Abstract
Introduction
Understanding the predictors of oral health behaviors in older adults helps to design effective interventions. This will improve their oral health and overall well-being. The present study aimed to determine the predictors of oral health-related behaviors in Iranian elderly based on the Extended Theory of Planned Behavior (ETPB).
Materials and methods
This cross-sectional study was conducted in Sanandaj City, western Iran, in 2024. In this research, 360 elderly people from retirement centers in Sanandaj City were surveyed using a multi-stage random sampling method. The data collection tools were the demographic characteristics questionnaire, the Extended Theory of Planned Behavior (ETPB) questionnaires, the Oral Health Literacy Adult Questionnaire (OHL-AQ), and clinical oral and dental examination. SPSS software version 26 was used for data analysis. The significance level was considered to be p < 0.05.
Results
A mean age of 63.82 (± 5.15) years was estimated for the 360 elderly. The linear regression results showed that all ETPB constructs predicted oral health behaviors in the studied elderly. This model could explain 40% of the variance in the oral health behaviors of the elderly. The strongest predictor of oral health behaviors was the behavioral intention construct (β = 0.404, p < 0.001. The Decayed, Missing, Filled Teeth (DMFT) crown index showed a significant positive correlation with oral health behaviors (r = 0.278, p < 0.001) and OHL (r = 0.230, p < 0.001) as well as a significant negative correlation with attitude (r = -0.257, p < 0.001).
Conclusion
The ETPB effectively identifies and predicts oral health behaviors in the elderly, with behavioral intention emerging as the strongest predictor. The DMFT-crown index correlated positively with oral health behaviors and oral health literacy, while attitude showed a significant negative association. Based on these results, interventions should prioritize strengthening behavioral intention, improving attitudes, and enhancing oral health literacy through theory-based educational programs to promote sustainable health practices in this population.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12903-025-06180-2.
Keywords: Oral health, Aged, Theory of Planned Behavior, Iran
Introduction
Improved living conditions and increased life expectancy have caused the aging phenomenon in societies, making it a major public health challenge in the current world [1]. According to the World Health Organization (WHO), the proportion of the population over 60 years of age will almost double and reach 12 to 22% between 2015 and 2050 [2].
The physical, psychological, and social problems of the elderly population have increased significantly with the rise of this age group in various societies. These problems are particularly evident in chronic diseases and disorders such as oral and dental diseases [3, 4]. Oral and dental hygiene is an integral part of public health [5], and its neglect leads to tooth decay, gingivitis, dental plaque, and periodontitis [6]. Older people encounter common oral problems, including poor oral hygiene, which can be considered a risk factor for tooth loss, dry mouth, gum disease, tooth decay, oral mucosal disorders, chewing disorders, dehydration, malnutrition [5], heart disease [7], joint infections, and pneumonia [8]. In addition to facial aesthetic impairment, the elderly also experience functional impairments in daily life activities, from eating and chewing to speaking. These impairments result in communication disorders, decreased attendance in social gatherings, and reduced self-confidence [9]. Knowledge about oral health is a function of variables linked to oral health in older people and can improve their quality of life (QoL) [4]. The WHO has proposed that oral health is a key indicator of overall health, well-being, and QoL [10].
In recent years, many efforts have been made to improve oral health literacy (OHL), especially among the elderly [11]. OHL is defined as the degree to which individuals can obtain, process, and understand basic oral health information and services needed to make appropriate health decisions [12]. According to the literature, limited OHL is associated with an increased risk of oral diseases, adverse oral health outcomes, inappropriate oral health behaviors, and reduced use of oral health services [13]. Therefore, the design and implementation of OHL interventions for the elderly need special attention to reduce the adverse consequences of low OHL.
The results of a systematic study have shown that theory-based interventions have effectively promoted the oral health of the elderly [14]. The TPB is a within-individual theory designed to understand and predict human behavioral intentions [15]. According to this theory, the intention to perform a behavior is predicted by three factors (i.e., attitude toward the behavior, subjective norms, and perceived behavioral control, PBC) [16]. TPB is a flexible theory that allows for adding variables that can increase the explained variance [17, 18]. Evidence indicates that the constructs of TPB have explained about 60% of the variance in the intention to promote the elderly’s oral health behaviors [19–21]. Therefore, the research team decided to add the OHL variable to this theory, based on existing evidence, to increase its predictive power and design and implement more effective interventions [10, 17, 18].
