The Relationship Between Social Media Addiction and Social Phobia Among Saudi Adolescents: A Cross-Sectional Study

Abstract

Social media addiction (SMA) and social phobia (SP) are significant adolescent mental health concerns. In Saudi Arabia, despite high social media penetration, the association between these two constructs remains under-researched, particularly in the Aseer region. This cross-sectional study, conducted from January to March 2025, recruited 384 Saudi adolescents aged 11–19 from schools in the Aseer region using multistage cluster sampling. Participants completed validated self-report measures, including the Social Phobia Inventory (SPIN) and the Al-Menayes Social Media Addiction Scale. A refined “Core SMA” subscale was created based on expert consensus criteria to enhance measurement precision. The prevalence of moderate-to-severe social phobia was 15.6%. A significant, moderate positive correlation emerged between SP and SMA (Spearman’s ρ = 0.294, p < 0.001). After adjusting for age, gender, and family income, adolescents with moderate social phobia had 2.15 times the odds of probable SMA compared to those with no SP (adjusted odds ratio [AOR] = 2.15, 95% CI: 1.15–4.04, p < 0.05), and this effect was more pronounced for those with severe social phobia (AOR = 2.56, 95% CI: 1.04–6.30, p < 0.05). This study demonstrates a clear relationship between social phobia severity and social media addiction among Saudi adolescents in the Aseer region. These findings support the urgent need for integrated mental health and digital literacy interventions that proactively screen for both conditions.

1. Introduction

The proliferation of social media platforms has fundamentally transformed global communication patterns, with adolescents representing one of the most highly engaged user demographics [1]. In the Kingdom of Saudi Arabia, this digital transformation is particularly evident, characterized by near-universal smartphone ownership and the ubiquitous integration of platforms like Snapchat, TikTok, and Instagram into the daily lives of young people [2,3]. While these technologies offer unprecedented opportunities for social connection and self-expression, a growing body of empirical evidence links their excessive and problematic use to a range of adverse mental health outcomes, including depressive symptomatology, anxiety, and sleep disturbances [4,5].

Within the spectrum of adolescent mental health, social anxiety disorder (SAD), or social phobia, stands as one of the most prevalent anxiety conditions, with a typical onset during the developmentally sensitive period of adolescence [6,7]. Concurrently, the construct of “social media addiction” or problematic social media use—conceptualized as a behavioral pattern characterized by salience, mood modification, tolerance, withdrawal, conflict, and relapse—has gained significant recognition as a public health concern [8,9]. Emerging international research consistently demonstrates a significant positive association between these two phenomena [10,11]. Theoretical mechanisms proposed to explain this relationship include social comparison processes, where exposure to idealized online self-presentations fosters feelings of inadequacy [12], and the fear-of-missing-out (FOMO), which drives compulsive checking behaviors [13]. Furthermore, the displacement of critical face-to-face social interactions with digital communication may impede the development of social skills and reinforce avoidance behaviors, thereby maintaining or exacerbating social anxiety [14,15].

Despite the high penetration of social media and the established vulnerability of adolescents to anxiety disorders, a critical research gap exists in the Saudi context, particularly concerning the specific relationship between social media addiction and social phobia. Previous investigations within Saudi Arabia have primarily focused on the impact of social media on sleep quality [16], general mental health [17], or its prevalence among university students [18]. A recent study in the Aseer region, for instance, highlighted that over 40% of secondary school students reported daily social media use exceeding five hours, which was significantly associated with poor sleep quality [3]. However, no published study has yet specifically and simultaneously investigated social media addiction and social phobia among school-attending adolescents in this understudied region [19,20].

The relationship between these psychological constructs is frequently conceptualized through the lens of the ‘Social Compensation Hypothesis.’ This framework suggests that individuals exhibiting high levels of social phobia may preferentially utilize online communication channels to compensate for perceived deficits in face-to-face social skills, thereby lowering inhibition and satisfying social needs. Complementing this perspective, the ‘Interaction of Person–Affect–Cognition–Execution’ (I-PACE) model provides a mechanistic explanation for the transition from habitual usage to pathological behavior. The I-PACE model posits that addictive behaviors develop from a complex interaction between predisposing personal characteristics—such as social phobia—and maladaptive affective responses to digital triggers, including the Fear of Missing Out (FOMO) and negative social comparison [21,22].

