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“Out of sight out of mind”: attentional characteristics in mothers who have children with autism

BMC Women's Health volume 25, Article number: 53 (2025) Cite this article

Abstract

Background

Families are faced with enormous challenges in caring for children with autism spectrum disorder (ASD) over a lifetime. As the main caregiver of children, mothers who have children with autism are in poor health compared to the mothers of typically developing (TD) children. Previous studies have revealed that the mental health of mothers has a direct impact on children. On the other hand, attention bias (AB) can be an important indicator of the mental status. Therefore, the characteristic of AB of mothers who have children with autism can be a window into the treatment of autism.

Methods

In this study, 28 mothers who have children with autism and 31 mothers of typically developing children completed the modified dot-probe task to explore the attention bias.

Results

We found that there was a significant difference of AB between mothers who have children with autism and mothers of typically developing children, which indicated that mothers who have children with autism tend to avoid negative emotional words.

Conclusions

The current study illuminates the attentional characteristics of mothers who have children with autism toward emotional words, which provides a new starting point for the intervention of mothers of children with autism.

Peer Review reports

Introduction

Autism spectrum disorder (ASD) is defined as a widespread developmental disorder disease caused by nervous system developmental disorder [20]. Statistically, ASD has developed from extremely rare diseases in the past to more common developmental disorders, ranking the first in the mental and developmental disorders of children [55]. Early diagnosis can receive earlier behavior-based intervention, leading to the improvements in core areas, such as social functioning and communication [39]. As we know, parents have a dynamic influence on the growth and development potential of children [11]. Thus, child- parent interaction therapy especially the positive affect of parents can effectively reduce children's behavioral problems and increase their adaptability [53]. With the increased dramatically in recent decades [2], caring for a child with ASD is challenging and play a vital role in children's rehabilitation training [44].

The majority of mothers in China engage in two actions against the backdrop of traditional culture: producing and parenting [59], this responsibility is greater in families with children with disabilities [63]. As mothers who have children with autism [24], they usually spend at least 2 h more than mothers of typically developing children to care for their children [52]. Previous results showed that parents who have children with autism have more mental health problems than parents of typically developing or other disabled children [25], especially mothers [8, 40]. As we know, the mental health of mothers have important impact on the rehabilitation of children. Therefore, paying attention to the mothers who have children with autism is of great significance to their children’s rehabilitation.

Attention bias (AB), which refers to the selective processing of a specific type or class of information that has particular relevance to an individual [15, 33]. Previous studies have shown that AB to positive stimuli is thought to be a resilience factor of mental health and well-being [10]. Conversely, negative AB is identified as a risk factor for the onset and persistence of psychological issues [56]. During the dot-probe task, the individual attentional bias indices are calculated by subtracting reaction times (RTs) on congruent trials from RTs on incongruent trials [32, 54]. A positive attentional bias score indicates attending to the threatening stimulus. A negative attentional bias index score indicates avoidance of threat (zero = no bias) [27, 35]. The more cognitive engagement in a particular stimulus, the stronger the AB [30]. For instance, individual attention processing continuously allocates a greater proportion of attention resources to real or experimentally induced threat stimuli [23]. Compared with the neutral stimuli, AB appears when individual shows abnormal attention to negative stimuli [1].

Previous studies have found that people with mental problems such as addicted and users of social media with negative emotions had AB to negative faces [21] and negative emotional words [62] by using the modified dot-probe task. Recently, a study found that parents of children with autism did not exhibit an attentional bias towards sad faces [29]. As we know, the arousal of emotional pictures (e.g.faces) and words are different from each other [6, 26]. Unfortunately, the characteristic of AB in mothers who have children with autism is still unknown. Therefore, we explored the characteristic of attention in mothers of children with autism to emotional words by completing a modified dot-probe task. We hypothesized that mothers of children with autism might have an AB toward negative words.

Method

Participants and recruitment

Participants were recruited through advertisements posted on social media and visited in communities, kindergartens, primary schools and special education institutions. A total of 287 mothers of children with special needs and 324 mothers of typically developing children were interviewed, excluding other mothers of children with special needs, 51 mothers of children with autism and 66 mothers of typically developing children were willing to participate in the experiment. For personal reasons, 7 mothers of children with autism and 21 mothers of typically developing children told us they could not carry out the experiment before the experiment. Besides, 16 mothers of children with autism and 14 mothers of typically developing children were excluded from the study during the study doing due to they could not complete the experiment in a quiet room without their children. Only 32 mothers of children with autism and 31 mothers of typically developing children completed the whole experiment. Because the AQ questionnaire involves age, only 28 mothers of children with autism and 31 mothers of typically developing children were included in the analysis. The age of the subjects in the two groups ranged from 30 to 47 years old (M = 35.407, SD = 3.761), and there was no significant difference between the two groups (t = −0.648, p > 0.05). All participants were right-handed, with typically developing or corrected vision and no color blindness, excluding organic diseases and psychological diseases, and the first language is Chinese.

