a temporal analysis of free toy play and distractibility in young children choi anderson 1991 jecp

IOURNAL OF EXPERIMENTAL CHILD PSYCHOLOGY 52, 41-69 (1991)

A Temporal Analysis of Free Toy Play and Distractibility in Young Children

HYEWON PARK CHOI* AND DANIEL R. ANDERsoNt

*University of &an, and tlJniversity of Massachusetts, Amherst

Hypothesizing that children become attentionally engaged during play in a manner similar to that found during television viewing, the temporal structure of free toy play by 5year-olds was examined. In Study 1, 10 children were videotaped during 3 h of play. Play episode lengths were lognormally distributed for each child, with no autocorrelation. Lengths of play episodes were not predicted by time into play session, cumulative play with the particular toy, likelihood of choosing the toy, time since last play with the toy, or sex. Hazard functions for each child were quite similar, increasing to a point between 3 and 14 s after play was initiated, then greatly decreasing thereafter. Study 2 tested the hypothesis that these hazard functions reflect attentional engagement by presenting audiovisual distracters during free toy play by thirty 5-year-olds. Probability of distraction increased to a peak at about 12 s after a play episode began and steadily declined thereafter. Reaction times of headturns toward the distractor, moreover, inversely paralleled the probability of distraction. Attentional engagement is initially fragile and becomes more so for a period of about 12 s into toy play episodes and strengthens thereafter. A model assuming toy play consists of a chain of actions linked by attentional inertia is sufficient to account for these findings. Parallels between toy play and looking at television are discussed. o iw Academic

Press. Inc.

INTRODUCTION

Watching a child play with toys, one is often struck by the degree to which he or she may become deeply absorbed. Similarly, children’s absorbed attention to television has frequently been noted and has been the

This report is based on a dissertation submitted by the first author to the University of Massachusetts in partial fulfillment of the requirements for the Ph.D. Data collection was supported by a grant from the National Science Foundation. The authors thank Rachel Clifton, Arnold Well, Hui-Kuang Hsieh, Leah Larkey, Nancy Myers, Phillippe Rochat, John Burns, and Patricia Collins for their comments. Special thanks go to Pearlie Pitts (receptionist), Le Anne Dyal and Lyn Crevier (video tape raters), Peter Lee, Eric Brewer, and John Burns (computer programming). Correspondence and requests for reprints should be sent to Daniel R. Anderson, Department of Psychology, University of Massachusetts. Amherst, MA 01003.

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0022-0965/91 $3.00 Copyright 0 1991 by Academic Press. Inc.

All rights of reproduction in any form resewed.

42 CHOI AND ANDERSON

occasion for considerable commentary, if not controversy. Theorists as diverse and significant as William James (1890) and Donald Hebb (1949) have argued that such attentional absorption is a fundamental property of psychology. Deep attentional engagement is especially likely to occur, James argued, in situations which are intellectually congenial to the participant. James called such absorption in pleasant cognitive activities “passive intellectual attention” and argued that it provides the basis for much sustained cognitive activity in adults as well as children. He contrasted it to “active” attention which requires effort and will in order to sustain cognitive processing; active attention is required in tasks of little intrinsic interest to the participant or where task materials are difficult to comprehend.

Especially in preschool children, most sustained attention and behavior does not occur in situations requiring James’ active attention. In fact, the largest proportion of American preschool child-waking time is taken up by two activities: free play with toys and watching television (e.g., Timmer, Eccles & O’Brien, 1985). The nature of attention in such free time activities has only recently received research interest despite frequent as- sertions that both toy play and TV viewing have major influences on cognitive development, including the ability to sustain attention (cf. An- derson & Collins, 1988; Rubin, Fein, & Vandenberg, 1983; Singer, 1980).

In this paper we examine sustained free play with toys by young children, with particular reference to the time course of deeply engaged play. The motivation and methodology is based on our work on visual attention to television by children. We hypothesize that there are underlying similarities in sustained attention during television viewing and sustained free play with toys. In particular, we suggest that both consist of a succession of cognitive acts linked by progressively stronger orientation to the medium of cognition (the toy or TV). Arguments that receptive and productive information processing may draw on similar underlying mechanisms are not unprecedented. Shepard (1984), for example, argued that visual imagery and dreams obey the same constraints found in ordinary visual perception.

Many would be surprised if parallels were found between toy play and TV viewing (e.g., Singer, 1980). Superficially, the differences are salient. While toy play is behaviorally active and is cognitively productive, TV viewing is behaviorally inactive and is cognitively receptive. Moreover, a child’s visual attention to TV is to some extent temporally driven by the sequential structure of the TV program. There is no analogous temporal driving of play by most toys; episodes of solitary toy play are ordinarily initiated and terminated by the child alone. We argue, however, that there are deeper similarities which should be reflected in the temporal structure of the two activities. These similarities include the voluntary and self-selected nature of these activities, their schematic organization, their

TOY PLAY AND DISTRACTIBILITY 43

correspondence with James’ (1890) notions of passive intellectual attention, and their potentially intermittent nature.

While knowledge about children’s attention to television has increased greatly in recent years, there has been considerably less modern research on factors which sustain toy play. Early research on sustained toy play (e.g., Bestor, 1934; Cushing, 1929) failed to find a context-free developmental “constant” of “attention span.” This failure subsequently reduced interest in the problem (cf. Moyer & Gilmer, 1955), which has only recently been revived (Ruff & Lawson, 1990). Methodologies which have been developed for the study of television viewing, however, allow new approaches. In the present research, these methodologies are applied in order to determine whether the temporal structure of toy play in fact parallels that for TV viewing. First, however, some methodologies and findings from the television research are described.

Looking at Television

In the television research, the primary unit of analysis has been the “look,” the period of time from the onset of an episode of visual orientation toward the TV screen until its offset. Characteristically, children look at and away from television on the order of 150 times an hour, with the distribution of look lengths highly positively skewed. While the ma- jority of looks are under about 3 s in length, some may last as long as 10 min (Anderson & Field, 1991; Anderson & Smith, 1984). There is thus great variability in the lengths of individual looks but the general shape of the distribution is highly consistent between subjects and across different kinds of program content.

Look lengths are determined by a large group of factors (see Anderson & Burns, 1991; Anderson & Larch, 1983, and Huston & Wright, 1983, for reviews), but for present purposes we concentrate on schema-based cognition and attentional inertia.

