Unique and Shared Mechanisms of Reading Skill and Anxiety Symptoms in Children
Jiulin Dai
Department of Psychology and Human Development, Peabody College, Vanderbilt University Mentor: Dr. James R. Booth
March 20, 2023
Abstract
The current study examines the distinct and common mechanisms underlying individual differences in reading skill and anxiety symptoms in children ages 7- to 12-years-old. A
standardized oral word reading assessment is used to measure reading skill and a questionnaire is used to measure anxiety symptoms. Mechanisms are measured by a rhyming task manipulating lexical processing (i.e. low- versus high-frequency words), valence reactivity (i.e. negative versus neutral images) and working memory load (i.e. 2- versus 1-back). Overall, we observed a non-significant, negative relation between word reading skill and anxiety symptoms. Using hierarchical regressions, we observed 1) weak evidence supporting lexical processing as a mechanism of word reading skill, 2) no evidence supporting valence reactivity as a mechanism of anxiety symptoms, 3) weak evidence for working memory relating to both word reading skill and anxiety symptoms but word reading skill explains unique variance above and beyond anxiety symptoms. Although these findings were inconsistent with our hypotheses and prior literature, they could be due to the small sample size and the lack of less skilled readers in our present study. This study lays the groundwork for future brain imaging study and helps us gain a better understanding of mechanisms of reading and anxiety, which may ultimately inform intervention strategies for children struggling in these areas.
Introduction
Reading difficulties and anxiety symptoms are prevalent in school-age children and can negatively affect academic performance, social development, and general well-being (Mazzone et al., 2007). Anxiety has one of the highest incidence rates among all mental disorders in youths, and approximately 9.4% of children and adolescents ages 3-17 are diagnosed with anxiety disorders (Bitsko et al., 2022). About 5-10% of children in the U.S. also experience difficulties with reading, often characterized by deficits in word recognition (Mancheva et al., 2015;
Schilling, 1988). The co-morbidity of anxiety symptoms and reading difficulties is common, and poor readers have about a threefold chance of having an anxiety disorder compared to typical readers (Goldston et al., 2007).
Children’s reading skills fall on a normally distributed continuum, with those with reading difficulties being at least one standard deviation below the mean (Cilibraso & Tsimpli, 2020; Galuschka & Schulte-Körne, 2016; Snowling, 1998). It is common practice to group together these individuals and categorically compare them to “typically developing” readers.
However, prior work has shown that children ages 8-14 years old with dyslexia varied in the severity of their reading difficulties (Edwards et al., 2018). Likewise, children exhibit different levels of subthreshold anxiety symptoms that are associated with various vulnerability factors (Burstein et al., 2014; Möller, et al., 2014; Murray et al., 2009). Thus, to advance our
understanding of the interrelations between the development of reading difficulties and anxiety symptoms in all children, it is critical to study the common and distinct mechanisms underlying the individual differences in these two domains. A better understanding of the mechanisms may allow researchers to develop more effective and targeted interventions for those who struggle with reading or anxiety. In the current study, we focus on three main constructs of interest –
lexical processing, valence reactivity, and working memory – to examine their relations to children’s reading skills and anxiety symptoms.
Reading Skills and Lexical Processing
Successful reading at text levels relies on sufficient single word reading skill. Prior literature suggests that word reading skill is determined by lexical processing, or the rapid, automatic decoding and retrieval of the orthographic, phonological, and semantic information of a written word (Perfetti, 2007; Perfetti & Stafura, 2014). Studies on adults and typically
developing 6- to 13-years-olds showed that individual differences in lexical decision tasks, such as distinguishing between real and pseudowords, were positively correlated with word reading skill (Hsiao & Nation, 2018; Mancheva et al., 2015; Schilling, 1988). Similarly, a study on typically developing 10-year-olds with and without dyslexia concluded that the former group had lower accuracy and longer response time on a lexical decision task, indicating less efficient lexical processing (Martens & de Jong, 2006). Taken together, the prior literature suggests a robust positive relation between word reading skill and lexical processing.
Lexical processing is influenced by various lexical characteristics of a word, one of which is word frequency. Across age groups, high-frequency words, or words that appear more often in a language corpus, are more efficiently processed than low-frequency words, or words that appear less often in the corpus (Brysbaert et al., 2017; Joseph et al., 2013; Schmalz et al., 2013; van Heuven et al., 2014). This phenomenon is known as the word frequency effect.
Individual differences in lexical processing of words are determined by a reader’s experience with these words and the diversity of contexts in which these words appear (Nation, 2017).
Compared to less skilled readers, skilled readers may process some low-frequency words as efficiently as high-frequency words because their experience with these words is more frequent,
which creates more stable representations to allow efficient lexical processing. Therefore, the word frequency effect may be more prominent for less skilled readers than for more skilled readers (Perfetti, 2007). Findings from imaging studies on 10-year-old children support this idea, as children with dyslexia experienced a larger word frequency effect than typically developing children (Dürrwächter, et al., 2010; Grande, et al., 2011; Heim et al., 2013). Similarly, behavioral studies also showed a greater word frequency effect (lower accuracy, longer reaction time) in word reading tasks in children with dyslexia than in typically developing children (Davies et al., 2007; van der Leji & van Daal, 1999).
Together, prior studies have suggested that children with lower reading skills may exhibit a greater word frequency effect due to less efficient lexical processing. In the current study, we will examine the relations between individual differences in word reading skills and lexical processing in elementary-school-age children, with lexical processing operationalized using word frequency.
Anxiety Symptoms and Valence Reactivity
One characteristic of anxiety is the tendency to disproportionally allocate attentional resources toward negative, such as threatening, stimuli and/or to have trouble disengaging attention from such stimuli (e.g., Bar-Haim et al., 2005; Koster et al., 2006; Mogg et al., 1997).
