Abstract
Background
This study aimed to explore the knowledge, attitudes, and practices (KAP) of family members of children aged 2–6 years who snore, particularly regarding prevention, treatment, and care.
Methods
Conducted in Shenzhen from July 20 to October 20, 2024, data were collected using structured questionnaires assessing demographics and KAP scores.
Results
A total of 483 valid questionnaires were analyzed, with 318 (65.84%) completed by mothers. The majority of children (164, 33.95%) were 4 years old, and 254 (52.59%) were boys; 237 (49.07%) had snored for 6–12 months. The mean knowledge, attitude, and practice scores were 9.17 ± 2.98 (range: 0–12), 21.21 ± 1.44 (range: 5–25), and 22.34 ± 3.55 (range: 6–30), respectively. Mediation analysis found that average monthly income per person (β = 0.303, P = 0.005), education or training (β = -5.334, P = 0.020), and gender (β = -0.941, P = 0.012) had significant direct effects on knowledge. Meanwhile, knowledge (β = 0.23, P = 0.011), children’s age (β = 0.157, P = 0.006), education or training (β = 0.484, P = 0.008), duration of the child had snoring (β = -0.286, P = 0.007), and education level (β = 0.785, P = 0.014) had significant direct effects on attitude. Further, knowledge (β = 0.590, P = 0.011), attitude (β = 0.428, P = 0.008), employment status (β = -1.609, P = 0.031), children’s age (β = 0.22, P = 0.037) had significant direct effects on practice.
Conclusion
This study highlight the crucial roles of knowledge and attitude in shaping care practices, and underscore the significant influence of demographic factors (such as income, education/training, and caregiver gender) on KAP scores. These insights suggest that targeted interventions focusing on increasing awareness and providing specific education/training are essential to improve the prevention, treatment, and care practices for childhood snoring.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-23952-1.
Keywords: Snoring; Children; Knowledge, attitudes, and practices; Sleep-Disordered breathing; Family health; Health education; Cross-Sectional study
Background
Snoring, a manifestation of sleep-related breathing disorders, is widely recognized as a common symptom of airway obstruction. In recent years, the prevalence of pediatric snoring has increased, driven by rising comorbidities such as asthma and allergies, lifestyle changes, and elevated obesity risk [1]. The prevalence of habitual snoring among children is estimated to range from 1.5 to 27.6% [2]. Sleep-related breathing disorders are among the most prevalent sleep problems in children, disrupting sleep architecture and potentially leading to long-term adverse health outcomes, including cardiovascular diseases and neurocognitive dysfunction. Furthermore, sleep disturbances negatively affect children’s normal development, contributing to language delays and behavioral issues [3]. For example, children aged 5–7 years with primary snoring are more frequently reported by parents to have attention problems, social difficulties, and anxiety or depressive symptoms compared to peers without a history of snoring. Additionally, these children score lower on measures of certain linguistic and visuospatial abilities [4].
Early childhood, particularly the ages of 2 to 6, is a critical period for achieving developmental milestones. The quality of sleep during this stage plays a fundamental role in brain development, learning capacity, and emotional regulation [5]. Poor sleep quality not only contributes to behavioral challenges during the day but also adversely affects family dynamics, increasing parental stress and reducing overall quality of life [6]. Despite the increasing recognition of the severity of sleep-related breathing disorders in children, significant gaps in awareness persist among parents and the general public. Many parents perceive pediatric snoring as a harmless condition rather than a potential health risk, delaying diagnosis and treatment. Such delays exacerbate the condition and hinder children’s development, emphasizing the need to address parental misconceptions and close information gaps.
The Knowledge-Attitude-Practice (KAP) framework is a critical tool in understanding health behaviors [6]. When paired with KAP questionnaires, it provides comprehensive insights into the knowledge, attitudes, and practices of specific populations in healthcare contexts. This approach is valuable for assessing both the demand for and acceptance of relevant health information and interventions [7]. The framework operates on the principle that knowledge informs attitudes, which in turn guide behaviors. By identifying gaps in these dimensions, the KAP model can inform targeted interventions to improve health literacy and promote positive behavioral changes [8].
Given the profound impact of sleep problems on child development and family well-being, this study aims to investigate the KAP of family members of children aged 2–6 years who snore. Specifically, it focuses on their understanding of pediatric snoring, its prevention, treatment, and care. By identifying gaps in knowledge and attitudes, this research seeks to promote evidence-based parenting practices and improve the management of children’s health.
