
IMPACT OF SOCIAL MEDIA ON YOUTH'S MENTAL HEALTH
By Khadija Abdullahi for We Hold a Hand
ABSTRACT
Social media has changed how we engage, communicate, and retrieve information. Over the past decade, it has had a significant impact on our daily lives; its use has skyrockete,d leading to a decrease in face-to-face interactions amongst youth. It has some benefits like improved communication, sharing of information, job opportunities, but nevertheless it has some disadvantages such as cyberbullying, misinformatio,n and scams. Excessive use of social media has been associated with lower psychological well-being; however, the quality rather than the quantity can determine whether the experience will increase or decrease the user’s mental health. This study aims at exploring the impact of social media on the mental health of youths and identifying ways to reduce the negative effects. Fifteen individuals (n=15) volunteered for the study and were subjected to a 24-hour social media detox. There was a significant positive mood change after the detox. Which suggests that the participants were in a better mood after the detox. At the end of the experiment, social media was found to have a positive impact on mood and stress.
INTRODUCTION
Before the rise of social media, youth behavior was largely influenced by face-to-face interactions, traditional media (television, radio, newspapers), and direct communication with peers and family (Boyd & Ellison, 2007). Social media has changed how we engage, communicate and retrieve information (Raju, 2025). Over the past decade it has had a significant impact on our daily lives, its use has skyrocketed leading to a decrease in face-to-face interactions amongst youth (Allen, 2019). It has some benefits like improved communication, sharing of information, job opportunity but nevertheless it has some disadvantages such as cyberbullying, misinformation and scams (Raju, 2025).
Millions of people suffer from mental health illnesses around the world. Mental health disorders can greatly hinder everyday activities, people with mental health conditions encounter difficulties in their social, work, and personal lives. Disorders like depression and anxiety can result in lower productivity and a diminished quality of life. There has been a recent increase in the use of social media amongst youth which has been associated with poor self-esteem and loneliness. This study aims at exploring the impact of social media on the mental health of youths and identifying ways to reduce the negative effects.
LITERATURE REVIEW
Before the rise of social media, youth behavior was largely influenced by face-to-face interactions, traditional media (television, radio, newspapers), and direct communication with peers and family. Socialization occurred in physical settings such as schools, community centers, and family gatherings (Boyd & Ellison, 2007). After the introduction of social media, youth behavior has shifted towards increased screen time, online socialization, and reliance on digital communication (Griffiths and Kuss, 2017). In 2021, more than half of the world population had a social media account, and the average user spends a couple of hours per day on average on social media platforms (Braghieri et al., 2022). Excessive use of social media can have severe consequences, starting with anxiety and potentially leading to depression (Bashir and Bhat, 2017, Khalaf et al., 2023). Although, the impact of social media on a user's mental health depends more on how they engage with it rather than how much time they spend on it (Zsila and Reyes, 2023). Social media has improved communications between friends and family regardless of the distance. It has become a powerful tool for raising awareness about mental health issues, reducing stigma, and promoting empathy and understanding. It is used for marketing and promotions for businesses and brands, like ads on Instagram and Facebook, it has also made searching and gaining knowledge easier, it provides job opportunities (content creator), networking opportunities (Raju, 2025).
METHODS AND METHODOLOGIES
Experimental Design
For the study, we used quantitative data, to examine the psychological effect of a 24-hour detox social media detox on mood and stress levels. Problematic internet use has been associated with a coping strategy for dealing with unpleasant emotions (Gioia et al., 2021). The aim was to determine if there was a change in mood, productivity and stress level after a temporary abstinence from social media and to assess participants willingness to reduce social media usage.
Participants
Fifteen individuals (n=15) volunteered for this study, smaller sample size may limit generalizability however they can provide preliminary insights into behavior trend (Valkenburg et al., 2022) inclusion criteria required active social media users who were willing to refrain from social media (Frost et al., 2021) for 24 hours. No restriction was placed on age, sex, and frequency for social media use.
Procedure
We used a structural approach for data collection.
- Pre-detox phase; the participants reported in a questionnaire the social media app they use frequently, the number hours spent on it daily and reason. They also reported their initial mood on a numerical scale of 0-10 and how often they observed a change in their stress level and their thoughts on the impact of social media on their mental health, before going off social media.
- Detox phase the abstained from social media for 24 hours.
- Post-detox phase; the participants reported their mood level on a scale of 0-10, their stress level, a loss or increase in social connection, productivity level, and what they spent their time on during the detox. Additional questions assessed participants' willingness to reduce social media usage and assess their perceived mental health benefit after the detox.
Some of the questions asked are:
- On average, how many hours do you spend on social media?
- In the past 24 hours, how often have you felt stressed, anxious, or overwhelmed?
- Did you notice any change in your productiveness during the detox?