Children’s comprehension of television content is schematically organized, with temporal fluctuations of attention largely in service of comprehension activities (cf. Anderson & Larch, 1983; Collins, 1983; Mea- dowcroft & Reeves, 1989). Rendering content less organized or incomprehensible not only reduces comprehension, but also reduces attention (cf. Anderson, Larch, Field, & Sanders, 1981; Collins, Wellman, Kenniston, & Westby, 1978; Pingree, 1986). Because cognitive schemas grow in number, power, and complexity with age over the preschool years, there should be a consequent growth in attention to television. This has been observed both in laboratory and home investigations (e.g., Anderson & Levin, 1976; Anderson, Larch, Field, Collins, & Nathan, 1986).

A typical television program consists of sequences of shots or actions which form scenes, which in turn form larger units, such as acts. Sustained attention across actions and scenes is essential for the inferences necessary


for comprehension and requires a chain of comprehension acts by the child (cf. Anderson & Smith, 1984; Hochberg & Brooks, 1978). Anderson and Larch (1983) have argued that an attentional “glue” is required to sustain attention across the units in order to link the comprehension acts. They suggested that such a glue exists in television viewing and labeled it “attentional inertia.”

Attentional inertia is manifested as an increasing tendency to sustain orientation to television as the time the orientation has already been continuously sustained increases. We have hypothesized (Anderson, Choi, & Larch, 1987) that it is characteristic of activities such as TV viewing and toy play: activities which are schematically structured by chains of sequential actions or comprehension acts and which are consistent with James’ (1890) notion of passive intellectual attention. In essence, we suggest that attentional inertia reflects an underlying process which sustains orientation to the medium of a cognitive activity (e.g., the TV or the toy) even as the moment to moment content of that activity changes and the momentary focus of attention shifts. It is thus the basis for sustained orientation independent of the content of thought or perception. As such, attentional inertia may be a primitive process which directs orientation with a status similar to, but the inverse of, habituation (An- derson & Larch, 1983). Attentional inertia allows, for example, a child to sustain orientation to a source of discourse (such as a TV program), even when that discourse changes content or becomes momentarily incomprehensible. It may also allow a child to productively sustain and extend play schemas. The idea is not completely original: Hebb (1949) argued that such a higher order attentional phenomenon must exist in order to sustain an animal’s orientation to a task situation even as the momentary focus of the animal’s attention changes. James (1890) noted that, when engaged in passive intellectual attention, an individual may readily progress from idea to idea, becoming lost in thought.

Attentional inertia was initially described by Anderson, Alwitt, Larch, and Levin (1979) in terms of the conditional probability that looks would survive through each successive 3-s interval from their onset given that they had already survived to the beginning of the interval. We will describe Anderson et al.? (1979) and later results, however, in terms of the more commonly employed statistical term “hazard” or one minus the conditional survival probability (i.e., the conditional probability that the look terminates). Anderson et al. (1979) found that the hazard curve for looks sharply decreased for 15 s after which it leveled off and continued to decrease slowly. Descriptively, the longer a look remained in progress, the less likely it was to terminate within the next 3-s interval. Group curves were found to be highly representative of curves for individual viewers, and curves for adults were found to be similar to those of child viewers. Unpublished analyses in our laboratory indicate that look lengths


are distributed approximately lognormally and that the hazard curve is in fact nonmonotonic; hazard values increase over the first 1 or 2 s of looks and then progressively decrease thereafter. Such nonmonotonic hazard functions are characteristic of lognormally distributed data (Lee, 1980).

A major question addressed in the television research is whether the hazard curve for looks at TV indicates an underlying time course in attentional engagement. If so, the viewer’s attention should become less vulnerable to factors such as changes in content or distractions which would otherwise tend to terminate looks.

Anderson and Larch (1983) approached this problem by examining preschoolers’ looks at TV during showings of Sesame Street. They were particularly interested in the fate of looks which were in progress at the time one major unit of content ended and another began; normally a look which encounters such a content boundary has a strong likelihood of terminating (Alwitt, Anderson, Larch, & Levin, 1980). Anderson and Larch (1983) found, however, the longer a child had been continuously looking at the screen prior to a major change in content, the longer the child would continue to look after the change in content. That is, attentional inertia served to drive looks across content boundaries so that the child was more likely to be exposed to the new content. Attentional inertia thus served to make the child less vulnerable to changes of content. If attentional inertia links comprehension acts, the links grow stronger the longer attention is sustained.

Anderson et al. (1987) and Larch and Castle (in press) examined children’s resistance to external disruptions during TV viewing. Anderson et al. (1987) presented a 4-s audiovisual slide distraction at random intervals throughout a l-h presentation of Sesame Street to preschool children. They found that, if a child had been looking at the TV for 15 s or longer, the probability of turning toward the distractor was substantially lower than if the child had been continuously looking for less than 15 s. Moreover, if a child did turn to look at the distractor, the reaction time of the head turn was slower if the child had been looking for 15 s or longer. Larch and Castle (in press) gave 5-year-olds a reaction time task to an auditory signal while Sesame Street was presented. If a child continuously looked at the TV program for 15 s or longer, the reaction time to the secondary task was slower than if the child continuously looked for less than 15 s. The authors of both these studies concluded that the child’s attention becomes progressively engaged over the time course of an episode of looking at television.

Sustained Toy Play

There is considerable reason to believe that, like looking at television, sustained toy play is schematically organized. In a detailed analysis of 4- to 8-year-olds’ verbalizations and actions, Eckler and Weininger (1989)


found that toy play typically consisted of a sequence of actions forming storylike episodes with connections between episodes becoming more causal in older children. Analogous to expectations for looking at television, it would be expected that sustained play would tend to increase in length with age. This has been verified (Eckler & Weininger, 1989; Ruff & Lawson, 1990).

If toy play is sustained by processes shared with television viewing, then attentional inertia may be common to both. Our initial observations suggest this may be so.

Many of our studies of children’s TV viewing have been conducted with toys available throughout the TV program. We observed that the periods when the child did not look at the TV (called “pauses”) tend to be lognormally distributed. Moreover, Anderson et al. (1987) found that children were less likely to look at a distractor slide if the pause lasted longer than 15 s. Since the pauses were typically occupied by toy play, we speculated that attentional inertia may apply to play as well as TV viewing. This hypothesis received some support in a reanalysis of toy play during TV viewing in an earlier study (Field & Anderson, 1985). In that study, individual episodes of toy play were coded. Reanalysis indicated that these expisodes of toy play were lognormally distributed, with hazard functions similar to those for TV viewing. It should be pointed out, however, that the toy play episodes in that study were heavily influenced by the child’s monitoring of the TV audio; a play episode is likely to be terminated because the child detects something of interest on the TV. The present work therefore examines free play unconfounded by the presence of TV.

