51 Association between trajectories of childhood adversity and mental health and lifestyle behaviours in adolescence in a longitudinal cohort of Canadian children.
Bibliographic record
Abstract
Abstract Background Adverse childhood experiences (ACEs) are strongly associated with adult negative health outcomes and harmful lifestyle behaviours. Most research measured ACEs retrospectively through adult recall or at one or two times across childhood, limiting our understanding of the timing, frequency and patterns of ACEs across childhood. The impact of repeated or early exposure to ACEs is well-documented, presenting a strong case for identifying the evolving patterns of ACEs exposure across childhood. Few studies, and none in Canada, have described the distribution of children across distinct groups of ACEs exposure and if belonging to such group impacts mental health and lifestyle behaviors during adolescence. Objectives This study aimed to describe the trajectories of ACEs among children from 0 to 13 years old in the province of Quebec, Canada and to examine the association between the ACEs trajectories during childhood and mental health diagnosis and lifestyle behaviours at 17 years old. Design/Methods Data from the Quebec Longitudinal Study of Child Development, which followed babies born in Quebec in 1997-1998 until 25 years old, was used. Six categories of ACEs were examined at 8 different time points between 5 months and 13 years of age: physical abuse, emotional abuse, violence against the mother, maternal substance abuse, maternal depression, and peer victimization. Each ACE category was assessed using one to three questions at each time points. A cumulative score, ranging from 0 to 6, was created for each time point. Trajectories were estimated using latent class growth analysis. Outcomes included four lifestyle behaviours (regular substance use, tobacco use, binge drinking and sedentary lifestyle) self-reported by the 17 years old adolescent and youth mental health diagnosis reported by the primary care provider. Weighted multiple logistic regression was used to assess the association with mental health and lifestyle behaviours at 17 years old. Results The analysis revealed three latent trajectories: a low, medium and high ACE group. ACE scores remained relatively stable across childhood for all three trajectories. Adolescents in the high ACE group had higher odds of engaging in regular drug use, regular smoking and adopting a sedentary lifestyle. No association was found between high ACE and mental health diagnosis or binge drinking. Conclusion A small group of children was identified as being chronically exposed to high levels of adversity. Membership to this group was associated with harmful lifestyle behaviours.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".