Re-imagining Risk communication: A Review of Kenya Ministry of Health Risk Communication Strategies During the First Phase of COVID-19 Pandemic. (Research Proposal Sample)

Re-imagining Risk communication: A Review of Kenya Ministry of Health Risk Communication Strategies During the First Phase of COVID-19 Pandemic. UP2080244 Contents TOC \o "1-3" \h \z \u Abstract PAGEREF _Toc123392887 \h 3Aims of the research Project PAGEREF _Toc123392888 \h 3Literature Review PAGEREF _Toc123392889 \h 3Methodology PAGEREF _Toc123392890 \h 4Critical discussion PAGEREF _Toc123392891 \h 5REFERENCES PAGEREF _Toc123392892 \h 6 Abstract This research will focus on the practical strategies that were implemented by the Kenya government ministry of health(MoH) in undertaking risk communication during the first phase of COVID-19 Pandemic. The study through content analysis will help determine predominant risk communication models or strategies put in place to manage and prevent the risk of COVID-19 infection as part of COVID-19 risk management. The first phase is considered in this paper as a crisis period based on the nature and development of COVID-19 pandemic. There is minimal information on the risk communication strategies and their impact in Kenya during this period. This paper seeks to establish the pathway taken by the Kenya government and in particular the MoH in risk communication. The paper intends to review risk communication strategies of MoH in using twitter with a view of providing future recommendations on risk communication strategy. Aims of the research Project In detail the objectives of this research are to determine * Which risk communication strategies if any and the critical factors that were used by the Kenya ministry of health to manage the risk. * Determine if there are any risk communication strategies or model suited through twitter. * To explore recommendations on how the MoH could improve future risk communication strategies during Crisis period. The research will focus on risk communication strategies through twitter handled by the Ministry Of Health In Kenya. It is anticipated that the research will offer insights that could contribute to the growing literature of risk communication. Literature Review Risk communication plays a central role in exchange of information that target individuals, groups, and institutions((Infanti et al.,2013).This information encompasses passage of actionable risk information for purposes of risk management like preparation, protection, responding or recovery(Meredith, et al.,2018). A lot of studies have given credence to the role of risk communication in risk management cycle. Ideally, in identification of hazard, risk analysis and development, implementation, and evaluation of policies (Infanti et al.,2013). There are many literatures that discusses theories on risk management. These include evaluation framework(Dickman, et al.,2015) mental noise(Atman,1994)and value Model(Sheppard et al.,2012)This not withstanding, studies have also shown paucity, ineficiencies and irregular application of risk management theories, in risk managment through the top down communication(Paton et al.,2005). There is limited literature and inconsistent application of these theories during Covid-19 period. Available literature and discussion has continuously pointed to Risk communication in accidents, disasters mainly as a communication tool for information management, awareness, warning or governing a response(Mackie & Netten,2011). Other studies have focused solely on risk communication as tools that support ICT operations in both design and improving communication(Albano et al.,2015) Previous research on risk communication have highlighted various themes, firstly there is a huge amount of literatures which highlights the links risk communication and perceptions (Rosi et al., 2021).Studies conducted by (Rosi et al., 2021) have shown that Sociodemographic factors and vulnerability have influence on risk communication. Other studies have highlighted the impact of emotional state on risk communication (Yıldırım & Güler, 2020, Chan & Ho, 2018).A crisis calls for identifying possible risk, analyzing the risk, and deciding how to frame the issue (Ndlela, 2018).Much of the literature on risk communication also studies standpoints and principles related to risk communication from a sociocultural perspective(Wardman, 2014, Ndlela, 2018). Risk perception correlates incomparably with reported acquisition of preventative health practices (Dryhurst et al., 2020). Several studies have highlighted theories on capacity of individuals to process risk information in stressful situation also referred to as Mental noise.Mental noise theory/model focuses on how individuals view information under stressful conditions(Bourrier, 2018). Risk communication being the interchange of information regarding risks, mental noise poses an enormous threat in delivering vital risk information in times of a crisis (Covello & Milligan, 2018). Data from several