Tuberculosis (TB) infections remain a global health burden with a high incidence rate in South-East Asia, including Indonesia. TB control strategy is founded on early case detection and complete treatment to minimize transmission and prevent the emergence of drug resistance. However, many patients face challenges to comply with daily medication, causing many to adhere inconsistently or stop prematurely. Technological solutions could enhance adherence to treatment and support national screening and follow-up policies. These include telephone video communication, enabling health professionals to watch patients take their medication, address patients' concerns, and provide advice and support. This manuscript describes the outcome of a qualitative pilot study, based on a series of focus group discussions to assess the knowledge, attitudes, and behaviors, on the potential utilization of mobile technology for health purposes with a particular focus on TB treatment follow-up. The findings illustrate that general knowledge of mobile health technologies, of their legal framework of operations, and of their exact potential within the healthcare system is incomplete or poor. The novel findings are as follows: (a) the willingness of participants to learn about these technologies, (b) the open and welcoming attitude toward receiving such information even within frontline community settings, and (c) the willingness to back a government-supported, healthcare-driven set of such initiatives. Potential implementation barriers have also been highlighted. This study is an important first step toward understanding the attitudes and behaviors on utilizing mobile health technology for TB in Indonesia. Mycobacterium tuberculosis with millions of new infections reported globally and a significant number of deaths. In 2014, 1.4 million people globally died from TB, reducing slightly to 1.2 million in 2018; with an estimated 10 million new infections reported per year over the last few years (Tuberculosis (TB) is one of the infectious diseases caused by ew years , while mMost TB patients are curable by a course of treatment, which is globally affordable, although this treatment takes a minimum of 6 months to complete and 2 years or longer for multidrug-resistant tuberculosis (MDR-TB) . The curIn Indonesia, in particular, the incidence, and by consequence, the human and financial cost of TB infections remains extremely high . Some ofPsychosocial support for Indonesian TB patients is a significant component in the management of TB drug side effects. Drugs supervisors (Pengawas Menelan Obat) are the people tasked to provide education and encouragement to the patients to maintain their treatment, organizing, when possible, individual meetings, community meetings, as well as support group meetings. The drug supervisors must be people who are already trained and accepted by the TB patients . The neeOne of these novel technological solutions to TB treatment monitoring is telephone video communication, enabling health professionals to watch patients take their medication, address patients' concerns, and provide advice and support –19. VideThis manuscript describes the outcome of a qualitative pilot study, based on a series of focus groups, to assess the knowledge—attitudes toward and behaviors on the potential utilization—of mobile technology for health purposes with a particular focus on TB treatment follow-up. Similar studies have taken place previously in other countries, though the global picture on the subject and, in particular, in the areas addressed by the current manuscript, remains incomplete –23. The This is the first time to our knowledge that this topic is discussed in this manner in Indonesia—outside of a narrow academic or political context and with a direct link to potential clinical utility, so that it can provide pilot data for the eventual development of a community-engaged intervention. Furthermore, the focus groups aimed to identify locally relevant priority areas where the participants felt that the implementation of mobile health technology would have the highest impact and reduce the burden of disease in the community.A community-based participatory research (CBPR) team comprising of active academic researchers in public health from the local university  and the INDOHUN network with projects active in community one-health engagement  sought to gain insight on person knowledge, attitudes, and behaviors related to mobile-technology utilization for TB treatment monitoring and follow-up, by conducting a qualitative research study. The UGM Institutional Review Board approved this study. The team jointly designed the study and selected a qualitative research approach using focus groups to address the specific aims. The CBPR team developed a focus group moderator's guide with semistructured questions related to the use of mobile health technology  using bilingual, bicultural moderators with participants from local communities from April to October 2018. Several study participants had low levels of English proficiency. To ensure that participants understood the aims and purpose of the study, a short description was provided as introduction in Indonesian. The semistructured questions were stated in both English and Indonesian, while most of the discussion took place in Indonesian. The participants received a light meal for their time. The structure of the focus group was repeated over the different events; it included two short keynote presentations providing (i) the definitions of mobile health and a few short examples of potential public health use from other resource-restricted settings globally and (ii) the framework for the regulation and implementation of mobile health solutions within Indonesia. The aim of these short presentations was to provide a common starting point, as well as to delineate the area of interest across the different focus groups.Prior to starting the focus group discussions, facilitators (a) introduced themselves, (b) outlined the structure of the focus group, (c) instructed in the importance of confidentiality, and (d) collected selected sociodemographic information  through a brief survey.Focus groups facilitated in Indonesian were transcribed verbatim and translated into English by the UGM and INDOHUN teams. Data were de-identified and unique IDs given to each participant and moderator. Participants were asked general questions pertaining to beliefs of health, which progressed to the specific list of questions  leading Members from the research team independently conducted an initial review and coded transcripts. Preliminary thematic groups were generated and were linked to interview texts using traditional content analysis. Emerging themes were discussed and presented at team meetings. During these meetings, discordant codes were discussed until consensus was reached.There are advantages and challenges in conducting qualitative research via focus groups. For example, focus groups, not individual interviews, were chosen as the preferred method because data are obtained from the communication between participants, as they share experiences and comment on different perspectives. This would be suppressed during a more formal interview setting. Also, sometimes, participants are more open when less inhibited members explore difficult topics and more open in a group format . The floUncertainties or disagreements were resolved by consensus discussion among the moderators and participants during the focus group. The identified themes are expected to be presented at an annual meeting of public health and research stakeholders by the INDOHUN colleagues (including some of the focus group participants) to confirm that interpretation of results was consistent with the intended meaning.The CBPR team recruited 46 participants with a slight majority identifying as female . Sixteen participants were frontline clinical staff from primary healthcare centers ; 11 participants were academic researchers in public health ; 12 were public health practitioners , and 7 were ex-TB patients who have completed their respective treatments and are being followed-up actively  . The FGsThree major themes emerged from the analysis of the data: (a) the increasing knowledge at all levels of healthcare activity in terms of the potential of mobile-enabled health technologies; (b) the structural and societal barriers associated with implementing potential mobile-based solutions; and (c) the need for government-driven, community-engaged implementations complemented by educational initiatives. There were no differences noted between communities or by gender, thus the results are consistent for the FGs.Regarding overall knowledge, most FG participants agreed that there is a gradual implementation of mobile health technology in Indonesia through several applications known to them, which are approved by the Data Centre and Information Department of the Ministry of Health . Such examples include the Integrated Referral Information System  used in tertiary referral hospitals, the Integrated Nutrition Information System  used in primary healthcare centers (Puskesmas), the Integrated Emergency Response System  used by the general public. Interestingly, while the professionals in the FGs were familiar at a minimum with the names of these systems and their basic aims, the patient FG was not fully aware of all of these systems or of their functions, though they were aware that some such systems exist. Specifically, both the patient and frontline staff FGs mentioned the current extensive use of automated messaging services and Whatsapp-based messaging as blanket reminder services for the adherence to the TB treatment between doctors' visits.There was an overall positive attitude toward potential mobile health implementations. In particular, it was clear, especially by public health practitioners, that mobile health technology is considered vital in providing different solutions potentially to be implemented in almost every sector in Indonesian healthcare, from the general public, to frontline staff needs. However, from the outset of the discussions, several problems were identified relating to such a deployment. These can be summarized as lack of a planned integration between initiatives already taking place in different sectors. Therefore, it was considered