This anxiety-related attentional bias contributes to valence hyper-reactivity, which is an intense and frequent emotional response to perceived negative stimuli that is often seen in anxious individuals (Carthy et al., 2009). Valence reactivity, typically assessed with emotional face stimuli, has been observed in both anxious children and adults (Bar-Haim et al., 2007; Dudeney et al., 2015). Bar-Haim et al. (2007) conducted a meta-analysis of studies with different
populations of anxious individuals (i.e., individuals with different clinical disorders and high-
anxious nonclinical individuals from both developmental and adult populations) and non-anxious individuals. Results demonstrate that people with anxiety allocate significantly more attentional resources to threatening stimuli than those without anxiety, and that this attentional bias does not differ across age groups or groups of people with trait anxiety compared to clinically diagnosed anxiety. A meta-analysis done exclusively on 4- to 18-year-olds also showed that children exhibited a greater attentional bias towards threatening stimuli compared to neutral stimuli, and this bias was greater in anxious children than in typically developing children (Dudeney et al., 2015). An empirical study on 8- to 12-year-olds further found that the intensity of this valence reactivity was positively correlated with children’s anxiety symptom severity (Waters et al., 2010). These findings are consistent with other studies demonstrating that anxious children displayed an attentional bias toward angry faces but not happy faces (e.g., Monk et al., 2006;
Roy et al., 2008). Together, prior research on the relations between anxiety and valence reactivity suggests that compared to typically developing children, children with anxiety
symptoms showed hyper-reactivity to negative stimuli, rather than emotional stimuli in general, due to the biased attention allocation towards this emotional state. In the current study, we aim to replicate this effect using images with negative valence.
Reading Skills and Working Memory
Working memory can be defined as the capacity to store information for short periods while engaging in cognitively demanding activities (Baddeley, 1986; Savage et al., 2007). One key element that differentiates working memory from passive short-term memory is the central executive system that controls, coordinates, and allocates attentional resources (Baddeley &
Hitch; 1974; Baddeley, 1986; 2000; Cowan, 2008; Repovš & Baddeley, 2006). Therefore, recent studies often use more complex working memory tasks instead of simple span tasks, such as the
n-back task. In the n-back paradigm, participants are presented with a sequence of stimuli and asked to determine whether the current stimulus matches with the stimulus n items ago. This dynamic working memory task requires constant monitoring, updating, and manipulating
remembered information, thus placing a heavy demand on the central executive system (e.g., see Kane et al., 2007, for review).
Because of the high co-morbidity of reading difficulties and anxiety symptoms, it is possible that there are shared factors underlying these two conditions, one of which is working memory. Working memory capacity is a major contributor to successful word reading
competency (e.g., Daneman & Carpenter, 1980; Gathercole & Baddeley, 1989; Jeffries &
Everatt, 2004). Prior research on typically developing children and children with dyslexia in the third and fourth grades showed that working memory significantly predicted word recognition skill in both groups (Wang & Yang, 2014). In the same study, working memory contributed an additional 16% and 18% of unique variance in typically developing and dyslexic children’s word recognition skill, respectively, above variance already explained by age, non-verbal IQ, and other cognitive processing skill. A meta-analysis on 5- to 18-year-olds also showed that children with reading difficulties scored lower on working memory measures than children without reading difficulties (Swanson, Zheng, & Jerman, 2009).
Prior research has examined the relation between individual differences in reading skill and working memory using different tasks. A meta-analysis has found a moderate correlation (r=0.29) between these two constructs across age groups in non-clinical populations (Peng et al., 2018). Regarding children who struggle with reading, the existing studies primarily looked at this relationship at a group level (e.g., typically developing children vs. children with dyslexia).
A few empirical studies have examined the relationship between reading skill and working
memory in children and adolescents using the n-back paradigm. For example, a study on ninth- grade Japanese boys with reading difficulties and their typically developing peers showed that the two groups performed similarly on 0-back trials, but those with reading difficulties had significantly lower accuracy and longer response time on 1-, 2-, and 3-back trials (Yanai &
Maekawa, 2011). This pattern of results is similar to those from a study of 13-year-old
Norwegian children (Beneventi et al., 2010) and those from a study of 9- to 12-year-old Chinese children (Xu et al., 2015), both using the n-back design. In the current study, we will examine the relation between individual differences in word reading skill and performance on a dynamic n- back working memory task involving lexical processing in school-age children.
Anxiety Symptoms and Working Memory
Working memory deficits are commonly associated with anxiety symptoms, and this relationship may be bidirectional. According to the processing efficiency theory (PET;
Derakshan & Eysenck, 2009), the valence hyper-reactivity seen in anxious individuals can lead to the reallocation of the attentional resources from the task-relevant information to the more salient, task-irrelevant stimuli. Because attentional resources are limited, this reallocation may yield a worse behavioral performance on attentionally demanding tasks, such as tasks with high working memory load (e.g., see Moran, 2016, for a review; Ashcraft & Kirk, 2001; Corbetta &
Shulman, 2002; Darke, 1988; Shackman et al., 2006). On the other hand, deficits in working memory may also lead to heightened anxiety symptoms because of inefficient cognitive reappraisal (Petkus et al., 2017). Cognitive reappraisal is a form of emotion regulation that involves reconstructing the meaning of an emotion-eliciting stimulus or situation to change its emotional impact. More frequent usage of cognitive reappraisal is found to be associated with lower self-reported anxiety symptoms in adults and adolescents (Andreotti et al., 2011; Garnefski
et al., 2002; Lazarus & Alfert, 1964; Moore et al., 2008). Cognitive reappraisal places a
significant demand on working memory (Lee & Xue, 2016; Ochsner & Gross, 2008). Therefore, people with working memory deficits may be less capable of reappraising emotional stimuli, which could lead to greater anxiety symptoms (Schmeichel et al., 2008).
The negative bidirectional relation between anxiety symptoms and working memory is consistent in the literature (Aronen et al., 2004; Ladouceur et al., 2009; Moran, 2016). A meta- analysis has found that clinically diagnosed and self-reported anxiety symptoms correlate with poorer performance across various working memory tasks and age groups (Moran, 2016). An empirical study on 6- to 13-year-olds also shows that children with lower performance on visual n-back working memory tasks had higher teacher-reported anxiety symptoms (Aronen et al., 2004). The relation between working memory and anxiety symptoms may be more pronounced when negative stimuli co-occur with cognitively demanding tasks. In a study by Ladouceur et al.
