ABSTRACT
Background
Temporomandibular disorders (TMDs) impair oral health‐related quality of life (OHRQoL) through pain, dysfunction and psychosocial distress. Oral behaviours may exacerbate these impacts, but their associations across TMD subtypes remain underexplored.
Objectives
This study examined oral behaviours across TMD subtypes and their relationships with psychological distress, alongside their four‐dimensional impacts on OHRQoL.
Methods
A total of 989 first‐visit TMD patients (mean age 29.7 years [SD 10.6]; 80.6% female) completed the Oral Behaviour Checklist, Patient Health Questionnaire‐9, General Anxiety Disorder‐7 and Oral Health Impact Profile for TMDs. Diagnoses followed DC/TMD protocol, classifying participants into intra‐articular (IT: 28.9%), pain‐related (PT: 38.4%) and combined (CT: 32.7%) TMD subtypes. Jaw overuse behaviour (JOB) was categorised as normal (NO: 18.6%), low (LO: 29.4%) or high (HO: 52.0%). Analyses included nonparametric tests, Spearman correlations and logistic regressions (α = 0.05).
Results
CT and PT reported more frequent waking‐state nonfunctional oral activities (WN), higher psychological distress and poorer OHRQoL than IT. HO showed significantly greater impairment across all four OHRQoL dimensions: oral function, orofacial pain, orofacial appearance and psychosocial impact. Appearance and function consistently ranked highest among dimensions. Depression and anxiety were moderately correlated with psychosocial impact (rs = 0.51–0.65). High JOB was associated with younger age (OR 0.95), higher education (ORs 2.01–2.59) and depression (OR 1.07). Low OHRQoL was linked to female sex (OR 1.67), older age (OR 1.03), PT/CT subtypes (ORs 2.49–3.60), WN (OR 1.16) and anxiety (OR 1.29).
Conclusions
Oral behaviours, especially WN, are significantly associated with psychological distress and multidimensional OHRQoL impairment in TMD patients, with distinct patterns across diagnostic subtypes.
Keywords: oral behaviours, oral health, psychological distress, quality of life, temporomandibular disorders
This study demonstrates that oral behaviours, particularly waking‐state nonfunctional oral activities, are significantly associated with psychological distress and multidimensional impairment in OHRQoL among patients with TMDs.
1. Background
Temporomandibular disorders (TMDs) refer to a diverse group of over 30 conditions involving pain and functional impairment in the temporomandibular joints (TMJs), jaw muscles and supporting structures [1]. They rank as the second most prevalent musculoskeletal disorder after low back pain, affecting up to 34% of the global population, with women aged 20–40 years exhibiting greater susceptibility [2, 3, 4]. Guided by the Diagnostic Criteria for TMDs (DC/TMD) and its tiered reporting schema, common TMDs can be classified into three diagnostic subtypes: intra‐articular (IT), which includes TMJ disc displacements, degenerative joint disease and subluxation; pain‐related (PT), covering TMJ arthralgia, masticatory muscle myalgia and TMD‐related headaches and combined (CT), where both IT and PT conditions are present [5, 6]. The aetiology of TMDs follows the biopsychosocial model, arising from dynamic interactions among factors such as genetics, hormones, age, biological sex, trauma, sleep disorders, somatic symptoms, psychological distress and oral [7, 8, 9, 10, 11].
Oral behaviours encompass functional and nonfunctional activities of the masticatory system during sleep and wakefulness [12, 13, 14]. Sleeping‐state oral activities (SA) include teeth clenching or grinding and sleep‐related habits or positions that place pressure on the jaws. In contrast, waking‐state nonfunctional oral activities (WN) involve repetitive teeth clenching or grinding, abnormal jaw or tongue positioning and habits like object biting or gum chewing. Waking‐state functional activities (WF) are normal behaviours like eating, talking and yawning [14]. Oral behaviours can be assessed via self‐reports, clinician evaluations or technology‐based instruments. Among these, self‐reported questionnaires, particularly the Oral Behaviour Checklist (OBC), are the most practical and widely used [13, 14, 15]. The OBC quantifies ‘jaw overuse behavior’ (JOB) and is integrated into both the DC/TMD Axis II psychosocial‐behavioural assessment and the Standardized Tool for the Assessment of Bruxism (STAB) protocols [5, 15]. Its reliability and validity have been established in clinical and naturalistic settings [16, 17, 18].
Oral health‐related quality of life (OHRQoL) reflects the impact of oral conditions on overall well‐being and daily activities, spanning functional, physical, psychological and social domains [19, 20]. While all TMD conditions adversely affect OHRQoL, the impact is markedly greater in the presence of pain [21, 22]. However, empirical evidence does not support the original seven‐domain structure of the Oral Health Impact Profile (OHIP), an extensively used OHRQoL measure in dental and TMD research [23]. In response, an international workgroup introduced a four‐dimensional framework for assessing OHRQoL: oral function (OF), orofacial pain (OP), orofacial appearance (OA) and psychosocial impact (PI) [23, 24]. Recent findings support the applicability of the four‐dimensional framework to TMDs, and its adoption as a standardised OHRQoL metric could improve comparability with studies on other oral conditions [25].
Oral behaviours can affect the OHRQoL of TMD patients through direct and indirect pathways. Directly, oral activities during sleep and wakefulness may exacerbate jaw pain, hinder jaw function and disrupt sleep. Indirectly, these behaviours are related to psychological distress and heightened stress reactivity, which amplify pain perception and undermine emotional resilience, ultimately reducing self‐esteem, diminishing social participation and impairing overall well‐being [21, 26, 27, 28, 29]. Given the limited research on the impact of oral behaviours on OHRQoL and the emerging relevance of the four‐dimensional OHIP framework, this study aimed to (1) compare the frequency and nature of oral behaviours, along with psychological distress levels, across different TMD diagnostic subtypes; (2) examine the interrelationships between SA, WN and WF with the four OHRQoL dimensions and (3) identify biopsychosocial factors linked to high JOB and low OHRQoL. The research hypotheses were as follows: (a) patients with PT and CT exhibit higher frequencies of oral behaviours and greater psychological distress compared to those with IT; (b) WN show stronger correlations with impaired OHRQoL across all four dimensions than either SA or WF and (c) sex, age, education level and psychological distress are significantly associated with high jaw overuse behaviour and low OHRQoL.
2. Methods
2.1. Study Design and Population
Approval for this prospective observational study was granted by the Ethics Committee of Stomatology, Sichuan University (WCHSIRB‐D‐2022‐212). A sample size estimate of 690 participants was computed using G*Power (version 3.1.9.3) to detect differences in JOB across TMD subtypes. The calculation was based on an analysis of variance model with three groups, assuming a small effect size (f = 0.15), 95% power and an alpha error of 0.05 [26, 30]. Consecutive first‐visit patients were enrolled between January 2022 and June 2025 from the TMD clinic of West China Hospital of Stomatology, Sichuan University. Inclusion criteria were age 18 years or older, fluency in Chinese, presence of TMD signs/symptoms and absence of other orofacial pain conditions such as odontogenic or neuropathic pain. Exclusion criteria were a history of TMJ trauma or surgery, recent analgesic use (within the past 3 months), cognitive impairment or illiteracy and incomplete DC/TMD physical diagnosis or patient‐reported outcomes. All eligible patients were informed about the study, and written consent was obtained for the use of de‐identified data in research. At the initial visit, participants were instructed to provide sociodemographic information and to complete a battery of self‐reported measures, including the Chinese versions of the DC/TMD Symptom Questionnaire (SQ), OBC, Patient Health Questionnaire‐9 (PHQ‐9), Generalized Anxiety Disorder‐7 (GAD‐7) and the OHIP for TMDs (OHIP‐TMD) [5, 13, 31, 32, 33, 34].
