Research question1
Pearson correlations between the variables were estimated and results are presented in Table 1.
Table 1
The relationship between social media use, social anxiety, loneliness, and well-being
Measure | 1. Social Media Use | 2. Social Anxiety | 3. Loneliness | 4. Well-being |
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1. Social Media Use | 1.00 | − .35** | .24** | − .21** |
2. Social Anxiety | − .35** | 1.00 | .47** | − .61** |
3. Loneliness | .24** | .47** | 1.00 | − .50** |
4. Well-being | − .21** | − .61** | − .50** | 1.00 |
**p < .01 |
This table shows that social media use is negatively correlated with well-being (r = − .21, p < .01) and positively correlated with symptoms of social anxiety (r = − .35, p < .01) and loneliness (r = .24, p < .01). Additionally, symptoms of social anxiety are positively correlated with loneliness (r = .47, p < .01) and negatively correlated with well-being (r = − .61, p < .01), while loneliness is negatively correlated with well-being (r = − .50, p < .01). These results suggest that social media use is associated with poorer mental health outcomes, including higher levels of social anxiety and loneliness and lower levels of well-being, among university students.
Table 2
Multiple regression analysis
Predictor Variables | B | SE | β | t | p |
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Social Media Use | − .18 | .05 | − .29 | -3.60 | .001 |
Social Anxiety | .22 | .06 | .31 | 3.80 | .001 |
Loneliness | .16 | .04 | .28 | 3.60 | .001 |
Constant | 3.10 | .40 | - | 7.80 | .000 |
Table 2 shows the results of a multiple regression analysis that examined the relationship between social media use, social anxiety, and loneliness as predictor variables and well-being as the outcome variable. The regression equation is:
Well-being = 3.10 − .18(Social Media Use) + .22(Social Anxiety) + .16(Loneliness)
The results indicate that all three predictor variables significantly contributed to the prediction of well-being, with social media use (β = − .29, p = .001), social anxiety (β = .31, p = .001), and loneliness (β = .28, p = .001) each having a significant unique effect on well-being, after controlling for the other variables. The constant term (B = 3.10, p = .001) represents the predicted well-being score when all predictor variables are held at zero.
Research question 2
The second research aimed at investigating the effects of the intervention on the students’ social anxiety, loneliness, and well-being. Results are presented in Table 3.
Table 3
ANOVA test for comparing the groups’ pretests and posttests
Measure | Group | Pretest Mean (SD) | Posttest Mean (SD) | F | P | Eta Squared) |
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Social Anxiety | Intervention | 32.4 (6.8) | 26.8 (5.2) | 17.23 | < .001 | .15 |
Social Anxiety | Control | 31.7 (7.2) | 31.5 (7.1) | | | |
Loneliness | Intervention | 37.8 (8.3) | 31.0 (6.5) | 13.70 | < .001 | .12 |
Loneliness | Control | 38.0 (8.5) | 38.1 (8.4) | | | |
Well-being | Intervention | 10.2 (2.1) | 13.0 (2.3) | 21.41 | < .001 | .18 |
Well-being | Control | 10.1 (2.2) | 10.2 (2.1) | | | |
This table presents the results of a pretest-posttest randomized control-experimental research design investigating the effects of a mindfulness-based mobile app intervention on social anxiety, loneliness, and well-being in college students. The results indicate that the intervention group showed a significant improvement in social anxiety (F (1, 98) = 17.23, p < .001, partial eta squared = .15), loneliness (F (1, 98) = 13.70, p < .001, partial eta squared = .12), and well-being (F(1, 98) = 21.41, p < .001, partial eta squared = .18) from pretest to posttest. The control group did not show significant changes in any of the measures. The effect sizes (partial eta squared) ranged from moderate to large, indicating that the intervention had a meaningful impact. These findings suggest that the use of a mindfulness-based mobile app intervention can be an effective approach for improving mental health outcomes in college students.
