Phase II – Screen Time Log

Phase II: Screen Time Log

Participants who indicated interest and consent to continued study involvement were then contacted by the researchers. At this point, the participants’ survey number was used as a reference to maintain anonymity. The screen time logs are a collection of behavioural observation data, tracking how much time each participant spends on social media daily.

The screen time log was tracked across a one-week duration in the beginning of November 2021. Some participants had sent days that were not described by the example for the search but were still included in the data collection, recorded under the days they had provided. The screen time data was used to confirm social media screen time usage over the specified period of time. Social media usage data is collected and provided by most cellular phones (e.g., Apple and Android); this feature (if available) was used to date the back data to the week prior. By tracking the data before the meeting, possible limitations that may be caused due to participant bias were reduced. Farnsworth (2019) explains that “participants will sometimes second-guess what the researcher is after, or change their answers or behaviors in different ways, depending on the experiment or environment. This is called participant bias, or response bias, and it can have a huge impact on research findings” (para. 2).

The sample for the screen time log includes the young adults, aged 18–24, that had previously completed the initial survey and consented to disclose their social media usage data. This sample is not exclusive to university students, but through the availability of the personal outreach of the research team, it was assumed many of the participants would be students. The sample was localized to the Edmonton region. The sample participants were required to have the screen time tracking feature downloaded to their cellular phones, computer and/or other devices they use daily to qualify for continued participation.

Participants were required to have mobile devices with screen time tracking to represent the sample of social media users. Through “always on” technologies, the availability of communication is now the norm for many people for most of the day (Ling, 2012). Abstaining from media use and communication access is an action that now requires intentions, planning, and specific arrangements (Klimmt et al., 2018). The current climate of society calls for the use of mobile devices and social media in young adults’ daily routines, therefore providing the opportunity to track how much of the modern daily device usage is spent on social media.

Data collected was used to generate the average social media usage hours across the sample, as well as noting the maximum and minimal times. The data was then compared to the peer-reviewed research on addictions and social media usage to see how the data correlates to previous research and definitions. The data collected was measured at a ratio level, providing the ability to record precise hours of usage across all participants. The precise hours were then analyzed by external factors such as the participants’ general schedule, daily social availability, and the significance of the weekday to usage. Qualitative data measured these external factors  that control daily time and accessibility participants have to their devices for social media usage. The amount of time each participant has in their schedule available to use social media impacts the results. For example, if a participant is working or in classes that day, they may not have time to be on social media, compared to a day off where they have more time to spend online than usual. It is important to note that participants may have to use social media for their jobs. This factor may cause limitations and skew data; this was reduced by asking participants about the correlation between social media and work during this time.

In summary, the screen time log consists of data collection already provided by the participant’s cellular phone devices. This methodology requires education on how to access the desired data, and confirmation of the collected data’s validity. An example of a screen time data log was created to show what information was key in gaining a general sense of social media timing through quantitative data. The screen time log results were analyzed with the variables previously mentioned to generate an accurate representation of causal claims.