The Fatigue Spiral: How Excessive Choices Drain Cognitive Energy—And the Minimalist System That Sustains Focus and Resilience E-Book

Brandon Fletcher

• Herausgeber: BookRix
• Kategorie: Fachliteratur
• Sprache: Englisch

Veröffentlichungsjahr: 2025

Beschreibung

Decision fatigue is no longer a metaphor—it is a measurable cognitive liability. Experts across psychology, neuroscience, and behavioral economics agree: too many choices erode attention, increase errors, and accelerate burnout. In high-stakes professional and research environments, the costs are profound.

This book explores the science of decision fatigue, revealing how complexity in daily habits, environments, and workflows undermines sustained performance. Backed by cutting-edge empirical studies, it demonstrates how cluttered routines silently exhaust executive function, disrupt self-regulation, and weaken long-term productivity.

But within this challenge lies a solution. By applying a minimalist, evidence-based system, professionals can dramatically reduce cognitive load while enhancing clarity, resilience, and adaptability. Through sustainable practices grounded in research, this framework shows how less input leads to more capacity for deep thinking, innovation, and high-level work.

Written for researchers, leaders, and advanced practitioners, this book moves beyond lifestyle advice into rigorous strategy. It provides the analytical tools and practical steps to build sustainable focus, optimize habits, and harness the science of simplicity for enduring cognitive performance.

Leseprobe

Brandon Fletcher

The Fatigue Spiral: How Excessive Choices Drain Cognitive Energy—And the Minimalist System That Sustains Focus and Resilience

Copyright © 2025 by Brandon Fletcher

All rights reserved. No part of this publication may be reproduced, stored or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise without written permission from the publisher. It is illegal to copy this book, post it to a website, or distribute it by any other means without permission.

This novel is entirely a work of fiction. The names, characters and incidents portrayed in it are the work of the author's imagination. Any resemblance to actual persons, living or dead, events or localities is entirely coincidental.

Brandon Fletcher asserts the moral right to be identified as the author of this work.

Brandon Fletcher has no responsibility for the persistence or accuracy of URLs for external or third-party Internet Websites referred to in this publication and does not guarantee that any content on such Websites is, or will remain, accurate or appropriate.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book and on its cover are trade names, service marks, trademarks and registered trademarks of their respective owners. The publishers and the book are not associated with any product or vendor mentioned in this book. None of the companies referenced within the book have endorsed the book.

