- Research
- Open access
- Published:
The strongest predictors of compliance with health protocols among marketers and guilds based on the transtheoretical model
BMC Public Health volume 24, Article number: 1892 (2024)
Abstract
Background
Global communication, an integral part of modern life, increases the risk of transmitting infectious diseases to individuals. Based on the transtheoretical model (TTM), this study aimed to identify the most effective factors in adherence to health protocols among marketers and guilds.
Methods
This cross-sectional study was conducted among 400 market sellers and guilds of Ardabil City, Iran, in 2023. The TTM questionnaire was distributed among the participants which included four sub-constructs: (1) stages of change, (2) process of change, (3) self-efficacy, and (4) decisional balance. The data were analyzed using SPSS version 20. One-way ANOVA and linear regression tests were employed to evaluate the prediction of effective factors of the stage transition.
Results
Most participants (63.5%) were between 21 and 40. Most participants (65.5%) were in the passive stages of change (precontemplation, contemplation, and preparation). Pros (β = 0.133, P < 0.001) and behavioral processes of change (β = 0.058, P < 0.001) were the strongest predictors of the stage of change or improvement of stages of participants’ willingness to follow health protocols.
Conclusion
A correct understanding of the stages of behavior change can strengthen strategies for promoting healthy behaviors. Also, understanding the benefits of healthy behavior means compliance with health protocols and behavioral processes such as stimulus control, reinforcement management, counterconditioning, and self-liberation, along with high self-efficacy, have an impact on improving the stages of behavior change.
Introduction
Although the World Health Organization has declared that COVID-19 is no longer a “global health emergency,” it emphasizes that it is still a global health threat [1]. A pandemic that affected various components of the worldwide community, including public health, economics, education, and mental health, resulted in more than 7 million deaths [2]. In terms of the number of patients and deaths in the Eastern Mediterranean region, Iran was the leader of the countries severely affected by COVID-19 [3, 4].
During the coronavirus pandemic, healthcare systems in all countries were severely affected. Governments prescribed quarantines and communication restrictions at various intervals, either helpful or ineffective, depending on the circumstances [5]. With the out-of-control spread of COVID-19 and numerous problems in the health service system, individual preventive measures have become one of the most effective ways to prevent the spread of the coronavirus in the world [6]. Personal protective measures (such as wearing a face mask, washing hands, and personal hygiene) and social distancing were among the preventive protocols that helped reduce the risk of infection and control the spread of the disease [7].
Identifying the factors affecting compliance with health protocols for the prevention of COVID-19 is essential for any planning and intervention to maintain community health [8]. Studies conducted during the recent epidemic in Iran have examined a wide range of health issues, including risk perception and risk communication related to the preventive behavior of COVID-19 [7, 9,10,11].
Various studies using models and theories of behavioral sciences have been conducted worldwide during the COVID-19 pandemic, including the health belief model (HBM), the theory of planned behavior (TPB), the theory of reasoned action, social cognition theory, socio-ecological model, extended parallel process model, and transtheoretical model (TTM). Meanwhile, the HBM and the TPB have been the most frequent, and few studies have been conducted with TTM [12].
One of the main issues neglected in the studies is determining the stages of behavior change in compliance with health protocols and the predictors of stage improvement, such as processes of change and decisional balance. In health education, the fundamental principle is determining the stages of change individuals undergo to tailor the training and achieve optimal results. The transtheoretical model (TTM) consists of four sub-constructs: stages of change, processes of change (cognitive-behavioral), decision-making balance, and self-efficacy. It first assesses the stage of change in individuals’ health behavior and then identifies which sub-construct effectively promotes or reduces the stages of change. The stages of change have two subgroups: the passive stages of change (precontemplation, Contemplation, and Preparation), in which changes have not yet occurred, and the active stages of change (Action and Maintenance), in which behavioral changes have occurred [13,14,15,16]. Kamran et al. (2023) found that all dimensions of health-promoting behaviors had a significant relationship with the stages of behavior change, decisional balance, and self-efficacy based on TTM in students [17]. In the study of Nishimoto et al. (2023), the results showed that about a quarter of the participants were in the active stages (action and maintenance) of changing healthy behavior and physical activity during COVID-19 [18]. The results of an online survey in the United States also showed that there are reliable and valid measures of TTM constructs to understand the motivation to receive the Covid-19 vaccine [19].
