The Impact of Parenting Style on Attitudes toward Masturbation: A Latent Profile Analysis
Bibliographic record
Abstract
Parents play a vital role in the development of their children's sexual attitudes and behaviors; however, little is known about the impact of parenting on masturbation attitudes. The present study aimed to explore the role of discussions with parents about attitudes toward masturbation. Additionally, latent profile analysis (LPA) was used to determine whether subgroups of exposure to distinct parenting styles exist, and if so, the extent to which they are related to the formation of masturbation attitudes. A convenience sample of 279 university students aged 18-21 completed an anonymous self-report survey. Participants who had not discussed masturbation with their parents reported significantly more negative attitudes than those who had discussed it. In general, participants who perceived their parents to be high in both rejection and control reported more negative attitudes toward masturbation than participants whose parents were lower in rejection and lower in control. The LPA revealed three parenting profiles that were differentially related to young adults' masturbation attitudes: Permissive Parenting, Typical Parenting, and Authoritarian Parenting. An exploratory analysis found that female participants endorsed fewer negative attitudes toward masturbation than their male counterparts. Bayesian statistics were used to improve the interpretation of the data, allow for more meaningful and accurate conclusions, and provide converging evidence with the null hypothesis significance testing results. Implications and limitations are discussed within the context of current masturbation and parenting style research.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".