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Contents

1. Chapter 1

2. Chapter 1: Defining the Fatigue Spiral—From Concept to Measurable Liability

3. Chapter 2: Historical and Theoretical Roots—How Research Approached Choice and Fatigue

4. Chapter 3: Measuring Decision Fatigue—Methods, Metrics, and Validity

5. Chapter 4: Neural Mechanisms—Executive Control, Salience, and the Energy Costs of Choice

6. Chapter 5: Behavioral Economics of Choice—When More Options Reduce Value

7. Chapter 6: Habit Architecture and Cognitive Energy Minimalism

8. Chapter 7: Environmental and Contextual Contributors to Cognitive Load

9. Chapter 8: Workflow Design and Cognitive Ergonomics for High-Performance Teams

10. Chapter 9: Individual Interventions—Scheduling, Recovery, and Cognitive Hygiene

11. Chapter 10: Organizational Strategies—Policy, Culture, and Leadership to Prevent Overload

12. Chapter 11: Technology, Automation, and the Paradox of Choice Reduction

13. Chapter 12: Recovery, Plasticity, and Long-Term Resilience

14. Chapter 13: Research Agenda—Key Questions, Experimental Designs, and Open Problems

15. Chapter 14: The Minimal Cognitive Load System—A Practical Framework for Experts and Leaders

16. Chapter 1: Defining the Fatigue Spiral—From Concept to Measurable Liability

17. Chapter 2: Historical and Theoretical Roots—How Research Approached Choice and Fatigue

18. Chapter 3: Measuring Decision Fatigue—Methods, Metrics, and Validity

19. Chapter 4: Neural Mechanisms—Executive Control, Salience, and the Energy Costs of Choice

20. Chapter 5: Behavioral Economics of Choice—When More Options Reduce Value

21. Chapter 6: Habit Architecture and Cognitive Energy Minimalism

22. Chapter 7: Environmental and Contextual Contributors to Cognitive Load

23. Chapter 8: Workflow Design and Cognitive Ergonomics for High-Performance Teams

24. Chapter 9: Individual Interventions—Scheduling, Recovery, and Cognitive Hygiene

25. Chapter 10: Organizational Strategies—Policy, Culture, and Leadership to Prevent Overload

26. Chapter 11: Technology, Automation, and the Paradox of Choice Reduction

27. Chapter 12: Recovery, Plasticity, and Long-Term Resilience

28. Chapter 13: Research Agenda—Key Questions, Experimental Designs, and Open Problems

29. Chapter 14: The Minimal Cognitive Load System—A Practical Framework for Experts and Leaders

1

Chapter 1

Table of Contents

2

Chapter 1: Defining the Fatigue Spiral—From Concept to Measurable Liability

Defining decision fatigue as an operational cognitive liability

Distinguishing decision fatigue from mental fatigue, ego depletion, cognitive load, and burnout

Core independent variables that drive the fatigue spiral

Neural and physiological mechanisms linked to decision fatigue

Measurement strategies and experimental designs for reliable assessment

Translational framework: evidence-based minimalism as diagnostic and intervention

3

Chapter 2: Historical and Theoretical Roots—How Research Approached Choice and Fatigue

Early Foundations: Signal Detection and Attention Resource Views

Resource Models and the Rise of Ego Depletion

Dual-Process, Bounded Rationality, and Sequential Choice

Sequential Choice Experiments and Time-on-Task Findings

Neuroscience: Executive Function, Cognitive Energy, and Network Dynamics

Methodological Shifts: From Lab Tasks to Field Measurement and Operationalization

4

Chapter 3: Measuring Decision Fatigue—Methods, Metrics, and Validity

Fundamentals of operationalizing decision fatigue

Behavioral performance metrics and task design

Physiological and neurophysiological markers

Subjective measures, ecological sampling, and calibration

Statistical modeling, composite indices, and validation

5

Chapter 4: Neural Mechanisms—Executive Control, Salience, and the Energy Costs of Choice

Neural substrates of control and salience

Metabolic and hemodynamic costs of prolonged decision making

Dopamine, effort allocation, and valuation under choice load

Network dynamics, signal-to-noise, and control fragility

Temporal dynamics and accumulation of cognitive fatigue

Translational targets: reducing neural cost through structure and timing

6

Chapter 5: Behavioral Economics of Choice—When More Options Reduce Value

Theoretical foundations: choice overload, bounded rationality, and value decline

Empirical evidence: what replicates, what depends on context

Cognitive mechanisms: attention, working memory, valuation, and mental energy

Sequential dependency and temporal structure: how prior choices reshape later valuation

Design implications: pruning options, structuring defaults, and institutional minimalism

7

Chapter 6: Habit Architecture and Cognitive Energy Minimalism

Conceptual foundations of cognitive energy minimalism

Mechanisms that convert decisions into habits

Taxonomy of habit interventions

Design principles for high-variability contexts

Boundaries and failure modes of automation

Experimental designs and measurement strategies

8

Chapter 7: Environmental and Contextual Contributors to Cognitive Load

Spatial configuration and physical layout

Information density and interface complexity

Interruptions, task switching, and temporal fragmentation

Multimodal sensory load and noise

Signage, affordances, and wayfinding

Environmental interventions and measurement checklist

9

Chapter 8: Workflow Design and Cognitive Ergonomics for High-Performance Teams

Cognitive ergonomics: foundational principles for workflows

Task decomposition and cognitive chunking

Temporal batching and schedule architecture

Decision triage and role specialization

Handoff protocols and queue management

Metrics, pilots, and scaling operational changes

10

Chapter 9: Individual Interventions—Scheduling, Recovery, and Cognitive Hygiene

Prioritized Scheduling: Reserve Peak Capacity for Core Decision Work

Strategic Breaks and Micro-Recovery: Evidence-Based Pause Architectures

Sleep and Circadian Alignment: Timing Work to Biology

Nutrition and Hydration: Metabolic Support for Executive Control

Cognitive Training, Task Design, and Executive Offloading

Monitoring Overload and Adaptive Reallocation: From Detection to Action

11

Chapter 10: Organizational Strategies—Policy, Culture, and Leadership to Prevent Overload

