The DOI matches its Crossref record, with a small difference in title or year; 51 of the 51 references it cites were found in a registry or an index; 12 of the 42 sources its claims cite were checked for support.
What Makes Interruptions Disruptive?: A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption
Open accessAbstract
In this paper we present a computational cognitive model of task interruption and resumption, focusing on the effects of the problem state bottleneck. Previous studies have shown that the disruptiveness of interruptions is for an important part determined by three factors: interruption duration, interrupting-task complexity, and moment of interruption. However, an integrated theory of these effects is still missing. Based on previous research into multitasking, we propose a first step towards such a theory in the form of a process model that attributes these effects to problem state requirements of both the interrupted and the interrupting task. Subsequently, we tested two predictions of this model in two experiments. The experiments confirmed that problem state requirements are an important predictor for the disruptiveness of interruptions. This suggests that interfaces should be designed to a) interrupt users at low-problem state moments and b) maintain the problem state for the user when interrupted.
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Claims the paper makes
12 of 42 cited sources checked · 8 supported · 0 flagged · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Several studies have shown that the longer the interruption is, the longer it takes to resume the interrupted task [4,23,35]”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > What Makes Interruptions Disruptive?
What the sources say
- Partly supportedcites [4] 4. Altmann, E.M., Trafton, J.G., and Hambrick, D.Z. Momentary interruptions can derail the train of thought. Journal of Experimental Psychology: General 143, 1 (2014), 215-226. sourceExperimental — accuracy not yet measured
Analysis 1 (p. 5) reports a small increase in post-interruption response latency in Experiment 1, whose interruptions averaged 4.4 seconds, but no latency effect in Experiment 2, whose interruptions averaged 2.8 seconds. This is consistent with the claim, but the paper does not establish that resumption time increases as interruption duration increases; the experiments also differed in the interruption task. (LLM, conf=0.84)
- Supportedcites [23] 23. Hodgetts, H.M. and Jones, D.M. Interruption of the Tower of London task: support for a goal-activation approach. Journal of Experimental Psychology: General 135, 1 (2006), 103-15. source
The Results and Discussion (p. 6) report that participants resumed the Tower of London task significantly more slowly after an 18-second interruption than after a 6-second interruption. The General Discussion (p. 11) also states that longer intervening activities increased the time cost of resuming the task. (LLM, conf=0.94)
- Not checked — no full text of the sourcecites [35] 35. Monk, C.A., Trafton, J.G., and Boehm-Davis, D.A. The effect of interruption duration and demand on resuming suspended goals. Journal of Experimental Psychology: Applied 14, 4 (2008), 299-313. source
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The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“In addition, more complex interruptions (e.g., solving 17+36 as compared to 2+3; [23]) also lead to longer resumption times [13,14,20,23,35].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > What Makes Interruptions Disruptive?
What the sources say
- Not matchedcites [13] 13. Cades, D.M., Davis, D.A.B., Trafton, J.G., and Monk, C.A. Does the Difficulty of an Interruption Affect our Ability to Resume? In Proc. HFES. 2007, 234-238.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites [14] 14. Cades, D.M., Werner, N., Boehm-Davis, D.A., Trafton, J.G., and Monk, C.A. Dealing with Interruptions can be Complex, but does Interruption Complexity Matter: A Mental Resources Approach to Quantifying Disruptions. In Proc. HFES. 2008, 398-402. source
- Not checked — no full text of the sourcecites [20] 20. Gillie, T. and Broadbent, D.E. What makes interruptions disruptive? A study of length, similarity, and complexity. Psychological Research 50, (1989), 243- 250. source
- Supportedcites [23] 23. Hodgetts, H.M. and Jones, D.M. Interruption of the Tower of London task: support for a goal-activation approach. Journal of Experimental Psychology: General 135, 1 (2006), 103-15. source
The Results and Discussion (p. 10) report that resumption times were longer after complex arithmetic interruptions than after simple ones, even when interruption length was controlled. (LLM, conf=0.94)
- Not checked — no full text of the sourcecites [35] 35. Monk, C.A., Trafton, J.G., and Boehm-Davis, D.A. The effect of interruption duration and demand on resuming suspended goals. Journal of Experimental Psychology: Applied 14, 4 (2008), 299-313. source
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The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“These studies confirmed that users take less time to resume a task when interrupted at low-workload moments [25,26] (see [32] for an additional example).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > What Makes Interruptions Disruptive?
