The Impact of Social Media Use on Mental Health and Family Functioning Within Web-Based Communities in Saudi Arabia: Ethnographic Correlational Study
Bibliographic record
Abstract
BACKGROUND: In recent years, increasing numbers of parents, activists, and decision-makers have raised concerns about the potential adverse effects of social media use on both mental health and family functioning. Although some studies have indicated associations between social media use and negative mental health outcomes, others have found no evidence of mental health harm. OBJECTIVE: This correlation study investigated the interplay between social media use, mental health, and family functioning. Analyzing data from 314 users, this study explores diverse mental health outcomes. The study places particular emphasis on the Saudi Arabian sample, providing valuable insights into the cultural context and shedding light on the specific dynamics of social media's impact on mental well-being and family dynamics in this demographic context. METHODS: We collected data through a subsection of an anonymous web-based survey titled "The Effect of COVID-19 on Social Media Usage, Mental Health, and Family Functioning." The survey was distributed through diverse web-based platforms in Saudi Arabia, emphasizing the Saudi sample. The participants indicated their social media accounts and estimated their daily use. Mental health was assessed using the General Health Questionnaire and family functioning was evaluated using the Family Assessment Device Questionnaire. In addition, 6 mental health conditions (anxiety, self-esteem, depression, body dysmorphia, social media addiction, and eating disorders) were self-reported by participants. RESULTS: The study demonstrates a pattern of frequent social media use, with a significant portion dedicating 3-5 hours daily for web-based activities, and most of the sample accessed platforms multiple times a day. Despite concerns about social media addiction and perceived unhealthiness, participants cited staying connected with friends and family as their primary motivation for social media use. WhatsApp was perceived as the most positively impactful, whereas TikTok was considered the most negative for our Saudi sample. YouTube, Instagram, and Snapchat users reported poorer mental health compared with nonusers of these platforms. Mental health effects encompassed anxiety and addiction, with age and gender emerging as significant factors. Associations between social media use and family functioning were evident, with higher social media quartiles correlating with a greater likelihood of mental health and unhealthy family functioning. Logistic regression identified age and gender as factors linked to affected mental health, particularly noting that female participants aged 25-34 years were found to be more susceptible to affected mental health. In addition, multivariable analysis identified age and social media use quartiles as factors associated with poor family functioning. CONCLUSIONS: This study examined how social media affects mental health and family functioning in Saudi Arabia. These findings underscore the need for culturally tailored interventions to address these challenges, considering diverse demographic needs. Recognizing these nuances can guide the development of interventions to promote digital well-being, acknowledging the importance of familial connections in Saudi society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".