ArticlePDF Available

Technoference: Parent Distraction With Technology and Associations With Child Behavior Problems


Abstract and Figures

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.
Content may be subject to copyright.
Technoference: Parent Distraction with Technology and Associations with
Child Behavior Problems
This is the author version of the following article: McDaniel, B. T., & Radesky, J. (2017). Technoference:
Parent distraction by technology and associations with child behavior problems. Child Development.,
which has been published in final form at
This article may be used for non-commercial purposes in accordance with the Wiley Self-Archiving Policy
[ ].
Brandon T. McDaniel, Ph.D.a
Jenny S. Radesky, MDb
a Illinois State University; Department of Family and Consumer Sciences; Normal, IL.
b Division of Developmental Behavioral Pediatrics, University of Michigan Medical School,
Ann Arbor, MI
Corresponding Author: Brandon T. McDaniel, Department of Family and Consumer Sciences;
Campus Box 5060, Normal, IL. Email: Phone: 309-438-5802.
We would like to thank the families who participated in this research, as well as the research
assistants who made all of this recruitment and data collection possible. We would also like to
acknowledge the College of Health and Human Development, the Department of Human
Development and Family Studies, as well as the Bennett Pierce Prevention Research Center at
The Pennsylvania State University which awarded research funds to the first author to complete
this research. This research was also supported by the National Institute on Drug Abuse
(T32DA017629) and the National Institute of Child Health and Human Development
(F31HD084118). The content is solely the responsibility of the authors and does not necessarily
represent the official views of the National Institutes of Health.
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. Using parent reports from 170 U.S. families (child mean age = 3.04
years) and Actor Partner Interdependence Modeling, we found 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.
Keywords: Parent media use; digital technology; smartphones; child behavior; parent-child
relationship; problematic phone use; parenting
Technoference: Parent Distraction with Technology and Associations with
Child Behavior Problems
Emerging mobile and digital technologies such as smartphones, tablets, wearables, and
other mobile devices are now embedded throughout the daily lives of young children and their
families, with research evidence on their use and effects lagging behind their rate of adoption
(Radesky, Schumacher, & Zuckerman, 2015b). These multimodal devices, with their access to
unlimited Internet content, social contacts, work duties, information, and personal data, have
revolutionized the ways in which people interact with digital technology and with each other
(Katz, 2002; Campbell, Ling, & Bayer, 2014).
Despite the significant benefits that individuals reap from their use of technology, such as
increased social support (McDaniel, Coyne, & Holmes, 2012) and the ability to work from home
(Chesley, Slibak, & Wajcman, 2013), sociological and psychological research has highlighted
the potential for disruption of in-person social dynamics when mobile and digital technologies
are in use. This was initially described as ‘absent presence,’ or the act of being physically
present but having one’s mind elsewhere based on communication or content from mobile
phones (Gergen, 2002), followed by descriptions of new social norms allowing invasion of
portable devices into personal spaces (Ito, Okabe, & Matsuda, 2005; Campbell & Park, 2008).
More recently, the concept of ‘technoference,’ defined as everyday interruptions in interpersonal
interactions or time spent together that occur due to digital and mobile technology devices, has
been introduced (McDaniel, 2015; McDaniel & Coyne, 2016a). Such interruptions may occur
during face-to-face conversations, routines such as mealtimes or play, or the perception of an
intrusion felt by an individual when another person interacts with digital technology during time
together. In adult romantic relationships, technoference has been associated with more conflict
with one’s partner over technology use and poorer relationship satisfaction (McDaniel & Coyne,
2016a) as well as more negative perceptions of coparenting quality (McDaniel & Coyne, 2016b).
In a separate line of investigation, overuse of technology has been studied in terms of
Internet addiction and self-reported problematic mobile phone use behaviors (e.g., having
difficulty disconnecting, ruminating about possible messages received, etc.); both are associated
with mental health problems such as depression, anxiety, and social difficulties (e.g., Bianchi &
Phillips, 2005). Psychological correlates of problematic mobile technology use have included
anxious dependence in relationships (Cheever, Rosen, Carrier, & Chavez, 2014), poorer self-
regulation abilities and lower degree of mindfulness (Feldman, Greeson, Renna, & Robbins-
Monteith, 2011), susceptibility to the unconscious automaticity of mobile phone checking (Bayer
& Campbell, 2012; Drouin, Kaiser, & Miller, 2012), or perceiving social norms of needing to
answer calls or texts (Rainie & Keeter, 2006). However, none of these studies have specifically
examined these dynamics in the context of parenting.
In an attempt to define what constitutes ‘problematic’ media use for parents, several
studies have examined how parent digital technology use associates with quality and quantity of
parent-child interactions. Adding to a literature showing interruption of parent-child play by
background television (Kirkorian, Pempek, Murphy, Schmidt, & Anderson, 2009), recent studies
have suggested that parent mobile technology use around children is associated with fewer
parent-child interactions (Radesky, Miller, Rosenblum, Appugliese, Kaciroti, & Lumeng,
2015a), lower responsivity to child bids (Hiniker, Sobel, Suh, Sung, Lee, & Kientz, 2015), and
qualitative observations of parent hostility in response to child bids for attention (Radesky,
Kistin, Zuckerman, Nitzberg, Gross, Kaplan-Sanoff, Augustyn, & Silverstein, 2014).
Additionally, technological interruption during parenting has been associated with mothers'
perceptions of lower coparenting quality (McDaniel & Coyne, 2016b). In interviews, children
describe feeling that parents should not use digital technology during family routines because of
their expectation that the parent be present and model good digital technology habits (Hiniker,
Shoenebeck, & Kientz, 2016). Parents echo this experience of discomfort with ‘absent presence’
when using digital technology around their children, describing it as “multitasking” that makes
them feel less effective in their parenting (Radesky et al., 2016).
However, this emerging literature on parent digital technology use and parent-child
relationships is limited by small sample sizes, assessment of parent digital technology use only
during brief episodes such as meals or playground visits, and none have specifically examined
child behavioral outcomes. Because of the hypothesized potential for technology to alter
parenting responsiveness, which is an important predictor of positive child social-emotional
outcomes (see Bornstein, Tamis-Lemonda, Hahn, & Haynes, 2008; Davidov & Grusec, 2006),
more research on parent digital technology use and child behavior is needed. The aim of the
present study was to examine cross-sectional associations between problematic parent digital
technology use (e.g., having trouble resisting the urge to check the device, using the device too
much, etc.), technoference (i.e., technology interference) in parent-child interactions, and child
behavior. We hypothesized that greater self-reported problematic digital technology use would
be associated with more frequent technoference in daily parent-child interactions (H1); and
greater reported technoference in daily parent-child interactions would be associated with greater
child externalizing and internalizing behavior (H2), as has been described in prior ethnographic
work (Radesky et al., 2014).