Modern theories of toy play provide little guidance concerning temporal structure and attentional engagement except that processes of stimulus satiation and habituation are frequently invoked, especially in discussions of infant play (e.g., Hutt, 1970; Ruff, 1984, 1986). If these processes are dominant, and rates of stimulus satiation did not vary greatly across toys, one might expect that the hazard function for episodes of toy play would generally increase rather than decrease; that is, the longer a child continuously plays with a given toy, the more likely it would become that play would terminate. Moreover, it would also be expected that play episodes would become progressively shorter during an extended play session. If these phenomena were observed, toy play would be temporally structured in a manner quite different from TV viewing (Alwitt et al., 1980; Anderson & Levin. 1976).

In summary, classic views of sustained attention (James, 1890; Hebb, 1949) are suggestive that similar processes might underlie sustained toy play and attention to TV. We hypothesize that both involve a chain of cognitive acts, each of which take time and during which the child is


relatively undistractible. Orientation is sustained across acts by attentional inertia. A lognormal distribution of play episode lengths as well as look lengths would be expected from such a view, since approximately lognormal distributions of event lengths result when events result from multiple subevents (e.g., a chain of play actions) prior to termination (Koch, 1966, 1969). A lognormal distribution is produced by multiples of a normal variate (Koch, 1966).

In contrast, however, some theories of toy play invoke stimulus satiation and habituation as paramount, and one theorist (Singer, 1980) argues that TV viewing and toy play are fundamentally different: Toy play is structured by internal fantasies whereas attention to TV is driven by stimulus change which repeatedly invokes orienting reflexes. These latter theories would suggest little similarity in the temporal structuring or attentional engagement of the two activities.

Study 1 of the present research quantitatively describes the temporal aspects of ten 5-year-old children’s free play with a large number of toys in two 90-min play sessions. Five year olds were observed because their visual attention to the TV has been extensively studied and because they readily engage in toy play. The use of long play sessions allows the coding of a relatively large number of play episodes for each child as well as allowing stimulus satiation, habituation, and fatigue processes to become manifest, if indeed they are characteristic. The relatively large number of different toys makes the results less determined by the specific prop- erties of particular toys (cf. Moyer & Gilmer, 1955). If play is sustained by processes similar to those which sustain looking at television, it is expected that play episodes are lognormally distributed, with a nonmonotonic but generally decreasing hazard function. Study 1 also provides analyses which determine whether stimulus satiation, attentional habituation, or fatigue processes are manifest. Such processes are not characteristic of TV viewing, and, we predict, are not characteristic of free toy play in 5-year-olds.

Study 2 uses the procedure of Anderson et al. (1987) to examine distractibility of thirty 5-year-olds during play. In particular, if the hazard function for play reflects attentional engagement, then the time course of distractibility should parallel that of the hazard function as it does for TV viewing.

In this research, episodes of toy play were operationally defined as continuous play activities. These included examining and/or handling a specific toy. A play episode was defined as beginning when visual orientation and/or handling was focused on a toy and ended when these behaviors were shifted to a different toy or a nonplay activity. It should be noted that toys were chosen to be easily incorporated into symbolic play by 5-year-olds. On the whole, an episode of free play by the present


definition may be considered to be roughly equivalent to an episode of attention as the term has been commonly used in prior play research (e.g., McCall, 1974).

STUDY 1

Method

Subjects. Ten 5-year-old (plus or minus one month) children equally divided by sex contributed data to the study. An additional three children’s data were lost due to technical problems (bad videotape recording) and one child did not play with the toys. This child appeared to be extremely shy and sat next to her mother without examining the toys. The children were recruited based on birth records.

Setting, material, and apparatus. Children were individually observed over two 1.5-h sessions in a comfortably furnished and carpeted room. In the room was a book case which contained a variety of toys suitable for free play. The toys were chosen because they were judged by the researchers to easily promote symbolic play and to be generally familiar to American 5year-olds. The toys were: an airplane, wooden and plastic blocks, chalk, two dolls, several groups of Fisher-Price “little people,” coloring book, crayons, Fisher-Price boat, farm, hospital, school, Sesame Street scene (with accessories), flag, helicopter, iron, four cars, two pup- pets, oven, clock, puzzles, Rainbowbrite set, Snoopy doll, two kinds of stacking toys, teddy bear, two telephones, tool box set, two transformer toys, and a workbench set. A Playdough set was used in Study 1 but not Study 2. A variety of magazines for the parent and refreshments for both the parent and the child were provided.

Children were videotaped using three cameras placed in the playroom, each equipped with a wide angle lens. Two microphones were also installed in the playroom. All the other equipment was located in an adjacent observation room. Pictures from each camera were sent to a videotape recorder via separate monitors as well as a video switcher.

Procedure. In each session children were videotaped individually with a parent in the same room. The child was asked to play alone while the parent was busy reading. The parent was instructed to avoid distracting the child from play with the toys.

Throughout the session the experimenter used the video switcher to select the camera that gave the best view of the child’s play. After each session the parent was paid five dollars. The interval between the two sessions was variable among children ranging from 2 days to a week.

Data scoring and reduction. The tape rating apparatus included a vid- eocassette deck (SONY BVU 200), a high resolution monitor, a time- code generator/reader, and a control box, all of which were monitored and controlled by a computer. The control box had buttons which allowed


the rater to play the tape forward or backward at different speeds as well as rate toy play.

For rating of play episodes each frame of each videotape was uniquely labeled with computer readable longitudinal and vertical interval SMPTE time code by means of a Datum time-code generator/reader. During rating, as the tape was played either backward or forward, the time-code reader provided the computer with the current videoframe number.

Each tape was rated in terms of the beginning and end of each play episode with a specific toy. Near the beginning of a play episode, the rater slowed the deck to l/5 speed and at the judged exact onset of play pushed the pause button to stop the tape and then pushed two buttons successively. These two buttons corresponded to a two-digit number assigned to each toy. The rater than released the pause button and played the tape forward until she found the offset of that episode and then pushed the pause button and the same two buttons again to record the offset of that episode. The computer recorded all the button pushes in terms of the number assigned to each button and the time code concurrent at the time the button was pushed. Since there are 30 video frames per second, the maximum temporal resolution of this procedure is approximately .033 sec. The primary data of this study then are the times of onset and offset of each toy play episode along with the identity of the toy.

Shifts of involvement between two or more small accessories from Fisher-Price Little-People-Set toys (such as Sesame Street, farm, school, etc.) were recorded as one episode as long as an observer judged the play as being essentially continuous. When the child played with more than one toy simultaneously, only play with the primary toy was rated.

To examine the reliability of rating, two raters independently rated one child’s 3 h of play. The percentage agreement between the two raters for every .1-s interval was 95 and the phi coefficient was .86.

