Temporal dynamics of spatial attentional biases toward obesity stereotypes among females with weight dissatisfaction

Temporal dynamics of spatial attentional biases toward obesity stereotypes among females with weight dissatisfaction | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 20 November 2025 V1 Latest version Share on Temporal dynamics of spatial attentional biases toward obesity stereotypes among females with weight dissatisfaction Authors : Jiayi Yao 0009-0001-3001-2163 , Jing Gao , Xuechen Leng , Xiaocui Yu , Ting Wang , Chengzhi Feng , and Wenfeng Feng 0000-0002-7664-5863 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176362231.17665020/v1 142 views 71 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract There is robust evidence indicating general attentional biases toward weight-related information among females with high levels of body dissatisfaction. Although individuals with obesity are often stereotyped as possessing both positive traits (e.g., broad-minded) and negative traits (e.g., laziness), attentional biases toward positive and negative obesity stereotypes in females with high weight dissatisfaction remain unclear. In the present study, event-related potentials (ERPs) were recorded from 25 female participants with high weight dissatisfaction (HWD) and 25 with low weight dissatisfaction (LWD) during a dot-probe task. In this task, negative and positive obesity-stereotypical trait words, along with neutral household words, were presented as cues, followed by a visual target that appeared at either a congruent or incongruent location. The results showed that positive obesity-stereotypical trait words elicited a significant N2pc component in both groups. In contrast, negative obesity-stereotypical trait words elicited a significant N2pc only in the HWD group, not in the LWD group. Importantly, the N2pc amplitudes in response to negative obesity-stereotypical trait words were significantly larger in the HWD group than in the LWD group. Furthermore, a significant Pd component was observed exclusively for negative obesity-stereotypical trait words in the HWD group, whereas no such effect was observed in the LWD group. These findings suggest that both positive and negative obesity stereotypes initially capture spatial attention. However, only negative obesity stereotypes are subsequently suppressed following the early attentional orienting in females with HWD. 1. Introduction Body weight and shape are significant concerns for many women, largely because appearance-focused social media propagates an unrealistic thin ideal (Devine et al., 2022). This exposure leads many women to internalize beliefs such as “thin is better” (Wang et al., 2020) and “thin is beautiful” (Wu et al., 2021), which in turn heightens feelings of fatness and increase anxiety about their weight. Importantly, weight dissatisfaction has been shown to prospectively predict a range of negative psychological and behavioral outcomes, including depression, anxiety, and eating disorders (Aspen et al., 2013; Paterna et al., 2021). Cognitive theories of body dissatisfaction propose that schemas related to appearance, shape, and weight influence the processing of information about body image. Thus, body image schemas may be accompanied by cognitive biases, leading to selective attention to, or processing of, body image information in the environment. These selective cognitive processes, in turn, lead to increased body dissatisfaction (Cash & Labarge, 1996; Williamson et al., 2004). Support for these theories comes from research showing that females with high weight dissatisfaction (HWD) when compared to those with low weight dissatisfaction (LWD), display attentional biases toward weight-related information . Specifically, fatness-related stimuli initially capture attention (Gao et al., 2011a, 2012; Glauert et al., 2010; Lyu et al., 2019), followed by delayed disengagement from these stimuli (Feng et al., 2010; Gao et al., 2011a, 2012, 2013). These findings are supported by electrophysiological studies, demonstrating that the N100/N170 (Schupp & Renner, 2011; Uusberg et al., 2018) and P3/LPP amplitudes (Gao et al., 2011b; Uusberg et al., 2018) elicited by fatness-related words were larger than those elicited by neutral words among females with HWD. Additionally, several studies have found attentional facilitation toward thinness-related stimuli (Gao et al., 2011a, 2012) and attentional avoidance of thinness-related information (Gao et al., 2011a, 2012; Lyu et al., 2019). However, previous studies have primarily focused on attentional biases toward weight-related information in females with HWD. Cognitive-behavioral models of eating disorders suggest that individuals with eating disorders develop maladaptive schemas related to body shape, weight, and self-concept (Vitousek & Hollon, 1990; Williamson et al., 2004). These schemas from a dense associative network that links “thinness” with positive attributes and associates “fatness” with various negative traits. In recent decades, the global prevalence of obesity has increased significantly, accompanied by rising societal discrimination against overweight and obese individuals, who are often subjected to stereotypes and prejudice (Westbury et al., 2023). Obesity stereotypes refer to the attitudes and beliefs about the characteristics of individuals with obesity (Kim & Jarry, 2014), with common portrayals depicting them as lazy, lacking self-discipline, and willpower (Jovančević & Jović, 2022). Research has shown that individuals with higher levels of body dissatisfaction tend to hold more negative implicit and explicit attitudes toward individuals with obesity (O’Brien et al., 2007). Additionally, people may internalize negative obesity stereotypes and evaluate themselves based on their weight. This phenomenon, known as weight bias internalization (Pearl & Dovidio, 2014), is particularly prevalent among women. Numerous studies have found a positive association between