Methods
Study design and participants
Study design and participants
This cross-sectional study was conducted in Shenzhen from July 20 to October 20, 2024, with family members of children aged 2–6 years who experience snoring as the study population. The inclusion criteria were: (1) Family members of children aged 2–6 years with snoring; (2) Family members proficient in using smartphones; (3) Family members of children aged 2–6 years diagnosed with tonsillitis, adenoiditis, or rhinitis. Family members who declined participation in the survey were excluded. This study was approved by the Ethics Committee of Shenzhen GuangMing District People’s Hospital in the Guangming District of Shenzhen, and informed consent was obtained from all participants prior to their inclusion in the study.
Questionnaire introduction
Following the design of the questionnaire, a small-scale pilot test involving 30 participants was conducted, of which 28 responses were valid, yielding an overall reliability coefficient of 0.916. To assess the structural validity of the questionnaire during the pre-test, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was calculated. The KMO value was 0.894, indicating that the data were appropriate for factor analysis and the questionnaire exhibited good structural validity. The Cronbach’s α coefficient of knowledge, attitude and practice dimensions were 0.955, 0.950 and 0.800, respectively. The questionnaire development process incorporated a two-round structured expert review, which served a similar purpose in ensuring content validity. In the first round, three Ear, Nose and Throat (ENT) specialists assessed the initial draft and provided feedback to enhance its relevance to the target population and the comprehensiveness of the measured dimensions. Based on their input, targeted revisions were made. In the second round, two additional ENT specialists reviewed the updated version and suggested further refinements, particularly regarding items related to sleep environment and dietary influences on symptom improvement. This expert review process ensured that the final questionnaire was clinically informed, population-appropriate, and structurally sound.
The final version of the questionnaire, written in Chinese, consisted of four sections: demographic data, knowledge dimension, attitude dimension, and practice dimension. The knowledge dimension included six questions scored as follows: “very knowledgeable” (2 points), “heard of it” (1 point), and “not clear” (0 points), with a total possible score ranging from 0 to 12 points. The attitude dimension comprised five questions using a 5-point Likert scale, ranging from “very willing/confident” (5 points) to “very unwilling/no confidence” (1 point), with a total score range of 5 to 25 points. The practice dimension included six questions, also assessed on a 5-point Likert scale, with responses ranging from “always” (5 points) to “never” (1 point), with a total score range of 6 to 30 points. Attaining scores above 70% of the maximum in each section indicated adequate knowledge, positive attitude, and proactive practice [9, 10]. The questionnaire was developed and administered in Chinese, which is the native language of the study population. The English version presented in this manuscript was translated solely for the purpose of international academic communication.
Quality control
The questionnaires were distributed to participants through the Questionnaire Star and iDiao platforms (https://www.idiaoyan.com/desktop/index). Recruitment efforts targeted specific demographic tags, including location (Shenzhen), status as parents, and having children aged 2–6 years. Participants were further screened through a key question: “Has your child ever snored?” Several quality control measures were implemented to ensure data validity. Questionnaires completed in less than one minute were deemed invalid, and restrictions were applied to limit each participant to a single submission per WeChat ID or IP address, ensuring that responses were not duplicated. During the pretest phase, 30 questionnaires were distributed, and 28 valid responses were returned. The overall Cronbach’s α coefficient for the pretest was 0.916, with coefficients of 0.955, 0.950, and 0.800 for the knowledge, attitude, and practice dimensions, respectively. These results confirmed the reliability and internal consistency of the questionnaire across all dimensions.
Sample size calculation
A sample size estimation was conducted based on the Events Per Variable (EPV) principle, which is commonly used in multivariate analyses. Assuming a minimum of 5 to 10 participants per variable, and considering that the study included up to 30 variables across regression and SEM analyses, a sample size of at least 150–300 participants would be appropriate. With a final sample of 483 valid questionnaires, the study meets the required threshold for statistical reliability.
Statistical methods
Data analysis was conducted using SPSS 27.0 (IBM Corp., Armonk, NY, USA) and AMOS 26.0 (IBM Corp., Armonk, NY, USA). Continuous data were presented as means and standard deviations (SD), while categorical data were expressed as n (%). Demographic characteristics and knowledge, attitude, and practice (KAP) scores were summarized using these measures, and responses to individual KAP questions were expressed as percentages. For group comparisons, the independent t-test was used for normally distributed continuous variables when comparing two groups, while the Wilcoxon Mann-Whitney test was applied to non-normally distributed variables. For comparisons among three or more groups, analysis of variance (ANOVA) was used for normally distributed data with equal variances, while the Kruskal-Wallis test was applied to non-normally distributed or unequal variance data. Post hoc analyses, adjusted using Bonferroni correction, were performed when significant differences were detected in ANOVA. Correlation analysis examined relationships between KAP scores, using Pearson’s correlation coefficient for normally distributed data and Spearman’s rank correlation coefficient for non-normally distributed data. Univariate and multivariate regression analyses were conducted to explore associations between demographic characteristics and KAP scores. The practice score was dichotomized using the median value of 22 as the cut-off point. Practice scores above 22 were categorized as good practice, while scores equal to or below 22 were categorized as poor practice. Variables with P < 0.05 in univariate analysis were included in multivariate models, with continuous variables categorized based on the mean or median, depending on distribution. Structural equation modeling (SEM) and mediation analysis were employed to analyze the relationships among KAP dimensions, with model fit assessed using the root mean square error of approximation (RMSEA), incremental fit index (IFI), Tucker-Lewis index (TLI), and comparative fit index (CFI). Acceptable model fit was defined as RMSEA < 0.08 and IFI, TLI, and CFI > 0.90. All P-values were reported to three decimal places, with P < 0.05 considered statistically significant.
