RELATIONSHIPS BETWEEN CHILDHOOD EXPOSURE TO VIOLENCE, POSTTRAUMATIC STRESS, RESILIENCE, AND ALCOHOL MISUSE IN MI'KMAQ ADOLESCENTS
Bibliographic record
Abstract
This research was conducted in partnership with a Nova Scotain Mi’kmaq (First Nation)\ncommunity that was interested in learning more about how exposure to violence (EV)\nmight be related to youth alcohol use. There are many consequences of childhood\nexposure to violence (EV), but two of the more notable consequences of EV are\nposttraumatic stress (PTS) symptoms and excessive or problematic alcohol misuse. Given\nthe strong relationship in the literature between each of the PTS symptom clusters and\nalcohol problems, it was hypothesized that these symptom clusters would mediate the\nrelationship between EV and alcohol misuse. Study 1 demonstrated that PTS\nhyperarousal symptoms, but none of the other PTS symptoms, fully mediated the\nrelationship between EV and alcohol misuse, even after controlling for depressive\nsymptoms, age and gender. The literature on EV also demonstrates that despite its\nnumerous potential negative consequences, some youth continue to thrive. This thriving\nin the face of hardship is called resilience. Study 2 employed a direct measure of\nresilience (Child and Youth Resilience Measure; Ungar et al, 2008) to examine which if\nany aspects of resilience can successfully buffer youth from experiencing negative mental\nhealth consequences after EV. Study 2 demonstrated that all three aspects of resilience\n(i.e., individual, family, and community) moderated the relationship between EV and\nPTS reexperiencing symptoms. More specifically, at higher levels of resilience, the\npositive relationship between EV and PTS reexperiencing symptoms was dampened.\nStudy 3 documented the collaborative-research process from beginning (i.e., research\nquestion formation) to end (i.e., implementation of action-based recommendations). It\nhighlighted how the research questions outlined in Studies 1 and 2 were relevant to both\nthe specific community in question, as well as some Aboriginal communities more\nbroadly. It also highlighted how the first author participated in a research process that is\ndescribed by the Canadian Institutes of Health Research (CIHR) as Integrated Knowledge\nTranslation (KT). And finally, it identified via qualitative and quantitative methods how\nthe research process as a whole has helped equip the community with more tools to tackle\nthe problems that its members have identified as important for study and change.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".