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SupervisingChildrenDuringParentalDistractions.pdf

Supervising Children During Parental Distractions

Richard E. Boles,1 PHD and Michael C. Roberts,2 PHD 1Cincinnati Children’s Hospital Medical Center, Cincinnati and 2Clinical Child Psychology Program,

University of Kansas

Objective To examine the effects of parenting distractions on supervising behaviors in relation to child risky

behaviors. Methods Forty preschool-aged children and their parents were randomly assigned to occupy a

simulated home living room for 45 min with the parent involved in either (a) no planned distraction, (b) a

telephone call distraction, (c) a TV show distraction, or (d) a computer assignment distraction. Parent and

child behaviors were recorded and coded. Results Parent supervising behaviors were significantly

intercorrelated but revealed no relation to risky child behavior. Children showed higher risky behavior during

parental distractions and steadily over time when parent distractions occurred. Additionally, younger children

were more likely to engage in risky behavior when compared to older children. Conclusions Parents

showed significant reductions in their ability to supervise children during distractions, limiting the ability to

provide education or to take immediate action necessary to prevent or minimize possible injuries.

Key words childhood injuries; observation; parent distractions; supervision.

Unintentional injuries are the most significant health

challenge for children and adolescents from age 1 to 19

years with home injuries a major proportion of the

problem (Guyer et al., 1999; National Center for Injury

Prevention and Control, 2001, 2002). For preschool

children, home injuries likely result from child, parent,

and environmental variables interacting within family and

cultural contexts. The extent to which these variables

contribute to the occurrence of an injury, however, is still

poorly understood. (National Center for Injury and

Prevention and Control, 2002). One limitation to a

multi-factorial understanding has been the limited empiri-

cal knowledge on child supervision, an often cited parent-

related factor in injuries among young children (Cataldo,

Finney, Richman, & Riley, 1992; Gärling & Gärling, 1993;

Morrongiello & Dawber, 1998). Only recently have

researchers begun to explore supervision in relation to

pediatric injuries, providing conceptual models, assess-

ment instruments, and methodological guidance for

empirical investigations (Morrongiello, Corbett, McCourt,

& Johnston, 2006; Morrongiello & House, 2004; Saluja

et al., 2004).

The Relationship of Supervision to Child Injury

Currently a dearth of knowledge exists regarding the actual

practices of caregivers during interactions with children in

the home. Emerging evidence has shown that closer

supervision provides a protective role and is linked with

fewer child injuries (Morrongiello, Ondejko, & Littlejohn,

2004). Additionally, parents increase their supervision

with children who are reported as risk takers, sensation

seeking, and impulsive (Morrongiello et al., 2006).

However, behavioral observations of parents supervising

children on playgrounds have shown only limited relation

to injury risk (Morrongiello & House, 2004), and much

less is known about the relation of observed supervising

behaviors within a home environment and child risk

behaviors. For example, in a study conducted by

researchers at Safe Kids from 2000–2001, it was shown

that 88% of drowning victims were being supervised by

caregivers (Cody, Quraishi, Dastur, & Mickalide, 2004).

Among parents who supervise children during swimming,

distractions were reported as common occurrences

All correspondence concerning this article should be addressed to: Richard E. Boles, PhD, Cincinnati Children’s Hospital Medical Center, Division of Behavioral Medicine and Clinical Psychology, MLC 3015, 3333 Burnet Avenue, Cincinnati, OH 45229-3039, USA. E-mail: [email protected]

Journal of Pediatric Psychology 33(8) pp. 833–841, 2008 doi:10.1093/jpepsy/jsn021

Advance Access publication March 10, 2008 Journal of Pediatric Psychology vol. 33 no. 8 � The Author 2008. Published by Oxford University Press on behalf of the Society of Pediatric Psychology.

All rights reserved. For permissions, please e-mail: [email protected]

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[e.g., talking to someone (38%), reading (18%), eating

(17%), and using the phone (11%)]. Supervision investiga-

tions have not systematically explored how parents modify

their supervision practices during typical home distrac-

tions. This is a key factor when considering most parents

are at home when their children are becoming injured

(Shannon, Brashaw, Lewis, & Feldman, 1992).

