Usability and feasibility of PreventS-MD web app for stroke prevention.
Stroke
epidemiology
hypertension
prevention
risk factors
stroke facilities
Journal
International journal of stroke : official journal of the International Stroke Society
ISSN: 1747-4949
Titre abrégé: Int J Stroke
Pays: United States
ID NLM: 101274068
Informations de publication
Date de publication:
19 Aug 2023
19 Aug 2023
Historique:
pubmed:
24
7
2023
medline:
24
7
2023
entrez:
24
7
2023
Statut:
aheadofprint
Résumé
Most strokes and cardiovascular diseases (CVDs) are potentially preventable if their risk factors are identified and well controlled. Digital platforms, such as the PreventS-MD web app (PreventS-MD) may aid health care professionals (HCPs) in assessing and managing risk factors and promoting lifestyle changes for their patients. This is a mixed-methods cross-sectional two-phase survey using a largely positivist (quantitative and qualitative) framework. During Phase 1, a prototype of PreventS-MD was tested internationally by 59 of 69 consenting HCPs of different backgrounds, age, sex, working experience, and specialties using hypothetical data. Collected comments/suggestions from the study HCPs in Phase 1 were reviewed and implemented. In Phase 2, a near-final version of PreventS-MD was developed and tested by 58 of 72 consenting HCPs using both hypothetical and real patient (n = 10) data. Qualitative semi-structured interviews with real patients (n = 10) were conducted, and 1 month adherence to the preventive recommendations was assessed by self-reporting. The four System Usability Scale (SUS) groups of scores (0-50 unacceptable; 51-68 poor; 68-80.3 good; >80.3 excellent) were used to determine usability of PreventS-MD. Ninety-nine HCPs from 27 countries (45% from low- to middle-income countries) participated in the study, and out of them, 10 HCPs were involved in the development of PreventS before the study, and therefore were not involved in the survey. Of the remaining 89 HCPs, 69 consented to the first phase of the survey, and 59 of them completed the first phase of the survey (response rate 86%), and 58 completed the second phase of the survey (response rate 84%). The SUS scores supported good usability of the prototype (mean score = 80.2; 95% CI [77.0-84.0]) and excellent usability of the final version of PreventS-MD (mean score = 81.7; 95% CI [79.1-84.3]) in the field. Scores were not affected by the age, sex, working experience, or specialty of the HCPs. One-month follow-up of the patients confirmed the high level of satisfaction/acceptability of PreventS-MD and (100%) adherence to the recommendations. The PreventS-MD web app has a high level of usability, feasibility, and satisfaction by HCPs and individuals at risk of stroke/CVD. Individuals at risk of stroke/CVD demonstrated a high level of confidence and motivation in following and adhering to preventive recommendations generated by PreventS-MD.
Sections du résumé
BACKGROUND
UNASSIGNED
Most strokes and cardiovascular diseases (CVDs) are potentially preventable if their risk factors are identified and well controlled. Digital platforms, such as the PreventS-MD web app (PreventS-MD) may aid health care professionals (HCPs) in assessing and managing risk factors and promoting lifestyle changes for their patients.
METHODS
UNASSIGNED
This is a mixed-methods cross-sectional two-phase survey using a largely positivist (quantitative and qualitative) framework. During Phase 1, a prototype of PreventS-MD was tested internationally by 59 of 69 consenting HCPs of different backgrounds, age, sex, working experience, and specialties using hypothetical data. Collected comments/suggestions from the study HCPs in Phase 1 were reviewed and implemented. In Phase 2, a near-final version of PreventS-MD was developed and tested by 58 of 72 consenting HCPs using both hypothetical and real patient (n = 10) data. Qualitative semi-structured interviews with real patients (n = 10) were conducted, and 1 month adherence to the preventive recommendations was assessed by self-reporting. The four System Usability Scale (SUS) groups of scores (0-50 unacceptable; 51-68 poor; 68-80.3 good; >80.3 excellent) were used to determine usability of PreventS-MD.