critical that as part of the future deployment of mobile health technologies, the plans for their integration to existing healthcare functions (and complementarity with existing ones) should become a critical deciding factor.Nomenclature and Health Literacy should also be mentioned here as a subtheme. From the FG discussions, participants mentioned that they lacked awareness of the scientific terms associated with mobile health. This lack of awareness hampers the understanding of the full potential of using such technologies and can create inconsistencies in terms of the expectations and influence a distant or less-less welcoming behavior toward mobile health. Across the different FGs, it was advised that if full-scale adoption by the public and the wider healthcare sector in Indonesia is the eventual aim, then the descriptive terms should exist in very simple language (in Bahasa Indonesia), accompanied by a number of explanatory pictures/depictions.Assessing the knowledge in terms of structural barriers, the lack of a specific legal framework was mentioned by healthcare professionals in the FGs. In Indonesia there exists a basic regulation and policies related to the application of technology . Nevertheless, the latter law provisions do not specifically regulate the implementation of Mobile Health Technology. The Yogyakarta region specifically serves as a provincial model in Indonesia for community-oriented services utilizing communication technologies . This might explain the heightened sense and general consensus observed in healthcare professionals, for the need of developing a legal framework to specifically address and regulate the implementation of mobile health technologies.There was a general concern expressed as many FG participants spoke about several barriers to accessing healthcare. Such barriers contribute toward a more cautious attitude when it comes to the potential adoption on mobile health technology. For example, the language barrier was mentioned often, and in quite a similar manner, across the different groups, as language barriers can compromise the patient navigation. Participants mentioned they need someone who understands both the medical and technical languages and is able to translate the information “speak[ing] the dialect of the same community,” as frontline staff added. This allows the translation of information effectively from English into Indonesian and then into local, regional dialect(s). Numerous participants mentioned that the drugs supervisors (Pengawas Menelan Obat) might fulfill this role within the local context. Another possible barrier is the lack of confidence in western medical approaches, which needs to be taken into account when providing information about mobile health technologies originating from outside of Indonesia.One constant subtheme across the different groups was the notion of “workload creep” as a barrier to eventual adoption of such technologies in the field. Participants felt people would tend to emphasize the potential benefit of mobile health technologies, without balancing appropriately potential pressures elsewhere in the system . For example, some participants mentioned that even when a video directly observed therapy for TB is implemented, while the potential patient benefits are clear, the potential workload implications on frontline healthcare staff are yet to be defined.FG participants were also concerned about practical aspects: for example, the cost in accessing enough data quotes for video-based applications, and second, the quality of existing connections on mobile networks. While most of Indonesia is covered by mobile networks, and most Indonesians are owners of mobile phones, the quality of these networks is not uniform across all areas depending on population density and geography, nor is access to newer smartphones equally distributed in the population, allowing for video-based applications, which will affect the end-user behavior during a potential nationwide implementation of such initiatives, especially in remote and poorer areas of the country.FG participants expressed a wide range of responses and opinions regarding the potential models of introduction and implementation of such mobile health technologies. The overall knowledge consensus was that an initiative, such as a potential one relating to TB treatment monitoring and follow-up, should be nationwide and supported by the central government, in line with other such recent initiatives .Several examples participants mentioned were of implementation models driven by primary or tertiary healthcare structures. In the particular case of existing TB pathways in Indonesia, the current national healthcare system expects most TB patients to be treated by primary healthcare centers, with referrals to specialist tertiary centers be limited only to MDR-TB patients. Navigating through this tiered system is already challenging for individuals who are of the lowest income and/or educational levels, often resulting to a delay or interruption of patients' treatments. Additionally, there is limited data linkage/transfer between the different healthcare tiers; thus, any mobile-driven technology would need to bridge and converse with the different healthcare tiers, as well as be resilient to limitations in terms of healthcare data availability.Therefore, in some FGs, the favorable position was that mobile healthcare technologies focusing on TB should be supported by the central government/public health departments through the central framework and overseeing mechanisms, and be driven in terms of implementation by the primary healthcare centers. This allows a close support of the initiative by drugs supervisors and an easy/ier information flow to patients. Across each FG, participants mentioned the importance of involving influential community leaders like civic leaders in helping to provide awareness of such a potential initiative.The potential of such mobile health technologies for a number of overlapping healthcare aspects  was currently not promoted in public health efforts. A number of FG participants stated that there is a paucity of pilot studies to support the introduction of such technologies. A participant in a frontline medical unit stated she did not know anything about mobile-driven technologies until she did her final year of training. When asked, “If there is an official approval process for allowing the introduction of such technologies?,” several members mentioned they did not know what such a process might be and needed more information. For instance, one participant mentioned, “[the] need for specific regulation to allow potential implementation.” There was also a lack of awareness of the breadth of such mobile-driven health technologies. One participant maintained that “there are different types of these applications” but “didn't have access to information about the different kinds.” However, participants were aware that they are not utilized for clinical purposes in Indonesia; some  have used applications for personal fitness/well-being requirements, and a very low number  for managerial purposes within their healthcare organization.Continuing with the overall positive attitude toward mobile health, participants in all FGs expressed interest in learning more about mobile health technologies. For example, the need to learn about the implementation in other countries/communities of similar societal challenges, and not from more advanced nations, which is applicable only to upper-class levels of society and not the majority of the Indonesian population. Others discussed that partnerships for health education and promotion were most appropriate with academic institutions and community-based organizations, to pilot test such implementation attempts and provide the first evidence from within Indonesia before embarking on a nationwide initiative. Participants indicated the importance of having someone explain the nature of mobile health technologies (as was provided during the opening of the FG sessions). Last, several participants felt that it is important for individuals to start discussing such technologies within academic institutions so as to increase awareness of the potential to eventually save lives. More importantly, participants recognized the need for Indonesia to move forward with the rest of the world in this developing healthcare field.To our knowledge, this is the first qualitative research study examining knowledge, attitudes, and behaviors toward mobile health technologies in Indonesia and, in particular, for the treatment and follow-up of TB patients. Findings from this pilot study provide insight on areas of research focus. Having a moderator team consisting of members with demonstrated community-based engagements, from the INDOHUN network, helped to increase trust and foster an understanding of shared community values. Information from this study provides evidence to support the creation, testing, and eventual development of professionally and culturally appropriate strategies in Indonesia to introduce mobile health technologies, eventually for a wider public use.The findings illustrate that general knowledge of mobile health technologies, of their legal framework of operations, and of their exact potential within the healthcare system can be characterized as incomplete or poor. There is general knowledge that such technologies exist, but not a detailed operational exposure to them and their potential applications. There was a general positive attitude throughout the FGs toward mobile health technologies and their potential applications, especially as the benefits to the population and potential reach and immediacy of applying this technology was evident to participants from the outset. At the same time, there was also concern on the number of challenges that lay ahead for such technologies to be applied on a larger scale or even nationwide. These challenges can be at the individual level , to the local level  to the national level . Last, the behavior toward the mobile health technologies can be characterized as cautious and distant overall. There have been previous successful as well as unsuccessful attempts in Indonesia in rolling out nationwide healthcare initiatives, and as such, a general cautious behavior has ensued. However, this does not seem to be specific to