Access to telehealth by stroke patients: which are the main barriers and how they are explained by the UTAUT theoretical model? A systematic review
DOI:
https://doi.org/10.1590/1809-2950/e22009023ptKeywords:
| Barriers to Access of Health Services, Telerehabilitation, Telehealth, Stroke, Physical Therapy ModalitiesAbstract
Stroke is a chronic health condition that
requires monitoring. In this sense, telehealth emerges
as a tool to enable better access. However, since it is
related to use of technology, this modality might face
new barriers. Our goal was to identify, with a systematic
literature review, the perceived barriers to telehealth
access by stroke patients and conceptualize them within
the Unified Theory of Acceptance and Use of Technology
(UTAUT) model. The systematic review was carried out in the following electronic databases: PubMed, MEDLINE, SciELO,
LILACS, and PEDro; and the combination of descriptors were:
“Barriers to Access to Health Care,” “Telerehabilitation,” “Telehealth,”
“Stroke,” and “Physical Therapy Modalities.” The included studies
focused on telehealth barriers perceived by stroke patients. Initially,
298 articles were found, 295 via databases search, and three
via active search; of these, only six articles were included in this
review. Overall, the articles revealed the perception of more than
220 stroke patients, with barriers categorized into eight types,
most of them related to the dimensions of Effort Expectancy and
Facilitating Conditions of the UTAUT model. The barriers of the
Effort Expectation dimension that are related to the knowledge in
the use of technologies are likely to be overcome since training can
be carried out before the telehealth service. However, the barriers
related to the Facilitating Conditions dimension regarding financial
aspects, the internet, and home context are difficult to overcome,
possibly interfering with user’s acceptance of telehealth.
Downloads
References
Krishnamurthi RV, Ikeda T, Feigin VL. Global, regional and
country-specific burden of ischaemic stroke, intracerebral
haemorrhage, and subarachnoid haemorrhage: a systematic
analysis of the Global Burden of Disease Study 2017.
Neuroepidemiology. 2020;54(2):171-9. doi: 10.1159/000506396.
Copstein L, Fernandes JG, Bastos GAN. Prevalence and risk factors
for stroke in a population of Southern Brazil. Arq Neuropsiquiatr.
;71(5):294-300. doi: 10.1590/0004-282X20130024.
Duncan PW, Zorowitz R, Bates B, Choi JY, Glasberg JJ,
et al. Management of adult stroke rehabilitation care:
a clinical practice guideline. Stroke. 2005;36(9):e100-43
doi: 10.1161/01.STR.0000180861.54180.FF.
Furlan L. Potential barriers and promising opportunities for stroke
rehabilitation in Brazil. Int J Stroke. 2014;9(Suppl A100):144.
doi: 10.1111/ijs.12338.
Sarfo FS, Adamu S, Awuah D, Sarfo-Kantanka O, Ovbiagele B.
Potential role of tele-rehabilitation to address barriers to
implementation of physical therapy among West African stroke
survivors: a cross-sectional survey. J Neurol Sci. 2017;381:203-8.
doi: 10.1016/j.jns.2017.08.3265.
Silva MA, Santos MLM, Bonilha LAS. Users’ perceptions of
outpatient physiotherapy in the public healthcare system in
Campo Grande (MS, Brazil): problem-solving capacity and
difficulties. Interface Comun Saude Educ. 2014;18(48):75-86.
Lieneck C, Herzog B, Krips R. Analysis of facilitators and
barriers to the delivery of routine care during the COVID-19
global pandemic: a systematic review. Healthcare (Basel).
;9(5):528. doi: 10.3390/healthcare9050528.
Caetano R, Silva AB, Guedes ACCM, Paiva CCN, Ribeiro GR,
et al. Challenges and opportunities for telehealth during the
COVID-19 pandemic: ideas on spaces and initiatives in the
Brazilian context. Cad Saude Publica. 2020;36(5):e00088920.
doi: 10.1590/0102-311X00088920.
Laver KE, Adey-Wakeling Z, Crotty M, Lannin NA, George S,
et al. Telerehabilitation services for stroke. Cochrane
Database Syst Rev. 2020;(1):CD010255. doi: 10.1002/
CD010255.pub3.