Results. The children played with toys during most of the sessions (range from 77.8 to 92.8%). When they were not playing with toys, they were usually interacting with the parent, eating, engaging in play not focused on a toy, briefly napping, or engaged in diffuse activity. A 2 (sex) by 2 (session) multivariate analysis of variance revealed no significant effects for mean, median, lowest quartile, upper quartile, longest, or standard deviation of episode length. It was decided, therefore, to combine play episodes across the two sessions for subsequent analysis.

Table 1 provides basic descriptive analyses of play episode length for each subject. The number of play episodes ranged from 92 to 233, averaging 166.6. Median play episode lengths ranged from 10.0 to 34.4 s, and mean lengths ranged from 34.3 to 106.0 s with an unweighted average across subjects of 61.3 s. Standard deviations were large, ranging from 55.7 to 199.7, averaging 116.0. The large difference between mean and median episode lengths is indicative that they are not normally distributed;


TABLE 1 SUMMARY OF PLAY EPISODE LENGTHS IN STUDY 1

Girl No. 1 Girl No. 2 Girl No. 3 Girl No. 4 Girl No. 5

N Average Median SD Longest episode Lower quartile Upper quartile

N Average Median SD Longest episode Lower quartile Upper quartile

92 185 122 224 210 106.0 40.2 88.4 34.3 44.6 18.2 10.1 28.7 15.1 10.5

197.7 93.8 168.0 55.7 94.6 963.3 795.3 1128.2 344.2 776.4

4.7 4.3 10.7 4.6 4.2 112.1 31.7 87.5 35.2 37.5

Boy No. 1 Boy No. 2 Boy No. 3 Boy No. 4 Boy No. 5

130 181 233 120 169 81.6 58.3 41.5 59.2 58.7 34.4 23.0 13.2 13.7 17.2

113.7 92.9 90.4 139.5 113.8 707.3 804.2 845.7 1133.7 831.2

13.9 10.6 5.3 5.3 5.6 98.0 60.8 36.0 43.8 61.1

this inference was supported by large values of skewness and kurtosis for each subject.

In order to examine the distributions, the data from each child were separately plotted as frequency histograms. All plots looked quite similar: They were all positively skewed. Figure 1, based on 5-s intervals, provides a typical example from a single boy (boy 3 from Table 1). Figure 2 provides a relative frequency histogram for all 1666 play episodes from all 10 children. In general, while most play episodes were under 30 s in length, there were some quite long episodes. Across children, the longest single play episodes ranged from 344.2 to 1133.7 s, averaging 753.3 s.

To characterize the distribution underlying play episode lengths, each child’s data were individually fitted to the following plausible distributions: exponential, gamma, lognormal, and Weibull. Goodness of fit tests were applied using the Kolmogorov-Smirnov one-sample test. The results were straightforward; the best fit for each subject was provided by the lognormal distribution. For no subject was there a significant (p < .OS) departure from a lognormal fit whereas for each of the other distributions some or all the subjects showed significant departures. For the lognormal distribution, the measure of goodness of fit, DN, ranged from .041 to .093, averaging .066.

In order to maximize the amount of data per subject, the above analyses considered episode lengths aggregated across individual toys. The question is whether the results would also hold for play with particular toys. We approached this by examining the distributions of play episode lengths

TOY PLAY AND DISTRACTIBILITY

60-

50-

40-

5 8 3 30 -

E

20 -

10 -

0 --

51

0 30 60 90 120 150 180

Seconds FIG. 1. Frequency histogram (5-s intervals) of play episode lengths from a 5-year-old

boy.

for the three most frequently used toys for each subject. The IZS for these analyses ranged from 9 to 41. The power of the distribution analyses is thus weak. The analysis examined DN, the measure of goodness of fit by the Kolmogorov-Smirnov test, for the normal, lognormal, exponential, Weibull, and gamma distributions. The results were clear and supported the analyses on the data aggregated across toys: In 24 of 30 analyses, the best fit was provided by the lognormal distribution. Of the remainder, 3 were best fit by the Weibull distribution, 2 by the exponential distribution, and 1 by the gamma distribution. In each of these 6 exceptions, the lognormal fit was a close second.

Autocorrelation analyses were performed for each subject on data aggregated across toys up to lag 20 (i.e., the correlation of episode n with episode 12 + 1, II + 2, . . . , IZ + 20). There were no significant auto- correlations for any subject at lag 1 or 2, and the number of autocorre- lations significant at the .05 level did not exceed that expected by chance. There was thus no evidence of autocorrelation, that is, current episode

52

0.24 t

Seconds

FIG. 2. Relative frequency of play episode lengths (5-s intervals).

length did not predict future episode length for any subject. This result indicates that the individual play episode can reasonably be treated as an independent unit of analysis. It also indicates that play episode length is not likely determined by some underlying state of arousal or attention which goes much beyond the time course of the play episode itself.

The final descriptive analyses calculated for each child the conditional probability of play episodes terminating by time t + i, where i = 1 s, given that they had already survived to time t. This conditional probability, hazard, is routinely employed in studies of biological survival and in engineering studies of the failure of components in technological systems (Lee, 1980). A plot of hazard against survival time for play episodes provides an indication of the time course of vulnerability to termination. Because the data for each subject are reasonably fit by the lognormal distribution, it was expected that the empirical hazard function would be nonmonotonic, rising to a peak and then declining toward a zero asymptote as time becomes large (Watson & Wells, 1961).

An example hazard plot for one child is shown in Fig. 3 (the same

0.1

0.08

0.06

a m”

0.04

0.02

0

TOY PLAY AND DISTRACTIBILITY

0 5 10 15 20 25 30

Seconds FIG. 3. Hazard functions of play episode lengths from the same data used in Fig. 1.

The irregular function was obtained by smoothing over a 5-s window. The smooth function was based on the best fitting lognormal distribution for the data. Raw hazard values are shown as single data points.

boy’s data are shown in Fig. 1). Raw hazard values based on l-s intervals are presented as individual data points; the irregular line represents smoothed raw values based on a 5-s averaging window. The smooth line represents the best fitting theoretical hazard function derived from the lognormal distribution (cf. Lee, 1980). The plot for each of the 10 children showed results quite similar to those of Fig. 3; the hazard values peaked between 3 and 14 s and then declined thereafter. The average time to the peak was 7 s. A hazard plot based on the aggregated data of all 10 subjects is shown in Fig. 4.

