# Facial cues of sickness reduce trustworthiness judgements, with stronger effects in women

Megan N Cesarini-Williams, Julie Lasselin, Mats Lekander, John Axelsson,

Mats J Olsson, Arnaud Tognetti

► To cite this version:

Megan N Cesarini-Williams, Julie Lasselin, Mats Lekander, John Axelsson, Mats J Olsson, et al. Facial cues of sickness reduce trustworthiness judgements, with stronger effects in women. Brain, Behavior, and Immunity, 2025, 130, pp.106102. 10.1016/j.bbi.2025.106102. hal-05271984

HAL Id: hal-05271984

https://hal.inrae.fr/hal-05271984v1

Submitted on 22 Sep 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>
Full-length Article

# Facial cues of sickness reduce trustworthiness judgements, with stronger effects in women

Megan N. Cesarini-Williams<sup>a</sup>, Julie Lasselin<sup>a,b,c,d</sup>, Mats Lekander<sup>a,b,c</sup>, John Axelsson<sup>a,b</sup>, Mats J. Olsson<sup>a</sup>, Arnaud Tognetti<sup>a,e,*</sup>

<figure><img src="image_2.png" /></figure>

ARTICLE INFO

Keywords:

Sickness cues

Trustworthiness

Disease avoidance

Sickness detection

Behavioral immune system

Approach-avoidance behaviors

Lipopolysaccharide

Pro-inflammatory markers

Acute inflammation

Sex differences

ABSTRACT

A behavioral defense against disease involves detecting sickness cues in others and responding adaptively, such as by avoiding social interactions. While studies have shown that humans can discriminate sickness cues above chance in faces after sickness induction, whether this discrimination affects approach-avoidance behaviors remains uncertain. Here, we investigated how facial sickness cues influence judgments of trustworthiness, serving as a proxy measure for social avoidance. In a prior study, facial photographs were taken of 21 individuals when sick (two hours after an endotoxin injection causing a transient systemic inflammation) and healthy (following placebo injection). In the current study, participants in two separate experiments viewed these paired facial photographs and were asked, in a two-alternative forced-choice paradigm, to identify which face appeared sick (n = 94) or more trustworthy (n = 82). Participants discriminated sick faces significantly above chance (73.1 %), with females (76.0 %) performing significantly better than males (69.3 %). Additionally, sick faces were perceived as significantly less trustworthy, being selected in only 34.9 % of trials. Notably, the higher the sickness discrimination accuracy for a particular face, the less likely that face was to be judged as trustworthy. Moreover, females (30.5 %) were significantly less likely than males (39.5 %) to judge sick faces as the more trustworthy looking. Individual differences in participants' disease vulnerability, disgust sensitivity, and frequency of sickness, as well as facial stimulus participants' inflammatory response intensity measured via interleukin-6 blood concentrations, body temperature, and sickness symptoms, did not predict sickness discrimination accuracy or trustworthiness judgments. Together, these findings suggest that visual sickness cues negatively affect trustworthiness judgments, potentially reflecting social avoidant behaviors towards individuals who appear sick. While judgments of facial trustworthiness may be considered a social inference about whether an individual is safe to approach, future research should also include manifest measures of approach-avoidance in response to sickness cues.

# 1. Introduction

Pathogens have long posed a significant threat to humans and other animals, resulting in the evolution of sophisticated immune systems. While highly effective, mounting an immune response is metabolically costly and trigger sickness behaviors, such as fatigue, loss of appetite, and physical inactivity (Dantzer, 2009; Van Blerkom, 2003), that can increase other fitness risks, including starvation, predation, and missed mating opportunities (Shakhar and Shakhar, 2015). Thus, natural

selection likely favored additional adaptations for disease avoidance that inhibit exposure to infectious agents and minimize the need for initiating a cost-intensive immune response. These adaptations comprise a behavioral defense against disease that includes perceptual, emotional, cognitive, and behavioral mechanisms for detecting and avoiding disease-relevant cues (Schaller, 2015; Schaller et al., 2003).

A behavioral defense against disease is particularly important in social species, where physical interactions among conspecifics increase pathogen transmission (Hart, 2011; Schaller and Park, 2011). Several

<footnote><sup>a</sup> Department of Clinical Neuroscience, Division of Psychology, Karolinska Institutet, Stockholm, Sweden</footnote>

<footnote><sup>b</sup> Department of Psychology, Division of Psychobiology and Epidemiology, Stress Research Institute, Stockholm University, Stockholm, Sweden</footnote>

<footnote><sup>c</sup> Osher Center for Integrative Health, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden</footnote>

<footnote><sup>d</sup> Department of Biomedical and Clinical Sciences, Linköping University, Sweden</footnote>

<footnote><sup>e</sup> CEE-M, University of Montpellier, CNRS, INRAE, Institut Agro, Montpellier, France</footnote>

<footnote>* Corresponding author at: Division of Psychology, Department of Clinical Neuroscience Karolinska Institutet Nobels väg 9, 171 77 Stockholm, Sweden.
E-mail address: arnaud.tognetti@ki.se (A. Tognetti).</footnote>
social species, such as rodents, chimpanzees, mandrills, and Caribbean
spiny lobsters are known to recognize infected conspecifics and to avoid
social contact with them (e.g., Arakawa et al., 2011; Behringer et al.,
2006; Behringer and Butler, 2010; Hart, 2011; Poirotte et al., 2017,
Ehman & Scott, 2001; Kavaliers et al., 2005; Kavaliers & Colwell, 1995).
Humans show similar abilities in discerning cues of sickness in their
peers (Arshamian et al., 2021; Axelsson et al., 2018; Hansson et al.,
2023; Henderson et al., 2016, 2017; Leschak et al., 2022; Leung et al.,
2023, 2024; Olsson et al., 2014; Regenbogen et al., 2017; Sarolidou
et al., 2020a, 2020b; Tognetti et al., 2023b, 2023c; Tskhay et al., 2016).
Specifically, transient systemic inflammation induced by intravenous
injection of the bacterial endotoxin lipopolysaccharide causes observ-
able perceptual changes to body odor (Gordon et al., 2023, 2018; Olsson
et al., 2014), facial traits (Axelsson et al., 2018; Henderson et al., 2017;
Sarolidou et al., 2019), and gait pattern (Hansson et al., 2023; Lasselin
et al., 2020).

Although detecting sickness cues is thought to elicit adaptive moti-
vational responses that facilitate avoidance (for review, see Schaller,
2011), few studies have directly tested whether these cues trigger
avoidance behaviors. A couple of studies have demonstrated that people
indicate a greater distance, on average, from strangers displaying con-
spicuous facial sickness cues, such as a photoshopped flu-like appear-
ance (red nose and dark undereye circles) or rash (Bressan, 2020;
Magalhäes and Soares, 2023; van Leeuwen and Petersen, 2018). Simi-
larly, one study found that faces of individuals who were naturally ill
were rated as less approachable (Leung et al., 2023). Additionally,
limited work has linked acute inflammation-induced sickness to a
greater dislike of sick faces (Regenbogen et al., 2017; Sarolidou et al.,
2020a), with faces of those exhibiting stronger inflammatory responses
being the most disliked (Leschak et al., 2022). The current study adds to
this literature by examining how both naturalistic and inflammation-
induced sickness cues alter perceptions of facial trustworthiness, a key
social attribute that strongly influences approach-avoidance decisions
(for reviews see, Todorov et al., 2015; Zebrowitz, 2017) and thus serves
as a relevant proxy for social avoidance behavior.

The perception of trustworthiness (or untrustworthiness) in others'
faces may be relevant for survival, functioning as an evolved mechanism
for assessing others' intentions as helpful or harmful (Cosmides and
Tooby, 1992; Oosterhof and Todorov, 2008; Todorov et al., 2008). In
line with this view, functional neuroimaging studies indicate that evalu-
ations of a face's trustworthiness form after only a brief glance and
occur spontaneously and automatically, involving activity in the
amygdala—a subcortical structure implicated in detecting potentially
dangerous or threatening stimuli (Engell et al., 2007; Freeman et al.,
2014; Phelps and LeDoux, 2005; Todorov et al., 2013, 2011; Winston
et al., 2002). Experimental studies also show that untrustworthy-looking
faces elicit reduced trust and cooperation in economic games (Chang
et al., 2010; Ewing et al., 2015; Rezlescu et al., 2012; Stirrat and Perrett,
2010; van't Wout and Sanfey, 2008) and trigger avoidance-oriented
behaviors, such as greater interpersonal distance (Radke et al., 2018;
Slepian et al., 2017, Slepian et al., 2012). Beyond experimental work,
judgments of facial trustworthiness have tangible real-world conse-
quences, influencing employment, financial, and legal decisions to the
disadvantage of those perceived as untrustworthy (e.g., Ballew and
Todorov, 2007; Ert et al., 2016; Gomulya et al., 2017; Porter et al., 2010;
Wilson and Rule, 2015).