mobile health technologies, but rather relating to the magnitude and operational complexity of such a task.The novel findings of this study were: (A) the willingness of participants to learn about these technologies, as during the FGs there were repeated questions to the moderators and other participants to provide examples and online points of reference for further investigation. (B) The open and welcoming attitude of the participants toward receiving such information even within frontline community settings. This was perhaps surprising, as frontline staff are under constant pressure and often under resourced; hence, a discussion on a potential new initiatives might have not been welcome, expected to be greeted with heightened concern. However, there is clear acceptance that the benefits of mobile health technology are likely to outweigh potential disadvantages stemming from any complexity of implementation. (C) The willingness of participants to back a government-supported, primary healthcare-driven set of such initiatives. Various barriers to the implementation, operation, and eventual adoption, were described. In other parts of the world, studies have reported poor uptake of such technologies when the communication between various sections of the healthcare system was suboptimal, as well as within different units; this was supported from the opinions shared in our study , 34.A previous work showed an agreement by healthcare providers and public health professionals that mobile health technologies can improve patient care, as this technology is perceived as able to reach most patients, when needed , 36. WhiOur results indicate that participants had some level of understanding of the various models of implementing such healthcare initiatives, based on recent nationwide campaigns within Indonesia. However, further research and education are needed to enhance the understanding of the potential barriers and facilitators before aiming to adopt such technologies widely. This was evident as several participants mentioned that access to reliable networks, data packages, and appropriate devices, would become immediate stumbling blocks in implementing such initiatives. This has been demonstrated previously in other resource-limited settings , 42.Another subtheme emerging as a barrier is language and understanding. This notion is quite consistent with previous research in low-resource settings, and geographies where multiple languages coexist , 44. WayThe limitation of our study is that it might not be generalizable to the populations of South-East Asia, indeed, even Indonesia itself. Recruitment for the focus groups was limited by the sample size, as this was a pilot study with insufficient resources to conduct additional focus group sessions to allow for a more comprehensive comparison between groups . Moreover, the focus group participants were self-selected and may not represent the majority of the population or the majority of opinion within their respective population groups. Another limitation is the need for having these observations validated through their presentation to the stakeholders as well as to the Indonesian healthcare community to ensure that the presented views are, indeed, widely representative. Furthermore, we acknowledge that the academic medical centers included in this study do not represent all types of facilities in which people are hospitalized and that any potential implementation might differ according to local needs and requirements. Nonetheless, we acknowledge the early nature of our findings in this rapidly evolving field. Finally, despite our efforts, our findings may not be exhaustive; they more than likely underscore considerable challenges and barriers to implementation and adoption as perceived by stakeholder participants.The entire issue of mobile health technologies, especially for remote patient monitoring, is attracting a great deal of attention worldwide because it presents a unique way to provide information and resources to healthcare professionals and patients alike, and may be a promising tool to support healthcare . The finThe themes expressed through the FGs provide a common ground, making it possible to better understand the challenges and opportunities related to mobile health technology utilization. While some of the aspects to the potential adoption are similar to those identified in systematic reviews about other technological applications , this study has enabled us to identify factors that are specific to mobile health in one of the most populous nations of the world, Indonesia.Based on these early findings, our most notable recommendation is that the findings described in the current manuscript would need to be further validated by a wider participation from the existing focus group stakeholder categories and expanded, through additional focus groups with other key stakeholders . This should allow the development of a core set of understanding regarding the knowledge, attitudes, and behaviors of Indonesians toward mobile health technologies and advance safe, coordinated, and effective dialogue and implementation of such technologies for patient-centered care. Further qualitative and quantitative research should build upon these concepts, enhance the themes we identified, test design assumptions, and measure the impact on outcomes.Where authors are identified as personnel of the International Agency for Research on Cancer /WHO, the authors alone are responsible for the views expressed in this article, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/WHO.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by UGM Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.DA, ZK, and WTA contributed to study concept and design. WTA, RA, HD contributed on acquisition of data, data analysis, interpretation of data, and drafting of the manuscript. ZK, DN, WA, and AH contributed in interpretation of data, and critical revision of the manuscript and final approval of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We used latent variables and structural equation modeling to test the hypotheses derived from the 3Cs model. The findings indicate that there are some differences in the types of preventive behaviors adopted in the two countries. In Israel, higher levels of confidence predicted the adoption of avoidant behaviors and more constraints predicted engaging in fewer avoidant behaviors. In China, more constraints also contributed to the adoption of fewer avoidant behaviors, but people’s level of confidence fully mediated this result. The multi-group analysis indicated that the conceptualized model fits the Chinese and Israeli data reasonably well. The findings suggest that the 3Cs model can be generalized from getting vaccinated to adopting avoidant behaviors and that the model can be used across cultures and countries.The COVID-19 pandemic represents a massive global health crisis. The rapid transmission rate of the virus, as well as the lack of effective medications and vaccines, has posed serious challenges to controlling the spread of the disease. Dealing with this public health crisis has required major changes in people’s behavior, including the adoption of social distancing measures such as avoiding meeting with family members and friends, crowded places, and public transportation. The purpose of this study is to investigate the factors associated with the adoption of these behaviors in China and Israel. We relied on the 3Cs model that has been used to predict the adoption of a specific preventive behavior (vaccinations) with the goal of testing its applicability to other preventive behaviors such as in response to the COVID-19 pandemic. The model indicates that confidence in social institutions, complacency (fear of and assessments about the risk of becoming ill) and constraints (levels of self-efficacy and confidence in being able to engage in the behaviors) are predictors of adopting preventive behaviors. Data were collected in China and Israel through an online survey of the population ( At the end of 2019, the COVID-19 pandemic broke out initially in Wuhan, China, and expanded rapidly, creating a massive public health crisis worldwide. During our data collection period in April 2020 the World Health Organization reported over 1 million confirmed cases globally, resulting in a more than tenfold increase in less than a month  than other models with invariance constraints  and they are confident that they can engage in them (efficacy expectations) will they actually adopt them. This finding is consistent with previous research on other pandemics such as Influenza A (H1N1) in Hong Kong, In that study, trust in social institutions was not directly associated with avoidant behavior, but was more strongly associated with efficacy expectations. Thus, efforts should be made to promote more confidence in people’s ability to engage in behavioral change by enhancing their understanding of the outcomes of doing so and developing their efficacy to engage in such behavior. This suggestion highlights the communication dynamics between social institutions, especially governments, and the public. Communication strategies during a pandemic should put more emphasis on encouraging people to engage in avoidant behavior by raising their expectations about the beneficial outcomes of doing so and inspiring their efficacy expectations.Another interesting finding was that the level of confidence in the government, hospitals, and medical workers was rather close in both Israel and China. Given that the levels of trust in these three groups were similar, we can conclude that the public regards them as sharing responsibility during the pandemic. Therefore, if one party in this triumvirate loses the public’s confidence, the other two remaining parties will be adversely influenced by this loss of trust.The level of complacency in Israel and China had opposite associations with the adoption of avoidant behavior, and the absolute magnitude of the two associations was close. These divergences could be attributed to the difference in perceptions of complacency between these two groups. The Chinese participants felt they were less likely to become infected than the Israelis. However, if they were infected, they expected the impact to be more severe than the Israelis did.During the data collection