Loading

Social Media Use & Feelings of Nihilism CMN490 Research Study by Richard Howard

Research Problem & Objectives

Following an observation of what appears to be an increase in nihilistic humour online, the possibility of a relationship between nihilistic thought and social media usage arose. This study takes inspiration from existing research into the relationship between social media use and mental health to investigate this possibility. Thus, this study was created to answer the following research questions:

1. Is there a relationship/correlation between social media usage (SMU) and feelings of nihilism (FoN) among young adults?

2. What is the nature of the relationship between SMU and FoN among young adults?

As this study deals with a subject material, nihilism, that is rarely measured in quantitative research, it is important to establish the definitions from which the study is based. For the purposes of this study nihilism is defined as the belief that life does not have any inherent meaning or purpose. However, as it is unlikely that use of social media would inspire a change in examined philosophical belief, the variable of concern is feelings of nihilism rather than nihilism itself. Thus, given the stated definition of nihilism, feelings of nihilism are defined here as feelings of purposelessness, meaninglessness, absurdity or similar, regardless of general individual belief.

While this study may at first seem trivial and niche, there may in fact be significant value to be found in studying the relationship between SMU and FoN, particularly in fields such as online communication. Beyond contributing to the existing body of research on the impacts of SMU, this study may also prove valuable for communicators attempting to motivate action in their audiences. For example, consider the role of a communicator attempting to motivate action on climate change or a similarly important political issue. As FoN are associated with feelings of purposelessness or meaninglessness it is reasonable to assume that an individual with high levels of FoN may have greater skepticism about the potential value and impact of such action. As a result it will likely be more difficult for the communicator to motivate action among their audience should the audience be prone to higher FoN. Communicator's may also find related research dealing with the nature of communication platforms and nihilism to be useful when devising communication strategies. While it is beyond the scope of this study to determine with any degree of certainty the relationship between SMU and FoN, this study may nonetheless prove valuable by highlighting new avenues for research. Recommendations of which areas of research may prove most valuable as next steps will be discussed further in the results and analysis section of the webpage.

Lastly, it is important to note that given similarities between FoN and symptoms of depression it will be difficult to ensure that results captured by the FoN variable are not simply a manifestation of said symptoms. As such, this study will also aim to control for prior existing mental health conditions among participants. However, it cannot be guaranteed that overlap between the two variables will not occur and more research will be needed to determine the best way to accurately measure FoN.

Methodology

Subjects

The sample population of this study are young adults of university age and older, specifically 18-28 years old. This sample population was chosen for several reasons. Specifically, they were chosen for their relevance to the topic's inspiration as well as their proximity and accessibility as subjects. Further, it was important to limit the age range of participants given differing attitudes and approaches to technology among age groups. While increasing the number of age categories would potentially allow for greater insight into the relationship between FoN and SMU, it is necessary given the study's limited scope and resources to eliminate additional variables. Similarly, no data was collected on the subjects' race, gender, class, or other similar characteristics. Further research may wish to expand on the foundation here by including such characteristics. Finally, while the subject group chosen here is rather limited, it nonetheless should prove sufficient for this study given that it does not attempt to prove causation, and that any correlation established between SMU and FoN is only preliminary and the grounds for further research.

Data Collection

Sampling was carried out using an online survey that was passed around to classmates, colleagues, and friends, allowing for a diverse selection of participants with significant variance in social media usage levels. The survey form was hosted on Google Forms and the survey results were important into SPSS for further analysis.

Measurement

The primary variables, as previously mentioned, are: feelings of nihilism (FoN) and social media usage (SMU). The control variables used are: mental health problems (MHP) and emotional wellbeing (EWb) with mental health problems representing a dichotomized measure of EWb meant to assess the likelihood that the subject had prior mental health problems. As one might expect, EWb represents the subject's state of emotional wellbeing.

