Cognitive engagement and story comprehension in typically developing children and children with ADHD from preschool through elementary school

Cognitive Engagement and Story Comprehension in Typically DevelopingChildren and Children With ADHD From Preschool

Through Elementary School

Elizabeth P. Lorch, Richard Milich, Clarese C. Astrin, and Kristen S. BerthiaumeUniversity of Kentucky

The present study examined children’s cognitive engagement with television as a function of thecontinuity of central or incidental content and whether this varied with age and clinical status. InExperiment 1, 9- to 11-year-old children’s response times on a secondary task were slower the later aprobe occurred in a sequence of central events, and response times predicted recall. Experiment 2extended these results to 6- to 8-year-old children. Experiment 3 revealed that children with attention-deficit/hyperactivity disorder (ADHD) failed to show the pattern consistently observed for comparisonchildren. The results support the hypothesis that typically developing children build a representationduring viewing that reflects the causal structure of the televised story but that this skill is deficient in 4-to 9-year-old children with ADHD.

Keywords: ADHD, cognitive engagement, secondary probe, attention

Supplemental data: http://dx.doi.org/10.1037/0012-1649.42.6.1206.supp

Knowledge of children’s story comprehension has been in-formed by theories of the comprehension process. A theme com-mon to most theories is an emphasis on the causal and enablingrelations between events in a story, which define plot-relevantevents and give the story coherence (Ackerman, 1986; Black &Bower, 1980; Graesser & Clark, 1985; Mandler & Johnson, 1977;Trabasso, Secco, & van den Broek, 1984; van den Broek, 1997).Characteristics of the causal structure of stories have been found topredict a product of children’s comprehension—that is, memoryfor story events (e.g., Trabasso et al., 1984; van den Broek, 1989;van den Broek, Lorch, & Thurlow, 1996)—with effects becomingstronger with age (Nezworski, Stein, & Trabasso, 1982; Schmidt &Paris, 1983; van den Broek et al., 1996). However, much lessresearch has investigated the online processes children may engagein to detect and use causal relations between events to build arepresentation of a story (Ackerman, Paine, & Silver, 1991; Tra-basso & Nickels, 1992; Trabasso, Stein, Rodkin, Munger, &Baughn, 1992). One avenue of research that may contribute toknowledge of children’s online story comprehension processes isthe study of systematic variations in children’s attention to tele-vised stories (Anderson & Lorch, 1983; Huston & Wright, 1983).The present series of studies builds on this line of research byusing a measure of moment-to-moment cognitive capacity usage toinvestigate several questions. First, does children’s cognitive en-

gagement with a televised story vary as a function of the contin-uation of plot-relevant content? Second, does this pattern differ asa function of age? Finally, do children with documented attentionproblems and story comprehension difficulties (i.e., diagnosedwith attention deficit/hyperactivity disorder [ADHD]) differ incognitive engagement from comparison children?

Influences on Children’s Attention to Television

Several theoretical viewpoints on children’s television viewingconcur that children, from an early age, are active viewers whosevisual attention to television is guided by ongoing comprehension,expectations, and purposes for viewing (Anderson & Lorch, 1983;Huston & Wright, 1983; Salomon, 1983). For example, Andersonand Lorch (1983) proposed that for young children, a look at thetelevision may begin in response to any of several possible rea-sons, including stimuli that elicit orienting responses; formal fea-tures that signal informative, appealing, child-relevant content(Alwitt, Anderson, Lorch, & Levin, 1980); and cues derived fromthe behavior of other children (Anderson, Lorch, Smith, Bradford,& Levin, 1981). Once a look has begun, its continuation primarilydepends on the child’s ongoing judgments of whether programcontent is comprehensible (Anderson, Lorch, Field, & Sanders,1981; Lorch, Anderson, & Levin, 1979; Pingree, 1986).

Huston and Wright (1983) discussed similar factors as influ-ences on visual attention but conceptualized a series of decisionschildren make about whether to continue a look at the television.At the beginning of a look, decisions are most heavily a functionof formal characteristics, once again those that are indicative ofinformative, interesting, child-relevant content (Calvert, Huston,Watkins, & Wright, 1982; Huston et al., 1981). If a look continues,more extensive, deeper cognitive processing takes place, such thata subsequent decision is affected by both current comprehension

Elizabeth P. Lorch, Richard Milich, Clarese C. Astrin, and Kristen S.Berthiaume, Department of Psychology, University of Kentucky.

This research was supported by National Institute of Mental HealthGrant MH47386.

Correspondence concerning this article should be addressed to ElizabethP. Lorch, Department of Psychology, University of Kentucky, Lexington,KY 40506-0044. E-mail: [email protected]

Developmental Psychology Copyright 2006 by the American Psychological Association2006, Vol. 42, No. 6, 1206–1219 0012-1649/06/$12.00 DOI: 10.1037/0012-1649.42.6.1206

1206

and initial expectations about content (Campbell, Wright, & Hus-ton, 1987; Rolandelli, Wright, Huston, & Eakins, 1991). As furthercycles occur, later decisions are increasingly influenced by deeperprocessing and more elaborated expectations about story content(Hawkins, Tapper, Bruce, & Pingree, 1995; Rolandelli et al.,1991). In addition, Huston and Wright (1983) proposed that thereare changes in these cycles of decisions as development advances.For younger children, the continuation of a look at the televisionmay be more dependent on superficial features of the program thanfor older children, who are more likely to make elaborated deci-sions on the basis of deeper processing of content (Rolandelli etal., 1991).

These perspectives and their associated empirical support indi-cate that children’s visual attention to television varies systemat-ically in relation to program characteristics. Huston and Wright’s(1983) perspective also suggests a context for the online process-ing of television story structure. To the extent that children buildan ongoing representation of the interrelations among story eventsduring viewing, measures of attention may reveal effects of eventcentrality, causal structure, and plot development.

Several investigations suggest such indications of children’sonline processing of structural features of television stories.School-age children have been found to look at the television moreduring presentation of material that adults rated as important (i.e.,central) to the plot of the story than during material rated as low inimportance (Baer & Lorch, 1990; Lorch & Baer, 1997). Mead-owcroft and Reeves (1989) obtained a related finding using asecondary task technique to assess cognitive engagement with thetelevision program. The secondary task technique is based on theassumptions that mental processing requires time and that centralprocessing capacity is limited (Basil, 1994; Kahneman, 1973).Thus, the more attentional capacity is engaged by a continuousprimary task, such as viewing a television program, the less isavailable for a secondary task, such as a keypress in response to anoccasional auditory tone (Britton, Graesser, Glynn, Hamilton, &Penland, 1983; Britton & Tesser, 1982; Thorson, Reeves, &Schleuder, 1985). Meadowcroft and Reeves (1989) found that 5- to8-year-old children who had tested high in the development ofstory schema skills showed greater cognitive engagement (i.e.,slower responses to secondary probes) with central content pre-sented in a normal story structure than with the same contentpresented out of order and thus in the absence of a coherent storystructure.

Two additional studies also compared children’s responses tonormally structured, coherent stories and stories in which sceneshad been edited out of sequence, via existing edit points (Hawkins,Kim, & Pingree, 1991; Lorch & Castle, 1997). The use of existingedit points allowed the edited stories to be locally comprehensiblebut lacking in a coherent story structure. Both studies used thesame types of Sesame Street stories, and in both studies childrenshowed high visual attention to normal stories and to edited stories.Both studies, however, revealed indications that children’s atten-tion was engaged more systematically by the normally structuredstories. Lorch and Castle (1997), using the secondary task meth-odology, found that 5-year-old children showed greater cognitiveengagement during the second half of normal stories than duringthe first half, but the authors did not observe this difference for thestories shown in edited form. Hawkins et al. (1991) investigatedthe predictability in 3- to 6-year-old children’s visual attention

from one 3-s interval to the next (after removal of varianceresulting from overall attention, age, and tape version). Consistentwith the results of Lorch and Castle (1997), Hawkins et al. (1991)found much higher stability in attention late in normal stories thanin edited stories. Taken together, the findings of Hawkins et al.(1991), Lorch and Castle (1997), and Meadowcroft and Reeves(1989) suggest that children’s attention is responsive to the plotrelevance of story content and becomes increasingly engaged as ameaningful narrative structure develops.

The major purpose of the current studies is to extend investiga-tion of school-age children’s online cognitive processing of tele-vision story content by examining whether children’s cognitiveengagement with a television program increases as sequences ofstory content that are central to the plot continue or decreases assequences of content that are incidental to the plot continue. Inaddition, Experiment 2 investigates whether there are developmen-tal differences in children’s cognitive engagement as a function ofthe continuity of central or incidental content.

Finally, Experiment 3 examines the cognitive engagement ofchildren with ADHD, whose problems in sustaining attention andcomprehending causal relations have been well documented(Lorch, Eastham, et al., 2004; Milich, Lorch, & Berthiaume,2005). Two studies have investigated directly the role of cognitiveengagement in story comprehension among children with ADHD.Lorch, Eastham, et al. (2004) used a television viewing method-ology to test the hypothesis that differences in cognitive engage-ment would account for group differences in recall of causalrelations (i.e., “why” questions) when toys were present duringviewing. The results of three different analytic strategies con-verged to support the hypothesis that greater cognitive engage-ment, as indexed by long looks (i.e., longer than 15 s) at thetelevision, enabled comparison children to form a more completerepresentation of the relations among story events, thereby ac-counting for differences between the comparison and ADHDgroups in understanding causal relations questions. Thus, the find-ings from Lorch, Eastham, et al. (2004) constitute the first com-pelling evidence that the amount of time spent in deeper cognitiveprocessing during long looks helps explain the differential patternsof recall in children with ADHD and comparison children.