Although there is little evidence of the use of TTM for preventive behaviors against COVID-19, considering the excellent previous records of this model in predicting health behaviors [20,21,22]. This study aimed to identify the most effective factors in promoting adherence to health protocols among marketers and guilds of Ardabil City.
Method
The study setting and participants
This cross-sectional study was conducted among the market sellers and guilds of Ardabil City in 2023. Due to the high volume of physical contact in the market and the possibility of transmission of infectious diseases, especially COVID-19, marketers and guilds were selected as the target group in this study. According to statistics, there are 14,000 licensed guild units in this city. Considering the heterogeneity of the statistical population, the number of samples was determined using Cochran’s formula. The required sample size was 375, considering d = 0.05 and Z = 1.96.
Considering a 10% margin of error, the estimated number of participants required for the study was 400. A random cluster sampling method was used, and the city’s main markets were selected as the primary clusters. Sampling was then conducted from each cluster using a random number table. The inclusion criteria were being active as a marketer, having an economic activity license, the shop being active, and the desire to participate in the research. The exclusion criteria included the participants’ unwillingness to participate in the study. Data were collected using a questionnaire that the researcher designed. The data collection process was done after explaining the study’s objectives and obtaining informed consent from the patients. According to paragraphs 7, 25, and 26 of the Helsinki Declaration, to respect the research units, it was not necessary to write the name and surname of the research units when completing the questionnaire. Four hundred people participated in this study. Among the participants, 202 (50.5%) were single, and 198 (49.5%) were married. Also, 316 people (79%) lived in urban areas and 84 (21%) lived in rural areas. In terms of education level, 76 people (19%) had high school, 132 people (33%) had a diploma, 136 people (34%) had an associate’s and bachelor’s degree, and 56 people (14%) had a master’s degree.
Measurements and scoring
The questionnaire consisted of three parts: 6 questions about demographic variables, five questions on health behaviors during COVID-19, and a TTM researcher-made scale. The TTM scale in the present study had four sub-constructs: (1) stages of change, (2) processes of change, (3) self-efficacy, and (4) decisional balance. Stages of change were assessed using five questions to determine readiness and measure people’s progress toward change regarding adopting preventive health protocols for COVID-19 (Precontemplation, Contemplation, Preparation, Action, and Maintenance). These questions were evaluated using a two-point scale (yes-no). For example, to assess the precontemplation stage, I do not follow the preventive protocols of COVID-19 and do not think about following them. To evaluate the action stage, I have been following the health protocols for preventing COVID-19 for less than six months. The process of change was assessed using 30 questions that were rated on a five-point Likert scale, ranging from “never” (score of 1) to “always” (score of 5). These questions assessed how a person’s cognition and behavior regarding past experiences in the previous month could influence their adherence to health protocols for preventing COVID-19. The process of change includes ten processes, for each of which three questions were designed. We also evaluated self-efficacy using six questions that gauged an individual’s ability to overcome potential obstacles and resist the temptation to neglect health protocols for preventing COVID-19. The assessment was conducted on a five-point Likert scale, ranging from “1” (very low) to “5” (very high). The decisional balance was evaluated through 10 questions that explored an individual’s decision-making process regarding adopting preventive health protocols for COVID-19. These questions illustrated how a person decides to use or abstain from preventive health measures in various situations. The decisional balance includes two sub-structures: benefits (Pros) and disadvantages (Cons); each was evaluated with five questions. Responses were rated on a five-point Likert scale, ranging from “not very important” with a score of 1 to “very important” with a score of 5 [23,24,25].
Questionnaire validations were conducted using the Content Validation Index (CVI) and Content Validation Ratio (CVR). The questionnaire was administered to a panel of experts comprising ten health education specialists, three infectious disease specialists, and two epidemiologists. The CVI scores for the stages of change, process of change, self-efficacy, and decisional balance were 87%, 96%, 88%, and 90%, respectively. The CVR scores for these dimensions were 88%, 90%, 80%, and 78%, respectively. In addition, using Cronbach’s alpha coefficient, the internal consistency of the self-efficacy subscales, processes of change, and decisional balance was confirmed with values of 0.891, 0.732, and 0.701.
