Phones, laptops, and connected devices are now built into most workflows, but the same always-available design also creates frequent opportunities for attention to fracture. Research in cognitive psychology and workplace economics increasingly treats distraction as more than “time wasted” on a screen. It can show up as reduced working memory, weaker reasoning on demanding tasks, and a higher tendency to drift toward irrelevant cues—effects that matter most when work requires sustained mental effort, problem solving, and complex decision-making.

One of the clearest demonstrations comes from Ward, Duke, Gneezy, and Bos’s “brain drain” experiments on smartphone presence. Across two lab studies with university participants, simply having one’s own smartphone present reduced available cognitive capacity, even when people were not using it and did not report thinking about it.

The researchers manipulated salience by placing phones on the desk (high salience), in a pocket/bag (medium), or in another room (low). Performance improved as phones became less salient, with a significant linear trend: as smartphone salience increased, available working memory capacity and fluid intelligence decreased. In a follow-up experiment, turning phones fully off (vs. on and silenced) did not remove the effect, supporting the idea that the cost is not just about incoming notifications.

Importantly, the effect was strongest among participants higher in smartphone dependence: those who felt they “needed” their phone most showed the biggest cognitive penalty when it was nearby. Meanwhile, a separate line of evidence links distraction to broader information-processing habits: Ophir, Nass, and Wagner found that heavy media multitaskers were more susceptible to interference from irrelevant stimuli and performed worse on a task-switching measure, consistent with reduced filtering of distractions.

Workplace research complements the lab picture by testing what happens when phone access is restricted during routine labor. Chadi, Mechtel, and Mertins ran a field experiment during a nationwide telephone survey and randomly imposed smartphone-use bans for interviewers working alone. They observed substantial increases in effort under bans, and they did not find evidence that bans triggered negative reactions tied to perceived employer distrust.

However, higher effort did not automatically translate into clear economic benefits, because the number of completed interviews did not necessarily rise in step with effort. This aligns with a practical takeaway from the cognitive studies: removing distraction can improve mental capacity and task engagement, but output gains depend on whether the job’s bottleneck is attention, skill, process design, or constraints outside the worker’s control.

Across contexts, the science in these sources points to a consistent hierarchy of solutions. Turning the phone face down or powering it off is not reliably sufficient when the device remains nearby and salient. The most supported intervention is planned separation—creating defined periods where the phone is physically removed (for example, placed in another room).

In education research, a systematic review by Martin, Long, Haywood, and Xie also emphasizes a multi-factor model: distractions arise from technology factors, personal needs, and the environment, and prevention strategies span environment rules, technology controls, and behavioral interventions—with no single lever working everywhere.