نیت کشاورزان به سازگاری با تغییرات اقلیمی، کاربرد مدل توسعه‌یافته تلفیق تئوری‌های رفتار برنامه‌ریزی‌شده و انگیزش حفاظت

 A B S T R A C T
Climate change has become one of the most important global challenges threatening the environment and food security. This study utilized an integrated model of the theory of planned behavior and protection motivation to examine farmers' intentions and behaviors regarding climate change adaptation in Meshkinshahr County. Results showed that the model explained 84% of the variance in intention and 56% of the variance in behavior. Perceived vulnerability was the most significant factor influencing intention. Perceived severity had no significant effect on intention, suggesting that farmers were aware of the vulnerability of climate change but did not know enough about its severity. Since the impact of climate change is gradual and farmers do not have a complete understanding of this issue, it is necessary to familiarize them with the extent of climate change impacts through mass media, educational videos, and other extension campaigns. Self-efficacy had a significant influence on the intention; therefore, extension training should be provided to enable them to apply adaptation techniques cost-effectively. The impact of attitude on intention showed a need to improve farmers' attitudes towards climate change. Considering the impact of trust and belief on farmers' intentions, it is necessary to increase farmers' belief in the importance and adverse impacts of these changes and to gain farmers' trust in the effectiveness of climate change adaptation methods. Significant differences in farmers' intentions to adapt to climate change were found in terms of gender, education, place of residence, and number of family members.
Extended abstract
Introduction
Global climate change has increasingly emerged as one of the most significant global challenges threatening the environment and global food security, particularly in less developed regions. The direct impacts of climate change on the agricultural sector include food insecurity, an increase in pests and diseases that negatively impact agricultural productivity, increased erosion and a decline in soil fertility. It is important to mitigate these impacts by enabling farmers to adapt and cope with the negative impacts on agriculture and their livelihoods. Effective adaptation can significantly reduce the magnitude of climate change impacts. Adaptation refers to actions to maintain a system's ability to cope with climate change. It can significantly reduce vulnerability to change and protect the rural community in mitigating potential risks and coping with the negative consequences of change. Various theories and models have been developed to analyze people's intentions and behaviors. Ajzen's theory of planned behavior (TPB) is one of the most widely used theories. It assumes that a person's intention to engage in a certain behavior is influenced by their attitudes, subjective norms, and perceived behavioral control. The Protection Motivation Theory (PMT), developed by Davis et al. (2015), was used to assess how motivation influences individuals' health behaviors. The PMT consists of two components: threat appraisal, which is measured by perceived threat and perceived severity, and coping appraisal, which is measured by self-efficacy, response efficacy, and response cost. This study used an extended model integrating TPB and PMT to examine farmers' intentions and behaviors related to climate change adaptation.
 
Methodology
This study was conducted in Meshkinshahr County. A cross-sectional survey method utilizing a multi-stage sampling strategy was employed for data collection. The statistical population comprised orchard farmers in the county. A sample of 220 farmers was selected using the Cochran formula. The research instrument was a questionnaire. It developed based on the study's theoretical framework and a comprehensive literature review. The questionnaire included the respondents' socioeconomic characteristics and eight model constructs. A panel of experts validated the research tool. A pilot study was conducted with 30 farmers outside the sample area to test the validity of the questionnaire and make any necessary corrections. The calculated alpha values for all constructs were above 0.7, indicating acceptable reliability of the research instrument. SPSS version 22 was used for initial statistical analyses, and Structural Equation Modeling (SEM) with PLS software was utilized to model and predict the effects of factors influencing farmers' intentions and behaviors regarding adaptation. The goodness of fit for the model was assessed first. The reliability of the research model was confirmed using composite reliability coefficients and Cronbach's alpha. Indicators of discriminant validity, as well as convergent and divergent validity, were employed to evaluate the model's validity.
 
Results and Discussion
The results indicated that, with the exception of perceived severity, all hypotheses of the study were confirmed, explaining 84% of the variance in intention. The perceived vulnerability had the most significant impact on farmers' intentions, suggesting that their willingness to adapt to climate change largely depends on their perception of vulnerability. The significant effect of attitude on intention implies that a positive attitude toward new ideas leads to better preparation and a greater intention to implement them. Self-efficacy also significantly affected intention, indicating that individuals with higher perceived self-efficacy are more likely to seek coping strategies and take adaptation measures when facing challenges such as climate change. The significant influence of trust on intention shows that farmers are more inclined to adapt when they trust government officials and agricultural experts. Furthermore, the positive effect of belief in climate change on intention highlights that as farmers increasingly recognize changing climate conditions, they are more willing to adapt. This finding underscores the necessity for extension services to provide relevant information that aids farmers in adapting to climate change. Conversely, the lack of a significant effect of perceived severity on intention may stem from inadequate policy interventions and farmers' limited understanding of climate change. Additionally, behavioral intention positively affected actual adaptation behavior, explaining 56% of the variance in that behavior, thus confirming the foundational premise of the TPB. Moreover, significant differences in socioeconomic variables were evident among farmers based on gender, education, family size, and place of residence. Male and more educated farmers and those with larger families in rural areas were more likely to adapt to climate change.
 
Conclusion
Utilizing an extended model of the integrated TPB-PMT, this study explored farmers' intentions and behaviors related to climate change adaptation in Meshkinshahr County. The model successfully explained variance in farmers’ intentions, which in turn accounted for 56% of the variance in behavior. The findings offer new insights into the effectiveness of these theories in predicting farmers’ intentions and their adoption of climate change adaptation strategies, with important implications for agricultural policy and extension services. Among the model constructs, perceived vulnerability emerged as the most crucial factor influencing intention, while perceived severity showed no significant impact, indicating that farmers are somewhat aware of their vulnerability to climate change but lack sufficient knowledge of the severity of its consequences. As climate change continues to affect the agricultural sector, it is vital to conduct extension campaigns to educate and prepare farmers for adaptation.
 
Funding
This research was supported by the University of Mohaghegh Ardabili (Research grant number 1402/d/9/11487).
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.