2.2. TMD Diagnosis and Subtypes
The clinical examination was conducted by three examiners who were trained and calibrated in the DC/TMD methodology, with inter‐examiner reliability (Cohen's kappa) ranging from 0.706 to 0.842. The examination included assessment of pain locations, palpation‐induced pain, TMJ noises, jaw deviations and the range of mandibular movements. In cases where structural pathology was evident, such as TMJ degeneration, persistent disc displacement without reduction or neoplastic lesions, diagnoses were confirmed using cone‐beam computed tomography (CBCT) and magnetic resonance imaging (MRI). TMD diagnoses were determined using DC/TMD diagnostic algorithms, integrating symptom history, clinical findings and imaging results. Participants were subsequently assigned to one of three diagnostic subtypes: IT, PT or CT.
2.3. Study Measures
2.3.1. OBC
The 21‐item OBC was used to assess the frequency of oral behaviours during sleep and wakefulness [13]. Items were rated on a 5‐point scale from 0 (‘none of the time’) to 4 (‘4–7 nights per week’ or ‘all of the time’). Total OBC scores reflected overall JOB and were categorised as normal (NO: 0–16), low (LO: 17–24) or high (HO: 25–84 points) [13, 26]. SA subscale scores were derived from the two sleeping‐state items, while WN and WF subscale scores were computed from six waking‐state nonfunctional and six functional items, as specified by Donnarumma et al. [14]. Higher SA, WN and WF scores correspond to greater frequency of oral behaviours during their respective states.
2.3.2. PHQ‐9 and GAD‐7
The 9‐item PHQ‐9 and 7‐item GAD‐7 were used to evaluate the severity of depressive and anxious symptoms respectively [31, 32]. Both measures have demonstrated strong psychometric properties in diverse populations [35]. Items were rated on a 4‐point scale from 0 (‘not at all’) to 3 (‘nearly every day’). Total PHQ‐9 and GAD‐7 scores were computed by summing responses for all items, with higher scores indicating greater symptom severity. PHQ‐9 scores were categorised as mild (≥ 5), moderate (≥ 10), moderately severe (≥ 15) or severe (≥ 20 points), whereas GAD‐7 scores were classified as mild (≥ 5), moderate (≥ 10) or severe (≥ 15 points).
2.3.3. OHIP‐TMD
The 22‐item OHIP‐TMD was used to assess OHRQoL across four dimensions: OF, OP, OA and PI. It consisted of 20 items adapted from the OHIP‐49 and two additional items derived from qualitative research involving TMD patients [33]. The OHIP‐TMD showed robust psychometric properties and good discriminative capacity [19, 33, 34, 36]. Item‐to‐dimension mapping adhered to the recommendations of the international workgroup, with the two qualitatively derived items describing difficulties with chewing and mouth opening or closing assigned to the OF dimension, and the originally unmapped item concerning ‘feeling miserable’ allocated to the PI dimension [23]. Items were rated on a 5‐point scale from 0 (‘never’) to 4 (‘very often’). Global and dimension OHIP‐TMD scores were calculated by summing the responses to all 22 items and the items corresponding to each dimension, with OF (5 items, 0–20), OP (4 items, 0–16), OA (2 items, 0–8) and PI (11 items, 0–44), yielding a total possible score of 0–88. Normalised dimension scores were also derived by dividing raw scores by the number of contributing items, thereby enabling equitable comparisons across dimensions with differing ranges. All statistical analyses were performed on raw values. Higher global dimension and normalised OHIP‐TMD scores consistently indicate poorer OHRQoL.
2.4. Statistical Analyses
Statistical analyses were conducted using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria), with a predefined significance level of 0.05. Categorical variables were summarised as counts and percentages, and examined using the Chi‐square test. Continuous variables were reported as means with standard deviations (SDs), and medians with interquartile ranges (IQRs). The Shapiro–Wilk test was used to assess normality, revealing a non‐normal distribution. Consequently, the Kruskal–Wallis test, Dunn's post hoc procedure with Benjamini–Hochberg correction and Spearman's rank‐order correlation were employed. Spearman correlation coefficients (rs) were categorised as weak (≥ 0.1), moderate (≥ 0.4), strong (≥ 0.7) or very strong (≥ 0.9) [37]. Univariate and multivariate logistic regression analyses were used to identify biopsychosocial factors associated with high JOB and low OHRQoL. Low OHRQoL status was defined based on a median split of global OHIP scores. Nonsignificant variables were eliminated via a stepwise selection approach combining forward and backward procedures, based on a significance threshold of p < 0.10. Outcomes were presented as odds ratios (ORs) with corresponding 95% confidence intervals (CIs), and effect sizes were categorised as small (OR = 0.7–1.5), medium (OR = 0.4–0.7 or 1.5–2.5) and large (OR < 0.4 or > 2.5) [38]. To assess potential collinearity in the regression models, variance inflation factors (VIF) and condition indices were examined, with all values falling within acceptable thresholds (VIF < 5; condition index < 30).
3. Results
Of the 1372 patients screened, 1035 met the inclusion criteria, and none declined participation. Forty‐four were excluded for TMJ trauma or surgery, and two for cleft lip and palate. The final sample comprised 989 participants, with a mean age of 29.7 years (SD = 10.6), and 80.6% were female. Tables 1 and 2 present biopsychosocial and behavioural profiles across TMD subtypes and JOB levels. IT, PT and CT accounted for 28.9%, 38.4% and 32.7% of participant diagnoses, respectively, while 18.6%, 29.4% and 52.0% of participants reported NO, LO and HO. Among TMD subtypes, significant differences were observed in sex distribution (female: CT > IT > PT), age (PT > CT > IT), WN scores (PT, CT > IT), depression (PT, CT > IT) and anxiety (PT, CT > IT). Individuals with CT and PT had substantially higher global, OF, OP, OA and PI scores than those with IT. Across JOB levels, significant differences were noted in sex distribution (female: HO > LO > NO), age (NO > LO > HO), education level (college/university and graduate education: HO > LO > NO), depression (HO > LO > NO) and anxiety (HO > LO > NO). Individuals with HO had considerably higher global and all four dimension scores than those with LO and NO.
TABLE 1.
