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Journal of Neurology

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Open Access 17-10-2023 | Review

eHealth tools to assess the neurological function for research, in absence of the neurologist – a systematic review, part I (software)

Authors: Vasco Ribeiro Ferreira, Esther Metting, Joshua Schauble, Hamed Seddighi, Lise Beumeler, Valentina Gallo

Published in: Journal of Neurology | Issue 1/2024

Abstract

Background

Neurological disorders remain a worldwide concern due to their increasing prevalence and mortality, combined with the lack of available treatment, in most cases. Exploring protective and risk factors associated with the development of neurological disorders will allow for improving prevention strategies. However, ascertaining neurological outcomes in population-based studies can be both complex and costly. The application of eHealth tools in research may contribute to lowering the costs and increase accessibility. The aim of this systematic review is to map existing eHealth tools assessing neurological signs and/or symptoms for epidemiological research.

Methods

Four search engines (PubMed, Web of Science, Scopus & EBSCOHost) were used to retrieve articles on the development, validation, or implementation of eHealth tools to assess neurological signs and/or symptoms. The clinical and technical properties of the software tools were summarised. Due to high numbers, only software tools are presented here.

Findings

A total of 42 tools were retrieved. These captured signs and/or symptoms belonging to four neurological domains: cognitive function, motor function, cranial nerves, and gait and coordination. An additional fifth category of composite tools was added. Most of the tools were available in English and were developed for smartphone device, with the remaining tools being available as web-based platforms. Less than half of the captured tools were fully validated, and only approximately half were still active at the time of data collection.

Interpretation

The identified tools often presented limitations either due to language barriers or lack of proper validation. Maintenance and durability of most tools were low. The present mapping exercise offers a detailed guide for epidemiologists to identify the most appropriate eHealth tool for their research.

Funding

The current study was funded by a PhD position at the University of Groningen. No additional funding was acquired.

Reddy KS (2016) Global Burden of Disease Study 2015 provides GPS for global health 2030. The Lancet 388(10053):1448–1449

Feigin VL, Nichols E, Alam T, Bannick MS, Beghi E, Blake N et al (2019) Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology 18(5):459–480

Feigin VL, Vos T, Nichols E, Owolabi MO, Carroll WM, Dichgans M et al (2020) The global burden of neurological disorders: translating evidence into policy. The Lancet Neurology 19(3):255–265PubMed

Eysenbach G (2001) What is e-health? J Med Internet Res 3(2):e20PubMedPubMedCentral

Peterson CB, Hamilton C, Hasvold P. From innovation to implementation: eHealth in the WHO European region. Copenhagen, Denmark: WHO Regional Office for Europe; 2016. 98 p.

Chattopadhyay S (2012) A prototype depression screening tool for rural healthcare: a step towards ehealth informatics. J Med Imaging Hlth Inform 2(3):244–249

Guitton MJ (2021) Something good out of something bad: eHealth and telemedicine in the Post-COVID era. Comput Hum Behav 123:106882

Steele Gray C, Miller D, Kuluski K, Cott C (2014) Tying ehealth tools to patient needs: exploring the use of ehealth for community-dwelling patients with complex chronic disease and Disability. JMIR Res Protoc 3(4):e67PubMedPubMedCentral

Mentis AFA, Dardiotis E, Efthymiou V, Chrousos GP (2021) Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews. BMC Med 19(1):6PubMedPubMedCentral

10.

Archer N, Lokker C, Ghasemaghaei M, DiLiberto D (2021) eHealth Implementation Issues in Low-Resource Countries: Model, Survey, and Analysis of User Experience. J Med Internet Res 23(6):e23715PubMedPubMedCentral

11.

Ferreira VR, Seddighi H, Beumeler L, Metting E, Gallo V (2022) eHealth tools to assess neurological function: a systematic review protocol for a mapping exercise. BMJ Open 12(9):e062691PubMedPubMedCentral

12.

Fuller G. Neurological Examination Made Easy. 6th ed. Elsevier; 2019.

13.

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA et al (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med 6(7):e1000100PubMedPubMedCentral

14.

Microsoft Corporation. Microsoft Visio [Internet]. 2018. Available from: https://products.office.com/en/visio/flowchart-software

15.