Geographically, the Aseer region presents a unique cultural milieu within the Kingdom of Saudi Arabia. Although the region mirrors the nation’s globally high rates of digital adoption, it retains a distinct semi-urban social structure characterized by robust tribal and community ties [23]. This dichotomy creates a specific dynamic regarding social connectivity that may differ significantly from purely urbanized centers. Furthermore, acknowledging the biopsychosocial nature of adolescent development, physical health markers such as Body Mass Index (BMI) and behavioral factors like tobacco use have been consistently linked to adolescent anxiety in international literature; consequently, these variables were included as exploratory covariates in this study to ensure a comprehensive analysis.

Therefore, this study aims to bridge the existing empirical gap by examining the specific relationship between social media addiction and social phobia among adolescents in the Aseer Region. The findings are intended to provide essential foundational epidemiological data, which is critical for informing targeted public health interventions and designing mental health promotion strategies tailored to the unique needs of this vulnerable population.

2. Materials and Methods

2.1. Study Design and Setting

This analytic cross-sectional study was conducted between January and March 2025. The setting included public intermediate and secondary schools within the Aseer region, a major administrative area in southwestern Saudi Arabia.

2.2. Participants and Sampling

Inclusion criteria were Saudi adolescents aged 11–19 years currently enrolled in the selected schools. Exclusion criteria included refusal to participate, absence on the day of data collection, or submission of incomplete questionnaires (missing > 10% of items).

The study employed a multistage cluster sampling strategy. First, the Aseer region was stratified into its three principal governorates. Second, using a random number generator, three schools were randomly selected from the Ministry of Education’s comprehensive list for each governorate (Total = 9 schools). Third, three classes were randomly selected from each school (Total = 27 classes).

The minimum required sample size was calculated using OpenEpi (Version 3.0, Rollins School of Public Health at Emory University, Atlanta, Georgia, USA). Based on a previously reported 13% prevalence of social phobia [24], with a 5% margin of error, 95% confidence level, and 80% statistical power, the initial sample size was 174. To account for the cluster sampling method, a design effect of 2 was applied, increasing the minimum required sample size to 348.

A total of 452 students across the 27 selected classes were identified as eligible and invited to participate. From this group, 384 students provided assent and completed the survey, resulting in a final response rate of 85.0%. Non-participation (n = 68) was primarily due to student absence on the day of data collection (n = 40; 8.8% of those invited). The remaining eligible students declined to participate (n = 28; 6.2%).

2.3. Data Collection and Measures

Data were collected using a paper-based, structured, self-administered questionnaire. A trained team, including the principal investigator and two research nurses, was present during data collection to clarify any ambiguities for the participants. The questionnaire collected information on socio-demographics and included validated scales to assess social media use, addiction, and social phobia.

• Socio-demographic and Health Information: Data on socio-demographic variables, including age, gender, parental education, parental occupation, and monthly family income, were collected. Height and weight were directly measured by trained research staff to calculate Body Mass Index (BMI), which was then categorized based on World Health Organization (WHO) criteria.
• Social Media Use: Participants reported their daily time spent on social media (categorized as <3, 3–5, or >5 h) and identified the specific platforms they used from a checklist.
• Social Media Addiction (SMA): Assessed using the Al-Menayes Scale [25]. This 14-item instrument utilizes a 5-point frequency rating scale (1 = Rarely to 5 = Always) to measure symptoms of addictive behavior. An example item is “I neglect my school duties because of social media.” In the present study, the scale demonstrated good internal consistency (Cronbach’s α = 0.83). A total score was calculated, where higher scores indicate a greater degree of addiction.
• Social Phobia (SP): Measured using the Social Phobia Inventory (SPIN) [26]. This 17-item self-report scale assesses fear, avoidance, and physiological distress using a 5-point scale (0 = Not at all to 4 = Extremely). An example item is “I avoid talking to people in authority.” The validated Arabic version [27] demonstrated high reliability in this study (Cronbach’s α = 0.80). Total scores were used to classify severity: No/Minimal (0–20), Mild (21–30), Moderate (31–40), and Severe (41–68).

2.4. Ethical Considerations

The study protocol was approved by the Institutional Review Board (IRB) of the Armed Forces Hospital Southern Region. Written informed consent was secured from the parents or legal guardians of all participants, and written assent was obtained from the adolescents themselves. Participation was voluntary and anonymous, and the confidentiality of all data was maintained throughout the study.