Biopsychosocial and behavioural profiles across TMD diagnostic subtypes.
| Variables | All participants | Intra‐articular TMDs [IT] | Pain‐related TMDs [PT] | Combined TMDs [CT] | p Post hoc | Effect size V or ϵ2 |
|---|---|---|---|---|---|---|
| Total, n (%) | 989 (100) | 349 (35.29) | 210 (21.23) | 430 (43.48) | ||
| Sex | < 0.001 | 0.133 (small) | ||||
| Male, n (%) | 192 (19.41) | 77 (40.10) | 56 (29.17) | 59 (30.73) | ||
| Female, n (%) | 797 (80.59) | 272 (34.13) | 154 (19.32) | 371 (46.55) | ||
| Age | < 0.001 | 0.018 (small) | ||||
| Mean (SD) | 29.65 (10.64) | 27.96 (9.18) | 31.79 (11.11) | 29.97 (11.30) | ||
| Median (IQR) | 26.00 (10.83) | 26.00 (8.00) | 29.00 (14.00) | 26.00 (10.62) | PT > CT > IT | |
| Education | 0.276 | |||||
| Primary/Secondary, n (%) | 146 (14.76) | 42 (28.77) | 35 (23.97) | 69 (47.26) | ||
| College/University, n (%) | 703 (71.08) | 249 (35.42) | 149 (21.19) | 305 (43.39) | ||
| Graduate School, n (%) | 140 (14.16) | 58 (41.43) | 26 (18.57) | 56 (40.00) | ||
| Total OBC (TO) | 0.178 | |||||
| Mean (SD) | 24.80 (9.19) | 24.11 (9.34) | 25.13 (9.34) | 25.20 (8.97) | ||
| Median (IQR) | 25.00 (12.00) | 24.00 (12.00) | 25.00 (13.00) | 26.00 (12.00) | ||
| Sleeping‐state (SA) | 0.869 | |||||
| Mean (SD) | 4.30 (2.14) | 4.24 (2.19) | 4.32 (2.10) | 4.34 (2.11) | ||
| Median (IQR) | 4.00 (3.00) | 4.00 (3.00) | 4.00 (3.00) | 4.00 (3.00) | ||
| Waking‐state nonfunctional (WN) | 0.011 | 0.007 (negligible) | ||||
| Mean (SD) | 6.41 (4.06) | 5.95 (4.07) | 6.90 (4.24) | 6.55 (3.93) | ||
| Median (IQR) | 6.00 (6.00) | 5.00 (6.00) | 7.00 (6.00) | 7.00 (5.00) | PT, CT > IT | |
| Waking‐state functional (WF) | 0.219 | |||||
| Mean (SD) | 7.58 (3.09) | 7.64 (3.11) | 7.29 (3.00) | 7.67 (3.12) | ||
| Median (IQR) | 8.00 (4.00) | 8.00 (4.00) | 7.00 (4.00) | 8.00 (4.00) | ||
| Depression (PD) | < 0.001 | 0.028 (small) | ||||
| Mean (SD) | 4.90 (4.77) | 3.89 (4.25) | 5.51 (5.16) | 5.44 (4.85) | ||
| Median (IQR) | 4.00 (6.00) | 3.00 (6.00) | 5.00 (6.00) | 5.00 (6.75) | PT, CT > IT | |
| Anxiety (PA) | < 0.001 | 0.035 (small) | ||||
| Mean (SD) | 4.63 (4.65) | 3.51 (4.05) | 5.27 (4.95) | 5.22 (4.79) | ||
| Median (IQR) | 4.00 (6.00) | 2.00 (5.00) | 4.00 (6.00) | 4.00 (6.00) | PT, CT > IT | |
| Global OHIP (GO) | < 0.001 | 0.149 (large) | ||||
| Mean (SD) | 32.19 (16.94) | 23.52 (15.50) | 35.67 (16.60) | 37.53 (15.37) | ||
| Median (IQR) | 32.00 (23.00) | 22.00 (22.00) | 35.50 (21.50) | 37.00 (21.00) | CT, PT > IT | |
| Oral function (OF) | < 0.001 | 0.172 (large) | ||||
| Mean (SD) | 8.33 (4.47) | 5.91 (4.02) | 8.77 (4.23) | 10.08 (4.02) | ||
| Median (IQR) | 8.00 (6.00) | 6.00 (6.00) | 9.00 (5.00) | 10.00 (6.00) | CT > PT > IT | |
| Orofacial pain (OP) | < 0.001 | 0.260 (large) | ||||
| Mean (SD) | 5.02 (3.24) | 2.85 (2.60) | 6.33 (3.01) | 6.14 (2.89) | ||
| Median (IQR) | 5.00 (5.00) | 2.00 (3.00) | 6.00 (4.00) | 6.00 (4.00) | PT, CT > IT | |
| Orofacial appearance (OA) | < 0.001 | 0.037 (small) | ||||
| Mean (SD) | 4.43 (2.12) | 3.88 (2.16) | 4.53 (2.13) | 4.83 (1.99) | ||
| Median (IQR) | 4.00 (3.00) | 4.00 (3.00) | 5.00 (3.00) | 5.00 (2.00) | CT, PT > IT | |
| Psychosocial impact (PI) | < 0.001 | 0.074 (medium) | ||||
| Mean (SD) | 14.41 (9.71) | 10.89 (9.07) | 16.03 (9.72) | 16.48 (9.43) | ||
| Median (IQR) | 14.00 (15.00) | 9.00 (14.00) | 16.00 (13.00) | 16.50 (12.00) | CT, PT > IT |
Note: Results of Chi‐square test and Kruskal–Wallis/post hoc Dunn's test with Benjamini–Hochberg adjustment. Bold indicates p < 0.05. Effect sizes were calculated for results with p < 0.05 and interpreted according to Cohen's benchmarks. For the Chi‐square test, Cramér's V was interpreted based on degrees of freedom (e.g., for df = 1: small = 0.10, medium = 0.30, large = 0.50; for df = 2: small = 0.07, medium = 0.21, large = 0.35). For the Kruskal–Wallis test, Epsilon‐squared (ϵ2) values of 0.01, 0.06 and 0.14 represented small, medium and large effects respectively. Higher effects mean a greater clinical distinction.
Abbreviations: IQR, Interquartile range; OBC, Oral Behaviours Checklist; OHIP, Oral Health Impact Profile; SD, Standard deviation.
TABLE 2.
Biopsychosocial profiles and distribution of TMD subtypes across ‘jaw overuse behavior’ (JOB) levels.