Procedure

The study was approved by a university and all subjects signed the informed consent form. All participants completed the demographic variables and questionnaires, and then completed the modified dot-probe task.

Dot-probe task

Participants were seated in front of a monitor and informed that they would be presented with a series of pairs of words presented side-by-side on the screen, and that one word would disappear to be replaced by a black dot. At the beginning of each trial a central fixation cross would be presented for 500 ms, immediately followed by a word pair for 1500 ms. After words offset, the dot probe appeared at the location of either the right or the left picture and remained on screen until the participant pressed one of the response keys: the “F” (left) or “J” (right) keys on the keyboard, when the presentation time of the detection point reaches 2000 ms at the longest. Participants were instructed that they should indicate the dot position as quickly as possible without compromising accuracy. After a valid response there was a 500 ms interval, then the fixation cross of the next trial was presented (Fig. 1).

Fig. 1
figure 1

Experimental procedures

Full size image

Before the formal experiment, the subjects need to complete 10 trial to familiarize themselves with the experimental procedures, and the correct rate reaches 100% in the practice stage before entering the formal experiment. The formal experiment includes 30 pairs of positive neutral words and 30 pairs of negative neutral words. In order to balance the order effect and the position of the detection point, each word pair appears twice, and each word appears four times, with a total of 240 trial, which are randomly presented.

Materials

The Autism Spectrum Quotient: Children’s version (AQ-Child)

It was compiled by Baron-Cohen in 2008, which is a questionnaire for parents' evaluation and is suitable for autism screening of children aged 4–11 [3]. The scale is divided into five dimensions, with a total of 50 items, and each item is scored by 0 ~ 3 points and 4 grades. The total score of the scale is 0 ~ 150 points. The higher the total score, the more severe the autism symptoms are. AQ Children's Edition-Chinese Edition was revised by mental health professionals of children and adolescents in Peking University Sixth Hospital. Cronbach α coefficient of the whole scale is 0. 94, and Cronbach α coefficient of five subscales is 0. 69 ~ 0.89, which shows that the scale has good internal consistency [28].

The Chinese Attention to Positive and Negative Inventory (APNI)

It is a revision of the English version of Noguchi (2006), which is used to evaluate the individual's attention to positive and negative information in life [9]. It consists of 22 items, which are divided into positive information attention subscale (API) and negative information attention subscale (ANI). The scale is graded from 1 (completely inconsistent) to 5 (completely consistent). The higher the API score, the more obvious the positive attention bias, and the higher the ANI score, the more obvious the negative attention bias. The internal consistency coefficients of the two subscales are 0.84 and 0.72, respectively.

The Beck Depression Inventory-II of Chinese version (BDI-II-C)

This scale is used to evaluate the severity of depressive symptoms in the past two weeks [22]. It contains 21 items, each of which has a score of 0 ~ 3. The total score of the scale is the sum of the scores of 21 items, with a total score ranging from 0 to 63. According to the original scale of Beck, the total score of 0 ~ 13 is no depression, 14 ~ 19 is mild depression, 20 ~ 28 is moderate depression and 29 ~ 63 is severe depression [5].

Chinese Affective Words System (CAWS)

From the Chinese affective words system (CAWS) [60] selected 30 positive, 30 negative and 30 neutral words, each of which includes 10 verbs, 10 nouns and 10 adjectives. Such as “绝望” (juéwàng: desperation),“机场” (jīchǎng: airport) and “赞叹” (zàntàn: praise). Valence, arousal and familiarity were evaluated on a Likert 9- point scale. The three categories of words differ significantly in terms of valence and arousal, but not in terms of familiarity, and the word frequencies, strokes and speech are equal. Results indicated significantly higher valence of positive words relative to neutral s and negative words, significantly higher valence of neutral words relative to negative words, and significantly higher arousal of positive and negative words relative to neutral ones.

Plan of analysis

First of all, the correct rate of the formal experiment of the two groups was analyzed, and the correct rate of each group was above 95%, and there was no significant difference between the two groups (p > 0.05).