MHP and EWb were both measured using the MHI-5 (including questions from the SF-36 pertaining to fatigue for potentially relevant extra data). Participants were asked for each question “How much of the time during the past 4 weeks…” with options from 1 to 6 representing:

  1. None of the time
  2. A Little of the time
  3. Some of the time
  4. A good bit of the time
  5. Most of the time
  6. All of the time

The questions were scored according to recommendations from the SF-36, with the only change being that the ordering of choices was reversed (instead of 1 representing All of the time, here it represents none of the time). Each numbered ranking corresponded to the following scores

  1. = 0
  2. = 20
  3. = 40
  4. = 60
  5. = 80
  6. = 100

Scoring was organized such that a lower score and higher score represent lower emotional wellbeing and higher emotional wellbeing (and thus higher MHP and lower MHP) respectively. Thus, questions that were negatively phrased were recoded as follows:

  1. = 100
  2. = 80
  3. = 60
  4. = 40
  5. = 20
  6. = 0

These scores were then averaged to create scoring for EWb, which in turn is used to determine MHP by dichotomizing EWb. Using Velden et. al. as a guide the cut off of 60 was chosen, such that EWb scores above were recorded as 0 for MHP indicating a lack of mental health problems, and those less than or equal to 60 were recorded as 1 indicating the potential presence of mental health problems.

FoN was measured using questions created for this survey based on mental health questions from the MHI-5. For each question participants were asked to rank how frequently they felt the described feeling on a scale from 1 to 6. The numbered rankings were labelled as such:

  1. Never
  2. Very infrequently
  3. Infrequently
  4. Somewhat frequently
  5. Frequently
  6. Very frequently

The questions were presented as follows: “How frequently during the past 4 weeks...”

  1. Have you felt a sense of purpose in your life?
  2. Have you felt apathetic?
  3. Have you felt that you make a meaningful contribution to society?
  4. Have you felt that life is meaningless?
  5. Have you felt the state of the world is strange or absurd?

FoN was scored similarly to EWb, as the questions were formatted after the MHI-5, with a higher score representing higher levels of FoN. In this case positively phrased questions were recoded. Negatively phrased questions were scored as follows:

  1. 0
  2. 20
  3. 40
  4. 60
  5. 80
  6. 100

And positively phrased questions as:

  1. 100
  2. 80
  3. 60
  4. 40
  5. 20
  6. 0

Scores were then combined and averaged to achieve a combined score for FoN

Social Media Usage was measured using questions based on Velden et. al.’s study. Participants were asked to select, on a scale from 1 hour to 10 hours, the amount of time they spent per week on each type of social media. The questions were as follows:

  1. How many hours per week do you typically spend reading and viewing social media? (Including but not limited to Facebook, Instagram, Twitter, YouTube, LinkedIn, Google+, Pinterest, Flickr or similar services)
  2. How many hours per week do you typically spend chatting, video calling or sending messages? (Using WhatsApp, Telegram, Snapchat, Skype or similar services?
  3. How many hours per week do you typically spend posting messages, photos and short films on social media yourself ? (e.g. Facebook, Instagram, Twitter, YouTube, LinkedIn, Google+, Pinterest, Flickr, or similar services)

Participants were then asked to “Please enter the total combined number of hours you typically spend engaging in online activities like those above.” This allowed for students who spent greater than 10 hours per week to enter the total as well as allowing for the inclusion of hours spent on social media that participants believed fell outside of the above categories.

No scoring was necessary for Social Media Usage as the responses were already in hours.

Analysis

After results were gathered and scored, they were analyzed using SPSS in order to determine the extent to which a correlation between FoN and SMU can be observed. Namely, the following analyses were run using SPSS: bivariate correlation (Figure. 1), partial correlation (Figure. 2), & linear regression (Figure. 3). Below are the results for each analysis followed by a brief discussion of their meaning and significance.

Results

Figure. 1

This first test (Figure. 1) was a simple bivariate correlation analysis that assesses the degree of correlation between a variety of 2 variable pairs. As you can see, social media usage and feelings of nihilism showed a negative correlation significant at the 0.05 level. Specifically the significance value of the correlation is 0.034, which is relatively strong, however it is important to note that this only assesses the correlation between the 2 variables without controlling for anything else. This is important as feelings of nihilism and mental health problem show an even more significant correlation at 0.028. Given this, it is important to test whether or not FoN remains correlated with SMU when MHP is controlled for.

Figure. 2

This chart (Figure. 2) shows the results of a partial correlation test wherein MHP is controlled for. As you can see the significance value for the correlation between SMU and FoN has increased from 0.034 to 0.075 implying a decrease in significance and placing the correlation between the two variables outside of the 0.05 level significance threshold. At this point, then, it would seem that for the purposes of this study it cannot be concluded that there is a correlation between feelings of nihilism and social media usage when controlling for mental health conditions. Before discussing the implications of these findings it was also worthwhile to run linear regression analysis to get a view of the larger picture.