(2009), children showed longer response times on an n-back task when presented with fearful faces than non-anxious children. In summary, lower working memory capacity may be a
predictor and consequence of both reading skills and anxiety symptoms. Thus, the current study aims to examine whether working memory is a common underlying factor of reading difficulties and anxiety symptoms.
To better understand the unique and shared mechanisms underlying individual
differences in reading skills and anxiety symptoms, we will examine their relations with lexical processing, valence reactivity, and working memory using a n-back word rhyming task in 7- to 12-year-olds. Specifically, the research aims of the current study will assess 1) the relation of word reading skill to lexical processing, 2) the relation of anxiety symptoms to valence
reactivity, and 3) the relation of word reading skill and anxiety symptoms to working memory.
Method Participants
32 native-English-speaking children are included in the final analysis of the study (Mage= 10.2 (1.4), range = 7-12 years). Data from those who met the following inclusionary criteria were analyzed from an initial sample of 58 who participated: no 1) psychiatric disorders (participants with anxiety disorders will only be excluded if taking medications); 2) neurological disease or epilepsy; 3) preterm birth before 34 weeks; 4) birth complications requiring admission into neonatal intensive care unit; 5) head injury requiring emergency medical evaluation; 6) uncorrected vision; 7) uncorrected hearing loss; 8) intellectual disability, and 9) learning
disability (except for reading difficulties). Participants were also excluded for missing data, poor task performance, and outlier analyses (described below).
Materials
Woodcock-Johnson Letter Word Identification (WJ-ID)
The WJ-ID is a subtest of the Woodcock-Johnson III Test of Achievement standardized assessment that measures word recognition skills (Woodcock et al., 2001). Participants are presented with single words and must read aloud each presented word in one try without
hesitation or repetition. The words increase in difficulty and assessment is discontinued when six consecutive items are incorrectly read. The raw score from a total 76 items is used in the
analysis.
Screen for Child Anxiety Related Disorders (SCARED)
SCARED is a 41-item assessment of trait anxiety that screens for childhood anxiety disorders including generalized anxiety disorder, separation anxiety disorder, panic disorder, and social phobia. The raw score on the child form is used in the study, with a higher score indicating
more severe anxiety symptoms. The highest possible score is 82, and a score of 25 may indicate the presence of an anxiety disorder (Birmaher et al., 1999).
N-back Word Rhyming Task
Lexical processing, valence reactivity, and working memory are measured using an experimental n-back word rhyming task. Participants see a continuous presentation of visual words and are asked to make a rhyming judgment between the current word and the word presented 2-back or 1-back. Participants press two keys on the keyboard to indicate if the word pairs rhyme or do not rhyme. This represents our working memory manipulation, and each n- back condition is presented half of the time. Words used in the rhyming task also manipulate lexical processing such that half of the stimuli consist of low-frequency words and the other half of high-frequency words. Between each word, participants passively see images depicting objects, animals, and scenes with half of them tapping into negative and half of them conveying neutral valence reactivity.
The task consists of four runs, each with four lexical blocks. The lexical blocks are evenly divided into eight conditions based on the 2x2x2 design: lexical processing (low- vs.
high-frequency), valence reactivity (negative vs. neutral), and working memory (2-back vs. 1- back). Each lexical block contains 12 trials, yielding a total of 48 trials per run and 192 trials in the entire task. Half of the lexical trials rhyme (e.g., hill-fill) and half do not rhyme (e.g., well- town). Before each visually presented word appears ( ≤ 1000ms), participants passively see an image for 500ms, drawn from the Open Affective Standardized Image Set (OASIS) picture database (Kurdi, Lozano, & Banaji, 2017). Half of the images are of negative valence and the other half are of neutral valence. The same image is in the background during the presentation of the word (displayed for ≤ 1000ms) and displayed for another 2000ms after the word
disappears. The image is followed by a 500ms fixation cross before the next image appears (see Figure 1).
Each lexical block is followed by a perceptual block with eight trials. A perceptual trial contains a pixelated word with a solid or dashed border. Participants are asked to indicate if the border is solid or dashed. Before each scrambled word, participants will see a pixelated image.
The pixelated words and images are selected from the words and images used in lexical blocks and randomly scrambled to a 20x20 image. The timing and the presentation format of perceptual blocks are identical to those of the lexical blocks (see Figure 1). A total of 24 perceptual trials will be presented for each run, yielding a total of 192 perceptual trials throughout the entire task.
The perceptual conditions are not analyzed in the study.
Procedures
Before scheduling a testing session, parents complete a consent form followed by an eligibility form that includes demographic and background information. Eligible participants are invited for a testing session conducted in-person at the Brain Development Laboratory at
Vanderbilt University. Each session lasts about two hours and includes parent and child questionnaires, a standardized assessment of reading, and an experimental word rhyming task, described above. After child participants give assent, a second research personnel directs the parent/guardian to complete questionnaires in a different testing room. Participants are seated in front of a desktop computer used for administering questionnaires and the experimental task. A recording device is placed on the table in front of the participant to record responses for the standardized reading assessment for double scoring purposes.
Participants are first walked through task instructions using PowerPoint (~11 minutes) and then asked to complete two practice training runs on the n-back word rhyming task (~3
minutes each). The practice runs are repeated if an overall score of at least 60% accuracy is not reached on the first attempt. After two repeated practices, participants proceed with the task regardless of accuracy. Participants then complete four runs of the word rhyming experimental task. Each run takes approximately seven minutes to complete.
Design Study Design
The current study uses an experimental, within-subject design to examine the
mechanisms underlying individual differences in word reading skills and anxiety symptoms.
Each participant completes all assessments and experimental tasks including the WJ-ID, SCARED, and an n-back word rhyming task that manipulates lexical processing, valence
reactivity, and working memory. The following dependent variables will be used in the analyses:
the performance difference (separately, for accuracy and response time) between 1) low and high word frequency conditions, 2) negative and neutral valence conditions, and 3) 2-back and 1-back working memory conditions. The two independent variables are word reading skill measured by WJ-ID and anxiety symptoms measured by SCARED.
Analytical Plan
The research questions, hypotheses, and planned and exploratory analyses were pre- registered on Open Science Framework (https://doi.org/10.17605/OSF.IO/FT7J4).