Formulas Used
- Mood Change
Mood_Change = Mood_After - Mood_Before
- Ordinal to Numeric Mapping
- Stress Before:
- Never = 0, Rarely = 1, Sometimes = 2, Often = 3, Always = 4
- Never = 0, Rarely = 1, Sometimes = 2, Often = 3, Always = 4
- Stress Change:
- Less stressed = +1, Same = 0, More stressed = –1
- Less stressed = +1, Same = 0, More stressed = –1
- Mood Influence:
- Stress Before:
- Positively = +1, Maybe = 0, Negatively = –1
- Reduce Usage:
- Yes = 1, Maybe = 0.5, No = 0
- Correlation Coefficient (r)
Pearson's formula used for numeric fields
STATISTICAL ANALYSIS
Data were analysed using Pearson’s correlation coefficient (r) to assess relationships between mood change and other variables (Field, 2018). A p-value was calculated to determine statistical significance. Values of p > 0.05 were considered statistically insignificant.
RESULTS
Mood and Stress Outcomes.
Mood: Average mood increased after the 24-hour detox. There was a significant proportion of the participants experienced a positive mood change after the detox. Which suggests that the participants were in a better mood after the detox.
Stress: Participants reported less stress overall.
Mood Distribution
A significant number of the participants showed an improvement in their moods, with few experiencing neutral or negative moods.
Variables Compared | Correlation (r)
| Interpretation
Mood Change ↔ Mood After
| +0.80 | Strong – greater improvement led to higher mood after
Mood Change ↔ Stress Change Score | +0.61 | Strong – less stress linked with mood boost
Mood Change ↔ Mood Before | –0.63
| Moderate – those starting lower improved more
Mood Change ↔ Reduce_Usage | +0.35
| Moderate – improved mood → more open to usage reduction
| Interpretation
Mood Change ↔ Mood After
| +0.80 | Strong – greater improvement led to higher mood after
Mood Change ↔ Stress Change Score | +0.61 | Strong – less stress linked with mood boost
Mood Change ↔ Mood Before | –0.63
| Moderate – those starting lower improved more
Mood Change ↔ Reduce_Usage | +0.35
| Moderate – improved mood → more open to usage reduction
Correlation coefficient (r) ≈ 0.35
P-value ≈ 0.19 which indicates that the results are not statistically significant likely due to sample size limitation.
Correlations Summary
Variables | Correlation | Interpretation
Mood_Before ↔ Mood_After | -0.04 | No relation (people with low mood before didn’t always improve more)
Mood_Change ↔ Mood_After | +0.80 | Strong — greater improvement = higher post-detox mood
Mood_Change ↔ Mood_Before | -0.63 | Negative — those who started lower improved more
Mood_Change ↔ Stress_Change_Score | +0.61 | Strong — less stress = improved mood
Mood_Change ↔ Reduce_Usage | +0.35 | Moderate — improved mood = more willing to cut usage
Mood_Change ↔ Mood_Influence_Score | +0.50 | Moderate — mood improvement matched perceived mental health benefits
Stress_Before_Score ↔ Mood_Before | -0.50 | Moderate — high stress = lower mood before detox
Mood_After ↔ Mood_Influence_Score | +0.58 | Strong — happier people after detox believed it helped.
Mood_Before ↔ Mood_After | -0.04 | No relation (people with low mood before didn’t always improve more)
Mood_Change ↔ Mood_After | +0.80 | Strong — greater improvement = higher post-detox mood
Mood_Change ↔ Mood_Before | -0.63 | Negative — those who started lower improved more
Mood_Change ↔ Stress_Change_Score | +0.61 | Strong — less stress = improved mood
Mood_Change ↔ Reduce_Usage | +0.35 | Moderate — improved mood = more willing to cut usage
Mood_Change ↔ Mood_Influence_Score | +0.50 | Moderate — mood improvement matched perceived mental health benefits
Stress_Before_Score ↔ Mood_Before | -0.50 | Moderate — high stress = lower mood before detox
Mood_After ↔ Mood_Influence_Score | +0.58 | Strong — happier people after detox believed it helped.
DISCUSSION
The experiment was carried out to assess the impact of social media on the mental health of youth. The pathophysiology of psychiatric disease including depression and anxiety is significantly influenced by stress (Sulakhiye et al., 2016). A positive mood change after the detox was observed which could be as a result of an increased social connectedness and life satisfaction, decrease in anxiety and stress, and improvement on the quality of sleep (de Hessele and Montag, 2024; Coyne and Woodruff, 2023). From the result obtained it could be deduced that different use and motive can explain why people have high screen time but low problematic social media use, motives like information seeking and work.
CONCLUSION
This study surveyed the psychological impacts of a 24-hour social media detox on mood, stress and overall wellbeing of youths. Social media improves communication, awareness, job opportunity and can be used to gain knowledge, however it is used for cyberbullying, disseminating false information, users may experience the fear of missing out and excessive usage has been associated with low psychological wellbeing.
These findings emphasize the need for promoting mindful social media use, while complete avoidance may not be feasible or beneficial to everyone, structured detox periods could be an effective approach in mental health therapy and prevention. Future studies should involve larger and more diverse groups to enhance the applicability of these findings and investigate the long-term effects. This research emphasizes that digital wellbeing is not about complete abstinence but rather on knowing when to connect and disconnect and also separating fiction from reality.
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