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Record W4324307194 · doi:10.1186/s40814-023-01266-6

Patterns of preschool children’s screen time, parent–child interactions, and cognitive development in early childhood: a pilot study

2023· article· en· W4324307194 on OpenAlexafffundabout
Jasmine Rai, Madison Predy, Sandra A. Wiebe, Christina M. Rinaldi, Yao Zheng, Valerie Carson

Bibliographic record

VenuePilot and Feasibility Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchKillam TrustsStollery Children’s Hospital FoundationChildren's Hospital FoundationUniversity of AlbertaWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsPsychologyContext (archaeology)Bonferroni correctionCognitionDevelopmental psychologyRepeated measures designSession (web analytics)Cognitive developmentChild developmentTest (biology)Computer science

Abstract

fetched live from OpenAlex

BACKGROUND: The primary objective of this study was to explore the feasibility of a virtual study protocol for a future longitudinal study, including recruitment, study measures, and procedures. The secondary objective was to examine preliminary hypotheses of associations, including 1) the correlations between total duration and patterns of screen time and cognitive development, and 2) the differences in quality of parent-child interactions for two screen-based tasks and a storybook reading task. METHODS: Participants included 44 children aged 3 years and their parents from Edmonton, Alberta and surrounding areas. Children's screen time patterns (i.e., type, device, content, context) were parental-reported using a 2-week online daily diary design. Children's cognitive development (i.e., working memory, inhibitory control, self-control, and language) was measured virtually through a recorded Zoom session. Parent-child interactions during three separate tasks (i.e., video, electronic game, and storybook reading) were also measured virtually through a separate recorded Zoom session (n = 42). The quality of the interactions was determined by the Parent-Child Interaction System (PARCHISY). Descriptive statistics, Intra-class correlations (ICC), Spearman's Rho correlations, and a one-way repeated measures ANOVA with a post-hoc Bonferroni test were conducted. RESULTS: All virtual protocol procedures ran smoothly. Most (70%) participants were recruited from four 1-week directly targeted Facebook ads. High completion rates and high inter-rater reliability in a random sample (Diary: 95% for 13/14 days; Cognitive development: 98% 3/4 tests, ICC > 0.93; Parent-child interactions: 100% for 3 tasks, Weighted Kappa ≥ 0.84) were observed for measures. Across cognitive development outcomes, medium effect sizes were observed for five correlations, with positive correlations observed with certain content (i.e., educational screen time) and negative associations observed for total screen time and certain types (show/movie/video viewing) and contexts (i.e., co-use). Medium and large effect sizes were observed for the differences in parent-child interaction quality between the three tasks. CONCLUSIONS: The virtual study protocol appeared feasible. Preliminary findings suggest it may be important to go beyond total duration and consider type, content, and context when examining the association between screen time and cognitive development. A future longitudinal study using this virtual protocol will be conducted with a larger and more generalizable sample.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.365
Teacher spread0.247 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations23
Published2023
Admission routes3
Has abstractyes

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