Medical mistrust and its association with cyberchondria: A cross-sectional study among Lebanese adults

Abstract

BACKGROUND

Medical mistrust, defined as a lack of confidence in physicians and healthcare institutions, has been linked to poorer adherence, vaccine hesitancy, and reduced engagement with care. In parallel, cyberchondria, characterized by excessive and anxiety-driven online health information seeking, has emerged as a growing concern, particularly in settings where trust in healthcare systems is strained. In Lebanon, recurrent economic, political, and health system crises may amplify both mistrust and reliance on online sources; however, the relationship between medical mistrust and cyberchondria has not been examined.

AIM

To evaluate the relationship between medical mistrust and cyberchondria among Lebanese adults and to examine their association with previous medical errors.

METHODS

A cross-sectional online survey was conducted between August and October 2022 among 474 Lebanese residents aged ≥ 18 years, recruited using convenience and snowball sampling via social media and community networks. The questionnaire collected sociodemographic data, physical and mental health history, coronavirus disease 2019 (COVID-19) vaccination status and trust, and previous experiences of misdiagnosis or mistreatment. Medical mistrust was measured with the 17-item Medical Mistrust Index (MMI-17), and cyberchondria with the 12-item Short Cyberchondria Severity Scale (CSS-12). Data were analyzed using descriptive statistics, independent-samples t-test, analysis of variance, and simple linear regression, with a significance level of P < 0.05.

RESULTS

The sample was predominantly young adults, with a slight female majority and over half being students. Higher MMI-17 scores were observed among males, participants aged 26 years to 35 years, those reporting mental health conditions, individuals who lacked trust in the COVID-19 vaccine, and those with a history of misdiagnosis, mistreatment, loss of a relative due to medical error, or preference for herbal medicine. Higher CSS-12 scores were found among males, residents of certain governorates, participants with physical or mental health conditions, those who did not trust the COVID-19 vaccine, and individuals reporting previous misdiagnosis, loss due to medical error, or preference for herbal medicine. In simple linear regression, medical mistrust was positively associated with cyberchondria (unstandardized β approximately 0.37; P < 0.001), with medical mistrust explaining a small proportion of the variance in CSS-12 scores (R² approximately 0.03).

CONCLUSION

The sample was predominantly young adult students, with a slight female majority. Higher MMI-17 scores were observed among males; participants aged 26 to 35 years; those reporting mental health conditions; individuals who lacked trust in the COVID-19 vaccine; and those with a history of misdiagnosis, mistreatment, loss of a relative due to medical error, or preference for herbal medicine. Higher CSS-12 scores were found among males; residents of certain governorates; participants with physical or mental health conditions; those who did not trust the COVID-19 vaccine; and individuals reporting previous misdiagnosis, loss due to medical error, or preference for herbal medicine. In simple linear regression, medical mistrust was positively associated with cyberchondria (unstandardized β approximately 0.37; P < 0.001), with medical mistrust explaining a small proportion of the variance in CSS-12 scores (R² approximately 0.03).

Key Words: Medical mistrust; Cyberchondria; Health anxiety; Medical errors; Patient-physician communication

Core Tip: This study explored the relationship between medical mistrust and cyberchondria among Lebanese adults. A significant positive correlation was identified, indicating that individuals with higher medical mistrust scores were more likely to exhibit severe cyberchondria behaviors. Previous medical errors, mental health conditions, and vaccine hesitancy were key contributing factors. Addressing patient physician communication and restoring trust in healthcare systems may help mitigate excessive online health-information seeking and improve health outcomes.

INTRODUCTION

Trust is a complex construct with multiple definitions in the health literature, one of which is a bond between two individuals or between an individual and a system[1]. It is considered a core element of healthcare, in which the patient’s best interests are paramount[2]. Mistrust, however, is not merely the opposite of trust; it stems from conflict between opposing sides and from the belief that decisions are not in one’s best interest. Thus, medical mistrust reflects tension and a lack of confidence between patients and healthcare systems[3]. It revolves around past medical incidents, vulnerability, confidentiality with physicians, and lack of patient-centered communication[4,5]. The literature has examined medical mistrust in relation to adherence to human immunodeficiency virus treatment, acceptance of coronavirus disease 2019 (COVID-19) vaccination, and experiences of racism among Black African Americans[6,7]. Mistrust in medical professions appears to be increasing; for example, a 2019 study highlighted how mistrust in medicine contributed to the rise of the anti-vaccination movement in the United States, resulting in measles outbreaks in several regions[3]. Medical mistrust centers on the belief that physicians act contrary to patients’ best interests[8]. In clinical settings, it is particularly important because it affects patients’ engagement with care and their future healthcare decisions[9]. These developments raise the concern that individuals who mistrust healthcare professionals may increasingly turn to alternative sources of information, particularly the Internet, when making health decisions.

