Abstract
Objective:
This systematic review aimed to assess the global application of behavioral change theory and models on COVID-19 preventive behaviors.
Methods:
This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedure. Databases such as PubMed/MIDLINE, Web of Science, Scopus, EMB ASE, World Health Organization libraries, and Google Scholar were used to search all published articles in the area of application of behavioral change theory and model on COVID-19 preventive behavior until October 1, 2022. Studies published in another language other than English were excluded. Two independent reviewers did the article selection and quality check. A third reviewer asked if any disagreement were found.
Result:
Seventeen thousand four hundred thirty-six total articles were retrieved from all sources after the removal of duplicated articles and those not evaluating the outcome of interest were excluded. Finally, 82 articles done using behavioral change theory and model on COVID-19 preventive behaviors were included. The health belief model (HBM) and theory of planned behavior (TPB) were most commonly used in COVID-19 preventive behaviors. The constructs of most behavioral theories and models were significantly associated with COVID-19 preventive behaviors such as hand washing, face mask use, vaccine uptake, social isolation, self-quarantine, social distance, and use of sanitizers.
Conclusion:
This systematic review summarizes comprehensive evidence on the application of behavioral change theory and model on COVID-19 preventive behaviors globally. A total of seven behavioral change theories and models were included. The HBM and TPBs were most commonly used for COVID-19 preventive behaviors. Therefore, the application of behavioral change theory and models is recommended for developing behavioral change interventional strategies.
Introduction
A cluster of pneumonia cases in Wuhan, China, near the end of 2019 was caused to a severe acute respiratory syndrome coronavirus 2, which then spread like wildfire. 1 The amount and length of exposure, the implementation of preventative measures, and individual characteristics all affect the risk of COVID-19 transfer from one person to another. 2 COVID-19 is transmitting through respiratory droplets, close contact with infected individuals, secretions, saliva, and respiratory droplets produced when an infected person talks, sneezes, or coughs. A reverse transcription polymerase chain reaction test is used to detect the virus. 3
Behavioral change theories and models are a set of interrelated concepts, definitions, and prepositions that describe, explain, predict, or control behaviors. 4 They are used to understand why people do or do not practice health-promoting behaviors; identify what information is needed to design an effective intervention strategy; and help to set priorities for health education and promotion interventions. 5 The health belief model (HBM), theory of reasoned action (TRA), theory of planned behaviors (TPBs), trans theoretical model (TTM), extended parallel process model (EPPM), socio-ecological model (SEM), social cognitive theory (SCT), and diffusion of innovation theory are the most commonly used in behavioral change interventional strategies. The HBM is used to understand the failure of people to adopt disease prevention strategies or screening tests for the early detection of disease. It has six constructs (perceived susceptibility, perceived severity, perceived barrier, perceived benefit, self-efficacy, and cues to action). 6 TPB and TRA state that behavioral achievement depends on behavioral intention. TRA constructs (attitude and subjective norm) were predictors of COVID-19 preventive behaviors such as hand washing, mask wearing, and COVID-19 vaccination. 7 The TTM focuses on the decision-making of the individual with intentional change, with five stages (pre-contemplation, contemplation, preparation, action, and maintenance). 5
The EPPM suggests that if people do not believe there is a consequence of failing to use certain behaviors, they will not be motivated to use them. 5 SEM is an all-encompassing framework that describes how an individual’s behaviors are influenced by intrapersonal, interpersonal, organizational, community, and public policy factors. SCT states that learning occurs in a social context with a dynamic and reciprocal interaction of the person, environment, and behavior. 8
Different COVID-19 preventive behaviors are advised by the World Health Organization (WHO), such as receiving the recommended doses of the COVID-19 vaccine, maintaining a safe distance from others, donning a mask, washing one’s hands, covering one’s mouth when coughing or sneezing, and remaining at home. 9 The HBM structure is recognized as an important predictor of influenza vaccination exposure, and its structure differs depending on the national context and epidemiological conditions. 10 The study demonstrated that behavioral change models, such as the HBM and TPB, might be used to determine the factors that influence vaccine uptake.11,12
