Evidence map›Paper›PMID 41422066›Full record

ArticlePopulation health metrics2025

Mediating effects between social capital and health care utilization in Italy-a structural equation model analysis.

Tallys Feldens, Chiara Seghieri, Andrea Fontana, Paolo Berta

Abstract read
In one paragraph

Article in Population health metrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Tallys FeldensIstituto di Management, L'EMbeDS, Scuola Superiore Sant 'Anna di Pisa, Piazza Martiri della Libertà, 33, Pisa, Italy.ORCID 0000-0002-1804-8315
Chiara SeghieriIstituto di Management, L'EMbeDS, Scuola Superiore Sant 'Anna di Pisa, Piazza Martiri della Libertà, 33, Pisa, Italy. chiara.seghieri@santannapisa.it.ORCID 0000-0002-3910-7775
Andrea FontanaUniversità degli Studi di Milano-Bicocca, Milan, Italy.
Paolo BertaUniversità degli Studi di Milano-Bicocca, Milan, Italy.ORCID 0000-0003-0984-4288

Funding

NextGenerationEU CUP: B53D23016730006
6 · The paper itself

Abstract

backgroundSocial capital, in its broad definitions, has been linked to improved health outcomes, yet the scarce consistency of social capital measurements and its further effects on healthcare utilization remain less clear. Particularly in Italy, where regional disparities and an aging population challenge the healthcare system, understanding these dynamics is crucial. This study proposes two population-based indicators of social capital and investigates whether they influence health itself and healthcare utilization.

methodItalian population data from 2014 to 2023 was used to develop two social capital measurements: Social support and Social participation, applying Item Response Theory (IRT). Hence, we applied structural equation modeling (SEM) to explore the pathways between social capital, self-reported health status, and healthcare utilization. The analysis includes control variables for demographic and behavioral factors.

resultsOur main findings contribute with the current literature by identifying that population-based measures for social support and social participation may be useful for empirical research, and both direct and indirect effects of social constructs were found significantly associated with health and health utilization outcomes. Both social participation and social support were found to exert significant positive effects on self-perceived health and health utilization. The model suggests that while better social connections contribute to improved health, such increased support and participation can also lead to increased healthcare-seeking behavior.

conclusionSocial capital plays a dual role in shaping both health outcomes and healthcare utilization in Italy. Our findings highlight the relevance of social resources as population-level determinants of health and access, suggesting that strengthening community networks and health literacy can reduce inequities and enhance the efficiency of healthcare systems.

Indexed as

Patient Acceptance of Health CareSocial CapitalAdolescentAdultAgedFemaleHealth StatusHumansItalyLatent Class AnalysisMaleMiddle AgedSocial ParticipationSocial SupportYoung AdultHealthcare utilizationItalySocial capital

Identifiers

PMID41422066
PMCPMC12750791

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LicenceCC BY
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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.