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Record W2045924560 · doi:10.1080/15504263.2013.778930

Relationships Among Depression, PTSD, Methamphetamine Abuse, and Psychosis

2013· article· en· W2045924560 on OpenAlexafffundabout
Tania Lecomte, Karine Paquin, Kim T. Mueser, G. William MacEwan, Elliot M. Goldner, Allen E. Thornton, Johann Brink, Donna J. Lang, Shimi Kang, Alasdair M. Barr, William G. Honer

Bibliographic record

VenueJournal of Dual Diagnosis · 2013
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityUniversité de Montréal
FundersCanadian Institutes of Health ResearchUniversity of British ColumbiaRush UniversityCentre for Addiction and Mental HealthProvincial Health Services AuthorityAstraZeneca
KeywordsDepression (economics)PsychiatryPsychosisMethamphetamineMedicineSubstance abuseOdds ratioDepressive symptomsPoison controlPsychologyClinical psychologyLogistic regressionInternal medicineAnxiety

Abstract

fetched live from OpenAlex

Objective: Research suggests several possible associations among methamphetamine abuse, psychotic symptoms, depression, and posttraumatic stress disorder (PTSD), but the exact nature and clinical significance of these associations is unclear. Individuals who abuse methamphetamine increasingly present in hospital emergency rooms with acute psychiatric symptoms. The aim of this study was to identify patterns of depressive symptoms and explore predictors of acute versus sustained depressive symptoms in individuals who abuse methamphetamine and who have had psychotic symptoms. Methods: This longitudinal study, conducted in Vancouver, British Columbia, included 295 participants with methamphetamine use disorder who were seeking psychiatric help for depressive or psychotic symptoms, assessed at baseline and monthly for 6 months. Measures included substance use (including frequency, quantity, and route of administration), family history of psychosis and depression, trauma exposure, and PTSD symptoms. Results: Trajectory analyses on depressive symptoms revealed two profiles of depression: one with more severe and sustained depressive symptoms and one with decreasing and lower levels of depressive symptoms. Group comparisons showed that those with more severe and persistent depressive symptoms had more family history of depression ( p < .05), more years of alcohol and cocaine abuse ( p < .01), more traumatic events ( p < .001), and more PTSD symptoms ( p < .001). Logistic regression suggested that the strongest predictors of belonging to the high depression group were more severe psychotic symptoms at baseline (odds ratio [OR] = 2.03, p < .001), followed by quantity of methamphetamine used in the month preceding baseline (OR = 1.13, p < .05), severity of PTSD symptoms at baseline (OR = 1.07, p < .001), and the frequency of drug injection (OR = 1.25, p < .05). Conclusions: Our results are similar to those of other studies suggesting that depression and psychosis often coexist and that the intensity of methamphetamine abuse is linked to the severity of the depressive symptoms. The individuals who took part in this study had many coexisting problems, such as PTSD symptoms, polysubstance abuse, depression, and psychosis. In fact, depression, psychosis, PTSD, and substance abuse appeared to be intertwined in their development and expression. A more comprehensive treatment program to help individuals with multiple coexisting psychiatric and substance misuse issues is needed.

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 score0.019
Threshold uncertainty score0.535

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 head0.289
Teacher spread0.248 · 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

Citations15
Published2013
Admission routes3
Has abstractyes

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