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Record W4387700922 · doi:10.55905/revconv.16n.10-182

Association between depressive symptoms and temporomandibular disorders among students

2023· article· en· W4387700922 on OpenAlexaff
Mariana de Oliveira Sanchez, Rejane Christine de Sousa Queiroz, Cecília Cláudia Costa Ribeiro, Sílvia Carneiro de Lucena Ferreira, Mario Brondani, Marcela Mayana Pereira Franco, Cláudia Maria Coêlho Alves

Bibliographic record

VenueContribuciones a las Ciencias Sociales · 2023
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of British Columbia
FundersFundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do MaranhãoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMedicineDepressive symptomsConfoundingDepression (economics)Signs and symptomsLogistic regressionAssociation (psychology)Internal medicineResearch Diagnostic CriteriaCross-sectional studyPhysical therapyClinical psychologyPsychiatryAnxietyPsychologyPathology

Abstract

fetched live from OpenAlex

To evaluate the association between depressive symptoms and the severity of temporomandibular disorders (TMD). This cross-sectional study (763 students) used the Fonseca Anamnestic Index and Axis II of the Research Diagnostic Criteria for TMD. Pearson’s correlation test was applied to evaluate associations of sociodemographic and clinical characteristics with TMD (p ≤ 0.05). Multinomial logistic regression was performed to adjust for confounding variables. The prevalence of signs and symptoms of TMD among the participants was 63.8% (47.6% had signs and symptoms of depression). Students with moderate depressive symptoms were 5.11 times more likely to develop severe TMD symptoms (p < 0.001). Students with severe depressive symptoms were 12.51 times more likely to develop signs and symptoms of TMD (p < 0.001). There was a significant association between depressive symptoms and signs and symptoms of TMD. The greater the severity of symptoms of depression, the higher the risk of developing signs and symptoms of TMD.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.371
Teacher spread0.335 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

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