Introduction

As internet access has become more widespread, individuals increasingly rely on it for self-diagnosing health issues, often without considering the credibility of the information they find. The prevalence of internet self-diagnosis in general population has risen significantly, reaching approximately 85% in the Arab world1. Many factors contribute to this prevalence, including, sociodemographic characteristics, health anxiety (cyberchondria), and health concerns (somatic symptoms)2,3,4 but limited research has explored these factors specifically in the Saudi population.

Experiencing clinically relevant physical symptoms, such as pain, fatigue, or shortness of breath— without a clear medical cause—may lead to somatic symptom disorder (SSD)5. In Saudi Arabia, fast internet and smartphone accessibility facilitate easy access to online health information. Cultural norms, stigma surrounding certain health conditions, and uneven access to advanced healthcare services—especially in remote areas—often drive individuals to rely on the internet for self-diagnosis and reassurance without medical supervision6.

Unsupervised internet self-diagnosis can increase health anxiety and negatively impact mental well-being7,8. This phenomenon, known as cyberchondria, is characterized by a dysfunctional behavioral prototype where individuals excessively and anxiously engage in seeking medical or health-related information on the internet5. As internet use and health anxiety continue to rise, cyberchondria is becoming a growing concern globally, including Saudi Arabia9. The interaction between cyberchondria, somatic symptom disorder, and internet self-diagnosis increase reliance on self-diagnosis, and self-management, while delaying professional medical care consultations, potentially creating a harmful cycle that worsens overall health8,10,11. To help prevent this cycle, keeping in mind the limited research in the Middle East on the relationship between these three factors, this study aimed to address the gap by investigating the prevalence and interconnections of these aspects within a Saudi population.

Methodology

Study design and settings

This cross-sectional observational study was conducted between January and March 2024 using an anonymous online questionnaire after obtaining institutional review board approval from Princess Nourah bint Abdulrahman university (23-1049) and following the Declaration of Helsinki, the International Medical Association’s code of ethics.

Study population

Saudi residents aged 18 and above were recruited through various social media platforms. Participants were informed about the study’s objectives and provided electronic informed consent prior to participation. Responses that were incomplete or submitted by individuals under the age of 18 were automatically excluded from the analysis.

Sample technique

The sample size was calculated using G-power based on an expected difference of 0.10, a margin of error of 2.5%, a 95% confidence interval (alpha = 0.05), and a study power of 99%. This yielded a sample size of 912, which was increased to 1377 to ensure adequate data quality and to account for potential issues like incomplete responses. A convenience sample from various regions across Saudi Arabia were recruited. While this method enabled efficient data collection, it may introduce selection bias and limit the generalizability of the results due to potential over- or under-representation of certain groups. However, the relatively large sample size might have improved representativeness and allowed for more detailed subgroup analyses, thereby increasing statistical power and the relevance of the findings. Moreover, data quality was maintained by applying defined inclusion criteria, and by utilizing standardized, validated Arabic versions of the Cyberchondria Severity Scale12, and the Somatic Symptom Scale13.

Data collecting instrument

The questionnaire was designed to collect information on participants prevalence of internet self-diagnosis, cyberchondria severity score, somatic symptom score, and sociodemographic details. Sociodemographic section gathered information on age, gender, marital status, nationality, area of residence, educational level and background, monthly income, chronic diseases, weight, and height.

The prevalence of participants’ use of internet self-diagnosis and its impact on their medical-seeking behavior were evaluated through a series of questions. Participants reported the frequency of their self-diagnosis behaviors on a five-point Likert scale, ranging from “Never” to “Very often; more than six times.” This section also examined motivating factors driving the use of internet self-diagnosis, such as the types of health conditions and symptom severity they searched for, assessed through six yes/no questions. Additionally, participants indicated their preference for self-diagnosis over seeking professional advice using yes/no question and rated their reasons for this preference, using a five-point Likert scale from “Strongly disagree” to “Strongly agree.” The outcome of internet self-diagnosis on participants’ self-management behaviors was also evaluated through multiple-selections question.