The results of Lorch, Eastham, et al. (2004) suggest that varia-tions in cognitive engagement may account for the problems thatchildren with ADHD have with causal relations questions. How-ever, the degree of cognitive engagement was inferred from timespent in long looks. The secondary task may offer a more directway to assess cognitive engagement. To date, only one study hasused this procedure with an ADHD sample (Whirley, Lorch,Lemberger, & Milich, 2003). In this study, participants were 22boys with ADHD and 36 comparison boys, ranging in age from 9to 11 years. Boys with ADHD responded significantly slower thanthe comparison boys, a common finding in reaction time studies.More important, the patterns of response times (RTs) across thecentral sequences differed between the two groups of boys. Thecomparison boys showed the predicted pattern of longer RTs (i.e.,increased cognitive engagement) the longer into a central sequencethe probes appeared. In contrast, the boys with ADHD actuallyshowed shorter RTs from the beginning to the middle of the centralsequences, which suggests decreased cognitive engagement as thecentral sequences progressed. It was only for probes occurring latein the central sequences that the RTs of the boys with ADHD

1207COGNITIVE ENGAGEMENT WITH TELEVISION

https://www.researchgate.net/publication/5349165_Difficulties_in_Comprehending_Causal_Relations_Among_Children_With_ADHD_The_Role_of_Cognitive_Engagement?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

https://www.researchgate.net/publication/5349165_Difficulties_in_Comprehending_Causal_Relations_Among_Children_With_ADHD_The_Role_of_Cognitive_Engagement?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

https://www.researchgate.net/publication/240699950_The_Ups_and_Downs_of_Attention_to_Television?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

https://www.researchgate.net/publication/240699950_The_Ups_and_Downs_of_Attention_to_Television?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

https://www.researchgate.net/publication/249683029_Influence_of_Story_Schema_Development_on_Children's_Attention_to_Television?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

https://www.researchgate.net/publication/223901916_Effects_of_prior_knowledge_on_use_of_cognitive_capacity_in_three_complex_cognitive_tasks?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

showed the expected increase. In Experiment 3, we use a devel-opmental perspective to compare the cognitive engagement ofchildren with ADHD and their comparison peers, using an agerange that included younger children (i.e., 4 to 9 years) than theprevious secondary task studies.

To address whether children’s cognitive engagement is relatedto the development of content that varies in plot relevance, pro-grams were selected that contained strong narrative structures,with story lines revolving around child characters, and that enabledthe identification of continuous sequences (approximately 15 s ormore) of events that were central or incidental to the plot. Centralsequences are those that are crucial to plot development, whereasincidental sequences are ones that could be removed withoutaffecting the coherence of the story. Central and incidental se-quences of events were operationalized in terms of the combina-tion of two criteria: whether events in the sequence were part of thecausal chain leading from the beginning to the eventual outcome ofthe story (as opposed to “dead end” events), and whether eventswere high or low in centrality, as determined by college studentraters (see Experiment 1 Method section for greater detail). Foreach central or incidental sequence of events, several positionswere identified as potential times for presentation of secondaryprobes. Watching and understanding the television program wasdefined as the primary task, and children were told that theirknowledge of story events would be tested after viewing. As achild watched the program, auditory probes were presented atpreselected times. The child’s secondary task was to press a key asquickly as possible whenever a probe was presented.

Within the constraints of this task, visual attention was expectedto be very high, so the cycles of viewing decisions described byHuston and Wright (1983) were not expected to occur. Probe RTs,however, may capture similar decisions concerning whether toengage in deeper and more elaborative processing. If childrenbuild a representation during viewing that reflects the causalstructure of a televised story, they should show increasing cogni-tive engagement as a sequence of central story content continues,because they will encounter events that can be related to the mainthread of the story. Therefore, the later a probe was presented in asequence of central events, the slower children’s responses wereexpected to be. In contrast, this pattern was not expected to occuras a sequence of incidental events continued. The lack of connec-tions to the causal chain of the story should lead to more superfi-cial processing. Thus, children’s RTs might be unrelated to probeposition or might even become shorter the later a probe waspresented in a sequence of incidental events.

Experiment 1

Method

Participants

Participants were 27 boys and 33 girls, ages 9–11 years (M � 10.05, SD �0.81). Participants were primarily Caucasian (88.33%), with some AfricanAmerican children (8.33%) and children of other ethnic identifications(3.33%). Most parents’ education included at least some college; the averageparent was a college graduate (M � 16.98 years of education). Children wererecruited through advertisements in the newspaper and from an existing poolof experimental volunteers. For Experiment 1, children were screened forbehavioral problems or attentional difficulties, such as ADHD, in a recruitmentphone call and were not included in the study if the parent indicated the child

had ever been referred for any attentional or behavioral difficulties. Childrenwere paid $5 for their participation, which lasted about 45 min. Data were lostfrom 2 participants as a result of equipment malfunction.

Materials

Each participant viewed one episode of the situation comedy GrowingPains. This program was chosen specifically because its content is suitableand interesting for children. Furthermore, the plot of this specific episode(“Dad’s Birthday”) centered on the activities of one of the child charactersin the family. A synopsis of the plot appears in the Appendix, which isavailable on the Web. With all commercials removed, the episode is 23 minin length. A detailed audiovisual script of the program was created as partof a previous study (Lorch et al., 2000). The script was divided into 407individual units of meaning, with each unit representing a single idea or event.

In accordance with procedures defined by Trabasso and van den Broek(1985), a causal network representation of the story was derived. On thebasis of the causal network analysis, each idea unit was coded as to whetherit was on or off the causal chain. The causal chain is a sequence of eventsthat are causally linked together and carry the story from the beginning tothe end. All story events are either part of the causal chain (i.e., causallyconnected to prior and subsequent events) or dead-end events (i.e., notcausally connected to prior and subsequent events on the causal chain).

Each idea unit also had been rated by 58 college students for itscentrality to the story, on a scale from 1 to 7. The students first watched theprogram and then were given scripts representing the individual units in theprogram. In assigning their ratings, they were instructed to consider howmuch plot-relevant information the unit conveyed, how much would be lostif the unit were removed from the program, and how much the unitenhanced understanding of the plot. Mean centrality ratings were calcu-lated across all students for each idea unit.

For the purposes of the present study, an individual unit was consideredto be central if it both was on the causal chain and had a mean centralityrating of at least 5.15 out of 7, the upper quartile of centrality ratings. Anindividual unit was considered to be incidental if it both was off the causalchain (a dead-end event) and had a mean centrality rating of no more than3.30, the lower quartile of ratings. Given these classifications, nine con-tinuous sequences of primarily central events and nine continuous se-quences of primarily incidental events were identified. A description ofeach sequence and its order of appearance in the Growing Pains episodeappears in the Appendix (available on the Web). The length of the se-quences varied from 15 to 90 s, and sequences contained between 4 and 30idea units. In central sequences, the mean centrality rating of the units was5.53, 77% of the individual units were in the upper quartile of the ratings,and 72.4% of the individual units were on the causal chain. In incidentalsequences, the mean centrality rating of the units was 2.88, 85% of theindividual units were in the lower quartile of the ratings, and none of theindividual units were on the causal chain. In general, individual units ineither type of sequence that did not meet strict criteria for the sequencetended to be brief and isolated.

To track online variations in children’s cognitive engagement with thetelevision story, we placed 26 auditory target probes at preselected pointsduring these sequences of story events. The basic positions for targetprobes were approximately 2, 7, or 12 s into the sequence.1 In addition, in

1 The nine central and nine incidental sequences exhausted all possiblesequences of story events that met criteria for classification as central orincidental and continued for a minimum of 15 s. Fifteen seconds waschosen as the minimum because this is the asymptote of the attentionalinertia function (Anderson & Lorch, 1983). The basic probe positions of 2,7, and 12 s were chosen to represent early, middle, and later positionswithin the 15-s interval. The number of later probes was constrained by thenumber of sequences longer than 24 s.

1208 LORCH, MILICH, ASTRIN, AND BERTHIAUME

https://www.researchgate.net/publication/232484098_Comprehension_of_televised_stories_in_boys_with_attention_deficithyperactivity_disorder_and_nonreferred_boys?el=1_x_8&enrichId=rgreq-ff3485ac-be79-4e10-8f1a-bda687f06ae5&enrichSource=Y292ZXJQYWdlOzY3MDg3MTU7QVM6MTAyMDQ2NzU3ODE4MzgwQDE0MDEzNDEyNTE0MzU=

sequences lasting 24 s or longer, later probe positions were added to thebasic probes. We created three series of probe assignments to counterbal-ance probe position across sequences. Each participant was randomlyassigned to one of these three series. Each series contained 3 probes in eachbasic position (i.e., 2, 7, and 12 s), at each centrality level, and 4 probes inthe later positions during sequences longer than 24 s, for a total of 13central and 13 incidental target probes. We inserted 12 filler probes in theprogram to prevent participants from detecting a pattern or being able topredict probes and make anticipatory responses, which resulted in a total of38 probes during the episode.