Supporting the idea that trustworthiness judgments function as an
evolved threat appraisal system, research shows that individuals with
stronger disease concerns, such as heightened sensitivity to human-
contaminant disgust or frequent worries about pathogens, tend to
maintain greater interpersonal distance and display increased social
distrust, perceiving others as potential sources of infection (Aarøe et al.,
2016; Fan and Olatunji, 2013; Park, 2015). While these findings high-
light important individual differences in disease avoidance, research has
also revealed consistent sex differences in these behaviors. Females, for
instance, consistently report higher disgust sensitivity when exposed to

disease-connoting stimuli, such as images of vomit, bodily fluids, sores,
or visibly infected individuals (Al-Shawaf et al., 2018; Curtis et al., 2004;
Prokop and Jančovičová, 2013; Tybur et al., 2011), and score higher
than males on the Disgust Scale, which measures multiple domains of
disgust elicitors (Haidt et al., 1994). Recent exploratory findings suggest
that females are also more accurate and faster than males at dis-
tinguishing sick from healthy faces (Tognetti et al., 2023b), likely
reflecting evolved differences in disease detection and avoidance
(Morrow, 2015; Roved et al., 2017).

Building on these studies and prior research on sickness perception and facial trustworthiness, our study aimed to (i) determine whether observers can discriminate between sick and healthy facial photographs of volunteers with induced acute experimental inflammation above chance, (ii) examine whether faces displaying inflammation cues are judged as less trustworthy, reflecting a potential behavioral tendency to avoid infectious individuals, and (iii) evaluate whether women outperform men in sickness discrimination and exhibit stronger changes in trustworthiness judgments. Additionally, we sought to (iv) assess how individual differences in self-reported disease vulnerability, disgust sensitivity, and frequency of sickness relate to both discrimination accuracy and trustworthiness judgments. We also (v) investigated whether the intensity of inflammation-induced sickness responses—measured by IL-6 levels, body temperature, and self-reported sickness—affects these judgments, as well as (vi) the relationship between sickness discrimination accuracy and perceptions of facial trustworthiness.

## 2. Methods

### 2.1. Facial stimulus participants

#### 2.1.1. Stimuli collection and processing

The stimuli used in this study consisted of headshots collected during a prior experiment investigating sickness detection and the behavioral and physiological changes that occur during an acute systemic inflammation (Lasselin et al., 2017). For a detailed description of their experimental endotoxemia model, please refer to Lasselin et al. (2017). This initial experiment, along with other studies utilizing the same stimuli, received approval from the regional ethical review board in Stockholm, Sweden (Dnr 2014/1946-31/1, 2015/204-32, 2015/1415-32).

Lasselin et al. (2017) used a double-blind, randomized, placebo-
controlled, crossover design. Twenty-two participants (mean age: 23
± 4; age range: 19–34; 9 women) participated in 2 sessions spaced 3 to 4
weeks apart. During one session, they received an injection of lipo-
polysaccharide (LPS, Escherichia coli endotoxin, Lot HOK354, CAT
number 1235503, United States Pharmacopeia, Rockville, MD, USA) at a
dose of 2 ng/kg of body weight. The LPS injection induced a transient
systemic inflammatory response and sickness behaviors (Lasselin et al.,
2017). During the other session, they received a placebo injection (i.e.,
0.9 % NaCl, physiological saline). The order of injections was random-
ized and counterbalanced.

Headshots were taken 2 h post-injection in both conditions. Head-
shots were taken under a standardized flash condition using a Nikon D90
(Nikon Corp., Tokyo, Japan) with a 50-mm lens, an aperture speed of 1/
125, an ISO value of 200, and at a resolution of 4288 x 2848. The white
balance was set to 5880 Kelvin. Participants did not wear makeup,
glasses, or jewelry. They were seated on a stool in front of a white
background and instructed to look directly into the camera with a
neutral, relaxed expression. One male participant was excluded due to
large differences between the two conditions (hair in front the forehead,
beard), resulting in a final stimulus set consisting of headshots of n = 21
participants. These headshots were subsequently cropped, centered on
the eyes and excised using an oval black mask to only show the face (see
Fig. 1).
<figure><img src="image_3.png" /><figcaption>Fig. 1. Depiction of one of the pairs of facial stimuli used. Headshots were taken two hours after LPS (left) and saline (right) injection.</figcaption></figure>

### 2.1.2. Sickness responses

We assessed sickness response intensity using the measurements taken closest to the time the headshots were captured: plasma concentration of interleukin (IL)-6 (a pro-inflammatory marker) and body temperature 2 h post-injection —corresponding to the peak sickness response to LPS (Lasselin et al., 2017)— and scores on the SicknessQ, a 10-item questionnaire assessing perceived sickness (Andreasson et al., 2018) 1.5 h post-injection. IL-6 data for one participant in the LPS condition were unavailable due to difficulties with blood collection.

## 2.2. Main experiment

### 2.2.1. Participants

Participants who had just completed a separate study at the Laboratory of Experimental Economics at the University of Montpellier were subsequently invited to participate voluntarily in the current study without compensation. Participants were randomly assigned to participate in one of two conditions. In one condition, n = 94 (54 females) participants (mean age: 25.9 ± 6.2; age range: 18–59) were asked to select the sick face, while in the other condition, n = 82 (42 females) participants (mean age: 25.4 ± 7.1; age range: 18–65) were asked to select the more trustworthy-looking face.

### 2.2.2. Rating procedure

Participants were presented with a series of 21 pairs of headshots (for an example of one pair, refer to Fig. 1). Each pair consisted of facial photographs of the same individual taken when they were sick (photographed 2 h after LPS injection) and when they were healthy (photographed 2 h after placebo injection). The rating procedure was conducted using a computerized two-alternative forced-choice paradigm. The paired headshots were displayed side-by-side, with the position (left/right) of the sick and healthy faces randomized, as well as the order in which pairs were presented. Participants were randomly assigned to one of two groups. In the first group, n = 94 participants were asked to select the face that appeared the sickest for each of the 21 paired headshots. In the second group, n = 82 participants were instructed to choose the face that looked the most trustworthy for each pair.

Additionally, participants completed a brief socio-demographic questionnaire, providing information on their age, biological sex (male/female), and income. They also answered three questions assessing their perceived vulnerability to diseases and their sensitivity to disgust: (1) “How many times have you been sick in the last 6 months?” (2) “In general, I am very sensitive to infectious diseases (e.g., cold, flu),” and (3) “In general, I feel disgusted very easily.” For the latter two questions, responses were recorded on a 7-point scale, ranging from 1

(strongly disagree) to 7 (strongly agree).

## 2.3. Statistical analyses

### 2.3.1. Experimental manipulation of the inflammatory response

As reported earlier (Lasselin et al., 2018, Lasselin et al., 2017), endotoxin administration effectively manipulated the immune system of facial stimulus participants evidenced by increases in body temperature and pro-inflammatory markers (i.e., IL-6) in the LPS condition compared to placebo. In the current study, we again confirmed this successful manipulation in our subsample of participants (N = 21, after excluding one participant; see above) at the closest time points when photographs were taken. Paired-samples *t*-tests confirmed significant differences in body temperature and IL-6 concentrations 2 h post-injection, as well as sickness symptom scores 1.5 h post-injection. IL-6 concentrations were log-transformed to meet normality assumptions.

### 2.3.2. Sickness discrimination

Our initial analysis focused on assessing the accuracy of participants in discriminating sick faces from paired sick and healthy faces. To evaluate this, a one-sample *t*-test was used to compare the mean success rate against the random expectation of 50 %.

