Oral Health Service Utilization Behavior and Its Influencing Factors Among Older Adults: An Empirical Study Based on the Composite Health Behavior Model

Oral Health Service Utilization Behavior and Its Influencing Factors Among Older Adults: An Empirical Study Based on the Composite Health Behavior Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Oral Health Service Utilization Behavior and Its Influencing Factors Among Older Adults: An Empirical Study Based on the Composite Health Behavior Model Xiaoyuan Pan, Shuwen Su, Jianli Li, Leyi Han, Xinyue Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7235151/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background China's aging population faces significant unmet oral healthcare needs, and delays in seeking care exacerbate the disease burden. Currently, there is a lack of empirical research applying comprehensive health behavior models to understand the pathway relationships among influencing factors in this population. Methods A cross-sectional study was conducted between July and September 2023 among 356 community-dwelling older adults in Foshan and Guangzhou, using a theory-driven questionnaire. Group comparisons employed independent t-tests or ANOVA for sociodemographic variables. Structural equation modeling (SEM) validated pathways. Results Significant differences were observed: 1) Sex and age affected individual model variables; 2) Education, residence location, and economic status influenced multiple variables; 3) Living arrangement showed no significant effects. Only 33.7% of older adults proactively sought oral health knowledge, while 65.7% did not receive regular dental check-ups. Merely 51.2% sought treatments (e.g., scaling, fillings, extractions, dentures, implants). When acute oral pain disrupted daily life, 24.7% still delayed seeking care. SEM revealed: 1) Behavioral Intention/Control had the strongest total effect on utilization behavior ( β = 0.593); 2) This was followed by Perceived Benefits ( β = 0.404); 3) Subjective Norms exerted only indirect effects ( β = 0.216); 4) Both Subjective Norms ( β = 0.365) and Perceived Benefits ( β = 0.282) directly influenced Behavioral Intention/Control. Conclusion Oral health service utilization among older adults in China remains largely passive. Our model identifies three key modifiable factors: Behavioral Intention/Control, Perceived Benefits, and Subjective Norms. Strategies to improve service utilization should focus on strengthening social support and addressing unrealistic health perceptions. Health sciences/Health care Health sciences/Medical research Biological sciences/Psychology Social science/Psychology Geriatric oral health Health services utilization Structural equation modeling Health belief model Theory of planned behavior Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Oral health service utilization is defined as "the actual amount of dental services received by residents, reflecting both service provision and institutional efficiency" 1 . Regular utilization enables early detection and management of oral diseases through preventive care, effectively maintaining oral health while reducing long-term treatment frequency and costs. As China's population rapidly ages—with adults aged ≥ 60 years increasing by 5.44% from 2010 to 2020 and reaching 264.02 million (18.7% of the population) in 2020 2 —older adults face disproportionately poor oral health. The Fourth National Oral Health Survey revealed alarming statistics among those aged 65–74: 98% had Decayed/Missing/Filled Teeth (DMFT), 90.3% exhibited dental calculus, and only 9.3% maintained periodontal health 3 . This underscores an urgent need to address oral health disparities in China's aging population. These findings indicate suboptimal oral health behaviors among older adults in China, where behavioral factors constitute critical modifiable targets for intervention.​​ The determinants of elderly health behavior are multifaceted, yet empirical applications of established behavioral theories (e.g., HBM, TPB) remain limited in oral health research within China's context 4 . Existing studies predominantly focus on clinical outcomes rather than comprehensively exploring psychosocial determinants, resulting in insufficient theoretical foundations for evidence-based interventions 5 . Behavioral theories transcend mere categorization of health habits; they provide mechanistic frameworks for designing targeted interventions across individual, community, and policy levels 6 . As emphasized by the UK National Institute for Health and Care Excellence (NICE), "theory-based behavior change interventions demonstrate greater efficacy than atheoretical approaches" 7 . Globally, preventive dentistry increasingly employs behavioral theories to enhance self-care and treatment adherence, evidenced by the 11th European Workshop on Periodontology recommending psychological methods for plaque control in periodontal management 8 . Consequently, theoretically grounded identification of influencing factors and pathways represents the vanguard of oral health interventions 9 . Among behavioral frameworks, the Health Belief Model (HBM) and Theory of Planned Behavior (TPB) are most established. This study therefore integrates HBM and TPB to develop a composite model specific to elderly oral health service utilization, aiming to elucidate behavioral mechanisms and inform targeted interventions. Materials and Methods 2.1 Theoretical Framework and Composite Model Construction 2.1.1 Health Belief Model (HBM) The core of the Health Belief Model (HBM) is perception, which refers to the perception of disease threat and the evaluation of behaviors. This encompasses: Perceived Susceptibility, Perceived Severity, Perceived Benefits, and Perceived Barriers. Subsequent scholars have further developed two additional core components: Self-Efficacy and Cues to Action. Self-efficacy represents the assessment of one's ability to successfully adopt a health behavior, while cues to action are stimuli that prompt the initiation of action, such as noticing gum swelling, pain, or bleeding 10 . A schematic diagram of the Health Belief Model is shown in Fig. 1. 2.1.2 Theory of Planned Behavior (TPB) The Theory of Planned Behavior (TPB) comprises five main components: Attitude toward the Behavior, Subjective Norm, Perceived Behavioral Control, Behavioral Intention, and Behavior 11 . TPB posits that behavior is determined by behavioral intention. Behavioral intention, in turn, is influenced by three factors: attitude toward the behavior, subjective norm, and perceived behavioral control. A schematic diagram of the Theory of Planned Behavior is shown in Fig. 2. Note The dashed line signifies that accurate perceived behavioral control can serve as a valid proxy measure for actual control conditions, enabling direct prediction of the likelihood of behavior occurrence 2.1.3 Integrated Model Development The contents of the HBM and TPB are closely interrelated. Therefore, during the integration process in this study, similar dimensions were streamlined. In the TPB, Attitude toward the Behavior can be divided into positive and negative attitudes. Conversely, the HBM includes Perceived Benefits and Perceived Barriers, which correspond to positive and negative attitudes, respectively, in terms of cost-benefit analysis 12 . Consequently, in this study's integrated model, the two variables Perceived Benefits and Perceived Barriers jointly replace the Attitude toward the Behavior variable from the TPB. Furthermore, Perceived Susceptibility and Perceived Severity within the HBM exhibit a high degree of correlation. Precedents exist in previous integrated model research where scholars have combined these two constructs 13 . Thus, this study merged them into a single variable termed Perceived Threat (encompassing perceived risk and severity). Both Self-Efficacy (HBM) and Perceived Behavioral Control (TPB) pertain to an individual's beliefs about their capabilities: Self-efficacy focuses on confidence in one's own ability, while perceived behavioral control emphasizes the sense of control over the environment or situation. Both significantly influence an individual's behavioral choices and psychological state and should therefore be comprehensively considered in practical applications 14 . To streamline the model, this study does not separately discuss self-efficacy. Perceived Behavioral Control encompasses two aspects: capability to perform the behavior and autonomy in performing it 15 . The concept of behavioral autonomy is somewhat analogous to behavioral intention. Moreover, within the TPB, perceived behavioral control can also moderate the influence of attitudes and subjective norms on behavioral intention, as well as the influence of behavioral intention on behavior. Behavior is the result of the combined effect of behavioral intention and perceived behavioral control 16 . Perceived behavioral control can thus be used alongside behavioral intention to predict the occurrence of behavior, given the correlation between them 17 . Consequently, this study introduces a new dimension—" Behavioral Intention and Control (BIC) "—which encompasses the original constructs of perceived behavioral control and behavioral intention. The integrated model comprises six variables: ① Perceived Benefit (PBE), ② Perceived Barrier (PBA), ③ Perceived Threat (PS), ④ Subjective Norm (SN), ⑤ Behavioral Intention and Control (BIC), and ⑥ Behavior (B). Table 1 details the integration of the original components from the two models. Definitions of the variables in the newly constructed integrated model are provided in Table 2. The hypothesized path relationships between the model components are illustrated in Fig. 3. Table 1 Integration of Original Components from Two Theoretical Models No. Original Component Source Model Composite Model Component 1 Positive Attitude TPB ① Perceived Benefit, ② Perceived Barrier 2 Negative Attitude TPB 3 Perceived Benefit HBM 4 Perceived Barrier HBM 5 Perceived Susceptibility HBM ③Perceived Threat 6 Perceived Severity HBM 7 Subjective Norm TPB ④ Subjective Norm 8 Perceived Behavioral Control TPB ⑤Behavioral Intention and Control 9 Behavioral Intention TPB 10 Self-Efficacy HBM 11 Behavior HBM、TPB ⑥Behavior Table 2 Newly constructed composite model building block variable definitions Variable Abbreviation Definition ①Perceived Benefit PBE Subjective evaluation held by the elderly regarding the potential positive outcomes of engaging in oral health service utilization behavior ②Perceived Barrier PBA Subjective assessment of the difficulties potentially encountered during the process of oral health service utilization behavior ③Perceived Threat PT Subjective assessment of the risk of disease and its consequences ④Subjective Norm SN Individual's subjective perception of social pressure concerning whether or not to adopt oral health service utilization behavior ⑤Behavioral Intention and Control BIC Capability and autonomy to perform oral health service utilization behavior ⑥Behavior B Oral health service utilization behavior Note H1 : Perceived Benefit (PBE) has a positive effect on Behavioral Intention and Control (BIC). H2 Perceived Benefit (PBE) has a positive effect on Behavior (B). H3 Perceived Barrier (PBA) has a negative effect on Behavioral Intention and Control (BIC). H4 Perceived Barrier (PBA) has a negative effect on Behavior (B). H5 Perceived Threat (PT) has a positive effect on Behavioral Intention and Control (BIC). H6 Perceived Threat (PT) has a positive effect on Behavior (B). H7 Subjective Norm (SN) has a positive effect on Behavioral Intention and Control (BIC). H8 Subjective Norm (SN) has a positive effect on Behavior (B). H9 Behavioral Intention and Control (BIC) has a positive effect on Behavior (B). 2.2 Research Methods 2.2.1 Questionnaire Design A questionnaire was self-developed by integrating the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). This study referenced established scales and drew upon previous research findings to formulate items for each dimension: (1)Items for the Behavior (B), Perceived Benefit (PBE), Perceived Barrier (PBA), and Perceived Threat (PS) dimensions were developed based on the research by Nakazono et al. (1997) 18 and Xiang et al. (2020) 19 (2)Items for Subjective Norm (SN) were adapted from the work of Liu Yuqin (2019) 13 ; (3)Items for Behavioral Intention & Control (BIC) were developed referencing studies by Ju Taoran (2018) 20 and Sun Tao (2013) 21 . The questionnaire was specifically designed considering the behavioral and psychological characteristics of the elderly population. It underwent refinement through expert review and a pilot pre-survey before finalization. The final questionnaire comprised 26 items across six dimensions: Behavior (B), Perceived Benefit (PBE), Perceived Barrier (PBA), Perceived Threat (PS), Subjective Norm (SN), and Behavioral Intention & Control (BIC). Given the potentially limited comprehension abilities of elderly respondents, all items utilized a 5-point Likert scale, ranging from "Strongly Disagree" (scored 1) to "Strongly Agree" (scored 5), with higher scores indicating more positive responses. Questionnaire Quality Assessment: Exploratory Factor Analysis (EFA) extracted six principal components, accounting for a cumulative variance contribution rate of 62.616%. Factor loadings for all items ranged from 0.517 to 0.817. The overall Cronbach's α coefficient for the scale was 0.864, indicating good reliability and validity. 