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Health-related hazards have a detrimental impact on society. The health emergency and disaster management system (Health EDMS), such as a contact-tracing application, is used to respond to and cope with health-related hazards. User compliance with Health EDMS warnings is key to its success. However, it was reported that user compliance with such a system remains low.
Through a systematic literature review, this study aims to identify the theories and corresponding factors that explain user compliance with the warning message provided by Health EDMS.
The systematic literature review was conducted using Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 guidelines. The search was performed using the online databases Scopus, ScienceDirect, ProQuest, IEEE, and PubMed, for English journal papers published between January 2000 and February 2022.
A total of 14 papers were selected for the review based on our inclusion and exclusion criteria. Previous research adopted 6 theories when examining user compliance, and central to the research was Health EDMS. To better understand Health EDMS, based on the literature reviewed, we mapped the activities and features of Health EDMS with the key stakeholders involved. We identified features that require involvement from individual users, which are surveillance and monitoring features and medical care and logistic assistance features. We then proposed a framework showing the individual, technological, and social influencing factors of the use of these features, which in turn affects compliance with the warning message from Health EDMS.
Research on the Health EDMS topic increased rapidly in 2021 due to the COVID-19 pandemic. An in-depth understanding of Health EDMS and user compliance before designing the system is essential for governments and developers to increase the effectiveness of Health EDMS. Through a systematic literature review, this study proposed a research framework and identified research gaps for future research on this topic.
Emergencies and disasters threaten the safety of human life and trigger acute feelings of stress, anxiety, and uncertainty [
Previous studies [
With the increasing risk of emergency and disaster, research related to EDMSs is constantly evolving for various hazard types, including health-related hazards. Health-related hazards, such as disease outbreaks (eg, COVID-19, avian influenza, and Ebola), are 1 of the most common hazardous events [
Health-related hazards have different characteristics from natural disasters and disasters caused by humans. When a natural disaster or human-induced disaster occurs, people are advised to evacuate to a safe place. In contrast, during a pandemic, people must stay at home or be quarantined to prevent disease transmission [
Understanding individual behavior toward Health EDMS is essential because health EDM is not solely the government's responsibility [
The extant literature reviews focus on the acceptance and adoption of Health EDMS. Although they have offered valuable insights into the development of studies in the Health EDMS field, little attention has been paid to how effective the warning message provided by Health EDMS generates user compliance [
To answer this question, we reviewed concepts related to hazards, the EDM cycle, and EDMS features from previous research to understand the activities and stakeholders involved in EDM. After that, we mapped the EDMS feature into a CTA to find out which EDMS features have been implemented to deal with health-related hazards. We also analyzed the roles and authorization of stakeholders in each feature to find out which features involve user participation and compliance. Through this mapping, this research can make a specific contribution regarding user participation in Health EDMS and compliance with Health EDMS’s warning message.
Our systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 method because it has clear, structured, transparent, and complete reporting of systematic reviews [
This paper is organized into 5 sections. Section 1 describes the research background and explains the key concepts, and the research methodology is discussed in Section 2. Next, the results and discussion of this study are elaborated in Sections 3 and 4. The final section concludes this study.
Before discussing emergencies and disasters, it is important to understand the definition and classification of hazards. A hazard is a process, phenomenon, or human activity that can harm people's lives and health, damage property, disrupt social and economic activities, and damage the environment [
Hazards have the potential to create any scale of emergency or disaster. Emergency and disaster, at first glance, have a similar meaning, but there are fundamental differences between the two. An emergency can be defined as a severe disruption to the functioning of a community or society, causing human, material, economic, or environmental impacts, which can be overcome by the internal resources of the community and society itself [
To answer the research question, we need to understand the general concept of EDM. As previously mentioned, the terms “emergency management” and “disaster management” are often used interchangeably because they have considerable overlap [
The EDM cycle. EDM: emergency and disaster management.
