Re-considering ‘impact’ for longitudinal social science research: towards more scientific approaches to theorising and measuring the influence of cohort studies

Demonstrating ‘impact’ has become increasingly important in research and academia alongside growing consideration of the social effects of research and the ethical standards involved. However, there are also concerns about a preoccupation with ‘impact’ in academia, which may result in a narrow focus on applied research. The most common definitions of impact (for example, UK Research Excellence Framework) emphasise generating measurable change outside of academia. However, this may overlook other important endeavours, such as influencing discourse and development of theory. The implicit assumption that single research projects will trigger measurable policy change is often unrealistic. Data infrastructures are also expected to demonstrate their ‘impact’, yet existing definitions are levied at the individual researcher or substantive projects. Such definitions do not account for the additional assumptions required for infrastructure to be impactful, and arguably, in their current form are not fit for purpose in demonstrating the full contribution of longitudinal and life course studies to society. We argue that broader definitions of impact should be considered for longitudinal studies and data infrastructure, that account for the importance of ‘influence’, and recognise the many and multifaceted contributions of longitudinal and life course research. Here we aim to (1) review definitions of impact in the context of longitudinal and life course studies, using UK national cohorts as a case studies; (2) to provide a working definition appropriate for longitudinal research, that incorporates ‘influence’; and (3) to consider approaches that can be utilised to track impact.

Publication Details

Journal
UCL Discovery (University College London)
Published
2025-06-02
Primary Topic
Scientific Computing and Data Management
Type
article
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article

Re-considering ‘impact’ for longitudinal social science research: towards more scientific approaches to theorising and measuring the influence of cohort studies

UCL Discovery (University College London)
Scientific Computing and Data Management
article

Re-considering ‘impact’ for longitudinal social science research: towards more scientific approaches to theorising and measuring the influence of cohort studies

article en

Abstract

Demonstrating ‘impact’ has become increasingly important in research and academia alongside growing consideration of the social effects of research and the ethical standards involved. However, there are also concerns about a preoccupation with ‘impact’ in academia, which may result in a narrow focus on applied research. The most common definitions of impact (for example, UK Research Excellence Framework) emphasise generating measurable change outside of academia. However, this may overlook other important endeavours, such as influencing discourse and development of theory. The implicit assumption that single research projects will trigger measurable policy change is often unrealistic. Data infrastructures are also expected to demonstrate their ‘impact’, yet existing definitions are levied at the individual researcher or substantive projects. Such definitions do not account for the additional assumptions required for infrastructure to be impactful, and arguably, in their current form are not fit for purpose in demonstrating the full contribution of longitudinal and life course studies to society. We argue that broader definitions of impact should be considered for longitudinal studies and data infrastructure, that account for the importance of ‘influence’, and recognise the many and multifaceted contributions of longitudinal and life course research. Here we aim to (1) review definitions of impact in the context of longitudinal and life course studies, using UK national cohorts as a case studies; (2) to provide a working definition appropriate for longitudinal research, that incorporates ‘influence’; and (3) to consider approaches that can be utilised to track impact.

UCL Discovery (University College London)
Industry, innovation and infrastructure
Openalex Percentile: Top 31%
Scientific Computing and Data Management
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Re-considering ‘impact’ for longitudinal social science research: towards more scientific approaches to theorising and measuring the influence of cohort studies · UCL Discovery (University College London) (2025) | TGRS Research Map | TGRS