Policy design and cognitive load calculus

Meeting hygiene, calendar design, and time-boxed defaults

Information governance: signals, noise, and curated flows

Delegated authority, decision rights, and escalation pathways

Measuring impact: operational and cognitive metrics for pilots

Culture, leadership, and sustaining low-friction practices

12

Chapter 11: Technology, Automation, and the Paradox of Choice Reduction

Technology’s dual role in cognitive load

Design principles that genuinely reduce decision work

Common failure modes that increase cognitive burden

Metrics and criteria for evaluating net cognitive cost

Experimental paradigms to test cognitive impact

Best practices for integrating decision aids into expert workflows

13

Chapter 12: Recovery, Plasticity, and Long-Term Resilience

Sleep, Slow-Wave Consolidation, and Metabolic Reset

Active Rest, Micro-Recovery, and Transition Routines

Neural Plasticity, Offloading, and Adaptive Remapping of Control Networks

Organizational Policies, Scheduling, and Cultural Protections for Recovery

14

Chapter 13: Research Agenda—Key Questions, Experimental Designs, and Open Problems

Priority research questions and framing

Mechanisms: linking choice load to sustained performance decline

Experimental designs and multimodal measurement

Individual differences: moderators and susceptibility

Organizational interventions, ethics, and scaling

Data standards, collaboration, and open problems

15

Chapter 14: The Minimal Cognitive Load System—A Practical Framework for Experts and Leaders

System Overview and Principles

Measuring Decision Density

Environmental Triage

Habit Architecture Templates

Workflow Redesign Heuristics

Governance, 90-Day Pilots, and Scaling

16

Chapter 1: Defining the Fatigue Spiral—From Concept to Measurable Liability

This opening chapter grounds the book in a clear, operational definition of decision fatigue as a measurable cognitive liability rather than a casual metaphor. It explains why treating decision fatigue as an empirical phenomenon matters for researchers and leaders: when choices, micro-decisions, and environmental complexity accumulate, executive function resources decline in predictable ways. The chapter maps the construct space, distinguishing decision fatigue from related concepts such as mental fatigue, ego depletion, cognitive load, and burnout.

Readers will find precision about the dependent variables typically affected by excessive choice—accuracy, reaction time, error rate, persistence on demanding tasks, and self-regulation—and the independent variables that drive the spiral, including choice frequency, choice complexity, and interrupted workflow. The chapter also outlines the logic of the book: show the mechanisms, synthesize the evidence across disciplines, and build an evidence-based minimalist system to reduce cognitive burden while preserving adaptive flexibility. Throughout, the framing is practical and research-driven: this is a diagnostic framework for designing experiments, measuring cognitive cost, and testing interventions in real-world professional settings. By the end of the chapter, experts will have a usable conceptual model that prepares them to evaluate the empirical claims in subsequent chapters and to translate those claims into testable workplace strategies.

Defining decision fatigue as an operational cognitive liability

This section defines decision fatigue as an operational, measurable depletion of cognitive capacity in professional settings.

Decision fatigue is characterized by systematic declines in accuracy, slower reaction times, and increased error rates on control-demanding tasks.

Decision fatigue manifests as reproducible declines in task accuracy, lengthened reaction times, and higher error rates on cognitive-control–demanding tasks. These signatures appear across inhibitory control, working memory updating, and task-switching paradigms, and they are evident in both simple vigilance tasks and complex decision environments. Empirical studies report systematic shifts in response distributions — including increased lapses, longer tail RTs, and reduced sensitivity in signal-detection metrics — rather than random noise.

Quantifying these patterns requires decomposition of observed performance into processing speed, response criterion, and variability components. Methods such as drift-diffusion modeling, ex-Gaussian RT analysis, and signal-detection approaches help distinguish slowed evidence accumulation from lowered decision thresholds. For practitioners, these distinctions matter: slower accumulation implies reduced cognitive throughput, whereas threshold shifts indicate tolerance for risk or effort. Both pathways reliably index a measurable cognitive liability that undermines high-stakes professional performance.

Treat it as a dependent variable indexed by behavioral performance, self-regulation failures, and persistence on effortful tasks.

