Behavioral and parental predictors of infant and toddler sleep quality

Abstract

Background

Sleep is critical for early development, yet sleep disturbances are prevalent. In low- and middle-income countries (LMICs) like Iran, cultural practices can significantly shape sleep behaviors. This study aimed to identify behavioral and parental factors associated with sleep quality among infants and toddlers aged 0–36 months in Iran.

Methods

This cross-sectional study surveyed 358 parents using the validated Persian version of the Brief Infant Sleep Questionnaire-Revised (BISQ-R). Multiple linear regression was conducted to examine associations between behavioral and parental factors and the BISQ-R Total Sleep Score.

Results

The mean Total Sleep Score was 64.2 (SD = 14.3), indicating moderate overall sleep quality. The final regression model explained 28% of the variance in sleep scores (Adjusted R² =0.28, p<.001). Pre-sleep screen time, bed-sharing, and increasing child age were significantly negatively associated with sleep quality, whereas higher birth weight and greater parental education were positively associated.

Conclusion

Modifiable behaviors, particularly screen use before bedtime and bed-sharing, were significantly associated with poorer parent-reported sleep quality in this cultural context. These findings highlight the need for culturally sensitive parental education and anticipatory guidance to support healthy sleep hygiene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-026-06713-w.

Introduction

Sleep disturbances are among the most frequently reported concerns among parents of infants and toddlers, with approximately 25–30% indicating that their child experiences some form of sleep difficulty [1–3]. Among toddlers, bedtime resistance and frequent night wakings affect about 25–30%, while parasomnias such as sleepwalking and night terrors are observed in nearly half of this age group [4].

Typically, toddlers sleep between 11 and 12 h per day during their second year of life, with only a slight decline as they grow older. Most take a single daily nap, which is often phased out by the end of the second or third year [5]. Although night wakings tend to decrease with age, many toddlers still awaken at least once per week and seek parental attention. The extent to which these awakenings become problematic largely depends on the child’s ability to self-soothe and return to sleep without external intervention [6].

Emerging evidence indicates that insufficient or disrupted sleep during early childhood is associated with a range of adverse health outcomes, including elevated blood pressure, high cholesterol, insulin resistance, and an increased risk of obesity [7, 8]. Additionally, sleep-deprived children are more susceptible to common infections, such as colds. Beyond physical health, adequate sleep plays a critical role in cognitive development, emotional regulation, and social functioning—both at home and in early education environments. Failure to establish healthy sleep patterns during this formative period can lead to long-term and potentially irreversible consequences [7, 9, 10].

Given these potential risks, understanding the role of modifiable parental behaviors in shaping children’s sleep is crucial. For example, parental presence during bedtime routines has been associated with more frequent night wakings and prolonged sleep onset. Importantly, evidence shows that changing such behaviors can significantly improve sleep outcomes in infants and toddlers [10–12].

Early identification and intervention are therefore essential. Screening tools that are accessible to both parents and healthcare providers can facilitate timely recognition and management of sleep problems during the critical first three years of life [13]. However, assessing sleep in early childhood remains methodologically challenging in epidemiological research [14].

Among the behavioral and environmental contributors to sleep disruption, the growing use of electronic devices—such as televisions, smartphones, and tablets—has emerged as a particularly worrisome factor [15]. The blue light emitted from these screens interferes with melatonin production and disrupts circadian rhythms. Young children are especially vulnerable to such environmental stimuli, making screen exposure a significant threat to both sleep quantity and quality [16].

Moreover, cultural factors can shape sleep practices. In many non-Western societies, including Iran, co-sleeping is a culturally accepted norm and may interact with other behaviors, such as screen use, to influence sleep patterns [17–19]. Despite the high prevalence of sleep problems in early childhood and the rising use of digital media, few studies in Iran have examined these relationships in depth.

In light of these considerations, the present study aimed to describe the prevalence of sleep disturbances and patterns of electronic media exposure among Iranian children aged 0–36 months, examine the associations between screen use, co-sleeping practices, and sleep quality, and identify the most significant predictors of sleep quality in this age group.

