MétaCan
Menu
Back to cohort
Record W6999930950

Drug addiction and emotional dysregulation in young adults

2017· article· en· W6999930950 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2017
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaYoung adultAddictionSensation seekingEmotional intelligenceLogistic regressionDrugMcNemar's test
DOInot available

Abstract

fetched live from OpenAlex

Background: It is widely acknowledged that drug addiction is characterized by emotional dysregulation. Relatively few studies in this field, however, have focused on early adulthood. Aim: The present study aims to assess emotional functioning in young adults (aged 18-24) with drug addiction who have already been admitted to residential treatment. Methods: A group of young drug addicts admitted to residential treatment (N=41) was compared with a group of young adults without Substance Use Disorder (N=27). A series of psychological self-report questionnaires on emotional functioning, Toronto Alexithymia Scale-20 item, Sensation Seeking Scale–VI, Emotional Quotient Inventory and Observer Alexithymia Scale were administered. Descriptive and nonparametric analyses (Pearson’s chi square test, Mann-Whitney U test, and McNemar test) were performed. Results: High rates of alexithymia emerged from the administration of the observer scale, in contradiction with the self-report evaluation; also, past experiences related to sensation seeking and inadequate emotional intelligence abilities were identified as characteristics of this clinical group. Conclusions: Our results suggest that drug dependence in young adults is characterized by difficulties in emotional regulation, indicating the importance of specific and new treatment methodologies

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.309
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueIRIS Research product catalog (Sapienza University of Rome)Same topicPsychosomatic Disorders and Their TreatmentsFrench-language works237,207