2.5. Statistical Analysis

All data were analyzed using IBM SPSS Statistics for Windows (Version 28.0, IBM Corporation, Armonk, NY, USA). Descriptive statistics (frequencies, percentages) were generated to summarize participant characteristics, social media usage, and the prevalence of social phobia.

The Shapiro–Wilk test indicated that the social phobia scores were not normally distributed (p < 0.001), necessitating the use of non-parametric tests. Bivariate analyses of categorical variables were conducted using the Pearson Chi-square test, with Fisher’s exact test applied when expected cell counts were below five. The relationship between the continuous social media addiction score and the ordinal social phobia score was examined using Spearman’s rank correlation coefficient (ρ).

Binary logistic regression was used to model the relationship between explanatory variables and the likelihood of Social Media Addiction (SMA). The dependent variable was constructed through a theory-driven process adapted from Castro-Calvo et al.’s [28] international expert consensus on diagnostic criteria for gaming disorder. Consistent with recommendations to prioritize functional impairment over simple frequency of use, we created a ‘Core SMA’ subscale by computing the mean of six specific items from the Al-Menayes Scale. These items assess: neglect of school duties, withdrawal symptoms, familial complaints, grade deterioration, cancelation of social visits, and preoccupation. The internal consistency of this subscale was acceptable (Cronbach’s α = 0.80). Because the distribution of these scores violated the normality assumptions required for linear regression (Shapiro–Wilk test, p < 0.001) and lacking established clinical cut-offs for this specific population, the continuous score was dichotomized at the median to create the binary outcome (Non-Addicted Use vs. Probable SMA).

3. Results

3.1. Participant Characteristics

The study included 384 adolescent participants. Demographic and general characteristics are detailed in

Table 1. Demographic and General Characteristics of Participants (N = 384).

Variable	Category	N (%)
Gender	Male	224 (58.3)
	Female	160 (41.7)
Age (in years)	11–13	90 (23.4)
	14–16	203 (52.9)
	17–19	91 (23.7)
BMI	<18.5	122 (31.8)
	18.5–24.9	192 (50.0)
	25–29.9	38 (9.9)
	≥30	32 (8.3)
Monthly Family Income	<5000 SR	45 (11.7)
	5001–20,000 SR	262 (68.2)
	>20,000 SR	77 (20.1)
Educational Level of Father	Elementary or illiterate	26 (6.8)
	Intermediate or high school	170 (44.3)
	University or above	188 (48.9)
Educational Level of Mother	Elementary or illiterate	71 (18.5)
	Intermediate or high school	143 (37.2)
	University or above	170 (44.3)
Father Occupation	Unemployed or retired	108 (28.1)
	Military sector	163 (42.4)
	Non-military sector	113 (29.4)
Mother Occupation	Unemployed or retired	287 (74.7)
	Military sector	1 (0.3)
	Non-military sector	96 (25.0)
Current Smoking Status	Yes	17 (4.4)
	No	367 (95.6)
Social Phobia categories distribution	No Social Phobia	269 (70.1)
	Mild	50 (13.0)
	Moderate	37 (9.6)
	Severe	22 (5.7)

. The sample was predominantly male (58.3%, n = 224) and aged between 14 and 16 years (52.9%, n = 203). Half of the participants (50.0%, n = 192) had a normal BMI, while 31.8% (n = 122) were underweight. A majority (68.2%, n = 262) reported a monthly family income between 5001 and 20,000 Saudi Riyals. Regarding parental education, 48.9% (n = 188) of fathers and 44.3% (n = 170) of mothers had completed university-level education or higher. Most mothers were unemployed or retired (74.7%, n = 287). Current smoking was reported by 4.4% (n = 17) of participants.

Social phobia assessment data were available for 378 participants (98.4%). Of this subgroup, 71.2% (n = 269) were classified as having no social phobia. The remainder were categorized as having mild (13.2%, n = 50), moderate (9.8%, n = 37), or severe (5.8%, n = 22) social phobia.

3.2. Social Media Usage

As shown in

Table 2. Social Media Use Among Participants (N = 384).

