Research on the Influencing Factors and Cultivation of Adolescents' Sense of Meaning in Life from the Perspective of Positive Psychology
Bibliographic record
Abstract
Currently, the mental health problems of adolescents are becoming increasingly serious, among which depression and suicide are closely related to the lack of a sense of meaning in life. From the perspective of positive psychology, the sense of meaning in life, as an important positive psychological resource, can help individuals cope with crises and setbacks, enhance psychological resilience, and promote physical and mental health. Based on Steger and Wong's theoretical framework, the study explored the positive factors affecting adolescents' sense of meaning in life, including positive emotions, positive personality traits (extraversion, appropriateness), and positive social organization systems (e.g., social connections, prosocial behaviors, and family upbringing styles). Based on these findings, this paper proposes a systematic cultivation strategy that integrates the construction of a multifaceted education system for positive emotions and meaning exploration, optimizes family upbringing to strengthen the sense of belonging and autonomy, expands opportunities for prosocial behaviors and social connections, and fosters positive traits and self-regulation abilities. The aim is to provide both theoretical and practical guidance on adolescents' mental health education and to contribute to the enhancement and comprehensive development of their sense of meaning in life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".