Abstract
Purpose
To identify latent profiles of oral health self-management among adolescents undergoing fixed orthodontic treatment and examine the factors associated with profile membership.
Patients and Methods
A cross-sectional study was conducted among 395 adolescents aged 12–18 years undergoing fixed orthodontic treatment. Latent profile analysis was performed using the knowledge, beliefs, behaviors, and environment dimensions of oral health self-management as continuous observed indicators. Multinomial logistic regression was used to examine the associations of e-health literacy, family care, self-efficacy, dental anxiety, and age with profile membership.
Results
Three latent profiles were identified: the behavior–environment vulnerable profile (C1, 20.00%), the moderate and stable profile (C2, 50.38%), and the high and balanced profile (C3, 29.62%). Compared with the behavior–environment vulnerable profile, higher family care was associated with greater odds of belonging to the moderate and stable profile, whereas older age was associated with lower odds of belonging to this profile. Higher e-health literacy, family care, and self-efficacy were associated with greater odds of belonging to the high and balanced profile. Higher dental anxiety and older age were associated with lower odds of belonging to this profile.
Conclusion
Oral health self-management among adolescents undergoing fixed orthodontic treatment showed meaningful heterogeneity. The identified profiles and associated factors may help clinicians recognize differences in adolescents’ self-management needs and inform the future development of profile-informed oral health education and follow-up support.
Keywords: e-health literacy, self-efficacy, dental anxiety, family care, person-centered analysis
Introduction
Fixed orthodontic treatment is an important approach for improving dental alignment and re-establishing functional occlusal relationships.1 With increasing awareness of oral health and growing demand for orthodontic care, more adolescents are undergoing fixed orthodontic treatment. However, orthodontic treatment usually lasts for two to three years, during which adolescents must maintain good oral hygiene and treatment adherence.2,3 In addition, the brackets, archwires, and other components of fixed appliances can promote food impaction and plaque retention, making oral cleaning more difficult.4 Inadequate oral hygiene and poor adherence during treatment may increase the risk of gingivitis, enamel demineralization, dental caries, and white spot lesions and may also compromise treatment efficiency and outcomes.5,6 Therefore, effective oral health self-management is particularly important for adolescents receiving fixed orthodontic treatment.
Oral health self-management among adolescents undergoing fixed orthodontic treatment is not a simple process determined solely by knowledge. Effective self-management requires adolescents not only to understand what they should do, but also to translate oral health information into daily practices, sustain confidence in coping with treatment-related challenges, and obtain appropriate support from family members.7 In this sense, self-management represents a multidimensional process involving information processing, behavioral implementation, environmental support, and psychological regulation. Previous studies have also shown that adolescents may understand oral health recommendations yet experience difficulties in maintaining daily oral care, applying health information, sustaining motivation, or obtaining adequate support.8,9 Knowledge, positive beliefs, and actual practices therefore do not necessarily develop at the same level. As adolescence is an important developmental period for the formation of health behaviors and increasing personal responsibility, examining these dimensions together may provide a more complete understanding of how adolescents manage their oral health during orthodontic treatment.10
Social Cognitive Theory (SCT) was used as an organizing framework for selecting and interpreting the factors associated with oral health self-management. SCT emphasizes that individual behavior develops through the continuous interaction of personal, environmental, and behavioral factors.11 Within this framework, e-health literacy can be conceptualized as a personal cognitive resource that supports the acquisition, evaluation, and application of digital health information, although it is not an original construct of SCT.12 Self-efficacy, a central construct of SCT, reflects adolescents’ confidence in their ability to perform and sustain oral health-related behaviors.13 Dental anxiety was conceptualized as an affective personal factor related to engagement with dental care,14 whereas family care, reflecting perceived family functioning, was positioned as an environmental support factor.15 These variables were therefore selected as theory-informed correlates of oral health self-management rather than as predetermined causal factors.
Previous studies of oral health self-management among adolescents undergoing fixed orthodontic treatment have predominantly used variable-centered approaches, such as total-score comparisons, correlation analysis, and regression analysis.8,9,16 These methods are valuable for estimating average relationships between variables, but they generally treat the study population as relatively homogeneous. Consequently, they may fail to identify adolescents who have similar overall self-management scores but markedly different configurations across knowledge, beliefs, behaviors, and environmental support.
Latent profile analysis (LPA) is a person-centered statistical method that can identify unobserved subgroups within a sample based on multiple continuous observed indicators.17,18 Compared with variable-centered analysis, this approach can reveal whether distinct configurations of oral health self-management exist within the same population and can provide a basis for identifying adolescents with different support needs. Although person-centered methods have been applied to self-management and other patient-reported outcomes in different populations, to the best of our knowledge, no published study has used this method to examine oral health self-management profiles among adolescents undergoing fixed orthodontic treatment.19,20 This represents an important gap because this population faces prolonged treatment demands and substantial variation in its capacity to maintain daily oral health behaviors.Identifying such profiles may help clarify heterogeneity in this population and provide a basis for recognizing adolescents with different patterns of self-management and support needs.
Accordingly, this study aimed to: (1) identify latent profiles of oral health self-management among adolescents undergoing fixed orthodontic treatment based on the dimensions of knowledge, beliefs, behaviors, and environment; and (2) examine the associations of e-health literacy, self-efficacy, dental anxiety, and family care with latent profile membership. Because previous profile-based evidence in this specific population was unavailable, the identification and enumeration of latent profiles were exploratory. Guided by SCT and previous empirical evidence, we expected that higher e-health literacy, stronger self-efficacy, greater family care, and lower dental anxiety would be associated with membership in profiles characterized by more favorable oral health self-management.
Material and Methods
Participants
This cross-sectional study used convenience sampling to recruit adolescent patients who were undergoing fixed orthodontic treatment in the Department of Orthodontics at a tertiary stomatological hospital in Yunnan Province, China, from January to April 2026.The inclusion criteria were as follows: (1) aged 12–18 years; (2) had received fixed orthodontic treatment for at least 3 months; (3) were able to read and complete the questionnaire independently; and (4) had obtained informed consent from their legal guardians. The exclusion criteria were as follows: (1) having major systemic diseases or psychological disorders; (2) undergoing other concurrent dental treatments, such as implant therapy or prosthodontic treatment; and (3) having hearing, speech, or communication impairments.
Sample Size
The initial sample size was estimated using the following single-population proportion formula for a cross-sectional survey: 
,21 where n represents the required sample size, Z1-α/2 represents the standard normal value corresponding to the specified type I error, P represents the anticipated population proportion, and δ represents the allowable error. In the present study, α was set at 0.05, corresponding to Z1-α/2 = 1.96; P was set at 0.50; and δ was set at 0.05. The value of P was set at 0.50 because it produces the maximum variance and therefore provides the most conservative sample size estimate when the anticipated population proportion is unknown. The sample size was calculated as follows: 
. After rounding up, the minimum required sample size was 385 participants.
For latent profile analysis, there is no universally applicable formula or fixed minimum sample size. The required sample size depends on several characteristics, including the number of indicators and profiles, the relative size of each profile, the degree of separation between profiles, and the model specification.22 Methodological guidance suggests that approximately 300 or more participants is generally desirable for applied latent class or profile analyses, although smaller samples may be adequate for simpler models with well-separated profiles.23 The final sample comprised 395 adolescents, exceeding both the minimum sample size estimated for the cross-sectional survey and the practical sample size recommendation for latent profile analysis.
Measures
Sociodemographic Questionnaire
A self-designed sociodemographic questionnaire was used to collect participants’ demographic and clinical information, including sex, age, grade, monthly household income, highest parental educational level, and travel time to the clinic.
e-Health Literacy Scale
The e-Health Literacy Scale (eHEALS) was developed by Norman and Skinner and subsequently translated and adapted into Chinese by Guo et al.24,25 The scale consists of 8 items across three dimensions: the ability to use, evaluate, and make decisions based on online health information and services. Each item is rated on a 5-point Likert scale, ranging from 1 = “strongly disagree” to 5 = “strongly agree,” with total scores ranging from 8 to 40. Higher scores indicate higher levels of e-health literacy. In the present study, Cronbach’s α for this scale was 0.879.
Family Adaptation, Partnership, Growth, Affection, Resolve Index
The Family Adaptation, Partnership, Growth, Affection, and Resolve Index (Family APGAR Index) was originally developed by Smilkstein and subsequently translated into Chinese by Lü et al.26,27 It assesses five dimensions of family function: adaptation, partnership, growth, affection, and resolve. The scale uses a 3-point Likert scoring method, with responses scored from 0 to 2, representing “hardly ever,” “some of the time,” and “almost always,” respectively. The total score ranges from 0 to 10, with scores of 7–10, 4–6, and 0–3 indicating good family function, moderate family dysfunction, and severe family dysfunction, respectively. Higher scores indicate better family function. In the present study, Cronbach’s α for this scale was 0.848.
General Self-Efficacy Scale
The General Self-Efficacy Scale (GSES) was developed by Schwarzer et al in 1999.28 This study used the Chinese version translated and validated by Wang et al.29 The Chinese version of the GSES contains 10 items, with total scores ranging from 10 to 40. Scores below 20 indicate low self-efficacy, scores of 20–30 indicate moderate self-efficacy, and scores of 31–40 indicate high self-efficacy. Higher scores indicate stronger self-efficacy. In the present study, Cronbach’s α for this scale was 0.896.
Modified Dental Anxiety Scale
The Modified Dental Anxiety Scale (MDAS) was developed by Humphris et al.30 It contains 5 items, each with five response options: not anxious = 1, slightly anxious = 2, anxious = 3, very anxious = 4, and extremely anxious = 5. The total score ranges from 5 to 25, with higher scores indicating higher levels of dental anxiety. In the present study, Cronbach’s α for this scale was 0.688, indicating marginal internal consistency. The MDAS was retained because it was the prespecified instrument used to assess dental anxiety; however, findings involving dental anxiety were interpreted cautiously.
