Starcevic and Berle [14] presented a definition of cyberchondria as “an excessive or repeated search for health-related information on the internet, driven by distress or anxiety about health, which only amplifies such distress or anxiety”; moreover, “it does not denote a diagnosis and occurs as part of health anxiety and hypochondriasis.” While giving a theoretical and empirically based framework, this definition also reformed the operationalization of cyberchondria by defining a process that includes a causal bidirectional relationship between cyberchondria and HA. It is important to underline that defining the precursors (HA as a trigger) and consequences (exacerbation of HA) of health-related internet use differentiates cyberchondria from merely searching the web for health-related information. Moreover, the multidimensionality of the construct was implied (eg, distress, excessiveness, and compulsion) [17]. Starcevic and Berle [14] hypothesized that cyberchondria-related behavior may be a form of reassurance seeking but that it should not be classified as a classic safety behavior, as in the short term, it increases anxiety instead of decreasing it [32]. If this definition is correct, it is important to explain how health-related internet use increases HA and why this behavior does not stop despite its adverse effects. In this regard, factors that amplify anxiety during health-related internet use are presented [33], which are assumed to set vicious circles in motion. They include the misinterpretation of the rank order of search results as pointing to the likely cause of a searched symptom [6,34] and the questionable trustworthiness of web-based health information [35]. However, current and partly inhomogeneous results raise doubts in this context [13,34,36].

White and Horvitz [6] hypothesized that a process referred to as query escalation is highly relevant for increased HA during medical web-based searches. They defined cyberchondria as “the unfounded escalation of concerns about common symptomatology, based on the review of search results and literature on the Web.” Escalations, in turn, were defined as special cases of cyberchondria during health-related internet use. They were operationalized as a shift of attention concerning the content of the information sought: away from a probable cause (eg, dehydration) for a common symptom (eg, a headache) to a serious illness (eg, cancer), which is a very unlikely cause for the bodily sensation.

To investigate this process, 11,158 naturalistic logs of a large (N=515) nonclinical sample’s internet searches were analyzed [6]. Approximately 2% of all queries had medical content, and 5.3% of them escalated, thus verifying the existence of query escalations. However, as the direct effects on HA were not assessed, it could not be shown that this was a mediating process for experiencing increased anxiety. Evidence was found that searches were performed repeatedly, as 78.3% of all medical queries contained a symptom that was sought again within 2 weeks after the initial search. Moreover, the results indicated that health-related internet use occurred impulsively with a switch between longer abstinent episodes and episodes of intensive searching behavior, which might be indicative of an intermittent reinforcement pattern.

Singh and Brown [37] investigated the occurrence and consequences of query escalations in dependence on the HA level of their participants in a laboratory experiment. They found that escalations resulted in higher anxiety compared with nonescalations, regardless of previously existing HA, and highly health-anxious individuals were significantly more likely to escalate. Approximately 60% of all participants performed at least one escalated health-related internet use.

There are initial indications for the relevance of query escalation as a moderating mechanism for the negative effects of health-related internet use and these lead to the conclusion that attentional aspects might be of relevance in cyberchondria. In a consecutive study, White and Horvitz [34] showed that potentially alarming content (eg, heart attack and medical emergency) in captions, snippets, and URLs of search results influences the search-result click-through behavior so that this attribute makes them more likely to be selected.

Cyberchondria was usually assessed using single items referring to the frequency or duration as well as the emotional consequences of health-related internet use [4,13,20]. These operationalizations neither took into account the postulated process character nor the multidimensionality of this construct [6,14]. In 2014, McElroy and Shevlin [17] developed the Cyberchondria Severity Scale (CSS), designed as a continuous measure of distress because of health-related internet use (according to previous conceptualizations [4,6,13,14]). This self-assessment questionnaire comprises 33 items that ask questions on a 5-point Likert scale about the frequency of web-based health-related behaviors. In contrast to previous assessment strategies, the CSS consists of five interpretable factors that reflect different dimensions of cyberchondria [16,17,38,39]. The factor compulsion reflects the different ways in which a web-based health-related search can unintentionally interrupt other web-based and offline activities. The dimension distress mirrors subjective negative emotional states because of health searches on the internet (stress, worry, anxiety, panic, and irritation). The factor excessiveness captures repeated searches for the same topic and the use of numerous sources. These 3 dimensions were also proposed by Starcevic and Berle [14]. Two additional subfacets are presented: all items loading on the factor reassurance seeking (hereafter called reassurance) indicate the felt need for reassurance from medical professionals triggered by information found on the web, representing a behavioral consequence of cyberchondria. The factor mistrust of medical professionals (hereafter called mistrust) reflects the conflict that web searchers have concerning whether to trust their medical professional over their own research results and self-diagnosis.