Data analysis
The data were analyzed using SPSS version 20. Descriptive statistics, including mean and standard deviation tests, were employed to examine the demographic characteristics and scores derived from the model’s constructs. An analysis of variance test was conducted to assess the relationship between the model variables and demographic factors. We used linear regression to determine predictors of the stage of change as a dependent variable, where self-efficacy, processes of change (behavioral Process of change and experiential process of change), and decisional balance (Pros and Cons) were independent variables. The histogram and its results confirmed the normality of the data. The scatter plot also confirmed a correlation and linear relationship between the dependent and independent variables. Durbin Watson’s (DW) statistic showed no autocorrelation between the data (DW = 1.865).
Result
In this study, 400 marketers from Ardabil city with a mean age of 32.02 ± 6.39 years participated. Half of the people have used a mask for at least a year to prevent COVID-19, and most people (276, 69%) have followed the pattern of hand washing (20–60 s). Table 1 provides more details on preventive behaviors of COVID-19.
The study’s results showed that the majority of the participants did not adhere to the health protocols for the prevention of COVID-19. As shown in Table 2, the majority of the participants (65.5%) were in the passive stages of behavior change (precontemplation, contemplation, and preparation), and only 34.5% were in the active stages, including action and maintenance.
The Pearson correlation coefficient results showed that the transtheoretical model’s sub-constructs are highly correlated. Pros were positively related to the stages of change, while Cons had a negative but non-significant relationship with stages of behavior change. (See Table 3)
The mean scores of the process of change showed that the behavioral process of change, such as stimulus control, self-liberation, and reinforcement management, played a greater role in keeping samples in the highest level of compliance with health protocols. The post hoc test showed that the mean scores of the process of change in the maintenance and action stages were higher than all the passive stages. (See Table 4)
The results of linear regression showed that Pros (β = 0.133, P < 0.001), behavioral processes of change (β = 0.058, P < 0.001), experimental processes of change (β = 0.053, P < 0.001), and self-efficacy (β = 0.007, P < 0.001) were the significant predictors of improvement of stage of change to follow health protocols. It should be noted that Cons did not play an important role in the regression model (See Table 5).
Discussion
This study aimed to determine the factors that affect the stages of change or adherence to health protocols among marketers and guilds based on the transtheoretical model (TTM). Findings revealed that most participants were in the inactive stages (pre-contemplation, contemplation, and preparation), while only 34.5% of the samples were in the active stages (action and maintenance) of adhering to the health protocols for preventing COVID-19. We did not find a study that similarly addressed the stages of behavior change in compliance with health protocols during the COVID-19 pandemic. However, some other studies show similar results in the distribution of people in active and passive stages of behavior change. For example, Kamran et al. (2023) reported that the distribution of students in the active phases of physical activity and healthy eating during COVID-19 was 38.3% and 45.4%, respectively [17]. A study in Japan has indicated that more than 60% of people are in the completely inactive stages of pre-contemplation and contemplation about increasing physical activity during the COVID-19 pandemic [18]. In a systematic review based on the results of two studies, Anagaw et al. evaluated TTM as a successful framework for predicting health promotion behaviors and vaccination against COVID-19. Due to the limited evidence, unfortunately, they also did not provide more information about the application and achievements of TTM in the COVID-19 pandemic and preventive behaviors [12].
The basic point is to understand the necessity and importance of determining the stages of behavior change. This study’s results show that most participants did not follow preventive health protocols. Those 65% in the three inactive stages (pre-thinking) need targeted educational intervention to become aware of the subject, receive knowledge, and be stimulated to change behavior. Prochaska believes that change means phenomena that occur over time; therefore, determining the stages of behavior change based on specific times is necessary to develop targeted educational interventions [26].
However, what causes people to move through different stages is a set of factors such as processes of change, decisional balance, and self-efficacy. In the present study, the mean scores of cognitive and behavioral processes of change in the maintenance and action stages were higher, indicating that participants successfully overcame objections to compliance with health protocols (Cons). These findings are consistent with the results reported in a study conducted by Wollesen et al. [27]. Prochaska considers processes of change as the driving force for people to climb the stages of change [26].