period, the outbreak was gradually brought under control in China. Wuhan emerged from lockdown on April 8, 2020, indicating that the threat of infection had declined. This information might have made the Chinese participants feel that it was less likely that they would become infected. Their stronger sense about the severity of the infection might be due to the large number of deaths and infected people who were still in treatment. In contrast, in Israel, new confirmed cases surged at the end of March, but there were only 20 deaths. Given these statistics, the Israelis might have concluded that they were more likely to become infected, but doing so would not necessarily be fatal.The combination of the Chinese participants’ perceptions about their relative lack of risk of contracting the virus and the high death rate associated with the disease complicated the role of complacency in the adoption of avoidant behaviors. This positive association between complacency and engaging in avoidant behaviors was consistent with a previous study about Influenza A (H1N1) in which the relatively mild effects of the flu provided little motivation for people to change their behavior . As suchAnother important contribution of this study is our demonstration of the ability to generalize the 3Cs model to contexts other than just becoming vaccinated. Our study is the first to explore the validity of the model in other contexts, particularly with regard to preventive behavior in a pandemic. Despite the fact that the implications of complacency, confidence, and constraints are not identical with regard to being vaccinated and engaging in avoidant behaviors, the model can still provide a mechanism for understanding behavioral change. In accordance with our hypotheses, we indicated that complacency about the possible risks, confidence in social institutions, and constraints regarding expectations are associated with people’s behavior during a pandemic.Our comparative study also demonstrated the ability to generalize the 3Cs model. We used a conceptual model as a comparative framework to understand how multiple variables function differently in both countries. The Israeli and Chinese participants varied significantly in their levels of complacency, confidence, and constraints, as well as the extent of their engagement in avoidant behavior. For example, both the Israeli and Chinese participants reported significant awareness of the benefits of social distancing. However, the Chinese participants were more optimistic about the situation. They indicated that they felt less susceptible to the disease, had fewer constraints and more confidence than the Israeli participants, but regarded the virus as more serious. Therefore, they were more likely to engage in six out of the nine recommended behaviors. The only exceptions were avoiding shaking hands, crowded, airless places, and public transportation.Our findings also have several practical implications. First, they suggest that efficient public health campaigns and communications during the outbreak designed to promote the adoption of avoidant behavior must target people’s expectations, particularly with regard to the beneficial outcomes and efficacy of doing so. The goal is to reduce the public’s perceptions about the constraints on their adopting such behavior. Furthermore, these campaigns should promote confidence in social institutions, specifically, the government, hospitals and medical personnel. At the same time, the public’s level of complacency may vary throughout this dynamic situation and deserves a more detailed investigation. Last but not least, the government should work closely with the health care system to build a transparent and responsive communication to the public, to assess individual’s perception, emotional status and increase public support. In the meantime, difficulties in employment, need for daily supplies, epidemic prevention and control supplies, transportation could be the sources of public negative perception and behavior adoption. Policies concerning these issues should be implemented to ease this hardship.There are some limitations to this study. First, even though the data came from two countries dealing with COVID-19, the data were cross sectional. Our assessments of perceptions and engagement in avoidant behavior were post hoc and cross-sectional. Thus, we could not evaluate causality properly. The cross-sectional nature of these data limits our ability to draw conclusions about causal directions.Second, although there is extensive research on whether cognition precedes or follows appraisals, there is no consensus on the issue . PreviouAt the same time, reverse causality might have affected our interpretation of the perceptions associated with avoidant behavior. Engaging in such behavior might promote positive and negative changes in complacency, confidence, and constraints. Social distancing challenges people’s instincts of connecting with others . The isoIn addition, cognitive perceptions and patterns of social contact are culturally based. They are rooted in social norms of behavior, and culturally specific socialization patterns. In this research, we did not collect data about indicators of cultural values. Meanwhile, differences in lifestyle and daily routine could impact individuals’ decision-making processes during the pandemic, and therefore could change the dynamic of virus transmission. These differences roused by geographic, institutional, and social factors could complex the cross-cultural comparison research that has not been included in this study. Doing so would help us determine the interaction between cultural factors and people’s perceptions and behaviors, promoting international comparisons.Third, the study may suffer from some potential bias. The use of an online survey meant that we could reach only participants who were Internet users. These participants are more likely to receive instant information about the pandemic and may be more avid followers of the news. These factors could bias the results. Furthermore, the data were self-reports, leading to the possibility of social desirability bias resulting from pressure to conform to social expectations. Nevertheless, despite these limitations, our study benefits from the fact that we asked about the actual behaviors people had adopted, not their future plans for doing so. We were also able to validate the possibility of applying the 3Cs model to dealing with the COVID-19 pandemic and provided a cross-national comparison of our hypotheses.


Traumatic brain injury (TBI) is the main cause of mortality and severe morbidity in cyclists admitted to Dutch emergency departments (EDs). Although the use of bicycle helmets is an effective way of preventing TBI, this is uncommon in the Netherlands. An option to increase its use is through a legal enforcement. However, little is known about the cost-effectiveness of such mandatory use of helmets in the Dutch context.The current study aimed to assess the cost-effectiveness of a law that enforces helmet use to reduce TBI and TBI-related mortality.The cost-effectiveness was estimated through decision tree modelling. In this study, wearing bicycle helmets enforced by law was compared with the current situation of infrequent voluntary helmet use. The total Dutch cycling population, consisting of 13.5 million people, was included in the model. Model data and parameters were obtained from Statistics Netherlands, the National Road Traffic Database, Dutch Injury Surveillance System, and literature. Effects included were numbers of TBI, death, and disability-adjusted life years (DALY). Costs included were healthcare costs, costs of productivity losses, and helmet costs. Sensitivity analysis was performed to assess which parameter had the largest influence on the incremental cost-effectiveness ratio (ICER).The intervention would lead to an estimated reduction of 2942 cases of TBI and 46 deaths.Overall, the incremental costs per 1) death averted, 2) per TBI averted, and 3) per DALY averted were estimated at 1) € 2,002,766, 2) € 31,028 and 3) € 28,465, respectively. Most favorable were the incremental costs per DALY in the 65+ age group: € 17,775.The overall costs per DALY averted surpassed the Dutch willingness to pay threshold value of € 20,000 for cost-effectiveness of preventive interventions. However, the cost per DALY averted for the elderly was below this threshold, indicating that in this age group largest effects can be reached. If the price of a helmet would reduce by 20%, which is non-hypothetical in a situation of large-scale purchases and use of these helmets, the introduction of this regulation would result in an intervention that is almost cost-effective in all age groups. In the Netherlands, cycling is a common mode of transportation and bicycle trips account for up to 28% of all transfers made . Dutch pTraumatic brain injury (TBI) is the main cause of severe morbidity and mortality after an accident involving bicyclists. More specifically, 32% out of all hospitalized cyclists with severe injury has a head or brain injury , 4, 6. TMost survivors of this form of injury remain impaired for life. TBI has been associated with a decline in cognitive capacity, long lasting physical disability and handicap, and the development of mental illness –9. The cAbout 75% of all bicycle-related head injuries are caused by single-bicycle accidents, i.e. accidents without any motorized vehicles involved. In most cases this involves falls or collisions with an obstacle . PolindeBicycle helmets are not mandatory in the Netherlands and are generally only used by young children, mountain bikers and racing cyclist . AccordiThe cost-effectiveness of legislation that enforces the use of bicycle helmets was assessed through a decision-tree model based on parameters obtained from the literature and several databases. According to the Dutch guideline for economic evaluations, a societal perspective was used, implying that not only healthcare costs but also non-healthcare costs such as cost of lost productivity, were included .The model had a lifetime horizon and compared the cost and effects of the status quo, voluntary helmet use, with the cost and effects of the intervention, mandatory helmet use for all cyclists regardless of age.In this economic evaluation, behavioral changes as