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Possible sleep and awake bruxism, chronotype profile and TMD symptoms among Turkish dental students.

Ozge Kırarslan KaragozBengisu YildirimAysila Tekeli SimsekCansu Gül Efeoğlu KocaMehmet Igneci
Published in: Chronobiology international (2021)
It was hypothesized that an individual's chronotype profile has an effect on the performance of work or study tasks. Dental students have to cope with both academic and clinical workloads, and the latter requires extra concentration. The first aim was to evaluate the association of sleep bruxism (SB) and awake bruxism (AB) with sleep related items, temporomandibular disorder (TMD) complaints, and chronotype profile; the second aim was to evaluate the association between complaints of TMD and chronotype profile among dental students. The present cross-sectional descriptive study involved 218 dental students whose ages ranged between 18 and 30 years. In order to gather data, students were required to respond to a questionnaire, which aimed to evaluate possible SB and possible AB occurrence and demographics, sleep-related items and complaints of TMD. For the assessment of the chronotype profile, the morningness-eveningness questionnaire (MEQ) was used. The chi-square test, the Mann-Whitney U test, and t-test analyses were performed to evaluate the factors associated with SB, AB and chronotype profile. The frequency of self-reported SB was 25.2% and AB was 28.9%. The prevalence in the eveningness profile who reported possible AB was 45.3%, while it was 24.2% in intermediate individuals and 18.8% in the morningness profile. An association was also found between possible AB and eveningness chronotype profile (p = .009). No association was found between other temporomandibular joint (TMJ) pain and noise and chronotype profiles (p > .05). An association was found between possible AB and eveningness chronotype profile but no association was found between possible SB and chronotype profile. Moreover, complaint of TMD (face, head, neck pain) was observed particularly in students with an eveningness profile.
Keyphrases
  • cross sectional
  • physical activity
  • risk factors
  • chronic pain
  • oral health
  • machine learning
  • air pollution
  • artificial intelligence
  • spinal cord
  • big data
  • psychometric properties