The Geography of Climate Change Adaptation in the Vietnam Northern Mountains: A Quantitative Analysis for Intentions of Indigenous Ethnic Minorities Using Structural Equation Modeling (SEM) and Protection Motivation Theory (PMT)

2021 ◽  
pp. 275-291
Author(s):  
An Thinh Nguyen ◽  
Ha Thi Thu Pham ◽  
Quoc Anh Trinh ◽  
Thuy Linh Do ◽  
Phuong Anh Dang ◽  
...  
Keyword(s):  
Climate Change ◽  
Structural Equation Modeling ◽  
Quantitative Analysis ◽  
Ethnic Minorities ◽  
Climate Change Adaptation ◽  
Structural Equation ◽  
Protection Motivation Theory ◽  
Equation Modeling ◽  
Protection Motivation ◽  
Motivation Theory

scholarly journals Farmers’ Intention to Climate Change Adaptation in Agriculture in the Red River Delta Biosphere Reserve (Vietnam): A Combination of Structural Equation Modeling (SEM) and Protection Motivation Theory (PMT)

2019 ◽  
Vol 11 (10) ◽  
pp. 2993 ◽  
Author(s):  
The Anh Luu ◽  
An Thinh Nguyen ◽  
Quoc Anh Trinh ◽  
Van Tuan Pham ◽  
Ba Bien Le ◽  
...  
Keyword(s):  
Climate Change ◽  
Structural Equation Modeling ◽  
Climate Change Adaptation ◽  
Structural Equation ◽  
Biosphere Reserve ◽  
Protection Motivation Theory ◽  
Red River ◽  
Equation Modeling ◽  
Red River Delta ◽  
Climate Risks

Coastal communities living in the low delta areas of Vietnam are increasingly vulnerable to tropical storms and related natural hazards of global climate change. Particularly in the Red River Delta Biosphere Reserve (RRDBR), farmers change the crop structure and diversify agricultural systems to adapt to the changing climate. The paper deals with a quantitative approach combined with behavior theories and surveyed data to analyze farmers’ intention to climate change adaptation in agriculture. Based on the Protection Motivation Theory (PMT), seven constructs are developed to a questionnaire surveying 526 local farmers: risk perception, belief, habit, maladaptation, subjective norm, adaptation assessment, and adaptation intention. Structural Equation Modeling (SEM) is implemented to extract eight factors and to quantify the relationship between protective behavior factors with the adaptation intention of the surveyed farmers. Two bootstrap samples of sizes 800 and 1200 are generated to estimate the coefficients and standard errors. The SEM result suggests a regional and three local structural models for climate change adaptation intention of farmers living in the RRDBR. Farmers show a higher adaptation intention when they perceive higher climate risks threatening their physical health, finances, production, social relationships, and psychology. In contrast, farmers are less likely to intend to adapt when they are subject to wishful thinking, deny the climate risks, or believe in fatalism.

scholarly journals The protection motivation theory for predict intention of COVID-19 vaccination in Iran: a structural equation modeling approach

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alireza Ansari-Moghaddam ◽  
Maryam Seraji ◽  
Zahra Sharafi ◽  
Mahdi Mohammadi ◽  
Hassan Okati-Aliabad
Keyword(s):  
Structural Equation Modeling ◽  
Self Efficacy ◽  
Structural Equation ◽  
Adult Population ◽  
Protection Motivation Theory ◽  
Equation Modeling ◽  
Protection Motivation ◽  
Motivation Theory ◽  
Perceived Severity ◽  
Response Efficacy

