Introduction

Dry eye is a prevalent chronic eye disease, and its incidence has been rising steadily in recent years. Globally, the prevalence of dry eye ranges from 5 to 50%, with higher rates observed in women than in men1,2. In China, the incidence among adults is reported to be 21–30%, with regional variations3,4. Mild to moderate dry eye is increasingly prevalent, impacting daily activities and work performance, while severe cases may result in significant visual impairment or blindness5.

This increase in incidence is attributed to advances in clinical diagnosis and treatment, as well as changes in modern lifestyle. Considerable evidence indicates that dry eye is increasingly being recognized as a lifestyle disease6,7. Unhealthy habits such as overuse of digital devices, insufficient sleep, lack of physical activity, and prolonged sedentary behavior contribute to the development of dry eye8. Furthermore, environmental pollution and lifestyle changes have exacerbated the condition in China, where the incidence of dry eye continues to rise9.

The Knowledge, Attitude, and Practices (KAP) survey serves as an important diagnostic tool, helping to evaluate a group’s understanding, beliefs, and actions regarding health issues. It is based on the principle that knowledge positively influences attitudes, which in turn shape behaviors10,11. Research shows that lifestyle interventions such as regular exercise12 and dietary habits, including the use of supplements like vitamins A, B complexes, C, E, and omega-3 fatty acids, can positively impact tear stability, tear production, and alleviate symptoms of dry eye13,14,15,16.

There is currently a lack of KAP studies focusing on lifestyle-related dry eye. This study aims to fill that gap by assessing patients’ KAP on this condition, which could help develop more effective, tailored interventions to address the specific lifestyle factors contributing to dry eye.

Methods

Study design and participants

This cross-sectional study was conducted at the Ophthalmology Hospital of the China Academy of Chinese Medical Sciences from 1 July 2024 to 26 July 2024, with patients serving as the study participants. Inclusion Criteria: (1) Patients diagnosed with dry eye by an experienced ophthalmologist, following the diagnostic criteria outlined in the Chinese Clinical Diagnosis and Treatment Guidelines for Dry Eye edited by Liu Zuguo (China Science and Technology Press, 2023); (2) Aged 18 to 80 years, inclusive, regardless of gender; (3) Capable of understanding and voluntarily participating in the survey; (4) Willing and able to cooperate with eye examinations. Those disagree with this study were excluded. After a detailed study protocol was finalized (before participants are recruited), we submit an ethics application to the Ethics Committee. This study protocol was approved by the Ethics Committee of the Ophthalmology Hospital of the China Academy of Chinese Medical Sciences (YKEC-KT-2022-012-P004), and all participants provided written informed consent which was issued along with the first page of the questionnaire.

Questionnaire design

The questionnaire was developed based on relevant guidelines and expert consensus, specifically drawing from the Chinese Dry Eye Expert Consensus: Lifestyle-Related Dry Eye (2022)17 and the Chinese Clinical Diagnosis and Treatment Guidelines for Dry Eye (2023), edited by Liu Zuguo (China Science and Technology Press). After drafting the initial version, the questionnaire was revised according to expert feedback and underwent a pilot test with 44 participants, resulting in a Cronbach’s α of 0.916, indicating strong internal consistency.

The final questionnaire, written in Chinese (an English translation is provided in the online Appendix), comprised five dimensions with a total of 51 items. These included 14 items for basic demographic information, 8 items for the knowledge dimension (with item 3 containing two sub-items), 9 items for the attitude dimension, and 10 items for the practice dimension. For statistical analysis, scores were assigned based on the number of items and the options selected.

In the knowledge dimension, responses were scored as follows: “Very knowledgeable” = 2 points, “Heard of it” = 1 point, and “Unfamiliar” = 0 points, with a possible total score ranging from 0 to 18 points. Both the attitude and practice dimensions employed a five-point Likert scale, ranging from very positive (5 points) to very negative (1 point). In the attitude dimension, items 2–9 were scored from a = 5 to e = 1, while item 1 was reverse-scored, with a = 1 to e = 5, allowing for a total score range of 9 to 45 points. For the practice dimension, all 10 items were scored from a = 5 to e = 1, yielding a total score range of 10 to 50 points.