Before the formal analysis, the data were sorted out, and the data with reaction time less than 200 ms and more than 1200 ms were excluded to reduce the possibility of interference with the experimental results [38]. Then, the data were further screened to remove the data except the three standard deviations, and all the data with reaction errors and no response were deleted [41, 51]. After finishing the preliminary arrangement of the data, SPSS 20.0 was used for statistical analysis. Firstly, the difference test was carried out on the questionnaire data of the two groups, then the difference test was carried out on the behavioral data of the two groups according to the AB index.

Results

Questionnaire difference

As can be seen from Table 1, there were significant differences between the two groups in the AQ questionnaire, which shows that the autistic characteristics of children with autism are significantly higher than those of typically developing children; there was a significant difference in depression scores between the two groups, indicating that the level of depression of mothers who have children with autism was significantly higher than that of mothers of typically developing children; there was no significant difference in positive and negative information attention scale.

Table 1 Difference test (M ± SD) between the two groups in each questionnaire
Full size table

Difference analysis of AB index

To determine the difference of AB between the two groups, we conducted a 2(group: mothers of children with autism or control group of typically developing children) × 2 (emotional words: negative or positive) ANOVA (see Table 2). The results show that there is interaction between groups and emotional words (F = 7.267, p < 0.05, η2p = 0.113), and the main effects of groups and emotional words are not significant (F = 0.230, p > 0.05, η2p = 0.004; F = 0.151, p > 0.05, η2p = 0.003).

Table 2 Summary of ANOVA results for AB scores
Full size table

Furthermore, the simple effect analysis (see Fig. 2) showed that the AB index of negative words of children with autism 's mothers is significantly lower than that of typically developing children's mothers (F = 4.527, p < 0.05), and it is also significantly lower than that of positive words (F = 6.651, p < 0.05). There is no significant difference between typically developing children's mothers in the AB index of positive words and negative words (F = 2.804, p > 0.05).

Fig. 2
figure 2

Interaction effect between groups and emotional words

Full size image

The AB indices of the two groups were substituted into a single-sample t-test respectively to make a comparison with 0. The results showed that the AB index of mothers who have children with autism was significantly lower than 0, and there was no significant difference between the indices of AB of mothers who have children with autism and 0(t = −2.471, p < 0.05; t = 0.599, p > 0.05). There is no significant difference between the indices of AB of typically developing children's mothers to negative emotional words and positive emotional words and 0(t = 1.010, p > 0.05; t = −1.558, p > 0.05). Results indicated that mothers of children with autism avoid negative emotional words.

Discussion

The current study explored the attentional characteristics in mothers of children with autism with a modified dot-probe task. We found that mothers who have children with autism showed no attentional bias toward either positive or negative information in the questionnaire, while they tended to avoid negative emotional words in the dot-probe task. Self-reporting always presents a limitation because of possible bias in subjective evaluations (Shenaar‐Golan, 2015). AB toward positive and negative information was self-reported, and so may be confounded by response-biases [45].

In contrast to our initial hypotheses, we found that mothers of children with autism tended to avoid negative words. In this study, mothers who have children with autism are more depressed than mothers of typically developing children, which is consistent with the results of He 's research [19]. Niedenthal (1994) believed that an individual's emotional state is consistent with their cognitive orientation. When processing external information, individuals have a tendency to process information that is consistent with their current emotional state [64]. It has been found that individuals exhibit AB toward negative stimuli when in a state of negative emotional priming [12]. However, this study did not assess the emotional state of the mothers who have children with autism before the experiment began, nor did it trigger their negative emotions. Future research could benefit significantly from assessing the emotional state of the mothers prior to the experiment, in order to ensure that both groups of mothers maintain a consistent emotional state throughout the study.

The observed attentional avoidance at 1500 ms stimulus presentation is in line with the findings by Mogg (2004). The 1500 ms used in this study is a longer stimulus presentation time. Attention avoidance was observed when the stimulus presentation lasted for a long time, but it was not observed when the stimulus presentation lasted for a short or medium time [16, 31, 48, 58]. Avoidance hypothesis held that individuals are inclined to focus more on information related to threats, and in order to maintain psychological stability, they often avoid negative stimuli to reduce the cognitive processing of negative stimuli [34]. Whether avoidance occurs, may critically depend upon the intensity of threat. If the threat value is low, individuals may not feel the need to avert their attention from the stimulus. It is possible that only stimuli with high threat value will elicit attentional avoidance [27]. Compared with mothers of typically developing children, mothers of children with autism were more depressed. This suggested that negative emotional words could constitute a significant-threat stimulus for mothers of children with autism. When the stimuli were presented for an extended period, subjects had sufficient time to visually switch between the two messages. After initially noticing the higher threat message, mothers of children with autism employed avoidance strategies to reduce tension. In addition, presentations of the same stimulus may have expedited the identification of the threatening stimulus, which could have facilitated attentional avoidance [27]. In this study, each word is repeated four times, which may cause attention avoidance.

