Predicting Seat Belt Use Behavior among Adolescents Using the Theory of Planned Behavior and Its Extension

Authors
F. Malekpour 1
L. Tapak 2
B. Moeini 3
H. Sadeghi-Bazargani 4
F. Rezapur-Shahkolai 5
1 Department of Public Health, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
2 “Department of Biostatistics, School of Public Health” and “Noncommunicable Diseases Research Center”, Hamadan University of Medical Science, Hamadan, Iran
3 “Department of Public Health, School of Public Health” and “Social Determinants of Health Research Center”, Hamadan University of Medical Sciences, Hamadan, Iran
4 Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
5 “Department of Public Health, School of Public Health” and “Research Center for Health Sciences” Hamadan University of Medical Sciences, Hamadan, Iran
10.58209/hehp.13.2.315
Abstract
Aims: The rate of seat belt use among adolescents as a passenger age group is lower than that of adults. There is limited research on seat belt usage among adolescents. The present study aimed to compare the predictability of seat belt-wearing behavior among adolescents using the theory of planned behavior and its extension.

Instrument & Methods: This cross-sectional study was conducted among 952 adolescent students as car occupants. A researcher-developed questionnaire was used for data collection. In the extended theory of planned behavior, constructs related to threat appraisal were added to the theory of planned behavior. These constructs included perceived severity, perceived rewards, and perceived sensitivity. Structural equation modeling was used to determine which theory better predicts seat belt use behavior.

Findings: The mean score for seat belt use among adolescent students was unfavorable. Structural equation modeling confirmed the validity of both the theory of planned behavior and its extension in predicting seat belt use behavior among adolescents. However, in the extended theory of planned behavior, the additional constructs of threat assessment—such as perceived rewards, perceived severity, and perceived sensitivity—showed no statistically significant relationship with behavioral intention. Consequently, the inclusion of threat assessment dimensions did not enhance the prediction of seat belt-wearing behavior.

Conclusion: The rate of seat belt use among adolescent students is unfavorable, and the theory of planned behavior is an appropriate framework for predicting seat belt use among this demographic.

Keywords

Subjects

Introduction
Road traffic injuries (RTIs) are considered one of the main causes of death and disability worldwide [1]. According to statistics from the World Health Organization (WHO) in 2015, the number of victims of road accidents was 1.25 million people globally [2]. This figure rose to 1.35 million in December 2018, indicating an increase in road accidents in recent years [1]. RTIs are predictable and preventable events and are regarded as one of the most significant health problems globally, particularly in developing countries [3]. According to a report by the Iranian Legal Medicine Organization (ILMO), 16,778 people died, and 317,120 were injured due to RTIs in 2021 [4].
The non-use of seat belts is one of the primary causes of injury and death resulting from RTIs among young car occupants [5]. Wearing a seat belt prevents a person from being thrown out of the car, distributes the force of impact over a wide area of the body, slows down the deceleration process, and helps prevent serious injuries to the head and spinal column. Using a seat belt, whether as a driver or passenger, reduces the risk of death and severe injuries by 50% [6]. The percentage of adolescents wearing seat belts as car occupants is at a low level [7]. Several studies have reported that adolescents are at a heightened risk of death and injury on the roads. One reason for this increased risk is that adolescents often engage in various unsafe and potentially risky road behaviors, which further elevate their chances of death and injury on the roads [8-13].
The theory of planned behavior (TPB) is used to predict behavior by assessing a person’s intention to perform a specific action. According to TPB, the primary factor determining a person’s behavior is their intention, which is influenced by three constructs: attitude, subjective norms, and perceived behavioral control [14]. Among the theories utilized to investigate the factors affecting individual motivation and behavior is the protection motivation theory (PMT) [15]. Proposed by Rogers in 1975 and based on the value-expectation model, PMT aims to elucidate the influence of fear on health-related attitudes and behaviors. According to this theory, when individuals encounter fear-inducing messages, two types of cognitive evaluations are involved: threat assessment and coping assessment [16]. Threat assessment evaluates maladaptive behaviors and includes rewards for misbehavior as well as threat perception (severity and sensitivity). Rewards for maladaptive behaviors increase the likelihood of selecting such responses, while perceived threats decrease this likelihood [17].
Given the focus of this study and a review of previous research on promoting seat belt use among adolescents, the TPB was extended to incorporate constructs of threat assessment derived from PMT. As noted, the percentage of seat belt use among adolescents in the passenger age group is lower than that of adults. There is limited research on seat belt-wearing behavior among adolescents. Due to a lack of emotional and cognitive maturity in this age group, promoting beliefs regarding the effectiveness of seat belts in reducing the severity of RTIs could be beneficial. An educational model plays a crucial role in identifying and addressing educational needs. The present study aimed to compare the predictability of seat belt-wearing behavior among adolescents using TPB and its extension.