weight bias internalization and body dissatisfaction in female undergraduates (Bennett et al., 2022; Purton et al., 2019; Romano et al., 2021). Following the internalization of weight-based negative stereotypes, individuals often develop distorted perceptions of their own body shape and adopt these stereotypes as their own. This can lead to self-rejection, which further exacerbates body dissatisfaction. Moreover, Macho et al. (2023) demonstrated that, after controlling for body mass index (BMI), internalized weight bias remained a significant predictor of body dissatisfaction, exerting a stronger effect than BMI itself. This finding suggests that subjective perceptions of body weight and internalized negative weight-related beliefs may play a more critical role in shaping body dissatisfaction than objective weight. The aforementioned studies have established that females with HWD exhibit attentional biases toward weight-related information and that weight bias internalization is significantly associated with body dissatisfaction. However, to date, research has not examined whether females with HWD display attentional biases specifically toward obesity-stereotype information that does not explicitly reference ”fatness.” Moreover, previous studies on obesity stereotypes have predominantly used only negative obesity-stereotypical traits as experimental stimuli, neglecting the fact that societal cognitive evaluations of individuals with overweight or obesity are multidimensional. These evaluations also encompass positive obesity stereotypes, such as traits like kindness and cuteness (Kim & Jarry, 2014; Wu & Zhang, 2024). The present study investigated the temporal dynamics of spatial attentional biases toward obesity stereotype information in females with HWD. We adapted event-related potentials (ERPs) in a dot-probe task from Leng et al. (2024), where negative and positive obesity-stereotypical trait words served as task-irrelevant cues. Based on cognitive-behavioral models and previous research on the relationship between body dissatisfaction and obesity stereotypes, we hypothesized that, compared to the LWD group, the HWD group would exhibit spatial attentional biases toward obesity-stereotypical trait words. Specifically, if initial attentional orienting and/or suppression were present in the HWD group, larger N2pc and/or Pd amplitudes would be elicited by obesity-stereotypical trait words, but not in the LWD group. 2. Method To determine the sample size for a between-subjects 2 (HWD vs. LWD) × within-subjects 3 (positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) repeated-measures analysis of variance (ANOVA), an a priori power analysis was conducted using G*Power (Faul et al., 2007). The analysis of the group and word type interaction assumed a moderate effect size (Cohen’s f = 0.25), an alpha level of 0.05, a power of 0.95, a nonsphericity correction of 1, and a correlation of 0.5 between repeated measures. The minimum total sample size required to detect the interaction effect was calculated to be 44 participants. Participants recruited via on-campus advertisements were categorized into the HWD or LWD group according to their scores on the Negative Physical Self Scale–Fatness subscale (NPSS-F; Chen et al., 2006). The NPSS-F comprises 11 items assessing weight-related thoughts, feelings, and behaviors, rated on a 5-point Likert scale ranging from 0 (not at all like me) to 4 (very much like me) . The final score was calculated as the average of all item scores, with higher scores indicating greater weight dissatisfaction. The internal consistency coefficient ( α ) has a value of 0.94 in the current sample. Following the classification criteria of Feng et al. (2010), participants with scores above 2.0 were categorized as HWD, while those scoring below 1.0 were assigned to the LWD group. The mean NPSS-F score of the HWD group ( M = 2.38, SD = 0.42) was significantly higher than that of the LWD group ( M = 0.52, SD = 0.31), t (48) = 18.00, p < .001, d = 5.20. Four participants were excluded due to excessive EEG artifacts (≥ 40%), resulting in a final sample of 50 participants: 25 in the HWD group and 25 in the LWD group. All participants were aged between 18 and 25 years ( M = 20.56, SD = 1.74), and BMI was calculated using self-reported height and weight [BMI = weight (kg) / height² (m²)]. The HWD group ( M = 21.21, SD = 2.20) had a significantly higher mean BMI than the LWD group ( M = 19.43, SD = 1.97), t (48) = 3.02, p < 0.05, d = 0.86. It should be noted that the present study included only female undergraduates with a BMI ranging from 18.5 to 24.9 kg/m 2 , in order to minimize potential confounding effects of eating disorders and chronic diseases associated with overweight and obesity. It should be noted that participants in the present study were selected only female undergraduates with a BMI in the range of 18.5–24.9 kg/m², in order to exclude potential confounding effects of eating disorders and chronic diseases associated with overweight and obesity. All participants were right-handed, had normal or corrected-to-normal vision, and reported no history of neurological or psychiatric disorders. In accordance with the Declaration of Helsinki, written informed consent was obtained from all participants prior to participation. The study protocol was approved by the Human Research Protections Program of Soochow University. Twenty positive and twenty negative obesity-stereotypical trait words, along with sixty neutral words (e.g., furniture-related terms), were selected from previous studies (Puhl et al., 2005; Wei et al., 2022). Thirty-four participants, who did not participate in the formal experiment, rated these words on four dimensions: relevance to obesity-stereotypical traits, valence, arousal, and familiarity, using a 7-point Likert scale (1 = not at all, 7 = extremely). The selection criteria were as follows: words with an average obesity-stereotype relevance rating between 4.5 and 7 and an