Does Early Emotional Distress Predict Later Child Involvement in Gambling?
Bibliographic record
Abstract
OBJECTIVE: Younger people are engaging in gambling, with some showing excessive involvement. Although a consequence of gambling could be anxiety and depression, emotional distress could be a precursor to gambling involvement. This could reflect developmental proneness toward problem behaviour. We assessed whether early emotional distress directly influences later gambling or if it operates through an indirect pathway. METHODS: Using a prospective longitudinal design, an intentional subsample of children from the 1999 kindergarten cohort of the Montreal Longitudinal Preschool Study (Quebec) from intact families were retraced in 2005 for follow-up in Grade 6. Consenting parents and children were separately interviewed. Key child variables and sources included kindergarten teacher ratings of emotional distress and impulsivity and self-reported parent and child gambling. RESULTS: Higher levels of teacher-rated emotional distress in kindergarten significantly predicted a higher propensity toward later gambling behaviour. Impulsivity, a factor often comorbidly present with emotional distress, completely explained this predictive relation above and beyond potential child- and family-related confounds, including parental gambling. CONCLUSIONS: Children with higher levels of emotional distress at kindergarten were more inclined toward child gambling behaviour in Grade 6. The influence of early emotional distress completely vanished when behaviours reflecting impulsivity were considered when predicting later child gambling behaviour. The relation between emotional distress and child gambling involvement in children was thus explained by its comorbidity with early impulsivity. This study does not rule out the possibility that emotional distress could become a correlate or consequence of excessive involvement in gambling activities at a later developmental period.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".