Saluja et al. (2004) provided a conceptual model of

parent supervising behaviors in which a hierarchy of

supervision strategies defines supervision in a way that

can be systematically measured for a relation to injury

risk. Three dimensions were described that included

(a) attention, (b) proximity, and (c) continuity. Attention

encompassed the level of engagement between the super-

visor and child in addition to visual and auditory

components, ranging from directly visually focused to no

visual contact with the child. Proximity indicated the

distance between the supervisor and child, ranging from

touching ability to out of reach and beyond reach at large

distances. Continuity described the extent to which the

supervisor demonstrates the first two dimensions in a

continuous, intermittent, or nonexistent (absent)

approach. The present study attempts to test the critical

elements of the Saluja et al. (2004) model of parent

supervision by measuring multiple observable behavioral

components: (a) attention (i.e., visual attention based on

ability to make eye contact with the child), (b) engagement

(i.e., verbal and/or physical interactions between the child

and parent, and (c) proximity (i.e., how close the parent is

to the child).

Primary Study Goals and Hypotheses

The primary purpose of the present study is to identify

parenting behaviors associated with risky child behaviors

within a simulated home setting, with consideration of the

influence of parent distractions in order to understand

potential changes in parenting behaviors when their

attention shifts away from the child. Our goal was to

address an existing gap in the literature regarding the link

among parent supervision and child behaviors based on

observations within a home setting. Previous studies

utilizing observational methodologies to study injuries

helped shape the present approach (Cataldo et al.,

1992; Morrongiello & Dawber, 1998; Morrongiello &

House, 2004). Due to the potential for participants to

change their behavior after being asked to participate

in an observational study (Haynes & Horn, 1982), we

explored the effects of masking the study aims for half

of the sample. Although the literature is not entirely

consistent, most rigorous studies have shown limited

reactivity effects (Jacob, Tennenbaum, Seilhamer, Bargiel,

& Sharon, 1994).

We hypothesized that parenting behaviors would

change during the distraction periods. Specifically, we

expected engagement and eye contact to decrease between

parents and children during the parent distractions while

proximity would increase during distractions. Additionally,

we hypothesized an inverse association between risky child

behaviors and parental supervision behaviors. Finally, we

expected minimal differences of reactivity between

informed and uninformed groups.

Methods Participants

Participants were 40 parent–child dyads aged 2 to 5 years

(M ¼ 4.4, SD ¼ 1.1). Parents were primarily Caucasian

(93%) and well educated with all having attended some

college and 62.5% had obtained a bachelors degree or

higher. Participating parents were most often the mother

(85%) with an average age of 32.6 years (SD ¼ 5.7).

A power analysis determined that 40 participants were

adequate to detect for possible effect sizes.

Procedure

Parents and their children were recruited from a mid-

western preschool population. Criteria for study eligibility

included that the child: (a) had to be aged 2–5 years,

(b) spoke English as a first language, (c) did not have a

parent reported developmental disability, and (d) had

not participated in an injury related study within the

past 12 months. Parents and children visited a University

clinic and were provided a project description and signed a

consent form (as approved by the Institutional Review

Board). The researcher also collected verbal assent from

each child. A random numbers table was generated by

a computer program to develop four equal groups of 10

(i.e., four distractions) across two conditions (i.e., informed

or misinformed). Half of the sample was randomly assigned

to be told the study was about child supervision and

informed that they would be videotaped while in the room.

The remaining random sample half was informed the study

was about child patience and they were not informed

about being videotaped until after the observation.

The parent and child were then informed that they

were to occupy another clinic room for 45 min. The

parents were read a brief description of what to expect

while in the room, depending on the condition they were

randomly assigned. Specifically, parents in the Phone

Distraction group were told that a cordless phone was

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placed in the room (out of child reach) and would ring

sometime during the time they are in the room. They were

told to answer the phone to answer a series of questions by

the researcher on child patience (e.g., ‘‘describe your

experiences going to grocery store with your child’’) timed

to last �15 min. Parents in the TV Distraction group were

told an electronic timer would sound after an unspecified

period (i.e., 15 min) of time, which indicated they needed

to turn on the TV and watch a VCR tape of a typical TV

program (i.e., a 15 min segment on meal preparations). In

an effort to increase parent adherence toward watching the

TV program, parents were instructed to pay close attention

to the program in order to answer follow-up questions.

