Evidence map›Paper›PMID 42438156›Full record

ArticleThe journals of gerontology. Series B, Psychological sciences and social sciences2026

Growth mindset and grit as psychological resources in later life: age, socioeconomic status, and health patterning in the English Longitudinal Study of Ageing.

Paola Zaninotto, Bran Knowles, Jasmine Fledderjohann, Alice Ashcroft, Andrew Steptoe

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Article in The journals of gerontology. Series B, Psychological sciences and social sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Paola ZaninottoDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.ORCID 0000-0003-3036-0499
Bran KnowlesSchool of Computing and Communications, Lancaster University, Lancaster, United Kingdom.ORCID 0000-0002-2554-1896
Jasmine FledderjohannSchool of Social Sciences, Lancaster University, Lancaster, United Kingdom.ORCID 0000-0003-4952-7658
Alice AshcroftDigital Heard Ltd, Lancaster, United Kingdom.
Andrew SteptoeDepartment of Behavioural Science and Health, University College London, London, United Kingdom.ORCID 0000-0001-7808-4943

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
Department of Health and Social CareEPSRC EP/W025337/1National Institute on Aging of the National Institutes of Health R01AG017644NIA NIH HHS R01 AG017644NIH HHSNIHR 198_1074_03
6 · The paper itself

Abstract

objectivesGrowth Mindset and Grit have been proposed as key psychological resources for resilience and adaptation, yet their manifestation and social distribution in later life remain underexplored. This study examines the structure, distribution, and correlates of proxy indicators of Growth Mindset and Grit using the English Longitudinal Study of Ageing (ELSA).

methodsProxy indicators reflecting learning behavior, personality traits, affect, and beliefs were used to derive 3 components of Growth Mindset (education-, personality-, and belief-based) and 2 components of Grit (affective- and personality-based). Multinomial logistic regression models were used to examine the correlates of Growth Mindset and Grit components, including age, socioeconomic status, health, and cognitive functioning.

resultsDistinct distributional patterns emerged across components. Education-based Growth Mindset was concentrated in lower categories, whereas personality-, belief-, and affect-based components showed greater variability. Older age was associated with lower Growth Mindset, particularly in education- and belief-based domains, while associations with Grit were more nuanced, including a lower likelihood of low affect-based Grit among older adults. Higher educational attainment, employment, wealth, and better memory performance were associated with more favorable profiles across selected domains. Living alone and limiting longstanding illness were consistently associated with less favorable profiles. DISCUSSION: Growth Mindset and Grit-related proxy indicators were socially patterned and showed distinct associations across belief, personality, affective, and behavioral domains in later life. The differing distributions observed across these domains highlight the importance of distinguishing between opportunity-constrained behavioral indicators, such as formal learning, and more dispositional characteristics when studying psychological resources in older populations.

Indexed as

Adaptation, PsychologicalAgingHealth StatusPersonalityResilience, PsychologicalSocial ClassAgedAged, 80 and overEducational StatusEnglandFemaleHumansLongitudinal StudiesMaleMiddle AgedSocioeconomic Disparities in HealthLearning behaviorPersonality traitsSocioeconomic status

Identifiers

PMID42438156
PMCPMC13589786

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.