Counting the Wait: Effects of Temporal Feedback on Downstream Task Performance and Perceived Wait-Time Experience during System-Imposed Delays

TL;DR

This study investigates how system-imposed waits, manipulated via Temporal Feedback Mode (No Time Display, Elapsed-Time, Remaining-Time) and Wait Duration (10, 30, 60 s), shape downstream task performance and user experience in a controlled visual-reasoning task. Across 425 participants, the authors show that while Remaining-Time amplifies frustration and No Time Display inflates perceived duration, these cues do not translate into improvements or declines in post-wait performance. Using ANCOVA to control for baseline performance and ART ANOVA for subjective measures, they find additive effects on experience but no interaction or performance gains. The findings support design guidelines that prioritize experiential factors—uncertainty, pacing, and anticipation—over performance enhancements in latency-prone systems, and they outline boundary conditions and future directions for more ecologically valid investigations. The work contributes to theoretically grounding how temporal cues influence waiting perception and provides practical recommendations for timing interfaces in digital workflows where delays are inevitable.

Abstract

System-imposed wait times can significantly disrupt digital workflows, affecting user experience and task performance. Prior HCI research has examined how temporal feedback, such as feedback mode (Elapsed-Time vs. Remaining-Time) shapes wait-time perception. However, few studies have investigated how such feedback influences users' downstream task performance, as well as overall affective and cognitive experience. To study these effects, we conducted an online experiment where 425 participants performing a visual reasoning task experienced a 10-, 30-, or 60-second wait with a Remaining-Time, Elapsed-Time, or No Time Display. Findings show that temporal feedback mode shapes how waiting is perceived: Remaining-Time feedback increased frustration relative to Elapsed-Time feedback, while No Time Display made waits feel longer and heightened ambiguity. Notably, these experiential differences did not translate into differences in post-wait task performance. Integrating psychophysical and cognitive science perspectives, we discuss implications for implementing temporal feedback in latency-prone digital systems.

Figures (8)

• Figure 1: Example CLEVR image used in the experimental task; additional sample questions with answer options are provided in Appendix \ref{['appendix-examples']}.
• Figure 2: Overview of the study workflow. Participants (N = 425; between-subjects) completed a visual reasoning task in two 3-min segments separated by a system-imposed wait. We crossed Temporal Feedback Mode (No Time Display, Elapsed-Time, Remaining-Time) with Wait Duration (10 s, 30 s, 60 s) and randomly assigned participants to one of nine conditions. After Segment 2, a post-task survey assessed workload, emotional state, perceived time, and interpretations of the wait.
• Figure 3: Three experimental wait-screen conditions varying in Temporal Feedback Mode: (A) No Time Display, (B) Elapsed-Time, and (C) Remaining-Time. The numerical display (when present) updates once per second (1 Hz), and all conditions show the same base message during the wait. Each feedback mode was paired with one of three wait durations (10s, 30s, 60s).
• Figure 4: Covariate-adjusted mean performance across Temporal Feedback Modes and Wait Durations from the ANCOVA model. Error bars represent 95% confidence intervals.
• Figure 5: Summary of wait-perceptual outcomes: (a) Proportion of participants who recalled a wait, with error bars representing 95% confidence intervals (Wilson method). (b) Perceived duration ratings on a 7-point scale.