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Record W4415667026 · doi:10.1038/s41598-025-21580-8

The effects of psychological functioning on substance use and treatment outcomes among people with HIV

2025· article· en· W4415667026 on OpenAlexfundno aff
Lunthita Duthely, Renae D. Schmidt, Rui Duan, Sophia Gonzalez, Lisa R. Metsch, Daniel J. Feaster, Adam W. Carrico, Viviana E. Horigian

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Drug Abuse Treatment Clinical Trials NetworkNational Institute on Drug AbuseYork UniversityUniversity of Miami
KeywordsPsychological distressPsychological interventionMental healthSubstance useHuman immunodeficiency virus (HIV)Distress

Abstract

fetched live from OpenAlex

The interrelatedness of mental health status and HIV-related outcomes is well-documented. However, the long-term relationship between psychological distress and health outcomes among persons with HIV, co-diagnosed with substance use disorders (SUD), is understudied. We measured psychological distress among men and women with HIV who use drugs, using a low-burden instrument, and tested its effect, longitudinally, on HIV and substance use-related outcomes. Recently hospitalized, adult men and women co-diagnosed with HIV and SUD were surveyed for psychological distress, using the 18-item Brief Symptom Inventory (BSI-18). We tested the short-term (6 months) and long-term (12 months) effect of psychological distress on HIV-related and substance use-related outcomes. Psychological distress predicted higher engagement with SUD treatment and higher substance use, which decreased rapidly, and significantly, over time. No significant relationship was found between psychological distress and HIV viral load suppression. Using brief and easy to administer measures, early detection of psychological distress among persons with HIV and SUD, could avert negative, long-term health consequences-warranting further investigation of interventions that address mental health challenges faced by this population.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.331
Teacher spread0.307 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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