| Variables | All participants | Normal (NO) | Low jaw overuse (LO) | High jaw overuse (HO) | p Post hoc | Effect size V or ϵ2 |
|---|---|---|---|---|---|---|
| Total, n (%) | 989 (100) | 184 (18.60) | 291 (29.42) | 514 (51.97) | ||
| Sex | < 0.001 | 0.120 (small) | ||||
| Male, n (%) | 192 (19.41) | 52 (27.08) | 60 (31.25) | 80 (41.67) | ||
| Female, n (%) | 797 (80.59) | 132 (16.56) | 231 (28.98) | 434 (54.45) | ||
| Age | < 0.001 | 0.092 (medium) | ||||
| Mean (SD) | 29.65 (10.64) | 37.31 (13.86) | 29.54 (10.11) | 26.97 (7.97) | ||
| Median (IQR) | 26.00 (10.83) | 34.00 (22.00) | 27.00 (11.00) | 25.00 (7.00) | NO > LO > HO | |
| Education | < 0.001 | 0.192 (small) | ||||
| Primary/Secondary, n (%) | 146 (14.76) | 63 (43.15) | 39 (26.71) | 44 (30.14) | ||
| College/University, n (%) | 703 (71.08) | 104 (14.79) | 212 (30.16) | 387 (55.05) | ||
| Graduate School, n (%) | 140 (14.16) | 17 (12.14) | 40 (28.57) | 83 (59.29) | ||
| TMD subtypes | 0.458 | |||||
| Intra‐articular, n (%) | 349 (35.29) | 70 (20.06) | 107 (30.66) | 172 (49.28) | ||
| Pain‐related, n (%) | 210 (21.23) | 35 (16.67) | 68 (32.38) | 107 (50.95) | ||
| Combined, n (%) | 430 (43.48) | 79 (18.37) | 116 (26.98) | 235 (54.65) | ||
| Depression (PD) | < 0.001 | 0.075 (medium) | ||||
| Mean (SD) | 4.90 (4.77) | 2.94 (3.73) | 4.29 (4.31) | 5.96 (5.07) | ||
| Median (IQR) | 4.00 (6.00) | 2.00 (4.00) | 3.00 (5.00) | 5.00 (7.00) | HO > LO > NO | |
| Anxiety (PA) | < 0.001 | 0.055 (small) | ||||
| Mean (SD) | 4.63 (4.65) | 3.19 (4.18) | 4.00 (4.16) | 5.50 (4.88) | ||
| Median (IQR) | 4.00 (6.00) | 1.00 (5.00) | 3.00 (5.00) | 5.00 (5.00) | HO > LO > NO | |
| Global OHIP (GO) | < 0.001 | 0.056 (small) | ||||
| Mean (SD) | 32.19 (16.94) | 25.03 (17.95) | 30.44 (15.19) | 35.75 (16.58) | ||
| Median (IQR) | 32.00 (23.00) | 24.00 (27.25) | 30.00 (23.00) | 35.50 (21.75) | HO > LO > NO | |
| Oral function (OF) | < 0.001 | 0.018 (small) | ||||
| Mean (SD) | 8.33 (4.47) | 7.21 (4.97) | 8.05 (4.13) | 8.89 (4.37) | ||
| Median (IQR) | 8.00 (6.00) | 7.00 (8.00) | 8.00 (6.00) | 9.00 (6.00) | HO > LO, NO | |
| Orofacial pain (OP) | < 0.001 | 0.035 (small) | ||||
| Mean (SD) | 5.02 (3.24) | 3.96 (3.48) | 4.80 (2.94) | 5.52 (3.21) | ||
| Median (IQR) | 5.00 (5.00) | 4.00 (5.00) | 5.00 (4.00) | 6.00 (4.00) | HO > LO > NO | |
| Orofacial appearance (OA) | < 0.001 | 0.057 (small) | ||||
| Mean (SD) | 4.43 (2.12) | 3.35 (2.42) | 4.35 (1.83) | 4.86 (2.02) | ||
| Median (IQR) | 4.00 (3.00) | 4.00 (4.00) | 4.00 (3.00) | 5.00 (3.00) | HO > LO > NO | |
| Psychosocial impact (PI) | < 0.001 | 0.058 (small) | ||||
| Mean (SD) | 14.41 (9.71) | 10.50 (9.63) | 13.24 (8.85) | 16.47 (9.69) | ||
| Median (IQR) | 14.00 (15.00) | 9.00 (15.00) | 13.00 (14.50) | 16.00 (14.00) | HO > LO > NO |
Note: Results of Chi‐square test and Kruskal–Wallis/post hoc Dunn's test with Benjamini–Hochberg adjustment. Bold indicates p < 0.05. Effect sizes were calculated for results with p < 0.05 and interpreted according to Cohen's benchmarks. For the Chi‐square test, Cramér's V was interpreted based on degrees of freedom (e.g., for df = 1: small = 0.10, medium = 0.30, large = 0.50; for df = 2: small = 0.07, medium = 0.21, large = 0.35). For the Kruskal–Wallis test, Epsilon‐squared (ϵ2) values of 0.01, 0.06 and 0.14 represented small, medium and large effects respectively. Higher effects mean a greater clinical distinction.
Abbreviations: IQR, Interquartile range; OHIP, Oral Health Impact Profile; SD, Standard deviation.
Table 3 compares normalised OHIP dimension scores across JOB levels, stratified by TMD subtype. For the IT group, significant differences were observed in global OHIP (HO, LO > NO), OF (HO, LO > NO), OP (HO, LO > NO), OA (HO, LO > NO) and PI (HO > LO > NO) dimension scores. For the PT group, significant differences were noted in global OHIP (HO > NO), OP (HO > NO), OA (HO > NO) and PI (HO > NO) dimension scores. For the CT group, significant differences were found in global OHIP (HO > NO), OP (HO > NO), OA (HO, LO > NO) and PI (HO > LO > NO) dimension scores. Across TMD subtypes, distinct and consistent patterns emerged in the relative burden of OHIP dimensions when stratified by JOB levels. For IT, the hierarchy remained stable across all JOB strata: OA > OF > PI > OP. For PT, the dimensional pattern was similarly consistent across JOB levels: OA > OF > OP > PI. A transitional shift was observed for CT. The NO group followed the PT pattern: OA > OF > OP > PI. In contrast, both LO and HO groups showed a reordering: OA > OF > PI > OP.
TABLE 3.
Comparison of normalised OHIP dimension scores across ‘jaw overuse behavior’ (JOB) levels stratified by TMD subtypes.
| TMD subtype | Variables | All in subtype | Normal (NO) | Low jaw overuse (LO) | High jaw overuse (HO) | p Post hoc | Effect size V or ϵ2 |
|---|---|---|---|---|---|---|---|
| Intra‐articular | Total, n (%) | 349 (100) | 70 (20.06) | 107 (30.66) | 172 (49.28) | ||
| GO | < 0.001 | 0.081 (medium) | |||||
| Mean (SD) | 23.52 (15.50) | 15.46 (13.44) | 22.38 (12.68) | 27.51 (16.51) | |||
| Median (IQR) | 22.00 (22.00) | 11.50 (20.75) | 20.00 (18.00) | 26.00 (24.00) | HO > LO > NO | ||
| Normalised OF | < 0.001 | 0.039 (small) | |||||
| Mean (SD) | 1.18 (0.80) | 0.87 (0.80) | 1.16 (0.74) | 1.32 (0.81) | |||