Instrument and Methods
Study setting
This cross-sectional study was conducted from November 30, 2019, to January 5, 2020, among 952 adolescent students in Tabriz, Iran.
Participants and sampling
Based on the sample size, 952 students were randomly selected; however, 10 participants did not complete the questionnaire, resulting in 942 students who participated in the study. The inclusion criteria required participants to be enrolled in junior high schools in the 7th, 8th, or 9th grades, to be willing to participate in the study, and to have their parents’ consent for their involvement. The self-reporting method was used to collect data.
Data collection tool
For data collection, a researcher-developed questionnaire that was validated in our previous study was used. The content validity index (CVI) and content validity ratio (CVR) for all the constructs of the questionnaire were greater than 0.9 and 0.8, respectively [18]. The questionnaire consisted of 76 questions related to the constructs of the TPB and 96 questions pertaining to the extended TPB, aimed at identifying the determining factors for seat belt use among students. Based on the constructs of the TPB, the questionnaire included subjective norms, attitude, perceived behavioral control, behavioral intention, and actual behavior regarding seat belt use. A 5-point Likert scale was employed, ranging from 5 (strongly agree) to 1 (strongly disagree), for the constructs of subjective norms, attitude, perceived behavioral control, and behavioral intention.
Attitude toward seat belt use was measured using two dimensions: behavioral beliefs, which included seven items (e.g., “Wearing a seat belt protects my health”), and assessment of behavioral outcomes, which also included seven items (e.g., “It is important to me to protect my health by wearing a seat belt”). The construct of subjective norms was measured with two dimensions: normative beliefs, consisting of eight items (e.g., “My father insists that I wear a seat belt whenever I get in the car”), and motivation to comply, which included eight items (e.g., “My father’s emphasis on wearing seat belts is important to me”). The construct of perceived behavioral control was measured using two dimensions: control opinions, which consisted of nine items (e.g., “Wearing a seat belt makes me feel restricted in my movements”), and perceived power, which also included nine items (e.g., “Restricting movement in the car when wearing a seat belt causes me not to wear it”). The construct of intentions was measured with four items (e.g., “I intend to wear a seat belt as a rear-seat occupant of a car outside the city”). The construct of behaviors was measured with four items (e.g., “When I sit in the rear seat of the car as an occupant outside the city, I wear my seat belt”). A 5-point Likert scale was used for the questions on intention and behavior, ranging from 5 (always) to 1 (never).
In the extended TPB, the construct of appraisal threat is added to the TPB. The construct of appraisal threat consists of perceived severity, perceived rewards, and perceived sensitivity. A 5-point Likert scale was used, ranging from 1 (strongly agree) to 5 (strongly disagree). The questions on perceived severity included four items (e.g., “If I have an accident, I may be injured”), while perceived sensitivity comprised nine items (e.g., “As a result of the damage caused by a traffic accident, my health may be in danger”), and perceived rewards included six items (e.g., “As a passenger, I feel more comfortable when I wear a seat belt”).
Statistical analysis
Structural equation modeling (SEM) was conducted using AMOS software 24 to verify which model better predicts seat belt use behavior. The χ²/df, root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis index (TLI) or non-normed fit index (NNFI), normed fit index (NFI), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), and parsimonious goodness of fit index (PGFI) were adopted to assess the adequacy of the model. A statistically significant result was considered for a p-value lower than 0.05.