Participants & Procedure
Participants included mothers and fathers from 183 heterosexual couples with a young
child who took part in the Daily Family Life Project (McDaniel, 2016), a longitudinal study of
parenting and family relationships conducted from 2014 to 2016. Participants were recruited
through: (1) letters and phone calls to families who were part of a family research database in a
Northeastern U.S. state, (2) announcements on parenting websites and listservs, and (3) flyers in
the local community. To be eligible to participate, individuals had to speak English, be over age
18, be a parent of a child age 5 or younger, and currently live with their spouse/partner and child.
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 also completed follow-up assessments at approximately 1, 3, and 6 months. At
baseline, 98% (n = 360) of parents completed their survey.
In the present study, we utilized the baseline survey data of 333 of these 360 parents (168
mothers and 165 fathers from 170 families) who had completed child behavior rating scales; 11
families (n = 22 parents) who had a child younger than 1 year were excluded from the present
analysis, since the behavior rating items were not appropriate for infants. In addition, 3 mothers
and 3 fathers were missing behavior ratings, and 1 mother and 4 fathers did not respond to their
surveys and thus provided no baseline data at all. In our analytic sample of 333 parents, families
resided in the following U.S. regions: 53% Northeast, 16% Midwest, 16% South, and 15% West.
On average, mothers were 31.82 years old (SD = 4.22; range 22 to 42), and fathers were 33.34
(SD = 4.93; range 22 to 52). Most families (61%) had more than one child (M = 1.90, SD =
0.91), and the index child was 3.04 years old on average (SD = 1.24; Range = 1.0 to 5.5 years;
55% female). Most parents were Caucasian (92%), married (95%), and had at least a Bachelor’s
degree (73%). Median yearly household income was approximately $69,500 (M = $75,360, SD
= $39,320), but ranged from no income to $250,000, with 20% of families reporting some form
of state or federal assistance (e.g., medical assistance, food stamps). Average relationship length
was 10.13 years (SD = 4.02), with 93% in a relationship of 5 years or longer.
Utilizing chi-squares and t-tests to examine potential demographic differences between
our analytic sample and those not in our analyses due to having a child under age 1 or who were
missing behavioral rating data, we found that parents in our sample were on average older (t
(360) = 2.18, p = .03), in a longer relationship (t (360) = 2.61, p = .009), and had more children (t
(360) = 3.63, p < .001); the samples were otherwise similar.
Parent problematic digital technology use. We assessed parent problematic digital
technology use using a 3-item self-report scale adapted from prior studies of problematic mobile
phone use (e.g., Derks & Bakker, 2014): (1) “When my mobile phone alerts me to indicate new
messages, I cannot resist checking them.” (2) “I often think about calls or messages I might
receive on my mobile phone. (3) I feel like I use my mobile phone too much. Parents
responded on a 6-point scale ranging from 1 (strongly disagree) to 6 (strongly agree). Items
were averaged to produce an overall score (for mothers, M = 3.24, SD = 1.18; for fathers, M =
2.87, SD = 1.17) with higher scores indicating more problematic use (Cronbach's alpha = .74 for
mothers, .78 for fathers).
Technoference in parent-child relationships. Perceived technoference (i.e., technology
interference) in the mother-child relationship and in the father-child relationship was assessed via
mother and father self-report. Items were adapted from the Technology Device Interference
Scale (TDIS; McDaniel & Coyne, 2016a), which originally measured technoference in couple
relationships; for this study, we reworded the scale to refer to interactions with one's child.
Parents were asked, "On a typical day, about how many times do the following devices interrupt
a conversation or activity you are engaged in with your child?" The 6 items on the scale included
the following devices: (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 across these various devices
(i.e., some devices might interfere more than others), it was not appropriate to calculate
Cronbach's alpha. Items were averaged, with higher scores representing more frequent
technoference in the parent-child relationship; raw mean scores are reported in Table 1. We also
found that participants' scores were positively skewed (skewness values for the overall mean
score were 2.38 for mothers and 3.46 for fathers); therefore, we performed a square root
transformation on the overall mean scores, which resulted in scores that were more normally
distributed and more appropriate for analysis (skewness = -0.04 for mothers, 0.57 for fathers).
Child externalizing and internalizing behavior problems. Parents completed the
items that make up the internalizing (36 items) and externalizing scales (24 items) of the Child
Behavioral Checklist (CBCL; Achenbach & Rescorla, 2000). These items concern their child
now or within the past two months on a 3-point scale ranging from 0 (not true, as far as you
know) 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 alpha for internalizing = .90 for mothers, .88 for fathers; alpha for
externalizing = .92 for mothers, .93 for fathers). We then converted these raw sum scores to
normed externalizing and internalizing t-scores for analysis (Achenbach & Rescorla, 2000).
Potential confounding variables. Parents reported their age, educational attainment,
marital status, race/ethnicity, family composition, household income, and child’s age, gender,
and health at baseline. They also reported their child’s daily duration of screen media use, as
well as measures of coparenting quality, depressive symptoms, and parenting stress.
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 = .77 for mothers, .76 for fathers).
As this sample consists of two-parent families, we controlled for coparenting qualityor
how well parents work together in rearing their child as a parenting team (e.g., Feinberg et al.,
2012). Coparenting quality has been shown to predict child behavior problems (e.g., Murphy,
Jacobvitz, & Hazen, 2015); therefore, controlling for the potential influences of coparenting
lends further weight to any potential associations we may find between technoference and child
behavior. We assessed coparenting quality with an established measure, the Coparenting
Relationship Scale (CRS; Feinberg et al., 2012) which consists of 35 items (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") that assess various dimensions of coparenting such as support, undermining, and
agreement on a 7-point scale ranging from 0 (not true of us) to 6 (very true of us). After reverse
coding negatively worded items, all items were averaged to produce an overall coparenting score
with higher scores indicating parent perceptions of higher quality coparenting (Cronbach's alpha
= .94 for mothers, .93 for fathers).
Depressive symptoms were measured utilizing the validated Center for Epidemiologic
Studies Depression Scale (CES-D; Radloff, 1977). 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 = .90 for mothers,
.80 for fathers). We controlled for depressive symptoms as depressed mood has been associated
with quality of parent-child interactions (e.g., Elliston et al., 2008; McDaniel & Teti, 2012) and
greater technoference in couple relationships (McDaniel & Coyne, 2016a).
