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Record W4416286752 · doi:10.1007/s44202-025-00499-1

Relationship between non-suicidal self-injury and thyroid hormone levels in female adolescents with depression and bipolar disorder

2025· article· en· W4416286752 on OpenAlexaboutno aff
Ruiying Wang, Huizheng Hu, Binyan Wu

Bibliographic record

VenueDiscover Psychology · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
FundersShaanxi Science and Technology Association
KeywordsDepression (economics)ThyroidHormoneThyroid functionBipolar disorderThyroid hormones

Abstract

fetched live from OpenAlex

Abstract Objective To investigate the relationship between non-suicidal self-injury (NSSI) and thyroid hormone levels in female adolescents with mental disorders and to provide a theoretical basis for psychiatrists to identify and intervene in NSSI. Methods In this study, we enrolled 289 female adolescents diagnosed with NSSI (NSSI group) according to the Diagnostic and Statistical Manual of Mental Disorders (5th edition), alongside a control group of 285 healthy female adolescents. The clinical data of the study subjects were collected and the levels of thyroid hormones were determined. The thyroid function of the subjects was evaluated according to the levels of FT3, FT4, T4, T3 and TSH, and the differences between the NSSI group and the control group were analyzed. The Ottawa Self-Injury Inventory was used to evaluate the self-injury status of the study subjects, and the HAMD-17 was used to assess the degree of clinical depression. Results In this study, the TSH level in the NSSI group was higher than that in the control group (P < 0.01), and the T3, T4, and FT3 levels were lower than those in the control group (P < 0.05). The HAMD-17 score in the NSSI group was higher than that in the control group (P < 0.01), and the score on the self-injury questionnaire in the NSSI group was higher than that in the control group (P < 0.01). Conclusion NSSI in female adolescents with depression or bipolar disorder may be associated with low thyroid hormone levels.

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 score0.014
Threshold uncertainty score0.919

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 head0.026
GPT teacher head0.342
Teacher spread0.315 · 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
Published2025
Admission routes1
Has abstractyes

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