Results
Basic information on the population
A total of 500 questionnaires were collected, of which 17 were excluded due to logical errors, resulting in 483 valid questionnaires for analysis. Among the 483 participants, 318 (65.84%) were mothers of the affected children, 273 (56.52%) were younger than 35 years old, 384 (79.50%) were living in commercial housing, 392 (81.16%) had an education of Bachelor’s/Master’s degree and above, 232 (48.03%) had an average monthly per capita income of 10,000–20,000 Yuan, and 344 (71.22%) had received education or training regarding prevention, treatment, and care of childhood snoring. Among the children, 164 (33.95%) were 4 years old, 254 (52.59%) were boys, 237 (49.07%) had snoring for 6–12 months. The mean knowledge, attitude, and practice scores were 9.17 ± 2.98 (range: 0–12), 21.21 ± 1.44 (range: 5–25), and 22.34 ± 3.55 (range: 6–30), respectively. Analyses of demographic characteristics found that participants’ knowledge, attitude, and practice scores varied across gender (P = 0.018, P = 0.012, P = 0.005), education level (P < 0.001, P < 0.001, P < 0.001), average monthly per capita income (P < 0.001, P = 0.004, P < 0.001), relationship with the child (P = 0.025, P = 0.020, P = 0.001), age of the child (P = 0.009, P = 0.002, P = 0.004), duration of the child’s snoring (P < 0.001, P = 0.004, P < 0.001), and education or training (P < 0.001, P < 0.001, P < 0.001). Meanwhile, differences in knowledge and practice scores were more likely to be found among participants with different type of residence (P < 0.001 and P < 0.001) and employment status (P = 0.006 and P < 0.001) (Table 1).
Table 1.
Demographic characteristics
| Variables | N (%) | Knowledge | Attitude | Practice | |||
|---|---|---|---|---|---|---|---|
| Mean (SD) | P | Mean (SD) | P | Mean (SD) | P | ||
| Total | 483 | 9.17 (2.98) | 21.21 (1.44) | 22.34 (3.55) | |||
| Gender | 0.018 | 0.012 | 0.005 | ||||
| Male | 160 (33.13) | 9.61 (2.96) | 21.46 (1.34) | 22.91 (3.54) | |||
| Female | 323 (66.87) | 8.96 (2.97) | 21.09 (1.48) | 22.06 (3.52) | |||
| Age (years old) | 0.121 | 0.728 | 0.363 | ||||
| <35 | 273 (56.52) | 9.35 (2.98) | 21.22 (1.50) | 22.45 (3.56) | |||
| ≥ 35 | 210 (43.48) | 8.95 (2.97) | 21.20 (1.36) | 22.20 (3.53) | |||
| Type of residence | < 0.001 | 0.284 | < 0.001 | ||||
| Commercial housing | 384 (79.50) | 9.60 (2.80) | 21.27 (1.36) | 22.74 (3.37) | |||
| Affordable housing | 42 (8.70) | 8.02 (3.03) | 20.88 (1.73) | 22.02 (3.92) | |||
| Rental housing | 57 (11.80) | 7.16 (3.08) | 21.04 (1.71) | 19.89 (3.47) | |||
| Education level | < 0.001 | < 0.001 | < 0.001 | ||||
| High school or below | 91 (18.84) | 7.55 (3.02) | 20.29 (1.64) | 20.33 (3.75) | |||
| Bachelor’s/master’s degree or above | 392 (81.16) | 9.55 (2.84) | 21.42 (1.30) | 22.81 (3.33) | |||
| Employment status | 0.006 | 0.082 | < 0.001 | ||||
| Employed | 455 (94.20) | 9.27 (2.93) | 21.24 (1.42) | 22.54 (3.44) | |||
| Unemployed | 28 (5.80) | 7.54 (3.32) | 20.68 (1.70) | 19.14 (3.77) | |||
| Average monthly per capita income | < 0.001 | 0.004 | < 0.001 | ||||
| < 5000 | 37 (7.66) | 6.57 (2.72) | 20.73 (1.61) | 19.59 (3.31) | |||
| 5000–10,000 | 142 (29.40) | 8.75 (2.82) | 21.00 (1.51) | 22.25 (3.57) | |||
| 10,000–20,000 | 232 (48.03) | 9.64 (3.00) | 21.27 (1.43) | 22.56 (3.53) | |||