Parents in the Computer Distraction group waited until an

electronic timer alarm sounded after 15 min, which

indicated they needed to turn on the computer that

revealed a program already up on the screen. The computer

program was created by the author using PowerPoint�.

Specifically, an automated presentation was provided to

parents on the subject of child patience. The slide show

was initiated by parents who pushed a marked button. The

slides were timed to advance automatically, creating a

15 min presentation. Parents in the Computer Distraction

group were also told to pay close attention to the computer

program in order to answer follow-up questions by the

researcher. After parents in each distracted condition

completed the distraction, they remained in the room for a

final 15 min. Finally, parents in the condition with no

planned distractions were told to remain in the room for

45 min, in which follow-up questions would be adminis-

tered. At the end, the parents and their children entered

a separate room and completed the structured interview on

room hazards and the demographic questionnaire.

Debriefing

Because this experimental method involved an alteration of

informed consent, a debriefing period occurred directly

after all study protocols had occurred for the entire sample.

The actual purpose of obtaining information on super-

vision behaviors was explained to the uninformed sample

half with clarifications of why it was necessary to refrain

from revealing the study purpose until after the observa-

tions and information were collected. Participants in the

previously uninformed group were also informed that they

were videotaped and provided an explanation that it was

necessary to reliably code each of the parent and child

behaviors using a recording device. They were reminded

of their right to withdraw from the study and remove

their data from the project at this time without penalty

before completing a second informed consent form.

No participants in the uninformed group withdrew from

the study after debriefing. Parents in the informed group

were also debriefed on the study aims immediately after

participation. Parents were given $25 for their time

participating.

Materials

Simulated Home Environment

Observations took place in a university clinic room

designed to replicate a typical home environment. The

room contained furniture (i.e., a couch, end tables, a floor

lamp, plants, padded chairs, a desktop computer,

telephone, TV, and VCR) in addition to objects classified

into two groups: (a) low injury risk (e.g., a pillow) and

(b) high injury risk (e.g., a knife, medicine, a step ladder,

5-gallon bucket, a lighter, and a spray cleaner).1 The

furniture was arranged on the perimeter of the room walls,

with the risky objects were placed in varied locations (e.g.,

a pill container was on an end table, the knife was on a

table, and the lighter was in the seat portion of a padded

chair at the side edge, similar to where a lighter might be if

one had fallen out of a pocket. Objects were classified into

group 1 or 2 based on a sorting task by two experts on

child injury with 100% agreement. The selected risky

objects were based on developmentally related injuries to

this particular age group (National Center for Injury and

Prevention and Control, 2001, 2002).

Measures

Demographic Form

Demographic information was collected from parents via a

self-report questionnaire. Information collected included:

(a) parent education, (b) occupation, (c) housing condi-

tion, (d) child health and past injury history, and

(e) amount of time spent on a computer, watching TV,

and talking on the phone.

Structured Interview on Room Hazards

A brief structured interview on parent recall of conditions

was conducted in order to assess the parent’s level of

awareness of risky and nonrisky items in the simulated

1Each risky object had been modified to be relatively safe and

many had been utilized in our prior studies. The knife was a folding

type with a dulled blade, the medicine was candy placed in a 7-day

medicine organizer without safety locking lids, the bucket did not

contain any water and had a large warning label attached to the

side, the lighter (which did not have a safety feature) was drained of

the fluid and the flint was removed to prevent spark, the spray

cleaner was water mixed with food coloring, and a step stool

utilized one step and multiple safety labels were attached to its

surface.

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home room, the interaction their child had with such

items, and the potential level of risk for injury for their

child if they interacted with a risky item. Specifically,

parents were asked to consider how likely they thought an

injury could occur when their child interacted with an

identified home hazard by providing a rating from 1 to 5,

where 1 indicated that a parent did not think any injury

would likely happen and 5 meant an injury would

absolutely happen.

