The prevalence of feigning and concealment of Covid-19 infections in an international sample (2024)

Participants

Initially, 646 people joined the study. However, their responses were screened using the following exclusion criteria: (1) informed consent not provided (n = 3), (2) permission to use their data not provided (n = 47), (3) not answering all the questions (n = 127), (4) under legal age (<18, n = 3) and (5) proper elaboration on the study at the end (n = 3, see Procedure). The final sample consisted of 463 participants, with an average age of 29 years (SD = 12.33; range 18–84). With 70.8% (n = 328) females were overrepresented; 28.3% (n = 131) identified as men, and four participants identified as non-binary. Because health regulations differed across countries, we asked participants where they spent most of the time during the pandemic period (previous 3 years). The following countries were mentioned: the Netherlands (48.1%), Greece (32.2%), Croatia (6.6%) and USA (4.2%), countries where they were also currently residing.

We collected other demographic background information about our sample, such as education, employment, income and living situation (see Table 1). Most participants had either a high school qualification (48.6%) or a bachelor’s degree (30.2%). Regarding employment status, the most frequently endorsed categories were full time employment (35.4%) and being a student (38%). Almost half earned a yearly income between 10,000 and 20,000 euros (45.5%), and almost half of the sample lived with their parents (45.6%). As living situation could have an impact on one’s willingness to report Covid-19 infection, we checked whether participants lived with a person who would be, under the WHO advice, considered vulnerable to the virus (i.e. people older than 60 and/or with pre-existing respiratory or immune system related issues²). A third of the sample, indeed, lived with a vulnerable person (36.4%).

Finally, participants rated their current health on 5-point measure (lower values indicating poorer health), and whether they had any chronic health complaints (yes/no). The average health rating was ‘good’ (M = 3.95, SD = 0.76, range 1–5), and 17.7% (n = 82) indicated having chronic health issues, such as asthma, allergies, migraines and blood pressure problems.

Questionnaire

We created a questionnaire for the purpose of this study containing 36 questions (see Supplemental file). The first part contained demographic questions (cf. supra Table 1). Next, a question about having experienced a coronavirus infection was presented, and when participants indicated that they had had such infection in the past, they were queried about the frequency of infections and the type of symptoms they experienced. People who claimed to not have had a coronavirus infection would not be presented those questions; accordingly, the number of questions presented varied across participants depending on their answers. Next, we provided a question about whether they had feigned a coronavirus infection during the period of 3 years, which was the time interval between the start of the pandemic and this study. Depending on their answer, participants were given different follow up questions. For instance, if feigning was indicated, then this was followed-up by questions about the type of the symptoms a person had been feigning and the motivation for doing so. If a participant reported not having feigned a coronavirus infection, they were asked about others and whether they knew anyone who had been feigning a coronavirus infection. The same procedure was followed for questions regarding coronavirus symptoms concealment. This structure of protocol was employed to secure that the study duration and task load were relatively similar for all participants. All participants were asked to rate how frequently the general public engages in feigning (i.e. pretending to have) and concealing (i.e. pretending not to have) Covid-19 infections using a 5-point Likert scale (1 being never and 5 indicating all the time).

Procedure

We used Qualtrics to administer questions to participants. We, an international group of researchers, employed convenience sampling by distributing an online questionnaire to people in our professional and private networks, as well as posting the study on social media (Twitter, Facebook). In the invitation letter, we provided basic information about the study and informed participants that their participation was purely voluntary, that data would be processed in an anonymized way, and that they would be joining a lottery for a €10 voucher. After agreeing to participate, participants needed to provide informed consent and only then they were presented the questionnaire (see above). Our inquiry about participants’ symptom (mis)reporting specified the time period of 3 years prior to their participation, which took place during March, April and May 2023. After answering all of the questions, participants were asked to briefly describe the study (i.e. elaboration of the task), in order for us to ensure that participants were attentively responding. Thus, this question served as an elimination criterion (n = 3). Lastly, participants had to evaluate their participation (motivation, clarity, honesty), and were given a debriefing form, after which they were asked if they explicitly provide a permission to use and store their data according to the ethical requirements at our institution. The study was approved by the standing Ethical Committee of Erasmus University Rotterdam, the Netherlands.

Data analyses

The data were first screened using the exclusion criteria (see Participants section). After exclusion of non-eligible participants, descriptive analyses were run. To inspect group differences, we used Welch t-test and Mann Whitney U-test (see Delacre et al., 2017). In doing so, we applied Bonferroni corrections on the basis of the number of comparisons. The data file and the outputs are available at Open Science Framework (https://osf.io/tv4k3/?view_only=8f5b2cfbdd4e4f8fb7d83faa63bef8b7).

Participation evaluation

Participants had to rate their motivation, the clarity of questions, potential discomfort they had experienced and their honesty using 5-point scales (with lower values indicating lower levels and higher values higher levels). Participants indicated moderate motivation (M = 3.35, SD = 0.91, range 1–5), high clarity of questions (M = 4.43, SD = 0.71, range 2–5), low discomfort (M = 1.35, SD = 0.90, range 1–5) and high honesty (M = 4.88, SD = 0.35, range 3–5).