Cyberchondria Severity Scale (CSS) was used to measure excessive internet health-related use and associated anxiety. The validated Arabic version of the questionnaire12 was used to ensure linguistic and cultural appropriateness for the Saudi population. It contained 12-items scored on a Likert-type system ranging from 1 (never) to 5 (always). Total scores ranged from 12 to 60 where higher scores indicated greater severity and likelihood of cyberchondria. The scale assessed four factors: excessiveness, distress, compulsion, and reassurance showing high internal consistency, with a Cronbach’s alpha of 0.92. In the current study, Cronbach’s alpha of the CSS was 0.88.

Somatic Symptom Scale (SSS) had strong psychometric properties and consisted of 8-item scale that assessed the somatic symptom burden on individuals with overall Cronbach’s alpha of 0.8014. The Arabic version of the 8-item scale had been utilized by Alalawi et al.13 to assess somatic symptom disorder among Arabic-speaking populations at the primary healthcare level, indicating its applicability in this context13. Each item was scored on a Likert-type system ranging from 0 (not at all) to 4 (very much); total scores ranged from 0 to 32. Scores of 0–3 indicated no to minimal burden, 4–7 indicated low burden, 8–11 indicated medium burden, 12–15 indicated high burden, and 16–23 indicated very high burden13. In the current study, the Cronbach alpha of SSS was 0.82.

Participant recruitment and data quality assurance

Data were collected through an online questionnaire distributed via widely used social media platforms in Saudi Arabia, including Twitter (X), WhatsApp, and Instagram, to ensure broad reach across various regions and different segments of the Saudi population. The internet usage in Saudi Arabia is reported to be 100% in year 2023 according to World Telecommunication indicators database15. As the target population of the study are those who are using the internet to estimate the cyberchondria level, the online distribution of the questionnaire was the best choice for reaching the largest number of the target population. No paid advertisements or targeted demographic strategies were employed. The online questionnaire was designed using obligatory response settings, which required participants to complete all items before submission preventing duplicate submissions by restricting responses to one per device. Additionally, incomplete questionnaires were automatically excluded from the final dataset to maintain the integrity and reliability of the collected data. The questionnaire achieved an 84% completion rate, with a total of 1,377 completed responses.

Statistical analysis

Data was entered and analyzed using SPSS. K-means cluster analysis was applied to classify participants into two distinct groups—low and high—based on scores from the Cyberchondria Severity Scale and Somatic Symptom Scale. This method identified natural groupings with similar characteristics by minimizing the distance between data points and their cluster centroids, resulting in compact, well-separated clusters. This grouping enabled meaningful segmentation for analyzing associations with sociodemographic characteristics and internet self-diagnosis behavior. Descriptive statistics were presented using frequencies and percentage for qualitative variables, in addition to means and standard deviations for quantitative variables. Chi-square tests were employed to examine the relationships between categorical variables. T-tests were utilized to compare mean differences in continuous variables. The level of significance was set at p < 0.05. A linear regression analysis was performed to investigate the role of sociodemographic variables and frequency of internet-based self-diagnosis as predictors of higher scores of cyberchondria and somatic symptoms.

Results

Out of the total distributed questionnaires, 84% were fully completed, resulting in 1,377 valid responses. The majority were females (85.2%), over 30 years of age (52%) and married (53.4%). Most lived in central (48.4% ) or eastern (37.3%) urban regions and had moderate to high socioeconomic status. In terms of education, 75.2% held undergraduate degrees, and 21.6% were specialized in healthcare background. Regarding health status, 68.5% reported no chronic issues, and most had normal to overweight body mass index Table 1.

Table 1 Sample characteristics (n=1377).
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Participants were categorized into two clusters based on their CSS and SSS scores: Cluster 1 (n = 724) had higher scores, and cluster 2 (n = 653) had lower scores Fig. 1. The mean CSS for Cluster one and two were 37 ± 7 and 26 ± 7; respectively, while mean SSS for cluster one and two were 17 ± 5 and 8 ± 5; respectively Fig. 2.

Fig. 1
figure 1

K-mean cluster analysis of participants based on cyberchondria severity and somatic symptoms scores.

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Fig. 2
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Cyberchondria severity scale and somatic symptom scale among two clusters.