a result of the compulsory wearing of a helmet were not taken into account because conclusive evidence on such behavioral changes were not available.The model contained a cohort that consists of all Dutch cyclists that use a non-racing or non-mountain bike, i.e. users of a utility bicycle. It was assumed that users of racing and mountain bikes are also users of the utility bicycle. This type of bicycle is most common for daily use in the Netherlands and will hereafter simply be referred to as ‘bicycle‘. The total number of cyclists was retrieved from Statistics Netherlands . Data onThe intervention under analysis is a hypothetical law imposing everyone in the Netherlands to wear a helmet when riding a utility bicycle. The comparator is the current situation of only voluntary helmet use.TBI-related disease burden without a helmet law, the current situationAge specific estimates of bicycle-related TBI incidence and mortality were obtained from the Dutch Injury Surveillance System (LIS) and the mortality statistics of Statistics Netherlands Table  30, 31], 3130, 3b.Helmet useAll data used from the Dutch Injury Surveillance System, Dutch Burden of injury Model, and national mortality statistics relate specifically to users of utility bicycles in 2017. The annual probability of having TBI was calculated by dividing the incidence of TBI by the total number of cyclist within each age group . Because of the very low voluntary helmet use in the country, it was assumed that none of the cases with TBI had worn a helmet. The probability of mortality due to bicycle related TBI was calculated by dividing the mortality by the incidence of TBI within each age group.ref) + (Pref ∗OR), where Pref stands for the prevalence of TBI in the group not wearing a helmet [An estimate on bicycle helmet efficacy was obtained from a recent and comprehensive review and meta-analysis . As thisa helmet .c.TBI-related disease burden following legislationThe overall helmet-wearing rate of all injured cyclists that were registered in the Dutch Injury Surveillance System was obtained (2%). This rate was also taken as the helmet-wearing rate in the general population. Estimates on compliance to mandatory bicycle helmet use in other countries were obtained by combining data from literature. Helmet wearing rates following introduction of legislation in New Zealand, Canada, the United States, and Australia were used , 36–39. Probability of having TBI for helmet wearers was calculated by multiplying the baseline probability of acquiring TBI as a bicyclist with the relative risk (RR) of TBI for helmet wearers.Incidence of TBI for helmet wearers was obtained by multiplying the projected helmet-wearing rate with the total number of cyclists for a specific age group. This group of helmet wearers was then multiplied with the probability of having TBI for helmet wearers.Incidence of TBI for non-helmet wearers was obtained by multiplying the projected group of non-helmet wearers with the probability of having TBI for non-helmet wearers.Mortality was calculated by multiplying the bicycle related TBI incidence with the probability of mortality due to bicycle related TBI.YLD was calculated by multiplying the YLD in the situation without a helmet law with the ratio of the incidence of TBI in the situation with the helmet law to the incidence of TBI in the situation without the helmet law.YLL was calculated by multiplying the YLL in the situation without a helmet law with the ratio of the mortality in the situation with the helmet law to the mortality in the situation without mandatory helmet use.Calculations were as follows:Healthcare costsThe types of costs that were included in the model were healthcare costs, costs due to lost productivity for both people that survived TBI and for people that died from TBI, and the annual cost of purchasing helmets. All costs were expressed in 2017 euros.b.Productivity lossesTreatment costs of bicycle related TBI were obtained from the Dutch Burden of Injury Model and included general practitioner care, ambulance transport, hospital, physiotherapy, home care and domestic help, nursing homes, and rehabilitation care. These costs occurred within the first year after the injury and were assumed an acceptable representation of the total treatment costs. No data are available for the health care costs after year 1. Total treatment costs for survivors under the helmet law condition were calculated by multiplying the projected incidence of TBI with the mean treatment costs per TBI.c.Helmet costsThe loss of productivity of people that survived TBI were also obtained from the Dutch Burden of Injury Model and were calculated using the friction-cost method, as advised by the Dutch guidelines for health economic evaluation . Only peThe mean bicycle helmet price was estimated in the same way as was done in German cost-benefit-research . The coswww.amazon.de was also used. The mean of these two prices was taken and corrected for Dutch price levels [The mean recommended retail price for the twelve best-selling helmets on e levels . Everyone levels . Yearly Incremental cost-utility ratios (ICERs) were estimated by dividing the difference in costs between the current situation and the implementation of mandatory bicycle helmet use, by the difference in effects between both scenarios. This means that ICERs were estimated for respectively bicycle related TBI, death, and DALYs averted.One way sensitivity analysis was performed to assess the uncertainty surrounding the following model parameters: incidence of TBI, mortality, YLL, disability adjustments in YLD, number of years lived with a disability, costs of healthcare resources use, costs due to productivity loss, annual helmet costs, current helmet wearing percentage, projected future helmet wearing percentage, efficacy of the helmet, and total number of cyclists. The scores were decreased and increased by 20% for each variable separately, except for the projected helmet-wearing rate. This variable was increased to its maximum value of 100%. Results of the sensitivity analyses were displayed in tornado plots. Annual helmet costs were varied with a factor in the range of 10–200%.Additionally, the human-capital method was used to calculate productivity losses for people that died due to TBI. The use of this method assumes that productivity is lost for the full duration of absence from work until age of retirement, and hence, that costs of productivity losses stretch out over a much longer period than the friction period only .. These Effects and costs that occurred after 1 year were discounted in accordance with the Dutch guideline for economic evaluations . YLL andTable In 2017, 8016 cases of TBI were registered in Dutch EDs among users of utility bicycles . PSA would have resulted in more reliable and specific ICERs by adding information about the distribution of the model parameters. However, information about the distribution was unavailable for a large number of parameters. The probability of TBI is unrelated to the intensity of bicycle use, while those who cycle more are at greater exposure to TBI risk than those who rarely use a bike. No data are available about bike use intensity. Unfortunately, data on electric bicycles use were not available so we could not distinguish this group of cyclists in this economic evaluation. The fact that we only had healthcare costs available for the first year leads to an underestimation of the cost-effectiveness of the use. Finally, we did not include police enforcement and regulation costs in our study, due to data limitations. The ICERs as estimated in this study may be less beneficial when these costs would have been taken into account. On the other hand, the fact that we only included TBI and not all other injury costs, such as related to fractures, nor other costs of accidents, such as material damage and indirect costs of traffic jams, may have prevented us from reporting more favorable ICERs.Our results are specific for the Dutch cycling context and, as a consequence, not directly transferable to other countries’ settings. First, in the Netherlands cycling is much more common than in other European countries, Denmark excluded. The infrastructure with cycle lanes and other traffic aspects, such as right of way for cyclists and legal responsibility of motorized traffic in any traffic accident, regardless of actual responsibility, differs enormously from other countries. Consequently, injury risks differ substantially, independent of helmet use. Second, in the Netherlands most cyclist currently do not wear a helmet, whereas in most other countries helmet use is common.The current research shows that a law that enforces the use of bicycle helmets for every age group is not cost-effective with an ICER of €28,465 per DALY averted which is higher than the accepted Dutch reference value for cost-effectiveness of preventive interventions. With respect to the difference between age groups, we found this intervention to be cost-effective for people aged 65 years and over due to their relatively high risk of getting TBI with an ICER of €17,775 per DALY averted. One must realize that the costs of the intervention are primarily paid by the individual citizen and the revenues are mainly for the whole society. The acquisition of helmets proved to be an important cost item. If the price of a helmet reduces with 20%, which is a possibility due to large-scale purchases and use of these helmets, the introduction of this regulation would result in an intervention that is approximately cost-effective for all age groups. As this is the first study in the Netherlands that evaluates the cost-effectiveness of enforcing helmet use for cyclists, this can add to the debate around regulating helmet use in general and more specifically for the elderly. We recommend future research towards the mechanisms behind the increased cycling risks for the elderly and the acceptability of a helmet law. We also advise to make the registration of the use of an electric bicycle at the ED standard practice, as the electric bicycle is likely to have an increasing and significant role in TBI. To conclude, although Dutch society is at present not very enthusiastic to wear bicycle helmets, a law that enforces helmet use may be an effective and also cost-effective intervention, certainly in the elderly.