Considering the growing global elderly population and the importance of oral health for their quality of life, an in-depth understanding of the factors influencing their oral health behaviors (OHB) remains elusive. Previous studies have largely examined the associations between demographic factors, socioeconomic status, education, and some health behaviors with oral health in the elderly [22, 23]. However, these quantitative, descriptive studies cannot deeply identify the mental and motivational processes behind oral health behaviors. While qualitative research can provide a deeper understanding of older adults’ experiences, beliefs, and behavioral barriers, psychological theories, such as the Theory of Planned Behavior (TPB), can provide a structured framework for identifying and predicting the determinants of oral health behaviors and facilitate the design of more targeted interventions. [23, 24]. By focusing on the role of attitudes, subjective norms, and perceived behavioral control, the Theory of Planned Behavior can help identify key factors influencing oral health behaviors among the elderly and pave the way for evidence-based intervention design. To address this research gap, the present study aimed to identify the predictors of oral health-related behaviors among Iranian elderly based on the Extended Theory of Planned Behavior (ETPB) and provide a scientific basis for planning and implementing effective interventions in this field. The hypothesis of the present study was that the constructs ETPB can predict oral health behaviors in Iranian elderly people.
Methods
Study design and subjects
The present cross-sectional descriptive-analytical study was conducted in Sanandaj, western Iran, in 2024. A sample size of 310 people was estimated based on previous studies [25, 26] and considering the value of σ × 0.10 for the accuracy value (d). A final sample size of 360 individuals was estimated by enumerating lost cases and missing data (15%). The sampling location was the retirement centers (n = 14) in Sanandaj City, nine covering a population of > 200 people. The study samples were selected from these centers through the systematic random method (40 samples per center). The inclusion criteria for the study were an age of ≥ 60 years, absence of any cognitive impairment, having at least three natural teeth, no severe physical or mental illness, and the ability to communicate verbally to answer the questionnaire questions. The exclusion criterion was incomplete filling out of the questionnaires. Written informed consent was obtained from all elderly subjects.
Data collection
The required information was collected through clinical examination and three questionnaires, which were completed through interviews by one of the authors. The completion of the questionnaires lasted 20 min on average. These questionnaires included:
The demographic characteristics questionnaire contained questions concerning age, gender, marital status, education level, and income.
Oral Health Literacy Adult Questionnaire (OHL-AQ): The psychometric evaluation of the tool was conducted by Naghibi Sistani et al. (2013) in Iran [27]. This valid and reliable tool was developed to measure oral health literacy in older adults. International oral health literacy questionnaires were used in the development of the questions [28–31]. This questionnaire consisted of 17 questions in four sections: comprehension (six questions), working with numbers (four questions), listening (two questions), and decision-making (five questions). Correct answers were scored 1 and incorrect answers or questions that were unanswered scored 0. The sum of correct answers was then calculated to provide the total score for the questionnaire ranging from 1 to 17. OHL-AQ is divided based on the obtained scores of 0–9 (insufficient), 10–11 (moderate), and 12–17 (sufficient) (Appendix 1).
