Evidence map›Paper›PMID 31199445›Full record

ArticleJAMA network open2019

Suicide Among Older Adults Living in or Transitioning to Residential Long-term Care, 2003 to 2015.

Briana Mezuk, Tomohiro M Ko, Viktoryia A Kalesnikava, David Jurgens

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
7.0field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Article
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  7. Article
  8. Article
  9. Review
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  11. Review
  12. Article
  13. Suicide in late life: A viewpoint.Preventive medicine · 2021
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Selection bias and misclassification in case-control studies conducted using the National Violent Death Reporting System.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2020
    Article
  19. Suicidal Ideation in US Nursing Homes: Association With Individual and Facility Factors.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2020
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Briana MezukInstitute for Social Research, University of Michigan, Ann Arbor.
Tomohiro M KoDepartment of Epidemiology, University of Michigan School of Public Health, Ann Arbor.
Viktoryia A KalesnikavaDepartment of Epidemiology, University of Michigan School of Public Health, Ann Arbor.
David JurgensSchool of Information, University of Michigan, Ann Arbor.
University of Michigan–Ann Arbor · US

Funding

A public health approach to understanding suicide in long-term careR21MH108989 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MEZUK, BRIANA · 2017 to 2018
$407k
NIMH NIH HHS R21 MH108989
6 · The paper itself

Abstract

Importance: Almost 25% of Medicare beneficiaries live in residential long-term care (LTC) (eg, independent or assisted living facility or nursing home). There are few reliable statistics on completed suicide in LTC, in part because of data limitations. Objectives: To estimate the number of suicides associated with residential LTC (ie, among persons in a facility, transitioning into or out of a facility, or otherwise associated with LTC) among adults 55 and older and, secondarily, to identify whether machine learning tools could improve the quality of suicide surveillance data. Design, Setting, and Participants: Cross-sectional epidemiologic study (conducted in 2018) of restricted-access data from the National Violent Death Reporting System (NVDRS) (2003-2015) using restricted-access case narratives from suicides and undetermined deaths among adults 55 years and older in 27 states. Participants were all suicides and undetermined deaths (N = 47 759) among persons 55 years and older. Exposure: Long-term care cited in the coroner/medical examiner case narrative, whether as a reason for self-harm or the injury location, identified using machine learning natural language processing (NLP) algorithms plus manual review of texts. Main Outcomes and Measures: Number and characteristics (eg, demographics, health history, and means of injury) of suicides associated with LTC. The κ statistic was used to estimate the reliability of the existing NVDRS injury location codes relative to cases identified by the algorithm. Results: Among 47 759 persons 55 years and older (median age, 64 years; 77.6% male; 90.0% non-Hispanic white), this study identified 1037 suicide deaths associated with LTC, including 428 among older adults living in LTC, 449 among older adults transitioning to LTC, and 160 otherwise associated with LTC. In contrast, there were only 263 cases coded with the existing NVDRS location code "supervised residential facility," which had poor agreement with cases that the algorithm identified as occurring in LTC (κ statistic, 0.30; 95% CI, 0.26-0.35). Conclusions and Relevance: Over a 13-year period, approximately 2.2% of suicides among adults 55 years and older were associated with LTC in some manner. Clinicians, administrators, and policy makers should consider ways to promote the mental health and well-being of older adults experiencing functioning limitations and their families. Natural language processing may be a useful way to improve abstraction of variables in the NVDRS.

Indexed as

AgedAged, 80 and overCross-Sectional StudiesFemaleHumansLong-Term CareMaleMedicareMiddle AgedNursing HomesPopulation SurveillanceQuality of LifeSuicideUnited States

Identifiers

PMID31199445
PMCPMC6575144
OpenAlexW2950129493

What OpenQuestion holds

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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.