The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index; 3 of the 44 sources its claims cite were checked for support.
The Conceptual and Methodological Mayhem of “Screen Time”
Open accessPublished version of a preprint
Abstract
Debates concerning the impacts of screen time are widespread. Existing research presents mixed findings, and lacks longitudinal evidence for any causal or long-term effects. We present a critical account of the current shortcomings of the screen time literature. These include poor conceptualisation, the use of non-standardised measures that are predominantly self-report, and issues with measuring screen time over time and context. Based on these issues, we make a series of recommendations as a basis for furthering academic and public debate. These include drawing on a user-focused approach in order to seek the various affordances gained from “screen use”. Within this, we can better understand the way in which these vary across time and context, and make distinction between objective measures of “screen time” compared to those more subjective experiences of uses or affordances, and the differential impacts these may bring.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This critical review argues that “screen time” research suffers from poor conceptualization, non-standardized self-report measures, and context/time measurement problems, producing mixed and weak evidence. It recommends retiring “screen time” and adopting user-focused, affordance-based “screen use” measures, including objective data and control groups where feasible.
Key findings
- Definitions of screen time vary widely; the WHO definition focuses on sedentary screen time and excludes active screen-based games such as exergaming, while the field often treats screen time as a unidimensional construct.
- Self-report estimates are inaccurate: Ernala et al. found participants were most accurate—only 34%—when reporting number of Facebook visits per day, but very inaccurate for “time,” “minutes,” or “hours” spent on Facebook; smartphone users tend to underestimate use, and Facebook users overreport time but underreport visits.
- Evidence for causal or long-term effects is weak: reviews and meta-analyses report mixed findings, and longitudinal studies observe either no or very small effects of screen time on depressive symptoms, video games, social media, and passive screen use.
- The authors recommend retiring the term “screen time,” differentiating numerical screen time from goal-directed “screen use,” and using user-focused, affordance-based measures, objective data, taxonomies, and control groups.
Methods
- Design: conceptual/critical review and commentary; no primary data, sample, or empirical study are reported.
- Evidence base: cites existing reviews, meta-analyses, longitudinal studies, and measurement studies; no systematic search strategy or inclusion criteria are described.
- Main analysis: narrative critique organized around four issues—conceptual chaos, poor estimates, variation across contexts, and change over time—followed by recommendations.
Limitations
- The paper does not state formal limitations of its own approach.
- Evident from the text: it is a critical/conceptual account rather than a systematic review, with no reported systematic search, data extraction, or quality appraisal.
- Evident from the text: the recommendations—such as retiring “screen time,” adopting affordance-based measures, and using control groups—are proposals not empirically tested in this paper.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
18 Not checked yet · 14 Own interpretation · 5 No basis given · 1 Partly supported · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“there lacks clear longitudinal evidence that they represent a pure causal effect driven by screen media [5,6,7]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Supportedcites [5] Jensen, 2019, Young adolescents’ digital technology use and mental health symptoms: Little evidence of longitudinal or daily linkages, Clin. Psychol. Sci. source
The Discussion says much of the literature is cross-sectional, which prohibits causal inference, and that the few longitudinal and experimental studies have yielded mixed results with small effects. The Conclusions report little evidence of either a correlational or causal linkage in this longitudinal study. The supplied passages do not give page numbers. (LLM, conf=0.92)
- Supportedcites [6] Orben, 2019, Social Media’s Enduring Effect on Adolescent Life Satisfaction, Proc. Natl. Acad. Sci. USA source
The Abstract says that cross-sectional associations cannot be assumed to reflect within-person effects over time, and that research has had few means of separating longitudinal effects from modeling artifacts. It also describes the observed social-media effects as small and potentially reciprocal, supporting the caution against treating the associations as a pure effect of screen media. (LLM, conf=0.90)
- Partly supportedcites [7] Orben, 2019, The association between adolescent well-being and digital technology use, Nat. Hum. Behav. sourceExperimental — accuracy not yet measured
In the discussion (p. 14), the paper says its analyses cannot establish whether technology use causes lower adolescent well-being: most large-scale datasets permit only cross-sectional correlations, and confounding or reverse causation remains possible. That supports the caution against treating observed associations as a pure screen-media effect, but the paper does not establish the more specific claim that the literature lacks clear longitudinal evidence. (LLM, conf=0.84)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
None of the sources cited for this claim have been checked yet.
In the paper
“other factors tend to explain far more variability when researchers adopt more theoretically-aligned approaches that explain the link between screen time and psychosocial well-being [3,7]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Not checked yetcites [3] Odgers, 2020, Annual Research Review: Adolescent Mental Health in the Digital Age: Facts, Fears, and Future Directions, J. Child. Psychol. Psychiatry source
- Not checked yetcites [7] Orben, 2019, The association between adolescent well-being and digital technology use, Nat. Hum. Behav. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“a growing consensus has emerged suggesting that the associations observed between screen time and psychological or health outcomes are very small in size”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Not checked yetcites [5] Jensen, 2019, Young adolescents’ digital technology use and mental health symptoms: Little evidence of longitudinal or daily linkages, Clin. Psychol. Sci. source
- Not checked yetcites [6] Orben, 2019, Social Media’s Enduring Effect on Adolescent Life Satisfaction, Proc. Natl. Acad. Sci. USA source
- Not checked yetcites [7] Orben, 2019, The association between adolescent well-being and digital technology use, Nat. Hum. Behav. source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“there is wide variation in the self-report measures used to capture screen time.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
plain- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim have been checked yet.