| > 20,000 | 72 (14.91) | 9.86 (2.50) | 21.67 (1.11) | 23.21 (3.04) | |||
| Marital status | 0.584 | 0.112 | 0.133 | ||||
| Married | 480 (99.38) | 9.18 (2.98) | 21.22 (1.44) | 22.36 (3.55) | |||
| Divorced | 3 (0.62) | 8.33 (2.89) | 20.00 (1.00) | 19.67 (2.52) | |||
| Relationship with the child | 0.025 | 0.020 | 0.001 | ||||
| Father | 158 (32.71) | 9.66 (2.93) | 21.49 (1.32) | 23.00 (3.47) | |||
| Mother | 318 (65.84) | 8.95 (2.98) | 21.08 (1.48) | 22.08 (3.52) | |||
| Grandparents | 7 (1.45) | 8.29 (2.93) | 21.00 (1.73) | 19.00 (3.51) | |||
| Age of the child(years old) | 0.009 | 0.002 | 0.004 | ||||
| 2 | 35 (7.25) | 7.86 (3.04) | 20.31 (1.73) | 21.14 (3.15) | |||
| 3 | 99 (20.50) | 8.75 (2.91) | 21.08 (1.47) | 21.63 (3.21) | |||
| 4 | 164 (33.95) | 9.49 (3.08) | 21.30 (1.47) | 22.32 (3.80) | |||
| 5 | 126 (26.09) | 9.49 (2.93) | 21.49 (1.24) | 22.98 (3.44) | |||
| 6 | 59 (12.22) | 9.12 (2.62) | 21.10 (1.32) | 22.93 (3.48) | |||
| Child’s gender | 0.439 | 0.093 | 0.750 | ||||
| Boy | 254 (52.59) | 9.02 (3.18) | 21.32 (1.42) | 22.27 (3.64) | |||
| Girl | 229 (47.41) | 9.35 (2.73) | 21.08 (1.46) | 22.42 (3.44) | |||
| Duration of the child’s snoring | < 0.001 | 0.004 | < 0.001 | ||||
| Less than 6 months | 114 (23.60) | 8.10 (3.18) | 21.16 (1.51) | 21.20 (3.44) | |||
| 6–12 months | 237 (49.07) | 9.65 (2.84) | 21.41 (1.35) | 22.92 (3.44) | |||
| > 12 months | 132 (27.33) | 9.25 (2.81) | 20.89 (1.48) | 22.27 (3.62) | |||
| Education or training regarding prevention, treatment, and care of childhood snoring | < 0.001 | < 0.001 | < 0.001 | ||||
| Yes | 344 (71.22) | 10.73 (1.77) | 21.47 (1.28) | 23.67 (2.73) | |||
| No | 139 (28.78) | 5.33 (1.49) | 20.56 (1.60) | 19.04 (3.17) | |||
Knowledge, attitude, and practice dimensions
The distribution of knowledge dimensions showed that the three questions with the highest number of participants choosing the “not sure” option were “Do you know which factors may cause childhood snoring?” (K3) with 17.60%, “Do you understand some methods for preventing and treating childhood snoring?” (K6) with 13.87%, and “Do you understand some methods for preventing and treating childhood snoring?” (K5) with 13.04% (Supplementary Fig. 1A). Responses to the attitudinal dimension showed that all participants demonstrated positive attitudes towards taking childhood snoring seriously (A1) and monitoring and assessing symptoms (A3). However, 50.93% were neutral about their willingness to collaborate with doctors or other professionals to develop and implement a treatment and care plan for their child’s snoring (A5) (Supplementary Fig. 1B). When it comes to relevant practices, 18.63% rarely and 1.24% never taken measures to improve their child’s sleep environment (P2), 7.66% rarely and 0.83% never strictly follow the advice of doctors or professionals in implementing the prevention and treatment plan for their child’s snoring (P3), and 7.04% rarely and 1.24% never consciously controlling their child’s diet and lifestyle to prevent or reduce snoring (P4) (Supplementary Fig. 1C).
Correlations between KAP
In the correlation analysis, significant positive correlations were found between knowledge and attitude (r = 0.400, P < 0.001), knowledge and practice (r = 0.660, P < 0.001), as well as attitude and practice (r = 0.433, P < 0.001), respectively (Table 2).
Table 2.