Hsu WY, Rowles W, Anguera JA, Anderson A, Younger JW, Friedman S et al (2021) Assessing cognitive function in multiple sclerosis with digital tools: observational study. J Med Internet Res 23(12):e25748PubMedPubMedCentral

16.

Twomey DM, Wrigley C, Ahearne C, Murphy R, De Haan M, Marlow N et al (2018) Feasibility of using touch screen technology for early cognitive assessment in children. Arch Dis Child 103(9):853–858PubMed

17.

Rentz DM, Dekhtyar M, Sherman J, Burnham S, Blacker D, Aghjayan SL et al (2016) The Feasibility of At-Home iPad Cognitive Testing For Use in Clinical Trials. J Prev Alzheimers Dis 3(1):8–12PubMedPubMedCentral

18.

Middleton RM, Pearson OR, Ingram G, Craig EM, Rodgers WJ, Downing-Wood H et al (2020) A rapid electronic cognitive assessment measure for multiple sclerosis: validation of cognitive reaction, an electronic version of the symbol digit modalities test. J Med Internet Res 22(9):e18234PubMedPubMedCentral

19.

Thabtah F, Mampusti E, Peebles D, Herradura R, Varghese J (2019) A Mobile-based screening system for data analyses of early dementia traits detection. J Med Syst 44:1

20.

Simfukwe C, Youn Y, Kim S, An S. Digital trail making test-black and white: Normal vs MCI. Applied Neuropsychology-Adult.

21.

Hsu WY, Rowles W, Anguera J, Zhao C, Anderson A, Alexander A et al (2021) Application of an adaptive, digital, game-based approach for cognitive assessment in multiple sclerosis: observational study. J Med Internet Res 23(1):e24356PubMedPubMedCentral

22.

Newland P, Oliver B, Newland JM, Thomas FP (2019) Testing feasibility of a mobile application to monitor fatigue in people with multiple sclerosis. J Neurosci Nurs 51(6):331–334PubMed

23.

Jongstra S, Wijsman L, Cachucho R, Hoevenaar-Blom M, Mooijaart S, Richard E (2017) Cognitive testing in people at increased risk of dementia using a smartphone app: the ivitality proof-of-principle study. JMIR Mhealth And Uhealth. 5(5):e68PubMedPubMedCentral

24.

Holding BC Ingre, M, Petrovic, P, Sundelin, T, Axelsson, J. (2021) Quantifying Cognitive Impairment After Sleep Deprivation at Different Times of Day: A Proof of Concept Using Ultra-Short Smartphone-Based Tests. Frontiers in Behavioral Neuroscience 15.

25.

Weizenbaum EL, Fulford D, Torous J, Pinsky E, Kolachalama VB, Cronin-Golomb A (2021) Smartphone-based neuropsychological assessment in Parkinson’s disease: feasibility, validity, and contextually driven variability in cognition. J Int Neuropsycho Societ : JINS 17:1–13

26.

Zorluoglu G, Kamasak ME, Tavacioglu L, Ozanar PO (2015) A mobile application for cognitive screening of dementia. Computer Methods Programs Biomed 118(2):252

27.

Clionsky M, Clionsky E (2014) Psychometric equivalence of a paper-based and computerized (iPad) version of the memory orientation screening test (MOST^®). Clin Neuropsychol 28(5):747–755PubMed

28.

Brearly T, Rowland J, Martindale S, Shura R, Curry D, Taber K (2019) Comparability of iPad and web-based nih toolbox cognitive battery administration in veterans. Arch Clin Neuropsychol 34(4):524–530PubMed

29.

Demeyere N, Haupt M, Webb S, Strobel L, Milosevich E, Moore M et al (2021) Introducing the tablet-based Oxford cognitive screen-Plus (OCS-Plus) as an assessment tool for subtle cognitive impairments. Sci Rep 12(11):1

30.

Dorociak KE, Mattek N, Lee J, Leese MI, Bouranis N, Imtiaz D et al (2021) The survey for memory, attention, and reaction time (SMART): development and validation of a brief web-based measure of cognition for older adults. Gerontology 67(6):740–752PubMed

31.

Lunardini F, Luperto M, Romeo M, Basilico N, Daniele K, Azzolino D et al (2020) Supervised digital neuropsychological tests for cognitive decline in older adults: usability and clinical validity study. JMIR Mhealth Uhealth 8(9):e17963PubMedPubMedCentral

32.