Design

The study utilized comparisons of multi-phase conditions,

in which the 45 min period of time in the room is divided

into three phases: (a) no planned distractions, (b) a plan-

ned distraction period, and (c) no planned distractions.

Each phase lasted 15 min that was monitored by the

researcher or parent using digital stopwatches. Ten parent–

child dyads were randomly assigned to one of four

conditions: (a) Phone Distraction, (b) TV Distraction,

(c) Computer Distraction, or (d) No Distraction.

Data Analysis

Observational Data Processing

Observational data were obtained by recording 45 min

segments of parent–child interaction on to VHS tapes,

using a video camera permanently mounted in the upper

corner of the observation room. A VCR was affixed to a

shelf beneath the camera and hidden by a plant. The VHS

tape was later converted to DVD format in order to be

analyzed by observational software. The observational

software used to code and analyze behavior was The

Observer� and The Observer Video Pro� (Noldus, version

5.0.25, The Netherlands).

Coding Scheme

In order to reliably code behavioral data, a behavioral

coding scheme was developed based on the model

proposed by Saluja et al. (2004), although not all

components of the model could be examined given that

the parent and child dyads remained in the room together

and in relatively close proximity (i.e., auditory attention

and far proximity beyond a single room were not coded).

Three parent behaviors (proximity, visual attention, and

engagement) and one child behavior (risky behavior) were

coded as the primary behaviors for analyses using the

following operational definitions. Close Proximity was

coded when the parent was touching or within an arm’s

reach of their child; Close Visual Attention was coded when

a parent positioned her/his head in a direct line of vision or

within peripheral view of their child; Engagement was

coded during activity in which the parent and child are

both simultaneously involved. Involvement may have been

verbal (e.g., communicating with each other), nonverbal

(e.g., actively listening to story telling or to a direction with

parental eye contact), and active (e.g., following a request

to retrieve an item). Examples include: a parent reading a

book to their child who has occasional eye contact with the

book or parent, the parent and child throwing a ball back

and forth, or sitting together talking. Risk Taking behavior

was coded when the child physically touched a predeter-

mined risky object.

Four conceptually similar behaviors were also coded

during each interval. For example, Far Proximity was coded

when a child was beyond the reach of parent; No Visual

Attention was coded when a parent was turned away from a

child; No Engagement was coded during any activity

performed by the parent, in which the child has no

involvement or interaction. This behavior was defined as

when a parent provides no verbal and physical attention

during an activity (e.g., visual focal or peripheral atten-

tion is withheld and no interaction is made with the

child). Examples include the parent watching the TV but

the child is NOT watching the TV and the parent is not

talking to the child (even though the child may still be in

the view of the parent). Finally, No Risk Taking was coded

when no interaction with hazards occurred during the

interval. Preliminary data analyses of the four primary

study variables revealed significant negatively correlated

findings with their opposite behavior (e.g., Close Proximity

and Far Proximity, r ¼ �.81, p ¼ .005). Therefore, only

three supervision behavioral components representing

potentially safer parenting behaviors and one child

behavior were analyzed for this study (e.g., Close

Proximity, Close Visual Attention, Engagement, and

Risk Taking).

Behaviors were coded as events during 15 s intervals.

That is, regardless of duration, a behavior was counted

once and only once if it occurred during each 15 s interval.

The available software enabled coders to rewind, pause,

and fast forward observational data during coding,

maximizing adequate assessment of all behaviors.

Reliability Training

All reported data were coded by the primary coder after

training and an independent coder established interrater

reliability. A Cohen’s Kappa coefficient was calculated in

order to evaluate the level of performance using randomly

selected data. A minimum of .75 kappa values, suggesting

strong agreement above chance, was used to indicate

reliable coding has occurred (Fleiss, 1981). After being

trained to reliability four randomly selected 45-min

observations (representing 10% of the total data) were

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selected for coding by an individual who had limited

knowledge of research objectives. Twelve Kappa coeffi-

cients (three parenting behaviors across four participants)

for supervising behaviors showed an average value of .88

(SD ¼ 0.09), ranging from .72 to 1.00. A separate analysis

of agreement for Risk Taking behavior for all 12

observations indicated a 100% agreement for all observa-

tions, suggesting satisfactory interrater reliability.