The TPB Questionnaire was a researcher-made questionnaire whose validity and reliability were confirmed here. An initial questionnaire with 35 questions was initially prepared using the relevant literature for the psychometric evaluation of the questionnaire. Then, the content validity was examined using the content validity ratio (CVR) and content validity index (CVI). In this respect, the initially designed questionnaire was reviewed by a 10-person panel consisting of health education and health promotion specialists. The average values of the content validity indices were estimated at CVR = 0.92 and CVI = 0.89. The panel of experts reviewed the questionnaire items in terms of writing style, grammatical rules, and the adequate number of questions for each construct. Changes were made based on the content validity examination, and the questionnaire was completed in a sample of older people (n = 30). This stage was conducted to examine the face validity [32] of the questionnaire by potential study participants by assessing the level of difficulty (in understanding phrases and words), the degree of appropriateness (suitability and good relationships of phrases with the questionnaire dimensions), and the ambiguity (the possibility of misinterpretations from phrases or inadequacy in the meanings of words) of the questionnaire items. Six questions were changed at this stage. The internal consistency of the questionnaire was measured with a Cronbach’s alpha coefficient of 0.90. Reliability was also assessed using a test–retest method with an interval of two weeks. The results of the reliability analysis demonstrate a high level of stability and consistency of the measurement tool across the two phases of testing and retesting. The mean scores for all items in both phases are very close to each other, and no statistically significant differences were observed between them, as indicated by all P-values being greater than 0.05. ICC range was 97–99. The number of questions in the questionnaire was finally reduced to 35 questions as follows: attitude (12 questions), subjective norms (5 questions), Perceived behavioral control (9 questions), behavioral intention (5 questions), and behavior (4 questions). The questions were rated on a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) (Appendix 2). The range of questionnaire scores was 35 to 175. The total score, derived from the sum of responses in all sections, provides a comprehensive index of an individual’s likelihood to engage in oral health behaviors. Higher scores indicate a more positive attitude toward oral health, a stronger perception of social support for these behaviors (subjective norms), greater confidence in one’s ability to perform these behaviors (perceived behavioral control), and a stronger intention to perform them. This is supported by the fact that they have performed the behavior more frequently in the past year.
After completing the questionnaires, clinical oral and dental examinations were conducted by a trained and calibrated dental hygienist (Appendix 3). The participants’ oral health status was examined clinically using examination equipment, including mirrors and probes on dental units. The examinations included the assessment of Decayed, Missing, and Filled Teeth (DMFT), the modified Community Periodontal Index (CPI) [33] and the Simplified Oral Hygiene Index [34]. These assessments were performed according to the standardized diagnostic criteria outlined in the World Health Organization guidelines [33]. To ensure consistency in clinical assessments, the dental hygienist underwent a calibration session with a senior dentist prior to data collection. The calibration was conducted by an assistant professor of community oral health at Hamadan University of Medical Sciences, who is currently working in the Department of Community Oral Health. The calibration process was based on standard diagnostic criteria outlined in WHO guidelines and relevant scientific literature [33, 34] The inter-rater reliability for oral health indices was assessed in a pilot sample, yielding a kappa coefficient of 0.78, indicating substantial agreement.
Statistical analysis
All the collected data were analyzed with SPSS software (ver. 24) using the chi-square, t-test, Pearson’s correlation coefficient, one-way analysis of variance, and multiple linear regression tests at a significance level of < 0.05.
Results
A mean age (standard deviation) of 63.82 (5.15) years was estimated for the 360 studied elderly, 51.49% of whom were men. About one-third of the elderly held academic education (30%). More details about demographic information are listed in Table 1. Table 2 shows significant differences in tooth brushing and flossing frequencies across all ETPB constructs except subjective norms (p < 0.001), while regular dental visits differed significantly by attitude (p < 0.001), PBC (p = 0.003), and OHL (p < 0.001), and mouthwash use was significantly associated only with behavioral intention (p < 0.001).
Table 1.
Demographic characteristics of the participants (n = 360)
| Characteristics | Categories | n | % |
|---|---|---|---|
| Gender | Male | 187 | 51.94 |
| Female | 173 | 48.05 | |
| Age(years) | 60–64 | 239 | 66.38 |
| 65–69 | 70 | 19.44 | |
| ≥ 70 | 51 | 14.16 | |
| Education level | Illiterate | 20 | 5.56 |
| Elementary school | 59 | 16.39 | |
| Secondary school | 38 | 10.55 | |
| High school | 135 | 37.50 | |
| Academic | 108 | 30.00 | |
| Smoking | No | 259 | 71.94 |
| Yes | 101 | 28.05 | |
| Marital status | Single/widowed/divorced | 79 | 21.94 |
| Married | 281 | 78.05 | |
| Information sources about dental health | Public health center | 220 | 61.11 |
| Family | 24 | 6.66 | |
| Mass media | 89 | 24.72 | |
| Social network | 27 | 7.50 | |
| Financial status | Insufficient (moderate/poor) | 332 | 92.22 |
| Sufficient | 28 | 7.77 |
Table 2.