After participants completed the questionnaire, the average scores were categorized as follows: for the knowledge dimension, 0–9 points indicated insufficient knowledge, 10–12 points indicated moderate knowledge, and 13–18 points indicated sufficient knowledge. In the attitude dimension, scores of 9–22 points indicated a negative attitude, 23–31 points indicated a neutral attitude, and 32–45 points indicated a positive attitude. For the practice dimension, scores of 10–25 points indicated negative practice, 26–35 points indicated moderate practice, and 36–50 points indicated positive practice. Scores exceeding 70% of the maximum in each section indicated adequate knowledge, a positive attitude, and proactive practices18.

Questionnaire quality control

The questionnaire data were collected through electronic questionnaires, using WeChat QR code scanning in both WeChat groups and clinics. Prior to the survey, research assistants received training on the study’s objectives and the survey method. Patients were informed about the study’s purpose, potential risks, and the Ethics Review Committee’s approval before participating. Participation was entirely voluntary, and after obtaining patients’ consent, they were assured that any personal privacy information would be strictly confidential and not disclosed. Research assistants were instructed not to provide any mandatory guidance during the questionnaire process, ensuring that patients answered truthfully based on their own circumstances.

To maintain quality control during the survey, a quality control manager ensured that all personnel followed standard operating procedures and monitored the quality control process throughout the study. Additionally, a data manager was responsible for data entry, editing, and management. The Cronbach’s α coefficient for the overall valid questionnaire was 0.875, indicating good internal consistency further.

Sample size

Sample size was calculated using the formula for cross-sectional studies: α = 0.05,\(\:\:\text{n}={\left(\frac{{Z}_{1-\alpha\:/2}}{\delta\:}\right)}^{2}\times\:p\times\:\left(1-p\right)\) where \(\:{Z}_{1-\alpha\:/2}\)=1.96 when α = 0.05, the assumed degree of variability of p=0.5 maximizes the required sample size, and δ is admissible error (which was 5% here). The theoretical sample size of 480 included an additional 20% to account for potential dropouts.

Statistical analysis

Descriptive analysis was performed on the demographic data and KAP scores, with normally distributed variables presented as mean ± SD, and categorical data as n (%). For KAP score comparisons, continuous variables were tested for normality. If normally distributed, mean ± SD and t-tests were used; if not, the median (range) and Mann-Whitney U tests were applied. ANOVA was used for comparisons across three or more groups when applicable. Pearson correlation analysis assessed the relationships between the three KAP dimensions. Path analysis explored the mediation effects between KAP and demographic characteristics. A 1st round fitting for the path analysis model: Inclusion of all variables with differences and continuous variables. The 2nd round fitting for the path analysis model (adjustement): Removal of non-significant paths and MI adjustment. A two-sided P-value less than 0.05 was considered statistically significant.

Results

Demographic characteristics

Among the 562 enrolled participants, 556 provided valid responses after excluding incomplete or rapid submissions, yielding a validity rate of 98.93%. Of the participants, 342 (61.51%) were female, with a mean age of 39.26 ± 13.56 years and a mean BMI of 24.14 ± 5.05 kg/m². A total of 334 participants (60.07%) held a college or bachelor’s degree, 212 (38.13%) had relatives or friends with dry eye, 143 (25.72%) reported other eye conditions, 157 (28.24%) had sleep disorders, 147 (26.44%) had makeup habits, and 264 (47.48%) engaged in regular physical exercise. The mean scores for knowledge, attitudes, and practices were 7.44 ± 4.65, 35.20 ± 4.10, and 35.77 ± 6.15, respectively. Significant differences in knowledge scores were observed among participants with varying levels of education (P < 0.001), employment status (P < 0.001), household monthly per capita income (P = 0.017), presence of dry eye in relatives or friends (P < 0.001), and makeup habits (P = 0.015). Differences in attitude scores were significant for participants with different BMI (P = 0.045), education levels (P < 0.001), employment status (P < 0.001), household monthly per capita income (P = 0.005), smoking status (P = 0.003), and dry eye in relatives or friends (P = 0.035). In terms of practice scores, significant differences were found based on gender (P < 0.001), household monthly per capita income (P = 0.016), smoking status (P = 0.002), alcohol consumption (P < 0.001), dry eye status in relatives or friends (P = 0.027), and engagement in regular physical exercise (P < 0.001) (Table 1).