A set of comprehension questions was developed for the televisionprogram. The questions tested factual information that was presented in theprogram during sequences containing probes. Discrete events that occurredclose in time to a secondary task probe were chosen to be tested, andstraightforward questions were designed to test children’s memory for eachevent. An example question testing memory for a central story event (seeAppendix, available on the Web) is “Ben has to return the camera. Whatelse does he have to do as part of his punishment?” (return money andapologize to neighbors). Twenty-five cued recall questions were devel-oped; 14 tested central content, and 11 tested incidental content. Everysequence was represented by at least 1 question, with two sequencesrepresented by 2 questions, two represented by 3 questions, and tworepresented by 4 questions.

Procedure

The participants were brought to the on-campus television viewingfacility by a parent. Each child participated individually. Before the ex-periment began, informed consent was obtained from the parent. After abrief conversation with the experimenter to help the child feel comfortable(e.g., talking to the child about school, activities, pets), the child was shownto his or her seat in the television viewing room. The child was seated ata table, with a computer keyboard on the table in front of him or her. Theprobes were generated by an IBM computer that was located on the floornext to the child. Responses were made on the keyboard on the table infront of the child. RTs for each probe were recorded (in milliseconds) fromthe beginning of the probe until the child responded by pressing the spacebar. The probe continued until a response was made. If no response wasmade, the sound ended after 5 s.

A television was situated on a desk near one corner of the table, with thetelevision screen about 5 ft (1.5 m) from the child’s seat. A video camerawas mounted on the wall in a position that allowed the image to includeboth the child and the television. For the child to look at the television, heor she needed to make a noticeable head movement. This enabled theexperimenter to record looks toward and away from the television. Eachchild was videotaped during the entire experimental session, and visualattention to the television was later coded from the videotape.

After the child was seated in the room, the experimenter obtained his orher verbal assent to participate in the study. Once the child agreed toparticipate, the experimenter explained the procedure to the child, empha-sizing that watching the television program was the primary task andresponding to the probe was the secondary task. It was explained to theparticipants that they would hear sounds that they should turn off asquickly as possible by pressing the space bar on a computer keyboardlocated on the table in front of them. Participants were instructed to keeptheir dominant hand directly in front of the computer keyboard throughoutthe entire television program. To help the child do this, the experimenterplaced a loose Velcro strap across the child’s wrist. After the procedurewas explained, the child was given an opportunity to practice. A computerprogram presented five probes that were randomly spaced throughout a2-min period. Each child pressed the space bar in response to every practiceprobe. It was again emphasized to the child that watching and understand-ing the program was the primary task, and each child was told that after theprogram ended there would be some questions about the television show.

After the child indicated verbally that he or she understood the instructionsand had satisfactorily completed the practice probe program, the experi-mental session began. The experimenter started the videotape that playedthe television show and synchronized the probe program to the tape beforeleaving the room.

When the television program was finished, the experimenter reenteredthe room and began the cued recall questioning session. The testing sessionwas videotaped to allow later scoring of cued recall questions. The ques-tions were asked in the order in which the content was presented in theshow. If the child did not answer a question correctly, the experimentersupplied the correct answer and then continued to the next question until allquestions were asked. The child was then debriefed, paid, and thanked forhis or her participation.

Results and Discussion

Dependent Measures

The main dependent variable was RT to 26 target probes.Thirty-eight probes sounded during the program. Thirteen targetprobes occurred during sequences of central content, and 13 oc-curred during sequences of incidental content. The remainingprobes were fillers and were not analyzed. Two participants’ RTdata included one impossibly fast RT (32 ms for 1 child, 112 msfor the other). These responses were not included in the calculationof means for the categories. Two participants failed to respond to1 probe. We obtained category means for these participants bycomputing means of the remaining RTs in the category.

Performance on the cued recall questions was scored fromtranscripts of the videotape. Each answer was assigned a score of1 for correct and 0 for incorrect. An independent rater scored 25%of participants’ cued recall responses, with 92% agreement. Theproportion correct was computed for each participant separatelyfor central and incidental questions.

Participants’ visual attention to the television was coded fromvideotapes. Using a computer program synchronized to the begin-ning of the television program, we obtained a continuous record ofthe child’s looks at and away from the television. This continuousrecord of looks allowed for identification of looking status at thetime of every probe as either on or off task. The mean percentageof visual attention was at ceiling (M � 0.96, SD � 0.04). RT datawere analyzed after removal of all probe RTs that occurred duringa look away from the television (n � 51, less than 5% of targetprobes). The pattern of results is identical with these RTs included,but analyses reported in this article exclude RTs to probes thatsounded during looks away from the television (Lorch & Castle,1997).

RTs

Mean response times were analyzed in a repeated measuresanalysis of variance (ANOVA), with centrality (central and inci-dental) and probe position (2, 7, 12 s into sequence, and laterposition) as within-subject variables. Follow-up linear trend anal-yses tested the a priori prediction that RTs to probes wouldincrease as the time into a sequence of central content increased. Inaddition, we tested whether RTs to probes would decrease as timeinto a sequence of incidental content increased. Mean RTs as afunction of centrality and probe position are depicted in Figure 1.

As hypothesized, a significant interaction was observed betweencentrality and probe position, F(3, 171) � 3.32, p � .022. Linear


trend analyses indicated that RTs to probes occurring duringcentral sequences increased as time into the sequences increased,F(1, 57) � 4.30, p � .05 (effect size r � .26), and RTs to probesoccurring during incidental sequences decreased as time into thesequences increased, F(1, 57) � 6.16, p � .05 (r � .31).Follow-up analyses controlling family-wise error rate indicatedthat the mean RT in the central, 2-s position was significantlyshorter than the central, later position RT, t(58) � 2.36, p � .05(r � .30). The incidental, 2-s position RT was significantly slowerthan the incidental, later position RT, t(58) � 2.29, p � .05 (r �.29). Unexpectedly, children were significantly slower in respond-ing to probes that sounded during incidental sequences (M �612.73) than to probes during central sequences (M � 572.15),F(1, 57) � 9.84, p � .004 (r � .38). No main effect was observedfor probe position (F � 1, p � .05).

Cued Recall Performance

We conducted a t test on cued recall scores to evaluate differ-ences between performance on central and incidental content.Performance on the cued recall questions was significantly betterfor those questions tapping central content (M � 0.85, SD � 0.11)than for those tapping incidental content (M � 0.61, SD � 0.18),t(57) � 12.05, p � .001 (r � .84). This result replicates the patternobserved in numerous previous studies of children’s comprehen-sion of both televised and written stories (e.g., Lorch, Bellack, &Augsbach, 1987; van den Broek, 1989; van den Broek et al., 1996).

A further question concerns the possibility of a relation betweencued recall performance and RTs to secondary probes. If children’scognitive engagement with the televised story varies systemati-

cally, one might expect that recall performance would be related todiffering levels of engagement. Each cued recall question testedinformation that was presented during or close to a unit thatcontained a probe. Mean RTs were computed for probes corre-sponding to questions that each child answered correctly andquestions answered incorrectly. Regardless of centrality, chil-dren’s RTs corresponding to questions they answered correctlytended to be longer (M � 601.77) than their RTs corresponding toquestions they answered incorrectly (M � 587.83), F(1, 48) �3.71, p � .06 (r � .27). This suggests an association betweenonline cognitive engagement with the televised story and laterrecall of specific material.

As predicted, 9- to 11-year-old children’s cognitive engagementwas related to the continuity of central or incidental content.Children’s probe RTs indicated that the longer a sequence ofcentral story content continued, the more engaged children be-came, and that as a sequence of incidental content continued, theybecame less engaged. Children’s increased engagement was alsorelated to better performance on story comprehension measures.Further discussion of the results from all three experiments isreserved for the general discussion.

Experiment 2

Experiment 1 examined cognitive engagement in children ages9 to 11 years, but an unanswered question is whether youngerschool-aged children would also use the causal structure of atelevised story to guide their engagement. Memory for story eventsamong preschoolers and young school-age children is influencedby characteristics of the story’s causal structure, but the impact of

550

600

650

700

750

800

850

2 7 12 Later

Probe Position (Seconds into Sequence)

RT

in m

illis

eco

nd

s

Central

Incidental

Figure 1. Mean probe response times (RTs) as a function of time into central and incidental sequences forExperiment 1.


causal factors increases with age (van den Broek et al., 1996).Children also show improvement with age in detecting connec-tions between groups of events (van den Broek, 1989). In addition,young children show differential responses to global story struc-ture, showing increased attentional engagement as normal storiesdevelop but no systematic change in engagement to scrambledstories (Lorch & Castle, 1997). However, it is unknown whetheryounger children would show online sensitivity to the role differ-ent events play in a coherent story structure. Huston and Wright’s(1983) theoretical perspective suggests that with development,children may become more accomplished at using the story con-tent to determine when deeper and more elaborative processing isnecessary. Thus, Experiment 2 was designed to replicate Experi-ment 1 and to determine whether there are developmental differ-ences in children’s cognitive engagement as a function of thecontinuity of central and incidental content. On the basis of theresults of Experiment 1, it was predicted that older school-agedchildren would show decreasing engagement with the television asincidental content continued and increasing engagement as centralcontent continued. Children in the younger age group may be moredependent on formal features of the television program as a guideto their attention, so their engagement may not be as sensitive tothe causal structure of the story as that of older children.