average valence rating between 4.5 and 7 were classified as positive obesity-stereotypical trait words; words with an average obesity-stereotype relevance rating between 4.5 and 7 and an average valence rating between 1 and 3.5 were classified as negative obesity-stereotypical trait words; words with an average obesity-stereotype relevance rating between 1 and 2 and an average valence rating between 3.5 and 4.5 were classified as neutral words. In addition, all selected words had familiarity ratings above 5. Ultimately, ten positive obesity-stereotypical trait words (e.g., approachable, easy-going), ten negative obesity-stereotypical trait words (e.g., lazy, undisciplined), and forty neutral words (e.g., teapot, towel) were included as experimental stimuli (see Appendix A). A one-way analysis of variance (ANOVA) examined the effect of word type (positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) on score ratings. Positive obesity-stereotypical trait words (5.84 ± 0.45) and neutral words (4.15 ± 0.16) were rated as significantly more pleasant than negative obesity-stereotypical trait words (1.98 ± 0.25). Furthermore, positive obesity-stereotypical trait words were rated as more pleasant than neutral words ( ps < 0.001) [ F (2, 57) = 639.13, p < 0.001, η² p = 0.96]. For arousal ratings, both positive (3.89 ± 0.38) and negative obesity-stereotypical trait words (3.71 ± 0.13) scored significantly higher than neutral words (2.49 ± 0.22) ( ps 0.05) [ F (2, 57) = 191.29, p < 0.001, η² p = 0.87]. In terms of relevance to obesity-stereotypical traits, both positive (5.50 ± 0.17) and negative obesity-stereotypical trait words (5.63 ± 0.40) scored significantly higher than neutral words (1.61 ± 0.27) ( ps 0.05) [ F (2, 57) = 1355.49, p 0.05; positive obesity-stereotypical trait words: 5.88 ± 0.34; negative obesity-stereotypical trait words: 5.83 ± 0.20; neutral words: 5.82 ± 0.36) [ F (2, 57) = 0.12, p = 0.88, η² p = 0.004]. The selected words were then used to create 10 positive obesity-stereotypical–neutral word pairs, 10 negative obesity-stereotypical–neutral word pairs, and 10 neutral–neutral word pairs. Word lists were matched for mean word length in terms of the total number of Chinese characters. The experiment was programmed in MATLAB R2017a using Psychophysics Toolbox 3.0 and conducted on a 27-inch LCD monitor (1920 × 1080 resolution, 120 Hz refresh rate) against a white background. Participants were seated comfortably in a dimly lit room approximately 80 cm from the screen. The experiment employed a dot-probe paradigm (Leng et al., 2024), as illustrated in Figure 1. Each trial began with a centrally presented fixation cross (0.25° × 0.25°), displayed for a randomized duration between 600 and 900 ms. This was followed by a word pair: either a positive obesity-stereotypical trait word paired with a neutral word, a negative obesity-stereotypical trait word paired with a neutral word, or two neutral words. The word pair was presented bilaterally (3.0° × 1.5°) for 250 ms. In each pair, one word appeared randomly on the left or right side, and the other was presented on the opposite side. After a 150 ms interstimulus interval, a probe pair consisting of two differently colored circles with notches (3.12° × 3.12°) appeared on both sides of the fixation cross for 150 ms. The probe circles were rendered in red (RGB: 255, 25, 84), blue (RGB: 77, 157, 67), or green (RGB: 77, 138, 238). Participants were instructed to identify the notch orientation (upward or downward) of the target-colored circle as quickly and accurately as possible by pressing the “K” or “L” key. The response key mapping was counterbalanced across participants. The probe display remained on screen until a response was made or 1350 ms had elapsed. In each block, one color was designated as the target color. A trial was classified as congruent if the target color appeared on the same side as an obesity-stereotypical trait word and incongruent if it appeared on the opposite side. Trials without the target color were classified as absent. For neutral word pairs, one word was randomly selected as the target for analysis, with congruency defined similarly, based on whether the target-colored probe appeared on the same or opposite side as the selected neutral word. The formal experiment consisted of 18 blocks, each comprising 80 trials. Each experimental condition, defined by a 3 (word type: positive, negative, neutral) × 3 (probe congruency: congruent, incongruent, absent) factorial design, comprised 144 trials. Additionally, a blank condition in which no probe pair was presented also included 144 trials. Fig. 1. Trial sequence of the dot-probe task. Each trial began with a fixation cross (600–900 ms), followed by a bilateral presentation of a word pair for 250 ms. The word pair consisted of either an obesity-stereotypical trait word paired with a neutral word, or two neutral words. After a 150 ms interstimulus interval, a pair of colored probe circles with notches appeared for 150 ms, with one circle designated as the target color for that block. Participants responded to the notch orientation of the target-colored circle. Trials were classified as congruent or incongruent based on whether the target-colored probe appeared on the same side as or opposite to the obesity-stereotypical trait word (or a randomly selected word in neutral pairs). Trials without the target-colored probe were classified as target-absent, and trials with no probe were labeled as blank. The probe display remained on screen until a response was made or 1350 ms had elapsed. 