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A predictive model of the sunscreen use in the paddy workers based on the health action process approach model: a path analysis

A predictive model of the sunscreen use in the paddy workers based on the health action process... Background: Skin cancer is considered as one of the most common cancers in the world. There is little information about identifying factors affecting sunscreen use among paddy workers and their protective behavior. The present study aimed to determine a predictive model of the sunscreen use in the paddy workers based on the health action process approach model (HAPA). Methods: This cross-sectional study was conducted on 177 paddy workers who engaged in agricultural work in the north of Iran in 2018. Convenience sampling methods was used. Inclusion criteria were being a farmer for 5 years, working under the sunshine more than 2 h per day, and above the age of 30 years. A multi-sectional questionnaire (intention, risk perception (RP), outcome expectation (OE), action self-efficacy (ASE), action planning (AP), coping planning (CP), coping SE (CSE), self-monitoring (SM), and sunscreen use) was used for data collection. Data were analyzed with SPSS-21 and Lisrel-8.8 software. Results: The mean age of participants was 47.78 ± 12.66 years. The final path model fitted well (comparative fit index (CFI) = 0.98, RMSEA = 0.000), only coping self-efficacy (CSE) from both direct and indirect paths had an impact on sunscreen use (B = 0.73). Among the variables which are influenced only in one direction, coping planning (CP) had the most direct influence (B = 0.30) on behavior, and action planning had the lowest influence (B = 0.24). Conclusion: Coping self-efficacy was the most important factor which had influence on the use of sunscreen, and it should be considered when designing interventional programs related to sunscreen use among paddy workers. Keywords: Skin cancer, Sunscreen, Paddy workers, HAPA, Path analysis * Correspondence: Leilisalehi88@gamil.com Research Center for Health, Safety and Environment, Alborz University of Medical Sciences, Karaj, Iran Department of Health Education & Promotion, Alborz University of Medical Sciences, Karaj, Iran Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 2 of 7 1 Introduction (RP), Outcome Expectation (OE), and Action Self- Skin cancer is considered as one of the most common Efficacy (ASE). These factors lead to the intention of cancers in the world [1], and its prevalence is increasing. behavior. After the formation of the intention, the This cancer affects one of every five American people person enters to the voluntary phase, which involves and leads to more than 10,000 deaths annually in the Action Planning (AP), Coping Planning (CP), and USA [2]. This cancer is also one of the most common Coping Self-Efficacy (CSE) [18]. types of cancers in Iran [3]. Knowing the factors that affect the behavior, their im- Ultraviolet (UV) radiation is considered as the most portance and their direct and indirect effects of each of important cause of skin cancer [4]. Concerns related the variables will help planners and educators in design- to occupational exposure to sunlight increase with the ing appropriate educational interventions. In this regard, increase of skin cancer incidence [5, 6]. In relation to Craciun [18] conducted a study on female students by this cancer, the main emphasis is on outdoor jobs [7]. using the HAPA to identify the intermediary compo- Farmers are among the most susceptible individuals nents of the use of sunscreen and showed that the plan- to sunburn risk with consequent increase of the risk ning variables just play a mediating role in the use of of skin cancer. While there is a little information sunscreen for women. This study aimed to determine about the factors affecting their performance and the predictive model of the sunscreen use for paddy their protective behavior [8], there have been some workers by using HAPA (Fig. 1). studies conducted to understand the effective factors on the use of sunscreen, and a variety of factors have 2 Methods been suggested like risk perception [9], perceived sen- 2.1 Study design and participants sitivity [10], self-efficacy [11], and outcome expect- This cross-sectional study was carried out on 177 paddy ation [12]. workers in 2018. These farmers were engaged in agricul- The health action process approach model (HAPA) is tural work in the villages of the Rood River in the north considered as a predictive model for understanding the of Iran (Gilan province). Five of the 460 villages in behavioral change mechanisms, and there are various ex- Roudsar were selected by cluster random sampling to perimental evidences to support this approach in differ- access the study subjects. The inclusion criteria were be- ent health behaviors such as healthy eating [13], ing a farmer for 5 years, working under the sunshine for vaccination [14], condom using [15], dental floss, phys- more than 2 h per day, and above the age of 30 years. ical activity, and management of diabetes [16]. Farmers who were eligible for entrance in the study were The HAPA was first proposed by Schwarzer et al. selected by the convenience sampling method. By refer- [17] and is consisted of two phases named voluntary ring to the selected villages and agricultural lands, 354 and motivational. The motivational phase focuses on farmers were surveyed in terms of inclusion criteria, and beliefs