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Record W4382011399 · doi:10.1002/brb3.3077

How does the continued use of the mask affect the craniofacial region? A cross‐sectional study

2023· article· en· W4382011399 on OpenAlexaff
Elena Marqués‐Sulé, Gemma Victoria Espí‐López, Lucas Monzani, Luis Suso‐Martí, Miriam Calderón Rel, Anna Arnal‐Gómez

Bibliographic record

VenueBrain and Behavior · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Coronavirus disease 2019 (COVID-19)Cross-sectional studyAffect (linguistics)Face masksCraniofacialDentistryInternal medicinePsychologyDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim was to compare the effects between pre-pandemic mask-free living versus pandemic-related continuous mask use. METHODS: A retrospective study was carried out. This study was conducted with 542 face mask users. Assessments included presence, frequency and impact of headache, temporomandibular disorders, and quality of life (QoL). RESULTS: Continuous mask use had a large main effect on headache, temporomandibular pain, and QoL (p < .0001; d = 1.25), but this effect was nuanced by mask type. Participants who declared suffering from headache increased by 84% with cloth masks, and by 25% with FFP2 masks. Temporomandibular pain increased by 50% and by 39% when wearing surgical masks and FFP2, respectively (p < .06; d = .19). The mask type did not nuance the effect on headache impact (p > .05; d = .06). QoL decreased regardless of mask type (p < .05; d = .21), the decrease being 38% for surgical masks, and 31% for either cloth or FFP2 masks. CONCLUSIONS: Continuous mask use, regardless of type, increased existence of headache, headache impact, temporomandibular pain, and reduced QoL.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.044
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.078
GPT teacher head0.372
Teacher spread0.294 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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