As noted earlier, discussions of play have often invoked stimulus satiation or attentional habituation as explanatory factors. The following analyses asked whether such factors are likely operative in determining play episode lengths. A number of within-session variables were chosen as mapping onto these factors: elapsed time into the session, time since

0.1

0.08

0.06

%

B 0.04

0.02

0 I,~,,l,,,,l~~~~l~~~~l,~~11~~~~~

0 10 20 30 40 50 60

Seconds FIG. 4. Hazard functions of play episode lengths based on data from 10 children. The

functions were obtained by the same method as in the legend to Fig. 3.

the child last played with the particular toy, cumulative time the toy was already played with prior to the current episode, and toy preference, i.e., the percentage of total episodes the toy was chosen as an object of play. If fatigue or stimulus satiation factors are substantially operative during extended play, one might expect that play episode lengths would decrease over time and with cumulative play with a particular toy. If there is recovery, one might also expect that episode lengths would increase with time since the child last played with a particular toy. The toy preference variable was included to test the possibility that the attention-getting potential of a toy is correlated with its attention-holding potential.

Using an exploratory stepwise regression procedure, these four variables were regressed on the log transformed play episode lengths for each subject separately. The results of these 10 regression analyses were not impressive: Adjusted r square values ranged from zero to .077. One variable (toy preference) significantly predicted episode lengths for 3 of the 10 children, and another (time in the play session) was significant for


2 children. Toy preference predicted shorter play episode length and time into session predicted longer episodes. On the whole, however, it must be concluded that the four variables examined here have little predictive value. Additional exploratory analyses employing nonlinear models did no better. There was thus no evidence that fatigue or stimulus satiation variables were operative in this extended free play situation.

Finally, individual differences in play episode lengths were examined across the two sessions. The correlation of average episode length was modest, r(8) = .43, and nonsignificant for this small rz. Correlations for median, standard deviation, longest episode, and average upper quartile episode length were .43, .31, - .13, and 53, respectively. Only two measures, lowest quartile length and time to the peak of the hazard function, showed any promise as reliable measures of individual differences with correlations of .89, p < .OOl, and .70, p < .05, respectively. These two variables, in turn, are substantially correlated with each other, r = .70.

Discussion

Study 1 utilized observation and coding methodologies originally developed for the study of visual attention to television. This approach produced a number of observations new to the toy play research literature. First, the large number of extremely short play episodes have not pre- viously been reported. The failure to note this aspect of play is probably due to the common use of trial or time sampling methodologies which ignore onsets and offsets of play behavior. Rather, results are typically reported as percentage of play during a given unit of time or percentage of time samples in which play was observed (cf. Fenson, Sapper, & Min- ner, 1974; Krakow & Kopp, 1983). The observation of many short episodes parallels observations of looking at television, in which numerous short looks are typically observed (e.g., Anderson & Field, 1991). Also observed, on the other hand, were exceptionally long continuous play episodes; the longest lasted nearly 19 min. Such long play episodes are unlikely to be observed in typical studies in which total observation periods are on the order of 10 min. Again, exceptionally long episodes of visual attention are observed during TV viewing. In general, play episode lengths form a highly skewed lognormal distribution, as is found for looks at television.

The failure to find any autocorrelation between play episode lengths is suggestive that factors which produce sustained play operate primarily within rather than between play episodes. Such independence of play episodes is consistent with the idea that each episode contains within it one or more self-contained “stories” (cf. Eckler & Weininger, 1989). This interpretation is further supported by the failure to find any general effect on episode length of cumulative play with the particular toy, time into the play session, or time since the particular toy was last used. Even toy


preference in the sense of frequency with which a toy is chosen has little predictive value in determining play episode length. Common hypotheses of stimulus salience, satiation, or fatigue receive no support in these analyses if they are assumed to operate cumulatively or across play episodes.

For each subject the hazard function for play episodes was highly similar. The function was nonmonotonic such that play episodes peaked in vulnerability to termination from 3 to 14 s after a play episode began, declining drastically thereafter. After a minute of continuous play the episode was about a third as likely to terminate in any given second as it was during its peak vulnerability.

Thus far the findings are parallel to those for visual attention to television with the exception that the peak in vulnerability to termination of a look at TV is only about 1 or 2 s from its onset. Later in this paper, we provide a theoretical interpretation of the peak of the hazard function as reflecting the average length of the initial unit of action. Theoretically, then, during TV viewing children sample units of content which are of shorter duration than the units of action initially instantiated during play. Beyond the peak, play episodes and TV looks are empirically character- ized by a progressive decrease in the hazard of termination the longer they have been in progress. We hypothesize that the hazard function reflects attentional engagement, a hypothesis examined in Study 2.

Study 2 of the present research adopts the methodology employed by Anderson et al. (1987) to examine distractibility during free toy play. Based on the hazard results of Study 1, it is predicted that distractibility will be high early in a play episode, peak between 3 and 14 s, and then substantially decline thereafter. It is also predicted that reaction times of head turns to the distractor will inversely follow this pattern.

STUDY 2

Method

Subjects. The subjects were 15 male and 15 female 5-year-olds (plus or minus one month). The recruitment procedure was the same as in Study 1. Six of the initial group of 36 subjects were eliminated from the ex- periment: Five children’s data could not be used due to equipment mal- functions and one subject played too little to provide usable data.

Setting, material, and apparatus. The play setting was exactly the same as that of Study 1 except that a slide projection screen was attached to one wall. The 45.7 x 45.7-cm screen was located 1 m from the floor.

Under computer control, 180 slides were presented in blocks of interslide intervals of 5, 10, 15, 20, and 25 s in a random order without replacement following the end of the previous slide. The distractor slides consisted of a variety of scenes judged appealing to young children. The


onset of each slide was signaled by a .5 s “beep”; the slide remained on for 4 s and was replaced by a dark screen for the interslide interval.

Play was recorded in the same way as in Study 1 except that at the time of recording, SMPTE time-code was recorded on a second audio channel by means of a BTX time-code generator.

Procedure. Children were individually videotaped during the l-h play session. The parent was seated in a standard location and asked not to initiate interaction with her child. The child was told to play alone.

Rating of the video tapes for play episodes was exactly the same as in Study 1. In addition to identifying play episodes, head turns and reaction times of head turns to the distractor were obtained by a separate rating of the same tapes. Reaction time was defined as the number of elapsed videoframes between the onset of the distraction and the beginning of the head turn toward the slide times 33 ms. Rating of head turns and reaction times proceeded as follows: Near the onset of the beep, the rater slowed the deck to l/5 speed and at the onset of the beep which signaled the slide the rater pushed the pause button to halt the deck. The rater then pushed a designated button twice to market the onset of the beep. The onset of the head turn was rated in exactly the same way as the rating of the beep.

To obtain interrater reliability for head turn and reaction time measures, two raters rated one subject’s tape independently. Agreement for the headturns was 99%, phi (178) = .96, and the correlation of reaction time ratings was (r(24) = 83).

