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Summary of Smartphone‐based evaluation of awake bruxism behaviours in a sample of healthy young adults

Findings from two University centres

Alessandra Zani, Frank Lobbezoo, [...], and Daniele Manfredini





(Ref ID): PMC8453860

Chosen Image filename:  PMC8453860_Table_01.jpg


Document structure and format:


I. Introduction:


The research paper, "Smartphone‐based evaluation of awake bruxism behaviours in a sample of healthy young adults: findings from two University centres", examines the use of a smartphone-based ecological momentary assessment (EMA) strategy to assess the frequency of awake bruxism (AB) behaviors in healthy young adults. The main research objective was to determine the frequency of AB behaviors using EMA technology, which allows data to be collected in real-time over a certain time frame at multiple recording points during the day.


II. Methodology:


The study recruited 153 healthy young adults between the ages of 18-29 from two different Italian universities. Participants were asked to use a smartphone application that sent 20 alerts per day at random times for seven days. Upon alert receipt, participants had to report in real-time one of the five oral conditions (relaxed jaw muscles, teeth contact, mandible bracing, teeth clenching, and teeth grinding) associated with AB. An average frequency was calculated for each day, and a coefficient of variation (CV) of frequency data was calculated for each condition. Data were analyzed using statistical analyses.


III. Results:


The relaxed jaw muscles condition was found to be the most prevalent condition, with an average frequency of 76.4%, while teeth grinding was the least prevalent, with an average frequency of 0.5%. Teeth contact was found to be the most prevalent behavior with an average frequency of 57.5%-69.7%. The study found no significant differences in frequency data between the two universities. The study also found that the relaxed jaw muscles condition was more frequent in males than in females.


IV. Discussion:


The results indicate that the average frequency of AB behaviors in healthy young adults is around 23.6%, as investigated using the EMA approach. This study has implications for the assessment of AB in healthy individuals and highlights the need for cross-cultural comparisons. However, the study has limitations, including the relatively small sample size and the fact that participants were recruited from two Italian universities which may not be generalizable to other populations. Further research is needed to build on these findings.


V. Conclusion:


This research paper provides valuable insights into the frequency of AB behaviors and the use of smartphone-based EMA technology in assessing these behaviors. While the study has several limitations, it highlights the potential of EMA technology in studying AB behaviors in otherwise healthy individuals and the need for further research in this area.

TABLE 1: Average response rate to the alerts (mean values and SD) over the 7‐day observation period
Courtesy of PMC8453860


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