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Technoference: Longitudinal Associations between Parent Technology Use, Parenting Stress, and Child Behavior Problems

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Technoference: Longitudinal Associations between Parent Technology Use, Parenting Stress, and Child Behavior Problems

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Background and objectives: Heavy parent digital technology use has been associated with suboptimal parent-child interactions and internalizing/externalizing child behavior, but directionality of associations is unclear. This study aims to investigate longitudinal bidirectional associations between parent technology use and child behavior, and understand whether this is mediated by parenting stress. Methods: Participants included 183 couples with a young child (age 0-5 years, mean = 3.0 years) who completed surveys at baseline, 1, 3 and 6 months. Cross-lagged structural equation models of parent technology interference during parent-child activities, parenting stress, and child externalizing and internalizing behavior were tested. Results: Controlling for potential confounders, we found that across all time points (1) greater child externalizing behavior predicted greater technology interference, via greater parenting stress; and (2) technology interference often predicted greater externalizing behavior. Although associations between child internalizing behavior and technology interference were relatively weaker, bidirectional associations were more consistent for child withdrawal behaviors. Conclusions: Our results suggest bidirectional dynamics in which (a) parents, stressed by their child's difficult behavior, may then withdraw from parent-child interactions with technology and (b) this higher technology use during parent-child interactions may influence externalizing and withdrawal behaviors over time.
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Technoference: Longitudinal Associations between Parent
Technology Use, Parenting Stress, and Child Behavior Problems
Brandon T. McDaniel1 and Jenny S. Radesky2
1Illinois State University, Normal, IL
2University of Michigan Medical School, Ann Arbor, MI
Abstract
Background and Objectives: Heavy parent digital technology use has been associated with
suboptimal parent-child interactions and internalizing/externalizing child behavior, but
directionality of associations is unclear. This study aims to investigate longitudinal bidirectional
associations between parent technology use and child behavior, and understand whether this is
mediated by parenting stress
Methods: Participants included 183 couples with a young child (age 0–5 years, mean = 3.0
years) who completed surveys at baseline, 1, 3, and 6 months. Cross-lagged structural equation
models of parent technology interference during parent-child activities, parenting stress, and child
externalizing and internalizing behavior were tested.
Results: Controlling for potential confounders, we found that across all time points (1) greater
child externalizing behavior predicted greater technology interference, via greater parenting stress;
and (2) technology interference often predicted greater externalizing behavior. Although
associations between child internalizing behavior and technology interference were relatively
weaker, bidirectional associations were more consistent for child withdrawal behaviors.
Conclusions: Our results suggest bidirectional dynamics in which (a) parents, stressed by their
child’s difficult behavior, may then withdraw from parent-child interactions with technology and
(b) this higher technology use during parent-child interactions may influence externalizing and
withdrawal behaviors over time.
INTRODUCTION
Despite being a cultural norm,(1) mobile phone use in public and private spaces is frequently
described as an uncomfortable interruption by users(2) and their social companions.(3)
Studies suggest that adults experience more frustration and conflict,(4, 5) less in-depth
conversation,(6) and lower sense of empathy(7) when mobile devices are used during social
interactions. Parents are now estimated to use digital media (e.g., television, computers,
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Corresponding Author: Brandon T. McDaniel, Ph.D., Department of Family and Consumer Sciences, Illinois State University,
Phone: 309-438-5802, btmcdaniel.phd@gmail.com.
Disclosure Statement: The authors have no financial conflicts of interest relevant to this article to disclose
HHS Public Access
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Pediatr Res
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Published in final edited form as:
Pediatr Res
. 2018 August ; 84(2): 210–218. doi:10.1038/s41390-018-0052-6.
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smartphones, tablets) an average of 9 hours per day,(8) with approximately 3 hours per day
on their smartphones.(9)
Parent mobile device use has received particular scrutiny because the portability of devices
has facilitated their use during many family activities such as meals, playtime, and bedtime,
(10) which have an important role in shaping child social-emotional health.(11–13) In
naturalistic observations of families, Radesky and colleagues recorded less conversation and
more parent hostility in response to child bids for attention when parents’ attention was
absorbed in their mobile devices.(14) Subsequent studies have documented associations
between parent mobile device use and fewer parent-child interactions during videotaped
eating tasks,(15) as well as lower responsiveness to child bids for attention on the
playground.(16) When interviewed about the experience of parenting in the presence of
mobile devices, parents reported feeling emotionally and cognitively affected by their
mobile device use in ways that can make it difficult to read and respond to child behavioral
cues.(2)
However, only one prior study has examined links between parent device use and child
behavioral outcomes. McDaniel and Radesky found cross-sectional associations between
parent technology interference (“technoference,” defined by McDaniel and Coyne(4) as
everyday interruptions in interpersonal interactions or time spent together that occur due to
digital and mobile technology devices) and higher child externalizing (e.g., tantrums,
emotional reactivity) and internalizing (e.g., anxiety, withdrawal) behavior problems –
especially for mother-child activity interruptions.(17) However, directionality of these
associations remains unclear. While it is plausible that interrupted parent-child play or
reduced parent responsiveness could contribute to child behavioral problems, it is also
possible that parents use technology to cope with parenting stresses – e.g., to escape from
parenting demands(3) or to connect with other parents for social support.(18) In semi-
structured interviews, parents have described using mobile devices when needing a break
from difficult child behavior, relieving stress through use of entertainment apps, or to keep
their household quiet.(2)
Another limitation of the existing literature is the lack of longitudinal studies; thus,
examination of transactional processes(19) (i.e., the bidirectional influences of child and
environment over time) in parent media use and child outcomes has not been possible. The
aim of the present study was to build upon prior cross-sectional findings by examining
transactional associations between technoference in parent-child activities and child
behavior in a cohort of mothers, fathers, and their young children. In line with prior work,
(17) we hypothesized that more frequent technoference in daily mother-child and father-
child interactions would predict higher ratings of child internalizing and externalizing
behavior (H1); higher ratings of child internalizing and externalizing behavior would predict
higher parenting stress (H2); and higher parenting stress would predict more frequent
technology interference (as parents withdraw to technology to escape or self-regulate, H3).
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PATIENTS AND METHODS
Participants & Procedure
Participants included mothers and fathers from 183 couples with a young child who took
part in the
Daily Family Life Project
,(20) a longitudinal study of parenting and family
relationships conducted from 2014 to 2016. Participants were recruited through letters and
phone calls to families who were part of a family research database in a Northeastern U.S.
state as well as via flyers in the local community. Announcements were also posted to
various online resources and listservs in order to expand our reach to individuals in other
areas of the U.S. To be eligible to participate, individuals had to be at least 18 years old, a
parent of a child age 5 years or younger, speak English, and currently live with their child
and spouse/partner. Their spouse/partner also had to be willing to participate. Participants
were emailed a survey link through which they completed informed consent and a baseline
online survey via Qualtrics. Participants completed follow-up online assessments at
approximately 1, 3, and 6 months.
In the present study, we first excluded 11 families whose child was younger than 1 year at
baseline, since the behavior rating items were not standardized for infants. We utilized data
from all remaining parents who had data from at least one time point, which resulted in an
analytic sample of 337 parents (171 mothers and 166 fathers; 92% of the original sample of
366 parents); 70% of these 337 parents had data across all time points. In the analytic
sample of 337 parents, families resided in the following U.S. regions: 54% Northeast, 16%
Midwest, 15% South, and 15% West. On average, mothers were 31.7 years old (
SD
= 4.3;
range 22–42), and fathers were 33.3 (
SD
= 4.9; range 22–52). Most families (61%) had more
than one child (
M
= 1.90,
SD
= 0.91), and the index child was 3.0 years old on average (
SD
= 1.2;
Range
= 1.0–5.5 years; 55% female). Most parents were married (94%), and had at
least a Bachelor’s degree (72%). The race/ethnicity breakdown was 91% Caucasian, 3%
Latino, 2% Black/African American, 2% Asian American, and 2% Other. Median yearly
household income was approximately $69,500 (
M
= $74,870,
SD
= $39,470), with 21% of
families reporting some form of state or federal assistance (e.g., medical assistance, food
stamps). Utilizing chi-squares and t-tests, we found that parents in our analytic sample were
in a longer relationship (
t
(360) = 1.945,
p
= .052) and had more children (
t
(360) = 3.79,
p
< .001) than excluded participants; the samples were otherwise similar.