Method

Participants

Participants were 54 younger elementary school-aged children (25boys), ages 6 to 8 (M � 7.83, SD � 0.64), and 57 older elementaryschool-aged children (31 boys), ages 9 to 11 (M � 10.70, SD � 0.56), noneof whom had participated in Experiment 1. Participants were primarilyCaucasian (89.52%), with some African American children (5.71%) andchildren of other ethnic identification (4.76%). Most parents’ educationincluded at least some college; the average parent was a college graduate(M � 16.31 years of education). Children were recruited through adver-tisements in the newspaper and from an existing pool of experimentalvolunteers. Children were paid $10 for their participation, which lastedabout 1 hr. Data were lost from 6 participants as a result of equipmentmalfunction or failure to follow instructions.

Materials and Procedure

The materials and procedure were identical to those of Experiment 1.


Probe RTs

Mean RTs were analyzed in a mixed ANOVA, with age as abetween-subjects variable and centrality (central and incidental)and probe position (2, 7, 12 s into sequence, and later position) aswithin-subject variables. On the basis of the results for Experiment1, follow-up linear trend analyses tested the a priori prediction thatRTs to probes would increase as the time into a sequence of centralcontent increased, whereas RTs to probes would decrease as thetime into a sequence of incidental content increased. More childrenin the younger group (n � 11) than in the older group (n � 1)failed to respond to at least one probe, �2(1, N � 111) � 47.34,p � .01. Mean probe RTs were calculated from the remaining RTs.

As hypothesized, children’s RTs to secondary probes variedjointly as a function of when in a sequence a probe occurred and

whether the sequence presented central or incidental content, F(3,306) � 9.116, p � .001. As shown in Figure 2, linear trendanalyses revealed that RTs increased the longer a sequence ofcentral content continued, F(1, 104) � 34.34, p � .001 (r � .51),and that RTs decreased the longer a sequence of incidental contentcontinued, F(1, 104) � 11.19, p � .001 (r � .31). Follow-upanalyses indicated that for central sequences, RTs for each of thefirst three probe positions differed significantly from RTs for thelater probe position, and RTs for the 2-s position differed fromthose for the 7-s position (ts ranged from 2.5 to 5.2, p � .05). Forthe incidental sequences, only the 12-s and later probe positionsdiffered significantly, t(104) � 2.4, p � .05 (r � .23).

Although older children responded more quickly (M � 601.52)to probes than younger children (M � 836.48), F(1, 102) � 36.47,p � .001 (r � .51), there were no significant differences in thepatterns of probe RTs as a function of age. As found in Experiment1, probe RTs were longer during incidental sequences (M �741.99) than during central sequences of content (M � 689.58),F(1, 102) � 10.95, p � .001 (r � .31).


Children correctly answered a higher proportion of questionstesting central content (M � .81) than questions testing inci-dental content (M � .47), F(1, 103) � 474.85, p � .001 (r �.90). Although older children (M � .73) correctly answered ahigher proportion of questions than younger children (M � .58),F(1, 103) � 48.01, p � .001 (r � .56), the influence ofcentrality on recall performance did not differ as a function ofage, F(1, 103) � 1.

We also examined whether children’s recall performance wasrelated to differing levels of engagement. Overall, central contentquestions that were answered correctly were associated withlonger RTs to probes during presentation of target content (M �722.8 ms) than RTs to probes associated with central contentquestions that were answered incorrectly (M � 673.4 ms), F(1,88) � 9.63, p � .01 (r � .31). This difference was significant forolder children, t(41) � 3.70, p � .001 (r � .55), but not foryounger children, t(47) � 0.90, p � .10.

Experiment 3

The findings of Experiments 1 and 2 demonstrate that onlinevariations in children’s cognitive engagement with a televisedstory are related to the continuity of central or incidental content.As indicated by probe RTs, children became increasingly engagedthe longer sequences of central events continued but decreasedtheir cognitive engagement the longer sequences of incidentalevents continued. Furthermore, this pattern of results was consis-tent from the ages of 6 to 11. These findings indicate that even theyounger children were sensitive to the causal structure of the story,using it to guide their allocation of cognitive resources. Given thereliable findings obtained for comparison children in Experiments1 and 2, Experiment 3 was designed to examine the cognitiveengagement of children with ADHD, whose problems in sustain-ing attention and comprehending causal relations have been welldocumented (Lorch, Eastham, et al., 2004).

As discussed earlier, two studies have addressed the issue ofcognitive engagement among children with ADHD. The results of


Lorch, Eastham, et al. (2004) suggest that variations in cognitiveengagement, as operationalized by time spent in long looks, ac-count for the problems that children with ADHD have with causalrelations questions. However, the degree of cognitive engagementwas inferred from time spent in long looks. By using the secondarytask implemented in Experiments 1 and 2, Whirley et al. (2003)offered a more direct assessment of cognitive engagement among9- to 11-year-old boys with ADHD. The boys with ADHD failedto show the same systematic increase in cognitive engagementobserved in comparison boys as central sequences progressed.

Experiment 3 was designed to replicate and extend the findingsof Experiments 1 and 2 and from Whirley et al. (2003). In Exper-iment 3, we use a developmental perspective to compare thecognitive engagement of children with ADHD and their compar-ison peers, using an age range that includes younger children (i.e.,4 to 9 years) than the previous secondary task studies. Lorch andCastle (1997), using the secondary task, found that 5-year-oldsdemonstrated variations in cognitive engagement as a function ofdramatic differences in the comprehensibility of television pro-gramming. However, in Experiment 3, like Experiments 1 and 2,the task used investigates whether children make changes in theircognitive engagement as a sequence of central or incidental eventsdevelops. Thus, Experiment 3 integrates the developmental per-spective offered by Experiments 1 and 2 with the questions raisedby Whirley et al. concerning children with ADHD.

A second purpose of Experiment 3 was to assess children’smetacognitive understanding of the importance of events to theplot of the story. The secondary task is designed to tap moment-to-moment variations in cognitive engagement in relation to thecentrality of the events. In contrast, a metacognitive understandingrefers to whether, after viewing the program, children are able tomake explicit differentiations among events in terms of their

importance to the overall story. To accomplish this purpose, weasked the children in Experiment 3 to sort pictures of story eventsinto categories of low, medium, or high importance, and wecompared age and diagnostic group differences in sorting accu-racy. In addition, we assessed the role of sorting accuracy inaccounting both for moment-to-moment engagement on the sec-ondary task and for the postviewing measure of story recall.

Method

Participants

This study was part of a larger longitudinal project designed to examinestory comprehension and its relation to attention among children withADHD. Although the original sample included 193 children, data for 28children had to be eliminated. This resulted in a final sample of 64 children(49 boys, 15 girls) with a confirmed diagnosis of ADHD and 101 com-parison children (61 boys, 40 girls), ranging in age from 4.0 to 9.9 years(M � 7.5 years). Each group of children was further classified into two agegroups, a group of 64 younger children (between 4 and 7 years 0 monthsof age; M � 5.75 years), and a group of 101 older children (between 7years 1 month and 9 years 11 months of age; M � 8.5 years).

To ensure an accurate diagnosis of ADHD, we used a three-step processin the recruitment of children assigned to the ADHD group. First, allchildren assigned to this group were referred from medical care settingswhere, independently of the current study, they had received a diagnosis ofADHD/combined type according to criteria in the Diagnostic and Statis-tical Manual of Mental Disorders (4th ed., text rev.; American PsychiatricAssociation, 2000). Second, referred children’s medical records were re-viewed before they were admitted into the study. This review focused oninformation regarding the children’s behavior, intellectual and academicfunctioning, medical history, age of diagnosis, and other relevant issues.Children were excluded from the current study if information obtainedduring the review described a symptom picture inconsistent with ADHD/

500

600

700

800

900

1000

1100

2 7 12 Later


RT

in m

illis

eco

nd

s

Central Incidental

Figure 2. Mean probe response times (RTs) as a function of time into central and incidental sequences forExperiment 2.


combined type, if their IQ score was less than 70, or if they were takingmedications that could not be discontinued for the study. The mere pres-ence of comorbid diagnoses (e.g., oppositional defiant disorder or conductdisorder) was not cause for exclusion from the study. Children whoseprincipal ADHD symptoms related to inattention were excluded from thisstudy because of growing empirical evidence suggesting that children withattentional difficulties in the absence of hyperactivity and impulsivity maybest be classified as suffering from a distinct disorder that is not a subtypeof ADHD (Milich, Balentine, & Lynam, 2001).

At a final step, the diagnosis of ADHD/combined type was confirmed byresearch staff using a semistructured parent interview designed to assessthe presence of ADHD or oppositional defiant disorder according toDSM–IV criteria. This same interview has been used successfully for theclassification of children with ADHD in previous studies (Lorch et al.,2000; Lorch, Eastham, et al., 2004; Whirley et al., 2003). An earlier studyfound the interrater reliability for number of ADHD symptoms endorsed inthe parent interviews to be 99% (Lorch et al., 1999). Children were notassigned to the ADHD group unless this interview confirmed a diagnosisof ADHD/combined type. Children taking stimulant medication did notreceive their medication on the day of the study.

Children in the comparison group were recruited through newspaperadvertisements and flyers. Children were excluded from participation inthis group if data gathered through a parent interview and the ChildBehavior Checklist (Achenbach, 1991) suggested the presence of anybehavior or learning disorders. Once admitted into the study, parents had tocomplete a semistructured parent interview designed to assess the presenceof ADHD or oppositional defiant disorder according to DSM–IV criteria.Children who met three or more criteria for inattention or hyperactivitywere not included in the final analyses.

