Effects of Compulsive Internet Use on Health Anxiety: A Mediation Model

doi:10.21203/rs.3.rs-3748060/v1

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Effects of Compulsive Internet Use on Health Anxiety: A Mediation Model

https://doi.org/10.21203/rs.3.rs-3748060/v1

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To gain a deeper understanding of the factors influencing health anxiety, this paper proposes a moderated mediating model to explore the interrelationships among compulsive Internet use, intolerance of uncertainty, information avoidance, and health anxiety. By analyzing these variables within the proposed framework, we aim to shed light on the complex dynamics that contribute to health anxiety.

Methods: This study included 239 randomly selected undergraduates. We used the Whiteley Index, Information Avoidance questionnaire, Compulsive Internet Use Scale, and Uncertainty Intolerance Questionnaire to comprehensively assess their behaviors and attitudes.

Results: (a) The study revealed a positive association between compulsive internet use and health anxiety. (b) Intolerance of uncertainty was identified as a mediator in the relationship between compulsive Internet use and health anxiety. (c) Information avoidance does not mediate the effects of compulsive internet use and intolerance of uncertainty on health anxiety; instead, it directly contributes to increased levels of health anxiety.

Conclusion: Compulsive internet use predicts and exacerbates health anxiety by increasing individuals' intolerance of uncertainty. Information avoidance directly exacerbates health anxiety. Effective interventions should focus on reducing compulsive internet use, enhancing tolerance for uncertainty, and addressing information avoidance tendencies to alleviate health anxiety. These findings provide valuable theoretical support for targeted health anxiety interventions.

Compulsive Internet Use

Information Avoidance

Health Anxiety

Intolerance of Uncertainty

Health anxiety is a clinical symptom that significantly impacts individuals' daily functioning and physical and mental well-being. It manifests through uncontrollable anxiety, irrational meta-cognitive beliefs, and safety-seeking behaviors. With the widespread use of the Internet, an emerging manifestation of health anxiety is observed - excessive online health information seeking ¹. This behavior not only imposes a considerable economic burden on patients but also strains healthcare resources. The present study contributes to a deeper understanding of the relationship between health anxiety and specific factors, offering valuable insights for prevention and therapeutic interventions. By shedding light on this connection, it can aid in developing effective strategies to tackle health anxiety and optimize treatment programs¹.

Recent research has indicated that individuals with health anxiety exhibit a tendency to focus on specific disease-related information rather than exploring content related to affective disorders. This behavior of selectively examining disease items first suggests that online research for health-related information could play a significant role in influencing people's behavior ^2–4. On one hand, individuals with health anxiety may prefer to seek health information online to engage in self-diagnosis and safety-seeking behaviors. However, on the other hand, research suggests that users with pre-existing health concerns might experience heightened anxiety after seeking health information on the Internet¹⁵. Despite some studies proposing that seeking health information online may not effectively alleviate users' anxiety, there is evidence to suggest that prolonged and frequent use of the Internet for health-related research could potentially exacerbate health anxiety⁵. Consequently, there remains a need for further investigation into the relationship between Internet use, information-seeking behavior, and health anxiety.

A preliminary analysis of the information behavior among individuals with health anxiety revealed that they exhibited compulsive and repetitive tendencies while searching for health information on the Internet. Moreover, these individuals displayed clear withdrawal responses when they stopped using the Internet, resembling symptoms associated with Obsessive - Compulsive Disorder (OCD). This persistent and time-consuming behavior, characterized by disregarding other responsibilities and repeatedly seeking the same information online, is referred to as compulsive network use⁶. Further examination of self-reports from patients with health anxiety showed that those who experienced heightened levels of health anxiety after searching for medical information online tended to engage in more compulsive network use compared to other sources of health anxiety⁷. While some studies have established significant positive associations between network hypochondria (Cyberchondria) and compulsive network use in relation to health anxiety⁸, there remains a limited understanding of the direct impact of compulsive network use on health anxiety. Consequently, this study aims to address this gap and proposes the following hypothesis (H1): There is a positive correlation between compulsive network use and health anxiety among college students, and compulsive network use behavior can positively predict health anxiety^{7, 8}.