Covid-19 infection prevalence

Three hundred eighty-four participants (82.9%) indicated having had a Covid-19 infection in the past. Most participants had the infection once or twice, but some indicated to have suffered from it five times (maximum value). The most prevalent symptoms were exhaustion, blocked nose, fever and cough (see Table 2).

To test for age differences between those who reported having experienced a Covid-19 episode (n = 384) and those who said they did not (n = 79), we performed a Welch t-test. The first group was, on average, younger (M = 27.95, SD = 11.04) than the second group (M = 33.78, SD = 16.53), Welch t(92.81) = 3.00, p = 0.003, Cohen’s d = 0.48. Further, those who reported to have had the infection, more often reported chronic health issues compared to those who did not report having attracted the coronavirus: Mann Whitney U = 13,545, z = 2.26, p = 0.023, r = 0.11. There were no differences between these groups in terms of gender, education, employment or income.

Prevalence of feigned Covid-19 infections

Sixty-five participants (14.1%; 95% CI [11, 17]) admitted having feigned a Covid-infection at least once. Of these, 55 (9%) said they completely fabricated it, 1.1% (n = 5) reported feigning previously existing symptoms even after the infection had passed and 3.5% (n = 16) had a normal cold but pretended it was a Covid-19 infection. Participants, on average, engaged in feigning twice, with maximum reported frequency of 10 instances. The most commonly reported symptoms in feigned cases were cough, fever and exhaustion (see Table 2). Compared with self-declared authentic infection reports, feigned instances included less frequently all other typical symptoms, such as blocked nose, exhaustion, loss of smell and taste and muscle aches. The majority of those who had engaged in feigning a Covid-infection were familiar with the condition as they also reported being infected in the past (81.5%, n = 53).

Main reasons for feigning were preferring to stay at home (52%, n = 34), to obtain sick leave from school or work (38.5%, n = 25), to avoid commitments (35.4%, n = 23) and to avoid risky situations to protect others (24.6%, n = 16). Two participants also indicated academic benefits (e.g. deadline extensions) and four reported excusing a failed exam by referring to an infection.

Using Mann Whitney U-tests, we checked whether there were differences between participants who said they had feigned (n = 65) and those who said they had not (n = 398) in terms of age, gender, education, health ratings and living situation (i.e. whether they lived with a vulnerable person). There were no such differences, all Mann Whitney Us < 12,147.5, Z_s < 1.56, p_s > 0.128.

Participants’ estimation of feigning prevalence

Those who said they had never feigned a coronavirus infection (N = 398) were asked whether they knew others who had feigned it; 32.7% (95% CI [28, 37]; n = 130) said they knew such a person. A vast majority got the confirmation directly from the feigner (82.3%, n = 107), whereas others were informed by third parties (7.7%, n = 10), and still others said their intuition told them (4.6%, n = 6). When asked which symptoms the feigners falsely claimed, participants most frequently indicated being told about cough (64%, n = 84) and fever (65.4%, n = 85), whereas blocked nose (37.7%, n = 49) and exhaustion (31.5%, n = 41) were less often mentioned, a pattern that corresponds well with the prevalences in Table 2. We also asked whether they knew about the motivation for feigners, and the most often mentioned motives were to stay at home (61%, n = 79), obtain sick leave (67.7%, n = 88) or avoid duties/commitments (31.5%, n = 41), which again reflects the outcomes of feigners’ self-report presented above.

All participants were asked to rate, using a 5-point scale (range from never to all the time), how often general public engages in pretending to have coronavirus infection. Only 7.1% (n = 33) said never, whereas the rest of the sample (92.9%, n = 430) indicated different frequencies, with the majority indicating from time to time (55%, n = 236), whereas a considerable minority said rarely (33.5%, n = 144). Forty-seven participants (11%) reported that others feigned the condition frequently (n = 47), and three participants said all the time.

Prevalence of concealed Covid-19 infections

Fifty participants (11.8%, 95% CI [6, 12]) said they had previously experienced a Covid-19 infection but had kept this hidden. On average, two instances of concealment were reported (range 1–3). Twenty-one (42%) knew they had the infection but claimed to only have a normal cold, 15 (30%) falsely claimed that their infection had passed although they still had it, and 14 (28%) claimed to be completely healthy even though they knew they were infected.

Main self-declared motives were not wanting others to know and make it a ‘big deal’ (32%, n = 16), not wanting to miss out on a party/festival (38%, n = 19), and not wanting more days off (20%, n = 10). The rest of the responses indicated having other obligations (e.g. exams, important meeting), and avoiding responsibility for spreading the virus to friends.

Participants who concealed a coronavirus infection (n = 50) differed only in one aspect from those who said they had never engaged in concealment (n = 413): the first group was younger than the second, Mann Whitney U_s = 7815.5, Z = 2.79, p = 0.005, r = 0.11. There were no significant group differences for gender, education, health ratings or living situation.

