The health benefits of physical activity (PA) participation are well-documented in many systematic reviews (Warburton, & Bredin, 2017). The World Health Organization recommends that "adults should do at least 150–300 minutes of moderate-intensity aerobic PA" (Bull, et al., 2020, p. 1456). However, sedentary behaviors are prevalent in many societies. Significantly, individuals' PA level decreases during university years (Small, Bailey-Davis, Morgan, & Maggs, 2013). It is crucial to find ways to support the PA level of university students. Transtheoretical model is a useful framework for understanding individuals' behavior changes in healthy habits (Kohl, Murroy, & Salvo, 2019). This model indicates that individuals follow a series of stages: precontemplation, contemplation, preparation, action, and maintenance (Marcus & Lewis, 2003).

Based on the model, individuals show sedentary behaviors, and PA is not an option for them in the first stage (precontemplation). In the second stage, they only think about doing exercise. The third stage involves a plan preparation for participating in PA. The following stage is action stage, and individuals perform some activities. The last stage is maintenance time and it is hard to achieve this stage for some people. Individuals regularly attend different types of physical activities in the last stage. Corbin and his colleagues (2014) emphasize that the main aim is to support individuals progress to the last stage, which might be challenging. Therefore, it is essential to investigate the factors that might associated with the stages of change in PA. Perceived benefits and perceived barriers of PA participation might affect stages of exercise behavior change. Thus, the purpose of this study was to examine the relationship between stages of exercise behavior change and perceived exercise benefits/behaviors among university students. Moreover, the current study examined PA and screen time behaviors among the students. Two main research questions of this study are a) what is the relationship between stages of exercise behavior change and perceived exercise benefits/barriers among university students? and b) What is the role of physical activity participation on stages of exercise behavior change and perceived exercise benefits/barriers among university students.

This study utilized a descriptive and correlational research design that aimed to assess the exercise benefits/barriers through students' perceptions and examine stages of exercise behavior change. Participants were selected by using a purposeful sampling method. Undergraduate students in a Turkish state university constituted the study sample and took elective courses from the physical education and sports department. Out of 66 undergraduate students who participated in the study voluntarily, 22 of them were female, and 44 of them were male. The mean of students' age is 22.53 (SD = 1.44). The mean of their height is 176.50 (SD=8.70), whereas the mean of their weight is 74.44 (SD= 15.80). As data collection instruments, Exercise Benefits/Barriers Scale (EBBS) (Sechrist, Walker, & Pender, 1987), Exercise Stages of Change Questionnaire (ESOCQ) (Marcus & Lewis, 2003), and a demographic information sheet were used. Turkish adaptation of the EBBS was done by, Ortabağ, Ceylan, Akyüz, and Bebiş (2010), and this scale was used to assess university students' perceived benefits/barriers of engaging in PA. It includes 43 questions. Turkish adaptation of ESOCQ was performed by Cengiz, Aşçı, and İnce (2010), and it is used to identify university students' exercise stages of change. It includes 4 questions. Students filled out a demographic information form to determine their general physical activity and screen time behaviours. It includes 6 questions. Prior to the data collection, human subjects ethics committee approval was obtained. Consent forms from participants were gathered. Data were collected during the regular class hour in paper and pencil format. The administration of the instrument lasted approximately 8-10 minutes. Data were analyzed with descriptive and inferential statistics using SPSS 26 for Windows. In descriptive statistics, means, standard deviations, and frequencies were calculated. In inferential statistics, Chi-square test for independence correlation, a point-biserial correlation, and an independent t-test was run. Chi-square test for independence was run to analyze the correlation between students' stage of change and regular PA participation. A point-biserial correlation was run to analyze the correlation between students' stage of change and their perceived exercise benefits/barriers. An independent t-test was run to analyze the differences between the groups who participate in regular PA and those who do not regarding the scores of exercise benefit scale. An alpha level of .05 was established for all statistical tests.

The study results revealed that 30 students do regular PA; however, 36 of them do not do regular PA. Besides, 26 students engage in PA more than 2.5 hours in a week. When considering their stages of change results, only four students are in precontemplation stage, 25 students are in contemplation stage. Thirteen of them are in preparation stage, eight of them are in action stage, rest of them are in maintenance stage. When splitting the data based on regular PA status, 12 students participating in PA are in maintenance stage, and only one student is in precontemplation stage. On the other hand, most students who do not participate in PA regularly are in precontemplation and preparation stages. Main results of the study indicated that regular PA participation is significantly related to stages of change levels χ2 (4) = 43.207, p < .05. It is found a positive correlation between stages of change and students' score in the exercise benefits/barriers scale (rpb = .304, n = 66, p <.05). Furthermore, findings revealed that students participating in regular PA (M = 138.53, SD= 12.69) had high score in the exercise benefits scale than the students who do not (M = 129.86, SD= 15.57), t (64) = -2.448, p <.05, r2 = .08. Eta square shows that it has a moderate effect. In conclusion, these findings might be useful to create policies in order to track university students’ perceptions about physical activity and their stages of exercise behavior change. Physical activity interventions might be provided as a further step to increase university students’ physical activity level based on the physical activity strategy for the WHO European Region 2016–2025 (WHO, 2016) on university campuses.

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