Methods

Study design and participants

This cross-sectional study was conducted from June 2024 to February 2025 in Isfahan, Iran. Participants were recruited from local health centers during routine child health assessments and vaccination visits. A total of 450 parents of eligible children aged 0–36 months were approached, of whom 400 (88.9%) consented to participate. After excluding surveys with substantial missing data (n = 42), the final analytical sample consisted of 358 parent-infant dyads. A sample of this size was deemed sufficient to provide stable estimates for the regression model based on precedents in similar pediatric sleep studies. This study was reported in accordance with the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines for cross-sectional studies [20].

Sampling method

A multi-stage sampling strategy was employed. First, health centers across Isfahan were stratified based on geographical region. In the second stage, simple random sampling was used to select participants from each stratum. For each center, a numbered list of eligible children was generated. Participants were then randomly selected without replacement using a computer-generated random number sequence until the sample quota for each center was fulfilled.

Inclusion and exclusion criteria

Children eligible for inclusion in the study were between 0 and 36 months of age, and their parents expressed willingness to participate and provided informed consent. Children were excluded from the study if they were hospitalized during the study period, were currently using medications known to affect sleep patterns, or had diagnosed physical or psychological conditions that could influence their sleep.

Data collection instruments

Data for this study were collected using two primary methods: a standardized questionnaire and a structured parent interview.

Brief infant sleep questionnaire-revised (BISQ-R)

The primary outcome was the Total Sleep Score from the 32-item long-form of the Brief Infant Sleep Questionnaire-Revised (BISQ-R), calculated using the norm-referenced, age-based system developed by Mindell et al. (2019) [21]. This composite score is scaled from 0 to 100, where higher scores indicate better overall sleep quality, and is derived from three subscales: Infant Sleep (measuring core sleep patterns), Parent Perception (assessing the caregiver’s view of sleep problems), and Parent Behavior (capturing sleep-related routines). While the score provides a continuous measure of sleep quality, no official clinical cut-off points have been established.

Structured parent interview

A structured interview was conducted to gather sociodemographic and key behavioral data. This included:

• ◦ Sociodemographic Information: Parent’s age, highest level of education, and the number of household members.

• ◦ Bed-sharing Practices: Bed-sharing was operationalized as the child sleeping on the same surface (e.g., bed or mattress) as a parent for more than half of the night on four or more nights per week [22, 23]. This variable was dichotomized to distinguish habitual bed-sharing from occasional or situational co-sleeping. This decision was guided by both conceptual and empirical considerations. Conceptually, habitual bed-sharing reflects a stable sleep arrangement likely to have sustained implications for sleep regulation and parental perceptions, whereas infrequent bed-sharing may represent temporary responses to illness, distress, or environmental disruptions. Empirically, preliminary analyses indicated a markedly skewed distribution of bed-sharing frequency, limiting its suitability as a continuous predictor. Similar dichotomization approaches have been employed in prior pediatric sleep research to capture clinically meaningful sleep behavior patterns [22, 24, 25]. Nevertheless, the potential loss of variability associated with dichotomization is acknowledged as a limitation [26].

• ◦ Pre-Sleep Screen Exposure: This was quantified by asking parents to report the average number of minutes their child was exposed to any screen (television, phone, or tablet) within the 60 min prior to bedtime on a typical day.

Instrument validity and reliability

Since no validated Persian version of the BISQ-R (long form with 32 items) was available, a rigorous, multi-phase translation and psychometric validation process was conducted to ensure cultural and linguistic appropriateness as well as measurement accuracy.

Translation process

With formal permission from the original developer, the BISQ-R was translated into Persian using the Brislin back-translation model. Two independent bilingual (Persian–English) translators performed the forward translation. A third expert reconciled the two versions into a single draft. This draft was then back-translated into English by two other bilingual translators who were unfamiliar with the original instrument. The back-translated versions were compared with the original BISQ-R to ensure semantic, idiomatic, and conceptual equivalence. The final Persian version was reviewed and approved by the research team and the original author.

Face validity

Face validity was assessed both qualitatively and quantitatively. A panel of 15 parents of infants aged 0–36 months evaluated each item for clarity, relevance, and comprehensibility. The impact score for each item was calculated using the following formula.

All items achieved an impact score above 1.5, the established threshold for retention, indicating strong face validity.

Content validity

Content validity was evaluated by a panel of fifteen experts, including three pediatricians, one child psychologist, five specialist nurses, three nursing professors, and three sleep researchers.

