The DOI matches its Crossref record; 46 of the 47 references it cites were found in a registry or an index; none of the 59 sources its claims cite is checked for support yet.
The effects of smartphones on well-being: theoretical integration and research agenda
Abstract
As smartphones become ever more integrated in people's lives, a burgeoning new area of research has emerged on their well-being effects. We propose that disparate strands of research and apparently contradictory findings can be integrated under three basic hypotheses, positing that smartphones influence well-being by (1) replacing other activities (displacement hypothesis), (2) interfering with concurrent activities (interference hypothesis), and (3) affording access to information and activities that would otherwise be unavailable (complementarity hypothesis). Using this framework, we highlight methodological issues and go beyond net effects to examine how and when phones boost versus hurt well-being. We examine both psychological and contextual mediators and moderators of the effects, thus outlining an agenda for future research.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
The paper proposes a displacement–interference–complementarity (D.I.C.) framework to integrate contradictory findings on how smartphones affect well-being, arguing that phones can both hurt and boost well-being depending on when and how they are used. It concludes that net effects are typically small to negligible but can become substantial with heavy, problematic use, and it calls for experimental and objective-measurement research.
Key findings
- Screen time predicts slightly lower well-being across large representative adolescent samples, but the net negative effect is small and non-linear: some screen time is better than none, while heavy use is worse. One cited study found screen media use accounted for only 0.4% of variance in well-being; another found adolescents spending 5+ hours/day on digital screens were twice as likely as light users to have attempted suicide.
- Self-reported phone use is imprecise and biased: subjective estimates of average screen time share as little as 10% variance with objective measures; light users tend to overestimate and heavy users underestimate. Frequency and time of phone use are distinct, sharing only about 10%–15% variance; people check phones about 50 times/day, usually just over a minute at a time, with only 5% of instances lasting longer than 10 minutes.
- Interference effects are supported by a 14-day field experiment in which batching notifications three times daily made users happier and less stressed, mediated by improved subjective quality of attention. Mere-presence effects on social connection remain uncertain: one small study found effects for meaningful but not casual topics, but a replication failed, and both studies were likely underpowered (Ns < 100).
- Complementarity effects show phones can boost well-being when they afford otherwise unavailable information, communication, or comfort—for example, after social exclusion, phone access reduced salivary alpha-amylase reactivity in a 148-participant experiment, and phone use provided comfort in stressful situations.
Methods
- Design: theoretical integration and research agenda, not a new empirical study; the authors synthesize disparate findings into three hypotheses—displacement, interference, and complementarity—and present a D.I.C. framework in Table 1.
- Data: review focuses on research published since 2018, drawing on earlier work when needed; cited evidence includes large representative adolescent samples, experience-sampling and objective usage-tracking studies, field experiments, and lab experiments.
- Analysis: conceptual review and framework development, specifying primary predictors, mediators/mechanisms, and moderators/interactions for each hypothesis; no formal meta-analysis or new data collection is reported.
Limitations
- Stated: correlational findings need experimental tests for causal conclusions; measurement must distinguish screen time, frequency of use, notifications, and mere presence, and move beyond imprecise, biased self-reports to objective measures obtained over multiple days via mobile sensing.
- Stated: research needs to focus more on when multifunctional devices are beneficial versus detrimental; the authors describe their conclusions as “(very) preliminary,” and note that mere-presence studies were likely underpowered (Ns < 100).
- Evident: as a review and agenda-setting article, it does not provide new empirical tests of the D.I.C. framework, and its integration relies on selected findings rather than a systematic meta-analytic synthesis.
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Claims the paper makes
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None of the sources cited for this claim have been checked yet.
In the paper
“Importantly, these studies also show that this net negative effect is small and that the relationship is not linear: People who spend some time in front of screens feel better than those who spend no time, but heavy users feel notably worse [5, 6*].”
What the sources say
- Not checked yetcites [5] [5]. Przybylski AK, Weinstein N: A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychol Sci 2017, 28: 204-215. https://doi.org/10.1177/0956797616678438 - source
- Not checked yetcites [6*]
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“Importantly, these studies also show that this net negative effect is small and that the relationship is not linear: People who spend some time in front of screens feel better than those who spend no time, but heavy users feel notably worse [5, 6*].”
What the sources say
- Not checked yetcites [5] [5]. Przybylski AK, Weinstein N: A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychol Sci 2017, 28: 204-215. https://doi.org/10.1177/0956797616678438 - source
- Not checked yetcites [6*]
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“People's subjective estimates of their average screen time share as little as 10% variance with their actual screen time when measured objectively [9].”
