Influence of Alexithymia on Somatic Complaints among Japanese Adolescents: A survey research
Bibliographic record
Abstract
Abstract Background The purpose of this study is to examine alexithymic tendencies in Japanese adolescents (aged 12–20) and their effects on somatic complaints. Methods Participants were Japanese adolescents (n = 2,759). Alexithymic tendencies were assessed by the Alexithymia Scale for Adolescents (ASA), and somatic complaints by the Somatic Complaint List (SCL). Results The following results were obtained. 1) ASA total scores remained at a high level from early to late adolescence. 2) Among the ASA subfactors, difficulty identifying feelings (DIF) and difficulty describing feelings (DDF), increased during adolescence, whereas externally oriented thinking (EOT) decreased; as a result, the ASA total scores remained high. 3) DIF significantly affected somatic complaints among adolescents irrespective of their academic year and gender. 4) DDF only had an effect of increasing somatic complaints in junior high and high school-aged male participants, and this effect disappeared as respondents’ age grew and they were university students. This shows that the effect of alexithymic tendencies on somatic complaints changed with age. Conclusion Compared to the results of previous studies, the results of this study showed that alexithymic tendencies among Japanese adolescents are consistently high. The study further revealed that the increasing somatic complaints were consistently influenced by DIF.
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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 | 0.000 |
| 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) | 0.001 | 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".