In the paper
“accumulating evidence indicates that timing functions are impaired in a variety of developmental disorders including ADHD [32,33], dyslexia [34], and autism [35,36].”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
What the sources say
- Not checked yetcites [32] Marx, 2017, Living in the fast lane: Evidence for a global perceptual timing deficit in childhood ADHD caused by distinct but partially overlapping task-dependent cognitive mechanisms, Front. Hum. Neurosci. source
- Not checked yetcites [33] Noreika, 2013, Timing deficits in attention-deficit/hyperactivity disorder (ADHD): Evidence from neurocognitive and neuroimaging studies, Neuropsychologia source
- Not checked yetcites [34] Gooch, 2011, Time perception, phonological skills and executive function in children with dyslexia and/or ADHD symptoms, J. Child Psychol. Psychiatry source
- Not checked yetcites [35] Isaksson, 2018, Is there a generalized timing impairment in autism spectrum disorders across time scales and paradigms?, J. Psychiatr. Res. source
- Not checked yetcites [36] Karaminis, 2016, Central tendency effects in time interval reproduction in autism, Sci. Rep. source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“recent reviews and meta-analyses repeatedly conclude that the evidence base is difficult to interpret and presents mixed findings [3,4]”
- Also stated in: § Abstract · plain
“Existing research presents mixed findings, and lacks longitudinal evidence for any causal or long-term effects.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Not checked yetcites [3] Odgers, 2020, Annual Research Review: Adolescent Mental Health in the Digital Age: Facts, Fears, and Future Directions, J. Child. Psychol. Psychiatry source
- Not checked yetcites [4] Orben, 2020, Teenagers, Screens and Social Media: A Narrative Review of Reviews and Key Studies, Soc. Psychiatry Psychiatr. Epidemiol. source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Abstract · plain
None of the sources cited for this claim have been checked yet.
In the paper
“evidence suggests that these can be particularly ill-fitting for the purposes of gaining accurate data on people’s technology-related use [27,37,38]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
What the sources say
- Not checked yetcites [27] Ernala, S.K., Burke, M., Leavitt, A., and Ellison, N.B. (2020, January 25–30). How well do people report time spent on Facebook? An evaluation of established survey questions with recommendations. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA. source
- Not checked yetcites [37] Ellis, 2019, Are smartphones really that bad? Improving the psychological measurement of technology-related behaviors, Comput. Hum. Behav. source
- Not checked yetcites [38] Sewall, C.J.R., Bear, T.B., Merranko, J., and Rosen, D. (2020). How psychosocial well-being and usage amount predict inaccuracies in retrospective estimates of digital technology use. Mob. Media Commun. source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Definitions of screen time vary, which poses a myriad of issues relating to harmonisation, measurement and comparison.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“when comparing smartphone users’ estimates of their own smartphone use, and checking behaviours with their actual use (garnered from smartphone data), they tend to underestimate these behaviours [39]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
What the sources say
- Not checked yetcites [39] Andrews, S., Ellis, D.A., Shaw, H., and Piwek, L. (2015). Beyond self report: Tools to compare estimated and real-world Smartphone use. PLoS ONE, 10. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is unclear how applicable any given measure of “screen time” will be for the duration of a given piece of research.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 10
- Probably not a substantial claim. 8
In the paper
“for social networking sites such as Facebook, compared to actual use garnered from log data, people tend to overreport how much time they spend on Facebook but underreport how many times they visit per day [27]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
What the sources say
- Not checked yetcites [27] Ernala, S.K., Burke, M., Leavitt, A., and Ellison, N.B. (2020, January 25–30). How well do people report time spent on Facebook? An evaluation of established survey questions with recommendations. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“adversity in childhood consistently predicts poor psychosocial functioning and long-term health outcomes [12]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Not checked yetcites [12] Bellis, 2014, Adverse childhood experiences: Retrospective study to determine their impact on adult health behaviours and health outcomes in a UK population, J. Public Health source
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is far from clear whether participants can accurately estimate the amount of screen time they engage in or whether this estimate is systematically biased by screen use itself.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“social support garnered through screen-based activities [8], types of social interactions [9], pre-existing levels of social anxiety [10], and fear of missing out [11] might be more influential in predicting well-being outcomes than screen time directly.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 1. Introduction
What the sources say
- Not checked yetcites [8] Wang, 2018, The exacerbating role of perceived social support and the "buffering" role of depression in the relation between sensation seeking and adolescent smartphone addiction, Pers. Individ. Dif. source
- Not checked yetcites [9] Twenge, 2019, Less in-person social interaction with peers among US adolescents in the 21st century and links to loneliness, J. Soc. Pers. Relat. source
- Not checked yetcites [10] Hong, 2019, The mediating and moderating roles of social anxiety and relatedness need satisfaction on the relationship between shyness and problematic mobile phone use among adolescents, Comput. Hum. Behav. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“even simple screen time measures can be expected to include a high degree of measurement error, which is likely to contribute toward contradictory and inconsistent empirical results.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The WHO, therefore, does not include screen activities like exergaming”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
What the sources say
- Not checked yetcites [14] World Health Organization (2020, April 17). Guidelines on Physical Activity, Sedentary Behaviour and Sleep for Children under 5 Years of Age. Available online: https://apps.who.int/iris/handle/10665/311664. source
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“adolescents with neurodevelopmental disorders have higher rates of social media use [28] and may use screens to support social and communication skills [29]”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
What the sources say
- Not checked yetcites [28] Nereim, 2019, A primary care pediatrician’s guide to assessing problematic interactive media use, Curr. Opin. Pediatr. source
- Not checked yetcites [29] Petrou, 2016, A trial of an iPad™ intervention targeting social communication skills in children with autism, Autism source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“there is a tendency to assume that screen time is a largely unidimensional or homogeneous construct, with little work to unify definitions or ensure that conceptualisations are agreed upon.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“participants were most accurate (albeit only at a rate of 34%) when reporting on number of times per day they visited Facebook, but very inaccurate when gauging how many “time”, “minutes” or “hours” they had spent on average per day on Facebook”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 2. Issue 1—Conceptual Chaos—What Is Screen Time?