Treat decision fatigue explicitly as a dependent variable operationalized through convergent behavioral and self-regulatory indices. Core objective measures include lapsing errors, accuracy, reaction-time distributions, and task persistence (time-on-task or voluntary dropout). Complement these with behavioral proxies of self-regulation—impulsive choices in intertemporal or dietary tasks, escalation of risk-taking, or increased susceptibility to bribery/ethical lapses in experimental paradigms.

Subjective and physiological measures (self-report momentary fatigue, pupil diameter, heart-rate variability) provide triangulation but should not substitute for primary behavioral endpoints. For rigorous inference, pre-specify primary and secondary DVs, correct for multiple comparisons, and report both raw and change scores. In applied settings, express DV change relative to baseline capacity to estimate operational risk: percentage decline in accuracy per hour, increased probability of critical errors after n choices, or reduced persistence under standard cognitive load. This multidimensional indexing renders decision fatigue a quantifiable outcome for research and practice.

Operationalization requires precise task selection, pre-specified metrics, and baseline calibration to capture within-subject change.

Operationalizing decision fatigue requires rigorous task selection, pre-specified metrics, and individualized baseline calibration. Choose tasks that tax the target executive components—response inhibition, working memory capacity, or sustained attention—rather than heterogeneous composite tasks that obscure mechanism. Predefine primary outcome metrics (e.g., d-prime, median RT, omission rate, persistence duration) and statistical thresholds to avoid post hoc cherry-picking.

Baseline calibration is essential: run participants through a calibration session to estimate stable performance ceilings, practice effects, and diurnal variability. Use adaptive titration where possible to equate subjective difficulty across subjects, and include manipulation checks to confirm engagement. Report reliability statistics, minimal detectable change, and intraclass correlations for repeated measures. Together, these practices permit sensitive within-subject comparisons, improve statistical power, and make observed changes interpretable as true cognitive liability rather than measurement noise.

Measure time course: acute episodes after intense choice bouts versus cumulative declines across a workday or week.

Measure the time course of decision fatigue by distinguishing acute episodes that follow intense choice bouts from slower, cumulative declines across a workday or week. Acute effects can emerge within minutes after a dense sequence of high-stakes choices and are best captured with event-related designs, rapid pre/post task comparisons, or high-resolution reaction-time sampling. In contrast, cumulative liability accumulates gradually and requires longitudinal monitoring—experience sampling, ecological momentary assessment (EMA), or passive digital phenotyping across days.

Analytic strategies should reflect temporal scale: use mixed-effects growth models, change-point detection, and time-varying covariates to model recovery, saturation, and lagged effects. Consider recovery dynamics—sleep, breaks, and low-demand activities—and test boundary conditions such as circadian phase and workload shifts. Mapping both acute and chronic trajectories enables targeted interventions timed to vulnerability windows.

Report both absolute deficits and relative vulnerability to interruptions, stressors, and reward manipulations to capture liability.

Report both absolute deficits and relative vulnerability to contextual disruptors—interruptions, stressors, and reward manipulations—to fully characterize decision fatigue as a liability. Absolute metrics quantify loss (e.g., decline in accuracy points, mean RT increase, or reduced persistence minutes) against an individual’s calibrated baseline or a normative benchmark. These figures are critical for operational risk assessment and capacity planning.

Relative vulnerability captures sensitivity: how much performance degrades when exposed to interruptions, acute stress, monetary incentives, or altered reward structures. Test interactions and moderation with trait characteristics (cognitive reserve, trait self-control), situational moderators (task complexity, time pressure), and protective behaviors (scheduled breaks, automated defaults). Report standardized effect sizes, confidence intervals, and conditional effects to convey both population-level impact and heterogeneity. This dual reporting enables researchers and leaders to translate lab signals into practical thresholds for decision architecture and workload design.

Distinguishing decision fatigue from mental fatigue, ego depletion, cognitive load, and burnout

Clarifies boundaries between decision fatigue and related concepts to avoid conflation in experiments and practice.

Mental fatigue is broader and often subjective; decision fatigue is a task-linked decline in executive control resources.

Mental fatigue denotes a diffuse, often phenomenological state characterized by reduced vigor, increased malaise, and generalized cognitive slowing. It encompasses affective and motivational components that reflect whole-system wear, emerging after prolonged wakefulness, sustained attention, or emotional strain. Importantly, mental fatigue is frequently reported via subjective scales (e.g., visual analogue scales, Karolinska Sleepiness Scale) and correlates with broad performance decrements across domains.

