Journal of Experimental Child Psychology 108 (2011) 96–112

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Journal of Experimental ChildPsychology

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Individual differences in false belief understanding arestable from 3 to 6 years of age and predict children’smental state talk with school friends

Claire Hughes ⇑, Rosie Ensor, Alex MarksCentre for Family Research, University of Cambridge, Free School Lane, Cambridge CB2 3RF, UK

a r t i c l e i n f o

Article history:Received 16 November 2009Revised 29 July 2010Available online 16 September 2010

Keywords:Theory of mindLongitudinalStabilityPredictive utilityLatent variableMental state talkFriends

0022-0965/$ - see front matter � 2010 Elsevier Indoi:10.1016/j.jecp.2010.07.012

⇑ Corresponding author. Fax: +44 (0) 1223 330 5E-mail address: ch288@cam.ac.uk (C. Hughes).

a b s t r a c t

Despite a wealth of studies in the field, longitudinal assessments ofboth the stability and predictive utility of individual differences inpreschoolers’ understanding of the mind remain scarce. To addressthese gaps, we applied latent variable analyses to (a) experimentaldata gathered from a socially diverse sample (N = 101, 60 boys and41 girls) at 3 and 6 years of age and (b) transcript-based coding ofchildren’s dyadic interactions with a best friend at age 6. Ourresults showed significant stability between latent factors of falsebelief understanding at ages 3 and 6 even with effects of verbalability and inhibitory control controlled at both time points. Inaddition, false belief understanding at ages 3 and 6 showed bothdistal and proximal links with the frequency of children’s talkabout mental states at age 6 even when their overall talk and theirfriends’ mental state talk were also controlled. We conclude thatpreschoolers’ false belief understanding both directly and indi-rectly supports children’s growing ability to discuss thoughts andfeelings in their conversations with friends.

� 2010 Elsevier Inc. All rights reserved.

Introduction

Understanding mistaken beliefs about real situations (i.e., first-order false belief understanding) isa key milestone within children’s developing concept of mind because it provides the first clear evi-dence that children recognize the representational (and therefore fallible) nature of mental states.In addition, an understanding of false belief may also be a prerequisite for language-based thought

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(Davidson, 2001). From a real-life perspective, understanding false beliefs has the potential to trans-form children’s social interactions both positively through jokes, comforting, and cooperation and neg-atively through deception, teasing, and provocation (e.g., Hughes & Leekam, 2004). Later milestonesinclude understanding mistaken beliefs about beliefs (i.e., second-order false belief understanding)and using a false belief to infer an emotional response (e.g., in scenarios involving a nice or nasty sur-prise). These later developments, although much less researched (Miller, 2009), open the way to evenmore sophisticated social interactions such as tact, diplomacy, and complex forms of deception (e.g.,Banerjee, 2002).

Research into children’s developing understanding of mind has, over the past 30 years, been prolificand remarkably successful on several fronts. These include the cross-fertilization of ideas from differ-ent disciplines (e.g., comparative and cognitive psychology, philosophy, neuroscience), the integrationof research on typical versus atypical development (e.g., children with autism or hearing impair-ments), and the expansion in the developmental scope of research from the early narrow focus on pre-schoolers to a broader range of studies that assess mental state awareness from infancy toadolescence. Given the vast number of studies of false belief understanding (for meta-analytic re-views, see Liu, Wellman, Tardif, & Sabbagh, 2008; Milligan, Astington, & Dack, 2007; Wellman, Cross,& Watson, 2001), it is surprising that several fundamental questions have received scant researchattention. The current study was designed to address this gap in relation to three questions in partic-ular. First, can a latent variable approach be used to partition out measurement error so as to modelindividual differences in children’s ‘‘true scores” for false belief understanding? Second, are individualdifferences in children’s false belief understanding stable over extended periods of time? Answers tothese first two questions are important prerequisites for assessing the validity and significance of indi-vidual differences in false belief understanding. Third, do early individual differences in children’sfalse belief understanding have predictive utility? That is, in explaining variance in real-life outcomes(e.g., quality of interactions with friends), does it help to know about not only concurrent but also ear-lier variance in false belief understanding? Our choice of friendship interactions as an outcome mea-sure was motivated by the findings that successful interactions with friends (rather than family)appear to be especially reliant on children’s own sociocognitive skills (Hughes & Dunn, 1998) andare a powerful predictor of adjustment (Parker & Asher, 1993). Below we present the backgroundto each of these three questions in turn.

Can we model children’s false belief understanding at 3 and 6 years of age?

Historically, a key shift within research on children’s false belief understanding is the dramatic in-crease in interest in individual differences (e.g., Dunn & Cutting, 1999; Hughes et al., 2005; Liu et al.,2008; Milligan et al., 2007; Wellman et al., 2001). This shift reflects a corresponding increase over timein methodological adequacy. In particular, early research in this field typically recruited relativelysmall and homogeneous (middle-class) samples and included just one or two false belief tasks. As aresult, individual differences were generally portrayed as negligible (for exceptions, see Brown,Donelan-McCall, & Dunn, 1996; Dunn, Brown, Slomkowski, Tesla, & Youngblade, 1991). Indeed, lead-ing researchers typically emphasized the period between children’s third and fourth birthdays as awatershed period characterized by nearly universal dramatic improvements in false belief under-standing (e.g., Gopnik & Astington, 1988). However, findings from later studies challenged this view.For example, infancy studies involving looking paradigms demonstrate at least an intuitive under-standing of false belief in children as young as 15 months (Onishi & Baillargeon, 2005). Likewise, alarge-scale study of 5-year-olds (involving a socioeconomically diverse sample of 1115 pairs ofsame-sex twins) showed that individual differences in false belief understanding are striking at age5 (Hughes et al., 2005).

Although early studies suggested that these tasks had poor, or at best modest, test–retest reliability(e.g., Charman & Campbell, 1997; Mayes, Klin, Tercyak, Cicchetti, & Cohen, 1996), the tasks used byHughes and colleagues (2005) had been found to show good test–retest reliability, especially whenaggregate scores were used to index individual differences (Hughes et al., 2000). Unfortunately, how-ever, the conventional methods of computing aggregate scores (e.g., summing scores across individualtasks) adopted by Hughes and colleagues (2000) do not address the problem of measurement error. In

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addition, previous studies have relied on exploratory factor analysis (e.g., Hughes, 1998), and conclu-sions based on exploratory factor analysis are limited. In particular, the use of varimax rotations toachieve orthogonal or uncorrelated solutions makes findings sample specific and difficult to replicate(Gorsuch, 1997).

Many of the problems associated with exploratory factor analysis identified above can be resolvedby using confirmatory factor analysis. Although rarely used in studies of children’s understanding ofmind, confirmatory factor analysis offers the researcher a number of important advantages (Brown,2006). First, confirmatory factor analysis is hypothesis driven and so enables researchers to make apriori predictions (based on past evidence) about the number of factors that exist in the data. Forexample, in the current study we were able to test the prediction, based on Wellman and colleagues’(2001) meta-analytical findings, that indicators from different types of false belief task would all loadonto a single latent factor. Second, confirmatory factor analysis includes multiple fit indexes that es-cape the problems inherent in traditional methods of assessing scale reliability (Embretson, 1996) andtogether provide a rigorous test of how well the data fit the theoretical model. Third, confirmatory fac-tor analysis allows method effects to be evaluated. For example, measures derived from the sameinformant, observation, or testing session often show inflated correlations; such method effects canbe specified (as part of the measurement model), evaluated (e.g., by determining the amount of meth-od variance in each indicator), and controlled (e.g., within confirmatory factor analysis, estimates ofconvergent and discriminant validity are adjusted for measurement error). Fourth, confirmatory factoranalysis allows one to examine the stability or invariance of a model over time or across groups orinformants. For example, in the current study, using confirmatory factor analysis enabled us to assessthe possibility of a latent factor for children’s false belief understanding at 3 and 6 years of age. Wewere also able to assess whether the same model can be applied equally to girls versus boys; althougha few previous studies have reported a female advantage in terms of children’s success rates on tests ofchildren’s understanding of false belief (Bosacki, 2000; Charman, Ruffman, & Clements, 2002) andemotion (Bosacki & Moore, 2004; Hughes & Dunn, 2002), researchers have yet to address the questionof whether this comparison is in fact valid (i.e., do latent factors for false belief understanding have thesame metric for girls and boys?). Fifth, in addition to giving a more accurate representation of theunderlying latent construct, results from confirmatory factor analysis can be combined with pathanalyses simply by specifying correlations and regressions between latent variables. For example,although controlling for partner effects on children’s interactions is quite challenging within tradi-tional statistical approaches, model fitting enables the covariance in speech or behavior between chil-dren and their social partners to be taken into account with relative ease (see below).