2.4. Behavioral analysis Trials with incorrect responses or response times (RTs) exceeding three standard deviations from the mean were excluded from the analysis. A three-way repeated-measures ANOVA was conducted with group (HWD vs. LWD) as a between-subjects factor, and word type (positive obesity-stereotypical, negative obesity-stereotypical, neutral) and probe congruency (congruent vs. incongruent) as within-subjects factors, to analyze both accuracy and RTs. EEG signals were recorded using a 64-channel Quik-Cap (NeuroScan, Inc.) based on a modified 10–10 system montage (Zhao et al., 2022). Horizontal and vertical electrooculograms (HEOG and VEOG) were recorded to monitor eye movements. Electrode impedances were kept below 5 kΩ. The EEG and EOG signals were amplified with a gain of 10,000, band-pass filtered between 0.05 and 100 Hz, and continuously digitized at a sampling rate of 1,000 Hz. EEG data preprocessing was conducted using MATLAB R2017a with the EEGLAB (Delorme & Makeig, 2004) and ERPLAB (Lopez-Calderon & Luck, 2014) toolboxes. The raw EEG data were downsampled to 500 Hz and re-referenced to the average of the left and right mastoids. A high-pass filter at 0.1 Hz and a low-pass filter at 30 Hz were applied. For the analysis of word stimuli, epochs were extracted from 100 ms to 400 ms after stimulus onset; for target stimuli, epochs ranged from 100 ms to 600 ms post-onset. Trials with voltages exceeding ± 80 μV were excluded to eliminate artifacts related to blinks, eye movements, and muscle activity. For each condition, average waveforms were computed from the remaining artifact-free trials for each participant. 2.5.1. ERPs to cue stimuli The N2pc and Pd components were measured using difference waves, calculated by subtracting the waveform from the hemisphere ipsilateral to the cue stimulus from the waveform from the hemisphere contralateral to the cue stimulus. Electrode site and time window selection were based on visual inspection of averaged waveforms and prior research. In line with previous studies, occipital electrodes (P7/P8 and PO7/PO8) and time windows of 240–290 ms for the N2pc component and 315–385 ms for the Pd component were selected (Holmes et al., 2014; Kerzel et al., 2018; Neumann et al., 2018). To analyze cue stimuli, mean amplitudes of the N2pc and Pd components for each condition were compared to 0 using one-sample t-tests to assess the presence of these components. A 2 (group: HWD vs. LWD) × 3 (word type: positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) ANOVA was conducted on N2pc and Pd mean amplitudes. 2.5.2. ERPs to target stimuli Prior to analyzing the target-elicited ERP data, ERPs from cue-only trials were subtracted to eliminate potential contamination from overlapping cue-related activity. This subtraction allowed for the isolation of target-specific ERP responses. For example, to obtain uncontaminated visual ERPs, the responses elicited by visual stimuli presented on the left were corrected by subtracting the corresponding ERPs from blank trials preceding those stimuli. Contralateral and ipsilateral ERP waveforms were computed by averaging correct trials across both target locations (left vs. right) and recording hemispheres (left vs. right), relative to stimulus position. For the analysis of target-elicited components, P7/P8 electrodes were used to extract P1 (110–140 ms) and N1 (175–205 ms), while C1/C2 and CP1/CP2 were selected for analyzing the P3 component within a 380–450 ms time window. Mean amplitudes for P1, N1, and P3 were subjected to a 3 (word type: positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) × 2 (probe congruency: congruent vs. incongruent) × 2 (group: HWD vs. LWD) repeated-measures ANOVA. Planned comparisons were conducted to test specific hypotheses (Cai et al., 2020; Leng et al., 2024; Righart & De Gelder, 2008). For P1 and N1, larger amplitudes for congruently cued targets relative to incongruently cued targets would indicate cue-driven attentional orienting in the HWD and/or LWD group (Leng et al., 2024; Zimmer et al., 2019). Conversely, larger P3 amplitudes for incongruently cued targets would suggest greater attentional reallocation to the uncued location (Liu et al., 2015). All statistical analyses were conducted using IBM SPSS Statistics 25.0. A significance threshold of p < 0.05 was applied throughout. When assumptions of sphericity were violated, the Greenhouse–Geisser correction was employed. Post-hoc comparisons were Bonferroni-adjusted to control for multiple testing. Effect sizes were reported as partial eta squared ( η² p ) for ANOVAs and Cohen’s d for t -tests. 3. Results 3.1. Behavioral analysis Accuracy was compared using three-way ANOVAs with the factors of group (HWD group vs. LWD group), word type (positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral), and probe congruency (congruent vs. incongruent). No significant main effects or interactions were observed for accuracy [word type: F (2, 96) = 0.61, p = 0.45, η² p = 0.01; group: F (1, 48) = 0.11, p = 0.75, η² p = 0.002; probe congruency: F (1, 48) = 1.70, p = 0.20, η² p = 0.03; word type × group: F (2, 96) = 0.72, p = 0.41, η² p = 0.02; probe congruency × group: F (1, 48) = 0.52, p = 0.47, η² p = 0.01; word type × probe congruency: F (2, 96) = 1.03, p = 0.32, η² p = 0.02; word type × group × probe congruency: F (2, 96) = 1.10, p = 0.30, η² p = 0.02]. The same three-way ANOVAs were conducted to analyze RTs. The results indicated a significant interaction between group and word type [ F (2, 96) = 4.20, p = 0.02, η² p = 0.08]. In the HWD group, the main effect of word type was significant [ F (2, 47) = 3.33, p = 0.04, η² p = 0.12], with RTs for negative obesity-stereotypical trait words (564.09 ± 52.21 ms) being significantly longer than those for neutral words (560.78 ± 50.31 ms) [ t (24) = 2.43, p = 0.02, d = 0.49]. However, RTs for positive obesity-stereotypical trait words (562.13 ± 52.40 ms) did not differ significantly from either of the other two word types [positive obesity-stereotypical vs. negative obesity-stereotypical: t (24) = -1.35, p = 0.19, d = -0.27; positive obesity-stereotypical vs. neutral: t (24) = 0.97, p = 0.34, d = 0.19]. The LWD group did not show this difference [ F (2, 47) = 2.10, p = 0.13, η² p = 0.08]. There were no significant main effects for group [ F (1, 48) = 1.94, p = 0.17, η² p = 0.04], word type [ F (2, 96) = 0.77, p = 0.46, η² p = 0.02], or probe congruency [ F (1, 48) = 2.75, p = 0.10, η² p = 0.05]. Additionally, no significant interactions were observed for group × probe congruency [ F (1, 48) = 0.75, p = 0.39, η² p = 0.02], word type × probe congruency [ F (2, 96) = 0.57, p = 0.57, η² p = 0.01], or group × word type × probe congruency [ F (2, 96) = 1.31, p = 0.28, η² p = 0.03]. 