Can ChatGPT Provide Useful Guidance to Assess the Current State of and Future Priorities for Aging Research in the Social Sciences?

The multifaceted implications of global population aging require regular assessments of the current state of aging-related social science research and the identification of potential future research priorities in this important area. Given the multi-, inter-, and transdisciplinary nature of this field, such assessments typically require the involvement of experts from diverse backgrounds to ensure a comprehensive picture and to synthesize understudied and newly emerging topics into a future research agenda. We explored to what extent ChatGPT (version GPT-4, OpenAI) might be a useful tool for synthesizing the current state of research and identifying promising future research areas, which could feed into expert panel discussions for priority setting. ChatGPT proposed a long list of topics and specific research questions that are useful in summarizing current views on research priorities across diverse sources. To illustrate, the top five priorities for future aging research identified by ChatGPT were digital integration, climate change and older populations, mental health and aging, aging in diverse contexts, and post-pandemic aging. In conclusion, ChatGPT may be a useful tool for identifying research agenda priorities across organizations present in the web, but the lack of transparency requires that experts critically evaluate the values and views underlying selected priorities.

Authors

Institutions

Publication Details

Journal
Journal of Aging & Social Policy
Published
2024-11-04
DOI
https://doi.org/10.1080/08959420.2024.2422669
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.24

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Can ChatGPT Provide Useful Guidance to Assess the Current State of and Future Priorities for Aging Research in the Social Sciences?

Mauricio Avendaño, John Beard, Maud Wieczorek, Jürgen Maurer et al.
2 citations
Journal of Aging & Social Policy
Artificial Intelligence in Healthcare and Education
0.24
article

Can ChatGPT Provide Useful Guidance to Assess the Current State of and Future Priorities for Aging Research in the Social Sciences?

Mauricio Avendaño, John Beard, Maud Wieczorek, Jürgen Maurer, Matthias Kliegel, Françis Guillemin
article en
2 citations

Abstract

The multifaceted implications of global population aging require regular assessments of the current state of aging-related social science research and the identification of potential future research priorities in this important area. Given the multi-, inter-, and transdisciplinary nature of this field, such assessments typically require the involvement of experts from diverse backgrounds to ensure a comprehensive picture and to synthesize understudied and newly emerging topics into a future research agenda. We explored to what extent ChatGPT (version GPT-4, OpenAI) might be a useful tool for synthesizing the current state of research and identifying promising future research areas, which could feed into expert panel discussions for priority setting. ChatGPT proposed a long list of topics and specific research questions that are useful in summarizing current views on research priorities across diverse sources. To illustrate, the top five priorities for future aging research identified by ChatGPT were digital integration, climate change and older populations, mental health and aging, aging in diverse contexts, and post-pandemic aging. In conclusion, ChatGPT may be a useful tool for identifying research agenda priorities across organizations present in the web, but the lack of transparency requires that experts critically evaluate the values and views underlying selected priorities.

Journal of Aging & Social PolicyVol. 37(4)
University of Geneva (CH), Inserm (FR), FORS – Swiss Centre of Expertise in the Social Sciences (CH), Centre universitaire de médecine générale et santé publique, Lausanne (CH), Interdisciplinarité en Santé Publique Interventions et Instruments de mesure complexes – Région Est (FR), Columbia University (US), Université de Lorraine (FR), University of Lausanne (CH)
Velux Stiftung
Openalex Percentile: Top 39%
Artificial Intelligence in Healthcare and Education
0.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.