In this study, we hypothesized that higher levels of medical mistrust are associated with greater cyberchondria, as mistrust may drive individuals away from professional advice and toward excessive online health information seeking.

Previous medical errors and misdiagnoses represent a significant public health issue and pose a major threat to patient care[10,11]. Medical errors include technical errors, system-related errors, and human errors such as errors in medication, diagnosis, and treatment[12]. Although medical errors are inevitable, their prevalence is what concerns patients the most[12]. A study in Iran approximated a 50% prevalence of medical errors[12], and another study in the United Kingdom estimated a 57.9% prevalence of medication errors[13]. Furthermore, low-income and middle-income countries suffer 2.6 million deaths annually due to unsafe healthcare practices[10]. Nationally, a Lebanese study found that 59.6% of 277 patients were taking at least one inappropriate medication[14]. Numbers such as these have taken their toll on patients, as trust between physicians and the public is wavering[11]. Individuals who have experienced or perceived medical errors may develop lasting mistrust toward healthcare professionals and become reluctant to rely solely on medical advice. This can lead to greater reliance on the internet rather than medical professionals when seeking information about one’s health[15], potentially setting the stage for excessive and anxiety-driven online health information seeking.

In recent decades, access to medical information has become easier, with many people having free access to large amounts of health-related information online[16]. This is especially evident during pandemics, when traditional and social media are flooded with conflicting and sometimes alarming information that can trigger anxiety in the population[17]. This accessibility has contributed to the rise of cyberchondria, a behavior characterized by excessive and frequent online searching for illnesses, often exacerbated by high levels of anxiety[18]. Even though cyberchondria is not mentioned directly, it is used as one of the diagnostic features of illness anxiety disorder, distinguished by the patient’s irrational degree of online searching for their suspected disease[19,20]. To put it simply, cyberchondria is a reassurance-seeking safety behavior in individuals with high levels of health anxiety[21]. Cyberchondria is said to involve an augmented emotional state, inability to tolerate uncertainty, and skepticism of the healthcare system[18,21,22]. Approximately 60% to 80% of Americans use the Internet to search for health-related information, but only about 2% of these searches lead to reliable medical content[23]. A 2016 United Kingdom study showed that more than 50% of people search for medical information online[24]. The study showed that cyberchondria is interrelated with obsessive-compulsive symptoms similar to those seen in obsessive-compulsive disorder[25]. A study done in Lebanon during the COVID-19 pandemic also found an association between cyberchondria and quality of life, mediated by factors such as anxiety, depression, and mental health issues[26]. Taken together, these findings suggest that in an environment where trust in healthcare may be compromised, easy access to unfiltered online information can promote a cycle in which mistrust and health anxiety drive repeated, excessive health-related searches, i.e., cyberchondria.

Certain studies emphasize that the mistrust factor in the Cyberchondria Severity Scale (CSS) cannot be overlooked when assessing its relation to cyberchondria[15,27]. Others, however, have highlighted that the mistrust factor in the CSS is non-essential and not strongly associated with cyberchondria, and have therefore excluded it from shorter versions of the scale[28-30]. These mixed psychometric findings leave uncertainty about how strongly mistrust is actually related to cyberchondria, particularly when mistrust is measured independently rather than as a single subdimension of a broader scale. During the COVID-19 pandemic, several surveys worldwide highlighted that medical mistrust was associated with lower adherence to protective measures and greater susceptibility to misinformation, while anxiety about infection was linked to extensive online health information seeking[7,31]. A United Stated study found a high prevalence of medical mistrust regarding COVID-19 vaccination: 75% of participants were less likely to join vaccine trials and 52% were unwilling to take the vaccine[32], with Black African Americans reporting the highest medical mistrust scores[32]. The patient-physician relationship has become increasingly strained due to recent alarming events in the medical field, which may hinder accurate diagnosis and negatively affect patients’ health[33]. Interpersonal trust between patients and providers is often neglected, even though it is the foundation of proper healthcare[34]. In this context, it is plausible that individuals who mistrust physicians are especially likely to rely on online sources for reassurance, thereby increasing their risk of developing cyberchondria; yet this hypothesis has rarely been tested using dedicated measures of medical mistrust and cyberchondria in the same study.

