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Record W4414489460 · doi:10.1111/joor.70064

Cognitive Domain Impairments in Chronic Painful Temporomandibular Disorders: Associations With Pain Intensity, Hypervigilance and Catastrophising: A Cross‐Sectional Analysis

2025· article· en· W4414489460 on OpenAlexaboutno aff
Luiza Guilherme Antunes, César Bataglion, Maria Helena Fernandes, Melissa de Oliveira Melchior, Laís Valencise Magri

Bibliographic record

VenueJournal of Oral Rehabilitation · 2025
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsnot available
FundersUniversidade de São PauloPro-Reitoria de Pesquisa, Universidade de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsHypervigilanceCognitionChronic painPain catastrophizingExecutive functionsPerspective (graphical)

Abstract

fetched live from OpenAlex

BACKGROUND: This study aimed to investigate the associations between pain intensity, hypervigilance and catastrophising with specific cognitive domains in patients with chronic painful temporomandibular disorders (TMD), focusing on identifying cognitive deficit domains. METHODS: A cross-sectional study was conducted with a sample of 80 participants (41 chronic painful, 39 controls). TMD was diagnosed according to the Diagnostic Criteria for TMD. Cognitive performance was assessed using the Montreal Cognitive Assessment (MOCA), while pain-related factors were evaluated using the Pain Vigilance Awareness Questionnaire, the Pain Catastrophizing Scale and Pain Intensity. Statistical analyses included independent t-tests to compare group means, followed by multiple regression analysis to examine the associations between cognitive domains and pain-related variables. RESULTS: Compared to controls, TMD patients showed significantly lower MOCA scores in visuospatial/executive functioning (mean difference = 3.3, p = 0.03), attention (mean difference = -2.5, p < 0.002) and memory (mean difference = -1.8, p = 0.001). Higher pain intensity was significantly associated with visuospatial/executive deficits (β = -0.34, 95% CI: -0.50 to -0.18; p < 0.001), while catastrophising was strongly linked to reduced attention (β = -0.05, 95% CI: -0.08 to -0.02; p < 0.001). Hypervigilance showed a significant negative correlation with memory performance (β = -0.04, p = 0.003). CONCLUSIONS: Our study reveals that chronic painful TMD is associated with some cognitive impairments, particularly in visuospatial/executive functioning, attention and memory. Elevated pain intensity and catastrophising emerged as the most impactful factors, closely linked to deficits in these cognitive domains. These findings identify executive control, attention and memory as the cognitive domains most vulnerable to the influence of chronic pain in TMD patients. SIGNIFICANCE: This study provides novel insights into the cognitive impairments associated with chronic painful TMD. By demonstrating strong associations between pain intensity, hypervigilance and catastrophising with deficits in executive function, attention and memory, our findings highlight the cognitive burden of chronic TMD. These results underscore the necessity of integrating cognitive and psychological assessments into clinical management, fostering a more comprehensive approach to treatment that extends beyond pain relief to improving cognitive function and overall quality of life.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.379
Teacher spread0.363 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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