In the present study, it is also evident that people in higher stages have obtained higher scores in behavioral and experimental processes. Therefore, to upgrade people from precontemplation and contemplation stages to more active stages, interventions should focus on processes of change. Interventional studies based on TTM have well shown the impact of changes in processes on the promotion of change stages [28,29,30].
We found that all sub-constructs within the transtheoretical model had a significant relationship with each other. Notably, the Cons sub-construct of decisional balance (representing opinions against the decision to follow health protocols) did not demonstrate a substantial relationship with the stages of change. These findings are consistent with the results obtained in studies conducted by Sacco et al. [31] and Khani Jeihooni et al. [32]. The balance of deciding to perform a healthy behavior is achieved when a person overcomes negative thoughts by overcoming negative feelings and correctly understanding risk.
Self-efficacy was also one of the factors affecting the stages of behavior change, although its effect was weaker than the behavioral processes, Pros, and experimental processes. In a study by Kordi-Kalaki et al. (2022), self-efficacy directly affected performing recommended preventive behaviors for COVID-19 in Iranian adults [33].
Using an extended parallel process model, Yoon et al. (2022) showed that self-efficacy has strong effects on personal hygiene behaviors and social distancing to prevent COVID-19 [34].
Kamran et al. (2023) showed that the self-efficacy score related to physical activity and healthy nutrition in precontemplators was significantly lower than in the active stages (action and maintenance). This study shows that having more self-efficacy is an effective factor in placing people in higher stages of change and adopting health-promoting behaviors [17].
Despite the numerous studies on the effect of self-efficacy on preventive behaviors, Rui et al. (2021) in China concluded that self-efficacy did not have a positive effect on preventive behaviors against COVID-19. They attributed this lack of association to the non-specific measurement scale of their study [35].
A proper preparedness plan is very important for the community’s well-being during crises and disasters. Without such planning, rumors can prevail and overshadow positive thoughts. Ultimately, this can reduce the overall perception of risk in the community and potentially lead to non-compliance with health plans during disasters. [11] This result is based on many studies that have confirmed the effective role of risk perception and risk communication in promoting preventive behaviors against COVID-19 [36,37,38,39,40].
Limitation
The reliance on a self-report questionnaire imposes constraints on the external validity of this study and may introduce bias in the responses from the research samples. Additionally, the extensive number of questions in Prochaska’s model served as another limitation in this study, as participants during the pandemic showed less interest in responding to lengthy questionnaires.
Conclusion
The results of this study showed that most marketers in Ardabil City are in the passive stages of observing health protocols. Therefore, due to the many interactions and communications this group has with people, it is necessary to design and implement educational interventions to promote preventive behaviors in them. These interventions can benefit from the effective factors identified as significant in this study, such as behavioral and experimental processes and self-efficacy. Meanwhile, marketers’ risk perception can be considered by improving their understanding of the benefits of following health protocols and overcoming the disadvantages.
Data availability
No datasets were generated or analysed during the current study.
References
Wise J. Covid-19: WHO declares end of global health emergency. British Medical Journal Publishing Group; 2023.
Sarker R, Roknuzzaman A, Hossain MJ, Bhuiyan MA, Islam MR. The WHO declares COVID-19 is no longer a public health emergency of international concern: benefits, challenges, and necessary precautions to come back to normal life. Int J Surg. 2023;109(9):2851–2.
Ariapooran S, Khezeli M. Symptoms of anxiety disorders in Iranian adolescents with hearing loss during the COVID-19 pandemic. BMC Psychiatry. 2021;21:1–5.
Ariapooran S, Ahadi B, Khezeli M. Depression, anxiety, and suicidal ideation in nurses with and without symptoms of secondary traumatic stress during the COVID-19 outbreak. Arch Psychiatr Nurs. 2022;37:76–81.
Dirani KM, Abadi M, Alizadeh A, Barhate B, Garza RC, Gunasekara N, et al. Leadership competencies and the essential role of human resource development in times of crisis: a response to Covid-19 pandemic. Hum Resource Dev Int. 2020;23(4):380–94.
Mahmoodpour-Azari M, Rezaei S, Badiee N, Hajizadeh M, Mohammadi A, Kazemi-Karyani A, et al. The COVID-19 pandemic and healthcare utilization in Iran: evidence from an interrupted time series analysis. Osong Public Health Res Perspect. 2023;14(3):180.