Kokubo N, Yokoi Y, Saitoh Y, Murata M, Maruo K, Takebayashi Y et al (2018) A new device-aided cognitive function test, User eXperience-trail making test (UX-TMT), sensitively detects neuropsychological performance in patients with dementia and Parkinson’s disease. BMC Psychiatry 18(1):220PubMedPubMedCentral

33.

Dimauro G Di Nicola, V, Bevilacqua, V, Caivano, D, Girardi, F. (2017) Assessment of speech intelligibility in Parkinson’s disease using a speech-to-text system. IEEE Access 5

34.

Wilson P, Leitner C, Moussalli A. Mapping the Potential of eHealth: Empowering the Citizen through eHealth Tools and Services. 53.

35.

Wilson RS, Leurgans SE, Boyle PA, Schneider JA, Bennett DA (2010) Neurodegenerative basis of age-related cognitive decline. Neurology 75(12):1070–1078PubMedPubMedCentral

36.

Alberts JL, Koop MM, McGinley MP, Penko AL, Fernandez HH, Shook S et al (2021) Use of a smartphone to gather parkinson’s disease neurological vital signs during the COVID-19 pandemic. Parkinsons Dis 2021:5534282PubMedPubMedCentral

37.

Rosenthal BD Jenkins, TJ, Ranade, A, Bhatt, S, Hsu, WK, Patel, AA. (2019) The use of a novel tablet application to quantify dysfunction in cervical spondylotic myelopathy patients. Spine Journal. 19.

38.

Kostikis N Hristu Varsakelis, D, Arnaoutoglou, M, Kotsavasiloglou, C. A smartphone-based tool for assessing parkinsonian hand tremor. IEEE Journal of Biomedical and Health Informatics. 2015;19.

39.

Kassavetis P Saifee, TA, Roussos, G, Drougkas, L, Kojovic, M, Rothwell, JC, Edwards, MJ, Bhatia, KP. (2016) Developing a tool for remote digital assessment of parkinson’s disease. Movement Disorders Clinical Practice 3

40.

Lee CY, Kang SJ, Hong SK, Ma HI, Lee U, Kim YJ (2016) A validation study of a smartphone-based finger tapping application for quantitative assessment of bradykinesia in parkinson’s disease. PLoS ONE 11(7):e0158852PubMedPubMedCentral

41.

Kuosmanen E, Wolling F, Vega J, Kan V, Nishiyama Y, Harper S et al (2020) Smartphone-based monitoring of parkinson disease: quasi-experimental study to quantify hand tremor severity and medication effectiveness. JMIR Mhealth Uhealth 8(11):e21543PubMedPubMedCentral

42.

Linder S, Koop M, Tucker D, Guzi K, Gray D, Alberts J (2021) Development and validation of a mobile application to detect visual dysfunction following mild traumatic brain injury. Mil Med 186:584–591PubMed

43.

Quinn TJ, Livingstone I, Weir A, Shaw R, Breckenridge A, McAlpine C et al (2018) Accuracy and feasibility of an android-based digital assessment tool for post stroke visual disorders-the strokevision app. Front Neurol 9:146PubMedPubMedCentral

44.

Tosic L, Goldberger E, Maldaner N, Sosnova M, Zeitlberger AM, Staartjes VE et al (2020) Normative data of a smartphone app-based 6-minute walking test, test-retest reliability, and content validity with patient-reported outcome measures. J Neurosurg Spine 29:1–10

45.

Arcuria G, Marcotulli C, Amuso R, Dattilo G, Galasso C, Pierelli F et al (2020) Developing a smartphone application, triaxial accelerometer-based, to quantify static and dynamic balance deficits in patients with cerebellar ataxias. J Neurol 267(3):625–639PubMed

46.

Marano M Motolese, F, Rossi, M, Magliozzi, A, Yekutieli, Z, Di Lazzaro, V. (2021) Remote smartphone gait monitoring and fall prediction in Parkinson’s disease during the COVID-19 lockdown. Neurological Sciences 42.

47.

Bourke A, Scotland A, Lipsmeier F, Gossens C, Lindemann M. Gait Characteristics Harvested during a Smartphone-Based Self-Administered 2-Minute Walk Test in People with Multiple Sclerosis: Test-Retest Reliability and Minimum Detectable Change. SENSORS. 2020

48.

