Parental Optimism and Perceived Control over Children’s Initiation of Tobacco, Cannabis, and Opioid Use
Bibliographic record
Abstract
Families play an important role in helping teenagers avoid using tobacco, cannabis, and opioids, but some parents may underestimate the risk of their children using those substances. This study aimed to determine parents’ perceived likelihood of their child initiating tobacco, cannabis, and opioid use, as well as the control they have in preventing their child from using those substances. We surveyed 427 parents of children aged 0–18 years old using the online Amazon Mechanical Turk platform in the spring of 2019. We measured participants’ perceived likelihood of their child initiating tobacco, cannabis, or opioid use before the age of 18 compared to other children, using a five-point Likert scale. This perceived likelihood was dichotomized between optimistic (less likely than average) and non-optimistic (average or more likely than average). Independent variables included parental tobacco use, perceived parental control, and perceived severity of the behavior. Participants with missing data and participants with children who had already initiated substance use were excluded from statistical analyses. Mean age of participants was 38.1 years (Standard Deviation 8.4); 67% were female. Level of parental optimism was 59% for cannabis, 77% for tobacco, and 82% for opioids. Perceived severity was significantly lower for cannabis use (71/100) than tobacco (90/100) and opioid use (92/100) (p < 0.001). Current smokers were less likely than never smokers to be optimistic about their child’s risk of initiating using tobacco (Adjusted Odds Ratio (AOR): 0.18 [95% Confidence Interval (CI) 0.10–0.34]) or cannabis (AOR: 0.21 [95% CI 0.12–0.38]). Parental perceived likelihood of a child initiating substance use represents an understudied and potential target for substance use prevention.
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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 | 0.006 |
| 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) | 0.002 | 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".