The studies showed that there are global variations in vaccine acceptance among different populations. The vaccine-acceptance rates were the highest among adults in Ecuador (97%), Malaysia (94.3%), and Indonesia (93.3%) and the lowest among adults in Lebanon (21.0%). 13 Overall, COVID-19 vaccination intention globally ranged from 27.7% to 93.3% and sociodemographic differences, perceptions of risk and susceptibility to COVID-19, and vaccine attributes influenced vaccination intention. 14 The studies showed that adequate knowledge, attitudes, and risk perception, source of information, self-efficacy, trust in health authorities, people’s beliefs were determinants of adherence to COVID-19 preventive measures, and population behavior changes depend on the population’s knowledge about the disease and individuals’ ability to perceive risks associated with the virus and to adapt their behavior accordingly.15–18
The study using TPB showed that more attitudes that are positive, greater social norms increased perceived control, and higher intentions were related to higher adherence to hand washing. 19 Participants’ subjective norms and perceived behavioral control were the factors associated with their intention and good knowledge and a positive attitude was found to be significant factors associated with the participants’ preventive practice.20,21
The study revealed that adherence to COVID-19 precautionary measures was wearing a face mask (96.4%), and social distancing (42.3%) and their adherence to those measures were found to be significantly associated with HBM constructs. 22 Individual level higher scores of COVID-19 fear, knowledge, age, and personal attitudes, at the interpersonal level COVID-19 information sharing, cultural norms and household income, and better evaluation of the national government policies about COVID-19 at the policy level were positively associated with COVID-19 preventive behaviors.23–26 Therefore, the purpose of this systematic review was to assess the applicability of behavioral change theory and models on COVID-19 preventive behavior globally.
Research question
What is the application of behavioral change theory and model on COVID-19 preventive behavior?
How do behavioral change theory and model predict COVID-19 preventive behaviors?
Methods
Search strategy
We have used online databases such as PubMed/MIDLINE, EMB ASE, Web of Science, Google Scholar, WHO libraries, and African Journals used to retrieve articles that were done on the applicability of behavioral change theory and model on COVID-19 preventive behavior. The search term was developed by using the following key terms: HBM, TRA, TPB, EPPM, SCT, SEM, TTM, COVID-19 preventive behavior or preventive measure (Vaccine acceptance, intention to the vaccine, hand washing, social distance, face mask wear, use of sanitizer, avoid public transport, social isolation, and avoid party meeting) and Boolean operators “AND” and “OR” were used for this purpose.
Inclusion and exclusion
This systematic review includes all publications which fulfil the following parameters: publications studying COVID-19 preventive behaviors using behavioral change theory and models like HBM, TRA, EPPM, TPB, SCT, TTM, AND SEM were included, whereas publications in a language other than English, short reports, letters to editors, and discussions were excluded in the present systematic review.
Eligibility criteria
Included articles in this systematic review were all articles published in English, articles published until October 1, 2022, all cross-sectional studies included, and we excluded articles based on the following criteria: articles with poor quality, study protocols, systematic reviews, unpublished articles, and letters to editors.
Data extraction
Articles extracted from databases were exported to Endnote version 9 software, after removing the duplicates, all articles were exported to a Microsoft Excel spread sheet. TFA and ETF were done for data extraction. Studies were retrieved by using search terms from all databases and additional sources screened for inclusion criteria. Then, articles that fulfilled the inclusion criteria were undertaken full-text review for admissibility and extraction. Preferred Reporting Item for Systematic Review and Meta-analysis flowchart used throughout all steps.
Quality assessment
Two reviewer writers independently evaluated the quality of the studies included in this systematic review, and a third reviewer settled disagreements. The Newcastle–Ottawa Scale (NOS) criteria were used for quality assessment to include this systematic review. For observational investigations, this tool provides 10 points in each of the three modified NOS component domains. 27 Studies that received five or more points were included (Table 1).
Modified Newcastle–Ottawa Scale regarding star allocation to assess the quality of cross-sectional studies for (out of a total of seven stars) included in the systematic review of application of behavioral change theory and model on COVID-19 preventive behaviors globally, 2022.
Data analysis
Descriptive statics were used to summarize the study findings. Due to the heterogeneity of study participants, we cannot conduct a meta-analysis.
Result
A total of 17,436 articles were retired from all sources after the removal of 8496 duplicated articles and 8940 articles were assessed by using titles/abstracts from these 8537 articles were excluded due to not evaluating the outcome of interest (COVID-19 preventive behavior) and did not apply behavioral change theory and model as a conceptual framework. Four hundred three articles underwent full-text review and finally, 82 articles were included in this review (Figure 1).