Intolerance of Uncertainty (IU), also known as unbearable uncertainty or uncertainty tolerance, is a fundamental psychodynamic trait that pertains to an individual's response to situations involving ambiguity and the unknown⁹. When an individual's tolerance for uncertainty decreases, they are more likely to experience emotional anxiety and fear, and they may seek cognitive closure, which can significantly impact their ability to make subsequent decisions^{10, 11}. Furthermore, reduced uncertainty tolerance can lead to heightened concerns about potential illnesses, making it an essential factor for predicting anxiety, depression, and compulsive behaviors^12–14. Notably, individuals with low uncertainty tolerance who frequently engage in online activities that increase uncertainty, such as compulsive network use, and maybe they are more likely to experience heightened health anxiety^15–17. Given these observations, this study hypothesized the following (H2): Compulsive network use not only directly leads to health anxiety but also exacerbates health anxiety by reducing uncertainty tolerance among internet users^18–20.

Some theories suggest that health anxiety arises not only from personal negative health beliefs influencing emotions, cognition, and behavior but also from deficiencies in health information literacy, which may be a contributing factor to health anxiety²¹. While existing research has focused on the impact of active health information-seeking behaviors on health anxiety^{7, 8}, there is a lack of empirical research exploring the relationship between information avoidance during information-seeking and health anxiety.

Information avoidance refers to the deliberate avoidance or delay in seeking specific information^{22, 23} and is characterized by self-driven and voluntary access to information²⁴. Previous studies have explained the link between information avoidance and anxiety through cognitive disalignment theory, selective exposure hypothesis, and information utility theory. However, recent research has found that information avoidance may not necessarily alleviate anxiety; in fact, it can lead to the formation of information cocoons, reinforcing avoidance behavior and reducing individuals' ability to use health information, ultimately contributing to increased health anxiety^{19, 20, 25}. In light of these findings, this study proposes the following hypothesis (H3): Information avoidance will influence the second half of the mediation effect model, affecting users' information utilization and moderating uncertainty tolerance (refer to Fig. 1).

Epidemiological surveys examining health anxiety have revealed a concerning upward trend in college students' concerns about their own health in recent years²⁶. It has been posited that college students, driven by their high health expectations and commendable information literacy, are more inclined to seek health-related information via the Internet compared to other demographic groups²⁷. Given the widespread usage of Internet-enabled devices such as mobile phones, tablets, and computers among college students, they are particularly susceptible to compulsive Internet use.

This research aims to investigate the intricate relationship between compulsive network use, information avoidance, uncertainty tolerance, and health anxiety in college students through the administration of a questionnaire survey. By scrutinizing the influence of uncertainty tolerance and information avoidance on health anxiety, this study seeks to identify the factors contributing to health anxiety and shed light on the significant impact of compulsive network use, uncertainty tolerance, and information avoidance on this phenomenon. The findings of this study are expected to enhance our comprehension of the mechanisms underlying health anxiety, as well as offer valuable insights into potential interventions and measures for its prevention and management. As such, it aims to provide a solid theoretical foundation for future research on the development and mitigation of health anxiety.

2.1 Participants

This study employed a convenient sampling method to select participants from five universities in Tianjin, Hohhot, and Shanghai between May 10, 2021, and June 10. During the survey research process, the questionnaire does not involve critical personal information such as names, property, or family members' details. The survey content is strictly limited to scientific research and will not disclose any personal information externally. Before the commencement of the questionnaire, participants were provided with an explanation outlining their rights. Continued participation in responding to the questionnaire implies informed consent and voluntary engagement in the survey.The content, methods, and results of this study comply with Chinese laws and regulations as well as applicable international norms and standards. Additionally, it does not involve human experiments, animal experiments, or clinical intervention studies.

A total of 280 questionnaires were distributed to students, and 245 completed questionnaires were successfully collected and included in the analysis. After excluding participants who were on suspension, employed, or providing services, the final sample size for analysis was 239, resulting in a recovery rate of 85.35%. This sample comprised 82 male participants and 157 female participants, aged between 17 and 27 years old (= 21.06, s = 2.14).

