Evaluating Links between Social Withdrawal Motivations and Indices of Psychosocial Adjustment among Norwegian Emerging Adults
Bibliographic record
Abstract
Social withdrawal is the behavioral tendency to remove oneself from social situations – a tendency that often contributes to reductions in individuals’ mental health. The current study evaluated the links between different motivations for social withdrawal (shyness, unsociability, social avoidance) and indices of psychosocial adjustment in a Norwegian sample of emerging adults. Participants were N = 194 Norwegian university students who completed self-report measures of life satisfaction, loneliness, and depressive symptoms, as well as withdrawal motivations. Among the results, a newly translated version of the Social Preference Scale-Revised (SPS-R) was validated for use in Norway. Findings showed that shyness was uniquely and positively associated with loneliness and depressive symptoms, as well as lower life satisfaction, whereas social avoidance was positively associated with depressive symptoms. Unsociability was uniquely linked to lower levels of loneliness and depressive symptoms. Findings provide novel information about the psychosocial correlates of social withdrawal motivations during emerging adulthood in the under-explored cultural context of Norway. Understanding nuances in the correlates of different motivations may aid in the development of culturally and developmentally sensitive interventions.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".