Patterns of attentional biases in children and emotional symptoms during the COVID-19 pandemic: a two-wave longitudinal study

doi:10.21203/rs.3.rs-2313188/v1

Background. It is unknown how the patterns of negative and positive attentional biases in children predict fear of COVID-19, anxiety, and depression during the COVID-19 pandemic. The study identified profiles of negative and positive attentional biases in children and examined their association with emotional symptoms during the COVID-19 pandemic.

Method. 322 children were involved in a two-wave longitudinal study. Children completed the self-report assessment of fear of COVID-19, anxiety, depression, and attention to positive and negative information in classrooms. After six months, they completed the second assessment of fear of COVID-19, anxiety, and depression in classrooms.

Results. Higher fear of COVID-19 was related to higher anxiety and depression throughout the assessment period. Three profiles of negative and positive attentional biases were revealed in children. Children with a “moderate positive and high negative attentional biases” profile had significantly higher fear of COVID-19 pandemic, anxiety, and depression than children with a “high positive and moderate negative attentional biases” profile. Children with a “low positive and negative attentional biases” profile were not significantly different in fear of COVID-19, anxiety, and depression than those with the other two profiles.

Conclusions. Patterns of negative and positive attentional biases were related to emotional symptoms during the COVID-19 pandemic. It might be important to consider children's overall patterns of negative and positive attentional biases to identify children at risk of higher emotional symptoms.

Latent profiles

attentional bias

anxiety

depression

fear of COVID-19

children

The COVID-19 pandemic has led to an increase in the rate of emotional symptoms among children (Nazish, Zeshan, & Pervaiz, 2020). Previous research demonstrated increased fear of COVID-19 pandemic and hightened anxiety and depression symptoms in children during the COVID-19 pandemic (Nimphy, Elzinga, Van der Does, & Aktar, 2022; Yue, Zang, Le, & An, 2022). Based on the cognitive models, the tendency to attend to threatening or awarding information is one of the cognitive styles, contributing to emotional symptoms, including fear, anxiety, and depression symptoms (Clauss et al., 2022; Williams, 1997). Although research has demonstrated that low positive attentional bias and high negative attentional bias are risk factors underlying the emotional problems during the COVID-19 pandemic, there are insufficient studies that take a holistic approach and investigate individual differences in their patterns of attending to positive and negative information. Without a holistic perspective, it is unknown if a person who is high in both positive and higher negative attentional biases develops higher or lower emotional symptoms than a person who is low in both positive and lower negative attentional biases. Longitudinal studies that examine how the profiles of attentional preferences affect emotional symptoms during the COVID-19 pandemic are particularly scarce. Considering the importance of attentional bias in children’s development of internalizing symptoms, more research might be needed to investigate how children’s overall patterns of attentional biases are related to the development of fear, anxiety, and depression during the COVID-19 pandemic.

To address these research gaps, the present study aimed to reveal profiles of attentional biases and to examine how these profiles were associated with the development of fear of COVID-19, anxiety, and depression in children during the COVID-19 pandemic.

Attentional Bias and Internalizing Symptoms

Attentional bias refers to the cognitive tendency to shift attention toward negative or positive stimuli (Karin Mogg & Bradley, 2018). Based on the cognitive models, negative attentional bias is the vulnerability factor for the development of anxiety and depression in children (Karin. Mogg & Bradley, 2016; Williams, 1997). Research recruited 1291 children worldwide and assessed their negative attentional bias through behavioral tasks (Abend et al., 2018). The study revealed a significant positive association between negative attentional bias and anxiety symptoms. The association between negative attentional bias and depression was also positive in children (Hankin, Gibb, Abela, & Flory, 2010; Maalouf et al., 2012; Salum et al., 2013). Another study that measured positive attentional bias in children of 7 to 17 years by the eye-tracking technique found that compared to non-anxious children, anxious children had lower attention toward positive information (Gamble & Rapee, 2009). For depression, a meta-analysis involving 16 studies found that depressed people had impaired positive attentional bias (Suslow et al., 2020). A longitudinal study showed that low positive attentional bias measured by spatial orienting tasks might cause increased depression and anxiety symptoms for adolescents of 16 years (Vrijen, Hartman, & Oldehinkel, 2019). For negative attentional bias, a longitudinal study revealed that high negative attentional bias measured by the self-report inventory predicted the developmental trajectories of high anxiety in children of 9 to 11 years over three years (Ho, Zhang, Lai, & Dai, 2021). Interventions that reduce negative attentional bias, including attentional bias modification, have shown efficacy in relieving anxiety and depression symptoms in children and adolescents (Krejtz, Holas, Rusanowska, & Nezlek, 2018; Kress & Aue, 2019; McDermott & Dozois, 2015). This evidence further supported that high negative attentional bias might affect high anxiety and depression symptoms.