Experience avoidance (EA) refers to people's attempts to control or change the form, frequency, or sensitivity to situations in which their internal experiences occur in their minds [18]. It is the practice of avoiding negative internal experiences [4]. Avoidance coping is additionally associated with negative psychological outcomes [46]. Studies have shown, EA could be an important factor contributing to depression in patients with mental disorders [49]. And Tull pointed out EA accounted for a greater proportion of the unique variance in depression [57]. Meanwhile, the advent of language exponentially increases the number of potential cues for danger, and a human may become motivated to avoid not only external cues of actual danger, but also symbolic representations of that aversive experience [7]. Decoding the emotional value of words takes time [47]. According to acceptance and commitment therapy (ACT) theory, human language and cognitive abilities help people to make evaluations, predictions, and avoidance of danger in the external world [61]. Mothers of children with autism a higher depression compared to mothers of typically developing children in our research. When faced with negative emotional words for a long time, they can recognize negative emotions in words and adopt experiential avoidance strategy to avoid being in danger. Furthermore, according to Gross's emotional regulation model, situation selection refers to approaching or avoiding certain people, places, or objects in order to regulate emotions [17]. In the face of dangerous situations, mothers of children with autism may take avoid measures to cope with their negative emotions. Thus, mothers who have children with autism avoid negative emotional words after observing them because the stimulus were appeared repeatedly for a long time. This is known as "out of sight, out of mind," and it helps them avoid bad emotions.

Limitations

Even though we are the first study to explore the characteristics of attention in mothers of children with autism, there are still some limitations in our study. Firstly, the study was cross-sectional in nature and did not follow individuals over time. Therefore, the findings are uncertain as to whether the AB of mothers who have children with autism will change with time. Longitudinal study can be used to examine the change of AB with time in the future, or neuroimaging technology can be used to understand the potential neural mechanism. Secondly, a prominent idea about attentional processing of threat is the “vigilance–avoidance” pattern. Individuals initially attend to threat, but this is often followed by attentional avoidance of threat [34, 37]. In this study, it is impossible to determine whether the mothers of children with autism are alert to negative words at first. In the future, we can set a variety of stimulus presentation times to explore the AB of mothers of children with autism to negative emotional words in different time processes. Moreover, the dot-probe results cannot discern whether the AB indicates faster initial orienting to negative emotional words and/or difficulties disengaging from negative emotional words; as such, future research could include a neutral condition (i.e., trials in which neutral stimulus appears at both locations) to distinguish these effects. Finally, compared with traditional behavioral experiments, eye movement tasks are not as easily affected by factors such as distraction and inhibition of behavioral responses. In addition, brain-imaging techniques such as ERP and fMRI can be introduced in future research to study the characteristics of AB of mothers who children with autism from a physiological point of view.

Conclusion

Despite these limitations, the current study illuminates the important result that mothers of children with autism tend to avoid negative emotional words. This demonstrated that mothers may not be able to confront their negative emotions and choose to avoid them as a means of self-protection. When a threatening stimulus does not require immediate responding, attentional avoidance may be a strategy to maintain goal-directed behavior [13, 36] or to regulate mood [14]. However, attentional avoidance may lead to a short-term inhibition of fear and anxiety, but may—ironically—lead to more fear and anxiety in the long term. In the future, mothers of children with autism can be provided with guidance to confront their negative emotions and adopt reasonable methods for emotional regulation, so as to improve their AB and improve their mental health. This study provides a new perspective for the intervention of mothers of children with autism and for creating a good family atmosphere for promoting children's rehabilitation.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

ASD:

Autism spectrum disorder

TD:

Typically developing

AB:

Attention bias

EA:

Experience avoidance

ACT:

Acceptance and commitment therapy

References

  1. Abado E, Richter T, & Okon-Singer H. Attention bias toward negative stimuli. In Cognitive Biases in Health and Psychiatric Disorders. 2020; (pp. 19–40). https://doiorg.publicaciones.saludcastillayleon.es/10.1016/b978-0-12-816660-4.00002-7

  2. Allison C, Baron-Cohen S, Bolton P, Brayne C, Matthews FE, Scott FJ, Williams J. Prevalence of autism-spectrum conditions: UK school-based population study. Br J Psychiatry. 2009;194(6):500–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1192/bjp.bp.108.059345.