Oral Health Self-Management Ability Questionnaire for Adolescent Patients with Fixed Orthodontic Appliances
The Oral Health Self-Management Ability Questionnaire for adolescent patients with fixed orthodontic appliances was developed by Liu et al.7 The questionnaire evaluates self-management ability in four dimensions: knowledge, beliefs, behaviors, and environment. The full version contains 50 items and uses a 5-point Likert scoring method.For the knowledge dimension, response options range from 1 = “do not understand at all” to 5 = “understand very well.” For the belief dimension, response options range from 1 = “strongly disagree” to 5 = “strongly agree.” For the behavior and environment dimensions, response options range from 1 = “never” to 5 = “always.” Higher scores indicate better oral health self-management ability. In the present study, Cronbach’s α was 0.932 for the total scale and 0.907, 0.769, 0.805, and 0.649 for the knowledge, belief, behavior, and environment dimensions, respectively.The environment dimension showed modest internal consistency. Nevertheless, it was retained because it represents a predefined and theoretically relevant component of the original instrument and captures the environmental support conditions under which adolescents perform oral health self-management. Results involving this dimension and the latent profiles derived from it were therefore interpreted cautiously.
Data Collection
Data were collected on site by uniformly trained research assistants. During the patients’ follow-up visits, the research assistants explained the purpose and significance of the study to eligible participants. After informed consent had been obtained, participants completed either an electronic or paper-based questionnaire independently. A total of 395 valid questionnaires were collected.
Statistical Analysis
Data were analyzed using IBM SPSS Statistics version 22.0 and R version 4.4.1. Descriptive statistics were first performed for sociodemographic characteristics and key study variables. Continuous variables were expressed as means and standard deviations, whereas categorical variables were presented as frequencies and percentages.
Latent profile analysis was conducted using the mean scores of the knowledge, belief, behavior, and environment dimensions as continuous observed indicators. These four indicators were selected because they correspond to the predefined multidimensional structure of the Oral Health Self-Management Ability Questionnaire and represent distinct but related components of self-management, including cognitive understanding, health-related beliefs, behavioral implementation, and environmental support. Using the four dimension scores rather than the 50 individual items also provided a more parsimonious model and allowed the analysis to focus on clinically interpretable patterns across the major domains of oral health self-management.
Models containing one to five profiles were estimated. The primary models specified equal indicator variances across profiles and zero within-profile covariances. Model selection was based on an integrated evaluation of statistical fit, classification precision, profile size, parsimony, and substantive interpretability.17
The Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted Bayesian information criterion (aBIC) were used to assess relative model fit, with lower values indicating better fit. The Lo–Mendell–Rubin likelihood ratio test (LMR) and bootstrap likelihood ratio test (BLRT) were used to compare models with K and K − 1 profiles, with a statistically significant P value indicating that the K-profile model provided a better fit.
Entropy was used to assess classification precision, with values closer to 1 indicating clearer classification. An entropy value of approximately 0.80 or higher was considered a practical indicator of good classification quality. The absolute number and relative proportion of participants in each profile were also examined, with approximately 50 participants per profile used as a practical reference. In addition, competing solutions were evaluated to determine whether the addition of a profile yielded a substantively distinct and clinically interpretable pattern rather than merely subdividing an existing profile into adjacent levels. The final profile solution was retained after balancing all statistical and substantive criteria.
After the optimal latent profile solution was determined, sociodemographic characteristics and key variables were compared across the identified profiles. Categorical variables were compared using the chi-square test, and continuous variables were compared using one-way analysis of variance.
Variables showing statistically significant differences in the univariate analyses were considered for inclusion in the multinomial logistic regression model. Before model estimation, the association between age and grade was examined using Spearman’s rank correlation to assess potential redundancy between these two indicators of developmental stage. Because age and grade were strongly correlated, grade was excluded from the multivariable model to reduce potential multicollinearity and improve model parsimony. Age was retained as a continuous covariate because it preserved more individual-level information and required fewer model parameters.Multinomial logistic regression was subsequently performed with latent profile membership as the dependent variable and e-health literacy, family care, self-efficacy, dental anxiety, and age as independent variables. The behavior–environment vulnerable profile (C1) was used as the reference category. The results are presented as odds ratios with 95% confidence intervals. A two-sided P value < 0.05 was considered statistically significant.
Ethical Considerations
This study was approved by the Medical Ethics Review Committee of the Affiliated Stomatological Hospital of Kunming Medical University (approval No. KYKQ2025MEC0153). All participants and their legal guardians voluntarily participated in the study after being fully informed of its purpose and procedures. The survey data were used only for scientific research, and participants’ privacy and personal information were strictly protected.
Results
Sociodemographic Characteristics and Main Variable Scores
A total of 400 questionnaires were distributed, and 395 valid questionnaires were returned, yielding an effective response rate of 98.75%. The final sample included 395 adolescents undergoing fixed orthodontic treatment. Participants were aged 12–18 years, with a mean age of 14.22 ± 1.64 years. The mean scores for e-health literacy, family care, self-efficacy, and dental anxiety were 31.58 ± 4.42, 8.20 ± 2.10, 26.07 ± 5.19, and 8.32 ± 2.63, respectively. The mean scores for the four dimensions of oral health self-management—knowledge, beliefs, behaviors, and environment—were 3.95 ± 0.52, 3.99 ± 0.44, 3.72 ± 0.56, and 3.93 ± 0.69, respectively. Detailed sociodemographic characteristics are presented in Table 1.