Based on the pre-registered inclusionary criteria, participants were excluded from the final analyses for the following criteria: 1) incomplete data for the WJ-ID, SCARED, and all four runs of the n-back word rhyming task (N=0) 2) WJ-ID standardized scores and SCARED raw scores are above or below three standard deviations of the mean scores of the sample (N=1); 3) accuracy on n-back word rhyming task being lower than 40% in any of the eight conditions of
the n-back word rhyming task (N=19); 4) having greater than 20% of trials with no response in any of the eight conditions of the n-back word rhyming task (N=1); 5) having a response bias greater than 40% accuracy difference between the “yes” response and the “no” response on any of the eight conditions of the n-back word rhyming task (N=5). “Yes” response accuracy, for example, is calculated by the number of “yes” trials correctly answered divided by the total number of trials for which “yes” is the correct response.
First, a partial correlation will test the relation between word reading skill (WJ-ID raw score) and anxiety symptoms (SCARED raw score) with age as a covariate. We expect there to be a negative association between reading skill and anxiety symptoms.
Second, 2x2x2 ANOVAs will test the effects of lexical processing (low- vs. high- frequency), valence reactivity (negative vs. neutral), and working memory (2-back vs. 1-back).
Two ANOVAs are computed, one for task accuracy and one for task response time. We expect lower accuracy and slower response time for low- compared to high-frequency, for negative compared to neutral valence and for 2-back compared to 1-back working memory.
Third, to examine the relation between reading skill and lexical processing (research question1), we compute two hierarchical regressions, one for task accuracy and one for task response time. The dependent measure is word frequency effect (low->high-frequency for 1-back neutral conditions). Age is entered as the first predictor (Model 1), anxiety symptoms as the second predictor (Model 2), and word reading skill as the third predictor (Model 3). We expect anxiety symptoms to not explain significant unique variance (R2 change in Model 2), but word reading skill to explain significant unique variance (R2 change in Model 3).
To examine the relation between anxiety symptoms and valence reactivity (research question 2), we compute two hierarchical regressions, one for task accuracy and one for task
response time. The dependent measure is valence reactivity (negative>neutral for 1-back high- frequency conditions). Age is entered as the first predictor (Model 1), reading skill as the second predictor (Model 2), and anxiety symptoms as the third predictor (Model 3). We expect reading skill to not explain significant unique variance (R2 change in Model 2), but anxiety symptoms to explain significant unique variance (R2 change in Model 3).
Lastly, to examine the relation between word reading skill and anxiety symptoms to working memory (research question 3), we compute four hierarchical regressions, two for task accuracy and two for task response time. The dependent measure is working memory (2-back>1- back for high-frequency neutral conditions). In two regressions, age is entered as the first
predictor (Model 1), reading skill as the second predictor (Model 2), and anxiety symptoms as the third predictor (Model 3). We expect reading skill to explain significant unique variance (R2 change in Model 2), but anxiety symptoms to not explain significant unique variance (R2 change in Model 3). In two regressions, age is entered as the first predictor (Model 1), anxiety symptoms as the second predictor (Model 2), and word reading skill as the third predictor (Model 3). We expect anxiety symptoms to explain significant unique variance (R2 change in Model 2), but word reading skill to not explain significant unique variance (R2 change in Model 3).
In our pre-registration, we also planned to conduct an exploratory analysis to test research questions 1, 2, and 3, not with the difference score for the dependent variable, but for low-
frequency (for 1-back neutral), negative images (for 1-back high-frequency), and 2-back (for high-frequency neutral).
Results
Descriptive data for the WJ-ID word reading and SCARED anxiety assessments are shown in Figure 2. Standardized WJ-ID score ranged from 99 to 135 (M (SD)=112.0 (8.7)),
indicating that participants in this study were a group of average to above average skilled readers. The SCARED raw score ranged from 2 to 59 (M (SD)=22.9 (12.9)), indicating good variability in anxiety symptoms among our participants (see Figure 2). A score above 25 may indicate the presence of anxiety disorder (Birmaher et al., 1999).
Partial Correlation
A Pearson’s partial correlation indicated a non-significant, negative relation between word reading skill and anxiety symptoms while including age as a covariate (r(30)=-0.27, p=0.15). Although this result is not significant, the negative trend between word reading skill and anxiety symptoms is consistent with our prediction (see Figure 2). This means that participants with greater anxiety symptoms exhibited lower word reading skill.
ANOVA
A 2x2x2 ANOVA yielded a significant main effect of working memory load on task accuracy, F(1, 252) = 88.55, p < 0.001, partial η2=0.26, indicating that participants performed better on the 1-back (M (SD) = 0.90 (0.09)) than on the 2-back (M (SD) = 0.76 (0.11)) working- memory-load condition, collapsed across the valence and word frequency conditions (see Figure 3). There was no significant main effect of word frequency (F (1, 252) = 1.22, p = 0.27, partial η2
= 0.00) nor valence (F (1, 252) = 0.43, p = 0.51, partial η2 = 0.00) on task accuracy. As
anticipated, participants showed higher accuracy on the high-word-frequency condition (M (SD)
= 0.84 (0.09)) than the low-word-frequency condition (M (SD) = 0.82 (0.10) and a higher accuracy on the neutral condition (M (SD) = 0.83 (0.09)) than the negative condition (M (SD) = 0.82 (0.09)), although neither of these were statistically robust. Additionally, there was no lexical processing x valence reactivity x working memory interaction effects (p > 0.1).
Similarly, there was a significant main effect of working memory load on task response time, F (1, 252) = 11.279, p < 0.001, partial η2 = 0.04. Participants responded faster on the 1- back condition (M (SD) = 1223.83 (320.15)) than on the 2-back condition (M (SD)=1368.56 (343.67)). There was no significant main effect of either word frequency (F (1, 252) = 0.03, p = 0.87, partial η2 = 0.00) or valence (F (1,252) = 0.46, p = 0.50, partial η2 = 0.00) on task response time. Consistent with our hypotheses, participants showed longer response time on the negative valence condition (M (SD ) = 1310.78 (324.83)) compared to the neutral valence condition (M (SD) = 1281.61 (318.17)), despite a lack of statistical significance. Contrary to what we
expected, participants had longer response times on the high-word-frequency condition (M (SD)
= 1299.83 (316.81)) than on the low-word-frequency condition (M (SD)=1292.56 (327.04)), though the difference was negligible. There also was no interaction effect for response time (p >
0.10).