During the COVID-19 pandemic, children have experienced increased fear of COVID-19 infection (Jefsen, Rohde, Nørremark, & Østergaard, 2020). A meta-analysis has suggested that higher attention toward threats was related to higher fear-related symptoms (Clauss et al., 2022). Thus, attentional bias toward threats might also be related to higher fear of COVID-19. Moreover, a longitudinal study on individuals who experienced lockdown due to the COVID-19 pandemic in Italy found that higher attention toward COVID-related threatening stimuli was associated with higher health anxiety (Cannito et al., 2020). Higher attention toward COVID-19-related stimuli was associated with higher COVID-19 anxiety syndrome (Albery, Spada, & Nikčević, 2021). Therefore, research on attentional bias during the COVID-19 pandemic might provide important implications for identifying children who are more likely to show stronger fear of COVID-19, anxiety, and depression during the COVID-19 pandemic.

Profiles of Negative and Positive Attentional Biases

Profiles of negative and positive attentional biases depicted overall patterns of attentional preferences to negative and positive stimuli. Although negative attentional bias might be the opposite of positive attentional bias in terms of the affective valence of preferred stimuli, people might have low negative attentional bias and low positive attentional bias simultaneously. The presence of high negative and high positive attentional biases might predict lower emotional symptoms than those with high negative and low positive attentional biases. For example, a study has shown that attentional bias toward threats was linked to high self-report anxiety only in individuals with a tendency to attend away from positive information (Wei, Roodenrys, & Miller, 2021). Latent profile analysis is a person-centered statistical approach that is commonly used to reveal heterogeneous groups of people with common patterns of external or internal behavior (Perzow, Bray, Wadsworth, Young, & Hankin, 2021). A cross-sectional study assessed attentional biases by self-report inventories in inpatients of 60 to 90 years and revealed four distinct profiles of positive and negative attentional biases with latent profile analysis (Ji et al., 2022). The four profiles consisted of “no positive and negative bias” which included 9.3% of participants, “minor positive bias & no negative bias” (48.0%), “major positive bias & minor negative bias” (25.6%), and “major positive bias & no negative bias” (17.1%). The “no positive and negative bias” and the “minor positive bias & no negative bias” groups had higher depression symptoms than the “major positive bias & no negative bias” group, suggesting that high positive attentional bias was a protective factor buffering depression symptoms. However, it is unclear if the results can be replicated in children during the COVID-19 pandemic. Moreover, the study is cross-sectional, which has limited ability to imply causality. Thus, more longitudinal research on children’s profiles of attentional biases is needed to understand how profiles of attentional bias affect fear of COVID-19, depression, and anxiety during the COVID-19 pandemic.

The Current Study

The current research recruited a sample of children from a primary school to reveal the relationship of profiles of attentional biases to fear of COVID-19, anxiety and depression during the COVID-19 pandemic. Based on the previous evidence, distinct profiles of attentional biases would be revealed which might include profiles of “low negative and positive attentional bias”, “low negative and high positive attentional bias”, “high negative and low positive attentional bias” and “high negative and positive attentional bias”. Compared to the “high negative and positive attentional bias” profile, the “low negative attentional bias and high positive attentional bias” profile would predict low fear, anxiety and depression symptoms during the COVID-19 pandemic. While compared to the “low negative and positive attentional bias” profile, the “high negative attentional bias and low positive attentional bias” profile would be related to more fear, anxiety and depression symptoms in children during the COVID-19 pandemic.