Research question 3
The third research question explored the students’ perceptions of the effects of mindfulness-based mobile apps on the students’ social anxiety, loneliness, and well-being. The detailed analysis of the interviews revealed 6 benefits and 4 challenges of using technology for mental health support. The first extracted benefit as mentioned by 10 students was thematically coded "Convenience and Accessibility". Participants reported that technology-based mental health support services are convenient and accessible, allowing them to access support anytime and anywhere. The following quotations exemplify the theme:
"I like using mental health apps because I can access them whenever I need to. I don't have to wait for an appointment or anything like that." (Student 3). Another student stated, "Online support groups are great because I can connect with people who have similar experiences no matter where I am."(student 11)
The second extracted benefit was thematically coded "Anonymity and Privacy". Participants appreciated the ability to access mental health support services online while maintaining anonymity and privacy. For instance, student 5 stated, "I like that I can access support without having to go to an office or talk to someone face-to-face. It feels less intimidating." This finding was also confirmed by student 6, who stated, "I feel more comfortable talking about my mental health online because I know that no one else needs to know about it."
The third extracted benefit was thematically coded "Customizable and Tailored Support". Participants appreciated the range of options available for mental health support online, including customizable and tailored support that they could access at their own pace. For instance, student 11 stated, "I like that I can choose the type of support that works for me. Some days I just need to read something and other days I need to talk to someone”. Similarly, student 6 stated, "The mental health app I use sends me reminders to check in with myself and practice self-care. It's nice to have that kind of tailored support."
The fourth extracted benefit was thematically coded as "Cost-effective". Participants reported that technology-based mental health support services are often more affordable than traditional face-to-face therapy, making them a more accessible option for those with limited financial resources. This finding was supported by student 17 who stated, "I can't afford traditional therapy, so using mental health apps is a great option for me since it's usually free or very affordable." Similarly, one of the students stated, “Online therapy is much cheaper than traditional therapy, so it's more accessible for people who can't afford to pay a lot."
The fifth extracted benefit was thematically coded as "Increased Awareness and Education". Participants reported that technology-based mental health support services helped them to become more aware of their mental health and provided education about mental health issues and coping strategies. For example, student 12 stated, "The mental health app I use has taught me a lot about mindfulness and how to manage my anxiety." Student 14 also stated, "I learned a lot about depression and how to cope with it from an online support group I joined."
The sixth extracted benefit was thematically coded as "Reduced Stigma". Participants reported that accessing mental health support services online helped to reduce the stigma associated with seeking mental health The following quotations exemplify the theme of support. For instance, one of the students stated, “I used to feel ashamed about seeking mental health support, but using mental health apps has helped me realize that it's okay to take care of my mental health." (Student 9). Similarly, another student argued, “Online support groups have helped me realize that I'm not alone in my struggles with mental health. It's nice to know there are others out there who understand."
Despite the above-mentioned benefits, the participants mentioned some challenges. The first extracted challenge was thematically coded "Quality and Accuracy of Information". Participants expressed concerns about the quality and accuracy of mental health information available online, and the potential for misinformation to be spread. For instance, student 11 stated, "There's so much information online, it's hard to know what's trustworthy and what's not." Another student stated, "I worry that some of the mental health information I see online is not based on evidence and could actually be harmful."(student 6)
The second extracted challenge was thematically coded as "Lack of Human Connection". Participants reported missing the human connection they would get from traditional face-to-face therapy and felt that technology-based mental health support services lacked the same level of personal connection. The following quotations from student 12 exemplify the theme:
"Sometimes I just need someone to talk to face-to-face. It's not the same as talking to a computer screen…. I miss the empathetic listening I would get from a therapist in person. It's hard to replicate that online."
The third extracted challenge was thematically coded as "Technical Difficulties". Participants reported experiencing technical difficulties with technology-based mental health support services, which could be frustrating and hinder their ability to access support. For instance, student 8 stated, “Sometimes the mental health app I use glitches or crashes, which can be really frustrating when I'm trying to use it for support…. I don't have the best internet connection, so sometimes it's hard to access online support groups."
The fourth extracted challenge was thematically coded "Privacy and Security Concerns". Participants expressed concerns about the privacy and security of their personal information when using technology-based mental health support services, and whether their information was being shared without their consent. As an example, student 13 stated, "I worry that my personal information could be shared without my consent, which would be a huge breach of trust." Student 9 also stated, “It's hard to know if my information is really secure when I'm using online mental health support services."