Measures
Technoference in parent-child activities.—At each data collection wave,
technoference (i.e., technology interference) in mother-child activities and father-child
activities was assessed via mother and father self-report. Items were adapted from the
Technology Device Interference Scale (TDIS),(4) a measure of technoference in couple
relationships that is associated with couple relationship health.(4) Instead of assessing
duration of parent media use, this scale measures the extent to which different forms of
technology intrude in or interrupt interpersonal interactions and activities during daily
routines; the scale used in the current study was reworded to refer specifically to interactions
with one’s child, and has been used in in prior research.(17) Items asked, “On a typical day,
about how many times do the following devices interrupt a conversation or activity you are
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engaged in with your child?” The 6 items on the scale included: (1) cellphone/smartphone,
(2) television, (3) computer, (4) tablet, (5) iPod, and (6) video game console. Parents
responded to each item on a 7-point scale ranging from 0 (
none
) to 6 (
more than 20 times
).
As this is a count measure and we expected there to be variability (as opposed to
consistency) within individuals’ responses, it not appropriate to calculate Cronbach’s
alpha(21) (however, the alpha ranged from .69 to .82 across time points). Parents were
queried about different devices separately because of the assumption that different modes of
technology use may with parent-child activities to varying degrees, yet the level of
technoference from various devices was often correlated (inter-item correlations .24 to .71,
ps
< .001). Items were therefore averaged, with higher scores representing more frequent
technoference in parent-child activities.
Child externalizing and internalizing behavior problems.—At each data collection
wave, parents completed the internalizing (36 items) and externalizing scales (24 items) of
the Child Behavioral Checklist (CBCL).(22) These items ask parents to rate their child now
or within the past two months on a 3-point scale ranging from 0 (
not true
) to 2 (
very true or
often true
). Internalizing consists of items such as “whining,” “sulks a lot,” and “feelings are
easily hurt.” Externalizing consists of items such as “can’t sit still, restless, or hyperactive,”
“easily frustrated,” and “temper tantrums or hot temper.” Items were summed to produce
separate mother and father ratings of internalizing and externalizing child behavior
(Cronbach’s alphas for internalizing ranged from .89 to .94 across time points; alphas for
externalizing ranged from .92 to .93). We then converted raw sum scores to normed
externalizing and internalizing T-scores for analysis. Additionally, we conducted post-hoc
analyses with the internalizing subscales (Emotional Reactivity, Anxiety/Depression,
Somatic Complaints, and Withdrawal) and externalizing subscales (Attention Problems and
Aggression).
Parenting Stress.—At each data collection wave, parents completed 27 items from the
Parenting Stress Index (PSI).(23) We used 27 items from the 36-item PSI Short Form due to
lower factor loadings on 9 of the items, as others have done.(24),(23) Items were averaged to
produce an overall stress score (Cronbach’s alphas ranged from .91 to .94 across time
points).
Potential confounding variables.—At baseline, parents reported their age, educational
attainment, marital status, race/ethnicity, family composition, household income, and child’s
age, gender, and health. They also completed measures of coparenting quality, depressive
symptoms, and reported on their child’s daily duration of screen media use.
As this sample consists of two-parent families, we controlled for coparenting quality—or
how well parents work together in childrearing(24) – which has been associated with child
behavior problems(25) and technoference.(10, 21) Both parents completed the Coparenting
Relationship Scale,(24) a 35-item scale (e.g., “When I’m at my wits end as a parent, partner
gives me extra support I need” and “My partner undermines my parenting”) rated on a 7-
point scale (0 =
not true of us
to 6 =
very true of us
). After reverse coding negatively worded
items, items were averaged to produce an overall score with higher scores indicating higher
coparenting quality (Cronbach’s alpha = .94).
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Depressive symptoms were measured utilizing the validated Center for Epidemiologic
Studies Depression Scale (CES-D).(26) Participants rated how often they experienced 20
symptoms (e.g., “I felt depressed” and “I felt sad”) in the past week on a 4-point scale
ranging from 0 (
rarely or none of the time, less than 1 day
) to 3 (
most or all of the time, 5 to
7 days
). Items were averaged to produce an overall depression score (Cronbach’s alpha = .
89). We controlled for depressive symptoms as depressed mood has been associated with
quality of parent-child interactions(27) and greater relationship technoference.(4)
At baseline, parents rated how much time, on a typical day, their child spent using screen
media devices across 8 items (e.g., computer, TV, smartphone, tablet, video games) on an
11-point scale ranging from 0 (
None
) to 10 (
7 or more hours
). Items were summed to
produce an overall child screen use score (Cronbach’s alpha = .78). We controlled for child
screen media use because it is strongly associated with both parent media use(9) and child
social-emotional outcomes.(28)
Data Analysis
We utilized structural equation modeling (SEM) to test two separate models, one for child
externalizing and one for child internalizing, of: (H1) more frequent technoference in parent-
child interactions predicting higher ratings of child behavior problems; (H2) higher ratings
of child behavior problems predicting higher parenting stress; and (H3) higher parenting
stress predicting more frequent technoference in parent-child activities. The models were
tested utilizing AMOS.(29) Standardized estimates are shown for the models in Figures 1
and 2. Potential confounders including parent characteristics, child age, child screen use,
parent depressive symptoms, and coparenting quality were entered into the models but were
removed from the final models as results did not change significantly. Structural equation
modeling was utilized as this allowed us to examine the complex cross-lagged paths between
our various predictors and outcomes across multiple waves of data collection
simultaneously, while also controlling for prior levels of the variables and better accounting
for potential error in the modeling.(29) SEM also allows for assessments of model goodness
of fit(30) and handling of missing data are using full information maximum likelihood
estimation.
Based on prior evidence showing different cross-sectional associations between maternal
technoference and paternal technoference with child behavior,(17) we also examined
whether model paths and estimates were significantly different for mothers and fathers.
Through a multi-group SEM analysis, we first tested whether the statistical fit of the model
significantly worsened when we constrained the model paths to be equal across mothers and
fathers. If it is found that the fit worsens significantly, this suggests that at least some of the
paths in the model must be different for mothers and fathers. We then compared model paths
between mothers and fathers to find where they differed from one another and no longer
constrained those specific paths to be equal across mothers and fathers.
Finally, in post-hoc analyses, we examined subscales of the CBCL Internalizing Scale
(Emotional Reactivity, Anxiety/Depression, Somatic Complaints, and Withdrawal) and
Externalizing Scale (Attention Problems and Aggression) to determine whether specific
aspects of child behavior were more strongly associated with parenting stress and parent
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technoference in our models. As above, these models were tested for differential
associations between mothers and fathers.
RESULTS
Descriptive data are presented in Table 1; for simplicity of interpretation, variables are
presented as averages over the four data collection waves. On average, across all four time
points, mothers perceived 1.65 devices and fathers perceived 1.43 devices as interfering in
their interactions with their child at least once on a typical day; of note, interference was
reported as not occurring at all on a daily basis in only 4.9% of mothers and 9.6% of fathers.
Over half (55.5%) of mothers and 43.0% of fathers reported that 2 or more devices
interrupted their parent-child activities on a daily basis. Parents who reported no
technoference over any of the time points were very similar to the other parents in our
sample in terms of age, ethnicity, marital status, child age, education, and income; only in
fathers who reported no technoference at all did we see that these fathers had a higher family
income as compared with other fathers (
t
(174) = −2.23,
p
< .05). Maternal and paternal
technoference were moderately correlated over the study period (.26 −.58,
ps
< .001).