Abstract Background Many efforts are being made around the world to discover the vaccine against COVID-19. After discovering the vaccine, its acceptance by individuals is a fundamental issue for disease control. This study aimed to examine COVID-19 vaccination intention determinants based on the protection motivation theory (PMT). Methods We conducted a cross-sectional study in the Iranian adult population and surveyed 256 study participants from the first to the 30th of June 2020 with a web-based self-administered questionnaire. We used Structural Equation Modeling (SEM) to investigate the interrelationship between COVID-19 vaccination intention and perceived susceptibility, perceived severity, perceived self-efficacy, and perceived response efficacy. Results SEM showed that perceived severity to COVID-19 (β = .17, p < .001), perceived self-efficacy about receiving the COVID-19 vaccine (β = .26, p < .001), and the perceived response efficacy of the COVID-19 vaccine (β = .70, p < .001) were significant predictors of vaccination intention. PMT accounted for 61.5% of the variance in intention to COVID-19 vaccination, and perceived response efficacy was the strongest predictor of COVID-19 vaccination intention. Conclusions This study found the PMT constructs are useful in predicting COVID-19 vaccination intention. Programs designed to increase the vaccination rate after discovering the COVID-19 vaccine can include interventions on the severity of the COVID-19, the self-efficacy of individuals receiving the vaccine, and the effectiveness of the vaccine in preventing infection.

scholarly journals The Protection motivation theory for predict intention of COVID-19 vaccination in Iran: A structural equation modeling approach

2021 ◽  
Author(s):  
Alireza Ansari-Moghaddam ◽  
Maryam Seraji ◽  
Zahra Sharafi ◽  
Mahdi Mohammadi ◽  
Hassan Okati-Aliabad
Keyword(s):  
Structural Equation Modeling ◽  
Self Efficacy ◽  
Structural Equation ◽  
Adult Population ◽  
Protection Motivation Theory ◽  
Equation Modeling ◽  
Protection Motivation ◽  
Motivation Theory ◽  
Perceived Severity ◽  
Response Efficacy

Abstract BackgroundMany efforts are being made around the world to discover the vaccine against COVID-19. After discovering the vaccine, its acceptance by individuals is a fundamental issue for disease control. This study aimed to examine COVID-19 vaccination intention determinants based on the protection motivation theory (PMT). Methods We conducted a cross-sectional study in the Iranian adult population and surveyed study participants from the first to the 30th of June 2020 with a web-based self-administered questionnaire. We used Structural Equation Modeling (SEM) to investigate the interrelationship between COVID-19 vaccination intention and perceived susceptibility, perceived severity, perceived self-efficacy, and perceived response efficacy. Results SEM showed that perceived severity to COVID-19 (β=.17, p < .001), perceived self-efficacy about receiving the COVID-19 vaccine (β=.26, p < .001), and the perceived response efficacy of the COVID-19 vaccine (β=.70, p < .001) were significant predictors of vaccination intention. PMT accounted for 61.5% of the variance in intention to COVID-19 vaccination, and response efficacy was the strongest predictor of COVID-19 vaccination intention. ConclusionsThis study found the PMT constructs are useful in predicting COVID-19 vaccination intention. Programs designed to increase the vaccination rate after discovering the COVID-19 vaccine can include interventions on the severity of the COVID-19, the self-efficacy of individuals receiving the vaccine, and the effectiveness of the vaccine in preventing infection.

scholarly journals Can Protection Motivation Theory Explain Farmers’ Adaptation to Climate Change Decision Making in The Gambia?

Climate ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 13 ◽  
Author(s):  
Abdoul Bagagnan ◽  
Issa Ouedraogo ◽  
William M. Fonta ◽  
Musa Sowe ◽  
Anne Wallis
Keyword(s):  
Climate Change ◽  
Water Conservation ◽  
Protection Motivation Theory ◽  
The Gambia ◽  
Equation Modeling ◽  
Protection Motivation ◽  
Motivation Theory ◽  
Adaptation Measures ◽  
River Region ◽  
Capacity Degradation