As detailed in Multimedia Appendix 4 [16-19,26,40,41] all CSS subscales showed moderate to strong intercorrelations, except for the mistrust factor, where only small or nonexistent associations were observed.

Although factor analyses revealed a five-factor structure of the CSS items, further analyses and observed correlation patterns raised doubts concerning the affiliation of mistrust to the concept of cyberchondria [16,38,39]. Higher-order factor analyses showed that a model consisting of a separate mistrust factor and a bifactor model comprising a general cyberchondria factor and 4 independent dimensions (compulsion, distress, excessiveness, and reassurance) best fit the data [16,38]. This showed that models generating a general cyberchondria factor had a superior fit to the data when mistrust was excluded. The four-factor structure was also found in a network analysis [42] that additionally revealed that no symptom seemed to be more central to the cyberchondria construct than others. On the other hand, Norr et al [38] pointed out that the findings regarding the mistrust factor may be attributable to method variance as all items of the scale are designed inversely. However, this approach has not been further investigated. Furthermore, qualitative data suggest that a certain mistrust of medical professionals and, specifically, of doctors, may play an important role [1]. In this context, a distinction has to be made between the affiliation of mistrust to the CSS and the affiliation of mistrust of doctors to cyberchondria; however, this question cannot be answered at this time. Further investigation is needed that takes into account the possibility that the CSS may not assess the construct in its entirety and that the general cyberchondria factor may represent a dimension of cyberchondria that is only weakly associated with mistrust. The original and revised CSS total scores (removing the mistrust items) were highly correlated (r=0.99 [16]).

Regarding convergent validity, the most important indicator for the CSS is its potential association with HA (see section Health Anxiety). Correlation analyses demonstrated that the CSS data were more strongly associated with anxiety (r=0.43; P≤.01) than with stress (r=0.37; P≤.01) and depression (r=0.24; P≤.01 [17]) using the short version of the Depression, Anxiety and Stress Scale [43]. The degree of association varies according to the theoretical similarities of the different constructs. Moreover, Fergus [16] showed that the CSS total score and the total score revised were more strongly associated with HA (r=0.59 and r=0.58, respectively; both P<.01) than with obsessive-compulsive symptoms (for both total scores, r=0.49; P<.01), as assessed using the Dimensional Obsessive-Compulsive Scale (DOCS) [44]. Barke et al [39] found medium positive correlations between the CSS global score and somatic symptoms (r=0.40; P<.01; assessed with the somatic symptom scale of the Patient Health Questionnaire [45,46]), depressive symptoms (r=0.31; P<.01; assessed with the short form of the Center for Epidemiologic Studies Depression Scale [47,48]), and health care use (r=0.29; P<.01; assessed with the Health Care Utilization questionnaire [49]).

As can be seen in Multimedia Appendix 4, the CSS subscales show different internal consistencies ranging from a high level for compulsion and distress to a good level for excessiveness, reassurance, and mistrust. The CSS total scale showed excellent internal consistency and split-half reliability without exception (α=.93-.96 [16,17,19,38,39]).

The first results show that the CSS seems to be unrelated to age [39], whereas results regarding sex differences are heterogeneous [2,39]. Too little information is currently available to finally evaluate these factors.

Other versions of the CSS regarding language (German [39] and Polish [40]) and length (short versions in English [50] and German [39]) show psychometric qualities comparable with the original version.