Variable	Category	N (%)
Using social media	Yes	377 (98.2)
	No	7 (1.8)
Time spent on social media	<3 h	132 (34.4)
	3–5 h	152 (39.6)
	>5 h	99 (25.8)
Twitter (X)	Yes	109 (28.4)
	No	275 (71.6)
TikTok	Yes	285 (74.2)
	No	99 (25.8)
Instagram	Yes	188 (49.0)
	No	196 (51.0)
YouTube	Yes	313 (81.5)
	No	71 (18.5)
WhatsApp	Yes	319 (83.1)
	No	65 (16.9)
Snapchat	Yes	324 (84.4)
	No	60 (15.6)
Telegram	Yes	160 (41.7)
	No	224 (58.3)
Twitch	Yes	35 (9.1)
	No	349 (90.9)

Multiple selections were possible for social media platform use.

, social media use was nearly universal, with 98.2% (n = 377) of participants active on at least one platform. Among 383 respondents who provided data on usage duration, the most common daily duration was 3–5 h (39.6%, n = 152), followed by less than 3 h (34.4%, n = 132). Multiple selections were permitted for platform use. The most widely used platforms were Snapchat (84.4%, n = 324), WhatsApp (83.1%, n = 319), YouTube (81.5%, n = 313), and TikTok (74.2%, n = 285).

3.3. Association Between Participant Characteristics and Social Phobia

Associations between participant characteristics and social phobia severity were evaluated among the 378 participants with complete data (

Table 3. Association of Demographic and Behavioral Characteristics with Social Phobia Severity (N = 384).

Characteristic	No Social Phobia (n = 269)	Mild (n = 50)	Moderate (n = 37)	Severe (n = 22)	p-Value
Gender					0.003 *
Female	99 (36.8%)	22 (44.0%)	22 (59.5%)	15 (68.2%)
Male	170 (63.2%)	28 (56.0%)	15 (40.5%)	7 (31.8%)
Tobacco Use					0.598
No	259 (96.3%)	46 (92.0%)	35 (94.6%)	21 (95.5%)
Yes	10 (3.7%)	4 (8.0%)	2 (5.4%)	1 (4.5%)
Body Mass Index					0.894
Underweight	88 (32.7%)	16 (32.0%)	10 (27.0%)	7 (31.8%)
Normal	132 (49.1%)	24 (48.0%)	21 (56.8%)	11 (50.0%)
Overweight	25 (9.3%)	7 (14.0%)	3 (8.1%)	3 (13.6%)
Obese	18 (6.7%)	3 (6.0%)	3 (8.1%)	0 (0.0%)
Morbidly Obese	6 (2.2%)	0 (0.0%)	0 (0.0%)	1 (4.5%)
Father’s Education					0.558
Elementary or less	18 (6.7%)	1 (2.0%)	4 (10.8%)	2 (9.1%)
Intermediate or high school	118 (43.9%)	26 (52.0%)	16 (43.2%)	7 (31.8%)
University or above	133 (49.4%)	23 (46.0%)	17 (45.9%)	13 (59.1%)
Mother’s Education					0.515
Elementary or less	43 (16.0%)	10 (20.0%)	10 (27.0%)	6 (27.3%)
Intermediate or high school	106 (39.4%)	16 (32.0%)	13 (35.1%)	6 (27.3%)
University or above	120 (44.6%)	24 (48.0%)	14 (37.8%)	10 (45.5%)
Family Income (SAR)					0.007 †
Less than 5000	26 (9.7%)	2 (4.0%)	8 (21.6%)	6 (27.3%)
5001–20,000	189 (70.3%)	37 (74.0%)	25 (67.6%)	9 (40.9%)
More than 20,000	54 (20.1%)	11 (22.0%)	4 (10.8%)	7 (31.8%)
Father’s Occupation					0.705
Unemployed or Retired	77 (28.6%)	11 (22.0%)	11 (29.7%)	7 (31.8%)
Non-military sector	75 (27.9%)	14 (28.0%)	14 (37.8%)	7 (31.8%)
Military sector	117 (43.5%)	25 (50.0%)	12 (32.4%)	8 (36.4%)
Mother’s Occupation					0.006 †
Unemployed or Retired	198 (73.6%)	38 (76.0%)	31 (83.8%)	15 (68.2%)
Non-military sector	71 (26.4%)	12 (24.0%)	6 (16.2%)	6 (27.3%)
Military sector	0 (0.0%)	0 (0.0%)	0 (0.0%)	1 (4.5%)
Social Media Use					0.045 *
Less than 3 h	96 (35.8%)	20 (40.0%)	10 (27.0%)	3 (13.6%)
3–5 h	108 (40.3%)	21 (42.0%)	13 (35.1%)	8 (36.4%)
More than 5 h	64 (23.9%)	9 (18.0%)	14 (37.8%)	11 (50.0%)

Data are presented as n (%). * Statistically significant (p < 0.05) based on the Chi-square test. † Statistically significant (p < 0.05) based on Fisher’s exact test. SAR: Saudi Riyal.