Preferred Reporting Item for Systematic Review and Meta-analysis flowchart of the study selection process on applicability of behavioral change theory and model on COVID-19 preventive behavior globally, systematic review.
Characteristics of articles included in this review
This systematic review includes studies done on the applicability of behavioral change theory and model on COVID-19 preventive behaviors studies published until October 1, 2022, and eighty-two articles that were done globally. The study design used for all studies was cross-sectional. The most commonly used behavioral change theory and model used on COVID-19 preventive behavior are HBM (38) and TPB (27) articles. Most studies using behavioral change theory and model on COVID-19 preventive behavior done in China (17) out of this HBM (7) and TPB (7), United States (12) TPB (6) and HBM (4) and Iran (9) HBM (7) and EPPM (2).
Application of behavioral change theory and model on COVID-19 preventive behavior
In this systematic review, behavioral change theory and model applied to describe COVID-19 preventive behavior were HBM, TRA, TPB, EPPM, SCT, TTM, and SEM.
There are 38 studies based on HBM in this systematic review, and constructs of HBM (perceived vulnerability, perceived severity, perceived barrier, perceived advantages, cues to action, and self-efficacy) were positively associated with COVID-19 preventive behavior. The most typical preventive behaviors such as planning to get vaccinated, accepting vaccinations, wearing a face mask, keeping social distance, washing hands with soap and water, using hand sanitizer, self-quarantining, staying at home, not touching one’s face, and not going to public meetings. In this review, COVID-19 vaccine acceptance was positively correlated with all HBM constructs (perceived susceptibility, perceived severity, perceived barrier, perceived benefit, cues to action, and self-efficacy),23,28–32 and constructs were also correlated with behavioral intention to engage in COVID-19 preventive behavior.24,33–37
The application of TPB to COVID-19 preventive behaviors is based on 27 articles included in this systematic review, and the dimensions of TPB (attitude, social norm, and perceived behavioral control) were significantly associated with COVID-19 preventive behaviors. In the United States and China, respectively, seven and six studies based on TPB were published. A study done based on TPB behavioral intention ranges from 64.9% to 70.6%to take COVID-19 vaccine uptake and the behavioral intention was positively associated with COVID-19 vaccine acceptance.38–44 This systematic review also included articles done using TRA five, EPPM seven, TTM two, SEM two, and SCT one.
Participants from a diverse range of studies, including adults, people over the age of 60, parents of young children, adolescents, high school, college, and university students, pregnant women, nurses, doctors, dentists, and pharmacists, as well as government employees, were included in this systematic review (Table 2).
Descriptive of the results of the applicability of behavioral change theory and models on COVID-19 preventive behaviors, worldwide: Systematic review.
AT: attitude; BI: behavioral intention; SN: subjective norm; DN: descriptive norm; EPPM: extended parallel process mode; HBM: health belief model; PBC: perceived behavioral control; TTM: trans theoretical model; HCW: health care worker; PB: perceived benefit; PS: perceived severity; PBr: perceived barrier; VA: vaccine accepatnce.
Discussion
The WHO advises many measures to avoid the epidemics of COVID-19. To have an adequate understanding of the barriers and facilitators of implementing preventive behaviors, researchers have employed a variety of behavioral change theories and models. This systematic review’s objective was to assess the application of behavioral change theory and model on COVID-19 preventative behaviors across the globe. This systematic review incorporated 82 articles based on different behavioral change theories and models to predict COVID-19 preventive behaviors. From this HBM (38), TPB (27), EPPM (7), TRA (5), TTM, SEM (2) each, and SCT (1) articles were incorporated.
According to a review of 38 articles based on HBMs conducted in various nations, acceptability of the COVID-19 vaccine ranges from 37.2% to 77.4% with the highest acceptance recorded in China among pregnant women.24,28–31,33,45,46 This difference might be the use of diverse assessment instruments, and the heterogeneous study participants from various nations with distinct cultures, norms, and beliefs may be the likely causes of the variation in variance explained by HBM components.