Table 1 Baseline characteristics.
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Knowledge, attitude, and practice

The distribution of knowledge dimensions shown that the three questions with the highest number of participants choosing the “Not Clear” option were “Dry eye related to diet: This mainly involves dry eye caused by inadequate nutritional intake, high-fat diets, and excessive alcohol consumption.” (K3.2) with 37.59%, “As lifestyle-related dry eye is often a mixed type, patients should actively seek information from doctors about the clinical characteristics of their dry eye condition and consider a comprehensive treatment plan that includes both medication and non-medication treatments.” (K4) with 35.61%, and “Non-pharmacological treatments mainly include physical therapies, the use of moisture chamber glasses, punctual plugs, intense pulsed light therapy, and thermal pulsation therapy.” (K6) with 35.43% (Table S1).

When it comes to related attitudes, 10.25% strongly agreed or agreed that dry eye is not a major concern and does not require much attention (A1), while another 18.53% were neutral. Meanwhile, 44.61% strongly agreed or agreed that adequate fluid intake is not directly related to dry eye (A7), also another 29.68% were neutral (Table S2).

Responses to the practice dimension showed that 46.04% strongly agreed or agreed that they rarely take the initiative to adjust their eye habits even when they feel uncomfortable (P3). On the other hand, 17.63% disagreed or strongly disagreed that they would take regular eye breaks and massages (P4), and 19.97% disagreed or strongly disagreed that they would try to follow the Mediterranean dietary pattern (P7) (Table S3).

Correlations between KAP

Correlation analysis revealed significant positive correlations between knowledge and attitude (r = 0.255, P < 0.001) and between knowledge and practice (r = 0.333, P < 0.001). Additionally, a significant correlation was observed between attitude and practice (r = 0.351, P < 0.001) (Table 2).

Table 2 Correlation analysis.
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Interactions among KAP and demographic characteristics

Path analysis was performed and the coefficients for each path were shown in Table S4. The fitting index of CMIN/DF = 4.013, RMSEA = 0.074; IFI = 0.875; TLI = 0.817; CFI = 0.873, signifying that the data satisfactorily fit the structural model (Table S5). Moreover, the mediation analysis based on the path analysis revealed that age (β = -0.172, P = 0.010) and the presence of dry eye in relatives or friends (β = -0.228, P = 0.009) directly influenced knowledge. Attitude was directly influenced by knowledge (β = 0.233, P = 0.007), smoking (β = 0.095, P = 0.027), and education (β = 0.248, P = 0.014). Practice was directly influenced by knowledge (β = 0.260, P = 0.014), attitude (β = 0.267, P = 0.004), regular physical exercise (β = 0.173, P = 0.012), and gender (β = 0.124, P = 0.009). Additionally, age (β = -0.040, P = 0.005) and the presence of dry eye in relatives or friends (β = 0.053, P = 0.006) indirectly influenced attitude. Practice was indirectly influenced by knowledge (β = 0.062, P = 0.003), age (β = -0.055, P = 0.005), the presence of dry eye in relatives or friends (β = -0.073, P = 0.007), smoking (β = 0.025, P = 0.015), and education (β = 0.066, P = 0.003) (Table 3 and Fig. 1).