that force a person to have particular behav- eventually 177 farmers entered the study. iors and includes the factors such as Risk Perception Fig. 1 The default relationship between the variables, based on the health action process approach (HAPA) Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 3 of 7 2.2 Sample size “Using the sunscreen during the working under the For determining the sample size, usually, N = 100–150 is sunlight, will reduce sun burning and the itching”. considered the minimum sample size for conducting The higher score represented more OE. The path analysis [19]. Cronbach's alpha coefficient for this part was 0.89. For better access to the farmers, the researchers gets (e). Action Self-Efficacy (ASE): The ability to use of in contact with them in the agricultural land during the sunscreen was assessed by three statements. For ex- summer season of agriculture (from June till September). ample, “I'm sure that I can use sunscreen during At the beginning, the study aims were explained to the the working on agricultural land”. The higher score subjects and farmers who were willing to participate in represented more ASE. The Cronbach's alpha coef- the study, and the written consent form was obtained. ficient for this part was 0.71. Each questionnaire was completed within 30 min ap- (f). Action Planning (AP): AP was assessed by one proximately. Filling the questionnaire was conducted by statement; “I have planned to use sunscreen interview, and the interviews were conducted by a appropriately during the working under the trained interviewer (The first author: HP). sunlight, in specific times and locations”. The Cronbach’s alpha coefficient for this part was 0.71. 2.3 Instruments (g). Coping Planning (CP): CP was evaluated with three 2.3.1 A multi-sectional questionnaire based on HAPA was questions by considering the potential barriers, e.g., used to collect data “I have plan to use sunscreen properly during the The validity and reliability of the questionnaire was working under the sunlight at specific time, and assessed by the content validity and the Cronbach’s specific location even if others ridicule me”, “I plan alpha coefficient, respectively. For content validity, we to use sunscreen properly while working under the used the opinions of 10 specialists (experts in the field). sun at specific time and locations even if I face lack The Cronbach’s alpha will be presented when describing of time”. The Cronbach’s alpha coefficient for this each component. This questionnaire included demo- part was 0.81. graphic characteristics, motivational factors (risk percep- (h).Coping Self-Efficacy (CSE): CSE was evaluated by a tion, outcome expectation, and action self-efficacy), and person’s belief about his own ability to overcome volitional factors (action planning, coping planning, cop- the obstacles in order to fulfill specific behavior. In ing self-efficacy, self-monitoring), intention, and sun- this study, three main barriers for using sunscreen screen use as follows: (distance, time limitation, and gender restrictions) were considered. These barriers were distinguished (a). Demographic characteristics and basic data related during a preliminary study, e.g., “I believe that des- to sunscreen include age, sex, education, economic pite the distance, I can buy sunscreen in the city status, years of employment in farming, sunburn when I am buying other supplies”, “I believe that I history, and a history of sunscreen. can use sunscreen in spite of gender restriction and (b).Intention: The individual decision to use sunscreen ridicule by others”. The Cronbach’s alpha coefficient or not was assessed by two questions, e.g., “I plan to for this part was 0.81. use a sunscreen with an appropriate SPF during the (i). Self-Monitoring (SM): The control of a person working under the sunlight”, furthermore, I intend regarding the appropriate use of sunscreen was to use sunscreen, during the working under the assessed by three statements, e.g., “I constantly sunlight, also “I intend to renew it every two monitor myself for using a sunscreen with a hours”. The Cronbach’s alpha coefficient calculated suitable SPF when I work in the sun”. The for this section was 0.89. Cronbach’s alpha coefficient for this part was 0.70. (c). Risk Perception (RP): RP was assessed by five The higher score indicates more control on the questions, e.g., “When I am working under the behavior. sunlight without using sunscreen, there are (j). Sunscreen use: The behavior was examined by three possibilities of the occurrence of freckle and statements, I regularly use sunscreen during the unpleasant appearance”. Higher scores represent working on agricultural lands, “When I’m working more risk perception of ultraviolet (UV) and on agricultural lands, I renew my use of sunscreen sunburn. The Cronbach’s alpha coefficient for this every two hours”, “When I am using sunscreen, I part was 0.82. notice to its SPF (Sun Protection Factor )and its (d).Outcome Expectation (OE): The benefits of using amount”. the sunscreen was evaluated by 4 statements. For example, “Using the sunscreen during the working The instrument questions were scored based on a 4- under the sunlight makes my skin look fresher”, point Likert scale from strongly agree to strongly Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 4 of 7 disagree. The questionnaire was filled by the participants Table 1 The demographic characteristics of the (n = 177) Iranian’s paddy workers