Mean (SD) of the Extended Theory Planned Behavior constructs based on frequency of oral health behaviors
| Times | Always | Often | Sometimes | Rarely | Never | P-value |
|---|---|---|---|---|---|---|
| Variables | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | |
| Behavior 1: Brushing teeth | ||||||
| Attitude | 54.21 (4.88) | 51.08 (4.88) | 50.58 (5.65) | 48.14 (6.90) | 47.80 (6.25) | > 0.001 |
| Subjective norms | 16.193.97) | 16.81 (5.09) | 16.77 (3.33) | 16.82 (3.72) | 17.06 (3.12) | 0.708 |
| Perceived control | 34.48 (4.66) | 32.78 (5.17) | 32.25(4.55) | 28.88(5.92) | 30.06(4.28) | > 0.001 |
| Intention | 15.10 (4.30) | 12.56 (4.19) | 14.36(4.56) | 10.28(3.69) | 11.33(4.49) | > 0.001 |
| Oral health literacy | 10.74 (2.46) | 8.77 (2.75) | 8.22 (2.70) | 8.02 (2.77) | 9.60 (3.26) | > 0.001 |
| Behavior 2: Use of dental floss | ||||||
| Attitude | 55.46 (4.26) | 53.69 (5.54) | 52.92 (5.45) | 51.00 (5.35) | 5048 (6.37) | > 0.001 |
| Subjective norms | 17.38 (3.60) | 16.50 (4.48) | 16.76 (3.25) | 16.95 (5.84) | 16.01 (3.85) | 0.275 |
| Perceived control | 36.24 (3.90) | 35.61 (4.57) | 35.92 (3.80) | 32.53 (4.90) | 30.25 (4.66) | > 0.001 |
| Intention | 17. 42 (4.38) | 15.38(4.01) | 15.35(3.52) | 12.85(3.99) | 11.54(3.90) | > 0.001 |
| Oral health literacy | 10. 74 (3.12) | 10. 36 (2.63) | 10. 20 (2.57) | 8. 70 (2.96) | 9. 11 (2.68) | > 0.001 |
| Behavior 3: Regular visits to the dentist | ||||||
| Attitude | 55. 22 (4.58) | 54. 22 (4.91) | 53. 89 (4.68) | 50. 85 (6.10) | 50. 36 (7.30) | > 0.001 |
| Subjective norms | 15. 66 (4.86) | 16. 41 (3.30) | 17. 00 (3.72) | 16. 20 (4.66) | 17. 16 (3.26) | 0.354 |
| Perceived control | 35. 51 (5.37) | 33. 96 (5.37) | 34. 05 (4.96) | 32. 51 (5.29) | 31. 53 (4.34) | > 0.003 |
| Intention | 18. 85 (3.97) | 16. 13 (4.47) | 15. 18 (4.27) | 12. 15 (3.74) | 11. 89 (4.11) | 0.174 |
| Oral health literacy | 10. 51 (3.43) | 10. 63 (2.96) | 10. 22 (2.52) | 9. 33 (2.64) | 8. 63 (3.16) | > 0.001 |
| Behavior 4: Use of mouthwash | ||||||
| Attitude | 51. 62 (5.62) | 54. 00 (6.91) | 53. 52 (5.72) | 51. 75(6.44) | 52. 10(5.82) | 0.529 |
| Subjective norms | 15. 75 (5.31) | 18. 10(4.67) | 16. 23(3.90) | 17. 21(3.56) | 16. 21(4.35) | 0.244 |
| Perceived control | 32. 62 (7.63) | 35. 30 (6.63) | 35. 05 (4.53) | 32. 85 (4.53) | 32. 81 (5.33) | 0.108 |
| Intention | 16. 62 (5.82) | 15. 40 (5.39) | 16. 88 (5.48) | 13. 69 (4.15) | 13. 11 (4.22) | > 0.001 |
| Oral health literacy | 8. 62 (2.61) | 9. 30 (2.94) | 10. 52 (2.78) | 9. 26 (3.08) | 9. 76 (2.74) | 0.174 |
The linear regression results revealed that all ETPB constructs were predictors of oral health behaviors in the studied elderly. This model could explain 40% of the variance in the elderly’s oral health behaviors (Adjusted R2 = 0.40, p < 0.001). The strongest predictor of oral health behaviors was the behavioral intention construct (β = 0.404, p < 0.001) (Table 3).