The second phase, preparedness, aims to prepare the community to respond to a hazard [
Each activity shown in
This research focuses on community stakeholders affected by health hazards. Individuals can contribute to community-level surveillance, household preparedness, first-aid training, and emergency response [
Various studies have used different terms to describe the EDMS features for each of the 4 EDM phases. The term “emergency management system” is used by the United Nations [
Based on
System features and key stakeholders of an EDMSa for the mitigation (MT) activity.
Activity code and system feature | Key stakeholders | |||||
|
|
Cob | Gc | Hd | Oe | Rof |
|
||||||
|
MT1.1. Manage document repositories [ |
N/Ag | Ah | Ci | N/A | N/A |
|
MT1.2. Create maps [ |
N/A | A | C | N/A | N/A |
|
MT1.3. Disseminate information to increase public awareness [ |
Ij | A | I | I | N/A |
|
||||||
|
MT2.1. Identify possible hazards [ |
I | A | C | I | N/A |
|
MT2.2. Assess vulnerability and impact of the hazard [ |
I | A | C | I | N/A |
|
MT2.3. Assess local capacity capability [ |
N/A | A | C | I | N/A |
|
||||||
|
MT3.1. Develop mitigation strategy and policy [ |
I | A | C | I | N/A |
|
MT3.2. Manage data on zonation, land use, and hazard-resistant infrastructure [ |
I | A | N/A | I | N/A |
|
||||||
|
MT4.1. Monitor and report the potential hazard [ |
I | A | Rk | I | N/A |
|
MT4.2. Manage vaccination system data [ |
I | A | R | I | N/A |
aEDMS: emergency and disaster management system.
bCo: community.
cG: governments.
dH: health institutions.
eO: other groups.
fRo: regional and international organizations.
gN/A: not applicable.
hA: accountable.
iC: consulted.
jI: informed.
kR: responsible.
System features and key stakeholders of an EDMSa for the preparedness (PR) activity.
Activity code and system feature | Key stakeholders | |||||
|
|
Cob | Gc | Hd | Oe | Rof |
|
||||||
|
PR1.1. Manage a hazard database [ |
N/Ag | Ah | Ii | I | I |
|
PR1.2. Manage available resources and personnel database [ |
N/A | A | I | I | I |
|
||||||
|
PR2.1. Create an emergency and disaster plan [ |
N/A | A | Cj | N/A | C |
|
PR2.2. Manage multiorganizational partnership and communication [ |
N/A | A | Rk | R | R |
|
PR2.3. Manage financial resources [ |
N/A | A | N/A | N/A | N/A |
|
||||||
|
PR3.1. Manage personnel recruitment and allocation [ |
N/A | A | I | I | I |
|
PR3.2. Manage training and scenario data [ |
N/A | A | I | I | I |
|
||||||
|
PR4.1. Manage supplies and equipment procurement and storage [ |
N/A | A | N/A | N/A | N/A |
|
||||||
|
PR5.1. Monitor, detect, and report the potential hazard [ |
N/A | A | C | I | C |
|
PR5.2. Analyze spatial data [ |
N/A | A | C | N/A | C |
|
PR5.3. Disseminate an early warning [ |
I | A | A | I | A |
aEDMS: emergency and disaster management system.
bCo: community.
cG: governments.
dH: health institutions.
eO: other groups.
fRo: regional and international organizations.
gN/A: not applicable.
hA: accountable.
iI: informed.
jC: consulted.
kR: responsible.
System features and key stakeholders of an EDMSa for the response (RS) activity.