2.2.2 Data Collection From July to September 2023, a convenience sampling method was employed to recruit 356 elderly individuals from five communities in Foshan and Guangzhou cities for questionnaire surveys.Inclusion Criteria:(1)Aged ≥ 60 years; (2)Cognitively clear and able to complete the questionnaire independently, or able to complete it successfully with assistance from researchers; (3)Provided informed consent and participated in the survey. Based on established recommendations for minimum sample size in structural equation modeling (e.g., requiring 300 samples for models with 5–7 variables), a target sample size was set. A total of 352 questionnaires were returned. After excluding 26 invalid responses, 326 valid questionnaires were obtained. The scale developed in this study contained 26 measurement items; the final sample size (n = 326) met the common "10 times rule" (minimum 10 cases per measured item), allowing for robust exploration of complex variable relationships within the model 22,23 . 1.2.3 Statistical Analysis Data processing and analysis were performed using SPSS software (version 19.0) and AMOS software (version 24.0). (1)Descriptive statistics (frequencies, percentages) were used to characterize the sociodemographic profile of the surveyed elderly participants and describe the current status of their oral health service utilization behavior; (2)Structural Equation Modeling (SEM) was employed to assess the goodness-of-fit of the integrated model of elderly oral health service utilization behavior; (3)Effect analysis and path analysis were conducted on the integrated model within the SEM framework. Results 2.1 Analysis of Sociodemographic Characteristics This study identified the basic characteristics of the surveyed participants across dimensions including gender, age, education level, place of residence, economic status, and living arrangements. Questionnaire results showed that participants' ages ranged between 60 and 80 years. There were 132 male and 194 female participants. The proportion of participants with education levels above high school or secondary specialized education was relatively low. Only 11% of the elderly respondents self-reported experiencing family economic difficulties. A majority (82.3%) of the elderly lived with their spouse or children. The sample covered younger-old (60–69 years), middle-old (70–79 years), and older-old (≥ 80 years) age groups. Specific details are presented in Table 3 . Univariate analysis was employed to examine the variables of gender, age, education level, etc., within the personal background of the elderly participants, aiming to explore differences in psychological and behavioral manifestations of oral health service utilization across different group characteristics. As these variables could not be incorporated into the Structural Equation Model (SEM), univariate analysis was conducted using SPSS software (version 19.0). Each of the four background variables—age, education level, economic status, and place of residence—was divided into at least three groups. Therefore, one-way Analysis of Variance (ANOVA) was used to test for between-group differences in each variable across the questionnaire dimensions. Gender and place of residence were divided into only two groups, so independent samples *t*-tests were used for analysis. The results indicated:(1)Significant differences were found for gender and age in individual aspects of the model variables; (2)Significant differences were found across multiple aspects for participants grouped by education level, place of residence, and economic status; (3)No significant differences were found among participants grouped by living arrangements (P > 0.05).Detailed data are presented in Table 4 . Table 3 Socio-demographic characteristics of older adults interviewed (n = 326) Variable Group Frequency (n) Percentage (%) Gender Male 132 40.50% Female 194 59.50% Age (years) 60–69 172 52.80% 70–79 109 33.40% ≥ 80 45 13.80% Education Level Primary school 112 34.40% Junior high school 80 24.50% High school / Sec. spec. 68 20.90% College / Associate degree 54 16.60% Master's degree+ 12 3.70% Place of Residence Rural 148 45.40% Urban 178 54.60% Economic Status Very affluent 10 3.10% Relatively comfortable 96 29.40% Financially sufficient 184 56.40% Some financial difficulty 32 9.80% Severe financial difficulty 4 1.20% Living Arrangements Living alone 48 14.70% Living with spouse 142 43.60% Living with children 126 38.70% Other 10 3.10% Table 4 Behavioural and psychological variables of oral health service utilisation among the elderly grouped by socio-demographic factors and psychological variables Factor Group Behavior (B) Mean ± SE Stat.§ Perceived Benefit (PBE) Mean ± SD Stat.§ Perceived Barrier (PBA) Mean ± SD Stat.§ Subjective Norm (SN) Mean ± SD Stat.§ Perceived Threat (PS) Mean ± SD Stat.§ Behavioral Intention & Control (BIC) Mean ± SD Stat.§ Gender Male (n = 132) 2.77 ± 1.08 t =-1.778 4.06 ± 0.73 t =-0.600 3.08 ± 0.73 t =-0.290 3.50 ± 0.95 t =-2.594* 3.39 ± 0.71 t =-0.620 3.40 ± 0.80 t =-2.089* Female (n = 194) 2.99 ± 1.05 4.11 ± 0.71 3.11 ± 0.75 3.77 ± 0.89 3.44 ± 0.76 3.61 ± 0.80 Age (years) 60–69 (n = 172) 2.98 ± 1.03 F = 3.510* 4.15 ± 0.71 F = 1.370 3.08 ± 0.77 F = 1.337 3.65 ± 0.89 F = 0.067 3.51 ± 0.69 F = 3.557* 3.56 ± 0.80 F = 2.147 70–79 (n = 109) 2.91 ± 1.06 4.05 ± 0.67 3.06 ± 0.69 3.65 ± 0.92 3.28 ± 0.78 3.58 ± 0.73 ≥ 80 (n = 45) 2.56 ± 1.19 3.97 ± 0.83 3.27 ± 0.75 3.70 ± 1.09 3.39 ± 0.76 3.28 ± 0.94 Education Level Primary (n = 112) 2.92 ± 1.06 F = 8.083*** 3.98 ± 0.71 F = 3.184* 3.22 ± 0.63 F = 3.276* 3.57 ± 0.93 F = 0.756 3.34 ± 0.66 F = 3.716*** 3.37 ± 0.81 F = 4.993** Junior HS (n = 80) 2.92 ± 1.06 4.01 ± 0.78 3.14 ± 0.76 3.69 ± 0.89 3.35 ± 0.83 3.48 ± 0.83 HS/Secondary (n = 68) 3.00 ± 1.09 4.23 ± 0.62 2.83 ± 0.78 3.67 ± 1.05 3.42 ± 0.74 3.62 ± 0.79 College+ (n = 54) 3.23 ± 0.99 4.16 ± 0.76 3.09 ± 0.71 3.71 ± 0.82 3.50 ± 0.71 3.60 ± 0.70 Master's+ (n = 12) 4.00 ± 0.62 4.58 ± 0.35 3.25 ± 1.19 4.00 ± 0.85 4.15 ± 0.59 4.37 ± 0.50 Residence Rural (n = 148) 2.64 ± 1.01 t =-4.526*** 3.98 ± 0.73 t =-2.497* 3.21 ± 0.65 t = 2.361* 3.58 ± 0.89 t =-1.399 3.36 ± 0.72 t =-1.191 3.36 ± 0.80 t =-3.407** Urban (n = 178) 3.12 ± 1.07 4.18 ± 0.69 3.01 ± 0.81 3.72 ± 0.95 3.46 ± 0.75 3.66 ± 0.78 Economic Status Very affluent (n = 10) 3.23 ± 1.31 F = 2.988* 4.07 ± 0.72 F = 3.277* 3.24 ± 1.09 F = 1.426* 3.90 ± 0.90 F = 0.478 3.77 ± 0.79 F = 0.837 3.84 ± 0.79 F = 1.677 Comfortable (n = 96) 2.99 ± 1.06 4.17 ± 0.60 3.01 ± 0.74 3.69 ± 0.88 3.40 ± 0.67 3.56 ± 0.78 Sufficient (n = 184) 2.93 ± 1.04 4.13 ± 0.67 3.10 ± 0.75 3.65 ± 0.94 3.43 ± 0.77 3.54 ± 0.79 Some difficulty (n = 32) 2.46 ± 1.05 3.69 ± 1.06 3.36 ± 0.59 3.53 ± 0.98 3.29 ± 0.78 3.33 ± 0.86 Severe difficulty (n = 4) 2.08 ± 1.32 3.75 ± 1.17 3.10 ± 0.58 3.33 ± 1.25 3.46 ± 0.44 2.80 ± 1.12 Living Arrangement Alone (n = 48) 2.82 ± 1.17 F = 1.193 3.98 ± 0.85 F = 2.010 3.03 ± 0.67 F = 1.757 3.65 ± 0.87 F = 1.038 3.41 ± 0.82 F = 1.267 3.33 ± 0.94 F = 1.706 With spouse (n = 142) 2.99 ± 0.96 4.19 ± 0.64 3.18 ± 0.75 3.71 ± 0.86 3.50 ± 0.69 3.62 ± 0.73 With children (n = 126) 2.80 ± 1.12 4.01 ± 0.75 3.01 ± 0.76 3.57 ± 1.01 3.34 ± 0.71 3.50 ± 0.79 Other (n = 10) 3.23 ± 1.40 4.30 ± 0.55 3.36 ± 0.69 4.03 ± 1.02 3.23 ± 1.24 3.44 ± 1.18 Notes :① §: *t*-value for two-group comparisons; F-value for three or more groups; ② SE: Standard Error; SD: Standard Deviation; ③ Significance: ***p < 0.001, **p < 0.01, *p < 0.05; ④ Variables: B = Behavior; PBE = Perceived Benefit; PBA = Perceived Barrier; SN = Subjective Norm; PS = Perceived Threat; BIC = Behavioral Intention & Control. 3.2 Descriptive Analysis of Oral Health Service Utilization Behavior In the behavioral questionnaire:(1)Only 33.72% of elderly participants reported proactively learning about oral health knowledge; (2)A substantial majority (65.7%) indicated they did not proactively seek regular oral check-ups; (3)Merely 51.16% would proactively seek dental treatments (e.g., cleaning, fillings, extractions, dentures, or implants); (4)When acute oral pain affected daily life, 24.71% still reported not seeking timely medical care. Table 5 Current status of oral health service utilisation behaviours among older people (n = 326) Item Strongly Disagree n (%) Disagree n (%) Uncertain n (%) Agree n (%) Strongly Agree n (%) Proactively seek oral health knowledge 48 (13.95%) 117 (34.01%) 63 (18.31%) 96 (27.91%) 20 (5.81%) Schedule regular dental check-ups 66 (19.19%) 101 (29.36%) 59 (17.15%) 91 (26.45%) 27 (7.85%) Seek preventive/therapeutic dental services (e.g., scaling, fillings, extractions) 51 (14.83%) 77 (22.38%) 40 (11.63%) 134 (38.95%) 42 (12.21%) Visit dentists promptly for acute oral pain affecting daily life 22 (6.4%) 28 (10.17%) 35 (10.17%) 161 (46.8%) 98 (28.49%) These empirical findings indicate:(1)Low oral health awareness among the elderly: Both the awareness and behavior of proactively and regularly seeking oral health services were at alarmingly low levels, representing a key intervention point; (2)Inefficient health service utilization: Current oral health service utilization among the elderly is predominantly passive, with low efficiency. Pain-driven utilization (seeking care only when experiencing discomfort) is widespread. 3.3 Validation and Analysis of the Structural Equation Model for Elderly Oral Health Service Utilization Behavior 3.3.1 Model Fit Verification Based on the theoretically hypothesized model of elderly oral health service utilization behavior established previously, a structural equation model was constructed using AMOS software (version 24.0). In this hypothesized model, four variables—Perceived Benefit (PBE), Perceived Barrier (PBA), Perceived Threat (PS), and Subjective Norm (SN)—were specified as exogenous latent variables, while two variables—Behavioral Intention & Control (BIC) and Behavior (B)—were specified as endogenous latent variables. This framework constituted the structural equation model for "Elderly Oral Health Service Utilization Behavior," schematically represented in Fig. 4 . Prior to conducting path analysis, the reliability and validity of the hypothesized model must be established through model fit assessment—that is, by importing data into the constructed model for estimation. Prevailing methodological consensus holds that overall goodness-of-fit indices provide a feasible means to evaluate the model's fit, verifying the extent to which the hypothesized model aligns with the observed data. Consequently, this study employed a comprehensive set of overall fit indices to assess model adequacy. The global fit of the structural equation model was evaluated across three categories: absolute fit indices, incremental fit indices, and parsimonious fit indices. The formal questionnaire data were imported into AMOS 24.0 for processing. Analysis revealed the following fit indices: absolute fit indices are presented in Table 6 , incremental fit indices in Table 7 , and parsimonious fit indices in Table 8 . Synthesizing these results, the model demonstrated reasonable fit, indicating that the hypothesized model for this study is acceptable. Table 6 Absolute Fit Indices for Structural Equation Model Index Abbr. Criterion Value Evaluation Chi-square/Degrees of Freedom χ²/df 0.8 0.859 Reasonable fit Adjusted GFI AGFI 0.8–0.9 0.823 Reasonable fit Table 7 Incremental Fit Indices for Structural Equation Model Index Abbr. Criterion Value Evaluation Normed Fit Index NFI > 0.8 0.824 Reasonable fit Relative Fit Index RFI > 0.8 0.797 Marginal fit* Incremental Fit Index IFI > 0.8 0.887 Reasonable fit Tucker-Lewis Index TLI > 0.8 0.868 Reasonable fit Comparative Fit Index CFI > 0.8 0.886 Reasonable fit Note : RFI value (0.797) is marginally below threshold but acceptable given other indices Table 8 Parsimonious Fit Indices for Structural Equation Model Index Abbr. Criterion Value Evaluation Parsimonious GFI PGFI > 0.5 0.687 Reasonable fit Parsimonious Normed Fit Index PNFI > 0.5 0.712 Reasonable fit Parsimonious Comparative Fit Index PCFI > 0.5 0.768 Reasonable fit 2.3.2 Analysis of Research Path Hypothesis Verification A core function of constructing a Structural Equation Model (SEM) is to conduct an in-depth analysis of the path dependency relationships among multiple complex variables, aiming to reveal potential patterns of interaction between them. Therefore, following the model fit assessment, it is necessary to further test the original research hypotheses. Path analysis, as an effective tool within SEM suitable for handling continuous variable data, builds upon the analysis of correlations between variables to explore and infer potential causal chains. This study employed the Maximum Likelihood (ML) method for hypothesis testing of path causal relationships. In testing path coefficients, a research hypothesis is accepted only if the standardized coefficient is significantly different from zero and the p-value is < 0.05. Otherwise, the null hypothesis is retained. Table 9 path coefficients of the structural equation model of oral health service utilisation behaviour of older people Path Unstd. Coeff. S.E. C.R. p -value BIC←PBE .276 .067 4.140 *** BIC←PS .187 .074 2.512 .012 BIC←SN .337 .065 5.203 *** BIC←PBA − .070 .064 -1.089 .276 B←BIC .834 .129 6.461 *** B←PS − .159 .102 -1.554 .120 B←PBA − .034 .090 − .382 .702 B←PBE .330 .097 3.396 *** B←SN .008 .089 .089 .929 Notes : ①***p < 0.001, **p < 0.01, *p < 0.05; ②BIC = Behavioral Intention & Control; PBE = Perceived Benefit; PS = Perceived Threat; SN = Subjective Norm; PBA = Perceived Barrier; B = Behavior Analysis of Table 9 reveals:(1)Perceived Benefit (PBE) and Subjective Norm (SN) had significant effects on Behavioral Intention & Control (BIC) (p 0.05);(3)Behavioral Intention & Control (BIC) and Perceived Benefit (PBE) had significant effects on Behavior (B) (p 0.05). Consequently, the hypothesis validation results are presented in Table 10 . As shown, hypotheses H1, H2, H7, and H9 were supported in this study, while the remaining hypotheses were not supported. Table 10 Hypothesis Validation Results Hypo. Statement Result H1 Perceived Benefit → Behavioral Intention & Control (+) Supported H2 Perceived Benefit → Behavior (+) Supported H3 Perceived Barrier → Behavioral Intention & Control (-) Not Supported H4 Perceived Barrier → Behavior (-) Not Supported H5 Perceived Threat → Behavioral Intention & Control (+) Not Supported H6 Perceived Threat → Behavior (+) Not Supported H7 Subjective Norm → Behavioral Intention & Control (+) Supported H8 Subjective Norm → Behavior (+) Not Supported H9 Behavioral Intention & Control → Behavior (+) Supported The magnitude of the path relationships, i.e., the influence between latent variables, is expressed through the path coefficients. Extracting the standardized path coefficients and reconstructing the model diagram based on the supported hypotheses (H1, H2, H7, H9), the overall path relationships influencing elderly oral health service utilization behavior are depicted in Fig. 5 . Note Arrows indicate significant paths. Values represent standardized coefficients. Total effect of BIC on B is 0.593 As illustrated in Fig. 4 − 2, the influence of the four latent variables (PBE, SN, BIC, B) on elderly oral health service utilization behavior manifests through three primary pathways: (1)The variable "Behavioral Intention & Control (BIC)" has a direct positive effect on "Oral Health Service Utilization Behavior (B)", and this path exhibits the largest total effect (β = 0.593);(2)The variable "Perceived Benefit (PBE)" can both directly positively influence elderly oral health service utilization behavior (B) and indirectly positively influence it through its effect on the "Behavioral Intention & Control (BIC)" variable; (3)The variable "Subjective Norm (SN)" can only indirectly positively influence elderly oral health service utilization behavior (B) through the mediating role of the "Behavioral Intention & Control (BIC)" variable. 