Evidence map›Paper›PMID 27882208›Full record

ReviewAddiction & health2016

Maternal Separation and the Risk of Drug Abuse in Later Life.

Fatemeh Delavari, Vahid Sheibani, Saeed Esmaeili-Mahani, Nouzar Nakhaee

Abstract readReview
In one paragraph

Review in Addiction & health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. How childhood adversity affects components of decision making.Neuroscience and biobehavioral reviews · 2025
    Pooled it
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  5. Early Life Stress Impairs VTA Coordination of BLA Network and Behavioral States.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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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

4 authors.

Fatemeh DelavariPhD Candidate, Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Vahid SheibaniProfessor, Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Saeed Esmaeili-MahaniAssociate Professor, Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran.
Nouzar NakhaeeProfessor, Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maternal separation (MS) is defined as the termination of the continuity of mother-child relationship after the relationship is established. Although MS and maternal deprivation are different in terms of their definitions, these two terms are usually used interchangeably. This review aims to investigate the effect of MS on drug intake in adulthood. It has been proved that animal models are helpful in evaluating the effects of MS on drug intake risk in adulthood. There are relatively acceptable studies in this field on some drugs such as morphine, ethanol, and cocaine. However, very few animal studies, or even no animal study, have been conducted on some other drugs. The majority of these studies have considered MS as a risk factor for drug intake in adulthood. Different mechanisms are proposed for this phenomenon. Brain reward pathways are one of the main exploratory pathways of this process. Despite the importance of the issue, no human study with a specific concentration on investigating the relationship between MS and drug abuse in later life was found. Causal studies are warranted on humans to investigate the effect of MS on drug intake in later life.

Indexed as

AddictionEarly life stressMaternal deprivation

Identifiers

PMID27882208
PMCPMC5115644

What OpenQuestion holds

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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.