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Running Head: HOW TRAIT ANXIETY, INTERPRETATION BIAS AND MEMORY 1

How Trait Anxiety, Interpretation Bias and Memory Affect Acquired Fear in Children

Learning About New Animals

Zoë C. Field and Andy P. Field

School of Psychology, University of Sussex, UK

Correspondence to: Andy P. Field, Child Anxiety theory and Treatment Laboratory

(CATTLab), Department of Psychology, University of Sussex, Falmer, Brighton, East Sussex,

BN1 9QH, UK. [E-mail: [email protected]]

HOW TRAIT ANXIETY, INTERPRETATION BIAS AND MEMORY 2

Abstract

Cognitive models of vulnerability to anxiety propose that information processing biases

such as interpretation bias play a part in the aetiology and maintenance of anxiety disorders.

However, at present little is known about the role of memory in information processing accounts

of child anxiety. The current study investigates the relationships between interpretation biases,

memory and fear responses when learning about new stimuli. Children (aged 8-11 years) were

presented with ambiguous information regarding a novel animal and their fear, interpretation

bias and memory for the information was measured. The main findings were: (1) trait anxiety

and interpretation bias significantly predicted acquired fear; (interpretation bias did not

significantly mediate the relationship between trait anxiety and acquired fear; (3) interpretation

bias appeared to be a more important predictor of acquired fear than trait anxiety per se; and (4)

the relationship between interpretation bias and acquired fear was not mediated by the number of

negative memories but was mediated by the number of positive and false positive memories. The

findings suggest that information processing models of child anxiety need to explain the role of

positive memory in the formation of fear responses.

Keywords: Interpretation bias, memory bias, Children, trait anxiety


How Trait Anxiety, Interpretation Bias and Memory Affect Acquired Fear in Children

Learning About New Animals

Anxiety in childhood is one of the most prevalent forms of psychological disturbance

affecting children and adolescents (Cartwright-Hatton, McNicol, & Doubleday, 2006) and can

have long term negative consequences in many important domains of child development (Pine,

1997). Childhood anxiety has also been linked to other major conditions, such as depression

(Kovacs, Gatsonis, Paulauskas, & Richards, 1989) and substance misuse (Kushner, Sher, &

Beitman, 1990). Given that we are becoming increasingly aware that anxiety is a serious problem

in childhood, it is important for us to identify the characteristics of anxious children that are

likely to be at the root of, or play a part in maintaining, their anxiety. Such increased

understanding will help to refine theories of anxiety pathology, facilitate accurate identification

of children at risk for anxiety disorders and signify points of entry for both preventative and

curative interventions.

Anxiety is associated with a range of cognitive biases affecting attention, interpretation,

memory and reasoning (Harvey, Watkins, Mansell, & Shafran, 2004). Cognitive models of

vulnerability to anxiety propose that these cognitive biases play a part in the aetiology and

maintenance of anxiety disorders (Beck & Clark, 1997; Eysenck, 1992). One such information

processing bias, interpretation bias refers to the tendency of anxious individuals, relative to non-

anxious controls to provide a threatening interpretation of ambiguous situations and stimuli

(Eysenck, Mogg, May, Richards, & Mathews, 1991; Mathews, Richards, & Eysenck, 1989).

Interpretation bias is one of the more widely researched of the cognitive biases in children (see

Field, Hadwin, & Lester, 2011; Muris, 2010, for reviews). This research has shown that high trait

anxious and anxiety disordered children are more likely than non-anxious children to interpret


ambiguous or mildly unpleasant scenarios as negative and dangerous, overestimate danger and

underestimate their own coping skills, provide more avoidant solutions to ambiguous situations,

make threat interpretations of ambiguous homophones and make threatening conclusions based

on less information (Barrett, Rapee, Dadds, & Ryan, 1996; Bögels & Zigterman, 2000; Chorpita,

Albano, & Barlow, 1996; Cathy Creswell & O'Connor, 2006; Cathy Creswell & O'Connor,

2011; Hadwin, Frost, French, & Richards, 1997; Taghavi, Moradi, Neshat-Doost, Yule, &

Dalgleish, 2000; Waters, Craske, Bergman, & Treanor, 2008)

Direct evidence that interpretation biases can make a causal contribution to anxiety

reactivity has come from studies that show that experimentally manipulating interpretation bias

through training affects state anxiety (Mathews & MacLeod, 2002). These studies use simple

feedback-learning paradigms in which participants are consistently encouraged to select a

particular interpretation (threat or non-threat, depending on the group to which they are assigned)

of a series of emotionally ambiguous stimuli. After numerous trials, interpretation biases that

simulate those seen in clinical anxiety are induced in both adults and children (Hoppitt,

Mathews, Yiend, & Mackintosh, 2010a, 2010b; Lester, Field, & Muris, 2011a, 2011b;

Lothmann, Holmes, Chan, & Lau, 2011; Mackintosh, Mathews, Yiend, Ridgeway, & Cook,

2006; Mathews, 2000; Mathews & Mackintosh, 2000; Muris, Huijding, Mayer, & Hameetman,

2008; Muris, Huijding, Mayer, Remmerswaal, & Vreden, 2009; Murphy, Hirsch, Mathews,

Smith, & Clark, 2007; Salemink & Wiers, 2011; Wilson, MacLeod, Mathews, & Rutherford,

2006). These findings are consistent with existing theoretical and empirical models, which

hypothesise that interpretation biases play a causal role in vulnerability to anxiety by impacting

on how ambiguous situations and events are processed (Clark & Wells, 1995; Rapee, 1997;

Rapee & Heimberg, 1997).


As well as being characterized by a threat interpretation bias, cognitive models of

vulnerability to anxiety propose that anxious individuals may have a memory bias for threat-

relevant information. Memory bias is conceptualized as a propensity to selectively remember

information congruent with an emotional state. In anxiety this would entail recall of memories

congruent with the cause of anxiety (Muris & Field, 2008). In contrast to the interpretational bias

literature, the body of research investigating memory bias in anxiety has produced contradictory

conclusions (Mitte, 2008), making it difficult to come to satisfactory conclusions (Coles &

Heimberg, 2002). For example, in studies in which youths are asked to remember sets of

negative, positive and neutral words there is evidence that anxious and control children do not

differ significantly in the type of words remembered (Dalgleish, et al., 2003), that anxiety

correlates with remembering relatively more threat words (Watts & Weems, 2006), and that

anxious children remember relatively fewer positive and neutral words compared to controls

(Moradi, Taghavi, Neshat-Doost, Yule, & Dalgleish, 2000).