Participants

The study recruited a sample of middle-class 322 children from a primary school in Shenzhen, PRC. Regarding gender distribution, 53.8% (N=171) of participants were girls, and 46.2% (N=147) were boys; three participants did not indicate their gender. The average age of the sample was 9.54 years, ranging from 9 to 11 years (SD = .505 years). Exclusion criteria were 1) not able to fluently speak and understand simplified Chinese, 2) having a diagnosis of psychological disorders, and 3) birthplace outside of mainland China. Children who failed to complete one of the self-report assessments were excluded from the research. As a result, data from 264 children (N_boys=124 and N_girls=138) were input into analyses.

Procedure

The study was conducted from November 16^th to November 30^th, 2020, when the COVID-19 pandemic was ongoing. The prevention measures, including social distancing, were implemented during the period. Teachers in the primary school helped researchers disseminate informed consent forms and assent forms to parents and students. The signed informed consent and assent forms were collected one day before the date of data collection in the classrooms. Only children who signed the assent forms and obtained the signed informed consent forms from their parents participated in the study. On the data collection date, research assistants assigned a set of questionnaires to students during classes. The participants were informed that they could ask questions and withdraw from the study at any time without any consequence. At time one, students completed a set of questionnaires for children to assess their negative and positive attentional biases, fear of COVID-19, anxiety, and depression for approximately 45 minutes in the classrooms. After approximately six months, students completed the questionnaire to assess their fear of COVID-19, anxiety, and depression at time two in the classrooms for approximately 45 minutes. In each assessment, a teacher and researcher were present to answer students’ questions and ensure safety of students.

Measurement

Negative and Positive Attentional Biases

The eight-item brief version of the Attention to Positive and Negative Information Scale (brief APNIS) was administered to children (Chan, Ho, Tedeschi, & Leung, 2011; Noguchi, Gohm, & Dalsky, 2006). The scale had good structural validity. Refer to Appendix for the exploratory factor and confirmatory factor analysis of the scale. The internal consistency in the current study was satisfactory (API=.69; ANI=.76). Also, the scale showed good current validity as ANI and API had significant associations with anxiety and depression symptoms at T1 and T2 (Refer to Table 2). The scale was consisted of an Attention to Negative Information subscale (ANI; four items) and an Attention to Positive Information (API; four items) subscale, rated on a five point Likert scale. A negative attentional bias score was calculated by summing up scores from the ANI subscale. A positive attentional bias score was obtained by adding scores from the API subscale. Higher scores indicated higher attentional biases.

Emotional Symptoms

Anxiety and depression. The Chinese version of the Revised Child Anxiety and Depression Scale (Chorpita, Yim, Moffitt, Umemoto, & Francis, 2000) was used to measure children’s anxiety and depression symptoms. The Chinese version could be downloaded from the website (http://www.childfirst.ucla.edu/Resources.html). RCADS is a wildly used scale for childhood anxiety and depression. The 47 items of the scale can be grouped into the Anxiety Disorders and the Major Depression Disorder sub-scales, rated on a Likert scale from 0 to 3 (0 = “never”; 1 = “sometimes”; 2 = “often”; and 3 = “always”). The scale of Anxiety Disorders has 37 items (e.g., “afraid of looking foolish in front of people”), and the scale of Major Depressive Disorder includes 10 items (MDD; “feels nothing is much fun anymore”). An anxiety score and a depression score were calculated by summing up scores of the relevant items on the subscales of the Anxiety Disorder Symptoms and the Major Depression Symptoms, respectively. The scales showed excellent reliability with the current data (Time one: Anxiety Disorder Cronbach’s Alpha=. 95; Major Depression Disorder Cronbach’s Alpha=.88; Time two: Anxiety Disorder Cronbach’s Alpha=. 96; Major Depression Disorder Cronbach’s Alpha=.88).