Demographic characteristics for each group of children can be found inTable 1. Children in the comparison group averaged less than one symptomof ADHD. By comparison, children in the ADHD group averaged 15.84symptoms, a difference that was statistically significant, t(162) � 33.04,p � .001 (r � .93). There were no group differences in terms of age,t(162) � 0.587, p � .10, but the groups did differ significantly in terms ofmothers’ and fathers’ average years of education.2

Procedure

The materials and procedure were identical to those of Experiments 1and 2, except for the following three changes. First, because the childrenwere participating in a longitudinal investigation in which they wouldrepeat the secondary probe task at a later time period, two differentGrowing Pains episodes were used. One episode was the same as was used

in Experiments 1 and 2; the second one was newly prepared for this study,via the same procedures to identify appropriate probe positions in centraland incidental sequences. Similarly, appropriate cued recall questions weregenerated for content that was high or low in importance.

The second subsequent change in the procedures from the prior exper-iments was that the auditory probes placed 7 s into the sequences weredeleted, so that auditory probes only were presented at 2, 12, or 24 s or laterinto a sequence. This change was made to streamline the procedure andbecause in Whirley et al. (2003) the 7-s probe did not supply uniqueinformation. For both importance levels (i.e., central and incidental), eachseries contained between 4 and 5 probes in each basic position, resulting ina total of 13 probes for both the central and the incidental sequences. As inExperiments 1 and 2, each probe continued until a response was made.However, because of the younger age of the sample in Experiment 3, thesound ended after 7 s if no response was made. Twelve filler probes wereinserted in the program, so that each episode of the show consisted of 38probes, including 13 during presentation of central content, 13 duringincidental content, and 12 filler probes that were not analyzed.

The third change in the experimental protocol was to include a sortingtask after completion of the probe task. The sorting task provided ameasure of understanding of the importance of story events. The taskconsisted of 12 pictures: 4 depicting very important events from the story,4 depicting medium important events, and 4 depicting not importantevents. Selection of the 12 story events was based on the adult ratings ofimportance of story events, described earlier. Each event was described ina caption at the bottom of the picture. The examiner read each captionwhile showing the card to the child. As each card was read, it was placedon the table in front of the child. Under each of the three category labels(i.e., very important, medium important, not important) was placed a smallgrid, which was segmented into four spaces, each the size of a picture card.The three categories were carefully explained to the child. The child wasthen asked to place the picture cards under the appropriate categoryheading. Only four events could be placed in each category. The child wasallowed to ask for any event description to be repeated and could make asmany changes to the categorizations as desired.

2 Because of the group differences in parent education, analyses wererepeated with mothers’ years of education as a covariate. The pattern ofresults was unchanged with the covariate included. Similar analyses werenot undertaken for fathers’ years of education because of a higher fre-quency of missing data on this variable. However, the high correlationbetween mothers’ and fathers’ years of education (r � .89) suggests thatthe pattern of results would be the same.

Table 1Comparison of Two Diagnostic Groups in Experiment 3 on Relevant Demographic Variables

Factor

ADHD(n � 64)

Comparison(n � 101)

t(162) pM SD M SD

Age in yearsYounger group 5.88 0.85 5.72 0.76 0.82 .417Older group 8.61 0.96 8.48 0.85 0.72 .471

Mother’s education 14.02 2.20 15.63 2.25 4.44 .001Father’s education 14.09 3.38 16.30 3.05 4.18 .001DSM–IV–TR

Inattention 6.11 2.21 0.16 0.46 26.23 .001Hyp/imp 6.19 1.98 0.18 0.48 29.20 .001Oppositionality 3.49 2.31 0.27 0.71 13.69 .001

Note. ADHD � attention-deficit/hyperactivity disorder; DSM–IV–TR � Diagnostic and Statistical Manual ofMental Disorders (4th ed., text rev.); Hyp/imp � hyperactivity/impulsivity.


There were three dependent variables concerning importance judgmentsin the sorting task. The measure of gross errors included only those veryimportant events the child placed in the not important pile or vice versa.The number of seconds to complete the sorting task and the total numberof moves made in completing the sorting task were measures of impulsivityand of how effectively the child planned and executed sorting categoriza-tions. These are considered core symptoms of ADHD, so these measureswere included to determine whether such difficulties explained any groupdifferences in sorting errors.


The main dependent variable for the secondary task was RTs to26 target probes. Data for children were not included in the finalanalyses unless the children had responded to at least two of theprobes for any given probe position. Ten children were excludedbecause they responded to too few probes. Five of these childrenwere in the ADHD group, whereas 5 were comparison partici-pants, �2(1, N � 175) � 1, p � .10. Because of equipmentmalfunction, data for 18 children (10 comparison, 8 with ADHD)were not used. Excluding these 28 children left the final sample of64 children in the ADHD group and 101 children in the compar-ison group.

Probe RTs

To explore the patterns of engagement for children with ADHDversus comparison children, we performed a 2 � 2 � 2 � 3 mixedANOVA. Diagnostic group (comparison and ADHD) and agegroup (younger and older) were the between-subjects variables,and sequence type (central vs. incidental) and probe position (2,12, and 24 s and beyond into sequence) were the within-subjectvariables. Given the significant Centrality � Probe Position inter-actions found in Experiments 1 and 2, the primary effect of interestin Experiment 3 was the Diagnostic Group � Centrality � Probe

Position interaction, F(2, 161) � 3.5, p � .05. Because thisinteraction was significant and different patterns have been foundfor central and incidental sequences (Experiments 1 and 2; Whir-ley et al., 2003), the following results are presented separately forthe two types of sequences.

Central sequences. For central sequences, a significant maineffect of probe position, F(2, 161) � 13.36, p � .001, wasqualified by a significant Diagnostic Group � Probe Positioninteraction, F(2, 161) � 11.19, p � .001 (see Figure 3). Lineartrend analysis of this interaction indicated that RTs to probes forcomparison children increased as central content continued, F(1,100) � 38.70, p � .001 (r � .53). Follow-up analyses revealedthat RTs to the later probes were significantly longer than both the2-s probes, t(100) � 6.22, p � .01 (r � .53), and the 12-s probes,t(100) � 5.08, p � .01 (r � .21). In contrast to the pattern for thecomparison children, linear trend analysis of the RTs of childrenwith ADHD demonstrated no significant change as central se-quences progressed, F(1, 63) � 1.

Younger children were slower to respond to probes than olderchildren, F(1, 161) � 10.66, p � .001 (r � .25), but this maineffect was qualified by a significant Diagnostic Group � AgeGroup interaction, F(1, 161) � 4.59, p � .05 (r � .17). Youngercomparison children were significantly slower than their oldercounterparts, F(1, 99) � 24.18, p � .001 (r � .44), but youngerand older children with ADHD did not differ in overall RT, F(1,62) � 1.

Incidental sequences. For incidental sequences, there was amain effect of diagnostic group, such that children with ADHD(M � 911 ms) showed significantly longer RTs than comparisonchildren (M � 794 ms) to probes presented during incidentalsequences, F(1, 161) � 5.75, p � .05 (r � .19). Younger children(M � 948 ms) responded significantly slower than their oldercounterparts (M � 757 ms), F(1, 161) � 15.03, p � .001 (r � .29).

500

600

700

800

900

1000

1100

2 12 Later


RT

in m

illi

seco

nds

ADHD, Central Comparison, Central

ADHD, Incidental Comparison, Incidental

Figure 3. Mean probe response times (RTs) as a function of time into central and incidental sequences forchildren with attention-deficit/hyperactivity disorder (ADHD) and nonreferred children for Experiment 3.


There were no significant interactions for incidental sequences(see Figure 3).3


Percentage correct on cued recall questions was analyzed in a2 � 2 � 2 mixed ANOVA, with diagnostic group and age groupas between-subjects variables and centrality as a within-subjectvariable. Significant main effects of diagnostic group, F(1, 161) �6.05 p � .05 (r � .19); age group, F(1, 161) � 127.49, p � .001(r � .66); and centrality, F(1, 161) � 87.98, p � .001 (r � .59),were qualified by significant Diagnostic Group � Age Group, F(1,161) � 5.18, p � .05 (r � .18), and Centrality � Age Group, F(1,161) � 7.48, p � .01 (r � .21), interactions. Performance of oldercomparison children (M � 55% correct) was significantly betterthan that of the older children with ADHD (M � 44%), F(1, 99) �13.58, p � .001 (r � .35). Younger comparison children (M �23%) and younger children with ADHD (M � 23%) did not differin their cued recall performance, F(1, 62) � 1. Children correctlyanswered significantly more questions testing central content(M � 43%) than testing incidental content (M � 28%), and thiswas true for both the younger, t(63) � 4.3, p � .001 (r � .48), andthe older, t(100) � 10.2, p � .001 (r � .71), children. However,the difference in recall of central and incidental content was largerfor older children (mean difference � 20%) than for youngerchildren (mean difference � 11%), t(163) � 2.84, p � .005 (r �.22).