Table 1.
Univariate Analysis of Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment (n = 395)
| Variable | Category | Total, n (%) | C1 | C2 | C3 | χ2/F | P |
|---|---|---|---|---|---|---|---|
| Sex | Male | 121 (30.6) | 30 | 57 | 34 | 2.511 | 0.285 |
| Female | 274 (69.4) | 49 | 142 | 83 | |||
| Grade | Primary school | 24 (6.1) | 4 | 14 | 6 | 18.762 | 0.005 |
| Junior high school | 261 (66.1) | 40 | 131 | 90 | |||
| Senior high school | 98 (24.8) | 32 | 49 | 17 | |||
| College | 12 (3.0) | 3 | 5 | 4 | |||
| Highest parental educational level | Primary school or below | 16 (4.1) | 3 | 8 | 5 | 5.281 | 0.508 |
| Junior high school | 61 (15.4) | 9 | 30 | 22 | |||
| Senior high school or technical secondary school | 109 (27.6) | 18 | 62 | 29 | |||
| Junior college or bachelor’s degree or above | 209 (52.9) | 49 | 99 | 61 | |||
| Monthly household income, CNY | ≤3000 | 40 (10.1) | 4 | 20 | 16 | 4.874 | 0.301 |
| 3000–5000 | 224 (56.7) | 50 | 114 | 60 | |||
| >5000 | 131 (33.2) | 25 | 65 | 41 | |||
| Travel time to clinic | <15 min | 70 (17.7) | 14 | 30 | 26 | 7.528 | 0.275 |
| 16–30 min | 127 (32.2) | 30 | 62 | 35 | |||
| 31–60 min | 99 (25.1) | 22 | 53 | 24 | |||
| >60 min | 99 (25.1) | 13 | 54 | 32 | |||
| E-health literacy, mean ± SD | 29.62 ± 3.50 | 30.84 ± 4.17 | 34.15 ± 4.27 | 35.57 | <0.001 | ||
| Family care, mean ± SD | 7.10 ± 2.36 | 8.10 ± 2.08 | 9.09 ± 1.45 | 24.3 | <0.001 | ||
| Self-efficacy, mean ± SD | 23.72 ± 4.44 | 25.13 ± 4.56 | 29.27 ± 5.21 | 40.38 | <0.001 | ||
| Dental anxiety, mean ± SD | 8.85 ± 3.08 | 8.65 ± 2.55 | 7.39 ± 2.17 | 11.02 | <0.001 | ||
| Age, mean ± SD | 14.76 ± 1.63 | 14.13 ± 1.65 | 14.03 ± 1.57 | 5.57 | 0.004 | ||
Notes: C1, behavior–environment vulnerable profile; C2, moderate and stable profile; C3, high and balanced profile. Continuous variables were compared using one-way analysis of variance, and categorical variables were compared using the chi-square test.
Abbreviations: CNY, Chinese yuan; SD, standard deviation.
Latent Profile Analysis of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
Models containing one to five profiles were estimated, and the fit indices are presented in Table 2. Overall, the AIC and aBIC decreased as the number of profiles increased, whereas the BIC reached its lowest value in the four-profile model and increased in the five-profile model. The LMR and BLRT remained statistically significant across the competing models. Entropy was highest for the three-profile solution (0.812) and decreased to 0.784 and 0.723 for the four- and five-profile solutions, respectively.
Table 2.
Model Fit Indices for Latent Profile Analysis of Oral Health Self-Managemnet Among Adolescents Undergoing Fixed Orthodontic Treatment
| Model | AIC | BIC | aBIC | Entropy | LMR (P) | BLRT (P) | Class Probability |
|---|---|---|---|---|---|---|---|
| 1 | 2566 | 2597 | 2572 | — | — | — | — |
| 2 | 2033 | 2084 | 2043 | 0.810 | <0.001 | 0.0099 | 0.456 / 0.544 |
| 3a | 1857 | 1929 | 1871 | 0.812 | <0.001 | 0.0099 | 0.200 / 0.504 / 0.296 |
| 4 | 1810 | 1901 | 1828 | 0.784 | <0.001 | 0.0099 | 0.241 / 0.086 / 0.365 / 0.309 |
| 5 | 1795 | 1907 | 1818 | 0.723 | <0.001 | 0.0099 | 0.190 / 0.081 / 0.246 / 0.246 / 0.238 |
Notes: aThe three-profile solution was retained as the final model. Entropy is not applicable to the one-profile model.
Abbreviations: AIC, Akaike information criterion; aBIC, adjusted Bayesian information criterion; BIC, Bayesian information criterion; BLRT, bootstrap likelihood ratio test; LMR, Lo–Mendell–Rubin likelihood ratio test.
Although the four-profile solution showed better fit according to the information criteria, its smallest profile included only 34 participants (8.61%), compared with 79 participants (20.00%) in the three-profile solution. The relatively small profile raised concerns regarding the precision and stability of profile-specific estimates and the replicability of this subgroup in other samples. Substantive examination further showed that the additional profile mainly subdivided participants with adjacent moderate levels of oral health self-management and did not represent a clearly distinct pattern across the knowledge, belief, behavior, and environment dimensions. Considering classification precision, profile size, model parsimony, and substantive interpretability, the three-profile model was retained as the final solution.