Finally, we also controlled for parenting stress which we measured using 27 items from
the Parenting Stress Index (PSI; Abidin, 1995). Following other scholars in the field (e.g.,
Feinberg et al., 2010; Leavitt et al., 2016; Maas et al., 2015), we chose to use 27 items from the
36-item PSI Short Form due to lower factor loadings on 9 of the items, as was found by Abidin
(1995). Items were averaged to produce an overall stress score (Cronbach's alpha = .90 for
mothers, .92 for fathers). Parenting stressors are common in parents with young children (Crnic
& Low, 2002) and often predict poor family functioning (Cummings & Davies, 1994; Gelfand,
Teti, & Radin Fox, 1992). Feeling stressed could hypothetically lead parents to use digital
technology devices as a potential means of escape (Radesky et al., 2016) as well as to allow
children to more frequently use digital technology (Pempek & McDaniel, 2016).
Data Analysis
We first examined the associations between our study variables using bivariate
correlations in SPSS. Then, using Actor Partner Interdependence Modeling (APIM; Kenny,
Kashy, & Cook, 2006), we tested a structural equation model (SEM) of (H1) mother and father
problematic digital technology use predicting technoference in mother-child and father-child
interactions, which (H2) technoference then predicted mother and father reports of child
behavior problems. One model was tested for externalizing behavior, and one model was tested
for internalizing behavior (Figures 1 and 2). The models were tested utilizing AMOS (Arbuckle
& Wothke, 1999), and both mother and father variables were entered. Standardized estimates
are shown for the models in Figures 1 and 2. Mother and father ratings of parenting stress and
coparenting quality were also controlled in the models. Other potential confounders including
depressive symptoms, family income, parent education, marital status, race/ethnicity, child age,
child gender, child health status, and child screen use were also entered, but were removed from
the final models as results did not change significantly. Any missing data were handled using
full information maximum likelihood estimation. As access to and use of digital technology by
adults and children varies by child age and family socioeconomic status (e.g., Wartella et al.,
2013), we also examined potential moderation of path estimates in our final models by child age,
parent education, and family income.
Descriptive data and bivariate correlations for study variables are presented in Table 1.
On average, mothers and fathers perceived about 2 devices as interfering in their interactions
with their child at least once or more on a typical day, and only 11% of participants reported that
technoference did not occur. Furthermore, 17% of participants reported that technoference
occurred 1 time, 24% reported 2 times, and 48% reported 3 or more times on a typical day. On
average, 40% of mothers and 32% of fathers stated that they used digital technology (specifically
their mobile phone) in problematic ways (score of 3.5 or higher). Mothers perceived their phone
use as more problematic than fathers perceived their own use (t (162) = 3.15, p < .01). No
significant mean differences were found between mothers and fathers on other study variables. In
our sample, 4% of parents’ ratings of children met or exceeded the clinical cut-off (t-score of 70
or above; Achenbach & Rescorla, 2000) for externalizing behavior and 3% for internalizing
As expected, parent problematic digital technology use and technoference were
correlated (see Table 1). Additionally, in fathers, higher perceived problematic digital
technology use was associated with greater internalizing behavior, higher income, more child
screen time, and greater parenting stress; however, mothers’ problematic digital technology use
was not associated with any other variables besides technoference. In both mothers and fathers,
technoference in parent-child activities was associated with greater internalizing behavior and
more child screen time. Furthermore, technoference in parent-child activities was associated with
greater externalizing behavior as reported by mothers and worse perceptions of coparenting,
depressive symptoms, and parenting stress as reported by fathers.
The model predicting child externalizing behavior with technoference and parent
problematic digital technology use fit the data well (χ² (18) = 15.83, ns; RMSEA = .00; CFI =
.99) as did the model for internalizing behavior (χ² (18) = 11.74, ns; RMSEA = .00 CFI = .99).
As hypothesized (H1), greater mother and father problematic digital technology use significantly
predicted their perceptions of greater technoference in their own interactions with their child (for
mothers, β = .35, p < .001; for fathers, β = .39, p < .001). We also found support for hypothesis
2 in that greater technoference in the mother-child relationship significantly predicted greater
child externalizing behavior as reported by both mothers (β = .20, p < .001) and fathers (at the
trend level, β = .12, p = .06). Unexpectedly, technoference in the father-child relationship did
not predict greater externalizing behavior. Similar results also appeared for internalizing
behavior, adding further support for our hypothesis 2: Greater technoference in the mother-child
relationship significantly predicted greater child internalizing behavior as reported by both
mothers (β = .16, p < .01) and fathers (β = .14, p < .05), but again technoference in the father-
child relationship did not predict internalizing behavior.
We also examined whether the model results held when utilizing only mobile
technoference (e.g., phones, tablets, iPods) as opposed to all of the technoference items. After
entering the mobile technoference variable in the models in the place of overall technoference,
the models still fit the data well for externalizing (χ² (18) = 14.96, ns; RMSEA = .00; CFI = .99)
and internalizing (χ² (18) = 10.72, ns; RMSEA = .00; CFI = .99), and our results remained
significant. In other words, greater mother and father problematic mobile technology use
significantly predicted their perceptions of greater mobile technoference in their own interactions
with their child (for mothers, β = .34, p < .001; for fathers, β = .49, p < .001). Moreover, greater
mobile technoference in the mother-child relationship significantly predicted greater child
externalizing behavior as reported by both mothers (β = .17, p < .01) and fathers (β = .13, p =
.04) and significantly predicted greater child internalizing behavior as reported by both mothers
(β = .18, p < .01) and fathers (β = .17, p < .01).
To explore potential differences in the strength of these associations by child age, parent
education, and family income, we utilized a multigroup structural equation modeling approach in
AMOS. In this approach, the model fit is compared between a model where all paths are allowed
to vary freely across groups and a model where all paths are constrained to be equal across
groups. If a significant difference is found in the model fit, this suggests that differences exist in
some of the path estimates between the groups. We split our moderator variables into groups as
follows: child age (1 = age 3 and up, 0 = younger than 3), parent education (1 = Bachelor’s
degree or higher, 0 = less than a Bachelor’s degree), and family income (1 = higher than
$69,500, 0 = less than or equal to $69,500; family income was split at the median).
No differences were found in model fit for child age or father education. However, the
externalizing model with estimates constrained to be equal across groups showed worse fit with
mother education (Δχ² (19) = 35.93, p = .01) and family income (Δχ² (19) = 38.10, p < .01). The
same occurred for the internalizing model with mother education (Δχ² (19) = 35.41, p = .01) and
family income (Δχ² (19) = 37.83, p < .01). In terms of moderation of main model paths, the
association between fathers’ ratings of technoference and fathers’ ratings of externalizing child
behavior was stronger in families with lower maternal education (z = -1.98, p < .05), although
the path was not significant in either group. In terms of family income, the association between
mothers’ ratings of technoference and mothers’ ratings of externalizing behavior was stronger in
families with higher income (β = .33, p < .001) as compared to those with lower income (β = .03,
p = .78; z = 2.42, p < .05). No other significant differences emerged in our main model paths.
