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In the study, the association between demographic characteristics of commuter students and stress was evaluated through a questionnaire with ten questions that overlooked the sample demographics. Apart from the questionnaire, students were also provided a scale with 31 life events that vary from a family members death, to financial burdens in order to assess their stress level. In the questionnaire, students were asked about their age, gender, employment status, and much more. In the scale, students were required to make a check off any life events that were applicable to them in the past year.
Based on the amount of events they have checked off, it will determine how high or low their stress is. After the students filled out the questionnaire and stress scale, the demographics and stress level were compared to see if there was a correlation amongst both factors. The sampling method was non-probability since students were conveniently sampled in the San Diego State University commuter resource center. It was also a cross-sectional study that involved two visits at the resource center.
The independent variable of this study was the demographic characteristics and the dependent variable was the stress levels.
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The purpose of the study was to determine whether or not there is an association between the demographic characteristics of students and their stress levels. After looking reviewing the questionnaires and scales, it was found that there was a potential association between the demographics and stress levels. Some characteristics had associations where there were higher stress levels. Those with a part-time employment status and were of younger age were found to have high stress levels.
Within the study, the target population are commuter students who encounter diverse stress levels, depending on their demographics. Through a literature review search, it has been found that many commuter students are older than the average college student and have different sets of responsibilities such as careers, and families, that add on to the stress at school (Newbold, 2015, pg. 80).
When comparing commuter students to students living on campus, there a difference in the levels of involvement. For example, in a study from the Saint’s College of Maine it was confirmed that “over 66% of commuter students and 21% of residential students were engaged in no school sponsored activities during the Fall 2011 semester” (Alfano & Eduljee, 2013, pg. 339). Additionally, commuter students regard transportation stress primarily with congested traffic, accessible parking and the time it takes to commute (Hernandez, 2002, pg. 75). Commuter students are also more likely to work full-time, yet they are not as stressed as residential students because of they have more experience with time management (Lundberg, 2003). In this study, the relationship between stress and demographic characteristics will be examined in the context of SDSU commuter students. It is hypothesized that the demographic characteristics and stress have a relationship because there is a possibility that the demographics have an influence on the stress levels students obtain.
Within my study, my sample population was 12 San Diego State commuter students. The method utilized for my sampling was non-probability. Specifically convenience sampling because I mainly approached students who I found in the commuter resource center lounge. In my recruitment process, I began with a screener question where I would first ask students if they were commuters before having them complete their survey. This was an important element in my sampling process because not all students in the resource center were commuters. Additionally, I was mindful of including students of different races/ethnicities, and age groups. I recognized that I needed to include more males in my study in order to have a diverse sample. However, this was difficult to achieve because there were more female students in the commuter resource center then there were males. The day and time played a major role in my selected sample. I first visited the commuter resource center on a friday, yet there were not many students I could find to survey. I had to return on a Monday, at a much later hour after students had finished their classes. Because I utilized a non-probability sampling method, it cannot be assumed that this study will be generalizable to the entire San Diego State commuter community. Selection bias played a major factor when it came to the decision of generalizing the study to commuter students. Randomization is also needed in order to have a higher chance of generalizability in a study. In this study, randomization was not a method that was utilized to obtain a sample because I merely chose students who were unoccupied in the resource center. By having a small sample, it increased the level of voluntary response bias and affected the results of the study since only those who were willing to respond reported their stress levels.
In my study, the demographic characteristics are the independent variables. The variables were operationalized or defined by GPA, study time, race and ethnicity, parking issues on campus, transportation methods, gender, the time it takes to arrive on campus, employment status and the effect of commuting on the amount of time needed to study. When students were asked about their GPA, they were given four options of GPA measurements which varied from 1.0-1.9, 2.0-2.9, 3.0-3.9, and 4.0 and above. For the study time, students were questioned about the average studying time. This variable was measured by four different time frames that students could identify. These times frames were: 30 minutes, 1 hour, 2-3 hours and 4 hours. The variables race and ethnicity had seven attributes that students could select in the survey. Students could select from the options of African American/black, Pacific Islander, Caucasian, Native American, Hispanic/Latino, Asian and other. For the two variables: parking issues on campus and the effect of commuting on the amount of time needed to study, students were only given the options ‘yes’ and ‘no’. They were required to mention whether or not they did believe that they had a difficult time finding parking on campus and if living on campus does or does not have an effect on the amount of time needed to study. The transportation method was measured by six attributes that students would select. Students would have the choice of selecting a car, public transportation, a bike, walking, carpooling and other (Uber/Lyft). Gender was measured by the attributes female, male, transgender female, transgender male, gender non-conforming and other. The arrival time on campus is a variable that was measured by the four time frames: 20-30 minutes, 1 hour, 2-3 hours, and four hours. Employment status was measured by the three options: part-time, full-time or unemployed.
