Does Having Your Phone Nearby Hurt Concentration? A Review of the Evidence on the Brain Drain Effect

Keywords: smartphone presence; brain drain; working memory; sustained attention; notifications; replication; meta-analysis

Abstract

Background. A widely reported 2017 study concluded that the mere presence of one's own smartphone, silent and face down, reduces available cognitive capacity. The finding has shaped advice to students and office workers to put the phone in another room.

Aims. This review asks whether a phone that is nearby but unused lowers performance on tasks that demand concentration, and how that question differs from the effects of notifications and active use.

Method. A single-reviewer narrative review of peer-reviewed journal articles located through OpenAlex, Crossref, Semantic Scholar, Europe PMC and extended web searches in October 2026. Eighteen sources were included and appraised with the CRAAP test.

Results. The original experiments and several later ones reported costs of phone presence on working memory, recall or attention tests. A preregistered direct replication found none, and neither did a memory experiment, two classroom experiments or a study of schoolchildren. Three meta-analyses disagree in degree: one found a small negative pooled effect concentrated in memory tasks, one found a small effect on working memory and null effects elsewhere, and the largest found no effect (d = −0.02). Notifications and incoming messages produced clearer costs, and in one experiment a phone on silent carried a cost that a switched-off phone did not. In some studies the effect of presence depended on how much the person thought about the phone.

Conclusions. The evidence does not support a reliable average cost of a silent, unused phone in view. It supports reducing interruptions during demanding work, and it leaves open whether removing the phone helps particular people.

1. Introduction

In 2017, Adrian Ward, now at the University of Texas at Austin, and colleagues at the University of California San Diego published two experiments on what they called the brain drain hypothesis. Their claim was that a smartphone occupies limited cognitive resources simply by being present, even when its owner successfully resists checking it, and that the cost is largest for people most dependent on their phones (Ward et al., 2017).

A phone can affect concentration through at least two routes. It can interrupt, through alerts and incoming messages that pull attention away from the task. It can also, on the brain drain account, draw on attention silently, because part of the mind is busy not attending to it. These routes call for different remedies. The first is addressed by notification settings, and the second, if it exists, by distance. This review separates them and asks a narrow question: does a phone that is nearby, silent and unused lower performance on demanding tasks, and how large and reliable is that effect?

This Journal's review of background music while studying concerns sound that competes with verbal processing; the present review concerns a silent object.

2. Method

2.1 Search strategy

Searches were run in October 2026. OpenAlex was used to retrieve records, abstracts and author institutions by DOI; its search endpoint returned rate-limit errors during this run, so keyword searches were run in Crossref, Semantic Scholar and Europe PMC instead, supplemented by extended web searches. Search strings combined "smartphone", "mobile phone" or "cell phone" with "mere presence", "brain drain", "working memory", "attention", "notification", "separation" and "replication". Searches for counter-evidence used "no evidence", "did not replicate" and "null". Reference lists of the three meta-analyses were checked for primary experiments.

2.2 Eligibility criteria

Sources were included when they (a) appeared in a peer-reviewed journal, (b) reported a controlled experiment, a randomised trial or a meta-analysis, (c) manipulated the presence, availability or notifications of a phone, or access to its internet functions, and (d) measured attention, memory, learning or another cognitive outcome. Studies of social interaction, driving and walking were excluded, as were preprints, theses and conference papers. Where a preprint and a journal version of the same work existed, only the journal version was used.

2.3 Appraisal with the CRAAP test

Each source was appraised on the five CRAAP criteria. Currency weighed the publication date against later replications. Relevance assessed how closely the manipulation matched a phone that is present but unused, and how closely the task resembles focused work or study. Authority required publication in a peer-reviewed journal. Accuracy examined design, sample size, preregistration and whether conclusions stay within the data. Purpose checked for an academic aim and the absence of a commercial interest in the outcome. Full text was read for Böttger et al. (2023), Canale et al. (2019), Skowronek et al. (2023), Tanil and Yong (2020) and Hartanto et al. (2024). For Castelo et al. (2025) and Le Roux et al. (2025), the published article pages were read for design and results. For the other sources, data were taken from the published abstracts and bibliographic records.