Jokić-Begić et al [51] developed a short questionnaire (4 items) to assess cyberchondria as a safety behavior. Besides predictors and negative outcomes, positive consequences were also intended to be measured; however, analyses revealed an unclear factor structure.

Problematic internet use describes the excessive use of the internet [52] for purposes other than searching for medical information and an inability to control that use [53], therefore reflecting behaviors from the fields of compulsion and addiction. Fergus and Dolan [30] define cyberchondria as a form of problematic internet use that is intended to reduce negative emotions but actually leads to greater subjective distress. To investigate this assumption, they used the Compulsive Internet Use Scale [54] and operationalized cyberchondria as the impact of health-related internet use on HA assessed with a single item. Individuals experiencing increased HA because of health-related internet use reported significantly greater levels of problematic internet use (mean 25.35, SD 11.58) compared with individuals experiencing no impact on (mean 18.63, SD 10.56; Cohen d=0.61; P<.01) or a decrease in HA (mean 21.76, SD 10.43; Cohen d=0.33; P<.01). These group differences stayed robust even after controlling for the frequency of health-related internet use and negative affect. These findings were supported by Fergus and Spada [31], who found a strong association between cyberchondria (operationalized by the CSS) and problematic internet use (r=0.59; P<.001). In this study, problematic internet use was assessed using the Problematic Internet Use Questionnaire [55], which consists of 3 dimensions (obsession, neglect of other activities, and control disorder). In addition, multiple linear regression with N=337 participants showed the robustness of this relationship (step 2; β=.41; P<.001) by controlling for age, gender, physical health, negative affect, and HA, where HA was the only covariate that accounted for variance in cyberchondria scores. Besides, Starcevic et al [42] found a stronger relationship between cyberchondria and problematic internet use than with HA. However, their network analysis showed that cyberchondria and problematic internet use were related but distinct constructs.

Fergus and Spada [31] concluded that cyberchondria could be viewed as a specific form of problematic internet use, indicating that concepts of problematic internet use may be of relevance to understanding cyberchondria. In addition, cognitive-behavioral treatments for problematic internet use may also be used to treat cyberchondria [30].

Moreover, Singh and Brown [11] found significant positive correlations between HA and 6 indicators of addiction to health-related internet use (inter alia, unsuccessfully trying to cut back, negative feelings regarding a real or anticipated loss, negative consequences, and increasing use over time).

Together, these findings underline the relevance of the compulsive and addictive aspects of cyberchondria-specific behavior.

Fergus and Spada [22,31] hypothesized the conceptualization of cyberchondria according to the metacognitive model of emotional disorders [56]. Following this model, individuals engage in self-regulation strategies that maintain and worsen negative affective states because of their metacognitive beliefs. In terms of cyberchondria, this would mean that health-related images, memories, or thoughts trigger HA. At the same time, metacognitive beliefs are activated, which can be distinguished into two types: positive metacognitions associated with advantages of health-related worries (eg, “Considering all possibilities will help keep my mind at rest” [31]) and negative metacognitive beliefs associated with disadvantages or the uncontrollability of health-related worries (eg, “My thoughts are uncontrollable” [31]). To reduce the triggered HA, a self-regulation process, namely health-related internet use, is initiated. Plans for supposed successful self-regulation are represented as mentioned in metacognitive beliefs and additionally in beliefs about rituals and stop signals. Rituals refer to plans for coping with aversive inner emotional experiences, and stop signals refer to self-relevant goals that signal when to stop the self-regulation process. Negative metacognitive beliefs, especially regarding the performance of health-related internet use (eg, “Once I start searching I cannot stop” [31]), which can arise in the course, may lead to an increase in negative affect and, thus, lead to further self-regulation processes in the form of health-related internet uses, resulting in a repetitive and distress-evoking vicious circle.

