1. Background
Social media has become a vital tool in ensuring productivity among Undergraduates, as studies have shown an increased number of users globally [
1,
2]. It can be a website or an application that students utilize to interact with peers [
3], share ideas [
4], and become popular [
5]. It serves different purposes that aided online studies during the Covid-19 pandemic [
6], as social events were restricted. Most students have social media accounts like Facebook having, 2.9 billion monthly active users [
7]. Students have considered it helpful as it can help to maintain long-distance friendships and family relationships [
8].
Meanwhile, students obtain essential benefits such as scholarships [
9] and educative events [
10,
11] from some social media platforms. Considering benefits derived from Facebook, YouTube, WhatsApp, Instagram, Snapchat, Twitter, Google+, Pinterest, forums, etc., however, would be time-consuming. Most students tend to stay online for long hours [
12,
13] as some dedicate short hours to studies which could negatively affect their preparation for quizzes, exams, and academic performance [
14].
Studies have observed that social media could influence memory processes [
15,
16]. Working memory has remained the essential tool required for academic activities among students [
17]. Students utilize its availability to resolve issues and understand their study directives [
18,
19]. The process of how social media could influence working memory has not been well understood. Studies have shown that social media could have a positive effect [
4,
20,
21] that can help achieve educative and scientific [
14] activities to improve academic performance. Only a few students utilize social media to exploit educational purposes [
22]. In as much as there could be helpful events that can boost the knowledge and skills of a student, there has not been a significant association between social media usage and student GPA [
5,
23,
24]. Furthermore, most of these studies were not related to students working memory. Though good academic performance does not necessarily signify good memory, academic failure can be observed among students with memory issues [
25].
The study objective was to examine the influence of social media on undergraduates working memory and academic performance. The students were from three Universities: two from Tbilisi (the capital city) and one from Batumi. We assessed the association between the harmful use of social media on gender differences, physical activities, academic performance, and working memory. There are limited studies on this directive, and this study has helped in finding the relationship regarding such measures. This study would help the students to have a broad understanding of the wide-growing influence of social media in their careers.
Methodology
2.1. Study Design
This cross-sectional study was designed to examine the effect of social media on the working memory of undergraduate students from three different Universities in Georgia.
2.2. Data Collection
722 participants from three different universities completed this study. The collection survey form was distributed among Undergraduate students from the University of Georgia (UG), Eastern European University (EEU), and Batumi State University (BSU) through google forms. UG and EEU are in the capital city, and BSU is in Batumi City. Students from these universities were represented as they engaged each participant from 14th June to 2nd July 2023.
2.3. Participants
The study involved males and females above 18 years, Georgian and International students living and studying in Georgia. There was no reward to the participants as the responses were anonymous.
2.4. Informed Consent
Instructions and information on data privacy were available in the consent form and questionnaire to allow each participant to read through them before completing the study. The ethics approval for this study was provided by the Bioethics council of the University of Georgia.
2.5. Evaluation Tools and Techniques
The questionnaire consisted of sociodemographic characteristics (e.g., age, gender, and institution) and three sections; social media disorder scale (SMD), academic performance scale (APS), and working memory (WM).
SMD scale was developed based on nine DSM-5 criteria for internet gaming disorder which had a binary variable of yes/no responses with nine questions regarding the social media experience (e.g., Facebook, Twitter, Instagram, WhatsApp, Snap Chat, Pinterest, TikTok, Google+, weblogs, and forums) over the past year [
26]. Questions on preoccupation, tolerance, withdrawal, persistence, displacement, problems, deception, escape, and conflict were included in the measure which are elements of behavioral addictions [
27,
28,
29,
30,
31]. Based on DSM-5, an individual with five or more of the nine criteria for 12 months qualifies for internet addiction. [
26,
27].
APS comprises 8- questions with a 5-point Likert scale covering questions relating to students’ academic performance. Students were scored based as follows; strongly agree (5), agree (4), neutral (3), disagree (2), and strongly disagree (1). The criteria for rating the performance were excellent (33-40), good (25-32), moderate (17-24), poor (9-16), and failing (0-8).
WM has 30 questions divided into storage domain questions, attention domain, and executive domain [
32]. Each subcategory involved 10- questions presented randomly as storage domain questions representing the short-term storage ability of the participants, text comprehension, and mental articulation. The attention domain included questions on distractions and multitasking. The executive domain involved questions on the ability to make plans and decisions. Each question was rated on a 5-point Likert scale, from 4 (severe problems in daily life) to 0 (no problem). The maximal score for each domain was 40, and the total score was out of 120, as higher scores indicate more complaints [
33].