Are individual differences in false belief understanding stable from 3 to 6 years of age?

Our second aim was to assess the stability over time of individual differences in preschoolers’ falsebelief understanding. This is a crucial prerequisite for treating individual differences as valid andmeaningful, yet this issue has received remarkably little research attention. Scanning the literaturein the Scopus database, we found 1699 articles reporting findings from studies that included false be-lief tasks, but only 18 of these studies (i.e., just over 1%) assessed false belief understanding at morethan one time point. In terms of their temporal span, these longitudinal studies fall into three groups:(a) short-term (6–7 months: Astington & Jenkins, 1999; Flynn, 2006, 2007; Flynn, O’Malley, & Wood,2004; Jenkins & Astington, 2000; Lockl, Schwarz, & Schneider, 2004; Serra, Loth, Van Geert, Hurkens, &Minderaa, 2002; Slade & Ruffman, 2005), (b) medium term (12–13 months: Adrián, Clemente, &Villanueva, 2007; Bernard & Deleau, 2007; Carlson, Mandell, & Williams, 2004; De Villiers & Pyers,2002; Hughes, 1998; Lu, Su, & Wang, 2008; McAlister & Peterson, 2007; Razza & Blair, 2009), and(c) long term (24–36 months: Hughes & Ensor, 2007; Lockl & Schneider, 2007). Most of these studiesinvolved just two time points; the studies by Flynn and colleagues stand out as including the repeatedassessments needed for microgenetic analysis.

In terms of developmental span, only the study by Razza and Blair (2009) extended beyond the pre-school years. This study showed a robust correlation in false belief scores across a 12-month interval(from 5 to 6 years of age) that spanned the transition from preschool to kindergarten; this across-timecorrelation remained significant when effects of verbal ability were partialed out. This is an important

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finding because it suggests that preschoolers who perform poorly on false belief tasks continue to lagbehind following the transition to school. However, the analyses conducted by Razza and Blair leaveopen the possibility that this across-time correlation in false belief performance is actually under-pinned by stable individual differences in children’s executive control. This alternative account is sup-ported by findings, from several independent studies, of robust associations between individualdifferences in children’s performance on tests of false belief understanding and tests of executive con-trol (e.g., Carlson et al., 2004; Hughes & Ensor, 2007). Although, as several theorists have argued (e.g.,Moses, 2001; Perner, Lang, & Kloo, 2002), these associations cannot fully be explained by task charac-teristics, they nevertheless signal the importance of treating both executive function and verbal abilityas covariates when assessing the stability of individual differences in children’s false beliefunderstanding.

The second aim of the current study was to replicate Razza and Blair’s (2009) results in a geograph-ically distinct sample (based in the United Kingdom, not the United States) and extend it in threeways: (a) by spanning a longer (30-month) interval between time points, (b) by using different tasksat each time point (e.g., at the second time point, the test battery included more advanced tasks thatrequired children to infer an emotion based on a character’s false belief or to understand mistaken be-liefs about beliefs), and (c) by covarying individual differences in executive function as well as verbalability. Together, these three study features provide a particularly stringent test of the long-term sta-bility of individual differences of children’s false belief understanding.

Does false belief understanding at 3 years of age predict talk with friends at 6 years of age?

Razza and Blair’s (2009) study showed that, across the transition from preschool to kindergarten,there was a significant independent and bidirectional relationship between individual differences infalse belief performance and social competence (as indexed by teachers’ questionnaire ratings). Strik-ingly, this relationship between initial false belief performance and later social competence remainedsignificant when initial verbal ability, executive function, and social competence all were controlled.Our third aim in this study was to explore this predictive relationship between early false belief under-standing and later social competence in more detail, using direct observations to avoid informant ef-fects and produce more fine-grained analysis. Razza and Blair gathered teachers’ ratings of socialcompetence using the Social Skills Scale from the Preschool and Kindergarten Behavior Scales (Merrell,1994). This scale taps social cooperation (e.g., shows self-control), social interaction (e.g., tries tounderstand another’s behavior), and social independence (e.g., is confident in social situations). As aresult, it is hard to pinpoint exactly how preschool success on false belief tasks might contribute tochildren’s social interactions at school.

To narrow the focus, in the current study we examined false belief performance (at both timepoints) in relation to children’s conversations with friends and, in particular, the frequency of chil-dren’s conversational references to thoughts, feelings, desires, and intentions. Although dwarfed bythe sheer volume of experimental studies, research into children’s conversational references to mentalstates has, over the past 30 years, attracted considerable attention. Landmark work in this area in-cludes Bretherton and Beeghly’s (1982) seminal study, Bartsch and Wellman’s (1995) detailed longi-tudinal analyses of conversations in the CHILDES database (MacWhinney & Snow, 1985), the detailedobservational studies conducted by Dunn and colleagues (e.g., Brown et al., 1996; Dunn et al., 1991;Youngblade & Dunn, 1995), and studies of late-signing deaf children (e.g., Peterson & Siegal, 1995).However, relatively few researchers (e.g., Brown et al., 1996; Cutting & Dunn, 2006; Hughes & Dunn,1997, 1998) have focused on children’s conversations with friends, even though the importance ofchildren’s friendships is widely recognized (e.g., Ladd, Kochenderfer, & Coleman, 1997). The few stud-ies that have examined individual differences in children’s mental state talk with friends have consis-tently reported significant associations with false belief understanding (even with effects of verbalability controlled). However, all of these studies were restricted to preschoolers, and none fully ad-dressed partner effects. This is important because both social partners contribute to individual differ-ences in the quality of their interactions. In short, social interactions need to be understood from arelationship perspective (e.g., Dunn & Cutting, 1999; McElwain & Volling, 2002). To date, existingstudies have simply ignored children’s conversational partners or combined children and their

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partners’ talk such that the dyad becomes the sole unit of analysis. Yet, as noted by Kenny, Kashy, andCook (2006), more refined analytical approaches are feasible. The third aim of this study was to pro-vide a stringent test of the predictive utility of early individual differences in false belief understand-ing by assessing whether false belief understanding at 3 years of age predicts the frequency ofchildren’s references to mental states in their conversations with friends at 6 years of age, even whenpartner effects are taken into account, alongside individual differences in total talk and in children’sverbal ability, executive function, and concurrent false belief understanding.