Our study is the first to show significant associations between parent self-perceptions of
problematic digital technology use, perceived technoference in parenting, and reported child
behavioral difficulties. Perceived technoference in mother-child interactions was associated with
externalizing and internalizing behavior as rated by both mothers and fathers. The fact that
technoference in mother-child interactions also related to fathers' reports of child behavior lends
further weight to the current results, as this indicates that the results are not likely due to single
reporter bias.
Surprisingly, technoference in father-child interactions was not associated with reports of
externalizing or internalizing behavior by either parent. This discrepancy between findings
related to maternal versus paternal digital technology use is interesting and could be explained by
several mechanisms. First, fathers may be less reliable reporters of their own digital technology
use during parent-child activities; however we believe this is less likely given that fathers’ self-
reported problematic digital technology use was significantly correlated with their reports of
technoference. Another explanation is that children co-regulate their emotions and behavior
differently with their mothers and fathers (Lunkenheimer, Olson, Hollenstein, Sameroff, &
Winter, 2011), and thus may have differential reactions to changes in maternal versus paternal
responsiveness. It is also possible that children simply spent more time with their mothers on a
daily basis in our sample, so there were a greater number of opportunities for technoference in
mother-child activities as compared with fathers. In this study sample, 45% of mothers worked
30 hours or more per week versus 82% of fathers; therefore fathers may have taken part in fewer
activities with their children overall as compared with mothers.
As this is a cross-sectional analysis, it is important not to assume directionality between
technoference and externalizing or internalizing child behavior. In recent in-depth interviews,
parents reported having more difficulty multitasking between children and their mobile device,
making it more difficult to read and respond to child cues and effectively manage difficult child
behavior (Radesky et al., 2016). This concept is supported by naturalistic mealtime observations
of children escalating their behavior in order to get the attention of their mobile-device using
caregivers, who then sometimes responded with anger or frustration (Radesky et al., 2014). An
alternative explanation for our findings is that mothers who perceive their children as more
behaviorally dysregulated may use digital technology during parent-child activities as a means of
withdrawal (Nakamura, 2015), taking a break from difficult social interactions so that they can
lower their stress levels. 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 (Radesky et al., 2016). However, it is important to note that our
current results remained significant after controlling for parent depression or stress levels.
It is also possible that greater parent digital technology use is a marker of other parent or
household characteristics that independently predict digital technology use and child behavioral
problems, such as greater family dysfunction (Hinkley, Verbestel, Ahrens, et al., 2014). To
account for this we adjusted for numerous other household characteristics and coparenting
quality, and again our results remained. Nonetheless, it is possible that problematic digital
technology use is a marker of an unmeasured parent characteristic such as anxiety (e.g., Cheever,
Rosen, Carrier, & Chavez, 2014) or emotion regulation difficulties (e.g., Feldman et al., 2011).
As parent and child digital technology use differ depending on child age and family
socioeconomic factors (e.g., Wartella et al., 2013), we explored whether the strength of the
associations in our model would differ depending on such factors. Of particular note, mothers’
ratings of technoference in higher income households (as compared with those in lower income
households) were linked more strongly with mothers’ ratings of externalizing behavior. This
difference was not due to higher income families having access to a greater number of devices;
in post-hoc analyses we found no significant difference by family income in the number of
devices in the home, technoference, problematic digital technology use, or child externalizing
behavior. It is possible that the variance in child externalizing behavior in low-income
households is driven by other factors, such as stressful life events. We suggest that further
research is needed with larger, more diverse samples to better understand the potential
differences in these associations by income and other factors.
It is perhaps premature to draw implications from this study for clinical practice, but our
findings contribute to a growing literature showing associations between greater digital
technology use and potential relationship dysfunction (e.g., McDaniel & Coyne, 2016a;
McDaniel & Coyne, 2016b) or changes in interpersonal interactions (Przybylski & Weinstein,
2013). Although some professional societies such as Zero To Three and the American Academy
of Pediatrics now recommend “unplugged” family time, it has not yet been tested whether
manipulating digital technology use during parent-child activities leads to improvements in child
A primary limitation of this study was the use of parent self-reports of digital technology
use and child behavior; objective assessments of child behavior and parent/child digital
technology use would reassure us that observed associations are not due to reporter bias.
However, self-report methods allow examination of this topic in larger sample sizes and from
both parents, which were limitations of prior studies. Moreover, although effects were generally
small in size, the agreement of both maternal and paternal report of greater child behavioral
symptoms with greater maternal technoference provides some support to our findings. Future
studies should consider using methods such as video coding of child behavior during parent-
child activities.
Although this study was limited by its cross-sectional design and having a primarily
Caucasian, fairly-educated sample, its findings are a first glance at complex family processes
around rapidly adopted digital technologies. We were able to demonstrate that even low and
seemingly normative amounts of technoference were associated with greater child behavior
problems, which may have great public health relevance. Future, larger-scale and more diverse
studies should continue to examine whether associations between parent technoference and child
behavioral problems depend on other contextual influences such as parenting style, sensitivity, or
family stressors. Yet, we hope that our results can be a springboard for future research into both
the specific cascades of parent-child interactions that underlie these associations, as well as
longitudinal transactional relations between difficult child behavior, family digital technology
use, and parenting.
Abidin, R.R. (1995). Parenting Stress Index: Professional Manual (3rd ed.). Lutz, FL: Psychological
Assessment Resources, Inc.
Achenbach, T. M., & Rescorla, L. A. (2000). Manual for the ASEBA Preschool Forms and Profiles.
Burlington: University of Vermont, Department of Psychiatry.
Arbuckle, J. L. & Wothke, W. (1999). Amos 4.0 user’s guide. Chicago: Small Waters.
Bayer, J., & Campbell, S.W. (2012). Texting while driving on automatic: Considering the frequency-
independent side of habit. Computers in Human Behavior, 28, 2083-2090. doi:
Bianchi, A., & Phillips, J. G. (2005). Psychological predictors of problem mobile phone use.
Cyberpsychology & Behavior, 8, 39-51. doi: 10.1089/cpb.2005.8.39
Bornstein, M.H., Tamis-Lemonda, C.S., Hahn, C.S., Haynes, O.M. (2008). Maternal
responsiveness to young children at three ages: Longitudinal analysis of a
multidimensional, modular, and specific parenting construct. Dev Psychol, 44, 867-74.
doi: 10.1037/0012-1649.44.3.867
Campbell, S. W., & Ling, R., & Bayer, J. (2014). The structural transformation of mobile
communication: Implications for self and society. In M. B. Oliver & A. Raney (Eds.),
Media and social life (176-188). New York: Routledge.