2.3.3 Effect Analysis The effects within the model can be categorized into direct effects, indirect effects, and their composite total effects. The direct effect is represented by the standardized path coefficient between variables. The indirect effect is calculated as the product of the standardized path coefficients along a mediated pathway. The total effect is the sum of the direct and indirect effects. Based on the magnitude of total effects, the primary factors influencing elderly oral health service utilization behavior were ranked in descending order as follows: 1) Behavioral Intention & Control (BIC), 2) Perceived Benefit (PBE), and 3) Subjective Norm (SN). Specific values are presented in Table 11 . Table 11 Analysis of model effects Dependent Variable Independent Variable Direct Effect Indirect Effect Total Effect Behavior (B) BIC 0.593 - 0.593 PBE 0.239 0.165 0.404 SN - 0.216 0.216 BIC SN 0.365 - 0.365 PBE 0.282 - 0.282 Notes : ① B = Oral Health Service Utilization Behavior; BIC = Behavioral Intention & Control; PBE = Perceived Benefit; SN = Subjective Norm; ② "-" indicates no effect present. The empirical data demonstrate that:(1)The variable "Behavioral Intention & Control (BIC)" exerted the strongest influence on "Oral Health Service Utilization Behavior (B)" (Total Effect = 0.593); (2)The variable "Perceived Benefit (PBE)" had the second strongest influence (Total Effect = 0.404); (3)The variable "Subjective Norm (SN)" had the smallest influence, with no direct effect and only an indirect effect (Indirect Effect = 0.216; Total Effect = 0.216). Furthermore, regarding the factors influencing "Behavioral Intention & Control (BIC)":Both "Subjective Norm (SN)" and "Perceived Benefit (PBE)" exerted only direct effects (0.365 and 0.282, respectively), with no indirect pathways. Discussion This study aimed to identify key factors requiring intervention in elderly oral health service utilization behavior. Utilizing the classic Health Belief Model (HBM) and Theory of Planned Behavior (TPB) frameworks, we integrated and optimized these models considering the specific characteristics of the elderly population, constructing a composite model to better explain oral health service utilization behavior among older adults. Key findings based on the results are discussed below: (1) Descriptive Analysis: The Fourth National Oral Health Epidemiological Survey 3 revealed concerning oral health status among the 65–74 age group, suggesting a "high need" for oral health services. However, our study on the current status of oral health service utilization among the elderly in China identified a "low utilization" phenomenon. This contradiction between "high need and low utilization" underscores the critical necessity for interventions targeting elderly oral health service utilization behaviors. Therefore, there is an urgent need to intervene on influencing factors to improve the adoption rate of oral health utilization behaviors and promote elderly oral health. (2) Model Fit Analysis: The model demonstrated reasonable fit indices, indicating its suitability as a tool for explaining and predicting elderly oral health service utilization behavior. Such composite models can offer novel research perspectives and approaches for understanding this complex behavior. (3) Path Analysis: Three significant pathways (p < 0.001) were identified:①A direct positive path from "Behavioral Intention & Control (BIC)" to "Oral Health Service Utilization Behavior (B)". When elderly individuals possess stronger behavioral intention and perceived control, their capability and autonomy to perform the behavior are enhanced. These individuals are also more likely to believe in the effectiveness and benefits of utilizing oral health services, thereby increasing the likelihood of performing the behavior. This finding not only aligns with the fundamental assumptions of TPB but is also supported by multiple empirical studies 24 – 26 ; ②The influence path of the "Perceived Benefit (PBE)" variable resembles findings by Kiyak et al. 27 . PBE can both directly positively influence elderly oral health service utilization behavior (B) and indirectly influence it through BIC acting as a mediating variable. This conclusion bridges constructs from distinct models – Perceived Benefit from classic HBM and Behavioral Intention/Perceived Behavioral Control from traditional TPB – establishing a novel influence pathway for elderly oral health service utilization behavior; ③Subjective Norm (SN) did not establish a direct link with behavior (B) in the composite model. Instead, it exerted an indirect positive effect on elderly oral health service utilization behavior through the mediating role of BIC. This pathway of SN influencing behavior, solely through indirect means, is consistent with the classical TPB. (4) Effect Analysis: The newly conceptualized "Behavioral Intention & Control (BIC)" demonstrated the most significant influence on "Oral Health Service Utilization Behavior (B)" among all factors (Total Effect = 0.593). Research by Gamma et al. confirms the high correlation between behavioral intention and behavior 28 . Furthermore, studies 29 indicate that perceived behavioral control is a major predictor of both oral health behavioral intention and actual behavior, explaining 34% of behavioral variance. This supports BIC's role as a crucial predictor of elderly oral health service utilization behavior. Perceived Benefit (PBE) ranked second in influence (Total Effect = 0.404), followed by Subjective Norm (SN) (No direct effect, only Indirect Effect = 0.216). In social life, perceived benefit is a powerful driver of individual behavior. Compared to external directives, elderly individuals are more inclined to perform behaviors they perceive as personally beneficial. Furthermore, regarding the factors influencing BIC, both SN and PBE exerted only direct effects (0.365 and 0.282, respectively). As a vulnerable group, elderly individuals often consult family, friends, or healthcare professionals when encountering unfamiliar matters. These opinions significantly impact their behavioral intention and control (SN had a larger direct effect on BIC [0.365] than PBE [0.282]). Concurrently with this social influence, elderly individuals often receive tangible assistance from these sources (e.g., family members providing accompaniment to dental visits). This assistance not only boosts behavioral intention but also directly enhances the resources and capability required to perform oral health service utilization behaviors. Based on the identified key dimensions—Perceived Benefit (PBE), Subjective Norm (SN), and Behavioral Intention & Control (BIC)—we propose the following multi-level intervention strategies: (1)Enhancing Perceived Benefit (PBE):①Individual/Family Level: Recognize the decline in self-directed learning capacity among the elderly. Family members should actively accompany elders, share relevant oral health knowledge, watch educational TV programs together, consult oral healthcare books with them, and answer their questions; ②Societal Level: Mainstream media should prioritize oral health promotion. Healthcare institutions could establish specialized medical teams for community outreach programs, enhancing interactivity during educational sessions and bridging the gap with the public through community-based initiatives; ③Government bodies should optimize the allocation of oral health human resources and reasonably distribute oral healthcare resources to improve service experiences, thereby enhancing perceived benefits. (2)Leveraging Subjective Norm (SN):①Individual Level: It is essential for elderly individuals to actively listen to and consider advice from relatives, friends, or healthcare personnel regarding oral health; ②Family Level: Families can foster a home environment that values oral health, encourage elders to develop good oral hygiene habits, and regularly remind and accompany them to utilize oral health services; ③Societal Level: Similar to the family approach, society-wide oral health education should be promoted to cultivate a broader societal atmosphere that prioritizes oral health. (3)Strengthening Behavioral Intention & Control (BIC): This dimension, encompassing classical concepts of behavioral intention and perceived behavioral control, is the most influential in the model and serves as a proximal determinant of behavior. Recommendations under PBE and SN will inherently contribute to improving BIC levels. Additionally, as BIC includes the capability to perform the behavior, this can be bolstered by external support: Practical Support: Examples include family members accompanying elders to dental appointments and hospitals improving service accessibility and convenience.Core Insight: Genuine care and companionship for elders may be the most effective catalyst for promoting their healthcare-seeking behavior. Conclusion Under the analytical framework integrating the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB), this study employed empirical data to investigate the key influencing factors and underlying mechanisms of the "low utilization" phenomenon in oral health service utilization behavior among the elderly. Within the composite model, the identified influencing factors operate through distinct pathways: (1)The variable "Behavioral Intention & Control (BIC)" exerts a direct positive effect on "Elderly Oral Health Service Utilization Behavior (B)", demonstrating the largest total effect; (2)The variable "Perceived Benefit (PBE)" positively influences elderly oral health service utilization behavior both directly and indirectly by affecting the "Behavioral Intention & Control (BIC)" variable; (3)The variable "Subjective Norm (SN)" can only positively influence elderly oral health service utilization behavior indirectly, mediated through the "Behavioral Intention & Control (BIC)" variable. Therefore, it is recommended to implement strategies focusing on enhancing social support, addressing cognitive misconceptions, and strengthening the expectations and support from family, friends, and healthcare professionals. These interventions can effectively target Subjective Norm (SN), Behavioral Intention & Control (BIC), and Perceived Benefit (PBE), ultimately promoting proactive utilization of oral health services among the elderly population. Collectively, this study provides a scientific foundation and effective strategies for improving oral health status among older adults, contributing novel perspectives and insights to advance the process of healthy aging. Declaration of generative AI and AI-assisted technologies in the writing process. Statement: During the preparation of this work the author(s) used [Deepseek] in order to [Linguistic refinement]. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. Declarations Conflict of interest disclosure : There are no conflicts in relation to this study. Ethics approval statement : This cross-sectional study was approved bybBoard of Medical Ethics Committee of Foshan University(No. 2022001). Written consent from all participants was collected before the implementation of the study. This study was conducted in full accordance with the Helsinki Declaration. Clinical Trial Registration Not applicable (observational study). Patient consent statement Written consent from all participants was collected before the implementation of the study. Funding: This study was funded by a grant from National Natural Science Foundation of China (grant number: 72204046), a grant from Guangdong Philosophy and Social Science Foundation (grant number: GD24XGL003), a grant from Foshan Science and Technology Innovation Project (grant number: 2320001007325), and a grant from Guangdong Basic and Applied Basic Research Foundation (grant number: 2019A1515111102). Author Contribution (I) Conception and design: Xiaoyuan Pan, Shuwen Su.(II) Administrative support: Shuwen Su. (III) Provision of study materials : Xiaoyuan Pan,Jianli Li,Leyi Han ,Xinyue Chen.(IV) Collection and assembly of data:Xiaoyuan Pan,Jianli Li,Leyi Han ,Xinyue Chen.