Inattention over time-on-task: the role of motivation in mitigating temporal increases in media multitasking

The paper examines whether increasing motivation can mitigate temporal increases in media multitasking and associated declines in sustained attention and performance. Building on vigilance research showing attention and performance deteriorate with time-on-task, and recent work linking opportunity costs and boredom to rising media multitasking over time, the authors hypothesize that motivating instructions will elevate initial motivation and slow its decline, thereby attenuating increases in media multitasking and reducing the severity of performance decrements during a sustained attention (1-back) task.

Prior vigilance studies (e.g., Mackworth, 1948; Grier et al., 2003; Helton & Russell, 2011) show performance declines over time and self-reported decreases in attention. In contemporary settings, media multitasking often increases with time-on-task and correlates negatively with performance (Wammes et al., 2019; Drody et al., 2024; Ralph et al., 2020, 2021). Opportunity cost models (Kurzban et al., 2013) posit that perceived value of continuing a task decreases while the appeal of alternatives increases over time, with boredom signaling rising opportunity costs (Struk et al., 2020). Empirical work (Drody et al., 2024) found rising boredom and increased media multitasking with time, alongside reduced task effort and performance. Tam & Inzlicht (2024) further tie boredom and perceived opportunity costs to switching behavior in digital media. Interventions to curb media multitasking (education, awareness, blocking access) often show limited success, possibly because they fail to alter cost-benefit variables. Motivation reliably enhances attention and task performance (Engelmann & Pessoa, 2007; Robinson et al., 2012; Seli et al., 2015, 2019; Walsh et al., 2021), and Ralph et al. (2021) showed motivating instructions drastically reduced aggregate media multitasking. However, temporal dynamics of this effect remained unexplored.

Across two studies using a 1-back task with an optional concurrent video (TED talk “Brain Magic”), participants could toggle the video on/off via keypress, operationalizing media multitasking as the number of trials with the video on. Study 1 (re-analysis of Ralph et al., 2021 Experiment 1): - Participants: Initially N=166 (17–35 years, Mage≈19.43), recruited from a university pool; after exclusions (<30% hits or >20% false alarms), N=157 (78 Control, 79 Motivated; Mage=19.50, SD=2.51). - Task: 1-back task, 468 experimental trials (after removing 18 practice), each trial 500 ms letter (from B,F,K,H,M,Q,R,X,Z) followed by 2,000 ms fixation; respond if current letter matches previous; no performance feedback; continuous task (~20 min) without breaks except probes. - Media multitasking: Optional video displayed above stimuli; media multitasking quantified per trial. - Motivation manipulation: Random assignment. Control received standard instructions; Motivated were told they could leave early if performance up to ~20 min met criterion (in reality, duration identical across groups). - Self-reported motivation: Likert 1–7 assessed pre-task and post-task. - Analysis: Media multitasking summed per 9 blocks of 52 trials. GLMM with Poisson distribution; fixed effects: Condition (Control reference) and Block (centered), random intercepts and block slopes by participant. Performance (proportion hits, false alarms) analyzed via mixed factorial ANOVAs with Greenhouse–Geisser corrections due to sphericity violations. Study 2 (new online sample): - Participants: Recruited online from SONA; initially N=428 (1 agender, 6 genderqueer, 76 men, 339 women, 6 no answer; Mage=20.04, SD=3.36); after exclusions (<30% hits or >20% false alarms), final N=284 (154 Motivated, 130 Control; Mage=20.00, SD=3.40). - Task & media multitasking: Same 1-back and optional video paradigm; trials divided into 9 blocks of 52. - Motivation manipulation: Same instruction sets (Control vs Motivated with early-exit contingency). - Motivation measures: Pre- and post-task Likert 1–7; plus 9 in-task pseudo-random probes (one per block) “How motivated are you to do well on the (1-back) task?”. - Additional post-task questions: Enjoyment (1–7), interest (1–7), and in Motivated condition, specific motivation due to early exit (1–7). Assessed engagement in activities outside the experiment and whether they involved multimedia devices; supplementary analyses conducted excluding/including such participants. - Analytic approach: GLMM with Poisson for blockwise media multitasking, fixed effects Condition and centered Block, random intercepts/slopes; mixed-factorial ANOVAs for motivation over blocks and performance (hits, false alarms) over blocks with sphericity checks and Greenhouse–Geisser corrections.

