Evidence map›Paper›PMID 42721410›Full record

ArticleJMIR mHealth and uHealth2026

Objective Smartphone Screen Time Monitoring Among Caregivers of Preschool-Aged Children: Reliability Study of Monitoring Duration.

Joshua Culverhouse, Taylor Adair, Meghan Restino, Heidi M Weeks, Jenny S Radesky, R Glenn Weaver, Sarah Burkart, Hannah Parker, Olivia L Finnegan, Anthony J Holmes and 5 more

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Joshua CulverhouseDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0001-5345-5760
Taylor AdairDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0009-0008-8045-9984
Meghan RestinoDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0009-0004-1557-2471
Heidi M WeeksUniversity of Michigan School of Public Health, Ann Arbor, MI, United States.ORCID 0000-0003-3467-7987
Jenny S RadeskyUniversity of Michigan Medical School, Ann Arbor, MI, United States.ORCID 0000-0002-7721-7350
R Glenn WeaverDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0001-5889-974X
Sarah BurkartDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0002-0840-1680
Hannah ParkerDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0003-4197-7224
Olivia L FinneganDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0003-0625-1479
Anthony J HolmesDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0003-4711-629X
Keagan KielyDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0009-0008-0015-3484
Rahul GhosalDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, United States.ORCID 0000-0003-0939-4731
Srihari NelakuditiDepartment of Computer Science and Engineering, University of South Carolina, Columbia, SC, United States.ORCID 0000-0001-5990-394X
Michael W BeetsDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0001-6728-6742
Bridget ArmstrongDepartment of Exercise Science, University of South Carolina, PHRC - Room 140, 921 Assembly St, Columbia, SC, 29201, United States, 1 8032017927.ORCID 0000-0002-1909-8170

Funding

Targeting Behavioral Adjustment and Healthy Lifestyle in Preschool-Age Children Using an Integrated Family-Based InterventionP20GM130420 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI PRINZ, RONALD J · 2020 to 2024
$11.2M
Causes and Consequences of Preschooler's Digital Media Use: The Role of Sleep, Physical Activity, Sedentary Behavior and Social Emotional HealthR01HD112311 · NICHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI Bridget R. Armstrong · 2024 to 2026
$2.0M
NICHD NIH HHS R01 HD112311NIGMS NIH HHS P20 GM130420
6 · The paper itself

Abstract

Background: Reliable measurement of smartphone screen time is important for research examining associations between digital media use and health outcomes. Although objective monitoring tools reduce bias associated with self-report, the number of monitoring days required to reliably estimate typical smartphone use remains unclear. This question is particularly important for study design because longer monitoring periods increase participant burden and the likelihood of missing data. Objective: This study aimed to determine the minimum number of valid monitoring days within a 7-day measurement period required to reliably estimate average daily smartphone screen time during the same 7-day period among primary caregivers of preschool-aged children using 2 objective methods. Methods: This secondary analysis included caregivers participating in 2 observational studies conducted in the Eastern United States. Android users installed Chronicle, a passive sensing application that records raw Android UsageEvents data, which were preprocessed into smartphone session events (pickups where the device was unlocked). iOS users submitted daily screenshots of Apple Screen Time summaries. Reliability analyses included 100 Android Chronicle participants and 129 iOS Screenshot participants with at least 7 consecutive complete days of data. The primary outcome was day-level total smartphone screen time. For Android Chronicle, this was defined as the summed duration of device-unlock sessions across each calendar day, whereas for iOS Screenshot, this was defined as the daily total reported by Apple Screen Time. One-way random-effects intraclass correlation coefficients (ICC [1,1]) with 95% bootstrap CIs (500 resamples) were calculated separately for Android and iOS data. The Spearman-Brown prophecy formula was used to estimate the number of monitoring days required to achieve target reliability thresholds (ICC≥0.70, 0.80, and 0.90). Sensitivity analyses using the combined durations of sessions and glances produced similar conservative monitoring-day recommendations. Results: Single-day ICCs were 0.69 (95% CI 0.63-0.76) for Android Chronicle and 0.71 (95% CI 0.65-0.77) for iOS Screenshot data. Point-estimate projections indicated that 2 monitoring days were sufficient to achieve an ICC≥0.80 for both data sources. Using the more conservative criterion that the lower bound of the projected 95% CI exceeded 0.80, 3 monitoring days were required for both Android and iOS data. Screen time was significantly lower on weekends than on weekdays, suggesting that monitoring periods should include at least 1 weekend day. Conclusions: Among caregivers of preschool-aged children, relatively short objective monitoring periods may provide reliable estimates of average daily smartphone screen time within a 7-day monitoring period. Two monitoring days were sufficient under point-estimate projections, whereas 3 days were required using a conservative lower-bound criterion. These findings support the feasibility of brief smartphone monitoring protocols for estimating the 7-day average duration, while emphasizing the importance of including weekend representation and avoiding the extension of these estimates to longer-term habitual smartphone behavior or screen time metrics beyond duration without further evidence.

Indexed as

CaregiversScreen TimeSmartphoneChild, PreschoolFemaleHumansMaleReproducibility of ResultsTime Factorspassive sensingreliabilitysampling durationscreen timesmartphone

Identifiers

PMID42721410
PMCPMC13561401

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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.