Evidence map›Paper›PMID 29535647›Full record

ArticleFrontiers in psychiatry2018

Springtime Peaks and Christmas Troughs: A National Longitudinal Population-Based Study into Suicide Incidence Time Trends in the Netherlands.

Emma Hofstra, Iman Elfeddali, Marjan Bakker, Jacobus J de Jong, Chijs van Nieuwenhuizen, Christina M van der Feltz-Cornelis

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
–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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Risk-Taking Behavior among Suicide Attempters.Journal of clinical medicine · 2022
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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

6 authors.

Emma HofstraAcademic Department of Specialised Mental Health Care, GGz Breburg, Tilburg, Netherlands.
Iman ElfeddaliAcademic Department of Specialised Mental Health Care, GGz Breburg, Tilburg, Netherlands.
Marjan BakkerDepartment of Methodology and Statistics, Tilburg University, Tilburg, Netherlands.
Jacobus J de JongAcademic Department of Specialised Mental Health Care, GGz Breburg, Tilburg, Netherlands.
Chijs van NieuwenhuizenTranzo-Scientific Center for Care and Welfare, Tilburg University, Tilburg, Netherlands.
Christina M van der Feltz-CornelisAcademic Department of Specialised Mental Health Care, GGz Breburg, Tilburg, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTime trends are one of the most studied phenomena in suicide research; however, evidence for time trends in the Dutch population remains understudied. Insight into time trends can contribute to the development of effective suicide prevention strategies.

methodsTime trends in national daily and monthly data of 33,224 suicide events that occurred in the Netherlands from 1995 to 2015 were examined, as well as the influence of age, gender, and province, in a longitudinal population-based design with Poisson regression analyses and Bayesian change point analyses.

resultsSuicide incidence among Dutch residents increased from 2007 until 2015 by 38%. Suicide rates peak in spring, up to 8% higher than in summer (

conclusionEvidence was found for time trends in suicide incidence in the Netherlands. It is recommended to plan (mental) health care services to be available especially at high-risk moments, at spring time, and in the beginning of January. Further research is needed to explore the protective effect of Christmas in suicide incidence.

Indexed as

ageChristmasgenderNetherlandsprovinceseasonalitysuicidetime trends

Identifiers

PMID29535647
PMCPMC5834424

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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.