2.4 Appraisal results

Source	Design	Appraisal notes	Decision
Ward et al. (2017)	Two experiments	The founding study; consumer-research journal; later replications failed.	Included
Thornton et al. (2014)	Two experiments	Early mere-presence evidence; the title hedges its own claim.	Included, low weight
Stothart et al. (2015)	Experiment	Notifications without phone use; strong journal; tests interruption alone.	Included
Hartanto & Yang (2016)	Two experiments	Tests separation from the phone; relevant counter-hypothesis.	Included
Mendoza et al. (2018)	Two experiments, lecture	Realistic learning task; phone condition included incoming texts, so presence and interruption are combined.	Included with caveat
Johannes et al. (2019)	Preregistered experiment, Bayesian sequential design	Separates felt distraction from performance.	Included
Canale et al. (2019)	Experiment, n = 132	Compares phone switched off, phone on silent and a calculator.	Included
Tanil & Yong (2020)	Experiment, n = 119	Memory task; measures thoughts about the phone.	Included
Hartmann et al. (2020)	Experiment	Short-term and prospective memory; null main effect.	Included
Ruiz Pardo & Minda (2022)	Preregistered direct replication	Same tasks and conditions as Ward et al. Experiment 2; null.	Included
Böttger et al. (2023)	Meta-analysis, 22 studies, 43 effects	Pools use and presence; high heterogeneity.	Included with caveat
Skowronek et al. (2023)	Experiment, n = 42	Attention test at home over video call; small sample.	Included, low weight
Parry (2024)	Systematic review and six meta-analyses, k = 56	Separates cognitive functions; notes low power in the field.	Included
Hartanto et al. (2024)	Four-level meta-analysis, 166 effects, 33 studies	Largest synthesis; not preregistered; participant totals inconsistent between abstract and results.	Included
Castelo et al. (2025)	Preregistered randomised trial with waitlist control	Blocks mobile internet, a manipulation of access; low compliance.	Included with caveat
Le Roux et al. (2025)	Two cluster-randomised classroom experiments	Ecological setting; shares an author with Parry (2024).	Included
Figl et al. (2026)	Within-subjects online experiment, n = 162	Measures flow and learning; separates presence from use.	Included
Greenfield et al. (2026)	Repeated-measures experiment, n = 106 children	Reading comprehension at school; third- and sixth-grade children.	Included, limited generalisability

3. Findings

3.1 The original evidence

Ward et al. (2017) report two experiments in which participants completed cognitive tasks with their own phone on the desk, in a pocket or bag, or in another room. On their account, the mere presence of the phone reduced available cognitive capacity even when participants maintained sustained attention and did not check it, and the cost was highest for those highest in smartphone dependence. Earlier, Bill Thornton and colleagues at the University of Southern Maine had reported two studies in which a phone that was merely present diminished attention and task performance, especially on more demanding tasks; the title of their paper states that a phone "may" be distracting (Thornton et al., 2014).

Several later experiments reported costs of the same kind. Clarissa Tanil and Min Hooi Yong at Sunway University assigned 119 undergraduates to complete a demanding memory task with the phone face down on the desk or out of sight. Recall accuracy was higher without the phone (M = 14.21 against 13.08; d = 0.44). Smartphone addiction scores were unrelated to recall. How often participants reported thinking about their phone predicted lower accuracy, in both conditions (Tanil & Yong, 2020). At Paderborn University, Skowronek et al. (2023) gave 42 participants a standard paper-and-pencil attention test at home. Those with the phone covered on the table scored lower on the overall attention measure than those whose phone was switched off in another room (F(1, 40) = 6.17, p = .017, η² = .13), and worked more slowly; accuracy did not differ.

3.2 Replications that did not find the effect

Ana Cecilia Ruiz Pardo and John Paul Minda at Western University in Canada ran a preregistered direct replication of Ward et al.'s second experiment, using the same tasks and crossing phone location (desk, pocket or bag, outside the room) with power (on or off). There was no difference between location conditions on either the working memory task or the response-inhibition task (Ruiz Pardo & Minda, 2022). In Switzerland, Hartmann et al. (2020) found no overall effect of a phone on the desk on short-term or prospective memory. They did find a moderating effect, in the opposite direction to the one Ward et al. reported for dependence: for participants with low smartphone dependency, prospective memory was better when the phone was absent.

Studies in schools reached similar conclusions. Le Roux et al. (2025) ran two cluster-randomised experiments during ordinary class sessions at two South African high schools, with 195 and 115 learners, using a fluid-intelligence test. In the preregistered models, phone location did not significantly predict scores. Small differences appeared in some unadjusted comparisons, which the authors judged not robust, and they describe all their findings as tentative. Greenfield et al. (2026), at the University of California, Los Angeles, studied 106 third- and sixth-grade children. Those who had brought a phone to school took one reading-comprehension test with the phone beside them and another without it in sight. Whether the phone was in sight made no difference to comprehension.