The relevance of metacognitive aspects for cyberchondria was supported by several results from 3 web-based questionnaire surveys by the same authors [22,31], in which the Metacognitions Questionnaire–Health Anxiety (MCQ-HA; [57]) was used. It incorporates three metacognitive beliefs: thoughts can cause illness (MCQ-HA-C), biased thinking (MCQ-HA-B; eg, “Worrying about my health will help me cope”), and thoughts are uncontrollable (MCQ-HA-U). In all studies, zero-order correlation analyses revealed that all metacognition subscales were significantly correlated with cyberchondria (MCQ-HA-C: rs=0.32-0.49, all P<.001; MCQ-HA-B: rs=0.47-0.58, all P<.001; and MCQ-HA-U: rs=0.51-0.66, all P<.001).

Hierarchical multiple linear regression analyses statistically controlling for relevant covariates (ie, age, gender, physical health status, HA negative affect, and anxiety sensitivity) showed that negative metacognitions (ie, uncontrollability of thoughts [22,31], beliefs about rituals [22], and beliefs about stop signals [22]) and obsessive-compulsive symptoms [22] contributed significantly to the variance in cyberchondria. However, the analyses yielded inhomogeneous findings regarding the relevance of positive metacognitive beliefs [22,31]. Interestingly, neither anxiety sensitivity nor intolerance of uncertainty shared significant, unique associations with cyberchondria [22]. A supplemental analysis using HA as the criterion variable (instead of cyberchondria) and cyberchondria as a covariate revealed that beliefs about rituals and stop signals distinguish cyberchondria from HA.

In summary, the presented results support the importance of metacognitive aspects in the conceptualization of cyberchondria. Nevertheless, the proposed function as a predisposing and maintaining factor in the cyberchondria process needs to be further investigated. In particular, the heterogeneous findings regarding the relevance of negative (vs positive) metacognitive beliefs need further attention to clarify if they have a unique function in maintaining health-related internet use despite its adverse effects.

Correlation analyses further revealed that cyberchondria clusters most strongly correlated with the affective component of HA, more precisely with health worries (r=0.57; P<.01 [19]; Multimedia Appendix 5). This finding is consistent with the results of Norr et al [38], who found relations between cyberchondria and the SHAI, which is argued to primarily assess an affective component of HA [24]. As worry was found to be linked to safety behavior [80], the authors suggest that health-related internet use may be an activity performed to reduce health worries.

Until the publication of the CSS [17], cyberchondria was assessed in two parts using two items: (1) frequency or duration of health-related internet use, and (2) its effects. Corresponding studies are detailed in Multimedia Appendix 7 [4,11,13,20,36,81,82]. Mostly moderate positive correlations were reported, indicating that the more health-anxious a person was, the more frequently and longer he or she searched the web for health- and illness-related information. This association was also found when HA was not operationalized continuously but dichotomously by ranking the SHAI scores of participants and using the bottom and top quartiles [4]. TePoel et al [81] observed a moderate positive association between HA and health-related internet use, indicating that individuals with higher HA reported more health-related internet use. This was true for both HA groups, clinical (β=.26; P<.001) and nonclinical (β=.29; P<.001).

It is hypothesized that cyberchondria is connected with obsessive-compulsive symptoms. Correlational studies have used DOCS [44] to assess these. It consists of 4 dimensions: contamination, responsibility for harm (hereafter called responsibility), unacceptable thoughts (hereafter called thoughts), and symmetry. Each is judged for time spent, avoidance, distress, interference, and attempts to control. It was shown that the DOCS total scale is significantly correlated to the CSS total scales with (r=0.49, P<.01 [16]; r=0.38, P<.01 [40]) and without mistrust (r=0.49, P<.01 [16]; r=0.56, P<.001 [22]; r=0.38, P<.0 [40]) and to all CSS subscales (distress: r=0.50, P<.01 [16]; r=0.43, P<.01 [40]; compulsion: r=0.46, P<.01 [16]; r=0.34, P<.01 [40]; excessiveness: r=0.35, P<.01 [16]; r=0.31, P<.01 [40]; reassurance: r=0.27, P<.01 [16]; r=0.23, P<.01 [40]; mistrust: r=0.11, P<.01 [16]; r=0.07, not significant [40]), such that individuals with greater obsessive-compulsive symptoms experience greater cyberchondria. Moreover, as detailed in Multimedia Appendix 8 [18,19,40], all CSS and DOCS subscales showed significant and mostly moderate intercorrelations. No statement can be made about the mistrust factor as it was excluded from the primary analyses. Interestingly, correlation coefficients were consistently smaller in the study conducted by Fergus and Russell [16] compared with those by Norr et al [18]. This might originate from a range restriction because of stricter eligibility criteria used by Fergus and Russell [19] regarding the performance of health-related internet use and the nonexistence of a diagnosed medical condition.

