Evidence map›Paper›PMID 34803791›Full record

ReviewFrontiers in psychology2021

Choosing Death Over Survival: A Need to Identify Evolutionary Mechanisms Underlying Human Suicide.

Diya Chatterjee, Rishabh Rai

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in psychology, 2021. 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
1.0field-weighted citation impact, top 21% 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, 9 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

2 authors at 1 institution in 1 country.

Diya ChatterjeeDepartment of Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, India.
Rishabh RaiDepartment of Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, India.
Indian Institute of Technology Kharagpur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The act of killing self contradicts the central purpose of human evolution, that is, survival and propagation of one's genetic material. Yet, it continues to be one of the leading causes of human death. A handful of theories in the realm of evolutionary psychology have attempted to explain human suicide. The current article analyses the major components of certain prominent viewpoints, namely, Inclusive fitness, Bargaining model, Pain-Brain model, Psychological aposematism, and few other perspectives. The article argues that relatively more weightage has been given to understanding ultimate (the "why") rather than proximate (the "how") functionality of suicidal acts. Evolutionary theorists have consistently pointed out that to comprehensively understand a trait or behavior, one needs to delineate not only how it supports survival but also the evolution of the mechanisms underlying the trait or behavior. Existing theories on suicide have primarily focused on its fitness benefits on surviving kin instead of providing evolutionary explanations of the more complex mechanisms leading up to such self-destructive motivations. Thus, the current paper attempts to highlight this gap in theorizing while suggesting probable proximate explanations of suicide which stresses the need to diffuse attention paid to fitness consequences of the act alone. We speculate that such explorations are needed in order to build a robust and comprehensive evolutionary theory of human suicide.

Indexed as

evolutionary psychologyproximate explanationssuicidesuicidologyultimate explanations

Identifiers

PMID34803791
PMCPMC8595259
OpenAlexW3208871126

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.