Characteristics and Labeling of Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
The final three-profile solution showed distinct patterns across the knowledge, beliefs, behaviors, and environment dimensions. Based on the relative score levels and configurations of these dimensions, the profiles were labeled the behavior–environment vulnerable profile (C1), the moderate and stable profile (C2), and the high and balanced profile (C3).
C1 included 79 participants, accounting for 20.00% of the total sample. This profile showed a markedly uneven distribution across the four dimensions. In particular, the belief dimension scored relatively high, whereas the behavior and environment dimensions were notably lower, with mean scores below 3.5. These findings suggest that adolescents in this group may already possess some degree of oral health awareness and willingness to improve their behaviors, but still show clear deficiencies in behavioral implementation and external support. Therefore, this group was labeled the behavior–environment vulnerable profile.
C2 included 199 participants, accounting for 50.38% of the total sample. This profile showed moderately high scores across the four dimensions, with relatively small differences among them, indicating that these adolescents had a relatively stable level of oral health self-management. However, their overall level remained lower than that of C3. Therefore, this group was labeled the moderate and stable profile.
C3 included 117 participants, accounting for 29.62% of the total sample. This profile showed relatively high scores across all four dimensions, with a well-balanced distribution among dimensions, suggesting that these adolescents had better oral health knowledge, more positive health beliefs, more stable self-management behaviors, and a more supportive environment. Therefore, this group was labeled the high and balanced profile.
The latent profile characteristics of oral health self-management among adolescents undergoing fixed orthodontic treatment are shown in Figure 1, and the scores for each dimension across the three latent profiles are presented in Table 3.
Figure 1.
Latent Profile Characteristics of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment.
Notes: C1, behavior–environment vulnerable profile; C2, moderate and stable profile; C3, high and balanced profile.
Table 3.
Scores for Each Dimension of Oral Health Self-Management Across Different Latent Profiles (n = 395)
| Latent Profile | n | Proportion (%) | Knowledge | Beliefs | Behaviors | Environment |
|---|---|---|---|---|---|---|
| C1 | 79 | 20.00 | 3.40 | 3.50 | 2.97 | 3.11 |
| C2 | 199 | 50.38 | 3.85 | 3.91 | 3.66 | 3.92 |
| C3 | 117 | 29.62 | 4.49 | 4.44 | 4.33 | 4.51 |
Notes: C1, behavior–environment vulnerable profile; C2, moderate and stable profile; C3, high and balanced profile.
Univariate Analysis of Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
Univariate analysis showed statistically significant differences in grade, age, e-health literacy, family care, self-efficacy, and dental anxiety across the latent profiles of oral health self-management among adolescents undergoing fixed orthodontic treatment (all P < 0.05). Details are presented in Table 1.
Multivariate Analysis of Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
Variables showing statistically significant differences in the univariate analyses were considered for inclusion in the multinomial logistic regression model. Age and grade were strongly correlated (Spearman’s ρ = 0.802, P < 0.001); therefore, grade was excluded to reduce potential multicollinearity, whereas age was retained as a continuous covariate.E-health literacy, self-efficacy, dental anxiety, family care, and age were entered into the model as continuous variables using their original scores or values. The behavior–environment vulnerable profile was used as the reference category.
Compared with the behavior–environment vulnerable profile, adolescents with higher family care scores had higher odds of belonging to the moderate and stable profile (OR = 1.196, 95% CI: 1.058–1.351, P = 0.004), whereas older adolescents had lower odds of belonging to this profile (OR = 0.787, 95% CI: 0.669–0.927, P = 0.004). E-health literacy, self-efficacy, and dental anxiety were not significantly associated with membership in the moderate and stable profile.
Compared with the behavior–environment vulnerable profile, adolescents with higher e-health literacy (OR = 1.219, 95% CI: 1.114–1.335, P < 0.001), greater family care (OR = 1.486, 95% CI: 1.241–1.779, P < 0.001), and stronger self-efficacy (OR = 1.172, 95% CI: 1.086–1.265, P < 0.001) had higher odds of belonging to the high and balanced profile. In contrast, higher dental anxiety (OR = 0.863, 95% CI: 0.751–0.993, P = 0.040) and older age (OR = 0.751, 95% CI: 0.613–0.921, P = 0.006) were associated with lower odds of belonging to the high and balanced profile. The full regression results are presented in Table 4.
Table 4.