- Study 1 motivation (pre vs post): Main effect of Condition, F(1,155)=15.86, p<0.001, ηp²=0.09 (Motivated>Control); main effect of Time, F(1,155)=9.21, p=0.003, ηp²=0.06 (motivation decreased from start to end); no Condition×Time interaction, F(1,155)=1.35, p=0.25. - Study 1 media multitasking GLMM: No main effects of Condition or Block, but significant Block×Condition interaction (Motivated showed more gradual increases), Estimate=−0.18, SE=0.08, z=−2.17, p=0.030. - Study 1 performance over time: Proportion hits—Condition main effect, F(1,155)=10.81, p<0.001, ηp²=0.07 (Motivated>Control); Block main effect, F(5.55,860.04)=12.23, p<0.001, ηp²=0.07 (hits declined over time); Condition×Block interaction, F(5.55,860.04)=3.24, p=0.005, ηp²=0.02 (decline more gradual in Motivated). False alarms—no significant effects. - Study 2 motivation (pre vs post): Main effect of Time, F(1,282)=237.88, p<0.001, ηp²=0.46 (motivation decreased); no significant Condition effect, F(1,282)=3.26, p=0.072; Condition×Time trend, F(1,282)=3.78, p=0.053. Motivation over blocks: main effect of Condition, F(1,270)=10.60, p=0.001, ηp²=0.04 (Motivated higher); main effect of Block, F(3.71,1001.49)=138.13, p<0.001, ηp²=0.34 (decreasing over time); Condition×Block interaction, F(3.71,1001.49)=3.64, p=0.007, ηp²=0.01 (slower decline in Motivated). - Study 2 media multitasking GLMM: Condition effect, Estimate=−2.34, SE=0.57, z=−4.11, p<0.001 (Motivated less likely to multitask); Block main effect non-significant; Block×Condition interaction, Estimate=−0.13, SE=0.06, z=−2.09, p=0.04 (more gradual increase over time in Motivated). - Study 2 performance: Proportion hits—Condition main effect, F(1,282)=10.72, p=0.001, ηp²=0.04; Block main effect, F(4.43,1249.87)=60.05, p<0.001, ηp²=0.18 (declined over time); Condition×Block interaction, F(4.43,1249.87)=5.77, p<0.001, ηp²=0.02 (decline more gradual in Motivated). False alarms—no significant effects. - Additional: In Study 1, 36% of Control and 46% of Motivated participants never played the video. In Study 2, enjoyment and interest did not differ by condition; Motivated participants reported being motivated by early-exit instructions (M=5.29, SD=1.79). A substantial subset reported engaging in activities outside the experiment online; supplementary analyses yielded similar patterns though some effects were smaller or non-significant.

Across two studies, increased motivation attenuated temporal increases in media multitasking and slowed performance declines during a sustained attention task. Study 2 showed that in-the-moment motivation decreases with time-on-task but declines more gradually under motivating instructions. These findings support opportunity cost accounts of vigilance, wherein shifting cost-benefit calculations (e.g., rising boredom and perceived value of alternatives) drive attention away from the primary task. By increasing the value assigned to task performance, motivation helps maintain exploitation of the task and delays exploration of alternative activities (including media multitasking), thereby improving sustained attention and task outcomes.

The work demonstrates that elevating motivation at task onset mitigates temporal increases in media multitasking and reduces the severity of sustained attention decrements in performance. Motivation declines over time, but motivating instructions slow this decline, linking temporal changes in media multitasking to motivational dynamics. The findings bolster accounts that attribute vigilance decrements to evolving cost-benefit analyses rather than resource depletion alone. Future research should test diverse motivation manipulations (e.g., monetary incentives, point systems, gamification, leaderboards), evaluate effects across real-world settings (classrooms, workplaces) with fixed participation constraints, and examine robustness across different task types and durations.

- Task paradigm differs from traditional vigilance tasks (1-back ~20 min vs multi-hour vigilance with infrequent signals), potentially limiting generalizability. - Online Study 2 participants frequently reported engaging in activities outside the experimental context, which may dilute or mask effects; subsample analyses showed similar patterns but smaller or non-significant effects, suggesting subtle temporal impacts of motivation. - Media multitasking options were constrained (primarily the provided video), and behavior may be context-dependent; other environments show non-linear fluctuations. - The motivating instruction (early exit contingent on performance) may not be feasible in settings with fixed attendance requirements (e.g., classrooms, workplaces). - Effects appear modest; splitting samples reduced statistical significance in some analyses, indicating that the impact of motivation on temporal dynamics may be subtle and warrant further testing.