Serra-Añó P, Pedrero-Sánchez JF, Inglés M, Aguilar-Rodríguez M, Vargas-Villanueva I, López-Pascual J (2020) Assessment of Functional activities in individuals with Parkinson’s disease using a simple and Reliable smartphone-based procedure. Int J Environ Res Public Health 17:11

49.

Obuchi SP, Tsuchiya S, Kawai H (2018) Test-retest reliability of daily life gait speed as measured by smartphone global positioning system. Gait Posture 61:282PubMed

50.

Ishikawa M, Yamada S, Yamamoto K, Aoyagi Y (2019) Gait analysis in a component timed-up-and-go test using a smartphone application. J Neurol Sci 15(398):45–49

51.

Lee JB, Kim IS, Lee JJ, Park JH, Cho CB, Yang SH et al (2019) Validity of a smartphone application (sagittalmeter pro) for the measurement of sagittal balance parameters. World Neurosurg 126:e8-15PubMed

52.

Su D, Liu Z, Jiang X, Zhang F, Yu W, Ma H et al (2021) Simple smartphone-based assessment of gait characteristics in parkinson disease: validation study. JMIR Mhealth Uhealth 9(2):e25451PubMedPubMedCentral

53.

Pratap A, Grant D, Vegesna A, Tummalacherla M, Cohan S, Deshpande C et al (2020) 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 8(10):e22108PubMedPubMedCentral

54.

Frank B Fabian F, Brune B, Bozkurt B, Deuschl C, Nogueira RG, Kleinschnitz C, Köhrmann M, (2021) Validation of a shortened FAST-ED algorithm for smartphone app guided stroke triage. Therapeutic Advances in Neurological Disorders 14

55.

Baldereschi M, Di Carlo A, Piccardi B, Inzitari D (2016) The Italian stroke-app: ICTUS3R. Neurol Sci 37(6):991–994PubMed

56.

Arora S Venkataraman, V, Zhan, A, Donohue, S, Biglan, KM, Dorsey, ER, Little, MA. (2015) Detecting and monitoring the symptoms of Parkinson’s disease using smartphones: A pilot study. Parkinsonism and Related Disorders 21

57.

Park G, Balcer MJ, Hasanaj L, Joseph B, Kenney R, Hudson T et al (2022) The MICK (Mobile integrated cognitive kit) app: Digital rapid automatized naming for visual assessment across the spectrum of neurological disorders. J Neurol Sci 11(434):120150

58.

Pan D, Dhall R, Lieberman A, Petitti DB (2015) A mobile cloud-based Parkinson’s disease assessment system for home-based monitoring. JMIR Mhealth Uhealth 3(1):e29PubMedPubMedCentral

59.

Karr JE, Graham RB, Hofer SM, Muniz-Terrera G (2018) When does cognitive decline begin? A systematic review of change point studies on accelerated decline in cognitive and neurological outcomes preceding mild cognitive impairment, dementia, and death. Psychol Aging 33(2):195–218PubMedPubMedCentral

60.

Braak H, Rüb U, Del Tredici K (2006) Cognitive decline correlates with neuropathological stage in Parkinson’s disease. J Neurol Sci 248(1–2):255–258PubMed

61.

Dale O, Hagen KB (2007) Despite technical problems personal digital assistants outperform pen and paper when collecting patient diary data. J Clin Epidemiol 60(1):8–17PubMed

62.

Kazamel M, Stino AM, Smith AG (2021) Metabolic syndrome and peripheral neuropathy. Muscle Nerve 63(3):285–293PubMed

63.

Kirthi V, Perumbalath A, Brown E, Nevitt S, Petropoulos IN, Burgess J et al (2021) Prevalence of peripheral neuropathy in pre-diabetes: a systematic review. BMJ Open Diab Res Care 9(1):e002040PubMedPubMedCentral

64.

Fernandez C, Canadian Paediatric Society (CPS), Bioethics Committee. Ethical issues in health research in children. Paediatrics & Child Health. 2008 Oct 1;13(8):707–12.

65.