What the sources say
- Not checked yetcites [9] [9]. Araujo T, Wonneberger A, Neijens P, de Vreese C: How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use. Commun Methods Meas 2017 , 11: 173-190. https://doi.org/10.1080/19312458.2017.1317337 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“Importantly, these studies also show that this net negative effect is small and that the relationship is not linear: People who spend some time in front of screens feel better than those who spend no time, but heavy users feel notably worse [5, 6*].”
What the sources say
- Not checked yetcites [5] [5]. Przybylski AK, Weinstein N: A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychol Sci 2017, 28: 204-215. https://doi.org/10.1177/0956797616678438 - source
- Not checked yetcites [6*]
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA 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
“Thus, even when phone use is not replacing other activities, phones can still interfere with concurrent activities (Table 1).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
None of the sources cited for this claim have been checked yet.
In the paper
“Across large representative samples of adolescents, researchers have consistently found that more self-reported screen time-on all devices, digital devices only, and phones more specifically-predicts slightly lower well-being [4*,5,6*,7,8].”
What the sources say
- Not checked yetcites [4*]
- Not checked yetcites [5] [5]. Przybylski AK, Weinstein N: A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychol Sci 2017, 28: 204-215. https://doi.org/10.1177/0956797616678438 - source
- Not checked yetcites [6*]
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“From this perspective, smartphones can negatively impact well-being primarily by reducing the time we spend doing other activities that are essential for well-being, such as sleeping [18,19,20] or socializing [21].”
What the sources say
- Not checked yetcites [18] [18]. Christensen MA, Bettencourt L, Kaye L, Moturu ST, Nguyen KT, Olgin JE, Pletcher MJ, Marcus GM: Direct measurements of smartphone screen-time: Relationships with demographics and sleep . PLoS ONE 2016 , 11: 1-14. https://doi.org/10.1371/journal.pone.0165331 - source
- Not checked yetcites [19] [19]. Lanaj K, Johnson RE, Barnes CM: Beginning the workday yet already depleted? Consequences of late-night smartphone use and sleep. Organ Behav Hum Decis Process 2014, 124 :11-23. https://doi.org/10.1016/j.obhdp.2014.01.001 - source
- Not checked yetcites [20] [20]. Rosen L, Carrier LM, Miller A, Rokkum J, Ruiz A: Sleeping with technology: Cognitive, affective, and technology usage predictors of sleep problems among college students. Sleep Health 2016, 2: 49-56. https://doi.org/10.1016/j.sleh.2015.11.003 - source
- Not checked yetcites [21] [21]. Waytz A, Gray K: Does online technology make us more or less sociable? A preliminary review and call for research. Perspect Psychol Sci 2018 , 13: 473-491. https://doi.org/10.1177/1745691617746509 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA 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 if we measured phone screen time more precisely, however, we would still get an incomplete picture of the effects of smartphones on well-being.”
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“According to the interference hypothesis [24,25], the frequency of phone use is critical for understanding the effects of smartphones on well-being (Table 1).”
What the sources say
- Not checked yetcites [24] [24]. Kushlev K, Dwyer R, Dunn EW: The social price of constant connectivity: Smartphones impose subtle costs on well-being. Curr Dir Psychol Sci 2019 , 28: 347352. https://doi.org/10.1177/0963721419847200 - source
- Not checked yetcites [25] [25]. Sbarra DA, Briskin JL, Slatcher RB: Smartphones and close relationships: The case for an evolutionary mismatch. Perspect Psychol Sci 2019 , 14: 596-618. https://doi.org/10.1177/1745691619826535 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
None of the sources cited for this claim have been checked yet.
In the paper
“Importantly, these studies also show that this net negative effect is small and that the relationship is not linear: People who spend some time in front of screens feel better than those who spend no time, but heavy users feel notably worse [5, 6*].”
What the sources say
- Not checked yetcites [5] [5]. Przybylski AK, Weinstein N: A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychol Sci 2017, 28: 204-215. https://doi.org/10.1177/0956797616678438 - source
- Not checked yetcites [6*]
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- Probably not a substantial claim. 10
- It may state two separate claims as one. 12
None of the sources cited for this claim have been checked yet.
In the paper
“According to the displacement hypothesis [16], screen time-regardless of whether it is on a desktop, TV, or phone-influences psychological outcomes by replacing other activities (c.f., Bowling Alone ; [17]).”
What the sources say
- Not checked yetcites [16] [16]. Neuman SB: The displacement effect: Assessing the relation between television - viewing and reading performance. Read Res Q 1988 , 23: 414-440. https://doi.org/10.2307/747641 - source
- Not checked yetcites [17] [17]. Putnam RD: Bowling alone: America's declining social capital. J Democr 1995 , 6: 6578. https://doi.org/10.1353/jod.1995.0002 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
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
“We suggest that we cannot draw either of those conclusions based solely on correlational analyses of self-reported screen time.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Thus, though positively related, frequency and time of phone use are distinct variables, estimated to share only about 10%-15% variance [12**,13**].”
