Associations of maternal fatigue and perceived nurse–parent support with cyberchondria dimensions among mothers of hospitalized children aged 0–6 years: a path analysis

Abstract

Background

Cyberchondria has become increasingly prominent among mothers experiencing heightened uncertainty, stress, and caregiving burden during pediatric hospitalization, highlighting the critical role of professional nurse–parent support and holistic nursing care in managing this process.

Aim

To examine associations of maternal fatigue and perceived nurse–parent support with five dimensions of cyberchondria—compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals among mothers of hospitalized children aged 0–6 years using structural equation modeling.

Methods

This cross-sectional study was conducted between April and November 2025 in the pediatric wards of a Training and Research Hospital in western Türkiye. The sample consisted of 216 mothers of hospitalized children aged 0–6 years. Data were collected using the Brief Fatigue Inventory (BFI), the Nurse Parent Support Tool (NPST), and the Cyberchondria Severity Scale (CSS). Relationships among variables were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Standardized path coefficients (β), explained variance (R²), and bootstrapping (5,000 resamples) were used to evaluate the structural model.

Results

Mothers demonstrated moderate levels of cyberchondria (73.16 ± 23.31) and fatigue (2.86 ± 1.07). Nurse–parent support was significantly and negatively associated with all cyberchondria subdimensions (β ranging from − 0.335 to − 0.436, p < 0.001). Fatigue severity showed limited and subdimension-specific effects, whereas fatigue interference with daily activities was not a significant predictor. The model explained 11%–21% of the variance in cyberchondria subdimensions. Multi-group analyses indicated that the negative association between nurse–parent support and cyberchondria dimensions remained consistent across demographic subgroups.

Conclusion

Perceived nurse–parent support was consistently associated with lower levels of cyberchondria. These findings highlight the importance of structured nurse–parent communication and support when addressing cyberchondria-related online health information-seeking behaviors among mothers of hospitalized children.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12889-026-28911-y.

Introduction

Cyberchondria is defined as a condition in which individuals engage in excessive and repetitive online searches for health-related information, which, rather than alleviating anxiety as expected, paradoxically leads to increased distress [1], and it refers to the anxiety-provoking impact of online health information seeking [2]. Online health information seeking is not inherently maladaptive; when it is purposeful and proportionate to the information need, it may support parents’ understanding and communication with healthcare professionals. In contrast, cyberchondria involves excessive, repetitive, and difficult-to-control searching that increases rather than alleviates distress [2]. Individuals with a tendency toward cyberchondria are reported to interpret health-related situations through worst-case scenarios and to experience intense anxiety during the process of seeking information online [3]. Given that a substantial proportion of internet users search for information to identify disease symptoms, cyberchondria has emerged as a significant public health concern [4]. In particular, it has been suggested that mothers who exhibit heightened sensitivity regarding their children may engage in persistent online health searches, which can exacerbate cyberchondria and adversely affect mental well-being [5–7]. Beyond increasing anxiety, cyberchondria has been associated with several adverse outcomes, including excessive healthcare utilization, unnecessary medical consultations, impaired decision-making, and reduced trust in healthcare professionals [8, 9]. These behaviors may not only burden healthcare systems but also negatively affect caregiving quality, particularly in vulnerable populations such as parents of hospitalized children. In such contexts, maladaptive online health information–seeking behaviors may lead to delayed professional consultation, inappropriate self-management practices, or heightened distress that interferes with caregiving responsibilities [2, 10]. Epidemiological evidence indicates that a substantial proportion of individuals engage in online health information seeking, with studies indicating that more than 70% of internet users search for health-related information [11]. Among these individuals, a significant subset develops cyberchondria-related behaviors, particularly in high-stress contexts such as illness or caregiving [8]. Recent studies have reported moderate to high levels of cyberchondria across different populations, including parents and caregivers, highlighting its growing relevance as a public health concern [7, 12].

A child’s hospitalization represents a process that imposes substantial physical, emotional, and psychological burdens on families [13]. While children’s needs are prioritized in hospital settings, the stress and caregiving burden experienced by parents—particularly mothers—are often overlooked [14]. Uncertainties related to the child’s appearance, behaviors, and disease trajectory contribute to heightened parental stress and fatigue [15]. Disruptions in sleep duration and quality become almost inevitable in hospital environments; this, in turn, exacerbates fatigue and adversely affects cognitive functioning and mental clarity [16]. Moreover, the high caregiving demands associated with younger hospitalized children further intensify maternal fatigue levels [13, 17]. These conditions may increase vulnerability to maladaptive coping strategies, including excessive online health information seeking.