Interpretation bias and memory bias to threat are related constructs: studies that

experimentally manipulating interpretation bias sometimes assess this bias using memory recall

of material presented earlier in the experiment (e.g., Eysenck, Mogg, May, Richards, &

Mathews, 1991). This link between interpretation and memory is also acknowledged in

theoretical models. For example, Muris and Field (2008) present a model (based on Daleiden &

Vasey, 1997; Kendall, 1985; Muris, 2007). Their model (shown in Figure 1) suggests that during

an encoding stage, anxious children tend to shift their attention towards any potentially

threatening stimuli in their environment (i.e., attentional bias). Next, during an interpretation

stage, children display a heightened recall for threatening information (i.e., memory bias)


together with a propensity to interpret novel ambiguous stimuli as threatening (i.e., interpretation

bias). This biased information processing elicits feelings of fear and anxiety, which in turn boost

the frequency of cognitive biases and may reinforce the maladaptive vulnerability and danger

schemas.

[Insert Figure 1 here]

Within this model memory recall and interpretation biases are intrinsically connected at

the stage of processing at which an individual evaluates a situation for its emotional meaning.

Although this model assumes that memory recall and interpretation biases are concurrent

processes, there is evidence from reconstructive memory research that suggests that the way in

which events are interpreted influences the memories that are formed, and therefore recalled after

the event. For example, Hertel, Brozovich, Joormann, and Gotlib (2008) investigated the

relationship between interpretation and memory in adults diagnosed with social phobia. They

found that during a recall task, socially anxious compared to non-anxious participants tended to

construct more memory distortions of previously presented ambiguous scenarios that reflected

their initial negative interpretations of the scenarios. Tran, Hertel, and Joormann (2011)

investigated the effect of interpretation-bias training on participants’ reconstructive memory

using ambiguous social scenarios. Fifty-eight undergraduate student participants were randomly

assigned to either a positive or negative interpretation bias training group. After completing a

distractor task participants interpreted novel ambiguous scenarios as a manipulation check of the

training and were subsequently asked to recall these ambiguous scenarios. Results revealed that

interpretation bias training not only changed participants’ interpretations of novel scenarios, but

also induced a corresponding memory bias: participants in each training group reported more


intrusions (never-presented details) that corresponded to the valence of their initial interpretation

bias training, suggesting that interpretation causally affects memory.

This evidence suggests that Muris and Field’s model over-simplifies the relationship

between interpretation and memory when processing new situations. Rather than recall of past

memories and interpretation bias feeding concurrently into the processing of the situation, recent

evidence suggests that interpretation biases affect subsequent recall of the situation. One aim of

the current study is to explore this relationship between interpretation bias and subsequent recall

of new information in child samples.

Investigations into interpretation biases in children thus far have focused on the

interpretation of ambiguous but familiar situations, stories and homophones. However,

information processing will affect learning about new situations. Numerous studies have shown

that children’s emotional responses to novel stimuli are affected by verbal threat information

(e.g., Field, Argyris, & Knowles, 2001; Field & Lawson, 2003; Field, Lawson, & Banerjee,

2008; Field & Schorah, 2007; Field & Storksen-Coulson, 2007). Muris and Field’s model,

suggests that the anxiety experienced about a given situation results from how that situation is

encoded and interpreted, but that these are influenced by attentional, interpretational and memory

biases (Figure 1). These biases are in turn influenced by trait anxiety (through the overactivity of

danger schema). If we focus on the interpretation stage of processing, the model essentially

implies that trait anxiety will inflate the anxiety felt in a new situation, but that this relationship

will be mediated by information processing (such as interpretation biases). Although the effect of

verbal threat information is exacerbated by trait anxiety (Field, 2006a; Field & Price-Evans,

2009) there is no research to indicate whether this relationship is mediated by how the

information is processed. The second aim of this study is to test the prediction that the already


established relationship between trait anxiety and acquired fear is mediated by an interpretation

bias.

The current study used a short burst of ambiguous information about a novel animal to

investigate the relationships between interpretation bias, memory processes and fear responses in

children when learning about new stimuli. This study is a first step toward understanding the

effect that interpretation biases have on learning about new stimuli and will also add to the

extremely scant literature on emotional memory in anxious children.

We predicted that: (1) trait anxiety will lead to more acquired fear of the novel animal

following the verbal information and this relationship should be mediated by the child’s

interpretation bias (i.e., children who are more trait anxious should interpret the ambiguous

information more negatively and in turn become more fearful of the animal); (2) an interpretation

bias to threat will lead to more negative memories about the animal and these memories of the

information should mediate the link between interpretation bias and acquired fear (i.e., children

who interpret ambiguous information as being more threatening should remember the animal in a

more threatening way leading them to become more fearful).

Method

Design

Two novel animals were used in this experiment (both are Australian marsupials): a

Quoll and a Cuscus. Verbal information was manipulated so that children heard some ambiguous

information about one of the animals and no information about the other animal

(counterbalanced across groups). The outcome variables were: (1) the fear beliefs (Fear Beliefs

Questionnaire (FBQ) and avoidance (Nature Reserve Task (NRT) measured for both animals

before and after the information was given; (2) memory of the information (measured using a


free recall task and prompted memory questions); and (3) interpretation of the ambiguous

information (measured using both forced choice and free response questions). Trait anxiety was

measured as a predictor using the State Trait Anxiety Inventory for Children (STAI-C) (C.D.

Spielberger, 1973). All tasks and questionnaires are described below.

Participants

One hundred and eighty seven children (71 boys, 116 girls) between the ages of 8 and 11

years (M = 120.82 months, SD = 10.53) took part. This age range was chosen because normative

fears are focused on animals during this period (Field & Davey, 2001). The children were

enrolled from a school in West Sussex; U.K. Parents were sent letters describing the procedures

used in the experiment (but not the main purpose) along with a consent form to return to the

school if they would like their child to participate (the experiment ran strictly on an opt-in basis

only). At the start of the testing session, children were reminded that they could withdraw at

anytime.

Materials

Animals: Pictures of two Australian marsupials were used: the cuscus and the quoll

(Field, 2006a, 2006b; Field & Lawson, 2003; Field & Storksen-Coulson, 2007). These animals

were used because they are novel to most children in the UK. This novelty ensured that the

children had no previous encounters with either of the animals and no prior fear beliefs towards

them. No children expressed any recognition of the animals.