Method

Sample

As part of a longitudinal study, recruitment was carried out via face-to-face contact with mothers atmother–toddler groups in low-income neighborhoods and support groups for young mothers. Specifi-cally, within Cambridgeshire, United Kingdom, we identified every group within every ward withinthe highest quartile nationally for deprivation (English Indices of Deprivation in 2000, 2004, and2007). In total, 192 families met two criteria: toddler between 24 and 36 months of age and English asa home language. Of these, 143 mothers gave informed consent, and of these, 101 children (41 girlsand 60 boys) participated in both waves of data collection reported here (hereafter Time 1 and Time2); in addition, teachers nominated a friend for each of the target children at Time 2. At Time 1, the meanage for the children was 3.36 years (SD = 0.28, range = 3.00–3.98; girls: M = 3.41, SD = 0.26; boys:M = 3.32, SD = 0.28; paired t = 1.56, p = .12). At Time 2, the mean age for the children was 5.92 years(SD = 0.36, range = 5.12–6.82; girls: M = 5.93, SD = 0.38; boys: M = 5.92, SD = 0.35; paired t = 0.20,p = .84). The sample showed wide variation in vocabulary centile scores, assessed using the British Abil-ity Scales (BAS) at Time 1 (Elliott, Murray, & Pearson, 1983) and the British Picture Vocabulary Scale(BPVS) at Time 2 (Dunn, 1997). Specifically, at Time 1 the mean vocabulary centile score was 50.56(SD = 29.18, range = 4–99), and at Time 2 the mean vocabulary centile score was 37.82 (SD = 25.15,range = 0–92), paired t = 4.50, p < .001. Reflecting the local population, the sample was racially veryhomogeneous, with 97% of the children being Caucasian. In relation to maternal education, 18 mothershad no educational qualifications at all, 38 mothers had elementary (16 years of age) qualifications, 18mothers had higher (18 years of age) qualifications, and 27 mothers had university degrees. In relation tofamily structure, 27% of mothers were single parents, whereas 11% of children were singletons, 45% hadone sibling, 30% had two siblings, 10% had three siblings, and 4% had four to seven siblings.

Procedures

At each time point, children completed cognitive tasks across two 2-hour visits. In addition, at 6years of age, children were filmed for 15 min in dyadic play with a teacher-nominated best friend.Props for this play session consisted of a Playmobil Zoo (No. 3240) that included a building with enclo-sures and fences and four main areas for the animals, two zookeepers, a family of four, and eight ani-mals. Each family received a DVD of each play session as a token of thanks.

Tasks at 3 years of age

The first task tapped into children’s ability to recall their own false beliefs using a peep-throughpicture book (Balas, 2003) that had a deceptive element on four different pages (e.g., what appearsto be an orange turns out to be a sun). For each deceptive element, children were asked a forced-choicequestion to test their recall of their previous false belief (e.g., ‘‘Before we turned the page, what did youthink this would be, an orange or a sun?”). Children were also asked four corresponding forced-choicecontrol questions (e.g., ‘‘What is it really, an orange or a sun?”). The order of the alternatives was coun-terbalanced across children, who were credited with success on the test questions only if they alsopassed the corresponding reality control questions. Scores on this task ranged from 0 to 4 (RecallOwn False Belief).

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The second task also tapped into children’s ability to recall a false belief, as well as to predict an-other character’s false belief, using a deceptive content design (Bartsch & Wellman, 1989). Childrenwere shown a prototypical container (an egg box) and a plain tube and were asked which they thoughtcontained an egg. The boxes were then opened to reveal a realistic model egg in the plain tube. Nextthey were asked to recall their false belief (‘‘Before we looked, which box did you think had an egginside?”) as well as a reality control question (‘‘Which box really has an egg inside?”). They were thenintroduced to a ‘‘Granny” doll who wanted to make a cake and needed some eggs. The Granny doll‘‘walked” to the egg box, and children were asked to explain why she was looking in the egg box aswell as a second reality control question. For children who passed the corresponding reality questions,responses to the recall and explain false belief test questions (i.e., correct or incorrect) were summedto give a score of 0 to 2 (Recall Own/Explain Other False Belief).

The third task tapped into children’s ability to predict and explain another character’s false beliefusing an object transfer design that involved two well-known characters: ‘‘Noddy” and ‘‘Big Ears.”Props for this included toy figures and a set of miniature knives and forks that could be tidied awayin either a miniature drawer or a pot. Children received two test questions: (a) prediction of searchbehavior (‘‘Where will Noddy look for the knives?”) and (b) belief-based explanation (‘‘Why did Noddylook there?”). Children were asked both a memory control question (‘‘Where did Noddy put the knivesfirst of all?”) and a reality control question (‘‘Where are they really?”). Children were credited withsuccess on the test questions only if they also responded to the reality control questions. Scores on thistask ranged from 0 to 2 (Predict/Explain Other False Belief).

In addition, at 3 years of age, children completed the Baby Stroop task (Hughes & Ensor, 2005). Chil-dren were randomly assigned to either Group A (cup trials followed by spoon trials) or Group B (spoontrials followed by cup trials). On each trial, the experimenter showed children a big ‘‘Mummy spoon”/‘‘Mummy cup” and a little ‘‘baby spoon”/‘‘baby cup” and checked whether children understood whichwas which by asking them to point to the Mummy spoon/cup and then to the baby spoon/cup and repeat-ing these instructions until they clearly understood. Next the experimenter said, ‘‘Now we are going toplay a topsy-turvy game. We’re going to swap the two spoons [cups] around. So now Mummy is going touse the baby spoon [cup] and baby can use the big spoon [cup].” Then the experimenter hid both spoons/cups behind her back and brought one forward, saying, ‘‘In this topsy-turvy game, is this a baby spoon[cup] or a Mummy spoon [cup]? You tell me.” The experimenter gave feedback for each trial, whichwas presented in the following pseudo-random order: Mummy–baby–Mummy–baby–baby–Mummy.Performance was rated by the number of correct trials across all cup and spoon trials.

Tasks at 6 years of age

As at 3 years of age, the first false belief task at age 6 tapped children’s ability to recall their ownfalse belief and predict another’s false belief using a peep-through book, Can’t Sleep (Moerbeek, 1994),to present children with a deceptive identity. Specifically, on each page, the picture included an eyepeeping through that on the final page turned out to be a spot on a snake’s back. Children were askedtwo forced-choice test questions that tapped their understanding of false belief in self and other: ‘‘Be-fore we turned the page, what did you think this would be, an eye or a spot?” and ‘‘Look, this is Charlie[show puppet]. Charlie has never seen this book before. If we show him this picture, what will he thinkit is, an eye or a spot?” In both cases, we also asked a corresponding forced-choice control question:‘‘What is it really, an eye or a spot?” The order of the alternatives was counterbalanced across children,who were credited with success on the test questions only if they also passed the corresponding real-ity control questions. Scores on these two questions were combined to create a point indicator of 0 to2 (Recall Own/Predict Other False Belief).

As a parallel to the Noddy task administered at 3 years of age, the second false belief task at age 6was the classic ‘‘Sally Ann” scenario (Wimmer & Perner, 1983) enacted with two dolls, a basket, a box,and a very small ball. In this task, children were asked to explain a doll’s belief-based search for a ball(‘‘Why did Sally look there?”) as well as to answer a reality control question (‘‘Where is the ballreally?”). Children were credited with success on the test question only if they also responded tothe reality control question (Explain Other False Belief). Credit was given for responses that werecorrect but implicit (e.g., ‘‘Because that’s where she left it”).

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Two more advanced tasks administered at 6 years of age were based on the paradigm developed byHarris and colleagues (Harris, Johnson, Hutton, Andrews, & Cooke, 1989) to tap children’s ‘‘belief de-sire reasoning.” At the start of each task, children were introduced to a puppet character, ‘‘Leo lion”/‘‘Monty monkey”, who liked one thing (Coke/felt tips) and disliked another (milk/crayons). After twoquestions to check whether children understood the puppet’s likes/dislikes, the main part of eachstory involved an object substitution by a second puppet, ‘‘Croc crocodile”/‘‘Freddy frog”, which re-sulted in the key protagonist receiving a nice/nasty surprise (e.g., Croc pours out the Coke from itscan and replaces it with milk). Children were then asked two test questions (e.g., ‘‘When Leo first seesthe Coke can, how does he feel? Why does he feel that way?”). Answers to the questions across thetwo puppet stories were combined to create a point index of 0 to 4 for children’s ability to predictand explain a false belief-based emotion (Predict/Explain False Belief-Based Emotion). In addition,for each task, children received a first-order false belief question (e.g., ‘‘What does Leo think is insidethe can?”) as well as a control question (e.g., ‘‘What is in the can really?”). For children who passed thecorresponding control questions, correct responses to the false belief questions were combined to givea score of 0 to 2 (Predict Other False Belief).