Table 3 Mediation analysis based on the path analysis model.
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Fig. 1
Fig. 1
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Path analysis model depicting the relationships between demographic characteristics and knowledge, attitudes, and practices (KAP) regarding lifestyle-related dry eye. The structural equation modeling (SEM) results illustrate the direct and indirect relationships between demographic variables, knowledge, attitudes, and practices. Solid arrows indicate significant direct paths, with standardized path coefficients displayed along each path. Knowledge was directly influenced by age and the presence of dry eye in relatives or friends, suggesting that younger individuals and those with prior exposure to the condition exhibited greater awareness. Attitude was shaped by knowledge, education level, and smoking status, with higher education contributing to more positive attitudes and smoking associated with less favorable perceptions. Practice was directly influenced by knowledge and attitude, reinforcing the theoretical KAP model, where awareness and perception facilitate behavioral change. Regular physical exercise and gender were also significant predictors of practice, with physically active individuals and females more likely to adopt protective behaviors. Smoking had a direct negative effect on both attitude and practice, highlighting its detrimental impact on health-related behaviors. Indirect pathways were also observed, as age and family history of dry eye influenced practice through their effects on knowledge and attitude. The error terms (e1–e9) represent unexplained variance within the model. The model fit indices (CMIN/DF, RMSEA, IFI, TLI, and CFI) indicate an acceptable fit, supporting the robustness of the proposed relationships.

Discussion

Patients demonstrated inadequate knowledge, yet exhibited generally positive attitudes and proactive practices regarding lifestyle-related dry eye. Clinically, it is recommended to enhance patient education on lifestyle-related risk factors for dry eye, focusing on bridging the knowledge gaps to further improve preventive behaviors.

The main findings of this study reveal that while patients generally displayed positive attitudes and proactive practices toward lifestyle-related dry eye, their overall knowledge levels were insufficient. This imbalance in KAP results is consistent with previous studies, which suggest that a lack of adequate knowledge prevents patients from correctly associating their symptoms with dry eye before a formal diagnosis19. Patients have expressed the need for information presented in clear, accessible language to better understand their condition. To bridge the knowledge gap and enhance patient adherence, targeted educational interventions should include structured patient education sessions, digital health tools such as mobile reminders, and interactive workshops. These approaches can reinforce key information on preventive and therapeutic measures, facilitating sustained behavioral change. Moreover, the mediation analysis provides deeper insights into the complex interactions among demographic characteristics and KAP dimensions. Knowledge was influenced by both individual factors and external exposures, highlighting the role of prior awareness and access to health-related information. Attitude was directly shaped by knowledge, education level, and health-related behaviors, reinforcing the idea that higher awareness contributes to more positive perceptions. Smoking status, in particular, was associated with less favorable attitudes, suggesting a potential barrier to preventive engagement. Practice was strongly associated with both knowledge and attitude, supporting the theoretical KAP model, where higher awareness and positive perceptions facilitate behavioral change. Additionally, lifestyle habits such as regular physical activity played a key role in proactive practices, indicating that individuals who engage in overall healthier routines are more likely to adopt protective behaviors for dry eye management. Gender differences were also observed, with certain groups demonstrating a greater inclination toward preventive behaviors, which is consistent with previous research on health-seeking behaviors. Indirect pathways further emphasized the influence of background characteristics on KAP. Younger individuals exhibited higher knowledge levels, which in turn contributed to more favorable attitudes and practices. Having relatives or friends with dry eye was associated with increased awareness, but this did not necessarily translate into stronger attitudes or adherence to recommended practices, suggesting that exposure to the condition alone may not be sufficient to drive behavior change.

The knowledge distribution shows a clear deficiency in patient understanding, especially regarding the role of diet and non-pharmacological treatments for dry eye. Notably, over one-third of participants were unclear about the impact of diet on dry eye and the role of non-pharmacological treatments. These findings align with studies where insufficient patient knowledge was similarly observed, particularly in areas related to lifestyle modifications20,21. To address these gaps, educational interventions should incorporate targeted materials such as patient-friendly brochures, digital infographics, and video tutorials explaining the role of nutrition, hydration, and alternative therapies in dry eye management. Additionally, structured educational workshops within ophthalmology clinics could provide interactive learning opportunities, allowing patients to ask questions and receive tailored guidance from healthcare professionals. Tailored interventions that focus on raising awareness among groups with lower educational attainment or less access to healthcare, such as rural residents and those with lower incomes, could be particularly impactful, as supported by findings from other studies22,23,24.