in 2018 in three occasions (at the beginning, a month later, and 2 months later). Variable N (%) Age (mean ± SD) 47.12 ± 78.66 2.4 Ethical consideration 30–40 69 (38.99) The present study was approved by the Ethics Commit- 41–50 43 (24.29) tee of Alborz University of Medical Sciences (Ethical 51–60 34 (19.21) code: IR. ABZUMS. Rec. 1397.064), dated 05.08.2018. > 60 31 (17.51) Education 2.5 Data analysis > 12 64 (36.16) All data were analyzed by using SPSS software version 12 80 (45.20) 21 and LISRELS software version 8. First, the normality < 12 33 (18.64) of the variables was evaluated using the Kolmogorov– Smirnov test. Gender The significance of correlation between variables was Male 53 (29.94) considered as the first hypothesis of path analysis. The Female 124 (70.06) intention, RP, OE, ASE, AP, CP, CSE, and SM were con- Sunburn sidered as independent variables, and sunscreen use was Yes 168 (94.92) considered as a dependent variable. In order to evaluate No 9 (5.08) the fitness of the model, the fitting index such as x2/df, root mean square error of approximation (RMSEA), Farming history (mean ± SD) 18.67 ± 11.63 comparative fit index (CFI), goodness of fit index (GFI), 5–10 68 (38.42) and normal fit index (NFI) were computed. 11–20 60 (33.90) 21–30 26 (14.69) 3 Results > 30 23 (12.99) 3.1 Characteristics of participants Sunscreen use The mean age of the participants was 47.78 ± 12.66 years, Yes 107 (60.45) which ranged from 30 to 79 years. Average years of em- ployment in agriculture were 18.67 ± 11.63. The majority No 70 (39.55) of the subjects were women (69.3%), at the age of 40–30 Economic status years (40.68%), and 45.2% of them have diploma. Most High 3 (1.70) of the people who participated in this study had 5–10 Moderate 32 (18.08) years of work experience (38.42%). Positive sunburn his- Low 142 (80.22) tory was reported by 93.9%, and history of the sunscreen use was 60.45%. The socioeconomic status of the major- ity (79.3%) was inadequate (Table 1). The mean and the standard deviation of RP, OE, and ASE in this study respectively were 14.06 ± 3.65, 8.09 ± 2.34, and 7.12 ± 2.36. Table 2 displays the mean and the Table 2 Mean and standard deviation of the construct of HAPA standard deviation of the other constructs. (n = 177) The correlation between the study variables is shown Variable Mean SD Min Max in Table 3. The strongest correlation was between CSE RP 14.06 3.65 5 20 and SM. OE 8.09 2.34 3 12 ASE 7.12 2.36 3 12 3.2 Structure model AP 2.64 0.83 1 4 Based on the final model (Fig. 2), among the variables which are influenced only in one direction, CP had the CP 6.84 2.34 3 12 most direct association with behavior and AP had the CSE 6.84 2.37 3 12 lowest association. In an indirect route, ASE and the SM 9.06 3.03 4 16 intention had the most relationship with behavior; RP, Sunscreen use 4.28 1.64 3 12 and OE together had equal and the lowest association. RP Risk Perception, OE Outcome Expectation, ASE Action Self-Efficacy, AP Only CSE had direct and indirect paths. All the path- Action Planning, CP Coping Planning, CSE Coping Self-Efficacy, ways are shown in Table 4. SM Self-monitoring Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 5 of 7 Table 3 Correlations between RP, OE, ASE, CSE, AP, CP, and SM; intention; and behavior RP OE ASE AP CP CSE SM Behav Intent RP 1 OE 0.81** 1 ASE 0.630** 0.785** 1 AP 0.647** 0.726** 0.667** CP − 0.536** 0.670** 0.721** 0.688** 1 CSE 0.545** 0.691** 0.748** 0.701** 0.902** 1 SM 0.510** 0.625** 0.729** 0.638** 0.849** 0.851** 1 Sunscreen 0.065 0.208** 0.122* 0.168 0.144 0.210** 0.130 1 Intent 0.610** 0.726** 0.792** 0.677** 0.825** 0.820** 0.813** 0.157* 1 *Significant at level 0.05; **Significant at level 0,01 RP Risk Perception, OE Outcome Expectation, ASE Action Self-Efficacy, AP Action Planning, CP Coping Planning, CSE Coping Self-Efficacy, SM Self Monitoring, Intent Intention 4 Discussion The coping SE was the only variable that had both dir- Due to the final fitted model, AP and CP were two vari- ect and indirect paths on the behavior and had the ables, which are directly affecting the behavior of paddy greatest effect on sunscreen use among farmers, which is workers. the total of the direct and indirect, based on the final fit- Consistent with the current study finding, de Vries ted model. CSE is mentioned as a personal SE to over- et al.’s study showed that AP was the strongest predictor come the barriers. During the several situations, of sunscreen use in Belgian teens [20]. Planning plays an maintaining health behavior was harder than starting it, important role in the process of changing behavior and although for starting health behavior, ASE is sufficient, communicates between the intention and the behavior. but for maintaining it, CSE is required [24]. AP is more applicable in the early stages of behavior In a Nahar et al. study, ASE had a significant relation- change, and coping planning is more applicable in the ship with protective behaviors against the sunlight in next stages of behavior change [21]. In this study, both landscapers [25]. Although, in the study of Nahar, it has the AP and CP have been assessed together, and separ- not mentioned anything about the continuation and ately assessing these variables was impossible. Although, preservation of protective behaviors, and therefore, we some studies concluded that together, those two vari- cannot compare these two elements. ables are essential in changing behavior [22], and it is Based on