2.2 Research tools

To assess health anxiety, this study employed the revised Whiteley Index (WI) developed by Fergus^{28, 29}. The WI is a self-report measure that evaluates college students' levels of health anxiety related to their bodily concerns, fear of diseases, and disease-related beliefs. It consists of seven items, each scored on a 5-point Likert scale, ranging from 1 (almost no) to 5 (extremely much). A higher total score indicates a higher level of health anxiety. The Chinese version of the WI scale and its abbreviated version, WI-7, have demonstrated good reliability and validity in mainland and Hong Kong populations, respectively, as confirmed by previous research³⁰. Additionally, to align with the suggestions for improvement of the WI scale, an additional item concerning forced thinking was incorporated³¹. Compared to the simplified Chinese Health Anxiety Scale and the Chinese Disease Belief Scale, the WI scale offers the advantage of having fewer questions while encompassing more dimensions, along with stable reliability and validity. This makes it suitable for use in conjunction with other scales. For the current study, the internal consistency coefficient of the WI scale was found to be 0.92, indicating strong reliability⁴⁹.

In this research, we utilized the Compulsive Internet Use Scale (CIUS), which was originally developed by Meerkerk³² and later revised by Lin and Lee⁵⁰. The CIUS is composed of 14 items, and respondents rate each item on a 5-point scale (1 = never, 5 = often). A higher score on the CIUS indicates a stronger compulsion towards internet use. Previous studies have demonstrated the CIUS's effectiveness in assessing compulsive internet use, and in our study, we obtained a high concordance coefficient of 0.92, reinforcing its reliability.

To validate the measurement of compulsive internet use, we employed the Internet Use Frequency questionnaire (IUF), adapted from the Smartphone Use Frequency questionnaire (SUF) developed by Elhai et al⁵¹. In the scale, 1= 'extremely rare,' while 6= 'extremely frequent. The IUF served as a valuable calibration tool for this study, ensuring accurate assessment of forced network use.

In addition to the CIUS, we also utilized the Intolerance of Uncertainty Scale-12 (IUS-12), a Chinese-language scale, to measure individuals' tolerance for uncertainty^{33, 34}. The IUS-12 consists of 12 items, rated on a 5-point scale (1 = full compliance, 5 = full compliance). Higher total scores on the IUS-12 signify a lower tolerance for uncertainty. In our study, the internal consistency coefficient of the IUS-12 was found to be 0.87, indicating its robustness as a measurement tool.

This study employed the Information Avoidance Scale (IAS), adapted from Howell³⁵. The IAS consists of 8 items, rated on a 7-point scale (1 = very disagree, 7 = very agree), with higher scores indicating a stronger tendency to stick to initial opinions. We added personal health status as a key element and had three psychological researchers meticulously translate and revise the scale into Chinese while retaining the original 8 items. The third, fifth, seventh, and eighth items among the eight used reverse scoring. Our aim was to explore individuals' inclination to avoid information related to their personal health status and its potential impact on decision-making and information-seeking behaviors. The coefficient of agreement in this study was 0.75.

Overall, these carefully selected and validated scales allowed us to explore the compelling aspects of compulsive internet use and the role of uncertainty tolerance in our research effectively.

2.3 Statistical processing

SPSS 25.0 was used for data entry, description statistics, correlation analysis and common method bias. The test procedure of intermediary mediation analysis proposed by Wen was used to test model effects and PROCESS 3.5 were used for statistical analysis³⁶.

2.4 Common method Deviation test

The measurement of variables in this study were entirely self-reported, potentially a common methodological bias. In order to reduce the possible bias, statistical Harman single factor test for all variables into unified exploratory factor analysis, the results show that eight characteristic root more than 1, the first factor variation interpretation rate of 29.42%, less than 40% of the critical standard, that the common method deviation is not significant³⁷. This follows that common method bias did not seriously affect this study.

3.1 Correlation analysis

The study analyzed the total scores of compulsive Internet use, intolertance of uncertainty, information avoidance, Internet use frequency, and health anxiety scales. We have provided a sample description in Table 1.