### 2.3.3. Facial trustworthiness

We then examined how cues of sickness influenced judgments of facial trustworthiness. To assess this, a one-sample *t*-test was conducted to compare the mean proportion of times participants selected the sick face within a pair as appearing more trustworthy against the random expectation of 50 %.

### 2.3.4. Sex differences

Our next set of analyses explored whether there were sex differences in both sickness discrimination accuracy and perceived trustworthiness of sick faces. We employed a generalized linear mixed-effects model (GLMM) (using the glmer function) with a binomial error structure and maximum likelihood estimation (Laplace approximation). In this model, the dependent variable was either the successful discrimination of sick faces (coded as 0 = incorrect, 1 = correct) or whether a participant selected the sick face as the more trustworthy-looking option (coded as 0 = untrustworthy, 1 = trustworthy) for each of the 21 face pairs. The explanatory variable was “Sex,” while random intercepts were included for each face pair and each participant.

### 2.3.5. Disease traits and sickness perception

To investigate whether individual's sensitivity to disgust and vulnerability to disease influence sickness discrimination and
trustworthiness judgements, we used GLMMs. The dependent variable was either participant sickness discrimination accuracy (coded as 0 = incorrect, 1 = correct) or whether a participant selected the sick face as the more trustworthy-looking option (coded as 0 = untrustworthy, 1 = trustworthy). Explanatory variables included disease vulnerability, disgust sensitivity, and frequency of sickness in the past six months. Random intercepts were included for each face pair and participant. Given prior research identifying sex differences across several of these explanatory variables (e.g., Al-Shawaf et al., 2018; Curtis et al., 2004; Prokop and Jančovičová, 2013; Tognetti et al., 2023b; Tybur et al., 2011) and similar findings within our participants, we included 'Sex' as a confounding variable in the analysis. Detailed descriptive statistics for these disease-related traits are provided in the appendix (see Table A.1), pertaining to participants in both the sickness discrimination task (n = 94) and the trustworthiness judgments task (n = 82).

### 2.3.6. Effects of sickness responses on sickness discrimination and trustworthiness judgements

Additional GLMMs were conducted to assess whether facial stimulus participant sickness responses predicted participant discrimination accuracy and trustworthiness judgment. The dependent variable was either discrimination success (coded as 0 = incorrect, 1 = correct) or whether a participant selected the sick face as the more trustworthy-looking option (coded as 0 = untrustworthy, 1 = trustworthy). Explanatory variables included differences in IL-6 concentrations, body temperature, and sickness symptoms between the LPS and placebo conditions, and participant sex was added as a confounding variable. Random intercepts were included for each face pair and participant.

### 2.3.7. Correlation between sickness discrimination and trustworthiness judgments

Our final set of analyses explored the relationship between the accuracy of sickness discrimination and perceptions of trustworthiness for each face pair (N = 21). Specifically, we examined whether faces that were more accurately identified as sick were less likely to be judged as trustworthy. To assess this relationship, we calculated the proportion of times the sick face was chosen over the healthy face by participants in both task conditions (i.e., sickness discrimination and trustworthiness judgments). Because the aggregated data on sickness discrimination accuracy were not normally distributed, we utilized Spearman's rank correlation to evaluate the relationship between the proportions for each task.

### 2.3.8. Handling of outliers

For the dependent variables (sickness discrimination and trustworthiness judgment), outliers were defined as values more than three standard deviations from the mean, consistent with our previous work (Hansson et al., 2023) and following visual inspection to confirm approximate normality. For the sickness discrimination task, one participant successfully discriminated the sick face in only 3 out of 21 trials (> 4 SD) and was excluded from analysis, resulting in a final sample of n = 93 participants and 1,953 observations (i.e., sickness discrimination judgments). This participant's performance was four standard deviations below the mean, indicating a potential misunderstanding of the task (e.g., consistently selecting the healthy face instead; see Fig. A.1). Therefore, all analyses were conducted with this outlier excluded.

The distributions of the disease-related variables (disease vulnerability, disgust sensitivity, and frequency of sickness in the past six months) were not normal, so outliers were identified using the interquartile range (IQR) method with a 3 × IQR threshold. One participant in the sickness discrimination task and three participants in the facial trustworthiness task were identified as outliers based on their reported frequency of illness in the past six months (i.e., > 10 times). These participants were excluded from the GLMMs assessing disease traits as predictors of sickness discrimination accuracy and trustworthiness

judgments.

All statistical analyses were conducted in R, version 4.1.3 (R Core Team, 2022). For all GLMMs, the statistical significance of each variable was tested with likelihood ratio tests comparing the full model to those without the term of interest. In addition, because the explanatory variables may be intercorrelated, we checked for multicollinearity among the variables by calculating the variance inflation factor (VIF). However, we found no evidence of multicollinearity, as all variables showed a low VIF value for all models (VIF < 1.22). Effect sizes were calculated to aid interpretation. For t-tests, Cohen's d was computed using the cohen's d function from the rstatix package. For GLMMs, effect sizes were reported as odds ratios (OR) by exponentiating fixed-effect coefficients; additionally, for binary predictors (i.e., sex), risk ratios (RR) were computed using the oddsratio_to_riskratio function from the effectsize package to provide an intuitive measure of group differences in probabilities. The data set includes sensitive data for the facial stimulus participants and thus cannot be openly shared according to GDPR. However, the data are available upon request (and ethical authorization) to julie.lasselin@ki.se.

## 3. Results

### 3.1. Experimental manipulation of the inflammatory response

The photographs were taken two hours after LPS injection, when participants demonstrated significantly higher levels of IL-6 (LPS mean = 716.4 pg/mL, SD = 389.82; placebo mean = 1.95 pg/mL, SD = 1.41; t (19) = 37.95, p < 0.0001), tympanic temperature (LPS mean = 37.91 °C, SD = 0.44; placebo mean = 37.05 °C, SD = 0.32; t(20) = 7.51, p < 0.0001) and sickness behavior (LPS mean = 18.62, SD = 5.51; placebo mean = 5.52, SD = 3.19), t(20) = 9.43, p < 0.0001) compared with the placebo condition.

### 3.2. Sickness discrimination

To assess how well the participants could detect facial cues of sickness, we analyzed their accuracy in discriminating the sick face from the healthy face among the face pairs. Participants accurately identified the sick face in 73.12 % of trials, significantly above chance (50 %), t(92) = 16.77, p < 0.0001, 95 % CI [70.38, 75.86], with a large effect size (Cohen's d = 1.74), indicating a strong ability to correctly detect sick

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Sickness discrimination accuracy. Participants discriminated the sick face among pairs at above chance levels (73.12 %, p < 0.0001). Females (76.01 %) were significantly more accurate than males (69.29 %; p = 0.01).</figcaption></figure>
faces (see Fig. 2).

Females were, on average, more accurate (M = 76.01 %, SE = 1.69) at discriminating sick faces than males (M = 69.29 %, SE = 2.18; see Fig. 2). A GLMM revealed a significant effect of sex on sickness discrimination accuracy (β = −0.40, SE = 0.16, X²(1) = 6.13, p = 0.01; OR = 1.49, 95 % CI [1.09, 2.03]). The corresponding risk ratio (RR = 1.10) indicates that correctly identifying a sick face is about 10 % more likely in females than in males, reflecting a weak to moderate effect of sex. This finding confirms prior research demonstrating the ability to discriminate facial sickness cues, while also replicating recent exploratory findings suggesting that females are generally better than males at discriminating sick from healthy faces (Tognetti et al., 2023b).

### 3.3. Facial trustworthiness

To assess whether sickness as appraised from facial cues influenced participants' judgments of trustworthiness, we examined participants' choices when selecting the most trustworthy face within each pair. Participants chose the sick face as the more trustworthy-looking within a pair in only 34.90 % of trials, which was statistically significantly below the random expectation of 50 %, t(81) = −9.45, p < 0.001, with a 95 % confidence interval of [31.72, 38.08] (see Fig. 3). The corresponding effect size was large (Cohen's d = −1), indicating a strong tendency for participants to avoid judging sick faces as trustworthy.