Table 3.
Linear regression assessing variables predicting oral health behaviors
| Variable | B | SE | β | t | p-value | 95% CI for B |
|---|---|---|---|---|---|---|
| Attitude | 0.080 | 0.025 | 0.149 | 3.129 | 0.002 | 0.030, 0.129 |
| Subjective norms | -0.115 | 0.34 | -0.150 | -3.400 | 0.001 | -0.182, -0.049 |
| Perceived control | 0.120 | 0.031 | 0.195 | 3.813 | < 0.001 | 0.058, 0.182 |
| Intention | 0.284 | 0.036 | 0.404 | 7.806 | < 0.001 | 0.212, 0.356 |
| Oral health literacy | 0.124 | 0.049 | 0.111 | 2.525 | 0.012 | 0.028, 0.221 |
Adjusted R2 = 0.40, P < 0.001
Table 4 shows a strong positive correlation between DMFT-crown and DMFT-root indices (r = 0.858, p < 0.001). DMFT-crown positively correlates with oral health behaviors (r = 0.278) and OHL (r = 0.230), but negatively with attitude (r = -0.257) and PBC (r = -0.235). DMFT-root negatively correlates with oral health behaviors, intention, OHL, attitude, and PBC (all p < 0.001). Additionally, 16.39% and 15% of the elderly showed positive bleeding and pocket CPI indices, over half had good SOHI, and average DMFT scores were 15.74 (root) and 11.02 (crown). The DMFT-crown index showed a strong positive correlation with the DMFT-root index (r = 0.858) and positive correlations with oral health behaviors (r = 0.278) and OHL (r = 0.230), but negative correlations with attitude (r = -0.257) and PBC (r = -0.235), while the DMFT-root index negatively correlated with oral health behaviors, intention, OHL, attitude, and PBC; additionally, 16.39% and 15% of the elderly had positive bleeding and pocket CPI indices, over half had a good SOHI, and the average DMFT scores were 15.74 (root) and 11.02 (crown).
Table 4.
Descriptive information on Oral health indexes of the participants (n = 360)
| Oral health indexes | Status | % | Mean (SD) |
|---|---|---|---|
| Modified CPI index (Bleeding) | No | 83.61 | 0.16 (0.37) |
| Yes | 16.39 | ||
| Modified CPI index (Pocket) | No | 85 | 0.15 (0.35) |
| Yes | 15 | ||
| SOHI index (Debris/calculus) | Good | 59.11 | 1.63 (0.78) |
| Fair | 24.44 | ||
| Poor | 16.45 | ||
| DMFT index (root) | 15.74 (7.04) | ||
| DMFT index (crown) | 11.02 (7.77) |
Positive modified CPI (Bleeding) and CPI (Pocket) were found in 16.39% and 15.00% of the elderly, over half had good SOHI (using six index teeth), and mean root and crown DMFT scores were 15.74 and 11.02, respectively (Table 5).
Table 5.
Intra-correlations of DMFT and the Extended Theory Planned Behavior constructs
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|---|---|---|---|---|---|---|---|---|
| 1. Attitude | 1 | |||||||
| 2. Subjective norms | 0.244* | 1 | ||||||
| 3. Perceived control | 0.373* | 0.291* | 1 | |||||
| 4. Intention | 0.420* | 0.224* | 0.558* | 1 | ||||
| 5. Behaviors | 0.387* | 0.024 | 0.452* | 0.567* | 1 | |||
| 6. Oral health literacy | 0.284* | -0.083 | 0.187* | 0.230* | 0.293* | 1 | ||
| 7. DMFT-crown | -0.257* | 0.051 | -0.235* | -0.083 | 0.278* | 0.230* | 1 | |
| 8. DMFT-root | -0.293* | 0.048 | -0.290* | -0.363 | -0.421* | -0.340* | 0.858* | 1 |
*P < 0.00
Table 6 shows significant differences in SOHI levels across attitude, PBC, intention, behaviors, and OHL (p < 0.001), no difference in modified CPI (p > 0.05).