3.2. ERPs to cue stimuli 3.2.1. N2pc (240 – 290 ms) A one-sample t -test was conducted to compare the mean amplitudes of cue-elicited N2pc with zero for all word types, to determine whether a significant N2pc was elicited in both groups (see Fig. 2 and Fig. 3a). The results indicated that, in the HWD group, a significant N2pc was observed for both positive [ t (24) = -2.45, p = 0.02, d = -0.50] and negative obesity-stereotypical trait words [ t (24) = -4.69, p < 0.001, d = -0.96], but not for neutral words [ t (24) = -0.04, p = 0.97, d = -0.01]. In the LWD group, positive obesity-stereotypical trait words [ t (24) = -2.35, p = 0.03, d = -0.48] elicited a significant N2pc, while negative obesity-stereotypical trait words [ t (24) = -1.57, p = 0.13, d = -0.32] and neutral words [ t (24) = -0.35, p = 0.73, d = -0.07] did not. Furthermore, a 2 (group: HWD vs. LWD) × 3 (word type: positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) repeated-measures ANOVA on N2pc mean amplitudes revealed a significant main effect of word type [ F (2, 96) = 8.23, p = 0.001, η² p = 0.15]. Post hoc comparisons showed that both positive (-0.20 ± 0.41 μV) and negative obesity-stereotypical trait words (-0.28 ± 0.45 μV) elicited significantly larger N2pc amplitudes than neutral words (-0.01 ± 0.32 μV), while no significant difference was observed between positive and negative obesity-stereotypical trait words [positive obesity-stereotypical vs. negative obesity-stereotypical: 0.08 ± 0.07 μV (M ± SE, the same below); t (49) = 1.25, p = 0.22, d = 0.18; positive obesity-stereotypical vs. neutral: -0.19 ± 0.07 μV; t (49) = -2.81, p = 0.01, d = -0.40; negative obesity-stereotypical vs. neutral: -0.27 ± 0.08 μV; t (49) = -3.51, p < 0.001, d = -0.50]. Importantly, a significant interaction between word type and the group was found [ F (2, 96) = 4.31, p = 0.02, η² p = 0.08]. In the HWD group, the main effect of word type was significant [ F (2, 47) = 9.77, p < 0.001, η² p = 0.29]; specifically, negative obesity-stereotypical trait words (-0.46 ± 0.49 μV) elicited larger N2pc amplitudes compared to both positive obesity-stereotypical (-0.23 ± 0.46 μV) and neutral words (-0.002 ± 0.27 μV) [positive obesity-stereotypical vs. negative obesity-stereotypical: 0.23 ± 0.10 μV ( M ± SE , the same below); t (24) = 2.25, p = 0.03, d = 0.45; positive obesity-stereotypical vs. neutral: -0.22 ± 0.10 μV; t (24) = -2.40, p = 0.02, d = -0.48; negative obesity-stereotypical vs. neutral: -0.46 ± 0.12 μV; t (24) = -3.94, p < 0.001, d = -0.79]. In contrast, no significant differences in N2pc amplitudes across word types were found within the LWD group [ F (2, 47) = 1.19, p = 0.31, η² p = 0.05; positive obesity-stereotypical: -0.17 ± 0.37 μV; negative obesity-stereotypical: -0.12 ± 0.34 μV; neutral: -0.03 ± 0.37 μV]. Further analysis of the two-way interaction above in another direction revealed that only negative obesity-stereotypical trait words elicited larger N2pc amplitudes in the HWD group compared to the LWD group [HWD vs. LWD: -0.35 ± 0.12 μV ( M ± SE , the same below); t (48) = -2.97, p = 0.01, d = -0.84], with no significant differences observed for positive obesity-stereotypical or neutral words [HWD vs. LWD: -0.06 ± 0.12 μV; t (48) = -0.47, p = 0.64, d = -0.13] and neutral words [HWD vs. LWD: 0.02 ± 0.09 μV; t (48) = 0.26, p = 0.80, d = 0.07]. Additionally, no significant main effect of group was observed [ F (1, 48) = 2.72, p = 0.11, η² p = 0.05]. Fig. 2. Grand-averaged contralateral and ipsilateral waveforms, along with the difference waveforms (contralateral minus ipsilateral) for positive obesity-stereotypical, negative obesity-stereotypical, and neutral words at electrodes PO7/PO8 and P7/P8 for the HWD group (left) and the LWD group (right). The shaded areas represent the time windows for N2pc (240–290 ms) and Pd (315–385 ms). Fig. 3. Topographical distributions for positive obesity-stereotypical, negative obesity-stereotypical, and neutral words during the N2pc period (240–290 ms) and the Pd period (315–385 ms) for the HWD and LWD groups. The contralateral minus ipsilateral difference amplitudes are projected onto the right hemisphere. 3.2.2. Pd (315–385 ms) To determine whether a significant Pd was elicited (see Fig. 2 and Fig. 3b), one-sample t -tests were conducted to compare the average amplitudes of cue-elicited Pd with zero under three conditions. The results showed that, in the HWD group, a significant Pd was observed for negative obesity-stereotypical trait words [ t (24) = 2.24, p = 0.04, d = 0.46], but not for positive obesity-stereotypical trait words [ t (24) = 0.27, p = 0.79, d = 0.05] or neutral words [ t (24) = -0.31, p = 0.76, d = -0.06]. In the LWD group, positive [ t (24) = -0.60, p = 0.56, d = -0.12] and negative [ t (24) = 1.61, p = 0.12, d = 0.33] obesity-stereotypical trait words, as well as neutral words [ t (24) = -1.94, p = 0.07, d = -0.40], did not elicit a significant Pd. Furthermore, a 2 (group: HWD vs. LWD) × 3 (word type: positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) repeated-measures ANOVA for Pd mean amplitudes showed a significant main effect of word type [ F (2, 96) = 5.55, p = 0.01, η² p = 0.10]. Post hoc comparisons showed that negative obesity-stereotypical trait words (0.15 ± 0.40 μV) elicited significantly larger Pd amplitudes than neutral words (-0.07 ± 0.28 μV). However, no significant differences were found between positive obesity-stereotypical trait words (-0.01 ± 0.42 μV) and either negative obesity-stereotypical trait words or neutral words [positive obesity-stereotypical vs. negative obesity-stereotypical: -0.16 ± 0.07 μV ( M ± SE , the same below); t (49) = -2.49, p = 0.02, d = -0.35; positive obesity-stereotypical vs. neutral: 0.06 ± 0.07 μV; t (49) = 0.83, p = 0.41, d = 0.12; negative obesity-stereotypical vs. neutral: 0.22 ± 0.07 μV; t (49) = 3.21, p = 0.002, d = 0.45]. There was no significant main effect for group [ F (1, 48) = 0.77, p = 0.39, η² p = 0.02], nor was there a significant interaction between word type and group [ F (2, 96) = 0.24, p = 0.79, η² p = 0.01]. 