Activity code and system feature | Key stakeholders | |||||
|
|
Cob | Gc | Hd | Oe | Rof |
|
||||||
|
RS1.1. Manage shelter and response organization data [ |
Ig | Ah | Ri | R | I |
|
RS1.2. Manage missing person and victim data [ |
R | A | R | R | I |
|
RS1.3. Track personnel location [ |
I | A | R | R | I |
|
||||||
|
RS2.1. Monitor and report the ongoing hazard [ |
I | A | R | I | Cj |
|
RS2.2. Disseminate the warning and notification [ |
I | A | I | I | I |
|
RS2.3. Share timely, credible, and actionable information to the public through various channels (eg, mass media, social media) [ |
I | A | I | I | I |
|
||||||
|
RS3.1. Manage evacuation data [ |
I | A | R | R | I |
|
RS3.2. Manage request data to deliver assistance and aid supplies for threatened populations and field respondents [ |
R | A | R | R | I |
|
||||||
|
RS4.1. Manage tracing data [ |
R | A | R | I | C |
|
RS4.2. Manage first-aid and medical treatment data [ |
R | A | R | I | C |
|
RS4.3. Manage laboratory test data [ |
R | A | R | I | C |
|
||||||
|
RS5.1. Manage situational reports related to infrastructure damage [ |
R | A | N/Ak | R | I |
aEDMS: emergency and disaster management system.
bCo: community.
cG: governments.
dH: health institutions.
eO: other groups.
fRo: regional and international organizations.
gI: informed.
hA: accountable.
iR: responsible.
jC: consulted.
kN/A: not applicable.
System features and key stakeholders of an EDMSa for the recovery (RC) activity.
Activity code and system feature | Key stakeholders | |||||
|
|
Cob | Gc | Hd | Oe | Rof |
|
||||||
|
RC1.1. Collect data on the hazardous event and impacted population [ |
N/Ag | Ah | Ci | C | C |
|
RC1.2. Create reports related to the responses [ |
Ij | A | I | I | I |
|
||||||
|
RC2.1. Assess infrastructure and lifeline service damage [ |
N/A | A | N/A | I | I |
|
RC2.2. Manage data of infrastructure and lifeline services rebuilding [ |
I | A | N/A | I | C |
|
||||||
|
RC3.1. Manage continuous tracing or mapping of case data [ |
Rk | A | R | I | C |
|
RC3.2. Manage continuous medical treatment and mental health care [ |
R | A | R | I | C |
|
RC3.3. Manage continuous laboratory testing data [ |
R | A | R | I | C |
|
||||||
|
RC4.1. Manage continuous monitoring and reporting of hazards [ |
I | A | R | I | C |
|
||||||
|
RC5.1. Manage lessons learned data [ |
I | A | C | I | C |
aEDMS: emergency and disaster management system.
bCo: community.
cG: governments.
dH: health institutions.
eO: other groups.
fRo: regional and international organizations.
gN/A: not applicable.
hA: accountable.
iC: consulted.
jI: informed.
kR: responsible.
All the features analyzed in the previous section are used in a general EDMS dealing with all types of emergencies and disasters. To find out how these features have been used to address health-related disasters, we investigated their application to Health EDMS, an EDMS that is specifically used to respond to and cope with hazardous events that threaten public health. During the COVID-19 pandemic, Health EDMS was used by multiple countries to assist in contact tracing. Contact tracing is a control measure to prevent further disease transmission [
In this study, the discussion of Health EDMS will focus on a CTA because a CTA is a clear example of a technology application that deals with health emergencies and disasters. As a self-administered warning system, CTAs have been widely used in more than 50 countries [
There are 6 CTAs reviewed in
CTAa features.