the final fitted model, there was no direct re- believed that CP can boost the effects of AP [23]. lationship between intention and behavior; intention Fig. 2 Final path analysis model. RISKPERC: Risk Perception; OUTCOMEE: Outcome Expectation; ACTSELF: Action Self Efficacy; COPINGSE; Coping Self-Efficacy; MONITORS: Self – Monitoring; INTEN: Intention; ACTPLAN: Action Planning; CSE: Coping Planning; SCRENUSE: Sun Screen Use Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 6 of 7 Table 4 Direct and indirect associations between HAPA variables and sunscreen use Variable Direct effect Indirect effect Total effect t value (for direct) R RP - 0.0627 0.0627 4.33 0.65 OE - 0.0627 0.0627 4.33 Action SE - 0.1875 0.1875 6.24 Coping SE 0.59 0.144 0.734 18.35 SM 0.25 - 0.25 6.54 Intent - 0.165 0.165 - AP 0.24 - 0.24 - CP 0.30 - 0.30 RP risk perception, OE outcome expectation, Action SE action self-efficacy, Coping SE coping self-efficacy, CSE coping self-efficacy, SM self-monitoring, Intent intention, AP action planning, CP coping planning goes indirectly through the CP path on behavior, which behavior, as Sniehotta believes that in addition to AC is the same as the Craciun study that was planning a and CP, we need strategies such as social support and variable between the intention and sunscreen use among SM for changing behavior [32]. students. Based on the Craciun study, having a good intention leads to behavior, when we have the appropri- 4.1 Limitations of the study ate planning to overcome the barriers [18]. Given that the current study was conducted in the agri- According to Rhodes & de Bruijn’s study, intention de- cultural season, some factors such as farmers lacking termines 46% variation in behavior [26]; but despite hav- time for interview might influence data collection cycle ing good intentions, many planners are failing to although we attempted to adjust the interview time in conduct the behavior [27]. And the intention has the accordance with the participant’s conditions. limited predictive power [28], contrary to the planned behavior model and protection motivation theory as- 5 Conclusions sumptions, which considered intention as the strongest Coping SE is the most important factor which had influ- predictor of behavior. According to Rhodes & Dickau, ence on sunscreen use, and it should be considered in declaration of the intention was an essential factor for designing interventional study related to sunscreen use behavior, but it is not enough [29]. Planning will among paddy workers. Furthermore, it should be noticed increase the possibility of converting the intention to that the motivational factors are not sufficient, but we behavior [30]. should focus on the planning factors alongside the mo- According to Osch et al.’s study, their results showed tivational factors in changing behavior, in order to pro- that the motivational factors such as RP, OE, and ASE mote sunscreen use in farmers. did not directly affect behavior [31]. In accordance with these study results, the effects of Abbreviations RP and OE were the same as in predicting sunscreen use HAPA: Health action process approach; RP: Risk perception; OE: Outcome expectation; ASE: Action self-efficacy; AP: Action planning; CP: Coping and was less than ASE. While the Craciun [18] study planning; CSE: Coping self-efficacy; SM: Self-monitoring; RMSEA: Root mean represented that RP was less important in comparison square error of approximation; CFI: Comparative fit index; GFI: Goodness of with OE and ASE in the sunscreen use among students; fit index; NFI: Normal fit index; IFI: Incremental fit indices it seems that the different results are due to the differ- Acknowledgements ences in the subject’s characteristics; younger people We sincerely thank all participants who willingly took part in this study. often have less cautious behaviors and less risk percep- tion compared with older people, and the outcome ex- Consent to publish pectation is more important to them than older ones. Not applicable Both in this study and in Craciun’s study [18], SE was more important than the other motivational factors. In Authors’ contributions HP was the main investigator, analyzed the data and involved in drafting the current studies, like Craciun’s study, ASE was more im- manuscript. LS has supervised the study; contributed to the study design portant than RP or OE. As this study was carried out for and conducted the analysis. ZM critically evaluated the manuscript, helped people who are over 30 years with a mean age of 47 years in writing process and edited the paper. All authors read and approved the final version of manuscript. old, there is no definite opinion on this subject for re- searchers, until this study was conducted Funding In this study, SM has direct influence on the behavior. This study was conducted by funding from the research deputy of Alborz This variable in fact is a facilitator of changing the University of Medical Sciences. Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 7 of 7 Availability of data and materials 16. MacPhil M, Mullen B, Sharpe L, MacCan C, Todd J. Using the health action All datasets in this study are available on reasonable request. process approach to predict and improve health outcomes in individuals with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2014;7:469–79. 17. Schwarzer R, Richert J, Kreausukon P, Remme L, Wiedemann AU, Reuter T. Ethics approval and consent to participate Translating intentions into nutrition behaviors via planning requires self- The Ethics Committee of Alborz University of Medical Sciences approved the efficacy: evidence from Thailand and Germany. Int J Psychol. 2010;45:260–8. study (ID: Abzums.Rec.1397.064), dated 05.08.2018. All participants signed the 18. Craciun C, Schüz W, Lippke S, Schwarzer R. Facilitating sunscreen use in written consent forms. 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A predictive model of the sunscreen use in the paddy workers based on the health action process approach model: a path analysis

