1. Introduction
Physical activity (PA) refers to any form of activity that uses energy generated by skeletal muscle activity [
1], and regular physical activity is socially, psychologically, and physically beneficial for young people [
1]. Because of the evidence-based benefits of physical activity, it has been used as an intervention strategy to improve the mental and physical health of college students [
2]. Despite this, physical inactivity has become a significant public health problem affecting people worldwide [
3], and the World Health Organization (WHO) considers physical inactivity to be the fourth leading risk factor for global mortality [
1].
This global trend is no exception for Chinese students. Since 2010, the health level of Chinese college students has continued to decline, and the number of obese Chinese college students has steadily increased, mainly due to physical inactivity [
4]. Studies have also shown that the detection rate of depression among Chinese college students is as high as 31.38%, with an increasing trend year by year [
5]. This is partly due to physical inactivity, as adolescents who are physically active for more than 30 min and five or more times per week have a 60% reduction in self-reported depressive symptoms [
6]. Luo and colleagues also found that Chinese college students are dangerously clinically sedentary, as prolonged sitting can cause a variety of negative effects, including increased risk of chronic diseases, reduced cardiovascular health, and decreased bone density [
7]. In light of these situations, this study aims to explore ways to promote physical activity among Chinese college students by extending the Theory of Planned Behavior (TPB) with triggers.
The TPB has been widely used to analyze, explain, and predict behavior in various contexts, including education, medicine, and health [
8]. The TPB comprises attitude (AT), subjective norm (SN), perceived behavioral control (PBC), and behavioral intention (BI). AT, SN, and PBC are three social cognitive characteristics that significantly influence BI. AT refers to a person’s evaluation of behavior as favorable or unfavorable, while SN refers to the perceived societal pressure that influences individuals to engage in or refrain from a particular behavior. PBC represents an individual’s perceived ability to perform a specific behavior [
9]. Shen observed that AT, SN, and PBC can account for a significant amount of variation in PA intention, and each of these factors can predict PA behavior [
10]. Therefore, the TPB helps us to comprehend how intrinsic psychological factors, such as AT and PBC, and extrinsic social psychological factors, reflected by SN, influence PA behavior [
11].
While the TPB has been found to have a high explanatory power for BI, it has been criticized for its low explanatory power for behavior [
12]. According to Conroy and colleagues, people’s BI changes over time, and the longer the time between BI and behavior, the weaker the link between the two becomes [
13]. Sheeran also noted that although 47% of people have a positive BI to implement healthy behaviors, only 7% of them execute those behaviors [
14]. Furthermore, Zhang and Mao reported that the percentage of teenagers engaging in PA remains low despite a high BI to engage in PA. They proposed that other factors may affect PA behavior [
15]. Scholars have since explored ways to improve the explanatory power of the TPB for behavior. For instance, Feng and Mao introduced self-determined motivation into the TPB, but the improvement in explanatory power was limited [
3]. Bogg and Roberts proposed that promoting desired behavior and enhancing its performance are two key considerations to strengthen the association between BI and behavior [
16]. Hu found that planning can mediate the relationship between BI and behavior [
17]. As such, researchers have attempted to add variables to the TPB to understand the origins of people’s behaviors better. However, the relationship between BI and behavior remains unclear and limited. Thus, this study incorporates triggers into the TPB (namely, the TPBT) to gain a better understanding of the physical activity of Chinese college students.
Triggers come from the Fogg behavior model (FBM), a behavioral design theory proposed by Fogg [
18,
19]. Fogg stated that the FBM allows us to understand the drivers of human behavior and proposed that human behavior can be controlled by three factors: motivation, ability, and triggers [
18]. Numerous studies have examined the role of motivation and ability in human behavior, e.g., [
9,
20,
21], and what distinguishes the FBM from previous behavioral theories [
22] is the use of triggers. The triggers can be an alarm, a text message, an invitation, or someone’s encouragement for individuals to perform a target behavior. “Whatever the form, successful triggers have three characteristics: First, we notice the trigger. Second, we associate the trigger with a target behavior. Third, the trigger occurs when we are both motivated and able to perform the behavior” [
18] (p. 3). Fogg conceptualized three types of triggers, including sparks, facilitators, and signals [
18,
19]. A spark directly stimulates the user’s demand motivation and produces self-drive to promote the occurrence of the target behavior. A facilitator provides explicit guidance for the user’s target behavior. A signal acts as a reminder or cue to remind the individual to perform the target behavior [
18,
23]. Fogg argues that even if individuals have both the motivation and ability to engage in physical activity, they will not change their behavior without triggers [
18]. In other words, triggers are the final step in leading individuals to perform target behaviors [
24] and the determining factor for the occurrence of the behavior [
19].
Studies have been conducted to verify the roles of signals, sparks, and facilitators in promoting physical activity (PA). Cai [
25] conducted an experimental intervention on elderly chronic disease patients with PA deficiency by providing them with smart bracelets and sending health knowledge and regular reminders through the WeChat platform. The study found a significant increase in the total amount of PA after the intervention. Li et al. [
26] provided college students with daily articles and videos on physical exercise and fitness guidance through the WeChat platform. The study found that WeChat created a social and autonomous support environment, which improved the college students’ extracurricular physical activity. Similarly, Wang et al. [
27] reported that peer support positively and significantly impacted adolescents’ physical activity. Li et al. [
28] also demonstrated that parental, teacher, and friend support have a significant positive moderating effect on the relationship between exercise motivation and exercise persistence. Motivation to engage in physical activity and social support are found to be crucial in forming sport intention and maintaining sport behavior [
29,
30]. As such, various triggers have been separately experimented with and proven to be important interventions in promoting physical activity. However, studies that comprehensively address triggers are limited because a questionnaire to measure three types of triggers has only recently been developed [
22]. Therefore, the purpose of this study is to examine the moderating role of three types of triggers between BI and PA behavior. The following hypotheses are proposed.
Three types of triggers have a moderating effect on the relationship between BI and PA behavior.
The TPBT model can significantly predict college students’ PA behavior and improve the interpretation rate of PA behavior.