(V) Data analysis and interpretation: Shuwen Su, Xiaoyuan Pan,Jianli Li(VII) Final approval of manuscript: All authors Data Availability All data generated or analysed during this study are included in this published article (and its Supplementary Information files).The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Li, Y. The study on oral health service need, demand and utilization of40597 persons undergoing physical examination in Zunyi City , (2016). Mou, F. Theoretical and Practical Research on the CPC’s Response to the Aging Population Since the 18th CPC National Congress (Southwest Jiaotong University, 2022). Wang, X. ​The Fourth National Oral Health Epidemiological Survey Report 127 (The People's Health Press Co., Ltd, 2018). McNeil, D. W. et al. Consensus Statement on Future Directions for the Behavioral and Social Sciences in Oral Health. J. Dent. Res. 101 , 619–622. https://doi.org/10.1177/00220345211068033 (2022). Desai, J. & Nair, R. U. Oral Health Factors Related to Rapid Oral Health Deterioration among Older Adults: A Narrative Review. J. Clin. Med. 12 https://doi.org/10.3390/jcm12093202 (2023). Susan, M. et al. The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions. Ann. Behav. Med. 46 https://doi.org/10.1007/s12160-013-9486-6 (2013). Abraham, C., Kelly, M. P., West, R. & Michie, S. The UK National Institute for Health and Clinical Excellence public health guidance on behaviour change: a brief introduction. Psychol. Health Med. 14 , 1–8. https://doi.org/10.1080/13548500802537903 (2009). Tonetti, M. et al. Principles in prevention of periodontal diseases: Consensus report of group 1 of the 11th European Workshop on Periodontology on effective prevention of periodontal and peri-implant diseases. Journal of clinical periodontology , S5-11 (2015). https://doi.org/10.1111/jcpe.12368 Chan, C. C. K., Chan, A. K. Y., Chu, C. H. & Tsang, Y. C. Theory-based behavioral change interventions to improve periodontal health. Front. Oral Health . 4 , 1067092. https://doi.org/10.3389/froh.2023.1067092 (2023). Yang, T. 32–34 (People's Health Publishing House, (2007). Mohammadkhah, F. & Kamyab, A. Khani Jeihooni, A. Oral cancer preventive behaviors in rural women: application of the theory planned behavior. Front. oral health . 5 , 1408186. https://doi.org/10.3389/froh.2024.1408186 (2024). Zhu, J. Research on Influence Path of Buckwheat ProductConsumption Based on Health Belief Model andTheory of Planned (A&F University, 2021). Northwest. Yuqin, L. Research on the Occupational HealthBehavior of Construction Workers Based onthe Integration of the TPB with the HBM , Chongqing University (2019). Wang Factors influencing medical seeking intention of perimenopausal andpostmenopausal women: A study based on an integrated model (Jilin University, 2020). Ajzen, I. CONSTRUCTING A THEORY OF PLANNED BEHAVIOR QUESTIONNAIRE , https://people.umass.edu/aizen/pdf/tpb.intervention.pdf (. Wang, J., Geng, J. & Xiao, Y. From Intention to Behavior:An Integrated Model of Academic Entrepreneurial Behavior Based on Theory of Planned Behavior. Foreign Econ. Manage. 42 , 18 (2020). Ajzen, I. The theory of planned behavior, organizational behavior and human decision processes. J. Leisure Res. 50 , 176–211 (1991). Nakazono, T. T., Davidson, P. L. & Andersen, R. M. Oral health beliefs in diverse populations. Adv. Dent. Res. 11 , 235–244. https://doi.org/10.1177/08959374970110020601 (1997). Xiang, B., Wong, H. M., Cao, W., Perfecto, A. P. & McGrath, C. P. J. Development and validation of the Oral health behavior questionnaire for adolescents based on the health belief model (OHBQAHBM). BMC Public. Health . 20 https://doi.org/10.1186/s12889-020-08851-x (2020). Ju, T. Using the Integrated Theory of Health Behavior to investigate theself-management behavior among middle-aged patients with stroke (Qingdao University, 2018). Sun, T. Predicting Incontinent Women's Help-seeking Intention: AModel Based on The Theory of Planned Behavior (Shandong University, 2013). Wan, M. et al. Analysis of Obesity among Malaysian University Students: A Combination Study with the Application of Bayesian Structural Equation Modelling and Pearson Correlation. International J. Environ. Res. Public. Health 16 (2019). Wolf, E. J., Harrington, K. M., Clark, S. L. & Miller, M. W. Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educational Psychol. Meas. 73 , 913–934. https://doi.org/10.1177/0013164413495237 (2013). Bramantoro, T., Basiroh, E., Berniyanti, T., Setijanto, R. D. & Irmalia, W. R. Intention and Oral Health Behavior Perspective of Islamic Traditional Boarding School Students Based on Theory of Planned Behavior. Pesquisa Brasileira em Odontopediatria e Clínica Integrada . 20 https://doi.org/10.1590/pboci.2020.039 (2020). Li, W., Guo, J., Liu, W., Tu, J. & Tang, Q. Effect of older adults willingness on telemedicine usage: an integrated approach based on technology acceptance and decomposed theory of planned behavior model. BMC Geriatr. 24 , 765. https://doi.org/10.1186/s12877-024-05361-y (2024). Wang, X., Lee, C. F., Jiang, J., Zhang, G. & Wei, Z. Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model. Behavioral Sciences 13 (2023). Kiyak, H. A. & Reichmuth, M. Barriers to and Enablers of Older Adults’ Use of Dental Services. J. Dent. Educ. 69 , 975–986. doi.org/10.1002/j.0022-0337.2005.69.9.tb03994.x (2005). https://doi.org/https:// Gamma, A. E. et al. Contextual and psychosocial factors predicting Ebola prevention behaviours using the RANAS approach to behaviour change in Guinea-Bissau. BMC Public. Health . 17 , 446. https://doi.org/10.1186/s12889-017-4360-2 (2017). Shi, H. et al. Application of the extended theory of planned behavior to understand Chinese students’ intention to improve their oral health behaviors: a cross-sectional study. BMC Public. Health . 21 , 2303. https://doi.org/10.1186/s12889-021-12329-9 (2021). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7235151","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":609871359,"identity":"db84f31c-9520-4c3b-89c8-b74f07d401f8","order_by":0,"name":"Xiaoyuan Pan","email":"","orcid":"","institution":"Foshan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyuan","middleName":"","lastName":"Pan","suffix":""},{"id":609871360,"identity":"c3395bc8-47ad-46bb-9c33-7d3dae7ad07c","order_by":1,"name":"Shuwen 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Model（HBM）\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/3020cc220678e005f5dff57c.jpg"},{"id":105328107,"identity":"22d55805-f4cf-4cf4-8480-68c324778571","added_by":"auto","created_at":"2026-03-24 19:40:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":140832,"visible":true,"origin":"","legend":"\u003cp\u003eTheory of Planned Behavior（TPB）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003e\u003cem\u003eThe dashed line signifies that accurate perceived behavioral control can serve as a valid proxy measure for actual control conditions, enabling direct prediction of the likelihood of behavior occurrence\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/4df29dc9f25983a6cc43515a.jpg"},{"id":105565161,"identity":"8424d675-2e27-4fc1-9894-ad438cecf18a","added_by":"auto","created_at":"2026-03-27 12:52:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":265674,"visible":true,"origin":"","legend":"\u003cp\u003ePath relationship assumptions between the newly constructed composite model components\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eH1: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ePerceived Benefit (PBE) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH2:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Perceived Benefit (PBE) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH3:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Perceived Barrier (PBA) has a negative effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH4:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Perceived Barrier (PBA) has a negative effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH5:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Perceived Threat (PT) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH6:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Perceived Threat (PT) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH7: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eSubjective Norm (SN) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH8: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eSubjective Norm (SN) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eH9: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eBehavioral Intention and Control (BIC) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/6ebf5d4053a4b62a8dedb584.jpg"},{"id":105728009,"identity":"4d52b431-2cbf-44b5-a9c4-06c8ab3b96bd","added_by":"auto","created_at":"2026-03-30 11:08:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46121,"visible":true,"origin":"","legend":"\u003cp\u003eHypothetical modelling diagram\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/9806cb94d200e048a8121bc7.jpg"},{"id":105328104,"identity":"a3e6fd34-3b06-4e05-9d2a-36381cea4052","added_by":"auto","created_at":"2026-03-24 19:40:47","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":65551,"visible":true,"origin":"","legend":"\u003cp\u003eGeneral pathways of behavioural mechanisms for oral health service utilisation by older people\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eNote:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Arrows indicate significant paths. Values represent standardized coefficients. Total effect of BIC on B is 0.593\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/3e149d7a8204e1c553e7202d.jpg"},{"id":105898044,"identity":"c3bafaa3-a6b5-445e-9ca2-41194617f581","added_by":"auto","created_at":"2026-04-01 08:59:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2158958,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7235151/v1/61d53f6b-5ccd-4a07-a4e1-e7967b0850d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eOral Health Service Utilization Behavior and Its Influencing Factors Among Older Adults: An Empirical Study Based on the Composite Health Behavior Model\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral health service utilization is defined as \"the actual amount of dental services received by residents, reflecting both service provision and institutional efficiency\" \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Regular utilization enables early detection and management of oral diseases through preventive care, effectively maintaining oral health while reducing long-term treatment frequency and costs. As China's population rapidly ages\u0026mdash;with adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years increasing by 5.44% from 2010 to 2020 and reaching 264.02\u0026nbsp;million (18.7% of the population) in 2020 \u003csup\u003e2\u003c/sup\u003e\u0026mdash;older adults face disproportionately poor oral health. The Fourth National Oral Health Survey revealed alarming statistics among those aged 65\u0026ndash;74: 98% had Decayed/Missing/Filled Teeth (DMFT), 90.3% exhibited dental calculus, and only 9.3% maintained periodontal health \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. This underscores an urgent need to address oral health disparities in China's aging population.\u003c/p\u003e \u003cp\u003eThese findings indicate suboptimal oral health behaviors among older adults in China, where behavioral factors constitute critical modifiable targets for intervention.​​ The determinants of elderly health behavior are multifaceted, yet empirical applications of established behavioral theories (e.g., HBM, TPB) remain limited in oral health research within China's context\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Existing studies predominantly focus on clinical outcomes rather than comprehensively exploring psychosocial determinants, resulting in insufficient theoretical foundations for evidence-based interventions\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Behavioral theories transcend mere categorization of health habits; they provide mechanistic frameworks for designing targeted interventions across individual, community, and policy levels\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. As emphasized by the UK National Institute for Health and Care Excellence (NICE), \"theory-based behavior change interventions demonstrate greater efficacy than atheoretical approaches\" \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Globally, preventive dentistry increasingly employs behavioral theories to enhance self-care and treatment adherence, evidenced by the 11th European Workshop on Periodontology recommending psychological methods for plaque control in periodontal management \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Consequently, theoretically grounded identification of influencing factors and pathways represents the vanguard of oral health interventions \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong behavioral frameworks, the Health Belief Model (HBM) and Theory of Planned Behavior (TPB) are most established. This study therefore integrates HBM and TPB to develop a composite model specific to elderly oral health service utilization, aiming to elucidate behavioral mechanisms and inform targeted interventions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003e2.1 Theoretical Framework and Composite Model Construction\u003c/h2\u003e\n \u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003e2.1.1 Health Belief Model (HBM)\u003c/h2\u003e\n \u003cp\u003eThe core of the Health Belief Model (HBM) is perception, which refers to the perception of disease threat and the evaluation of behaviors. This encompasses: Perceived Susceptibility, Perceived Severity, Perceived Benefits, and Perceived Barriers. Subsequent scholars have further developed two additional core components: Self-Efficacy and Cues to Action. Self-efficacy represents the assessment of one\u0026apos;s ability to successfully adopt a health behavior, while cues to action are stimuli that prompt the initiation of action, such as noticing gum swelling, pain, or bleeding\u003csup\u003e10\u003c/sup\u003e. A schematic diagram of the Health Belief Model is shown in Fig.