Next, we investigated whether males and females differed in their trustworthiness judgments by assessing whether they were more likely to select the sick or healthy version of a face as the most trustworthy. Descriptive statistics indicated that females were less likely to choose the sick face (M = 30.50 %, SE = 1.87) as the more trustworthy-looking face within a pair compared to males (M = 39.52 %, SE = 2.44). A GLMM revealed a significant effect of sex on trustworthiness judgments (β = −0.43, SE = 0.15, X²(1) = 8.75, p = 0.003; OR = 0.65, 95 % CI [0.49, 0.87]). The corresponding risk ratio (RR = 0.77) indicates that females are about 23 % less likely than males to select the sick face as more trustworthy, reflecting a moderate effect of sex (see Fig. 3).

### 3.4. Participant disease-related traits and sickness perception

GLMMs were used to assess whether participants' self-reported disease vulnerability, disgust sensitivity, and frequency of sickness influenced sickness discrimination accuracy and trustworthiness judgments.

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Facial trustworthiness judgements. Participants selected sick faces as the more trustworthy significantly less often than healthy faces (34.90 %, p < 0.001). Females (30.50 %) were even less likely than males (39.52 %) to do so (p = 0.003).</figcaption></figure>

Results indicate that none of these disease-related characteristics significantly predicted sickness discrimination accuracy (disease vulnerability: β = −0.05, SE = 0.04, X2(1) = 1.31, p = 0.25, OR = 0.95, 95 % CI [0.87, 1.04]; disgust sensitivity: β = 0.08, SE = 0.04, X2(1) = 3.45, p = 0.06, OR = 1.09, 95 % CI [0.99, 1.19]; frequency of sickness: β = −0.01, SE = 0.07, X2(1) = 0.03, p = 0.85, OR = 0.99, 95 % CI [0.87, 1.12]), while controlling for the confounding effect of sex (β = 0.40, SE = 0.17, X2(1) = 5.78, p = 0.02; OR = 1.49, 95 % CI [1.08, 2.06]).

A separate GLMM revealed a significant effect of disgust sensitivity on trustworthiness judgments (β = 0.08, SE = 0.04, X²(1) = 4.38, p = 0.04). The corresponding OR = 1.09 (95 % CI [1.01, 1.18]) indicates that for each 1-unit increase in disgust sensitivity, the odds of selecting the healthy face as more trustworthy increase by about 9 %. Similar to the sickness discrimination findings, while sex was significant (β = −0.50, SE = 0.15, X2(1) = 11.31, p < 0.001; OR = 0.61, 95 % CI [0.45, 0.81]), neither disease vulnerability (β = 0.02, SE = 0.04, X2(1) = 0.18, p = 0.67; OR = 1.02, 95 % CI [0.94, 1.10]) nor frequency of sickness (β = −0.05, SE = 0.06, X2(1) = 0.70, p = 0.40; OR = 0.95, 95 % CI [0.85, 1.07]) significantly predicted trustworthiness judgments.

### 3.5. Effects of sickness responses on sickness discrimination and trustworthiness judgements

Additional GLMMs were used to examine whether facial stimulus participant sickness response intensity predicted participants' sickness discrimination accuracy and trustworthiness judgments. We observed no significant effects of LPS-induced changes in IL-6 concentrations (β = −0.20, SE = 0.27, X²(1) = 0.56, p = 0.45; OR = 0.82, 95 % CI [0.49, 1.38]), body temperature (β = −0.16, SE = 0.37, X²(1) = 0.18, p = 0.67; OR = 0.85, 95 % CI [0.42, 1.76]), and sickness symptoms (β = 0.02, SE = 0.03, X²(1) = 0.62, p = 0.43; OR = 1.02, 95 % CI [0.97, 1.08]) on participants' sickness discrimination accuracy while controlling for sex (β = 0.35, SE = 0.16, X²(1) = 4.75, p = 0.03; OR = 1.42, 95 % CI [1.04, 1.95]).

A separate GLMM examined whether facial stimulus participant sickness responses influenced participants' trustworthiness judgments while controlling for sex (β = −0.41, SE = 0.15, X²(1) = 7.89, p = 0.005; OR = 0.66, 95 % CI [0.50, 0.88]). Similar to the results for sickness discrimination accuracy, LPS-induced changes in IL-6 concentrations (β = 0.16, SE = 0.17, X²(1) = 0.83, p = 0.36; OR = 1.17, 95 % CI [0.83, 1.64]), body temperature (β = 0.12, SE = 0.24, X²(1) = 0.24, p = 0.62; OR = 1.12, 95 % CI [0.70, 1.80]), and sickness symptoms (β = 0.002, SE = 0.02, X²(1) = 0.02, p = 0.90; OR = 1.00, 95 % CI [0.96, 1.04]) were not significantly associated with trustworthiness ratings.

### 3.6. Correlation between sickness discrimination and trustworthiness judgments

We examined the relationship between the accuracy of sickness discrimination and trustworthiness judgments for each face pair (N = 21). A Spearman correlation analysis revealed a significant negative correlation between the proportion of times participants accurately discriminated the sick face within a pair and the proportion of times participants in the other condition judged that face as the most trustworthy (r = −0.68, p < 0.001; see Fig. 4). We infer that higher accuracy in sickness discrimination among participants for a specific face indicates that the face appears sicker; therefore, this finding suggests that the sicker a face looks, the less likely that face is to be judged as trustworthy.

## 4. Discussion

This study examined whether inflammation-induced sickness cues in faces can be detected and whether these cues influence trustworthiness judgments, shedding light on how humans use visual sickness cues to guide approach and avoidance behaviors. Consistent with prior
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Correlation between the proportion of times sick faces within a pair were selected as the most trustworthy and the proportion of times the sick face within a pair was successfully discriminated as the sick face. Results suggest that the sicker a face looks, the less likely that face will be selected as the most trustworthy (r = -0.68, p < 0.001).</figcaption></figure>

research, participants accurately discriminated between sick and healthy faces, with females exhibiting higher accuracy than males. Furthermore, our results extend the prior literature by demonstrating that facial sickness cues significantly influence trustworthiness judgments. In fact, faces identified with higher sickness discrimination accuracy, suggesting they appear sicker, were less likely to be perceived as trustworthy. Together with previous findings that sick faces are less liked than healthy faces (Leschak et al., 2022; Regenbogen et al., 2017; Sarolidou et al., 2020a), our results suggest that discrimination of visual sickness cues can elicit negative social evaluations that likely reflect underlying motivations to avoid pathogens, with these effects being more pronounced in females than in males.

Evidence that sick faces are perceived as less trustworthy aligns with broader research suggesting humans form rapid and spontaneous judgments of trustworthiness from faces (e.g., Engell et al., 2007; Willis and Todorov, 2006) and that these judgments influence approach-avoidance behaviors (e.g., Kim et al., 2012; Radke et al., 2018; Slepian et al., 2012). However, these judgments are often inaccurate (Jaeger et al., 2022; Zebrowitz and Montepare, 2008), likely due to an overgeneralization effect of facial features resembling emotional displays that communicate behavioral intentions (Secord, 1958; Todorov et al., 2008; Zebrowitz and Montepare, 2008). Neutral faces with subtle happy expressions are rated more trustworthy, while those with subtle angry expressions are rated less trustworthy, in part because emotional displays of anger communicate that a person should be avoided while happiness communicates that a person is safe to approach (Todorov et al., 2008; Zebrowitz and Montepare, 2008). Jaeger & Jones (2022) used machine learning to show that resemblance to certain emotional expressions was the strongest predictor of perceived trustworthiness among 28 theoretically important features. Notably, other work indicates an association between perceived facial expressions of negative emotions and visual sickness cues (Sarolidou et al., 2019; Tskhay et al., 2016). For example, Sarolidou et al. (2019) demonstrated that sick faces are perceived as expressing more negative emotions, such as sadness and disgust and less positive emotions, including happiness and surprise. Hence, one plausible explanation for the connection between visual sickness cues in the face and facial trustworthiness judgments is that sick faces display subtle negative expressions that adversely impact trustworthiness evaluations. Future work could evaluate the relationship between subtle emotional expressions perceived on sick faces and trustworthiness judgments of those faces.

In the present study, women demonstrated higher accuracy than men (76.01 % vs. 69.29 %) in sickness discrimination and were significantly less likely to perceive sick faces as trustworthy (30.5 % vs. 39.5 %).