Fear of COVID-19. Fear of COVID-19 was measured by the COVID-19 Fear Scale (CFS). CFS was adapted from the Chinese version of the 18-item SARS Fear Scale (SFS; Ho, Kwong-Lo, Mak, & Wong, 2005). Participants were asked to rate on a 4-point Likert scale how much the statement is true in the face of the COVID-19 pandemic. 0 indicates "definitely false" and 3 indicates "definitely true." The sample item includes "Fear that I will be infected." Three items were excluded from CFS ("Worry if I will be assigned to COVID-19 wards", "Feel distressed because of the upsurge in workload," and "Worry if my family or friends will keep a distance from me due to my job duties") because of their inapplicability to students. A CFS score was obtained by summing up scores from each item. The higher the CFS scores, the higher the fear of COVID-19. The scale demonstrated good internal consistency in the current study (T1 Cronbach's α=.94; T2 Cronbach's α=.95).

Data Analysis

Descriptive statistics were presented. Two-tailed Pearson’s partial correlation was investigated using SPSS version 22 to understand the association among psychological variables. Independent t-tests examined the gender differences in the psychological variables. Latent profile analyses were subsequently conducted to reveal profiles of negative and positive attentional biases in children with MPlus 7.4. With maximum likelihood estimation with robust standard error (MLR), heterogeneous profiles of attentional biases were revealed. The number of groups for the model was increased until the model was not significantly better than the model with one fewer group. Smaller values of the Bayesian Information Criterion (BIC) and Akaike information criteria (AIC), as well as the higher value of entropy, suggested a better model fit (Kline, 2005). The significant p values of the Vuong–Lo–Mendell–Rubin likelihood ratio test (VLMR), the adjusted Lo–Mendell–Rubin likelihood ratio test (Adj. LMR), as well as the Bootstrapped Likelihood ratio test (BLRT) showed that a model with k number of groups was significantly better than a model with k-1 groups (Kline, 2005). Next, Chi-Square analyses assessed if groups with distinct profiles of attentional biases differed in gender, age, and birthplace. Two repeated multivariate analyses of variance (MANOVA) were conducted to examine the effect of time, profiles of negative and positive attentional biases, as well as the interaction between profiles and time on anxiety and depression symptoms over 6 months. The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Descriptive Statistics

An independent t-test was performed with 262 participants to examine the difference between girls and boys in positive and negative attentional biases, fear of COVID-19, depression, and anxiety assessed at time one (T1) and time two (T2). Results revealed that girls and boys didn’t significantly differ in negative attentional bias, t (260)= 1.48, p=.14, positive attentional bias, t (260)=-.04, p=.97, and depression symptoms at T1, t (260)=1.41, p=.16 . Girls showed significantly higher anxiety symptoms at T1, t (260)= 3.13, p<.005, higher anxiety symptoms at T2, t (260)= 2.92, p<.005, and higher depression symptoms at T2, t (260)= 2.17, p<.05, than did boys. Also, girls were significantly higher in fear of COVID-19 at T1, t (257)= 2.12, p<.05, than were boys. Girls were significantly higher in fear of COVID-19 at T2, t (256)= 2.92, p<.005. Refer to Table 1for the means and standard deviations of each variable by gender.

The Pearson’s partial correlation, controlling for gender revealed that age was not significantly associated with positive attentional bias, r=-.01, p=.82, negative attentional bias, r=.04, p=.57, anxiety at T1, r=-.04, p=.52, depression at T1, r=-.03, p=.61, anxiety at T2, r=-.03, p=.60, and depression at T2, r=-.02, p=.76.

Higher anxiety symptoms at T1 and T2 were significantly related to higher depression at T1 and T2. They were also significantly associated with higher negative and lower positive attentional biases. Depression at T1 and T2 was positively and significantly associated with negative attentional bias; depression at T1 and T2 was negatively and significantly related to positive attentional bias. Higher fear of COVID-19 at T1 and T2 was associated with significantly higher anxiety and depression symptoms at T1 and T2. Also, higher fear of COVID-19 at T1 and T2 was significantly related to higher negative attentional bias. Higher fear of COVID-19 at T1 was significantly associated with lower positive attentional bias. Higher fear of COVID-19 at T2 was not significantly related to lower positive attentional bias. Higher anxiety at T1 was significantly related to higher anxiety at T2; higher depression at T1 was significantly related to higher depression at T2. Fear of COVID-19 at T1 was significantly related to higher fear of COVID-19 at T2. Negative attentional bias was not significantly associated with positive attentional bias. Refer to Table 2 for correlation coefficients.