Although an association between cyberchondria and obsessive-compulsive symptoms was confirmed, different hypotheses exist about the nature of this relationship. First, it is supposed that obsessive-compulsive symptoms are an essential part of the cyberchondria construct. As was seen in section Dimensional Conceptualizations of Cyberchondria, McElroy and Shevlin [17] argue that health-related internet use can interrupt other web-based and offline activities. The results regarding the CSS dimension compulsion are reported in the aforementioned section. Here, we recap the results briefly. The subscale correlates highly with the CSS total scale (r=0.82; P<.01) and shows moderate to strong correlations with the other CSS subscales (r=0.26-0.80, excluding mistrust). Factor analyses [16,38] showed that compulsion seems to be part of a higher-order cyberchondria factor.

Another group of authors hypothesized that obsessional and compulsive behavioral elements contribute to the maintenance of cyberchondria [26]. Starcevic and Berle [14] suggested that maintenance is because of the combination of (1) an obsessional doubt regarding the validity and sufficiency of information found on the web, and (2) a hope to find the one perfect explanation for the symptoms experienced, which may represent a compulsive element of the cyberchondria construct. Following this argument, the subject would assume that continuing to perform health-related internet use would increase the probability of finding the ultimate answer, and for this purpose, any anxiety triggered by health-related internet use is acceptable. However, no empirical findings exist to address this hypothesis. Norr et al [18] postulated maintenance of health-related internet use because of a positive bidirectional association between cyberchondria and symptoms related to the DOCS subscale contamination. If health-related internet use is carried out to obtain reassurance, this behavior may lead to an increased obsession with physical health, owing to the strong link between cyberchondria and HA. This, in turn, may lead to an increased urge to prevent contamination and illnesses, for example, by increased hand washing. This amplified obsession with health may lead to further health-related internet use. Moreover, it is conceivable that if individuals with cyberchondria believe that health-related internet use gives them the power to prevent future illnesses, there may be a connection to the DOCS subscale responsibility. The symmetry and thoughts subscales are postulated to be unrelated. The structural equation model confirmed the predicted unique relationships. This model, controlling for negative affect (Positive and Negative Affect Schedule [83]) and HA (SHAI [68]), provided a good fit to the data (χ²=2954.63; P<.05; CFI=0.94; Tucker–Lewis index=0.93; root mean square error of approximation=0.05; 90% CI 0.05-0.06). Norr et al [18] concluded that a co-occurrence of both constructs and repeated health-related internet use might function as a safety behavior to reduce contamination concerns or responsibility for harm.

Another approach by Fergus and Russell [19] hypothesized that the existing findings regarding associations are because of a redundancy of the constructs. Health-related internet use may represent the behavioral component of both HA (eg, reassurance seeking) and obsessive-compulsive symptoms (eg, neutralizing behavior). They conducted confirmatory factor analyses to examine whether intercorrelations among these 3 constructs were best represented by indicator loadings on the same or separate latent constructs. Analyses showed that cyberchondria seems to be a distinct construct from HA and obsessive-compulsive symptoms, although they are related as a correlated three-factor model provided the best fit to the data (χ²₍₄₁₎=149.3; comparative fit index=0.96; nonnormed fit index=0.95; standardized root mean square residual=0.06; root mean square error of approximation=0.08; 90% CI 0.69-0.99). In this model, a latent correlation of r=0.58 (P<.001) between cyberchondria and obsessive-compulsive symptoms was observed. This finding of distinctness of both constructs was confirmed by a network analysis by Starcevic et al [42].