To the best of our knowledge, medical mistrust has not been systematically examined in Lebanon, and its relationship with cyberchondria remains unexplored. The Lebanese context is characterized by repeated economic, political, and health system crises, which may heighten both mistrust in institutions and reliance on online information. Understanding how medical mistrust relates to cyberchondria in this setting is therefore essential for designing interventions that rebuild trust and promote safe health information-seeking behaviors.

This study evaluated the relationship between medical mistrust and cyberchondria among Lebanese adults and examined their association with previous medical errors.

MATERIALS AND METHODS

Study design and setting

This cross-sectional study was conducted between August and October 2022, using an online Google forms questionnaire distributed via various social media platforms to more than 1000 literate Lebanese residents aged 18 years and above, with convenience and snowball sampling. The minimal required sample size was 474, assuming a 70% response rate, a 95% confidence level, a 5% margin of error, and 80% power. We received 474 responses from different Lebanese districts (Akkar, Baalbeck El Hermel, Beirut, Bekaa, Mount Lebanon, Nabatieh, North Lebanon, South Lebanon). Inclusion and exclusion criteria: Lebanese residents aged 18 years and above who were able to read Arabic or English and who provided electronic informed consent were eligible to participate. Only respondents who completed the core sections of the questionnaire [sociodemographic data, Medical Mistrust Index (MMI), and 12-item Short CSS (CSS-12)] were included in the analysis. Participants with self-reported physical or mental health conditions were not excluded, as these variables were of interest in the present study.

Questionnaire

The questionnaire was available in both English and Arabic and was translated using a forward, backward translation procedure. A pilot study was conducted among 25 participants from the target population to assess clarity, wording, and length of the questionnaire. Based on their feedback, we simplified the wording of several sociodemographic and vaccination items, clarified response options for the mental health and medical error questions, and reorganized the order of some questions to improve flow and comprehensibility. The responses from these 25 pilot participants were not included in the final analytical sample. The survey included five sections: (1) Introduction and consent; (2) Sociodemographic data; (3) Data regarding COVID-19 vaccination and previous misdiagnoses; (4) Assessment of medical mistrust using the 17-item MMI (MMI-17)[35]; and (5) Assessment of cyberchondria using the CSS-12[28,30].

Sociodemographic data: This section included age, sex, nationality, place of residence, marital status, level of education, employment status, whether the participant is a student or works/studies in the healthcare field, monthly income, health and mental health conditions, and smoking status.

Relevant data: Participants were asked about their trust in the COVID-19 vaccine, number of doses taken, reasons for vaccination, type of healthcare facility usually attended, whether they had been misdiagnosed or mistreated and whether this led to permanent damage or the loss of a family member, and their preferred type of medicine (modern vs herbal/spiritual).

MMI: Participants’ level of medical mistrust was assessed using the MMI-17[35], which employs a 4-point Likert-type scale (“strongly disagree,” “disagree,” “agree,” and “strongly agree”), where “strongly disagree” = 1 and “strongly agree” = 4. Higher scores indicate greater levels of mistrust. Certain items were reverse-coded so that for these, “strongly agree” = 1 and “strongly disagree” = 4. In the present sample (n = 474), the scale’s Cronbach’s alpha was 0.79.

CSS-12: The CSS-12[28,30], derived from the original 33-item CSS (CSS-33), was used in this study. It evaluates cyberchondria across four dimensions: Excessiveness, distress, reassurance, and compulsion. It was scored on a 5-point Likert-type scale (“never,” “rarely”, “sometimes”, “often”, and “always”), where “never” = 1 and “always” = 5. Higher scores indicate greater cyberchondria severity. In this study, Cronbach’s alpha for the CSS-12 was 0.877.

Statistical analyses

Statistical analyses were performed using SPSS version 28.0 (IbM SPSS Statistics, Armonk, NY, United States). Data included both categorical and numerical variables: Categorical variables are presented as the absolute frequencies and percentages, and numerical variables as the mean ± SD. Normality of continuous variables was assessed using the Shapiro-Wilk test and visual inspection of histograms and Q-Q plots. Parametric tests were applied, including independent-samples t-tests and analysis of variance. Correlations between medical mistrust and cyberchondria were analyzed using a simple linear regression model. Significance was set at P < 0.05.

RESULTS

Demographics

A total of 474 participants from different Lebanese districts were included in the study. The majority were aged 18 years to 25 years, and females constituted 57.8% of the sample. Most participants were Lebanese, more than half were single, and just over half were students. Approximately one-third worked or studied in the healthcare field (Table 1).

