Data · dataset · 2026
Science, Arts, and National Mental Health: A Cross-National Panel Study of Intellectual Capital and Anxiety Prevalence
Listed in Teesside University Research Data Repository
The dataset supports the manuscript “Science, Arts, and National Mental Health: A Cross-National Panel Study of Intellectual Capital and Anxiety Prevalence.” It is a country-year panel dataset covering 149 countries over 26 years from 1995 to 2020, yielding approximately 3,874 observations.
Description
The dependent variable is national anxiety prevalence (NAP), measured as the population prevalence of anxiety and depression. The main explanatory variables capture national intellectual capital development in two domains: the sciences, measured through science, technology, engineering, and mathematics publication intensity per capita, and the arts, measured through social sciences, humanities, and creative arts publication intensity per capita.
The dataset also includes their interaction term to examine whether arts-based intellectual capital moderates the association between science-based intellectual capital and national mental health. Additional variables include education attainment among the population aged 15 and above, GDP per capita, R&D expenditure, health expenditure, internet diffusion, population size, economic freedom, political corruption, military spending, individualism, and OECD/developing-economy status.
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The data were assembled from internationally comparable sources, including the World Health Organization, Clarivate Journal
Citation
Reports, the World Bank, SIPRI, and institutional/economic indicators, and were prepared for longitudinal mixed-effects, robustness, lagged-effect, and sensitivity analyses.
Links
Where it is published
- DOI doi.org/10.17632/8gxw4j6htf.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Econometrics 73% · Longitudinal study 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/8gxw4j6htf.1 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:3802 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (73%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |