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Record W4399404691 · doi:10.1051/shsconf/202419303010

A General Overview on How Brain Mechanisms, Environmental Factors, and Personality Traits Affect the Development of Drug Addiction and Substance Abuse

2024· article· en· W4399404691 on OpenAlexaff
Meizhu Jiang

Bibliographic record

VenueSHS Web of Conferences · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAffect (linguistics)AddictionPsychologySubstance abuseBig Five personality traitsPersonalitySubstance useDrugClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

It is currently recognized that drug addiction is a brain disease brought on by substance usage, which modifies the biochemistry and structure of the brain and has multifaceted behavioral repercussions on those who abuse drugs. This article aims to discuss the biological, environmental, and personality factors that contribute to drug addiction by overviewing the brain mechanisms behind initial motivation and subsequent reinforcement of persistent drug use, as well as how environmental variables and personal traits affect individuals experimenting with drugs. Early drug addiction can be attributed to an innate reward circuit called the mesolimbic pathway. While subsequence craving is sustained by synaptic plasticity in the mesocorticolimbic dopamine system. Trauma histories, social norms and social networks, and early drug exposure due to family members' experiences with drug use can all serve as triggers for drug use. However, under specific conditions, some of these variables can also have the reverse effect, averting substance usage in the first place. Studies have found a correlation between drug abuse and personality disorders, and there are shared characteristics in the personalities of addicts, it is still impractical to say for sure whether a particular personality disorder is a root cause of drug addiction, and more research needs to be done.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.275
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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