Additionally, maternal reports of technoference were moderately to highly correlated over
the 6 months of the study period (.53 −.76,
ps
< .001), as were paternal reports of
technoference over the study period (.50 - .84,
ps
< .001). In our sample at baseline, 4% of
parents’ ratings of children met or exceeded the clinical cut-off (t-score of 70 or above)(22)
for externalizing behavior and 3% for internalizing behavior.
Tables 2 and 3 show bivariate associations between parent average technoference, parent/
child characteristics, and other study variables. In mothers, younger mother age was
associated with higher technoference, and in fathers, greater child media use was associated
with greater technoference. Parent race/ethnicity, education level, family income, and child
age were not associated with technoference levels (see Table 2). In both mothers and fathers,
higher technoference was associated with greater child externalizing and internalizing
behaviors, and higher parenting stress; higher technoference was also associated with lower
coparenting quality (fathers only) and greater parent depressive symptoms (mothers only)
(see Table 3).
As described above, we first examined whether the SEM model could be run for all parents
(mothers and fathers combined) or whether significant differences emerged in model paths
by parent gender utilizing a multi-group analysis. We found that the model fit was
significantly worse if all model paths were constrained across parent gender in both the
externalizing (Δχ² (21) = 54.14,
p
< .001) and internalizing models (Δχ² (21) = 53.61,
p
< .
001). We therefore examined the pairwise parameter comparisons in AMOS to identify
which paths were significantly different by parent gender. These few paths (displayed as
mother / father estimates in Figures 1 and 2) were then allowed to be freely estimated for
mothers and for fathers in the model, while all other paths were constrained to be equal
across parent gender. The final model for technoference, parent stress, and child
externalizing behavior fit the data well (χ² (73) = 109.53,
p
< .01; RMSEA = .03; CFI = .99)
as did the model for internalizing behavior (χ² (73) = 190.60,
p
< .001; RMSEA = .06 CFI
= .95).
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H1: Frequency of Technoference Would Predict Greater Child Behavior Problems
We found support for our hypothesis (H1) in the child externalizing behavior model, with
technoference in parent-child interactions predicting greater externalizing behavior at each
of the following time points (βs = .11, .16, and .13,
ps
< .01). H1 was only partially
supported for child internalizing behavior, with only month 3 technoference predicting
greater month 6 internalizing (β = .21,
p
< .001).
H2: Child Behavior Problems Would Predict Greater Parenting Stress
We found support for our hypothesis (H2) in the child externalizing behavior model, with
child externalizing predicting greater parenting stress at each of the following time points
(βs = .16, .15, and .12,
ps
< .01). H2 was only partially supported for child internalizing
behavior, with internalizing at baseline predicting greater parenting stress at month 1 (β = .
13,
p
< .01).
H3: Greater Parenting Stress Would Predict Greater Technoference
We found some support for our hypothesis (H3) in both the externalizing and internalizing
models, as parenting stress predicted later technoference from baseline to month 1 (βs = .19
and .15,
ps
< .01) and from month 1 to month 3 (βs = .17 and .19,
ps
< .001) in both models.
The path from month 3 parenting stress to month 6 technoference was in the hypothesized
direction but not statistically significant (
p
< .10).
Post-Hoc Analyses on Internalizing and Externalizing Subscales
All subscale model results, except for the withdrawal model, were very similar to the overall
internalizing or externalizing models. To reduce redundancy, we therefore only report the
model results for the withdrawal model here (χ² (73) = 201.26,
p
< .001; RMSEA = .06 CFI
= .95). These withdrawal model results were also similar to the overall internalizing model;
however, a few more model paths were significant (see Figure 3). In the withdrawal model,
we found partial support for our hypothesis (H1), with technoference in parent-child
interactions predicting greater withdrawal behavior at both month 1 and month 6 (βs = .09
and .32,
ps
< .01). We found partial support for our hypothesis (H2), with greater child
withdrawal predicting greater parenting stress at both month 1 and month 6 (βs = .18 and .
10,
ps
< .05). Finally, we found support for our hypothesis (H3), as greater parenting stress
predicted greater technoference at month 1 and 3 (βs = .18 and .16,
ps
< .001) and at a trend
level at month 6 (β = .07,
p
< .10).
DISCUSSION
This study is the first to show longitudinal associations between mother and father
technology use during parent-child activities and reported child behavioral difficulties, with
evidence of bidirectional associations between technoference and child externalizing
symptoms over the course of 6 months. Although technoference was sometimes associated
with greater child internalizing symptoms, bidirectional associations between internalizing
symptoms, parenting stress, and technoference were most consistent with regard to child
withdrawal.
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The bidirectional associations documented in this study are consistent with existing
literature. First, our models show evidence for high parent technology use predicting small
but significant increases in externalizing child behavioral difficulties, which is consistent
with public observations of children behaviorally escalating to get the attention of parents
absorbed in their mobile devices. In naturalistic observations, Radesky and colleagues
described recurrent instances of young children acting silly, raising their voices, and
showing more impulsive behaviors while their caregivers’ attention was attuned to a mobile
device during fast food meals.(14) A recent study of families’ mobile device use patterns
revealed that children are often frustrated by the sudden withdrawal of parental attention
when responding to a notification on a mobile device, especially if the reason for device use
is unclear.(3)
Another less immediate mechanism is that, when mobile device use displaces verbal and
nonverbal interaction(15) and responsiveness over time,(16) it is possible that children
receive less parent scaffolding – the parent’s ability to give the child just enough positive
support to perform a new skill on their own – in developing behavior regulation. In order to
effectively scaffold child social and emotional skills, parents need to understand the child’s
mental state and motivations for behavior, in order to intervene effectively to help the child
calm down, identify feelings, and problem-solve.(31) However, parents who frequently use
mobile devices during parent-child activities shower lower understanding of their child’s
mental state and intentions.(32) Work in pre-adolescents suggests that screen media use
displaces face-to-face interactions in such a way as to make it difficult to read others’
nonverbal social cues, and when digital media are restricted, children get better at
interpreting others’ emotional states.(33) The same mechanism could be occurring with
parents and their young children, whose social cues are not always easy or clear to interpret.
In prior in-depth interviews, parents have described difficulty dividing their attention
between children and the “always-on” work or social demands of their mobile device,
making it challenging to read and respond to child behavioral and emotional cues
contingently.(2)
Conversely, our models showed that child behavioral difficulties – especially externalizing –
were associated with later higher levels of parent stress, which in turn were associated with
higher downstream technology use during parent-child activities. Mobile and traditional
media have long been considered ways that adults relieve stress,(34) regulate boredom or
anxiety,(35) or withdraw from social interactions.(3, 36) Mobile communication researchers
posit that aspects of interactive design act upon brain reward circuits in such a way that they
induce pleasure(37) and habit-formation.(38) The same concepts hold for parents; in
qualitative interviews, many stay-at-home mothers reported using digital technology as a
way to “escape” the boredom or frustrations of childrearing, or to regulate their own
emotions or arousal;(2) reaching out to friends, catching up on the news, or playing games
were described as ways to take breaks from sometimes exhausting home routines. By
demonstrating parenting stress as mediator of these associations, our findings support a
conceptual model in which parents use digital technology devices as a potential means of
escape and for stress management.(2) A recent ecologic examination of everyday mobile
device use within the family context revealed that parents sometime use mobile devices as a
way to actively withdraw from parenting duties – pretending to be occupied with something
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important when children need help – and that this constituted a ‘desirable disengagement’ to
find time for oneself amid parenting demands.(3)
Overall, like most developmental processes, these results support the hypothesis that
relationships between parent technoference and child externalizing behavior are
transactional(19) and influence each other over time. In other words, parents who have
children with more externalizing problems become more stressed, which may lead to greater
technoference (e.g., withdrawal with technology), which in turn may contribute to more
child externalizing problems (and only sometimes internalizing problems). Our results
suggest that children may be more likely to act out over time in response to technoference as
opposed to internalize, although when we examined internalizing subscales, child
withdrawal was the most consistently associated with parent technoference over time. This
may be due to 1) parents responding to child withdrawal social cues by feeling they too can
disengage into their mobile device use, or 2) parent media use precipitating child withdrawal
from social interaction, which was observed in prior observational work.(14)
It is possible that greater parent digital technology use may also be a marker of other parent
or household characteristics that independently predict digital technology use, parenting
stress and child behavioral problems, such as greater family dysfunction,(39) parent mental
health or anxiety symptoms,(40) or work-life balance difficulties(41) – although controlling
for parent and child characteristics, as well as parent depression and coparenting quality, did
not change our model results significantly. However, we postulate that specific aspects of
digital technology, including persuasive design elements (i.e., design aspects that reward the
user for prolonged engagement),(42) are particularly appealing to parents with their own
self-regulation difficulties(43) or those frustrated with their family social environment,(2, 3)
which could lead to more technology interruptions than would otherwise occur. The
technoference method of assessing media use is particularly relevant to this hypothesis, since
it characterizes the invasion or interruption of life routines with mobile device use, through
notifications made by the phone or ad-hoc habitual usage on the part of the user. However,
experimental studies will be necessary to test these hypotheses.
