubMed Web of Science ®Google Scholar
• Cuesta-Gómez A, Sánchez-Herrera-Baeza P, Oña-Simbaña ED, et al. Effects of virtual reality associated with serious games for upper limb rehabilitation inpatients with multiple sclerosis: randomized controlled trial. J Neuroeng Rehab. 2020;17(1):1–10.
   PubMed Web of Science ®Google Scholar
• Van Beek JJW, Van Wegen EEH, Rietberg MB, et al. Feasibility of a home-based tablet app for dexterity training in multiple sclerosis: usability study. JMIR Mhealth Uhealth. 2020;8(6):e18204.
   PubMed Web of Science ®Google Scholar
• Van Beek JJW, Van Wegen EEH, Bol CD, et al. Tablet app based dexterity training in multiple sclerosis (TAD-MS): research protocol of a randomized controlled trial. Front Neurol. 2019;10:61.
   PubMed Web of Science ®Google Scholar
• Kamm CP, Mattle HP, Müri RM, et al. Home-based training to improve manual dexterity in patients with multiple sclerosis: a randomized controlled trial. Mult Scler. 2015;21(12):1546–1556.
   PubMed Web of Science ®Google Scholar
• Romberg A, Virtanen A, Ruutiainen J, et al. Effects of a 6-month exercise program on patients with multiple sclerosis: a randomized study. Neurology. 2004;63(11):2034–2038.
   PubMed Web of Science ®Google Scholar
• World Medical Association. Declaration of Helsinki, ethical principles for scientific requirements and research protocols. Bull World Health Organ. 2013;79(4):373.
   Google Scholar
• Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–173.
   PubMed Web of Science ®Google Scholar
• Mathiowetz V, Weber K, Kashman N, et al. Adult norms for the nine hole peg test of finger dexterity. Occup Ther J Res. 1985;5(1):24–38.
   Google Scholar
• Mokkink L, Knol D, Sonder J, et al. The Arm Function in Multiple Sclerosis Questionnaire (AMSQ): development and validation of a new tool using IRT methods. Disabil Rehabil. 2015;37(26):2445–2451.
   PubMed Web of Science ®Google Scholar
• Steinheimer S, Wendel M, Vanbellingen T, et al. The Arm Function in Multiple Sclerosis Questionnaire was successfully translated to German. J Hand Ther. 2018;31(1):137–140.e1.
   PubMed Web of Science ®Google Scholar
• Lamers I, Kelchtermans S, Baert I, et al. Upper limb assessment in multiple sclerosis: a systematic review of outcome measures and their psychometric properties. Arch Phys Med Rehabil. 2014;95(6):1184–1200.
   PubMed Web of Science ®Google Scholar
• Heldner MR, Vanbellingen T, Bohlhalter S, et al. Coin Rotation Task: a valid test for manual dexterity in multiple sclerosis. Phys Ther. 2014;94(11):1644–1651.
   PubMed Web of Science ®Google Scholar
• Paltamaa J, West H, Sarasoja T, et al. Reliability of physical functioning measures in ambulatory subjects with MS. Physiother Res Int. 2005;10(2):93–109.
   PubMedGoogle Scholar
• Hobart JC, Riazi A, Lamping DL, et al. How responsive is the Multiple Sclerosis Impact Scale (MSIS-29)? A comparison with some other self report scales. J Neurol Neurosurg Psychiatry. 2005;76(11):1539–1543.
   PubMed Web of Science ®Google Scholar
• Hobart J, Lamping D, Fitzpatrick R, et al. The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain. 2001;124(5):962–973.
   PubMed Web of Science ®Google Scholar
• Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–163.
   PubMed Web of Science ®Google Scholar
• Maula A, Lafond N, Orton E, et al. Use it or lose it: a qualitative study of the maintenance of physical activity in older adults. BMC Geriatr. 2019;19(1):1–13.
   PubMed Web of Science ®Google Scholar
• Garin O. Ceiling effect. In: Michalos AC, editor. Encyclopedia of quality of life and well-being research. Dordrecht: Springer Netherlands; 2014. p. 631–633.
   Google Scholar
• Bonnechère B, Rintala A, Spooren A, et al. Is mHealth a useful tool for self-assessment and rehabilitation of people with multiple sclerosis? A systematic review. Brain Sci. 2021;11(9):1187.
   PubMed Web of Science ®Google Scholar
• Di Tella S, Pagliari C, Blasi V, et al. Integrated telerehabilitation approach in multiple sclerosis: a systematic review and meta-analysis. J Telemed Telecare. 2020;26(7–8):385–399.
   PubMed Web of Science ®Google Scholar
• Charvet LE, Shaw MT, Haider L, et al. Remotely-delivered cognitive remediation in multiple sclerosis (MS): protocol and results from a pilot study. Mult Scler J Exp Transl Clin. 2015;1:1–10.
   Google Scholar
• Charvet LE, Yang J, Shaw MT, et al. Cognitive function in multiple sclerosis improves with telerehabilitation: results from a randomized controlled trial. PLOS One. 2017;12:1–13.
   Google Scholar
• Hancock LM, Bruce JM, Bruce AS, et al. Processing speed and working memory training in multiple sclerosis: a double-blind randomized controlled pilot study processing speed and working memory training in multiple sclerosis: a double-blind randomized controlled pilot study. J Clin Exp Neuropsychol. 2015;37(2):113–127.
   PubMed Web of Science ®Google Scholar
• Blanquero J, Cortés-Vega MD, García-Frasquet MÁ, et al. Exercises using a touchscreen tablet application improved functional ability more than an exercise program prescribed on paper in people after surgical carpal tunnel release: a randomised trial. J Physiother. 2019;65(2):81–87.
   PubMed Web of Science ®Google Scholar
• Kizony R, Zeilig G, Dudkiewicz I, et al. Tablet apps and dexterity: comparison between 3 age groups and proof of concept for stroke rehabilitation. J Neurol Phys Ther. 2016;40(1):31–39.
   PubMed Web of Science ®Google Scholar
• Halpern R, Agarwal S, Borton L, et al. Adherence and persistence among multiple sclerosis patients after one immunomodulatory therapy failure: retrospective claims analysis. Adv Ther. 2011;28(9):761–775.
   PubMed Web of Science ®Google Scholar
• Shatil E, Metzer A, Horvitz O, et al. Home-based personalized cognitive training in MS patients: a study of adherence and cognitive performance. NeuroRehabilitation. 2010;26(2):143–153.
   PubMed Web of Science ®Google Scholar
• Crayton H, Heyman RA, Rossman HS. A multimodal approach to managing the symptoms of multiple sclerosis. Neurology. 2004;63(11, Suppl. 5):S12–S18.
   PubMed Web of Science ®Google Scholar
• Fasczewski K, Gill D, Rothberger S. Physical activity motivation and benefits in people with multiple sclerosis. Disabil Rehabil. 2018;40(13):1517–1523.
   PubMed Web of Science ®Google Scholar
• Charvet LE. The Montreal Cognitive Assessment (MoCA) in multiple sclerosis: relation to clinical features. J Mult Scler. 2015;2(2):1–6.
   Google Scholar
• Weiner DL, Balasubramaniam V, Shah SI, et al. COVID-19 impact on research, lessons learned from COVID-19 research, implications for pediatric research. Pediatr Res. 2020;88(2):148–150.
   PubMed Web of Science ®Google Scholar