Digital health is a rapidly developing field which is positioned to transform the manner in which healthcare is delivered, especially amongst adolescents and young adults. In order to assess the efficacy of novel medical devices, clinicians and researchers often turn to the literature for guidance. Randomized control trials and the systematic reviews and meta-analyses that they inform are considered to be at the top of the evidence hierarchy. While they are excellent tools to identify and to summarize the best available evidence to answer a specific research question, they are poorly equipped to provide a more expansive understanding of the body of relevant literature in a timely manner. In this letter we discuss the utility of the scoping review, an underutilized style of academic writing designed to map key concepts in a body of literature. This method is ideal when reporting on the fast-paced field of digital medicine, as it allows for rapid synthesis of the available literature. Digital health technology can be utilized for numerous purposes including patient data collection, educational endeavors, improvement of medication compliance, and augmentation of clinician–patient communication. Systematic reviews have evaluated the efficacy of numerous eHealth interventions designed to target various health behaviors in pediatric patients with chronic diseases such as sickle cell disease2 and childhood cancer3. It has also been suggested that mobile phone apps may offer a feasible mechanism for implementing health interventions with the potential to impact health behaviors4. However, more research is required in this area. According to a national survey conducted by Common Sense Media, ~89% of teenagers own smartphones. This percentage has increased significantly since 2012, when only 41% of teens were in possession of these devices5. Thus, digital health technologies arguably provide the greatest benefit to adolescents, the population most tied to social media and smart devices, especially as they transition into adulthood and learn to manage their healthcare needs6.Digital medicine is a novel and rapidly evolving field which has the potential to revolutionize the way in which healthcare is delivered7. However, the rate at which new publications become available is far outpaced by the brisk development of new technologic advancements. In contrast to SRMAs, which are driven by focused primary questions, scoping reviews aim “to map the literature on a particular topic or research area and provide an opportunity to identify key concepts; gaps in the research; and types and sources of evidence to inform practice, policymaking, and research”8. Scoping reviews include diverse study types, presentations, and publications; this breadth and flexibility is their strength, and may be the best evidence assessment approach for the fast-moving field of digital medicine.In order to assess the efficacy of novel medical devices, clinicians and researchers often turn to the literature for guidance. Randomized control trials (RCTs) and the systematic reviews and meta-analyses (SRMAs) that they inform are considered to be at the top of the evidence hierarchy9. The findings of a 10-year-old study may be irrelevant to the currently available technology and clinical practice. Thus, the natural academic and funding cycle that governs the timelines of RCTs and SRMAs may lead to findings reported in manuscripts that are obsolete even before they are published.To illustrate, an RCT funded by a R01 grant takes ~3–5 years to plan and implement. Thus, by the time it is published and subsequently included in a SRMA, 10 or more years may have passed since the original research question was posed. In that same period of time, most digital technologies will have likely undergone one or possibly two significant revolutions as hardware and software are often upgraded on a yearly basis10. This necessarily strict and rigorous process limits SRMAs from providing a more expansive understanding of the body of relevant literature, thereby hindering timely contributions to the state of the science which are needed for cutting-edge application. SRMAs are also not designed to provide insights regarding clinical questions that cannot be easily addressed by RCTs or other more rigorously controlled studies. Entire segments of the literature which contribute to the development of a field of inquiry, such as cross-sectional and qualitative designed investigations, are not included as they are deemed less rigorous.Well-designed RCTs and SRMAs rely on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), Methodological Expectations of Campbell Collaboration Intervention Reviews (MECCIR), Methodological Expectations of Cochrane Intervention Reviews (MECIR), and other protocols that are highly structured and prescribed in order to identify and to summarize the best quality evidence for a specific research question11. The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) received $1.3 billion, <5%. This is not a new problem. As early as the mid-1990s, the US congress acknowledged that inadequate resources and attention were devoted to pediatric research conducted and supported by the NIH12. Recent data demonstrates that the static allocation of NIH funding for pediatric research coupled with reductions in the purchasing power of budgetary funding is negatively affecting the advancement of pediatric science13. The NIH is not unique in this inequity. It also pervades industry, academia, and other governmental agencies. This lack of funding and prioritization leads to reduced support for pediatric researchers, fewer high-quality RCTs, and even fewer SRMAs. The downstream effect is the publication of pediatric systematic reviews which are often only able to identify a handful of studies, leading to the ever-too-common statement “there is insufficient evidence to form a conclusion”14.This plight of outdated and potentially irrelevant publications pertaining to digital medicine and technology is even more complicated in pediatrics, a field which is grossly underfunded as a whole. According to the 2015 US Census Bureau Data, individuals <18 years of age represented nearly one-quarter of the US population. However, of the $30 billion NIH budget that year, the total NIH pediatric research portfolio was only $3.6 billion, ~12%Our Pediatric Asthma and Digital Health Research Group, which includes a research librarian, conducted searches on PubMed consisting of Medical Subject Headings (MeSH) terms and Title/Abstract keywords that combined the concept of pediatrics with systematic review, meta-analysis, or scoping reviews Table . Variati16. In particular, scoping reviews can be very useful in the assessment of digital health as the academic and funding life cycles of RCTs and SRMAs limit their ability to address the need for timely synthesis of the evidence to allow for an impact on such a quickly evolving field. For example, a recent scoping review of digital health apps in inflammatory bowel disease by Yin et al provides a systematic overview of apps that have been clinically evaluated, a summary of the evidence from each study, key features, and emerging themes and trends in the field17. The more inclusive nature of scoping reviews allowed the authors to broadly group apps into categories , to determine how they related to each other, and to make observations and recommendations about gaps in knowledge and future opportunities for research.The dramatic increase in the number of scoping reviews in medicine Fig.  is likel18. The implementation of standardized reporting guidelines for scoping reviews is certainly imperative to ensuring consistency in the literature. The high-impact pediatric journals  do not include scoping reviews as article submission options in their author guidelines, even while specifically identifying systematic reviews, meta-analyses, and narrative reviews as acceptable formats. This academic bias is likely to make scoping reviews less attractive projects for pediatric researchers, resulting in missed opportunities to meaningfully contribute to the literature and to advance pediatric research. A well-designed scoping review could potentially offer crucial insight into the implementation of new technological advances designed to monitor various medical conditions, including the impact that these devices have on patient education, quality of life, integration of patient data into the electronic health record, and other pertinent health outcomes19. In the case of digital health, scoping reviews will become absolutely necessary to better understand the development and implementation of new devices at an appropriate pace. This is perhaps most pressing in pediatrics, a population who is so dependent on technology. We hope that these comments call attention to this important issue.Despite the utility of scoping reviews, a negative bias exists as they are thought to be less rigorous and less structured than traditional SRMA