studies suggest that high stress levels also referred to as mental noise could affect the processing of information(Kanyi, 2020). Previous studies have investigated trust and risk communication.Trust determination theory shows that risk communication could directly be linked to trust (Balog‐Way et al., 2020) Extensive research has shown that fairness and trust are crucial to messengers delivering risk information in each area investigated by researchers, including nuclear power (Besley & Oh, 2014), climate change (Smith & Mayer, 2018), pharmaceuticals (Balog-Way et al., 2019), and autonomous vehicles (Liu et al., 2018).Credible sources especially when there is minimal information about a hazard or epidemic could be effective if messengers highly value trust(Blair et al., 2017; Cairns et al.,2013; Fancourt et al., 2020). Researchers recommend using different strategies where there is low or high trust and during different stages of a crisis such as the outbreak of an illness (Cairns et al., 2013; Fancourt et al., 2020). Many messengers of risk information understand the essence of transparency in rebuilding trust (Cucciniello et al., 2016; Keohane et al., 2014). Messengers who appear opaque may be construed as misinforming, misleading, or hiding things(Way et al., 2016). However, existing literature shows numerous transparency policies, which may have undesirable side effects and changing negative, positive, and limited effects on trust (Cucciniello et al., 2016) Building trust relies on adequate transparency (Keohane et al., 2014).The growth of social media and its acceptance over the past decade has also provided messengers with more opportunities (Panagiotopoulos et al., 2016; Vosoughi et al.,2018). One study showed comprehensive range of recipients receive their information based on trust as a basis of cultural factors(Blair et al., 2017). Some of studies of risk communication argues that stress places more weight on negative in comparisons to positive information (Vargas et al., 2021). Negative stories surrounding the pandemic, such as the lack of finances for PPEs, handwashing facilities were easily believed (USAID & MOH, 2021) this sometimes could focus on tones and facial expressions (Kiley Hamlin et al., 2014) Researchers have been monitoring Twitter posts and analyzing them to investigate the presence of negative dominance surrounding the coronavirus pandemic (Vargas et al., 2021).Research has shown that there was increasingly negative information surrounding the pandemic on Twitter. While positive information was designed to bring hope and encouragement, the public focused more on the negative side (Pascual-Ferrá et al., 2021). Risk communication Research has shown that there was increasingly negative information surrounding the pandemic on Twitter. While positive information was designed to bring hope and encouragement, the public focused more on the negative side (Pascual-Ferrá et al., 2021). Methodology The research will use content analysis of messages in tweets posted by the MoH through their official Twitter handle. The study will be in three phases; i) Extracting data, preparing and transforming. ii) Code schema buildout and application. iii) Content analysis. The study will use qualitative content analysis, which will entail extracting and analyzing relevant COVID- 19 related tweets from the MoH Twitter handle in Kenya from March 2020 to September 2020. The research will follow a retrospective approach, and will involve collecting the top seventy (70) tweets from MoH’s official Twitter handle with the most reactions, (10 tweets per month from March 2020 to September 2020). For inclusion and verifiability, the tweets will come from MoHs verified twitter handle written in English. Data collection will also use the search of tweets using keywords such as “Corona”, “COVID- 19”, “Covid”, “Coronavirus.” The study will use Twitter API search lodged in NodeXL (WHO, 2020). This will entail extracting and analyzing relevant COVID- 19 related tweets from the MoH Twitter handle in Kenya from March 2020 to September 2020. The research will focus on collecting the top seventy (70) tweets from MoH’s official Twitter handle with the most reactions, (10 tweets per month from March 2020 to September 2020). Data collection will also use the search of tweets using keywords such as “Corona”, “COVID- 19”, “Covid”, “Coronavirus.” To put together the data for analysis, similar tweets that appear more than once will be deleted following the (Unified Twitter ID). The unique Unified Twitter ID will be created Twitter related to each tweet. The total number of tweets drawn, the duplicates identified and removed will be described in the form of a table. There will be an exclusion of unrelated tweets in the period between March 2020 to September 2020 based on the research scope and objectives. Tweets that will not be in English, contain images and videos and no text, and those unrelated to COVID- 19 will be removed/discarded. This study’s code schema wi...