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Substance Use Disorder, Alexithymia, and Personality Disorders, What is the Link? Pilot African Study

2023· article· en· W4385581846 on OpenAlexaboutno aff
Ferdaouss Qassimi, Saı̈d Boujraf, Adam Khlifi, Ghizlane Lamgari, Zineb El Bourachedy, Aarab Chadya, Rachid Aalouane, Amine Bout

Bibliographic record

VenueOBM Neurobiology · 2023
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPersonalityPersonality disordersPsychologyClinical psychologyToronto Alexithymia ScaleAddictionPsychiatrySubstance abuse

Abstract

fetched live from OpenAlex

Alexithymia and personality disorders are common in substance use (SUD) patients. This association remains understudied and is considered to hurt the course and management of substance use disorder patients. To determine the prevalence of personality disorders (PD) and alexithymia in addiction care patients. Besides, we targeted investigating a possible link between alexithymia, different personality disorders and clinical aspects of substance use disorder including severity. This cross-sectional study was conducted in the Addictology Center of the university hospital of Fez. We recruited 54 patients with a confirmed substance use disorder according to the DSM 5 criteria. We used the psychometric scales of alexithymia (TAS-20) and the personality assessment scale (PDQ-4+). The average age of our sample was 27.07 ± 8.22. The percentage of poly-consumers of psychoactive substances was around 93%. The alexithymia patients constituted 48% of the sample. We found a significant association between alexithymia and the severity of SUD p-value of 0.033. Alexithymia appeared to be significantly associated with "Cluster A" of personality disorders p-value of 0.013 and more specifically with paranoid personality disorder p-value of 0.022. The mean PDQ-4+ score was significantly higher in the alexithymia group of patients (TAS-20 score ≥62) p-value of 0.047. 89% reported at least one specific personality disorder. Our results showed a significant association between the presence of a specific personality disorder and the existence of a severe substance use disorder p-value of 0.01. We also found that "Cluster A" of personality disorder diagnoses are significantly frequent within the severe subgroup of SUD p-value of 0.042. Our study suggested an overrepresentation of alexithymia and personality disorders in patients followed for SUD. It showed a direct link between alexithymia and personality disorder on the one hand, and the severity of the substance use disorder on the other. Extensive studies are required to fully elucidate the weight of alexithymia in SUD and PD. Such investigations would improve the therapeutical approach and the outcome.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.637

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 head0.041
GPT teacher head0.288
Teacher spread0.247 · 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 designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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