Findings
The mean students’ age was 13.42±1.01, with a minimum age of 12 years and a maximum age of 15 years. Of the students, 52.3% were female and 46.8% were male.
Among the constructs, perceived behavioral control had the lowest mean relative to the maximum obtainable score. The maximum obtainable score for seat belt use behavior among adolescent students was 55.88%, indicating that the rate of seat belt use among these students was unfavorable (Table 1).

Table 1. Mean values of the constructs of the theory of planned behavior (TPB) and its extension


The fit of the TPB and extended TPB was assessed using SEM (Figure 1).


Figure 1. Paths analyzed using the theory of planned behavior (TPB) in relation to seat belt use behavior

The CFI is a measure of fit; the closer its value is to one, the better the model fit is considered. In the model, the CFI value was 0.921 (Table 2).

Table 2. The goodness-of-fit indices of the structural equation model of the theory of planned behavior (TPB)


The TLI, also known as the unnormalized fit index, had an optimal value range between 0 and 1. In this analysis, a value of 0.945 indicates acceptable fit. The RMSEA represents the root mean square of the estimation error; values lower than 0.05 are considered indicative of acceptable fit, while values higher than 0.1 are regarded as indicative of poor model fit. The RMSEA value was 0.049, which indicates an appropriate fit of the model.
According to the indices estimated for the model (Table 2), two important fit indices are the ratio of Chi-square to degrees of freedom (χ²/df=28.3, p<0.001) and the root mean square of the approximation error (RMSEA=0.049). Both values were below 5 and 0.08, respectively, confirming the model’s fit. Additionally, the GFI, AGFI, CFI, NFI, and TLI values supported the validity of the model.
The one-way relationships between the constructs of perceived behavioral control and intention (p<0.001), intention and behavior (p<0.001), and perceived behavioral control and behavior (p<0.001) were all significant (Table 3).

Table 3. Path coefficients related to fitting SEM to determine one-way relationships between constructs of TPB


The two important fit indicators—χ²/df and RMSEA—confirmed the model’s fit. Furthermore, the values of the GFI, AGFI, CFI, NFI, and TLI reinforced the validity of the model (Table 4 and Figure 2).

Table 4. The goodness-of-fit indices of the structural equation model of the theory of planned behavior (TPB)



Figure 2. Paths analyzed using the extended theory of planned Behavior (TPB) in relation to seat belt use behavior

The one-way relationships between subjective norms and behavioral intention (p<0.001), behavioral intention and behavior (p<0.001), and perceived behavioral control and behavior (p<0.001) were all significant (Table 5).

Table 5. One-way relationships between the main constructs of the extended theory of planned behavior (TPB) and behavior


The coefficient of determination (R²) resulting from fitting structural equation models for behavioral intention and behavior in the TPB model was 0.69 and 0.57, respectively, while for the behavioral intention and behavior in the extended TPB model, the values were 0.68 and 0.56, respectively. Thus, the TPB and the extended TPB predicted a similar level of seat belt-wearing behavior.