(Insert Table 1 around here)

Profiles of Negative and Positive Attentional Biases at T1

The fit indices for models with one to five groups were examined with a latent profile analysis (refer to S.Table 1 in Supplementary Information for fit indices). The three-class model had the smallest BIC and AIC. The VLMR, Adj.LMR and BLRT tests were all significant for the three-class model. All p values of VLMR, Adj. LMR and BLRT were insignificant for the four-class model, which suggested that the four-class model was not significantly better than the three-group model. Thus, the three-class model showed the best model fit.

Class one had the lowest level of negative and positive attentional biases, and was named as “low positive and negative attentional biases” profile (4.3%). Class two had the highest positive attentional bias and moderate negative attentional bias, which was accordingly defined as the “high positive and moderate negative attentional biases” profile (38.5%). Class three had a moderate positive attentional bias and high negative attentional bias, which was named the “moderate positive and high negative attentional biases” profile (57.2%). Fig.1 shows the means of negative and positive attentional biases of the three profiles. The three classes were not significantly different in terms of gender, χ²(2) = .23, p = .89, birthplace, χ²(2) = 1.14, p = .57, and age, χ²(2) = 1.24, p = .54.

(Insert Figure 1 around here)

The Relationship of Profiles of Attentional Biases to Emotional Symptoms

Anxiety

A repeated MANOVA was performed to examine the between-subject effect of profiles and the within-subject effect of time, as well as the interaction effect between profiles and time on anxiety symptoms. Results suggested the within-subject effect of time was insignificant. The interaction between time and profiles was also insignificant. The between-subject effect of profiles on anxiety was significant. The Scheffe post hoc test showed that children with a “moderate positive and high negative attentional biases” profile had significantly higher anxiety symptoms than children with a “high positive and moderate negative attentional biases” profile. Children with a “low positive and negative attentional biases” profile were not significantly different in anxiety level from children with the other two profiles (refer to Table 2).

Depression

A repeated MANOVA for depression symptoms revealed an insignificant with-in-subject effect of time and an interaction effect of time and profiles. The between-subject effect of profiles was significant. The Scheffe post hoc test showed that children with a “moderate positive and high negative attentional biases” profile had significantly higher depression symptoms than children with a “high positive and moderate negative attentional biases” profile. Children with a “low positive and negative attentional biases” profile were not significantly different in depression symptoms from children with the other two profiles (refer to Table 2).

Fear of COVID-19

With the fear of COVID-19 as the dependent variable and patterns of attentional biases as the independent variable, a repeated MANOVA demonstrated a significant with-in-subject effect of time; fear of COVID-19 significantly increased from T1 to T2. The interaction effect of time and profiles was insignificant. The between-subject effect of profiles was significant. The Scheffe post hoc test showed that children with a “moderate positive and high negative attentional biases” profile demonstrated significantly higher fear of COVID-19 than children with a “high positive and moderate negative attentional biases” profile. Children with a “low positive and negative attentional biases” profile didn’t significantly differ in fear of COVID-19 from children with “moderate positive and high negative attentional biases” and “high positive and moderate negative attentional biases” (refer to Table 2).

(Insert Table 2 around here)

The study revealed three profiles of attentional biases that depicted the overall patterns of attention to negative and positive information in children’s daily life: “low positive and negative attentional biases” profile (4.3%), “high positive and moderate negative attentional biases” profile (38.5%), and “moderate positive and high negative attentional biases” profile (57.2%). Profiles of attentional biases showed a significant relationship with emotional symptoms over six months during the COVID-19 pandemic; the “moderate positive and high negative attentional biases” profile was related to significantly higher anxiety and depression symptoms than “high positive and moderate negative attentional biases” profile. The “low positive and negative attentional biases” profile was not significantly different from the other two profiles in emotional symptoms.