Regarding attitudes, the majority of participants held positive views about the importance of maintaining good lifestyle habits to manage dry eye. However, nearly half of the participants were neutral or uncertain about the relationship between fluid intake and dry eye. To address this, clinical practice should incorporate hydration education as part of routine ophthalmic consultations. Brief counseling sessions could emphasize the importance of fluid intake for tear production, supported by visual aids or mobile health applications that provide daily hydration reminders. Healthcare providers should deliver clear messages regarding the link between hydration and eye health, reinforced through visual aids or mobile health reminders25,26. Additionally, integrating smoking cessation advice into ophthalmology visits may help improve patient attitudes toward lifestyle-related risk factors, as smoking was identified as a negative predictor of attitude and practice in this study.

In terms of practices, although participants generally reported proactive behaviors, some areas still require improvement, particularly in taking regular eye breaks and following dietary recommendations. Over half of the respondents did not regularly take action to adjust their eye habits or follow dietary patterns, such as the Mediterranean diet. This finding is consistent with other research showing that even when patients have knowledge or positive attitudes, translating this into effective practice remains challenging27,28. To promote sustainable behavioral change, structured reminder systems such as smartphone applications sending notifications for screen breaks, eye massages, and hydration tracking could be implemented. Clinics could also distribute simple lifestyle checklists that encourage patients to self-monitor their adherence to protective habits, reinforcing positive behaviors. For individuals with identified risk factors like smoking or alcohol consumption, integrating these into broader wellness programs that address both dry eye and other health conditions may yield better adherence outcomes29,30.

The correlation analyses showed significant relationships between all three KAP dimensions, with stronger correlations observed between knowledge and practice, and attitude and practice. This finding aligns with previous research showing that while knowledge is a precursor to attitude development, practice is most influenced by both knowledge and attitudes31,32.

Both the correlation analysis and SEM results showed that smoking had a direct impact on patient attitudes and practices. Patients who smoked tended to have more negative attitudes and were less likely to engage in positive practices related to dry eye management. These findings are consistent with prior research that links smoking to poorer health behaviors and eye health outcomes33,34. Gender differences were also evident in both the correlation and SEM analyses, with females exhibiting more proactive practices compared to males. This gender disparity may be partly due to differences in health-seeking behaviors, as women tend to be more proactive in managing health-related issues35,36.

Regular physical exercise had a strong direct effect on practice, as demonstrated by both the correlation and SEM analyses. Participants who engaged in regular exercise were more likely to adopt positive practices related to managing dry eye. This finding aligns with existing literature that shows a correlation between physical activity and improved adherence to healthy behaviors37,38. Given this, ophthalmology clinics could promote exercise-based interventions, such as including exercise recommendations in patient education materials or collaborating with fitness programs to highlight the benefits of physical activity for eye health. While income and education levels showed some influence on knowledge and attitudes, these factors did not significantly impact practice in the SEM model. This discrepancy might suggest that even though higher income and education contribute to better knowledge and more positive attitudes, they do not automatically translate into action. This could be due to various barriers, such as a lack of time, access to resources, or the presence of other competing health priorities39,40. To overcome these barriers, future interventions should focus on integrating eye health recommendations into daily routines through simple, practical strategies that accommodate different socioeconomic backgrounds.

This study has several limitations. First, the cross-sectional design prevents the establishment of causal relationships between knowledge, attitudes, and practices and the incidence or severity of dry eye. While associations were identified, longitudinal or interventional studies are needed to determine whether improving knowledge and attitudes leads to sustained changes in preventive behaviors and clinical outcomes. Second, the use of self-reported questionnaires may introduce recall bias or social desirability bias, potentially affecting the accuracy of responses. Third, the study was conducted at a single ophthalmology hospital in China, which may limit the generalizability of the findings to broader populations. While the sample size was sufficient for statistical analysis, the study setting may not fully represent patients with different healthcare access, socioeconomic backgrounds, or cultural perspectives. Future research should consider multi-center studies or nationally representative samples to enhance the applicability of the findings across diverse populations.

In conclusion, patients demonstrated inadequate knowledge but exhibited generally positive attitudes and proactive practices regarding lifestyle-related dry eye. To improve patient outcomes, healthcare providers should implement structured education programs, integrate lifestyle counseling into routine ophthalmic care, and leverage digital health tools to enhance patient engagement and adherence. Educational interventions should be tailored to different demographic groups, particularly those with lower knowledge levels, to ensure accessibility and effectiveness.