Motivations for Social Withdrawal, Mental Health, and Well-Being in Emerging Adulthood: A Person-Oriented Approach
Bibliographic record
Abstract
Emerging adults seek solitude because of different underlying motivational and emotional processes. The current short-term longitudinal study aimed to: (1) identify subgroups of socially withdrawn emerging adults characterized by different motivations for solitude (shyness, unsociability, social avoidance) and affect (positive, negative); and (2) compare these subgroups in terms of indices of internalizing difficulties and life-satisfaction. Participants were N = 348 university students (Mage = 21.85 years, SD = 3.84) from Italy, who completed online questionnaires at two-time points separated by three months. Results from a latent profile analysis (LPA) suggested three distinct subgroups characterized by different social withdrawal motivations (i.e., shy, unsociable, and socially avoidant), as well as a non-withdrawn subgroup (characterized by low social withdrawal motivations, low negative affect, and high positive affect). Among the results, the socially avoidant subgroup reported the highest levels of social anxiety, whereas the avoidant and shy subgroups reported the highest loneliness and lowest life satisfaction. The unsociable subgroup appeared to be the most well-adjusted subgroup of socially withdrawn emerging adults and reported similar levels of life satisfaction as the non-withdrawn subgroup. Our findings confirmed the heterogeneity of emerging adults’ experiences of solitude, with different motivations for social withdrawal appearing to confer a differential risk for maladjustment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".