| Median (IQR) | 1.20 (1.20) | 0.60 (1.50) | 1.00 (1.00) | 1.20 (1.05) | HO, LO > NO | ||
| Normalised OP | < 0.001 | 0.060 (medium) | |||||
| Mean (SD) | 0.71 (0.65) | 0.42 (0.51) | 0.69 (0.57) | 0.85 (0.71) | |||
| Median (IQR) | 0.50 (0.75) | 0.25 (0.75) | 0.50 (0.75) | 0.75 (1.25) | HO, LO > NO | ||
| Normalised OA | < 0.001 | 0.072 (medium) | |||||
| Mean (SD) | 1.94 (1.08) | 1.32 (1.10) | 1.95 (0.86) | 2.18 (1.10) | |||
| Median (IQR) | 2.00 (1.50) | 1.25 (2.00) | 2.00 (1.00) | 2.00 (1.50) | HO, LO > NO | ||
| Normalised PI | < 0.001 | 0.074 (medium) | |||||
| Mean (SD) | 0.99 (0.82) | 0.62 (0.70) | 0.90 (0.70) | 1.20 (0.88) | |||
| Median (IQR) | 0.82 (1.27) | 0.36 (1.00) | 0.73 (1.00) | 1.09 (1.27) | HO > LO > NO | ||
| Pain‐related | Total, n (%) | 210 (100) | 35 (16.67) | 68 (32.38) | 107 (50.95) | ||
| GO | 0.009 | 0.036 (small) | |||||
| Mean (SD) | 35.67 (16.60) | 28.86 (18.56) | 34.12 (15.14) | 38.88 (16.16) | |||
| Median (IQR) | 35.50 (21.50) | 29.00 (28.00) | 34.00 (18.00) | 38.00 (21.50) | HO > NO | ||
| Normalised OF | 0.254 | ||||||
| Mean (SD) | 1.75 (0.85) | 1.61 (0.89) | 1.69 (0.77) | 1.84 (0.87) | |||
| Median (IQR) | 1.80 (1.00) | 1.60 (1.00) | 1.80 (0.85) | 2.00 (1.20) | |||
| Normalised OP | 0.008 | 0.037 (small) | |||||
| Mean (SD) | 1.58 (0.75) | 1.23 (0.92) | 1.53 (0.61) | 1.74 (0.74) | |||
| Median (IQR) | 1.50 (1.00) | 1.00 (1.50) | 1.50 (0.50) | 1.75 (1.00) | HO > NO | ||
| Normalised OA | 0.008 | 0.037 (small) | |||||
| Mean (SD) | 2.27 (1.06) | 1.74 (1.32) | 2.21 (0.94) | 2.48 (0.98) | |||
| Median (IQR) | 2.50 (1.50) | 2.00 (2.50) | 2.00 (1.50) | 2.50 (1.50) | HO > NO | ||
| Normalised PI | 0.015 | 0.031 (small) | |||||
| Mean (SD) | 1.46 (0.88) | 1.13 (0.93) | 1.38 (0.83) | 1.61 (0.88) | |||
| Median (IQR) | 1.45 (1.18) | 1.09 (1.45) | 1.36 (0.93) | 1.64 (1.09) | HO > NO | ||
| Combined | Total, n (%) | 430 (100) | 79 (18.37) | 116 (26.98) | 235 (54.65) | ||
| GO | < 0.001 | 0.037 (small) | |||||
| Mean (SD) | 37.53 (15.37) | 31.81 (17.61) | 35.70 (14.26) | 40.35 (14.47) | |||
| Median (IQR) | 37.00 (21.00) | 31.00 (25.50) | 36.00 (21.25) | 40.00 (19.50) | HO > LO, NO | ||
| Normalised OF | 0.189 | ||||||
| Mean (SD) | 2.02 (0.80) | 1.88 (0.96) | 1.98 (0.73) | 2.08 (0.78) | |||
| Median (IQR) | 2.00 (1.20) | 2.00 (1.40) | 2.00 (0.80) | 2.00 (1.00) | |||
| Normalise OP | 0.041 | 0.010 (small) | |||||
| Mean (SD) | 1.53 (0.72) | 1.39 (0.84) | 1.48 (0.67) | 1.61 (0.70) | |||
| Median (IQR) | 1.50 (1.00) | 1.25 (1.25) | 1.50 (1.00) | 1.50 (0.75) | HO > NO | ||
| Normalise OA | < 0.001 | 0.042 (small) | |||||
| Mean (SD) | 2.42 (0.99) | 1.96 (1.18) | 2.36 (0.91) | 2.59 (0.92) | |||
| Median (IQR) | 2.50 (1.00) | 2.00 (2.00) | 2.50 (1.00) | 2.50 (1.00) | HO, LO > NO | ||
| Normalise PI | < 0.001 | 0.044 (small) | |||||
| Mean (SD) | 1.50 (0.86) | 1.18 (0.91) | 1.38 (0.81) | 1.67 (0.83) | |||
| Median (IQR) | 1.50 (1.09) | 1.09 (1.23) | 1.45 (1.27) | 1.55 (1.09) | HO > LO, NO |
Note: Results of Chi‐square test and Kruskal–Wallis/post hoc Dunn's test with Benjamini–Hochberg adjustment. Bold indicates p < 0.05. Effect sizes were calculated for results with p < 0.05 and interpreted according to Cohen's benchmarks. For the Chi‐square test, Cramér's V was interpreted based on degrees of freedom (e.g., for df = 1: small = 0.10, medium = 0.30, large = 0.50; for df = 2: small = 0.07, medium = 0.21, large = 0.35). For the Kruskal–Wallis test, Epsilon‐squared (ϵ2) values of 0.01, 0.06 and 0.14 represented small, medium and large effects respectively. Higher effects mean a greater clinical distinction.
Abbreviations: GO, Global OHIP; IQR, Interquartile range; OA, Orofacial appearance; OF, Oral function; OP, Orofacial pain; PI, Psychosocial impact; SD, Standard deviation.
Tables 4, 5, 6 detail the correlation and logistic regression results. Cross‐measure analyses revealed moderate associations between psychological and OHRQoL measures across all TMD subtypes. In the IT group: depression correlated with global OHIP (rs = 0.47) and PI (rs = 0.52); anxiety with global OHIP (rs = 0.58), OA (rs = 0.50) and PI (rs = 0.63). In the PT group: depression with global OHIP (rs = 0.48) and PI (rs = 0.51); anxiety with global OHIP (rs = 0.59), OP (rs = 0.41), OA (rs = 0.47) and PI (rs = 0.65). In the CT group: depression with global OHIP (rs = 0.49) and PI (rs = 0.52); anxiety with global OHIP (rs = 0.58), OA (rs = 0.44) and PI (rs = 0.65). Within‐measure correlations showed moderate‐to‐strong associations across all TMD subtypes. In the IT group: total OBC with WN (rs = 0.82), WF (rs = 0.69) and SA (rs = 0.63); depression with anxiety (rs = 0.71); global OHIP with OA (rs = 0.82), PI (rs = 0.95), OF (rs = 0.80) and OP (rs = 0.70). In the PT group: total OBC with WN (rs = 0.82), WF (rs = 0.64) and SA (rs = 0.52); depression with anxiety (rs = 0.75); global OHIP with OA (rs = 0.80), PI (rs = 0.95), OF (rs = 0.78) and OP (rs = 0.72). In the CT group: total OBC with WN (rs = 0.81), WF (rs = 0.65) and SA (rs = 0.58); depression with anxiety (rs = 0.74); global OHIP with OA (rs = 0.79), PI (rs = 0.94), OF (rs = 0.71) and OP (rs = 0.64).
TABLE 4.
Correlations between oral behaviours, psychological and OHRQoL variables.