FINDINGS
UNASSIGNED
Ninety-nine HCPs from 27 countries (45% from low- to middle-income countries) participated in the study, and out of them, 10 HCPs were involved in the development of PreventS before the study, and therefore were not involved in the survey. Of the remaining 89 HCPs, 69 consented to the first phase of the survey, and 59 of them completed the first phase of the survey (response rate 86%), and 58 completed the second phase of the survey (response rate 84%). The SUS scores supported good usability of the prototype (mean score = 80.2; 95% CI [77.0-84.0]) and excellent usability of the final version of PreventS-MD (mean score = 81.7; 95% CI [79.1-84.3]) in the field. Scores were not affected by the age, sex, working experience, or specialty of the HCPs. One-month follow-up of the patients confirmed the high level of satisfaction/acceptability of PreventS-MD and (100%) adherence to the recommendations.
INTERPRETATION
UNASSIGNED
The PreventS-MD web app has a high level of usability, feasibility, and satisfaction by HCPs and individuals at risk of stroke/CVD. Individuals at risk of stroke/CVD demonstrated a high level of confidence and motivation in following and adhering to preventive recommendations generated by PreventS-MD.
Identifiants
pubmed: 37485871
doi: 10.1177/17474930231190745
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
17474930231190745Investigateurs
Foad Abd-Allah
(F)
Rufus Akinyemi
(R)
Reza Azarpazhooh
(R)
Anjali Bhatia
(A)
Philip M Bath
(PM)
Carol Brayne
(C)
Hrvoje Budincevic
(H)
Nicholas Child
(N)
Kamil Chwojnicki
(K)
Manuel Correia
(M)
Alan Davis
(A)
Gerry Devlin
(G)
Vida Demarin
(V)
Rajinder K Dhamija
(RK)
Ding Ding
(D)
Klara Dokova
(K)
Makarena Dudley
(M)
Jesse Dyer
(J)
Misty Edmonds
(M)
Marcela Ely
(M)
Mehdi Farhoudi
(M)
Svetlana Feigin
(S)
Caroline Fornolles
(C)
Aznida Firzah Abdul Aziz
(A)
Denis Gabriel
(D)
Seana Gall
(S)
Artyom Gil
(A)
Elena Gnedovskaya
(E)
Ann George
(A)
Michal Haršány
(M)
Matire Harwood
(M)
Argye Hillis
(A)
Zeng-Guang Hou
(ZG)
Kevin Hwang
(K)
Norlinah Ibrahim
(N)
Tania Ka'ai
(T)
Nidhi Kalra
(N)
Judith Katzenellenbogen
(J)
Law Zhe Kang
(L)
Arindam Kar
(A)
Bartosz Karaszewski
(B)
Vitalij Kazin
(V)
Miia Kivipelto
(M)
Saltanat Kamenova
(S)
Aida Kondybaeva
(A)
Pablo Lavados
(P)
Tsong-Hai Lee
(TH)
Liping Liu
(L)
Karim Mahawish
(K)
Michal Maluchnik
(M)
Sheila Martins
(S)
Farrah Mateen
(F)
Nahal Mavaddat
(N)
Man Mohan Mehndiratta
(M)
Robert Mikulik
(R)
Angela Oliver
(A)
Serefnur Özturk
(S)
Nikhil Patel
(N)
Michael Piradov
(M)
Binita Prakash
(B)
Tara Purvis
(T)
Ulf-Dietrich Reips
(UD)
Kev Roos
(K)
Jonathan Rosand
(J)
Ramesh Sahathevan
(R)
Lakshmanan Sekaran
(L)
Nikolay Shamalov
(N)
Deidre Anne De Silva
(D)
Vinod Singh
(V)
Alina Solomon
(A)
Padma Srivastava
(P)
Nijasri C Suwanwela
(NC)
Denise Taylor
(D)
Thomas Truelsen
(T)
Narayanaswamy Venketasubramanian
(N)
Ekaterina Volevach
(E)
Ondřej Volný
(O)
Joyce Wan
(J)
Katila Withanapathirana
(K)
Tamara Welte
(T)
David Wiebers
(D)
Andrea S Winkler
(AS)
Tissa Wijeratne
(T)
Teddy Wu
(T)
Wan Asyraf Wan Zaidi
(W)