As in Experiments 1 and 2, we examined whether recall perfor-mance was related to differing levels of engagement. Mean RTswere computed for probes corresponding to questions that eachchild answered correctly and questions each child answered incor-rectly, and this variable was found to interact with age group, F(1,145) � 3.75, p � .055 (r � .16), but not with diagnostic group,F(1, 145) � 1. Regardless of centrality, older children’s RTscorresponding to questions they answered correctly (M � 798 ms)tended to be longer than their RTs corresponding to questions theyanswered incorrectly (M � 754 ms), t(99) � 1.86, p � .067 (r �.14), but there was no significant difference for younger children(Ms � 932 and 954 ms, respectively), t(48) � 1. This suggests thatfor older children, increased online cognitive engagement wasassociated with greater recall of story events.

Importance Judgments

Three dependent variables concerning importance judgments inthe sorting task were analyzed in 2 � 2 ANOVAs, with diagnosticgroup and age group as between-subjects variables. The threedependent variables were (a) gross errors, which involved placinglow-importance pictures in the high-importance category, or viceversa; (b) number of seconds to complete the sorting task; and (c)number of moves made in completing the sorting task.

For gross errors, there were significant main effects of diagnos-tic group, F(1, 161) � 9.01, p � .01 (r � .23), and age group,F(1,161) � 44.91, p � .001 (r � .47). Children with ADHD (M �2.5) made more errors than comparison children (M � 1.9), andyounger children (M � 2.9) made more errors than older children(M � 1.5). To determine whether problems in impulsivity orplanning accounted for poorer performance among children withADHD, we analyzed average sorting time and number of sorting

moves. There were no main effects or interactions involving di-agnostic group for either measure. The only significant effect wasthat younger children (M � 13.2) made significantly fewer movesthan older children (M � 14.2), F(1, 159) � 4.56, p � .05 (r �.17).

Importance Judgments in Relation to CognitiveEngagement and Story Recall

We examined the extent to which importance judgments, asindexed by gross errors, accounted for group differences in thepattern of cognitive engagement and in recall performance byentering gross errors as a covariate in the original ANOVAs. Interms of the pattern of cognitive engagement, gross errors did notsignificantly relate to RT, F(1, 160) � 2.05, p � .10, nor did anyof the significant main effects or interactions change. However,gross errors did significantly predict cued recall performance, F(1,160) � 17.61, p � .001 (r � .31), and the main effect of diagnosticgroup was no longer significant, F(1, 160) � 2.39, p � .10.

General Discussion

The findings of these three investigations demonstrate that on-line variations in comparison children’s cognitive engagementwith a televised story were related to the continuity of centralcontent, and this conclusion held true for children ranging in agefrom 4 to 11. As indicated by probe RTs, comparison childrenbecame increasingly engaged the longer sequences of centralevents continued. In contrast, 4- to 9-year-old children withADHD showed no change in cognitive engagement as centralsequences progressed. In the discussion that follows, we firstexamine the general implications of these findings, then addressdevelopmental interpretations and consider specific ways the per-formance of children with ADHD differs from the patterns ob-tained for comparison children.

The pattern of changes in cognitive engagement is consistentwith earlier findings suggesting that children’s attention becomesmore engaged as a coherent story segment develops (Hawkins etal., 1991; Lorch & Castle, 1997; Meadowcroft & Reeves, 1989). Itis notable that the earlier studies examined relatively gross differ-ences in story structure (i.e., events in a meaningful order vs.events in a scrambled, nonsensical order). The current study,however, provides evidence of systematic changes in school-agechildren’s cognitive engagement in response to more subtle dif-ferences in the meaning of events. In the stories used in theseexperiments, all events occurred in a sensible order. However, as

3 Although children in both diagnostic groups demonstrated high rates ofvisual attention to the television, comparison children (M � 96%) weremore likely than children with ADHD (M � 90%) to be attending to thetelevision when target probes were presented, t(163) � 4.11, p � .001.Therefore, we repeated the analyses, excluding probes when children werenot attending to the television. This required dropping 10 additional chil-dren (3 comparison, 7 with ADHD) from the analyses, because not all cellshad a sufficient number of probes. Despite the loss of power, the pattern ofRT results remained the same, with a significant Group � Linear ProbePosition interaction for central sequences, F(1, 151) � 11.40, p � .001, butthe interaction failed to reach significance for incidental sequences, F(1,151) � 3.36, p � .05.


central sequences progressed, more content connected to the plotwas provided, eliciting greater cognitive engagement from chil-dren. In contrast, as incidental sequences progressed, plot devel-opment was not enhanced, leading either to decreased cognitiveengagement (Experiments 1 and 2) or to no systematic change inengagement (Experiment 3; Whirley et al., 2003).

The current findings are consistent with the notion that, duringviewing, children engage in the online construction of a storyrepresentation (Trabasso & Nickels, 1992; Trabasso et al., 1992).Sequences of central events consist primarily of events that arepart of the causal chain defining the plot of the story and areperceived as very important by adult viewers. As such, the eventsin central sequences figure importantly in a coherent representa-tion of the story. As children view the program and a sequence ofcentral content continues, they encounter events that can be con-nected to the main thread of the story. In contrast, incidental eventsare not part of the causal chain and are considered generallyunimportant by adult viewers. As a sequence of incidental eventscontinues, children encounter events that cannot be linked to theplot of the story. The lack of connections to the causal chain of thestory leads children to stop at more superficial processing; thus,they do not need to increase allocation of attention to eventspresented later in incidental sequences. These systematic changesin children’s cognitive engagement indicate that they are buildinga coherent representation during viewing that reflects the causalstructure of the story.

This online construction of a story representation also is con-sistent with Huston and Wright’s (1983) proposal that childrenmay engage in cycles of decisions concerning whether to performdeeper and more elaborative processing of material. Huston andWright’s theory was designed to predict patterns of visual attentionto television under conditions that enable children to engage inalternative activities (e.g., toy play). Under such conditions, visualattention is predicted by formal and content characteristics thatrelate to children’s comprehension (Alwitt et al., 1980; Campbellet al., 1987). Thus, visual attention provides one indication ofchildren’s cognitive processing during viewing. However, the taskconditions of the current study elicited consistently high levels ofvisual attention, even from younger children. RTs to secondaryprobes suggest that even while children maintained visual atten-tion, their decisions to engage in deeper processing were influ-enced by the centrality and continuity of content. These findingsindicate that the secondary task procedure can serve as a valuabletechnique for revealing subtle variations in children’s cognitiveengagement.

The clearest indication of systematic change in cognitive en-gagement as a function of time into a sequence is observed whenRTs to the later probes are considered. These later probes occurredafter a sequence of central content had been in progress for at least24 s. The strength of these effects for later probes suggests aconceptual parallel with the phenomenon of attentional inertia(Anderson, Choi, & Lorch, 1987). Attentional inertia refers to theobservation that the longer a look at the television has been inprogress, the higher is the probability that the look will continue,with this function leveling off at approximately 15 s into a look. Ofspecial relevance to the current study, converging evidence fromseveral measures indicates that cognitive engagement is greater ifa look has continued for at least 15 s than it is during a shorter look(Anderson et al., 1987; Burns & Anderson, 1993; Lorch & Castle,

1997). Similar to the increase in cognitive engagement for verylong looks, in the current study the continuation of central contentalso promoted increased cognitive engagement with the story, eventhough children maintained high levels of visual attention through-out the session. Thus, taken together, these findings highlight theimportance of long sequences on level of cognitive engagement forboth long looks and long sequences of a particular type of content.

Consistent with other investigations (Lorch et al., 1987; Tra-basso et al., 1984; van den Broek, 1989; van den Broek et al.,1996), children’s memory for central events was superior to theirmemory for incidental events. Thus, memory for story eventsreflects the causal structure of the story. Part of this effect may bedue to postviewing processes of structuring the story as content isretrieved during the recall task. However, the current results sug-gest that children’s systematic increases or decreases in theironline allocation of resources also may contribute to recall differ-ences. Consistent with this interpretation, children tended to showgreater cognitive engagement with events that they later recalled ata higher rate. This was true for central sequences across all threeexperiments and for incidental sequences in Experiments 1 and 3.Similar to these findings, Britton, Piha, Davis, and Wehausen(1978) provided evidence that learning from text was related toadult readers’ probe RTs.

Developmental Implications

One goal of the current investigation was to examine whetherolder and younger elementary school children would differ in theirpatterns of cognitive engagement as a function of the centrality andcontinuity of story content. Overall, children in both age groupsshowed similar systematic variations in cognitive engagement.These findings indicate that even the younger children were sen-sitive to the causal structure of the story, using it to guide theirallocation of cognitive resources.

Despite these similar patterns of engagement for the two agegroups, several results suggest that older children were moreeffective cognitive processors in their story comprehension andallocation of resources. First and not surprising, the older childrenwere faster to respond to probes and answered more cued recallquestions correctly. Second, only older children in Experiments 2and 3 demonstrated the relation between level of engagement andrecall of plot content. It may be that younger children can effec-tively vary allocation of attention in response to plot developmentbut lag behind older children in translating increased attention intoenhanced story recall. This hypothesized developmental progres-sion from behavioral response to enhanced understanding is sim-ilar to one observed in online text comprehension. That is, onencountering inconsistent information in a text, both younger andolder children slow their reading, but older children are more likelyto recall the inconsistency (Harris, Kruithof, Terwogt, & Visser,1981; Zabrucky & Ratner, 1986).