). A significant association was found between social phobia severity and gender (p = 0.003); the proportion of females increased across the severity levels, from 36.8% in the no-anxiety group to 68.2% in the severe group.

Statistically significant associations were also observed for time spent on social media (p = 0.045), family income (p = 0.007), and mother’s occupation (p = 0.006). The percentage of participants using social media for more than 5 h daily rose from 23.9% in the no-anxiety group to 50.0% in the severe phobia group. No significant associations were found between social phobia severity and tobacco use (p = 0.598), BMI (p = 0.894), father’s education (p = 0.558), mother’s education (p = 0.515), or father’s occupation (p = 0.705).

3.4. Correlation Between Social Phobia and Social Media Addiction

A bivariate correlation analysis was conducted to assess the relationship between social phobia score and social media addiction. The analysis included 377 participants for whom complete data were available for both variables. As detailed in

Table 4. Correlation Between Social Phobia Score and Social Media Addiction.

Variable	Social Phobia Score	Social Media Addiction
Social Phobia Score
Spearman’s rho	1.000	0.294 **
p-value (2-tailed)	–	<0.001
N	378	377
Social Media Addiction
Spearman’s rho	0.294 **	1.000
p-value (2-tailed)	<0.001	–
N	377	383

Complete data for both variables were available for 377 participants (98.2% of the total sample of 384). Missing data were handled using listwise deletion. ** Correlation is significant at p < 0.01 (two-tailed).

, Spearman’s rank correlation revealed a statistically significant, weak-to-moderate positive correlation between the social phobia score and social media addiction (ρ = 0.294, p < 0.001).

3.5. Predictors of Social Media Addiction

The results of the binary logistic regression are presented in

Table 5. Predictors of Social Media Addiction: A Multivariate Logistic Regression Analysis.

Predictor	Unadjusted OR (95% CI)	Adjusted OR (95% CI)
Social Phobia Severity
No Social Phobia	1.00 (Reference)	1.00 (Reference)
Mild	1.76 (0.92–3.38)	1.73 (0.90–3.34)
Moderate	2.23 (1.20–4.13) *	2.15 (1.15–4.04) *
Severe	2.79 (1.16–6.71) *	2.56 (1.04–6.30) *
Age (per year)	—	1.00 (0.89–1.13)
Gender
Female	—	1.00 (Reference)
Male	—	0.80 (0.51–1.23)
Family Income (SAR)
>20,000	—	1.00 (Reference)
5001–20,000	—	1.03 (0.47–2.28)
<5000	—	0.97 (0.49–1.91)

* Statistically significant (p < 0.05). SAR: Saudi Riyal. Variables entered in the model: Age, Gender, Family Income, and Social Phobia Severity.

. After adjusting for age, gender, and family income, social phobia severity was a significant predictor of SMA.

Compared to individuals with no SP, those with moderate social phobia had 2.15 times greater odds of having SMA (AOR = 2.15, 95% CI [1.15, 4.04], p < 0.05). The effect tended to be stronger for individuals with severe social phobia, who had 2.56 times greater odds of SMA (AOR = 2.56, 95% CI [1.04, 6.30], p < 0.05). The association for mild social phobia was not statistically significant. None of the covariates—age, gender, or family income—were significant predictors of Social Media Addiction in the analysis (all p > 0.05).

We tested for an interaction between gender and social phobia severity in the logistic regression model; the interaction term was not statistically significant (p > 0.05), indicating that the relationship between social phobia and SMA is robust across genders in this sample.

4. Discussion

A key feature of our study design was the use of a refined ‘Core SMA’ subscale to operationalize the addiction construct. Guided by expert consensus on clinically significant behavioral addiction, this subscale prioritized symptoms of functional impairment and preoccupation over simple frequency of use [28]. This approach facilitated a focused epidemiological analysis of the association between SP and problematic social media behaviors.

