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Record W4286229596 · doi:10.1111/add.16001

Emotion regulation in substance use disorders: a systematic review and meta‐analysis

2022· review· en· W4286229596 on OpenAlexafffund
Jordan Stellern, Ke Bin Xiao, Erin Grennell, Marcos Sanches, Joshua L. Gowin, Matthew E. Sloan

Bibliographic record

VenueAddiction · 2022
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsThe Scarborough HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersUniversity of Colorado School of Medicine, Anschutz Medical CampusCanadian Institutes of Health ResearchUniversity of TorontoOntario Ministry of Health and Long-Term Care
KeywordsMeta-analysisPsycINFOClinical psychologyStrictly standardized mean differencePsychologyPsychopathologyCognitive reappraisalPsychiatryMEDLINEMedicineInternal medicineCognition

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: The ability to regulate emotions effectively has been associated with resilience to psychopathology. Individuals with substance use disorders (SUDs) have been shown to have higher levels of negative emotionality, with some evidence suggesting impairment in emotion regulation compared with individuals without SUDs. However, no previous attempt has been made to systematically review the literature to assess the magnitude of this difference. We aimed to assess the association between SUD diagnosis and emotion regulation as measured by the Difficulties in Emotion Regulation Scale (DERS) and Emotion Regulation Questionnaire (ERQ) through a systematic review and meta-analysis of existing findings. METHODS: The systematic review was conducted using PubMed, PsycINFO and Embase. We examined cross-sectional studies that compared a SUD group with a control group and measured emotion regulation using the DERS or the ERQ. The primary analysis focused on papers using the DERS, as this was the predominant instrument in the literature. RESULTS: Twenty-two studies met our primary analysis criteria, representing 1936 individuals with a SUD and 1567 controls. Individuals with SUDs relative to controls had significantly greater DERS scores, with a mean difference of 21.44 [95% confidence interval (CI) = 16.49-26.40, P < 0.001] and Hedges' g = 1.05 (95% CI = 0.86-1.24, P < 0.001). The difference was robust, remaining significant after removing outliers and studies with high risk of bias. Individuals with SUDs demonstrated poorer emotion regulation on each subscale of the DERS, with the largest deficits in the Strategies and Impulse subscales. The ERQ analysis revealed greater use of expressive suppression in those with SUDs relative to controls (Hedges' g = 0.76, 95% CI = 0.25-1.28, P = 0.004). CONCLUSIONS: People with substance use disorders appear to have greater difficulties in emotion regulation than people without substance use disorders.

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)0.012
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.028
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.332
Teacher spread0.242 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations315
Published2022
Admission routes2
Has abstractyes

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