\u0026nbsp;1.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003e2.1.2 Theory of Planned Behavior (TPB)\u003c/h2\u003e\n \u003cp\u003eThe Theory of Planned Behavior (TPB) comprises five main components: Attitude toward the Behavior, Subjective Norm, Perceived Behavioral Control, Behavioral Intention, and Behavior\u003csup\u003e11\u003c/sup\u003e. TPB posits that behavior is determined by behavioral intention. Behavioral intention, in turn, is influenced by three factors: attitude toward the behavior, subjective norm, and perceived behavioral control. A schematic diagram of the Theory of Planned Behavior is shown in Fig.\u0026nbsp;2.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u0026nbsp;\u003c/strong\u003e\u003cem\u003eThe dashed line signifies that accurate perceived behavioral control can serve as a valid proxy measure for actual control conditions, enabling direct prediction of the likelihood of behavior occurrence\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e2.1.3 Integrated Model Development\u003c/h2\u003e\n \u003cp\u003eThe contents of the HBM and TPB are closely interrelated. Therefore, during the integration process in this study, similar dimensions were streamlined. In the TPB, Attitude toward the Behavior can be divided into positive and negative attitudes. Conversely, the HBM includes Perceived Benefits and Perceived Barriers, which correspond to positive and negative attitudes, respectively, in terms of cost-benefit analysis\u003csup\u003e12\u003c/sup\u003e. Consequently, in this study\u0026apos;s integrated model, the two variables Perceived Benefits and Perceived Barriers jointly replace the Attitude toward the Behavior variable from the TPB. Furthermore, Perceived Susceptibility and Perceived Severity within the HBM exhibit a high degree of correlation. Precedents exist in previous integrated model research where scholars have combined these two constructs\u003csup\u003e13\u003c/sup\u003e. Thus, this study merged them into a single variable termed Perceived Threat (encompassing perceived risk and severity).\u003c/p\u003e\n \u003cp\u003eBoth Self-Efficacy (HBM) and Perceived Behavioral Control (TPB) pertain to an individual\u0026apos;s beliefs about their capabilities: Self-efficacy focuses on confidence in one\u0026apos;s own ability, while perceived behavioral control emphasizes the sense of control over the environment or situation. Both significantly influence an individual\u0026apos;s behavioral choices and psychological state and should therefore be comprehensively considered in practical applications\u003csup\u003e14\u003c/sup\u003e. To streamline the model, this study does not separately discuss self-efficacy. Perceived Behavioral Control encompasses two aspects: capability to perform the behavior and autonomy in performing it\u003csup\u003e15\u003c/sup\u003e. The concept of behavioral autonomy is somewhat analogous to behavioral intention. Moreover, within the TPB, perceived behavioral control can also moderate the influence of attitudes and subjective norms on behavioral intention, as well as the influence of behavioral intention on behavior. Behavior is the result of the combined effect of behavioral intention and perceived behavioral control\u003csup\u003e16\u003c/sup\u003e. Perceived behavioral control can thus be used alongside behavioral intention to predict the occurrence of behavior, given the correlation between them\u003csup\u003e17\u003c/sup\u003e. Consequently, this study introduces a new dimension\u0026mdash;\u0026quot;\u003cstrong\u003eBehavioral Intention and Control (BIC)\u003c/strong\u003e\u0026quot;\u0026mdash;which encompasses the original constructs of perceived behavioral control and behavioral intention.\u003c/p\u003e\n \u003cp\u003eThe integrated model comprises six variables: ① Perceived Benefit (PBE), ② Perceived Barrier (PBA), ③ Perceived Threat (PS), ④ Subjective Norm (SN), ⑤ Behavioral Intention and Control (BIC), and ⑥ Behavior (B). Table 1 details the integration of the original components from the two models. Definitions of the variables in the newly constructed integrated model are provided in Table 2. The hypothesized path relationships between the model components are illustrated in Fig. 3.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eIntegration of Original Components from Two Theoretical Models\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOriginal Component\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSource Model\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eComposite Model Component\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePositive Attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\n \u003cp\u003e① Perceived Benefit, ② Perceived Barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNegative Attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTPB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Benefit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Susceptibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e③Perceived Threat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSubjective Norm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e④ Subjective Norm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Behavioral Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003e⑤Behavioral Intention and Control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBehavioral Intention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eTPB\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSelf-Efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBehavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHBM、TPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e⑥Behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eNewly constructed composite model building block variable definitions\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eDefinition\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e①Perceived Benefit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSubjective evaluation held by the elderly regarding the potential positive outcomes of engaging in oral health service utilization behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e②Perceived Barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSubjective assessment of the difficulties potentially encountered during the process of oral health service utilization behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e③Perceived Threat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSubjective assessment of the risk of disease and its consequences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e④Subjective Norm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIndividual\u0026apos;s subjective perception of social pressure concerning whether or not to adopt oral health service utilization behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e⑤Behavioral Intention and Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCapability and autonomy to perform oral health service utilization behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e⑥Behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eOral health service utilization behavior\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e: \u003cem\u003ePerceived Benefit (PBE) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived Benefit (PBE) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived Barrier (PBA) has a negative effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived Barrier (PBA) has a negative effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH5\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived Threat (PT) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH6\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003ePerceived Threat (PT) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH7\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSubjective Norm (SN) has a positive effect on Behavioral Intention and Control (BIC).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH8\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSubjective Norm (SN) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eH9\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eBehavioral Intention and Control (BIC) has a positive effect on Behavior (B).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e2.2 Research Methods\u003c/h2\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e2.2.1 Questionnaire Design\u003c/h2\u003e\n \u003cp\u003eA questionnaire was self-developed by integrating the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). This study referenced established scales and drew upon previous research findings to formulate items for each dimension: (1)Items for the Behavior (B), Perceived Benefit (PBE), Perceived Barrier (PBA), and Perceived Threat (PS) dimensions were developed based on the research by Nakazono et al. (1997)\u003csup\u003e18\u003c/sup\u003e and Xiang et al. (2020)\u003csup\u003e19\u003c/sup\u003e(2)Items for Subjective Norm (SN) were adapted from the work of Liu Yuqin (2019)\u003csup\u003e13\u003c/sup\u003e; (3)Items for Behavioral Intention \u0026amp; Control (BIC) were developed referencing studies by Ju Taoran (2018)\u003csup\u003e20\u003c/sup\u003e and Sun Tao (2013)\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eThe questionnaire was specifically designed considering the behavioral and psychological characteristics of the elderly population. It underwent refinement through expert review and a pilot pre-survey before finalization. The final questionnaire comprised 26 items across six dimensions: Behavior (B), Perceived Benefit (PBE), Perceived Barrier (PBA), Perceived Threat (PS), Subjective Norm (SN), and Behavioral Intention \u0026amp; Control (BIC). Given the potentially limited comprehension abilities of elderly respondents, all items utilized a 5-point Likert scale, ranging from \u0026quot;Strongly Disagree\u0026quot; (scored 1) to \u0026quot;Strongly Agree\u0026quot; (scored 5), with higher scores indicating more positive responses.\u003c/p\u003e\n \u003cp\u003eQuestionnaire Quality Assessment: Exploratory Factor Analysis (EFA) extracted six principal components, accounting for a cumulative variance contribution rate of 62.616%. Factor loadings for all items ranged from 0.517 to 0.817. The overall Cronbach\u0026apos;s \u0026alpha; coefficient for the scale was 0.864, indicating good reliability and validity.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e2.2.2 Data Collection\u003c/h2\u003e\n \u003cp\u003eFrom July to September 2023, a convenience sampling method was employed to recruit 356 elderly individuals from five communities in Foshan and Guangzhou cities for questionnaire surveys.Inclusion Criteria:(1)Aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years; (2)Cognitively clear and able to complete the questionnaire independently, or able to complete it successfully with assistance from researchers; (3)Provided informed consent and participated in the survey.\u003c/p\u003e\n \u003cp\u003eBased on established recommendations for minimum sample size in structural equation modeling (e.g., requiring 300 samples for models with 5\u0026ndash;7 variables), a target sample size was set. A total of 352 questionnaires were returned. After excluding 26 invalid responses, 326 valid questionnaires were obtained. The scale developed in this study contained 26 measurement items; the final sample size (n\u0026thinsp;=\u0026thinsp;326) met the common \u0026quot;10 times rule\u0026quot; (minimum 10 cases per measured item), allowing for robust exploration of complex variable relationships within the model\u003csup\u003e22,23\u003c/sup\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e1.2.3 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eData processing and analysis were performed using SPSS software (version 19.0) and AMOS software (version 24.0). (1)Descriptive statistics (frequencies, percentages) were used to characterize the sociodemographic profile of the surveyed elderly participants and describe the current status of their oral health service utilization behavior; (2)Structural Equation Modeling (SEM) was employed to assess the goodness-of-fit of the integrated model of elderly oral health service utilization behavior; (3)Effect analysis and path analysis were conducted on the integrated model within the SEM framework.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Analysis of Sociodemographic Characteristics\u003c/h2\u003e\n \u003cp\u003eThis study identified the basic characteristics of the surveyed participants across dimensions including gender, age, education level, place of residence, economic status, and living arrangements. Questionnaire results showed that participants\u0026apos; ages ranged between 60 and 80 years. There were 132 male and 194 female participants. The proportion of participants with education levels above high school or secondary specialized education was relatively low. Only 11% of the elderly respondents self-reported experiencing family economic difficulties. A majority (82.3%) of the elderly lived with their spouse or children. The sample covered younger-old (60\u0026ndash;69 years), middle-old (70\u0026ndash;79 years), and older-old (\u0026ge;\u0026thinsp;80 years) age groups. Specific details are presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eUnivariate analysis was employed to examine the variables of gender, age, education level, etc., within the personal background of the elderly participants, aiming to explore differences in psychological and behavioral manifestations of oral health service utilization across different group characteristics. As these variables could not be incorporated into the Structural Equation Model (SEM), univariate analysis was conducted using SPSS software (version 19.0).