• Content Validity Ratio (CVR) was calculated based on Lawshe’s method. All retained items met the critical threshold of 0.49 for fifteen experts.

• Item-Level Content Validity Index (I-CVI) and Scale-Level Content Validity Index (S-CVI) were calculated using Waltz and Bausell’s framework. I-CVI values ≥ 0.79 were deemed acceptable, and the S-CVI (average of I-CVIs) was 0.92, indicating excellent content validity.

Reliability

• Internal Consistency: The overall Cronbach’s alpha for the scale was 0.82, indicating good internal consistency.

• Test-Retest Reliability: A subset of 25 parents completed the questionnaire twice over a 3-week interval. The Intraclass Correlation Coefficient (ICC) for the total sleep score was 0.87 (95% CI: 0.76–0.93), indicating excellent temporal stability.

This entire validation process was conducted on the data from the 358 participants recruited for this study.

Data analysis

Descriptive statistics (means, standard deviations, medians, interquartile ranges [IQR], frequencies) were used to summarize variables. A standard multiple linear regression was conducted to identify predictors of the BISQ-R Total Sleep Score, with all predictors entered simultaneously. Covariates were selected a priori based on established literature and included child age, sex, birth weight, breastfeeding status, and parental education.

Model assumptions for the multiple linear regression were thoroughly checked. Linearity was assessed by examining scatterplots of the residuals against each predictor. Homoscedasticity (constant variance of errors) was confirmed by plotting standardized residuals against standardized predicted values, which showed no discernible pattern. The normality of residuals was verified using a P-P plot, which showed points closely following the diagonal line. Multicollinearity was assessed using the Variance Inflation Factor (VIF); all VIF values were below 2.0, well under the common threshold of 10, indicating no issues with multicollinearity.

Given the multi-stage sampling design, standard errors were adjusted for potential clustering by health center using robust variance estimators to ensure the reliability of the findings. Missing data were minimal (< 2% for any single variable) and handled with pairwise deletion. A p-value < 0.05 was considered statistically significant.

Results

Sample characteristics

The final sample included 358 parent-infant dyads from Isfahan, Iran. The demographic and clinical characteristics of the sample are presented in Table 1. The majority of infants were full-term (75.0%, n = 268), breastfed (80.0%, n = 286), and lived in households with more than three members (60.0%, n = 215).

Table 1.

Demographic characteristics of the study sample(N = 358)

Characteristic	Category	Value (n, %) or mean ± SD
Parent Demographics	Primary Respondent (Mother)	322 (90.0%)
	Age (years)	31.2 ± 4.5
	Education Level
	Diploma or less	90 (25.1%)
	Bachelor’s Degree	149 (41.6%)
	Master’s / PhD	119 (33.3%)
Infant Demographics
Gender (Male)		185 (51.7%)
Birth Status (Premature)		90 (25.1%)
Weight (kg)	0–6 months (n = 90)	Median = 5.8 [4.9, 6.7]
	6–12 months (n = 72)	Median = 8.9 [8.2, 9.5]
	12–24 months (n = 125)	Median = 11.2 [10.1, 12.4]
	24–36 months (n = 71)	Median = 13.8 [12.9, 14.7]
	Mean (SD)	7.1 ± 1.4
Head Circumference (cm)	0–6 months (n = 90)	Median = 40.5 [38.0, 42.5]
	6–12 months (n = 72)	Median = 45.0 [44.0, 46.0]
	12–24 months (n = 125)	Median = 47.5 [46.5, 48.5]
	24–36 months (n = 71)	Median = 49.0 [48.0, 50.0]
Sleep Pattern	Nighttime sleep (hours)*	Median = 9.5 [8.0, 10.5]

*Note. Unless otherwise indicated, values are presented as n (%). For skewed variables, values are Median [Interquartile Range]. Nighttime sleep excludes daytime naps

Sleep behaviors and predictors of sleep quality

The median nighttime sleep duration was 9.5 h, as shown in Table 1. A significant proportion of infants (65.0%, n = 233) engaged in bed-sharing. The most frequently reported sleep position was supine (50.0%, n = 179). A consistent bedtime routine was common (reported by 60.0% for seven days a week).