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Abstract

Background: Skin cancer is considered as one of the most common cancers in the world. There is little information about identifying factors affecting sunscreen use among paddy workers and their protective behavior. The present study aimed to determine a predictive model of the sunscreen use in the paddy workers based on the health action process approach model (HAPA). Methods: This cross-sectional study was conducted on 177 paddy workers who engaged in agricultural work in the north of Iran in 2018. Convenience sampling methods was used. Inclusion criteria were being a farmer for 5 years, working under the sunshine more than 2 h per day, and above the age of 30 years. A multi-sectional questionnaire (intention, risk perception (RP), outcome expectation (OE), action self-efficacy (ASE), action planning (AP), coping planning (CP), coping SE (CSE), self-monitoring (SM), and sunscreen use) was used for data collection. Data were analyzed with SPSS-21 and Lisrel-8.8 software. Results: The mean age of participants was 47.78 ± 12.66 years. The final path model fitted well (comparative fit index (CFI) = 0.98, RMSEA = 0.000), only coping self-efficacy (CSE) from both direct and indirect paths had an impact on sunscreen use (B = 0.73). Among the variables which are influenced only in one direction, coping planning (CP) had the most direct influence (B = 0.30) on behavior, and action planning had the lowest influence (B = 0.24). Conclusion: Coping self-efficacy was the most important factor which had influence on the use of sunscreen, and it should be considered when designing interventional programs related to sunscreen use among paddy workers. Keywords: Skin cancer, Sunscreen, Paddy workers, HAPA, Path analysis * Correspondence: Leilisalehi88@gamil.com Research Center for Health, Safety and Environment, Alborz University of Medical Sciences, Karaj, Iran Department of Health Education & Promotion, Alborz University of Medical Sciences, Karaj, Iran Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 2 of 7 1 Introduction (RP), Outcome Expectation (OE), and Action Self- Skin cancer is considered as one of the most common Efficacy (ASE). These factors lead to the intention of cancers in the world [1], and its prevalence is increasing. behavior. After the formation of the intention, the This cancer affects one of every five American people person enters to the voluntary phase, which involves and leads to more than 10,000 deaths annually in the Action Planning (AP), Coping Planning (CP), and USA [2]. This cancer is also one of the most common Coping Self-Efficacy (CSE) [18]. types of cancers in Iran [3]. Knowing the factors that affect the behavior, their im- Ultraviolet (UV) radiation is considered as the most portance and their direct and indirect effects of each of important cause of skin cancer [4]. Concerns related the variables will help planners and educators in design- to occupational exposure to sunlight increase with the ing appropriate educational interventions. In this regard, increase of skin cancer incidence [5, 6]. In relation to Craciun [18] conducted a study on female students by this cancer, the main emphasis is on outdoor jobs [7]. using the HAPA to identify the intermediary compo- Farmers are among the most susceptible individuals nents of the use of sunscreen and showed that the plan- to sunburn risk with consequent increase of the risk ning variables just play a mediating role in the use of of skin cancer. While there is a little information sunscreen for women. This study aimed to determine about the factors affecting their performance and the predictive model of the sunscreen use for paddy their protective behavior [8], there have been some workers by using HAPA (Fig. 1). studies conducted to understand the effective factors on the use of sunscreen, and a variety of factors have 2 Methods been suggested like risk perception [9], perceived sen- 2.1 Study design and participants sitivity [10], self-efficacy [11], and outcome expect- This cross-sectional study was carried out on 177 paddy ation [12]. workers in 2018. These farmers were engaged in agricul- The health action process approach model (HAPA) is tural work in the villages of the Rood River in the north considered as a predictive model for understanding the of Iran (Gilan province). Five of the 460 villages in behavioral change mechanisms, and there are various ex- Roudsar were selected by cluster random sampling to perimental evidences to support this approach in differ- access the study subjects. The inclusion criteria were be- ent health behaviors such as healthy eating [13], ing a farmer for 5 years, working under the sunshine for vaccination [14], condom using [15], dental floss, phys- more than 2 h per day, and above the age of 30 years. ical activity, and management of diabetes [16]. Farmers who were eligible for entrance in