Multinomial Logistic Regression Analysis of Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
| Comparison | Variable | β | SE | OR | 95% CI | P |
|---|---|---|---|---|---|---|
| C2 VS C1 | E-health literacy | 0.057 | 0.035 | 1.059 | 0.989–1.134 | 0.103 |
| Family care | 0.179 | 0.062 | 1.196 | 1.058–1.351 | 0.004 | |
| Self-efficacy | 0.044 | 0.033 | 1.045 | 0.980–1.114 | 0.180 | |
| Dental anxiety | 0.010 | 0.052 | 1.010 | 0.912–1.119 | 0.852 | |
| Age | −0.239 | 0.083 | 0.787 | 0.669–0.927 | 0.004 | |
| C3 VS C1 | E-health literacy | 0.198 | 0.046 | 1.219 | 1.114–1.335 | <0.001 |
| Family care | 0.396 | 0.092 | 1.486 | 1.241–1.779 | <0.001 | |
| Self-efficacy | 0.159 | 0.039 | 1.172 | 1.086–1.265 | <0.001 | |
| Dental anxiety | −0.147 | 0.071 | 0.863 | 0.751–0.993 | 0.040 | |
| Age | −0.286 | 0.104 | 0.751 | 0.613–0.921 | 0.006 |
Notes: The behavior–environment vulnerable profile was used as the reference category. All independent variables were entered as continuous variables without categorization. C1, behavior–environment vulnerable profile; C2, moderate and stable profile; C3, high and balanced profile.
Abbreviations: CI, confidence interval; OR, odds ratio; SE, standard error.
Discussion
Characteristics of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
Based on latent profile analysis, this study identified three latent profiles of oral health self-management among adolescents undergoing fixed orthodontic treatment: the behavior–environment vulnerable profile (C1, 20.00%), the moderate and stable profile (C2, 50.38%), and the high and balanced profile (C3, 29.62%). The largest proportion of participants belonged to C2, indicating that most adolescents demonstrated relatively stable but not optimal self-management across the four dimensions. Notably, one fifth of the participants belonged to C1 and showed pronounced weaknesses in the behavior and environment dimensions.
The identification of three profiles extends previous research that has primarily described oral health self-management using total scores or average associations. Previous studies among adolescents undergoing fixed orthodontic treatment have reported that self-management remains suboptimal in some patients and is related to multiple personal and contextual factors.8 The present findings add to this evidence by showing that limitations in self-management do not occur uniformly. Adolescents may differ not only in their overall level of self-management but also in the way knowledge, beliefs, behaviors, and environmental conditions are combined.
The behavior–environment vulnerable profile showed a structurally imbalanced pattern. Adolescents in this profile performed relatively well in the knowledge and belief dimensions but showed marked declines in the behavior and environment dimensions. This pattern suggests that their core problem may not simply be a lack of oral health knowledge or willingness to improve, but rather a failure to effectively translate knowledge and beliefs into daily behaviors. Similar discrepancies have been observed in orthodontic populations. Mansoor et al,31 for example, found that orthodontic patients generally demonstrated good awareness of oral hygiene but did not consistently translate that awareness into compliant behavior Studies examining knowledge, attitudes, and practices among orthodontic patients have likewise shown that adequate knowledge and positive attitudes do not invariably correspond to optimal oral health practices.16,32 A recent systematic review identified barriers and facilitators across cognitive, motivational, social, environmental, and opportunity-related domains, suggesting that information alone may be insufficient to establish and sustain oral health behavior.10 The lower environment score in the behavior–environment vulnerable profile may therefore reflect less favorable conditions for carrying out recommended practices, although the present study did not directly identify which environmental barriers were involved.
The moderate and stable profile showed relatively balanced scores across all four dimensions but at a lower overall level than the high and balanced profile.As this profile accounted for approximately half of the sample, it may reflect a common intermediate pattern during prolonged orthodontic treatment. These adolescents should not necessarily be regarded as having poor self-management. Rather, they may have established routine oral care practices while still experiencing limitations in consistency, motivation, information use, or environmental support. The predominance of this profile also suggests that a simple distinction between adequate and inadequate self-management may overlook clinically meaningful differences among adolescents with moderate performance.
The high and balanced profile was characterized by consistently favorable scores across knowledge, beliefs, behaviors, and environment. The alignment of these dimensions suggests that adolescents in this profile reported not only adequate cognitive preparation but also more consistent behavioral implementation and more favorable environmental conditions. Nevertheless, the profile should not be viewed as a fixed or permanently stable state. Oral health behavior may change during adolescence and over the course of orthodontic treatment as treatment burden, motivation, autonomy, and family involvement change.10 Longitudinal research is therefore needed to establish whether these profiles remain stable or whether adolescents move between them over time.
Factors Associated with Latent Profiles of Oral Health Self-Management Among Adolescents Undergoing Fixed Orthodontic Treatment
The patterns of associated factors were not identical across profile comparisons. Family care was associated with membership in both the moderate and stable profile and the high and balanced profile rather than the behavior–environment vulnerable profile. In contrast, e-health literacy, self-efficacy, and dental anxiety distinguished the high and balanced profile from the behavior–environment vulnerable profile but did not distinguish the moderate and stable profile from the behavior–environment vulnerable profile. Age was also associated with both profile comparisons. These findings suggest that the factors associated with attaining a moderate and stable level of self-management may differ from those associated with a consistently high and balanced pattern. Overall, the findings are broadly consistent with SCT, which emphasizes the joint relevance of personal characteristics and environmental conditions to health behavior.
Higher e-health literacy and self-efficacy were associated with membership in the high and balanced profile rather than the behavior–environment vulnerable profile, but neither factor significantly distinguished the moderate and stable profile from the behavior–environment vulnerable profile. This pattern suggests that these personal cognitive resources may be particularly relevant to the consistently favorable self-management configuration represented by the high and balanced profile, rather than merely differentiating an intermediate level of self-management.
