Evidence map›Paper›PMID 39655202›Full record

ReviewFrontiers in psychiatry2024

Dysregulation of dopamine neurotransmission in drug addicts: implications for criminal behavior and corrective interventions.

Chao Gu, Yu-Chang Geng, Li-Na Zhu

Abstract readReview
In one paragraph

Review in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

3 authors.

Chao Gu *Law School, Yangzhou University, Yangzhou, China.
Yu-Chang Geng *Law School, Yangzhou University, Yangzhou, China.
Li-Na ZhuCollege of Physical Education, Yangzhou University, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug addiction often correlates with criminal behavior. When investigating criminal behavior among individuals grappling with drug addiction, it becomes crucial to scrutinize the influence of dopamine. Substances such as heroin, morphine, methamphetamine and other drugs can cause abnormal dopamine secretion when people are addicted to them, which promotes changes in the brain's reward circuit and emotional balance, thereby increasing susceptibility to criminal behavior. The pivotal role of dopamine within the reward pathway and its regulatory function in emotional processes exert profound influence on behavior following drug simulation. These influences are primarily manifested by three distinct attributes: a singular criminal motive and objective, lack of moral sense, and impulsive decision-making processes. Drawing upon the distinctive dopaminergic dynamics inherent in individuals afflicted by drug addiction, this study advocates for targeted corrective interventions. The preventive paradigm encompasses the cultivation of supportive community environments, the establishment of comprehensive databases, and providing legal education and protection, among other initiatives. In terms of treatment, along with judicial sanctions and protections, exercise regimens and psychotherapeutic interventions are advocated. The corrective endeavor necessitates a synergistic integration of community-based and legalistic frameworks. The objective is to furnish guiding principles for tackling criminal behavior precipitated by aberrant dopamine secretion, underpinned by a scientifically informed approach.

Indexed as

corrective measurescriminal behaviordopaminedrug addictionphysical

Identifiers

PMID39655202
PMCPMC11625758

What OpenQuestion holds

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LicenceCC BY
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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.