What the sources say
- Supportedcites [25] 25. Iqbal, S.T. and Bailey, B.P. Investigating the effectiveness of mental workload as a predictor of opportune moments for interruption. In Proc. CHI. 2005, 1489-1492. source
The User Study section defines Best moments as low-workload boundaries. The Resumption Lag section reports that users resumed their tasks almost three times faster after interruptions at Best moments than at Worst or Random moments. (LLM, conf=0.94)
- Supportedcites [26] 26. Iqbal, S.T. and Bailey, B.P. Leveraging characteristics of task structure to predict the cost of interruption. In Proc. CHI. 2006, 741-750. source
The Introduction reports that interruptions at lower-workload subtask boundaries had meaningfully lower costs than those at higher-workload boundaries. The Measurements section defines that cost as resumption lag—the time until the first action on the resumed task—supporting the claim about taking less time to resume. (LLM, conf=0.90)
- Not checked — no full text of the sourcecites [32] 32. McFarlane, D. Comparison of Four Primary Methods for Coordinating the Interruption of People in Human- Computer Interaction. Human-Computer Interaction 17, 1 (2002), 63-139. source
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The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“In a series of experiments it was shown that subjects were considerably slower and made more errors when the problem state was required for two tasks, as compared to one or none of the tasks [8,10,11,12,37].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > The Problem State Bottleneck in Multitasking
What the sources say
- Not checked — no full text of the sourcecites [8] 8. Borst, J.P., Buwalda, T.A., Van Rijn, H., and Taatgen, N.A. Avoiding the Problem State Bottleneck by Strategic use of the Environment. Acta Psychologica 144, 2 (2013), 373-379. source
- Not checked — no full text of the sourcecites [10] 10. Borst, J.P., Taatgen, N.A., and Van Rijn, H. The Problem State: A Cognitive Bottleneck in Multitasking. Journal of Experimental Psychology: Learning, Memory, & Cognition 36, 2 (2010), 363- 382. source
- Not checked — no full text of the sourcecites [11] 11. Borst, J.P., Taatgen, N.A., and Van Rijn, H. Using a Symbolic Process Model as input for Model-Based fMRI Analysis: Locating the Neural Correlates of Problem State Replacements. NeuroImage 58, 1 (2011), 137-147. source
- Supportedcites [12] 12. Borst, J.P., Taatgen, N.A., Stocco, A., and Van Rijn, H. The Neural Correlates of Problem States: Testing fMRI Predictions of a Computational Model of Multitasking. PLoS ONE 5, 9 (2010), e12966. source
The Results (Behavioral Results, Discussion) report that when both tasks required a problem state, response times increased and accuracy decreased. The Introduction (A Priori Model Predictions) also reports that the hard–hard condition produced higher response times and lower accuracy than the other conditions in an earlier behavioral experiment. The supplied passages have section labels but no page numbers. (LLM, conf=0.93)
- Not checked — no full text of the sourcecites [37] 37. Nijboer, M., Borst, J.P., Van Rijn, H., and Taatgen, N.A. Single-task fMRI overlap predicts concurrent multitasking interference. NeuroImage 100, (2014), 60-74. source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesEvery source the paper cites for this claim was checked and supports it.