What the sources say
- Not checked yetcites [27] Ernala, S.K., Burke, M., Leavitt, A., and Ellison, N.B. (2020, January 25–30). How well do people report time spent on Facebook? An evaluation of established survey questions with recommendations. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Such studies are lacking because ensuring participant compliance is challenging [4,49], and those published fail to show consistent results [50,51,52].”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
What the sources say
- Not checked yetcites [4] Orben, 2020, Teenagers, Screens and Social Media: A Narrative Review of Reviews and Key Studies, Soc. Psychiatry Psychiatr. Epidemiol. source
- Not checked yetcites [49] Allcott, 2019, The welfare effects of social media, Am. Econ. Rev. source
- Not checked yetcites [50] Vanman, 2018, The burden of online friends: The effects of giving up Facebook on stress and well-being, J. Soc. Psychol. source
- Not checked yetcites [51] Tromholt, 2016, The Facebook Experiment: Quitting Facebook Leads to Higher Levels of Well-Being, Cyberpsychol. Behav. Soc. Netw. source
- Not checked yetcites [52] Hunt, 2018, No more FOMO: Limiting social media decreases loneliness and depression, J. Soc. Clin. Psychol. source
plain- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An affordance-based approach avoids relying on the commercial success of platforms or devices and instead establishes measurements which should theoretically remain more stable over time.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“there has been little movement in the field to develop high-quality screen time measures because this involves a variety of methodological, security and privacy challenges.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 3. Issue 2—Estimates Are Not Good Enough
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“researchers may also start to realise new opportunities by teasing out causal relationships between screen time and psychological impacts with observational data alone [54].”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
What the sources say
- Not checked yetcites [54] Rohrer, 2018, Thinking clearly about correlations and causation: Graphical causal models for observational data, Adv. Methods Pr. Psychol. Sci.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“studies of this nature would necessitate the use of control groups where subsets of participants are asked to refrain from using screens (or a certain subset of them).”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“repeated data collection can become disruptive for participants’ education and this can make it more likely that researchers will seek out measurements that are quick but which are less psychometrically substantive to draw strong conclusions.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 5. Issue 4—Screen Use Changes over Time
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“no research to date has used a profiling or cluster-based approach to explore how these various screen time proportionalities may map out onto psychological or behavioural outcomes.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 4. Issue 3—Screen Use Varies across Contexts
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While recording screen time on individual devices such as a smartphone, or a specific smartphone app is now possible, even these approaches will struggle to address how much time is spent on different forms of screen-based engagement which take place on multiple screens.”
§ The Conceptual and Methodological Mayhem of “Screen Time” > 4. Issue 3—Screen Use Varies across Contexts
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Concerns that screen time negatively impacts psychosocial functioning, health and behaviours are widespread.
“concerns that screen time negatively impacts psychosocial functioning, health and behaviours remain widespread, and are routinely voiced in academic, policy and media circles.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Most used self- or parent-reported data on total screen use rather than assessing specific device or activity types that might have differing associations with sleep.2,13”
From Screen Use at Bedtime and Sleep Duration and Quality Among Youths (2024) · cites this paper as [13]
Experimental — accuracy not yet measuredIn the citing paper
“Screen time does not capture the content or context of screen use, which could be examined in future research [20, 128].”
From Screen time and mental health: a prospective analysis of the Adolescent Brain Cognitive Development (ABCD) Study (2024) · cites this paper as [128]
Citations
Cites
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018) · Clinical Psychological Science · doi:10.1177/2167702617723376 · Cited by 1,705
The association between adolescent well-being and digital technology use
Orben, A., & Przybylski, A. K. (2019) · Nature Human Behaviour · doi:10.1038/s41562-018-0506-1 · Cited by 1,500
Self-citationTwenge, J. M., & Campbell, W. K. (2018) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2018.10.003 · Cited by 1,304
Odgers, C. L., & Jensen, M. R. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13190 · Cited by 1,189 · cited 2×
“Whilst some evidence routinely shows negative correlations between screen time and well-being [1,2], recent reviews and meta-analyses repeatedly conclude that the evidence base is difficult to interpret and presents mixed findings [3,4].”
BackgroundResultElhai, J. D., Levine, J. C., Dvorak, R. D., & Hall, B. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.079 · Cited by 1,020
Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data
Rohrer, J. M. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245917745629 · Cited by 1,002 · cited 1×
“Alternatively, researchers may also start to realise new opportunities by teasing out causal relationships between screen time and psychological impacts with observational data alone [54].”