the study were The HAPA was first proposed by Schwarzer et al. selected by the convenience sampling method. By refer- [17] and is consisted of two phases named voluntary ring to the selected villages and agricultural lands, 354 and motivational. The motivational phase focuses on farmers were surveyed in terms of inclusion criteria, and beliefs that force a person to have particular behav- eventually 177 farmers entered the study. iors and includes the factors such as Risk Perception Fig. 1 The default relationship between the variables, based on the health action process approach (HAPA) Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 3 of 7 2.2 Sample size “Using the sunscreen during the working under the For determining the sample size, usually, N = 100–150 is sunlight, will reduce sun burning and the itching”. considered the minimum sample size for conducting The higher score represented more OE. The path analysis [19]. Cronbach's alpha coefficient for this part was 0.89. For better access to the farmers, the researchers gets (e). Action Self-Efficacy (ASE): The ability to use of in contact with them in the agricultural land during the sunscreen was assessed by three statements. For ex- summer season of agriculture (from June till September). ample, “I'm sure that I can use sunscreen during At the beginning, the study aims were explained to the the working on agricultural land”. The higher score subjects and farmers who were willing to participate in represented more ASE. The Cronbach's alpha coef- the study, and the written consent form was obtained. ficient for this part was 0.71. Each questionnaire was completed within 30 min ap- (f). Action Planning (AP): AP was assessed by one proximately. Filling the questionnaire was conducted by statement; “I have planned to use sunscreen interview, and the interviews were conducted by a appropriately during the working under the trained interviewer (The first author: HP). sunlight, in specific times and locations”. The Cronbach’s alpha coefficient for this part was 0.71. 2.3 Instruments (g). Coping Planning (CP): CP was evaluated with three 2.3.1 A multi-sectional questionnaire based on HAPA was questions by considering the potential barriers, e.g., used to collect data “I have plan to use sunscreen properly during the The validity and reliability of the questionnaire was working under the sunlight at specific time, and assessed by the content validity and the Cronbach’s specific location even if others ridicule me”, “I plan alpha coefficient, respectively. For content validity, we to use sunscreen properly while working under the used the opinions of 10 specialists (experts in the field). sun at specific time and locations even if I face lack The Cronbach’s alpha will be presented when describing of time”. The Cronbach’s alpha coefficient for this each component. This questionnaire included demo- part was 0.81. graphic characteristics, motivational factors (risk percep- (h).Coping Self-Efficacy (CSE): CSE was evaluated by a tion, outcome expectation, and action self-efficacy), and person’s belief about his own ability to overcome volitional factors (action planning, coping planning, cop- the obstacles in order to fulfill specific behavior. In ing self-efficacy, self-monitoring), intention, and sun- this study, three main barriers for using sunscreen screen use as follows: (distance, time limitation, and gender restrictions) were considered. These barriers were distinguished (a). Demographic characteristics and basic data related during a preliminary study, e.g., “I believe that des- to sunscreen include age, sex, education, economic pite the distance, I can buy sunscreen in the city status, years of employment in farming, sunburn when I am buying other supplies”, “I believe that I history, and a history of sunscreen. can use sunscreen in spite of gender restriction and (b).Intention: The individual decision to use sunscreen ridicule by others”. The Cronbach’s alpha coefficient or not was assessed by two questions, e.g., “I plan to for this part was 0.81. use a sunscreen with an appropriate SPF during the (i). Self-Monitoring (SM): The control of a person working under the sunlight”, furthermore, I intend regarding the appropriate use of sunscreen was to use sunscreen, during the working under the assessed by three statements, e.g., “I constantly sunlight, also “I intend to renew it every two monitor myself for using a sunscreen with a hours”. The Cronbach’s alpha coefficient calculated suitable SPF when I work in the sun”. The for this section was 0.89. Cronbach’s alpha coefficient for this part was 0.70. (c). Risk Perception (RP): RP was assessed by five The higher score indicates more control on the questions, e.g., “When I am working under the behavior. sunlight without using sunscreen, there are (j). Sunscreen use: The behavior was examined by three possibilities of the occurrence of freckle and statements, I regularly use sunscreen during the unpleasant appearance”. Higher scores represent working on agricultural lands, “When I’m working more risk perception of ultraviolet (UV) and on agricultural lands, I renew my use of sunscreen sunburn. The Cronbach’s alpha coefficient for this every two hours”, “When I am using sunscreen, I part was 0.82. notice to its SPF (Sun Protection Factor )and its (d).Outcome Expectation (OE): The benefits of using amount”. the sunscreen was evaluated by 4 statements. For example, “Using the sunscreen during the working The