On the Relationship Between Hearing-Impaired College Students’ Self Consistency and Congruence,Alexithymia and Mental Health
Bibliographic record
Abstract
This article aims to explore the characteristics of college students’ alexithymia,self consistency and congruence,and mental health,as well as their correlations,by using the 20-item version of the Toronto Alexithymia Scale(TAS-20),the Self Consistency and Congruence Scale(SCCS),and the General Mental Health Questionnaire(GMHQ-12) to test 168 hearing-impaired college students from two universities,and to compare these students with 251 normal college students.The results show the following: The hearing-impaired college students show a significantly lower level of mental health and self consistency and congruence,as well as a higher level of alexithymia,than the normal college students;the two types of college students show a significant correlation between their alexithymia,self consistency and congruence,and mental health;for the normal college students,self consistency and congruence serves as a partial mediator between alexithymia and mental health,whereas for the hearing-impaired college students,it is a full mediator.In conclusion,it is necessary to emphasize the role of self consistency and congruence in hearing-impaired college students’ mental health education,as well as their particularity.
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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 | 0.000 |
| 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".