Psychosexual health’s impact on non-suicidal self-injury of college students
Bibliographic record
Abstract
To explore the correlation between Psychosexual Health development (APDS) and non-suicidal self-injury behaviors (NSSI) in adolescence, and investigate the mediating effects by adult attachment (AAS) and social supports (SSRS) between them. This study employs a missed design with quantitative pretests and tracing post-tests involving 1193 college students majoring in preschool and primary education. The participants are first-year (freshmen) and second-year students (sophmore), primarily women, at a higher vocational college in Shaanxi, utilizing APDS, AAS, SSRS and the NSSI questionnaires to evaluate the positive proportion of NSSI behaviors and obtained the ratio of 12.53% among normal individuals, and using SPSS Pearson relevant to analyse correlation of the variables and to test the mediating effect through Amos SEM equation model and Bootstrap method. Confirmed Psychosexual Health impacts on NSSI behaviors significantly, and the Chained mediating effect of AAS and SSRS between them. APDS can significantly negatively predict NSSI under the mediating effects of AAS and SSRS respectively, and insignificantly effect with the chained mediating effect of AAS and SSRS. Improving individual psychosexual health levels is conducive to developing secure adult attachment and promoting good social supports, with certain enlightening significance for decreasing and preventing NSSI behaviors among adolescents. We discussed future research directions based on our results, and revealed important significance timely intervening those with personality disorders and NSSI behaviors through carrying out psychosexual health education to cultivate their secure adult attachment and good social supports. In the meanwhile, to support individuals with psychological growth and group intervention on NSSI behaviors during adolescence, and put forward schools more effective educational guidance and methods of psychological health, by promoting their psychosexual health to enhance individual personality development and mental health levels. With anticipation to provide more scientific theoretical evidence and practical strategies for early educational guidance and group prevention measures in favor of implementing psychosexual health education to prevent NSSI behaviors timely among children and adolescents on campus.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".