In the paper
“which showed that Task Level, Difficulty of Next Subtask, and Carry-Over between Subtasks, were the most important predictors of interruption disruptiveness.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Supportedcites [26] 26. Iqbal, S.T. and Bailey, B.P. Leveraging characteristics of task structure to predict the cost of interruption. In Proc. CHI. 2006, 741-750. source
In “Determine the Most Predictive Factors” (page unavailable), the paper describes using stepwise regression to identify the candidate factors most predictive of resumption lag. The Discussion (page unavailable) names Level, Carryover, and Difficulty of Next Subtask as the three characteristics used to predict cost of interruption at subtask boundaries. (LLM, conf=0.94)
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The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“It was shown in multiple studies that it is better to be interrupted between tasks [25,26,34] than in the middle of a task.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Partly supportedcites [25] 25. Iqbal, S.T. and Bailey, B.P. Investigating the effectiveness of mental workload as a predictor of opportune moments for interruption. In Proc. CHI. 2005, 1489-1492. sourceExperimental — accuracy not yet measured
The Discussion reports that interruptions at predicted Best moments caused less disruption than interruptions at Random or Worst moments. But the User Study defines those moments as lower- and higher-workload boundaries within a task; it does not test interruptions between tasks against interruptions in the middle of a task. Page numbers are unavailable in our copy. (LLM, conf=0.86)
- Supportedcites [26] 26. Iqbal, S.T. and Bailey, B.P. Leveraging characteristics of task structure to predict the cost of interruption. In Proc. CHI. 2006, 741-750. source
The Introduction reports that interruptions at subtask boundaries have much lower costs than interruptions at nonboundary moments. The Empirical Cost of Interruption section likewise reports longer resumption times, more errors, and more negative affect when interruptions occur at random moments rather than boundaries. The paper's comparison is specifically about subtask boundaries, which supports the citing sentence's general point about interrupting between activities rather than mid-task. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites [34] 34. Monk, C.A., Boehm-Davis, D.A., and Trafton, J.G. Recovering From Interruptions: Implications for Driver Distraction Research. Human Factors 46, 4 (2004), 650-663. source
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A repeated-measures ANOVA (Table 1) confirmed main effects of Subtraction Difficulty and N-Back Difficulty.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the hard/hard condition, we found a significant effect of Interruption Duration (F(1,32) = 4.17, p = .0495,η p 2 = .12).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, there were fixed resumption costs of about 800 ms in all conditions.”
- Also stated in: § Model · plain
“The data shows a fixed cost of about 800 ms in all conditions.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § Model · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and did not predict the overall difference between easy and hard subtraction.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Discussion
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- Probably not a substantial claim. 17
- It may state two separate claims as one. 20
- The quote only partly states this claim. 2
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Memory-for-goals theory made the prediction that longer interruptions lead to longer resumption processes, which was confirmed by several studies [23,34,35,45].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > INTRODUCTION
What the sources say
- Supportedcites [23] 23. Hodgetts, H.M. and Jones, D.M. Interruption of the Tower of London task: support for a goal-activation approach. Journal of Experimental Psychology: General 135, 1 (2006), 103-15. source
The Length of Interruption section (p. 2) states that goal-memory models predict longer interruptions will make goals slower to reinstate. Experiment 1’s Results and Discussion (p. 6) report significantly slower resumption after 18-second than 6-second interruptions, confirming that prediction in this study. (LLM, conf=0.92)
- Not checked — no full text of the sourcecites [34] 34. Monk, C.A., Boehm-Davis, D.A., and Trafton, J.G. Recovering From Interruptions: Implications for Driver Distraction Research. Human Factors 46, 4 (2004), 650-663. source
- Not checked — no full text of the sourcecites [35] 35. Monk, C.A., Trafton, J.G., and Boehm-Davis, D.A. The effect of interruption duration and demand on resuming suspended goals. Journal of Experimental Psychology: Applied 14, 4 (2008), 299-313. source
- Not checked — no full text of the sourcecites [45] 45. Trafton, J.G., Altmann, E.M., Brock, D.P., and Mintz, F.E. Preparing to resume an interrupted task: effects of prospective goal encoding and retrospective rehearsal. International Journal of Human-Computer Studies 58, 5 (2003), 583-603. source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Memory-for-goals theory explains these effects by assuming that each task has an associated task goal, which is stored in declarative memory when an interruption occurs [2,3].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Memory for Goals
What the sources say
- Not checked — no full text of the sourcecites [2] 2. Altmann, E.M. and Trafton, J.G. Memory for goals: An activation-based model. Cognitive Science 26, (2002), 39-83. source
- Partly supportedcites [3] 3. Altmann, E.M. and Trafton, J.G. Timecourse of recovery from task interruption: data and a model. Psychonomic Bulletin & Review 14, 6 (2007), 1079- 84. sourceExperimental — accuracy not yet measured