Finally, at 6 years of age, children also received two second-order false belief stories. In the first ofthese (Sullivan, Zaitchik, & Tager-Flusberg, 1994), a mother tells her son, Peter, that she has boughthim a toy for his birthday, when in fact she has bought him a puppy. Unbeknownst to his mother, Pe-ter finds the birthday puppy. Peter’s grandmother then calls and asks his mother what Peter thinks hewill receive for his birthday. Children were asked a second-order test question (‘‘What does Mum sayto Granny?”) and a justification question (‘‘Why does she say that?”) as well as two control questions(‘‘Did Mum see Peter finding the present?” and ‘‘What has Mum really got Peter for his birthday?”).The second second-order false belief story (Perner & Wimmer, 1985) involved a similar plot but withtwo siblings, Mary and John, and a bar of chocolate. A similar set of test questions (second-order falsebelief and justification) and control questions (reality and memory) were asked. For children whopassed corresponding control questions, correct answers to these test questions were summed to givea point indicator of 0 to 4 (Predict/Explain Second-Order False Belief).

At 6 years of age, children also completed the Day/Night Stroop task (Gerstadt, Hong, & Diamond,1994). This task consisted of two conditions. On each of the 12 trials in the first (control) condition,children were shown one of two abstract patterns and asked to say either ‘‘day” or ‘‘night”. The second(test) condition also contained 12 trials (and the same responses), but this time the abstract patternswere replaced by pictures of the moon and the sun and children were asked to say ‘‘day” for a pictureof the moon and ‘‘night” for a picture of the sun. In both conditions, pictures were presented in a pseu-do-random order. Performance on the second (test) condition was rated by the total number of correcttrials. However, the data showed a strong positive skew, and to simplify analyses we recoded re-sponses into binary formats (two or more errors: n = 29 children [13 girls and 16 boys]; no more than1 error: n = 72 children [28 girls and 44 boys]). For consistency, we also recoded children’s Time 1 re-sponses into binary formats (two or more errors: n = 42 children [18 girls and 24 boys]; no more than1 error: n = 59 children [23 girls and 36 boys]).

Transcript-based coding

The transcripts were divided into conversational turns; a turn was defined as the utterances of onespeaker bounded by another speaker’s utterances (Shatz & Gelman, 1973) or a significant silence (usu-ally P5 s). Transcripts were coded for mental state reference using Brown and colleagues’ (1996)scheme, which includes three categories of mental states (cognitions, desires, and feelings) that canrefer to a friend, a child, or a third party. References to mental states that were conversational, repet-itive (within an utterance), and imitative were excluded. The most common cognitive terms recordedwere think, know, and variations thereof. The most common desire terms were need, want, would like/love. References to feelings included those that referred to an emotional state. The most common feel-ing terms noted were happy, scared, upset, and variations thereof. Here like was coded only when theterm referred to a state of enjoyment and not when it indicated ‘‘to want to have.” Coding was con-ducted by the second author; to establish interrater reliability, the third author independently coded20% of the transcripts. Cohen’s kappa was excellent (j = .98).

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Results

All 101 participants had complete task data at both time points. Table 1 shows descriptive statisticsfor the sample as a whole and for boys and girls separately. Note that there were no significant genderdifferences on any study measure, t 6 1.32, p P .19. We used MPlus 5 and a maximum likelihood func-tion to analyze the sample variance–covariance matrix. Good model fit was evaluated using the fol-lowing indices and criteria: standardized root mean square residual (SRMR) 6 .08, root mean squareerror of approximation (RMSEA) 6 .06, and comparative fit index (CFI) and Tucker–Lewis index (TLI),where values 6.95 indicate good model fit and values in the range of .90 to .95 suggest adequate mod-el fit.

Modeling children’s false belief understanding at 3 and 6 years of age

We used confirmatory factor analysis to specify a measurement model in which, at 3 and 6 years ofage, indicators of false belief understanding loaded onto a latent factor. The model was over identifiedwith v2(19) = 25.58, p = .14. With only one exception, each index suggested adequate model fit:SRMR = .06, RMSEA = .06, CFI = .91, and TLI = .87. Table 2 shows the completely standardized coeffi-cients; all factor loadings were statistically significant, p < .01, and the latent factors explained signif-icant variance in all but two indicators (R2 mean = .28, range = .15–.36). These results support thereliability of the latent constructs of false belief understanding at ages 3 and 6.

Next we tested the equivalence of the measurement model for boys versus girls using multiple-groups confirmatory factor analysis. That is, we simultaneously analyzed the measurement model intwo separate matrices: one for boys and the other for girls. To optimize model fit, the residual variancesof the following pair of indicators were allowed to correlate: within boys, at 6 years of age, Predict OtherFalse Belief and Predict/Explain Emotion-Based False Belief. To ensure the equivalence of measurement,we constrained like parameters (specifically, factor loadings and indicator intercepts) to be equal forboys versus girls. In addition, to ensure that any gender differences in the latent factors’ means wereinterpretable, we constrained their variances to be equal for boys versus girls. Finally, to identify themean structure component of the multiple-groups confirmatory factor analysis, we fixed the mean ofthe girls’ latent factor to zero. Thus, the mean of the boys’ latent factor represented the difference be-tween the two latent factors’ means. The model was overidentified with v2(51) = 57.254, p = .25. Eachindex suggested adequate model fit: SRMR = .10, RMSEA = .05, CFI = .92, and TLI = .92. There was no

Table 1Descriptive statistics for all study measures.

M SD Boys Girls

M SD M SD

Tasks: 3 years of ageRecall Own False Belief 1.11 1.17 1.02 1.12 1.32 1.27Recall Own/Explain Other False Belief 0.52 0.66 0.57 0.68 0.46 0.60Predict/Explain Other False Belief 0.30 0.58 0.28 0.52 0.33 0.66BAS receptive vocabulary (centile) 49.45 28.67 53.67 27.69 46.05 31.01Baby Stroop 10.07 2.39 10.23 2.19 9.85 2.66

Tasks: 6 years of ageRecall Own/Predict Other False Belief 1.57 0.57 1.61 0.56 1.51 0.56Explain Other False Belief 0.77 0.43 0.75 0.44 0.71 0.46Predict Other False Belief 1.73 0.60 1.72 0.64 1.71 0.60Predict/Explain False Belief-Based Emotion 3.85 0.55 3.92 0.42 3.76 0.70Predict/Explain Second-Order False Belief 1.42 1.60 1.36 1.56 1.66 1.68BPVS receptive vocabulary (centile) 38.38 24.65 40.57 26.21 33.76 23.31Day/Night Stroop 10.79 2.03 10.85 1.96 10.70 2.16

Observed talk: 6 years of ageChild to friend: Total turns/hour 333.77 100.45 328.64 105.86 325.06 96.79Child to friend: Mental state references/hour 42.30 25.41 40.85 25.07 44.42 26.03Friend to child: Mental state references/hour 49.67 30.68 46.61 28.31 54.09 32.04

Table 2Coefficients for confirmatory factor analyses of false belief understanding at 3 and 6 years of age.

Factor loading Residual variance

False belief: 3 years of ageRecall Own False Belief .60 .64Recall Own/Explain Other False Belief .43 .82Predict/Explain Other False Belief .57 .67

False belief: 6 years of ageRecall Own/Predict Other False Belief .50 .75Explain Other False Belief .59 .66Predict Other False Belief .57 .67Predict/Explain False Belief-Based Emotion .39 .85Predict/Explain Second-Order False Belief .51 .74

104 C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112

significant gender difference in the false belief understanding latent factor at either 3 years of age(z = –.06, p = .84) or 6 years of age (z = .07, p = .79).