| Variable | TO | SA | WN | WF | PD | PA | GO | OF | OP | OA |
|---|---|---|---|---|---|---|---|---|---|---|
| Intra‐articular TMD | ||||||||||
| TO | — | 0.63 *** | 0.82 *** | 0.69 *** | 0.26*** | 0.25*** | 0.32*** | 0.22*** | 0.25*** | 0.30*** |
| SA | 0.63 *** | — | 0.46 *** | 0.29*** | 0.10 | 0.09 | 0.17** | 0.14* | 0.11* | 0.19*** |
| WN | 0.82 *** | 0.46 *** | — | 0.36*** | 0.23*** | 0.25*** | 0.34*** | 0.23*** | 0.27*** | 0.32*** |
| WF | 0.69 *** | 0.29*** | 0.36*** | — | 0.20*** | 0.15** | 0.20*** | 0.13* | 0.13* | 0.19*** |
| PD | 0.26*** | 0.10 | 0.23*** | 0.20*** | — | 0.71 *** | 0.47 *** | 0.28*** | 0.27*** | 0.38*** |
| PA | 0.25*** | 0.09 | 0.25*** | 0.15** | 0.71 *** | — | 0.58 *** | 0.36*** | 0.29*** | 0.50 *** |
| GO | 0.32*** | 0.17** | 0.34*** | 0.20*** | 0.47 *** | 0.58 *** | — | 0.80 *** | 0.70 *** | 0.82 *** |
| OF | 0.22*** | 0.14* | 0.23*** | 0.13* | 0.28*** | 0.36*** | 0.80 *** | — | 0.57 *** | 0.55 *** |
| OP | 0.25*** | 0.11* | 0.27*** | 0.13* | 0.27*** | 0.29*** | 0.70 *** | 0.57 *** | — | 0.44 *** |
| OA | 0.30*** | 0.19*** | 0.32*** | 0.19*** | 0.38*** | 0.50 *** | 0.82 *** | 0.55 *** | 0.44 *** | — |
| PI | 0.32*** | 0.16** | 0.33*** | 0.20*** | 0.52 *** | 0.63 *** | 0.95 *** | 0.63 *** | 0.57 *** | 0.78 *** |
| Pain‐related TMD | ||||||||||
| TO | — | 0.52 *** | 0.82 *** | 0.64 *** | 0.33*** | 0.25*** | 0.25*** | 0.16* | 0.26*** | 0.24*** |
| SA | 0.52 *** | — | 0.33*** | 0.18** | 0.23** | 0.13 | 0.09 | 0.06 | 0.14 | 0.09 |
| WN | 0.82 *** | 0.33*** | — | 0.29*** | 0.25*** | 0.29*** | 0.24*** | 0.11 | 0.26*** | 0.25*** |
| WF | 0.64 *** | 0.18** | 0.29*** | — | 0.21** | 0.10 | 0.19** | 0.15* | 0.20** | 0.15* |
| PD | 0.33*** | 0.23** | 0.25*** | 0.21** | — | 0.75 *** | 0.48 *** | 0.25*** | 0.38*** | 0.33*** |
| PA | 0.25*** | 0.13 | 0.29*** | 0.10 | 0.75 *** | — | 0.59 *** | 0.30*** | 0.41 *** | 0.47 *** |
| GO | 0.25*** | 0.09 | 0.24*** | 0.19** | 0.48 *** | 0.59 *** | — | 0.78 *** | 0.72 *** | 0.80 *** |
| OF | 0.16* | 0.06 | 0.11 | 0.15* | 0.25*** | 0.30*** | 0.78 *** | — | 0.52 *** | 0.53 *** |
| OP | 0.26*** | 0.14 | 0.26*** | 0.20** | 0.38*** | 0.41 *** | 0.72 *** | 0.52 *** | — | 0.46 *** |
| OA | 0.24*** | 0.09 | 0.25*** | 0.15* | 0.33*** | 0.47 *** | 0.80 *** | 0.53 *** | 0.46 *** | — |
| PI | 0.22** | 0.09 | 0.24*** | 0.17* | 0.51 *** | 0.65 *** | 0.95 *** | 0.61 *** | 0.60 *** | 0.77 *** |
| Combined TMD | ||||||||||
| TO | — | 0.58 *** | 0.81 *** | 0.65 *** | 0.27*** | 0.23*** | 0.23*** | 0.13** | 0.17*** | 0.22*** |
| SA | 0.58 *** | — | 0.43 *** | 0.21*** | 0.18*** | 0.15** | 0.19*** | 0.04 | 0.19*** | 0.18*** |
| WN | 0.81 *** | 0.43 *** | — | 0.27*** | 0.28*** | 0.25*** | 0.32*** | 0.16** | 0.23*** | 0.28*** |
| WF | 0.65 *** | 0.21*** | 0.27*** | — | 0.12* | 0.09 | 0.00 | 0.03 | 0.03 | 0.06 |
| PD | 0.27*** | 0.18*** | 0.28*** | 0.12* | — | 0.74 *** | 0.49 *** | 0.22*** | 0.29*** | 0.34*** |
| PA | 0.23*** | 0.15** | 0.25*** | 0.09 | 0.74 *** | — | 0.58 *** | 0.25*** | 0.29*** | 0.44 *** |
| GO | 0.23*** | 0.19*** | 0.32*** | 0.00 | 0.49 *** | 0.58 *** | — | 0.71 *** | 0.64 *** | 0.79 *** |
| OF | 0.13** | 0.04 | 0.16** | 0.03 | 0.22*** | 0.25*** | 0.71 *** | — | 0.49 *** | 0.48 *** |
| OP | 0.17*** | 0.19*** | 0.23*** | 0.03 | 0.29*** | 0.29*** | 0.64 *** | 0.49 *** | — | 0.41 *** |
| OA | 0.22*** | 0.18*** | 0.28*** | 0.06 | 0.34*** | 0.44 *** | 0.79 *** | 0.48 *** | 0.41 *** | — |
| PI | 0.23*** | 0.19*** | 0.33*** | 0.00 | 0.52 *** | 0.65 *** | 0.94 *** | 0.50 *** | 0.46 *** | 0.74 *** |
Note: Results of Spearman's correlation with Benjamini–Hochberg Adjustment. Bold indicates correlation coefficient > 0.4.
Abbreviations: GO, Global OHIP score; OA, Oral appearance dimension score; OF, Oral function dimension score; OP, Orofacial pain dimension score; PA, Anxiety score (GAD‐7); PD, Depression score (PHQ‐9); PI, Psychosocial impact dimension score. SA, Sleeping‐state oral activity score; TO, Total OBC (jaw overuse behaviour) score; WF, Waking‐state functional oral activity score; WN, Waking‐state nonfunctional oral activity score.
p < 0.05.
p < 0.01.
p < 0.001.
TABLE 5.
Factors associated with high jaw overuse behaviour (JOB).
| Variables | Univariate | Multivariate | ||
|---|---|---|---|---|
| Odds ratio (95% CI) | p* | Odds ratio (95% CI) | p^ | |
| Sex | ||||
| Male | Reference | Reference | ||
| Female | 1.67 (1.22–2.31) | 0.002 | 1.40 (0.98–1.99) | 0.063 |
| Age | 0.95 (0.93–0.96) | < 0.001 | 0.95 (0.93–0.96) | < 0.001 |
| Education | ||||
| Primary/Secondary | Reference | Reference | ||
| College/University | 2.84 (1.95–4.20) | < 0.001 | 2.01 (1.29–3.18) | 0.002 |
| Graduate School | 3.38 (2.08–5.54) | < 0.001 | 2.59 (1.49–4.53) | < 0.001 |
| TMD subtypes | ||||
| Intra‐articular | Reference | Reference | ||
| Pain‐related | 1.07 (0.76–1.51) | 0.702 | 0.91 (0.60–1.39) | 0.671 |
| Combined | 1.24 (0.93–1.65) | 0.136 | 0.92 (0.64–1.31) | 0.648 |
| Depression | 1.11 (1.08–1.15) | < 0.001 | 1.07 (1.02–1.12) | 0.005 |
| Anxiety | 1.09 (1.06–1.13) | < 0.001 | 1.00 (0.95–1.05) | 0.996 |
| OHRQoL dimensions | ||||
| Oral function | 1.06 (1.03–1.09) | < 0.001 | 0.99 (0.95–1.04) | 0.666 |
| Orofacial pain | 1.11 (1.07–1.15) | < 0.001 | 1.06 (0.99–1.13) | 0.076 |
| Orofacial appearance | 1.23 (1.16–1.31) | < 0.001 | 1.07 (0.97–1.19) | 0.171 |
| Psychosocial impact | 1.05 (1.03–1.06) | < 0.001 | 1.02 (0.99–1.05) | 0.164 |
Note: Results of *univariate and ^multivariate logistic regression analyses. Bold indicates p < 0.05.
TABLE 6.