The Patterns Of Positive And Negative Attentional Biases

The current study revealed three profiles of positive and negative attentional biases in children during the COVID-19 pandemic. Over half of the children showed a “moderate positive and high negative attentional biases” profile, and only a small number of children had a “low positive and negative attentional biases” profile. Consistent with previous research, most children’s attentional bias towards negative stimuli tended to be moderate or high during the COVID-19 pandemic (e.g., Cannito et al., 2020). The results also added that the majority of children had a moderate or high attention to positive stimuli during the COVID-19 pandemic.

These results were inconsistent with the findings from a previous study by Ji et al. (2022), which revealed four profiles of attentional biases in adults by the APNIS: “no positive and negative bias” group (9.3%), “minor positive bias & no negative bias” group (48.0%), “major positive bias & minor negative bias” (25.6%), and “major positive bias & no negative bias” (17.1%). While both studies provided evidence that the fewest number of individuals showed zero to low negative and positive attentional biases in adults and children. This evidence supported that the majority of children had moderate to high levels of attentional biases during the COVID-19 pandemic. It should also be noted that for both the previous study by Ji et al. (2022) on adults and the current study on children, the profile of high negative and positive attentional biases was not revealed, suggesting that these children hardly show strong attentional bias towards both negative and positive stimuli.

Implications

The study revealed three patterns of attentional biases in children and assessed their association with emotional symptoms during the COVID-19 pandemic. The results provided important implications for the cognitive model of emotional disorders. A large proportion of children had the “moderate positive and high negative attentional biases” and the “high positive and moderate negative attentional biases” profiles. These children didn’t significantly differ in the development of emotional symptoms from the minority of children who had “low positive and negative attentional biases” during the COVID-19 pandemic. Thus, having high negative attentional bias or low positive attentional bias was not necessarily associated with high emotional symptoms; it is important to consider the overall patterns of positive and negative attentional biases. Indeed, inconsistent evidence on the relationship between negative attentional bias and emotional symptoms was sometimes revealed, which might be explained by the level of positive attentional biases in the participants (Neshat-Doost, Moradi, Taghavi, Yule, & Dalgleish, 2000; Waters, Lipp, & Spence, 2004). Therefore, involving only negative or positive attentional bias alone in the cognitive model of emotional symptoms might be problematic. Future endeavors might be put into examining the profiles of attentional biases in research to establish a cognitive model that depicted how the overall patterns of negative and positive attentional biases were related to emotional symptoms.

Moreover, results implied that clinicians should consider the overall patterns of negative and positive attentional biases when screening at-risk children during the COVID-19 pandemic. Clinicians might use the APNIS scale to facilitate the identification of children at higher risk of emotional symptoms during the COVID-19 pandemic. Children who simultaneously had patterns of high negative attentional bias and moderate positive attentional bias might be at higher risk of developing higher fear of COVID-19, anxiety and depression. Thus, these children might need early prevention against more severe emotional problems in the future.

Limitations

The results should be interpreted with caution. The study only involved a group of Chinese children transiting into early adolescence. Thus, the results might not be generalized to other populations, such as late adolescents or adults. Moreover, a cultural factor might be a significant factor affecting the overall patterns of attentional biases. Thus, future studies might need to examine how the profiles of attentional biases are manifested in children from other cultures. Also, fear of COVID-19, anxiety and depression symptoms were measured by self-report inventories, which might be affected by children’s memory biases. Future studies might need to include multiple measures of anxiety and depression including physiological measures of anxiety and depression. The self-report assessment of attentional biases might only reflect children’s dispositional tendency to attend to negative or positive information. It should be noted that the cognitive resources allocation process underlying attentional biases might be better measured by the behavioral tasks. Thus, future studies might use the behavioral measures of attentional biases to examine the profiles of attentional biases in children. The longitudinal study only lasted for 6 months. The failure to find significant time effects and interaction effects on anxiety and depression might be due to the relatively short interval between the two assessments. Future studies might expand the assessment interval and/or involve more assessments in a longer period.