Several non-exclusive mechanisms may underlie these sex differences. One possibility is that women may have lower perceptual thresholds for detecting both emotional and health-related facial cues. They generally outperform men in recognizing facial emotional expressions (Hall et al., 2025; McClure, 2000; Olderbak et al., 2019) and in color vision—reflecting the much lower prevalence of color blindness among women (0.4 % vs. 8 % in Caucasian populations) (Birch, 2012). These advantages are relevant for recognizing negative emotions such as sadness and disgust, which are more pronounced in sick faces (Axelsson et al., 2018; Sarolidou et al., 2019), and for detecting subtle skin color changes after sickness induction such as paleness or reduced redness (Axelsson et al., 2018; Henderson et al., 2017). Such perceptual sensitivity, which could be examined in future work using psychophysical measures of just-noticeable differences in facial redness or emotional intensity, likely explains both the higher accuracy observed here and our previous finding of faster responses by women without a speed-accuracy trade-off (Tognetti et al., 2023b).

Attentional mechanisms may also contribute; for example, women may allocate more attention to facial features signaling health or sickness, a possibility that could be tested with eye-tracking methods. In addition, experiential factors may play a role, as women's greater involvement in caregiving roles could increase their exposure to sick individuals, potentially enhancing their ability to learn and recognize relevant cues (Al-Shawaf et al., 2018; Curtis et al., 2004).

Hormonal influences are another plausible factor. During the luteal phase of the menstrual cycle—when progesterone levels are high relative to estrogen—the immune system's inflammatory response is weakened, increasing susceptibility to infection. This physiological vulnerability may be offset by heightened disgust and avoidance of potential disease cues, leading women to be more attentive and responsive to signs of sickness during this phase (Fessler and Navarrete, 2003; Fleischman and Fessler, 2011). However, evidence remains mixed in both humans and other animals (Bressan and Kramer, 2022; Fessler and Navarrete, 2003; Fleischman and Fessler, 2011; Kavaliers et al., 2021; Keller and Diekhof, 2024; Rafiee et al., 2023; Stern and Shiramizu, 2022; Zelazniewicz et al., 2016). Testing whether sickness detection accuracy and trustworthiness ratings vary systematically across menstrual phases could help clarify this link.

Beyond perceptual, attentional, and hormonal mechanisms, evolutionary pressures to protect themselves and their offspring from disease may have shaped sex differences in disease avoidance. Women's higher pathogen disgust sensitivity—hypothesized to reduce mother's infection risk during periods of high reproductive investment and to limit pathogen transmission to offspring due to close contact (e.g., during gestation, breastfeeding)—may lead to lower trust and stronger avoidance of individuals perceived as sick (Al-Shawaf et al., 2018; Curtis et al., 2004; Prokop and Jančovičová, 2013). Such heightened sensitivity is not unique to humans; in non-human primates, females display prophylactic behaviors that reduce parasite diversity and infection risk (e.g., Philippon et al., 2023; Poirotte et al., 2019, 2017; Poirotte and Kappeler, 2019; Sarabian et al., 2021; Sarabian and MacIntosh, 2015). In line with this framework, females in our sickness discrimination task reported higher perceived vulnerability to disease and higher sickness frequency than males. However, no significant sex differences emerged in disgust sensitivity (Table A.1), and none of these disease-related traits predicted sickness discrimination accuracy. In the trustworthiness task, there were no sex differences in the different disease-related traits and, while sex and disgust sensitivity predicted trustworthiness judgments, perceived disease vulnerability and sickness frequency did not. These results suggest that heightened disgust sensitivity—rather than perceived vulnerability or sickness frequency—may drive stronger avoidance and reduced trust toward individuals perceived as sick. However, the use of brief, unvalidated measures of disease vulnerability and disgust sensitivity limits the strength of these conclusions.

Overall, multiple interacting factors—including perceptual sensitivity, attentional allocation, hormonal modulation, experiential
learning, and evolved disease-avoidance tendencies—likely contribute to women's superior sickness detection. Future research should test these mechanisms directly to better understand the origins underlying sex differences in behavioral disease avoidance.

The present study also investigated whether facial stimulus partici-
pant sickness responses, measured via changes in IL-6, body tempera-
ture, and self-reported sickness symptoms, predicted participants'
sickness discrimination accuracy and trustworthiness judgments. No
significant effects were observed. This finding contrasts with prior
research by Leschak et al. (2022), which demonstrated that faces of
individuals exhibiting a stronger immune response (measured via IL-6
and TNF-alpha) following injection with a lower dose of endotoxin
(derived from Escherichia coli; 0.8 ng/kg of body weight) were less
liked. However, both the current and prior studies are limited by small
sample sizes (N = 21 and N = 15, respectively), warranting cautious
interpretation of these findings. Moreover, methodological differences
between the studies —such as endotoxin dosage and the presentation
format of faces (individual vs. paired)—may further account for the
inconsistency in results. Future research employing larger samples and
standardized methodologies is needed to clarify the relationship be-
tween the magnitude of inflammatory responses and behavioral avoid-
ance mechanisms.

While the present findings contribute to our understanding of how humans detect and respond to sickness cues, several limitations warrant consideration. One concerns the specificity of our perceptual measure: participants may not have evaluated trustworthiness exclusively, as judgments of this trait are strongly correlated with attractiveness and intelligence (Lundqvist et al., 1998). Indeed, Oosterhof & Todorov (2008) identified trustworthiness as the primary positively valenced dimension in facial evaluations, with other positive traits closely aligned along this dimension. In fact, their research found that facial evaluations could largely be reduced to two orthogonal dimensions: trustworthiness and dominance. Thus, even if participants assessed a related trait, their judgments are likely highly correlated with trustworthiness.

Another relates to behavioral outcomes, as the study did not include explicit measures of behavioral avoidance, even though trustworthiness judgments are known to predict approach-avoidance behaviors (Oosterhof and Todorov, 2008; Radke et al., 2018; Slepian et al., 2017, 2012; Todorov et al., 2008). Future research should consider implementing objective and quantitative measures of behavioral avoidance.

Three other methodological considerations apply. While this study utilized an experimental sickness model, more ecologically valid insights might be gained by using natural sickness models, such as upper respiratory infections (Tognetti et al., 2023a, 2023c). Future work may also benefit from combining sick faces with other sensory cues, such as sick body odors, as done in Regenbogen et al. (2017) and Sarolidou et al (2020a). Congruent cues from different sensory systems, especially if weak, lead to faster and more accurate discrimination when combined (Stein et al., 2014; Stevenson et al., 2014). Given the subtle nature of visual sickness cues used in this study, integrating multimodal cues could potentially amplify sex differences in sickness discrimination and subsequent avoidance behaviors.

Likewise, our use of a two-alternative forced-choice paradigm, while advantageous for experimental control and sensitivity, may not fully reflect real-world social judgments. Although the task may approximate natural comparative processes—such as recognizing changes in familiar faces—its artificial forced-choice nature limits the generalizability of findings to everyday social interactions. However, previous research using the same facial stimuli presented one by one has nonetheless demonstrated that people can reliably discriminate between sick and healthy individuals. Future studies could build on this by combining different paradigms to better capture the nuances of sickness perception.

Furthermore, participants were recruited immediately following
completion of a separate study and were not compensated for this task.
This may have differentially affected male and female motivation and
engagement, potentially contributing to the observed sex differences.

Nonetheless, this possibility seems unlikely, given that similar sex dif-
ferences in sickness discrimination were previously observed in a
compensated study employing comparable facial stimuli (Tognetti et al.,
2023b).

A final limitation concerns outlier detection: we applied a 3 SD cri-
terion for variables with normal distributions and a 3 × IQR criterion for
variables that were not normally distributed. While both methods are
commonly used, different approaches or thresholds could yield different
results, which should be considered when interpreting the findings.

5. Conclusion

Our findings confirm that humans can discriminate between sick and healthy faces based solely on cues of an acute inflammatory response. Facial sickness cues were further shown to be negatively related to trustworthiness judgments. Notably, we observe significant sex differences in sickness discrimination accuracy and find that females are more likely to judge sick faces as untrustworthy. Detecting and responding to phenotypic sickness cues may serve as an adaptive strategy, mitigating the costs of a full immune response and reducing contagion risks within social groups. Trustworthiness judgments, therefore, may function as an evolved mechanism for threat appraisal, guiding social interactions to limit disease transmission. Our study contributes to the literature on behavioral defenses against disease, highlighting the interplay between cognitive evaluations and adaptive behaviors in disease avoidance. Future research should directly examine overt approach-avoidance behaviors in response to sickness cues to gain insights into the behavioral correlates of trustworthiness judgments.