EDMSb feature code | PathCheck SafePlace (United States) | Aarogya Setu (India) | NHSc COVID19 (United Kingdom) | TousAntiCovid (France) | Trace Together (Singapore) | SwissCovid (Switzerland) | |||||||
|
|||||||||||||
|
RS1.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RS1.2 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RS1.3 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RS2.1 | Yes | Yes | Yes | Yes | Yes | No | ||||||
|
RS2.2 | Yes | Yes | Yes | Unknown | Yes | Unknown | ||||||
|
RS2.3 | Yes | Yes | Yes | Yes | Yes | No | ||||||
|
RS3.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RS3.2 | Yes | Yes | No | Unknown | No | Unknown | ||||||
|
RS4.1 | Yes | Yes | Yes | Yes | Yes | Yes | ||||||
|
RS4.2 | Yes | Yes | Yes | Unknown | No | Unknown | ||||||
|
RS4.3 | Yes | Yes | Yes | No | Yes | No | ||||||
|
RS5.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
|||||||||||||
|
RC1.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RC1.2 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RC2.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RC2.2 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
|
RC3.1 | Yes | Yes | Yes | Yes | Yes | Yes | ||||||
|
RC3.2 | Yes | Yes | Yes | Unknown | No | Unknown | ||||||
|
RC3.3 | Yes | Yes | Yes | No | Yes | No | ||||||
|
RC4.1 | Yes | Yes | Yes | Yes | Yes | No | ||||||
|
RC5.1 | Unknown | Unknown | Unknown | Unknown | Unknown | Unknown | ||||||
Total “yes,” n | 11 | 11 | 10 | 5 | 8 | 2 |
aCTA: contact-tracing application.
bEDMS: emergency and disaster management system.
cNHS: National Health Service.
Based on
Medical care provision (RS4) is 1 of the priority features in CTAs. CTAs provide automatic contact-tracing tools integrated with location mapping through GPS. Aarogya Setu integrates these tools with an electronic pass (e-pass) in transportation and public places [
In the previous section, there were 27 EDMS features that involved the user community. Meanwhile,
Compliance refers to the agreement with the expectations stated in the rules, standards, proposals, requests, orders, or suggestions [
Research on compliance has been investigated in various fields, and theories regarding compliance also come from multiple domains, such as psychology, criminology, health, management, and organization [
Health EDMS differs from other ISs as it is used in life-critical and time-sensitive situations, often with limited resources. Immediate compliance with the health notifications and warnings is essential to save lives [
A systematic literature review is a secondary study conducted to identify, evaluate, and interpret all available research relevant to a particular research question, topic area, or phenomenon of interest [
The search was conducted using the online databases Scopus, ScienceDirect, ProQuest, IEEE, and PubMed. The keywords or search strings used to search the papers were (“emergency” OR “disaster” OR “response” OR “notification” OR “warning” OR “alert” OR “tracing”) AND (“system” OR “apps” OR “application”) AND (“compliance”). The search was conducted for journal papers published between January 2000 and February 2022.
The inclusion criteria were the review guidelines for study selection, as displayed in
Inclusion and exclusion criteria.
|
Inclusion criteria | Exclusion criteria |
Paper type | Journal paper | Other than journal paper (eg, conference paper, book, editorial) |
Language | English | Other than English |
Publication date | January 2000-February 2022 | Before January 2000 and after February 2022 |
Topic | User compliance with Health EDMSa | Compliance with health behavior without the use of the system or application, organization compliance, and technical design of Health EDMS |
aEDMS: emergency and disaster management system.
The study selection was carried out as follows:
Step 1: The keyword or search string was searched in the aforementioned online databases. We limited the search to the abstract, title, or keyword fields. Duplicate records were removed.
Step 2: The title and abstract of the identified papers were reviewed based on the inclusion criteria. Papers that did not meet inclusion criteria were removed.
Step 3: The remaining papers were read in full to determine whether they met the inclusion criteria.
The data extraction process aimed to identify relevant information from the included studies that pertained to our research question. This process included producing a Microsoft Excel data sheet consisting of key aspects related to the research aim. The following data were extracted from each publication: title, author(s), year of publication, name of the journal, country, topic, research question or objective, factor(s), method, recommendation, finding, and research gap. Each paper's full text was read, and the research data were entered into the Excel sheet. Once the extraction was completed, the Excel sheet was reviewed, and then the findings of the studies were analyzed to answer the research question. The results of the review are discussed in the next section.