Meanwhile, the independent variable are the demographic characteristics, the dependent is variable is the stress that is operationalized by the student stress scale. In the student stress scale, students are presented with thirty-one life events and students were expected to check off whether or not these events have occurred to them in the past year. For example, students were asked if they had a change in financial status or the death of a close family member. Once students completed the stress scale, it was my responsibility to add up their total score to determine what their stress level was. The stress level on the scale was separated into five categories: major, serious, moderate, mild and very little stress. If a student had major stress, then their total points score was 300 and above. Students who had serious stress had a total points score of 250-299. Those who had moderate stress had a total points score of 200-249. Meanwhile, those who had mild stress had a total points score of 150-199. Students with very little stress had a total points score of 0-149.
The levels of measurement for my demographic independent variables were ratio, interval, and nominal. The variables: average study time per day, the arrival time on campus, and age are considered to be ratio measurements because their attribute’s options in the survey are different increments of time. For example: 30 minutes, 1 hour, 2-3 hours. Age is a continuous level of measurement with significant intervals that range from the age groups: 18-20 years old, 21-24, 25-28, 29-32, 33 and up. Meanwhile, the variable GPA has attributes that are interval levels of measurement. This variable is considered an interval because there is meaningful distance between the attributes of GPA ranges and no absolute zero, it is not possible to have a 0 GPA range. The variables gender, transportation mode, race/ethnicity, and employment status are nominal levels of measurement because the attributes involve multiple categories with no significant order. The final variables consisted of the difficulty of finding parking on campus and the effect of living off campus on the amount of time needed to study. The attributes of these variables are considered to be nominal levels of measurement because the options for participants were either yes or no. These are two categories that also do not have a significant order.
The dependent variable was the student’s stress scale, which can be considered an interval level of measurement because there is meaningful distance between the life events listed in the scale, with no absolute zero included. This scale was found to have high consistency with a study that examined male psychiatric outpatients and non-patients. When comparing the reliability of the scale for the control and experiemental group, it was found that the ranking order of important life events was had a realibility of 0.96 for the outpatient group, and had similar ranking scores to the control group. (Gerst, Grant, Sweetwood, & Yager, 1978, pg. 520). This is considered to be excellent reliability for a scale. Homes and Rahe (1967) confirmed that the scale has a positive correlation of 0.118 between the scale score results and mental illness results. Although the scale was created with the intention to measure life events and potential illnesses, it can still be applicable to college students who encounter with external stressors.
My commuter students study is cross-sectional because the data was collected at one period in time. The study cannot be generalizable to the general population of commuter students because it is not inclusive of commuter students who do not visit the commuter resource center. Cross-sectional studies are not beneficial because they limit the amount of information that can be obtained on the association of stress and demographics. It also does not take into account the shift of stress factors throughout the remaining college years. Within the survey, the demographic questions were primarily close-ended because students were given a range of options to choose from, however there were some questions that had open-ended answers, where students could select the option “other” and provide their own response. Since the questions were closed-ended, the study is reflective of quantitative research. The data collection technique for my study was survey research. Students were given a printed out survey and stress scale that they filled out on their own. The commuter students study attempted to examine the relationship between the demographic independent variables and the student stress scale dependent variables. By examining the relationship, the intent was to find a correlation between the demographic variables and the student stress scale variables in order to infer causation.
The main ethical principles of human subjects found in my study was respect for persons and beneficence. The participants in my study were asked to read a confidentiality statement, where they were informed about having the opportunity to leave the study if that was their choice and that their information was to be kept anonymously. All participants voluntarily participated in the study after they were informed of their rights. Participants benefits were maximized and harm was minimized during the study because their participation would not lead to any lethal or legal consequences after they disclosed their demographic information.
Within my sample of 12 commuter students, 66% were of the ages 18-20, 8.33% were in the age group 21-24, and 25% were in the age group 29-32. In addition, 91.66% of my sample identified was female, and 8.33% identified as male. 83.33% of my sample utilize cars as their main transportation method to school and 16.66% of the students would use public transportation. 75% of the students would take approximately 20-30 minutes to arrive on campus, 16.66% would take about an hour to arrive and 8.33% would take about two to three hours to arrive on campus. When students were asked if they feel that their study time was affected because they live off campus, 50% believed that his statement to be true, and 50% did not believe that the statement was true. 58.33% of the students confirmed that they did have a difficult time finding parking on campus and 41.66% did not have any difficulty with finding parking on campus. 8.33% of the students had a GPA between 1.0-1.9, 16.66% of the students had a GPA between 2.0-2.9, 58.33% of the students had a GPA between 3.0-3.9, and 16.66% of the students had a GPA that was 4.0 and above.
Commuter Students and Stress. (2022, Mar 28). Retrieved from https://studymoose.com/commuter-students-and-stress-essay
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