    Article  PubMed  Google Scholar 

  3. Auyeung B, Baron-Cohen S, Wheelwright S, Allison C. The Autism Spectrum Quotient: Children’s Version (AQ-Child). J Autism Dev Disord. 2008;38(7):1230–40. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10803-007-0504-z.

    Article  PubMed  Google Scholar 

  4. Baldour-Wang M, Kotov R, Gámez W, Chmielewski M, Ruggero CJ, Eaton NR. The structure of experiential avoidance and external validity: An investigation of the multidimensional experiential avoidance Questionnaire. J Psychopathol Behav Assess. 2024. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10862-024-10159-8.

    Article  Google Scholar 

  5. Beck AT, Steer RA, Ball R, Ranieri W. Comparison of Beck Depression Inventories-IA and -II in psychiatric outpatients. J Pers Assess. 1996;67(3):588–97. https://doiorg.publicaciones.saludcastillayleon.es/10.1207/s15327752jpa6703_13.

    Article  CAS  PubMed  Google Scholar 

  6. Carretié L, Hinojosa JA, Albert J, López-Martín S, De La Gándara BS, Igoa JM, Sotillo M. Modulation of ongoing cognitive processes by emotionally intense words. Psychophysiology. 2008;45(2):188–96. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1469-8986.2007.00617.x.

    Article  PubMed  Google Scholar 

  7. Chawla N, Ostafin B. Experiential avoidance as a functional dimensional approach to psychopathology: An empirical review. J Clin Psychol. 2007;63(9):871–90. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/jclp.20400.

    Article  PubMed  Google Scholar 

  8. Dabrowska A, Pisula E. Parenting stress and coping styles in mothers and fathers of pre-school children with autism and Down syndrome. J Intellect Disabil Res. 2010;54(3):266–80. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1365-2788.2010.01258.x.

    Article  CAS  PubMed  Google Scholar 

  9. Dai Q, Feng Z, Xu S. Validity and reliability of the Chinese Attention to Positive and Negative Inventory in college students. Chin Ment Health J. 2015;29(05):395–400.

    Google Scholar 

  10. David OA, and Magurean S. Positive attention bias trained during the rethink therapeutic online game and related improvements in children and adolescents’ mental health. Children. 2022; 9(11). https://doiorg.publicaciones.saludcastillayleon.es/10.3390/children9111600

  11. Denhoff E. The Impact of parents on the growth of exceptional children. Except Child. 1960;26(5):271–4. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/001440296002600507.

    Article  Google Scholar 

  12. Eastwood JD, Smilek D, Merikle PM. Differential attentional guidance by unattended faces expressing positive and negative emotion. Percept Psychophys. 2001;63(6):1004–13. https://doiorg.publicaciones.saludcastillayleon.es/10.3758/bf03194519.

    Article  CAS  PubMed  Google Scholar 

  13. Eccleston C, Crombez G. Pain demands attention: a cognitive-affective model of the interruptive function of pain. Psychol Bull. 1999;125(3):356–66. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0033-2909.125.3.356.

    Article  CAS  PubMed  Google Scholar 

  14. Ellenbogen MA, Schwartzman AE, Stewart J, Walker CD. Stress and selective attention: the interplay of mood, cortisol levels, and emotional information processing. Psychophysiology. 2002;39(6):723–32. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/1469-8986.3960723.

    Article  PubMed  Google Scholar 

  15. Gao X, Wang Q, Jackson T, Zhao G, Liang Y, Chen H. Biases in orienting and maintenance of attention among weight dissatisfied women: An eye-movement study. Behav Res Ther. 2011;49(4):252–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.brat.2011.01.009.

    Article  PubMed  Google Scholar 

  16. Garner M, Mogg K, Bradley BP. Orienting and maintenance of gaze to facial expressions in social anxiety. J Abnorm Psychol. 2006;115(4):760–70. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0021-843x.115.4.760.

    Article  PubMed  Google Scholar 

  17. Gross JJ. The emerging field of emotion regulation: An integrative review. Rev Gen Psychol. 1998;2(3):271–99. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/1089-2680.2.3.271.

    Article  Google Scholar 

  18. Hayes SC, Wilson KG, Gifford EV, Follette VM, et, a. Experiential avoidance and behavioral disorders: A functional dimensional approach to diagnosis and treatment. J Consult Clin Psychol. 1996;64(6):1152–68. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0022-006x.64.6.1152.