Correlation analysis
| Knowledge | Attitude | Practice | |
|---|---|---|---|
| Knowledge | 1 | ||
| Attitude | 0.400 (P < 0.001) | 1 | |
| Practice | 0.660 (P < 0.001) | 0.433 (P < 0.001) | 1 |
Univariate and multivariate analysis for practice dimension
Multivariate logistic regression showed that knowledge score (OR = 1.471, 95% CI: [1.256, 1.722], P < 0.001), attitude score (OR = 1.471, 95% CI: [1.222, 1.770], P < 0.001), living in affordable housing (OR = 4.508, 95% CI: [1.525, 13.332], P = 0.006), and unemployed (OR = 0.278, 95% CI: [0.093, 0.835], P = 0.022) were independently associated with practice (Table 3).
Table 3.
Factors associated with good practice (practice score > 22) using univariate and multivariate logistic regression analysis
| Variables | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | |
| Knowledge score | 1.622 (1.483, 1.774) | < 0.001 | 1.471 (1.256, 1.722) | < 0.001 |
| Attitude score | 1.772 (1.528, 2.055) | < 0.001 | 1.471 (1.222, 1.770) | < 0.001 |
| Gender | ||||
| Male | Ref. | Ref. | ||
| Female | 0.584 (0.391, 0.873) | 0.009 | 0.641 (0.371, 1.109) | 0.112 |
| Age (years old) | ||||
| <35 | Ref. | |||
| ≥ 35 | 0.801 (0.554, 1.158) | 0.239 | ||
| Type of residence | ||||
| Commercial housing | Ref. | Ref. | ||
| Affordable housing | 0.987 (0.508, 1.919) | 0.969 | 4.508 (1.525, 13.332) | 0.006 |
| Rental housing | 0.296 (0.166, 0.531) | < 0.001 | 0.759 (0.306, 1.879) | 0.551 |
| Education level | ||||
| High school or below | Ref. | Ref. | ||
| Bachelor’s/master’s degree or above | 2.975 (1.861, 4.757) | < 0.001 | 1.314 (0.675, 2.559) | 0.421 |
| Employment status | ||||
| Employed | Ref. | Ref. | ||
| Unemployed | 0.280 (0.124, 0.633) | 0.002 | 0.278 (0.093, 0.835) | 0.022 |
| Average monthly per capita income | ||||
| < 5000 | Ref. | Ref. | ||
| 5000–10,000 | 2.931 (1.364, 6.298) | 0.006 | 1.190 (0.436, 3.248) | 0.735 |
| 10,000–20,000 | 4.194 (2.000, 8.795) | < 0.001 | 1.444 (0.476, 4.377) | 0.516 |
| > 20,000 | 3.472 (1.503, 8.023) | 0.004 | 0.727 (0.216, 2.448) | 0.607 |
| Marital status | ||||
| Married | Ref. | |||
| Divorced | 0.316 (0.028, 3.513) | 0.349 | ||
| Age of the child(years old) | ||||
| 2 | Ref. | |||
| 3 | 1.133 (0.524, 2.452) | 0.751 | ||
| 4 | 1.595 (0.765, 3.324) | 0.213 | ||
| 5 | 1.889 (0.884, 4.036) | 0.101 | ||
| 6 | 1.478 (0.635, 3.439) | 0.364 | ||
| Child’s gender | ||||
| Boy | Ref. | |||
| Girl | 1.156 (0.801, 1.668) | 0.440 | ||
| Duration of the child’s snoring | ||||
| Less than 6 months | Ref. | |||
| 6–12 months | 1.448 (0.919, 2.281) | 0.111 | ||
| > 12 months | 1.245 (0.749, 2.070) | 0.397 | ||
| Education or training regarding prevention, treatment, and care of childhood snoring | ||||
| Yes | 10.263 (6.461, 16.303) | < 0.001 | 1.537 (0.636, 3.714) | 0.339 |
| No | Ref. | Ref. | ||
SEM analysis
SEM analysis showed that average monthly income per person (β = 0.303, P < 0.001), education or training (β = −5.334, P < 0.001), and gender (β = −0.941, P < 0.001) had specific effects on knowledge. Meanwhile, knowledge (β = 0.23, P < 0.001), child’s age (β = 0.157, P = 0.003), education or training (β = 0.484, P = 0.028), duration of the child had snoring (β = −0.286, P < 0.001), and education level (β = 0.785, P < 0.001) had specific effects on attitude. Further, knowledge (β = 0.59, P < 0.001), attitude (β = 0.428, P < 0.001), education or training (β = −0.873, P = 0.047), employment status (β = −1.609, P < 0.001), child’s age (β = 0.22, P = 0.03), relationship with the child (β = −0.843, P < 0.001), and gender (β = 0.521, P = 0.033) had specific effects on practice (Table 4 and Fig. 1).