The Modeling the Timecourse of Recovery section describes task representations that include goals and subgoals, and the Discussion describes retrieving a disrupted mental context after an interruption (pages unavailable in our copy). Neither passage says that each task has a single associated goal stored in declarative memory when the interruption occurs. (LLM, conf=0.82)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“It was shown that this was related to higher workload [24], as well as to higher resumption costs when interrupted during the subtask [25].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [24] 24. Iqbal, S.T., Adamczyk, P., Zheng, X., and Bailey, B.P. Towards an index of opportunity: understanding changes in mental workload during task execution. In Proc. SIGCHI. 2005, 311-320. source
- Partly supportedcites [25] 25. Iqbal, S.T. and Bailey, B.P. Investigating the effectiveness of mental workload as a predictor of opportune moments for interruption. In Proc. CHI. 2005, 1489-1492. sourceExperimental — accuracy not yet measured
The ‘Moments for Interruption’ section identifies a high-workload point in route planning between recalling and entering information. The ‘Resumption Lag’ section reports longer resumption times at high-workload (‘Worst’) than low-workload (‘Best’) interruption points, but reports this timing effect across tasks, not specifically for route planning. It does not establish that maintaining a problem state during a subtask caused the higher resumption cost. (LLM, conf=0.84)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Figure 6B shows the fit of a memory-for-problem-states model.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Model
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The ANOVA (Table 2) confirmed these results: besides main effects of Text-Entry Difficulty, N-Back Difficulty, and Interruption Duration”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Participant accuracy on the n-back task was above 85% in all conditions.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the hard subtraction/easy n-back condition the resumption costs were slightly higher, but did not increase with interruption duration either.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The threeway interaction showed a trend towards significance.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Results
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As the data shows a fixed cost of about 400 ms in all conditions, we added this cost to the model.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Model
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If both tasks require a problem state, the problem state of the primary task is automatically stored in declarative memory during an interruption, where it starts to decay (analogously to task goals in memory-forgoals).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > MEMORY FOR PROBLEM STATES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
- The authors state this as an assumption: Information in the problem state can be accessed instantly, without incurring a time cost.
- Rests on an assumption: When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
- Rests on an assumption: The problem state resource can store at most a single chunk of information at a time.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As in memory-for-goals, the longer the interruption, the further the activation level of the problem state will have decayed, and the longer it takes to retrieve it from memory -explaining the interruption duration effect.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > MEMORY FOR PROBLEM STATES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: Information in the problem state can be accessed instantly, without incurring a time cost.
- Rests on an assumption: When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
- Rests on an assumption: The problem state resource can store at most a single chunk of information at a time.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The main idea of memory-for-problem-states is that both the primary and the secondary, interrupting task can have an associated problem state.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > MEMORY FOR PROBLEM STATES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
- The authors state this as an assumption: Information in the problem state can be accessed instantly, without incurring a time cost.
- Rests on an assumption: When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
- Rests on an assumption: The problem state resource can store at most a single chunk of information at a time.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“The problem state acts as a processing bottleneck in multitasking, as it can only maintain information for a single task at a time, and thus causes interference when required by multiple tasks concurrently.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > The Problem State Bottleneck in Multitasking
What the sources say
- Not checked — no full text of the sourcecites [5] 5. Anderson, J.R. Human symbol manipulation within an integrated cognitive architecture. Cognitive Science 29, (2005), 313-341. source
- Not checked — no full text of the sourcecites [10] 10. Borst, J.P., Taatgen, N.A., and Van Rijn, H. The Problem State: A Cognitive Bottleneck in Multitasking. Journal of Experimental Psychology: Learning, Memory, & Cognition 36, 2 (2010), 363- 382. source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Taken together, memory-for-goals provides a simple and powerful explanation for the interruption duration effect, but its explanation for the interrupting-task complexity effect is less convincing, given that users often do not seem to rehearse during an interruption.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Memory for Goals
What the sources say
- Not matchedcites [13] 13. Cades, D.M., Davis, D.A.B., Trafton, J.G., and Monk, C.A. Does the Difficulty of an Interruption Affect our Ability to Resume? In Proc. HFES. 2007, 234-238.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [29] 29. Katidioti, I., Borst, J.P., and Taatgen, N.A. What Happens When We Switch Tasks: Pupil dilation in multitasking. Journal of Experimental Psychology: Applied, (in press).
