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Record W3194226598 · doi:10.1111/ajad.13209

Cognitive improvement among abstinent methamphetamine users: A 2‐year prospective longitudinal study

2021· article· en· W3194226598 on OpenAlex
Tong‐Yu Wang, Tengteng Fan, Julia Lappin, Xiaodong Li, Yimiao Zhao, Ping Wu, Jie Shi, Yanping Bao, Lin Lü

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAmerican Journal on Addictions · 2021
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsGeeAbstinenceGeneralized estimating equationLongitudinal studyRepeated measures designConfidence intervalProspective cohort studyCognitionMontreal Cognitive AssessmentPsychologyDemographyMedicineInternal medicinePsychiatryCognitive impairmentStatistics

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The adverse impact of chronic methamphetamine (MA) use on cognitive function has been described in previous studies, but limited evidence is available for abstinent users from prospective longitudinal studies. The aim of the present study was to assess cognitive function of varying abstinent duration. METHODS: This prospective longitudinal study was conducted with baseline and four follow-up interviews every 6 months over 2 years in 358 MA users in Guangdong province, China. The Montreal Cognitive Assessment (MoCA) was used to measure cognitive function. Generalized estimating equation (GEE) analysis was used to examine within-subjects relationships between abstinence and cognitive consequences over time. RESULTS: The repeated measure analysis of variance showed significant differences in the total MoCA score and all subscale scores (except Orientation) in the 24 months follow-up. The GEE model showed that abstinence from MA in the past 6 months predicted an increase of 0.66 (95% confidence interval [CI] = 0.29 to 1.05, p = .002) in MoCA score changes compared with the nonabstinence MA users. Abstinence in the past 12, 18, and 24 months predicted an increase in MoCA total score changes of 1.25 (95% CI = -0.23 to 2.74), 2.15 (95% CI = -0.79 to 5.09), and 5.28 (95% CI = -2.01 to 12.58), respectively, but none of these was statistically significant. DISCUSSION AND CONCLUSIONS: Cognitive function was potentially improved following 6 months of MA abstinence. SCIENTIFIC SIGNIFICANCE: This study extends prior research by long-term follow-up in big sample MA abstinence users. Findings from study support the need for a comprehensive measure to decrease MA use and promote the recovery of cognitive impairment.

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.

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 score0.047
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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