Hierarchical Regression: Research Question 1
Hierarchical regression analyses revealed no evidence (ΔR2 < 5%) in support of lexical processing as a unique mechanism of word reading skill (see Table 1). The average low->high- frequency contrast for 1-back, neutral condition yielded a very small difference for both accuracy (M=-0.02, SD=0.06) and response time (M=-18.30, SD=159.55). Across the models tested, for both task accuracy and response time, there was little to no change in the percent variance of lexical processing explained by anxiety symptoms and word reading skill after accounting for age. Consistent with our hypothesis, anxiety symptoms accounted for less than 2% of variance in lexical processing above and beyond that accounted for by age (accuracy: F(1,29)=0.42, p=0.52;
response time: F(1,29)=0.01, p=0.91). In consistent with our hypothesis, word reading skill accounted for less than 5% variance in lexical processing above and beyond that accounted for
by age and anxiety symptoms (accuracy: F(1,28)=0.54, p=0.46; response time: F(1,28)=0.00, p=0.99). In total, the model accounted for 3.4% and 16.4% of the variance in lexical processing for accuracy and for response time, respectively. Interestingly, age was a significant predictor of response time in the first two models, which meant that compared to younger children, older children spent a more equivalent amount of time on high- and low-frequency conditions, indicating more sufficient lexical processing.
Hierarchical Regression: Research Question 2
Hierarchical regression analyses also revealed no evidence in support of valence reactivity as a unique mechanism of anxiety symptoms (see Table 2). The average negative >
neutral contrast for 1-back, high-frequency condition yielded a very small difference for both accuracy (M=-0.02, SD=0.08) and response time (M=-0.76, SD=142.10). Across the models tested for both task accuracy and response time, there was little to no difference in percent variance of valence reactivity explained by word reading skill and anxiety symptoms skill after accounting for age. Consistent with the hypothesis, word reading skill accounted for less than 1%
variance in valence reactivity above and beyond that accounted for by age (accuracy:
F(1,29)=0.024, p=0.877; response time: F(1,29)=0.042, p=0.839). In consistent with the hypothesis, anxiety symptoms accounted for less than 1% variance in lexical processing above and beyond that accounted for by age and word reading skill (accuracy: F(1,28)=0.083, p=0.776;
response time: F(1,28)=0.110, p=0.743). In total, the model accounted for 3% and 1.4% variance in valence reactivity for accuracy and response time, respectively.
Hierarchical Regression: Research Question 3
Lastly, hierarchical regression analyses revealed no evidence in support of working memory as a mechanism of anxiety symptoms or a common mechanism of both word reading
skill and anxiety symptoms, but they revealed weak evidence (ΔR2 > 5%) in support of working memory as a mechanism of word reading (see Tables 3 and 4). There was a significant
performance difference (both accuracy and response time) for the 2-back > 1-back contrast under high-frequency, neutral condition (accuracy: M=-0.16, SD=0.10; response time: M=123.18, SD=218.57). The first hierarchical regression included age as the predictor in the first model, age and anxiety symptoms as the predictors in the second model, and age, anxiety symptoms, and word reading skill as the predictors in the third model (see Table 3). Inconsistent with our hypothesis, anxiety symptoms accounted for less than 2% variance in working memory above and beyond that accounted for by age (accuracy: F(1,29)=0.145, p=0.707; response time:
F(1,29)=0.450, p=0.508). Although not significant, word reading skill accounted for an
additional 7.8% variance in working memory above and beyond that accounted for by age and anxiety symptoms for accuracy and less than 2% for response time (accuracy: F(1,28)=2.49, p=0.126; response time: F(1,28)=0.503, p=0.484). For accuracy, the change in variance explained after adding word reading skill as a predictor was still greater than that of any other predictors across models. This was also inconsistent with our hypothesis, as we predicted that word reading skill would not explain unique variance above and beyond that explained by anxiety symptoms. Although the overall model only explained 12.6% and 3.8% variance in working memory for accuracy and response time, respectively, the increase in percent variance explained after adding word reading skill may indicate that compared to anxiety symptoms, working memory is more related to word reading skill.
The second hierarchical regression analysis showed a similar pattern to the first, with no evidence to support working memory as a common mechanism but weak evidence to support working memory as a mechanism of word reading skill (see Table 4). Compared to anxiety
symptoms, word reading skill was more strongly related to working memory and accounted for 6.3% variance in working memory above and beyond that accounted for by age for accuracy and less than 1% for response time (accuracy: F(1,29)=2.018, p=0.167; response time:
F(1,29)=0.255, p=0.618). Anxiety symptoms accounted for less than 3% variance in working memory above and beyond that accounted for by age and word reading skill (accuracy:
F(1,28)=0.620, p=0.438; response time: F(1,28)=0.699, p=0.410). While there was a minimal change in percent variance of working memory explained between word reading skill and anxiety symptoms after accounting for age for both task accuracy and response time, which was consistent with our hypothesis, the overall model was not significant, so we could not conclude that word reading skill and anxiety symptoms explained common variance in working memory.
Exploratory Analyses
The pre-registered exploratory analyses tested the same hierarchical regressions as previously done, but used only the more difficult conditions for word frequency (i.e., low- frequency under 1-back, neutral condition), valence reactivity (i.e., negative valence under 1- back, high-frequency condition), and working memory (i.e., 2-back under high-frequency, neutral condition) rather than the difference contrast (e.g., 2-back>1-back). The patterns for all three exploratory analyses were similar to what we observed for the planned analyses.