Stability of individual differences in false belief understanding from 3 to 6 years of age

To assess the stability of individual differences in false belief understanding from 3 to 6 years ofage, we adapted our measurement model. We included the regression of the false belief understandinglatent factor at age 6 on the false belief understanding latent factor at age 3. At each time point, weestimated the covariances between the false belief understanding latent factor and two indicators:receptive vocabulary and inhibitory control. In addition, we covaried the false belief understanding la-tent factor at age 6 with an indicator of age. (Note that the covariance between the false belief under-standing latent factor at age 3 and an indicator of age, .02, was not significant, z = .14, p = .89.) Tooptimize model fit, we regressed the indicator of receptive vocabulary at age 6 on the indicator ofreceptive vocabulary at age 3; at each time point, we correlated the indicators of receptive vocabularyand inhibitory control; and at age 6, we covaried the indicator of age with the indicators of receptivevocabulary and inhibitory control. The model was overidentified with v2(58) = 71.08, p = .12. All in-dexes suggested adequate model fit: RMSEA = .05, SRMR = .08, CFI = .93, and TLI = .91. All of the stan-dardized coefficients shown in Fig. 1 are significant (p < .05). Individual differences in the falsebelief understanding latent factors showed significant stability between ages 3 and 6 independentof covariances with concurrent inhibitory control and receptive vocabulary.

The covariance between the false belief understanding latent factor and the indicator of receptivevocabulary was .87 at 3 years of age and .66 at 6 years of age. To test whether this difference was sig-nificant, we constrained the covariance to be equal (.77) at each time point. This constraint signifi-cantly degraded the absolute model fit, v2 difference (1) = 4.67, p < .05. In other words, thecorrelation between false belief understanding and verbal ability was significantly stronger at age 3than at age 6.

Does false belief understanding at 3 years of age predict talk with friends at 6 years of age?

Next we extended our model to include indicators of children’s talk with friends: total number ofutterances and number of references to desires, cognitions, and emotions. We estimated the covari-ance between (a) children’s total number of utterances and their mental state references and (b) chil-dren’s and friends’ mental state references. We also included the correlation between children’smental state references and the false belief understanding latent factor at 6 years of age and theregression from children’s mental state references to the false belief understanding latent factor at3 years of age. The model was overidentified with v2(96) = 123.76, p < .05. Three indexes suggestedadequate model fit, and one index fell just below the threshold: RMSEA = .05, SRMR = .10, CFI = .90,and TLI = .87. All of the standardized coefficients shown in Fig. 2 are significant (p < .05). At age 6,the false belief understanding latent factor was significantly correlated with children’s mental state

.66

.46

Inhibitory Control: Age 3

Inhibitory Control: Age 6 .42 .3

2

Verbal Ability: Age 3

Verbal Ability: Age 6 .28

.66 .24

.87

False Belief: Age 3

.26 .31 .32

.93 .90 . 90

Recall ow

n False Belief

Recall ow

n / explain other False Belief

Predict / explain other False Belief

.43

Explain other False B

elief

Predict / Explain False B

elief-Based E

motion

Recall ow

n / predict other False Belief

Predict other False Belief

False Belief: Age 6

.58 .50 .33 .58

.89 .82 .75 .64

Predict / explain second-order False Belief

.65

Age 6

.45

.35

.21

Fig. 1. Latent factors for false belief understanding are stable from 3 to 6 years of age.

C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112 105

talk (p < .001). Given this covariance, it is striking that the path from the false belief understanding atage 3 to the mental state talk at age 6 was also significant (p < .05).

Discussion

This longitudinal study yielded three sets of findings. First, our confirmatory factor analysesshowed that individual differences in children’s performances on false belief tasks at 3 and 6 yearsof age could be characterized by a latent construct that fit the data equally well for girls and boysand showed no mean gender difference. Second, even when the robust associations with verbal abilityand inhibitory control were taken into account, individual differences in children’s false belief under-standing showed significant stability over a period of 30 months that spanned the transition to school.Interestingly, although statistically significant at both time points, the association between false beliefunderstanding and verbal ability was significantly stronger at age 3 than at age 6. Third, false beliefunderstanding at ages 3 and 6 showed independent distal and proximal associations with the fre-quency of children’s mental state references during their conversations with friends even when theirtotal talk, the frequency of their friends’ mental state references, and their verbal ability and inhibitory

.87

.67

.37

Child / Friend

Child / Friend Turns

.46

.49

.22

Friend / Child

mental state talk mental state talk

Inhibitory Control: Age 3

.32

.21

Verbal Ability: Age 3

.24

False Belief: Age 3

.26 .32 .33

.93 .90 .89

Recall ow

n False Belief

Recall ow

n / explain other False Belief

Predict / explain other False Belief

.41

Explain other False B

elief

Predict / explain False Belief-based em

otion

Recall ow

n / predict other False Belief

Predict other False Belief

False Belief: Age 6

.58 .51 .37 .58

.86 .84 .75 .67

Predict / explain second-order False Belief

.66

Inhibitory Control: Age 6 .47

Verbal Ability: Age 6 .29

.60

Age 6

.37

.35

.21

Fig. 2. Latent factors for false belief understanding show both distal and proximal associations with children’s mental state talkto friends.

106 C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112

control at both time points all were taken into account. Below we discuss each of these findings in turnbefore identifying strengths and weaknesses of the current study.

Modeling children’s false belief understanding

Despite being very widely used, false belief tasks have also attracted several different kinds of crit-icism. For example, Fabricius and Khalil (2003) argued that children can pass false belief tasks without

C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112 107

reasoning about beliefs by using a ‘‘perceptual access” approach in which they judge that a personwho has not seen the true state of affairs will act incorrectly. More generally, false belief tasks can pro-vide only an impure measure of children’s understanding of mind. To address this issue, the currentstudy adopted a latent variable approach in which effects of measurement error can be partitionedout, such that analyses (e.g., with regard to the stability of individual differences) are based on ‘‘truescores” for each child. At this point, it should be acknowledged that the psychometric properties offalse belief tasks provide a real challenge for researchers conducting latent variable analyses. Forexample, children are generally coded as simply passing or failing each task, such that several tasksare needed. In addition, to avoid practice effects and ensure developmentally appropriate testing,studies typically adopt different tasks at different time points, precluding the use of latent growthmodeling.

Nevertheless, at least two previous studies in this field have successfully adopted latent variableanalyses. In the first, Wellman and Liu (2004) applied both Guttman scaling and Rasch analysis todemonstrate the sequential nature of developments in children’s growing understanding of mind.In the second, Bright-Paul, Jarrold, and Wright (2008) used latent trait analysis to show that links be-tween individual differences in false belief understanding and resistance to misleading suggestions areunitary (rather than multicomponential) in nature and hinge on improvements in children’s sourcemonitoring. The results from the current study add to these findings that support the value of adoptinga model fitting approach to examine children’s responses to theory-of-mind tasks and are encouragingin several respects.

The confirmatory factor analysis demonstrates the reliability of our assessments of individual dif-ferences in children’s false belief understanding at both 3 and 6 years of age. Our results showed that,at each time point, there was no difference between boys’ and girls’ understanding of mind. Interest-ingly, although a few previous studies have reported a weak gender difference (favoring girls) in falsebelief performance among preschoolers (e.g., Charman et al., 2002) and preadolescents (Bosacki,2000), a recent study of adults reported a modest gender difference in the opposite direction, thatis, a male advantage (Russell, Tchanturia, Rahman, & Schmidt, 2007). Note, however, that genderwas not featured in any of the three independent meta-analytical reviews of development in false be-lief understanding cited in the Introduction. Viewed in this context, the lack of gender differences inour model of false belief understanding at ages 3 and 6 indicates that the isolated reports of genderdifferences in false belief understanding noted above should probably be attributed to error ratherthan to differences in children’s ‘‘true” scores.