Results

Average lengths of play episodes ranged from 13.56 s to 49.52 sec. These are shorter than those obtained from Study 1, presumably due to distraction. The total amount of play ranged from 73.1 to 95.6% of the session.

The main analysis of Study 2 concerns changes in distractibility as a function of play episode length at the time of the distractor. Preliminary inspection of the data was accomplished by calculating a smoothed second by second plot of the probability of distraction for the first 30 s of play episodes (aggregated across all subjects). This plot revealed an inverted U-shaped curve which peaked at about 12 s. Unfortunately, a l-s interval is too small to use as a basis of statistical analysis since many subjects had no or only a few distracters presented during any given second. By the lognormal nature of the episode length distribution, moreover, fewer and fewer data are available in each successive same-sized interval.

We decided, therefore, to use logarithmically structured intervals (base 2). Base 2 intervals gave us relatively small units while minimizing missing data. The intervals for the analysis were bounded by 1, 2, 4, 8, 16, 32, 64, and 128 s, plus the interval consisting of all play episode times greater

0.5

0.4

2 3 s b J 0.3

Q4 0

g 0.2 3 &

PI

0.1

0

CHOI AND ANDERSON

0

Seconds

FIG. 5. Mean probability of distraction as a function of play episode length prior to the distractor.

than 128 s. The main analysis was a 2 (sex) by 9 (interval) multivariate analysis of variance using the interval variable as a repeated measure. The dependent variable was the proportion of headturns to the distractor. If a subject had only 1 or zero distracters presented during a given interval, the data for that subject in that interval were counted as missing and replaced by the mean for that cell with appropriate adjustment in the degrees of freedom. Missing data occurred in the first, second, third, eighth, and ninth intervals, with the following frequencies, in order: 1, 1, 1, 1, 4.

The analysis revealed only a main effect of interval, F(8, 21) = 15.51, p < .OOl. The mean proportions for each interval are plotted in Fig. 5. By inspection, the function rises to a peak in the fourth interval (8 to 16s), and substantially declines thereafter. This inspection is substantiated by the following significant polynomial trend effects: order 1, F(1, 28) = 25.99, order 2, F(1, 28) = 27.90, order 4, F( 1, 28) = 12.50.


Seconds

FIG. 6. Reaction time (ms) of head turns to the distractor as a function of play episode length prior to the distractor.

The second analysis examines the reaction times of headturns to the distractor as a function of play episode length at the time the distraction occurs. Statistical analysis was complicated by the fact that only about 25% of all distractor presentations resulted in head turns. Combined with the lognormal distribution of play episode length, relatively large intervals had to be employed in order to minimize missing data. As a consequence, four logarithmically structured (base 4) intervals were used: 0 to 4 s, 4 to 16 s, 16 to 64 s, and 64 s or greater. The multivariate analysis of variance used a 2 (sex) by 4 (interval) design with average reaction time of the headturn as the dependent variable. Data were considered missing if only 1 or zero headturns occurred for a subject in a given interval. There were 9 missing data, 5, 1, 1, and 2 in the four intervals, in order.

The analysis revealed only a significant interval effect, F(3, 26) = 3.49, p < .05. Average reaction times for the intervals were 1068, 970, 1007, and 1154 msec, respectively, as plotted in Fig. 6. The U-shaped trend in


reaction times was supported by a significant quadratic trend component F(1, 28) = 8.17.

DISCUSSION

The goal of this research was to determine whether there are temporal parallels between looking at television and free play with toys. Using methodologies originally developed for research on television viewing behavior, the present work departs from prior research on free play behavior in two major ways: 1) The setting and time frame is more typical of those in which free play is likely to occur at home; that is, a wide selection of toys were available, and the amount of time to play was relatively unrestricted. 2) We examined individual episodes of sustained play, rather than collapsing data by means of trial-based or time-sampling procedures.

The salient findings of Study 1 were: 1) Episode lengths average about a minute in length but are lognormally distributed so that there is a preponderance of short episodes (the overall median is 16.6 s). The longest episodes, nevertheless, last more than 10 min. 2) There is no autocorrelation between episode lengths. 3) Prior play with a toy, cumulative play, or time since the toy was last used did not predict episode length. 4) The hazard function for toy play episodes peaks from 3 to 14 s (averaging 7 s) and declines thereafter.

Study 2 found that distractibility from episodes of play follows a time course roughly parallel to that of the hazard function: Distractibility increased to a peak at about 12 s after play episodes had begun, and steadily declined thereafter. Reaction times of headturns toward the distractor inversely approximated this time course.

The quantitative parallels between toy play and looks at TV are striking. In both cases distributions are skewed such that short episodes predom- inate, and in both cases distributions for individual subjects are well described as lognormal. Also, in both cases, the hazard function, following an early peak, steadily declines. In both play and TV viewing, moreover, the hazard function predicts the time course of distractibility, and, if a child is distracted, the hazard function predicts the reaction time of the head turn toward the distractor. In quantitative terms, the chief difference between episodes of looks at TV and episodes of toy play is that the hazard function for TV looks has a peak from about 1 to 2 s in contrast to the peak for play at from 3 to 14 s. This early peak in TV viewing provides relatively more very short looks at TV, producing a mean look length of about 13 s in 5-year-olds viewing Sesame Street (Anderson, Larch, Smith, Bradford, & Levin, 1981). Beyond the peak, however, the hazard functions for looks at TV and toy play are very similar.

Although the productive activity of toy play and the receptive activity of TV viewing are clearly not the same behaviors, the present findings


support our hypothesis that they have important similarities in underlying processes. Invoking ideas from James (1890) and Hebb (1949), we suggested that this similarity resides partly in the nature of cognitive processing in both activities and in the presence of attentional inertia. We will now specify a model which incorporates these ideas, discuss the results in terms of the model, and then consider some alternatives.

A Model of Sustained Toy Play and Looking at Television

Koch (1966, 1969), in discussing the ubiquity of the lognormal distribution in biology, noted that lognormal distributions of event lengths imply that the event goes through multiple phases. If both toy play and looking at TV are schematically structured, then the phases might be elements of the schemas or the schemas themselves. Each activity, therefore, might be viewed as a chain of schematic elements. Based on James’ (1890) notion of passive intellectual attention, as long as a schematic element is instantiated, the child has a focus of attention and therefore a strong tendency to sustain the activity and resist distraction. When an element has been completely produced or processed, however, the activity is vulnerable to termination because there is, at least momentarily, no attentional focus. If orientation to the toy (or TV) is maintained across this interval, however, a new element can be instantiated and the activity can continue. The question arises as to what sustains orientation across the intervals between schema elements. We argue that there is a generalized tendency to sustain orientation to the medium of production (the toy) or reception (the TV) and that this tendency deepens as a function of time that orientation has already been sustained; it is this tendency that we call attentional inertia.