Figure. 3

The above (Figure. 3) shows the results of a linear regression analysis testing the relationship between the predicted variable, FoN, and two predictor variables, SMU & MHP. What these results indicate is that MHP had a higher significance score than SMU, meaning that MHP is a stronger predictor of FoN than SMU. However, it is worth noting that neither of the two variables achieved significance at the 0.05 level.

Discussion

Of the information gleaned from these results, the fact that the correlation between FoN and SMU (without control) is negative is of particular interest. As the study was initially inspired by an observed rise in nihilistic humour among young adults online, it was expected that should a correlation exist between the two variables that it would be positive. Rather, the negative correlation that was observed actually implies that, when MHP is not controlled for, participants who used social media more often reported experiencing feelings of nihilism less frequently. While this study is only preliminary and any results should be taken with a grain of salt, it is nonetheless interesting to examine what this correlation might imply about the nature of the relationship between FoN and SMU. Should a more expansive study show similar results, this might imply a number of relationships between the two variables. For instance, it is possible that those who experience FoN more frequently end up using social media less often. Alternatively, it could be that more frequent use of social media and the increased connectivity with other individuals that accompanies it may reduce FoN. Nonetheless, this research is still only preliminary and further research is necessary before any such conclusions are drawn.

Particularly, the lack of a statistically significant relationship when controlling for MHP must be discussed. While it would at first seem that these results indicate a lack of correlation between feelings of nihilism and social media usage, the reality is not so simple. Firstly, the inherent overlap between FoN and MHP (particularly depression) means that one cannot be certain of the extent to which each variable is being accurately analyzed. While the MHI-5 survey form used to assess MHP has significant research reinforcing the forms usefulness in assessing existing mental health problems, it is far from an actual psychological diagnosis. It is difficult to say then where the line between the two variables exists. Second, as the relationship between FoN and MHP is itself not established, one can also not be certain of the degree to which the variables need to be separate. It is possible, for instance, that given the similarities between the symptoms of MHP and FoN that the experience of FoN could contribute to MHP. Should this be the case it would not stand to reason that overlap between the variables requires controlling for one or the other as they may be measuring the same thing depending on the context. This is not to say that FoN and MHP are innately linked, as one can reasonably assume that FoN may arise without MHP (particularly from a philosophical perspective). Rather, this means that a particular question meant to assess either MHP or FoN might also be feasibly used to assess the other, and that as a result a positive response to said question may be the result of the presence of the variable not being tested for. For example, one may ask a participant to rate how often "they have been a happy person" intending to assess the existence of MHP. However, a participant who does not have any MHP may still answer positively to such a question as a result of their FoN.

With this in mind there are several key conclusions to be drawn from this study, as well as areas upon which future research may build. First, it can be concluded that FoN and SMU are at the very least negatively correlated when other variables are not controlled for. It may be valuable, then, to attempt to control for other variables besides MHP and also to test different sample populations. Those who belong to demographics with a different relationship to technology and social media, for instance, may not have the same relationship between FoN and SMU. Another possible avenue for future research may be in assessing the relationship between FoN and MHP as well as research into the nature of FoN as a variable in and of itself. As mentioned earlier, this may take the form of analyzing the extent to which FoN and MHP overlap and whether or not the nature of the variables requires that they be controlled for when studying one or the other.

Researcher Biography

This study is the work of Richard Howard, a 4th year professional communication student at Ryerson University. He is completing a Bachelor of Arts with minors in both philosophy and public relations.

Having previously studied electrical engineering at the University of Waterloo, his interests include technology, digital communication, and philosophy. Of particular interest is the application of philosophical concepts to other fields such as communication.

References

36-Item Short Form Survey Instrument (SF-36). (n.d.). RAND Corporation. https://www.rand.org/health-care/surveys_tools/mos/36-item-short-form/survey-instrument.html

van der Velden, P. G., Setti, I., van der Meulen, E., & Das, M. (2019). Does social networking sites use predict mental health and sleep problems when prior problems and loneliness are taken into account? A population-based prospective study. Computers in Human Behavior, 93, 200–209. https://doi.org/10.1016/j.chb.2018.11.047

Created By
Richard Howard
Appreciate

Credits:

Created with an image by Ali Yahya - "A man waiting for his date that never came. Sad."