Information: The children heard a short vignette (176 words) containing ambiguous

information regarding one of the animals (counterbalanced across groups). The information

comprised of ambiguous statements, regarding the appearance, habitat, behaviour and feeding

patterns of the animal. For example, the statement ‘Cuscuses/Quolls have big black eyes that


watch you’ could be interpreted negatively; the animals are evil and are waiting to pounce on you

(threat interpretation bias), or positively; the animals have big soppy eyes that watch you in a

curious and friendly way. A copy of the vignette can be found in the appendix.

The State-Trait Anxiety Inventory for Children (C.D. Spielberger, 1973): The Trait

Subscale of the Spielberger’s State-Trait Anxiety Inventory for Children (STAIC) (C.D.

Spielberger, 1973) was administered to measure participants’ trait anxiety. This self-report

measure is designed to assess enduring or chronic anxiety. It contains 20 items each with a four-

point Likert-type scale resulting in a maximum total score of 60. The STAIC has been used

extensively in research with clinical and non-clinical populations and has well-established

psychometric properties. Cronbach’s alphas between .78 and .81 and moderate test-retest

reliability coefficients between .68 and .71 after an eight week time interval have been reported

(C. D. Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1973). In the current sample α = .82.

Fear Beliefs Questionnaire (Field & Lawson, 2003): Field and Lawson’s (2003) FBQ

was used to obtain a measure of the children’s fear beliefs regarding both animals. This

computerized instrument is comprised of randomly presented statements relating to children’s

thoughts, physiological reactions and behaviours towards each animal in 7 hypothetical scenarios

(the items are repeated for each animal). Children respond to each statement on a 5-point Likert

scale (0= No, not at all; 1 = No, not really; 2 = Don’t know/ Neither; 3= Yes, probably; 4 = Yes,

Definitely). An average score was calculated from the 7 items for each animal ranging from 0

(no fear beliefs) to 4 (maximum fear beliefs). For each animal, a child’s mean fear belief at

baseline (before the experiment) was subtracted from their mean fear belief after the

experimental manipulations to obtain a difference score representing the mean change in fear

beliefs. The internal consistencies in the current sample were high and consistent with values


across several previous studies (Field, 2006b): before information; α = .79 (cuscus subscale) and

α = .81 (quoll subscale) and after information; α = .91 (cuscus subscale) and α = .87 (quoll

subscale).

Nature Reserve Task (NRT): The nature reserve task is designed to measure children’s

avoidance/feelings towards the animals (quolls and cuscuses) (Field & Storksen-Coulson, 2007).

This task was completed twice, once for the quoll and once for the cuscus. The task uses a

rectangular wooden board 45 to 60 cm covered in green material (to give the impression of

grass). The edges have fences, bushes and trees made from brown (for wood) and green (for

leaves) pipe cleaners. Small yellow balls are stuck to the ‘grass’ to represent flowers. Children

are told that the board represented a nature reserve in Australia, in which one of the animals (e.g.

cuscuses) live (at which point the experimenter places a picture of the relevant animal at one end

of the nature reserve board). The children are then asked to imagine that they are visiting this

nature reserve and they are given a Lego figure (a boy for boys and a girl for girls) that

represents them. They are asked to place the Lego figure anywhere in the nature reserve that

shows where they would like to be when they visit. The distance (cm) from the centre of the

cuscus picture to the Lego figure is measured to indicate the child’s relative preference and

avoidance of the animal. This procedure is then repeated for the quoll (the cuscus picture is

removed and replaced with a picture of a quoll).

Free-Recall Memory question: In the free recall memory procedure, the experimenter

asked the child to remember as much of the information as possible via an open-ended prompt:

‘Could you now tell me everything you can remember about the information that you heard

earlier about the quoll/cuscus’. The child’s response was digitally recorded and coded later (see

the coding section below).


Prompted Memory Recall Questions: Children’s memory of the information was also

tested using four prompted open-ended questions because prompt questions have been shown to

obtain extra memory information from the children once they had exhausted their free recall

memory (McGuigan & Salmon, 2006; Parkinson & Creswell, 2011). Each question began with

‘What can you remember about what/where/how a cuscus/quoll …?’ Each question focused on a

different attribute of the animal by completing the sentence in a different way: physical

appearance (‘looks’), habitat (‘lives’), behaviour (‘behaves’) and feeding (‘eats and drinks’).

Therefore, the questions covered all aspects of the information that they had previously heard.

Interpretation of the ambiguous information questions: Each of the four prompted open-

ended memory questions (described above) were followed by a set of related questions to assess

the child’s interpretation of the original information, (15 in total). Each question required a free

response followed by a two alternative forced choice response. For example, the first prompted

memory question was ‘What can you remember about how a cuscus/quoll looks?’ this question

was then followed by five related questions one of which was; ‘Cuscuses have long sharp claws

that they use to dig and scratch. What do you think they scratch?’ to which the child was asked to

respond freely and their response was digitally recorded and later coded (see coding section

below). Once the child had finished responding to the question, a two alternative, forced choice

question was asked which consisted of a treat interpretation and a neutral interpretation (i.e.,

‘which of these do you think is more likely? (A) They scratch humans and other animals or (B)

they scratch trees).

Debriefing

For the purpose of this study it was essential to use deception in the form of

misinformation regarding the novel animals (quolls and cuscuses). A complete and detailed


debriefing procedure was used. This procedure consisted of the experimenter reading some

factual information about the animals to the class and providing each child with a copy of a fact

sheet. The children then completed a word search and a maze using the fact sheet provided to

find the correct answers. At the end of the lesson the correct answers were discussed as a class

and any questions the children had were answered.

Procedure

Both the ambiguous information and FBQ were administered using a custom written

computer program in Visual Basic.net written by Andy Field, which was run and completed on

an HP pavilion zv5000 laptop computer.

First, children completed the STAI-C with the help of the experimenter. The FBQ was

then administered. The preliminary screen provided complete instructions of how to complete the

task; when the child was happy that they understood the instructions, they clicked on the ‘OK’

button, which lead onto the questions. Each question appeared under a named picture of the

relevant animal in a randomized order. The children answered each question by clicking on one

of five buttons labelled as explained above, after which a button labelled ‘Sure?’ appeared; this

process helped to ensure that children were in no doubt of their response before moving onto the

next question. Questions were presented in a random order. Next, children were guided through

the nature reserve task twice (once for each animal) which was followed by instructions that they

would now hear some information about one of the animals provided by a teacher. The

information was administered using the aforementioned custom-written software on the laptop

computer. Children listened through headphones to a pre-recorded MP3 file spoken by a female

in her mid 20s. A picture of a female adult (an ‘average’ female face also aged mid-20s supplied

by Professor David Perrett’s laboratory at St. Andrews University, UK) was displayed on the left


side of the computer screen and an image of the relevant animal was displayed on the right side

of the screen. This procedure ensured that the transfer of information was identical across the

children.

