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Siregar et al. BMC Public Health (2021) 21:1308 https://doi.org/10.1186/s12889-021-11384-6 RESEARCH Open Access Potentials of community-based early detection of cardiovascular disease risk during the COVID-19 pandemic Kemal Nazarudin Siregar1,2*, Rico Kurniawan1, Ryza Jazid BaharuddinNur3, Dion Zein Nuridzin3, Yolanda Handayani2, Retnowati3, Rohjayanti4 and Lindawati Halim5 Abstract Background: The Coronavirus Disease 2019 (COVID-19) pandemic has led to a significant decline in Non Communicable Diseases (NCD) screening and early detection activities, especially Cardiovascular Disease (CVD). This study aims to assess the potential of community-based self-screening of CVD risk through the mhealth application. Methods: This is operational research by actively involving the community to carry out self-screening through the mHealth application. Community health workers were recruited as facilitators who encourage the community to carry out self-screening. To evaluate the potential of community-based self-screening of CVD risk, we use several indicators: responses rate, level of CVD risk, and community acceptance. Results: Of the 846 individuals reached by the cadres, 53% or 442 individuals carried out self-screening. Based on the results of self-screening of CVD risk, it is known that around 21.3% are at high risk of developing CVD in the next 10 years. The results of the evaluation of semi-structured questions showed that about 48% of the people had positive impressions, 22% assessed that this self-screening could increase awareness and was informative, 3% suggested improvements to self-screening tools. Conclusion: Cadres play an important role in reaching and facilitating the community in their environment to remain aware of their health conditions by conducting self-screening of CVD risk. The availability of the mHealth application that the public can easily access can simplify CVD risk prediction and expand screening coverage, especially during the COVID-19 pandemic, where there are social restrictions policies and community activities. Keywords: Early detection, Cardiovascular disease, Community-based, COVID-19, Mhealth Introduction the main risk factors for CVD are metabolic factors as- CVD is currently one of the leading causes of death, ac- sociated with hypertension, diabetes mellitus, and hyper- counting for about one-third of all deaths worldwide, cholesterolemia. In 2018, the Indonesian Basic Health four-fifths of which occur in developing countries [1]. In Research showed that the proportion of the most com- Indonesia, the main cause of morbidity and mortality is mon diseases was hypertension at 63.5%, diabetes melli- CVD responsible for one-third of all deaths [2]. Some of tus at 5.7%, heart disease at 4.5%, and stroke at 4.4% [3]. The Indonesian Basic Health Research has reported an * Correspondence: [email protected] increasing trend in hypertension, diabetes mellitus, and 1 Department of Biostatistics and Population Studies, Faculty of Public Health, stroke in Indonesia [4]. Observing the development of Universitas Indonesia, Depok, Indonesia 2Health Informatics Research Cluster, Faculty of Public Health, Universitas the CVD problem in Indonesia, which the COVID-19 Indonesia, Depok, Indonesia Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Siregar et al. BMC Public Health (2021) 21:1308 Page 2 of 8 pandemic has exacerbated, it is necessary to prepare encourage community members’ active participation in more responsive public health efforts to control CVD. self-screening and early detection of CVD. The most effective management of CVD is focused on The recruited cadres were given training on CVD and screening and early detection of preventable risk factors. the mHealth application as a self-screening and early de- Studies have shown that preventing disease and death tection of CVD risk. Furthermore, the cadres are asked from CVD will not be effective without population-based to actively reach the community in their environment to risk factor investigations and strengthening public aware- encourage the community to carry out independent ness about CVD prevention [5–7]. The data regarding the early detection through the mhealth application. In this distribution of CVD risk factors in the community is cur- study, we asked each cadre to reach at least 25 people rently insufficient to determine the appropriate interven- aged 15 years and over in their environment who can ac- tion. Therefore, a community-based early detection cess an early detection tool for CVD risk using mHealth. mechanism for CVD risk factors needs to be developed to In the outreach process, the cadres then broadcast strengthen the disease control program. WhatsApp messages that contain written informed con- Addressing this problem, the Government of Indonesia sent and the link to access the tool for early detection of has actually implemented a community-based control CVD risk to the community. People who receive mes- program under the health center at the sub-district level. sages from cadres independently conduct the early de- The program’s main target so far is the elderly. However, tection of CVD risk by filling out an online form using this program is underutilized. It is marked by low cover- the mHealth application. age, and since the COVID-19 outbreak, this program has almost stopped. The COVID-19 pandemic has led to a Development of mHealth for cardiovascular disease risk significant decline in CVD screening and treatment [8]. assessment Thus, the research question is, how can CVD control The CVD risk early detection form was modified and activities be reactivated so that early detection in the com- adapted according to WHO Stepwise [11]. The CVD risk munity during the COVID-19 pandemic can be conducted early detection form is then translated into an online properly? form that can be accessed easily with a smartphone A community-based participatory program (CPBR) is an using an open data kit (ODK) platform. The use of the approach to involve the community in research actively. ODK platform as a mHealth application here because is Research conducted by Tremblay et al. using the CBPR ap- considered quite easy and simple, so it is expected that proach can show significant processes and results such as the public can use it easily. creating awareness; shifting norms and beliefs about NCD When the community has completed the early detec- in the community; fostering community mobilization, col- tion independently, they will get the CVD risk calcula- laboration, and leadership around this issue; building com- tion results automatically displayed on the online form. munity capacity, skills, and expertise in NCD prevention; Automatically, the mHealth application will send the creating a culture of collaboration and resource sharing database of the results of the community self-screening among community organizations and permeating the NCD to a server that can be accessed by health workers so prevention agenda into other organizations [9]. CBPR that the data becomes a reference for health workers to enables researchers to understand better community strengthen the program. strengths, challenges, and opportunities [10]. mHealth performed the CVD risk assessment by calcu- This study aims to assess the potential of community- lating a risk index based on behavioral indicators using based self-screening of CVD risk through the mhealth the simple risk score (EZ-CVD) [12]. According to the application. We propose this research’s novelty because respondent’s answer, the risk index is calculated auto- it provides self-screening mechanisms and tools that are matically in the mHealth application based on the easily accessible to the public, especially during a pan- weighted results of the risk factor indicators. The results demic and even after the pandemic is over. of this risk index calculation are categorized into high risk (score ≥ 20%) and low risk (score < 20%). The risk Methods index can be read directly by respondents via mHealth. Building a community-based participatory program The risk assessment data were then analyzed descrip- To obtain the potential for self-screening and early detec- tively to assess mHealth’s ability to detect risk factors for tion of CVD risk in the community, we conducted an oper- CVD in the community. ational study in Babakan Madang District, Bogor Regency, in September–November 2020. Babakan Madang District Evaluation of community-based early detection of CVD consists of nine villages. We recruited two cadres in each risk village. Cadre or community health workers, voluntary- We use three indicators to evaluate the potential of based health workers, were prepared to reach out and community-based Early Detection of Cardiovascular Siregar et al. BMC Public Health (2021) 21:1308 Page 3 of 8 Disease Risk, that are response rate, the level of CVD is suitable for using the community as an early detection risk, and the community acceptance regarding self- tool for CVD during the COVID-19 pandemic.

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