Table 4.
Structural equation modeling (SEM)
| β | P | |||
|---|---|---|---|---|
| K | <--- | Average monthly income per person | 0.303 | < 0.001 |
| K | <--- | Education or training regarding prevention, treatment, and care of childhood snoring | −5.334 | < 0.001 |
| K | <--- | Your gender | −0.941 | < 0.001 |
| A | <--- | Child’s age | 0.157 | 0.003 |
| A | <--- | Education or training regarding prevention, treatment, and care of childhood snoring | 0.484 | 0.028 |
| A | <--- | Duration of the child had snoring | −0.286 | < 0.001 |
| A | <--- | Education level | 0.785 | < 0.001 |
| A | <--- | K | 0.23 | < 0.001 |
| P | <--- | A | 0.428 | < 0.001 |
| P | <--- | Education or training regarding prevention, treatment, and care of childhood snoring | −0.873 | 0.047 |
| P | <--- | Employment status | −1.609 | < 0.001 |
| P | <--- | Child’s age | 0.22 | 0.03 |
| P | <--- | Relationship with the child | −0.843 | < 0.001 |
| P | <--- | K | 0.59 | < 0.001 |
| P | <--- | Your gender | 0.521 | 0.033 |
Fig. 1.
Structural equation modeling (SEM)
Mediation analysis
Mediation analysis found that average monthly income per person (β = 0.303, P = 0.005), education or training (β = −5.334, P = 0.020), and gender (β = −0.941, P = 0.012) had significant direct effects on knowledge. Meanwhile, knowledge (β = 0.23, P = 0.011), children’s age (β = 0.157, P = 0.006), education or training (β = 0.484, P = 0.008), duration of the child had snoring (β = −0.286, P = 0.007), and education level (β = 0.785, P = 0.014) had significant direct effects on attitude. Further, knowledge (β = 0.590, P = 0.011), attitude (β = 0.428, P = 0.008), employment status (β = −1.609, P = 0.031), children’s age (β = 0.22, P = 0.037) had significant direct effects on practice. Education or training regarding prevention, treatment, and care of childhood snoring had significant indirect effects on attitude (β = −1.229, P = 0.010) and practice (β = −3.468, P = 0.013). Average monthly income per person (β = 0.070, P = 0.003) and gender (β =−0.217, P = 0.004) had a significant indirect effect on attitude. Knowledge, children’s age, average monthly income per person, gender, duration of the child’s snoring, and education level also had significant indirect effects on practice, with β values of 0.099 (P = 0.009), 0.067 (P = 0.005), 0.209 (P = 0.005), −0.649 (P = 0.006), −0.122 (P = 0.005), and 0.336 (P = 0.014), respectively (Table 5).
Table 5.
Mediation analysis
| Path | Total effect | Direct effect | Indirect effect | |||||
|---|---|---|---|---|---|---|---|---|
| Estimate (95%CI) | P | Estimate (95%CI) | P | Estimate (95%CI) | P | |||
| K | <--- | Average monthly income per person | 0.303 (0.157,0.457) | 0.005 | 0.303 (0.157,0.457) | 0.005 | ||
| <--- | Education or training regarding prevention, treatment, and care of childhood snoring | −5.334 (−5.567,−5.013) | 0.020 | −5.334 (−5.567,−5.013) | 0.020 | |||
| <--- | Your gender | −0.941 (−1.168,0.679) | 0.012 | −0.941 (−1.168,0.679) | 0.012 | |||
| A | <--- | Child’s age | 0.157 (0.070,0.243) | 0.006 | 0.157 (0.070,0.243) | 0.006 | ||
| <--- | Education or training regarding prevention, treatment, and care of childhood snoring | −0.746 (0.493,1.034) | 0.014 | 0.484 (0.194,1.057) | 0.008 | −1.229 (−1.548,−0.879) | 0.010 | |
| <--- | Duration of the child had snoring | −0.286 (−0.434,−0.152) | 0.007 | −0.286 (−0.434,−0.152) | 0.007 | |||
| <--- | Education level | 0.785 (0.493,1.034) | 0.014 | 0.785 (0.493,1.034) | 0.014 | |||
| <--- | Average monthly income per person | 0.070 (0.037,0.113) | 0.003 | |||||
| <--- | Gender | −0.217 (−0.312,−0.151) | 0.004 | |||||
| <--- | K | 0.230 (0.167,0.288) | 0.011 | 0.230 (0.167,0.288) | 0.011 | |||
| P | <--- | A | 0.428 (0.271,0.615) | 0.008 | 0.428 (0.271,0.615) | 0.008 | ||
| <--- | Education or training regarding prevention, treatment, and care of childhood snoring | −4.342 (−4.899,−3.933) | 0.005 | −0.873 (−1.587,−0.053) | 0.073 | −3.468 (−4.054,−2.757) | 0.013 | |
| <--- | Employment status | −1.609 (−2.476,−0.387) | 0.031 | −1.609 (−2.476,−0.387) | 0.031 | |||
| <--- | Child’s age | 0.287 (0.084,0.461) | 0.020 | 0.220 (0.050,0.385) | 0.037 | 0.067 (0.031,0.122) | 0.005 | |
| <--- | Relationship with the child | −0.843 (−2.086,0.263) | 0.242 | −0.843 (−2.086,0.263) | 0.242 | |||
| <--- | K | 0.689 (0.564,0.801) | 0.011 | 0.590 (0.464,0.705) | 0.011 | 0.099 (0.055,0.143) | 0.009 | |
| <--- | Gender | −0.128 (−1.245,1.245) | 0.853 | 0.521 (−0.524,2.017) | 0.506 | −0.649 (−0.910,−0.466) | 0.006 | |
| <--- | Duration of the child had snoring | −0.122 (−0.216,−0.056) | 0.005 | |||||