BackgroundNo More FOMO: Limiting Social Media Decreases Loneliness and Depression
Hunt, M. G., Marx, R., Lipson, C., & Young, J. (2018) · Journal of Social and Clinical Psychology · doi:10.1521/jscp.2018.37.10.751 · Cited by 947
The welfare effects of social media
Allcott, H., Braghieri, L., Eichmeyer, S., & Gentzkow, M. (2020) · American Economic Review · doi:10.1257/aer.20190658 · Cited by 857 · cited 1×
“Such studies are lacking because ensuring participant compliance is challenging [4,49], and those published fail to show consistent results [50–52].”
ResultNesi, J., & Prinstein, M. J. (2015) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-015-0020-0 · Cited by 758
Teenagers, screens and social media: a narrative review of reviews and key studies
Orben, A. (2020) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-019-01825-4 · Cited by 706
Self-citation
Research works printed but not linked: 1
- Oxford University Press (2020). Oxford English Dictionary (2020), Oxford University Press.
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Items 101–200 of 289
Types and contexts of child mobile screen use and associations with early childhood behavior
Mallawaarachchi, S. R., Anglim, J., & Horwood, S. (2024) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2024.10.010 · Cited by 19
Emerging adults’ digital technology engagement and mental health during the COVID-19 pandemic
Chase, G. E., Brown, M. T., & Jensen, M. R. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1023514 · Cited by 14
“Overall, it is increasingly clear that rigorous research on digital technology engagement and mental health must respond to calls for more objective and nuanced assessment of the uses and affordances of different types of media use (Ellis et al., 2019; Kaye et al., 2020).”
Backgroundde Casteele, M. V., Soenens, B., Ponnet, K. S., Perneel, S., Flamant, N., & Vansteenkiste, M. (2023) · Interacting with Computers · doi:10.1093/iwc/iwad055 · Cited by 22
Context matters: How smartphone (mis)use may disrupt early emotion regulation development
Roberts, M. Z., Flagg, A. M., & Lin, B. (2021) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2021.100919 · Cited by 12
Passive and social screen time in children with autism and in association with obesity
Must, A., Eliasziw, M., Stanish, H., Curtin, C., Bandini, L., & Bowling, A. (2023) · Frontiers in Pediatrics · doi:10.3389/fped.2023.1198033 · Cited by 12
“, texting while watching television) (46).”
Shaw, D. J., Kaye, L. K., Ngombe, N., Kessler, K., & Pennington, C. R. (2022) · PLoS ONE · doi:10.1371/journal.pone.0276765 · Cited by 18
“Importantly, though, while such direct tracking of activity is considered widely to be the gold standard method (see [17, 31]), the necessary reliance upon the willingness of individuals to allow researchers to monitor their (natural) usage raises questions concerning sampling bias [32].”
BackgroundSelf-citationOn the hermeneutics of screen time
Aagaard, J., Steninge, E., & Zhang, Y. (2021) · AI & Society · doi:10.1007/s00146-021-01223-y · Cited by 11
Why most psychological research findings are not even wrongPreprint
Scheel, A. M. (2021) · Infant and Child Development · doi:10.31234/osf.io/8w2sd · Cited by 61
Young Children's screen habits: Identifying child and family contributors
Tan, T. X., Jing, X., & Guan, W. (2023) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2023.100284 · Cited by 13
Sa'ari, A. S., Hamid, M. R. A., Azizan, N. A., & Ismail, N. H. (2024) · Physiology & Behavior · doi:10.1016/j.physbeh.2024.114562 · Cited by 11
Goh, A. Y. H., Hartanto, A., Kasturiratna, K. T. A. S., & Majeed, N. M. (2025) · Social Media + Society · doi:10.1177/20563051251313855 · Cited by 14
“Recent studies have consistently demonstrated weak correlations between self-reported smartphone usage and objective measures, with a tendency for users to over-report their usage (Kaye et al., 2020; Parry et al., 2021).”
Zimmermann, L., & Sobolev, M. (2020) · doi:10.31234/osf.io/nmgdz · Cited by 10
Beyond screen time: The core influences of problematic screen use on adolescent development networks
Xu, L., Song, K., Deng, H.-Y., Geng, X., Zhang, J., Fang, X., Potenza, M. N., & Zhang, J. (2025) · Journal of Behavioral Addictions · doi:10.1556/2006.2025.00035 · Cited by 16
“Even when considering peer, family, and school environments, problematic screen use remains a pivotal factor, suggesting that regulating digital technology use may not be a Sisyphean Cycle (Orben, 2020).”
Murcia, K., Cross, E., Seitz, J., et al. (2024) · Children & Society · doi:10.1111/chso.12905 · Cited by 9
Brosnan, B. J., Meredith-Jones, K. A., Haszard, J. J., Wickham, S.-R., Galland, B. C., Russell‐Camp, T., & Taylor, R. W. (2025) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-024-01698-0 · Cited by 13
“While these tools offer promise for accurately determining screen time on specific devices (e.g., Android phones) [12], they do not capture interactions and usage across all types of digital devices [13, 14].”