Rezaei M, Gilan NR, Almasi A, Khezeli M, Nazar FJ, Shushtari ZJ, et al. The role of risk perception, risk communication, and demographic factors in COVID-19 preventive behaviors: an online survey in Iran. Osong Public Health Res Perspect. 2022;13(4):282.
Yoosefi Lebni J, Pavee S, Saki M, Ziapour A, Ahmadi A, Khezeli M. Determinants of observing health protocols related to preventing COVID-19 in adult women: a qualitative study in Iran. Front Public Health. 2022;10:969658.
Khezeli M, Tavan A, Narimani S, Hoseini V, Hosseinzadeh EZ, Motamedi P. Risk perception and avoidance of preventive behavior on the COVID-19 among cancer patients. Health Sci Rep. 2023;6(7):e1401.
Heydari ST, Zarei L, Sadati AK, Moradi N, Akbari M, Mehralian G, Lankarani KB. The effect of risk communication on preventive and protective behaviours during the COVID-19 outbreak: mediating role of risk perception. BMC Public Health. 2021;21:1–11.
Narimani S, Mozaffari N, Soola AH, Nasiri R, Omidi T, Sedri N, Tavan A. Risk communication and risk perception along with its influencing factors in Covid-19 disease: focusing on the extended parallel process model. Int J Disaster Risk Reduct. 2023;86:103547.
Anagaw TF, Tiruneh MG, Fenta ET. Application of behavioral change theory and models on COVID-19 preventive behaviors, worldwide: a systematic review. SAGE Open Med. 2023;11:20503121231159750.
Hassani L, Pournarani R, Aghamolaei T, Mohseni S, Narimani S. Breakfast Eating in Elementary School students in Jiroft, Iran: an application of Transtheoretical Model. Progress Psychiatry Behav Sci. 2023;17(1).
Hashemzadeh M, Rahimi A, Zare-Farashbandi F, Alavi-Naeini AM, Daei A. Transtheoretical model of health behavioral change: a systematic review. Iran J Nurs Midwifery Res. 2019;24(2):83.
Mohajeri M, Narimani S, Shahbazzadeh F, Bahrampanah S, Ghaderi V. Applying the trans-theoretical model to determine the mediating effect self-efficacy in breakfast consumption among children. Nutr Food Sci. 2022;52(3):523–33.
Mohajeri M, Narimani S, Shahbazzadeh F, Bahrampanah S, Qaderi V. Assessing readiness to change in regular breakfast consumption among elementary students. J Educ Health Promotion. 2021;10(1).
Kamran A, Aliakbari P, Nasimi Doost Azgomi R, Naeim M. Action status and willingness to change health-promoting behaviors during the COVID-19 pandemic among elementary school children: a study based on Prochaska’s stages of behavior change theory (TTM). BMC Public Health. 2023;23(1):248.
Nishimoto D, Kodama S, Nishio I, Makizako H. Association between the perception of Behavior Change and Habitual Exercise during COVID-19: a cross-sectional online survey in Japan. Int J Environ Res Public Health. 2022;20(1):356.
Sacco A, Robbins ML, Paiva AL, Monahan K, Lindsey H, Reyes C, Rusnock A. Measuring motivation for COVID-19 vaccination: an application of the Transtheoretical Model. Am J Health Promotion. 2023;37(8):1109–20.
Nakabayashi J, Melo GR-i, Toral N. Transtheoretical model-based nutritional interventions in adolescents: a systematic review. BMC Public Health. 2020;20:1–14.
Sjattar EL, Arafat R. Transtheoretical model on the self-care behavior of hypertension patients: a systematic review. J Health Res. 2021;36(5):847–58.
Imeri H, Toth J, Arnold A, Barnard M. Use of the transtheoretical model in medication adherence: a systematic review. Res Social Administrative Pharm. 2022;18(5):2778–85.
Casais B. Conceptualizing an Omnichannel Approach for Social Marketing under the assumptions of the Transtheoretical Model of Change. Social Mark Q. 2023;29(3):208–24.
Hunter H. The transtheoretical model of behavior change: implications for social work practice. J Hum Behav Social Environ. 2023:1–15.