Campbell, S. W, & Park, Y.J. (2008). Social implications of mobile telephony: The rise of personal
communication society. Sociology Compass, 2, 371-387. doi: 10.1111/j.1751-
Cheever, N.A., Rosen, L.D., Carrier, L.M., & Chavez, A. (2014). 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, 37, 290-297. doi: 10.1016/j.chb.2014.05.002
Chesley, N. A., Slibak, A., & Wajcman, J. (2013). Information and communication technology use
and work-life integration. In D. Major & R. Burke (Eds.), Handbook of work-life integration
of professionals: Challenges and opportunities, 245-266. Elgar Publications.
Crnic, K., & Low, C. (2002). Everyday stresses and parenting. In M. Bornstein (ed.), Handbook of
parenting: Practical issues in parenting (2nd edition), vol. 5. (pp. 243-267). Lawrence
Erlbaum Associates: Mahwah, NJ.
Cummings, E. M., & Davies, P. T. (1994). Maternal depression and child development. Journal of
Child Psychology and Psychiatry, 35, 73-112. doi: 10.1111/j.1469-7610.1994.tb01133.x
Davidov, M., Grusec, J.E. (2006). Untangling the links of parental responsiveness to distress and
warmth to child outcomes. Child Development, 77, 44-58. doi: 10.1111/j.1467-
Derks, D., & Bakker, A. B. (2014). Smartphone use, workhome interference, and burnout: A diary
study on the role of recovery. Applied Psychology, 63, 411-440. doi: 10.1111/j.1464-
Drouin, M., Kaiser, D. H., & Miller, D. A. (2012). Phantom vibrations among undergraduates:
Prevalence and associated psychological characteristics. Computers in Human Behavior, 28,
1490-1496. doi: 10.1016/j.chb.2012.03.013
Elliston, D., McHale, J., Talbot, J., Parmley, M., & KuerstenHogan, R. (2008). Withdrawal from
coparenting interactions during early infancy. Family Process, 47, 481-499. doi:
Feinberg, M. E., Brown, L. D., & Kan, M. L. (2012). A multi-domain self-report measure of
coparenting. Parenting, 12, 1-21. doi: 10.1080/15295192.2012.638870
Feinberg, M. E., Jones, D. E., Kan, M. L., & Goslin, M. C. (2010). Effects of Family
Foundations on parents and children: 3.5 years after baseline. Journal of Family
Psychology, 24, 532-542. doi: 10.1037/a0020837
Feldman, G., Greeson, J., Renna, M., & Robbins-Monteith, K. (2011). Mindfulness predicts less
texting while driving among young adults: Examining attention- and emotion-regulation
motives as potential mediators. Personality and Individual Differences, 51, 856-861. doi:
Gelfand, D. M., Teti, D. M., & Radin Fox, C. E. (1992). Sources of parenting stress for depressed
and nondepressed mothers and infants. Journal of Clinical Child & Adol. Psych., 21, 262.
doi: 10.1207/s15374424jccp2103_8
Gergen, K.J., & Gergen, K.J. (2002). The challenge of absent presence. In J. E. Katz & J. E. Aakhus
(Eds.), Perpetual Contact: Mobile Communication, Private Talk, Public Performance (pp.
227-241). Cambridge, UK: Cambridge University Press.
Hiniker, A., Sobel, K., Suh, H., Sung, Y.C., Lee, C.P., & Kientz, J. (2015). Texting while
parenting: How adults use mobile phones while caring for children at the playground.
Proceedings of CHI 2015; Seoul South Korea. doi: 10.1145/2702123.2702199
Hiniker, A., Schoenebeck, S.Y., Kientz, J.A. (2016). Not at the dinner table: Parents’ and
children’s perspectives on family technology rules. CSCW '16, ACM doi:
Hinkley, T., Verbestel, V., Ahrens, W., Lissner, L., Molnar, D., Moreno, LA., et al. (2014). Early
childhood electronic media use as a predictor of poorer well-being: A prospective cohort
study. JAMA Pediatrics, 168, 485-492. doi: 10.1001/jamapediatrics.2014.94
Ito, M., Okabe, D. & Matsuda, M. (2005). Personal, portable, pedestrian: Mobile phones in Japanese
life. East Asian Science, Technology, and Society: an International Journal, 3, 147-151.
Katz, J.E. (2002). Perpetual contact: Mobile communication, private talk, public performance.
Cambridge, UK: Cambridge University Press.
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. New York: Guilford.
Kirkorian, H.L., Pempek, T.A., Murphy, L.A., Schmidt, M.A., & Anderson, D.R. (2009). The
impact of background television on parent-child interaction. Child Development, 80,
1350-1359. doi: 10.1111/j.1467-8624.2009.01337.x
Leavitt, C. E., McDaniel, B. T., Maas, M. K., & Feinberg, M. E. (2016). Parenting stress and
sexual satisfaction among first-time parents: A dyadic approach. Sex Roles. doi:
Lunkenheimer, E.S., Olson, S.L., Hollenstein, T., Sameroff, A.J., & Winter, C. (2011). Dyadic
flexibility and positive affect in parent-child coregulation and the development of child
behavior problems. Dev. Psychopathology, 23, 577-591. doi:
Maas, M. K., McDaniel, B. T., Feinberg, M. E., & Jones, D. E. (2015). Division of labor and
multiple domains of sexual satisfaction among first-time parents. Journal of Family
Issues. doi: 10.1177/0192513X15604343
McDaniel, B. T. (2015). “Technoference”: Everyday intrusions and interruptions of technology
in couple and family relationships. In C. J. Bruess (Ed.), Family communication in the
age of digital and social media. New York: Peter Lang Publishing.
McDaniel, B. T. (2016). Understanding stability and change in daily coparenting: Predictors
and outcomes in families with young children (Doctoral dissertation, The Pennsylvania
State University).
McDaniel, B. T., & Coyne, S. M. (2016a). “Technoference”: The interference of technology in
couple relationships and implications for women’s personal and relational well-being.
Psychology of Popular Media Culture, 5, 85-98. doi: 10.1037/ppm0000065
McDaniel, B. T., & Coyne, S. M. (2016b). The interference of technology in the coparenting of
young children: Implications for mothers’ perceptions of coparenting. The Social Science
Journal, 53, 435-443. doi: 10.1016/j.soscij.2016.04.010
McDaniel, B. T., Coyne, S. M., & Holmes, E. K. (2012). New mothers and media use: Associations
between blogging, social networking, and maternal well-being. Maternal and Child Health
Journal, 16, 1509-1517. doi: 10.1007/s10995-011-0918-2
McDaniel, B. T., & Teti, D. M. (2012). Coparenting during the first three months after birth: The role
of infant sleep quality. Journal of Family Psychology, 26, 886-895. doi: 10.1037/a0030707
Murphy, S. E., Jacobvitz, D. B., & Hazen, N. L. (2015). What’s so bad about competitive
coparenting? Family-level predictors of children’s externalizing symptoms. Journal of Child
and Family Studies, 1-7. doi: 10.1007/s10826-015-0321-5
Nakamura, T. (2015). The action of looking at a mobile phone display as nonverbal behavior/
communication: A theoretical perspective. Computers in Human Behavior, 43, 68-75. doi:
Pempek, T., & McDaniel, B. T. (2016). Young children’s tablet use and associations with
maternal well-being. Journal of Child and Family Studies, 25, 2636-2647. doi:
Przybylski, A. K., & Weinstein, N. (2013). 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, 30, 237-246. doi: 10.1177/0265407512453827.