Table 1 Demographic data of respondents.

Characteristics (n = 474)	n (%)
Age (years)
18-25	257 (54.2)
26-35	65 (13.7)
36-45	65 (13.7)
46-55	60 (12.7)
56-65	22 (4.6)
66-75	-
> 75	5 (1.1)
Sex
Male	200 (42.2)
Female	274 (57.8)
Nationality
Lebanese	457 (69.4)
Palestinian	2 (0.4)
Syrian	10 (2.1)
Others1	5 (1.1)
Place of Residence
Akkar	17 (3.6)
Baalbeck-El Hermel	19 (4)
Beirut	130 (27.4)
Bekaa	46 (9.7)
Mount Lebanon	73 (15.4)
Nabatieh	12 (2.5)
North Lebanon	57 (12)
South Lebanon	120 (25.3)
Marital status
Single	297 (62.7)
Married	159 (33.5)
Divorced	10 (2.1)
Widowed	8 (1.7)
Highest level of education
Not educated	3 (0.6)
Entered but didn’t finish high school	25 (5.3)
High school diploma	171 (35.1)
Bachelor’s degree	198 (41.8)
Post graduate degree	77 (16.2)
Employment status
Employed	154 (32.5)
Self-employed	67 (14.1)
Unemployed	253 (53.4)
Currently, you are a student
Yes	255 (53.8)
No	219 (46.2)
Currently, you are a worker/student in the healthcare field
Yes	158 (33.3)
No	316 (66.7)
Monthly income of the family
Less than 500 United States dollars	216 (45.6)
500-1000 United States dollars	105 (22.2)
1000-2000 United States dollars	71 (15)
More than 2000 United States dollars	82 (17.3)

¹Including Iraq, Venezuela, Brazil, and the United States of America.

Medical and social history

Less than one-quarter of respondents (108/474) reported having health conditions, most commonly cardiovascular diseases (36.11%). Mental health conditions were reported by 176 participants (37.1%), with stress and anxiety being the most prevalent (72.73%). In total, 154 participants (32.5%) identified as smokers.

Medical trust

Among all respondents, 68.6% reported trusting the COVID-19 vaccine, and 88.97% had received at least one vaccine dose. Of those vaccinated, most (61.2%) had received two doses, 31.4% had three doses, and 66.4% indicated health and safety as their primary motivation. The majority of participants received medical care in private hospitals (42.2%), followed by private clinics (29.1%) and governmental hospitals (11.2%). A total of 30.4% reported having been misdiagnosed, and 28.9% reported receiving the wrong treatment. A small proportion (6.1%) experienced permanent damage due to medical error, while 31.9% reported losing someone close due to a medical error. Most respondents (82.5%) preferred modern medicine to herbal alternatives (Table 2).

Table 2 Medical trust of respondent.

Characteristics (n = 474)	n (%)
Do you trust the COVID-19 vaccine?
Yes	325 (68.6)
No	149 (31.4)
Did you take the COVID-19 vaccine?
Yes	417 (88.97)
No	57 (12.03)
How many COVID-19 vaccine doses did you take? (n = 417)
I took the 1 dose	21 (5)
I took 2 doses	255 (61.2)
I took 3 doses	131 (31.4)
I took 4 doses	10 (2.4)
What was the main reason you took the COVID-19 vaccine? (n = 417)
For my health and to stay safe	277 (66.4)
My parents pushed me to get vaccinated	6 (1.4)
It was mandatory at my workplace/university	85 (20.4)
In order to travel/go to nightclubs and restaurants that mandate vaccination	47 (11.3)
Other reasons	2 (0.5)
Where do you usually receive medical care?
Governmental hospitals	53 (11.2)
Private hospitals	200 (42.2)
University hospitals	46 (9.7)
Private clinic	138 (29.1)
Dispensary	27 (5.7)
Other sites	10 (2.1)
Have you been misdiagnosed before?
Yes	144 (30.4)
No	330 (69.6)
Have you been given the wrong treatment before?
Yes	137 (28.9)
No	337 (71.1)
Have you been suffering any permanent damage due to a medical error?
Yes	29 (6.1)
No	445 (93.9)
Have you lost anyone close to you due to a medical error?
Yes	151 (31.9)
No	323 (68.1)
Which do you prefer?
Modern medicine	391 (82.5)
Herbal medicine	83 (17.5)

COVID-19: Coronavirus disease 2019.