Stability of individual differences in false belief understanding across the transition to school

As any quick check on a search engine will reveal, studies that involve false belief tasks now liter-ally number in the thousands. Given this vast body of research, it is striking that only a score of studieshave assessed children’s false belief comprehension at more than one time point. The current studyadds to this minority and is, to our knowledge, only the second to examine individual differences infalse belief comprehension across the transition to school. In addition, compared with the earlier studyby Razza and Blair (2009), three features of the current study make estimates of across-time correla-tions rather conservative: its extended temporal span (30 months as compared with 12 months), theuse of different tasks at each time point (simple false belief tasks at 3 years of age and advanced falsebelief tasks at 6 years of age), and the inclusion of both verbal ability and inhibitory control as covar-iates at each time point. Given these features, the association between the latent factors of false beliefunderstanding at ages 3 and 6 indicates impressive stability, with individual differences in false beliefunderstanding at age 3 explaining 44% of the variance in false belief understanding at age 6.

Interestingly, our analyses also suggested both developmental stability and change in the corre-lates of individual differences in false belief understanding. Specifically, latent factor scores for chil-dren’s false belief performance showed similar associations with the (categorical) measure ofinhibitory control at each time point but showed significantly stronger associations with verbal abilityat 3 years of age than at 6 years of age (even though each association was statistically significant). Thisage-related decline in the strength of the association between false belief performance and verbal abil-ity is open to at least two different interpretations. First, there may be a threshold effect (cf. Happé,

108 C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112

1995), such that beyond a given level of verbal competence, further gains in verbal ability bring onlydiminished returns with regard to children’s awareness of mental states. Alternatively, the reducedassociation between verbal ability and false belief comprehension may be related to differences inthe items used to index vocabulary levels at each time point. Teasing apart these competing proposalswould require a broader battery of verbal ability assessments at each time point.

Another potentially fruitful direction for future research would be to examine the extent to whichthe stability of individual differences in false belief understanding reflects the influence of geneticversus environmental factors. The findings from the handful of existing twin studies of individual dif-ferences in theory of mind indicate a developmental shift from moderate genetic influences in 2- and3-year-olds (e.g., Hughes & Cutting, 1999; Ronald, Happé, Hughes, & Plomin, 2005) toward substantialenvironmental influences in 5- and 6-year-olds (e.g., Hughes et al., 2005; Ronald, Viding, Happé, &Plomin, 2006). However, these findings leave open the question of whether the stability of individualdifferences in theory of mind is best explained in terms of genetic or environmental factors. Findingsfrom longitudinal studies with genetically sensitive designs (e.g., the Colorado Adoption Project) indi-cate that general cognitive ability shows significant and substantial genetic stability from 2, 3, and 4years of age to adulthood (DeFries, Plomin, & LaBuda, 1987). Therefore, our prediction is that althoughenvironmental factors may be central to accounts of individual differences in the growth of children’sfalse belief understanding over time, genetic factors are likely to be central in explaining the stabilityof individual differences in false belief understanding. But of course, what are needed from futureresearch are empirical tests for these proposals.

Early false belief understanding predicts the quality of later interactions with friends

Although Bretherton and Beeghly’s (1982) study of young children’s talk about inner states was aseminal influence on research into children’s understanding of mind, naturalistic observational studiesof this kind have been dwarfed by the sheer volume of experimental studies in this field. At least threefactors contribute to this imbalance. First, although experimental tasks such as the false belief para-digm are quick and easy to administer, collecting, transcribing, and coding children’s social interac-tions is highly labor intensive. Second, success on the false belief task quickly became the litmustest for crediting children with a theory of mind, leading to a narrow focus on children’s understandingof epistemic states rather than the broader set of inner states (e.g., desires, feelings) that are promi-nent in everyday interactions. Third, as noted earlier, conclusions from observational studies are con-strained by partner effects that often have a powerful influence on children’s talk and behavior.

To address this challenge, the third aim of the current study was to examine individual differencesin children’s false belief understanding at 3 years of age in relation to variation in the frequency ofchildren’s references to mental states in their conversations with friends at 6 years of age, controllingboth for the overall quantity of children’s talk with friends and for friends’ mental state references. Asillustrated in Fig. 2, even with these effects controlled (along with verbal ability and inhibitory controlat both time points), individual differences in false belief understanding at ages 3 and 6 both were sig-nificantly associated with individual differences in the frequency with which 6-year-olds referred tomental states (e.g., thoughts, feelings, desires, intentions) in their conversations with friends. (Notethat our coding scheme was restricted to genuine references to mental states, such that repetitive, imi-tative, or ‘‘filler” terms were excluded.)

Importantly, these associations were independent of each other. In other words, the longitudinalassociation between false belief understanding at 3 years of age and children’s talk about cognitivestates at 6 years of age was not fully explained by the stability of false belief understanding acrossthese two time points. Instead, our results point to an additive effect that might reflect increased socialopportunities for children who show an early mastery of false belief. Findings from previous studiessuggest that a number of different social processes may contribute to this indirect path between earlyfalse belief comprehension and later talk about mental states. Specifically, individual differences inpreschoolers’ performance on false belief tasks have been found to predict several key indicators ofthe quality of friendship interactions, including high rates of (a) connected conversations (Slomkowski& Dunn, 1996), (b) coordinated play (Dunn & Cutting, 1999; McElwain & Volling, 2002), and (c)collaborative planning (Jenkins & Astington, 2000) as well as low rates of negative behavior during

C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112 109

competitive play (Hughes, Cutting, & Dunn, 2001). Taken together, these findings suggest that earlymastery of false belief understanding promotes harmonious interactions with peers that are likelyto increase children’s motivation to discuss thoughts and feelings with friends. In turn, such discoursemay lead to a virtuous circle by providing the foundation for reciprocity in children’s social interac-tions. Indirect support for this proposal comes from observations of conversations between childrenin the current sample at 2 years of age with siblings and with mothers. Specifically, 2-year-oldswho showed high rates of mental state talk also showed elevated rates of reciprocal play with siblings(Hughes, Fujisawa, Ensor, Lecce, & Marfleet, 2006) and connected conversations with mothers (Ensor &Hughes, 2008).

However, it should be noted that findings from other studies are more equivocal. For example,among hard-to-manage preschoolers, negative behaviors toward friends appear to show specific asso-ciations with deficits in executive function rather than in false belief understanding (Dunn & Hughes,2001; Hughes, White, Sharpen, & Dunn, 2000). In addition, studies of peer rejection in 4- to 6-year-olds indicate only modest relations with theory-of-mind performance (Badenes, Estevan, & Bacete,2000; Slaughter, Dennis, & Pritchard, 2002; but see also Peterson & Siegal, 2002). Similarly, in a lon-gitudinal study of British children who were adopted from Romanian orphanages (Colvert et al., 2008),emotional difficulties at 11 years of age were found to be related to prior deficits in emotion recogni-tion but not to deficits in false belief understanding. Together, these findings suggest that independentassociations between false belief understanding and social interactions may be weaker among at-riskgroups. Unfortunately, testing for such a moderation effect requires the combination of large samplesizes and labor-intensive observations and so was beyond the scope of the current study.

Strengths and weaknesses of the study

We believe that the findings from this study demonstrate the feasibility and value of adopting alatent variable approach to assess the stability and significance of individual differences in false beliefunderstanding. Achieving this methodological contribution to the field depended on two key features:(a) a temporally extended interval that spanned the transition to school and (b) transcripts for directobservations of interactions with friends for a relatively large sample of children. Despite thesestrengths, the current study does leave several desiderata. In particular, more work is needed to devel-op false belief task batteries with good psychometric properties that are appropriate for use with bothpreschoolers and school-aged children. Leading researchers in the field have made significant steps inthis direction (Wellman & Liu, 2004); we hope that the findings from the current study serve as animpetus for further progress in developing task batteries. In addition, the inclusion of further timepoints would enable the shapes of these trajectories to be considered. Furthermore, although our re-sults did not indicate any gender differences in children’s false belief understanding (such that, for rea-sons of parsimony, gender was not included in subsequent models), it is possible that such contrastswould have emerged with a larger sample. Finally, practical constraints meant that it was difficult toassess all of the children at the same point in the school year, such that there was considerable var-iability in age at the second time point; this problem was addressed by including age as a covariate inthe model. Overall, however, we hope that our findings encourage others to conduct longitudinal la-tent variable analyses so as to enrich further our understanding of the distinct ways in which earlyindividual differences in children’s false belief understanding contribute to the formation and mainte-nance of children’s friendships.

