Adolescents’ perceived mattering to parents and friends: Testing cross-lagged associations with psychosocial well-being
Bibliographic record
Abstract
Mattering is the tendency to view the self as significant to other people. Theoretically, mattering has been proposed to promote psychosocial well-being. Although prior research has found positive associations between mattering to parents and psychosocial well-being among adolescents, extant studies have not clarified whether perceptions of mattering predict psychosocial well-being or the other way around. Thus, the direction of the association needs verification. The purpose of this study was to examine the direction of associations between adolescents’ mattering to parents and friends and adolescents’ depressive symptoms and problem behaviors using cross-lag models. A two-wave annual survey assessed mattering to family and friends, depressive symptoms, and problem behaviors of students in grades 6 to 9 ( N = 164; 56.1% girls) in a school district in western Canada (Time 1 age range = 11 to 15 years; mean age = 12.23; standard deviation = 1.07). Structural equation modeling was used to assess concurrent, auto-regressive, and cross-lagged associations between mattering and psychosocial well-being. Mattering to mother, father, and friends was assessed in separate models. Significant lags were found only between mattering to friends and depressive symptoms and problem behaviors, with positive associations suggesting a form of socialization through mattering. With one exception, mattering to parents was not directly associated with psychosocial well-being over time. However, gender moderated the association between mattering to mother (Time 1), depressive symptoms (Time 2), problem behaviors (Time 1), and mattering to mother (Time 2). Taken together, these results suggest that mattering may not be as strongly protective of adolescent well-being as previously suggested.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".