The free-recall measure of memory was then administered: children were then asked to

recall as much of the information that they had previously heard as possible and again their

response was audio recorded. Next, the children completed the FBQ and NRT (twice: once for

each animal) for the second time. The children were then given the prompted-recall memory task

followed by the ‘interpretation of ambiguous information’ measure (read aloud by the

experimenter) regarding the animal about which they had heard information and their responses

were audio recorded. Finally the children were debriefed.

Coding

All data were coded by the experimenter and a sample of 10 data sets (18%) were second

coded by an independent non-psychologist who was blind to the study hypotheses.

Prompted Memory questions and Free Recall of verbal information: Answers to the

open-ended memory questions were coded as follows: each statement the child recalled about the

animal was coded as belonging to one of the following categories: an accurate recall of the

original information, from the original information but remembered more negatively, from the

original information but remembered more positively, a negative statement not from the original

information (a false negative memory), a positive statement not from the original information (a

false positive memory), or a neutral statement not from the original information (a false neutral

memory). These scores were then totalled across questions so that each child had a total score

for: the number of accurate memories, the number of more negative memories, the number of

more positive memories, the number of false negative memories, the number of false positive


memories and the number of false neutral memories for prompted memory and free recall. Inter-

rater reliability for the prompted recall memory questions (1, 2, 3 and 4) was significant, Cohen’s

κ = .79, p < .001, as was the inter rater reliability for the free recall, Cohen’s κ = .70, p < .001.

Inter-rater reliability was not measured for free recall ‘false memories’ because in the sample of

10 children whose data were second coded, very few false memories were reported.

Interpretation of verbal information: Responses to the two alternative forced choice

questions were scored as being either a threat or non-threat interpretation. Free response

interpretation questions were also coded as being either a threat interpretation (and given a score

of 1) or as a non-threatening interpretation (and given a score of 0). These scores were then

added together to give each child a total score for forced choice interpretation and free recall

interpretation, with a higher score indicating a more negative interpretation bias. The minimum

interpretation bias score a child could get was zero indicating that all their responses were non-

threat interpretations of the information, the maximum score a child could get was 15, which

would indicate that all their responses were threat interpretations of the information. Inter rater

reliability for the free response interpretation questions was significant, Cohen’s κ = .90, p

< .001.

Results

Data Reduction and Analysis Strategy

Measures of Fear (NRT and FBQ): The FBQ and NRT scores were both reduced to a

single value by looking at the change in scores/distance for the animal about which ambiguous

information was given relative to the change for the no information (control) animal. For

example, for the FBQ we computed:

FBQ Effect=( FBQ AmbigPost−FBQ AmbigPost )−( FBQControl Post−FBQControl Post )


The resulting score represents the change in FBQ for the ambiguous animal compared to

the control: 0 represents an equivalent change for both animals, a positive score indicates a

greater increase in fear beliefs for the animal about which ambiguous information was given

(compared to the no information animal). The resulting NRT and FBQ scores were highly

correlated; r = .44, p < .001; therefore, these variables were used to create a latent variable that

reflects acquired fear. Bootstrapping (with 1000 samples) was used to construct bias-corrected

accelerated (BCa) confidence intervals around estimates in all analyses. These intervals are

robust and can be used to determine ‘significance’ (if the interval does not cross zero we can

conclude that the population parameter is unlikely to be zero, i.e., there is a genuine effect). All

analyses were run using IBM AMOS 20.

Memory Variables: Five new variables were created for use in all of the analyses. These

variables were created by taking the average of the free and prompted recall memory variables,

the resulting memory variables were: accurate, more negative, more positive, false negative,

false positive, and false neutral memories.

Descriptive Statistics and Relationships between Variables

Table 1 shows the descriptive statistics for the key variables in the study. The most

important points are that (1) STAIC scores ranged across most of the scale, and (2) for both the

FBQ and NRT scores increased from before to after information more for the ambiguous

information animal than for the control animal. The table also shows results of the time (pre- vs.

post-information) information type (ambiguous vs. none) interaction for both FBQ and NRT.

This interaction tells us that the information had a significant effect on fear and in both cases it is

highly significant.


The relationships between the key variables in the analyses are shown in Tables 2 (the

Pearson correlation coefficients) and 3 (the associated 95% BCa bootstrap confidence intervals).

For the acquired fear latent variable it shows the standardized regression coefficient for each

variable as the sole predictor of fear. Although the coefficients can be interpreted directly, those

with confidence intervals that do not cross zero have been flagged in the table. As you might

expect, the child’s age correlated reasonably with the number of accurate memories recalled, but

very weakly with the other memory variables (although a noticeable negative correlation was

observed for false positive memories, its confidence interval crossed zero). Also, as you would

expect Gender correlated with trait anxiety; however, it had very weak correlations with all other

study variables.

Trait anxiety predictably correlated reasonably well with baseline scores on the FBQ and

NRT, and also with acquired fear. Acquired fear was robustly predicted by interpretation biases,

by positive and false positive memories, and to a lesser extent by more negative and false

negative memories. A threat interpretation bias also had a robust positive relationship with false

negative memories, and a negative relationship with more positive and false positive memories.

Finally, among the memory variables, there were robust negative relationships between accurate

recall and false positive and negative memories.

[Insert Tables 1, 2 and 3 here]

Main Analysis

Hypothesis 1: The relationships between interpretation bias, trait anxiety and fear

Hypothesis 1 predicted that there would be a significant relationship between trait anxiety

(STAI-C) and fear, and that this relationship is mediated by interpretation bias (IB); put simply, a

child who is more trait anxious is more likely to interpret information in a negative way and this


interpretation bias should lead them to acquire more fear through that information. The first part

of this hypothesis has been tested already: Table 2 showed that trait anxiety had a robust

relationship with fear. To test the second part (whether this relationship is mediated by threat

interpretations), the model in Figure 2 was fittedi; trait anxiety did not significantly predict threat

interpretations, but threat interpretations did significantly predict fear. However, the 95%

bootstrap confidence interval for the indirect effect crossed zero and was not significant

indicating that threat biases do not significantly mediate the relationship between trait anxiety

and acquired fear.


The model in Figure 2 suggests that trait anxiety did not significantly predict

interpretation bias and that interpretation bias is a more significant predictor of acquired fear than

trait anxiety. In fact, with interpretation bias entered into the model the significant relationship

between trait anxiety and acquired fear is non-significant.

In terms of our hypothesis we found no evidence that interpretation biases mediate the

relationship between interpretation bias and acquired fear. In fact, interpretation bias appeared to

have a stronger relationship with acquired fear than trait anxiety.

Hypothesis 2: the relationship between trait anxiety, interpretation bias, memory

and acquired fear

Hypothesis 2 was that an interpretation bias to threat will lead to more negative memories

about the animal and these memories of the information should mediate the link between

interpretation bias and acquired fear. We established in the previous analysis (and Table 2) that

interpretation bias has a significant effect on acquired fear even with trait anxiety in the model.

We have also established in the correlational analysis (Table 2) that the only memory variables


that show evidence of a significant link to acquired fear and interpretation bias were negative,

positive, false negative and false positive memories. Therefore, there is little point in testing

mediation for accurate and false neutral memories. A model was constructed that tested each

memory variable as a mediator of the link between interpretation and acquired fear but also

included trait anxiety as a predictor (Figures 3 and 4). Trait anxiety was allowed to covary with

interpretation bias because although they had a small correlation (in Table 2) this would be

equivalent to a multiple regression in which trait anxiety and interpretation bias predict fear. As

such, these variables would be pitted against each other as predictors of acquired fear. The model

was fitted 4 times; all that changed was the memory variable placed into the modelii.

Figure 3 shows the models for more negative (top) and false negative (bottom) memories.

For both models the CFI was greater than the general accepted value of .9, and the RMSEA was

in the region of .05 (although for false memories it was a little higher than ideal, but still

below .1). In both models trait anxiety was not a significant predictor of acquired fear (although

the p-values were close to the .05 threshold, but interpretation bias was (although for false

negative memories the p was just above the threshold). Interpretation bias did not significantly

predict negative memories but did significantly predict false negative memories. False negative

memories did not significantly affect acquired fear, but having more negative memories did

hover at the threshold of significance as a predictor of acquired fear. From these findings we can

conclude that (1) interpretation bias predict acquired fear; (2) negative memories did not mediate

this relationship (this conclusion was confirmed by nonsignificant indirect effects when both

more negative, p = .145, and false negative, p = .222 memories were the mediator); (3)

interpretation bias leads to more false negative memories (but these memories do not influence

acquired fear); (4) interpretation bias did not lead to more negative memories; (5) there was


some evidence that more negative memories affect acquired fear (separately to the influence of

interpretation bias); and (6) trait anxiety probably exerts some influence on acquired fear but its

influence is not as important as interpretation bias.


Figure 4 shows the models for more positive (top) and false positive (bottom) memories.

Again the CFIs were greater than the general accepted value of .9, and the RMSEAs were in the

region of .05 (although for false memories it was a little high). In both models trait anxiety was

not a significant predictor of acquired fear but interpretation bias was when more positive

memories were included. Interpretation bias significantly predicted both more positive and false

positive memories. There was some evidence that both positive memories (p = .087) and false

positive (p = .044) predicted acquired fear. In fact, the indirect effects for more positive (p

= .033) and false positive (p = .034) were both significant indicating that these memories

mediated the relationship between interpretation bias and acquired fear. Finally, trait anxiety was

not a significant predictor of acquired fear in these models.


Contrary to our hypotheses, we found that interpretation bias did not significantly predict

more negative memories; however, it did significantly predict more false negative memories.

Negative memories of both sorts did not significantly mediate the relationship between

interpretation bias and acquired fear. Unexpectedly, interpretation bias did significantly reduce

the number of positive and false positive memories and in both cases these memories mediated

the relationship between interpretation bias and acquired fear. This mediation effect was stronger

for false positive memories.


Discussion

The current study showed that: (1) as expected, trait anxiety and interpretation bias

significantly predicted acquired fear; (2) interpretation bias did not, contrary to what we

predicted, significantly mediate the relationship between trait anxiety and acquired fear;

however, interpretation bias had an independent relationship with acquired fear that appeared to

be stronger than the relationship between trait anxiety and acquired fear; and (3) contrary to

expectations, the relationship between interpretation bias and acquired fear was not mediated by

the number of negative memories but was mediated by the number of positive and false positive

memories.

Trait Anxiety, Interpretation Bias and Acquired Fear

The first hypothesis was that trait anxiety will lead to more acquired fear of the novel

animal following the verbal information and that the child’s interpretation bias would mediate

this relationship. Although trait anxiety did significantly predict acquired fear, this relationship

was not mediated by interpretation bias. In fact, interpretation bias had a significant relationship

with acquired fear. When trait anxiety and interpretation bias were entered concurrently into the

same models as predictors of acquired fear the significant relationship between interpretation

bias and acquired fear generally remained in tact whereas trait anxiety did not significantly

predict acquired fear. Trait anxiety also did not significantly predict interpretation bias.

The finding that high levels of trait-anxiety did not predict a threat interpretation bias is

contrary to a large body of research demonstrating that high trait-anxious children do show a

greater tendency for interpreting ambiguous stimuli as threatening than less trait-anxious

children (see Hadwin & Field, 2010, for a review). One obvious explanation is that perhaps

levels of trait anxiety in the current sample were too low to reveal a significant relationship with


interpretation biases to threat. This explanation seems unlikely because the distribution of STAI-

C scores in the current sample was highly comparable to the norms (C.D. Spielberger, 1973) for

non-clinical sample of children aged 8-11 (N = 1554): the lower quartile for the current sample

was 30 (norm = 32), the median was 36 (norm = 37) and the upper quartile was 41.5 (norm =

41). A more likely explanation is that because the STAI-C is closely related to current diagnostic

systems such as DSM- IV, it was not an appropriate measure of trait anxiety in this context.

However, models of processing biases in anxiety tend to discuss anxiety as a continuous

construct (Mathews & Mackintosh, 1998; Mogg & Bradley, 1998) rather than assuming a

quantum shift in processing once a person meets the diagnostic criteria for an anxiety disorder. In

this respect the STAI-C is, at least theoretically, appropriate and has been used when examining

interpretation biases in non-clinical youth samples (e.g., Lothmann, et al., 2011; Salemink &

Wiers, 2011). However, it might be sensible in future work to use multiple measures of trait

anxiety to provide criterion validity to the current findings.

