Understanding pathways between PTSD, homelessness, and substance use among adolescents.
Bibliographic record
Abstract
= 15.6; 74% male) completed baseline, 3-, 6-, and 12-month assessments. Autoregressive latent trajectory with structured residual (ALT-SR) models were used to examine within- and between-person relationships. We found continued support for prior work at the between-person level of analysis. At the within-person level, during the treatment phase, PTSD emerged as a key mechanism predicting both return to use and increased days of homelessness posttreatment. Further, greater substance use at treatment completion was associated with greater PTSD symptoms and homelessness, prospectively. The current study extends the previous work to consider individual level processes in conjunction with overarching event level predictors of homelessness. We found that PTSD symptomology is a driving factor that influences, both directly and indirectly, experiences of homelessness posttreatment. Interventions may wish to incorporate trauma informed approaches for youth entering treatment as this may mitigate long-term experiences of homelessness and return to substance use. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".