Correlation between medical mistrust and cyberchondria

Linear regression analysis was used to determine whether medical mistrust predicted cyberchondria. Higher MMI scores were a significant predictor of higher CSS-12 scores (unstandardized β = 0.366, P < 0.001), and variations in medical mistrust scores explained 3.1% of the variance in cyberchondria (R² = 0.031; Table 3).

Table 3 Predictor of cyberchondria severity score.

Predictor	Unstandardized beta	Standardized beta	R2	P value
MMI	0.366	0.177	0.031	< 0.01

MMI: Medical Mistrust Index.

Medical Mistrust and Cyberchondria Scales: The MMI-17 mean score was significantly associated with: (1) Age (26 years to 35 years = highest mean 2.55; P = 0.016); (2) Sex (males = 2.63 vs females = 2.52; P < 0.001); (3) Mental health conditions (2.65 vs 2.54; P < 0.001); (4) Lack of COVID-19 vaccine trust (2.69 vs 2.53; P < 0.001); (5) Previous misdiagnosis (2.69 vs 2.53; P < 0.001); (6) Previous mistreatment (2.65 vs 2.55; P = 0.002); (7) Loss of someone due to medical error (2.64 vs 2.56; P = 0.011); and (8) Preference for herbal medicine (2.72 vs 2.55; P < 0.001). No significant associations were found with place of residence, education level, income, or type of healthcare facility (Table 4).

Table 4 Medical Mistrust Index correlations.

Characteristics (n = 474)	Medical Mistrust Index Score mean/4	P value
Age (years)
18-25	2.57	0.016a
26-35	2.69
36-45	2.56
46-55	2.61
56-65	2.42
66-75	-
> 75	2.62
Sex
Male	2.63	< 0.01b
Female	2.52
Place of residence
Akkar	2.59	0.243
Baalbeck-El Hermel	2.60
Beirut	2.56
Bekaa	2.60
Mount Lebanon	2.53
Nabatieh	2.71
North Lebanon	2.67
South Lebanon	2.57
Highest level of education
Not educated	2.29	0.072
Entered but didn’t finish high school	2.48
High school diploma	2.55
Bachelor’s degree	2.61
Postgraduate degree	2.62
Currently, you are a worker/student in the healthcare field
Yes	2.54	0.065
No	2.60
Monthly Income of the family
Less than 500 United States dollars	2.59	0.655
500-1000 United States dollars	2.55
1000-2000 United States dollars	2.59
More than 2000 United States dollars	2.60
Suffering from health conditions
Yes	2.57	0.684
No	2.58
Suffering from mental health conditions
Yes	2.65	< 0.01b
No	2.54
Do you trust the COVID-19 vaccine?
Yes	2.53	< 0.01b
No	2.69
Did you take the COVID-19 vaccine?
Yes	2.49	0.072
No	2.59
What was the main reason you took the COVID-19 vaccine?
For my health and to stay safe	2.51	< 0.01b
My parents pushed me to get vaccinated	2.67
It was mandatory at my workplace/university	2.67
In order to travel/go to nightclubs and restaurants that mandate vaccination	2.71
Other reasons	1.79
Where do you usually receive medical care?
Governmental hospitals	2.62	0.845
Private hospitals	2.59
University hospitals	2.53
Private clinic	2.57
Dispensary	2.58
Other sites	2.61
Have you been misdiagnosed before?
Yes	2.69	< 0.01b
No	2.53
Have you been given the wrong treatment before?
Yes	2.65	0.002a
No	2.55
Have you been suffering any permanent damage due to a medical error?
Yes	2.67	0.063
No	2.58
Have you lost anyone close to you due to a medical error?
Yes	2.64	0.011a
No	2.56
Which do you prefer?
Modern medicine	2.55	< 0.01b
Herbal medicine	2.72

^aP < 0.05.

^bP < 0.01.

COVID-19: Coronavirus disease 2019.

Males showed significantly higher CSS-12 scores (2.27 ± 0.45) than females (2.08 ± 0.40; P = 0.002). The CSS-12 score was also significantly associated with: (1) Place of residence (Baalbeck-El Hermel = highest mean 2.55; P = 0.023); (2) Physical health conditions (2.33 vs 2.15; P = 0.017); (3) Mental health conditions (2.34 vs 2.10; P < 0.001); (4) Lack of COVID-19 vaccine trust (2.31 vs 2.14; P = 0.01); (5) Previous misdiagnosis (2.30 vs 2.14; P = 0.024); (6) Loss of someone due to medical error (2.31 vs 2.14; P = 0.011); and (7) Preference for herbal medicine (2.35 vs 2.16; P = 0.019). No significant associations were found with age group, education level, healthcare occupation, income, medical care setting, prior wrong treatment, or permanent damage (Table 5).

