Quantifying resilience of humans and other animals

Scheffer, Marten; Bolhuis, J.E.; Borsboom, Denny; Buchman, Timothy G.; Gijzel, Sanne M.W.; Goulson, Dave; Kammenga, J.E.; Kemp, B.; Leemput, Ingrid A. van de; Levin, Simon A.; Martin, Carmel M.; Melis, René J. F.; Nes, Egbert H. van; Romero, L. Michael; Rikkert, Marcel G M Olde

doi:10.1073/pnas.1810630115

Cited by 235 publications

(271 citation statements)

References 111 publications

(138 reference statements)

Supporting

Mentioning

262

Contrasting

Unclassified

Order By: Relevance

“…A promising approach to obtain accurate risk estimations comes from the theory of complex systems. Examples of such complex systems are ecosystems, which are known to make shifts from a forest state to a swamp state, or the financial market, which can experience a sudden collapse [3,4]. Although such changes are results of numerous mechanistic interactions, complex systems theory states that the stability of a system, i.e., how hard it is for a large change to occur, can be quantified in one characteristic: an index of resilience.…”

Section: Introductionmentioning

confidence: 99%

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

Kuranova

Booij

Menne-Lothmann

et al. 2020

BMC Med

View full text Add to dashboard Cite

Introduction: There is growing evidence that mental disorders behave like complex dynamic systems. Complex dynamic systems theory states that a slower recovery from small perturbations indicates a loss of resilience of a system. This study is the first to test whether the speed of recovery of affect states from small daily life perturbations predicts changes in psychopathological symptoms over 1 year in a group of adolescents at increased risk for mental disorders.Methods: We used data from 157 adolescents from the TWINSSCAN study. Course of psychopathology was operationalized as the 1-year change in the Symptom Checklist-90 sum score. Two groups were defined: one with stable and one with increasing symptom levels. Time-series data on momentary daily affect and daily unpleasant events were collected 10 times a day for 6 days at baseline. We modeled the time-lagged effect of daily unpleasant events on negative and positive affect after each unpleasant event experienced, to examine at which time point the impact of the events is no longer detectable.Results: There was a significant difference between groups in the effect of unpleasant events on negative affect 90 min after the events were reported. Stratified by group, in the Increase group, the effect of unpleasant events on both negative (B = 0.05, p < 0.01) and positive affect (B = − 0. 08, p < 0.01) was still detectable 90 min after the events, whereas in the Stable group this was not the case. Conclusion: Findings cautiously suggest that adolescents who develop more symptoms in the following year may display a slower affect recovery from daily perturbations at baseline. This supports the notion that mental health may behave according to the laws of a complex dynamic system. Future research needs to examine whether these dynamic indicators of system resilience may prove valuable for personalized risk assessment in this field.

show abstract

Section: Introductionmentioning

confidence: 99%

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

Kuranova

Booij

Menne-Lothmann

et al. 2020

BMC Med

View full text Add to dashboard Cite

show abstract

“…In time series with sufficiently high frequency and length, dynamical indicators of resilience (DIORs), such as variance and temporal autocorrelation, can be calculated. DIORs have been developed as predictors in other complex dynamical systems, such as ecosystems and the climate, and have been hypothesized as a means to quantify resilience of humans as well …”

Section: Dynamical Resilience Measurementsmentioning

confidence: 99%

“…This process diminishes the recovery potential of the person as a whole. Figure adapted from Scheffer et al…”

Section: Linking Interactions Between Subsystemsmentioning

confidence: 99%

“…DIORs have been developed as predictors in other complex dynamical systems, such as ecosystems and the climate, 34 and have been hypothesized as a means to quantify resilience of humans as well. 35,36 DIORs were tested in a previous study that monitored self-rated health in a small group of older adults. 37 These older persons rated their own physical, mental, and social health daily for 100 consecutive days.…”

Section: Microrecoveries In Response To Natural Perturbationsmentioning

confidence: 99%

“…This process diminishes the recovery potential of the person as a whole. Figure adapted from Scheffer et al 35 the patient's signs and symptoms in daily clinical communication. This exploration may help increase awareness and make sense of the multisystem connections at all levels that contribute to the patient's varying course of recovery or decline and may offer unique opportunities for resilience management.…”

Section: Extending Clinical Reasoning By Addressing Interconnectionsmentioning

confidence: 99%

See 2 more Smart Citations

Resilience in Clinical Care: Getting a Grip on the Recovery Potential of Older Adults

Gijzel

Whitson

Leemput

et al. 2019

J American Geriatrics Society

Self Cite

View full text Add to dashboard Cite

Background Geriatricians are often confronted with unexpected health outcomes in older adults with complex multimorbidity. Aging researchers have recently called for a focus on physical resilience as a new approach to explaining such outcomes. Physical resilience, defined as the ability to resist functional decline or recover health following a stressor, is an emerging construct. Methods Based on an outline of the state‐of‐the‐art in research on the measurement of physical resilience, this article describes what tests to predict resilience can already be used in clinical practice and which innovations are to be expected soon. Results An older adult's recovery potential is currently predicted by static tests of physiological reserves. Although geriatric medicine typically adopts a multidisciplinary view of the patient and implicitly performs resilience management to a certain extent, clinical management of older adults can benefit from explicitly applying the dynamical concept of resilience. Two crucial leads for advancing our capacity to measure and manage the resilience of individual patients are advocated: first, performing multiple repeated measurements around a stressor can provide insight about the patient's dynamic responses to stressors; and, second, linking psychological and physiological subsystems, as proposed by network studies on resilience, can provide insight into dynamic interactions involved in a resilient response. Conclusion A big challenge still lies ahead in translating the dynamical concept of resilience into clinical tools and guidelines. As a first step in bridging this gap, this article outlines what opportunities clinicians and researchers can already exploit to improve prediction, understanding, and management of resilience of older adults. J Am Geriatr Soc 67:2650–2657, 2019

show abstract

A Dynamical Systems View of Psychiatric Disorders—Practical Implications

Scheffer,

Bockting,

Borsboom

et al. 2024

JAMA Psychiatry

Self Cite

View full text Add to dashboard Cite

ImportanceDynamical systems theory is widely used to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. It has been suggested that the same theory may be used to explain the nature and dynamics of psychiatric disorders, which may come and go with symptoms changing over a lifetime. Here we review evidence for the practical applicability of this theory and its quantitative tools in psychiatry.ObservationsEmerging results suggest that time series of mood and behavior may be used to monitor the resilience of patients using the same generic dynamical indicators that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforest and tipping elements of the climate system. Other dynamical systems tools used in ecology and climate science open ways to infer personalized webs of causality for patients that may be used to identify targets for intervention. Meanwhile, experiences in ecological restoration help make sense of the occasional long-term success of short interventions.Conclusions and RelevanceThose observations, while promising, evoke follow-up questions on how best to collect dynamic data, infer informative timescales, construct mechanistic models, and measure the effect of interventions on resilience. Done well, monitoring resilience to inform well-timed interventions may be integrated into approaches that give patients an active role in the lifelong challenge of managing their resilience and knowing when to seek professional help.

show abstract

Quantifying resilience of humans and other animals

Cited by 235 publications

References 111 publications

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

Resilience in Clinical Care: Getting a Grip on the Recovery Potential of Older Adults

A Dynamical Systems View of Psychiatric Disorders—Practical Implications

Contact Info

Product

Resources

About