During this process, nurse–parent support plays a critical role in helping mothers cope with stress and uncertainty. Professional nurse–parent support is an approach grounded in social support models and is regarded as an integral component of care in pediatric nursing practice [18]. Through continuous interaction with families in hospital settings, nurses establish effective communication and facilitate parental engagement in the care process by providing information and counseling [19, 20]. A positive, supportive, and trust-based nurse–parent relationship contributes to reductions in maternal anxiety and enables mothers to perceive the caregiving process as more manageable and controllable [21, 22].

From a theoretical perspective, the relationships among maternal fatigue, perceived nurse–parent support, and cyberchondria can be explained within the framework of stress and coping theory [23]. Uncertainties experienced during critical periods such as pregnancy and motherhood drive women to seek health information online; however, this process often creates a “vicious cycle” that increases anxiety and maternal psychological fatigue [24]. Under these conditions, maternal fatigue and excessive online health information–seeking behavior, defined as cyberchondria, may reinforce each other. During the perinatal period, anxiety and stress levels increase due to lack of information, conflicting health advice, and uncertainties regarding the infant’s development [25]. Anxiety and depression are strong predictors of postpartum fatigue and are also directly associated with increased online searching and health-related anxiety [26]. Since online information is often inconsistent, mothers may become even more anxious, and frequent, uncontrolled searching behaviors may further exacerbate fatigue, sleep disturbances, and burnout [27].

The present study specifically focused on mothers because they are generally the primary caregivers during child hospitalization and often assume the greatest responsibility for direct caregiving activities, emotional support, and health-related decision making [28]. Previous research has consistently shown that mothers experience higher levels of caregiving burden, stress, and emotional distress than other family members during pediatric hospitalization, making them particularly vulnerable to maladaptive coping responses such as excessive online health information seeking [29].

Furthermore, the hospital setting provides a unique context in which uncertainty, perceived threat, and information needs are intensified [30]. According to Stress and Coping Theory, individuals facing stressful situations engage in cognitive appraisal processes and adopt coping strategies to manage perceived demands [25]. In this context, cyberchondria may be interpreted as a maladaptive coping response aimed at reducing uncertainty through repeated online health information seeking, whereas nurse–parent support may function as an external coping resource that helps mothers appraise stressful situations more effectively and reduces reliance on excessive online reassurance seeking. Therefore, examining these relationships within a pediatric hospitalization setting provides an appropriate framework for understanding how professional support and maternal fatigue interact in shaping cyberchondria-related behaviors.

Conversely, perceived nurse–parent support represents a critical protective factor that may buffer the effects of stress and uncertainty. Nursing support has strategic importance in combating cyberchondria, which has rapidly increased in the digital age. Although health anxiety and intolerance of uncertainty are well-established psychological correlates of cyberchondria [3], the present study focused specifically on caregiving-related fatigue and nurse–parent support as a potentially modifiable nursing care factor. In pediatric settings, within the framework of family-centered care, significant associations have been identified between nurse–parent support and levels of anxiety and cyberchondria among families of children. Although there are no studies directly examining the relationship between these variables, both areas converge around parental anxiety, information-seeking behavior, and psychosocial support. Strong nurse–parent communication, along with accurate and consistent information, may reduce parental uncertainty and anxiety, thereby weakening the cycle of “repeated online reassurance seeking” that contributes to cyberchondria [31].

Current evidence indicates that cyberchondria, maternal fatigue, and nurse–parent support have largely been studied separately, and their individual associations with stress, anxiety, and caregiving burden are relatively well established [7, 32–34]. However, existing findings remain fragmented, as most studies have not examined how these variables interact within high-stress clinical contexts such as pediatric hospitalization. In particular, the relative associations of professional support and maternal fatigue with cyberchondria remain unclear. Although previous studies have demonstrated associations between cyberchondria, parental anxiety, caregiving burden, and fatigue, these relationships have generally been examined in isolation. Moreover, limited attention has been given to the potential role of professional healthcare support in shaping online health information–seeking behaviors among caregivers of hospitalized children. Consequently, it remains unclear whether nurse–parent support may act as a protective factor against cyberchondria in mothers experiencing caregiving-related fatigue. Addressing this gap is important for developing evidence-based family-centered nursing interventions aimed at reducing health anxiety and improving caregiver well-being during pediatric hospitalization. Accordingly, evidence examining the simultaneous relationships of maternal fatigue and perceived nurse–parent support with the separate dimensions of cyberchondria among mothers of hospitalized children remains limited. This represents a significant gap in the literature.

