The mere presence of a smartphone reduces basal attentional performance

This study investigates whether the mere presence of one’s own smartphone—specifically, a switched-off device—impairs attention by consuming limited cognitive resources. Drawing on working memory models and Cognitive Load Theory, the authors posit that smartphones function as extraneous cognitive load even without interaction, potentially diverting attention and reducing performance. Prior literature offers mixed evidence: several studies show that smartphone presence or availability (often with devices turned on) reduces attention, working memory, and task performance, whereas recent work reports null effects in some memory domains and failed replications. To clarify these inconsistencies, the present study focuses on basal attentional processes (low-level tasks) rather than only high-level or complex tasks and tests the hypothesis that mere smartphone presence reduces attentional performance in college students.

• Cognitive resource limits and executive functions suggest competing demands impair performance; Cognitive Load Theory distinguishes intrinsic from extraneous load, with overload reducing cognitive abilities.
• Distraction by smartphone cues (notifications, sounds, vibrations) impairs attention and learning; even passive notifications can be disruptive.
• Mere presence/availability effects: Studies (e.g., Thornton et al., Ward et al., Ito & Kawahara, Tanil & Yong, Canale et al., Liu et al., Schwaiger & Tahir) often report reduced working memory, attention, learning, and increased task difficulty when phones are present/available. Location (on desk vs. in another room) can modulate effects; some work finds effects regardless of power state, others only when phones are on.
• Moderators: smartphone dependence/addiction, internet attachment, excessive use may exacerbate interference.
• Contradictory findings: Some studies (e.g., Hartmann et al., Ruiz Pardo & Minda) found no overall presence effects on certain memory tasks and failed to replicate earlier results.
• Task demand: Several reports suggest effects emerge mainly in high-level tasks; low-level/basal attentional tasks often show weaker or null effects. The present study tests whether basal attentional performance is also impaired by mere presence of a switched-off phone.

Design: Between-subjects experimental study conducted via online video conferences due to COVID-19. Participants were randomly assigned to perform an attention test either with a switched-off smartphone present on the desk (face down) or with the switched-off smartphone placed outside the room (absent condition).

Participants: 49 college students initially recruited; 7 excluded (procedure issues, test errors, prior familiarity with the test), yielding N=42 (45.2% female), age 20–34 years (M=27.29, SD=2.87). Data were collected across 12 videoconference sessions (1–5 participants per session) in Feb–Mar 2021. Participation was voluntary, with informed consent and ethics approval from Paderborn University.

Attention measure: d2-R concentration and attention test. Task: cross out target letters (d with two marks) among 789 characters across 14 lines, with 20 s per line (total 4 min 40 s). Outputs: AP (attention performance; speed adjusted for errors), PTO (processed target objects; speed), and E% (standardized error percentage; accuracy). The d2-R assesses basal attentional processes and processing speed/accuracy.

Smartphone dependence: German short version of the Smartphone Addiction Scale (d-KV-SSS; 10 items; 6-point Likert; total 10–60; higher scores indicate stronger dependence). Minor wording modifications for clarity; Cronbach’s alpha = 0.78.

Procedure: Participants received detailed preparatory instructions to minimize distractions, including disabling computer notifications and arranging a clear desk with only test materials, pen, and smartphone. A standardized instruction video (to be watched on their own smartphone) ensured uniform guidance and verified phone ownership. After the video, participants were instructed to either place the switched-off phone on the desk (presence) or outside the room (absence). The experimenter delivered standardized test instructions and paced the d2-R (cues every 20 s). After the d2-R, participants completed the d-KV-SSS.

Statistical analysis: One-tailed one-way ANOVAs tested effects of condition (with vs. without smartphone) on AP, PTO, and E% (α=0.05). Assumptions (normality, homogeneity, independence) were checked; ANOVA used despite some non-normality due to robustness. Effect sizes reported as η² (small=0.01, medium=0.06, large=0.14). ANCOVA tested moderation by smartphone dependence.

• Attention performance (AP): Significant reduction with smartphone present vs. absent, F(1,40)=6.168, p=0.017, η²=0.134 (tending toward a large effect). Means: Without smartphone M=108.95; With smartphone M=99.71.
• Processing speed (PTO): Significant reduction with smartphone present vs. absent, F(1,40)=7.592, p=0.009, η²=0.160 (large effect). Means: Without smartphone M=108.57; With smartphone M=98.48.
• Accuracy (E%): No significant difference between conditions, F(1,40)=2.088, p=0.156, η²=0.050.
• Smartphone dependence (d-KV-SSS): Overall mean M=29.47 (SD=8.38); no significant mean difference between conditions, F(40,1)=0.065, p>0.05. ANCOVA showed no significant interaction; smartphone dependence did not moderate the presence effect.

Findings support the hypothesis that the mere presence of a switched-off smartphone reduces basal attentional performance by slowing processing speed, consistent with Cognitive Load Theory: the smartphone acts as extraneous load that consumes limited cognitive resources even without active interaction or visible attention. Contrary to several prior reports that effects arise mainly in high-level tasks, this study demonstrates a clear effect on low-level/basal attentional performance (d2-R). This aligns with research showing slower performance under phone availability and extends it to the mere presence of a switched-off phone. Results suggest spatial separation from one’s smartphone can mitigate interference, echoing prior work on phone location effects. While some studies report null effects for certain memory tasks or failed replications, the current findings clarify that basal attentional speed is particularly vulnerable to phone presence. The discussion also acknowledges contexts where phone presence might diffuse attention and benefit creativity, underscoring the need to match device policies to task demands.

The study shows that even the mere presence of one’s switched-off smartphone reduces attentional performance, primarily by slowing processing speed on a basal attention task. This contributes new evidence that low-level attentional processes are susceptible to smartphone presence, supporting a cognitive load account. Practically, moving the smartphone out of the room is an effective, simple strategy to avoid attentional costs during study or work. Future research should: (1) evaluate generalizability with larger, more diverse samples; (2) examine additional moderators (e.g., stronger dependence subgroups, device ownership effects); (3) compare settings (lab vs. naturalistic); (4) test other devices (e.g., tablets) and task types (including high-level vs. low-level); and (5) balance potential costs with contexts that may benefit from diffused attention (e.g., creativity tasks).

• Online, non-laboratory setting may introduce uncontrolled environmental distractions despite standardized instructions.
• Small, homogeneous sample (N=42), predominantly White, highly educated, young adults, limiting generalizability.
• Participants used their personal smartphones, introducing variability in device characteristics and personal relevance.
• Some deviations in instruction implementation across home environments cannot be fully ruled out.
• Low to moderate smartphone dependence in the sample may have limited detection of moderation effects.