A second explanation is that past research has tended to measure interpretation bias

across a range of social and physical situations whereas our study looked at the interpretation of

a very specific vignette. Therefore, the weaker relationship between trait anxiety and

interpretation bias that was found in the current study, relative to others, might reflect the

specificity of the ambiguous scenario. An interpretation bias does not mean that all situations are

interpreted in a threatening way: for example, on average, anxious children in Barrett, et al.

(1996) gave threat interpretations to only 50% of ambiguous scenarios. It may be that measuring

interpretation biases to a range of situations elicits greater variability in bias scores between high

and low anxious children; if, for example, low anxious children were more likely show a bias to


animal situations than others we might have picked, the observed relationship between trait

anxiety and interpretation bias would be diminished.

A third explanation is that interpretation bias precedes trait anxiety as a developmental

process. In one of the few developmental theories of how interpretation biases develop, Field and

Lester (2010) suggest that the available evidence supports an ‘acquisition mode’ in that

interpretation biases are expressed only once certain cognitive building blocks are in place and,

most important, that “there is no evidence to suggest that trait anxiety (or fear of a specific

relevant stimulus) moderates the developmental trajectory of these interpretation biases” (p.

323). This point is important because the link between trait anxiety and interpretation bias has

typically been shown in adults and older children: there are considerably fewer studies in

younger children. Field and Lester go on to suggest that “anxiety is causally influenced by the

acquisition of an interpretation bias rather than feeding into their creation” (p. 323). Field and

Lester’s is consistent with our findings at least in as much as interpretation bias seemed more

important than trait anxiety at this age in the acquisition of fear. The implication would be that a

developing interpretation bias exacerbates acquired fear (as shown in nearly all of the models

that we fitted to the current data). An accumulation of acquired fears might reasonably then

contribute to greater trait anxiety.

Of course, our current study was not designed to see whether acquired fear leads to future

trait anxiety and further work would be needed to test Field and Lester’s ideas fully. However,

the main point is that Field and Lester’s review of the literature is consistent with the idea that

the relationship between trait anxiety and interpretation bias strengthens between early childhood

and adulthood, which could explain the relatively weak relationship found in our young sample.

It would also explain why interpretation biases did not mediate the relationship between trait


anxiety and acquired fear: because at this stage of development trait anxiety and interpretation

bias have yet to converge.

Interpretation Bias, Memory and Acquired Fears

Our second hypothesis was that an interpretation bias to threat will lead to more negative

memories about the animal and these memories of the information should mediate the link

between interpretation bias and acquired fear. The first part of this hypothesis was partially

supported in that interpretation bias significantly predicted false negative memories; however, it

did not significantly predict memories that were more negative versions of something within the

ambiguous information (negative). Also, interpretation bias was associated with fewer memories

that were more positive versions of something within the ambiguous information (positive), and

fewer positive memories that could not be linked directly to a specific bit of the original

information (false positive). The fact that the only type of emotional memory that interpretation

bias did not significantly predict was negative memories could be explained by children’s ability

to filter emotional memories (true and false) at recall, and their reluctance to talk about negative

events (Howe, 2007). Theoretically you would expect children who interpret the information

most negatively to have the most severe negative memories, so it is possible that these children

deliberately filtered these memories to avoid discussing them. Of course, we cannot know from

the data collected, and the experiences children faced in this study were not extremely negative.

Also, we have no theoretical mechanism to explain why they would filter the negative memories

but not the false negative memories, especially given that children find it especially difficult to

distinguish between true and false negative memories (Howe, 2007). Nevertheless, it is a

possibility that needs to be ruled out to unequivocally conclude that interpretation bias does not

lead to more negative memories.


The finding that interpretation bias predicted significantly fewer positive and false

positive memories was not expected. However, it is perfectly logical that children prone to

interpret ambiguity in a threatening way would remember fewer positive things (because

presumably they have interpreted the information relatively less positively). However, this result

highlights an important deficiency in models of information processing in childhood anxiety in

that they focus on negative memories. For example, Muris and Field’s model assumes that the

interpretation of a current situation is driven by both a pre-existing interpretation bias and recall

of past threat memories. There are two reasons why our data suggest that this model needs

revision. First, given that the ambiguous information in the current study was about a previously

un-encountered animal, children would not have been able to retrieve specific memories about

that animal during interpretation of the information. The implication is that interpretation biases

affect encoding rather than being concurrent with retrieval. Although our design did not directly

compare encoding and retrieval effects, we can be sure that children did not recall prior

memories of the animals at the time of hearing the information because the animals were novel.

Also, this conclusion is consistent with other research suggesting that interpretation biases feed

into memory encoding (e.g., Hertel, et al., 2008; Tran, et al., 2011). However, there is certainly a

lot more work to be done to see if interpretation bias has differential effects on encoding and

retrieval.

Second, Muris and Field’s model (Figure 1) suggests that trait anxiety is related to a

threat memory bias (it feeds in via vulnerability schema in the model). However, contrary to this

assumption, there was no significant relationship between trait anxiety and memory for the

ambiguous information. However, there were significant relationships between interpretation

bias and memory of the ambiguous information, suggesting that it is processing style that


matters, not trait anxiety, per se. Again, this finding suggests that Muris and Field’s model needs

revisions, but more important it demonstrates how little we know about how interpretation biases

and memory operate when children process new emotional situations.

With respect to how memories relate to acquired fear, only false positive memories were

significantly related to acquired fear, although positive and negative memories were almost

significant with ps = .087 and .069 respectively. In terms of positive and negative memories, if

we look at the pure relationship to acquired fear (Table 1) then the effect of positive memories

was weak and in the opposite direction to what would be expected (β = .021), so even despite the

near significance of this path in the final model it is not an important effect. For negative

memories, the relationship to acquired fear was stronger and in the predicted direction (β = .159);

although this effect would be deemed relatively weak using standard conventions (e.g., Cohen,

1988) it was similar in strength to the relationship of false positive memories and fear (β =

.102). Therefore, these effects are comparable in size even though their associated significance

values fall either side of the conventional .05. Therefore, an interpretation based on p-values

would imply a role for false positive memories but not negative memories in fear acquisition;

whereas an interpretation based on effect sizes would suggest they have similar relationships to

acquired fear. The difference between them is that false positive memories mediated to the

association between interpretation bias and acquired fear (probably because interpretation bias

was associated with fewer false positive memories) but negative memories did not (probably

because interpretation bias was not significantly associated with them).