Radesky, J.S., Kistin, C., Eisenberg, S., Gross, J., Block, G., Zuckerman, B., Silverstein, B.
(2016). Parent perspectives on their mobile technology use: The excitement and
exhaustion of parenting while connected. Journal of Developmental Behavioral
Pediatrics, 37, 694-701. doi: 10.1097/DBP.0000000000000357
Radesky, J. S., Kistin, C. J., Zuckerman, B., Nitzberg, K., Gross, J., Kaplan-Sanoff, M., ... &
Silverstein, M. (2014). Patterns of mobile device use by caregivers and children during
meals in fast food restaurants. Pediatrics, 133, e843-e849. doi: 10.1542/peds.2013-3703
Radesky, J., Miller, A. L., Rosenblum, K. L., Appugliese, D., Kaciroti, N., & Lumeng, J. C.
(2015a). Maternal mobile device use during a structured parentchild interaction task.
Academic Pediatrics, 15, 238-244. doi: 10.1016/j.acap.2014.10.001
Radesky, J. S., Schumacher, J., & Zuckerman, B. (2015b). Mobile and interactive media use by
young children: The good, the bad, and the unknown. Pediatrics, 135, 1-3. doi:
Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general
population. Applied Psychological Measurement, 1, 385-401. doi:
Rainie, L., & Keeter, S. (2006). Americans and their cell phones. Pew Internet & American Life
Project. Retrieved from
Wartella, E., Rideout, V., Lauricella, A., & Connell, S. (2013). Parenting in the age of digital
technology: A national survey. Center on Media and Human Development. Retrieved
Table 1. Bivariate Correlations and Descriptives for Study Variables for Fathers (above diagonal) and Mothers (below diagonal)
Problematic digital
technology use
Technology interference
Externalizing Behavior
Internalizing Behavior
Parent age
Child age
Child screen time
Parenting stress
Std. Dev.
Std. Dev.
Note. *p < .05, **p < .01, ***p < .001. N = 168 mothers and 165 fathers (from 170 families). Correlations for fathers are presented above the
diagonal and for mothers below the diagonal. Correlations between fathers and mothers are bolded, italicized, and on the diagonal. Income is in
$1,000 units, and Externalizing and Internalizing scores are in normed t-score units.
Figure 1. Model of parent problematic digital technology use predicting technoference during
parent-child interactions which finally predicts child externalizing behavior. Standardized
estimates are reported. Parenting stress and coparenting quality were also controlled in the model
(paths not displayed here). Entering demographics, depression, and child age and media use as
controls did not change the results and were therefore omitted from the final model. Note: *** p
< .001, ** p < .01, * p = .06.
Figure 2. Model of parent problematic digital technology use predicting technoference during
parent-child interactions which finally predicts child internalizing behavior. Standardized
estimates are reported. Parenting stress and coparenting quality were also controlled in the model
(paths not displayed here). Entering demographics, depression, and child age and media use as
controls did not change the results and were therefore omitted from the final model. Note: *** p
< .001, ** p < .01, * p < .05.
... In recent years, many scholars adopt this concept as displacement hypothesis to study internet and social media use (e.g., Huang et al. 2022;Kushlev & Leitao, 2020;Twenge et al., 2019;Winstone et al., 2021). Several studies found that technology use could impact adolescents' academic performances (Tang & Patrick, 2018) and problem behaviors (Houghton et al., 2018;McDaniel & Radesky, 2018;Wong et al., 2020) through replacing the activities such as learning opportunities. Even though many studies examine internet use through displacement hypothesis recently, these studies rarely use non-western samples. ...
... The protective role of adolescents' academic performance on the negative effects of internet use on development has been reported in different studies (Mehrvarz et al., 2021;Zhu et al., 2011). The findings support the claim of the displacement hypothesis that increased internet use could contribute to adolescents' externalizing problems through decreased learning opportunities and poor academic performances (Houghton et al., 2018;McDaniel & Radesky, 2018;Tang & Patrick, 2018;Wong et al, 2020). ...
... It also supports the protective function of improving school grades in the previous literature (Riehm et al., 2019;Wong et al., 2020). It further supports the displacement hypothesis that internet use for entertainment purposes could contribute to adolescents' externalizing problems across sociocultural contexts (McDaniel & Radesky, 2018;Wong et al., 2020). Future studies may focus on the parental roles in adolescents' internet use and developmental outcomes to understand nuances of cultural differences in non-western sociocultural contexts. ...
Full-text available
Adolescent internet use in non-western countries and its association with behavioral problems are understudied. Informed by Bronfenbrenner's socioecological framework and displacement hypothesis, this study explored adolescent internet use in rural and urban China and examined the mediation of academic performances between internet use and problem behaviors. Samples included 3,379 adolescents aged between 9-17 years from a nationally representative program. Results showed that rural adolescents had less access to mobile phones and internet, and use them less frequently than urban peers. Hybrid structural equation modeling results revealed that academic rankings fully mediated the association between internet use and externalizing behaviors. Stepwise regression results indicated rural adolescents who use internet were more vulnerable to negative influences of increased online entertainment time than urban peers. Findings contributed to the understanding of internet use of adolescents in rural and urban residency in China. Implications are discussed for practices, policies, and future research.
... McDaniel and Radesky found that mother technoference in parenting was positively correlated with child externalizing and internalizing behaviors, while father technoference in parenting was not related to the child's problem behavior. 39 Therefore, father phubbing and mother phubbing may affect children's development differently. It is necessary to explore their influences respectively. ...
... However, parental phubbing violates these expectations, interrupting parent-child communication and resulting in reduced interaction and poor responsiveness to children's cues. 39 This impact of expectancy violation conveys a message of diminished importance and value of children to their parents, leading to lower self-esteem and less positive self-concept. Therefore, parents must create a secure and supportive environment that promotes children's healthy self-worth and identity development. ...