Table 1

Sample Characteristics
Measure	Item	M ± SD	Frequency(Percentage)
Gender	Male		82(34.31%)
Gender	Female		157(65.69%)
Age		21.06 ± 2.14
Education	University below bachelor's		40(16.74%)
	Bachelor’s degree		165(69.04%)
	Above bachelor’s degree		34(14.23%)
Scales	1. Compulsive Internet Use	42.93 ± 12.14
	2. Intolerant of Uncertainty	36.59 ± 8.90
	3. Health Anxiety	19.29 ± 7.57
	4. Information Avoidance	24.55 ± 8.28
	5. Internet Use Frequency	42.77 ± 10.30

Spearman correlation analyses were employed to assess the relationships among diverse scoring variables. The findings indicated significant positive associations between compulsive network use and health anxiety, as well as between network use frequency and health anxiety. Moreover, a significant correlation was observed between uncertainty tolerance and health anxiety, along with health information avoidance and health anxiety. Table 2 presents a summary of the results.

Table 2

Preliminary Correlations: Outcome Variables and Potential Covariates.
	CIU	IU	IA	HA
1. Compulsive Internet Use	——
2. Intolerant of Uncertainty	0.50**	——
3. Information Avoidance	0.08	0.13*	——
4. Health Anxiety	0.40**	0.58**	0.21**	——
5. Internet Use Frequency	0.56**	0.40**	-0.05**	0.29**
Data were analyzed by Pearson correlation, * p < 0.05, * * p < 0.01, * * * p < 0.001 (two-tailed), correlations were significant. CIU = Compulsive Internet Use, IU = Intolerant of Uncertainty, IA = Information Avoidance, HA = Health Anxiety

3.2 Preliminary statistical analysis

Firstly, we examined whether there were differences in the scores of WI scores among participants based on gender and age. Gender (t = -1.03, p > 0.05) and age (F = 1.03, p > 0.05) did not significantly affect the total WI scores.

Based on the WI scale score x̄ ± 1 standard deviation (1 SD), participants were divided into two groups: a high tendency of health anxiety group (n = 41) and a low tendency group (n = 41). Independent sample t-tests were performed to compare the scores of compulsive network use, network use frequency, and health information avoidance between the two groups.

The results revealed that there was no significant difference in health information avoidance between the high-tendency and low-tendency groups (t = -1.98, p > 0.05). However, there were significant differences in compulsive network use (t = -5.81, p < 0.05, Cohen's d = -1.24) and intolerance of uncertainty(t = -8.49, p < 0.05, Cohen's d = -1.83) between the two groups.

Regarding the Internet Use Frequency (IUF) total score, a significant difference was observed between the low and high tendency groups (t = -4.53, p < 0.01, Cohen's d = -0.98). Among the various features and functions assessed, no significant differences were found for learning functions. The low-level group and high-level group exhibit significant differences in the frequency of using the internet for purposes other than studying.

3.3 Test of the mediation effect of the intolerance of uncertainty

The mediation of uncertainty was assessed through regression analysis for individual pathways, and the results are presented in Table 3. The findings indicate that compulsive network use has a positive impact on health anxiety, partly mediated by uncertainty tolerance. In other words, compulsive network use reduces users' ability to tolerate uncertainty, leading to increased concerns about their own health. To validate the mediation effects, a bootstrap test was conducted following the testing procedure for mediation effects. The results revealed that the mediation effect of uncertainty between compulsive network use and health anxiety was statistically significant (b = 0.15, se = 0.05, 95% confidence interval [0.17, 0.35]), accounting for 64.75% of the total effect. This confirms that uncertainty plays a partial mediating role in the relationship between compulsive network use and health anxiety.

Table 3

Mediation Effect of the Intolerance of Uncertainty
Item	Health anxiety			Intolerance of uncertainty			Health anxiety
	β	SE	t	β	SE	t	β	SE	t
Compulsive internet use	0.40	0.04	6.64^***	0.50	0.04	8.86^**	0.14	0.04	2.31^**
Intolerance of uncertainty							0.51	0.05	8.53^***
R²		0.16			0.25			0.36
F		44.07^***			48.45^***			65.6^***

* p < 0.05, * * p < 0.01, * * * p < 0.001 (two-tailed), correlations were significant.

3.4 Mediator model test with regulation

In order to examine the potential impact of information avoidance regulation on the relationship between uncertainty tolerance, compulsive network use, and health anxiety, a standardized mediation model was employed (Model 58 in PROCESS) involving four variables: compulsive network use (x), uncertainty tolerance (w), health anxiety (y), and health information avoidance (u). The results of the adjusted mediation test are presented in Table 4.