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Trial order was random.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Procedure
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Also, it is unclear how memory-for-goals accounts for the moment-of-interruption effect.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Memory for Goals
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“By scrambling the words, we controlled for letter-based effects, while preventing the use of strategies to predict the next letter.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > EXPERIMENT 2: TEXT-ENTRY & N-BACK
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Three subjects had to be excluded because they underperformed on the hard subtraction task (< 65% correct or slower than 3,500 ms per response), two subjects for underperforming on the hard nback task (< 80% correct), and one subject because of health problems, leaving 33 complete data sets (23 female, age range 18-27, mean age 20.7).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Subjects
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, if the secondary task does not require a problem state, it will not disrupt the problem state of the primary task, which will therefore again not show an interruption duration effect.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > MEMORY FOR PROBLEM STATES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: Information in the problem state can be accessed instantly, without incurring a time cost.
- Rests on an assumption: When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
- Rests on an assumption: The problem state resource can store at most a single chunk of information at a time.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“After the interruption, the primary task's problem state has to be retrieved from memory, which takes time and can lead to errors when an incorrect (i.e.older) problem state is retrieved.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > MEMORY FOR PROBLEM STATES
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclearIt may state two separate claims as one.
- The authors state this as an assumption: Information in the problem state can be accessed instantly, without incurring a time cost.
- Rests on an assumption: When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
- Rests on an assumption: The problem state resource can store at most a single chunk of information at a time.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, in the hard condition subjects mentally had to keep track of whether a 'carry' was in progress (solved columns were masked to ensure that subjects maintained carries mentally, Figure 3).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > EXPERIMENT 1: SUBTRACTION AND N-BACK
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Memory-for-problem-states is based on memory-forgoals theory [2] and on research into the problem state bottleneck [10].”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [2] 2. Altmann, E.M. and Trafton, J.G. Memory for goals: An activation-based model. Cognitive Science 26, (2002), 39-83. source
- Not checked — no full text of the sourcecites [10] 10. Borst, J.P., Taatgen, N.A., and Van Rijn, H. The Problem State: A Cognitive Bottleneck in Multitasking. Journal of Experimental Psychology: Learning, Memory, & Cognition 36, 2 (2010), 363- 382. source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It can be regarded as a more specific version of memory-for-goals: instead of focusing on general task goals, memory-for-problem-states looks in detail at the cognitive requirements of each task.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, complexity is all-or-nothing in our framework: a secondary task requires a problem state or not.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The longer the interruption, the further their activation in memory will have decayed, and the longer it takes to retrieve them.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
- The authors state this as an assumption: The problem state(s) associated with the primary task are stored in declarative memory during an interruption and have to be retrieved on resumption.