We recognize that the primary limitation of this study was the use of parent self-reports of
digital technology use and child behavior, rather than observational methods, which could
lead to single-reporter bias. However, self-report methods allow examination of mobile
device use by both parents over recurrent time points, which has not been studied in prior
publications,(2, 14, 15) and allow feasible data collection within a larger sample size.
Although effects were generally small in size, their consistent associations over time,
particularly for child externalizing behavior, suggest that cumulative effects on parent or
child behavior could become clinically relevant. Additionally, it is possible that internalizing
behaviors might be more likely than externalizing behaviors to go unnoticed by parents
distracted by technology, potentially leading to the differing results in the externalizing and
internalizing models. Future observational work will be necessary to objectively characterize
children’s reactions to parent mobile device use. This study was also limited by having a
primarily Caucasian, cohabiting, fairly-educated sample, so results may not be generalizable
to the entire U.S. population, but its findings are an important contribution to the
understanding of complex family processes around rapidly adopted digital technologies. Our
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findings also emphasize the importance of technology interference in relatively well-
educated families, who are not often conceived as being ‘at risk’ in terms of high media use.
(9) Given these findings’ relevance for understanding contextual influences on child
behavior and for crafting clinical recommendations, they should be replicated in larger and
more diverse cohorts.
CONCLUSION
This study’s findings have several implications for future research and clinical work. Given
the transactional nature of technology use and child development/behavior, future studies
should consider using statistical approaches that allow examination of bidirectional
associations. It will be important to measure how parents are using mobile devices
throughout the day, including content and motivations for use (e.g., entertainment, work-
related). Moreover, sequential analysis of parent-child interaction during mobile device use
will be helpful to determine whether, moment to moment, child behavioral difficulties
appear to precipitate or stem from parent technology use.
Clinically, our results suggest that mobile devices and other digital technology are
potentially serving stress-relieving purposes for parents, but at the same time potentially
displacing opportunities for parent-child connection important to child health and
development. In addition to parents setting their own media limits – for example through the
American Academy of Pediatrics’ Family Media Use Plan – it may be important to help
parents build awareness regarding their relationship with technology and how media
influences family dynamics. At the same time, it will also be necessary to provide skills for
managing difficult child behavior and reducing parenting stress. However, because our study
suggests small but significant long-term associations between technoference and child
externalizing and internalizing behavior, it would be worthwhile to study whether
experimental manipulation of parent mobile phone use habits – for example through
unplugged family routines or less intrusive digital design(44) – might lead to improvements
in the parent-child relationship and child behavior.
Statement of Financial Support:
College of Health and Human Development, Department of Human Development and Family Studies, and the
Bennett Pierce Prevention Research Center at The Pennsylvania State University; NIDA (T32DA017629); NICHD
(F31 HD084118)
References
1. Ling R The mobile connection: The cell phone’s impact on society: Morgan Kaufmann; 2004.
2. Radesky JS, Kistin C, Eisenberg S, Gross J, Block G, Zuckerman B, et al. Parent perspectives on
their mobile technology use: the excitement and exhaustion of parenting while connected. Journal of
Developmental & Behavioral Pediatrics. 2016;37(9):694–701.
3. Oduor E, Neustaedter C, Odom W, Tang A, Moallem N, Tory M, et al., editors. The Frustrations and
Benefits of Mobile Device Usage in the Home when Co-Present with Family Members.2016 ACM
Conference on Designing Interactive Systems; 2016: ACM.
4. McDaniel BT, Coyne SM. “Technoference”: The interference of technology in couple relationships
and implications for women’s personal and relational well-being. Psychology of Popular Media
Culture. 2016;5(1):85.
McDaniel and Radesky Page 10
Pediatr Res
. Author manuscript; available in PMC 2018 December 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
5. McDaniel BT, Galovan AM, Cravens JD, Drouin M. “Technoference” and implications for mothers’
and fathers’ couple and coparenting relationship quality. Computers in Human Behavior.
2018;80:303–13.
6. Przybylski AK, Weinstein N. Can you connect with me now? How the presence of mobile
communication technology influences face-to-face conversation quality. Journal of Social and
Personal Relationships. 2013;30(3):237–46.
7. Misra S, Cheng L, Genevie J, Yuan M. The iPhone effect: the quality of in-person social interactions
in the presence of mobile devices. Environment and Behavior. 2016;48(2):275–98.
8. Lauricella AR, Cingel DP, Beaudoin-Ryan L, Robb MB, Saphir M, Wartella E. The Common Sense
Census: Plugged-in parents of tweens and teens. Common Sense Media. 2017.
9. Wartella E, Rideout V, Lauricella A Parenting in the Age of Digital Technology2014. Available
from: http://cmhd.northwestern.edu/wp-content/uploads/2015/06/
ParentingAgeDigitalTechnology.REVISED.FINAL_.2014.pdf.
10. McDaniel BT, Coyne SM. Technology interference in the parenting of young children:
Implications for mothers’ perceptions of coparenting. The Social Science Journal. 2016;53(4):
435–43.
11. Bornstein MH, Tamis-Lemonda CS, Hahn CS, Haynes OM. Maternal responsiveness to young
children at three ages: longitudinal analysis of a multidimensional, modular, and specific parenting
construct. Developmental psychology. 2008;44(3):867–74. [PubMed: 18473650]
12. Johnson SB, Riley AW, Granger DA, Riis J. The science of early life toxic stress for pediatric
practice and advocacy. Pediatrics. 2013;131(2):319–27. [PubMed: 23339224]
13. Davidov M, Grusec JE. Untangling the links of parental responsiveness to distress and warmth to
child outcomes. Child development. 2006;77(1):44–58. [PubMed: 16460524]
14. Radesky JS, Kistin CJ, Zuckerman B, Nitzberg K, Gross J, Kaplan-Sanoff M, et al. Patterns of
mobile device use by caregivers and children during meals in fast food restaurants. Pediatrics.
2014;133(4):e843–9. [PubMed: 24616357]
15. Radesky J, Miller AL, Rosenblum KL, Appugliese D, Kaciroti N, Lumeng JC. Maternal mobile
device use during a structured parent-child interaction task. Academic pediatrics. 2015;15(2):238–
44. [PubMed: 25454369]
16. Hiniker A, Sobel K, Suh H, Sung Y-C, Lee CP, Kientz JA, editors. Texting while parenting: How
adults use mobile phones while caring for children at the playground. 33rd Annual ACM
Conference on Human Factors in Computing Systems; 2015: ACM.
17. McDaniel BT, Radesky JS. Technoference: Parent distraction with technology and associations
with child behavior problems. Child development. 2018;89(1):100–9. [PubMed: 28493400]
18. McDaniel BT, Coyne SM, Holmes EK. New mothers and media use: Associations between
blogging, social networking, and maternal well-being. Maternal and child health journal.