    Article  CAS  PubMed  Google Scholar 

  19. He L, Zhou C, and  Li H. Correlation between coping style and mental health of the autism children's parents. Chin J Child Health Care. 2015; 23(09):937–939+946. https://link.cnki.net/urlid/61.1346.r.20150714.1633.004

  20. Hodges H, Fealko C, and Soares N. Autism spectrum disorder: definition, epidemiology, causes, and clinical evaluation. Transl Pediatrics. 2020; 9(S1): S55-S65. https://doiorg.publicaciones.saludcastillayleon.es/10.21037/tp.2019.09.09

  21. Hu Y, Guo J, Jou M, Zhou S, Wang D, Maguire P, . . . Qu F. Investigating the attentional bias and information processing mechanism of mobile phone addicts towards emotional information. Computers in Human Behavior. 2020; 110. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.chb.2020.106378

  22. Jiang S, and Yang W. Factor structure of the Beck Depression Inventory-II of Chinese version among Chinese undergraduates. Chin J Clin Psychol. 2020; 28(2):299–305. https://doiorg.publicaciones.saludcastillayleon.es/10.16128/j.cnki.1005-3611.2020.02.017

  23. Joyal M, Wensing T, Levasseur-Moreau J, Leblond JT, Sack A, & Fecteau S. Characterizing emotional Stroop interference in posttraumatic stress disorder, major depression and anxiety disorders: A systematic review and meta-analysis. Plos One. 2019; 14(4). https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0214998

  24. Kaji N, Ando S, Nishida A, Yamasaki S, Kuwabara H, Kanehara A, . . . Kasai K. Children with special health care needs and mothers' anxiety/depression: Findings from the Tokyo Teen Cohort study. Psychiatry Clin Neurosci. 2021; 75(12):394–400. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/pcn.13301

  25. Kasari C, Sigman M. Linking parental perceptions to interactions in young children with autism. J Autism Dev Disord. 1997;27(1):39–57. https://doiorg.publicaciones.saludcastillayleon.es/10.1023/a:1025869105208.

    Article  CAS  PubMed  Google Scholar 

  26. Keil A. Macroscopic brain dynamics during verbal and pictorial processing of affective stimuli. In S. Anders, G. Ende, M. Junghofer, J. Kissler, & D. Wildgruber (Eds.), Progress in Brain Research (Vol. 156, pp. 217–232). 2006. Elsevier. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0079-6123(06)56011-X

  27. Koster EHW, Verschuere B, Crombez G, Van Damme S. Time-course of attention for threatening pictures in high and low trait anxiety. Behav Res Ther. 2005;43(8):1087–98. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.brat.2004.08.004.

    Article  PubMed  Google Scholar 

  28. Li H, Liu J, Jia M, Yang L, Li X, Zhang A, and Pang J. Reliability and validity of the Chinese version of Autism Spectrum Quotient-Children's version. Chin Mental Health J. 2018; 32(12):1000–1005. https://link.cnki.net/urlid/11.1873.r.20181126.1820.014

  29. Lovell B, McCarty K, Penfold P. and Wetherell MA. Clinically elevated depression scores do not produce negative attentional biases in caregivers of autistic children. Front Psychiatry. 2023; 14. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyt.2023.1192669

  30. Lucion MK, Oliveira V, Bizarro L, Bischoff AR, Silveira PP, Kauer-Sant’Anna M. Attentional bias toward infant faces – Review of the adaptive and clinical relevance. Int J Psychophysiol. 2017;114:1–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ijpsycho.2017.01.008.

    Article  PubMed  Google Scholar 

  31. Lyu Z, Zheng P, and Wang Z. Time course of attentional biases toward body shapes in women who are overweight or obese. Cognitive Therapy and Research. 2018; 43. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10608-018-9978-6

  32. MacLeod C, Mathews A. Anxiety and the allocation of attention to threat. The Quarterly Journal of Experimental Psychology Section A. 1988;40(4):653–70. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/14640748808402292.

    Article  CAS  Google Scholar 

  33. MacLeod C, Mathews A, Tata P. Attentional bias in emotional disorders. J Abnorm Psychol. 1986;95(1):15–20. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/0021-843x.95.1.15.

    Article  CAS  PubMed  Google Scholar 

  34. Mathews A. Why worry? The cognitive function of anxiety. Behav Res Ther. 1990;28(6):455–68. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/0005-7967(90)90132-3.

    Article  CAS  PubMed  Google Scholar 

  35. Mogg K, Bradley B, Miles F, Dixon R. BRIEF REPORT Time course of attentional bias for threat scenes: Testing the vigilance-avoidance hypothesis. Cogn Emot. 2004;18(5):689–700. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02699930341000158.

