Neurotic psychopathology and alexithymia among winter swimmers and controls - a prospective study
Bibliographic record
Abstract
Random samples of 25 voluntary Finnish winter swimmers (7 males, 18 females) and 11 controls (3 males, 8 females were followed prospectively during the winter season from October 1999 to May 2000 to (determine whether winter swimming is beneficial for mental well-being, as many of its practitioners claim. The Crown-Crisp Experimental Index (CCEI) was used for measuring free-floating anxiety, phobic anxiety, obsessionality, depression, somatic anxiety and hysteria, and the 20-item version of the Toronto Alexithymia Scale (TAS-20) for measuring alexithymia. Self-reported somatic and mental health and the reasons for and the frequency of winter-swimming were asked, too. As resealed by open questions, the winter swimmers reported positive effects of winter swimming. Several of the swimmers also told that they had started winter swimming to improve their physical and mental health. Their experience was that the swimming had relieved physical symptoms and made their mood more positive. However, we found no major differences between winter swimmers and controls in any CCEI or TAS variables. The structured questionnaires do not necessarily, however, reach subjective feelings and experiences.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".