Overall sleep quality, measured by the BISQ-R Total Sleep Score, had a mean of 64.2 (SD = 14.3). An independent samples t-test revealed that the bed-sharing group had significantly lower sleep scores (M = 61.1) than the non-bed-sharing group (M = 68.4), t (356) = 2.43, p = .016.

Correlational analysis indicated that parental Perception had the strongest positive correlation with sleep quality (r = + 0.34), while pre-sleep screen exposure had the strongest negative correlation (r = -.28) (Table 2).

Table 2.

Pearson correlations among study variables (N = 358)

Variable	1	2	3	4	5	6	7	8
1. BISQ-R Total Sleep Score	—
2. Child Age (months)	−0.22**	—
3. Bed-sharing (Yes = 1)	−0.19**	0.26**	—
4. Pre-sleep Screen Time (min)	−0.28**	0.31**	0.21**	—
5. Infant Weight (kg)	0.20**	0.64**	0.14*	0.18**	—
6. Parental Education (Level)	0.18*	−0.16*	−0.11*	−0.19**	0.09	—
7. Breastfeeding (Yes = 1)	0.15*	−0.24**	−0.13*	−0.17**	−0.10	0.12*	—
8. Child Sex (Male = 1)	−0.04	0.02	0.01	0.03	0.05	−0.01	−0.02	—

Pearson correlation coefficients are shown. *p < .05. **p < .01. Higher BISQ-R scores indicate better sleep quality. Bed-sharing and breastfeeding were coded as 0 = No, 1 = Yes. Parental education was coded as 1 = Diploma or less, 2 = Bachelor’s, 3 = Master’s/PhD

Hierarchical multiple linear regression was conducted to examine predictors of BISQ-R Total Sleep Score (Table 3). In Step 1, non-modifiable child and family characteristics—including child age, child sex, birth status, and parental education—were entered into the model. This model was statistically significant, accounting for 19% of the variance in sleep quality (R² = 0.19, adjusted R² = 0.18), F (4, 353) = 20.74, p < .001. Within this step, older child age was significantly associated with poorer sleep quality (β = −0.19, p = .003), whereas higher parental education was associated with better sleep quality (β = 0.12, p = .030). Child sex and birth status were not significant predictors.

Table 3.

Hierarchical multiple linear regression predicting BISQ-R total sleep score (N = 358)

Predictor	B	SE	95% CI	β	t	p
Step 1: Non-modifiable characteristics
Intercept	70.12	4.10	[62.06, 78.18]	—	17.10	< 0.001
Child age (months)	−1.18	0.39	[− 1.95, − 0.41]	−0.19	−3.03	0.003
Child sex (male = 1)	−0.92	1.05	[− 2.99, 1.15]	−0.04	−0.88	0.379
Birth status (preterm = 1)	−1.65	1.12	[− 3.85, 0.55]	−0.07	−1.47	0.142
Parental education level	2.14	0.98	[0.22, 4.06]	0.12	2.18	0.030
Step 2: Modifiable sleep-related behaviors
Intercept	67.80	4.25	[59.44, 76.16]	—	15.09	< 0.001
Child age (months)	−1.24	0.41	[− 2.05, − 0.43]	−0.20	−3.02	0.003
Parental education level	2.03	1.01	[0.17, 4.13]	0.11	2.01	0.047
Bed-sharing (yes = 1)	−3.40	1.56	[− 6.50, − 0.40]	−0.14	−2.19	0.029
Pre-sleep screen time (min)	−0.21	0.07	[− 0.35, − 0.07]	−0.19	−3.00	0.003
Infant weight (kg)	1.87	0.62	[0.68, 3.12]	0.16	3.01	0.003
Breastfeeding (yes = 1)	1.75	1.10	[− 0.41, 3.91]	0.08	1.59	0.115

Model fit (Step 1). R² = 0.19, Adjusted R² = 0.18, F (4, 353) = 20.74, p < .001

Model fit (Step 2 – final model). R² = 0.28, Adjusted R² = 0.27 ΔR² = 0.09, ΔF (3, 350) = 14.62, p < .001

CI confidence interval. Child sex coded as 0 = female, 1 = male. Birth status coded as 0 = term, 1 = preterm. Bed-sharing and breastfeeding coded as 0 = no, 1 = yes. Parental education coded as 1 = diploma or less, 2 = bachelor’s, 3 = master’s/PhD. Step 1

In Step 2, modifiable sleep-related behaviors and health characteristics—bed-sharing, pre-sleep screen exposure, infant weight, and breastfeeding status—were added to the model. The inclusion of these variables resulted in a significant improvement in explained variance (ΔR² = 0.09), ΔF (3, 350) = 14.62, p < .001. The final model accounted for 28% of the variance in sleep quality (adjusted R² = 0.27).

