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Record W4406722911 · doi:10.2196/57636

Parental Technoference and Child Problematic Media Use: Meta-Analysis

2025· review· en· W4406722911 on OpenAlexaff
Jinghui Zhang, Qing Zhang, Bowen Xiao, Yuxuan Cao, Yu Chen, Yan Li

Bibliographic record

VenueJournal of Medical Internet Research · 2025
Typereview
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsycINFOModerationPsychologyMeta-analysisObservational studySystematic reviewSample size determinationClinical psychologyMEDLINEMedicineSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Parental technoference, the interruption of parent-child interactions by technology, has been associated with negative outcomes in children's media use. However, the magnitude of this relationship and its moderating factors remain unclear. OBJECTIVE: This study aims to systematically examine the relationship between parental technoference and child problematic media use, as well as to identify moderating factors such as age, parental technoference group, study design, and type of problematic media use. METHODS: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a comprehensive literature search was conducted up to August 2024 across multiple databases, including Web of Science, EBSCO, ProQuest, PubMed, PsycINFO, and China National Knowledge Infrastructure, using predefined search strings. A total of 53 studies with a total of 60,555 participants (mean age of 13.84, SD 1.18 years) were included. Inclusion criteria comprised studies involving children under the age of 22 years, assessing the association between parental technoference and child problematic media use with valid measures, and reporting necessary statistical data. Exclusion criteria included studies focusing on other child outcomes, having sample sizes <30, or being case reports or review papers. The risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. A random-effects meta-analysis was performed using R (version 4.2.1; R Foundation for Statistical Computing) with the meta and metafor packages to evaluate the association and conduct moderator analyses. RESULTS: The meta-analysis identified a significant positive association between parental technoference and child problematic media use (r=0.296, 95% CI 0.259-0.331). Moderator analyses revealed that both parental technoference group (P<.001) and study design (P=.008) significantly influenced this relationship. Specifically, the association was stronger when both parents engaged in technoference compared to when only 1 parent did, and in cross-sectional studies compared to longitudinal studies. Age, gender, publication status, and type of problematic media use did not significantly moderate the relationship (all P>.05). CONCLUSIONS: This meta-analysis provides robust evidence of the association between parental technoference and child problematic media use. The findings highlight the need for family-based interventions and underscore the importance of longitudinal research to understand the temporal dynamics of this relationship better. TRIAL REGISTRATION: PROSPERO CRD42023471997; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=471997.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.047
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0180.064
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.310
GPT teacher head0.513
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2025
Admission routes1
Has abstractyes

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