Table 6.
ANOVA results of SOHI index levels based on the Extended Theory Planned Behavior construct
| Variables | SOHI index (Debris/calculus) | N | Mean (SD) | p-value |
|---|---|---|---|---|
| Attitude | Good | 202 | 53.49 (5.35) | 0.001 > |
| Fair | 88 | 51.93 (6.23) | ||
| Poor | 70 | 48.78 (6.15) | ||
| Subjective norms | Good | 202 | 16.13 (3.92) | 0.105 |
| Fair | 88 | 17.26 (5.21) | ||
| Poor | 70 | 16.62 (3.22) | ||
| Perceived control | Good | 202 | 34.12 (4.91) | 0.001 > |
| Fair | 88 | 32.50 (5.35) | ||
| Poor | 70 | 30.90 (5.04) | ||
| Intention | Good | 202 | 15.02 (4.48) | 0.001 > |
| Fair | 88 | 12.51 (4.22) | ||
| Poor | 70 | 11.65 (3.87) | ||
| Oral health literacy | Good | 202 | 11.72 (3.00) | 0.001 > |
| Fair | 88 | 10.02 (3.16) | ||
| Poor | 70 | 8.88 (2.68) | ||
| Variables | Modified CPI index (Bleeding) | N | Mean (SD) | p-value |
| Attitude | No | 306 | 52.61 (5.92) | 0.523 |
| Yes | 59 | 50.08 (5.97) | ||
| Subjective norms | No | 306 | 16.57 (4.20) | 0.808 |
| Yes | 59 | 16.18 (4.00) | ||
| Perceived control | No | 306 | 33.38 (5.13) | 0.876 |
| Yes | 59 | 31.62 (5.28) | ||
| Intention | No | 306 | 13.94 (4.54) | 0.851 |
| Yes | 59 | 12.79 (443) | ||
| Behavior | No | 306 | 10.88 (4.90) | 0.636 |
| Yes | 59 | 10.10(3.08) | ||
| Oral health literacy | No | 306 | 9.74 (2.85) | 0.862 |
| Yes | 59 | 9.33 (2.82) | ||
| Variables | Modified CPI index (Pocket) | N | Mean (SD) | p-value |
| Attitude | No | 306 | 52.32 (5.98) | 0.74 |
| Yes | 54 | 51.48 (6.09) | ||
| Subjective norms | No | 306 | 16.68 (4.22) | 0.592 |
| Yes | 54 | 15.48 (3.72) | ||
| Perceived control | No | 306 | 33.12 (5.24) | 0.155 |
| Yes | 54 | 32.94 (4.94) | ||
| Intention | No | 306 | 13.70 (4.62) | 0.184 |
| Yes | 54 | 14.03 (4.09) | ||
| Behavior | No | 306 | 10.75 (3.15) | 0.465 |
| Yes | 54 | 10.75 (3.44) | ||
| Oral health literacy | No | 306 | 9.77 (2.79) | 0.184 |
| Yes | 54 | 9.11 (3.24) |
Discussion
The present study aimed to determine the predictors of oral health-related behaviors of the elderly based on the ETPB. The study results demonstrated that all ETPB constructs were predictors of oral health behaviors in the studied elderly, which could totally explain 40% of the variance in the elderly’s oral health behaviors.
Among the constructs of the ETPB, the constructs of attitude, PBC, and behavioral intention were significantly different between the mean frequency of brushing and flossing behaviors, except for abstract norms.