First, we identified a significant burden of psychosocial morbidity. Among 378 participants with complete data, the point prevalence of any self-reported SP symptom was 28.8%, while the prevalence of clinically significant (moderate to severe) symptoms was 15.6% (n = 59). This figure for clinically significant SP not only exceeds the 13% previously reported in a broader adolescent cohort [24] but also surpasses the upper range of most international lifetime prevalence estimates (7–13%) [6,29,30], underscoring the severity of this issue within our study population. This escalation may be attributable to the rapid socio-cultural transition within the Aseer region, where traditional communal norms are increasingly intersected by digital isolation [23]. Furthermore, this increase likely reflects the lingering ‘re-entry anxiety’ of the post-pandemic era, where prolonged periods of social distancing may have eroded face-to-face social competence and heightened sensitivity to social evaluation among adolescents reintegrating into physical school environments.

Second, we empirically quantified the potent association between these two constructs. SP and probable SMA were significantly correlated (Spearman’s ρ = 0.294, p < 0.001). Crucially, our multivariate logistic regression model demonstrated that social phobia severity was a significant independent predictor of probable SMA, even after adjusting for age, gender, and family income. Specifically, adolescents with moderate social phobia had 2.15 times the odds of probable SMA compared with peers reporting no SP (AOR = 2.15, 95% CI: 1.15–4.04, p < 0.05). This effect tended to be stronger for individuals with severe social phobia, who had 2.56 times the odds of probable SMA (AOR = 2.56, 95% CI: 1.04–6.30, p < 0.05).

This strong response association provides quantitative support for the Social Compensation Hypothesis [31,32]. This model posits that individuals with SP preferentially use the controlled environment of social media to regulate their anxiety. However, our findings suggest this compensatory strategy becomes maladaptive. The reliance on digital communication to avoid real-world stress may create a cycle of dependency, where the ‘safety’ of the online world reinforces avoidance behaviors, deepening both the addiction and the social phobia [33,34].

A potential concern in this field is the conceptual overlap between SMA and social avoidance. To address this, our ‘Core SMA’ measure specifically prioritized items related to negative consequences (conflict, withdrawal, grade decline) rather than motivation [28]. This distinction ensures that we are measuring the pathological outcomes of addiction, rather than just the coping mechanism itself.

Consistent with global trends in internalizing disorders, females in our sample reported significantly higher SP severity [35,36,37]. However, the absence of a significant gender interaction in our model implies that the risk is uniform: the ‘social compensation’ mechanism where anxiety drives addictive use operates with equal potency across both genders.

Regarding the exploratory covariates, we did not observe significant associations between social phobia and BMI or smoking status in this sample. While some international literature suggests bidirectional links between anxiety and maladaptive health behaviors, our findings indicate that for this specific demographic, digital coping mechanisms (i.e., social media use) may be more salient correlates of social anxiety than physiological or substance-related factors.

These findings have direct implications for clinical practice and public health policy. Clinicians treating adolescents with SP should proactively screen for problematic social media use as a potential comorbidity. Conversely, individuals presenting with SMA should be assessed for underlying SP, which might be the primary driver of the behavior. In educational settings, our data underscore the need for integrated programs that extend beyond simple digital literacy to simultaneously address mental health, promote adaptive coping mechanisms, and build real-world social competence.

Limitations

These findings must be interpreted within the context of several critical limitations. The foremost is the cross-sectional design, which inherently prohibits any inference of causality. We have demonstrated a strong, significant association, but we cannot conclude that SP causes SMA. It is equally plausible that problematic social media use with its attendant social comparisons and potential for negative online interactions exacerbates or even triggers SP. This question of temporality can only be resolved through future longitudinal cohort studies.

Second, this study relied exclusively on self-report measures. This introduces potential recall bias (particularly for daily hours of use) and social desirability bias. Given the stigma surrounding mental health in many contexts, it is possible that the true prevalence of both SP and SMA has been underestimated in our sample. Third, our sampling frame was limited to adolescents enrolled in school, thereby excluding those who have dropped out, a population that may be at even higher risk for both conditions. Finally, while our regression model adjusted for key demographics, it may be subject to residual confounding from unmeasured variables, such as comorbid depression, generalized anxiety, or underlying personality traits.

5. Conclusions

This study confirms a significant relationship between SP and SMA among adolescents in Aseer, Saudi Arabia. The prevalence of clinically significant SP was 15.6%, and the adjusted odds of probable SMA increased from 2.15 times for moderate SP to 2.56 times for severe SP compared to non-anxious peers. These findings provide a clear evidence base for public health interventions that must screen for and treat these conditions in an integrated manner.