Cognitive Engagement in Children With ADHD

In dramatic contrast to the systematic changes in cognitiveengagement observed for comparison children, children withADHD showed no variation in probe RTs as sequences of centralor incidental material progressed. As such, the group difference inthe pattern of cognitive engagement was even more marked than


that reported by Whirley et al. (2003), who found that only late incentral sequences did children with ADHD begin to show in-creased engagement. Given that Whirley et al.’s sample was sev-eral years older than the children in Experiment 3, this suggeststhat children with ADHD show a pronounced developmental delayin adjusting their cognitive engagement in response to the impor-tance of current content to the developing story. Even comparisonchildren as young as 4 years of age showed the expected linearincrease as central content progressed, whereas it was not until age9 at the earliest (Whirley et al., 2003) that children with ADHDdemonstrated an increase in cognitive engagement from the be-ginning to the end of central sequences. However, it should benoted that the children with ADHD in the Whirley et al. studyshowed a decrease in cognitive engagement during central se-quences prior to the significant increase in RTs at the last probeposition. This pattern has not been observed for any age group ofcomparison children.

It should be noted that, in general, the children with ADHD hadsignificantly longer RTs than the comparison children. This mightlead one to the interpretation that children with ADHD are moreengaged with the television program than comparison children.However, it is well documented that children with ADHD dem-onstrate slower responses on a variety of reaction time tasks,including simple reaction time tasks requiring virtually no cogni-tive processing (Douglas, 1999). Just as we would not argue thatyounger children’s longer RTs in Experiment 2 indicate they weremore engaged than older children, we would not conclude pro-cessing differences on the basis of overall group RT comparisons.Instead, as we have argued throughout, it is the increase in RTs ascentral sequences progress that is indicative of increasedengagement.

The present results concerning the children with ADHD areconceptually similar to those reported by Meadowcroft and Reeves(1989). Their finding that only children with well-developed storyschema knowledge showed differences in engagement as storycoherence varied is consistent with prior results that children withADHD are deficient in their appreciation of story structure vari-ables (Lorch, O’Neil, et al., 2004; Renz et al., 2003). The resultsof both Experiment 3 and Meadowcroft and Reeves reinforce theview that appropriate adjustments in cognitive engagement arerelated to the ability to achieve coherent story representations.

The results for children with ADHD also are conceptuallysimilar to those of Lorch, Eastham, et al. (2004), who manipulatedlevels of visual attention and operationalized cognitive engage-ment in terms of long looks (i.e., at least 15 s) at the television.Findings from both investigations support the interpretation thatcomparison children are better able than children with ADHD toalter cognitive engagement in response to changes in story content.In Lorch, Eastham, et al.’s study, the amount of time spent indeeper cognitive processing during long looks helped to explainthe differential patterns of recall in children with ADHD andcomparison children. In Experiment 3, the systematic changes incognitive engagement demonstrated by comparison children sug-gest that these children constructed a more complete story repre-sentation than children with ADHD. Thus, there is compellingevidence (Experiment 3; Lorch, Eastham, et al., 2004; Whirley etal., 2003) across a wide age range and different methodologies thatchildren with ADHD have significant difficulties achieving and

sustaining cognitive engagement. In turn, these difficulties impairthe story comprehension of children with ADHD.

Limitations

One limitation of the current series of experiments is that theyall used one or two episodes of the same situation comedy pro-gram. The degree to which the obtained results would generalize toother types of programming or even other situation comedies isunknown. However, both Growing Pains episodes were selectedon the basis of their strong narrative structures. Both episodesconformed to prototypical story structures (Mandler & Johnson,1977), in which an initiating event creates a goal that the protag-onist must reach through a series of attempts to overcome obsta-cles to goal attainment. As such, we expect that the current studies’consistent finding of increased engagement as central sequencesprogressed would be replicated in experiments using other pro-grams with strong narrative structures.

Although the core finding of increased RTs as central sequencescontinued was consistent for comparison children across the threestudies, there were a few inconsistent or unexpected results, espe-cially concerning the patterns of RTs for incidental sequences. InExperiments 1 and 2, RTs to probes occurring early in incidentalsequences were longer than RTs to probes in the same position incentral sequences. Furthermore, although Experiments 1 and 2revealed decreases in engagement as incidental sequences pro-gressed, no such decrease was found in Experiment 3 for eitherdiagnostic group. These inconsistencies for incidental sequencesmay reflect the possibility that factors other than the plot relevanceof story content influence children’s engagement with these se-quences. Because the initially long RTs to incidental probes inExperiments 1 and 2 were particularly unexpected, we examinedthe content of these sequences to see whether we could identifyany other differences between the central and incidental sequencesto account for these findings. There were no differences betweensequence type in the amount of dialogue, the incidence of the laughtrack, episode boundaries, or scene changes. Several of the inci-dental sequences appear to be for comedic purposes rather than toprovide plot-relevant content. It may be that children’s attentionwas drawn to these moments of comic relief, but when childrenrealized that the content was not necessary for understanding theplot, engagement was quickly reduced. The fact that in Experiment3 incidental sequences did not provoke initially longer RTs, norwas there any change as the sequences progressed, may reflect theaddition of a second television program. Perhaps it is not surpris-ing that there is inconsistency in the patterns of responses toincidental sequences, because, by definition, these sequences areextraneous to the plot and thus are likely to produce unpredictableinfluences on children’s engagement. The most critical point is thatno group of children ever became more engaged with incidentalmaterial as the sequences progressed. For future research, theprimary focus should be on children’s engagement with centralcontent, with incidental sequences serving merely as a control toensure that increases in RTs are specific to central sequences.

Future Directions

Additional research is needed to better understand and evaluatethe development of children’s online processes of building story


representations, both for comparison children and for those diag-nosed with ADHD. Many of the conclusions about the develop-ment of story comprehension have been inferred from studiesexamining recall of story events. To create a fuller understandingof children’s comprehension, more research is needed using meth-odologies that examine online processes of story comprehension. Itmay be possible to use the secondary task methodology with bothtelevised stories and written stories in a converging operationsapproach to gain more specific information about children’s onlineprocessing of stories (Beentjes & van der Voort, 1993). Use oftelevised stories makes it possible to present more lengthy andcomplex stories and to study a relatively wide age range ofchildren. Use of the secondary task methodology during reading ofwritten stories (Britton et al., 1978; Britton & Tesser, 1982),however, would permit greater control over specific content andvariations in story structure. Another methodology that could beused to examine ongoing story processing, particularly in youngerchildren, is online story narration (Renz et al., 2003; Trabasso &Nickels, 1992; Trabasso et al., 1992). This methodology examinesthe extent to which children use a goal-based structure to incor-porate new information into their ongoing story representation.

Future research also can examine how deficits in cognitiveengagement for children with ADHD might account for theirwell-documented academic problems. Results of this and otherstudies (e.g., Lorch, O’Neil, et al., 2004) indicate that the academicdeficits associated with ADHD go beyond mere problems insustaining attention and instead reflect difficulties in sustainingcognitive engagement, identifying important content, and makingconnections among story events (Milich et al., 2005). Futureresearch also can begin to test the efficacy of academic interven-tions designed to target these specific deficits. Such targeted in-terventions may include the mapping of important story events andtheir interconnections, training in the focused use of advance-organizing techniques, and learning studying strategies that em-phasize connections among story events (Berthiaume, in press).

In summary, the current investigation provides evidence that 4-to 11-year-old comparison children, but not children with ADHD,systematically vary their cognitive engagement while watching atelevised story in a way that is appropriate for building a coherentstory representation. A more thorough understanding of children’sstory comprehension processes may be helpful for understandingcomprehension processes in general. In school, many tasks thatchildren complete are related to story comprehension, and anunderstanding of processing during these tasks may assist andguide the presentation of material to be maximally beneficial tochildren’s learning, especially for children who experience aca-demic difficulties.

References

Achenbach, T. M. (1991). Manual for the Child Behavior Checklist.Burlington: Department of Psychiatry, University of Vermont.

Ackerman, B. P. (1986). Referential and causal coherence in the storycomprehension of children and adults. Journal of Experimental ChildPsychology, 41, 336–366.

Ackerman, B. P., Paine, J., & Silver, D. (1991). Building a story repre-sentation: The effects of early concepts on later causal inferences bychildren. Developmental Psychology, 27, 370–380.

Alwitt, L. F., Anderson, D. R., Lorch, E. P., & Levin, S. R. (1980).

Preschool children’s visual attention to attributes of television. HumanCommunication Research, 7, 52–67.

American Psychiatric Association. (2000). Diagnostic and statistical man-ual of mental disorders (4th ed., text rev.). Washington, DC: Author.

Anderson, D. R., Choi, H. P., & Lorch, E. P. (1987). Attentional inertiareduces distractibility in young children’s television viewing. ChildDevelopment, 58, 798–806.

Anderson, D. R., & Lorch, E. P. (1983). Looking at television: Action orreaction? In J. Bryant & D. R. Anderson (Eds.), Children’s understand-ing of television: Research on attention and comprehension (pp. 1–33).New York: Academic Press.

Anderson, D. R., Lorch, E. P., Field, D. E., & Sanders, J. (1981). Theeffects of TV program comprehensibility on preschool children’s visualattention to television. Child Development, 52, 151–157.

Anderson, D. R., Lorch, E. P., Smith, R., Bradford, R., & Levin, S. R.(1981). The effects of peer presence on preschool children’s visualattention to television. Developmental Psychology, 17, 446–453.

