Psychological Distress & Social Media
Psychological distress and problematic social media use among Moroccan youth mediated by fear of missing out and social media engagement
Based on a cross-sectional study of Moroccan adolescents and young adults (N=2202), this paper identifies a 25.5% prevalence of problematic social media use (PSMU). It highlights significant associations between PSMU and psychological distress (depression, anxiety, stress), with fear of missing out (FoMO) and social media engagement (SME) partially mediating these relationships. The study reveals higher PSMU rates among females, older adolescents, urban residents, and those with lower socioeconomic status. The model explained 35% of the variance in PSMU, underscoring the need for tailored interventions.
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Prevalence of Problematic Social Media Use (PSMU) among Moroccan youth
Key Organizational Impact
Insights from this research highlight critical areas for developing effective digital well-being strategies within youth-focused programs and educational institutions.
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Variance in PSMU Explained
Higher
Among Females & Older Youth
Strongest
FoMO & SME Mediation
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Key Insights from the Study
The study found a 25.5% prevalence rate of Problematic Social Media Use (PSMU) among Moroccan adolescents and young adults. This rate is comparable to global averages in upper-middle-income regions. PSMU was notably higher among females (27.5% vs 22.6% males), older adolescents, urban residents, and those from lower socioeconomic backgrounds. Psychological distress (depression, anxiety, and stress) was positively and significantly correlated with PSMU. Furthermore, Fear of Missing Out (FoMO) and Social Media Engagement (SME) were identified as partial mediators in the relationship between psychological distress and PSMU, indicating complex interaction pathways.
Study Design and Participants
This was a cross-sectional survey (N=2202) conducted among Moroccan adolescents and young adults (1298 females, 904 males) aged 14-23 years (M=16.81; SD=1.23). Participants were recruited from secondary schools in both urban and rural areas using stratified random sampling. A mixed-mode data collection (paper and online via Google Forms) was employed. Validated instruments included the Bergen Social Media Addiction Scale (BSMAS) for PSMU, DASS-21 for depression, anxiety, and stress, the Fear of Missing Out (FoMO) scale, and the Social Media Engagement Questionnaire (SMEQ).
Analytical Approach & Key Findings
Statistical analyses included descriptive statistics, Pearson correlations, and multiple mediation models using Structural Equation Modeling (SEM). The SEM model demonstrated an excellent fit to the data (x²(3) = 4.141, p = 0.232) and explained 35% of the total variance in PSMU (R² = 0.35), indicating a substantial effect. Depression, anxiety, and stress were all positively associated with PSMU, both directly and indirectly. FoMO (β = 0.291) and SME (β = 0.241) emerged as significant predictors and mediators, highlighting their crucial role in the pathways from psychological distress to problematic social media use.
Broader Implications for Well-being
The findings underscore the significant public health concern of PSMU in the MENA region. The interplay between psychological distress and social media behaviors suggests a critical need for culturally tailored prevention and intervention programs. These programs should focus on promoting healthier digital habits, enhancing emotional management skills, reducing FoMO, and strengthening digital literacy. Furthermore, acknowledging socioeconomic and demographic disparities in PSMU rates is vital for equitable and effective interventions, aiming to safeguard adolescent well-being in an increasingly digital world.
Enterprise Process Flow
Psychological Distress (Depression, Anxiety, Stress)
→
Fear of Missing Out (FoMO)
→
Social Media Engagement (SME)
→
Problematic Social Media Use (PSMU)
| Factor Category | Specific Factors |
|---|---|
| Demographics |
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| Socioeconomic |
|
| Behavioral |
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| Primary Internet Activity |
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Impact of Psychological Distress on PSMU
Scenario: A Moroccan adolescent experiencing elevated levels of depression and anxiety, struggling with traditional coping mechanisms, increasingly turns to social media for solace and distraction. This heightened engagement, particularly driven by a fear of missing out on social interactions and updates (FoMO), leads to compulsive checking behavior and excessive time spent online, ultimately exacerbating their problematic social media use. The platform's algorithm-driven content and constant social feedback further reinforce this cycle.
Outcome: Without targeted interventions addressing underlying psychological distress and fostering healthier digital habits, the adolescent's well-being is further compromised, demonstrating the complex interplay of emotional vulnerability and digital engagement in PSMU.
Advanced AI ROI Calculator
Estimate the potential savings and reclaimed productivity hours by implementing AI solutions tailored to reduce PSMU and enhance well-being.
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Our AI Implementation Roadmap
A structured approach to integrating AI solutions for youth digital well-being, from initial assessment to ongoing optimization.
Phase 1: Assessment & Strategy
Analyze current PSMU prevalence, identify key distress factors, and define intervention goals. Develop a tailored AI strategy, including content moderation, personalized well-being resources, and FoMO reduction tools.
Phase 2: Pilot Program & Refinement
Implement AI tools in a pilot group of adolescents, collecting feedback and performance metrics. Iterate on the AI models and intervention strategies based on real-world data to maximize effectiveness and cultural relevance.
Phase 3: Full-Scale Implementation
Roll out the refined AI solution across the target population, integrating it seamlessly with existing educational and support systems. Provide training for educators and counselors on leveraging AI insights for personalized interventions.
Phase 4: Monitoring & Optimization
Continuously monitor PSMU trends, psychological well-being indicators, and AI system performance. Use advanced analytics to identify new patterns, predict risks, and further optimize AI interventions for sustained positive impact.
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