In the final model, habitual bed-sharing (β = −0.14, p = .029), greater pre-sleep screen exposure (β = −0.19, p = .003), and older child age (β = −0.20, p = .003) were independently associated with poorer sleep quality. In contrast, higher infant weight (β = 0.16, p = .003) and higher parental education (β = 0.11, p = .047) were associated with better sleep quality. Breastfeeding status was not significantly associated with BISQ-R scores in the fully adjusted model.

Discussion

This study examined the influence of bed-sharing, screen time, and various parental and demographic factors on sleep quality among infants and toddlers in Isfahan, Iran. The findings underscore the pivotal role of modifiable behavioral factors in shaping early childhood sleep patterns.

The mean total sleep score indicated moderate sleep quality, consistent with previous studies reporting high prevalence of sleep disturbances among young children [1, 2]. Bed-sharing was a significant negative predictor of sleep quality, highlighting the need for a culturally nuanced interpretation. While it is a normative and valued practice in many Iranian families [27], close sensory proximity may lead to more frequent awakenings, which are captured by the BISQ-R as indicators of poorer sleep. This finding should not be interpreted as a recommendation against bed-sharing, but rather as evidence of its potential association with perceived sleep disruption in this specific context. Furthermore, the nature of bed-sharing likely evolves with development; it may be primarily parent-initiated for caregiving in infancy, while toddlers might seek it out independently. This complexity should be considered when interpreting the results.

Similar findings have been reported elsewhere. Garrido et al. (2024) found that co-sleeping during infancy was associated with lower sleep quality in preschool-aged children [28]. Likewise, Volkovich et al. (2015) observed that mothers of co-sleeping infants reported more frequent night wakings and rest disturbances due to sensory proximity [23]. Together with our results, these findings suggest that while bed-sharing may support emotional closeness, it can also contribute to fragmented sleep. Given the cross-sectional design, it is also plausible that children experiencing poorer sleep may elicit more bed-sharing or screen exposure from caregivers as adaptive strategies, rather than these behaviors solely causing reduced sleep quality. Longitudinal research has shown that associations between sleep and screen use can be bidirectional, where media use predicts later sleep patterns and sleep patterns predict later media use, underscoring the need for prospective designs to clarify directionality [29]. Future longitudinal research is needed to disentangle the directionality of these associations, as most existing evidence from cross-sectional studies cannot establish causal order [30].

Screen exposure before bedtime was another factor negatively associated with sleep quality. Consistent with prior research, screen use correlates with delayed sleep onset, shorter duration, and poorer sleep quality in children [31]. Gomes et al. (2024) reported links between screen time and longer sleep onset latency and increased daytime sleepiness [32]. while dos Santos et al. (2024) demonstrated that exposure to bright screens suppresses melatonin production and disrupts circadian rhythms [33]. Blue light emitted from screens delays melatonin secretion, thereby fragmenting sleep cycles [34, 35]. Infants and toddlers may be particularly vulnerable due to heightened physiological sensitivity.

Positive predictors of sleep quality included higher infant weight and greater parental education. Higher weight likely reflects better general health and developmental stability, supporting more consolidated sleep [7]. Parental education may enhance awareness of healthy sleep practices, such as consistent bedtime routines and reduced pre-sleep stimulation [36]. Additionally, parental education also serves as a proxy for broader socioeconomic status (SES), a factor not directly measured in this study but known to strongly influence child health and developmental outcomes [37].

An intriguing finding was that older child age predicted lower parent-reported sleep quality. Although this seems counterintuitive—since sleep architecture typically matures and stabilizes during early childhood [38, 39], it may reflect evolving parental perceptions rather than actual deterioration in sleep. As toddlers gain autonomy, behaviors such as bedtime resistance and night awakenings related to separation anxiety become more prominent. These behaviors are heavily weighted in sleep questionnaires, potentially leading parents to perceive sleep as poorer, even when objective sleep parameters remain stable or improve. This discrepancy highlights the importance of distinguishing between physiological sleep maturation and subjective parental evaluation.