For research question 1, there was weak evidence of lexical processing as a unique mechanism of word reading skill (see Table 5). Anxiety symptoms accounted for less than 3%
variance in lexical processing above and beyond that accounted for by age (accuracy:
F(1,29)=0.00 p=0.98; response time: F(1,29)=1.01, p=0.32). Word reading skill accounted for 8.8% and 1% variance in lexical processing above and beyond that accounted for by age and anxiety symptoms for accuracy and response time, respectively (accuracy: F(1,28)=2.77, p=0.11;
response time: F(1,28)=0.44, p=0.51). Although the change in variance for accuracy after adding word reading skill was not significant, it was large compared to other changes and was consistent with our hypothesis. Similar to the planned hierarchical regression analysis, we observed a strong predictive power of age on response time for all three models. This indicates that overall, older children were more efficient at processing low-frequency words than younger children.
Likewise, for research question 2, we saw no evidence in support of valence reactivity as a unique mechanism of anxiety symptoms (see Table 6). Consistent with our hypothesis, word reading skill accounted for less than 4% variance in valence reactivity above and beyond that accounted for by age (accuracy: F(1,29)=1.20, p=0.28; response time: F(1,29)=0.57, p=0.45).
Inconsistent with our hypothesis, anxiety symptoms also accounted for less than 2% variance in lexical processing above and beyond that accounted for by age and word reading skill (accuracy:
F(1,28)=0.18, p=0.67; response time: F(1,28)=0.39, p=0.54). Age was also a significant predictor of response time on negative, 1-back, high-frequency condition in model 1 but not model 2 and 3. This meant that when age was the sole predictor of response time, older children appeared to react faster with negative distractor images in the task than younger children.
Nevertheless, this relation changed after including word reading skill, which was likely due to the strong correlation between these two variables. Even though the age and word reading skill correlation did not reach the threshold for collinearity, it was statistically significant (r=0.56, p<0.001).
Finally, consistent with the planned analyses, there was no evidence to suggest that working memory was a common mechanism of word reading skill and anxiety symptoms (see Table 7 & 8). However, unlike with the planned analyses, there was weak evidence suggesting working memory as a mechanism of anxiety symptoms but not word reading skill. When we
included working memory (2-back) as the dependent variable, age as the predictor in the first model, age and anxiety symptoms as the predictors in the second model, and age, anxiety symptoms, and word reading skill as the predictors in the third model, anxiety symptoms accounted for 0 % variance in working memory performance for accuracy and 5.6 % for response time above and beyond that accounted for by age (accuracy: F(1,29)=0.00, p=0.99;
response time: F(1,29)=2.02, p=0.17). The change in percent variance after adding anxiety symptoms as a predictor was greater than 5%, and provides weak evidence in support of our hypothesis that word reading skill was related to anxiety symptoms. Consistent with the hypothesis, word reading skill accounted for less than 1% variance in working memory performance above and beyond that accounted for by age and anxiety symptoms (accuracy:
F(1,28)=0.11, p=0.74; response time: F(1,28)=0.01, p=0.92). However, when we included working memory (2-back) as the dependent variable, age as the predictor in the first model, age and word reading skill as the predictors in the second model, and age, word reading skill, and anxiety symptoms as the predictors in the third model, word reading skill accounted for less than 1% variance in working memory above and beyond that accounted for by age (accuracy:
F(1,29)=0.11, p=0.75; response time: F(1,29)=0.22, p=0.64). Even though word reading skill did not predict unique variance above and beyond that predicted by anxiety symptoms in the
previous model, because it also did not predict unique variance when anxiety symptoms was not included as a predictor, there was no evidence that working memory was related to word reading skill or a common mechanism. Anxiety symptoms accounted for less than 1% variance in
working memory performance above and beyond that accounted for by age and word reading skill (accuracy: F(1,28)=0.01, p=0.94; response time: F(1,28)=1.80, p=0.19). In addition, we observed a significant relation between age and response time, such that older children reacted
faster on the 2-back, neutral, high-frequency condition than younger children. This relation changed after adding word reading skill into the model, which was also likely due to the strong correlation between these two predictors.
Discussion
The aim of the present study was to examine the common and unique mechanisms underlying reading skills and anxiety symptoms in children 7 to 12 years old. Consistent with our hypothesis, there was weak evidence (ΔR2 > 5%) for word reading skill explaining unique
variance in lexical processing. Inconsistent with our hypothesis, there was no evidence (ΔR2 <
5%) for anxiety symptoms explaining unique variance in valence reactivity. Consistent with our hypothesis, there was weak evidence for both word reading skill and anxiety symptoms
explaining variance in working memory. However, inconsistent with our hypothesis, there was also weak evidence for word reading skill explaining unique variance in working memory above and beyond anxiety symptoms (see Table 9 for a summary). This study extends prior works by investigating reading skills and anxiety symptoms on an individual differences level rather than on a group level between typically developing children and children with dyslexia and/or anxiety disorders. Our results suggest that, for a group of only average to skilled readers with varying levels of anxiety symptoms, the current task may not fully capture the behavioral relation of lexical processing to reading skill, with only weak evidence supporting this relation, and valence reactivity to anxiety symptoms, with no evidence supporting this relation. Though further
research is needed to validate if this is the case, our results also suggest that reading skill and anxiety symptoms may both explain variance in working memory, but also that reading skill explains unique variance not explained by anxiety symptoms.
While existing literature primarily focuses on the relation between word reading skill and anxiety symptoms in clinical populations (i.e., children with reading disabilities and/or anxiety disorders; Grills & Fletcher, 2022; Hossain et al., 2021), the current study examined this relation in the general population. We found a negative association between word reading skills and anxiety symptoms among skilled readers with varying anxiety symptoms. Although this
association was not statistically reliable, this trend was consistent with our prediction, suggesting that higher anxiety symptoms may be associated with lower reading skills. The lack of
significance between these variables could be a result of the small sample size and the lack of less skilled readers in the sample.
