To determine whether there is a general capacity for all working memory tasks, Turner and Engle (1989) developed a task called operation-word-spanor OSPAN. In this task, participants are asked to read and verify a simple math problem (such as "Is (4/2)-1=1 ?) and then read a word after the operation (such as SNOW). After a series of problems and words has been presented, the participants recall the words that followed each operation. The number of operation-word strings in a sequence is increased and decreased to measure the participant's operation span. Operation span measures predict verbal abilities and reading comprehension even though the subjects are solving mathematical problems. Engle and his colleagues have argued that this implies a general pool of resources that is used in every type of working memory situation.
We suggest that smartphones may also impair cognitive performance by affecting the allocation of attentional resources, even when consumers successfully resist the urge to multitask, mind-wander, or otherwise (consciously) attend to their phones—that is, when their phones are merely present.
"...the attractiveness of these high-priority stimuli should predict not just their ability to capture the orientation of attention, but also the cognitive costs associated with inhibiting this automatic attention response. "
We propose that the mere presence of one’s smartphone may impose a “brain drain” as limited-capacity attentional resources are recruited to inhibit automatic attention to one’s phone, and are thus unavailable for engaging with the task at hand.
We propose that the mere presence of one’s smartphone may impose a “brain drain” as limited-capacity attentional resources are recruited to inhibit automatic attention to one’s phone, and are thus unavailable for engaging with the task at hand.
Prior research suggests that smartphones are chronically salient for many individuals, even when they are located out of sight in one’s pocket or bag (e.g., Deb 2015).
We posit that individual differences in dependence on one’s smartphone will moderate the effects of smartphone salience on available cognitive capacity, such that individuals who most depend on their phones will suffer the most from their presence— and benefit the most from their absence.
After participants entered the testing room, they completed two tasks intended to measure available cognitive capacity: the Automated Operation Span task (Spain; Unsworth et al.2005) and a 10-item subset of Raven’ standard Progressive Matrices (RSPM; Raven, Raven, and Court 1998).
The OSpan task, a prominent measure of WMC, assesses the ability to keep track of task-relevant information while engaging in complex cognitive tasks.
In each trial set, participants complete a series of math problems (information processing) while simultaneously updating and remembering a randomly generated letter sequence (information maintenance).
The RSPM test, a nonverbal measure of Gf, was developed to isolate individuals’ capacity for understanding and solving novel problems (fluid intelligence), independent of any influence of accumulated knowledge or domain-specific skill (crystallized intelligence).
In each trial, participants are shown an incomplete pattern matrix and asked to select the element that best completes the pattern.
Next, participants completed a questionnaire that included items related to their experiences in the lab and their lay beliefs about the connection between smartphones and performance.
Other room condition performed better than those in the desk condition p=0.002
Pocket/bag condition did not perform significantly differently from those in either desk p=0.09 or other room p=0.11
It revealed a significant desk -> pocket/bag -> other room p=0.002
- Experiment:: 01
Our data indicate that the mere presence of one’s smartphone adversely affects two domain-general measures of cognitive capacity—available working memory capacity (WMC) and functional fluid intelligence (Gf)—even when participants are not using their phones and do not report thinking about them .
- Experiment:: 02
Data from experiment 2 replicate this effect on available cognitive capacity, show no effect on a behavioural measure of sustained attention, and provide evidence that individual differences in consumers’ dependence on their devices moderate the effects of smartphone salience on available WMC.
Five hundred forty-eight undergraduates (53.3% female; Mage 5 21.1 years; SDage 5 2.4 years) participated for course credit.
Our final sample consisted of 520 smartphone users.
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