2012;16(7):1509–17. [PubMed: 22094592]
19. Sameroff A Transactional models in early social relations. Human development. 1975;18(1–2):65–
79.
20. McDaniel B Technoference”: Everyday intrusions and interruptions of technology in couple and
family relationships Family communication in the age of digital and social media New York: Peter
Lang Publishing Submitted: 9 2013.
21. Technoference: Parent Distraction with Technology and Associations with Child Behavior
Problems [Internet]. In press.
22. Achenbach TM, Rescorla LA. Manual for the ASEBA preschool forms & profiles: An integrated
system of multi-informant assessment; Child behavior checklist for ages 1 1/2–5; Language
development survey; Caregiver-teacher report form: University of Vermont; 2000.
23. Abidin RR. Parenting stress index Odessa, FL: Psychological Assessment Resources. Inc; 1995.
24. Feinberg ME, Brown LD, Kan ML. A multi-domain self-report measure of coparenting. Parenting.
2012;12(1):1–21. [PubMed: 23166477]
25. Murphy SE, Jacobvitz DB, Hazen NL. What’s so bad about competitive coparenting? Family-level
predictors of children’s externalizing symptoms. Journal of Child and Family Studies. 2016;25(5):
1684–90.
McDaniel and Radesky Page 11
Pediatr Res
. Author manuscript; available in PMC 2018 December 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
26. Radloff LS. The CES-D scale a self-report depression scale for research in the general population.
Applied psychological measurement. 1977;1(3):385–401.
27. McDaniel BT, Teti DM. Coparenting quality during the first three months after birth: the role of
infant sleep quality. Journal of Family Psychology. 2012;26(6):886. [PubMed: 23244456]
28. Radesky J, Christakis D, Hill D, Ameenuddin N, Chassiakos Y, Cross C, et al. Media and Young
Minds. Pediatrics 2016;138(5).
29. Arbuckle JL, Wothke W. Amos 4.0 user’s guide: SmallWaters Corporation Chicago, IL; 1999.
30. Buhi ER, Goodson P, Neilands TB. Structural equation modeling: a primer for health behavior
researchers. American journal of health behavior. 2007;31(1):74–85. [PubMed: 17181464]
31. Rosenblum KL, Dayton CJ, McDonough S. Communicating feelings: Links between mothers’
representations of their infants, parenting, and infant emotional development. 2006.
32. Radesky JS LC, Appugliese D, Miller AL, Lumeng JC, Rosenblum KL. Maternal mental
representations of the child and mobile phone use during parent-child mealtimes. Journal of
Developmental Behavioral Pediatrics. In press.
33. Uhls YT, Michikyan M, Morris J, Garcia D, Small GW, Zgourou E, et al. Five days at outdoor
education camp without screens improves preteen skills with nonverbal emotion cues. Computers
in Human Behavior. 2014;39:387–92.
34. Hiniker A, Patel SN, Kohno T, Kientz JA, editors. Why would you do that? predicting the uses and
gratifications behind smartphone-usage behaviors.2016 ACM International Joint Conference on
Pervasive and Ubiquitous Computing; 2016: ACM.
35. Bayer JB, Dal Cin S, Campbell SW, Panek E. Consciousness and SelfRegulation in Mobile
Communication. Human Communication Research. 2016;42(1):71–97.
36. Nakamura T The action of looking at a mobile phone display as nonverbal behavior/
communication: A theoretical perspective. Computers in Human Behavior. 2015;43:68–75.
37. Brand M, Young KS, Laier C. Prefrontal control and Internet addiction: a theoretical model and
review of neuropsychological and neuroimaging findings. Frontiers in human neuroscience.
2014;8:375. [PubMed: 24904393]
38. Bayer JB, Campbell SW. Texting while driving on automatic: Considering the frequency-
independent side of habit. Computers in Human Behavior. 2012;28(6):2083–90.
39. Hinkley T, Verbestel V, Ahrens W, Lissner L, Molnár D, Moreno LA, et al. Early childhood
electronic media use as a predictor of poorer well-being: a prospective cohort study. JAMA
pediatrics. 2014;168(5):485–92. [PubMed: 24639016]
40. Cheever NA, Rosen LD, Carrier LM, Chavez A. Out of sight is not out of mind: The impact of
restricting wireless mobile device use on anxiety levels among low, moderate and high users.
Computers in Human Behavior. 2014;37:290–7.
41. Chesley N Blurring boundaries? Linking technology use, spillover, individual distress, and family
satisfaction. Journal of Marriage and Family. 2005;67(5):1237–48.
42. Harris T How Technology is Hijacking Your Mind from a Magician and Google Design Ethicist
2016 Available from: https://journal.thriveglobal.com/how-technology-hijacks-peoples-minds-
from-a-magician-and-google-s-design-ethicist-56d62ef5edf3.
43. Van Deursen AJ, Bolle CL, Hegner SM, Kommers PA. Modeling habitual and addictive
smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress,
self-regulation, age, and gender. Computers in human behavior. 2015;45:411–20.
44. Hiniker A, Hong SR, Kohno T, Kientz JA, editors. MyTime: Designing and Evaluating an
Intervention for Smartphone Non-Use.2016 CHI Conference on Human Factors in Computing
Systems; 2016: ACM.
McDaniel and Radesky Page 12
Pediatr Res
. Author manuscript; available in PMC 2018 December 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Figure 1.
Structural equation model of longitudinal associations between parent-reported technology
interference in the parent-child relationship and child externalizing behavior, with parenting
stress as the mediator between externalizing behavior and later parent-child technology
interference. Standardized path estimates are displayed. Mothers’ and fathers’ estimates are
displayed as mother / father when found to be significantly different between mothers and
fathers; all other model paths were constrained to be equal between mothers and fathers.
Parent characteristics, child age, child screen use, parent depressive symptoms, and
coparenting quality were controlled but then removed as results did not change. ***p < .001,
**p < .01, *p < .05
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Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Figure 2.
Structural equation model of longitudinal associations between parent-reported technology
interference in the parent-child relationship and child internalizing behavior, with parenting
stress as the mediator between internalizing behavior and later parent-child technology
interference. Standardized path estimates are displayed. Mothers’ and fathers’ estimates are
displayed as mother / father when found to be significantly different between mothers and
fathers; all other model paths were constrained to be equal between mothers and fathers.
Parent characteristics, child age, child screen use, parent depressive symptoms, and
coparenting quality were controlled but then removed as results did not change. ***p < .001,
**p < .01, *p < .05, †p < .10.
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Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Figure 3.
Structural equation model of longitudinal associations between parent-reported technology
interference in the parent-child relationship and child withdrawal behavior, with parenting
stress as the mediator between withdrawal behavior and later parent-child technology
interference. Standardized path estimates are displayed. Mothers’ and fathers’ estimates are
displayed as mother / father when found to be significantly different between mothers and
fathers; all other model paths were constrained to be equal between mothers and fathers.
***p < .001, **p < .01, *p < .05, †p < .10.
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Author Manuscript Author Manuscript Author Manuscript Author Manuscript
McDaniel and Radesky Page 16
Table 1.
Descriptive Information on Parent-Reported Technoference, Child Behavior Ratings, and Other Study
Variables (Averaged Across All Time Points)
Mothers Fathers
Correlation Between
Mothers & Fathers
Diff. Between
Mothers &
Fathers
Mean (SD) Mean (SD) t-value
Technoference
0.44 (0.39) 0.38 (0.51) .51
***
1.88
Number of devices that interfere at least once per
day (n / %)
1.65 (0.98) 1.43 (1.15) .23
**
2.18
*
None 9 4.9% 17 9.6%
One 72 39.6% 84 47.5%
Two 69 37.9% 47 26.6%
Three or more 32 17.6% 29 16.4%
Child Behavior Ratings
Externalizing (CBCL; t-scored) 45.22 (9.97) 45.19 (10.52) .65
***
0.05
Internalizing (CBCL; t-scored) 41.08 (11.43) 40.58 (11.88) .61
***
0.64
Other Study Variables
Parenting Stress 1.96 (0.58) 1.95 (0.56) .55
***
0.29
Depressive Symptoms 10.84 (8.14) 9.91 (8.09) .34
***
1.33
Coparenting Quality 4.99 (0.75) 4.96 (0.72) .49
***
0.54
Note: The values in this table were calculated by averaging across all four time points, and all those who had at least one time point of child
behavior rating (CBCL) data were included. Differences between mothers and fathers were examined utilizing pairwise t-tests on 176 families.