Preliminary Data Screening

Examinations of standardized values for all variables

revealed five values greater than �3.29 (p < .001, two-

tailed test). Affected variables included Risk Taking (one

score from each phase for a total of 3, but not from the

same individual), one score on Engagement during the first

phase, and one score on Close Visual Attention from the

postdistraction phase. These extreme values were across

participants, indicating a univariate approach could be

utilized to reduce the impact of such scores on other data.

Specifically, these raw scores were assigned a value of 1

unit larger or smaller, depending on the direction of the

outlier, than the next most extreme score in the

distribution.

Results

Means and standard deviations for parent supervising

behaviors and child risk taking behaviors across time

periods and between distraction groups are displayed in

Table I. The results for parent and child behaviors are

presented separately in which four one-way repeated-

measures analysis of variance (ANOVA) were conducted

for each observed parent and child behavior (see Fig. 1, in

which the y-axis represents the average number of times

the target behavior occurred during intervals across

participants).

Risky Child Behaviors

Overall, a marginally significant omnibus interaction effect

for child Risk Taking across distraction groups was

observed, F(6, 72) ¼ 1.9, p ¼ .09 (partial eta squared ¼ .14;

see Fig. 1A). As a result, no further follow-up tests were

conducted.

Parent Supervising Behaviors

When examining parent behaviors (shown in Fig. 1B),

Close Visual Attention observations showed a significant

interaction effect by Group, F(6, 72) ¼ 6.43, p < .001,

(partial eta squared ¼ .35). Specifically, during the

Computer Distraction phase, a significant reduction

(p < .001) in Close Visual Attention was revealed when

compared with all other distraction groups. That is,

parents showed a significant reduction in the number of

times they made Close Visual Attention with their child

while using the computer.

A significant interaction effect was also detected

between Close Proximity X Group, F(6, 72) ¼ 2.56,

p < .05 (partial eta squared ¼ .18). Specifically, a significant

quadratic effect (p < .001) can be seen in Fig. 1C, in which

parents in the Phone Distraction group significantly

reduced their proximity to their child during the distraction

phase and then significantly increased in proximity during

the postphase when compared with both distraction and

baseline phases. Additionally, significant differences were

shown between distraction groups during only the post-

phase in which parents in the Computer Distraction group

showed significantly less proximity to their children when

compared with all other groups (p < .05).