2.6. Statistical Analysis
The data was analyzed using Statistical Package for Social Science (SPSS Inc., Chicago, IL, version 25.0 for Windows) software. Descriptive analyses were assessed for all study populations, characteristics, frequencies, percentages, means, and standard deviations. We analyzed the comparison between gender difference, nationality, and Universities, and statistically significant at p<0.05. Before assessing the association between variables and multivariate analysis, APS and WM scores were grouped into dichotomous responses (Good/Needs improvement). The students that had cutoff < 24 were in ALS performance and > 25 WM subcategories, ‘’needs improvement’’. The odds ratio (OR) and prevalence evaluation at 95% confidence intervals (95% Cl) were presented.
3.0. Results3.1. Students’ Demographic Distribution
58.7% were female students (
Figure 1), the mean age was 21.94 (SD ± 2.8), and most of the participants were international students (
Figure 2) from all three universities (BSU, UG, and EEU,
Figure 3). In
Table 1, the distribution of social media usage disorder among the students was observed higher in certain categories such as preoccupation (41.6%), persistence (60.9%), displacement (44.3%), and escape (67.6%). In the Supplementary Table S1, 16.2% of students needed an improvement in their academic performance. The students that had higher scores (>25) in the storage domain (4.4%), attention domain (6.2%), and executive domain (4.4%) had complaints (Table S1).
From
Table 2, the student’s demographic analysis based on cities (Tbilisi and Batumi) showed that more students from Tbilisi had persistence (59.8%), escape (69%) complaints, and students from Batumi had more preoccupation (43%), persistence (62.5%) and escape (65.7%). Table S2, showed that 14.5% and 18.4% of students in Tbilisi and Batumi needed an improvement in their academic performance. Few students from WM subcategories had complaints. From Table S2, 4.1% and 4.9% of students from Tbilisi and Batumi respectively, had short term storage domain, as 6.1% ( Batumi) and 6.3% (Tbilisi) required more action in the short-term.
In
Table 3, students from UG had more complaints about persistence (58.7%), displacement (48.7%), and escape (67.9%), students from EEU had more complaints about preoccupation (44.2%), persistence (62.8%) and escape (73.5%), and students from BSU had more complaints on preoccupation (43%), persistence (62.5%), displacement (41.4), and escape (65.7). In Table S3, 16% (UG students), 18.4% (BSU students) and 10.6% (EEU students) complained of moderate to poor academic performance. As 7.3% (UG students), and 6.1 (BSU students) had more complaints with attention domain, 3.5% (EEU) had the same complaints in all WM subcategories.
3.2. Association between Social Media Usage Disorder, Gender Differences, and Physical Activities
From
Table 4, 35.9% of male students and 64.1% of female students are at increased risk of using social media as an escape from negative feelings (OR 0.50; χ2 (18.206), p= 0.000, 95% Cl[0.368-0.692]). 51.6% of male students and 48.4% of female students had the risk of conflict with families and friends because of social media (OR 1.65; χ2 (6.507), p= 0.011, 95% Cl[1.122-2.452]
Table 4).
As illustrated in
Table 5, 89.7% that perform physical activities, considering their academic workload had the risk of preoccupation complaints (OR 1.91); χ2 (5.379), p= 0.020, 95% Cl[1.097-3.329]). 87.9% felt dissatisfied regularly because they wanted to spend more time on social media (OR 2.23; χ2 (8.361), p= 0.004, 95% Cl[1.281-3.908]
Table 5). As 87.8% of students intended to neglect other activities because of social media (OR 3.34; χ2 (17.054), p= 0.000, 95% Cl[1.834-6.112]
Table 5).
3.3. Association between Social Media Usage Disorder, Academic Performance, and Working Memory
In
Table 6, 80.3% of students that had good academic performance are at risk of neglecting activities such as hobbies, sports, and class assignments because of social media (OR 0.63; χ2 (5.133), p= 0.023, 95% Cl[0.425-0.942]). Most of the students with good academic performance had the risk of having arguments with friends because of social media usage (90%, OR 1.13; χ2 (5.368), p= 0.021, 95% Cl[1.099-3.470]
Table 6).
Table 7 presented that 94% of students with good working memory had the risk of withdrawal complaints (OR 0.34; χ2 (6.865a), p= 0.009, 95% Cl[0.154-0.793]). As 93.4% of having conflicts with parents, siblings, and partners as a result of social media.
3.4. Multivariate Analyses Predicting Academic Performance among the Students
The multicollinearity in social media addiction was evaluated following that all independent variables did not strongly correlate with the dependent. In the final model, out of the fourteen variables represented, physical activities, displacement, and problems were significant correlates of academic performance (
Table 8). The strongest correlate was physical activities which had an adjusted odd ratio (aOR) of 2.18 times. Students that complained of neglecting other activities for the purpose of social media are likely to have poor academic performance (aOR1.59) which is the same with students that had arguments with others because of social media usage (aOR 0.47).