*** p
< .001,
** p
< .01,
*p
< .05,
p
= .06.
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McDaniel and Radesky Page 17
Table 2.
Baseline Demographic Characteristics and Associations with Parent-Reported Technoference (Averaged
Across All Time Points)
Mothers Fathers
Technoference*Technoference*
n (n = 182) % Mean (SD) n (n = 177) % Mean (SD)
Parent Age (years)
<29 49 26.9% 0.60
a
b(0.57) 28 15.8% 0.46 (0.64)
29–34 89 48.9% 0.36
a
(0.28) 90 50.8% 0.41 (0.59)
>=35 44 24.2% 0.43b(0.29) 59 33.3% 0.29 (0.22)
Child Age (years)
<2 54 29.7% 0.46 (0.41) 52 29.4% 0.46 (0.69)
2–3 83 45.6% 0.42 (0.30) 77 43.5% 0.29 (0.24)
>=4 45 24.7% 0.48 (0.51) 48 27.1% 0.44 (0.59)
Child Media Use Frequency
<=3 62 34.0% 0.43 (0.28) 55 31.1% 0.26c(0.29)
4–7 70 38.5% 0.39 (0.28) 73 41.2% 0.34d(0.34)
>=8 50 27.5% 0.55 (0.58) 49 27.7% 0.57cd (0.80)
Race/Ethnicity
Nonwhite 13 7.1% 0.60 (0.71) 19 10.7% 0.52 (0.69)
White 169 92.9% 0.43 (0.36) 158 89.3% 0.36 (0.49)
Education
Some college or less 44 24.2% 0.42 (0.45) 57 32.2% 0.44 (0.67)
Bachelor’s degree or higher 138 75.8% 0.45 (0.37) 120 67.8% 0.35 (0.42)
Family Income
<$53,000 59 32.4% 0.47 (0.37) 57 32.2% 0.41 (0.65)
$53,000-$85,000 61 33.5% 0.41 (0.30) 59 33.3% 0.33 (0.31)
>$85,000 62 34.1% 0.46 (0.48) 61 34.5% 0.40 (0.53)
Note:
*
The technoference values in this table were calculated by averaging across all four time points, and all those who had at least one time point of
child behavior rating (CBCL) data were included.
a.
Superscripts represent significant differences at p < .05 between technoference levels marked by that specific letter (e.g., a, b, c, d, e) within
categories and within gender (not across gender).
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McDaniel and Radesky Page 18
Table 3.
Associations between Parent-Reported Technoference and Main Study Variables (Averaged Across All Time
Points)
Mothers Fathers
Technoference*Technoference*
n (n = 182) % Mean (SD) n (n = 177) % Mean (SD)
Externalizing (CBCL; t-scored)*
Low (<44) 91 50.0% 0.37
a
(0.26) 85 48.0% 0.30e(0.34)
High (>=44) 91 50.0% 0.52
a
(0.48) 92 52.0% 0.46e(0.62)
Internalizing (CBCL; t-scored)*
Low (<41) 92 50.5% 0.37b(0.24) 89 50.3% 0.31f(0.34)
High (>=41) 90 49.5% 0.52b(0.49) 88 49.7% 0.45f(0.64)
Parenting Stress*
Low (<2) 95 52.2% 0.38c(0.25) 95 53.7% 0.30g(0.30)
High (>=2) 87 47.8% 0.51c(0.49) 82 46.3% 0.47g(0.67)
Depressive Symptoms*
Low (<8.5) 89 48.9% 0.37d(0.25) 94 53.1% 0.32 (0.31)
High (>=8.5) 93 51.1% 0.51d(0.48) 83 46.9% 0.45 (0.67)
Coparenting Quality*
Low (<5) 79 43.4% 0.49 (0.51) 84 47.5% 0.49h(0.69)
High (>=5) 103 56.6% 0.41 (0.27) 93 52.5% 0.28h(0.24)
Note:
*
The values in this table were calculated by averaging across all four time points, and all those who had at least one time point of child behavior
rating (CBCL) data were included. Low/High values were split near the median across mothers and fathers.
a.
Superscripts represent significant differences at p < .05 between technoference levels within categories and within gender (not across gender).
Note that superscript
f
represents a
p
-value of .08.
Pediatr Res
. Author manuscript; available in PMC 2018 December 13.
... Such technology-based interruptions in parent-child interactions are associated with less than optimal patterns of cognitive and socioemotional development Radesky, 2018a, 2018b;Sundqvist et al., 2020;Wong et al., 2020). Recent studies show that parent-related factors such as depressive symptoms and parenting stress are related to the frequency of technology-based interruptions and parents' problematic use of mobile technology (e.g., feeling an urge to check their mobile phones; McDaniel and Radesky, 2018b;McDaniel, 2021;Newsham et al., 2020). It has been suggested that parents may turn to their mobile devices as a mechanism for coping with stress (Radesky et al., 2016;Torres et al., 2021;Wolfers, 2021). ...
... Higher stress associated with the demands of caring for one's children (i.e., parenting stress) is linked to more frequent interruptions in parent-child interactions due to the use of digital devices (McDaniel and Radesky, 2018b). A higher degree of parenting stress is also related to more problematic use of mobile devices by parents, as in finding it difficult to refrain from checking their devices for notifications (McDaniel, 2021). ...
... In addition to our main variables of interest, we measured the educational level of mothers and fathers, employment status of mothers, household income, household size, and mothers' level of perceived support from other people. These were some of the factors that have been found to be related to parental stress (e.g., Gyamfi et al., 2001;Saisto et al., 2008;Samuels-Dennis, 2006), parents' daily and problematic smartphone use (e.g., McDaniel and Radesky, 2018a;Wartella et al., 2013), and technology-based interruptions they experience with their children (e.g., McDaniel and Radesky, 2018b). Perceived social support was particularly an important measure considering our Turkish sample. ...
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A growing body of research indicates that parents’ smartphone use is associated with interruptions in parent–child interactions and lower levels of parental responsiveness, which may adversely affect children’s cognitive and socioemotional development. Studies suggest that parent–child interactions are more frequently interrupted by the use of screen-based devices if parents experience more stress specifically resulting from the demands of parenting, yet there are unexamined questions. Is parents’ general daily stress related to technology-based interruptions in parent–child interactions? If so, does parents’ use of mobile technology mediate this relationship? In this first study testing the mediating role of parental use of mobile phones between parental stress and technology-based interruptions in parent–child interactions, we collected data from 604 mothers of children younger than age six with an online survey. Results showed that controlling for child age, family income, mothers’ employment status, household size, and maternal and paternal education, more stressed mothers reported using their mobile phones more problematically (e.g., not being able to resist checking messages), which was linked to more frequent perceived interruptions in the interactions with their children. Our results suggest that using mobile phones may serve as an outlet for stressed parents and is related to disruptions in the flow of parent–child interactions.
... Thus, research is needed which provides a more differentiated One of the factors that seems to play a role in parental smartphone use is stress: In an interview study, parents reported both stress-reducing and stress-inducing effects of their smartphone use while parenting . Similarly, in a longitudinal study, McDaniel and Radesky (2018a) found that increased parenting stress predicted increased technological interference with parent-child interactions ("technoference") over time. These studies suggest that parents seem to use their smartphones to cope with stress. ...
