Smartphone‐based evaluation of awake bruxism behaviours in a sample of healthy young adults: findings from two University centres

Abstract A smartphone‐based ecological momentary assessment (EMA) strategy was used to assess the frequency of awake bruxism behaviours, based on the report of five oral conditions (ie relaxed jaw muscles, teeth contact, mandible bracing, teeth clenching and teeth grinding). One hundred and fifty‐three (N = 153) healthy young adults (mean ± SD age = 22.9 ± 3.2 years), recruited in two different Italian Universities, used a dedicated smartphone application that sent 20 alerts/day at random times for seven days. Upon alert receipt, the subjects had to report in real‐time one of the above five possible oral conditions. Individual data were used to calculate an average frequency of the study population for each day. For each condition, a coefficient of variation (CV) of frequency data was calculated as the ratio between SD and mean values over the seven recording days. Average frequency of the different behaviours over the seven days was as follows: relaxed jaw muscle, 76.4%; teeth contact, 13.6%; mandible bracing, 7.0%; teeth clenching, 2.5%; and teeth grinding, 0.5%. No significant differences were found in frequency data between the two University samples. The relaxed jaw muscles condition was more frequent in males (80.7 ± 17.7) than in females (73.4 ± 22.2). The frequency of relaxed jaw muscles condition over the period of observation had a very low coefficient of variation (0.27), while for the different awake bruxism behaviours, CV was in a range between 1.5 (teeth contact) and 4.3 (teeth grinding). Teeth contact was the most prevalent behaviour (57.5–69.7). Findings from this investigation suggest that the average frequency of AB behaviours over one week, investigated using EMA‐approach, is around 23.6%.


| INTRODUC TI ON
Bruxism is a much-debated topic in dentistry and several other disciplines because of its multifaceted clinical relationship with many conditions and consequences. 1 Recently, an expert panel including professionals from different specialties (ie dentists, oro-facial pain experts, psychologists) proposed separate definitions for awake and sleep bruxism and provided suggestions on the assessment strategies. 2 In particular, while most research so far has been focused on the approaches to evaluate sleep bruxism (SB) (ie polysomnography [PSG], electromyography [EMG]) 3,4 knowledge is poor on awake bruxism (AB).
Awake bruxism is now defined as 'a masticatory muscle activity during wakefulness which is characterized by repetitive or sustained tooth contact and/or bracing or thrusting of the mandible and is not a movement disorder in otherwise healthy individuals'. 2 This definition embraces the concept of bruxism as a behaviour that is not necessarily pathological and/or has clinical consequences. 5,6 Within this premise, it is important to determine the frequency of AB in otherwise healthy individuals for comparisons with other populations, such as individuals with possible risk factors for additive bruxism (eg psychological factors, comorbid conditions) and/or with possible bruxism consequences (eg muscle fatigue and pain, tooth wear).
Besides, cross-cultural comparisons are needed to assess the influence of different social environments and living habits on bruxism behaviours. Thus, the definition of AB has implications concerning the assessment, which should possibly be more elaborated than the single-item self-reported strategies that were used both in adults 7 and in children/adolescents 8 in the past decades.
AB can be assessed with a combination of non-instrumental (ie self-report and clinical observation) and instrumental (ie EMG) approaches as well as with ecological momentary assessment (EMA) strategies. 2,9 EMA is an umbrella term that gathers together the possible approaches relying on the real-time report of a behaviour or condition under study. 10 It potentially addresses the limitations of traditional reporting methods, such as retrospective reports, singleitem diaries and questionnaires. 7 EMA strategies allow collecting real-time data over a certain time frame at multiple recording points during the day, close in time with the experience in the natural environment. 11 The everyday ('real world') environment, in which subjects report an experience while going on with their lives, increases the representativeness and possible generalisation of these ecological findings to an individual's real life. 12 EMA has already been proven useful in the research field to assess oral activity 13 but EMAbased data on AB are fragmental and limited to a few investigations on selected behaviours. 14-17 Also, it must be pointed out that all studies on AB are antecedent to the 2018 definition. 2 Considering these drawbacks, a smartphone-based strategy that was recently introduced to implement EMA in the clinical research setting was adapted to collect data on the reported frequency of all the conditions (ie teeth contacting habits, mandible bracing, teeth clenching and teeth grinding) that are potentially part of the AB spectrum. 12,18 To get deeper into this issue, an early report provided data on the frequency of the above-described AB behaviours over one week in a sample of healthy young adults by the adoption of a dedicated smartphone application. 19 Findings reported a 28.3% frequency of AB behaviours, with a low coefficient of variation for the report of relaxed jaw muscle condition.
Based on that, this investigation represents an extension of the first AB-smartphone EMA paper by Bracci et al. 19 , with the aim of collecting data on a larger sample and, importantly, on study populations recruited in two different centres. To pursue this goal, this investigation was designed to assess the frequency of AB behaviours by the adoption of EMA smartphone-based technology over one week in a sample of healthy young adults recruited in two different University Centers. All participants were asked to attend an information session with the leading investigators (A.Z., A.B. and D.M.). During that session, the aim of the study was explained and they received a pass code for a free download of the application on their smartphones. The students had already received seminars on bruxism and received an explanation on the study aims and how to use the application. The app is based on the principle of collecting self-reported experience during everyday life (ie 'ecological approach') and sends sound messages at random hours during the day to alert the individual on the condition of his/her teeth and jaw muscles. People who are using the app have to answer within 5 min by touching on the smartphone display the icon that refers to the current condition of his/her jaw muscles: relaxed jaw muscles, teeth contact, mandible bracing, teeth clenching and teeth grinding. For other details on the application and the software, readers are referred to the original publication. 18 The five conditions were explained in person to all individuals during the training sessions, also with the support of several images and videos. The conditions were defined as follows:

