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Record W2970854645 · doi:10.3389/fpsyg.2019.02106

Mindfulness and Suicide Risk in Undergraduates: Exploring the Mediating Effect of Alexithymia

2019· article· en· W2970854645 on OpenAlexaboutno aff
Yuan Fang, Baoer Zeng, Peiyi Chen, Yiling Mai, Shan Teng, Minting Zhang, Jingbo Zhao, Xueling Yang, Jiubo Zhao

Bibliographic record

VenueFrontiers in Psychology · 2019
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
FundersMinistry of Education, India
KeywordsAlexithymiaMindfulnessPsychologyToronto Alexithymia ScaleClinical psychologyFeelingIntervention (counseling)PsychiatrySocial psychology

Abstract

fetched live from OpenAlex

The present study was designed to examine the relationship between dispositional mindfulness and suicide risk in undergraduates, and it further explored the potential mediating role of alexithymia in this relationship. A total of 2,633 undergraduates completed the Mindful Attention Awareness Scale (MAAS), the Suicidal Behaviors Questionnaire - Revised (SBQ-R), and the 20-item Toronto Alexithymia Scale (TAS-20). The results indicate that mindfulness and suicide risk were negatively correlated, and alexithymia partially mediated the relationship between mindfulness and suicide risk only in the female undergraduates. Moreover, only the difficulty in identifying feelings (DIF) factor of alexithymia mediated the relationship between mindfulness and suicide risk in the female undergraduates. These findings contribute to the potential mechanism that explains the relationship between mindfulness and suicide risk. Furthermore, it is possible to implement mindfulness in the suicide intervention of alexithymic individuals.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2019
Admission routes1
Has abstractyes

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