... Two studies focus at least in part on parental coping with stress using mobile devices in everyday situations (McDaniel & Radesky, 2018a;. interviewed 35 caregivers about their perspectives on their smartphone use. ...
... Research on phone use while parenting has increased in recent years, leading to several review papers published in the last two years Hood et al., 2021;Knitter & Zemp, 2020;. The current research landscape of parental phone use includes a range of studies employing observations in public places Hiniker et al., 2015;, experiments in the laboratory (Konrad et al., 2021;Reed et al., 2017), and survey research (McDaniel & Radesky, 2018a, 2018bModecki et al., 2020). ...
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Being a parent of young children is associated with both joy and stress. High parental stress was shown to be associated with decreased parental wellbeing and negative child outcomes. Thus, it is important that parents successfully cope with stress. Research has shown that becoming a parent often results in constraints on time allocation and a perceived state of isolation, making it harder to cope with stress. Smartphones might be a useful tool for parental stress management. For most parents, smartphones are always and easily accessible. Moreover, smartphones can provide many resources such as social support and information and can be used for short periods. Accordingly, first studies show that parents often use their smartphones to cope with stress. However, parental smartphone use has been widely problematized in academic and public discussions because smartphones are said to distract parents from interacting with their children. Research on how parents use smartphones to their benefit is still limited. Moreover, we do not know yet whether and under what circumstances coping using smartphones effectively reduces parental stress. To fill this knowledge gap, I examined in my dissertation how mothers of young children use their smartphones for coping with stress and under what circumstances coping using smartphones is effective. As mothers are still the primary caregivers, my dissertation mainly focuses on mothers. In a first theoretical step, I conducted a systematic scoping review summarizing and integrating the previous literature on media use for coping. Many studies assessed how media are used for coping. However, the literature had not clearly identified where media have their place in stress management models. In the scoping review, I suggested placing media in the transactional model of stress and coping by differentiating between coping strategies, such as social support or distraction and coping tools, such as talking to a friend or using a smartphone. When confronted with a stressful encounter, individuals choose a combination of coping tools and coping strategies to cope with stress. The fit of this combination with the situational circumstances determines whether the coping efforts are successful. Based on this conceptualization, I conducted a qualitative focus groups study and a quantitative experience sampling study (ESS). In the focus group study, building on a synthesis of the literature on digital media use for parenting and smartphone use while parenting, I interviewed parents in a medium-sized city and a parent-child health retreat clinic about how they use their smartphones for stress management. In the ESS, I additionally drew on theoretical conceptualizations from mobile communication and digital wellbeing research. Over 200 mothers filled in four questionnaires a day for one week and answered questions about a stressful situation that had happened in the last two hours. Both studies showed that when mothers are in stressful situations with their children, they mainly use their phones to distract themselves from the stressful encounter and to find information and support. In the focus groups study, parents reported many instances in which they successfully used their phones for stress coping. In the ESS, mothers, however, experienced a smaller stress decrease in stressful situations in which they used their phone than in situations involving no phone use. Using positive phone content, though, was related to increased coping effectiveness. My dissertation also demonstrated that social norms around maternal smartphone use play an important role when mothers use their phones for coping with stress. To explore this, I suggested a social constructivist viewpoint on media use and media effects. This viewpoint posits that the perception of and feelings around ones own media use are just as important for media effects as characteristics of objectively measurable media use, such as usage time. Further, I argue that these media use perceptions are influenced by what others say about media use and are, thus, socially constructed. Confirming the value of this viewpoint, I show in the ESS that mothers who perceived stronger injunctive norms against parental phone use experienced increased guilt when they used their phone for stress coping. Feelings of guilt around phone use in turn were related to a diminished coping effectiveness. Overall, my dissertation shows that by using positive content, mothers can use their smartphones to their benefit when they are confronted with stressful situations. Negative social norms against parental smartphone use can, by inducing guilt, be associated with diminished coping effectiveness when mothers use their phone to cope with stress. Therefore, academic and public discussions around smartphone use should consider the benefits of smartphone use for parents so that a more nuanced debate does not lead to social pressure and feelings of guilt among parents.
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... Furthermore, as parents reported higher problematic use of technology (e.g., using devices too much, having trouble to suppress the urge to check their device), they also reported more interruptions in parent-child interactions due to technology (McDaniel & Radesky, 2018a). Parenting stress was another predictor of technological interruptions (McDaniel & Radesky, 2018b). To replicate and extend these previous findings, we collected data about parental stress, parental problematic use of mobile devices, and the frequency of interruptions in parent-child interactions. ...
Chapter
We investigated the use of screen media by Turkish children younger than age six and how this use relates to child-related (e.g., temperament), parent-related (e.g., parental stress), and home-related (e.g., family size) factors via an online survey for parents (N = 1214). Our results showed that children spent more time using screen media in more crowded homes and if their temperament was perceived as more difficult by their parents. Their screen time was also longer when their parents used more screen media, received less support from others, and had more positive attitudes towards technological devices. Furthermore, parental stress was related to parents’ problematic use of mobile devices, which led to more interruptions in parent-child interactions. Our findings suggest that factors related to parents and the home environment are closely linked to children’s screen media consumption.KeywordsScreen mediaMobile devicesSurveyEarly childhood
... In line with these findings, a recent study demonstrated that socioeconomical status accounted for almost half of the self-regulation and media exposure links [80]. Research indicates that another moderator of discussed associations may be parental strain that leads parents to use screen media when they feel overwhelmed and not capable of coping with children's difficulties themselves [80][81][82]. However, scholars report that using media devices as a tool to regulate children's emotionality and behavior may in fact lead to increases in negative emotionality, creating a vicious circle of inadequate parental interventions and augmenting self-regulatory problems. ...
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Screen media are ubiquitous in human life across all age, cultural and socioeconomic groups. The ceaseless and dynamic growth of technological possibilities has given rise to questions regarding their effect on the well-being of children. Research in this area largely consists of cross-sectional studies; experimental and randomized studies are rare, which makes drawing causative conclusions difficult. However, the prevailing approach towards the use of screen media by children has focused on time limitations. The emerging evidence supports a more nuanced perspective. It appears that the older the child, the more important how the screen media are used becomes. Concentrating on the quality of the screen, time has become increasingly relevant in the recent COVID-19 pandemic, which necessitated a transfer of educational and social functioning from real-life to the digital world. With this review, we aimed at gathering current knowledge on the correlations of different screen media use and development outcomes, as well as providing an overview of potential benefits that new technologies may provide to the pediatric population. To summarize, if one cannot evade screen time in children, how can we use it for children’s maximum advantage?
... Realmente com esses dados não espanta que o estudo durante a pandemia COVID-19 encontrou uma incidência grande de transtornos mentais comuns (75%) e um relato percebido de estresse em 94% dos participantes. Se ainda antes da pandemia, um estudo longitudinal recente havia indicado uma associação bidirecional importante entre comportamentos externalizantes dos filhos, estresse parental e uso de telas na primeira infância (4) , avaliar a saúde mental pode ser crucial no oferecimento de telas na primeira infância. ...
... Adolescents with low self-esteem may cause more parenting stresses, thereby leading parents to pay attention to their smartphones. This view has been roughly supported by two studies, which show that parents escape from parenting stresses or seek social support using technology devices when children exhibit internalizing and externalizing behavior problems (McDaniel & Radesky, 2018a;2018b). Based on theories and previous cross-sectional studies, the present study used a crosslagged model to explore the bidirectional associations between parental phubbing and self-esteem among Chinese adolescents. ...