In The Gambia, climate change has affected, and continues to affect, the agriculture sector. Thus, there is a need to develop and understand effective agricultural adaptation policies. The present study used protection motivation theory to describe farmers’ adoption of climate change adaptation measures in the Central River Region of The Gambia. Primary data were collected in eight communities of the region. A transect walk was conducted, followed by a survey of farmers (n = 283). Perception data collected referred back to the past 20 years, with stated implementation addressing current adaptation practices. Results showed that the perception variables, namely, severity, ability to withstand, and internal barriers, were significantly correlated with protection motivation, while protection motivation and stated implementation for water conservation technique were strongly correlated. Structural equation modeling confirmed the mediation role of protection motivation between farmers’ “stated implementation” of adaptation measures and their perception of climate variability. A decrease in soil water storage capacity, degradation of the quality of soil surface structure, and a decrease of the length of the growing season are all factors that motivate farmers to implement an adaptation measure. The cost of the implementation and farmers’ vulnerability are factors that prevent implantation of adaptation measures. This study suggested that farmers’ resilience should be improved and adaptation measures should be subsidized in order to make them more accessible to farmers.

scholarly journals Determinants of Climate Change Mitigation and Adaptation strategies: An Application of Protection Motivation Theory

2019 ◽  
Vol 42 (337) ◽  
pp. 9-25 ◽  
Author(s):  
Dereje Tesema Regasa ◽  
Nega Abera Akirso
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Qualitative Data ◽  
Protection Motivation Theory ◽  
Mitigation Strategies ◽  
Research Approach ◽  
Protection Motivation ◽  
Motivation Theory ◽  
Climate Change Effects ◽  
Adaptation And Mitigation

Abstract Climate change is an inevitable global challenge of the 21st century. For developing countries like Ethiopia, it intensifies existing challenges towards ensuring sustainable development. Adopting the protection motivation theory, this study examined factors affecting the practice of climate change adaptation and mitigation strategies among farmers. The study employed a mixed research approach to assess the subjective understanding of farmers about climate change threats and identify factors determining their responses to climate change effects. Qualitative data were collected using focus group discussions and interviews. Quantitative information was gathered using semi-structured survey from 296 randomly selected farmers. Qualitative data was dominantly analyzed using content analysis, while descriptive and inferential statistics were applied to analyze quantitative data. Almost all respondents (97%) perceived that climate change was occurring and threatening their wellbeing. Dwindling precipitation, increasing temperature and occurrence of human and animal disease were perceived to represent climate change effects. From nationally initiated strategies, farmers were found to largely practice soil and water conservation, which they perceived as less costly and compatible to local knowledge. The result of binary logistic regression revealed that perceived severity of climate change, perceived susceptibility to climate change threat, perceived own ability to respond, response efficacy, and cost of practices predicted farmers’ motivation to practice climate change adaptation and mitigation strategies. Thus, building a resilient system should go beyond sensitizing climate response mechanisms. Policies should focus on human capital development and economic empowerment which would enable farmers to pursue context-specific adaptation and mitigation strategies, thereby maintaining a sustainable livelihood.

scholarly journals Determinants of Climate Change Mitigation and Adaptation Strategies: An Application of Protection Motivation Theory in Konta District, South Western Ethiopia

2019 ◽  
Vol 12 (19) ◽  
pp. 49-73
Author(s):  
Dereje Tesema Regasa ◽  
Nega Abera Akirso
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Water Conservation ◽  
Qualitative Data ◽  
Protection Motivation Theory ◽  
Mitigation Strategies ◽  
Research Approach ◽  
Protection Motivation ◽  
Motivation Theory ◽  
Adaptation And Mitigation