CRediT authorship contribution statement

**Megan N. Cesarini-Williams:** Writing – review & editing, Writing – original draft, Formal analysis. **Julie Lasselin:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Mats Lekander:** Writing – review & editing, Resources. **John Axelsson:** Writing – review & editing, Resources. **Mats J. Olsson:** Writing – review & editing, Supervision, Resources, Methodology, Funding acquisition, Conceptualization. **Arnaud Tognetti:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We express our gratitude to Michel Raymond for his valuable help in programming the computerized task used in this study.

Funding

The present study was supported by Swedish Research Council Grants 2016-02742 (MO), 2020-02567 (MO), and 2021-03184 (AT).

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbi.2025.106102.

Data availability

Data are available upon request (and ethical authorization) to julie.
lasselin@ki.se.

## References

Aarøe, L., Osmundsen, M., Petersen, M.B., 2016. Distrust as a disease avoidance strategy: individual differences in disgust sensitivity regulate generalized social trust. Front. Psychol. 7. https://doi.org/10.3389/fpsyg.2016.01038.

Al-Shawaf, L., Lewis, D.M.G., Buss, D.M., 2018. Sex differences in disgust: why are women more easily disgusted than men? Emot. Rev. 10, 149–160. https://doi.org/10.1177/1754073917709940.

Andreasson, A., Wicksell, R., Lodin, K., Karshikoff, B., Axelsson, J., Lekander, M., 2018. A global measure of sickness behaviour: Development of the sickness questionnaire. J. Health Psychol. 23, 1452–1463. https://doi.org/10.1177/1359105316659917.

Arakawa, H., Cruz, S., Deak, T., 2011. From models to mechanisms: Odorant communication as a key determinant of social behavior in rodents during illness-associated states. Neurosci. Biobehav. Rev. 35, 1916–1928. https://doi.org/10.1016/j.neubiorev.2011.03.007.

Arshamian, A., Sundelin, T., Wnuk, E., O'Meara, C., Burenhult, N., Rodriguez, G.G., Lekander, M., Olsson, M.J., Lasselin, J., Axelsson, J., Majid, A., 2021. Human sickness detection is not dependent on cultural experience. Proc. R. Soc. B Biol. Sci. 288, 20210922. https://doi.org/10.1098/rspb.2021.0922.

Axelsson, J., Sundelin, T., Olsson, M.J., Sorjonen, K., Axelsson, C., Lasselin, J., Lekander, M., 2018. Identification of acutely sick people and facial cues of sickness. Proc. R. Soc. B Biol. Sci. 285, 20172430.

Ballew, C.C., Todorov, A., 2007. Predicting political elections from rapid and unreflective face judgments. Proc. Natl. Acad. Sci. 104, 17948–17953.

Behringer, D.C., Butler, M.J., Shields, J.D., 2006. Avoidance of disease by social lobsters. Nature 441, 421. https://doi.org/10.1038/441421a.

Behringer, D.C., Butler, M.J., 2010. Disease avoidance influences shelter use and predation in Caribbean spiny lobster. Behav. Ecol. Sociobiol. 64, 747–755. https://doi.org/10.1007/s00265-009-0892-5.

Birch, J., 2012. Worldwide prevalence of red-green color deficiency. JOSA A 29, 313–320.

Bressan, P., 2020. Strangers look sicker (with implications in times of COVID-19), 2000158 BioEssays. https://doi.org/10.1002/bies.202000158.

Bressan, P., Kramer, P., 2022. Progesterone does raise disgust. Horm. Behav. 137, 104937. https://doi.org/10.1016/j.yhbeh.2021.104937.

Chang, L.J., Doll, B.B., van't Wout, M., Frank, M.J., Sanfey, A.G., 2010. Seeing is believing: Trustworthiness as a dynamic belief. Cognit. Psychol. 61, 87–105.

Cosmides, L., Tooby, J., 1992. Cognitive adaptations for social exchange. Adapt. Mind Evol. Psychol. Gener. Cult. 163, 163–228.

Curtis, V., Aunger, R., Rabie, T., 2004. Evidence that disgust evolved to protect from risk of disease. Proc. R. Soc. Lond. B Biol. Sci. 271, S131–S133. https://doi.org/10.1098/rslb.2003.0144.

Dantzer, R., 2009. Cytokine, sickness behavior, and depression. Immunol. Allergy Clin. 29, 247–264.

Ehman, K.D., Scott, M.E., 2001. Urinary odour preferences of MHC congenic female mice, Mus domesticus: Implications for kin recognition and detection of parasitized males. Anim. Behav. 62 (4), 781–789.

Engell, A.D., Haxby, J.V., Todorov, A., 2007. Implicit trustworthiness decisions: automatic coding of face properties in the human amygdala. J. Cogn. Neurosci. 19, 1508–1519.

Ert, A., Fleischer, A., Magen, N., 2016. Trust and reputation in the sharing economy: the role of personal photos in Airbnb. Tour. Manag. 55, 62–73.

Ewing, L., Caulfield, F., Read, A., Rhodes, G., 2015. Perceived trustworthiness of faces drives trust behaviour in children. Dev. Sci. 18, 327–334.

Fan, Q., Olatunji, B.O., 2013. Individual differences in disgust sensitivity and health-related avoidance: examination of specific associations. Personal. Individ. Differ. 55, 454–458.

Fessler, D.M., Navarrete, C.D., 2003. Domain-specific variation in disgust sensitivity across the menstrual cycle. Evol. Hum. Behav. 24, 406–417.

Fleischman, D.S., Fessler, D.M.T., 2011. Progesterone's effects on the psychology of disease avoidance: support for the compensatory behavioral prophylaxis hypothesis. Horm. Behav. 59, 271–275. https://doi.org/10.1016/j.yhbeh.2010.11.014.

Freeman, J.B., Stolier, R.M., Ingbretsen, Z.A., Hehman, E.A., 2014. Amygdala responsivity to high-level social information from unseen faces. J. Neurosci. 34, 10573–10581.

Gomulya, D., Wong, E.M., Ormiston, M.E., Boeker, W., 2017. The role of facial appearance on CEO selection after firm misconduct. J. Appl. Psychol. 102, 617.

Gordon, A.R., Kimball, B.A., Sorjonen, K., Karshikoff, B., Axelsson, J., Lekander, M., Lundström, J.N., Olsson, M.J., 2018. Detection of inflammation via volatile cues in human urine. Chem. Senses 43, 711–719. https://doi.org/10.1093/chemse/bjy059.

Gordon, A.R., Lundström, J.N., Kimball, B.A., Karshikoff, B., Sorjonen, K., Axelsson, J., Lekander, M., Olsson, M.J., 2023. Human scent as a first-line defense against disease. Sci. Rep. 13, 16709.

Haidt, J., McCauley, C., Rozin, P., 1994. Individual differences in sensitivity to disgust: a scale sampling seven domains of disgust elicitors. Personal. Individ. Differ. 16, 701–713.

Hall, J.A., Gunnery, S.D., Schlegel, K., 2025. Gender and Accuracy in Decoding Affect Cues: A Meta-Analysis. J. Intelligence 13, 38.

Hansson, L.S., Lasselin, J., Tognetti, A., Axelsson, J., Olsson, M.J., Sundelin, T., Lekander, M., 2023. The walking sick: perception of experimental sickness from biological motion. Brain Behav. Immun. 113, 319–327. https://doi.org/10.1016/j.bbi.2023.07.020.

Hart, B.L., 2011. Behavioural defences in animals against pathogens and parasites: parallels with the pillars of medicine in humans. Philos. Trans. r. Soc. B Biol. Sci. 366, 3406–3417.

Henderson, A.J., Holzleitner, I.J., Talamas, S.N., Perrett, D.I., 2016. Perception of health from facial cues. Philos. Trans. r. Soc. B Biol. Sci. 371, 20150380.