InfluentialZhao, Y., Han, X., Bagot, K. S., Tapert, S. F., Potenza, M. N., & Paulus, M. P. (2025) · npj Mental Health Research · doi:10.1038/s44184-025-00131-z · Cited by 12
Sârbu, E. A., Marici, M., Bostan, S., & Gavrilă-Ardelean, L. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021434 · Cited by 9
“Screen time refers to the sedentary or passive use of multimedia devices for entertainment [37].”
BackgroundYumen, Y., Takayama, Y., Hanzawa, F., Sakane, N., & Nagai, N. (2023) · Nutrients · doi:10.3390/nu15071589 · Cited by 11
“In the future, research using objective data logs and screen time applications to assess SNS use is needed [35].”
BackgroundDevelopment of a protocol for objectively measuring digital device use in youth.
Brosnan, B. J., Wickham, S.-R., Meredith-Jones, K. A., Galland, B. C., Haszard, J. J., & Taylor, R. W. (2023) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2023.05.004 · Cited by 7
Müller, M., & Montag, C. (2024) · Journal of Creativity · doi:10.1016/j.yjoc.2024.100081 · Cited by 12
El impacto del uso prolongado de pantallas en el desarrollo cognitivo de los estudiantes
Tulcanaza, P. E. E., Guarnizo, T. C., Nieves, J. M. N., Taco, B. N. I., Veas, L. J. V., & Chicaiza, D. C. F. (2024) · South Florida Journal of Development · doi:10.46932/sfjdv5n12-086 · Cited by 7
Ebner, K., Wehrt, W., & Souček, R. (2025) · International Journal of Workplace Health Management · doi:10.1108/ijwhm-12-2024-0249 · Cited by 9
Tie, B., Yang, X., & Qiu, J. (2024) · Body Image · doi:10.1016/j.bodyim.2023.101677 · Cited by 9
Alwazzeh, M., Harfouch, M., Hasan, M. A., Alqatari, S. G., AlSaid, A. H., & Alwazzeh, M. J. (2024) · Clinical Practice and Epidemiology in Mental Health · doi:10.2174/0117450179295575240520064919 · Cited by 11
Peng, Q., Wan, X., Li-min, Z., & Wang, X. (2024) · Early Child Development and Care · doi:10.1080/03004430.2024.2426573 · Cited by 7
Richards, O. K., & Veinot, T. C. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714039 · Cited by 7
Tracing Change in Social Media Use: A Qualitative Longitudinal Study
Jungselius, B., & Weilenmann, A. H. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713813 · Cited by 14
Assessing the Impact of Screen Time on the Motor Development of Children: A Systematic Review
Bakht, D., Yousaf, F., Alvi, Z., Ali, M. K. B., Khawar, M. M. H., Munir, L., Bokhari, S. F. H., Qureshi, M. N., Raza, M., & Qureshi, A. A. (2025) · Pediatric Discovery · doi:10.1002/pdi3.70002 · Cited by 14
Maerevoet, M., de Casteele, M. V., de Putte, E. V., Debeer, D., Hoorelbeke, K., Vansteenkiste, M., & Koster, E. H. W. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1548504 · Cited by 8
“Second, although prior experimental studies asked participants to limit or stop SMU during the experimental phase, most did not include a reliable measure of usage duration, such as a device-based tool or app, making it difficult to accurately assess compliance with restrictions (17, 18).”
dos Santos, P. C., da Costa, B. G. G., Lopes, M. V. V., Malheiros, L. E. A., Arundell, L., & da Silva, K. S. (2023) · International Journal of Public Health · doi:10.3389/ijph.2023.1605816 · Cited by 7
“) that can be performed by adolescents, since these ST types have different impacts on adolescents’ behavior and health [36].”
BackgroundWentz, E. E., Hoose, D. L., Holliday, K., McDonald, T., Silsby, K., Podvin, S., & Hirsh, A. (2023) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2023.09.012 · Cited by 6
Effects of media multitasking frequency on a novel volitional multitasking paradigm
Lopez, J. J., & Orr, J. M. (2022) · PeerJ · doi:10.7717/peerj.12603 · Cited by 6
Psychosocial Correlates of Recreational Screen Time among Adolescents
Roussel-Ouellet, J., Beaulieu, D., Vézina‐Im, L., Turcotte, S., Labbé, V., & Bouchard, D. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192416719 · Cited by 6
“It is difficult to ascertain whether the use of the Screen TimeBased Sedentary Behavior Questionnaire is responsible for this possible overestimation of adolescents’ recreational screen time or if adolescents are not fully aware of how much time they spend using screens recreationally, since there are many methodologi…”
BackgroundCreativity and Smartphone Use: Three Correlational StudiesPreprint
Olson, J. A., Sandra, D. A., Langer, E. J., et al. (2022) · doi:10.31234/osf.io/6grz7 · Cited by 6
Phippen, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95689-5.00097-3 · Cited by 6
Palma, G. D., Sala, E., Rubino, S., et al. (2023) · Bioengineering · doi:10.3390/bioengineering10060686 · Cited by 5
Eales, L., Giammanco, O., & Ferguson, G. M. (2024) · Journal of Children and Media · doi:10.1080/17482798.2024.2431968 · Cited by 6
“…problems with screen time measurement, and its small, non-clinically significant associations with child well-being in rigorous studies to date (Kaye et al., 2020; Przybylski et al., 2020), it is important for research to expand investigations of children’s screen media beyond time spent to…”
Muench, C., Link, J., & Carolus, A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-05014-5_14 · Cited by 5
Challenges and Opportunities of Using Redirection of Activity for Self-Regulation Online
Inie, N., Westh, B. H., Muller, J. H., & Lungu, M. F. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581342 · Cited by 5
“Mobile operating system creators now often provide their own applications for tracking screen use: iOS’s Screen Time and Android’s equivalent Digital Wellbeing allow users to gain insight and objective measurements into their own behaviour surrounding smartphone use [42].”