Factors associated with low OHRQoL.
| Variables | Univariate | Multivariate | ||
|---|---|---|---|---|
| Odds ratio (95% CI) | p* | Odds ratio (95% CI) | p^ | |
| Sex | ||||
| Male | Reference | Reference | ||
| Female | 2.03 (1.47–2.82) | < 0.001 | 1.67 (1.12–2.53) | 0.013 |
| Age | 1.02 (1.00–1.03) | 0.010 | 1.03 (1.01–1.05) | < 0.001 |
| Education | ||||
| Primary/Secondary | Reference | Reference | ||
| College/University | 0.70 (0.49–1.01) | 0.058 | 0.78 (0.47–1.29) | 0.326 |
| Graduate School | 0.48 (0.30–0.77) | 0.002 | 0.51 (0.27–0.96) | 0.036 |
| TMD subtypes | ||||
| Intra‐articular | Reference | Reference | ||
| Pain‐related | 3.26 (2.29–4.67) | < 0.001 | 2.49 (1.62–3.85) | < 0.001 |
| Combined | 4.18 (3.10–5.67) | < 0.001 | 3.60 (2.53–5.16) | < 0.001 |
| Jaw overuse behaviour | ||||
| No | Reference | Reference | ||
| Low | 1.65 (1.13–2.42) | 0.010 | 1.30 (0.74–2.30) | 0.371 |
| High | 2.72 (1.92–3.87) | < 0.001 | 0.88 (0.40–1.92) | 0.742 |
| Sleeping‐state oral activities | 1.10 (1.04–1.17) | 0.001 | 1.01 (0.92–1.11) | 0.829 |
| Waking‐state nonfunctional oral activities | 1.15 (1.11–1.19) | < 0.001 | 1.16 (1.09–1.23) | < 0.001 |
| Waking‐state functional activities | 1.04 (1.00–1.09) | 0.040 | 1.02 (0.95–1.08) | 0.643 |
| Depression | 1.26 (1.21–1.31) | < 0.001 | 1.05 (1.00–1.11) | 0.055 |
| Anxiety | 1.38 (1.32–1.46) | < 0.001 | 1.29 (1.21–1.38) | < 0.001 |
Note: Results of *univariate and ^multivariate logistic regression analyses. Bold indicates p < 0.05.
In univariate analyses, high JOB was significantly associated with female sex, younger age, higher education level, elevated depression and anxiety and greater impairment across oral function, all OHRQoL dimensions. In the corresponding multivariate model, significant variables linked to high JOB included younger age (OR = 0.95, 95% CI = 0.93–0.96), college/university education (OR = 2.01, 95% CI = 1.29–3.18), graduate education (OR = 2.59, 95% CI = 1.49–4.53) and higher depression (OR = 1.07, 95% CI = 1.02–1.12). For low OHRQoL, univariate analyses identified significant associations with female sex, older age, lower education level, PT and CT subtypes, JOB levels, as well as higher depression and anxiety. In the multivariate model, variables significantly linked to low OHRQoL included female sex (OR = 1.67, 95% CI = 1.12–2.53), older age (OR = 1.03, 95% CI = 1.01–1.05), graduate education (OR = 0.51, 95% CI = 0.27–0.96), PT (OR = 2.49, 95% CI = 1.62–3.85), CT (OR = 3.60, 95% CI = 2.53–5.16), WN (OR = 1.16, 95% CI = 1.09–1.23) and higher anxiety (OR = 1.29, 95% CI = 1.21–1.38).
4. Discussion
This study examined oral behaviours across TMD subtypes and their relationships with psychological distress and four‐dimensional impacts on OHRQoL. It also identified biopsychosocial factors associated with high JOB and low OHRQoL. The first and second hypotheses were confirmed: PT and CT showed higher oral behaviour scores and greater psychological distress than IT, with WN also demonstrating the strongest and most consistent correlations with impaired OHRQoL across all dimensions. The third hypothesis was partly supported: age and education were linked to high JOB and low OHRQoL, whereas depression and anxiety showed more differentiated patterns of associations. Although demographic and subtype distributions were consistent with earlier East Asian TMD research, the elevated rate of high JOB compared to Korean cohorts (52.0% vs. 15.1%) highlights cultural heterogeneity across East Asian TMD populations [6, 26]. The parallel analyses included comparative, correlational and regression‐based procedures, each designed to capture complementary aspects of the varied outcomes.
4.1. Comparative Analyses
Distinct biopsychosocial and behavioural profiles emerged across TMD subtypes and JOB levels. CT had the highest proportion of females, while PT was the oldest. Both PT and CT also showed elevated WN, depression and anxiety relative to IT, alongside significantly lower overall OHRQoL and greater impairment across all four dimensions. These patterns likely reflect biological and psychosocial mechanisms influencing TMD expression across sex and age [39]. Female predominance in CT aligns with oestrogen‐mediated amplification of inflammatory responses and central sensitisation, which increase vulnerability to degenerative joint changes and intensify pain symptoms [40, 41, 42]. The older age profile in PT may stem from cumulative biomechanical strain, neuroplastic changes that sustain pain persistence and age‐related alterations in systemic health and social context [42, 43]. Elevated psychological distress and maladaptive coping behaviours, both commonly associated with chronic pain, in PT and CT may further exacerbate symptom burden and compromise OHRQoL [22, 27, 42, 44].
Female predominance increased and age decreased with greater JOB severity, and higher educational attainment was more prevalent in the HO group. Depression and anxiety levels were highest in the HO group, followed by the LO group, with the NO group showing the lowest scores. Moreover, the HO group exhibited significantly lower overall OHRQoL and greater impairments across all four dimensions compared to both the LO and NO groups. The findings suggest that individuals with high JOB are typically younger, well‐educated women who experience elevated psychological distress and markedly poorer OHRQoL. Several mechanisms may contribute to these patterns: younger, educated females may be more susceptible to stress‐related oral behaviours as coping responses; the physical discomfort associated with these behaviours may reinforce emotional distress through a biobehavioural feedback loop and heightened symptom awareness may amplify perceived impairment [45, 46].
For all TMD subtypes, normalised OF, OP, OA and PI dimension scores showed increasing trends with greater JOB severity. In the IT group, all five dimensions differed significantly across JOB levels, while in the PT and CT groups, OP, OA and PI were significantly elevated in the HO group. The lack of OF differences in PT and CT points to a weaker association with oral behaviours, as pain mechanisms and central sensitisation may contribute more substantially to functional impairment. t [26, 42]. Across JOB levels and TMD subtypes, OA and OF consistently emerged as the most impaired OHIP dimensions, underscoring the role of aesthetic and functional deficits in shaping OHRQoL in TMD patients. OA also featured prominently in nonclinical populations, irrespective of TMD status and has been associated with malocclusion, which in some studies has been linked to reduced OHRQoL [25, 47]. Individuals with Angle Class II and III malocclusions, deep bite and crossbite have likewise been reported to show higher frequencies of TMD symptoms, though these reflect associations rather than causal relationships [48]. Dimensional hierarchies across JOB levels remained stable for IT and PT. In contrast, a hierarchy shift was observed in CT, where the NO group mirrored PT's pattern (OA > OF > OP > PI), but elevated PI scores in the LO and HO groups altered the order to OA > OF > PI > OP. This shift may reflect compounded psychosocial burden from coexisting TMD pain and TMJ dysfunction. Although statistically significant differences were observed, several dimension score differences were numerically small relative to their theoretical ranges. Given the large sample size, caution is warranted in interpreting these findings, as some differences (notably in OF and OP) are more likely to be clinically meaningful, whereas others (such as PI and normalised scores) appear modest.