Henderson, A.J., Lasselin, J., Lekander, M., Olsson, M.J., Powis, S.J., Axelsson, J., Perrett, D.I., 2017. Skin colour changes during experimentally-induced sickness. Brain Behav. Immun. 60, 312–318.

Jaeger, B., Jones, A.L., 2022. Which facial features are central in impression formation? Soc. Psychol. Personal. Sci. 13, 553–561. https://doi.org/10.1177/19485506211034979.

Jaeger, B., Oud, T., Williams, T., Krumhuber, E.G., Fehr, E., Engelmann, J.B., 2022. Can people detect the trustworthiness of strangers based on their facial appearance? Evol. Hum. Behav. 43, 296–303.

Kavaliers, M., Choleris, E., Pfaff, D.W., 2005. Recognition and avoidance of the odors of parasitized conspecifics and predators: Differential genomic correlates. Neurosci. Biobehav. Rev. 29 (8), 1347–1359.

Kavaliers, M., Bishnoi, I.R., Ossenkopp, K.-P., Choleris, E., 2021. Differential effects of progesterone on social recognition and the avoidance of pathogen threat by female mice. Horm. Behav. 127. https://doi.org/10.1016/j.yhbeh.2020.104873.

Kavaliers, M., Colwell, D.D., 1995. Odours of parasitized males induce aversive responses in female mice. Anim. Behav. 50 (5), 1161–1169.

Keller, J.K., Diekhof, E.K., 2024. Influence of female sex hormones on proactive behavioral and physiological immune parameters. Reprod. Biol. 24, 100880. https://doi.org/10.1016/j.repbio.2024.100880.

Kim, H., Choi, M.-J., Jang, I.-J., 2012. Lateral OFC activity predicts decision bias due to first impressions during imitatum games. J. Cogn. Neurosci. 24, 428–439.

Lasselin, J., Treadway, M.T., Lacourt, T.E., Soop, A., Olsson, M.J., Karshikoff, B., Paues-Göranson, S., Axelsson, J., Dantzer, R., Lekander, M., 2017. Lipopolysaccharide alters motivated behavior in a monetary reward task: a randomized trial. Neuropsychopharmacology 42, 801–810. https://doi.org/10.1038/npp.2016.191.

Lasselin, J., Petrovic, P., Olsson, M.J., Paues Göranson, S., Lekander, M., Jensen, K.B., Axelsson, J., 2018. Sickness behavior is not all about the immune response: possible roles of expectations and prediction errors in the worry of being sick. Brain Behav. Immun. 74, 213–221. https://doi.org/10.1016/j.bbi.2018.09.008.

Lasselin, J., Sundelin, T., Wayne, P.M., Olsson, M.J., Göranson, S.P., Axelsson, J., Lekander, M., 2020. Biological motion during inflammation in humans. Brain Behav. Immun. 84, 147–153.

Leshch, C.J., Hornstein, E.A., Haltom, K.E.B., Johnson, K.L., Breen, E.C., Irwin, M.R., Eisenberger, N.I., 2022. Ventromedial prefrontal cortex activity differentiates sick from healthy faces: associations with inflammatory responses and disease avoidance motivation. Brain Behav. Immun. 100, 48–54.

Leung, T.S., Maylott, S.E., Zeng, G., Nascimben, D.N., Jakobsen, K.V., Simpson, E.A., 2023. Behavioral and physiological sensitivity to natural sick faces. Brain Behav. Immun. 110, 195–211. https://doi.org/10.1016/j.bbi.2023.03.007.

Leung, T.S., Zeng, G., Maylott, S.E., Martinez, S.N., Jakobsen, K.V., Simpson, E.A., 2024. Infection detection in faces: Children's development of pathogen avoidance. Child Dev. 95. https://doi.org/10.1111/cdev.13983.

Lundqvist, D., Flykt, A., Ohman, A., 1998. Karolinska directed emotional faces. Cogn. Emot.

Magalhães, A.C., Soares, S.C., 2023. Interpersonal distance modulation by facial disease cues: Gender differences and increased avoidance. Preprint. https://doi.org/10.21203/rs.3.8s-2001875/v1.

McClure, E.B., 2000. A meta-analytic review of sex differences in facial expression processing and their development in infants, children, and adolescents. Psychol. Bull. 126, 424.

Morrow, E.H., 2015. The evolution of sex differences in disease. Biol. Sex Differ. 6, 5. https://doi.org/10.1186/s13293-015-0023-0.

Olderbak, S., Wilhelm, O., Hildebrandt, A., Quoidbach, J., 2019. Sex differences in facial emotion perception ability across the lifespan. Cogn. Emot. 33, 579–588. https://doi.org/10.1080/02699931.2018.1454403.

Olsson, M.J., Lundström, J.N., Kimball, B.A., Gordon, A.R., Karshikoff, B., Hosseini, N., Sorjonen, K., Olgart Höglund, C., Solares, C., Soop, A., Axelsson, J., Lekander, M., 2014. The scent of disease: human body odor contains an early chemosensory cue of sickness. Psychol. Sci. 25, 817–823. https://doi.org/10.1177/0956797613515681.

Oosterhof, N.N., Todorov, A., 2008. The functional basis of face evaluation. Proc. Natl. Acad. Sci. 105, 11087–11092.

Park, J.H., 2015. Introversion and human-contaminant disgust sensitivity predict personal space. Personal. Individ. Differ. 82, 185–187. https://doi.org/10.1016/j.paid.2015.03.030.

Phelps, E.A., LeDoux, J.E., 2005. Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron 48, 175–187.

Philippon, J., Serrano-Martínez, E., Poirotte, C., 2023. Fecal avoidance and gastrointestinal parasitism in semi-free ranging woolly monkeys (Lagothrix lagotricha poeppigii). Behav. Ecol. Sociobiol. 77, 41. https://doi.org/10.1007/s00265-023-03317-7.

Poirotte, C., Kappeler, P.M., 2019. Hygienic personalities in wild grey mouse lemurs vary adaptively with sex. Proc. R. Soc. B 286, 20190863.

Poirotte, C., Massol, F., Herbert, A., Willaume, E., Bomo, P.M., Kappeler, P.M., Charpentier, M.J.E., 2017. Mandrills use olfaction to socially avoid parasitized conspecifics. Sci. Adv. 3, e1601721. https://doi.org/10.1126/sciadv.1601721.

Poirotte, C., Sarabian, J., Ngoubangoye, B., MacIntosh, A.J., Charpentier, M., 2019. Faecal avoidance differs between the sexes but not with nematode infection risk in mandrills. Anim. Behav. 149, 97–106. https://doi.org/10.1016/j.anbehav.2019.01.013.
Porter, S., ten Brinke, L., Gustaw, C., 2010. Dangerous decisions: the impact of first impressions of trustworthiness on the evaluation of legal evidence and defendant culpability. Psychol. Crime Law 16, 477–491. https://doi.org/10.1080/10683160902926141.

Prokop, P., Jančovčíková, M., 2013. Disgust sensitivity and gender differences: an initial test of the parental investment hypothesis. Probl. Psychol. 21st Century 7, 40–48.

R Core Team, 2022. R: a language and environment for statistical computing.

Radke, S., Kalt, T., Wagels, L., Derntl, B., 2018. Implicit and explicit motivational tendencies to faces varying in trustworthiness and dominance in men. Front. Behav. Neurosci. 12, 8.

Rafiee, Y., Jones, B.C., Shiramizu, V., 2023. Is pathogen disgust increased on days of the menstrual cycle when progesterone is high? Evidence from a between-subjects study using estimated progesterone levels. Adapt. Hum. Behav. Physiol. 9, 26–36. https://doi.org/10.1007/s40750-022-00208-5.

Regenbogen, C., Axelsson, J., Lasselin, J., Porada, D.K., Sundelin, T., Peter, M.G., Lekander, M., Lundström, J.N., Olsson, M.J., 2017. Behavioral and neural correlates to multisensory detection of sick humans. Proc. Natl. Acad. Sci. 114, 6400–6405.

Rezlescu, C., Duchaine, B., Olivola, C.Y., Chater, N., 2012. Unfakeable facial configurations affect strategic choices in trust games with or without information about past behavior. PLoS One 7, e34293.