AbstractClimate change becomes a widely acknowledged and inevitable global challenge of 21st century. For developing countries like Ethiopia, it intensifies existing challenges of ensuring sustainable development. This study examined factors affecting climate change adaptation and mitigation strategies by taking in Protection Motivation Theory. The study draws on mixed research approach in order to assess the subjective understanding about climate change threats and identify the factors determining responses to climate change. While qualitative data were collected through focus group discussions and interviews, quantitative information was collected using semi structured survey from 296 randomly selected farmers from different agro-ecologies. Qualitative data was dominantly analyzed using content analysis while descriptive and inferential statistics were applied to analyze quantitative data. Almost all respondents (97%) perceived that climate change is occurring and threatening their wellbeing. Dwindling precipitation, increasing temperature and occurrence of human and animal disease were perceived to represent climate change. From nationally initiated strategies, farmers were found to largely practice soil and water conservation and agricultural intensification, which they perceived less costly and compatible to their level of expertise. The result of binary logistic regression revealed that perceived severity of climate change, perceived susceptibility to climate change threat, perceived own ability to respond, response efficacy and cost of practices predicted farmers motivation to practice climate change adaptation and mitigation strategies. Thus, building resilient system should go beyond sensitizing climate response mechanisms. Rural development and climate change adaptation policies should focus on human capital development and economic empowerment which would enable farmers pursue context specific adaptation and mitigation strategies thereby maintain sustainable livelihood.

scholarly journals Modeling and Analysis of Barriers to Climate Change Adaptation in Tehran

Climate ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 104
Author(s):  
Behnam Ghasemzadeh ◽  
Ayyoob Sharifi
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Structural Equation ◽  
Group Discussion ◽  
Climate Change Impacts ◽  
Equation Modeling ◽  
Interpretive Structural Modeling ◽  
Adaptation Measures ◽  
Modeling And Analysis ◽  
Management Plans

Since the impacts of climate change will last for many years, adaptation to this phenomenon should be prioritized in urban management plans. Although Tehran, the capital of Iran, has been subject to a variety of climate change impacts in recent years, appropriate adaptation measures to address them are yet to be taken. This study primarily aims to categorize the barriers to climate change adaptation in Tehran and analyze the way they interact with each other. The study was done in three steps: first, the focus group discussion (FGD) method was used to identify the barriers; next, the survey and the structural equation modeling (SEM) were used to validate the barriers, identify their importance, and examine their possible inter-relationships; and finally, the interpretive structural modeling (ISM) was applied to categorize and visualize the relationships between the barriers. Results show that barriers related to the ‘structure and culture of research’, ‘laws and regulations’, and ‘planning’ belong to the cluster of independent barriers and are of greater significance. The ‘social’ barrier and barriers related to ‘resources and resource management’ are identified as dependent barriers and are of lesser importance. Barriers related to ‘governance’, ‘awareness’, ‘education and knowledge’, ‘communication and interaction’, and ‘economy’ are identified at the intermediate cluster. The findings of this study can provide planners and decision makers with invaluable insights as to how to develop strategies for climate change adaptation in Tehran. Despite the scope of the study being confined to Tehran, its implications go far beyond this metropolis.

Structural Equation Modeling Facilitates Transdisciplinary Research on Agriculture and Climate Change

Crop Science ◽  
2014 ◽  
Vol 54 (2) ◽  
pp. 475-483 ◽  
Author(s):  
Richard. G. Smith ◽  
Adam S. Davis ◽  
Nicholas R. Jordan ◽  
Lesley W. Atwood ◽  
Amanda B. Daly ◽  
...  
Keyword(s):  
Climate Change ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Transdisciplinary Research ◽  
Equation Modeling

scholarly journals Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis (Preprint)

2020 ◽  
Author(s):  
Se Young Jung ◽  
Hee Hwang ◽  
Keehyuck Lee ◽  
Ho-Young Lee ◽  
Eunhye Kim ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Decision Support ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Structural Equation ◽  
Adverse Drug Events ◽  
Ease Of Use ◽  
Barriers And Facilitators ◽  
Equation Modeling ◽  
Successful Implementation

BACKGROUND Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts. OBJECTIVE In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators. METHODS A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation. RESULTS Quantitative analysis revealed that physicians’ expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability. CONCLUSIONS This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.

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