The selected electronic databases were searched following the previously explained search strategy. In total, 618 papers were retrieved. Next, duplicate papers were removed, resulting in 573 (92.7%) papers. The papers' titles and abstracts were reviewed by applying the inclusion criteria. After removing the papers that did not fulfill the inclusion criteria, we were left with 95 (16.6%) papers. Next, the papers' full texts were read to ensure they covered the predefined scope. This step resulted in 14 (14.7%) selected papers. A summary table of the characteristics of the included studies is provided in
PRISMA flow diagram. EDMS: emergency and disaster management system; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
The included papers showed that Health EDMS research was conducted in the United States (n=5, 35.7%), the United Kingdom (n=2, 14.3%), China (n=2, 14.3%), Switzerland (n=1, 7.1%), France (n=1, 7.1%), Germany (n=1, 7.1%), South Korea (n=1, 7.1%), and Israel (n=1, 7.1%).
Distribution of papers based on country.
From 2004 to 2022, 14 studies on user compliance with Health EDMS were found. There were relatively few studies before 2021. Research on Health EDMS compliance increased rapidly in 2021 (there were 7, 50.0%, studies) due to the COVID-19 pandemic. The COVID-19 pandemic has led to many studies on user compliance with CTAs, EDMSs for handling health-related emergencies and disasters.
Related to the sources of publications, 2 (14.3%) papers were published in the
The theories used in Health EDMS compliance research (
Theoretical lenses to investigate compliance with Health EDMSa.
Theory | Papers (N=14), n (%) | Reference(s) |
PADMb | 3 (21.4) | [ |
Etzioni’s compliance theory | 2 (14.3) | [ |
HBMc | 2 (14.3) | [ |
PMTd | 2 (14.3) | [ |
SARFe | 1 (7.1) | [ |
TAM2f | 1 (7.1) | [ |
TPBg | 1 (7.1) | [ |
aEDMS: emergency and disaster management system.
bPADM: protective action decision model.
cHBM: Health Belief Model.
dPMT: protection motivation theory.
eSARF: social amplification of risk framework.
fTAM2: extension of the technology acceptance model.
gTPB: theory of planned behavior.
The PADM is a framework for managing the societal response to environmental hazards [
Furthermore, the pre–decision-making process generates perceptions of the environmental threats, alternative protective actions, and relevant stakeholders (government, other groups, and community) [
Stakeholder perceptions and protective action perceptions have been shown to influence compliance with warnings during the avian influenza A (H7N9) outbreak [
Etzioni's compliance theory states that there are 2 parties to a compliance relationship: an actor who has power and another actor who responds to the power (subordinated actor) [
The subordinated actor can have 3 kinds of involvement: alienative, calculative, and moral [
Etzioni's compliance theory has been adapted to campus emergencies [
The HBM is a conceptual model for understanding why individuals do or do not perform various actions related to health behavior [
The HBM has been used to analyze individual compliance with warnings to take recommended protective actions during the H7N9 [
In a hazardous event, the increased fear of the individual also increases their intention to take action [
In Health EDMS compliance studies, the PMT has been used in campus emergency notification systems [
SARF describes a dynamic process for understanding how risk is perceived when communicated to the community [
Amplification occurs in 2 stages: when transferring information about the risk and when the community responds to the information [
SARF has been used to investigate compliance behavior in China during the COVID-19 pandemic [
TAM2 extends the original TAM by including additional key determinants of perceived usefulness and usage intention constructs: social influence and cognitive instrumental process [
Research on CTAs in the United Kingdom found that most TAM2 constructs significantly affect user behavior to download the application and comply with notifications [
The TPB was first introduced as a development of the theory of reasoned action (TRA) and has been most widely adopted in the research on motivations for human behavior. The TPB explains that behavior is influenced by intention and intention is determined by 3 types of beliefs: attitudes, subjective norms, and perceived behavioral control [
The TPB is 1 of the most influential theories in disaster and emergency preparedness planning. The TPB has been used to analyze the factors that affect rapid compliance with emergency notifications in 7 emergency scenarios in a campus: robbery, active shooter, building fire, hazardous material, riot/violent protest, air quality advisory, and health advisory [
This section summarizes the factors affecting compliance with Health EDMS from the selected papers. People can comply immediately or verify and then comply after receiving a warning [