| Education level | 0.336 (0.147,0.517) | 0.014 | ||||||
| Average monthly income per person | 0.209 (0.111,0.334) | 0.005 | ||||||
Discussion
This study found that family members of children aged 2–6 years who snore demonstrated moderate-to-high levels of knowledge, positive attitudes, and proactive practices concerning pediatric snoring and its prevention, treatment, and care, with significant interrelationships between these domains.
Family members demonstrated moderate-to-high levels of knowledge, particularly regarding the complications of pediatric snoring. However, foundational understanding of its causes and preventive measures remained limited. This is consistent with broader literature suggesting that while parents often recognize severe consequences of health issues, they may lack a deeper understanding of causative factors or preventive strategies due to insufficient education or exposure to reliable information sources [11]. For instance, studies on childhood respiratory conditions have shown similar trends, with caregivers prioritizing treatment over prevention, largely due to a lack of accessible and practical preventive guidance [12]. These findings suggest that while awareness campaigns are raising visibility, they may not adequately address the underlying knowledge gaps needed to empower families to adopt preventive behaviors.
Attitudes among respondents were generally positive, with most participants acknowledging the seriousness of snoring as a health issue and expressing a willingness to collaborate with healthcare professionals. However, a noteworthy proportion demonstrated less enthusiasm for engaging in educational activities or proactive measures. These findings align with existing research, which has noted that while families value professional guidance, they often view their role as reactive rather than proactive in managing health conditions [13]. For example, in studies on pediatric asthma, caregivers often emphasized the importance of healthcare professionals while deprioritizing their own role in long-term prevention and management [14, 15]. This highlights the need for targeted interventions that not only provide information but also emphasize the family’s active role in ensuring their child’s health outcomes.
Practice-related findings revealed a contrast, with many participants adhering to professional recommendations while fewer demonstrated proactive behaviors, such as seeking additional information or managing lifestyle factors like diet. These trends reflect systemic challenges, as documented in other healthcare studies, where structural barriers such as limited access to resources, time constraints, and cultural norms hinder families’ ability to engage in more comprehensive care practices [16]. For example, research in low-resource settings has consistently shown that families may prioritize immediate solutions, such as following medical advice, over long-term preventive measures due to perceived complexity or lack of support [17]. This suggests that existing healthcare frameworks may not sufficiently empower families to take ownership of preventive practices, instead positioning them as passive recipients of care.
Statistical analyses further illuminated the interconnected nature of KAP dimensions and the influence of socio-economic and demographic factors. Strong positive correlations between knowledge, attitudes, and practices reinforce findings from other studies, which emphasize the cascading effect of knowledge on behavior through attitudes [18]. SEM analysis revealed that higher levels of knowledge not only directly influenced practices but also mediated their effects through attitudes, demonstrating that improving one dimension can have broader impacts across the behavioral spectrum. This aligns with findings in maternal and child health, where educational interventions targeting knowledge have consistently led to more positive attitudes and better compliance with health recommendations [19, 20]. Furthermore, demographic and socio-economic factors played a significant role, with higher education levels and income strongly associated with better KAP outcomes. These findings mirror patterns observed in other studies, where higher socio-economic status is often linked to better access to healthcare resources, greater exposure to health education, and higher capacity to implement health-promoting behaviors [21]. Conversely, families with lower income or living in less stable housing demonstrated poorer outcomes, reflecting the persistent impact of social determinants of health.