What the sources say
- Not checked yetcites [12**]
- Not checked yetcites [13**]
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“Such measurement error, which depends on the construct measured, may change both the size of the effects and the shape of the relationship.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“We propose that disparate strands of research and apparently contradictory findings can be integrated under three basic hypotheses, positing that smartphones influence well-being by (1) replacing other activities ( displacement hypothesis ), (2) interfering with concurrent activities ( interference hypothesis ), and (3) affording access to information and activities that would otherwise be unavail”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably 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
“Thus, we must formulate a final complementarity hypothesis : Smartphones can boost well-being by affording access to information, communication, and experiences that would otherwise be unavailable.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“People check their phones frequently, an estimated 50 times a day, but they only spend a little over a minute on their phones at a time with only 5% of instances lasting longer than 10 minutes [15].”
What the sources say
- Not checked yetcites [15] [15]. MacKay J: Screen time stats 2019: Here's how much you use your phone during the workday. 2019. [Accessed April 24 2020] In: https://blog.rescuetime.com/screen-timestats-2018/ -
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“We propose that researchers' contradictory conclusions about the well-being effects of phones are largely due to methodological issues and can be integrated under an overarching theoretical framework by considering when, how, and why phones promote versus hurt wellbeing.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclearIt may state two separate claims as one.
In the paper
“Furthermore, light users tend to overestimate their screen time, whereas heavy users tend to underestimate their screen time [9].”
What the sources say
- Not checked yetcites [9] [9]. Araujo T, Wonneberger A, Neijens P, de Vreese C: How much time do you spend online? Understanding and improving the accuracy of self-reported measures of internet use. Commun Methods Meas 2017 , 11: 173-190. https://doi.org/10.1080/19312458.2017.1317337 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“Smartphones can and do provide benefits for well-being, but those benefits depend on people's current emotional experience, the contextual affordances, and the relevance of their phone use to current goals and activities (Table 1).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“We have proposed an overarching displacement-interference-complementarity (D.I.C.) theoretical framework (Table 1), which integrates apparently contradictory findings by considering how, when, and why phones impact well-being.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Having one's phone within easy reach does not directly impair people's ability to sustain attention, but it does impair cognitive capacity, such as working memory [33].”
What the sources say
- Not checked yetcites [33] [33]. Ward AF, Duke K, Gneezy A, Bos MW: Brain drain: The mere presence of one's own smartphone reduces available cognitive capacity. J Assoc Consum Res 2017, 2: 140154. https://doi.org/10.1086/691462 -
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt 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
“In contrast, the interference hypothesis predicts that phones will influence well-being to the extent that they distract people from other concurrent activities.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
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
“Based on the interference hypothesis, we can predict that the mere presence of one's phone should only interfere with one's ability to enjoy cognitively demanding activities (e.g., a deep conversation), but not simpler pleasures (e.g., a beautiful sunset).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
In the paper
“Indeed, although phone-mediated communication, such as text messaging, predicts lower well-being outcomes when people are concurrently socializing face-to-face, phone-mediated communication has little effect on well-being when people are alone [40].”
What the sources say
- Not checked yetcites [40] [40]. Kushlev K, Heintzelman SJ: Put the phone down: Testing a complement-interfere model of computer-mediated communication in the context of face-to-face interactions. Soc Psychol Personal Sci 2018, 9 :702-710. https://doi.org/10.1177/1948550617722199 - source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Recent research has suggested that even the mere presence of one's smartphone can impair basic cognitive processes [32,33].”
What the sources say
- Not checked yetcites [32] [32]. Canale N, Vieno A, Doro M, Rosa Mineo E, Marino C, Billieux J: Emotion-related impulsivity moderates the cognitive interference effect of smartphone availability on working memory. Sci Rep 2019, 9: 18519. https://doi.org/10.1038/s41598-019-54911-7 - source
- Not checked yetcites [33] [33]. Ward AF, Duke K, Gneezy A, Bos MW: Brain drain: The mere presence of one's own smartphone reduces available cognitive capacity. J Assoc Consum Res 2017, 2: 140154. https://doi.org/10.1086/691462 -
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“Finally, because the D.I.C. framework is formulated around the distinguishing factor of smartphones-their portability-the framework can easily be applied to the increasingly portable technologies of the future.”