Overall, the study identified three profiles of attentional biases: the “low negative and positive attentional biases” profile, the “moderate positive and high negative attentional biases” profile, and the “high positive and moderate negative attentional biases” profile. Children with the “moderate positive and high negative attentional biases” profile had significantly higher emotional symptoms during the COVID-19 pandemic. Psychologists may need to identify children with maladaptive profiles of attentional biases for early intervention. The results highlighted the importance of examining the overall patterns of negative and positive attentional biases when identifying at-risk children during the COVID-19 pandemic.

Acknowledgement: Thanks to the teacher Ms. Xiao Hong Ling for her help in the research project.

Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Disclosure statement

The authors declare that they have no conflict of interest.

Ethics approval and consent to participate. Ethics approval was obtained from the Human Subjects Ethics Sub-Committee of the City University of Hong Kong (2020-21-CIR2-B1;2019-20-CIR6-B5). Students’ parents who agreed their children to participate had signed the informed consent sheets and students had signed the assent sheets to participate.

Funding: The authors did not receive support from any organization for the submitted work

Conflict of interest: The corresponding author states that there is no conflict of interest.

The study was not preregistered.

Author contribution: Zhang Q. designed the study, collected data, did data analysis, wrote and revised manuscript

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Table 1. Mean (Standard Deviation) and correlations of Psychological Variables (n =262)

	Girls		Boys		Correlations
	Mean	(SD)	Mean	(SD)	r	r	r	r	r	r	r	r
					T1 ANI	T1 API	T1 Anxiety	T1 Depression	T1 Fear of COVID-19	T2 Anxiety	T2 Depression	T2 Fear of COVID-19
T1 ANI	11.51	4.05	10.80	3.75	—
T1 API	14.86	3.09	14.88	3.46	-.099	—
T1 Anxiety	29.55	23.23	21.46	17.86	.679**	-.178**	—
T1 Depression	5.75	5.74	4.81	4.95	.619**	-.210**	.868**	—
T1 Fear of COVID-19	14.69	11.39	11.79	10.52	.443**	-.160*	.610**	.509**	—
T2 Anxiety	29.11	21.67	21.80	18.55	.502**	-.180**	.721**	.655**	.572**	—
T2 Depression	6.51	5.87	5.05	5.00	.451**	-.224**	.595**	.651**	.473**	.852**	—
T2 Fear of COVID-19	28.29	11.29	24.30	10.58	.408**	-.071	.476**	.422**	.635**	.628**	.579**	—

* p< .05 ** p< .01

Table 2. Changes in anxiety and depression symptoms based on the three profiles of attentional biases

	1. Low negative and positive attentional bias		2. High positive and moderate negative attentional bias		3. Moderate positive and high negative attentional bias		Difference Between profiles	Time effect	Profile * Time
	M (SD)		M (SD)		M (SD)
	T1	T2	T1	T2	T1	T2	F	F	F
Anxiety	25.20 (19.33)	32.50 (16.51)	19.95 (19.34)	21.12 (20.94)	29.37 (21.63)	28.06 (20.10)	5.66** 2<3	1.89	2.01
Depression	7.10 (5.93)	8.60 (4.62)	3.93 (4.90)	4.54 (5.19)	6.08 (5.48)	6.45 (5.59)	6.43** 2<3	2.49	.34
Fear of COVID-19	13.80 (12.32)	20.60 (9.63)	10.77 (10.14)	24.63 (10.99)	14.76 (11.31)	27.74 (10.99)	4.10*	112.55**	2.64

* p< .05 ** p< .01

No competing interests reported.

SupplementaryInformation.docx
Appendix

Patterns of attentional biases in children and emotional symptoms during the COVID-19 pandemic: a two-wave longitudinal study

Status:

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Abstract

Figures

Background

Method

Results

Discussion

The Patterns Of Positive And Negative Attentional Biases

Implications

Limitations

Conclusions

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1