BackgroundTang, Z., Xiang, H., Geng, Y., Liao, X., Zhang, M., & Zhang, T. (2023) · Nursing and Health Sciences · doi:10.1111/nhs.13059 · Cited by 6
Parry, D. A., & Sewall, C. J. R. (2021) · doi:10.31235/osf.io/jzxun · Cited by 4
Arqueros, M., Pérez-Díez, I., García-Ramos, A., Ayad‐Ahmed, W., Sánchez, A., & de la Torre‐Luque, A. (2025) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-025-02712-x · Cited by 8
“Additionally, the influence of caregivers may be critical in shaping the regulatory effects of gaming, as parental guidance and co-playing behaviors have been associated with more balanced gaming habits and improved emotional coping strategies [48, 81, 89].”
Bediou, B., Cekic, S., & Bavelier, D. (2023) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13932 · Cited by 4
Haag, A., Nick, E. A., Chen, S., Telzer, E. H., Prinstein, M. J., & Bonanno, G. A. (2024) · Journal of Research on Adolescence · doi:10.1111/jora.13045 · Cited by 3
Ingram, G. (2020) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2020.100040 · Cited by 4
Buda, T. S., Khwaja, M. K., Garriga, R., & Matic, A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0284104 · Cited by 6
“Recently, scientists argued that there is a lack of strong evidence on the detrimental effects of smartphones use on our mental health [41, 42] and that previous studies and systematic reviews overestimated the negative associations [4].”
Corkin, M. T., Liang, J., Meissel, K., Peterson, E. R., Corkin, E., Lee, K. M., & Giacaman, N. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2296955 · Cited by 4
“Unfortunately, as yet there is no automated tool available for measuring total screen time in children or adolescents (Browne et al., 2021; Kaye et al. 2020), and this is compounded by children often utilising several screens across the day and the issue of young children frequently not owning…”
Empowering high school students with online game literacy
Suyanto, S., Yesicha, C., Nasution, B., Nurjanah, N., Wahidar, T. I., Ismandianto, I., & Putri, W. E. (2024) · Journal of Community Service and Empowerment · doi:10.22219/jcse.v5i1.29222 · Cited by 4
Methodological considerations for social media intervention studies
Abeele, M. V., Murphy, S. L., Lemahieu, L., & Koster, E. H. W. (2025) · Nature Reviews Psychology · doi:10.1038/s44159-025-00474-6 · Cited by 10
“…among scholars that the above concurrent, competing and contradictory mechanisms involve specific patterns of social media use and exposure 60 , are contingent on individual susceptibilities 61 and situational characteristics 62 , take place during sensitive developmental windows 34 , and…”
Doggett, A., Gohari, M. R., Godin, K. M., Ferro, M. A., Patte, K. A., & Leatherdale, S. T. (2021) · Substance Use & Misuse · doi:10.1080/10826084.2021.1922455 · Cited by 4
“Researchers have indicated that it is important for the STSB literature among youth populations to establish mechanisms of association, as cross-sectional associations are insufficient and may inappropriately conclude screen time is a generally negative behavior due to its associations with a variety of other health b…”
BackgroundMcFarland, S., Tan, T. Y., France, K. D., & Hoffmann, J. D. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1015635 · Cited by 7
Hornbæk, K., Lyngs, U., Iarygina, O., & Skov, M. B. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642820 · Cited by 5
Descarpentry, A., Melchior, M., Galéra, C., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2538083/v1 · Cited by 4
Questioning the Challenge to Screen Use Guidelines
L’Ecuyer, C., Semper, J. V. O., Montiel, I., Osorio, A., López–Fidalgo, J., & Salmerón-Ruiz, M. A. (2025) · Teoría de la Educación Revista Interuniversitaria · doi:10.14201/teri.31886 · Cited by 3
Deconstructing screen time: The connections between digital use, dissatisfaction, and disconnection
Jespersen, M. H., Albris, K., & Willadsen, H. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100655 · Cited by 5
Pennington, C. R., Murray, E. A. H., Kaye, L. K., Burgess, A., Kessler, K., & Shaw, D. J. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100753 · Cited by 4
Self-citationJackson, R. F., Meredith-Jones, K. A., Haszard, J. J., Galland, B. C., Morrison, S., Jaques, M. J. N., & Taylor, R. W. (2025) · Pediatric Obesity · doi:10.1111/ijpo.70050 · Cited by 3
“To date, most screen-based research has been limited to the use of subjective, predominantly questionnaire-based measures of screen use [14], which are reliant on memory and may be subject to social desirability bias, making it hard to determine true relationships between screen use and health [15].”