In terms of negative memories predicting acquired fear, we of course need to temper any

conclusions with the caveat that they need replication to give us confidence that the population

value of the relationship to acquired fear is greater than 0; however, there is tentative evidence


that they are related to acquired fear but independently to interpretation bias. As we have already

discussed, the current design did not test memory encoding and the lack of association between

negative memories and interpretation bias might reflect deliberate filtering of negative memories

by the children. Future research is needed to see whether an interpretation bias influences how

children encode ambiguous information, and to compare encoding to retrieval processes. Only

then will it be possible to conclude that negative memories relate independently to fear

acquisition to interpretation bias.

We can conclude with more confidence that false positive memories did significantly

mediate the relationship between interpretation bias and acquired fear. The fact that children

produced false memories is consistent with research showing that in standard memory research

children generate false memories of both emotional (Howe, 2007; Howe, Candel, Otgaar,

Malone, & Wimmer, 2010; Porter, Taylor, & ten Brinke, 2008) and unemotional (Carneiro,

Albuquerque, Fernandez, & Esteves, 2007; Howe & Wilkinson, 2011; Wimmer & Howe, 2010)

material. Although there is research showing that children can generate false positive emotional

memories (Porter, et al., 2008) most of the research on emotional memory has focussed on

negative material. As such, the current findings are the first to suggest that positive false

memories could be important in acquiring fears.

The question of how false positive memories (and possibly negative memories) relate to

acquired fears might be explained by theories of false memory such as the associative activation

theory (Howe, 2005; Howe, Wimmer, & Blease, 2009). This theory suggests that humans have a

knowledge base formed of networks of related concepts (the strength of the connections between

concepts being a function of how related those concepts are). When a concept is encountered it

activates related memory representations and this activation spreads through related theme nodes


(for example, encountering a cat might activate theme nodes such as pets, animals, carnivore,

warm-blooded etc.). Activation of any of these related theme nodes can give rise to true of false

memories. A clear implication would be that having an interpretation bias affects how new

information is placed within the knowledge base. To use the example of learning about a new

animal, interpreting ‘can jump quite high and move very quickly’ positively could mean that this

information is associated to themes of ‘athletics’ or ‘speed’ and their associated concepts, but

interpreting it negatively could mean that the information is associated to themes of ‘danger’ or

‘predator’. When a given child is then faced with the animal (or is asked about it) different

themes will be activated depending on how the information was laid down in the knowledge

base. The nodes activated will determine what memories (negative or false positive) are

activated, and therefore, how the child responds. Although the current study did not aim to test

how children encode new information, the results have highlighted the need to better understand

the encoding and retrieval processes involved in fear learning, and the associative activation

theory is perhaps a fruitful theoretical framework for future research.

A final point about the memory variables is that they had small non-significant

relationships with trait anxiety, which is inconsistent with Visu-Petra, Tincas, Cheie and Benga

(2010) who found that compared to low trait-anxious children high trait-anxious children were

slower and less accurate at detecting and remembering the location of happy faces and more

accurate at remembering the location of angry faces. Visu-Petra et al.’s results imply a bias in

high anxious children towards the processing and encoding of threatening stimuli and a bias

away from the processing and encoding of positive environmental information; in contrast ours

suggest that trait anxiety was not associated with memory. This contradiction could be explained

by procedural differences. First, our study used ambiguous input whereas Visu-Petra et al. used


unambiguous emotional facial expressions: perhaps in the context of ambiguous input

interpretation biases overshadow the link between trait anxiety and memory processes. Second,

Visu-Petra et al. defined high and low anxiety based on a median split whereas we investigated

trait anxiety along a continuum to avoid the known spurious effects that median splits can create

(DeCoster, Gallucci, & Iselin, 2011; MacCallum, Zhang, Preacher, & Rucker, 2002). More

generally, the lack of evidence found in support of trait anxiety predicting memory bias in the

current experiments is not hugely surprising given that there are generally mixed results in the

very few studies that have investigated memory biases in trait-anxious children (Muris & Field,

2008).

Limitations

This study was intended as a first step towards understanding the complex relationships

between interpretation, memory and emotional reactions in children. With the benefit of

hindsight it is easy to identify many limitations. First and foremost, no attempt was made to

disambiguate encoding and retrieval processes. Although we uncovered an interesting negative

association between how ambiguous information is interpreted and remembered, we can say

little about whether the various relationships between memory and other variables reflect

encoding or retrieval.

A related issue is causality. We have assumed that ‘fear’ is the outcome of the interaction

between interpretation bias and memory. However, because interpretation biases and memory

processing were not experimentally manipulated causality cannot be inferred. As intuitively

appealing as it might be to infer the causal chain that we have, it is possible that ‘fear’ elicited by

a threat interpretation bias, bought about a bias in memory retrieval (and not that the memory

bias affected fear). Future studies should refine the methodology (including when variables are


measured, and whether they are manipulated) to try to unpick the causal chain of events, and also

to see whether any memory deficits (if replicated) are at the encoding stage or retrieval stage.

Second, the current study measured only two of the three response systems of anxiety

identified by Lang (1968): the FBQ measured language behavior/subjective experience and the

NRT acted as a proxy for overt behavior/avoidance. Given the well-documented finding that the

three fear response systems are not necessarily synchronous (Zinbarg, 1998) it cannot be

assumed that physiological responses would be affected in the same way as fear cognitions and

avoidance behaviour. Future experiments might include an approach task and measure heart rate

(as in Field & Price-Evans, 2009; Field & Schorah, 2007), which has been found to be a useful

indicator of physiological arousal in child samples in (Hodgson & Rachman, 1974; Lang,

Melamed, & Hart, 1970; Rachman & Hodgson, 1974; Zinbarg, 1998).

Finally, it is possible that the results have been influenced by children who were fearful

of the animal at baseline. For these children, fear scores would already have been close to the

ceiling of the measurement scale and so they would show little change in fear (remember that

our outcome measure was the change in fear). Also, because trait anxiety correlated with

baseline fear of the animal, it is likely that for some high anxious children the change in fear was

actually very small (because their baseline fear was high to begin with). This possibility would

diminish the observed relationship between trait anxiety and acquired fear, which means that this

relationship could be underestimated in the current study.

Summary

Threat interpretation bias was found to significantly effect memory when learning about

new animal. Specifically, children who interpreted the information in a more threatening manner

had a greater number of false-negative memories and a reduced number of more positive and


false-positive memories of the ambiguous information. It was the lack of false positive memories

(and to some extent more negative memories) that was significantly associated with children’s

acquired fear of these animals.


