Associations of social support and alexithymia with psychological distress in Finnish young adults
Bibliographic record
Abstract
The positive influence of social support on psychological wellbeing is well documented but the research among young adults is scarce. Additionally, it is still unclear what type of social support explains the positive influence in this age group. Alexithymia has been linked to lacking social support and higher levels of psychological distress, but the underlying mechanisms are not well known. We aimed to assess the association of social support and alexithymia with psychological distress in a sample of young adults. The non-clinical sample comprised 316 young Finnish adults (mean age 23 years). Psychological distress was assessed using the 12-item General Health Questionnaire (GHQ-12), alexithymia was measured with the Toronto Alexithymia Scale (TAS-20) and social support with the Multidimensional Scale of Perceived Social Support (MSPSS). The associations were assessed using regression analyses. The TAS-20 (p = 0.002) and MSPSS (p = < 0.001) total scores were significantly associated with the GHQ-12 scores even after adjustment for sociodemographic variables. For the model with the TAS-20 and MSPSS subscales, the Difficulty Identifying Feelings subscale score of the TAS-20 scale (p < 0.001) and the Family subscale score of the MSPSS scale (p = 0.010) were significantly associated with the GHQ-12 scores. Our results show that low social support and high levels of alexithymia are associated with increased psychological distress both in females and males. Perceived social support from family explained the association between social support and psychological distress to a significant extent. Regarding alexithymia, the association with psychological distress was mainly related to difficulties identifying feelings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".