Baer, S. A., & Lorch, E. P. (1990, March). Effects of importance onchildren’s attention to television. Paper presented at the meeting of theSoutheastern Regional Conference on Human Development, Richmond,VA.

Basil, M. U. (1994). Secondary reaction-time measures. In A. Lang (Ed.),Measuring psychological responses to media messages (pp. 85–98).Hillsdale, NJ: Erlbaum.

Beentjes, J. W. J., & van der Voort, T. H. A. (1993). Television viewingversus reading: Mental effort, retention, and inferential learning. Com-munication Education, 42, 191–205.

Berthiaume, K. S. (in press). Attentional and story comprehension deficitsin children with ADHD: What is the connection? School PsychologyReview.

Black, J. B., & Bower, G. H. (1980). Story understanding as problemsolving. Poetics, 9, 223–250.

Britton, B. K., Graesser, A. C., Glynn, S. M., Hamilton, T., & Penland, M.(1983). Use of cognitive capacity in reading: Effects of some contentfeatures of text. Discourse Processes, 6, 39–57.

Britton, B. K., Piha, A., Davis, J., & Wehausen, E. (1978). Reading andcognitive capacity usage: Adjunct question effects. Memory and Cog-nition, 6, 266–273.

Britton, B. K., & Tesser, A. (1982). Effect of prior knowledge on use ofcognitive capacity in three complex cognitive tasks. Journal of VerbalLearning and Verbal Behavior, 21, 421–436.

Burns, J. J. & Anderson, D. R. (1993). Attentional inertia and recognitionmemory in adult television viewing. Communication Research, 20,777–799.

Calvert, S. L., Huston, A. C., Watkins, B. A., & Wright, J. C. (1982). Therelation between selective attention to television forms and children’scomprehension of content. Child Development, 53, 601–610.

Campbell, T. A., Wright, J. C., & Huston, A. C. (1987). Form cues andcontent difficulty as determinants of children’s cognitive processing oftelevised educational messages. Journal of Experimental Child Psychol-ogy, 43, 311–327.

Douglas, V. I. (1999). Cognitive control processes in attention-deficit/hyperactivity disorder. In H. C. Quay & A. E. Hogan (Eds.), Handbookof disruptive behavior disorders (pp. 105–139). New York: Kluwer.

Graesser, A. C., & Clark, L. F. (1985). The structures and procedures ofimplicit knowledge. Norwood, NJ: Ablex.

Harris, P. L., Kruithof, A., Terwogt, M., & Visser, T. (1981). Children’sdetection and awareness of textual anomaly. Journal of ExperimentalChild Psychology, 31, 1215–1223.

Hawkins, R. P., Kim, Y., & Pingree, S. (1991). The ups and downs ofattention to television. Communication Research, 18, 53–76.

Hawkins, R., Tapper, J., Bruce, L., & Pingree, S. (1995). Strategic andnonstrategic explanations for attentional inertia. Communication Re-search, 22, 188–206.


Huston, A. C., & Wright, J. C. (1983). Children’s processing of television:The informative functions of formal features. In J. Bryant & D. R.Anderson (Eds.), Children’s understanding of television: Research onattention and comprehension (pp. 35–58). New York: Academic Press.

Huston, A. C., Wright, J. C., Wartella, E., Rice, M. L., Watkins, B. A.,Campbell, T., & Potts, R. (1981). Communicating more than content:Formal features of children’s television programs. Journal of Commu-nication, 31, 32–48.

Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ:Prentice-Hall.

Lorch, E. P., Anderson, D. R., & Levin, S. R. (1979). The relationship ofvisual attention to children’s comprehension of television. Child Devel-opment, 50, 722–727.

Lorch, E. P., & Baer, S. A. (1997, April). Children’s strategic adjustmentsin attention to and recall from television. Paper presented at the meetingof the Society for Research in Child Development, Washington, DC.

Lorch, E. P., Bellack, D. R., & Augsbach, L. H. (1987). Young children’smemory for televised stories: Effects of importance. Child Development,58, 453–463.

Lorch, E. P., & Castle, V. J. (1997). Preschool children’s attention totelevision: Visual attention and probe response times. Journal of Exper-imental Child Psychology, 66, 111–127.

Lorch, E. P., Eastham, D., Milich, R., Lemberger, C. C., Sanchez, R. P.,Welsh, R., & van den Broek, P. (2004). Difficulties in comprehendingcausal relations among children with ADHD: The role of cognitiveengagement. Journal of Abnormal Psychology, 113, 56–63.

Lorch, E. P., Milich, R., Sanchez, R. P., van den Broek, P., Baer, S., Hooks,K., et al. (2000). Comprehension of televised stories in boys withattention deficit hyperactivity disorder and nonreferred boys. Journal ofAbnormal Psychology, 109, 321–330.

Lorch, E. P., O’Neil, K., Berthiaume, K. S., Milich, R., Eastham, D., &Brooks, T. (2004). Story comprehension and the impact of studying onrecall in children with ADHD. Journal of Clinical Child and AdolescentPsychology, 33, 506–515.

Lorch, E. P., Sanchez, R., van den Broek, P., Milich, R., Murphy, E. L.,Lorch, R., & Welsh, R. (1999). The relation of story structure propertiesto recall of television stories in young children with attention deficithyperactivity disorder and nonreferred peers. Journal of Abnormal ChildPsychology, 27, 293–309.

Mandler, J. M., & Johnson, N. S. (1977). Remembrance of things parsed:Story structure and recall. Cognitive Psychology, 9, 111–151.

Meadowcroft, J. M., & Reeves, B. (1989). Influence of story schemadevelopment on children’s attention to television. Communication Re-search, 16, 352–374.

Milich, R., Balentine, A., & Lynam, D. R. (2001). ADHD combined typeand ADHD predominantly inattentive type are distinct and unrelateddisorders. Clinical Psychology: Science and Practice, 8, 463–488.

Milich, R., Lorch, E. P., & Berthiaume, K. (2005). Story comprehension inchildren with ADHD: Research findings and treatment implications. InM. P. Larimer (Ed.), Progress in attention/deficit hyperactivity disorderresearch (pp. 111–137). Hauppauge, NY: Nova Science.

Nezworski, R., Stein, N. L., & Trabasso, T. (1982). Story structure vs.content in children’s recall. Journal of Verbal Learning and VerbalBehavior, 21, 196–206.

Pingree, S. (1986). Children’s activity and television comprehensibility.Communication Research, 13, 239–256.

Renz, K., Lorch, E. P., Milich, R., Lemberger, C., Bodner, A., & Welsh, R.(2003). On-line story representation in boys with attention deficit hy-peractivity disorder. Journal of Abnormal Child Psychology, 31, 93–104.

Rolandelli, D. R., Wright, J. C., Huston, A. C., & Eakins, D. (1991).Children’s auditory and visual processing of narrated and nonnarratedtelevision programming. Journal of Experimental Child Psychology, 51,90–122.

Salomon, G. (1983). Television watching and mental effort: A socialpsychological view. In J. Bryant & D. R. Anderson (Eds.), Children’sunderstanding of television: Research on attention and comprehension(pp. 181–198). New York: Academic Press.

Schmidt, C. R., & Paris, S. G. (1983). Children’s use of successive cluesto generate and monitor inferences. Child Development, 54, 742–759.

Thorson, E., Reeves, B., & Schleuder, J. (1985). Message complexity andattention to television. Communication Research, 12, 427–454.

Trabasso, T., & Nickels, M. (1992). The development of goal plans ofaction in the narration of a picture story. Discourse Processes, 15,249–275.

Trabasso, T., Secco, T., & van den Broek, P. (1984). Causal cohesion andstory coherence. In H. Mandl, N. L. Stein, & T. Trabasso (Eds.),Learning and comprehension of text (pp. 83–111). Hillsdale, NJ: Erl-baum.

Trabasso, T., Stein, N. L., Rodkin, P. C., Munger, M. P., & Baughn, C. R.(1992). Knowledge of goals and plans in the on-line narration of events.Cognitive Development, 7, 133–170.

Trabasso, T., & van den Broek, P. (1985). Causal thinking and the repre-sentation of narrative events. Journal of Memory and Language, 24,612–630.

van den Broek, P. (1989). Causal reasoning and inference making injudging the importance of story statements. Child Development, 60,286–297.

van den Broek, P. W. (1997). Discovering the cement of the universe: Thedevelopment of event comprehension from childhood to adulthood. In P.van den Broek, P. Bauer, & T. Bourg (Eds.), Developmental spans inevent comprehension: Bridging fictional and actual events (pp. 321–342). Hillsdale, NJ: Erlbaum.

van den Broek, P. W., Lorch, E. P., & Thurlow, R. (1996). Children’s andadults’ memory for television stories: The role of causal factors, story-grammar categories and hierarchical level. Child Development, 67,3010–3028.

Whirley, K. S., Lorch, E. P., Lemberger, C. C., & Milich, R. (2003). Onlinecognitive engagement of boys with ADHD. Journal of Attention Disor-ders, 7, 1–11.

Zabrucky, K., & Ratner, H. H. (1986). Children’s comprehension moni-toring and recall of inconsistent stories. Child Development, 57, 1401–1418.

Received May 24, 2005Revision received December 12, 2005

Accepted December 12, 2005 �


Documents

Cognitive engagement and story comprehension in typically developing children and children with ADHD from preschool through elementary school