By contrast, decision fatigue is a narrower construct: a measurable decline in executive control capacity linked specifically to repeated acts of choice and self-regulation. It manifests as systematic reductions in decision quality, increased impulsivity, and faster error rates on tasks requiring selection among options. Decision fatigue is therefore operationalizable with task-specific dependent variables (accuracy, choice consistency, reaction time) and can be isolated experimentally by manipulating choice frequency and complexity while controlling for global fatigue contributors.

Ego depletion historically posits a finite willpower pool; modern evidence reframes resource decline as context sensitive and measurable.

The ego-depletion model originally conceptualized self-control as a limited, single reservoir—exertion of self-control would temporarily deplete this reservoir, leading to poorer subsequent regulation. Early meta-analytic and experimental work supported this intuitively attractive metaphor.

Contemporary research, however, critiques the resource metaphor and emphasizes context sensitivity: motivational shifts, task framing, reward structure, and physiological states modulate apparent depletion. Neurobiological measures (e.g., prefrontal activation, dopaminergic indices) and rigorous preregistered replications reveal that observed declines are not purely a drained pool but arise from interactive influences on effort allocation and opportunity cost computations. For researchers, this reframing means designing protocols that distinguish motivational reallocation from true capacity impairment, using convergent physiological and behavioral markers rather than relying solely on sequential behavioral decrements.

Cognitive load concerns information processing demands; decision fatigue emphasizes repeated choice acts that tax self-regulation.

Cognitive load theory addresses the limitations of working memory when handling intrinsic, extraneous, and germane load during learning or problem solving. It predicts impaired encoding, integration, and transfer when processing demands exceed available working memory resources, and it is primarily concerned with information complexity and instructional design.

Decision fatigue, in contrast, centers on the cumulative burden of making selections—each choice invokes valuation, comparison, and inhibitory processes that engage executive control networks. While high cognitive load can exacerbate decision costs, decision fatigue is specifically about the temporal accumulation of choice-related control demands, producing shifts in risk preferences, simplified heuristics, and diminished persistence. Experimentally separating the two requires orthogonal manipulations: varying information complexity independently from choice frequency and assessing distinct dependent measures such as working memory span versus choice consistency and self-control performance.

Burnout is a chronic occupational syndrome with affective features; decision fatigue can be an acute mechanism that contributes to burnout.

Burnout is a multifaceted, work-related syndrome characterized by emotional exhaustion, depersonalization, and reduced professional efficacy. It unfolds over extended periods and is diagnosed through standardized inventories (e.g., Maslach Burnout Inventory) and longitudinal patterns of occupational dysfunction, with strong affective and social components.

Decision fatigue operates on a shorter timescale as an acute erosion of regulatory capacity resulting from dense or complex decision environments. Repeated episodes of decision fatigue can act as a proximal mechanism that accelerates the pathway to burnout by chronically elevating cognitive effort, depleting recovery opportunities, and increasing emotional strain. For applied researchers and leaders, monitoring decision load and instituting organizational interventions (choice architecture, role simplification, protected recovery periods) can reduce the cumulative exposure that links acute decision fatigue events to long-term burnout trajectories.

Distinguish by timescale, biomarkers, task specificity, and by including both subjective reports and objective performance measures.

Accurate operational distinctions require explicit multipronged measurement. Timescale separation—momentary (minutes to hours) for decision fatigue, prolonged (weeks to months) for burnout or chronic mental fatigue—guides sampling frequency and study duration. Biomarkers such as pupil dilation, heart rate variability, cortisol reactivity, and prefrontal EEG power provide objective indices that can discriminate transient executive overload from systemic dysregulation.

Task specificity matters: use choice-heavy paradigms to elicit decision fatigue and domain-general sustained-attention tasks to probe broader mental fatigue. Combine subjective instruments (fatigue scales, perceived effort) with objective metrics (reaction time variability, error rates, lapse probability) and multilevel models to parse within-person dynamics. This layered approach allows researchers to attribute variance to immediate choice accumulation versus enduring physiological or psychosocial factors.

Design experiments with appropriate controls to isolate choice-driven effects from general tiredness, stress, or sleep loss.

