Parent perspectives on sports betting and its effects on children
Bibliographic record
Abstract
Abstract Background Gambling-related harm is a global challenge. Sports betting is a rapidly growing form of gambling, facilitated by access to online wagering platforms and increased advertising. Most public health initiatives target ‘problem’ gamblers, ignoring socio-cultural influences. Within this context, we examine what parents think about sports betting, the potential impacts on their children, and whether they participate in sports betting around their children. Methods Using a survey of 3,481 Australian adult sports fans with dependent children, we analyse parental attitudes to sports betting and their concerns about possible effects on children. ANOVA and regression methods are used to test for differences in attitudes to sports betting between parents who are gamblers (sports and non-sports) and non-gamblers. Results Compared to non-gambling parents, sports-betting parents are much more permissive (by up to 0.9 standard deviations) of sports betting around and by children, and less concerned (by up to 0.6 standard deviations) about any harmful effects of sports betting on children. Sports betting parents place less importance on discussing the risks of sports betting with their children, and the more often a parent bets on sports, the less confident they are about having these discussions. Parents who bet on sports are 5.8 percentage points less likely than non-gambling parents to have had such conversations. Conclusions The strong influence of parent modelling and normalisation, combined with policy initiatives that recommend parents discuss potential sports betting risks with their children, implies that having a better understanding of attitudes will facilitate improved educational and harm minimisation policy initiatives. The findings of our study are important for public health policy and should inform interventions aimed at gambling harm reduction. Targeting sports betting parents with better tailored educational campaigns is warranted. Key messages • Children of parents who bet on sports are less likely to receive messages about the risks of sports betting, in addition to being exposed to role modelling that reinforces sports betting. • Compared to non-gambling parents, those who bet on sports have more permissive attitudes towards sports betting, suggesting targeted messaging and interventions are warranted.
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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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".