Evidence map›Paper›PMID 31879702›Full record

ArticleInnovation in aging2019

Repeated Bereavement Takes Its Toll on Subjective Well-Being.

Frank J Infurna, Axel Mayer

Open access · goldAbstract read
In one paragraph

Article in Innovation in aging, 2019. 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
1.6field-weighted citation impact, top 16% 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

1 citing paper in PubMed, 11 citations in OpenAlex.

  1. Article
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

2 authors at 2 institutions in 2 countries.

Frank J InfurnaDepartment of Psychology, Arizona State University, Tempe.
Axel MayerDepartment of Psychology, RWTH Aachen University, Germany.
Arizona State University · USRWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesThe bereavement literature has shown that losing close loved ones can lead to sustained declines in quality of life. Research in this area has typically focused on singular bereavement events, such as the loss of a spouse or child. Much less is known regarding the consequences of repeated bereavement or repeated losses in one's social network. RESEARCH DESIGN AND

methodsWe use longitudinal panel survey data from the Household Income and Labour Dynamics of Australia study to examine the effect of repeated bereavement in one's social network on cognitive and affective measures of subjective well-being and whether there are age differences in the magnitude of these effects across young adulthood, midlife, and old age. To address our research questions, we use a multiple-group discontinuous change model with random effects.

resultsRepeated deaths in one's social network had a nonlinear effect on life satisfaction and positive affect, suggesting that individuals were able to adapt to two bereavements, but each bereavement beyond two resulted in sustained lower levels. Negative affect did not show increases because of repeated bereavements. Repeated bereavement had the strongest effect for those in young adulthood and old age. DISCUSSION AND IMPLICATIONS: Our findings demonstrate that repeated bereavement has consequences for subjective well-being and that young and older adults are most vulnerable to repeated bereavement. Our discussion focuses on the conceptual and methodological advancements of our study for the examination of major life stressors.

Indexed as

Adult life-span developmentHousehold Income and Labour Dynamics of Australia Study (HILDA)Multilevel modelingReaction and adaptation to life eventsRepeated adversity

Identifiers

PMID31879702
PMCPMC6925407
OpenAlexW2996303747

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.