Experimental rigor demands isolating the causal role of choice accumulation. Randomized manipulations should independently vary choice frequency/complexity while holding total task duration, stimulus novelty, and cognitive load constant. Include active control conditions that equate attentional demand without introducing sequential selection requirements.

Pre-screen and monitor confounds: control for sleep quantity/quality, circadian timing, acute stress (validated questionnaires, salivary cortisol), and motivational incentives. Use within-subject crossover designs with adequate washout to reduce inter-individual variance and exploit physiological markers (pupillometry, HRV) as manipulation checks. Finally, preregister hypotheses and analysis plans, report null and effect-size estimates, and implement Bayesian or mixed-effects modeling to robustly attribute observed performance shifts to decision-specific mechanisms rather than generalized fatigue or stress.

Core independent variables that drive the fatigue spiral

Enumerates key drivers of cognitive liability that can be manipulated or measured in studies robustly.

Choice frequency: count of discrete decisions per unit time, which predicts cumulative executive cost in within-subject designs.

Choice frequency operationalizes the density of discrete decision events experienced by an individual over a defined interval (e.g., decisions/hour). In experimental work this is typically manipulated by altering decision rate while holding choice content constant, enabling within-subject contrasts that isolate cumulative executive cost from item-specific difficulty.

Empirically, higher decision frequency predicts systematic declines in accuracy, slower reaction times, and increased reliance on heuristics as trials accumulate. Measurement strategies include event logging, decision timestamps, and decision-density indices that normalize for task duration. Analytical approaches favor multilevel time-series or survival models to capture within-person trajectories and inflection points where performance slope increases.

For researchers and practitioners, frequency is a scalable lever: reducing decision events via batching, defaults, or automation can demonstrably preserve executive bandwidth and delay the onset of measurable fatigue.

Choice complexity: dimensionality, uncertainty, and payoff structure that increase deliberation and working memory demands.

Choice complexity refers to structural features of options that elevate cognitive processing: number of attributes (dimensionality), probabilistic uncertainty, and payoff heterogeneity. Each dimension independently and interactively inflates working memory load and deliberation time, producing longer latencies and higher error variability.

Operational measures include attribute count, branching factor in sequential choices, entropy of outcome distributions, and variance in expected value. Physiological and behavioral proxies—pupil dilation, response time distributions, and secondary-task interference—validate increased cognitive load. Neuroimaging links complexity to greater prefrontal activation and slower drift rates in decision models.

Experimentally, parametrically varying these features enables mapping of non-linear performance functions. For applied design, minimizing unnecessary attributes and making payoffs transparent reduces deliberation cost while preserving adaptive choice quality.

Interruptions and task switching: the cost of resuming goals amplifies accumulation of decision-related fatigue.

Interruptions and task switches impose reconfiguration costs: the time and cognitive steps required to rebuild task context and goal states. These costs compound decision-related fatigue by fragmenting working memory and increasing the number of micro-decisions needed to resume and reprioritize tasks.

Quantitatively, resumption lag, increased error probability post-interruption, and elevated switch costs in reaction time distributions are robust markers. Experimental paradigms measure interruption frequency, duration, and semantic distance from primary tasks to estimate additive cognitive load.

Beyond immediate performance decrements, repeated interruptions magnify depletion trajectories, accelerating declines in persistence and self-regulation. Mitigation tactics—structured interruption windows, explicit resumption cues, and contextual anchors—reduce reconstitution demands and preserve executive capacity across prolonged workflows.

Stakes and ambiguity: high stakes or ambiguous feedback alter motivational effort and shift vulnerability to depletion.

Stakes and ambiguity modulate how motivational systems allocate cognitive resources. High stakes can transiently mobilize effort, improving performance under short horizons, but sustained high-stakes demands increase vulnerability to fatigue by amplifying evaluative monitoring and stress physiology.

Ambiguous feedback compounds this effect: when outcomes provide noisy or delayed signals, individuals invest more deliberative effort and monitoring, inflating cognitive cost per decision. Operational manipulations include reward magnitude, performance-contingent penalties, and feedback clarity.

Empirical signatures include altered speed–accuracy tradeoffs, increased catecholamine responses, and greater variability in persistence. Crucially, stakes and ambiguity interact with individual differences in tolerance for uncertainty and motivational orientation, producing heterogeneous fatigue slopes that must be modeled as moderators in experimental and field studies.