Participants’ estimation of denial prevalence

The rest of the sample (n = 413) answered the question whether they were aware of anyone who had concealed having a coronavirus infection despite actually having contracted it. Two-hundred-ten participants (50.8%, 95% CI [46, 56]) indicated they did. The majority said to have had a direct confession from the concealer (55.2%, n = 116), 20.0% (n = 42) stated that the symptoms were obvious so there was no need for confirmation, and 14.3% (n = 30) got the evidence from other sources (e.g. mutual friends). Interestingly, 7.1% (n = 15) mentioned other methods of confirmation – such as having witnessed the positive test, or knowing that the concealer did not ‘believe in corona’ so that they would not test, nor admit it.

The motives participants assumed to play a role in denying having a coronavirus infection despite being ill were not wanting to miss out on a party/festival (29%, n = 134), not wanting others to know and make a big issue out of it (18%, n = 83), not wanting to stay at home (13%, n = 60) and not wanting more days off (8%, n = 37). Around 30 participants added responses that alluded to deniers being ‘anti-vaxxers’, who did not want to acknowledge that the virus is real.

All participants were again asked to provide their estimations, using a 5-point scale, about how often people engage in hiding coronavirus infection. Only 3% (n = 14) indicated that people never do that, whereas 97% reported different degrees of frequency. The majority (57%, n = 263) reported that people concealed Covid-19 moderately often, 20.5% (n = 95) said that people do it most of the time and 18% (n = 83) indicated that others hide coronavirus infection rarely, whereas eight participants thought it happens always.

Feigning and denial

Out of the entire sample (N = 463), only seven participants (1.5%) acknowledged that they had participated in both fabricating a Covid-19 infection in the past and, on other occasions, denying such an infection even though they were aware of having contracted the virus. Hence, it seems that people rather opt for one form of response bias.

Limitations and future directions

Our findings need to be considered in the context of this survey’s limitations. Although our sample was international, the vast majority of our participants were Dutch, Greek or American. Future surveys should try to expand to other countries, especially those that were known for having different (if any) restrictions during the pandemic, such as Sweden, which did not have any restrictions. It would be important to investigate whether a lack of such regulations prevented or significantly lowered response bias in self-declared Covid-19 episodes, especially concealment. Further, the majority of our sample were students under the age of 30, meaning that the generalizability of our findings is limited. Considering the findings about younger participants exhibiting more concealment regarding Covid-19 infections (O’Connor and Evans, 2022), better representation of different age groups seems like a necessary next step. More importantly, in order to ensure that the survey length was similar to all of our participants, some participants were not shown the same questions as others. For instance, those who directly admitted engaging in feigning were further questioned about symptoms, motivations etc., whereas those who denied feigning were asked about knowing others who fake. This way, we did not have a chance to hear from ‘feigners’ themselves whether they knew others who behaved in a similar way. Although all participants were later asked to rate the prevalence of faking in the general public, this oversight should be corrected in further investigations. Moreover, we did not directly ask about the impact the pandemic had on our participants, for instance, on their job security or living situation, which were both shown to be related to people’s way of reporting Covid-19 infections (Bayer and Kuhn, 2020; Lin et al., 2021). Finally, as our data suggest that the attitude towards coronavirus was one of the main motives for others to deny having the infection, we realized too late that asking participants about their views on coronavirus and vaccinations would have been an informative question that could potentially be related to the prevalence in which they feigned or concealed Covid-19. Thus, the issue of personal perception of the pandemic and its impact on one’s behaviour should be further explored in the follow-up research.

A more fundamental issue is, of course, whether people in a survey would admit feigning or denying a Covid-19 infection; and whether those who admit such behaviour can be trusted in all the other information that they provided. Given these concerns, we believe that the safest conclusion that can be drawn from our data is that feigning and concealment of Covid-19 infections did occur on a non-trivial scale.

sj-docx-1-hpq-10.1177_13591053231226033 – Supplemental material for The prevalence of feigning and concealment of Covid-19 infections in an international sample:

Supplemental material, sj-docx-1-hpq-10.1177_13591053231226033 for The prevalence of feigning and concealment of Covid-19 infections in an international sample by Irena Boskovic, Esteban Puente-López, Brechje Dandachi-FitzGerald and Harald Merckelbach in Journal of Health Psychology

Author contributions: First author created and supervised the project. Second and third authors reviewed and co-wrote the manuscript, the fourth author co-supervised the project and co-wrote the manuscript.

Data sharing statement: The data file and the outputs are available at Open Science Framework (https://osf.io/tv4k3/?view_only=8f5b2cfbdd4e4f8fb7d83faa63bef8b7).

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

Ethics approval: The study was conducted in accordance with the standards of the standing Ethical committee of the first authors’ institution, and in accordance with the Declaration of Helsinki.

ORCID iD: Irena Boskovic https://orcid.org/0000-0003-1675-1004

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