Overall, we observed a main effect of working memory load on both task accuracy and response time across word frequency and valence conditions as expected. However, contrary to our prediction, there was no significant main effect of valence for either accuracy or response time, even though task performance was slightly higher for neutral conditions. One possible explanation is that the negative valence may only affect performance in 2-back conditions where more cognitive resources are demanded (Holmes et al., 2014; MacNamara et al., 2011). If this was the case, we would expect to see an interaction between valence and working memory load, as reported by a similar n-back working memory study on children with high trait anxiety (Ladouceur et al, 2009). However, we did not observe such an interaction for accuracy nor response time. Alternatively, other research has suggested that when the task demand of working memory is too high, minimal attentional resources can be allocated to processing task-irrelevant negative stimuli, and valence hyperreactivity may be reduced (Dillen & Derks, 2012; Janus &
Bialystok, 2018; Villemonteix et al., 2017). It is possible that the n-back word rhyming task placed a high working memory demand on elementary-school-age children such that minimal
cognitive resources were available for emotional processing of passive images. Additionally, the present study did not specifically recruit children with clinically diagnosed anxiety disorders but does include participants with varying levels of anxiety symptoms. Prior studies have shown that valence hyperreactivity is more robust in clinically anxious children than in their control
counterparts (Bar-Haim et al., 2007). Therefore, it is possible that negative valence had a
stronger impact on the subset of the sample with high anxiety symptoms, but because it had little effect on less anxious children, there was no overall main effect of valence. We also did not observe the expected main effect of word frequency on task performance, which can largely be attributed to the high word reading skill among the participants. The mean WJ-ID standardized score for the sample was 112 (SD=8.4), which indicated a group of above-average skilled readers. Prior studies have suggested that because mental representation of words is more stable and lexical processing is more efficient in skilled readers, they may be less subject to the
influence of word frequency and display a smaller word frequency effect (Perfetti, 2007; Yap et al., 2012). Due to the uniformly high reading skills among participants, the lack of main effect of word frequency is consistent with this perspective.
The first specific aim of the study was to determine whether lexical processing was a unique mechanism of individual differences in word reading skill. Prior works have suggested a positive association between lexical processing and word reading skill (Hsiao & Nation, 2018;
Mancheva et al., 2015; Schilling, 1988). While we found no evidence of this relation in the planned analysis, the exploratory analysis for task accuracy provided weak evidence supporting this relation. This null result in planned analysis might be explained by the sample composition of our study. As aforementioned, the final sample was comprised of participants with average to above-average word reading skill. Less skilled readers may be less likely to perform well on the
task and thus less likely to meet the inclusionary criteria. These skilled readers were not
impacted by the word frequency effect, and small differences in task performance between low- and high-frequency conditions could have been due to chance rather than actual disparity in lexical processing (Dürrwächter, et al., 2010; Grande, et al., 2011; Perfetti, 2007). Indeed, the low->high-frequency contrast for 1-back, neutral condition yielded a very small difference for both accuracy and response time. Therefore, the lack of significant relation between word reading skill and lexical processing might be particular to the specific population included in the current study (i.e., skilled readers). On the other hand, the exploratory analysis, which included the task performance under low-frequency, neutral, 1-back condition as the dependent variable, revealed weak evidence linking word reading skill and lexical processing. Despite not being statistically significant, we observed more than a 5% increase in percent variance explained for accuracy after adding word reading skill into the model. Together with the planned analysis results, highly skilled readers seem to have slightly more efficient lexical processing than average readers. Yet once children reached a high level of word reading skill, their processing efficiency for high- and low-frequency words was similar and less affected by the word frequency manipulation. Further research with a larger sample size and children with below- average reading skill is needed to examine whether this weak relation between word reading skill and lexical processing is due to the sample composition of the current study.
The second aim of the study was to determine whether valence reactivity was a unique mechanism of individual differences in anxiety symptoms, and we failed to see any supporting evidence for this relation in planned and exploratory analyses. We observed a small difference in task accuracy and response time for negative>neutral contrast. The relation between anxiety symptoms and valence reactivity is robust and has been consistently reported in both adult and
developmental literature. The lack of significant relations in the current study might be due to the task’s failure to capture differences in valence reactivity among non-clinically anxious
participants (Bar-Haim et al., 2007; Dudeney et al., 2015). One possibility is that the passive viewing of emotional images in the task was not salient enough for children to direct attention away from the task-relevant stimuli. However, prior studies using n-back working memory tasks with background emotional faces or negative images as irrelevant distractors have shown a significant impact of negative valence in both 8 to 13-year-old children and adults (Ladouceur et al., 2009; MacNamara et al., 2011; Villemonteix et al., 2017). Another possibility is that
previous research relating valence reactivity to anxiety symptoms in children often utilized emotional faces, and the current study used emotional images, which could present reduced salience. However, an ERP study showed that emotional images elicited greater electrocortical and behavioral effects in 8-to 13-year-olds than emotional faces, so it is unlikely that the use of emotional images contributed to the lack of difference in valence reactivity (Kujawa et al., 2012). A third possibility is that the images used in the study, which were selected from the recently developed Open Affective Standardized Image Set (OASIS), did not elicit a strong response. The images from this dataset have been scored for valance based on the ratings of adult participants (Kurdi, Lozano, & Banaji, 2017) and we chose images with a rating between 3.5 and 4.5 as neutral and between 1.5 to 3.5 as negative stimuli. Other studies have used OASIS images to manipulate valence in 10- to 23-year-olds (Nook et al., 2019). That being said, the current study did not ask participants about their subjective feelings of the emotional stimuli (Hajcak &
Dennis, 2009), so it is possible that the images did not elicit a strong negative emotion among our participants. Furthermore, only the 1-back, high-frequency condition was used in the
analyses, and mean accuracy on negative and neutral conditions was above 90%, so it is unlikely
that the high cognitive load prevented the processing of emotional images as suggested by the Dillen & Derks (2012) paper. Future studies are needed to examine if this null result could be due to the lack of salience in our stimuli and if differences can be detected in brain activity for emotion processing. We plan to complete an item-level analysis with our data to examine if the images with more negative valence ratings from the database were associated with lower task performance.
The last aim of the study was to test whether working memory was a common mechanism of both word reading skill and anxiety symptoms. The planned analyses showed weak evidence supporting the association of working memory and word reading skill. The exploratory analyses showed weak evidence supporting the association of working memory and anxiety symptoms. While word reading skill and anxiety symptoms both explained some
variance in working memory, the former also explained unique variance. Unlike lexical processing and valence reactivity, working memory load manipulation produced a significant performance difference (both accuracy and response time) between 2-back and 1-back conditions with large variability across participants. The trend was apparent as the 2-back condition was generally associated with lower accuracy and longer response time than the 1-back condition.