Dumitrescu et al. (2011) reported that the studied elderly’s attitudes toward oral health behaviors and PBC predicted behavioral intention, while subjective norms could not predict oral health behaviors [35]. In addition, this finding in our study corresponded to that of Amin et al. (2019) [36].
In our study, attitude as an important construct played a role in predicting oral health behaviors. Hence, the presence of a good attitude and OHL is an important determinant for performing oral health behaviors in the elderly. This finding is in line with those reported by Rajeh et al. (2022). According to these authors, intention was significantly correlated with attitude, subjective norms, PBC, oral health knowledge, and current oral health behavior. They also introduced the attitude as the strongest predictor of intention to improve oral health behaviors [19]. Similarly, Shitu et al. (2021) claimed that attitude toward oral health behavior was the strongest intention predictor to improve oral health behaviors [20]. Mauline et al. (2019) found that subjective norms in oral health behaviors were a strong predictor [37], some of the reasons for this difference could be cultural differences in the influence of significant others. It seems that collectivist cultures such as India give an important role to the opinions and expectations of family and society in shaping health behaviors, making subjective norms more influential. In contrast, Iranian culture, with its own characteristics, including traditional attitudes, gender roles, and different access to health services, may show the impact of subjective norms differently. Also, factors such as the type of support (emotional, informational, etc.), personality traits of the individual and significant others (empathy, flexibility, extraversion, agreeableness), attachment style and how relationships are formed, cultural expectations and social values, the amount and quality of interactions, and family dynamics on the adoption of oral health behaviors of the older adults studied [38, 39].
some of the reasons for this difference could be cultural differences in the influence of significant others (factors such as the type of support (emotional, informational, etc.), personality traits of the individual and significant others (empathy, flexibility, extraversion, agreeableness), attachment style and how relationships are formed, cultural expectations and social values, the amount and quality of interactions, and family dynamics on the adoption of oral health behaviors of the older adults studied [38, 39].
Different cultures may interpret these factors in diverse ways because cultural norms, values, and beliefs shape how individuals perceive and respond to behaviors. What is considered important or acceptable in one culture might differ significantly in another, influencing attitudes, social pressures, and perceived control over behaviors. Therefore, cultural context plays a crucial role in understanding and applying these factors effectively.
Regarding the behavior of regular dental visits in the present study, significantly higher average attitudes, PBC, behavioral intention, and health literacy were reported by older people who regularly visited a dentist. Likewise, Batista et al. (2018) observed more favorable situations in regular dental visits and people with sufficient health literacy adopting toothbrushing behavior [40]. In using mouthwash behavior, there was a significant difference between the average frequencies of performing the behavior only in the behavioral intention construct, and no similar study was found in this field. In future studies, it seems necessary to pay more attention to the different oral health behaviors of the elderly. Meanwhile, appropriate interventions should be designed and implemented according to the predictors of each behavior to improve oral health in this vulnerable population.
The oral examination results in the elderly who were studied revealed the highest positive and significant correlation between the DMFT-crown index and the DMFT-root index. The DMFT-crown index showed a significant positive correlation with oral health behaviors and OHL, whereas it was significantly and negatively correlated with attitude and PBC. The DMFT-root index significantly negatively correlated with oral health behaviors, intention, OHL, attitude, and PBC. In this regard, no similar study was found in this field. This study reported positive modified CPI (Bleeding) and modified CPI (Pocket) indices in 16.39% and 15% of the studied elderly, respectively. This result is consistent with 16.3% and 21.8%, respectively, reported by Shayesteh et al. (2022) [41]. The results of the elderly oral examination revealed that the DMFT-crown index had the highest positive and significant correlation with the DMFT-root index. The DMFT-crown index showed a positive and significant correlation with oral health behaviors and OHL, while it was negatively and significantly correlated with attitude and PBC. Significant differences were observed between the different mean levels of SOHI in the constructs of attitude, PBC, behavioral intention, oral health behaviors, and OHL. Nevertheless, no significant differences were found between the different mean levels of modified CPI.
Good oral health conditions were observed in more than half of the elderly with the SOHI. In contrast, Tilaki et al. (2017) reported that this index was poor in the elderly studied [42]. This difference could be the different sociocultural conditions in the studied societies and the differences in policies supporting the elderly’s oral health and service provision procedures for this population in each region.