4.2. Correlation Analyses
Cross‐measure correlations revealed moderate associations between psychological distress and OHRQoL, with patterns varying across TMD subtypes. Depression was consistently associated with overall OHRQoL and PI, whereas anxiety showed broader associations across multiple OHIP dimensions. Oral behaviours were significantly but weakly correlated with psychological distress and OHRQoL, indicating a modest relationship that may reflect behavioural adaptations to pain or psychosocial burden rather than direct mechanistic pathways. Clinically, these findings underscore the importance of identifying and managing depression and anxiety to improve the OHRQoL of TMD patients. In addition to conventional therapies, psychological interventions such as cognitive‐behavioural therapy, stress management training and mindfulness‐based approaches may help alleviate emotional distress and enhance coping, thereby supporting more personalised and patient‐centric care [49].
Within‐measure correlations revealed strong internal coherence among OBC subscales and OHIP‐TMD dimensions. Across all TMD subtypes, WN showed the strongest association with total OBC scores, while PI was most strongly linked to global OHIP scores. These findings highlight WN and PI as the principal contributors to oral behaviour frequency and perceived oral health burden. Targeting WN through habit awareness, biofeedback and behavioural retraining, alongside mitigating PI via tailored psychological interventions, should thus be prioritised as part of comprehensive TMD management. The PHQ‐9 and GAD‐7 are components of the Patient Health Questionnaire suite, derived from the Primary Care Evaluation of Mental Disorders (PRIME‐MD) [50]. Their moderate‐to‐strong correlations are well documented and correspond to their frequent comorbidity, which has been attributed to shared negative affectivity, exposure to stressful life events, disruptions in cognitive processing and a common biological or genetic predisposition [26, 27, 51].
4.3. Regression Analyses
Following multivariate modelling, high JOB was significantly associated with age, education and depression, while low OHRQoL was linked to sex, age, education, TMD subtypes, WN and anxiety. Most effects were small, except for college/university education (OR = 2.01) and graduate education (OR = 2.59) in relation to high JOB, and for female sex (OR = 1.67), PT (OR = 2.49), CT (OR = 3.60) and graduate education (OR = 0.51) in relation to low OHRQoL, where medium‐to‐large effects were observed. The results indicate a complex interplay between oral behaviours, sociodemographic characteristics, psychological distress and TMD pain. Education, in particular, functioned as a double‐edged factor, associated with increased oral behaviour frequency yet protective against perceived oral health burden. This pattern may reflect differences in coping strategies, symptom awareness and engagement with health resources. Individuals with higher education may be more attuned to stress‐related oral behaviours while also possessing greater resilience and access to care that helps mitigate OHRQoL deterioration. The association between female sex and TMD pain with reduced OHRQoL is consistent with existing literature, which highlights sex, pain intensity and pain‐related interference as key correlates of impaired OHRQoL [21, 22, 52].
Collectively, findings from the parallel analyses underscore the importance of systematically screening oral behaviours and psychological distress to enhance clinical decision‐making, support risk stratification and guide personalised patient education, self‐care and comprehensive TMD management. This includes psychological and behavioural interventions designed to alleviate orofacial pain and psychosocial impact, while promoting oral function, coping capacity and overall well‐being. Potential feedback loops among oral behaviours, pain and distress may sustain symptom burden, and neurobiological mechanisms, such as central sensitisation, hypothalamic–pituitary–adrenal (HPA) axis dysregulation and oestrogen‐mediated inflammatory responses, may further complicate clinical trajectories, reinforcing the need for focused, longitudinal investigations [40, 42, 45].
4.4. Study Limitations
This study has several strengths, including a large and well‐powered sample, use of validated diagnostic protocols and measures, adoption of the four‐dimensional OHIP framework, and subtype‐stratified and parallel analyses. That said, it is not without limitations. First, the cross‐sectional design precludes causal inference, as temporal relationships among oral behaviours, psychological distress and OHRQoL cannot be established. Accordingly, interpretations implying causal directions have been avoided. While the observed associations provide clinically meaningful insights, longitudinal studies remain essential to clarify directionality, monitor changes over time and identify underlying mechanisms. Second, the participants were drawn from a single tertiary centre and were exclusively Chinese, which may result in selection bias and constrain the generalisability of the findings to other clinical contexts and racial groups. Third, the predominance of female TMD patients may affect the broader applicability of the results, as sex‐related differences in TMD prevalence, pain perception, psychological distress and OHRQoL have been documented [53]. This imbalance should be taken into account when interpreting the study outcomes. Fourth, reliance on self‐reported measures may introduce information bias, including recall inaccuracies and socially desirable response tendencies. In particular, the evaluation of oral activities during sleep and wakefulness was based solely on subjective appraisal, as objective techniques such as electromyographic recordings and ecological momentary assessment were not employed [18]. Fifth, dichotomising OHRQoL at the median may oversimplify the construct and reduce both analytical sensitivity and statistical power. This approach was adopted due to the absence of universally accepted thresholds for low OHRQoL with the OHIP‐TMD. Finally, unexamined confounding variables, including sleep quality, stress levels, lifestyle habits, malocclusion, stimulant use, comorbid oral conditions and pain duration, may have influenced the observed associations. Their omission reduces the model's ability to isolate the specific effects of each variable. Future studies should employ longitudinal, multi‐centre designs, incorporate diverse populations and integrate objective behavioural assessments to elucidate causal pathways, strengthen generalisability and account for additional key confounders.
5. Conclusion
This study demonstrates that oral behaviours, particularly WN, are significantly associated with psychological distress and multidimensional impairment in OHRQoL among patients with TMDs. PT and CT subtypes showed higher WN frequencies and greater psychological distress than IT, though these differences were small and largely within nonclinical ranges. High JOB was linked to younger age, higher education and elevated depression, whereas lower OHRQoL was associated with female sex, older age, painful TMDs, WN and anxiety. OA and OF consistently emerged as the most affected dimensions, with psychosocial burden more evident in CT subtypes. Overall, the findings highlight the relevance of oral behaviours and psychological screening in comprehensive TMD management, while underscoring that observed differences should be interpreted in light of their magnitude and clinical significance. Incorporating psychosocial‐behavioural assessments into routine care may enhance risk stratification, guide personalised education and inform targeted interventions. Longitudinal studies are needed to clarify causal pathways and optimise patient‐centred care approaches.
Author Contributions
Adrian Ujin Yap contributed to conceptualisation, methodology, visualisation, formal analysis, validation, resources, project administration and writing – original draft. Chen Li contributed to methodology, investigation, data curation, formal analysis, validation, software, resources and writing – review and editing. Hongyu Ming contributed to investigation, data curation, resources and writing – review and editing. Yunhao Zheng contributed to investigation, data curation, resources and writing – review and editing. Chenlu Liu contributed to methodology, investigation, data curation, formal analysis, validation, resources, project administration, funding acquisition and writing – review and editing. Jun Wang contributed to methodology, investigation, data curation, formal analysis, validation, resources, project administration, funding acquisition and writing – review and editing. Xin Xiong contributed to methodology, investigation, data curation, formal analysis, validation, resources, project administration, funding acquisition and writing – review and editing.
Funding
This work was supported by the National Natural Science Foundation of China (82301129), Science and Technology Project of Sichuan Province (2023NSFSC0556), Natural Science Foundation of Sichuan Province of China—Youth Fund Project (2025ZNSFSC1586) and the Clinical Research Project of West China Hospital of Stomatology, Sichuan University (LCYJ‐2023‐YY‐2).
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
The authors sincerely thank all patients who participated in this study.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.