instrument questions were scored based on a 4- under the sunlight makes my skin look fresher”, point Likert scale from strongly agree to strongly Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 4 of 7 disagree. The questionnaire was filled by the participants Table 1 The demographic characteristics of the (n = 177) Iranian’s paddy workers in 2018 in three occasions (at the beginning, a month later, and 2 months later). Variable N (%) Age (mean ± SD) 47.12 ± 78.66 2.4 Ethical consideration 30–40 69 (38.99) The present study was approved by the Ethics Commit- 41–50 43 (24.29) tee of Alborz University of Medical Sciences (Ethical 51–60 34 (19.21) code: IR. ABZUMS. Rec. 1397.064), dated 05.08.2018. > 60 31 (17.51) Education 2.5 Data analysis > 12 64 (36.16) All data were analyzed by using SPSS software version 12 80 (45.20) 21 and LISRELS software version 8. First, the normality < 12 33 (18.64) of the variables was evaluated using the Kolmogorov– Smirnov test. Gender The significance of correlation between variables was Male 53 (29.94) considered as the first hypothesis of path analysis. The Female 124 (70.06) intention, RP, OE, ASE, AP, CP, CSE, and SM were con- Sunburn sidered as independent variables, and sunscreen use was Yes 168 (94.92) considered as a dependent variable. In order to evaluate No 9 (5.08) the fitness of the model, the fitting index such as x2/df, root mean square error of approximation (RMSEA), Farming history (mean ± SD) 18.67 ± 11.63 comparative fit index (CFI), goodness of fit index (GFI), 5–10 68 (38.42) and normal fit index (NFI) were computed. 11–20 60 (33.90) 21–30 26 (14.69) 3 Results > 30 23 (12.99) 3.1 Characteristics of participants Sunscreen use The mean age of the participants was 47.78 ± 12.66 years, Yes 107 (60.45) which ranged from 30 to 79 years. Average years of em- ployment in agriculture were 18.67 ± 11.63. The majority No 70 (39.55) of the subjects were women (69.3%), at the age of 40–30 Economic status years (40.68%), and 45.2% of them have diploma. Most High 3 (1.70) of the people who participated in this study had 5–10 Moderate 32 (18.08) years of work experience (38.42%). Positive sunburn his- Low 142 (80.22) tory was reported by 93.9%, and history of the sunscreen use was 60.45%. The socioeconomic status of the major- ity (79.3%) was inadequate (Table 1). The mean and the standard deviation of RP, OE, and ASE in this study respectively were 14.06 ± 3.65, 8.09 ± 2.34, and 7.12 ± 2.36. Table 2 displays the mean and the Table 2 Mean and standard deviation of the construct of HAPA standard deviation of the other constructs. (n = 177) The correlation between the study variables is shown Variable Mean SD Min Max in Table 3. The strongest correlation was between CSE RP 14.06 3.65 5 20 and SM. OE 8.09 2.34 3 12 ASE 7.12 2.36 3 12 3.2 Structure model AP 2.64 0.83 1 4 Based on the final model (Fig. 2), among the variables which are influenced only in one direction, CP had the CP 6.84 2.34 3 12 most direct association with behavior and AP had the CSE 6.84 2.37 3 12 lowest association. In an indirect route, ASE and the SM 9.06 3.03 4 16 intention had the most relationship with behavior; RP, Sunscreen use 4.28 1.64 3 12 and OE together had equal and the lowest association. RP Risk Perception, OE Outcome Expectation, ASE Action Self-Efficacy, AP Only CSE had direct and indirect paths. All the path- Action Planning, CP Coping Planning, CSE Coping Self-Efficacy, ways are shown in Table 4. SM Self-monitoring Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 5 of 7 Table 3 Correlations between RP, OE, ASE, CSE, AP, CP, and SM; intention; and behavior RP OE ASE AP CP CSE SM Behav Intent RP 1 OE 0.81** 1 ASE 0.630** 0.785** 1 AP 0.647** 0.726** 0.667** CP − 0.536** 0.670** 0.721** 0.688** 1 CSE 0.545** 0.691** 0.748** 0.701** 0.902** 1 SM 0.510** 0.625** 0.729** 0.638** 0.849** 0.851** 1 Sunscreen 0.065 0.208** 0.122* 0.168 0.144 0.210** 0.130 1 Intent 0.610** 0.726** 0.792** 0.677** 0.825** 0.820** 0.813** 0.157* 1 *Significant at level 0.05; **Significant at level 0,01 RP Risk Perception, OE Outcome Expectation, ASE Action Self-Efficacy, AP Action Planning, CP Coping Planning, CSE Coping Self-Efficacy, SM Self Monitoring, Intent Intention 4 Discussion The coping SE was the only variable that had both dir- Due to the final fitted model, AP and CP were two vari- ect and indirect paths on the behavior and had the ables, which are directly affecting the behavior of paddy greatest effect on sunscreen use among farmers, which is workers. the total of the direct and indirect, based on the final fit- Consistent with the current study finding, de Vries ted model. CSE is mentioned as a personal SE to over- et al.’s study showed that AP was the strongest predictor come the barriers. During the several situations, of sunscreen use in Belgian teens [20]. Planning plays an maintaining health behavior was harder than starting it, important role in the process of changing behavior and although for starting health behavior, ASE is sufficient, communicates between the intention and the behavior. but for maintaining it, CSE is required [24]. AP is more applicable in the early stages of behavior In a Nahar et al. study, ASE had a significant relation- change, and coping planning is more applicable in the ship with protective behaviors against the sunlight in next stages of behavior change [21]. In this study, both landscapers [25]. Although, in the study of Nahar, it has the AP and CP have been assessed