Adolescents’ reports of chaos within the family home environment: Investigating associations with lifestyle behaviours and obesity
Bibliographic record
Abstract
OBJECTIVE: Disorganised and chaotic home environments may hinder the adoption of healthy lifestyle behaviours and contribute to excessive weight gain among adolescents. We examined whether self-reported level of chaos within the family home environment is associated with lifestyle behaviours and obesity in adolescent girls and boys. METHODS: Cross-sectional data from the 3rd wave of the Québec Adipose and Lifestyle Investigation in Youth (QUALITY) study were analyzed. The sample consisted of n = 377 White adolescents with a history of parental obesity. Home environment chaos was measured using the Confusion, Hubbub, and Order Scale (CHAOS) analyzed both continuously and dichotomized as high vs. low chaos. Body Mass Index z-scores (zBMI) were computed using WHO standards from measured weight and height. Physical activity (7-day accelerometry), vegetable and fruit intake (three 24-hour diet recalls), and leisure screen time and sleep duration (questionnaire) were assessed. Sex-specific linear regression models were used to estimate associations between level of family home environment chaos, lifestyle behaviours and zBMI. RESULTS: The overall level of chaos was low in our study sample, with higher reported levels among girls compared to boys. Among girls, high (vs low) chaos was associated with shorter sleep duration (hours/day) (B = - 0.44, 95% CI: -0.75, -0.14). No associations were observed for other lifestyle behaviours or for zBMI. CONCLUSION: In this sample of adolescents with a parental history of obesity, higher household chaos was not associated with obesity or lifestyle behaviours, except for sleep duration among girls. Replication of findings in more diverse samples is indicated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".