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Bivariate analysis between individuals in Cluster 1 and Cluster 2, conducted using the chi-square test, revealed that younger females with undergraduate education and lower socioeconomic status, as well as those with psychiatric or chronic somatic diseases—especially respiratory conditions—were significantly more likely to have higher cyberchondria and somatic symptoms scores Table 1.

All participants reported conducting online health searches for a variety of conditions, ranging from mild symptoms to acute and chronic illnesses. Over one-third searched 2–3 times in the past week, and 39% of cluster 1 participants searched more than four times weekly Fig. 3.

Fig. 3
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Frequency of Internet-based self-diagnosis/week among Cluster 1 and Cluster 2 participants; CSS cyberchondria severity scale, SSD somatic symptom disorder.

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Out of total, 604 participants (43.9%) preferred self-diagnosis online rather than consulting professionals. The motivations included: “It saves time” (33.7%), “It is affordable and accessible” (54.6%), “It fosters confidence and comfort” (34.1%), and “It reflects a low perceived need for seeking medical care” (17.4%) Table 2. Compared to cluster 2, cluster 1 participants reported significantly more confidence in online diagnosis (p = 0.015) and significantly less perceived need for professional care (p = 0.006) Fig. 4.

Table 2 Motivations behind participants’ preference for online Self-Diagnosis.
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Fig. 4
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The average score for each motivation to conduct internet self-diagnosis instead of seeking medical care in all participants.

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Regarding the outcome of participants’ self-management behaviors, 754 (54.7%) of the participants indicated a cautious approach and sought further confirmation from healthcare professionals before starting any prescribed treatment. Additionally, nearly half of the participants reported a willingness to adopt the suggested interventions, including lifestyle changes 433 (31.4%), natural herbal remedies 369 (26.8%), and over-the-counter medications 247 (17.9%). In contrast, 181 (13.1%) of the participants felt empowered and confident enough to follow the recommended treatment. Chi square test showed that participants with high CSS and SSS scores demonstrated a significant tendency to approach self-management cautiously. They demonstrated a significant preference for consulting healthcare professionals before taking any action (p = 0.02). They also reported significantly higher rates of utilizing prescribed interventions, including medications (p = 0.004), over-the-counter treatments (p = 0.004), and natural herbal remedies (p = 0.001) Fig. 5.

Fig. 5
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The responses reported by participants regarding their self- management behaviors after conducting an online self-diagnosis (multiple responses question).

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A linear regression analysis identified the following as independent predictors of higher CSS and SSS: younger age, female gender, lower socioeconomic status, existing health issues, and frequent online health searches Table 3.

Table 3 Factors associated with high scores of cyberchondria severity and somatic symptoms scores in logistic regression analysis.
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Discussion

The current study on cyberchondria, somatic symptoms, and internet self-diagnosis suggested a polygonal interaction between internet searching behavior, sociodemographic characteristics, and health-related factors in influencing somatic symptoms and cyberchondria severities among Saudi participants. These findings confirmed reports from previous studies about positive association between somatic symptoms and cyberchondria8,16,17. Co-occurrence of health issue, including mental health conditions can significantly exacerbate the cycle of health anxiety and excessive online health-related searches driven by self-diagnosis and reassurance-seeking behavior8,17.

The analysis was conducted based on sociodemographic variables. Findings revealed that young females from low to moderate socioeconomic backgrounds—especially those with existing health issues and frequent engagement in online health-related searches—demonstrated elevated levels of cyberchondria and somatic symptoms, aligning with patterns observed in previous studies. For instance, Santoro et al.8 and Almatham et al.16 identified female gender as a contributing factor to cyberchondria8,16, possibly due to a greater tendency toward somatic and internalizing symptoms. This predisposition may lead to excessive online health-related searches for reassurance, thereby exacerbating the severity of cyberchondria8,18. However, Aulia et al.19 did not find any significant gender differences in overall cyberchondria severity among first-year medical students, but they did observe distinct behavioral patterns. Male students often struggled to cope with health anxiety, whereas female students were more likely to manage it by seeking reassurance from medical professionals19.