References

Adrián, J., Clemente, R., & Villanueva, L. (2007). Mothers’ use of cognitive state verbs in picture-book reading and thedevelopment of children’s understanding of mind: A longitudinal study. Child Development, 78, 1052–1067.

Astington, J., & Jenkins, J. (1999). A longitudinal study of the relation between language and theory-of-mind development.Developmental Psychology, 35, 1311–1320.

Badenes, L., Estevan, R., & Bacete, F. (2000). Theory of mind and peer rejection at school. Social Development, 9, 273–283.Balas, V. (2003). Drôles de plats! Paris: Nathan.Banerjee, R. (2002). Children’s understanding of self-presentational behavior: Links with mental-state reasoning and the

attribution of embarrassment. Merrill–Palmer Quarterly, 48, 378–404.Bartsch, K., & Wellman, H. (1989). Young children’s attribution of action to beliefs and desires. Child Development, 60, 946–964.

110 C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112

Bartsch, K., & Wellman, H. (1995). Children talk about the mind. Oxford, UK: Oxford University Press.Bernard, S., & Deleau, M. (2007). Conversational perspective-taking and false belief attribution: A longitudinal study. British

Journal of Developmental Psychology, 25, 443–460.Bosacki, S. (2000). Theory of mind and self-concept in preadolescents: Links with gender and language. Journal of Educational

Psychology, 92, 709–717.Bosacki, S., & Moore, C. (2004). Preschoolers’ understanding of simple and complex emotions: Links with gender and language.

Sex Roles, 50, 659–675.Bretherton, I., & Beeghly, M. (1982). Talking about internal states: The acquisition of a theory of mind. Developmental Psychology,

18, 906–921.Bright-Paul, A., Jarrold, C., & Wright, D. (2008). Theory-of-mind development influences suggestibility and source monitoring.

Developmental Psychology, 44, 1055–1068.Brown, T. (2006). Confirmatory factor analysis for applied research. New York: Guilford.Brown, J., Donelan-McCall, N., & Dunn, J. (1996). Why talk about mental states? The significance of children’s conversations with

friends, siblings, and mothers. Child Development, 67, 836–849.Carlson, S., Mandell, D., & Williams, L. (2004). Executive function and theory of mind: Stability and prediction from ages 2 to 3.

Developmental Psychology, 40, 1105–1122.Charman, A., & Campbell, A. (1997). Reliability of theory of mind task performance by individuals with a learning disability: A

research note. Journal of Child Psychology and Psychiatry, 38, 725–730.Charman, A., Ruffman, T., & Clements, W. (2002). Is there a gender difference in false belief development? Social Development,

11, 1–10.Colvert, E., Rutter, M., Beckett, C., Castle, J., Groothues, C., Hawkins, A., et al (2008). Emotional difficulties in early adolescence

following severe early deprivation: Findings from the English and Romanian Adoptees Study. Development andPsychopathology, 20, 547–567.

Cutting, A., & Dunn, J. (2006). Conversations with siblings and with friends: Links between relationship quality and socialunderstanding. British Journal of Developmental Psychology, 24, 73–88.

Davidson, D. (2001). Externalisms. In P. Kotatko, P. Pagin, & G. Segal (Eds.), Interpreting Davidson (pp. 1–16). Stanford, CA: Centerfor the Study of Language and Information.

De Villiers, J., & Pyers, J. (2002). Complements to cognition: A longitudinal study of the relationship between complex syntaxand false-belief-understanding. Cognitive Development, 17, 1037–1060.

DeFries, J., Plomin, R., & LaBuda, M. (1987). Genetic stability of cognitive development from childhood to adulthood.Developmental Psychology, 23, 4–12.

Dunn, L. (1997). British picture vocabulary scale – revised. Windsor, UK: NFER-Nelson.Dunn, J., Brown, J., Slomkowski, C., Tesla, C., & Youngblade, L. (1991). Young children’s understanding of other people’s feelings

and beliefs: Individual differences and their antecedents. Child Development, 62, 1352–1366.Dunn, J., & Cutting, A. (1999). Understanding others, and individual differences in friendship interactions in young children.

Social Development, 8, 201–219.Dunn, J., & Hughes, C. (2001). ‘‘I got some swords and you’re dead!” Violent fantasy, antisocial behavior, friendship, and moral

sensibility in young ‘‘hard to manage” children. Child Development, 72, 491–505.Elliott, C., Murray, D., & Pearson, L. (1983). British Abilities Scales. Windsor, UK: NFER–Nelson.Embretson, S. (1996). The new rules of measurement. Psychological Assessment, 8, 341–349.Ensor, R., & Hughes, C. (2008). Content or connectedness? Early family talk and theory of mind in the toddler and preschool

years. Child Development, 79, 201–216.Fabricius, W., & Khalil, S. (2003). False beliefs or false positives? Limits on children’s understanding of mental representation.

Journal of Cognition and Development, 4, 239–262.Flynn, E. (2006). A microgenetic investigation of stability and continuity in theory of mind development. British Journal of

Developmental Psychology, 24, 631–654.Flynn, E. (2007). The role of inhibitory control in false-belief understanding. Infant and Child Development, 16, 53–69.Flynn, E., O’Malley, C., & Wood, D. (2004). A longitudinal, microgenetic study of the emergence of false-belief understanding and

inhibition skills. Developmental Science, 7, 103–115.Gerstadt, C., Hong, Y., & Diamond, A. (1994). The relationship between cognition and action: Performance of children 3½–7

years old on a Stroop-like day–night test. Cognition, 53, 129–153.Gopnik, A., & Astington, J. (1988). Children’s understanding of representational change and its relation to the understanding of

false belief and the appearance–reality distinction. Child Development, 59, 26–37.Gorsuch, R. (1997). Exploratory factor analysis: Its role in item analysis. Journal of Personality Assessment, 68, 532–560.Happé, F. (1995). The role of age and verbal ability in the theory of mind task performance of subjects with autism. Child

Development, 66, 843–855.Harris, P., Johnson, C., Hutton, D., Andrews, G., & Cooke, T. (1989). Young children’s theory of mind and emotion. Cognition and

Emotion, 3, 379–400.Hughes, C. (1998). Finding your marbles: Does preschoolers’ strategic behavior predict later understanding of mind?

Developmental Psychology, 34, 1326–1339.Hughes, C., Adlam, A., Happé, F., Jackson, J., Taylor, A., & Caspi, A. (2000). Good test–retest reliability for standard and advanced

false-belief tasks across a wide range of abilities. Journal of Child Psychology and Psychiatry, 41, 483–490.Hughes, C., & Cutting, A. (1999). Nature, nurture, and individual differences in early understanding of mind. Psychological

Science, 10, 429–432.Hughes, C., Cutting, A., & Dunn, J. (2001). Acting nasty in the face of failure? Longitudinal observations of ‘‘hard to manage”

children playing a rigged competitive game with a friend. Journal of Abnormal Child Psychology, 29, 403–416.Hughes, C., & Dunn, J. (1997). ‘‘Pretend you didn’t know”: Preschoolers’ talk about mental states in pretend play. Cognitive

Development, 12, 477–499.Hughes, C., & Dunn, J. (1998). Understanding mind and emotion: Longitudinal associations with mental-state talk between

young friends. Developmental Psychology, 34, 1026–1037.

