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Record W4392295371 · doi:10.5772/intechopen.113288

Relaxing Music in the Dental Waiting Room Has Paradoxical Effects on Dental Anxiety in Patients with High Cognitive and Social Anxiety Sensitivity

2024· book-chapter· en· W4392295371 on OpenAlexfundno aff
Emma E. Truffyn, Colin B Pridy, Margo C. Watt, A. T. Hill, Sherry H. Stewart

Bibliographic record

VenueIntechOpen eBooks · 2024
Typebook-chapter
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsnot available
FundersNova Scotia Health Research Foundation
KeywordsAnxiety sensitivityAnxietySocial anxietyPsychologyCognitionClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

We sought to determine the efficacy of a music intervention in decreasing state anxiety and dental-related anxiety among patients awaiting dental clinic services, particularly those with high AS-physical concerns (i.e., fear of adverse physical consequences of arousal sensations). Forty-six dental patients between the ages of 20 and 78 years (61% female) participated in the intervention. While awaiting dental procedures, patients completed the Anxiety Sensitivity Index-3 and were exposed to music selected by experts to be either relaxing (n = 24) or neutral (n = 22). During the exposure period, participants completed the State-Trait Anxiety Inventory-State Form-6, and the Dental Anxiety Scale-4 as outcome variables. Contrary to predictions, participants exposed to relaxing (vs. neutral) music did not report lower levels of dental or state anxiety. Paradoxically, participants in the relaxing music condition showed a significant positive correlation between AS-cognitive concerns (e.g., fear of losing control) and AS-social concerns (e.g., fear of public embarrassment) with dental anxiety. Dental clinics should be more intentional in their selection of music in the waiting room, as patients with high AS-cognitive and/or high AS-social concerns may experience a paradoxical increase in dental anxiety from music intended to be relaxing.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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
Published2024
Admission routes1
Has abstractyes

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