- Rests on an assumption: During an interruption, the activation of problem states in declarative memory decays with time.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Memory-for-problem-states can account for three important factors in interruption disruptiveness: interruption duration, interrupting-task complexity, and moment of interruption.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All three factors are clearly related to problem state requirements; especially Carry-Over is an almost identical concept.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“which the model explained by two problem states decaying in declarative memory instead of one, and both problem states having to be restored after an interruption.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Model
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Two problem states decay in declarative memory instead of one, and both problem states have to be restored after an interruption.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, where memory-for-goals predicts an interruption duration effect for every task, memory-for-problem-states specified this to tasks that need a problem state.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because the model assumes that subjects needed two problem states to perform the hard n-back task, it predicted an effect of interruption duration also when nback was easy, which was confirmed by the data.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Model
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: The model assumes that subjects needed two problem states to perform the hard n-back task.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This prediction was confirmed, and a memory-for-problemstates model gave a good account of the data.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: In Experiment 2, the hard text-entry task required two problem states: one for the word and one for the position in the word.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The effect was even stronger in the hard/hard condition -easy to see in the data (Fig. 6A) but also present in the model (Fig. 6B)”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Model
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“These costs might be due to general task reorientation costs, for instance related to task-set reconfiguration (cf.task switching, [36]).”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Not checked — no full text of the sourcecites [36] 36. Monsell, S. Task switching. Trends in Cognitive Sciences 7, 3 (2003), 134-140. source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“which is necessary given that”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
What the sources say
- Not matchedcites [35:302]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a stronger test, we subsequently derived two a priori predictions from the model.These predictions were confirmed by two behavioral experiments, yielding strong support for our theory.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > GENERAL DISCUSSION
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, Experiment 2 confirmed with a new task that there is no effect of interruption duration on resumption costs as long as the primary task does not require a problem state.”
§ What Makes Interruptions Disruptive? A Process-Model Account of the Effects of the Problem State Bottleneck on Task Interruption and Resumption > Discussion
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
An integrated theory of the effects of interruption duration, interrupting-task complexity, and moment of interruption is still missing.
“However, an integrated theory of these effects is still missing.”
The authors state this as an assumption.
The VCR task requires two problem states.
“Instead, it is assumed that the VCR task requires two problem states, given that it was a complex task with multiple sub-tasks.”
The authors state this as an assumption.
Information in the problem state can be accessed instantly, without incurring a time cost.
“It is assumed that information in the problem state can be accessed instantly, without incurring a time cost.”
The paper relies on this without support.
When a new representation is stored in the problem state, previous contents are automatically encoded in declarative memory.
“When a new representation is stored, previous contents are automatically encoded in declarative memory.”
The paper relies on this without support.
The problem state resource can store at most a single chunk of information at a time.
“The problem state resource is used to maintain intermediate information in a task and can store at most a single chunk of information at a time.”
The paper relies on this without support.
An integrated theory of the effects of interruptions is still absent.
“Although interruptions are ubiquitous in our society, an integrated theory of their effects is still absent.”
The authors state this as an assumption.
In Experiment 2, the hard text-entry task required two problem states: one for the word and one for the position in the word.
“We assumed that they needed two problem states for this: one for the word and one for the position in the word.”
The authors state this as an assumption.
The problem state(s) associated with the primary task are stored in declarative memory during an interruption and have to be retrieved on resumption.
“The interruption duration effect is explained by assuming that the problem state(s) associated with the primary task are stored in declarative memory during an interruption, and have to be retrieved on resumption.”
The authors state this as an assumption.
Complexity can be defined as problem state requirements of the secondary task.
“The effect of interrupting-task complexity is explained by assuming that complexity can be defined as problem state requirements of the secondary task.”
The authors state this as an assumption.
The model assumes that subjects needed two problem states to perform the hard n-back task.
“Because the model assumes that subjects needed two problem states to perform the hard n-back task”
The paper relies on this without support.
During an interruption, the activation of problem states in declarative memory decays with time.
“The longer the interruption, the further their activation in memory will have decayed, and the longer it takes to retrieve them.”
The paper relies on this without support.
Two problem states decay in declarative memory instead of one, and both problem states have to be restored after an interruption.
“which the model explained by two problem states decaying in declarative memory instead of one, and both problem states having to be restored after an interruption.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Since initial responses can be extreme outliers (Borst et al., 2015) we also excluded the initial responses until the first interrupted items.”
From Effect of Redundant Haptic Information on Task Performance during Visuo-Tactile Task Interruption and Recovery (2016) · cites this paper as Borst et al., 2015
Experimental — accuracy not yet measured
Statistics recomputed
Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.
- ConsistentF(1, 32) = 4.17reported p = .0495 · recomputed p = .049
“F(1,32) = 4.17, p = .0495”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Figure 1A is attributed to two different references
MinorThe main text identifies Figure 1A as data from Monk et al. [35], while the figure caption attributes those data to [34].