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Parental phubbing refers to a phenomenon in which parents are distracted by their smartphones when they interact with their children. It has become a common concern and linked to adolescents' internalizing and externalizing behavior problems. However, much remains unclear about reciprocal associations among parental phubbing, self-esteem, and suicidal ideation and the potential mechanisms underlying these associations. To address these gaps, the current study tested bidirectional relationships among parental phubbing, self-esteem, and suicidal ideation, as well as the mediating role of self-esteem. In addition, the present study examined whether these relationships varied by extraversion, gender, and perceived economic stress across three time points using a cross-lagged design. A total of 2407 Chinese adolescents (50.23% girls, Mage = 12.75, SD = 0.58 at baseline) participated in the study. The results showed that parental phubbing was associated with self-esteem as well as with suicidal ideation, and there were bidirectional relationships between self-esteem and suicidal ideation. Self-esteem significantly mediated the association between parental phubbing and suicidal ideation. Extraversion moderated the link between parental phubbing and suicidal ideation as well as self-esteem and suicidal ideation during the first year. Gender and perceived economic stress did not play a moderating role. The results indicate that parental phubbing is a new risk factor for adolescents' suicidal ideation. Parents concerned about adolescents' self-esteem and suicidal ideation should focus on minimizing the frequency of smartphone use and teach adolescents some social skills to seek more sources of social support.
Chapter
This chapter reviews research that describes the prevalence and potential impacts of technoference within family contexts. A focus is placed on the potential of parent mobile device use to interfere with responsive feeding and decrease the quality of parent-child feeding interactions during infancy. Recommendations are provided for how to help parents and caregivers balance the benefits they glean from technology with their children’s needs for sensitive, responsive, and engaged caregivers.
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The use of technology disrupts interpersonal communication and interaction and interferes with the communication process. One of the social areas where this is visible is communication between couples. For this reason, it is important to learn the positive or negative characteristics of the use of technological tools in the communication processes, relationship satisfaction and conflict situations of married couples with different age groups and different demographic characteristics, and the effects of technology use on their relationships. In this sense, to determine these effects, the research was carried out with the participation of 264 married people of different ages and demographic characteristics in the province of Istanbul. Technoference scale, relationship satisfaction scale, and romantic patrner conflict scale were used as data collection tools in the research. As a result of the analysis of the research data, it is observed that, in general, as people’s use of technology and the effect of technoference in the relationship increase, there is a decrease in people’s relationship satisfaction, and accordingly, indirect married couple conflicts in technology use also increase. In addition, married couples’ use of technology, relationship satisfaction, and attitudes towards conflict differ according to gender, age, education, and income level.
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Heavy parent digital technology use has been associated with suboptimal parent-child interactions, but no studies examine associations with child behavior. This study investigates whether parental problematic technology use is associated with technology-based interruptions in parent-child interactions, termed "technoference," and whether technoference is associated with child behavior problems. Parent reports from 170 U.S. families (child Mage = 3.04 years) and actor-partner interdependence modeling showed that maternal and paternal problematic digital technology use predicted greater technoference in mother-child and father-child interactions; then, maternal technoference predicted both mothers' and fathers' reports of child externalizing and internalizing behaviors. Results suggest that technological interruptions are associated with child problem behaviors, but directionality and transactional processes should be examined in future longitudinal studies.
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Technology devices and their characteristics have become more pervasive and enticing. The use of these new devices is common, and interruptions due to these devices are likely. This study examines the frequency of technology interference in (a) coparenting relationships—the relationship between parents as they parent their children together—during early infancy/childhood and in (b) various parenting domains (bedtime, mealtime, etc.), as well as (c) associations between technology interference and perceptions of coparenting quality as reported by 203 married/cohabiting mothers. Many mothers perceived that technology interrupted coparenting interactions on occasion, especially during unstructured parenting such as playtime. Mothers rating more interference reported worse coparenting, relationship satisfaction, and depressive symptoms. Technology interference predicted coparenting even after controlling for relationship satisfaction and depressive symptoms. Technology interference likely decreases coordination between parents, leaving some mothers feeling frustrated. Parents may be advised to critically examine and potentially regulate technology use during family interactions.
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Child development research suggests that using phones while caring for children can be problematic, but limited prior work in this space makes defining appropriate use challenging. We conducted the first exploration of whether adults feel pressure to limit phone use in this context and whether they choose to do so. Through mixed methods, we collected data from 466 adult caregivers at playgrounds. We found that phone use was a small part of playground time, yet a notable source of guilt. Adults engaged in systematic and specific phone-use and phone-non-use behaviors in order to prioritize their children above themselves. Our results indicate that caregiver values and self-control together predict behavior and can be used to model phone use in this context. Users' mixed success with engaging in intentional periods of non-use suggests that a design agenda which prioritizes cycles of engagement, disengagement, and re-engagement may be of value to this group.
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Technology devices are widely used today, creating opportunities to connect and communicate with distant others while also potentially disrupting communication and interactions between those who are physically present (i.e., technoference or phubbing). These disruptions in couple and coparenting relationships have the potential to negatively impact relationship outcomes. In this two-part study of 182 married/cohabiting couples from the Daily Family Life Project and 239 couples from the Couple Well-Being Project, we examined the role of technoference in couple and coparenting relationship quality and potential gender differences utilizing dyadic data. We found that greater technoference related to greater conflict over technology use, and greater conflict predicted lower relationship satisfaction and poorer perceptions of coparenting quality (Study 1). Using a more diverse sample (Study 2), we again found support for the main pathways tested in our first study, suggesting that results found in Study 1 and in previous work are not artifacts of sampling. As satisfaction, support, and agreement among relationship partners and parents are often critical to relationship health and family cohesion, it is important for couples and families to evaluate, monitor, and be willing to adapt their technology usage patterns so that these patterns do not cause conflict and possibly relationship deterioration over time.
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Infants, toddlers, and preschoolers are now growing up in environments saturated with a variety of traditional and new technologies, which they are adopting at increasing rates. Although there has been much hope for the educational potential of interactive media for young children, accompanied by fears about their overuse during this crucial period of rapid brain development, research in this area still remains limited. This policy statement reviews the existing literature on television, videos, and mobile/interactive technologies; their potential for educational benefit; and related health concerns for young children (0 to 5 years of age). The statement also highlights areas in which pediatric providers can offer specific guidance to families in managing their young children's media use, not only in terms of content or time limits, but also emphasizing the importance of parent-child shared media use and allowing the child time to take part in other developmentally healthy activities.
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Objective: Parent use of mobile devices (e.g., smartphones, tablets) while around their young children may be associated with fewer or more negative parent-child interactions, but parent perspectives regarding this issue have not been explored. We aimed to understand parent views regarding their mobile device use to identify actionable targets of potential intervention. Method: We conducted 35 in-depth semi-structured group and individual interviews with English-speaking caregivers of children 0 to 8 years old, purposively sampled from diverse ethnic backgrounds, educational levels, and employment statuses. Following thematic saturation, results were validated through expert triangulation and member checking. Results: Participants included 22 mothers, 9 fathers, and 4 grandmothers; 31% were single parents, 43% nonwhite race/ethnicity, and 40% completed high school or less. Participants consistently expressed a high degree of internal tension regarding their own mobile technology use, which centered around 3 themes relevant to intervention planning: (1) Cognitive tensions (multitasking between work and children, leading to information/role overload), (2) emotional tensions (stress-inducing and reducing effects), and (3) tensions around the parent-child dyad (disrupting family routines vs serving as a tool to keep the peace). Conclusion: Caregivers of young children describe many internal conflicts regarding their use of mobile technology, which may be windows for intervention. Helping caregivers understand such emotional and cognitive responses may help them balance family time with technology-based demands.
Conference Paper
Mobile devices have begun to raise questions around the potential for overuse when in the presence of family or friends. As such, we conducted a diary and interview study to understand how people use mobile devices in the presence of others at home, and how this shapes their behavior and household dynamics. Results show that family members become frustrated when others do non-urgent activities on their phones in the presence of others. Yet people often guess at what others are doing because of the personal nature of mobile devices. In some cases, people developed strategies to provide a greater sense of activity awareness to combat the problem. Mobile phone usage was sometimes perceived as beneficial by providing a mechanism for needed disengagement from family members. These findings suggest several opportunities for redesigning mobile device software to mitigate emergent frustrations, and open up new opportunities for nurturing social interactions among family members.