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Record W2369021207

On the Relationship Between Hearing-Impaired College Students’ Self Consistency and Congruence,Alexithymia and Mental Health

2013· article· en· W2369021207 on OpenAlexaboutno aff
Huoliang Gong

Bibliographic record

VenueZhongguo teshu jiaoyu · 2013
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyMental healthCongruence (geometry)Toronto Alexithymia ScaleClinical psychologyInternal consistencyHearing impairedConsistency (knowledge bases)Developmental psychologySocial psychologyPsychiatryPsychometricsAudiologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.302
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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