Therefore, the present study aimed to examine associations of maternal fatigue and perceived nurse–parent support with five dimensions of cyberchondria—compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals among mothers of hospitalized children aged 0–6 years using structural equation modeling, addressing the research question: What are the associations of maternal fatigue, perceived nurse–parent support and cyberchondria levels among mothers of hospitalized children aged 0–6 years?

Hypotheses of the study

Within this framework, the study hypotheses and the hypothesized model are presented below:

• H1. Higher fatigue severity is positively associated with each of the five dimensions of cyberchondria.

• H2. A greater impact of fatigue on daily life activities is positively associated with each of the five dimensions of cyberchondria.

• H3. Higher perceived nurse–parent support is negatively associated with each of the five dimensions of cyberchondria (Fig. 1).

Fig. 1.

Hypothesized model

Method

Study design, setting

This cross-sectional study was conducted between April and November 2025 in the pediatric wards of a Training and Research Hospital located in western Türkiye. The study was conducted according to EQUATOR guidelines and reported according to the STROBE checklist.

Guided by the study objectives and hypotheses, the present study addressed the following research question: “What are the effects of maternal fatigue and perceived nurse–parent support on cyberchondria levels among mothers of hospitalized children aged 0–6 years?” The methodological procedures and analytical strategy were designed to examine these relationships within a structural modeling framework.

Participants and sampling

The sample size was reconsidered in relation to the primary outcome variable, cyberchondria. However, since no prior studies have examined the relationships between maternal fatigue, nurse–parent support, and cyberchondria using structural equation modeling, an effect size specific to this model could not be directly derived from the literature.

Considering recommendations for structural equation modeling, such as the “10-times rule” and minimum sample size guidelines for PLS-SEM, the sample size of 216 was deemed sufficient to ensure model stability and reliable estimation [35, 36].

The adequacy of the sample size was not determined solely on the basis of the 10-times rule; it was also evaluated using an a priori statistical power analysis conducted with G*Power 3.1 [37, 38]. In the structural model, the maximum number of predictors directed toward any endogenous construct was three. Assuming three predictors, a medium effect size (f² = 0.15), a significance level of α = 0.05, and 80% statistical power, the minimum required sample size was calculated as 77. The total sample size of the present study (216) exceeded this minimum requirement. Therefore, the available sample was considered adequate for testing the principal relationships specified in the structural model. The 10-times rule was used only as a supplementary and approximate heuristic.

Initially, a total of 220 mothers were recruited. After excluding participants with incomplete responses (n = 4), data from 216 mothers were included in the final analysis.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (a) having a child aged 0–6 years (In this study, we focused on children aged 0–6 years due to their high dependency, greater vulnerability, and limited ability to express symptoms, which may increase caregiver uncertainty and health-related information-seeking behaviors), (b) voluntary participation in the study, (c) absence of communication difficulties, (d) maternal age ≥ 19 years, (e) the child’s hospitalization lasting at least 2–7 days, and (f) absence of congenital anomalies or acquired disabilities in the child.

The exclusion criteria included: (a) mothers whose children were transferred to another hospital during the data collection period, and (b) mothers with chronic diseases. These exclusions were applied to ensure valid assessment of fatigue levels measured by the scale and to minimize potential confounding effects. These criteria were defined to ensure a relatively homogeneous sample and to minimize potential confounding factors that could influence maternal fatigue and cyberchondria levels.

Data collection instruments

Parent and child demographic information form

This form, developed by the researchers, consists of 26 questions designed to gather information on the sociodemographic characteristics of the parents and children (Supplementary File 1).

Brief Fatigue Inventory (BFI)

The Brief Fatigue Inventory (BFI), originally developed by Mendoza et al. [39] and adapted for the Turkish population by Cinar et al. [40], demonstrated excellent internal consistency, with a Cronbach’s alpha coefficient of 0.98. The BFI assesses both fatigue severity—current, usual, and worst fatigue (items 1, 2, and 3)—and the impact of fatigue on daily life activities (items 4a, 4b, 4c, 4d, 4e, and 4f). The instrument consists of nine items, each rated on a scale ranging from 0 to 10.

