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Record W3015278765 · doi:10.1590/1980-5918.033.ao20

Impact of temporomandibular disorders on quality of life

2020· article· en· W3015278765 on OpenAlexaboutno aff
Débora Foger, Mariela Peralta-Mamani, Paulo Sérgio da Silva Santos

Bibliographic record

VenueFisioterapia em Movimento · 2020
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)MedicineInclusion and exclusion criteriaTemporomandibular jointResearch Diagnostic CriteriaTemporomandibular disorderQuality (philosophy)Physical therapyDentistryAlternative medicinePathologyNursing

Abstract

fetched live from OpenAlex

Abstract Introduction: Temporomandibular dysfunction (TMD) may have a major impact on quality of life. Objective: Thus, this integrative review assessed the impact of TMD on quality of life. Method: An electronic and manual search was conducted to identify studies that evaluated the impact of TMD on an individual’s quality of life. After the inclusion and exclusion criteria were met, seven articles were included and evaluated according to the quality of evidence using the Newcastle-Ottawa assessment. Results: The selected studies used different instruments to diagnose temporomandibular joint disorders and measure the quality of life. Only three studies used the RDC/TMD. As for quality of life, the most used instrument was the SF-36, followed by Br-MPQ and WHOQOL-Bref. Conclusion: The findings show that there is a negative impact of temporomandibular dysfunction on quality of life, especially regarding its severity. However, further studies are needed to confirm these results.

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)0.003
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.066
GPT teacher head0.423
Teacher spread0.357 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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