“Both effects were nicely demonstrated by Monk et al. [35].In their study, subjects were asked to perform a fairly complex VCR-programming task.This task was either interrupted by a blank screen, or by one of two different secondary tasks: a tracking task in which subjects had to use the mouse to track an icon on the screen, or a complex n-back task.The length of the interruptions was 3, 8, or 13 seconds.Figure 1A shows”
“Figure 1.A) Resumption time data of [34], B) model fit of memory-for-goals [43], and C) model fit of memory-for-problem-states.”
The model is said to assign two problem states to the wrong task
MinorThe Experiment 2 model section says the hard n-back task needs two problem states. The task description assigns the two problem states to hard text-entry instead, and says they represent the word and the position within it.
“Because the model assumes that subjects needed two problem states to perform the hard n-back task, it predicted an effect of interruption duration also when nback was easy, which was confirmed by the data.”
“We assumed that they needed two problem states for this: one for the word and one for the position in the word.”
Citations
Cites
Monsell, S. (2003) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(03)00028-7 · Cited by 2,984
How Can the Human Mind Occur in the Physical Universe?
Anderson, J. R. (2007) · doi:10.1093/acprof:oso/9780195324259.001.0001 · Cited by 1,483
Facebook and texting made me do it: Media-induced task-switching while studying
Rosen, L. D., Mark Carrier, L., & Cheever, N. A. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2012.12.001 · Cited by 875
A diary study of task switching and interruptions
Czerwinski, M., Horvitz, E., & Wilhite, S. (2004) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985715 · Cited by 830
Memory for goals: an activation‐based model
Altmann, E. M., & Trafton, J. G. (2002) · Cognitive Science · doi:10.1207/s15516709cog2601_2 · Cited by 795
"Constant, constant, multi-tasking craziness": managing multiple working spheres
González, V. M., & Mark, G. (2004) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985707 · Cited by 715
Chapter 2 Design for a Working Memory
Oberauer, K. (2009) · Psychology of Learning and Motivation · doi:10.1016/s0079-7421(09)51002-x · Cited by 636
The Scope and Importance of Human Interruption in Human-Computer Interaction Design
McFarlane, D. C., & Latorella, K. A. (2002) · Human–Computer Interaction · doi:10.1207/s15327051hci1701_1 · Cited by 536
If not now, when?: the effects of interruption at different moments within task execution
Adamczyk, P. D., & Bailey, B. P. (2004) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985727 · Cited by 531
No task left behind?: examining the nature of fragmented work
Mark, G., Gonzalez, V. M., & Harris, J. (2005) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1054972.1055017 · Cited by 503
Flagged first, then by citations
Research works printed but not linked: 4
- Anderson J.R., 2007, Oxford University Press
- Borst J.P., 2010, Memory, & Cognition 36, 2
- Cutrell E., 2001, Proc. INTERACT.
- Renaud K, 2000, Expediting Rapid Recovery from Interruptions by Providing a Visualisation of Application Activity, Proc. OZCHI, 348, 355
Cited by
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Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0025
– The Asian Conference on Psychology & the Behavioral Sciences 2020 Official Conference Proceedings
(2020) · ACP official conference proceedings · doi:10.22492/issn.2187-4743.2020 · Cited by 1
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0012
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0034
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0024
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0040
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0042
Computational representations and models
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192864543.003.0039
Metadata
- Authors
- Borst, J. P., Taatgen, N. A., & van Rijn, H.
- Affiliations
- University of Groningen (NL)
- University of Groningen, Groningen, Netherlands
- Venue
- Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2015-04-18
- Pages
- 2971-2980
- OpenAlex
- W2171022339
- Cited by
- 156
- References
- 50
- Citations by year
- 2026: 3 · 2025: 54 · 2024: 4 · 2023: 6 · 2022: 7 · 2021: 10 · 2020: 16 · 2019: 11 · 2018: 10 · 2017: 9 · 2016: 23 · 2015: 3
- FWCI
- 26.26
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- ERC (283597)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- task interruption, task resumption, computational cognitive model, multitasking, interruption duration, interface design, process model
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-11, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-11 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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