3.3 What the meta-analyses show

Three meta-analyses published between 2023 and 2024 summarise this literature, and they disagree in degree. Tobias Böttger and colleagues at the University of Augsburg pooled 43 effects from 22 studies and found a small negative effect (g = −0.14, 95% CI [−0.24, −0.03]) with substantial heterogeneity (I² = 61.84). Only the memory subgroup was significant (g = −0.23); effects on attention (g = −0.07) and general cognitive performance were not. Their abstract describes the pooled result as an effect of smartphone use and presence, so it does not isolate presence alone, and the pooled effect was significant for studies from Asia and not for those from Europe or North America (Böttger et al., 2023).

Douglas Parry at Stellenbosch University reported a systematic review and six meta-analyses (k = 56, n = 7,093). Working memory capacity was the only function with a significant negative pooled effect; the others produced null summary effects. Parry also found substantial methodological heterogeneity and generally poor statistical power, and concluded that the literature can neither firmly support nor refute the hypothesis (Parry, 2024). The largest synthesis, by Andree Hartanto and colleagues at Singapore Management University, combined 166 effect sizes from 33 studies and found no significant effect of phone presence on cognitive outcomes (d = −0.02, 95% CI [−0.06, 0.01]). The effect was not moderated by smartphone dependency, by where the phone was kept in the comparison condition, or by whether it lay face up or face down. For the operation span task, the working memory measure used by Ward et al., a small effect (d = −0.13) fell to d = −0.04 after adjustment for publication bias (Hartanto et al., 2024).

3.4 Notifications and availability

The evidence on interruption is more consistent. Cary Stothart and colleagues at Florida State University found that phone notifications alone significantly disrupted performance on an attention-demanding task, even though participants did not interact with the phone, and judged the disruption comparable in magnitude to effects seen when people actively use a phone (Stothart et al., 2015). Mendoza et al. (2018) showed a 20-minute lecture to students who either kept their phone, and received text messages during the lecture, or had it removed. Students who kept their phone did worse on quiz questions about material from the third quarter of the lecture. Because the phone condition included incoming texts, this study tests presence and interruption together.

Canale et al. (2019), at the University of Padua and the University of Luxembourg, separated the two more precisely. Students completed a visual working memory task with their phone visible and switched off, visible and on silent, or replaced by a calculator. Performance was lower with the phone on silent than with the phone switched off (d = 0.38), while neither phone condition differed significantly from the calculator. Students who tend to act rashly when in a strongly positive mood were most affected. The authors suggest that the possibility of receiving a message may be what produces the interference. In a preregistered experiment at Radboud University, Johannes et al. (2019) found that a visible phone made students feel more vigilant and distracted, especially when notifications arrived, yet these experiences were unrelated to performance on a response-inhibition task.

3.5 Separation, attention to the phone and flow

Removing the phone has its own effects. Hartanto and Yang (2016) found in two experiments that separating participants from their phone raised state anxiety, and that this anxiety mediated poorer performance on executive-function tasks. Le Roux et al. (2025) did not find raised anxiety when high school learners were separated from their phones. In an online learning experiment with 162 undergraduates at the University of Innsbruck, Figl et al. (2026) found that absence of the phone increased self-reported flow and reduced perceived distraction, and that flow predicted learning performance. In this study, active use of the phone disrupted flow, and mere presence had no significant overall effect on learning outcomes. Students higher in nomophobia, the fear of being without one's phone, were more distracted in every condition and performed better when the phone was absent.

A different manipulation tests access to the phone's internet functions. In a preregistered randomised trial, Noah Castelo of the University of Alberta, with Ward and colleagues, blocked all mobile internet on participants' iPhones for two weeks while calls and texts remained available. Sustained attention, measured with a continuous performance task, improved (d_z = 0.24 for the first intervention group). Only 119 of 467 participants met the preregistered compliance threshold of at least 10 blocked days, the sample was motivated to reduce phone use, and the control was a waitlist, so expectancy effects cannot be excluded (Castelo et al., 2025).

4. Discussion

4.1 Presence and interruption are different questions

The findings sort into two groups. Studies that manipulated whether a silent phone was present produced a mix of small effects and nulls, and the largest meta-analysis estimates the average effect at close to zero (Hartanto et al., 2024). Studies that manipulated notifications, incoming messages or whether the phone was switched on found costs more consistently (Stothart et al., 2015; Mendoza et al., 2018; Canale et al., 2019). A plausible reading is that the phone's cost lies mainly in what it might deliver. The brain drain account, in which presence alone consumes capacity, receives at most weak support for working memory tasks (Parry, 2024), and that support shrinks after correction for publication bias (Hartanto et al., 2024).

A second pattern concerns the person. In several studies, the effect of the phone depended on how much participants thought about it (Tanil & Yong, 2020), on impulsivity (Canale et al., 2019) or on fear of being without it (Figl et al., 2026). These moderators did not replicate cleanly: Hartmann et al. (2020) found an advantage of absence among participants with low dependency, and Hartanto et al. (2024) found no moderation by dependency. Individual differences appear to matter in some designs, and the literature has not yet identified which ones reliably.