Regarding age, Ezmeirlly and Farahat6, Rohilla et al.20, and Santoro et al.8 highlighted the higher prevalence of cyberchondria among younger participants, which tend to decrease as individuals progressed in their education, training, and expanded their knowledge6,8,20. Younger individuals who experienced greater social stressors and educational challenges, with limited coping strategies and emotional regulation skills may increase the severity of cyberchondria and excessive reassurance-seeking behavior through online health searches8,21. Additionally, frequent use of social media and digital health platforms among younger people can shape their perceptions of illness. However, the age gap in internet search behaviors has narrowed as older generations increasingly adopt technology and access online health resources21.

Regarding socioeconomic status, Nadeem et al.22 reported similar findings, revealing that low-income individuals showed higher levels of cyberchondria and somatic symptoms. This trend may reflect a greater dependence on internet-based self-diagnosis due to limited access to affordable healthcare22,23, as well as increased vulnerability to depression, health anxiety, and emotional distress—all of which contributed to heightened cyberchondria8.

Our findings revealed a rising interest among Saudi participants to seek health information online, with 43.9% preferring self-diagnosis over consulting healthcare professionals. This preference was driven by factors such as convenience, cost, accessibility, and increased confidence. These findings aligned with existing literature, highlighting a broader shift toward internet-based self-diagnosis due to ease of access, patient empowerment, and healthcare system limitations1,2,24. Al-Ghamdi et al.25 linked preference among Saudis to challenges in accessing healthcare and perceptions of inefficiency in the system. While online resources can aid psychoeducation by providing information and reducing stigma26. However, concerns remain about its reliability and its potential to increase anxiety or spread misinformation8,10,27. Consequently, our participants perceived the belief that “seeking medical care offered limited benefits” as a less common contributing factor for relying on internet self-diagnosis.

Nearly half of the Saudi participants showed a positive attitude towards health improvement, showing confidence in self-management and a willingness to adopt recommended interventions, particularly lifestyle changes and herbal remedies. However, they remained cautious and preferred seeking confirmation from healthcare professionals before starting any treatment based on online health information, —especially when experiencing increased levels of cyberchondria and somatic symptoms. Similarly, Aoun et al.2 found that half of participants consulted a doctor before taking medication, while the other half either self-medicated or relied on a pharmacist’s instruction2. Internet health searches enhance the patient-doctor relationship by offering reassurance and aiding patient preparation for medical consultations24, while literature presents mixed views on how such searches influence individual empowerment and confidence in self-management practices, including medication use, lifestyle changes, and herbal remedies28. In the context of self- management, Baggott et al.28 and Silver and Johnson29 identified important factors that significantly influence individuals’ intentions to self-medicate, such as the credibility of the source, clarity and reliability of the information, accessibility of healthcare, severity of symptoms, and the type of medication. These findings highlight the importance of professional guidance to ensure safe self-health decisions by directing individuals to reliable, evidence-based resources26.

Conclusion

This study assessed the prevalence of cyberchondria and somatic symptoms among Saudi participants and their association with online self-diagnosis. Notably, Higher cyberchondria and somatic symptoms were observed among younger women under 30 years old with adverse health conditions and individuals who frequently used the internet for self-diagnosis. Psychosocial factors influenced their tendency to engage in self-diagnosis and self-management intentions, highlighting the need for targeted interventions to improve online health literacy and critical evaluation skills. The study also emphasizes the impact of self-diagnosis on healthcare utilization and the patient-doctor relationship. However, it has several limitations. The cross-sectional design prevents causal inferences, the demographic limitations such as the sample being predominantly female sample may affect generalizability, and the use of convenience sampling, which could introduce selection bias. Additionally, reliance on self-reported questionnaires may lead to information bias. Despite these limitations, the large sample size and use of validated tools enhanced the study’s quality and statistical strength, providing valuable insights into cyberchondria, somatic symptoms, and internet self-diagnosis in Saudi Arabia. These findings can support public health policymakers and educators in creating guidelines, creating accessible, evidence-based digital health resources, and organize awareness campaigns to empower individuals’ informed health decisions, reduce anxiety, and alleviate somatic symptom burden. Longitudinal studies employing randomized sampling strategy are needed to explore the causal relationships between cyberchondria, somatic symptoms, and internet self-diagnosis, as well as, to identify the underlying psychological mechanisms, and the impact on healthcare utilization. Evaluating the effectiveness of health literacy interventions may contribute to reducing potential harms associated with internet self-diagnosis.