Table 5 Cyberchondria Severity Scale correlations.

Characteristics (n = 474)	Cyberchondria Severity Scale mean/5	P value
Age (years)
18-25	2.19	0.07
26-35	2.29
36-45	2.31
46-55	2.07
56-65	1.99
66-75	-
> 75	1.69
Sex
Male	2.27	0.002
Female	2.08
Place of residence
Akkar	2.24	0.023
Baalbeck-El Hermel	2.55
Beirut	2.14
Bekaa	2.16
Mount Lebanon	2.17
Nabatieh	2.13
North Lebanon	2.43
South Lebanon	2.11
Highest level of education
Not educated	1.96	0.174
Entered but didn’t finish high school	2.42
High school diploma	2.11
Bachelor’s degree	2.24
Post graduate degree	2.18
Currently, you are a worker/student in the healthcare field
Yes	2.25	0.159
No	2.16
Monthly income of the family
Less than 500 United States dollars	2.22	0.258
500-1000 United States dollars	2.08
1000-2000 United States dollars	2.18
More than 2000 United States dollars	2.27
Suffering from health conditions
Yes	2.33	0.017
No	2.15
Suffering from mental health conditions
Yes	2.34	< 0.01
No	2.10
Do you trust the COVID-19 vaccine?
Yes	2.14	0.01
No	2.31
Did you take the COVID-19 vaccine?
Yes	2.24	0.809
No	2.21
What was the main reason you took the COVID-19 vaccine?
For my health and to stay safe	2.14	0.296
My parents pushed me to get vaccinated	2.55
It was mandatory at my workplace/university	2.26
In order to travel/go to nightclubs and restaurants that mandate vaccination	2.14
Other reasons	1.92
Where do you usually receive medical care?
Governmental hospitals	2.29	0.384
Private hospitals	2.24
University hospitals	2.19
Private clinic	2.09
Dispensary	2.22
Other sites	2.07
Have you been misdiagnosed before?
Yes	2.30	0.024
No	2.14
Have you been given the wrong treatment before?
Yes	2.25	0.198
No	2.17
Have you been suffering any permanent damage due to a medical error?
Yes	2.29	0.399
No	2.18
Have you lost anyone close to you due to a medical error?
Yes	2.31	0.011
No	2.14
Which do you prefer?
Modern medicine	2.16	0.019
Herbal medicine	2.35

COVID-19: Coronavirus disease 2019.

DISCUSSION

The aim of this study was to identify mediating factors of medical mistrust and its relationship with cyberchondria. This cross-sectional study examined this relationship in a Lebanese adult population and explored its association with previous medical errors.

MMI and CSS Correlation

The CSS-12 is a brief measure derived from the CSS-33 developed by McElroy and Shevlin[15]. Factor-analytic and validation studies of the CSS-33 and CSS-12 have produced mixed conclusions about the role of the “mistrust of medical professionals” dimension[28-30]. In some work, mistrust has shown weaker factor loadings, lower internal consistency, or limited incremental validity compared with the core cyberchondria dimensions (excessiveness, distress, reassurance, and compulsion), leading authors to omit the mistrust factor from shortened versions of the scale or to treat it as non-essential[28-30]. These decisions were largely driven by psychometric optimization in predominantly non-clinical samples from high-income countries, often student or online convenience samples, and conceptualized mistrust narrowly as a subcomponent of cyberchondria rather than as a broader attitude toward healthcare systems. In our study, medical mistrust was measured independently with the MMI-17, which captures more global doubts about physicians and healthcare institutions, and was examined as a predictor of CSS-12 scores. This different operationalization of mistrust, combined with the specific Lebanese context of economic crisis and health system strain, may partly explain why we observed a statistically significant association between medical mistrust and cyberchondria, whereas some prior CSS-based studies concluded that the mistrust factor was not central to cyberchondria severity.

Although regression analysis showed that medical mistrust was a statistically significant predictor of CSS-12 scores (P < 0.001), the coefficient of determination was low (R² = 0.031), indicating that medical mistrust explained only 3.1% of the variance in cyberchondria. This small effect size suggests that, while the association between mistrust and cyberchondria is robust at the statistical level, medical mistrust is only one of several factors contributing to excessive online health information seeking. Previous research has highlighted the roles of health anxiety, depressive and anxiety symptoms, obsessive, compulsive traits, intolerance of uncertainty, and broader Internet use patterns in the development of cyberchondria[21-26]. These variables were not included in the present bivariate regression model and may account for additional variance in CSS-12 scores.