Full-text available
Introduction Parental phubbing refers to the act of parents using mobile phones in the presence of their children instead of engaging with them. With increasing smartphone use in many households, parental phubbing is a potential threat to children’s healthy development. This meta-analysis synthesized the existing evidence on the impact of parental phubbing on children’s social-emotional development to examine the effect sizes and identify the moderators. Methods Following the PRISMA guidelines, we conducted a systematic search across multiple electronic databases (Web of Science, EBSCO, ProQuest, Springer, and China National Knowledge Infrastructure) from 2012 to May 2023. Our search included both English and Chinese literature, encompassing published journal articles as well as thesis. To assess the risk of bias, we utilized the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Publication bias was evaluated using funnel plot interpretation and Egger’s regression intercept. Results Our comprehensive search identified 42 studies with 56,275 children and 59 effect sizes. A random-effects meta-analysis revealed that parental phubbing was positively associated with children’s internalizing problems (r = 0.270; 95% CI [0.234, 0.304]) and externalizing problems (r = 0.210; 95% CI [0.154, 0.264]), while negatively correlated with children’s self-concept (r = −0.206; 95% CI [−0.244, −0.168]) and social-emotional competence (r = −0.162; 95% CI [−0.207, −0.120]). Furthermore, the parental phubbing group moderated the association between parental phubbing and internalizing problems, when both parents engage in phubbing, there is a stronger association with children’s externalizing problems compared to when only one parent is engaging in phubbing. Discussion The findings of this meta-analysis provide strong evidence supporting the detrimental effects of parental phubbing on child social-emotional adjustment. Consequently, parents, researchers, and the government must collaborate to mitigate parental phubbing and promote the healthy development of children’s social-emotional abilities.
... In the current study, there is more literature demonstrating the negative impact of parental phubbing in adolescents [55,38]. Parental phubbing can easily induce a series of internalizing and externalizing problems [25,61], affect adolescents' anxiety and depression levels [37,48], show angry reactions, and even use excessive behavior as a response to parental phubbing [25]. ...
... The current study then examined whether parental phubbing moderated the relationship between bullying victimization and non-suicidal self-injury in adolescents. Although previous research has shown that parental phubbing signi cantly predicts adolescents' non-suicidal self-injury [15,22,37,48], this study to our knowledge is the rst to con rm that parental phubbing as a moderator diminishes the adverse effect of bullying victimization and adolescents' non-suicidal self-injury. This nding goes beyond previous studies by uncovering when the relationship between bullying victimization and non-suicidal self-injury in adolescents is weak. ...
Full-text available
Background There has been growing scholarly interest in understanding the adverse effects of bullying victimization on adolescents' development. However, it is less clear whether bullying victimization potentially increases adolescents' non-suicidal self-injury, to date, and the understanding of the factors, that may affect this relationship is also limited. The current study, therefore, examined the relationship between bullying victimization and non-suicidal self-injury in adolescents and sought to determine whether parental phubbing and perceived school climate simultaneously moderated this relationship. Methods The participants included 704 students (Mage = 15.15, SD = 0.98) from middle schools in China. They completed the questionnaires regarding their experience with bullying victimization, parental phubbing, perceived school climate and non-suicidal self-injury. Results The results indicated that adolescents with a high level of bullying victimization were likely to have a high level of non-suicidal self-injury, after controlling for age and gender. High parental phubbing adolescents who experienced higher levels of bullying victimization were more likely to be non-suicidal self-injury than low parental phubbing adolescents. Furthermore, higher levels of bullying victimization significantly predicted increases in adolescents' non-suicidal self-injury when they had high parental phubbing and low perceived school climate. In contrast, this effect became insignificant when parental phubbing was low and perceived school climate was high. Conclusions Our findings indicated bullying victimization affects non-suicidal self-injury in adolescents,This relationship is mediated by parental bowing and perceived school climate. Educators who are concerned about adolescents' non-suicidal self-injury should pay closer attention to parental phubbing, as well as their perceived school climate, to provide appropriate interventions.
... Social interactions are crucial for a healthy development because they built the foundation of processes related with personality and cognitive development, such as emotion regulation 51 . The interference of DM with parent-child interactions may compete with children's ability to concentrate and regulate their emotions, leading to internalizing and externalizing problems like reduced ability to control impulses 52 . Children and adolescents who used all DM except smartphone for > 2 h/day, had almost 2-point higher impulsivity score compared to children with low use of all media. ...
Full-text available
The digital environment can pose health risks through exposure to unhealthy content. Yet, little is known about its relation to children’s cognitive functioning. This study investigates the association between digital media (DM) exposure and children’s cognitive functioning. This cross-sectional study is based on examinations of children aged 8–18 years (N = 8673) of the I.Family cohort (2013–2014). Exposure to television, computer, smartphone and internet was self-reported (hours/day). Media multitasking (MMT) was defined as simultaneous use of computers with other digital or non-screen-based activities. Standard instruments were used to assess cognitive inflexibility (score: 0–39), decision-making ability (− 100 to + 100) and impulsivity (12–48). Adjusted regression coefficients and 99.9%CIs were calculated by generalized linear mixed-effects models. In total, 3261 participants provided data for impulsivity, 3441 for cognitive inflexibility and 4046 for decision-making. Exposure to smartphones and media multitasking were positively associated with impulsivity (βsmartphone = 0.74; 99.9%CI = 0.42–1.07; βMMT = 0.73; 99.9%CI = 0.35–1.12) and cognitive inflexibility (βsmartphone = 0.32; 99.9%CI = -0.02–0.66; βMMT = 0.39; 99.9%CI = 0.01–0.77) while being inversely associated with decision-making ability. Extensive smartphone/internet exposure combined with low computer/medium TV exposure was associated with higher impulsivity and cognitive inflexibility scores, especially in girls. DM exposure is adversely associated with cognitive functioning in children and adolescents. Children require protection against the likely adverse impact of digital environment.
... For example, with respect to romantic relationships, so-called "partner phubbing" or paying too much attention to one's smartphone while the partner is present, has been linked to lower relationship satisfaction (Al-Saggaf & O'Donnell, 2019; Beukeboom & Pollmann, 2021;Krasnova et al., 2016;McDaniel & Coyne, 2016;Nuñez & Radtke, 2023). Similarly, one study demonstrated that the frequency of technological interruptions of parent-child interactions was related to problematic behavior in children (McDaniel & Radesky, 2018). Hence, while fragmentation might not be directly associated with reduced well-being for the users themselves, their interaction partner might suffer and hence, ultimately, so too the quality of users' social relationships and their well-being. ...
Smartphones are an integral part of daily life for many people worldwide. However, concerns have been raised that long usage times and the fragmentation of daily life through smartphone usage are detrimental to wellbeing. This preregistered study assesses (1) whether differences in smartphone usage behaviors between individuals predict differences in a variety of well-being measures (between-person effects) and (2) whether differences in smartphone usage behaviors between situations predict whether an individual is feeling better or worse (within-person effects). In addition to total usage time, several indicators capturing the fragmentation of usage/nonusage time were developed. The study combines objectively measured smartphone usage with selfreports of well-being in surveys (N = 236) and an experience sampling period (N = 378, n = 5775 datapoints). To ensure the robustness of the results, we replicated our analyses in a second measurement period (surveys: N = 305; experience sampling: N = 534, n = 7287 datapoints) and considered the pattern of effects across different operational definitions and constructs. Results show that individuals who use their smartphone more report slightly lower well-being (between-person effect) but no evidence for within-person effects of total usage time emerged. With respect to fragmentation, we found no robust association with well-being.
