Association between posttraumatic stress disorder and nonfatal drug overdose.
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.
Bibliographic record
Abstract
OBJECTIVE: North America is in the midst of a growing drug overdose crisis. While prescription opioid misuse and synthetic opioids such as fentanyl have been implicated in the overdose crisis, less attention has been given to the role that posttraumatic stress disorder (PTSD) may play in this crisis. As such, this study sought to examine the relationship between PTSD and risk of nonfatal overdose among people who use drugs (PWUD). METHOD: Data were derived from three prospective cohorts of PWUD in Vancouver, Canada. For each participant, PTSD was assessed using the PTSD Checklist for the DSM-5. Multivariate logistic regression analysis was used to estimate the relationship between PTSD and nonfatal overdose, adjusting for potential confounders. RESULTS: Between 2016 and 2018 among 1,059 PWUD, including 363 (34%) nonmale participants, 171 (16%) experienced a nonfatal drug overdose in the past 6 months, and 414 (39%) met criteria for a provisional PTSD diagnosis. In multivariate analysis, PTSD (adjusted odds ratio = 1.98, 95% confidence interval [1.4, 2.79]) remained independently associated with nonfatal overdose after adjustment for a range of confounders. CONCLUSIONS: Among participants in these community-recruited cohorts of PWUD, having a provisional PTSD diagnosis nearly doubled the risk of nonfatal overdose. The findings from this study support the need to incorporate a trauma-informed approach within the current overdose prevention framework. Education and training relating to trauma and PTSD should be prioritized for health care professionals who work with and treat PWUD. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it