In summary, the available empirical evidence is insufficient to finally characterize the nature of the relationship between cyberchondria and obsessive-compulsive symptoms. Moreover, it remains unclear whether obsessive-compulsive symptoms contribute to the maintenance of cyberchondria or vice versa. One clear shortcoming of research to date is that exclusively cross-sectional questionnaire-based surveys exist, which do not allow the investigation of processes and causality. Experimental studies and longitudinal data are needed to answer these questions.

Intolerance of uncertainty is defined as a dispositional fear of the unknown [84]. It captures the inability to tolerate the uncertainty of ambiguous situations. It was found to comprise 2 dimensions, which are operationalized in the multidimensional Intolerance of Uncertainty Scale [85]: prospective intolerance of uncertainty reflects perceptions of threat as well as implications of future uncertainty. Inhibitory intolerance of uncertainty mirrors the desire to avoid uncertainty and behavioral symptoms of apprehension when faced with it. Considering intolerance of uncertainty as a risk factor for cyberchondria seems to be justified because of its substantial associations with HA [25,86].

The results from a qualitative interview study by Singh et al [1] support the relevance of uncertainty about whether one has an undiagnosed health issue for developing a felt need to go on the web and search for medical content. An association was confirmed by mainly medium-sized correlations (Multimedia Appendix 1), and a network analysis also revealed that both constructs were distinct [42]. In particular, inhibitory intolerance of uncertainty may be a risk factor for experiencing distress because of health-related internet use [21,25].

In addition, during health-related internet use, multiple medical possibilities are presented to the user [6], and for people with high intolerance of uncertainty, ambiguous situations were found to be distressing. Moreover, creating catastrophic interpretations of unclear health information is only related to HA at a high intolerance of uncertainty [24]. The moderating role of intolerance to uncertainty on the relationship between cyberchondria and HA seems conceivable to explain why some individuals experience worse HA as a consequence of health-related internet use, whereas others do not (see section Consequences of Health-Related Internet Use). A regression analysis by Fergus [20] confirmed this finding. The relationship between the frequency of health-related internet use and HA because of these searches was significant at high levels of intolerance of uncertainty (b=0.27; partial r=0.21; P<.01) but not at low (b=–0.06; partial r=–0.03, not significant).

This indicates that the desire to avoid uncertainty and negative reactions to it are strongly associated with experiencing negative affective states because of health-related internet use, potentially because of increased catastrophic thinking about the meaning of bodily symptoms, as concluded by Fergus [21]. Another conceivable explanation for this finding may be that the tendency to react negatively to uncertainty and the resulting desire to avoid it may lead to further health-related internet use to reduce uncertainty. However, the more health-related internet uses are conducted, the greater the possibility of finding ambiguous and inconsistent information, which has the potential to trigger the negative affect.

In addition, intolerance of uncertainty was also found to moderate another detrimental effect of health-related internet use concerning anxiety sensitivity (see section Anxiety Sensitivity). Only individuals with high intolerance of uncertainty experience elevated anxiety sensitivity as a consequence of viewing web-based medical content [23].

Although people with intolerance of uncertainty experience uncertainty in general as dangerous, people with high levels of anxiety sensitivity interpret anxiety-related symptoms as dangerous [23]. This was found to be a potential risk factor for HA [87], and therefore, a link between anxiety sensitivity and cyberchondria-specific behavior was hypothesized [21,25]. It is commonly operationalized by the Anxiety Sensitivity Index-3 [88], which consists of three lower dimensions reflecting different types of concerns: cognitive (ie, concerns about mental incapacitations), physical (ie, concerns about immediate complications), and social (ie, concerns about social rejection because of publicly observable symptoms of anxiety). Correlational analyses supported the relevance of anxiety sensitivity for the cyberchondria construct (Multimedia Appendix 2). The coefficients range from a moderate to a high level. Different conclusions can be drawn from this study. The results may indicate that health-related internet uses are performed on various concerns (cognitive, physical, and social). Moreover, anxiety sensitivity may be relevant, especially for those experiencing distress because of health-related internet use. The structural equation models that included anxiety sensitivity, intolerance of uncertainty, and HA (operationalized by the SHAI) as independent variables to predict cyberchondria (operationalized by the CSS total score, excluding mistrust) highlighted the important role of anxiety sensitivity as a predictor for cyberchondria in addition to the contributions of intolerance of uncertainty and HA [25]. However, besides the role of anxiety sensitivity as a risk factor, it was also hypothesized to be a detrimental consequence of health-related internet use. Corresponding results are reported in detail in the section Consequences of Health-Related Internet Use.