Current trends of reduced physical activity in different age groups of the population
Guseva, O. V. (2022) · Russian Journal of Preventive Medicine · doi:10.17116/profmed202225091111 · Cited by 3
Italian Validation of the Social Media Engagement Questionnaire (SME-Q): A Preregistered Study
Duradoni, M., Innocenti, F., Mattiassi, A. D. A., & Guazzini, A. (2023) · Human Behavior and Emerging Technologies · doi:10.1155/2023/2363112 · Cited by 3
Zimmermann, L. V., & Somasundaram, J. (2024) · Palgrave studies in marketing, organizations and society · doi:10.1007/978-3-031-60199-6_5 · Cited by 3
Human and digital ecosystems in the modern household
Briggs, P., Nicholson, J., & Lukins, R. S. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1426804 · Cited by 4
Digital Maturity: Development and Validation of the Digital Maturity Inventory (DIMI)Preprint
Laaber, F., Florack, A., Koch, T., et al. (2022) · doi:10.31219/osf.io/w7m8k · Cited by 2
Bediou, B., & Wac, K. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-818872-9.00190-4 · Cited by 3
Sedentary Behaviour at the Individual Level: Correlates, Theories, and Interventions
Biddle, S. (2023) · Springer series on epidemiology and public health · doi:10.1007/978-3-031-41881-5_16 · Cited by 2
Cuddihy, A., McCormack, D., Cross, J., Craig, S. N., & Fosker, T. (2025) · Review Journal of Autism and Developmental Disorders · doi:10.1007/s40489-025-00513-1 · Cited by 7
Red is angry, ice cream is happy - Capturing in the moment screen time emotions from children
Read, J. C., Horton, M., & Fitton, D. (2025) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3713043.3731531 · Cited by 2
“The overarching narrative in the literature is about managing screen time against a backdrop of considering that children are demonstrating problematic behaviour associated with screen use [10] and parents are struggling to cope with difficult behaviours [20, 24, 31].”
Feijóo, S., Laffan, D. A., Sargioti, A., Sciacca, B., McGarrigle, J., Heaney, D., & Norman, J. O. (2025) · Educational Review · doi:10.1080/00131911.2025.2582556 · Cited by 2
Leveraging Rational Addiction Theory to Reduce Mobile Usage
Somasundaram, J., Zimmermann, L., & Pham, Q. D. (2025) · Journal of Marketing · doi:10.1177/00222429251405841 · Cited by 4
Tie, B., Maheux, A. J., Xu, Y. V., Peng, Y., Wang, P., He, J., & Qiu, J. (2025) · Body Image · doi:10.1016/j.bodyim.2025.102006 · Cited by 3
Digital Media Use in Adolescents with Migraine: A Topical Review
Langdon, R., Gioia, G. A., & Law, E. F. (2025) · Current Pain and Headache Reports · doi:10.1007/s11916-025-01444-6 · Cited by 2
“…there is now expert consensus that digital media use screenings which are atheoretical, single dimension (e.g., reliant on screen time duration only), and self-report fail to capture nuances of not only how digital media is being used (content and context) but why (motivations for use) [22–24].”
Felt Time Scale (FTS): Measuring how people experience screen time
Dombrowski, J., & Trepte, S. (2026) · Communication Methods and Measures · doi:10.1080/19312458.2026.2627548 · Cited by 3
“The idea that users cannot accurately estimate their screen time has sparked extensive debate, raising concerns about the validity of self-report measures and the practical relevance of reported media effects (Kaye et al., 2020).”
Reid, C. A., Dhamankar, M., Marsh, S., Peterson, E. R., Erb, C. D., & Waldie, K. E. (2026) · Developmental Review · doi:10.1016/j.dr.2026.101266 · Cited by 3
Reconceptualizing cognitive-behavioral processes in youth anxiety in the digital age
Skjerdingstad, N., & Leigh, E. (2026) · Nature Mental Health · doi:10.1038/s44220-026-00633-5 · Cited by 2
“A major limitation in the field has been the lack of precise conceptualizations and measurements of social media use 20,21 .”
Screen time: how much is too much?
Davie, M. (2022) · Paediatrics and Child Health · doi:10.1016/j.paed.2022.05.005 · Cited by 2
Finnegan, O., Weaver, R. G., Yang, H., White, J. W., Nelakuditi, S., Zhong, Z., Ghosal, R., Tong, Y., Cepni, A. B., Adams, E. L., et al. (2024) · Human Behavior and Emerging Technologies · doi:10.1155/2024/5860114 · Cited by 3
“The introduction of mobile devices has substantially impacted the ways in which children consume media, such that children are more apt to use these devices sporadically due to the portable nature of these devices [8–10].”
Cerit, M., Zelikman, E., Cho, M.-J., Robinson, T. N., Reeves, B. B., Ram, N., & Haber, N. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3720055 · Cited by 4
Driscoll, J. W., Chen, Y., Shi, V., Vucharatavintara, I., Yao, Y., & Jin, H. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791622 · Cited by 2
Testing Concerns about Technology's Behavioral Impacts with N-of-one Trials
Matias, J. N., Pennington, E., & Chan, Z. T. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533227 · Cited by 2
“In line with other empirical research [31, 51], the consistentlynull results from the Gray Phone Challenge do not support the claims of technology critics that colorful screens are addicting people to their phones.”