E-health literacy reflects an individual’s ability to obtain, understand, evaluate, and apply health information in digital health environments. Compared with adolescents in the behavior–environment vulnerable profile, those with higher e-health literacy were more likely to be classified into the high and balanced profile. Adolescents receiving orthodontic treatment increasingly encounter oral health information through social media, online educational materials, mobile applications, and digital follow-up services. In such an information-rich environment, access alone may be insufficient; adolescents must also judge the reliability and relevance of information and translate it into daily care. Previous research in other self-management contexts has shown positive associations among eHealth literacy, empowerment, and self-management behavior,33 while research among young populations has similarly linked digital health literacy with self-management-related capacities.12 However, these studies were conducted in populations different from adolescents undergoing orthodontic treatment, and direct comparison should therefore be cautious.
Self-efficacy is a core construct of SCT and reflects an individual’s confidence in his or her ability to perform specific behaviors.13 In this study, compared with adolescents in the behavior–environment vulnerable profile, those with higher self-efficacy were more likely to be classified into the high and balanced profile. This finding is generally consistent with previous studies on oral health behaviors among adolescents. Dolatabadi et al reported that, among adolescents aged 12–18 years, individuals’ confidence in their own behavioral capability may influence their oral health practices34 Extending this evidence to the context of fixed orthodontic treatment, the present study suggests that self-efficacy may influence not only general oral health behaviors, but also adolescents’ ability to sustain continuous treatment-related behaviors, such as maintaining oral hygiene, attending follow-up visits, and caring for orthodontic appliances. Adolescents with higher self-efficacy are more likely to believe that they can cope with difficulties during treatment and continue performing oral health behaviors when facing obstacles,35 which may make them more likely to develop a high and balanced self-management pattern.
Dental anxiety represents an important emotional factor within the framework of SCT. The present results showed that, compared with adolescents in the behavior–environment vulnerable profile, those with higher dental anxiety were less likely to be classified into the high and balanced profile. This finding suggests that dental anxiety may affect whether adolescents can achieve a high level of self-management. It is consistent with previous studies on dental anxiety and oral health-seeking behaviors among adolescents. Balamurugan et al reported that dental anxiety may further interfere with the sustained implementation of oral health behaviors by increasing treatment avoidance, weakening adherence to follow-up visits, and reducing cooperation with care14 In the context of fixed orthodontic treatment, anxiety related to dental procedures or follow-up visits may coexist with difficulties in maintaining regular care behaviors. However, the MDAS showed marginal internal consistency in the present sample (Cronbach’s α = 0.688). Accordingly, this finding should be interpreted cautiously and confirmed using measures with stronger psychometric performance in future studies.
While e-health literacy, self-efficacy, and dental anxiety represent personal cognitive or emotional characteristics, family care reflects the environmental context in which adolescents maintain daily oral health self-management.
Family care reflects an important environmental factor in SCT. Higher family care was associated with greater odds of membership in both the moderate and stable profile and the high and balanced profile rather than the behavior–environment vulnerable profile. This finding highlights the relevance of the family environment to adolescents’ oral health self-management. During fixed orthodontic treatment, many daily care activities, including oral hygiene, dietary management, appliance care, and attendance at follow-up visits, take place within the family context. Supportive family functioning may provide emotional encouragement, practical assistance, and a stable environment for maintaining these behaviors. This interpretation is consistent with previous evidence linking family cohesion and family functioning with oral health-related behaviors among children and adolescents.15
Younger age was associated with greater odds of membership in both the moderate and stable profile and the high and balanced profile rather than the behavior–environment vulnerable profile. Although this result may initially appear counterintuitive, it is broadly consistent with recent evidence suggesting that adherence to preventive recommendations among adolescents with fixed orthodontic appliances may be poorer in older adolescents.36 The transition from early to later adolescence involves increasing autonomy, changing family involvement, greater academic and social demands, and stronger peer influences. Longitudinal evidence from general adolescent populations also indicates that oral health behaviors can change between childhood and adolescence as parental influence decreases and personal responsibility increases.37 Younger participants in the present sample may still have received more direct family involvement, whereas older adolescents may have had greater responsibility for their own care. However, these potential explanations were not directly measured.The age range in the present study was restricted to 12–18 years, and the cross-sectional analysis compared different individuals at one time point. It therefore cannot establish that self-management deteriorates as adolescents grow older. Longitudinal studies are needed to clarify developmental changes in self-management during orthodontic treatment.
Taken together, the findings indicate that membership in different oral health self-management profiles was associated with a combination of cognitive, emotional, environmental, and developmental characteristics. This pattern is broadly consistent with SCT, which emphasizes the interplay between personal factors, environmental conditions, and behavior.
Clinical Implications
The identified profiles may provide a preliminary framework for recognizing differences in oral health self-management needs among adolescents undergoing fixed orthodontic treatment. In clinical practice, assessment based solely on a total self-management score may overlook specific difficulties in knowledge, beliefs, behaviors, or environmental support. Incorporating brief assessments of these dimensions during treatment initiation and follow-up may help clinicians identify the domains in which an adolescent requires additional support.