MMI, sociodemographic factors, COVID-19 vaccination, and previous medical errors

To the best of our knowledge, the literature has not extensively examined the relationship between medical mistrust and sociodemographic variables. In our study, medical mistrust was significantly associated with the 26 years age to 35 years age group, the male sex, and the presence of mental health conditions. A 2021 global report found that one-third of Internet users were aged 25 years to 34 years[32], indicating this group’s high exposure to large volumes of potentially misleading health information. This aligns with our finding that participants aged 26-35 had higher MMI scores. In our sample, males also had higher mean MMI scores than females, suggesting that men may be more skeptical of medical advice and more likely to question providers’ motives or competence. This pattern has been attributed in other contexts to sex differences in health-seeking behavior, norms of self-reliance, and a greater tendency among men to delay care until problems become more severe, which may increase the likelihood of negative healthcare experiences and subsequent mistrust. We also found that participants aged 26-35 years had the highest MMI scores. Individuals in this age group are typically entering or consolidating their careers, forming families, and carrying substantial financial and caregiving responsibilities. In Lebanon, they have also been directly exposed to repeated economic and political crises and perceived shortcomings in the healthcare system, which may amplify feelings of vulnerability and reinforce skepticism toward institutions. Moreover, participants who reported anxiety, depression, or stress tended to have higher MMI scores than those without such conditions (Table 4), consistent with the idea that mental distress can heighten perceived threat and reduce tolerance for ambiguity in medical encounters, thereby increasing the likelihood of interpreting healthcare interactions as untrustworthy.

Vaccine hesitancy has been a key focus when linking medical mistrust to public health behavior. Multiple studies have demonstrated that higher MMI scores correlate with greater COVID-19 vaccine hesitancy[33,34]. Similar results were seen in our study, likely reflecting the spread of rumors regarding vaccine efficacy and dosage requirements. This may explain why participants who took the vaccine for mandatory reasons (e.g., workplace or travel) showed higher mistrust scores than those who took it voluntarily. Although our questionnaire focused on COVID-19 vaccination, similar patterns have been described for other vaccines, including routine childhood immunizations and seasonal influenza vaccines, where mistrust of pharmaceutical companies, concerns about side effects, and skepticism toward official recommendations have been linked to delayed or incomplete vaccination. These findings suggest that medical mistrust may not be limited to emergency situations such as the COVID-19 pandemic but may generalize to broader vaccine hesitancy across the life course.

Regarding medical misdiagnosis and mistreatment, our study found a significant relationship between both variables and medical mistrust. Previous research highlighted that repeated diagnostic error, such as in diabetes management, erode patients’ trust in modern medicine and healthcare institutions[35]. Trust can easily transform into mistrust; individuals who experience medical errors or mistreatment often lose confidence in the healthcare system and its professionals[36]. Beyond diabetes, medical errors and misdiagnoses have been documented in a wide range of conditions, such as delayed cancer diagnoses, missed myocardial infarctions or strokes, and medication errors leading to adverse drug reactions. System-level factors, including high patient volumes, limited consultation time, understaffing, lack of continuity of care, and inadequate communication have all been implicated in such events. When patients or their relatives experience these failures, they may turn to online sources to understand what went wrong, to seek second opinions, or to pre-empt future errors, thereby reinforcing both medical mistrust and cyberchondria.

Cyberchondria, sociodemographic factors, COVID-19 vaccination, and previous medical errors

Our findings also revealed associations between CSS-12 scores, male sex, and mental health conditions. Participants with existing physical or mental health issues had higher cyberchondria scores, likely due to increased health-related anxiety. A Lebanese study similarly found a significant link between cyberchondria and mental health symptoms such as anxiety and depression[26]. Comparable associations between cyberchondria, health anxiety, obsessive-compulsive symptoms, and intolerance of uncertainty were observed in other populations[37]. In our study, individuals with anxiety disorders showed the highest CSS-12 scores (mean = 2.34), supporting the cyclical nature of cyberchondria as a phenomenon driven by anxiety and excessive online searching for reassurance. This pattern is consistent with models that conceptualize cyberchondria as a reassurance-seeking safety behavior in people with elevated health anxiety, where repeated online searching temporarily reduces distress but ultimately maintains anxiety and doubt. Individuals with anxiety and depressive symptoms may also show greater intolerance of uncertainty, making ambiguous or conflicting online information particularly destabilizing and prompting further searches. These mechanisms help explain why participants with self-reported anxiety, depression, or stress in our study had some of the highest CSS-12 scores.

