A cross-sectional study on prevalence of cyberchondria and factors influencing it among undergraduate students

Kanganolli, Shameem R; N, Praveen Kumar

doi:10.5455/ijmsph.2020.01010202020022020

Cited by 6 publications

(6 citation statements)

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“…In line with these, an Indian study with information technology professionals showed a high 55.6% prevalence of cyberchondria [29]. Furthermore, a study with Indian medical undergraduates showed that cyberchondria prevalence was 37.5% [30]. In low-income countries, one of the reasons to engage in this online health-related search is the expensive health care facilities and poor accessibility to hospitals.…”

Section: Research Gapmentioning

confidence: 82%

Relationship between Health-Anxiety and Cyberchondria: Role of Metacognitive Beliefs

Nadeem

Malik

Atta

et al. 2022

JCM

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Purpose: The current study was designed to examine the relationship between health anxiety, cyberchondria (its constructs), and metacognitive beliefs. In addition, it also evaluated the moderating role of metacognitive beliefs in this relationship. Design and Method: The present study used the purposive sampling technique to acquire a sample of (N = 500) adults, among them (N = 256) women and (N = 244) men, and the age of the sample ranged from 20 to 50 years. Short Health Anxiety Inventory, Cyberchondria Severity Scale, and Metacognitions Questionnaire–Health Anxiety were used to operationalize the present study variables. Findings: The descriptive statistics revealed that all instruments have good psychometric properties, as Cronbach’s alpha coefficients for all scales are ≥0.70. In addition to this, the Pearson correlation showed that all variables of the present study have a significant positive correlation with each other. Furthermore, the regression analysis described that health anxiety and metacognitive beliefs (biased thinking and beliefs about uncontrollable thoughts) were the significant positive predictors of cyberchondria. Moreover, moderation analysis showed that metacognitive beliefs significantly strengthened the association between health anxiety and cyberchondria and its constructs. Practical Implications: The present study will help medical practitioners to understand how metacognitive beliefs and health anxiety can cause an increase in cyberchondria. This will help them to design better treatment plans for people with cyberchondria.

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Section: Research Gapmentioning

confidence: 82%

Relationship between Health-Anxiety and Cyberchondria: Role of Metacognitive Beliefs

Nadeem

Malik

Atta

et al. 2022

JCM

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“…It is plausible that smartphones can facilitate cyberchondria-related behaviors due to their portability and practicality. Additionally, a study showed that most online health searches (i.e., cyberchondria-related behaviors) are associated with internet use during the night-time (Kanganolli & Praveen, 2020 ), where it is likely that such online search is done via smartphone (for example, while lying in bed). Smartphones also allow the health-anxious person to search for health information while commuting to work or on the worksite and in other places where it would be impossible to use a desktop computer.…”

Section: Can Cyberchondria Predict Smartphone Addiction?mentioning

confidence: 99%

Are Cyberchondria and Intolerance of Uncertainty Related to Smartphone Addiction?

Vujić

Volarov

Latas

et al. 2023

Int J Ment Health Addiction

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Smartphones are a medium for performing online activities, and one such activity could be the compulsive online health information search — cyberchondria. This study aimed to test whether cyberchondria and intolerance of uncertainty (IU) positively predict smartphone addiction (SA), adjusted for age, gender, daily use duration, the reason for using smartphones, and symptoms of anxiety and depression. The sample consisted of 471 adults (55.2% women) from the general population without chronic diseases (Mage = 38.67). Regression analysis showed that IU was a positive predictor of SA (β = .17, p < .001), as well as cyberchondria (β = .14, p < .001), which had a unique contribution to the explanation of SA, relative to IU. Other significant predictors were average daily smartphone use and entertainment use, the latter being the strongest predictor in the model. These results revealed cyberchondria as a unique predictor of SA.

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“…While several studies have investigated cyberchondriac behavior and problematic smartphone usage among different population groups,[ 19 20 21 ] there is a dearth of comprehensive research specifically targeting the student population, particularly with regard to the distinction between medical and non-medical undergraduates. Since the health-related understanding is expected to differ between medical and non-medical undergraduates owing to the nature of their training,[ 22 23 24 ] it is likely to influence their online information-seeking behavior related to health matters.…”

Section: Introductionmentioning

confidence: 99%

The digital health dilemma: Exploring cyberchondria, well-being, and smartphone addiction in medical and non-medical undergraduates

Agrawal,

Khulbe,

Singh

et al. 2024

Indian Journal of Psychiatry

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Background: The Internet is a popular source of health information, but too much research can cause anxiety (cyberchondria). Medical and non-medical personnel interpret information differently, leading to varying rates of cyberchondria. Smartphone addiction may also contribute to cyberchondria and impact mental health. Methods: The study was an epidemiological survey-based investigation with a cross-sectional design involving undergraduate students (aged 18 years or older) from Indian universities or colleges. The study utilized the Cyberchondria Severity Scale-Short Form (CSS-12), WHO-5 well-being index, and Smartphone Addiction Scale-Short Version (SAS-SV). Results: A total of 1033 participants (53.1% females and 46.4% males) were recruited in the survey. Of the participants, 58.5% were pursuing medical or paramedical courses, while the remaining 41.5% belonged to the non-medical group. High-severity cyberchondria was present in about 4.4% of the students. The medical cohort demonstrated a significantly lower cumulative CSS in comparison to the non-medical cohort (t = - 3.90; P < 0.01). Smartphone addiction was observed in 57.2% of individuals in the medical group and 55.9% of individuals in the non-medical group (P = 0.68). Medical students had a significantly lower mean well-being score compared to non-medical students (58.4 vs. 59.6; P < 0.01). There was a positive correlation between cyberchondria severity and smartphone addiction, which was consistent across both groups. Conclusion: Medical students have less cyberchondria than non-medical students. Cyberchondria severity is linked to smartphone addiction. Non-medical students with cyberchondria have higher subjective well-being.

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A cross-sectional study on prevalence of cyberchondria and factors influencing it among undergraduate students

Cited by 6 publications

References 0 publications

Relationship between Health-Anxiety and Cyberchondria: Role of Metacognitive Beliefs

Relationship between Health-Anxiety and Cyberchondria: Role of Metacognitive Beliefs

Are Cyberchondria and Intolerance of Uncertainty Related to Smartphone Addiction?

The digital health dilemma: Exploring cyberchondria, well-being, and smartphone addiction in medical and non-medical undergraduates

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