Supplemental Digital Content is available in the text Coastal areas in Malaysia can have important impacts on the livelihoods and health of local communities. Efforts by Malaysian government to develop and improve the landscape and ecosystem have been planned; however, the progress has been relatively slow because some of the coastal areas are remote and relatively inaccessible. Thus, these coastal communities face various challenges in health, healthcare and quality of life. This paper presents a study protocol to examine the health status, healthcare utilisation, and quality of life among the coastal communities. In addition, the relationship between the community and their coastal environment is examined.The population of interest is the coastal communities residing within the Tun Mustapha Park in Sabah, Malaysia. The data collection is planned for a duration of 6 months and the findings are expected by December 2020. A random cluster sampling will be conducted at three districts of Sabah. This study will collect 600 adult respondents (300 households are estimated to be collected) at age of 18 and above. The project is a cross sectional study via face-to-face interview with administered questionnaires, anthropometrics measurements and observation of the living condition performed by trained interviewers. The environment influences the health of the population in various ways both positively and negatively. Several studies revealed that living close to the coastline encourages people to engage in recreational activities, which improves physical and psychological quality of life.–8 In addition, due to the remoteness, many coastal areas globally are underdeveloped and have not received enough attention from the local or national government even though many potential industrial resources are available. This has led to a slow rate of industrial activities and infrastructure development.Nevertheless, there are several factors contributing to the potential negative impacts on the people living in the coastal environment. Ecological factors such as extreme natural calamities, habitat modification, and water pollution in these areas can lead to serious diseases, injuries and inadequate nutrition.,11 These, in turn, can result in poor health and poor quality of life among the coastal communities, which may lead to numerous negative health consequences.One of the least developed infrastructures in many remote coastal areas is the provision of healthcare. The lack of progress in healthcare facilities and other associated resources has resulted in difficult access to these services, low health awareness and health inequalities between coastal, non-coastal and urban population.–14 Furthermore, inadequate access to healthcare services and limited health knowledge are associated with a higher burden of chronic diseases (e.g. cardiovascular and hypertension), and a high prevalence of tobacco, alcohol and illegal drug uses,16,17 among coastal communities.Studies have shown that several factors such as densely populated areas, poor housing condition with lack of supply to clean water, and improper waste disposal systems have exposed these populations to many infectious diseases including tuberculosis and parasitic infections.,19Due to the geographical location of Malaysia, coastal areas have an important influence on the livelihoods and health of the population. The coastal ecosystem in Malaysia supports a large proportion of the population by provision of significant resources for important industries such as urbanization, agriculture, fisheries, aquaculture, oil and gas exploitation, transportation, communication and recreation, all of which are linked to health benefits and risks of the community.–21 In contrast, the socioeconomic progress in Sabah has been relatively slow, mainly because the coastal zones in Sabah are isolated and inaccessible, as well as having language diversity and cultural differences. Even though public health facilities are available, they are limited and might not reach those in need due to insufficient infrastructure to access the services. In addition, Sabah is facing a high rate of poverty and an large influx of stateless and undocumented people in its coastal areas. Because of these factors, the coastal communities in Sabah are facing various health and healthcare challenges.In many local coastal areas, efforts to develop and improve the landscape and ecosystem have been planned extensively especially in Peninsular Malaysia.To date, research focusing on the health issues, healthcare gaps and health needs of people at coastal areas of Sabah are lacking. Therefore, this paper presents a study protocol to examine the health status, healthcare utilisation and quality of life of coastal communities in Sabah. In addition, the study protocol potentially could also be replicated in other remote coastal communities in the South-East Asian region.22.1https://www.blue-communities.org). The Blue Communities is a 4-year research capacity-building program focused on marine planning, food security and human health and well-being in marine protected areas located in South-East Asia, funded by Global Challenges Research Fund of United Kingdom Research and Innovation. The present study protocol is specifically developed for selected coastal communities in Malaysia.This study is one of the 12 projects under “Blue Communities” grant  boundary in Sabah. TMP was chosen because it is the largest marine protected area recently gazette in Malaysia; and the first multiple-use zoning areas, which was placed under joint-management program involving collaboration between the Sabah Park authorities, World Wildlife Fund (WWF) Malaysia, and local communities. Given the inadequate health-linked research, community health needs and potential risks of living in the coastal communities, this study is proposed to address these gaps by taking the unique perspective of examining linkages to the coastal and marine environment of these communities.Presently, TMP had been experiencing several environmental issues that can affect the human communities. It is under threat from habitat degradation and overfishing which will decrease the available marine resources resulting in negative impacts on the health and quality of life of the community.2.2 All villages included in this study are registered under the Sabah Parks supervision. The villages are all from three districts, within TMP, namely Kudat, Kota Marudu, and Pitas  2015, the overall disease prevalence of hypertension among 18 years and above in Malaysia is 30.3%. Using the overall hypertension in Malaysia of 30.3%,Therefore, this study will involve a collection of 600 adults. We estimate that from 600 adults, there will be about 300 households to be interviewed based on the assumption that 1 household has of 2 adults. To ensure that the districts in TMP are well represented, the percentage of population selected is determined to be at 50%, 30% and 20% for Kudat, Kota Marudu and Pitas from the total number of populations of these three districts, respectively. Therefore, from the 600 adults, 300 adults will be sampled from Kudat (from three randomly selected units), 180 adults (from 2 randomly selected units) from Kota Marudu and the remaining 120 adults (from 1 randomly selected unit) will be from Pitas.2.4The main tools and instruments of data collection are questionnaires which also include a form for physical examination and observation. In this study, the questionnaire entitled “Blue Communities Project 6 Household Survey” , that will be used for data collection) will be used. A pilot study to validate this questionnaire was conducted among the selected population in TMP prior to actual data collection. There are 2 versions of the questionnaire: one with Part A to Part I for the head of household; and another one with only Part C to Part I for other adult household members who are willing to join the survey. All participants must be 18 years old and above during time of the visit. The 9 parts of the full questionnaire are as follows:Part A: Housing and the environment (Head of household only)Questions in Part A will capture the characteristic of the household, housing infrastructure, surrounding area, excreta disposal, basic needs and basic amenities in the house.Part B: Household income (Head of household only)Questions in Part B will capture data on annual household income of the household from all possible income sources.Part C: Socio-demographic (All household members including head of household)Questions in Part C will capture sociodemographic information such as date of birth, ethnicity, academic background, employment status, relationship status, and other relevant information.Part D: Expenditure and utilization of healthcare goods and services (All household members including head of household)Questions in Part D will capture data on source of health payments, healthcare service utilisation, traditional and complementary medicine practice, and healthcare expenditure incurred.Part E: Modifiable lifestyle factors (All household members including head of household)Questions in Part E will capture information on tobacco consumption, nutritional intake, physical activity, medical condition and injury history.Part F: SF-12 quality of life (All household members including head of household)Questions in Part F will assess the quality of life of the study participant with the use of standard and generic quality of life assessment tool.Part G: Interaction with local marine environmentQuestions in Part G will capture the types of activities and exposures of the participants in the coastal area of TMP.Part H: Perceptions of the marine environment in TMP (All household members including head of household)Questions in Part H will elucidate the perceptions and awareness of the respondents on the drivers and pressures in marine environment in TMP.Part I: Medical proforma (All household members including head of household)Part I will assess the anthropometric measurement and blood pressure of the study participant. The anthropometric measurements that will be taken include height, weight, waist circumference and hip circumference.Other study tools that will be used in this survey are calibrated OMRON M2 HEM-7120 Automatic BP Monitor to measure respondents blood pressure, calibrated vertical SECA Portable 217 Stadiometer to measure respondents height, calibrated SECA 813 digital electronic weighing scale to measure respondent weight and SECA 201 Ergonomic measuring tape to measure respondent waist  and hip circumferences. The reading will be taken while sitting. Two readings will be taken for each study participant. Second reading will be taken, 1 minute after the first blood pressure measurement. If both are normal, the average of the readings will be documented. If either the first or the second readings is abnormal, the interviewer will proceed with third reading, 30 minutes after the second reading. If the third reading is high, then a referral letter to the nearest hospital will be given to the study participant. If the third reading of is normotensive, then the blood pressure finding will be