Our results also showed a significant relationship between CSS-12 scores and trust in COVID-19 vaccination. Studies in Indonesia and other countries have shown that higher levels of cyberchondria are associated with greater vaccine hesitancy[38]. Conversely, a study conducted in Iran reported that greater cyberchondria correlated with higher vaccination intentions[18]. This discrepancy may stem from varying types of information disseminated on social media across regions[18]. In times of major health crises like the COVID-19 pandemic, the continuous updates about vaccine types and doses likely heightened uncertainty and fueled online information-seeking behavior, thereby amplifying both cyberchondria and mistrust.

Furthermore, our findings demonstrated a statistically significant but small positive association between medical mistrust and CSS-12 scores, indicating that higher mistrust is linked to greater cyberchondria but that mistrust alone accounts for only a modest proportion of the variability in CSS-12 scores. This pattern suggests that medical mistrust is one contributing factor within a broader network of influences, including health anxiety, previous negative medical experiences, and exposure to inconsistent online information, that jointly shape how individuals search for and interpret health information. From a clinical perspective, interventions that aim to rebuild trust in healthcare providers while simultaneously addressing maladaptive online health information-seeking behaviors may be more effective than focusing on either component in isolation.

Our findings suggest several potential avenues for intervention that could simultaneously rebuild trust in healthcare providers and reduce maladaptive online health information-seeking. At the clinical level, training programs in patient-centered communication and shared decision-making could encourage physicians to explicitly invite discussion of information found online, validate patients’ concerns, and provide clear, tailored explanations about diagnoses and treatment options. Such open conversations may reduce feelings of being dismissed or misunderstood and, in turn, strengthen interpersonal trust. At the same time, clinicians can offer “information prescriptions” by directing patients to vetted, evidence-based websites or official health portals, thereby channeling online searches toward more reliable sources. At the system level, health authorities and professional bodies could develop and promote accessible, high-quality digital health platforms in Arabic that are clearly endorsed by trusted institutions. Finally, psychological interventions such as cognitive-behavioral approaches for health anxiety and cyberchondria, delivered in primary care or mental health settings, can target excessive checking and reassurance-seeking, improve tolerance of uncertainty, and teach patients how to critically appraise online information.

Limitations

Interpretation of the findings should take into account several limitations. First, the cross-sectional design precludes establishing causal relationships between medical mistrust and cyberchondria; the observed associations can only be interpreted as correlational. Second, all data were self-reported and may be subject to recall and social desirability biases. Third, convenience and snowball sampling via online platforms may have introduced selection bias toward younger, more educated, and more Internet-literate individuals, so the findings may not be generalizable to all Lebanese adults. Fourth, we did not adjust for all potential confounders in our regression analyses. In particular, self-reported mental health conditions (such as anxiety, depression, and stress) were common in our sample and are known to be associated with both medical mistrust and cyberchondria; failure to fully control for these factors may have inflated the observed association between mistrust and cyberchondria. Finally, the linear regression model explained only a small proportion of the variance in CSS-12 scores (R² = 0.031), indicating that additional unmeasured variables, such as the severity of health anxiety, obsessive-compulsive symptoms, and detailed patterns of Internet use are likely to play an important role.

CONCLUSION

Our study examined whether a relationship exists between medical mistrust and cyberchondria. Based on the positive correlation observed, we can conclude that higher mistrust is associated with higher cyberchondria scores. Previous medical errors and misdiagnoses correlated with greater levels of both medical mistrust and cyberchondria; therefore, addressing such errors in clinical practice is crucial to rebuild patient trust and enhance healthcare experiences. It has been said that misdiagnosis is the “next frontier for patient safety”[39]. Clinicians can help rebuild trust by adopting patient-centered communication, openly acknowledging and explaining potential errors, and guiding patients toward reliable online resources instead of avoiding discussion of Internet use. Health authorities and professional bodies may further support trust by developing transparent, evidence-based digital platforms in the local language that are clearly endorsed by trusted institutions. In parallel, psychological interventions such as cognitive-behavioral approaches for health anxiety and cyberchondria can reduce excessive checking and reassurance seeking. Future research should evaluate the effectiveness of such multilevel interventions in simultaneously reducing medical mistrust and cyberchondria in different populations.

ACKNOWLEDGEMENTS

The authors would like to thank all participants who took the time to complete the questionnaire. We also extend our gratitude to Beirut Arab University for its support throughout the research process. No writing or editorial assistance from third-party organizations was received for the preparation of this manuscript.