| MATERIAL S AND ME THODS
1. Relaxed jaw muscles: condition of perceived relaxation of jaw muscles without teeth contact; 2. Teeth contact: condition of slight teeth contact when the mouth is closed. More precisely, it was defined as the teeth contact the subject perceived when 40 µ articulating paper (Bausch Occlusion papier®; Bausch KG, Koln, Germany) is put between dental arches and the individual is asked to slightly keep the teeth in contact to retain it on site; 3. Mandible bracing: condition in which the jaw muscle stiffness or tension resembles that during teeth clenching, but without teeth contact; 4. Teeth clenching: all conditions in which teeth contacts are more marked than the above and jaw muscles are kept tense; 5. Teeth grinding: condition in which the opposite teeth are gnashed or ground, regardless of the intensity and direction of antagonist teeth contacts; After the explanations, the students downloaded the app and were instructed to start the first session of data collection the morning after. The software is set to send 20 alerts per day at random intervals and, based on a previous publication on the expected compliance, 20 the participants were asked to give at least 60% of valid answers/day (ie the answer must be given within five minutes, otherwise an error message appears on the display). Days with a compliance <60% were automatically discarded. The participants were taught to answer the alert by tapping the display within this time window from the alert sound. Data were recorded over a 7-day period, and the recording time was set from 8.00 to 12.30 and from 14.30 to 22.00. In order to have an as long as possible window-time recording, only lunch time was excluded and the subjects were instructed to ignore alerts during meals and particular activities (ie singing). In case of failure to reach of the minimum of valid answers per day, the software automatically sets another day of recording to complete the 7-day protocol. After seven valid days, the software generated an anonymous.csv file that the participants sent to the researchers via a dedicated email. Between-gender comparison was performed by using t test for unpaired data, with significance level set at p < .05. The same significance level was used for between-universities population comparison. In addition, as a second analysis, the prevalence values of each behaviour on a subject level, viz., the proportion of subjects indicating the behaviour at least one time, were determined for each day.
The data were collected by the leading author of this manuscript (A. Z.) in collaboration with two undergraduate dental students (one for each University) who are following the smartphone-EMA bruxism project as part of their dental degree thesis. All statistical procedures were performed with the software SPSS 25.0 (IBM, Milan, Italy).
The study protocol was approved by the Treviso Hospital's IRB (code #344-CES-AULSS9) All participants signed a written consent to take part in the study.

| RE SULTS
All 153 students attending the final three years of the two Dental Schools were invited to take part in the study (83 from the University of Siena and 70 from the University of Padova). The sample consisted of 93 females and 60 males, with a mean age of 22.9 years (range [19][20][21][22][23][24][25][26]. All students that were recruited and met the inclusion criteria completed the project. The average response rate to the alerts was 73.4 (±11.0) ( Table 1), without any difference between genders. The mean compliance per day (ie percentage of alerts to which the subjects responded) was 65.8 ± 11.5% of the total alerts.
The frequency of the relaxed jaw muscles condition was stable over the one-week span, with a very low coefficient of variation (CV, 'Teeth grinding' (4.25) ( Table 2).
As for the percentage of subjects reporting the different AB behaviours at least one time during the observation period, data showed that 'teeth grinding' was the least prevalent condition (range over the 7 days: 1.3%-6.6%). Teeth contact was the most prevalent behaviour, with a 69.7% prevalence of individuals reporting it on day 1 (range over the 7 days: 57.5%-69.7%) (