Fatigue severity is calculated by dividing the sum of items 1–3 by three, while the impact of fatigue on daily activities is calculated by dividing the sum of items 4a–4f by six. Higher scores indicate greater fatigue severity and a stronger negative impact on daily functioning. In the present study, fatigue was evaluated based on the total BFI score. The Cronbach’s alpha coefficient was 0.918 for fatigue severity, 0.831 for the impact of fatigue on daily life activities, and 0.851 for the total Brief Fatigue Inventory.

Nurse Parent Support Tool (NPST)

The Nurse Parent Support Tool (NPST), originally developed by Miles et al. [41] and psychometrically validated for the Turkish population by Yiğit et al. [15], consists of 21 items rated on a five-point Likert scale. four sub-scales. “Information and Communication Support” (9 questions), “Emotional Support” (3 questions), “Respect Support” (4 questions), “Providing Quality Care” (5 questions) are the sub-scales. Total scores range from 21 to 105, with higher scores indicating greater perceived nurse-provided parental support. Response options are scored as follows: 1 = almost never, 2 = occasionally, 3 = sometimes, 4 = most of the time, and 5 = always. In the present study, the NPST demonstrated good internal consistency, with a Cronbach’s alpha coefficient of 0.87. This study, Cronbach’s alpha coefficient for the total Nurse–Parent Support Tool was 0.951.

Cyberchondria Severity Scale (CSS)

The Cyberchondria Severity Scale (CSS) is a psychometric instrument developed by McElroy and Shevlin [1] to assess cyberchondria, defined as a form of anxiety characterized by excessive online health-related searching. The Turkish validity and reliability study of the CSS was conducted by Uzun and Zencir [42]. The scale consists of 33 items rated on a five-point Likert scale (1 = never, 2 = rarely, 3 = occasionally, 4 = frequently, 5 = always). Turkish validity and reliability scale consists of 33 items and five factors (compulsion, distress, excessiveness, reassurance, mistrust of medical professional).

Items comprising the Mistrust of Medical Professionals subscale are reverse scored. Total cyberchondria scores are calculated by summing all item responses, with higher scores indicating greater cyberchondria severity. Possible total scores range from 33 to 165. The CSS demonstrated good internal consistency, with a Cronbach’s alpha coefficient of 0.89 in the Turkish validation study. This study, for the Cyberchondria Severity Scale, the coefficients were 0.922 for compulsion, 0.853 for distress, 0.896 for excessiveness, 0.798 for reassurance, and 0.835 for mistrust of medical professionals. The Cronbach’s alpha coefficient for the total Cyberchondria Severity Scale was 0.937.

Data collection procedure

Data were collected through face-to-face interviews with mothers of children hospitalized in the pediatric wards. Data collection took place in a quiet room within the pediatric ward to ensure privacy and minimize interruptions. Participants who met the inclusion criteria were informed about the study by the researchers, and those who provided written informed consent were included. The data collection process was coordinated by an experienced academic researcher, and all interviewers were provided with guidance on the study protocol, ethical principles, and standardized administration of the instruments. Interviews were conducted using standardized procedures and lasted approximately 15–20 min. During this process, participants completed the data collection instruments after receiving detailed information about the study purpose, procedures, confidentiality, and the voluntary nature of participation.

Data analysis

For descriptive and correlational analyses, cyberchondria was evaluated using both the total CSS score and its subdimension scores. In the path analysis, the five cyberchondria dimensions—compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals—were included as separate dependent variables. The total Nurse Parent Support Tool score, fatigue severity, and the impact of fatigue on daily life activities were included as independent variables.

Data analyses were conducted using IBM SPSS Statistics version 23, G*Power 3.1.9.7, and SmartPLS version 4 software. The distribution of continuous variables was examined using the Kolmogorov–Smirnov test. Relationships between non-normally distributed variables were assessed using Spearman’s rho correlation coefficient.

Spearman correlation analysis was conducted as a preliminary bivariate analysis and was not used to select variables or modify the prespecified path model. The CSS total score was used to describe overall cyberchondria severity and its unadjusted associations with fatigue and nurse–parent support, whereas the five CSS dimensions were examined separately as dependent variables in the path model to identify dimension-specific associations.

Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized direct effects in the proposed model. Maternal fatigue and perceived nurse–parent support were specified as exogenous (independent) variables, whereas cyberchondria severity was modeled as the endogenous (dependent) variable. PLS-SEM was preferred due to its suitability for hypothesis-driven models, its ability to handle non-normal data distributions, and its robustness with relatively complex models and moderate sample sizes [37]. In addition, PLS-SEM allows the simultaneous estimation of relationships among latent constructs and their indicators.

To examine the potential influence of confounding variables, subgroup (stratified) analyses were conducted based on maternal age, education level, child’s age, and caregiver change during hospitalization. The structural model was re-estimated across these subgroups to assess the stability and consistency of the model.

Structural model evaluation was based on path coefficients (β), explained variance (R²), and t and p values obtained through bootstrapping with 5,000 resamples. Measurement model reliability was assessed using Cronbach’s alpha and composite reliability, while convergent validity was evaluated via average variance extracted (AVE) values.

In study, all hypothesized path relationships were specified prior to data analysis based on the theoretical framework and research hypotheses. Therefore, the analyses were conducted as hypothesis-driven (confirmatory) rather than exploratory. Furthermore, the findings were evaluated not solely on the basis of p values but through the joint consideration of standardized path coefficients (β), effect sizes (f²), explained variance (R²), and bootstrap confidence intervals.

The statistical significance of the path coefficients in the structural model was assessed using the nonparametric bootstrapping procedure in SmartPLS 4. The analysis was conducted with 5,000 bootstrap subsamples, a two-tailed test, and a 5% significance level. During bootstrapping, the sign change option was set to “no sign changes,” and standard errors, t values, and p values were obtained for the standardized path coefficients. The significance of the path coefficients was evaluated using a threshold of p < 0.05. In addition, the practical relevance of the models was interpreted by considering f² effect sizes together with the path coefficients, R² values, and adjusted R² values. Differences in path coefficients between subgroups were statistically compared using the Permutation Test implemented in SmartPLS, and between-group differences were evaluated based on the corresponding p values.

Descriptive statistics for quantitative variables were reported as mean ± standard deviation and median (minimum–maximum). Statistical significance was set at p < 0.05.

Potential confounding variables were considered during both the study design and analytical phases. To reduce heterogeneity, eligibility criteria were defined to include only mothers of hospitalized children aged 0–6 years and to exclude mothers with chronic illnesses that could independently influence fatigue levels. In addition, several demographic and caregiving-related variables, including maternal age, educational level, child age, and caregiver change during hospitalization, were evaluated through stratified subgroup analyses. The structural model was re-estimated within these subgroups to assess the stability of path coefficients and determine whether the observed associations were consistent across different participant characteristics. The largely stable findings across subgroup analyses suggested that the relationships identified in the model were not substantially influenced by these potential confounding factors.

In this study, the total scores of the Fatigue severity and impact of fatigue on daily life activities dimensions of the BFI and the Nurse–Parent Support Scale were included in the model. This decision was based on the scoring approaches recommended by the developers of these instruments and on the primary aim of the study. The study sought to examine the overall effects of these constructs, as represented by individuals’ total scores, on the subdimensions of cyberchondria severity. Therefore, total scores were used rather than including the subdimensions of each scale as separate latent variables in the model. This approach preserved the theoretical integrity of the model while reducing unnecessary model complexity and the number of parameters to be estimated, thereby enabling the construction of a more parsimonious and interpretable structural model.

Results

The age distribution of participating mothers (N = 216) indicated that the largest proportion was in the 30–35 age group (38.4%). Regarding children’s age, children aged 1–3 years constituted the largest group (38.9%). Of the hospitalized children, 58.3% were male and 41.7% were female. Nearly half of the mothers were high school graduates (46.3%), 83.8% were housewives, and 39.8% had two living children.

Most children were admitted through the emergency department (91.2%). The most common reasons for hospitalization were respiratory system diseases (40.3%). Most mothers did not receive support for childcare during hospitalization (78.2%), while spouses and mothers were the main sources of support among those receiving assistance. Almost all mothers remained in the hospital throughout the entire day (97.7%). The demographic characteristics of the participants are presented in Table 1.

Table 1.