Discussion
The present study aimed to compare the predictability of seat belt-wearing behavior among adolescents using TPB and its extension. The relationships among the constructs of the TPB and the intention of seat belt use behavior among adolescent students were assessed based on SEM. The indices of TLI, NFI, CFI, AGFI, and GFI confirmed the validity of the model. According to the TPB, the relationships between the constructs of perceived behavioral control and behavioral intention, behavioral intention and behavior, and perceived behavioral control and behavior were significant. In line with our results, some previous studies have reported that perceived behavioral control predicts the intention and behavior of wearing seat belts [19-21].
Consistent with our findings, previous research has indicated that subjective norms predict seat belt use behavior [20-23]. Additionally, the relationships among the constructs of the extended TPB, as well as the intention of seat belt use behavior and behavior among adolescent students, were assessed based on SEM. The indices of TLI, NFI, CFI, AGFI, and GFI confirmed the validity of the model. However, based on the extended TPB, the relationships between the constructs of perceived reward and behavioral intention, perceived severity and behavioral intention, and perceived sensitivity and behavior were not statistically significant.
Both the TPB and the extended TPB predicted a similar level of wearing a seat belt behavioral among adolescent students. In other words, adding the dimension of threat assessment to the TPB had no effect on the prediction of seat belt use behavior. The results of Foxwell et al. showed that the inclusion of habit, past behavior, and moral considerations in the TPB accounts for an additional amount of variance beyond the TPB parameters [24]. Another study reported that the added TPB constructs of habit, moral norm, and predicted regret are not significant predictors of seat belt wearing behavior [23].
Ali et al. demonstrated that the standard TPB constructs significantly predict behavioral intention regarding seat belt use [25]. Tavafian et al. found that, contrary to the results of the present study, perceived benefit and perceived barriers significantly predict seat belt use behavior; however, in line with the results of the present study, perceived severity does not significantly predict seat belt use behavior [20]. Gras et al. demonstrated that a perception of greater benefits does not predict wearing a seat belt. Adolescents as car occupants were the studied population, whereas previous studies focused on adults as drivers. Therefore, perceived benefits and perceived barriers may not be as important for adolescents [26].
Previous studies have reported that discomfort and limited movement are barriers to wearing seat belts and are negative, immediate consequences of not wearing them [27]. Tavafian et al. showed that both the TPB and health belief theory (HBM) have good predictive value, but the TPB demonstrated slightly more predictive power than the HBM [20]. Mehri et al. found that both TPB constructs (perceived behavioral control, subjective norms, and attitude) and HBM constructs (perceived susceptibility and severity, benefits and barriers, and cues to action) significantly predict the intention to wear a seat belt [21]. Liu & Liu utilized an extended TPB to predict seat belt use; their results showed that descriptive norms, attitude, and law enforcement significantly impact the intention to use seat belts in the rear seat of a car, along with perceived behavioral control and subjective norms [28].
In another study, Guo et al. discovered that the inclusion of susceptibility, severity, perceived benefit, and perceived law enforcement in the TPB enhances the model’s capacity to predict rear seat belt behavioral intention among older adults. They found that subjective norms, attitude, perceived behavioral control, severity, susceptibility, and law enforcement significantly affect behavioral intention [29]. A review and meta-analysis study reported the strength of the TPB in predicting aberrant driving intention and its usefulness in planning interventions aimed at changing aberrant driving behaviors [30].
The rate of seat belt use among adolescent students was unfavorable. The constructs of the TPB, such as attitude, subjective norms, perceived behavioral control, and behavioral intention, were good predictors of seat belt use behavior among adolescent students. In the extended TPB, the constructs of perceived severity, perceived reward, and perceived sensitivity were not predictors of seat belt use behavior. Therefore, the TPB is a suitable theory for predicting seat belt use among adolescent students.

Conclusion
The rate of seat belt use among adolescent students is unfavorable, and the TPB is an appropriate framework for predicting seat belt use among this demographic.

Acknowledgments: This study was confirmed and financially supported by Hamadan University of Medical Sciences (grant reference number: 9711237080) and Tabriz University of Medical Sciences (grant reference number: 62722). The authors would like to thank all the students who participated in this study and their parents.
Ethical Permissions: This study was approved by the Ethics Committee of Hamadan University of Medical Sciences under the ethical approval code IR.UMSHA.REC.1397.819 (the webpage of ethical approval is: file:///C:/Users/sphdrrezapur/Downloads/d876axiwpdhhz4.pdf).
Conflicts of Interests: The authors declared no conflict of interests.
Authors' Contribution: Malekpour F (First Author), Introduction Writer/Methodologist/Main Researcher/Discussion Writer/Statistical Analyst (30%); Tapak L (Second Author), Methodologist/Assistant Researcher/Statistical Analyst (15%); Moeini B (Third Author), Methodologist/Assistant Researcher/Discussion Writer (15%); Sadeghi-Bazargani H (Fourth Author), Methodologist/Assistant Researcher/Discussion Writer (10%); Rezapur-Shahkolai F (Fifth Author), Introduction Writer/Methodologist/Assistant Researcher/Discussion Writer/Statistical Analyst (30%)
Funding/Support: This study was financially supported by Hamadan University of Medical Sciences (Grant Ref No. 9711237080) and Tabriz University of Medical Sciences in Iran (Grant Ref. No. 62722).
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Health Education and Health Promotion
Volume 13, Issue 2
Spring 2025
Pages 315-321