Due to the final fitted model, AP and CP were two variables, which are directly affecting the behavior of paddy workers.
Consistent with the current study finding, de Vries et al.’s study showed that AP was the strongest predictor of sunscreen use in Belgian teens [20]. Planning plays an important role in the process of changing behavior and communicates between the intention and the behavior. AP is more applicable in the early stages of behavior change, and coping planning is more applicable in the next stages of behavior change [21]. In this study, both the AP and CP have been assessed together, and separately assessing these variables was impossible. Although, some studies concluded that together, those two variables are essential in changing behavior [22], and it is believed that CP can boost the effects of AP [23].
The coping SE was the only variable that had both direct and indirect paths on the behavior and had the greatest effect on sunscreen use among farmers, which is the total of the direct and indirect, based on the final fitted model. CSE is mentioned as a personal SE to overcome the barriers. During the several situations, maintaining health behavior was harder than starting it, although for starting health behavior, ASE is sufficient, but for maintaining it, CSE is required [24].
In a Nahar et al. study, ASE had a significant relationship with protective behaviors against the sunlight in landscapers [25]. Although, in the study of Nahar, it has not mentioned anything about the continuation and preservation of protective behaviors, and therefore, we cannot compare these two elements.
Based on the final fitted model, there was no direct relationship between intention and behavior; intention goes indirectly through the CP path on behavior, which is the same as the Craciun study that was planning a variable between the intention and sunscreen use among students. Based on the Craciun study, having a good intention leads to behavior, when we have the appropriate planning to overcome the barriers [18].
According to Rhodes & de Bruijn’s study, intention determines 46% variation in behavior [26]; but despite having good intentions,, many planners are failing to conduct the behavior [27]. And the intention has the limited predictive power [28], contrary to the planned behavior model and protection motivation theory assumptions, which considered intention as the strongest predictor of behavior. According to Rhodes & Dickau, declaration of the intention was an essential factor for behavior, but it is not enough [29]. Planning will increase the possibility of converting the intention to behavior [30].
According to Osch et al.’s study, their results showed that the motivational factors such as RP, OE, and ASE did not directly affect behavior [31].
In accordance with these study results, the effects of RP and OE were the same as in predicting sunscreen use and was less than ASE. While the Craciun [18] study represented that RP was less important in comparison with OE and ASE in the sunscreen use among students; it seems that the different results are due to the differences in the subject’s characteristics; younger people often have less cautious behaviors and less risk perception compared with older people, and the outcome expectation is more important to them than older ones. Both in this study and in Craciun’s study [18], SE was more important than the other motivational factors. In current studies, like Craciun’s study, ASE was more important than RP or OE. As this study was carried out for people who are over 30 years with a mean age of 47 years old, there is no definite opinion on this subject for researchers, until this study was conducted
In this study, SM has direct influence on the behavior. This variable in fact is a facilitator of changing the behavior, as Sniehotta believes that in addition to AC and CP, we need strategies such as social support and SM for changing behavior [32].
Limitations of the study
Given that the current study was conducted in the agricultural season, some factors such as farmers lacking time for interview might influence data collection cycle although we attempted to adjust the interview time in accordance with the participant’s conditions.