Ali MA, Alam K, Taylor B, Ashraf M (2021) Examining the determinants of eHealth usage among elderly people with disability: The moderating role of behavioural aspects. Int J Med Informatics 149:104411

66.

Alam K, Mahumud RA, Alam F, Keramat SA, Erdiaw-Kwasie MO, Sarker AR (2019) Determinants of access to eHealth services in regional Australia. Int J Med Informatics 131:103960

67.

De Main AS, Xie B, Shiroma K, Yeh T, Davis N, Han X (2022) Assessing the Effects of eHealth Tutorials on Older Adults’ eHealth Literacy. J Appl Gerontol 41(7):1675–1685PubMedPubMedCentral

68.

Humphreys GW, Duta MD, Montana L, Demeyere N, McCrory C, Rohr J et al (2017) Cognitive Function in low-income and low-literacy settings: validation of the tablet-based oxford cognitive Screen in the health and aging in africa: a longitudinal study of an INDEPTH community in South Africa (HAALSI). GERONB 72(1):38–50

69.

Raynor G, Baslet G (2021) A historical review of functional neurological disorder and comparison to contemporary models. Epilepsy & Behavior Reports 16:100489

70.

Spittel S, Kraus E, Maier A (2021) Dementia awareness challenges in sub-saharan africa: a cross-sectional survey conducted among school students in ghana. Am J Alzheimers Dis Other Demen 36:153331752110553

71.

Steinman L, van Pelt M, Hen H, Chhorvann C, Lan CS, Te V et al (2020) Can mHealth and eHealth improve management of diabetes and hypertension in a hard-to-reach population? —lessons learned from a process evaluation of digital health to support a peer educator model in Cambodia using the RE-AIM framework. mHealth 6(40):40PubMedPubMedCentral

72.

Karlyn A, Odindo S, Onyango R, Mbindyo C, Mberi T, Too G et al (2020) Testing mHealth solutions at the last mile: insights from a study of technology-assisted community health referrals in rural Kenya. mHealth 6(43):43PubMedPubMedCentral

73.

Lewis T, Synowiec C, Lagomarsino G, Schweitzer J (2012) E-health in low- and middle-income countries: findings from the center for health market innovations. Bull World Health Org 90(5):332–340PubMedPubMedCentral

74.

Montano IH, de la Torre DI, López-Izquierdo R, Villamor MAC, Martín-Rodríguez F (2021) Mobile triage applications: a systematic review in literature and play store. J Med Syst 45(9):86PubMedPubMedCentral

75.

Ioannidis JPA (2005) Why most published research findings are false. PLoS Med 2(8):e124PubMedPubMedCentral

76.

James L, Davies M, Mian S, Seghezzo G, Williamson E, Kemp S et al (2021) The BRAIN-Q, a tool for assessing self-reported sport-related concussions for epidemiological studies. Epidemiol Health 19(43):e2021086

77.

Gallo V, McElvenny DM, Seghezzo G, Kemp S, Williamson E, Lu K et al (2022) Concussion and long-term cognitive function among rugby players - The BRAIN Study. Alzheimer’s Dementia Journal Alzheimer’s Association 18(6):1164–1176

78.

Coiera E, Ammenwerth E, Georgiou A, Magrabi F (2018) Does health informatics have a replication crisis? J Am Med Inform Assoc 25(8):963–968PubMedPubMedCentral

79.

Kreps GL, Neuhauser L (2010) New directions in eHealth communication: Opportunities and challenges. Patient Educ Couns 78(3):329–336PubMed

80.

Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M (2015) Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth uHealth 3(1):e27PubMedPubMedCentral

Title: eHealth tools to assess the neurological function for research, in absence of the neurologist – a systematic review, part I (software)
Authors: Vasco Ribeiro Ferreira
Esther Metting
Joshua Schauble
Hamed Seddighi
Lise Beumeler
Valentina Gallo
Publication date: 17-10-2023
Publisher: Springer Berlin Heidelberg
Published in: Journal of Neurology / Issue 1/2024
Print ISSN: 0340-5354
Electronic ISSN: 1432-1459
DOI: https://doi.org/10.1007/s00415-023-12012-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

eHealth tools to assess the neurological function for research, in absence of the neurologist – a systematic review, part I (software)

Abstract

Background

Methods

Findings

Interpretation

Funding

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Findings

Interpretation

Funding

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