Evidence map›Paper›PMID 37268387›Full record

ArticleJournal of aging studies2023

Vulnerability in context; hard numbers, tricky words and grey areas for gerontology.

Linda Naughton, Miguel Padeiro, Beatriz Bueno-Larraz

Open access · greenAbstract read
In one paragraph

Article in Journal of aging studies, 2023. 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
2.9field-weighted citation impact, top 11% of its field
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, 6 citations in OpenAlex.

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 at 1 institution in 1 country.

Linda NaughtonUniversity of Coimbra, Portugal. Electronic address: Linda.Naughton@uc.pt.
Miguel PadeiroUniversity of Coimbra, Portugal.
Beatriz Bueno-LarrazIndependent Consultant.
University of Coimbra · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At the start of the COVID-19 pandemic, the Portuguese government identified those aged 70 or more as a risk group, placing a special duty of protection on them to shelter-at-home. This paper asks how Portuguese municipalities, using Facebook posts, communicated the risk to older adults and to what extent ageist stereotypes were found in the language and frames employed. Over 3800 Facebook posts made by Portuguese municipalities concerning older adults and COVID-19 published between March and July 2020 were analyzed. Language counts for age-related words were used in a first round of content analysis followed by a process of thematic analysis. Findings indicate that the language used to address Portuguese older adults could be understood as ageist in terms of homogenizing older people as a fixed group. The communication of risk was often conflated with the vulnerability narrative already observed in the extant literature. However, context- and culture-specific themes of 'solidarity', 'inter-relatedness', 'duty of care' and 'support for those living in isolation' were also found. The study highlights the extent to which language, culture and context are intertwined with our understanding of age, aging and ageism. It provides a culturally-specific case study, which challenges both gerontological interpretations of vulnerability and neoliberal frames which focus responsibility on the individual regardless of age. We argue that these alternative frames echo the emerging discourse of mutual aid and solidarity, providing a wider context for addressing vulnerability in a health crisis.

Indexed as

AgeismCOVID-19GeriatricsAgedAgingHumansPandemicsAgeismCOVID-19FacebookGerontologyInterdependenceOlder adultsPortugalSolidarityVulnerability

Identifiers

PMID37268387
PMCPMC10036039
OpenAlexW4360603253

What OpenQuestion holds

Textmetadata
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.