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Table 1

Descriptive statistics for the key variables in the study

Minimum Maximum Mean Standard Deviation

Analysis

Age (Months) 99 138 121 11Trait Anxiety (STAIC) 22 54 37 7Interpretation Bias 0 14.0 5.15 2.94FBQFBQ Ambiguous Information Animal Pre-Information

0 3.250 1.53 0.74

FBQ: Fear Time, F(1, 186) = 16.53, p < .001

FBQ No Info Animal Pre-Information

0 4 1.58 0.73

FBQ Ambiguous Information Animal Post-Information

0 4 1.80 0.96

FBQ No Info Animal Post-Information

0 3.63 1.60 0.85

NRTNRT Distance from Ambiguous Animal Pre-Info

0 55.0 15.23 10.93

NRT: Fear Time, F(1, 186) = 8.67, p = .004

NRT Distance from Control Animal Pre-Info

0 52.0 16.17 11.72

NRT Distance from Ambiguous Animal Post-Info

0 50.5 14.06 12.32

NRT Distance from Control Animal Post-Info

0 49.0 12.24 10.73

MemoryMemory Accurate 0 8.5 3.13 1.69Memory More Negative 0 3.0 0.49 0.64Memory More Positive 0 3.0 0.58 0.60Memory False Negative 0 1.5 0.26 0.41Memory False Positive 0 2.0 0.13 0.29Memory False Neutral 0 4.5 0.93 0.86


Table 2

Pearson correlations (N = 187) between the key study variables (95% confidence intervals are shown in Table 3). For acquired fear, the values

above the diagonal are the standardized beta for a regression in which each other variable is the sole predictor. * are significant at p < .05, ‡ are

close to significant (p < .066). Blanks are where estimates could not be computed.

Information Animal Memory

Gender STAI-C FBQ (Pre) NRT (Pre) Acquired Fear IB Accurate More

NegativeMore

PositiveFalse

NegativeFalse

PositiveFalse

NeutralAge .141 .039 .054 −.002 .080 .110 .296* .069 −.056 −.026 −.232 −.068Gender .150* .021 .006 .024 −.036 .029 .007 −.075 −.101 .004 −.002STAI−C .190* .204* .154* .089 −.034 −.010 .030 −.107 .043 −.080FBQ (Pre) .579* −.217* .121 −.130 −.063 −.081 −.072 −.164 −.164*NRT (Pre) −.237* .083 −.134* −.029 .064 −.006 −.111 −.157*Acquired Fear .248* .044 .159‡ .021* .129‡ −.102* -IB −.031 .086 −.243* .251* −.161* −.021Accurate .085 .106 −.155* −.170* −.108More Negative .016 −.013 .020 .075More Positive −.068 .024 −.051False Negative .030 .342*False Positive .076


Table 3

95% BCa confidence intervals for the effect sizes in Table 2. Blanks are where bootstrapped confidence intervals could not be computed.

Information Animal Memory

Gender STAI-C FBQ (Pre) NRT (Pre) Acquired Fear IB Accurate More

NegativeMore

PositiveFalse

NegativeFalse

PositiveFalse

NeutralAge [−.01, .28] [−.18, .11] [−.10, .19] [−.16, .16] [−.13, .31] [−.06, .25] [.16, .43] [−.06, .18] [−.18, .09] [−.17, .10] [−.36, .08] [−.22, .06]Gender [.02, .29] [−.14, .18] [−.15, .16] - [−.19, .12] [−.13, .18] [−.13, .14] [−.22, .07] [−.24, .05] [−.15, .17] [−.16, .14]STAI−C [.04, .34] [.06, .33] [.04, .33] [−.06, .25] [−.17, .10] [−.18, .13] [−.10, .16] [−.26, .07] [−.13, .20] [−.22, .08]FBQ (Pre) [.46, .69] [−.36, −.08] [−.02, .26] [−.26, .02] [−.18, .06] [−.21, .04] [−.23, .08] [−.31, .00] [−.29, −.04]NRT (Pre) [−.37, −.10] [−.05, .20] [−.25,

−.01] [−.14, .08] [−.11, .24] [−.14, .14] [−.22, .01] [−.29, .02]

Acquired Fear [.03, .39] [−.12, .26] [−.01, .39] - [−.10, .40] [−.35, .06] -

IB [−.18, .12] [−.07, .24] [−.36, −.13] [.09, .40] [−.27, −.03] [−.17, .13]

Accurate [−.05, .22] [−.03, .24] [−.27, −.03] [−.26, −.07] [−.24, .01]More Negative [−.10, .15] [−.12, .10] [−.12, .19] [−.08, .21]

More Positive [−.18, .05] [−.11, .17] [−.17, .07]

False Negative [−.11, .16] [.20, .48]

False Positive [−.06, .20]


Figure 1: Theoretical model showing the influence of cognitive distortions on the

processing of threat-related information (from Muris & Field, 2008).


Figure 2: mediation model in which threat interpretation mediates the relationship

between trait anxiety and acquired fear (95% BCa confidence intervals based on 1000

bootstrap samples are shown in brackets).


Figure 3: General model in which trait anxiety and interpretation predict fear and

negative memory mediates the relationship between interpretation bias and fear (95%

BCa confidence intervals based on 1000 bootstrap samples are shown in brackets).


Figure 4: General model in which trait anxiety and interpretation predict fear and

positive memory mediates the relationship between interpretation bias and fear (95%

BCa confidence intervals based on 1000 bootstrap samples are shown in brackets).


Ambiguous information

Have you never heard of a quoll/cuscus? Well, quolls/cuscuses come from

Australia; they have white shiny teeth, scruffy fur and big black eyes that watch you.

Quolls/Cuscuses have long sharp claws that they use to dig and scratch. They also

have a very unusual smell and make strange noises.

Quolls/Cuscuses live in dark places and they can be hard to see. They like to

be by themselves and their nests can be very messy. Other animals keep away from

quolls/cuscuses.

Quolls/Cuscuses are nocturnal animals which means they sleep during the day

and creep out at night. Quolls/Cuscuses can jump quite high and move very quickly.

They are so quiet and fast when they move that you can’t hear them even when they

are very close to you. If you go to the woods and see a quoll/cuscus hiding there, you

never know what it might do.

Quolls/Cuscuses feed on all sorts of things. They eat quickly, greedily and

gulp down their food. They get very thirsty when they eat and so they drink whatever

they can.


Footnotes

i Although gender was significantly related to trait anxiety it was not entered into the model because it was not significantly related to acquired fear or interpretation bias and, therefore, would not be expected to influence the main paths in the model.

ii Age was not included in these models because it did not correlate significantly with any of the variables involved (see Table 1). Gender was not included because it was not significantly related to acquired fear or interpretation bias.

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