For adolescents in the behavior–environment vulnerable profile, repeating knowledge-based education alone may be insufficient. Clinical conversations could explore practical barriers to daily oral hygiene, difficulties integrating care into everyday routines, and the availability of support. Adolescents in the moderate and stable profile may benefit from periodic reassessment and reinforcement of domains that remain inconsistent, whereas those in the high and balanced profile may require primarily maintenance-oriented follow-up.
Existing intervention research provides some support for moving beyond conventional information provision. Randomized studies have found that mobile applications, reminders, feedback, and behavior-change components can improve oral hygiene among patients with fixed orthodontic appliances, at least in the short term.38,39 A systematic review and meta-analysis also found that psychologically informed interventions may improve adolescent oral health behaviors, self-efficacy, and plaque outcomes in the short term, although the certainty of evidence was low and long-term effects were less clear.40 These findings support further testing of profile-informed approaches but do not establish that any specific intervention is effective for the profiles identified in the present study.
Strengths and Limitations
This study has several strengths. It used a person-centered approach to identify distinct configurations of oral health self-management among adolescents undergoing fixed orthodontic treatment, extending previous work based largely on total scores and average associations. The profile indicators represented cognitive, belief-related, behavioral, and environmental dimensions of self-management. The analysis of associated factors was also informed by SCT and incorporated cognitive, emotional, environmental, and developmental characteristics.
Several limitations should be considered. First, the cross-sectional design precludes conclusions regarding temporality or causality. The identified profiles represent patterns observed at a single time point and do not show whether adolescents move between profiles during treatment. Longitudinal studies are needed to examine profile stability and developmental trajectories.
Second, all primary variables were assessed using self-report questionnaires and may have been affected by recall bias or socially desirable responding. Future research should incorporate objective clinical and behavioral indicators, including plaque and gingival indices, white spot lesions, appointment attendance, and appliance maintenance.
Third, convenience sampling from a single tertiary stomatological hospital may have introduced selection bias. Adolescents who regularly attended follow-up visits and agreed to participate may differ from those with irregular attendance or limited access to orthodontic services. Consequently, the observed profile distribution and associated factors may not be fully generalizable to adolescents treated in other institutions, regions, or healthcare settings.
Finally, the MDAS and the environment dimension of the oral health self-management questionnaire showed marginal or modest internal consistency. These findings should therefore be interpreted cautiously.
Conclusion
Based on latent profile analysis, this study identified three latent profiles of oral health self-management among adolescents undergoing fixed orthodontic treatment: the behavior–environment vulnerable profile, the moderate and stable profile, and the high and balanced profile. These findings indicate that self-management ability in this population is not a single continuous construct, but rather shows clear heterogeneity across the dimensions of knowledge, beliefs, behaviors, and environmental support.The results highlight the substantial heterogeneity in oral health self-management among adolescents undergoing fixed orthodontic treatment and suggest that future interventions should not rely solely on standardized oral health education. Instead, stratified, precise, and individualized interventions should be developed according to the characteristics of different latent profiles.
Funding Statement
The authors received no specific funding for this work.
Declaration of Generative AI Use
During the preparation of this manuscript, the authors used ChatGPT, developed by OpenAI, based on the GPT-5.5 model, for English language polishing, grammar correction, and improvement of sentence clarity and readability. The tool was used solely to enhance linguistic expression and did not generate research ideas, study design, data, statistical analyses, results, interpretations, figures, tables, or references. The authors carefully reviewed and edited all AI-assisted outputs and take full responsibility for the content of the manuscript.
Abbreviations
aBIC, adjusted Bayesian information criterion; AIC, Akaike information criterion;APGAR, Adaptation, Partnership, Growth, Affection, and Resolve; BIC, Bayesian information criterion; BLRT, bootstrap likelihood ratio test;CI, confidence interval; CNY, Chinese yuan; eHEALS, e-Health Literacy Scale; e-health literacy, digital health literacy; GSES, General Self-Efficacy Scale;KAP, knowledge, attitude, and practice; LMR, Lo–Mendell–Rubin likelihood ratio test; LPA, latent profile analysis; MDAS, Modified Dental Anxiety Scale; OR, odds ratio;SCT, Social Cognitive Theory; SD, standard deviation; SE, standard error.
Data Sharing Statement
The datasets generated and/or analyzed during the current study are not publicly available due to the inclusion of potentially sensitive information from adolescent participants and restrictions related to participant privacy and ethical approval. De-identified data may be made available from the corresponding author upon reasonable request, subject to approval by the relevant ethics committee and compliance with applicable data protection requirements.
Ethics Approval and Informed Consent
This study was approved by the Ethics Committee of the Affiliated Stomatological Hospital of Kunming Medical University (approval No. KYKQ2025MEC0153) and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from the parents or legal guardians of all adolescent participants, and assent was obtained from the participants before data collection. All data were collected and analyzed anonymously.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.
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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 datasets generated and/or analyzed during the current study are not publicly available due to the inclusion of potentially sensitive information from adolescent participants and restrictions related to participant privacy and ethical approval. De-identified data may be made available from the corresponding author upon reasonable request, subject to approval by the relevant ethics committee and compliance with applicable data protection requirements.