Risk Factors for Developing Anxiety in Inuit Adolescents from Nunavik
Bibliographic record
Abstract
Background: Anxiety among Inuit adolescents in the Arctic has not previously been studied empirically, although the evidence of major anxiety-related problems in this community. In addition to describe anxiety markers, we examined their relationships with diverse developmental risk factors including exposure to environmental chemicals, a specific subject of concerns in Nunavik.Methods: Anxiety was assessed in 89 Inuit participants (Mean age=18.4y; Range=16.2 to 21.9y) enrolled in the longitudinal Nunavik Child Development Study. They completed the Screen for Child Anxiety Related Emotional Disorders (SCARED) and the State-Trait Anxiety Inventory (STAI) assessing situational (State) and general (Trait) anxiety levels. Potential risk factors of anxiety documented through follow-ups were examined at birth, at 11 years of age and at the time of assessment, including blood levels of chemicals (Hg, lead, PCBs), nutrients and vitamins, as well as age, sex, IQ, drug/alcohol, bullying, family violence, food insecurity, crowding and SES.Results: Anxiety scores on both questionnaires were high, particularly for the SCARED, which mean score was above the clinical threshold. Multiple regression results show that significant risk predictors of the SCARED scores were exposure to Hg during childhood (β=.25, p=.02) and adolescence (β=.27, p=.004), food insecurity (β=.27, p=.004), bullying history (β=.21, p=.03) and female status (β=.26, p=.01). For the STAI, the only significant predictor was IQ (β= -.27, p=.02) on Trait, whereas concentration of cord blood Hg (β=.25, p=.03), home crowding during childhood (β=.34, p=.002), adolescence (β=.23, p=.02), food insecurity (β=.22, p=.03), vitamin E (β=-.25, p=.02) and selenium (β=.21, p=.04) were found to be the significant predictors of anxiety on State.Conclusions: Our findings show that Inuit adolescents are at risk for anxiety via multiple contributing factors, particularly chronic exposure to Hg, food insecurity and female status.
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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 | 0.000 |
| 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) | 0.002 | 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".