Table 4

Analysis of Moderated Mediation Model
Item		Intolerance of uncertainty			Health anxiety
	β	SE	t	β	SE	t
Compulsive Internet use	0.12	0.13	0.95	0.08	0.04	2.32^*
Intolerance of uncertainty				0.15	0.15	0.99
Information avoidance	-0.33	0.23	-1.46	-0.25	0.2	-1.23
Compulsive internet use × Information avoidance	0.01	0.01	1.96
Intolerance of uncertainty × Information avoidance				0.01	0.01	1.93
R²		0.27			0.39
F		28.77			36.56^*

* p < 0.05, * * p < 0.01, * * * p < 0.001 (two-tailed), correlations were significant.

Regarding the intermediary variable IU, when it is at a low level, the bootstrapped 95% confidence interval does not include the number 0, indicating mediation at this level, with an effect value of 0.09; at the mean level, the bootstrapped 95% confidence interval does not include the number 0, indicating mediation at this level, with an effect value of 0.15; at a high level, the bootstrapped 95% confidence interval does not include the number 0, indicating mediation at this level, with an effect value of 0.22. In summary, the consistent mediation across different levels suggests that there might not be a moderating effect on mediation.

It is noteworthy that the moderating effect of health information avoidance in the model is not significant. This suggests that the relationship between compulsive internet use, intolerance of uncertainty, and health anxiety may not change based on the degree of health information avoidance. In other words, regardless of health information avoidance, maladaptive internet usage and low tolerance for uncertainty exacerbate health anxiety.

The study reveals a direct positive link between compulsive network use and health anxiety. Uncertainty tolerance acts as a mediator in this relationship. Lower uncertainty tolerance, combined with information avoidance, heightens health anxiety risk, particularly among college students. This emphasizes the complex interplay of these factors in driving health anxiety within compulsive network use.

4.1 Compulsive network use and health anxiety

This study investigated the connection between compulsive network use and health anxiety in college students. Compulsive network use displayed a notable positive correlation with health anxiety. In line with theoretical models, compulsive network use was found to positively predict health anxiety (supporting H1). Consistent with prior research, individuals with varying levels of health anxiety exhibit distinct patterns in their network use. Notably, those with higher health anxiety tend to display more pronounced traits of compulsive network use⁶.

Prior research indicates that compulsive network use often arises from users harboring irrational beliefs regarding health information. These negative metacognitive beliefs not only trigger heightened anxiety responses but also prompt individuals to escalate their search efforts and response frequency when faced with health-threatening information³⁸.

Interestingly, the adoption of compulsive network use as a coping mechanism to alleviate health anxiety yields counterintuitive outcomes. This approach not only fails to effectively alleviate anxiety but also consumes substantial time and energy resources. Consequently, individuals initially grappling with anxiety find themselves in a paradoxical situation, wherein their engagement in compulsive network use actually exacerbates their health anxiety symptoms³⁸.

Furthermore, certain researchers propose that compulsive network use manifests as a mechanism for confirming negative information. This leads individuals to repetitively search for the same content, fixating on adverse details to perform self-diagnoses²¹. On the other hand, an alternative perspective posits that compulsive network use stems from a quest for reassurance and health security online. However, this behavior can be influenced by the "silence spiral hypothesis" (The Spiral of Silence), which suggests that people are inclined to adopt negative viewpoints amid information dissemination³⁹.

According to cognitive dissonance theory, users tend to trust online content that aligns with their pre-existing beliefs to avoid cognitive conflicts⁴⁰. In their pursuit of health information that conforms to their perspectives, users invest heightened time, psychological, and cognitive resources during the search process. However, this intensified resource allocation may inadvertently diminish their ability to regulate their anxiety emotions, potentially exacerbating their anxiety levels.

The Internet use frequency questionnaire serves as a testament to the study's external validity. Notably, a significant disparity exists in the overall frequency of network usage between college students with more pronounced health anxiety and their less anxious counterparts. This observation aligns harmoniously with the consensus of prior research findings^{4, 26, 41}.

In the realm of web search activities, a conspicuous divergence surfaces, particularly in the domain of map utilization. This variance could be attributed, in part, to the resemblance between web and map searches, both necessitating cognitive skills related to visual exploration. Moreover, discernible discrepancies emerge in the frequencies of utilizing video, voice, and instant information functions. Such distinctions might be indicative of the health anxiety group's proclivity to seek reassurance and comfort from external sources.