BackgroundResultShaw, H., Ellis, D. A., Geyer, K., Davidson, B. I., Ziegler, F. V., & Smith, A. (2020) · Technology Mind and Behavior · doi:10.1037/tmb0000022.supp · Cited by 1
Self-citationLeveraging Rational Addiction Theory to Reduce Mobile UsagePreprint
Somasundaram, J., Zimmermann, L., & Duc, P. Q. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3719413 · Cited by 2
Somebody’s Watching Me: Smartphone Use Tracking and ReactivityPreprint
Tóth, R., & Trifonova, T. (2020) · doi:10.31235/osf.io/7aqdx · Cited by 2
Yee, A. Z. H., Yu, R., Lim, S. S., et al. (2022) · doi:10.31234/osf.io/sphq4 · Cited by 2
Eales, L., Wiglesworth, A., Klimes‐Dougan, B., & Cullen, K. R. (2023) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2023.05.009 · Cited by 2
Daily motivational underpinnings and outcomes of adolescent video gaming
Razum, J. (2023) · doi:10.17234/diss.2023.265864 · Cited by 2
Ethics and interventions: A commentary on how to “improve” prediction using behavior modification
Provost, F. J. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2022.10.001 · Cited by 1
Kućar, M., Vidaček-Hainš, V., & Kovacic, R. (2023) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.23919/mipro57284.2023.10159915 · Cited by 1
“Different ways of measuring SMU or the usage of a certain device are discussed in the introduction.”
BackgroundInfluentialLeão, L. C., da Silva, M. A., Azevedo, E. C., & Frizzo, G. B. (2024) · Springer eBooks · doi:10.1007/978-3-031-69224-6_2 · Cited by 1
Zhang, J., Sebben, S., & Browne, D. T. (2024) · Springer eBooks · doi:10.1007/978-3-031-69224-6_3 · Cited by 1
Yang, X., Zhang, D.-Q., & Liu, Y. (2025) · PLoS ONE · doi:10.1371/journal.pone.0318735 · Cited by 1
Is It Time to Abandon the Media Multitasking Index?
Parry, D. A., & Fisher, J. T. (2025) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105/a000470 · Cited by 1
Griffith, S. F., Vaclavik, D., Hart, K. C., Casanova, S. M., Goodman, A. C., Mac-Niven, A. C., & Bagner, D. M. (2025) · Journal of Children and Media · doi:10.1080/17482798.2025.2511716 · Cited by 1
“The increased difficulty involved in measuring young children’s screen media across multiple, sometimes shared, mobile (e.g., tablets and smartphones) and non-mobile (e.g., television) screen media devices has been frequently discussed in the literature (e.g., Kaye et al., 2020).”
O’Connor, T. M., Garza, T., Alam, U., Vadathya, A. K., Moreno, J. P., Beltran, A., Haidar, S., Haidar, N., Hughes, S. O., Thompson, D. I., et al. (2025) · Behaviour and Information Technology · doi:10.1080/0144929x.2025.2523452 · Cited by 1
Eales, L., Wiglesworth, A., Cullen, K. R., & Klimes‐Dougan, B. (2025) · Development and Psychopathology · doi:10.1017/s0954579425100655 · Cited by 4
Wang, H. F. W., Smith, S. S., O’Flaherty, M., Trost, S. G., Thomas, G., Walker, J. L., Fortnum, K., McNaughton, S. A., Cairney, J., & Bourke, M. (2025) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-025-07064-8 · Cited by 4
Gaeveren, K. V., Murphy, S. L., Vicente, D. D. S., & Abeele, M. V. (2025) · Mobile Media & Communication · doi:10.1177/20501579251377010 · Cited by 1
“To understand the nature of mobile communication, we should not treat “ smartphone screen time ” as a monolithic concept, but rather consider its theoretically relevant facets (Kaye et al., 2020; Meier & Reinecke, 2021).”
Taking the Long View on Digital Culture and Mental Health: Principles From Critical Realism.
Paquin, V. (2025) · Qualitative Health Research · doi:10.1177/10497323251389814 · Cited by 1
Know thyself through data: Improving WhatsApp interaction awareness with data-driven visualizations
Hakobyan, O., & Drimalla, H. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108867 · Cited by 1
Tóth, R., Fernández, A., García‐Manglano, J., & de la Rosa, P. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100891 · Cited by 1
Wernholm, M. (2025) · Journal of Research in Childhood Education · doi:10.1080/02568543.2025.2600993 · Cited by 1
Metadata
- Authors
- K. Kaye, L., Orben, A., A. Ellis, D., C. Hunter, S., & Houghton, S.
- Affiliations
- Department of Psychology, Edge Hill University, Ormskirk L39 4QP, UK
- MRC Cognition and Brain Sciences Unit (GB)
- School of Management, University of Bath, Bath BA2 7AY, UK
- Department of Psychology, Glasgow Caledonian University, Glasgow G4 0BA, UK
- The University of Western Australia (AU)
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2020-05-22
- Volume
- 17
- Issue
- 10
- Pages
- 3661
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC7277381
- OpenAlex
- W3026494741
- Semantic Scholar
- fa852005bc52ac924df6ef97a29a2222d469469b
- Cited by
- 304
- References
- 54
- Citations by year
- 2026: 49 · 2025: 54 · 2024: 55 · 2023: 49 · 2022: 54 · 2021: 32 · 2020: 10
- FWCI
- 56.47
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- UWA Profiles and Research Repository (UWA) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ResearchOnline (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Edge Hill University Research Information Repository (Edge Hill University) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Topics
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Keywords
- screen time, screen use, self-report measures, objective measures, longitudinal effects
- MeSH terms
- Screen Time, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-08, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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