Les écrans ont pris ces dernières années une importance considérable pour ce qui concerne l’éducation et la culture et de façon plus générale, la vie de notre société. En même temps, les pratiques excessives et problématiques se sont multipliées, alimentant d’énormes intérêts économiques. Les recherches actuelles tendent toutefois à s’éloigner d’une mise en cause des seuls écrans pour prendre en compte l’ensemble du mode de vie de l’enfant, incluant notamment les personnes disponibles à lui et les activités alternatives aux écrans disponibles dans son environnement. Ainsi la question principale des écrans cesse-t-elle d’être celle de leurs dangers, réels ou fantasmés, pour devenir celle de leurs droits.
Cet article propose une réflexion sur la question de la technoférence que représente l’écran au sens large chez le bébé de moins de 1 an. L’enquête réalisée auprès de parents d’un bébé de 6 mois à 1 an révèle une exposition passive et active très précoce, y compris chez les parents qui se disent attentifs à la question. Le bébé est ainsi souvent exposé via la propre exposition de son parent, un phénomène de technoférence parentale qui entrave les interactions quotidiennes à un âge où elles sont pourtant essentielles au développement du bébé.
Conference Paper
Full-text available
Parents and children both use technology actively and increasingly, but prior work shows that concerns about attention, family time, and family relationships abound. We conducted a survey with 249 parent-child pairs distributed across 40 U.S. states to understand the types of technology rules (also known as restrictive mediation) they have established in their family and how effective those rules are perceived to be. Our data robustly show that children (age 10-17) are more likely to follow rules that constrain technology activities (e.g., no Snapchat) than rules that constrain technology use in certain contexts (e.g., no phone at the dinner table). Children find context constraints harder to live up to, parents find them harder to enforce, and parents’ most common challenge when trying to enforce such rules is that children “can’t put it down.” This is consistent with the idea that banning certain technologies is currently easier than setting more nuanced boundaries. Parents and children agree that parents should also unplug when spending time with family, while children alone express frustration with the common parent practice of posting about children online. Together, our results suggest several mechanisms by which designers and families can improve parent-child relationships around technology use.
Full-text available
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.
Full-text available
The present paper reports on longitudinal associations between parenting stress and sexual satisfaction among 169 heterosexual couples in the first year after the birth of a first child. Actor Partner Interdependence Modeling (APIM) was used to model the effects of the mother’s and father’s parenting stress at 6 months after birth on sexual satisfaction at 1 year after birth. Based on social constructivist theory and scarcity theory, two hypotheses were posed: (a) mothers’ parenting stress will predict their own later sexual satisfaction whereas fathers’ parenting stress will not predict their own later sexual satisfaction (actor effects) and (b) mothers’ parenting stress will predict fathers’ later sexual satisfaction but fathers’ parenting stress will not predict mothers’ later sexual satisfaction (partner effects). On average, parents were only somewhat satisfied with their sex life. The first hypothesis was supported as greater parenting stress significantly predicted lower sexual satisfaction for mothers but not for fathers. The second hypothesis was also supported as mothers’ greater parenting stress significantly predicted less sexual satisfaction in fathers, whereas fathers’ parenting stress did not significantly predict mothers’ sexual satisfaction. We discuss how our results may be interpreted considering the social construction of gendered family roles.
Full-text available
While recent research has documented a rapid increase in the use of new technologies such as touchscreen tablets early in life, little is known about how young children use tablets, what activities they engage in, and whether family demographic and maternal well-being are associated with early use. Guided by Bronfenbrenner’s bioecological theory of human development, the current study addressed these questions with a cross-sectional, online survey of mothers with children between 12 and 48 months of age. Mothers reported on their child’s tablet use as well as their own personal well-being (depressive symptoms and role overload) and relational well-being (relationship satisfaction, coparenting quality, conflict frequency). Nearly 63 % of all mothers owned a tablet. Approximately 46 % of children with access typically use a tablet in an average day, with the majority using for 15 min or less. For families who owned a tablet, child’s frequency of use was positively associated with child’s age and mother’s use and negatively associated with mother’s relational well-being. Despite the American Academy of Pediatrics recommendation that screen media be avoided for children under 24 months, children in our study used tablets, albeit infrequently. Our findings suggest that it is important for researchers to consider the relationship between contextual factors within the family and child media use. Refining their focus for families with particular needs may allow child advocates and policy makers to develop more beneficial media recommendations for families with a variety of circumstances.
Conference Paper
Full-text available
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.
Full-text available
Competitive coparenting, defined as one parent undermining the other in the presence of the child or jockeying for control of the child, has been identified as a robust predictor of externalizing symptoms in children. But in addition to its core definition, competitive coparenting is also likely to involve a lack of cooperative coparenting, displays of negative affectivity, and family conflict, making it unclear what drives the relation between competitive coparenting and children’s externalizing symptoms. Thus, the present study aimed to examine the extent to which each aspect of family negativity contributes to externalizing symptoms in children, and in particular, whether the core definition of competitive coparenting (parental triangulation of the child) predicts their later externalizing symptoms above and beyond effects due to other types of negative family interaction. Both parents and their first-born child (N = 108 families) were observed in triadic family interactions when children were 24 months old, and children’s externalizing symptoms were rated by their teachers when children were 7 years old. Family interactions were coded at the triadic level for competitive coparenting, cooperative coparenting, negative affect, and conflict. First-order correlations indicated that competitive coparenting, negative affectivity, and family conflict within the triad were all associated with each other and with children’s externalizing symptoms. When all entered into a regression, however, competitive coparenting remained the sole predictor of later externalizing symptoms in children. Results suggest that the core definition of competitive coparenting predicts children’s externalizing symptoms beyond the general presence in family interaction of low cooperation, negative emotionality, and conflict.
The spread of mobile communication, most obtrusively as cell phones but increasingly in other wireless devices, is affecting people's lives and relationships to a previously unthought-of extent. Mobile phones, which are fast becoming ubiquitous, affect either directly or indirectly every aspect of our personal and professional lives. They have transformed social practices and changed the way we do business, yet surprisingly little serious academic work has been done on them. This 2002 book, with contributions from the foremost researchers in the field, studies the impact of the mobile phone on contemporary society from a social scientific perspective. Providing a comprehensive overview of mobile phones and social interaction, it comprises an introduction covering the key issues, a series of unique national studies and a final section examining specific issues.
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.