Parent and child Engagement also showed a significant

interaction effect, F(6, 72) ¼ 5.80, p < .001 (partial eta

squared ¼ .33). Specifically, with the exception of parents

in the No Distraction Group, all parent and child dyads

significantly reduced their Engagement with each other

during the distraction phase (all p < .05). Additionally, as

shown in Fig. 1D, parents and their children who were in

Table I. Means (SD) for Parent and Child Behaviors During all Phases

and Across Groups

Behavior Baseline Distraction Post

Phone Distraction Group

Parent

Visual attention 59.9 (0.3)a1 59.8 (0.4)a1 59.6 (1.3)a1

Close proximity 41.7 (6.9)a1 26.3 (16.5)a2 48.8 (12.1)a3

Engagement 59.3 (1.1)a1 23.5 (15.9)a2 59.5 (1.3)a1

Child risk taking 3.4 (5.4)a1 2.2 (3.2)a1 3.3 (7.7)a1

TV Distraction Group

Parent

Visual attention 59.9 (0.3)a1 59.5 (1.3)a1 59.6 (0.8)a1

Close proximity 29.7 (13.5)a1 35.9 (20.6)a1 41.7 (15.4)a,b1

Engagement 59.9 (0.3)a1 42.0 (12.6)b2 58.5 (1.4)a1

Child risk taking 3.7 (5.2)a1 7.3 (10.2)a1 1.7 (1.8)a1

Computer Distraction Group

Parent

Visual attention 59.9 (0.3)a1 41.5 (11.5)b2 59.5 (1.0)a1

Close proximity 40.6 (13.8)a1 22.2 (16.1)a1 28.5 (19.6)b1

Engagement 60.0 (0.0)a1 38.2 (14.4)b2 59.1 (1.6)a1

Child risk taking 4.1 (5.4)a1 6.1 (7.4)a1 3.4 (5.7)a1

No Distraction Group

Parent

Visual attention 59.9 (0.3)a1 59.8 (0.4)a1 59.8 (0.4)a1

Close proximity 42.3 (14.1)a1 30.6 (20.0)a1 36.7 (15.7)a,b1

Engagement 59.9 (0.3)a1 59.8 (0.4)c1 60.0 (0.0)a1

Child risk taking 1.2 (1.4)a1 3.9 (9.0)a1 6.8 (9.7)a1

Subscripts that differ by letter are significant across groups (p < .05); different

numerical subscripts significantly differ within groups (p < .05).

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the Phone Distraction group showed significantly less

Engagement compared with the TV and Computer Distrac-

tion groups who were all significantly lower on engagement

behaviors compared with the No Distraction group.

In order to test the effects of whether knowing the

study was about child supervision, multiple one-way

MANOVAs across all three time periods were conducted

which revealed no group differences between informed and

misinformed parent–child dyads on all parent and child

behaviors (p > .05). Parents who were not aware of being

in a study on child supervision while being videotaped

showed no significant differences in their parental

behaviors related to supervision when compared with

parents informed of the study aims.

Correlation Analyses

Intercorrelations were calculated among Parent age, Child

age, Risk Taking, and three parenting behaviors: Close

Visual Attention, Close Proximity, and Engagement.

During the baseline phase a significant negative relation

between Child Age and Risk Taking occurred in which

risky behavior was less likely to occur as children neared

age 5 (r ¼ �.53, p < .01). Additionally, a significant

positive relation was found between Parent Age and

Close Proximity in which older parents showed greater

Proximity (r ¼ .44, p < .01). Finally, parents who demon-

strated more Close Visual Attention were significantly more

likely to also show Engagement during the baseline phase

(r ¼ .34, p < .05).

During the distraction phase, a significant negative

relation between Child Age and Risk Taking remained from

baseline phase (r ¼ �.49, p < .01). Additionally, a sig-

nificant positive relation between Close Visual Attention

and Close Proximity occurred (r ¼ .39, p < .05) as well as a

significant positive relation between Close Proximity and

Engagement (r ¼ .35, p < .05). During the postphase, a

significant negative relation between Child Age and Risk

Taking remained from the previous phases (r ¼ �.44,

p < .01). Interestingly, no significant correlations were

found among child gender, major injury history, and Risk

Taking. Furthermore, analyses of parent report of room

hazards after the observation revealed no significant rela-

tionships on child or parent behaviors or family demo-

graphic variables.

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Figure 1. The average number of times the target behavior occurred during intervals across participants. (A) Mean number of Child Risk Taking behaviors by children during each experiment phase, by distraction group; (B) Mean number of parents’ Close Visual Attention with children during each experiment phase, by distraction group; (C) Mean number of parents’ Close Proximity with children during each experiment phase, by distraction group; and (D) Mean number of parents’ Engagement with children during each experiment phase, by distraction group.

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Discussion

Our findings are that parents show a shift in parental

supervision during typical home distractions. Compared

with parents who were not experimentally distracted, all

distractions significantly reduced parental engagement and

the parents’ visual attention was reduced while the parents

were engaged with the computer. Additionally, parents

were significantly more likely to be farther away from their

child during TV and phone distractions. These findings

largely support our hypotheses that parents would reduce

their supervision behaviors during common home distrac-

tions. The distractions in the current study were believed

to have generalizibility to the real home world of families,

given the common experiences of parents talking on the

phone, watching TV, or using a computer while super-

vising their child. This study provides a number of

important advancements in explicating the role of parental

supervision of preschool children during typical home

distractions. In addition, this study empirically addresses

methodological concerns often raised during observational

investigations, which can be useful when designing future

supervision investigations.

