Evidence map›Paper›PMID 40048153›Full record

ArticleJMIR pediatrics and parenting2025

Novel Profiles of Family Media Use: Latent Profile Analysis.

Nicole Hamp, Jenny Radesky, Heidi M Weeks, Alison L Miller, Niko Kaciroti

Abstract read
In one paragraph

Article in JMIR pediatrics and parenting, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nicole HampDivision of Developmental Behavioral Pediatrics, University of Michigan Medical School, D2204 CS Mott Children's Hospital, 1500 E. Medical Ctr Dr, Ann Arbor, MI, 48109-5718, United States, 1 2485615770.ORCID http://orcid.org/0000-0001-7124-3040
Jenny RadeskyDivision of Developmental Behavioral Pediatrics, University of Michigan Medical School, D2204 CS Mott Children's Hospital, 1500 E. Medical Ctr Dr, Ann Arbor, MI, 48109-5718, United States, 1 2485615770.ORCID http://orcid.org/0000-0002-7721-7350
Heidi M WeeksUniversity of Michigan School of Public Health, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0003-3467-7987
Alison L MillerUniversity of Michigan School of Public Health, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-9866-0204
Niko KacirotiUniversity of Michigan School of Public Health, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0001-8843-8231

Funding

Longitudinal associations between preschooler emotion regulation, executive function, and digital media use.R21HD094051 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RADESKY, JENNY S · 2018 to 2019
$429k
NICHD NIH HHS R21 HD094051
6 · The paper itself

Abstract

Background: Over the past 3 decades, digital and screen media have evolved from broadcast, stationary platforms to a complex environment of interactive, omnipresent, mobile media. Thus, clinical guidance centered around unidimensional concepts such as "screen time" must be modernized to help families navigate the intricate digital ecosystems of readily available entertainment and information. Objective: This study aimed to identify and examine distinct latent profiles of media use in families with young children. We hypothesized that latent profile analysis (LPA) would identify different media use profiles characterized by more heavy, reactive, individual, and permissive media use and more intentional, regulated, or shared uses of media. Methods: We analyzed data from 398 preschool-aged children. English-speaking parents were recruited through community settings. Participants completed surveys regarding several aspects of family media use, such as child device use or activities, parent concerns and attitudes, limit setting and mediation, parent media use, and technology interference, examined in an LPA. The number of latent media profiles was determined using Bayesian Information Criteria. Parents also completed validated scales of parenting stress, depression symptoms, parenting style, child behavior, child sleep, and household disorganization. Multivariable logistic regression was used to examine parent, child, and household predictors of group membership. Results: The LPA yielded 2 distinct groups that differed in the duration of media used by parents and children, to calm children or help them fall asleep. Statistically significant differences between groups included: families in group 1 (n=236, which we termed social-emotional drivers) had parents who preferred interactions via text or email to in-person (P=.01) and were more likely to use media to calm their children (P=.03); in contrast, families in group 2 (n=162, intentional media) used more task-oriented media, like audio and nongame apps (P=.01), had more concerns about effects of media on child language development (P=.04), and used more media restrictions (P=.01). In regression models, female sex of the parent respondent, greater number of siblings, and later child sleep midpoint independently predicted group 1 membership. Conclusions: Findings suggest divergent family media use patterns that can be categorized into 2 main media user groups: those using media to buffer social situations or regulate emotions and those planning mobile device use around functional purposes and concerns around media exposure. Profiles were associated with household size and child sleep. More research is needed to examine the impact of social and emotional uses of media on child outcomes.

Indexed as

childcomputer usedigital medialatent profile analysisLPAmedia usemobile mediapediatricspreschoolquestionnairesurveytechnology use

Identifiers

PMID40048153
PMCPMC11905923

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.