Consider the following model which explicitly incorporates these ideas: 1) When initiating the activity, the child selects and instantiates a schematic element from an available pool of elements with lengths normally distributed. In the case of toy play, this pool is the possible set of actions with the toy available to the child at that time (constrained by the per- ceived affordances offered by the toy, social constraints, and the constraints of any instantiated schema, e.g., certain actions would not fit particular ongoing play “stories”). In TV viewing, the pool is a set of comprehension acts constrained by the television stimulus itself as well as by the current comprehension schema. 2) As long as the element is instantiated, the child has a constant and low probability of distraction, d, during each unit of time. This assumption of the model is consistent with James’ notion of passive intellectual attention. 3) When an element is completed, the child may be distracted or simply terminate the activity with probability pr, where t is the time since the activity began. In general, po, the initial value of pt , is much greater than d. 4) P, changes over each unit of time such that p1 = ipI-, where 0 d i d 1.0; P, has a lower limit


equal to d.’ Insofar as p. is less than 1.0, there is a generalized tendency to sustain orientation to the medium right from the beginning. The degree to which i is less than 1.0 is the degree to which this tendency becomes strengthened over time (attentional inertia).

Simulations of the model readily produce data nearly identical to those of Study 1. As an example, the data of boy 3 were closely approximated by the following simulation parameters: mean schema element length of 4.5 s, standard deviation of schema element length equal to 2.5 s, d equal to .005, i equal to .96, and p. equal to .3. Each unit of time in the simulation was set equal to 1 .O s. A simulation of 300 play episodes yielded a mean episode length of 42.2 s, a median length of 13.2 s, and a standard deviation of 83.3 s. The data were distributed lognormally (DN was .061, p = .219). The hazard plot was quite similar to that in Fig. 3.

Simulations also produced data which plausibly matched TV viewing. For example, a simulation incorporating boy 3’s simulation parameters, but with a schema element length of 2.0 s (reflecting the peak of the hazard function in the television analyses) and standard deviation of 1.0 s, produced look lengths averaging 15.8 s, with a median of 5.5 s and standard deviation of 47.3 s. Again, the data were reasonably described as lognormal (DN = .048, p = .499). These simulated data are quite consistent with analyses we have conducted of 5-year-olds’ look lengths while watching Sesame Street with toys available.

Average theoretical schema element length tends to be reflected as the peak of the hazard curve (i.e., there is a high probability of termination at the completion of the first schema element because pt has not yet been driven to low levels by attentional inertia). In terms of the theory, then, TV viewing is accomplished by processing a succession of brief (approximately 1 to 2 s) units of action, dialogue, and settings, with attentional inertia making it progressively more likely that the next unit will be processed. Toy play, on the other hand, consists of a chain of actions which are generally of longer duration (averaging 3 to 14 s) than those units processed during TV viewing. Like TV viewing, however, attentional inertia progressively strengthens the links between play actions.

A chain of normally distributed action lengths are sufficient to produce lognormally distributed data without attentional inertia as shown by sim-

’ The hazard function generated by the lognormal distribution requires that, as time grows large, hazard approaches zero. This is implausible in both toy play and TV viewing and has been avoided in the present model. It is expected, therefore, that the model will produce data which only approximates the lognormal distribution. As a practical matter, the model generates data which are fit by the lognormal distribution about as well as the actual data. Koch (1969) notes that there are closely related distributions, produced by very similar underlying mechanisms, which are well fit by the lognormal distribution. An example is the inverse Gaussian distribution which does not asymptote as zero hazard (Chhikara & Folks, 1977).


ulations where i was set equal to 1.0. However, no combination of parameters produced data that looked either like toy play or TV viewing without attentional inertia (standard deviations were smaller than the mean whereas the actual data always have standard deviations several times larger than the mean). In general, simulations with the model showed that attentional inertia (i < 1.0) was necessary to obtain results similar to those for either toy play or TV viewing.

Our theory suggests that, during toy play or during TV viewing, there are two kinds of attentional engagement: schematic engagement and engagement with the medium itself. The idea of schematic engagement is consistent with other research and theory, both old and more recent. For example, decreased distractibility while processing auditory discourse has been associated with increased cognitive processing devoted to the primary listening task (Barr & Kapadnis, 1986) as has increased reaction times to a secondary task during reading (e.g., Britton. Piha, Davis, & Wehausen, 1978). James (1890) commented on this phenomenon: “When absorbed in intellectual attention we may become so inattentive to outer things as to be ‘absent-minded’ . . .” (pp. 418-419). Cowan (1988) argues that this ability to shut out distractions under some circumstances reflects a fundamental property of the human information processing system: “ . . . activation of memory categories corresponding to relevant stimuli or concepts also improves the subject’s resistance to the involuntary cap- turing of attention by irrelevant stimuli” (p. 172).

The idea that sustained orientation can allow generalized engagement with the medium, attentional inertia, is implicit in both James (1890) and Hebb (1949). The present theory makes this idea explicit and asserts that there is a time course over which such cognitive engagement deepens. Attentional inertia provides the glue by which involvement with the medium across successive schematic elements or even full schemas can be sustained. We do not know the circumstances under which attentional inertia is necessarily produced or not produced, but, following James (1890), we hypothesize that they involve moderately complex but comprehensible and enjoyable situations which afford the ready application of somewhat open-ended production and comprehension schemas. At- tentional inertia allows the child to construct more extensive (and possibly more elaborate) play episodes, and allows the child to sustain attention to a source of discourse even across changing content or content which may be difficult to comprehend.

Individual Differences

The present findings and theoretical hypotheses may have implications for considerations of individual differences in sustained attention. In Study 1, the most consistent individual differences were lowest quartile length and peak of the hazard function. According to the present model, these


differences result primarily from the average length of the initial instantiated schematic element. Thus, individual differences in sustained toy play may result from the average duration of the schematic elements guiding play.

The model may possibly illuminate more profound individual differences. Routh and Schroeder (1976) observed that children diagnosed with attention deficit disorder switched between toys more frequently than typical children; presumably, this finding indicates that there was less sustained play in the disordered children. In another parallel between toy play and TV viewing, Larch, Milich, Welsh, Yocum, Bluhm, and Klein (1987) reported that boys with attention deficit disorder have substantially shorter looks at television than do typical children. If episodes of toy play and TV viewing consist of a succession of cognitive acts deepened by attentional inertia, then attention deficit disorder could involve shortened schemas or reduced attentional inertia, or both. The analyses and experimental procedures used here may prove useful in future examinations of this disorder.