    Article  Google Scholar 

  36. Mogg K, Bradley BP. A cognitive-motivational analysis of anxiety. Behav Res Ther. 1998;36(9):809–48. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/s0005-7967(98)00063-1.

    Article  CAS  PubMed  Google Scholar 

  37. Mogg K, Mathews A, Weinman JJ. Memory bias in clinical anxiety. J Psychopathol Clin Sci. 1987;96(2):94–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1037//0021-843x.96.2.94.

  38. Mogg K, Wilson KA, Hayward C, Cunning D, Bradley BP. Attentional biases for threat in at-risk daughters and mothers with lifetime panic disorder. J Abnorm Psychol. 2012;121(4):852–62. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/a0028052.

    Article  PubMed  Google Scholar 

  39. Montes G, Halterman JS. Psychological functioning and coping among mothers of children with autism: A population-based study. Pediatrics. 2007;119(5):e1040–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1542/peds.2006-2819.

    Article  PubMed  Google Scholar 

  40. Nahar S, Zambelli Z, Halstead EJ. Risk and protective factors associated with maternal mental health in mothers of children with autism spectrum disorder. Res Dev Disabil. 2022;131: 104362. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ridd.2022.104362.

    Article  PubMed  Google Scholar 

  41. Nie Y, Liu L, Zeng Y, Ning Z. The Influence of moral self-control on altruistic tendencies: A study of attention bias. Studies of Psychology and Behavior. 2015;13(05):678–83.

    Google Scholar 

  42. Niedenthal PM, Setterlund MB. Emotion congruence in perception. Pers Soc Psychol Bull. 1994;20(4):401–11. https://doiorg.publicaciones.saludcastillayleon.es/10.1177/0146167294204007.

    Article  Google Scholar 

  43. Noguchi K, Gohm CL, Dalsky DJ. Cognitive tendencies of focusing on positive and negative information. J Res Pers. 2006;40(6):891–910. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jrp.2005.09.008.

    Article  Google Scholar 

  44. Patel S, Rivard M, Mello C, and Morin D. Parenting stress within mother-father dyads raising a young child with autism spectrum disorder. Research in Autism Spectrum Disorders. 2022; 99. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.rasd.2022.102051

  45. Peltz JS, Rogge RD, O’Connor TG. Adolescent sleep quality mediates family chaos and adolescent mental health: A daily diary-based study. J Fam Psychol. 2019;33(3):259–69. https://doiorg.publicaciones.saludcastillayleon.es/10.1037/fam0000491.

    Article  PubMed  Google Scholar 

  46. Penley JA, Tomaka J, Wiebe JS. The association of coping to physical and psychological health outcomes: A meta-analytic review. J Behav Med. 2002;25(6):551–603. https://doiorg.publicaciones.saludcastillayleon.es/10.1023/a:1020641400589.

    Article  PubMed  Google Scholar 

  47. Raccuglia RA, Phaf RH. Asymmetric affective evaluation of words and faces. Br J Psychol. 2011;88(1):93–116. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.2044-8295.1997.tb02623.x.

    Article  Google Scholar 

  48. Rohner J-C. The time-course of visual threat processing: High trait anxious individuals eventually avert their gaze from angry faces. Cogn Emot. 2002;16(6):837–44. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02699930143000572.

    Article  Google Scholar 

  49. Rueda B and Valls E. Relationships among stress, experiential avoidance and depression in psychiatric patients. Span J Psychol. 2016; 19. https://doiorg.publicaciones.saludcastillayleon.es/10.1017/sjp.2016.32

  50. Shenaar-Golan V. Hope and subjective well-being among parents of children with special needs. Child Fam Soc Work. 2015;22(1):306–16. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/cfs.12241.

    Article  Google Scholar 

  51. Shi Y, Luo Y. Characteristics of attention bias to baby face in college students. Chin Ment Health J. 2016;30(05):378–83.

    Google Scholar 

  52. Smith LE, Hong J, Seltzer MM, Greenberg JS, Almeida DM, Bishop SL. Daily experiences among mothers of adolescents and adults with autism spectrum disorder. J Autism Dev Disord. 2010;40(2):167–78. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10803-009-0844-y.