Beyond the direct associations, the mediating effect analysis provided insight into how background factors exert their influence through layered psychological and behavioral processes. Notably, education or training was indirectly associated with both attitude and practice, highlighting the importance of structured information in shaping family members’ perceptions and responses to pediatric snoring. Indirect effects on attitude were also identified for income and gender, pointing to the role of socio-demographic context in forming beliefs. With regard to practice, a wider range of variables-including knowledge, child’ s age, income, gender, duration of symptoms, and education level-showed significant indirect associations. This pattern suggests that practical caregiving behaviors do not emerge solely from surface-level understanding, but are mediated by deeper cognitive and contextual pathways. These findings reaffirm the KAP framework’ s layered logic, where knowledge informs attitudes, and both jointly influence behavior. They also suggest that successful intervention strategies must look beyond information dissemination and address the underlying social and psychological drivers of parental action.
One particularly concerning finding was the disparity in proactive behaviors, such as seeking additional information or implementing lifestyle changes. These less favorable results are consistent with broader healthcare patterns, where families often struggle to transition from knowledge to action due to systemic barriers. Socio-cultural factors, such as reliance on medical authority and limited health literacy, may also play a role, as noted in studies on chronic disease management [22].
To address these gaps, systemic changes in healthcare delivery are essential. One key recommendation is to integrate preventive education into routine pediatric care, ensuring that foundational knowledge gaps are addressed during regular medical consultations. For instance, healthcare providers could incorporate brief but structured educational sessions into routine visits, focusing on the causes, prevention, and management of pediatric snoring. Digital platforms, such as mobile applications and online workshops, could also be leveraged to provide families with accessible and interactive learning tools [23]. In addition to education, healthcare systems must address the socio-economic barriers that hinder proactive health behaviors. Subsidized healthcare programs and financial assistance for low-income families could reduce disparities in access to professional services and educational opportunities [24].
Long-term strategies should focus on creating sustainable systems of support that empower families to adopt preventive practices independently. Healthcare providers and community leaders could collaborate to establish mentorship programs, pairing experienced caregivers with those who are less confident or knowledgeable. Professional development programs for healthcare workers should emphasize the importance of culturally sensitive communication and family-centered care, enabling them to build trust and encourage greater family involvement [25].
This study has several limitations. First, as a cross-sectional design, it cannot establish causal relationships between the identified factors and the KAP of family members. Second, the data were collected through self-reported questionnaires, which may be subject to social desirability bias and recall bias, potentially affecting the accuracy of responses, particularly regarding the duration of children’s snoring and consistency of practices. Third, the study lacked objective clinical assessment of children’s sleep disturbances, relying solely on parents’ reports without polysomnography or other clinical measures to confirm severity. Fourth, the study was conducted in Shenzhen, a highly-developed urban area in China, which limits the generalizability of findings to rural populations who face different healthcare challenges and socio-cultural perspectives. While our findings have reference value for cities with similar economic levels to Shenzhen, future studies should include participants from diverse geographic and socioeconomic backgrounds. Fifth, the knowledge dimension assessment was based on self-reported awareness rather than objective testing, which may reflect perceived rather than actual understanding of pediatric snoring. Sixth, our online recruitment approach required smartphone proficiency, potentially excluding populations with limited digital literacy or technology access, which could introduce selection bias.
Conclusion
In conclusion, family members of children aged 2–6 years who snore demonstrated adequate knowledge, positive attitudes, and proactive practices regarding pediatric snoring and its prevention, treatment, and care, with significant correlations observed between knowledge, attitudes, and practices. Targeted interventions, including educational programs and support for families with lower socioeconomic status or employment constraints, could enhance their capacity to manage pediatric snoring effectively and improve related health outcomes.
Supplementary Information
Supplementary Material 1: Figure 1. Distribution of different dimension responses. A. Knowledge dimension responses. B. Attitude dimension responses. C. Practice dimension responses.
Acknowledgements
Not applicable.
Abbreviations
- KAP
Knowledge, attitudes, and practices
- SEM
Structural equation modeling
- ENT
Ear, nose and throat
- SD
Standard deviations
- ANOVA
Analysis of variance
Authors’ contributions
Fang Zheng Han carried out the studies, participated in collecting data and drafted the manuscript. performed the statistical analysis and participated in its design. Zhao Yan Xia participated in acquisition, analysis, or interpretation of data and draft the manuscript. All authors read and approved the final manuscript.
Funding
None.
Data availability
All data generated or analysed during this study are included in this published article.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Shenzhen GuangMing District People’s Hospital (LL-KT-2024070), I confirm that all methods were performed in accordance with the relevant guidelines. All procedures were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments, and informed consent was obtained from all participants.
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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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material 1: Figure 1. Distribution of different dimension responses. A. Knowledge dimension responses. B. Attitude dimension responses. C. Practice dimension responses.
Data Availability Statement
All data generated or analysed during this study are included in this published article.