\u003c/p\u003e\n \u003cp\u003eEach of the four background variables\u0026mdash;age, education level, economic status, and place of residence\u0026mdash;was divided into at least three groups. Therefore, one-way Analysis of Variance (ANOVA) was used to test for between-group differences in each variable across the questionnaire dimensions. Gender and place of residence were divided into only two groups, so independent samples *t*-tests were used for analysis.\u003c/p\u003e\n \u003cp\u003eThe results indicated:(1)Significant differences were found for gender and age in individual aspects of the model variables; (2)Significant differences were found across multiple aspects for participants grouped by education level, place of residence, and economic status; (3)No significant differences were found among participants grouped by living arrangements (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).Detailed data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic characteristics of older adults interviewed (n\u0026thinsp;=\u0026thinsp;326)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e40.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e59.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e60\u0026ndash;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e52.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70\u0026ndash;79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e33.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e13.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e34.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e24.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHigh school / Sec. spec.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e20.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCollege / Associate degree\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e16.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMaster\u0026apos;s degree+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003ePlace of Residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e45.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e54.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\n \u003cp\u003eEconomic Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eVery affluent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRelatively comfortable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e29.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFinancially sufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e56.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSome financial difficulty\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e9.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSevere financial difficulty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\n \u003cp\u003eLiving Arrangements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e14.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLiving with spouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e43.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLiving with children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e38.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e3.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBehavioural and psychological variables of oral health service utilisation among the elderly grouped by socio-demographic factors and psychological variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eBehavior (B)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ePerceived Benefit (PBE)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003ePerceived Barrier (PBA)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eSubjective Norm (SN)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003ePerceived Threat (PS)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003eBehavioral Intention \u0026amp; Control (BIC)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003eStat.\u0026sect;\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-1.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.594*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.089*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;194)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e60\u0026ndash;69 (n\u0026thinsp;=\u0026thinsp;172)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.510*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.557*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e70\u0026ndash;79 (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;80 (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePrimary (n\u0026thinsp;=\u0026thinsp;112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.083***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.184*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.276*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.716***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.993**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eJunior HS (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eHS/Secondary (n\u0026thinsp;=\u0026thinsp;68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e2.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCollege+ (n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMaster\u0026apos;s+ (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e4.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e4.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e4.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e4.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRural (n\u0026thinsp;=\u0026thinsp;148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-4.526***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-2.497*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.361*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-1.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e=-3.407**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUrban (n\u0026thinsp;=\u0026thinsp;178)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEconomic Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eVery affluent (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.988*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.277*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.426*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eComfortable (n\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSufficient (n\u0026thinsp;=\u0026thinsp;184)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSome difficulty (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSevere difficulty (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLiving Arrangement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAlone (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e3.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eWith spouse (n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eWith children (n\u0026thinsp;=\u0026thinsp;126)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOther (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c3\"\u003e\n \u003cp\u003e3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c5\"\u003e\n \u003cp\u003e4.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c7\"\u003e\n \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c9\"\u003e\n \u003cp\u003e4.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c11\"\u003e\n \u003cp\u003e3.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\" colname=\"c13\"\u003e\n \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\"\u003e\u003cstrong\u003eNotes\u003c/strong\u003e:①\u003cem\u003e\u0026sect;: *t*-value for two-group comparisons; F-value for three or more groups;\u003c/em\u003e ②\u003cem\u003eSE: Standard Error; SD: Standard Deviation;\u003c/em\u003e ③\u003cem\u003eSignificance: ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05;\u003c/em\u003e ④\u003cem\u003eVariables: B\u0026thinsp;=\u0026thinsp;Behavior; PBE\u0026thinsp;=\u0026thinsp;Perceived Benefit; PBA\u0026thinsp;=\u0026thinsp;Perceived Barrier; SN\u0026thinsp;=\u0026thinsp;Subjective Norm; PS\u0026thinsp;=\u0026thinsp;Perceived Threat; BIC\u0026thinsp;=\u0026thinsp;Behavioral Intention \u0026amp; Control.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Descriptive Analysis of Oral Health Service Utilization Behavior\u003c/h2\u003e\n \u003cp\u003eIn the behavioral questionnaire:(1)Only 33.72% of elderly participants reported proactively learning about oral health knowledge; (2)A substantial majority (65.7%) indicated they did not proactively seek regular oral check-ups; (3)Merely 51.16% would proactively seek dental treatments (e.g., cleaning, fillings, extractions, dentures, or implants); (4)When acute oral pain affected daily life, 24.71% still reported not seeking timely medical care.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCurrent status of oral health service utilisation behaviours among older people (n\u0026thinsp;=\u0026thinsp;326)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eStrongly Disagree\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eDisagree\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eUncertain\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eStrongly Agree\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProactively seek oral health knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003cp\u003e(13.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003cp\u003e(34.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003cp\u003e(18.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003cp\u003e(27.91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003cp\u003e(5.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSchedule regular dental check-ups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003cp\u003e(19.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003cp\u003e(29.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e(17.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e(26.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003cp\u003e(7.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSeek preventive/therapeutic dental services (e.g., scaling, fillings, extractions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003cp\u003e(14.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003cp\u003e(22.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003cp\u003e(11.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003cp\u003e(38.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003cp\u003e(12.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVisit dentists promptly for acute oral pain affecting daily life\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003cp\u003e(6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003cp\u003e(10.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e(10.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003cp\u003e(46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003cp\u003e(28.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThese empirical findings indicate:(1)Low oral health awareness among the elderly: Both the awareness and behavior of proactively and regularly seeking oral health services were at alarmingly low levels, representing a key intervention point; (2)Inefficient health service utilization: Current oral health service utilization among the elderly is predominantly passive, with low efficiency. Pain-driven utilization (seeking care only when experiencing discomfort) is widespread.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Validation and Analysis of the Structural Equation Model for Elderly Oral Health Service Utilization Behavior\u003c/h2\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.1 Model Fit Verification\u003c/h2\u003e\n \u003cp\u003eBased on the theoretically hypothesized model of elderly oral health service utilization behavior established previously, a structural equation model was constructed using AMOS software (version 24.0). In this hypothesized model, four variables\u0026mdash;Perceived Benefit (PBE), Perceived Barrier (PBA), Perceived Threat (PS), and Subjective Norm (SN)\u0026mdash;were specified as exogenous latent variables, while two variables\u0026mdash;Behavioral Intention \u0026amp; Control (BIC) and Behavior (B)\u0026mdash;were specified as endogenous latent variables. This framework constituted the structural equation model for \u0026quot;Elderly Oral Health Service Utilization Behavior,\u0026quot; schematically represented in Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003ePrior to conducting path analysis, the reliability and validity of the hypothesized model must be established through model fit assessment\u0026mdash;that is, by importing data into the constructed model for estimation. Prevailing methodological consensus holds that overall goodness-of-fit indices provide a feasible means to evaluate the model\u0026apos;s fit, verifying the extent to which the hypothesized model aligns with the observed data. Consequently, this study employed a comprehensive set of overall fit indices to assess model adequacy. The global fit of the structural equation model was evaluated across three categories: absolute fit indices, incremental fit indices, and parsimonious fit indices. The formal questionnaire data were imported into AMOS 24.0 for processing. Analysis revealed the following fit indices: absolute fit indices are presented in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, incremental fit indices in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, and parsimonious fit indices in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Synthesizing these results, the model demonstrated reasonable fit, indicating that the hypothesized model for this study is acceptable.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAbsolute Fit Indices for Structural Equation Model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAbbr.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCriterion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eEvaluation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eChi-square/Degrees of Freedom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2;/df\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRoot Mean Residual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.05\u0026ndash;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.05\u0026ndash;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGoodness-of-Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAdjusted GFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.8\u0026ndash;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eIncremental Fit Indices for Structural Equation Model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAbbr.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCriterion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eEvaluation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNormed Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eRelative Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eRFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eMarginal fit*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIncremental Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTucker-Lewis Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eComparative Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u003cem\u003eRFI value (0.797) is marginally below threshold but acceptable given other indices\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eParsimonious Fit Indices for Structural Equation Model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAbbr.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eCriterion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eEvaluation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eParsimonious GFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eParsimonious Normed Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eParsimonious Comparative Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReasonable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.2 Analysis of Research Path Hypothesis Verification\u003c/h2\u003e\n \u003cp\u003eA core function of constructing a Structural Equation Model (SEM) is to conduct an in-depth analysis of the path dependency relationships among multiple complex variables, aiming to reveal potential patterns of interaction between them. Therefore, following the model fit assessment, it is necessary to further test the original research hypotheses. Path analysis, as an effective tool within SEM suitable for handling continuous variable data, builds upon the analysis of correlations between variables to explore and infer potential causal chains.\u003c/p\u003e\n \u003cp\u003eThis study employed the Maximum Likelihood (ML) method for hypothesis testing of path causal relationships. In testing path coefficients, a research hypothesis is accepted only if the standardized coefficient is significantly different from zero and the p-value is \u0026lt;\u0026thinsp;0.05. Otherwise, the null hypothesis is retained.\u0026nbsp;\u003c/p\u003e\n \u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003epath coefficients of the structural equation model of oral health service utilisation behaviour of older people\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePath\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUnstd. Coeff.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eC.R.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBIC\u0026larr;PBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e4.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBIC\u0026larr;PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBIC\u0026larr;SN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBIC\u0026larr;PBA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e.276\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eB\u0026larr;BIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e6.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eB\u0026larr;PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-1.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eB\u0026larr;PBA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eB\u0026larr;PBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eB\u0026larr;SN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: \u003cem\u003e①***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ②BIC\u0026thinsp;=\u0026thinsp;Behavioral Intention \u0026amp; Control; PBE\u0026thinsp;=\u0026thinsp;Perceived Benefit; PS\u0026thinsp;=\u0026thinsp;Perceived Threat; SN\u0026thinsp;=\u0026thinsp;Subjective Norm; PBA\u0026thinsp;=\u0026thinsp;Perceived Barrier; B\u0026thinsp;=\u0026thinsp;Behavior\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eAnalysis of Table \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e reveals:(1)Perceived Benefit (PBE) and Subjective Norm (SN) had significant effects on Behavioral Intention \u0026amp; Control (BIC) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); (2)Perceived Threat (PS) and Perceived Barrier (PBA) did not have significant effects on BIC (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05);(3)Behavioral Intention \u0026amp; Control (BIC) and Perceived Benefit (PBE) had significant effects on Behavior (B) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001);(4)Perceived Threat (PS), Perceived Barrier (PBA), and Subjective Norm (SN) did not have significant direct effects on Behavior (B) (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cp\u003eConsequently, the hypothesis validation results are presented in Table \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. As shown, hypotheses H1, H2, H7, and H9 were supported in this study, while the remaining hypotheses were not supported.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHypothesis Validation Results\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHypo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eStatement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eResult\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Benefit \u0026rarr; Behavioral Intention \u0026amp; Control (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Benefit \u0026rarr; Behavior (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Barrier \u0026rarr; Behavioral Intention \u0026amp; Control (-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Barrier \u0026rarr; Behavior (-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Threat \u0026rarr; Behavioral Intention \u0026amp; Control (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePerceived Threat \u0026rarr; Behavior (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSubjective Norm \u0026rarr; Behavioral Intention \u0026amp; Control (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSubjective Norm \u0026rarr; Behavior (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNot Supported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBehavioral Intention \u0026amp; Control \u0026rarr; Behavior (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSupported\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe magnitude of the path relationships, i.e., the influence between latent variables, is expressed through the path coefficients. Extracting the standardized path coefficients and reconstructing the model diagram based on the supported hypotheses (H1, H2, H7, H9), the overall path relationships influencing elderly oral health service utilization behavior are depicted in Fig. \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eArrows indicate significant paths. Values represent standardized coefficients. Total effect of BIC on B is 0.593\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAs illustrated in Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;2, the influence of the four latent variables (PBE, SN, BIC, B) on elderly oral health service utilization behavior manifests through three primary pathways: (1)The variable \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; has a direct positive effect on \u0026quot;Oral Health Service Utilization Behavior (B)\u0026quot;, and this path exhibits the largest total effect (\u0026beta;\u0026thinsp;=\u0026thinsp;0.593);(2)The variable \u0026quot;Perceived Benefit (PBE)\u0026quot; can both directly positively influence elderly oral health service utilization behavior (B) and indirectly positively influence it through its effect on the \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; variable; (3)The variable \u0026quot;Subjective Norm (SN)\u0026quot; can only indirectly positively influence elderly oral health service utilization behavior (B) through the mediating role of the \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; variable.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003ch2\u003e2.3.3 Effect Analysis\u003c/h2\u003e\n \u003cp\u003eThe effects within the model can be categorized into direct effects, indirect effects, and their composite total effects. The direct effect is represented by the standardized path coefficient between variables. The indirect effect is calculated as the product of the standardized path coefficients along a mediated pathway. The total effect is the sum of the direct and indirect effects. Based on the magnitude of total effects, the primary factors influencing elderly oral health service utilization behavior were ranked in descending order as follows: 1) Behavioral Intention \u0026amp; Control (BIC), 2) Perceived Benefit (PBE), and 3) Subjective Norm (SN). Specific values are presented in Table \u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n \u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAnalysis of model effects\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIndependent Variable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eDirect Effect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eIndirect Effect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eTotal Effect\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBehavior (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePBE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: ①\u003cem\u003eB\u0026thinsp;=\u0026thinsp;Oral Health Service Utilization Behavior; BIC\u0026thinsp;=\u0026thinsp;Behavioral Intention \u0026amp; Control; PBE\u0026thinsp;=\u0026thinsp;Perceived Benefit; SN\u0026thinsp;=\u0026thinsp;Subjective Norm;\u003c/em\u003e ②\u003cem\u003e\u0026nbsp;\u0026quot;-\u0026quot; indicates no effect present.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe empirical data demonstrate that:(1)The variable \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; exerted the strongest influence on \u0026quot;Oral Health Service Utilization Behavior (B)\u0026quot; (Total Effect\u0026thinsp;=\u0026thinsp;0.593); (2)The variable \u0026quot;Perceived Benefit (PBE)\u0026quot; had the second strongest influence (Total Effect\u0026thinsp;=\u0026thinsp;0.404); (3)The variable \u0026quot;Subjective Norm (SN)\u0026quot; had the smallest influence, with no direct effect and only an indirect effect (Indirect Effect\u0026thinsp;=\u0026thinsp;0.216; Total Effect\u0026thinsp;=\u0026thinsp;0.216).\u003c/p\u003e\n \u003cp\u003eFurthermore, regarding the factors influencing \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot;:Both \u0026quot;Subjective Norm (SN)\u0026quot; and \u0026quot;Perceived Benefit (PBE)\u0026quot; exerted only direct effects (0.365 and 0.282, respectively), with no indirect pathways.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to identify key factors requiring intervention in elderly oral health service utilization behavior. Utilizing the classic Health Belief Model (HBM) and Theory of Planned Behavior (TPB) frameworks, we integrated and optimized these models considering the specific characteristics of the elderly population, constructing a composite model to better explain oral health service utilization behavior among older adults. Key findings based on the results are discussed below:\u003c/p\u003e \u003cp\u003e(1) Descriptive Analysis: The Fourth National Oral Health Epidemiological Survey\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e revealed concerning oral health status among the 65\u0026ndash;74 age group, suggesting a \"high need\" for oral health services. However, our study on the current status of oral health service utilization among the elderly in China identified a \"low utilization\" phenomenon. This contradiction between \"high need and low utilization\" underscores the critical necessity for interventions targeting elderly oral health service utilization behaviors. Therefore, there is an urgent need to intervene on influencing factors to improve the adoption rate of oral health utilization behaviors and promote elderly oral health.\u003c/p\u003e \u003cp\u003e(2) Model Fit Analysis: The model demonstrated reasonable fit indices, indicating its suitability as a tool for explaining and predicting elderly oral health service utilization behavior. Such composite models can offer novel research perspectives and approaches for understanding this complex behavior.\u003c/p\u003e \u003cp\u003e(3) Path Analysis: Three significant pathways (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were identified:①A direct positive path from \"Behavioral Intention \u0026amp; Control (BIC)\" to \"Oral Health Service Utilization Behavior (B)\". When elderly individuals possess stronger behavioral intention and perceived control, their capability and autonomy to perform the behavior are enhanced. These individuals are also more likely to believe in the effectiveness and benefits of utilizing oral health services, thereby increasing the likelihood of performing the behavior. This finding not only aligns with the fundamental assumptions of TPB but is also supported by multiple empirical studies\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e; ②The influence path of the \"Perceived Benefit (PBE)\" variable resembles findings by Kiyak et al.