    Article  PubMed  Google Scholar 

  53. Solomon M, Ono M, Timmer S, Goodlin-Jones B. The effectiveness of parent–child interaction therapy for families of children on the autism spectrum. J Autism Dev Disord. 2008;38(9):1767–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s10803-008-0567-5.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Stevens ES, Behar E and Siev J. The roles of disgust sensitivity and anxiety sensitivity in attentional bias in dental anxiety. J Anxiety Disord. 2021; 83. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.janxdis.2021.102450

  55. Sun, Y. r., Han, Y., & Cao, F. (2016). Emotional resiliency of parents of children with autism. China Journal of Health Psychology, 24(02), 292–296. https://doiorg.publicaciones.saludcastillayleon.es/10.13342/j.cnki.cjhp.2016.02.035

  56. Trapp W, Kalzendorf C, Baum C, Hajak G, Lautenbacher S. Attentional biases in patients suffering from unipolar depression: results of a dot probe task investigation. Psychiatry Res. 2018;261:325–31. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.psychres.2018.01.005.

    Article  PubMed  Google Scholar 

  57. Tull MT, Gratz KL, Salters K, Roemer L. The role of experiential avoidance in posttraumatic stress symptoms and symptoms of depression, anxiety, and somatization. Journal of Nervous & Mental Disease. 2004;192(11):754–61. https://doiorg.publicaciones.saludcastillayleon.es/10.1097/01.nmd.0000144694.30121.89.

    Article  Google Scholar 

  58. Wang J and Huang Y. Approach–Avoidance pattern of attentional bias in individuals with high tendencies toward problematic Internet pornography use. Front Psychiatry. 2022; 13. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fpsyt.2022.988435

  59. Wang R. Reflection on the studies of mother in modern China. History Research and Teaching. 2020. (01):33–39+165.

  60. Wang Y, Zhou L and Luo Y. The pilot establishent and evaluation of Chinese Affective Words System. Chin Mental Health J. 2008; (08): 608–612.

  61. Zhang Q, Wang S, Zhu Z. Acceptance and commitment therapy ( ACT): Psychopathological model and processes of change. Chin Ment Health J. 2012;26(05):377–81.

    CAS  Google Scholar 

  62. Zhao J, Zhou Z, Sun B, Zhang X, Zhang L and Fu S. Attentional bias is associated with negative emotions in problematic users of social media as measured by a dot-probe task. Int J Environ Res Public Health. 2022; 19(24). https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijerph192416938

  63. Zheng H, Hong M, lv J, Qiu F, Li A and Xia C. Current situation analysis of care support needs in children with disabilities: from a comprehensive rehabili‐tation perspective. Chin J Rehabil Theory Practice. 2021; 27(10): 1117–1126. https://link.cnki.net/urlid/11.3759.R.20211026.1433.002

  64. Zhu S and Zheng X. Effects of affective priming on attentional bias induced by short film. Psychological Science. 2009; 32(02):327–330. https://doiorg.publicaciones.saludcastillayleon.es/10.16719/j.cnki.1671-6981.2009.02.010

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Funding

This research was supported by Chongqing Social Science Planning and Cultivation Project(2020PY61)、General Project of Chongqing Natural Science Foundation (CSTB2024NSCQ-MSX1101), General Project of Chongqing Natural Science Foundation (CSTB2023NSCQ-MSX0431), Humanities and Social Sciences Research Project of Chongqing Municipal Education Commission(21SKGH026) and General Project of Humanities and Social Sciences Research of Chongqing Municipal Education Commission (22SKGH113).

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Authors and Affiliations

  1. School of Educational Sciences, Chongqing Normal University, Chongqing, China

    Xue Du, Shuanghong Gao, Ting Huang & Jian Liang

  2. Key Laboratory of Applied Psychology, Chongqing Normal University, Chongqing, China

    Xue Du, Shuanghong Gao, Ting Huang & Jian Liang

  3. College of Public Health, Chongqing Medical University, Chongqing, China

    Xiao Xiao

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Contributions

X.D. and S. Gao. contributed to the conception of the study, design, analysis, interpretation of the data and write-up of the manuscript. X.D., S. Gao., T.H. and J.L. were involved in editing and revising the manuscript. X.D. and X.X. provided funding acquisition. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Xue Du or Xiao Xiao.

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This study was conducted in accordance with the declaration of Helsinki and in accordance with the South African Good Clinical Practice guidelines. Ethical approval for this study was obtained from the Ethical Committee of Institute of Psychology, Chongqing Normal University (CNU-PSY-202209–023). All the participants have been informed and signed informed consent before the experiments.

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Du, X., Gao, S., Huang, T. et al. “Out of sight out of mind”: attentional characteristics in mothers who have children with autism. BMC Women's Health 25, 53 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12905-024-03534-w

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BMC Women's Health

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