HBM constructs (perceived susceptibility, perceived severity, perceived barrier. perceived benefits, cues to action, and self-efficacy) were positively associated with COVID-19 preventive behavior like face mask wearing,47–49 avoid gathering together, 48 social distance,47,50,51 self-quarantine, 51 adherence to COVID-19 preventive behaviors.30,52–62 This result shows that the HBMs can predict health preventive behavior.
In this systematic review, TPB was identified in 27 articles across the globe to predict COVID-19 preventive behaviors. Based on TPB the immediate predictors of the behavior are behavioral intention with constructs of attitude, subjective norm, and perceived behavioral control. 5 The TPB constructs (attitude, subjective norm, and perceived behavioral control) and behavioral intention were positively associated with hand washing practice,19,63,64 social distance,65–67 face mask-wearing,64,68–71 social isolation,72,73 and enhanced community quarantine. 74 This finding suggested that the TPB could be used to predict health preventive behavior; therefore, it is important to guide the development of effective healthy messages on COVID-19 preventive behaviors.
In this systematic review, there were six studies done with the application of EPPM on COVID-19 preventive behaviors in different study populations and types of preventive behaviors. It was stated that 86.1% of the adult population in France practice preventive behavior, 75 and 93.33% of dental nurse students in Iran practice hand washing with soap and water and use sanitizer. 76 The EPPM constructs such as perceived efficacy, perceived fear and perceived severity, response efficacy, and perceived susceptibility were positively associated with COVID-19 preventive behaviors.75–78 It was evidenced that 15% of the adult population in Nigeria had a high threat and efficacy domain 78 to practice preventive behavior, and among the adult population in Iran 54.6% of the participants were engaged in danger control and high-perceived efficacy. 77 This evidence explains the predictive ability of the EPPM on healthy preventive behavior.
This systematic review also evidenced that TRA predicts healthy preventive behaviors during COVID-19 epidemics. The constructs of TRA (AT, SN, and BI) were positively associated with COVID-19 preventive behavior such as wearing masks (79), COVID-19 vaccine,79–81 stay home, 82 wash hand,81,82 avoid party gathering, 79 avoid public transport, and compliance with quarantine. 81 In the adult population in the United Kingdom, 68% practice not visiting friends or other family members, and 64% practice hand washing when returning home. 81 A study in China revealed that the TRA model explained only 20% of the variance in preventive behaviors. 83
The study done on SEM showed that agreeing to take vaccines, encouraged by their employer family members, was positively associated with vaccine uptake, 79 and in the United States, 44% of parents have the intention to vaccinate their children. 84
A study done in China with SCT revealed that 70% of HCWs had the intention to take COVID-19 vaccines. The physical protective effect of vaccination and self-evaluative outcome expectation, self-efficacy, descriptive norm, subjective norm, professional norm, and moral norm were positively associated to take the COVID-19 vaccine. 85
The study done in Australia with the application of TTM showed that 87.9% of pharmaceutical professionals implemented preventive behavior. 86 A study in Israel using the TTM model variance explained 86% of vaccine intention. 87 This shows that the TTM had a significance to predict healthy preventive behavior.
Strength and limitation: This systematic review shows comprehensive evidence of the application of the behavioral change theory and model on COVID-19 preventive behaviors as strength. The limitation of this review was all the studies were cross-sectional that could not show a cause-effect relationship with the outcome variable, and the heterogeneity of the study participants prevent us from doing a meta-analysis.
Conclusion
This systematic review summarizes comprehensive evidence on the application of the behavioral change theory and model on COVID-19 preventive behaviors globally. The study participants were heterogeneous. A total of 82 articles use the behavioral change theory, and models including HBM, TRA, TPB, EPPM, SCT, SEM, and TTM were used on COVID-19 preventive behaviors in different countries around the world. The constructs of most behavioral theories and models were significantly associated with COVID-19 preventive behavior such as hand washing, face mask use, vaccine uptake, social isolation, self-quarantine, social distance, and use of sanitizers. Therefore, the application of the behavioral change theory and models was recommended to use to develop behavioral change interventional strategies.
Footnotes
Acknowledgements
We acknowledge the team members of this systematic review.
Author contributions
TFA and ETF contributed to data extraction, TFA, ETF, and MGT contributed to the quality check of extracted data, synthesis of result, write-up of discussion, and preparation of manuscript.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