Although not statistically reliable, children increased

their risk taking behaviors during distractions, except when

parents were on the phone, and showed a steady increase

in risk taking over time when parents were not distracted.

Additionally, there was a negative relation between the

variables measuring child age and risky behavior during all

three time periods. Even though not systematically

evaluated for this study, children who interacted with

risky objects most often attempted to bring the object to

a parent. Such behavior may be the result of prior parental

warnings regarding the dangerousness of similar objects. It

remains unclear, how many children become injured by

handling objects they have been told are dangerous and

attempt to move it to a safer location or to an adult. The

fact that children in the No Distraction group gradually

increased their risky behavior over time may indicate

boredom with the simulated environment and a tendency

to explore items, including risky objects initially perceived

as ‘‘off limits.’’

When combined across distraction groups, child risk

taking behaviors during the baseline (M ¼ 3.1; SD ¼ 4.6),

distraction phase (M ¼ 4.9; SD ¼ 7.9), and postphase

(M ¼ 3.8; SD ¼ 6.9) indicates that children showed an

average risky behavior about once every 5 min in an

unfamiliar environment. Our prior observational investiga-

tions without a parent present showed a lower rate of

contact with dangerous items (1.78 contacts every 15 min;

Boles, Roberts, Brown, & Mayes, 2005), which may reflect

the child’s belief that the environment is safer with a parent

present. Additional investigations may benefit from

including more postobservational interviews with children

to address these cognitions.

Contrary to our hypothesis, parents’ eye contact,

distance away from, and involvement with their children

were not statistically related to child risk taking behaviors.

This finding may be due, in part, to the belief that parents

may not have considered their child’s risky behaviors as

actually being dangerous but rather typical child behavior,

resulting in minimal systematic changes in parent

behaviors. In previous research, for example, parents

have reported that childhood injuries are expected during

childhood and not likely to be preventable by parents

(Morrongiello & Dayler, 1996). Additionally, parents’

report of the room’s risky objects and probability of their

child becoming injured showed no significant association

with actual supervision behaviors. This finding may show

how noninjurious events, despite a danger being present,

reinforces the belief that injury is unlikely and that

parenting behaviors need to be modified for the environ-

mental conditions.

After a distraction, parents made greater eye contact,

were more often close to their child, and were more

engaged with their child. Nonetheless, supervision beha-

viors were significantly intercorrelated during only the first

30 min, suggesting parents may change their supervision

practices over time. Thus, the present study provides only

limited support of the model of supervision behaviors from

Saluja et al. (2004) for understanding risky behaviors. In

particular, parents showed no significant changes in their

supervising behaviors related to their child’s risky behavior.

This finding is particularly striking given the tendency for

children to increase risky behaviors during most parent

distractions as well as across time. Moreover, during

distractions, parents showed significant reductions in their

ability to supervise their children, limiting the ability to

provide education or to take immediate action necessary to

prevent or minimize a possible injury after risky behavior.

This finding also provides evidence that the manipulation

was effective (and simulated real life).

Additional investigations are needed to assess the

impact of environmental modifications on not only risky

child behavior but also parental supervision. That is,

parents may be likely to modify their supervision behaviors

in terms of how close they are, how often they make direct

eye contact, and how often they engage in verbal or

physical interactions based on how they perceive the

environmental risk as well as beliefs about typical child

behavior. Clearly, this is a complex model of reciprocal

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interactions rather than a simple relationship of super-

vision ! risky behavior ! injuries.

Assessments regarding parents’ perceptions of child

behaviors during observations may also help identify

possible reasons parents’ supervision behaviors were not

related to risky child behaviors. Further, additional

variables such as verbal behavior and parental environ-

mental modifications require analyses to explicate the

relationship among supervising behaviors and risky child

behaviors in the home environment. For instance,

Morrongiello and Dawber (2000) found that when parents

observed children playing on a playground, girls received

more verbalizations of concern about their behavior, while

boys were given encouragement for risky behavior. Our

findings also revealed parents increased their level of

engagement following a distraction which may also be a

factor of general parenting practices. For instance, parents

who show authoritative parenting styles (e.g., high levels of

structure and warmth/involvement) may also have an

association with positive supervision behaviors. Future

supervision investigations may benefit from the inclusion

of parental assessments of parenting behaviors that impact

other child–parent interactions (e.g., compliance with

directions), beyond risk taking behaviors.