C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112 111

Hughes, C., & Dunn, J. (2002). ‘‘When I say a naughty word”: Children’s accounts of anger and sadness in self, mother, andfriend—Longitudinal findings from ages four to seven. British Journal of Developmental Psychology, 20, 515–535.

Hughes, C., & Ensor, R. (2005). Theory of mind and executive function in 2-year-olds: A family affair? DevelopmentalNeuropsychology, 28, 645–668.

Hughes, C., & Ensor, R. (2007). Executive function and theory of mind: Predictive relations from ages 2- to 4-years.Developmental Psychology, 43, 1447–1459.

Hughes, C., Fujisawa, K., Ensor, R., Lecce, S., & Marfleet, R. (2006). Cooperation and conversations about the mind: A study ofindividual differences in two-year-olds and their siblings. British Journal of Developmental Psychology, 24, 53–72.

Hughes, C., Jaffee, S., Happé, F., Taylor, A., Caspi, A., & Moffitt, T. (2005). Origins of individual differences in theory of mind: Fromnature to nurture? Child Development, 76, 356–370.

Hughes, C., & Leekam, S. (2004). What are the links between theory of mind and social relations? Review, reflections, and newdirections for studies of typical and atypical development. Social Development, 13, 590–619.

Hughes, C., White, A., Sharpen, J., & Dunn, J. (2000). Antisocial, angry, and unsympathetic: ‘‘Hard to manage” preschoolers’ peerproblems and possible social and cognitive influences. Journal of Child Psychology and Psychiatry, 41, 169–179.

Jenkins, J., & Astington, J. (2000). Theory of mind and social behavior: Causal models tested in a longitudinal study. Merrill–Palmer Quarterly, 46, 203–220.

Kenny, D., Kashy, D., & Cook, W. (2006). Dyadic data analysis. New York: Guilford.Ladd, G., Kochenderfer, B., & Coleman, C. (1997). Classroom peer acceptance, friendship, and victimization: Distinct relational

systems that contribute uniquely to children’s school adjustment. Child Development, 68, 1181–1197.Liu, D., Wellman, H. M., Tardif, T., & Sabbagh, M. A. (2008). Theory of mind development in Chinese children: A meta-analysis of

false-belief understanding across cultures and languages. Developmental Psychology, 44, 523–531.Lockl, K., & Schneider, W. (2007). Knowledge about the mind: Links between theory of mind and later metamemory. Child

Development, 78, 148–167.Lockl, K., Schwarz, S., & Schneider, W. (2004). Sprache und theory of mind: Eine längsschnittstudie bei drei-bis vierjährigen

[Language and theory of mind: A longitudinal study of three- to four-year-olds]. Zeitschrift für Entwicklungspsychologie undPadagogische Psychologie, 36, 207–220.

Lu, H., Su, Y., & Wang, Q. (2008). Talking about others facilitates theory of mind in Chinese preschoolers. DevelopmentalPsychology, 44, 1726–1736.

MacWhinney, B., & Snow, C. E. (1985). The child language data exchange system. Journal of Child Language, 12, 271–295.Mayes, L., Klin, A., Tercyak, K. P., Cicchetti, D. V., & Cohen, D. J. (1996). Test–retest reliability for false-belief tasks. Journal of Child

Psychology and Psychiatry, 37, 313–319.McAlister, A., & Peterson, C. (2007). A longitudinal study of child siblings and theory of mind development. Cognitive

Development, 22, 258–270.McElwain, N., & Volling, B. (2002). Relating individual control, social understanding, and gender to child–friend interaction: A

relationships perspective. Social Development, 11, 362–385.Merrell, K. (1994). Preschool and Kindergarten Behavior Scales. Brandon, VT: Clinical Psychology Publishing.Miller, S. (2009). Children’s understanding of second-order mental states. Psychological Bulletin, 135, 749–773.Milligan, K., Astington, J., & Dack, L. (2007). Language and theory of mind: Meta-analysis of the relation between language

ability and false-belief understanding. Child Development, 78, 622–646.Moerbeek, K. (1994). Can’t sleep. London: Western Publishing.Moses, L. (2001). Executive accounts of theory of mind development. Child Development, 3, 688–690.Onishi, K., & Baillargeon, R. (2005). Do 15-month-old infants understand false beliefs? Science, 308, 255–258.Parker, J. G., & Asher, S. R. (1993). Friendship and friendship quality in middle childhood: Links with peer group acceptance and

feelings of loneliness and social dissatisfaction. Developmental Psychology, 29, 611–621.Perner, J., Lang, B., & Kloo, D. (2002). Theory of mind and self-control: More than a common problem of inhibition. Child

Development, 73, 752–767.Perner, J., & Wimmer, H. (1985). ‘‘John thinks that Mary thinks that . . .”: Attribution of second-order beliefs by 5- to 10-year-old

children. Journal of Experimental Child Psychology, 39, 437–471.Peterson, C., & Siegal, M. (1995). Deafness, conversation, and theory of mind. Journal of Child Psychology and Psychiatry, 36,

459–474.Peterson, C., & Siegal, M. (2002). Mindreading and moral awareness in popular and rejected preschoolers. British Journal of

Developmental Psychology, 20, 205–224.Razza, R., & Blair, C. (2009). Associations among false-belief understanding, executive function, and social competence. A

longitudinal analysis. Journal of Applied Developmental Psychology, 30, 332–343.Ronald, A., Happé, F., Hughes, C., & Plomin, R. (2005). Nice and nasty theory of mind: Genetic and environmental contributions.

Social Development, 14, 664–684.Ronald, A., Viding, E., Happé, F., & Plomin, R. (2006). Individual differences in theory of mind ability in middle childhood and

links with verbal ability and autistic traits: A twin study. Social Neuroscience, 1, 412–425.Russell, T., Tchanturia, K., Rahman, Q., & Schmidt, U. (2007). Sex differences in theory of mind: A male advantage on Happé’s

‘‘cartoon” task. Cognition and Emotion, 21, 1554–1564.Serra, M., Loth, F., Van Geert, P., Hurkens, E., & Minderaa, R. (2002). ). Theory of mind in children with ‘‘lesser variants” of autism:

A longitudinal study. Journal of Child Psychology and Psychiatry and Allied Disciplines, 43, 885–900.Shatz, M., & Gelman, R. (1973). The development of communication skills: Modifications in the speech of young children as a

function of listener. Monographs of the Society for Research in Child Development, 38(5), 1–37.Slade, L., & Ruffman, T. (2005). How language does (and does not) relate to theory of mind: A longitudinal study of syntax,

semantics, working memory, and false belief. British Journal of Developmental Psychology, 23, 117–141.Slaughter, V., Dennis, M., & Pritchard, M. (2002). Theory of mind and peer acceptance in preschool children. British Journal of

Developmental Psychology, 20, 545–564.Slomkowski, C., & Dunn, J. (1996). Young children’s understanding of other people’s beliefs and feelings and their connected

communication with friends. Developmental Psychology, 32, 442–447.

112 C. Hughes et al. / Journal of Experimental Child Psychology 108 (2011) 96–112

Sullivan, K., Zaitchik, D., & Tager-Flusberg, H. (1994). Preschoolers can attribute second-order beliefs. Developmental Psychology,30, 395–402.

Wellman, H., Cross, D., & Watson, J. (2001). Meta-analysis of theory of mind development: The truth about false belief. ChildDevelopment, 72, 655–684.

Wellman, H., & Liu, D. (2004). Scaling of theory-of-mind tasks. Child Development, 75, 523–541.Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young

children’s understanding of deception. Cognition, 13, 103–128.Youngblade, L., & Dunn, J. (1995). Individual differences in young children’s pretend play with mother and sibling: Links to

relationships and understanding of other people’s feelings and beliefs. Child Development, 66, 1472–1492.