| D ISCUSS I ON
This study provides information on the frequency of different AB behaviours by the adoption of the EMA approach. Thanks to the use of smartphone technology, which takes advantage of a tool that is already part of the daily life for a large percentage of the population, 11,21 the ecological evaluation was well accepted by all individuals, with a mean compliance of over 70% of answered alerts.
The frequency of five specific conditions (ie relaxed jaw muscles, teeth contact, mandible bracing, teeth clenching and teeth grinding) was reported over a 7-day observation period. Such an approach allowed collecting a huge amount of data, with a total of more than 21 thousands alerts that should be answered with self-report of the condition in real time (up to 20 alerts × 153 participants x 7 days).
Findings of this study are hard to compare with other studies due to the different study designs (ie most studies are retrospective) and the commonly used strategy to collect self-reported data at single time points. 7 The massive data collection is a feature of all EMA observational studies and may help setting a reference value for EMAbased frequency of AB behaviour as well as comparing findings with single-item reports related to dietary or smoking habits, medication usage, psychological issues and comorbid conditions.
Results show that in a population of healthy young students, the most frequent AB behaviour over the 7-day observation was teeth contact (13.6%), while the least frequent was teeth grinding (0.5%).
Note: Mean frequency value is the number of positive responses for each specific behaviour per reporting period. For instance, a mean of 76.4% for the condition 'relaxed Jaw muscles' can be interpreted as equivalent to the report of 76.4% 'Relaxed jaw muscles' per 100 reporting alerts, meaning that, on average, each subject answered 'relaxed Jaw muscles' to 76.4% of the alerts, generalising from the random EMA sampling, with a minimum of 6.5% by at least 1 subject and a maximum of 100% by at least one subject. Coefficient of variation (CV) is expressed as the ratio between SD and mean values of frequency data over the 7 recordings day for each condition. As far as gender differences are concerned, the average frequency of the relaxed jaw muscles answer was more frequent in males than in females. This finding might be explained by the potential importance of psychological factors in the aetiology of AB and the assumption that females are more prone to suffer from stress and have a more emotion-focused coping style than males. 22 Nonetheless, it must be remarked that a previous systematic review did not find any gender differences in the frequency of AB, but none of the included studies were based on EMA. 7 Hence, the different methods that were used in the present study as compared to the previous investigations may explain the differences in gender-related findings.
It is noteworthy that no significant differences were found between the two University samples (Table 3 and Table 4). This finding is of particular importance if one considers the common belief that self-reported strategies for AB may lead to bias in the data collection due to the purported questionable validity of this approach. 23 In the present study, an identical explanation on the way of using the application was given to both study populations, with the same supporting materials (viz., slides, images, videos) presented by the same investigators. In addition, the participants downloaded the very same version of the smartphone application, regardless of the model of smartphone they owned. This attempt to minimise dishomogeneity of information might have been instrumental to 'calibrate' self-report at the individual and group level, as shown by the very similar findings on the frequency of AB behaviours in the two samples. Future studies might support the assumption that this approach, based on carefully organised training sessions, leads to a reliable EMA-based self-report. On the other hand, it must be underlined that the features of this study population might have positively influenced the results of all training efforts, since participants were dental students in their twenties. Factors such as age and dental training of the participants could also limit the possibility to generalise findings on the frequency data to the general population, which thus requires a further appraisal in more representative general population samples.
Interestingly, there was a very low coefficient of variation over one week for the relaxed jaw muscles condition (0.27; Table 2). isons are also possible, because the English version of BruxApp is adopted as a template for multi-language translation, according to a step-by-step procedure led by mother-tongue experts in the field 27 and used within the context of an ongoing multicentre project on bruxism epidemiology.

| CON CLUS IONS
Findings from this investigation suggest that the average frequency of AB behaviours over one week investigated using EMA approach is around 23.6%, and that the most frequent condition was 'teeth contact', with a percentage of 13.6%. Data retrieved in the two Universities samples were similar, thus suggesting that a carefully organised training session may be instrumental to minimise reporting bias. Similarly, the very low coefficient of variation over one week for the relaxed jaw muscles condition of (0.27) supports the use of smartphone-based EMA strategies as a promising tool to collect selfreported data for cross-cultural and cross-population comparisons.