In the context of chronic pain, the contribution of pain catastrophizing to cyberchondria has been investigated [63]. It has been shown that pain catastrophizing (ie, the tendency to ruminate and worry about pain [89]) significantly predicts cyberchondria and its facets (operationalized by the CSS), even when controlling for negative affect and HA. Individuals with chronic pain often experience anxiety and distress about the origin and consequences of their pain perceptions and search for answers on the web. Pain catastrophizing may amplify the negative affect and may contribute to the initiation of the cyberchondria-specific vicious circle, as postulated by Starcevic and Berle [14]. Further support is provided by logistic regression analysis that aims to predict engaging in health-related internet use by psychopathologies and somatic symptoms [5] and comprises data from 992 adults from the general population of whom, 751 (75.7%) reported engaging in health-related internet uses in the past 3 months. It was shown that conducting health-related internet uses was associated with HA, obsessive-compulsive symptoms, and intolerance of uncertainty (among other psychopathologies); however, only the severity of somatic symptoms independently predicted health-related internet use when each of these pathological domains was controlled for.

It has been hypothesized that health-related internet use is able to trigger further health care use to receive reassurance, especially in individuals with elevated HA. This hypothesis is supported by several findings. Singh and Brown [11] found a medium correlation between HA and the likelihood of visiting a physician after the search (r=0.22; P<.01). Our meta-regression (see section A Meta-analytic Integration of Cyberchondria Operationalized by the CSS) regarding the association between the CSS subscale reassurance and HA yielded a strong correlation (β=.44; P<.001). Eastin and Guinsler [92] investigated the moderating role of HA in this process. HA was operationalized by the Health Anxiety Questionnaire [93], health-related internet use by its frequency, and health care use because of health-related internet use by the frequency of physician consultations and the number of different physician visits. Regression analysis confirmed a significant interaction, indicating that as HA increases, the relationship between the frequency of health-related internet use and health care use increases. Furthermore, individuals with high HA (Illness Attitude Scale≥47 [41]) considered dysfunctional behavior (eg, physician hopping and ordering nonprescribed medication on the web) to be more likely because of health-related internet use [36]. In terms of the Cyberchondria model proposed by Brown et al [26], these results might indicate that individuals with normal levels of HA are better able to correctly judge the seriousness of the threat originating from health-related internet use and decide whether a physician consultation is necessary. Interestingly, it seems as if the use of physical health care plays a more important role compared with mental health care use. Using structural equation modeling, the CSS subscale reassurance showed a stronger association with the use of physical health care (β=.70) than with mental health care (β=.50) over the past 60 days [64]. In addition, the subscale excessiveness was negatively associated with mental health care use (β=–.49; P<.001), indicating that individuals who repeatedly engage in health-related internet use report less use of mental health care.

In an extension of the compulsion subfacet of cyberchondria [17], which reflects different ways in which health-related internet use can interrupt other web-based and offline activities, it was hypothesized that cyberchondria might lead to significant impairment in psychosocial functioning.

In line with this, it was found that cyberchondria was strongly associated with greater functional impairment even when controlling for the effects of HA (operationalized by the SHAI [68]) [64]. Functional impairment was defined as one’s ability to engage in daily activities, operationalized using the Sheehan Disability Scale [94]. Interestingly, when accounting for HA, CSS was not associated with decreased quality of life, which was operationalized as one’s overall level of contentment and satisfaction regarding 4 domains: physical and psychological health, social relationships, and environment (World Health Organization Quality of Life Assessment [95]). These results might indicate that individuals with cyberchondria may be satisfied with their lives, although they feel functionally impaired by their cyberchondria-specific behavior.