Evidence map›Paper›PMID 33720026›Full record

ArticleJournal of medical Internet research2021

Parents' Perspectives on Using Artificial Intelligence to Reduce Technology Interference During Early Childhood: Cross-sectional Online Survey.

Jill Glassman, Kathryn Humphreys, Serena Yeung, Michelle Smith, Adam Jauregui, Arnold Milstein, Lee Sanders

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

7 authors.

Jill GlassmanClinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-9847-9368
Kathryn HumphreysDepartment of Psychology and Human Development, Vanderbilt University, Nashville, TN, United States.ORCID 0000-0002-5715-6597
Serena YeungDepartment of Biomedical Data Science, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0003-0529-0628
Michelle SmithDivision of General Pediatrics, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-1769-1093
Adam JaureguiClinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0001-8928-3948
Arnold MilsteinClinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0002-2794-2378
Lee SandersDivision of General Pediatrics, School of Medicine, Stanford University, Stanford, CA, United States.ORCID 0000-0003-3231-6918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParents' use of mobile technologies may interfere with important parent-child interactions that are critical to healthy child development. This phenomenon is known as technoference. However, little is known about the population-wide awareness of this problem and the acceptability of artificial intelligence (AI)-based tools that help with mitigating technoference.

objectiveThis study aims to assess parents' awareness of technoference and its harms, the acceptability of AI tools for mitigating technoference, and how each of these constructs vary across sociodemographic factors.

methodsWe administered a web-based survey to a nationally representative sample of parents of children aged ≤5 years. Parents' perceptions that their own technology use had risen to potentially problematic levels in general, their perceptions of their own parenting technoference, and the degree to which they found AI tools for mitigating technoference acceptable were assessed by using adaptations of previously validated scales. Multiple regression and mediation analyses were used to assess the relationships between these scales and each of the 6 sociodemographic factors (parent age, sex, language, ethnicity, educational attainment, and family income).

resultsOf the 305 respondents, 280 provided data that met the established standards for analysis. Parents reported that a mean of 3.03 devices (SD 2.07) interfered daily in their interactions with their child. Almost two-thirds of the parents agreed with the statements "I am worried about the impact of my mobile electronic device use on my child" and "Using a computer-assisted coach while caring for my child would help me notice more quickly when my device use is interfering with my caregiving" (187/281, 66.5% and 184/282, 65.1%, respectively). Younger age, Hispanic ethnicity, and Spanish language spoken at home were associated with increased technoference awareness. Compared to parents' perceived technoference and sociodemographic factors, parents' perceptions of their own problematic technology use was the factor that was most associated with the acceptance of AI tools.

conclusionsParents reported high levels of mobile device use and technoference around their youngest children. Most parents across a wide sociodemographic spectrum, especially younger parents, found the use of AI tools to help mitigate technoference during parent-child daily interaction acceptable and useful.

Indexed as

Artificial IntelligenceParentsChild, PreschoolCross-Sectional StudiesHumansParent-Child RelationsParentingTechnologyartificial intelligencechild developmentdigital technologymobile phoneparenting

Identifiers

PMID33720026
PMCPMC8074848

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.