together, and separ- not mentioned anything about the continuation and ately assessing these variables was impossible. Although, preservation of protective behaviors, and therefore, we some studies concluded that together, those two vari- cannot compare these two elements. ables are essential in changing behavior [22], and it is Based on the final fitted model, there was no direct re- believed that CP can boost the effects of AP [23]. lationship between intention and behavior; intention Fig. 2 Final path analysis model. RISKPERC: Risk Perception; OUTCOMEE: Outcome Expectation; ACTSELF: Action Self Efficacy; COPINGSE; Coping Self-Efficacy; MONITORS: Self – Monitoring; INTEN: Intention; ACTPLAN: Action Planning; CSE: Coping Planning; SCRENUSE: Sun Screen Use Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 6 of 7 Table 4 Direct and indirect associations between HAPA variables and sunscreen use Variable Direct effect Indirect effect Total effect t value (for direct) R RP - 0.0627 0.0627 4.33 0.65 OE - 0.0627 0.0627 4.33 Action SE - 0.1875 0.1875 6.24 Coping SE 0.59 0.144 0.734 18.35 SM 0.25 - 0.25 6.54 Intent - 0.165 0.165 - AP 0.24 - 0.24 - CP 0.30 - 0.30 RP risk perception, OE outcome expectation, Action SE action self-efficacy, Coping SE coping self-efficacy, CSE coping self-efficacy, SM self-monitoring, Intent intention, AP action planning, CP coping planning goes indirectly through the CP path on behavior, which behavior, as Sniehotta believes that in addition to AC is the same as the Craciun study that was planning a and CP, we need strategies such as social support and variable between the intention and sunscreen use among SM for changing behavior [32]. students. Based on the Craciun study, having a good intention leads to behavior, when we have the appropri- 4.1 Limitations of the study ate planning to overcome the barriers [18]. Given that the current study was conducted in the agri- According to Rhodes & de Bruijn’s study, intention de- cultural season, some factors such as farmers lacking termines 46% variation in behavior [26]; but despite hav- time for interview might influence data collection cycle ing good intentions, many planners are failing to although we attempted to adjust the interview time in conduct the behavior [27]. And the intention has the accordance with the participant’s conditions. limited predictive power [28], contrary to the planned behavior model and protection motivation theory as- 5 Conclusions sumptions, which considered intention as the strongest Coping SE is the most important factor which had influ- predictor of behavior. According to Rhodes & Dickau, ence on sunscreen use, and it should be considered in declaration of the intention was an essential factor for designing interventional study related to sunscreen use behavior, but it is not enough [29]. Planning will among paddy workers. Furthermore, it should be noticed increase the possibility of converting the intention to that the motivational factors are not sufficient, but we behavior [30]. should focus on the planning factors alongside the mo- According to Osch et al.’s study, their results showed tivational factors in changing behavior, in order to pro- that the motivational factors such as RP, OE, and ASE mote sunscreen use in farmers. did not directly affect behavior [31]. In accordance with these study results, the effects of Abbreviations RP and OE were the same as in predicting sunscreen use HAPA: Health action process approach; RP: Risk perception; OE: Outcome expectation; ASE: Action self-efficacy; AP: Action planning; CP: Coping and was less than ASE. While the Craciun [18] study planning; CSE: Coping self-efficacy; SM: Self-monitoring; RMSEA: Root mean represented that RP was less important in comparison square error of approximation; CFI: Comparative fit index; GFI: Goodness of with OE and ASE in the sunscreen use among students; fit index; NFI: Normal fit index; IFI: Incremental fit indices it seems that the different results are due to the differ- Acknowledgements ences in the subject’s characteristics; younger people We sincerely thank all participants who willingly took part in this study. often have less cautious behaviors and less risk percep- tion compared with older people, and the outcome ex- Consent to publish pectation is more important to them than older ones. Not applicable Both in this study and in Craciun’s study [18], SE was more important than the other motivational factors. In Authors’ contributions HP was the main investigator, analyzed the data and involved in drafting the current studies, like Craciun’s study, ASE was more im- manuscript. LS has supervised the study; contributed to the study design portant than RP or OE. As this study was carried out for and conducted the analysis. ZM critically evaluated the manuscript, helped people who are over 30 years with a mean age of 47 years in writing process and edited the paper. All authors read and approved the final version of manuscript. old, there is no definite opinion on this subject for re- searchers, until this study was conducted Funding In this study, SM has direct influence on the behavior. This study was conducted by funding from the research deputy of Alborz This variable in fact is a facilitator of changing the University of Medical Sciences. Panahi et al. Journal of the Egyptian Public Health Association (2020) 95:23 Page 7 of 7 Availability of data and materials 16. 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