Evidence map›Paper›PMID 42163916›Full record

ArticleFrontiers in public health2026

Digital engagement in the silver economy.

Ieva Meidute-Kavaliauskiene, Olga Iurasova, Artūras Jakubavičius

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ieva Meidute-KavaliauskieneBusiness Management Faculty, Vilnius Gediminas Technical University, Vilnius, Lithuania.
Olga IurasovaBusiness Management Faculty, Vilnius Gediminas Technical University, Vilnius, Lithuania.
Artūras JakubavičiusBusiness Management Faculty, Vilnius Gediminas Technical University, Vilnius, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Population aging and accelerating digitalization increase the relevance of the silver economy, as country-level patterns of digital engagement among older age groups shape inclusion in markets and services. Methods: This study examines the country-level association between productive digital engagement among people aged 55-74 and two macroeconomic outcomes (GDP per capita and GNI per capita) across European countries plus Iceland and Norway, using OECD ICT Access and Usage by Households and Individuals indicators. Independent variables measure the national prevalence of purpose-specific online activities (online purchasing, online course participation, use of online ICT services, social networking, and health information search), a skills barrier (lack of skills for submitting online forms), and a digital infrastructure proxy (fixed broadband subscriptions). A multivariate linear regression model is estimated, and multicollinearity is assessed. Results: The models explain a substantial share of cross-country variation in GDP per capita (R Conclusion/implications: Cross-country differences in GDP per capita align more closely with the country-level prevalence of transactional and skill-building digital activities among people aged 55-74 than with internet-use frequency alone. Because the analysis is observational and based on national aggregates, the findings indicate associations at the country level and should not be interpreted as causal or as individual-level relationships.

Indexed as

Gross Domestic ProductInternetDigital MediaEuropeHumansassociationdigitaldigital engagementGDP per capitapeople aged 55–74silver economy

Identifiers

PMID42163916
PMCPMC13183795

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.