3.3. ERPs to probe stimuli 3.3.1. P1 (110–140 ms) A 3 (word type: positive obesity-stereotypical vs. negative obesity-stereotypical vs. neutral) × 2 (probe congruency: congruent vs. incongruent) × 2 (group: HWD vs. LWD) repeated-measures ANOVA on target-elicited P1 amplitudes revealed no significant main effects [word type: F (2, 96) = 0.89, p = 0.42, η² p = 0.02; probe congruency: F (1, 48) = 0.29, p = 0.59, η² p = 0.01; group: F (1, 48) = 1.07, p = 0.31, η² p = 0.02] or interactions [word type × probe congruency: F (2, 96) = 0.50, p = 0.59, η² p = 0.01; word type × group: F (2, 96) = 0.75, p = 0.48, η² p = 0.02; probe congruency × group: F (1, 48) = 0.16, p = 0.70, η² p = 0.003; word type × probe congruency × group: F (2, 96) = 0.64, p = 0.51, η² p = 0.01]. Planned comparisons tested the hypothesis that P1 amplitudes would be significantly larger for congruently cued targets compared to incongruently cued targets, depending on whether cue-induced attentional orienting occurred in the HWD or LWD group. Results showed no significant difference in P1 amplitudes between congruent and incongruent conditions for the HWD group, regardless of the preceding word type [positive obesity-stereotypical trait words: F (1, 24) = 0.03, p = 0.87, η² p = 0.001; negative obesity-stereotypical trait words: F (1, 24) = 3.27, p = 0.08, η² p = 0.12; neutral words: F (1, 24) = 0.12, p = 0.74, η² p = 0.01]. Similarly, for the LWD group, there was no significant difference in P1 amplitudes for target stimuli preceded by the three types of words between the congruent and incongruent conditions [positive obesity-stereotypical trait words: F (1, 24) = 0.01, p = 0.93, η² p < 0.001; negative obesity-stereotypical trait words: F (1, 24) < 0.001, p = 0.98, η² p < 0.001; neutral words: F (1, 24) = 0.01, p = 0.91, η² p = 0.001]. 3.3.2. N1 (175–205 ms) The target-elicited N1 amplitudes were analyzed using the same three-way repeated-measures ANOVA, which revealed no significant main effects [word type: F (2, 96) = 0.65, p = 0.53, η² p = 0.01; probe congruency: F (1, 48) = 1.25, p = 0.27, η² p = 0.03; group: F (1, 48) = 2.38, p = 0.13, η² p = 0.05] or interactions observed [word type × probe congruency: F (2, 96) = 0.47, p = 0.62, η² p = 0.01; word type × group: F (2, 96) = 1.38, p = 0.26, η² p = 0.03; probe congruency × group: F (1, 48) = 0.004, p = 0.95, η² p < 0.001; word type × probe congruency × group: F (2, 96) = 0.97, p = 0.38, η² p = 0.02]. Planned comparisons, consistent with the P1 analysis, indicated no significant differences in N1 amplitudes for visual targets preceded by any of the three word types in either congruent or incongruent trials for both the HWD and LWD groups [positive obesity-stereotypical trait words: F (1, 24) = 1.73, p = 0.20, η² p = 0.07; negative obesity-stereotypical trait words: F (1, 24) = 0.32, p = 0.58, η² p = 0.01; neutral words: F (1, 24) = 0.21, p = 0.65, η² p = 0.01] and the LWD group [positive obesity-stereotypical trait words: F (1, 24) = 0.01, p = 0.94, η² p < 0.001; negative obesity-stereotypical trait words: F (1, 24) = 0.13, p = 0.73, η² p = 0.01; neutral words: F (1, 24) = 1.64, p = 0.21, η² p = 0.06]. 3.3.3. P3 (380–450 ms) The target-elicited P3 amplitudes (see Fig. 4) were analyzed using the same three-way repeated-measures ANOVA, which revealed no significant main effects [word type: F (2, 96) = 1.41, p = 0.25, η² p = 0.03; probe congruency: F (1, 48) = 2.23, p = 0.14, η² p = 0.04; group: F (1, 48) = 0.29, p = 0.60, η² p = 0.01] or interactions [word type × probe congruency: F (2, 96) = 0.74, p = 0.48, η² p = 0.02; word type × group: F (2, 96) = 0.36, p = 0.67, η² p = 0.01; probe congruency × group: F (1, 48) = 1.04, p = 0.31, η² p = 0.02; word type × probe congruency × group: F (2, 96) = 1.03, p = 0.36, η² p = 0.02]. Planned comparisons were conducted to test the hypothesis that the P3 amplitudes would be larger at the incongruent location compared to the congruent location if the HWD or LWD group allocated more attentional resources to the location opposite the cue stimuli. Results indicated that, in the HWD group, visual targets preceded by negative obesity-stereotypical trait words elicited significantly larger P3 amplitudes under the incongruent condition (6.12 ± 4.21 μV) compared to the congruent condition (5.44 ± 4.52 μV) [ F (1, 24) = 5.00, p = 0.04, η² p = 0.17]. However, this difference was not observed for the other two word types [positive obesity-stereotypical trait words: F (1, 24) = 0.01, p = 0.92, η² p < 0.001; neutral words: F (1, 24) = 0.60, p = 0.45, η² p = 0.02]. In contrast, in the LWD group, no significant differences in P3 amplitudes were found for visual targets preceded by any of the three word types between congruent and incongruent conditions [positive obesity-stereotypical trait words: F (1, 24) = 0.36, p = 0.55, η² p = 0.02; negative obesity-stereotypical trait words: F (1, 24) = 0.03, p = 0.86, η² p = 0.001; neutral words: F (1, 24) = 0.02, p = 0.90, η² p = 0.001]. Fig. 4. ERP waveforms elicited by target stimuli preceded by three word types are shown under congruent and incongruent conditions for the HWD group (left) and the LWD group (right). Waveforms were recorded from C1/C2 and CP1/CP2 electrodes, contralateral to the stimulus location. Topographical distributions of target stimuli preceded by the three word types (positive obesity-stereotypical, negative obesity-stereotypical, and neutral words) are presented for the 380–450 ms time window under both congruent and incongruent conditions for the HWD and LWD groups. 4. Discussion Using a dot-probe paradigm combined with ERP techniques, the present study investigated the temporal dynamics of attentional bias toward both negative and positive obesity stereotypes in females with HWD. The ERP results showed that positive obesity-stereotypical trait words elicited a significant N2pc in both the HWD and LWD groups, reflecting early attentional orienting toward positive obesity stereotypes. In contrast, negative obesity-stereotypical trait words elicited a significant N2pc in the HWD group, but not in the LWD group. More importantly, N2pc amplitudes in response to negative obesity-stereotypical trait words were significantly larger in the HWD group than in the LWD group, suggesting enhanced attentional allocation toward negative obesity stereotypes in females with HWD. At a later processing stage, only negative obesity-stereotypical trait words elicited a significant Pd in the HWD group, indicating active suppression of negative obesity stereotypes. In the present study, attentional biases toward obesity stereotypes were not detected by RTs in either the HWD or LWD group. Previous studies have used behavioral measures to detect attentional biases for emotional stimuli (Kappenman et al., 2015; Puls & Rothermund, 2018). One potential explanation for these findings is that behavioral measures typically assess responses to a separate target presented several hundred milliseconds after the cue word, which may not adequately reflect the initial stages of attentional processing. Instead, these measures are more likely to capture attentional bias during the later stages of target processing (Kappenman et al., 2015; Moussally et al., 2016). Furthermore, Leng et al. (2024) attributed this non-significant result to the short presentation duration (200 ms), which may have prevented participants from allocating sufficient cognitive resources to process the word stimuli. In the present study, we extended the word presentation duration to 250 ms and included a 200 ms interstimulus interval (ISI), resulting in an SOA of 450 ms (comparable to the 500 ms SOA used by Moussally et al., 2016). However, this extended duration may still have been insufficient for effective processing of the word stimuli. Consequently, no attentional bias was observed at the behavioral level during the later stages of target processing. The ERP findings indicated that positive obesity-stereotypical trait words elicited a significant N2pc component in both groups. The N2pc component is associated with attentional orientation, with larger N2pc amplitudes reflecting enhanced attention toward specific stimuli (Kerzel et al., 2018; Wieser et al., 2018). The attentional bias toward positive obesity-stereotypical trait words observed in the present study is consistent with evidence showing that humans are highly sensitive to threatening cues and also rapidly orient toward rewarding or affirming information (Vuilleumier, 2005; Brosch et al., 2011). From an evolutionary perspective, positive stimuli often signal opportunities for reward, affiliation, or resource acquisition, all of which are crucial for long-term adaptation and well-being (Berridge & Kringelbach, 2008). At the neurocognitive level, such stimuli activate the reward system, including the amygdala and dopaminergic pathways (Murray, 2007), thereby enhancing early perceptual processing and increasing the likelihood of attentional capture. Importantly, meta-analytic findings suggest that this bias is strongest when positive stimuli are relevant to an individual’s current concerns or motivational states, such as self-affirmation or social belonging (Pool et al., 2016). In the present study, positive obesity-stereotypical trait words, such as “genuine” and “easygoing,” represent desirable qualities and were therefore likely to capture attention in both groups. These findings suggest a general mechanism whereby positive, socially meaningful information preferentially captures attention, irrespective of weight dissatisfaction. In contrast, negative obesity-stereotypical trait words elicited larger N2pc amplitudes compared to both positive obesity-stereotypical and neutral words in the HWD group. Additionally, the N2pc amplitudes for negative obesity-stereotypical trait words were larger in the HWD group than in the LWD group. These N2pc results suggest that females with HWD show enhanced attentional orienting toward negative obesity stereotypes. According to cognitive-behavioral theory (Vitousek & Hollon, 1990), females with body dissatisfaction exhibit heightened sensitivity to body-related cognitive content (e.g., obesity). When they habitually attend to such information, corresponding schemas are activated, facilitating the processing of schema-consistent information. This study further reveals that obesity-related stereotypical information, even without explicit weight-related meanings, can activate schema-related semantic associations in individuals with negative body self-image. Such activation leads females with HWD to overestimate the salience of negative obesity stereotypes—stimuli strongly associated with obesity—and consequently prioritize the allocation of attentional resources (Williamson et al., 2004). Rodgers and DuBois (2016) pointed out that word stimuli may resemble an individual’s internal dialogue and be interpreted as self-relevant information. For females with HWD, negative obesity stereotypes are not only external societal labels but may also activate their internal negative self-schemas. They may interpret negative obesity stereotype words as self-relevant evaluative information, internalizing them as external negative judgments about themselves, which enhances the subjective perception of such information. As a result, negative obesity stereotype information rapidly captures the attention of females with HWD. At a later stage, only negative obesity-stereotypical trait words elicited a significant Pd component in the HWD group. The