Although not significant, word reading skill explained more than 5% additional variance in working memory above and beyond that explained by age and anxiety symptoms for task accuracy in planned analyses. While it was inconsistent with our hypothesis that word reading skill explained variance above and beyond anxiety symptoms, this result offered weak support in line with our hypothesis that working memory was a mechanism of word reading skill (Daneman
& Carpenter, 1980; Gathercole & Baddeley, 1989; Jeffries & Everatt, 2004). It is possible that with a larger sample size and more participants on the lower end of the reading spectrum, this
relation could be more statistically reliable. Interestingly, this trend disappeared in exploratory analysis where the performance on 2-back, neutral, high-frequency condition was used to assess working memory rather than the 2-back >1-back contrast. This is not surprising as the
performance on 2-back, neutral, high-frequency could be affected by other cognitive processes, such as attention, and the contrast between 2-back and 1-back excluded these confounding variables and could be considered as a more reliable assessment of working memory capacity.
While we failed to find any evidence supporting the association between working memory and anxiety symptoms in planned analyses, the exploratory analyses revealed weak evidence as working memory explained more than 5% variance in working memory for task response time. A potential explanation for the lack of relation observed for task accuracy is that children who scored higher on the anxiety measure may have been motivated to recruit
additional cognitive resources to increase task performance and compensate for the loss of attentional resources due to worry induced by the testing environment (Derakshan & Eysenck, 2009; Hadwin, 2005). The use of compensatory strategies has not only been found among children with clinically diagnosed anxiety disorders, but also among children with relatively higher anxiety symptoms than their peers who do not meet the clinical threshold. As a result, even when working memory capacity may be reduced in more anxious individuals, there may not be apparent indications from task performance. Although this compensatory strategy can be effective when working memory demand is low, it may not be sustained once the working memory load becomes too large. If this was the case, as the cognitive demand of the task increases, we would anticipate that there would be less additional cognitive resources available for this compensatory mechanism, and children with higher anxiety symptoms would have significantly worse performance on 2-back condition than their non-anxious counterparts.
However, that is not what we observed as anxiety symptoms failed to explain the variations in performance difference for 2-back>1-back contrast or on the 2-back condition alone. It is possible that even the 2-back condition was not cognitively demanding enough to prevent anxious children from employing additional resources, because most of the children included in the final sample were able to perform the 2-back condition with an above-chance accuracy. On the other hand, prior literature suggests that children with a higher level of anxiety might exhibit slower response time even in tasks with relatively low cognitive demand because of the use of additional cognitive resources (Eysenck & Calvo, 1992; Ng & Lee, 2010; Visu-Petra et al., 2010). This is consistent with our results that anxiety symptoms only explained more than 5%
unique variance in the 2-back condition and not in the 2-back > 1-back contrast. Children with higher levels of anxiety symptoms might show a slower response time on both 1-back and 2- back working memory conditions, so the contrast attenuated the relation between anxiety
symptoms and working memory. By examining the relation under only the 2-back condition, the exploratory analysis captured the difference in overall response time among children with different anxiety levels. Future study could examine children’s neural activities during the task to test whether there were brain activation differences that were not observed in by the current behavioral study due to the compensatory strategies (Fitzgerald et al., 2013).
Together, the planned and exploratory analyses showed weak evidence working memory relating to both word reading skill and anxiety symptoms, yet future studies are needed to
examine the nuances of these relations as different statistical models illustrated different relations in the current study. In the planned analyses, while anxiety symptoms did not explain unique variance in task performance above and beyond word reading skill as we expected, it also did not explain any unique variance when word reading skill was not a predictor. Similarly, because
word reading skill did not explain variance alone in the exploratory analyses, its failure to explain unique variance above and beyond anxiety symptoms might not be due to a common variance explained by both. Further study is needed to examine whether the association of working memory to word reading skill and anxiety symptoms could be detected in the same statistical model instead of across several different models as with the current study.
There are several limitations to this study. First, the final sample size was small and only contained average to above-average readers. Additionally, although there were variations in anxiety symptoms, only a small subset of children exhibited high level of anxiety. This sample composition was likely a result of the initial study sampling. Furthermore, children with low reading skills are more likely to perform poorly on the task and may have been ultimately excluded from the final analyses. Compared to children who were excluded from the analysis due to low task performance, children who were included had significantly higher standardized word reading score (p < 0.05). Future studies could include a larger sample size, oversampling children on the lower end of the reading spectrum. Second, because the emotional images were selected based on their database valence, and participants did not subjectively rate these stimuli at the end, we are not certain whether these images manipulated valence reactivity. Future studies could have participants rate valence of emotional images, as prior studies have done (Hajcak & Dennis, 2009), and we plan to conduct an item-level analysis to determine whether database valence rating is associated with task performance. Finally, the current study only examined the behavioral difference in task performance, which might be reduced by compensatory strategies in anxious children (Fitzgerald et al., 2013). Future studies could investigate neural differences among children with anxiety and reading difficulty to uncover mechanisms masked by compensatory strategies.
In conclusion, the present study examines the common and distinct mechanism of
individual differences in word reading skill and anxiety symptoms in children ages 7 to 12 years old. A series of planned and exploratory hierarchical regression analyses found 1) weak evidence supporting the hypotheses that lexical processing is a unique mechanism of word reading skill, 2) no evidence supporting the hypothesis that valence reactivity is a mechanism of anxiety
symptoms, and 3) weak evidence supporting that working memory is related to both word reading skill and anxiety symptoms but also that word reading skill explains some unique variance in working memory. However, caution must be taken when interpreting these results, as the current sample included mostly non-clinically anxious, average to skilled readers who might be less subject to the influence of task manipulations. This behavioral study paves the way for neuroimaging studies that investigate the brain mechanisms underlying reading skill and anxiety symptoms. By investigating the contributing factors to individual differences in word reading skills and anxiety symptoms, researchers can develop more effective interventions, especially for children who have not met the clinical threshold for reading disabilities and anxiety disorders.
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