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
In the paper
“Consistent with these predictions, a small study found that the mere presence of a mobile phone during a dyadic social interaction, prevented people from cultivating a sense of social connection, trust, and empathy when discussing a meaningful topic but not when discussing a more casual topic: plastic holiday trees [34].”
What the sources say
- Not checked yetcites [34] [34]. Przybylski AK, Weinstein N: Can you connect with me now? How the presence of mobile communication technology influences face-to-face conversation quality. J Soc Pers Relat 2012, 30: 237-246. https://doi.org/10.1177/0265407512453827 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“- 3) The net effects of phones on well-being are typically small to negligible but become substantial with heavy, problematic (over)use (i.e., use that is likely to displace or interfere with other activities).”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclearIt 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
“Thus, the displacement hypothesis suggests that attention should moderate the relationship between screen time and well-being.”
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
In the paper
“While not as impactful as talking with somebody in person, receiving social support via text message is better for well-being than receiving no support at all [38].”
What the sources say
- Not checked yetcites [38] [38]. Holtzman S, DeClerck D, Turcotte K, Lisi D, Woodworth M: Emotional support during times of stress: Can text messaging compete with in-person interactions? Comput Human Behav 2017, 71: 130-139. https://doi.org/10.1016/j.chb.2017.01.043 - source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The authors state this as an assumption.
The net effects of phones on well-being at any given time depend on the well-being people gain by using their phones minus the well-being they would have gained had they not used their phones.
“The displacement and interference hypotheses both assume that the net effects of phones on well-being, at any given time, will depend on the well-being people gain by using their phones, minus the well-being that people would have gained had they not used their phones.”
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?
In the citing paper
“This perspective aligns with the displacement hypothesis, which posits that time spent on social media may have detrimental effects by displacing activities that are beneficial to well-being and health—for example, sleep, exercise, or face-to-face interactions.7,26”
From Social Media Use and Its Link to Physical Health Indicators (2022) · cites this paper as [26]
Citations
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“From this perspective, smartphones can negatively impact well-being primarily by reducing the time we spend doing other activities that are essential for well-being, such as sleeping [18,19,20] or socializing [21].”
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Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep
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Do smartphone usage scales predict behavior?
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The Ideal Self at Play: The Appeal of Video Games That Let You Be All You Can Be
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Two social lives: how differences between online and offline interaction influence social outcomes
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The Smartphone as a Pacifying Technology
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The displacement effect: assessing the relation between television viewing and reading performance
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Batching smartphone notifications can improve well-being
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Self-citationEllis, D. A. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.03.006 · Cited by 186
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Smartphones and close relationships: the case for an evolutionary mismatch
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Growing up in the digital age: Early learning and family media ecology
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Determining typical smartphone usage: What data do we need?
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[17] No-way InteractionsPreprint
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Flagged first, then by citations
1 of the 47 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Simonsohn, 2014, 5, e142559
Cited by
Sorted by citations
Godard, R., & Holtzman, S. (2023) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmad055 · Cited by 171
Marinucci, M., Pancani, L., Aureli, N., & Riva, P. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107102 · Cited by 119
A Nudge-Based Intervention to Reduce Problematic Smartphone Use: Randomised Controlled Trial
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“Problematic smartphone use may have negative consequences because it replaces or interferes with activities that increase well-being, such as sleeping, exercising, or (in-person) socialising (Kushlev & Leitao, 2020).”
BackgroundResultAbeele, M. V., Vandebosch, H., Koster, E. H. W., Leyn, T. D., Gaeveren, K. V., Vicente, D. D. S., Bruyssel, S. V., van Timmeren, T., Marez, L. D., Poels, K., et al. (2023) · Communication Theory · doi:10.1093/ct/qtad016 · Cited by 97
Gui, M., Gerosa, T., Argentin, G., & Losi, L. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104705 · Cited by 83
Metadata
- Authors
- Kushlev, K., & Leitao, M. R.
- Affiliations
- Georgetown University (US)
- Corresponding author
- Kushlev, Kostadin
- Venue
- Current Opinion in Psychology
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 36
- Pages
- 77-82
- ISSN
- 2352-250X (ISSN-L)
- OpenAlex
- W3027003509
- Semantic Scholar
- 70d0db5af49d3987c0399094f95ea28a6c07914b
- Cited by
- 129
- References
- 47
- Citations by year
- 2026: 36 · 2025: 18 · 2024: 20 · 2023: 24 · 2022: 16 · 2021: 13 · 2020: 2
- FWCI
- 2.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Current Opinion in Psychology (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Communication › Digital Media and Philosophy
- Keywords
- smartphones, well-being, displacement theory, interference hypothesis, complementarity hypothesis, psychological mediators, contextual moderators
- MeSH terms
- Smartphone, Humans
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