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. PBE can both directly positively influence elderly oral health service utilization behavior (B) and indirectly influence it through BIC acting as a mediating variable. This conclusion bridges constructs from distinct models \u0026ndash; Perceived Benefit from classic HBM and Behavioral Intention/Perceived Behavioral Control from traditional TPB \u0026ndash; establishing a novel influence pathway for elderly oral health service utilization behavior; ③Subjective Norm (SN) did not establish a direct link with behavior (B) in the composite model. Instead, it exerted an indirect positive effect on elderly oral health service utilization behavior through the mediating role of BIC. This pathway of SN influencing behavior, solely through indirect means, is consistent with the classical TPB.\u003c/p\u003e \u003cp\u003e(4) Effect Analysis: The newly conceptualized \"Behavioral Intention \u0026amp; Control (BIC)\" demonstrated the most significant influence on \"Oral Health Service Utilization Behavior (B)\" among all factors (Total Effect\u0026thinsp;=\u0026thinsp;0.593). Research by Gamma et al. confirms the high correlation between behavioral intention and behavior\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Furthermore, studies\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e indicate that perceived behavioral control is a major predictor of both oral health behavioral intention and actual behavior, explaining 34% of behavioral variance. This supports BIC's role as a crucial predictor of elderly oral health service utilization behavior. Perceived Benefit (PBE) ranked second in influence (Total Effect\u0026thinsp;=\u0026thinsp;0.404), followed by Subjective Norm (SN) (No direct effect, only Indirect Effect\u0026thinsp;=\u0026thinsp;0.216). In social life, perceived benefit is a powerful driver of individual behavior. Compared to external directives, elderly individuals are more inclined to perform behaviors they perceive as personally beneficial. Furthermore, regarding the factors influencing BIC, both SN and PBE exerted only direct effects (0.365 and 0.282, respectively). As a vulnerable group, elderly individuals often consult family, friends, or healthcare professionals when encountering unfamiliar matters. These opinions significantly impact their behavioral intention and control (SN had a larger direct effect on BIC [0.365] than PBE [0.282]). Concurrently with this social influence, elderly individuals often receive tangible assistance from these sources (e.g., family members providing accompaniment to dental visits). This assistance not only boosts behavioral intention but also directly enhances the resources and capability required to perform oral health service utilization behaviors.\u003c/p\u003e \u003cp\u003eBased on the identified key dimensions\u0026mdash;Perceived Benefit (PBE), Subjective Norm (SN), and Behavioral Intention \u0026amp; Control (BIC)\u0026mdash;we propose the following multi-level intervention strategies:\u003c/p\u003e \u003cp\u003e(1)Enhancing Perceived Benefit (PBE):①Individual/Family Level: Recognize the decline in self-directed learning capacity among the elderly. Family members should actively accompany elders, share relevant oral health knowledge, watch educational TV programs together, consult oral healthcare books with them, and answer their questions; ②Societal Level: Mainstream media should prioritize oral health promotion. Healthcare institutions could establish specialized medical teams for community outreach programs, enhancing interactivity during educational sessions and bridging the gap with the public through community-based initiatives; ③Government bodies should optimize the allocation of oral health human resources and reasonably distribute oral healthcare resources to improve service experiences, thereby enhancing perceived benefits.\u003c/p\u003e \u003cp\u003e (2)Leveraging Subjective Norm (SN):①Individual Level: It is essential for elderly individuals to actively listen to and consider advice from relatives, friends, or healthcare personnel regarding oral health; ②Family Level: Families can foster a home environment that values oral health, encourage elders to develop good oral hygiene habits, and regularly remind and accompany them to utilize oral health services; ③Societal Level: Similar to the family approach, society-wide oral health education should be promoted to cultivate a broader societal atmosphere that prioritizes oral health.\u003c/p\u003e \u003cp\u003e(3)Strengthening Behavioral Intention \u0026amp; Control (BIC): This dimension, encompassing classical concepts of behavioral intention and perceived behavioral control, is the most influential in the model and serves as a proximal determinant of behavior. Recommendations under PBE and SN will inherently contribute to improving BIC levels. Additionally, as BIC includes the capability to perform the behavior, this can be bolstered by external support: Practical Support: Examples include family members accompanying elders to dental appointments and hospitals improving service accessibility and convenience.Core Insight: Genuine care and companionship for elders may be the most effective catalyst for promoting their healthcare-seeking behavior.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eUnder the analytical framework integrating the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB), this study employed empirical data to investigate the key influencing factors and underlying mechanisms of the \u0026quot;low utilization\u0026quot; phenomenon in oral health service utilization behavior among the elderly.\u003c/p\u003e\n\u003cp\u003eWithin the composite model, the identified influencing factors operate through distinct pathways: (1)The variable \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; exerts a direct positive effect on \u0026quot;Elderly Oral Health Service Utilization Behavior (B)\u0026quot;, demonstrating the largest total effect; (2)The variable \u0026quot;Perceived Benefit (PBE)\u0026quot; positively influences elderly oral health service utilization behavior both directly and indirectly by affecting the \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; variable; (3)The variable \u0026quot;Subjective Norm (SN)\u0026quot; can only positively influence elderly oral health service utilization behavior indirectly, mediated through the \u0026quot;Behavioral Intention \u0026amp; Control (BIC)\u0026quot; variable.\u003c/p\u003e\n\u003cp\u003eTherefore, it is recommended to implement strategies focusing on enhancing social support, addressing cognitive misconceptions, and strengthening the expectations and support from family, friends, and healthcare professionals. These interventions can effectively target Subjective Norm (SN), Behavioral Intention \u0026amp; Control (BIC), and Perceived Benefit (PBE), ultimately promoting proactive utilization of oral health services among the elderly population.\u003c/p\u003e\n\u003cp\u003eCollectively, this study provides a scientific foundation and effective strategies for improving oral health status among older adults, contributing novel perspectives and insights to advance the process of healthy aging.\u003c/p\u003e\n\u003cp\u003eDeclaration of generative AI and AI-assisted technologies in the writing process.\u003c/p\u003e\n\u003cp\u003eStatement: During the preparation of this work the author(s) used [Deepseek] in order to [Linguistic refinement]. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003e \u003cem\u003eConflict of interest disclosure\u003c/em\u003e:\u003c/h2\u003e \u003cp\u003eThere are no conflicts in relation to this study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval\u003c/strong\u003e \u003cp\u003e\u003cb\u003estatement\u003c/b\u003e: This cross-sectional study was approved bybBoard of Medical Ethics Committee of Foshan University(No. 2022001). Written consent from all participants was collected before the implementation of the study. This study was conducted in full accordance with the Helsinki Declaration.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eClinical Trial Registration\u003c/strong\u003e \u003cp\u003eNot applicable (observational study).\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003ePatient consent statement\u003c/h2\u003e \u003cp\u003eWritten consent from all participants was collected before the implementation of the study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study was funded by a grant from National Natural Science Foundation of China (grant number: 72204046), a grant from Guangdong Philosophy and Social Science Foundation (grant number: GD24XGL003), a grant from Foshan Science and Technology Innovation Project (grant number: 2320001007325), and a grant from Guangdong Basic and Applied Basic Research Foundation (grant number: 2019A1515111102).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e(I) Conception and design: Xiaoyuan Pan, Shuwen Su.(II) Administrative support: Shuwen Su. (III) Provision of study materials : Xiaoyuan Pan,Jianli Li,Leyi Han ,Xinyue Chen.(IV) Collection and assembly of data:Xiaoyuan Pan,Jianli Li,Leyi Han ,Xinyue Chen.(V) Data analysis and interpretation: Shuwen Su, Xiaoyuan Pan,Jianli Li(VII) Final approval of manuscript: All authors\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article (and its Supplementary Information files).The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi, Y. \u003cem\u003eThe study on oral health service need, demand and utilization of40597 persons undergoing physical examination in Zunyi City\u003c/em\u003e, (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMou, F. \u003cem\u003eTheoretical and Practical Research on the CPC\u0026rsquo;s Response to the Aging Population Since the 18th CPC National Congress\u003c/em\u003e (Southwest Jiaotong University, 2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, X. \u003cem\u003e​The Fourth National Oral Health Epidemiological Survey Report\u003c/em\u003e127 (The People's Health Press Co., Ltd, 2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNeil, D. 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Health\u003c/em\u003e. \u003cb\u003e21\u003c/b\u003e, 2303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-021-12329-9\u003c/span\u003e\u003cspan address=\"10.1186/s12889-021-12329-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Geriatric oral health, Health services utilization, Structural equation modeling, Health belief model, Theory of planned behavior","lastPublishedDoi":"10.21203/rs.3.rs-7235151/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7235151/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eChina's aging population faces significant unmet oral healthcare needs, and delays in seeking care exacerbate the disease burden. Currently, there is a lack of empirical research applying comprehensive health behavior models to understand the pathway relationships among influencing factors in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted between July and September 2023 among 356 community-dwelling older adults in Foshan and Guangzhou, using a theory-driven questionnaire. Group comparisons employed independent t-tests or ANOVA for sociodemographic variables. Structural equation modeling (SEM) validated pathways.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSignificant differences were observed: 1) Sex and age affected individual model variables; 2) Education, residence location, and economic status influenced multiple variables; 3) Living arrangement showed no significant effects. Only 33.7% of older adults proactively sought oral health knowledge, while 65.7% did not receive regular dental check-ups. Merely 51.2% sought treatments (e.g., scaling, fillings, extractions, dentures, implants). When acute oral pain disrupted daily life, 24.7% still delayed seeking care. SEM revealed: 1) Behavioral Intention/Control had the strongest total effect on utilization behavior (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.593); 2) This was followed by Perceived Benefits (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.404); 3) Subjective Norms exerted only indirect effects (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.216); 4) Both Subjective Norms (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.365) and Perceived Benefits (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.282) directly influenced Behavioral Intention/Control.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOral health service utilization among older adults in China remains largely passive. Our model identifies three key modifiable factors: Behavioral Intention/Control, Perceived Benefits, and Subjective Norms. Strategies to improve service utilization should focus on strengthening social support and addressing unrealistic health perceptions.\u003c/p\u003e","manuscriptTitle":"Oral Health Service Utilization Behavior and Its Influencing Factors Among Older Adults: An Empirical Study Based on the Composite Health Behavior Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 19:40:42","doi":"10.21203/rs.3.rs-7235151/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90b659ea-a144-49be-b896-bc28304f6ff1","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65074708,"name":"Health sciences/Health care"},{"id":65074709,"name":"Health sciences/Medical research"},{"id":65074710,"name":"Biological sciences/Psychology"},{"id":65074711,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-04-01T08:57:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 19:40:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7235151","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7235151","identity":"rs-7235151","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}