Pd component has been identified as indicative of attentional suppression of lateral visual stimuli (Kerzel et al., 2018; Neumann et al., 2018). These results suggest that, following the initial attentional orientation, only negative obesity stereotypes were actively suppressed in the HWD group. This inference is supported by the finding that target stimuli preceded by negative obesity-stereotypical trait words elicited significantly larger P3 amplitudes in the incongruent condition compared to the congruent condition, but only in the HWD group, not the LWD group. The P3 component has been shown to serve as an index of location expectancy in spatial attention tasks (Mangun & Hillyard, 1991) and is linked to the voluntary orienting of attention (Polich, 2007; Zhang et al., 2014). For example, Liu et al. (2015) employed a dot-probe task to investigate the attentional modulation of disgust compared to anger. Their results indicated that P3 amplitudes were larger for invalid angry cues than for valid cues, suggesting that when the target did not appear at the location of the angry cue, participants needed more cognitive resources to disengage their attention from the anger-related cue and focus on the target. These results suggest that, following initial attentional orientation, only the HWD group actively suppressed attention to negative obesity-stereotypical words. Under the influence of contemporary societal beauty standards, women across different weight statuses tend to internalize weight-related biases. Empirical studies have shown that higher levels of body dissatisfaction are associated with greater endorsement of negative weight-related labels and stereotypes (Bennett et al., 2022; Purton et al., 2019; Romano et al., 2021), as well as increased experiences of negative emotions such as anxiety and depression (Macho et al., 2023). According to the vigilance-avoidance hypothesis (Mogg et al., 1997), anxious individuals typically show heightened initial vigilance toward threatening stimuli, followed by cognitive avoidance strategies to alleviate negative emotions (e.g., anxiety) and avoid detailed processing of the threatening information. Thus, for females with HWD, negative obesity-stereotypical information functions as a threatening stimulus that rapidly captures attention at an early stage. Subsequently, they may use attentional avoidance strategies to reduce the negative emotions triggered by obesity-related stereotypes. The findings suggest that females with HWD exhibit enhanced attentional capture and suppression toward negative obesity-stereotypical traits, indicating attentional biases not only toward weight-related information but also toward obesity stereotype information. This addresses a gap in the body image literature. Importantly, the results extend the applicability of cognitive-behavioral models (Vitousek & Hollon, 1990; Williamson et al., 2004) to nonclinical populations. According to these models, individuals with eating disorders develop a dense network linking ”fatness” to personal flaws. In this study, such maladaptive schemas may similarly increase the accessibility of negative obesity-stereotypical trait words for females with HWD, thereby intensifying their attentional engagement with these task-irrelevant negative obesity stereotypes. Furthermore, the findings highlight the critical role of negative valence in the attentional processing of obesity stereotypes among females with HWD. Cognitive-behavioral interventions aimed at reducing weight dissatisfaction could benefit from strategies that redirect attention away from the negative aspects of obesity stereotypes. 5. Conclusion In summary, this study is the first to investigate the mechanisms underlying the attentional processing of obesity stereotypes in females with high weight dissatisfaction. The results revealed that both positive and negative obesity stereotypes initially captured attention, but only negative obesity stereotypes were actively suppressed in females with high weight dissatisfaction. These findings offer new insights into cognitive-behavioral models of body image disturbance and suggest potential intervention strategies for alleviating weight dissatisfaction. Funding acknowledgment The current study was supported by the National Key Research and Development Program of China (2021ZD0202600 to W.F.F.), the National Natural Science Foundation of China (32171048 to W.F.F.), and the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX23_3200 to X.C.L). Conflict of interest All authors claim that there is no conflict of interest. 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ERP-study on the time course of disgust-motivated spatial avoidance. Biological Psychology , 144 , 20–27. https://doi.org/10.1016/j.biopsycho.2019.02.007 Supplementary Material File (fig4.eps) Download 10.68 MB Information & Authors Information Version history V1 Version 1 20 November 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Jiayi Yao 0009-0001-3001-2163 Soochow University School of Education Department of Psychology View all articles by this author Jing Gao Soochow University School of Education Department of Psychology View all articles by this author Xuechen Leng Soochow University School of Education Department of Psychology View all articles by this author Xiaocui Yu Soochow University School of Education Department of Psychology View all articles by this author Ting Wang Soochow University School of Education Department of Psychology View all articles by this author Chengzhi Feng Soochow University School of Education Department of Psychology View all articles by this author Wenfeng Feng 0000-0002-7664-5863 [email protected] Soochow University School of Education Department of Psychology View all articles by this author Metrics & Citations Metrics Article Usage 142 views 71 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jiayi Yao, Jing Gao, Xuechen Leng, et al. 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