4.2 Limitations of the evidence

Most experiments are small, and Parry (2024) reports generally poor statistical power in the field. Tasks are short laboratory measures, often a single working memory or attention test lasting minutes, whereas concentration at work or in study is sustained for hours. Most studies were not double-blind, so expectancy effects are possible (Hartanto et al., 2024). The meta-analyses overlap in their primary studies and differ in what they pool, which limits how independent their conclusions are. Le Roux et al. (2025) and Parry (2024) share an author. The trial by Castelo et al. (2025) changed access to the internet over two weeks, which is a different intervention from moving a phone across a room, and its low compliance and waitlist control limit causal inference.

5. Practical implications

The recommendations below are graded by the strength of the evidence behind them.

1. During demanding work, silence notifications and avoid receiving messages. Notifications disrupted attention even when ignored (Stothart et al., 2015), and incoming texts during a lecture lowered learning (Mendoza et al., 2018). Strength: moderate and consistent across designs.
2. Switching the phone off may help more than silent mode. A phone on silent produced a measurable cost that a switched-off phone did not (Canale et al., 2019). Strength: a single experiment.
3. Do not expect a large gain from moving a silent phone out of sight. The pooled estimates range from small to null (Böttger et al., 2023; Parry, 2024; Hartanto et al., 2024). Moving it costs little, and some people report less distraction and more absorption without it (Figl et al., 2026). Strength: the null average is well supported; the subjective benefit rests on one study.
4. Notice whether the phone occupies your thoughts. Thinking about the phone predicted poorer recall (Tanil & Yong, 2020), and people who fear being without it learned better when it was absent (Figl et al., 2026). If separation makes you anxious, distance may cost more than it saves (Hartanto & Yang, 2016). Strength: correlational within experiments.
5. Reducing mobile internet access over weeks may improve sustained attention for motivated people. Strength: one preregistered trial with low compliance (Castelo et al., 2025).

In practice, the most defensible step is to decide in advance when the phone will be checked, so that a block of focused work carries no incoming messages. A planning app such as Flowo can hold that block on the day's schedule; the notification settings remain a separate decision on the phone itself. The review of what happens after you start a task discusses why an interrupted task tends to pull attention back.

6. Limitations of this review

This is a narrative review with structured appraisal. It was not preregistered, a single reviewer conducted screening and appraisal, only English-language sources were searched, and publication bias was assessed only as reported by the included meta-analyses. Full text was read for seven sources; for the others, data were taken from abstracts and bibliographic records, so moderators reported only in full texts may be missing. Keyword searches could not use OpenAlex during this run, so studies indexed there alone may have been missed.

7. Conclusion

The claim that a silent smartphone within sight drains concentration rests on early experiments that later direct replications did not reproduce, and the largest meta-analysis places its average effect close to zero. A small cost to working memory or recall remains possible, especially in some people, but it is uncertain in size. The evidence is stronger for the phone as a source of interruption: notifications and incoming messages carried measurable costs. For focused work, that points to controlling what the phone can deliver during the session. The open questions concern long work sessions and the individual traits that make a phone hard to ignore, and they call for larger preregistered studies of realistic duration.

Frequently asked questions

Should I put my phone in another room to study?

The average effect of a silent phone in sight was close to zero in the largest meta-analysis (Hartanto et al., 2024). Moving it costs little, and one study found more absorption and less felt distraction without it (Figl et al., 2026). If being apart from the phone makes you anxious, that anxiety can itself lower performance (Hartanto & Yang, 2016).

Is silent mode enough?

In one experiment a phone on silent produced a cost to working memory that a switched-off phone did not (Canale et al., 2019). Notifications, even when ignored, disrupted attention in another (Stothart et al., 2015). Turning notifications off for the session is the step with the most support.

Does putting the phone face down help?

Placement face up or face down did not moderate the effect in the largest meta-analysis (Hartanto et al., 2024).

Was the brain drain study wrong?

A preregistered direct replication found no effect (Ruiz Pardo & Minda, 2022), and meta-analyses estimate the effect as small or null (Parry, 2024; Hartanto et al., 2024). The original result is best read as an early estimate that later work did not confirm at its original size.

References

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• Canale, N., Vieno, A., Doro, M., Rosa Mineo, E., Marino, C., & Billieux, J. (2019). Emotion-related impulsivity moderates the cognitive interference effect of smartphone availability on working memory. Scientific Reports, 9, Article 18519. https://doi.org/10.1038/s41598-019-54911-7
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Conflict of interest: the author is a co-founder of Flowo, a planning app. None of the studies cited was funded by or connected to the company.

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