Conversely, the utilization frequencies of music, games, social media, and films exhibit no noteworthy disparities between the two groups. This correspondence with existing research findings underscores the notion that these content categories primarily serve entertainment purposes, which may not be directly linked to health concerns within the realm of compulsive network use⁸. Additionally, this outcome might also imply that engagement in leisure activities like learning, watching TV, listening to music, and playing games fails to alleviate health anxiety. Thus, the comparable utilization patterns in these functions may not reveal significant differences.

This outcome also potentially indicates that individuals within the more adversely impacted clinical health anxiety group solely manifest negative ramifications in their information-seeking behaviors, without necessarily generalizing this impact to other facets of internet use.

4.2 Mediating role of intolerance of uncertainty

The findings of this study underscore the role of uncertainty tolerance as a mediator, exerting a partial mediating effect. Compulsive network use is observed to positively predict health anxiety, mediated through uncertainty tolerance (supporting H2). Decreased user tolerance for uncertain information is associated with heightened health anxiety, aligning with prior research outcomes^{15, 16}.

Uncertainty tolerance emerges as a notable predictor in mood disorders, manifesting early on in conditions such as anxiety, depression, and compulsions. Patients exhibit a fear of uncertain emotions, objects, and situations, struggling to cope with the anxiety stemming from the unknown. This highlights the psychological vulnerability of health anxiety groups, where the distress triggered by uncertainty compounds negative emotional experiences, potentially exacerbating the condition. Notably, uncertainty tolerance manifests in negative beliefs, behavioral inclinations, and emotional responses⁴².

In line with the cognitive-behavioral model theory^{38, 43}, individual experiences influence health beliefs. Reduced uncertainty tolerance may lead to the formation of negative beliefs about health information, resulting in a pessimistic evaluation and interpretation of sought-after health information. Additionally, the inability to tolerate uncertain content may drive users to intensify search efforts while avoiding less efficient information, ultimately hindering effective information utilization. This heightened anxious response to uncertainty further compounds the intricate relationship.

4.3 The effect of information avoidance

The moderating effect of information avoidance is not significant. Not supportive of H3^44–47. This outcome indicates that information avoidance may not have a direct association with compulsive internet use and intolerance of uncertainty. Even if compelled to increase internet usage frequency, the tendency to avoid health information remains consistent. It suggests that individuals might be selectively seeking specific health-related information while avoiding what they perceive as unnecessary information while searching for health-related information online. Although this search strategy may enhance the efficiency of search results by increasing search frequency, it could reduce the opportunity to access certain crucial health-related information, thus exacerbating health anxiety. Therefore, information avoidance may function as a criterion or belief influencing individuals' internet usage behavior. This result shows that users who tend to avoid information may not be able to effectively obtain information content when facing a large amount of health-related information, which interferes with users' ability to use information to solve health problems and causes people to suffer from health anxiety. This may be due to information avoidance associated with impaired cognitive flexibility in health-anxiety groups⁴⁴.The problem of impaired cognitive flexibility is prevalent in health-anxiety groups^{45, 46}, based on the "alert — avoidance" model theory proposed by the cognitive dissonance theory verified the idea of impaired cognitive flexibility, due to the health anxiety groups to disease information, in exposure to health-related negative stimuli, showed earlier than normal people noticed health-related negative information, later shift attention from the negative information⁴⁷。Because processing health information requires higher cognitive skills, search tasks are constantly switched during the search process. To reduce repeated switching between different search tasks, people with lower cognitive flexibility will take an active avoidance approach to reduce their transitions between different tasks.

Another view is that information avoidance, while reducing anxiety in a short period of time, does not change the risky health behaviors of individuals, let alone the negative beliefs about their own health. Therefore, negative beliefs and risk factors for health anxiety still exist, and they can still lead to health anxiety after avoiding threat messages. Moreover, the third view is that information avoidance is not the main cause of inducing health anxiety, but rather the influencing factor that maintains and aggravates health anxiety. Information avoidance may be affected by other information factors, such as information sources, information overload, and information anxiety⁴⁸, involved in the bidirectional promotion of compulsive network use and health anxiety. Therefore, information aversion may work together with other factors to affect health anxiety⁴⁸.