recorded. However, the interviewers will advise the participants to double-check his/her blood pressure at the clinic/hospital in the future. All the readings will be recorded in the questionnaire answer booklet.For blood pressure measurement, it will be categorised as normotensive, hypotensive, or hypertensive based on standard definitions used in the recent clinical practice guideline for management of hypertension in Malaysia.2.5Ketua Kampung or sometimes referred to as Ketua Adat) for the selected units.Prior to data collection, researchers will have to conduct ground-truthing of the study survey sites. This process is crucial to ensure that information provided is the same as that obtained on the ground. Information on study sites such as map of the selected units, number of houses in the units, and accessibility of transport to the units can be obtained from the local district office. An official letter for permission to acquire this information will be submitted to the local district offices. Once the information has been collected, the researchers will be in contact with the head of villages . If the village head is not available for ground-truthing, researchers must acquire permission from the village head to get help from local research liaison officers in Kudat, Kota Marudu and Pitas. During the ground-truth, the 3 most crucial observations that the project manager must acquire are as follows: the layout of the houses in the village , the population density in the village, and the transport accessibility to the village study site.The data collection is planned for a duration of 6 months and the findings are expected by December 2020 to plan for a subsequent health intervention programme. The main method of data collection is of administered questionnaire. The observation of house condition, its surrounding area and an individual physical examination will be conducted. Since the survey will involve multiple locations at TMP, it is estimated that 4 to 6 interviewers will be required during the fieldwork. The interviewers will be teamed in a group of 2 people. It is highly advisable to have one (1) male and one (1) female for each pair and at least one of the pair from the local community for security and dialect reasons. Researchers will then assign each pair to conduct the household survey at the selected villages using the prepared schedule.Ground staff  who acts as a liaison officer will be appointed. Prior to data collection, the ground staff will introduce the interviewers to the household members to ensure that the head and members of the household are present and give permission to enter their personal premise. Once the permission obtained, the interviewer will explain regarding the nature of study based on the participant's information sheet , which describes the participant's information sheet); afterward, the information sheet will be given to the participant(s) for reference. In addition, the interviewer will reassure the participants that the information given in the study will remain confidential and their participation is entirely voluntary.The face-to-face interview will begin shortly after the head and members of household have signed the consent form. All adults in the household that give their consent will be interviewed. Blood pressure and anthropometric measurements , will be taken during the face-to-face interview depending on the suitability and participant's preference.In the case where the head of the household is not present during the visit, the house will be marked in the map and a second visit will be arranged for the next day. However, the house will be excluded if the head of the household is still not present during the second visit.2.62.6.1At the end of each day of data collection, the project manager will gather all interviewers and conduct post-mortem session. Any loopholes identified during the process must be addressed immediately to avoid further mistakes and invalid data collected. In addition, the project manager will verify if the number of answer booklets tallies with the number of households surveyed. Upon verification, the answer booklets will be placed in a secure box, while the consent form will be kept in a separate secure box to avoid any breach of information. Only the project manager and the Principal Investigator have access right to these secured boxes.2.6.2Data entry is to be completed within 2 to 4 weeks after the completion of groundwork depending on the number of respondents. Once the data have been completely entered in the IBM SPSS version 24, a random cross-checking on the dataset will be performed to maintain data accuracy. The cross-checking will be set at 20% of the overall questionnaires entered. Data analysis will be divided into descriptive and analytical analysis. Descriptive analysis will be performed on the socio-demographic characteristics, anthropometry measurements, expenditure and utilisation of healthcare goods and services, modifiable lifestyle factors and reported quality of life among the study population. Analytical analysis will be conducted to determine the association between the socio-demographic characteristics, health status and modifiable risk factors with the quality of life and healthcare utilisation. Analysis of results will be done using IBM SPSS version 24. The data and results will be presented to and validated by relevant stakeholders and Blue Communities research group members in the form of reports and seminar sharing session2.6.3The present study has been given ethics approval by the University of Malaya Research Ethics Committee with a reference number of UM.TNC2/UMREC-522. Written informed consent will be obtained from all the respondents prior the interview. The results in the present study will be disseminated in peer-reviewed journal, academic conference, and stakeholder seminar.3 Lack of access to nutritional foods and poor knowledge on healthy diets were found to be the main risk factors for the problem. In addition, in a previous report, there were 30% to 60% of people in rural coastal areas in Sabah who were unaware that they had several non-communicable diseases and were at risk for developing cardiovascular diseases. This appeared to be mainly due to low awareness of routine health check-up and poor access to healthcare services particularly in the rural coastal areas.Previous studies have reported that the coastal communities in Sabah are facing several health and healthcare challenges. These included a nutritional inadequacy among children and adolescents in Sabah, either moderately or severely underweight, especially those who reside in the interior and coastal areas of Sabah. The majority of cases in Sabah are due to a type of plasmodium which is Plasmodium knowlesi.,28,29 Recently, Plasmodium knowlesi has emerged as a common and potentially fatal cause of human malaria in Malaysian Borneo. The main factors for malarial infection at coastal areas in Sabah are found to be poor housing construction, occupational exposure and seasonal factors.Malaria remains a significant public health problem in Sabah, with an incidence of 61.3 per 100,000 population and 23% among children less than 18 years of age. The cases detected among the immigrants in Malaysia are highest in Sabah, which accounts for at least 24% of the total annual cases detected. People of the Kadazan, Dusun and Murut (KDM) tribal communities appeared to be highly susceptible to the infection; and most of the KDM live in the interior parts of Sabah such as Kota Marudu, Pitas, Kota Belud and Pensiangan.On the other hand, Sabah also contributed to the highest number of tuberculosis cases in Malaysia. The influx of immigrants from neighbouring countries (Philippines and Indonesia) to Sabah appeared to have contributed to the annual cases in the states since 1982.The health status, healthcare utilisation and quality of life of coastal communities at Tun Mustapha Park, Kudat Sabah are the focal points of this study. This study aims to identify the factors that hinder the coastal communities in Sabah from accessing and receiving appropriate healthcare services. The information gathered here will be used to design an effective intervention to improve health status and improve quality of life of the community.4In conclusion, this study will determine the health status, healthcare utilization and quality of life of the coastal communities in Sabah. This study has the potential to increase awareness of health inequalities among these communities and to develop an intervention which was tailor according to the context-specific health and quality of life intervention program in the community. The experience and information generated by this study in these aspects should be of interest at the national and international level to improve the overall health and quality of life among the coastal communities, not only in the Sabah, but also in the South East Asia region.We are extremely grateful to colleagues within the Blue Communities project for their support. These include colleagues at the University of Exeter and Western Philippines University, who supported this work in developing parts G and H of the questionnaire. This work has received funding in part from the Global Challenges Research Fund (GCRF) via the United Kingdom Research and Innovation (UKRI) under grant agreement reference NE/P021107/1 to the Blue Communities project and University of Malaya (IF052-2017).Conceptualization: Maznah DahluiData collection: Mohd Aizat Zain, Mohd Iqbal Mohd NoorMethodology: Mohd Aizat Zain, Mohd Iqbal Mohd Noor, Kamal Solhaimi Fadzil, Amirah Azzeri, Julia Suhaimi, Fatimah Kari, Hafiz JaafarFunding acquisition: Hong Ching Goh, Amy Yee Hui ThenQuestionnaire development: Maznah Dahlui, Lota A Creencia, John Roderick Madarcos, Edgar Jose, Amirah Azzeri, Karyn MorrisseySupervision: Maznah Dahlui, Hong Ching Goh, Amy Yee Hui ThenWriting – original draft: Amirah AzzeriWriting – review & editing: Mohd Aizat Zain, Mohd Iqbal Mohd Noor, Maznah Dahlui, Amy Yee Hui Then, Hong Ching Goh, Lora E Fleming, Mathew P White