The present study provided initial evidence that

participant knowledge in fact does not change participant

behaviors in regard to socially desirable behaviors. That is,

parents who were aware they were being videotaped

showed no greater positive supervision behaviors (e.g.,

using more direct/peripheral eye contact) than parents who

were informed the study was about child patience. This

finding may make future observational studies, which are

potentially an important methodological procedure toward

validating supervision as a construct and subsequent

supervision questionnaires, more likely to be conducted.

Deceptive practices do not appear necessary in order to

minimize socially desirable behaviors.

The limitations of the present study should be

considered when evaluating the present findings. Most

importantly, the observations of parents and children took

place in a simulated home environment. Although precau-

tions were taken to help minimize this potential problem,

the simulated environment might have altered some

behaviors. For example, parents might have thought the

room had been safety proofed before entering with their

child. This potential limitation is countered, however, by

the fact that 100% of parents identified dangerous items in

the room, with an average of 4.75 items listed (ranging

from 3 to 9). Parents in the current study were well

educated and nearly all Caucasian. However, unintentional

injuries remain the leading cause of death in America for

individuals between the ages of 1 and 44 years, across

gender, race, and economic status (Centers for Disease

Control and Prevention, 2005). Developing the present

methodology to obtain these initial findings provided a

significant foundation to build on for future studies to

determine generalizibility to different types of parents. In

particular, there may be differential rates of supervision

behaviors related to diverse backgrounds, including ethnic

diversity and socioeconomic diversity. Understanding these

differences is important to designing tailored interventions

for at-risk populations and their associated risky behaviors.

In addition, our sample size may have limited our

ability to detect some relationships, despite having ade-

quate power for others. Although using a behavioral

observation methodology can be time and labor intensive,

which can limit the number of participants for feasibility

reasons, additional observation-based research may benefit

from using larger samples in order to test multiple num-

bers of hypotheses that deal with relationships that have

varied effect sizes.

As supervision of children continues to be explored as

a necessary construct toward identifying active-based

injury prevention programs, investigations are still

needed to explicate the role of not only nonverbal parent

behaviors, but also the way parents interact with their

environment to make supervising their children produc-

tive, manageable, and within their particular belief systems.

In particular, parents potentially use a combination of

parenting skills during supervision, including modifying

the environment, providing verbal and physical redirec-

tions, and making continuous estimates of risk for their

children for various contexts. However, given the current

number of home injuries still sustained by preschool

children each year, parents are likely not implementing

such skills each day or recognizing the role they have in

reducing the risk of injury for their child. In fact, parents

still often report not being able to prevent injuries and

‘‘accidents’’ are merely the result of bad luck (Morrongiello

& Dayler, 1996; Morrongiello & House, 2004). Therefore,

supervision investigations must also consider how best to

address such erroneous cognitive beliefs about environ-

mental risk as well as limited knowledge on typical child

development that likely impede behavioral interventions

that focus only on changing behaviors. Although it is

encouraging that supervision is increasingly being empiri-

cally investigated as a component of understanding

unintentional injuries, much greater attention is needed

on the development and assessment of comprehensive

models that capture the complex nature of unintentional

840 Boles and Roberts

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injuries. Only until such investigations are conducted will

the most effective interventions and prevention programs

be realized.

Acknowledgment

This study was supported in part by the 2004–2005

Student Fellowship Award from The Society for Public

Health Education Fellowship provided by the Centers for

Disease Control and Prevention and was based on R.E.B.

doctoral dissertation submitted to The University of

Kansas.

Conflicts of interest: None declared.

Received August 12, 2007; revisions received February 18,

2008; accepted February 20, 2008

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