Limitations of the Theory

The theory and model presented here are not intended to capture the full complexity of toy play and TV viewing; rather, the theory is meant to broadly account for the temporal structure of these behaviors. In particular, the theory, as presently formulated, does not take a position as to whether the schematic organization characteristic of these behaviors is imposed in a top-down fashion or is emergent through the child’s cognitive interactions with the toy or TV program. In either case, it might be expected that the binding between units of action or comprehension is stronger if the units fall within the same schematic structure rather than between structures. Also, the theory does not at this time deal with the attention-getting features of toys or TV programs, or specifically identify events which terminate periods of play or looking at TV (other than distracters). Nothing in the theory as proposed thus far excludes such extensions. Finally, as of this writing, no effort has been made to make the model mathematically analyzable or to provide formal parameter es- timation procedures. The model appears to be tractable, however, and should be mathematically analyzable.

Alternative Interpretations

Although our theory is sufficient to account for the present data, other interpretations are possible and cannot be completely excluded by the present research. The most obvious alternative, which can be excluded, is that each play episode (or look at TV) is sustained thorough each successive interval of time according to a constant probability which is determined at the beginning of the play episode (or look). This probability,


which could vary between episodes, might be determined by the attrac- tiveness of the toy (or TV scene) or might be determined by some internal state of the child. Once the episode is in progress, according to this alternative, the probability of an episode terminating remains constant through each interval of time. The child’s engagement during the episode, furthermore, is inversely related to this constant probability of termination. Long episodes, then, generally have high engagement and constant but low hazards, and short episodes have low engagement with constant but high hazards. Aggregating the multiple exponential distributions produced by these multiple constant hazards has been shown to produce a monotonically decreasing hazard function even though the underlying process for each episode does not change over time (e.g., Schmittlein & Morrison, 1981). Mendelson (1983) made essentially the same argument in suggesting that attentional inertia during TV viewing might be a form of averaging artifact.

This alternative can safely be excluded insofar as both toy play episodes and looks at TV have nonmonotonic hazard functions. Proschan (1963) proved that a nonmonotonic hazard function cannot be produced by aggregating exponential distributions. The underlying processes which sustain episodes must change over the time course of episodes.2

Another alternative explanation would grant that episodes are organized schematically, but assume that the schema lengths themselves are lognormally distributed. According to this view, play or looking is sustained as long as the schema remains instantiated and the distribution of play episode or look lengths simply reflects schema lengths. Distractibility, presumably, would be inversely related to schema length.

This alternative cannot be excluded as an explanation of the toy play data, but it raises the question of how play schema lengths or television content unit lengths are in fact distributed. There is no published information concerning this issue, so the alternative merely restates the finding of lognormally distributed play episodes, begging the question as to why schema lengths would be lognormally distributed. The alternative also provides no explanation as to why engagement (as measured by distractibility and reaction time of distraction) should vary inversely with schema length. Additionally, in TV viewing, lengths of looks which are in progress prior to major content boundaries positively predict lengths of those same

’ An anonymous reviewer suggested a more extreme alternative: Suppose each episode starts with a hazard near zero and that each hazard increases linearly with time the episode is in progress (i.e., a fatigue or habituation process), and that the slope of this increase

varies widely from episode to episode. Proschan’s (1963) proof indicates that a nonmonotonic hazard function is possible given such a model. Simulations of a model based on this notion were unable to produce data resembling those in the present research or an approximation of a lognormal distribution, although the model was able to produce nonmonotonic hazard

functions (albeit none that looked like those observed in the present data).


looks after the content boundaries (Anderson & Larch, 1983). Compre- hension schemas presumably change when the content changes, so that this alternative would predict no relationship of look lengths across content boundaries. While this alternative is a weak explanation of the play data, it could not account for TV viewing.

A further alternative would grant that toy play is a chain of schematic units, but would suggest that as each unit is added to the chain, the new unit is longer than that preceding it. Since the boundaries between the units grow farther apart, the vulnerability to distraction at the unit boundaries would decrease. Longer units as play is sustained might result from units becoming more complex in nature (cf. Eckler & Weininger, 1989) or because the child perceives more affordances for play offered by the toy. While again this theory would not account for the predictability of looks at TV across content boundaries, it could in principle account for the play data.

Regardless of whether the present theory, as instantiated in the model described above, is ultimately shown to be valid, the present results show that deeply engaged play is related to play episode length. The research adds to the remarkable parallels between play episode lengths and lengths of looks at television: both increase with age; both are reduced in hy- peractive children; both are lognormally distributed with similar hazard functions; both have distractibility functions which parallel the hazard functions; for both, when the child is distracted, the reaction times of head turns inversely parallel the hazard function.

Some (e.g., Singer, 1980) have argued that television viewing is a fundamentally different kind of behavior than cognitively productive behaviors such as free play. While it is clear that play is different from TV viewing, the present research suggests that there are also fundamental similarities.

Further Considerations

We suggest that the phenomenon of absorbed attention is a topic worthy of further intensive investigation. In regards to toy play, it is of interest whether play becomes more complex the longer play episodes are sustained, and whether attention becomes more focused. The techniques of Eckler and Weininger (1989) or of Ruff and Lawson (1990) may be applicable to these questions. Adaptations of the present methodology and theory could be applied to other important schematically structured leisure activities such as reading. Such research would require the iden- tification of the beginnings and endings of periods of continuous activity. In the case of reading, a pattern recognition computer program might be used to identify patterns of reading-like saccades in a situation where the reader has visual alternatives to continuous reading.

It is likely that the present theory and findings do not apply to situations


in which stimuli and behaviors are static or repetitious. Despite extensive work on vigilance in adults, for example, there have been no reports of phenomena analogous to attentional inertia. Vigilance tasks are externally imposed and are usually extremely repetitive with none of the narrative structure and stimulus change characteristic of TV viewing or toy play. Additional research, therefore, might attempt to determine the boundary conditions under which attentional inertia is and is not present. Clearly, converging operations are required before we can understand the conditions under which attentional inertia exists.

We suggest, nevertheless, that attentional inertia may be a general phenomenon of daily cognition. For example, we have the experience of finding it difficult getting absorbed in a reading or writing task, progressing in fits and starts, but often, once we have gotten going, we are able to progress for long periods without distraction. This subjective experience leads us to agree with Hebb (1949): “At a theoretical level, it seems . . . that there can be no explanation of learning and problem-solving in any mammal without reference to the persisting central neural influence that sustains activity in one particular direction” (p. 141). Understanding this form of persistence may prove to be of considerable utility.

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RECEIVED: May 1, 1989; REVISED December 14, 1990