Finally, higher parental Perception was associated with better sleep outcomes, emphasizing the role of parenting self-efficacy in promoting healthy sleep patterns. Interventions enhancing parental competence and confidence could meaningfully improve early childhood sleep [13].

Implications for practice and policy

The findings of this study carry important implications for pediatric health care and early childhood interventions. Promoting parental education on healthy bedtime routines, limiting pre-sleep screen exposure, and gradually encouraging independent sleep practices may enhance sleep quality and developmental outcomes. Pediatricians and primary health care providers should integrate anticipatory guidance on sleep hygiene into routine child health visits.

At the policy level, incorporating sleep health education into national child development and parenting programs could offer a cost-effective strategy to improve child well-being at the population level. These interventions should be culturally sensitive, acknowledging traditional caregiving practices such as bed-sharing, while guiding families toward sleep-promoting behaviors.

Strengths and limitations

A key strength of this study is the use of the BISQ-R, a standardized and psychometrically validated instrument that we rigorously translated and culturally adapted for the Persian context, thereby ensuring the linguistic and conceptual equivalence of our primary outcome measure. The study also employed a robust sampling strategy and examined multiple interacting predictors of sleep quality, providing a multidimensional understanding of the phenomenon. However, several limitations should be acknowledged. The cross-sectional design precludes causal inference. All sleep and behavioral data were based on parental reports, which may be subject to recall or social desirability bias; future studies would benefit from incorporating objective measures such as actigraphy. The findings may also have limited generalizability beyond urban Iranian populations.

Importantly, the broad age range of our sample (0–36 months) and the resulting inability to conduct statistically powered, age-stratified analyses (e.g., separate models for infants vs. toddlers) is an important limitation. The motivations and implications of practices like bed-sharing may differ across these developmental stages, but our combined analysis could not explore these nuances. Future studies with larger samples should examine age-specific patterns to clarify the developmental trajectories of sleep behaviors and their predictors.

Another key limitation is the absence of a direct assessment of parental mental health, including postpartum depressive symptoms. Given robust evidence that parental psychological well-being influences caregiving behaviors, parental perceptions, and child sleep outcomes, future research should incorporate validated mental health measures to more fully contextualize sleep-related behaviors and reports.

Conclusion

This study demonstrates that modifiable behavioral factors—particularly pre-sleep screen exposure and bed-sharing—are significant predictors of sleep quality among young Iranian children. The findings highlight the complex interaction between modern lifestyle habits and traditional caregiving practices in shaping early childhood sleep. Culturally sensitive, parent-focused interventions addressing these factors could improve child health outcomes and serve as scalable, low-cost public health strategies, especially in low- and middle-income countries (LMICs).

Further research is needed to confirm these findings longitudinally, examine causal and potentially bidirectional relationships, account for factors like parental mental health, and explore long-term developmental outcomes. Additionally, future work should investigate how digital media use interacts with socio-cultural caregiving norms to inform contextually appropriate sleep health policies and educational initiatives across diverse settings.

Declaration.

Authors’ contributions

F.K: Project Administration, Conceptualization, Methodology, Investigation, Writing – Original Draft, Formal Analysis. M.A: Supervision, Validation, Writing – Review & Editing, Final Approval of the Manuscript. A. Gh: Methodology, Data Curation, Writing – Review & Editing. S. Kh: Methodology, Data Curation, Writing – Review & Editing. All authors read and approved the final manuscript.

Funding statement

This research was supported by a grant from the Nursing and Midwifery Care Research Center, Isfahan University of Medical Sciences.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to participant confidentiality concerns but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Research Ethics Committee of the Schools of Nursing, Rehabilitation, and Management at Isfahan University of Medical Sciences (Approval ID: IR.MUI.NUREMA.REC.1401.031; Scientific Code: 2400282; Approval Date: 2024-05-07). Ethical principles were observed throughout the study in accordance with the Declaration of Helsinki. Informed consent was obtained from all participating parents or legal guardians prior to data collection. Participant confidentiality and data anonymity were strictly maintained.

Consent for publication

Written informed consent for the publication of anonymized data was obtained from the parents or legal guardians of all participants.

Competing interests

The authors declare no competing interests.