In addition, individual characteristics and social influence play a significant role in driving compliance [
Sorensen [
From the literature reviewed, our study identified 14 individual, 10 technological, and 4 social factors that influenced users' compliance with Health EDMS. Most of them were derived from the previously discussed behavior theories, while others were added by the researchers without referring to any particular theory. From individual factors, perceived risk and response efficacy are the most widely used predictors of compliance. From technological factors, the most frequently used factors are warning message characteristics. Moreover, subjective norms and stakeholder perception are the most researched social factors. A summary table of the individual, technological, and social factors influencing users' compliance with Health EDMS is provided in
EDM is 1 of the most challenging management tasks because decisions must be made in a short time, under a rapidly changing environment, with unique situations for each incident, and involve high operational costs [
This study mapped the EDMS features into CTA functionalities. Contact-tracing strategies have been implemented worldwide, with varying degrees of success [
Rapid compliance with warnings is vital to save lives. The features of Health EDMS can provide information and warnings that increase the sense of urgency and become a source of verification to improve compliance levels [
Proposed research framework. EDMS: emergency and disaster management system.
In the previous explanation (
Technological factors cover all aspects of information and technical quality. System notifications and warnings can change how individuals think and feel about threats and risks. Health EDMS must provide sufficient information to users about their possible risk exposure and the actions they should take [
In addition to technological and individual factors, the use and design of Health EDMS are influenced by social factors. Opinions from influential people, such as family, friends, or coworkers, encourage individuals to use Health EDMS [
The proposed research framework was developed based on our analysis of theories and corresponding factors affecting user compliance with Health EDMS in the existing literature. Future research can empirically examine the framework with a specific health EDMS. Collaborations with CTA providers are needed to examine actual compliance. In addition to the proposed research framework, we proposed 2 research topics on Health EDMS that require further investigation. First, Health EDMS has only implemented features to handle the response and recovery phases of EDM. The mitigation and preparedness phases of EDM are not supported by Health EDMS. Health EDMS should not only be used to respond to and cope with disasters but also be used to prevent and prepare for health-related hazards. Nevertheless, unlike natural disasters or human-induced disasters, such as forest fires, the characteristics of future health-related hazards are unknown. How to design features for mitigation and preparedness of future health-related hazards is an interesting research topic. Second, considering that a CTA is a relatively new IS implemented for a specific pandemic case, the effectiveness of CTA features in increasing user compliance with warnings has not been widely analyzed. Instead of examining a CTA as a whole, future research should investigate each feature of a CTA in depth toward increasing user compliance.
Health EDMS has been implemented to cope with health-related hazards. However, the compliance rate with Health EDMS remains low [
Hazard classification by WHO [
PRISMA 2020 checklist. PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
Studies included in the final review.
Factors affecting user compliance with Health EDMS. EDMS: emergency and disaster management system.
contact-tracing application
disaster management system
emergency and disaster management
emergency and disaster management system
emergency management system
avian influenza A
Health Belief Model
information system
nongovernment organization
protective action decision model
protection motivation theory
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
responsible, accountable, consulted, and informed
social amplification of risk framework
extension of the technology acceptance model
theory of planned behavior
World Health Organization
This work is supported by the Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT) grant from the Ministry of Education, Culture, Research, and Technology, Republic of Indonesia (contract number: NKB-905/UN2.RST/HKP.05.00/2022).
All data analyzed during this study are included in this published paper and its Multimedia Appendices.
None declared.