Roved, J., Westerdahl, H., Hasselquist, D., 2017. Sex differences in immune responses: Hormonal effects, antagonistic selection, and evolutionary consequences. Horm. Behav. 88, 95–105.

Sarabian, C., MacIntosh, A.J., 2015. Hygienic tendencies correlate with low geohelminth infection in free-ranging macaques. Biol. Lett. 11, 20150757.

Sarabian, C., Belais, R., MacIntosh, A.J.J., 2021. Avoidance of contaminated food correlates with low protozoan infection in bonobos. Front. Ecol. Evol. 9. https://doi.org/10.3389/fevo.2021.651159.

Sarolidou, G., Axelsson, J., Sundelin, T., Lasselin, J., Regenbogen, C., Sorjonen, K., Lundström, J.N., Lekander, M., Olsson, M.J., 2019. Emotional expressions of the sick face. Brain Behav. Immun. 80, 286–291. https://doi.org/10.1016/j.bbi.2019.04.003.

Sarolidou, G., Axelsson, J., Lasselin, J., Regenbogen, C., Sorjonen, K., Lundström, J.N., Lekander, M., Olsson, M.J., 2020a. People expressing olfactory and visual cues of disease are less liked. Philos. Trans. R. Soc. B Biol. Sci. 20190272.

Sarolidou, G., Tognetti, A., Lasselin, J., Regenbogen, C., Lundström, J.N., Kimball, B.A., Garke, M., Lekander, M., Axelsson, J., Olsson, M.J., 2020b. Olfactory communication of sickness cues in respiratory infection. Front. Psychol. 11, 1004. https://doi.org/10.3389/fpsyg.2020.01004.

Schaller, M., 2011. The behavioural immune system and the psychology of human sociality. Philos. Trans. R. Soc. B Biol. Sci. 366, 3418–3426.

Schaller, M., 2015. The behavioral immune system. In: The Handbook of Evolutionary Psychology. John Wiley & Sons, Ltd, pp. 1–19 https://doi.org/10.1002/9781119125563.evpych0107.

Schaller, M., Park, J.H., Faulkner, J., 2003. Prehistoric dangers and contemporary prejudices. Eur. Rev. Soc. Psychol. 14, 105–137.

Schaller, M., Park, J.H., 2011. The behavioral immune system (and why it matters). Curr. Dir. Psychol. Sci. 20, 99–103.

Secord, P.F., 1958. Facial features and inference processes in interpersonal perception. Pers. Percept. Interpers. Behav. 300–315.

Shakhar, K., Shakhar, G., 2015. Why do we feel sick when infected—can altruism play a role? PLoS Biol. 13, e1002276.

Slepian, M.L., Young, S.G., Rule, N.O., Weisbuch, M., Ambady, N., 2012. Embodied Impression Formation: Social Judgments and Motor Cues to Approach and Avoidance [WWW Document]. https://doi.org/10.1521/soco.2012.30.2.232. https://doi.org/10.1521/soco.2012.30.2.232.

Slepian, M.L., Young, S.G., Harmon-Jones, E., 2017. An approach-avoidance motivational model of trustworthiness judgments. Motiv. Sci. 3, 91–97. https://doi.org/10.1037/mot0000046.

Stein, B.E., Stanford, T.R., Rowland, B.A., 2014. Development of multisensory integration from the perspective of the individual neuron. Nat. Rev. Neurosci. 15, 520–535.

Stern, J., Shiramizu, V., 2022. Hormones, ovulatory cycle phase and pathogen disgust: a longitudinal investigation of the Compensatory Prophylaxis Hypothesis. Horm. Behav. 138, 105103.

Stevenson, R.A., Ghose, D., Fister, J.K., Sarko, D.K., Altieri, N.A., Nidiffer, A.R., Kurela, L. R., Siemann, J.K., James, T.W., Wallace, M.T., 2014. Identifying and quantifying multisensory integration: a tutorial review. Brain Topogr. 27, 707–730. https://doi.org/10.1007/s10548-014-0365-7.

Stirrat, M., Perrett, D.I., 2010. Valid facial cues to cooperation and trust: Male facial width and trustworthiness. Psychol. Sci. 21, 349–354.

Todorov, A., Baron, S.G., Oosterhof, N.N., 2008. Evaluating face trustworthiness: a model based approach. Soc. Cogn. Affect. Neurosci. 3, 119–127. https://doi.org/10.1093/scan/nsn009.

Todorov, A., Said, C.P., Oosterhof, N.N., Engell, A.D., 2011. Task-invariant brain responses to the social value of faces. J. Cogn. Neurosci. 23, 2766–2781.

Todorov, A., Mende-Siedlecki, P., Dotsch, R., 2013. Social judgments from faces. Curr. Opin. Neurobiol. 23, 373–380.

Todorov, A., Olivola, C.Y., Dotsch, R., Mende-Siedlecki, P., 2015. Social attributions from faces: determinants, consequences, accuracy, and functional significance. Annu. Rev. Psychol. https://doi.org/10.1146/annurev-psych-113011-143831.

Tognetti, A., Saluja, S., Lybert, N., Lasselin, J., Tamm, S., Lensmar, C., Karshikoff, B., Cervenka, S., Lekander, M., Olsson, M.J., 2023a. Olfactory cues of naturally occurring systemic inflammation: a pilot study of seasonal allergy. Neuroimmunomodulation 30, 338. https://doi.org/10.1159/000535047.

Tognetti, A., Thunell, E., Zakrzewska, M., Olofsson, J., Lekander, M., Axelsson, J., Olsson, M.J., 2023b. Discriminating between sick and healthy faces based on early sickness cues: an exploratory analysis of sex differences. Evol. Med. Public Health 11, 386–396. https://doi.org/10.1093/emph/eoad032.

Tognetti, A., Williams, M.N., Lybert, N., Lekander, M., Axelsson, J., Olsson, M.J., 2023c. Humans can detect axillary odor cues of an acute respiratory infection in others. Evol. Med. Public Health 11, 219–228. https://doi.org/10.1093/emph/eoad016.

Tskhay, K.O., Wilson, J.P., Rule, N.O., 2016. People use psychological cues to detect physical disease from faces. Pers. Soc. Psychol. Bull. 42, 1309–1320. https://doi.org/10.1177/0146167216656357.

Tybur, J.M., Bryan, A.D., Lieberman, D., Hooper, A.E.C., Merriman, L.A., 2011. Sex differences and sex similarities in disgust sensitivity. Personal. Individ. Differ. 51, 343–348.

Van Blerkom, L.M., 2003. Role of viruses in human evolution. Am. J. Phys. Anthropol. 122, 14–46. https://doi.org/10.1002/ajpa.10384.

van Leeuwen, F., Petersen, M.B., 2018. The behavioral immune system is designed to avoid infected individuals, not outgroups. Evol. Hum. Behav. 39, 226–234. https://doi.org/10.1016/j.evolhumbehav.2017.12.003.

van't Wout, M., Sanfey, A.G., 2008. Friend or foe: the effect of implicit trustworthiness judgments in social decision-making. Cognition 108, 796–803.

Willis, J., Todorov, A., 2006. First impressions: making up your mind after a 100-ms exposure to a face. Psychol. Sci. 17, 592–598.

Wilson, J.P., Rule, N.O., 2015. Facial trustworthiness predicts extreme criminal-sentencing outcomes. Psychol. Sci. 26, 1325–1331. https://doi.org/10.1177/0956797615590992.

Winston, J.S., Strange, B.A., O'Doherty, J., Dolan, R.J., 2002. Automatic and intentional brain responses during evaluation of trustworthiness of faces. Nat. Neurosci. 5, 277–283. https://doi.org/10.1038/nn816.

Zebrowitz, L.A., 2017. First impressions from faces. Curr. Dir. Psychol. Sci. 26, 237–242. https://doi.org/10.1177/0963721416683996.

Zebrowitz, L.A., Montepare, J.M., 2008. Social psychological face perception: why appearance matters. Soc. Pers. Psychol. Compass 2, 1497–1517. https://doi.org/10.1111/j.1751-9004.2008.00109.x.

Zelazniewicz, A., Borkowska, B., Nowak, J., Pawlowski, B., 2016. The progesterone level, leukocyte count and disgust sensitivity across the menstrual cycle. Physiol. Behav. 161, 60–65.