4.4 Response measures

According to the conclusions drawn in this study, health anxiety is affected by three factors: compulsive network use, uncertainty tolerance, and information avoidance. By intervening in the network-use behaviors of patients with health anxiety, Reduce continuous recommendations of health-related to disease in recommendation algorithms, Relieve negative emotional experiences, Reduce the sense of coercion in the search process; When the organizational structure of health information is adjusted by screening, sorting and integration, Enhance the review of disease and health-related information, Raise the threshold for relevant information release, Improve the accuracy and effectiveness of the information, Reduce the uncertainty of information search among health anxiety groups; Insert health-related tips in entertaining videos, music, fiction, Urge health anxiety patients with regular physical examination, Learn about health information from information released by professionals and authorities, Reduce the avoidance of your own health status. In addition, the health related information can use video, music, interactive games, health information to reduce the direct fuzzy description of disease degree and disease consequences, increase the diagnosis of disease and keep a healthy life skills, cultivate people healthy positive life concept, so as to reduce the overall health anxiety.

4.5 Research Limitations and Outlook

Although this study utilized a large sample, it may not fully represent the entire Chinese population in terms of socio-demographic variables. The cross-sectional research method used here limits our ability to infer causal relationships between variables. Additionally, the study only focused on one information factor's effect on health anxiety, neglecting other potential factors. Future research could employ experimental methods with detailed control variables or longitudinal tracking to investigate the established mediation model further. Furthermore, exploring the impact of various informational factors on health anxiety could enhance our understanding of this phenomenon.

In summary, this groundbreaking study revealed three main findings:

(a) A significant positive correlation exists between Compulsive Internet Use and Health Anxiety. (b) Uncertainty Intolerance acts as an intermediary variable, negatively mediating the relationship between Compulsive Internet Use and Health Anxiety. Additionally, Compulsive Internet Use positively impacts health anxiety through its influence on uncertainty tolerance. (c) Information avoidance does not mediate the effects of compulsive internet use and intolerance of uncertainty on health anxiety; instead, it directly contributes to increased levels of health anxiety.

These novel findings shed light on the intricate connections between Compulsive Internet Use, Uncertainty Intolerance, Information Avoidance, and Health Anxiety, contributing valuable insights to the existing body of knowledge in this area.

The following abbreviations are used in this manuscript:

WI Whiteley Index

CIUS the Compulsive Internet Use Scale

SUF the Smartphone Use Frequency questionnaire

IAS Information Avoidance Scale

a. Ethics declarations

The research project was approved by the Academic and Ethics Committee of Tianjin Normal University under the code of ethics 2023121301. All the participants have signed a written informed consent before participation. All methods were performed in accordance with the Declaration of Helsinki and participants could withdraw consent at any time.

b. Consent for publication

not applicable

c. Availability of data and materials

All of the material is owned by the authors or no permissions are required. The results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration by another publisher. I don't have any research data outside the submitted manuscript file.

d. Conflict of Interests

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

e. Funding

This work was funded by The National Social Science Fund of China - Health Anxiety and Coping Strategies of Information Poverty Group under the Health China Strategy (grant number: 21ATQ005).

f. Authors' contributions

W.L. and S.N. discussed the article’s research ideas, research methods, and framework. Specifically, W.L. is mainly responsible for conceptualization, literature review, and discussion. S.N. is responsible for data collection, data analysis, and the conclusion section. W.L. and S.N. are responsible for initial draft preparation. W.L. is responsible for revision and editing. All authors have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.

g. Acknowledgments: We would like to thank the undergraduates in five universities who participated in this research.

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No competing interests reported.

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Effects of Compulsive Internet Use on Health Anxiety: A Mediation Model

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Abstract

Figures

1 Introduction

2 Methods

2.1 Participants

2.2 Research tools

2.3 Statistical processing

2.4 Common method Deviation test

3 Results

3.1 Correlation analysis

3.2 Preliminary statistical analysis

3.3 Test of the mediation effect of the intolerance of uncertainty

3.4 Mediator model test with regulation

4 Discussion

4.1 Compulsive network use and health anxiety

4.2 Mediating role of intolerance of uncertainty

4.3 The effect of information avoidance

4.4 Response measures

4.5 Research Limitations and Outlook

5 Conclusion

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References

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