Sheng J, Shi P, Sun J, Feng X. Predictors of Physical Activity Behavior Transitions in Children and Adolescents: A Systematic Review Based on a Transtheoretical Model. Journal of Healthcare Engineering. 2023;2023.
Prochaska JO, Velicer WF. The transtheoretical model of health behavior change. Am J Health Promotion. 1997;12(1):38–48.
Wollesen B, Wildbredt A, van Schooten KS, Lim ML, Delbaere K. The effects of cognitive-motor training interventions on executive functions in older people: a systematic review and meta-analysis. Eur Rev Aging Phys Activity. 2020;17(1):1–22.
Abdelsalam N, Said M. Effect of transtheoretical model based intervention program on cigarette smoking cessation among technical secondary school male students in Zagazig City. Egypt Family Med J. 2018;2(2):32–45.
Pirzadeh A, Zamani F, Khoshali M, Kelishadi R. Web-based intervention on the promotion of physical activity among Iranian youth using the transtheoretical model. J Educ Health Promotion. 2020;9.
Fallahipour L, Nazari M, Karimi M, Zare E. Effectiveness of Educational Intervention Based on Transtheoretical Model on Physical Activity and Menopausal Symptoms. BioMed Res Int. 2022;2022.
Sacco A, Robbins ML, Paiva AL, Monahan K, Lindsey H, Reyes C, Rusnock A. Measuring motivation for COVID-19 vaccination: an application of the Transtheoretical Model. Am J Health Promotion. 2023:08901171231197899.
Khani Jeihooni A, Gholampour Y, Shokrpour N. Application of trans-theoretical model for smoking cessation in sample of Iranian men. J Subst Use. 2019;24(4):414–9.
Kordi-Kalaki F, Dehdari T, Abolghasemi J. Determinants of COVID-19 preventive health behaviors in Iranian adults based on extended parallel process model. Sci Rep. 2023;13(1):14416.
Yoon H, You M, Shon C. An application of the extended parallel process model to protective behaviors against COVID-19 in South Korea. PLoS ONE. 2022;17(3):e0261132.
Rui JR, Yang K, Chen J. Information sources, risk perception, and efficacy appraisal’s prediction of engagement in protective behaviors against COVID-19 in China: repeated cross-sectional survey. JMIR Hum Factors. 2021;8(1):e23232.
Samadipour E, Ghardashi F. Factors influencing iranians’ risk perception of Covid-19. J Mil Med. 2020;22(2):122–9.
Samadipour E, Ghardashi F, Aghaei N. Evaluation of risk perception of COVID-19 disease: a community-based participatory study. Disaster Med Pub Health Prep. 2023;17:e10.
Venkateshan M, Mishra P, Mohanty S, Shetty AP, Gomathi B, Das PK et al. Risk perception and preventive practice during the COVID-19 pandemic in the General Population. Cureus. 2023;15(3).
Lee YH, Heo H-H, Noh H, Jang DH, Choi Y-G, Jang WM, Lee JY. The association between the risk perceptions of COVID-19, trust in the government, political ideologies, and socio-demographic factors: a year-long cross-sectional study in South Korea. PLoS ONE. 2023;18(6):e0280779.
Nouri M, Hanifi N, Babaeivahed N, Mortaghy Ghasemy M. COVID-19 risk perception and its related factors and outcomes in vulnerable groups: a systematic review. Prev Care Nurs Midwifery J. 2023;13(1):1–13.
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
Fardin Shahbazzadeh, Nadia Sedri, and Sama Sabahi are responsible for the study design and data gathering. Sajjad Narimani and Asghar Tavan did the analyses and were responsible for data interpretation. Sajjad Narimani and Shandiz Moslehi conducted the drafting of the manuscript. Sajjad Narimani and Shandiz Moslehi and Asghar Tavan revised the draft of manuscript. All authors have read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethical approval and consent to participate
The Ethic Committee of Ardabil University of Medical Sciences (IR.ARUMS.REC.1400.288) granted ethical approval. This study was conducted after obtaining informed verbal consent from the participants.
Ethical guidelines
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Moslehi, S., Tavan, A., Narimani, S. et al. The strongest predictors of compliance with health protocols among marketers and guilds based on the transtheoretical model. BMC Public Health 24, 1892 (2024). https://doi.org/10.1186/s12889-024-19386-w
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s12889-024-19386-w