The OHL score of the studied elderly revealed adequate health literacy in only 28.61% of the elderly. A recent review by Huang (2024) claims that limited studies have been conducted on OHL in the elderly, and there is a need to prioritize efforts to improve the oral health of this vulnerable group [43]. Recently, Costa et al. (2024) in Portugal have evidenced low, moderate, and high OHL in 22.7%, 43.7%, and 33.6% of the studied elderly. This research indicated moderate OHL in the studied elderly and that appropriate educational programs need to be adopted through health promotion programs for the elderly to improve awareness and adopt oral health behaviors, focusing on prevention and education [44].
In Thailand, Khamrin et al. (2021) presented evidence that 53% of the studied elderly performed oral health behaviors at an average level. They also reported a positive relationship between OHL and oral healthcare behaviors among the elderly. In their study, 47.2% of the variance in oral healthcare behaviors was explained by variables such as self-efficacy, social support, and OHL [45].
Previous studies suggest that oral health behaviors, such as brushing, flossing, and delay in dental care, are probably less performed in older people with low OHL, leading to tooth loss [43–46]. In addition to increasing OHL, useful strategies, such as matching toothbrush handles with elderly assistive devices, can also be suggested in this vulnerable group [47]. Moreover, in addition to designing and implementing population-based educational interventions to improve OHL in the elderly, it seems necessary to pay sufficient attention to the elderly’s special conditions, e.g., physical and motor problems, in adopting oral health behaviors. The strengths of the present study include the fact that no oral indicators have been examined in previous studies. The present study is the first to utilize the ETPB to increase the ability to explain the variance of oral health behaviors. An important limitation of this study is the selection of a sample in which all participants were covered by pension insurance. This may make the generalization of the results to other groups of older people, especially those who are uninsured or live in rural areas, less accurate. Older people without pension insurance tend to have different conditions in terms of economic status and access to health services, which may affect their health and quality of life. In addition, rural elderly people have a different situation from urban elderly people due to geographical constraints and less access to medical facilities. Therefore, the results of this study, which were based on elderly people covered by urban pension insurance, may not be representative of the general situation of elderly people in the country, and its generalization should be made with caution. Future studies with a more diverse sample can help provide a more comprehensive understanding of the situation of the elderly in Iran. Two other limitations of this study were: First, completing the information using a questionnaire might have affected the participants’ responses in the form of more or less estimated responses. Second, given the nature of the study and the data collection method, interviewer bias can also be considered a limitation. Third, since the subjects were all covered by pension insurance, the generalization of the results to other groups of the elderly may involve some inaccuracy.
Conclusion
The findings demonstrate that the ETPB effectively identifies and predicts oral health behaviors in the elderly, with behavioral intention emerging as the strongest predictor. The DMFT-crown index correlated positively with oral health behaviors and oral health literacy, while attitude showed a significant negative association. Based on these results, interventions should prioritize strengthening behavioral intention, improving attitudes, and enhancing oral health literacy through theory-based educational programs to promote sustainable health practices in this population.
Supplementary Information
Acknowledgements
We are grateful to all of the participants in this study.
Clinical trial number
Not applicable.
Authors’ contributions
Study design: SB, SK, MA, MB, AKS, PFS, Data acquisition, analysis, and interpretation: SB, SK, EA, MA, MB, PFS, writing of the first draft: SB, SK, EA, MA, AKS, PFS, revising the first draft for important intellectual content SB, SK, MA, AKS, MB, PFS. All the authors have read and approved the final version of the manuscript.
Funding
This work was financially supported by the Vice Chancellor for Research and Technology, Hamadan University of Medical Sciences, Iran (No. 140110138639)).
Data availability
All supporting data is available through the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee at Hamadan University of Medical Sciences (Code: IR.UMSHA.REC.1401.829). All methods were carried out in accordance with the Declaration of Helsinki and relevant regulations. All participants completed a written informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
All supporting data is available through the corresponding author on reasonable request.