Pandian JD, Gall SL, Kate MP, Silva GS, Akinyemi RO, et
al. Prevention of stroke: a global perspective. Lancet.
;392(10154):1269-78. doi: 10.1016/S0140-6736(18)31269-8.
Khatun F, Palas JU, Ray P. Using the unified theory of acceptance
and use of technology model to analyze cloud-based
mHealth service for primary care. Digit Med. 2017;3(2):69-75.
doi: 10.4103/digm.digm_21_17.
Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance
of information technology: toward a unified view. MIS Q.
;27(3):425-78. doi: 10.2307/30036540.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC,
et al. The PRISMA 2020 statement: an updated guideline for
reporting systematic reviews. BMJ. 2021;372:n71. doi: 10.1016/j.
ijsu.2021.105906.
Øra HP, Kirmess M, Brady MC, Sørli H, Becker F. Technical features,
feasibility, and acceptability of augmented telerehabilitation in
post-stroke aphasia—experiences from a randomized controlled
trial. Front Neurol. 2020;11:671. doi: 10.3389/fneur.2020.00671.
Nemeth LS, Jenkins C, Jauch EC, Conway S, Pearlman A, et al.
A community-engaged assessment of barriers and facilitators
to rapid stroke treatment. Res Nurs Health. 2016;39(6):438-48.
doi: 10.1002/nur.21749.
Chen Y, Chen Y, Zheng K, Dodakian L, See J, et al. A qualitative
study on user acceptance of a home-based stroke
telerehabilitation system. Top Stroke Rehabil. 2020;27(2):81-92.
doi: 10.1080/10749357.2019.1683792.
Tyagi S, Lim DSY, Ho WHH, Koh YQ, Cai V, et al. Acceptance of
tele-rehabilitation by stroke patients: perceived barriers and
facilitators. Arch Phys Med Rehabil. 2018;99(12):2472-2477.e2.
doi: 10.1016/j.apmr.2018.04.033.
Chumbler NR, Quigley P, Li X, Morey M, Rose D, et al. Effects
of telerehabilitation on physical function and disability
for stroke patients: a randomized, controlled trial. Stroke.
;43(8):2168-74. doi: 10.1161/STROKEAHA.111.646943.
Wallace SE, Graham C, Saraceno A. Older adults’ use of
technology. Perspect Gerontol. 2013;18(2):50-9. doi: 10.1044/
gero18.2.50.
Chakraborty I, Hu PJH, Cui D. Examining the effects of cognitive
style in individuals’ technology use decision making. Decis
Support Syst. 2008;45(2):228-41. doi: 10.1016/j.dss.2007.02.003.
Martins EF, Sousa PHC, Barbosa PHFA, Menezes LT,
Costa AS. A Brazilian experience to describe functioning
and disability profiles provided by combined use of ICD and
ICF in chronic stroke patients at home-care. Disabil Rehabil.
;33(21-22):2064-74. doi: 10.3109/09638288.2011.560332.
Kauhanen M, Korpelainen J, Hiltunen P, Määttä R, Mononen H,
et al. Aphasia, depression, and non-verbal cognitive impairment
in ischaemic stroke. Cerebrovasc Dis. 2000;10(6):455-61.
doi: 10.1159/000016107.
Aprile I, Guardati G, Cipollini V, Papadopoulou D, Monteleone S,
et al. Influence of cognitive impairment on the recovery
of subjects with subacute stroke undergoing upper limb
robotic rehabilitation. Brain Sci. 2021;11(5):587. doi: 10.3390/
brainsci11050587.
Cumming TB, Marshall RS, Lazar RM. Stroke, cognitive deficits,
and rehabilitation: still an incomplete picture. Int J Stroke.
;8(1):38-45. doi: 10.1111/j.1747-4949.2012.00972.x.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Luana Karoline Castro Silva, Cristian Douglas Dantas de Sousa, Renata Viana Brígido de Moura Jucá, Ramon Távora Viana, Lidiane Andréa Oliveira Lima
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.