Sociodemographic and clinical characteristics of the participants (N = 216)

		N	%
Maternal age, years	18-23	21	9.7
	24-29	74	34.3
	30-35	83	38.4
	≥35	38	17.6
	Mean ± SD:
	Mean ± SD:
Child age	0–6 months	67	31.0
	7–11 months	44	20.4
	1–3 years	84	38.9
	4–6 years	21	9.7
	Mean ± SD:
Child Gender	Male	126	58.3
	Female	90	41.7
Maternal education	Literate	7	3.2
	Elementary school	51	23.6
	High school graduate	100	46.3
	University graduate	58	26.9
Maternal Employment Status	Employed	35	16.2
	Housewife	181	83.8
Number of living children	1	73	33.8
	2	86	39.8
	3	42	19.4
	≥ 4	15	6.9
Mode of admission	Emergency	197	91.2
	Planned hospitalization	2	0.9
	Polyclinic	17	7.9
The reason for the child’s admission to the hospital	Fever	54	25.0
	Respiratory system diseases	87	40.3
	Gastrointestinal diseases	68	31.5
	Skin and soft tissue infection	7	3.2
Child’s Presenting Symptomsa	Fever	138	63.9
	Diarrhea	30	13.9
	Nausea and vomiting	70	32.4
	Convulsion	4	1.9
	Respiratory distress	59	27.3
Mother’s status of getting support for the child’s care	Present	47	21.8
	Non-Present	169	78.2
The person being the source of support	Mother	22	10.2
	Sister	2	0.9
	Spouse	23	10.6
Time spent in hospital	Full day	211	97.7
	Only during the day	4	1.9
	Only at night	1	0.5
Primary source of information	Doctor	142	65.7
	Nurse-Midwife	67	31.0
	Internet	6	2.8
	Neighbors	1	0.5

^aMultiple symptoms were reported

The mean total score of the Brief Fatigue Inventory was 2.86 ± 1.07, the mean total score of the Nurse Parent Support Tool was 76.56 ± 20.37, and the mean total score of the Cyberchondria Severity Scale was 73.16 ± 23.31 (Table 2).

Table 2.

Descriptive statistics of the study variables

	Mean ± SD	Median (min: max)
Fatigue severity	3.32 ± 1.33	3.67 (0: 5)
Impact of fatigue on daily life activities	2.62 ± 1.21	2.67 (0: 5)
Brief Fatigue Inventory Total	2.86 ± 1.07	3 (0: 5)
Nurse Parent Support Tool Total	76.56 ± 20.37	78 (27: 105)
Compulsion	12.98 ± 6.61	9 (8: 38)
Distress	18.36 ± 6.65	18 (8: 36)
Excessiveness	21.28 ± 8.18	19 (8: 40)
Reassurance	13.69 ± 5.44	13 (6: 30)
Mistrust of medical professional	6.86 ± 3.61	6 (3: 15)
Cyberchondria Severity Scale Total	73.16 ± 23.31	68.5 (34: 141)

A statistically significant negative correlation was found between the total Brief Fatigue Inventory score and the Nurse–Parent Support Tool total score (r = − 0.189, p = 0.005). The impact of fatigue on daily life activities was also negatively correlated with nurse–parent support (r = − 0.226, p = 0.001). In addition, the total fatigue score (r = 0.161, p = 0.018) and the impact of fatigue on daily life activities (r = 0.156, p = 0.022) were positively correlated with the total Cyberchondria Severity Scale score. Fatigue severity was not significantly correlated with either nurse–parent support or total cyberchondria scores. The strongest correlation was observed between nurse–parent support and overall cyberchondria, indicating a moderate and statistically significant negative relationship (r = − 0.510, p < 0.001). (Table 3). The correlations presented in Table 3 represent unadjusted bivariate relationships; the subsequent path analysis tested the prespecified dimension-specific model and did not include the CSS total score as a dependent variable.

Table 3.

Correlations among fatigue, nurse–parent support, and cyberchondria total and dimension scores

		1	2	3	4	5	6	7	8	9
1 Fatigue severity
2 Impact of fatigue on daily life activities	r*	0.394
	p	< 0.001
3 BFI Total	r*	0.696	0.922
	p	< 0.001	< 0.001
4 NPST Tool Total	r*	-0.077	-0.226	-0.189
	p	0.260	0.001	0.005
5 Compulsion	r*	0.082	0.031	0.048	-0.200
	p	0.231	0.654	0.479	0.003
6 Distress	r*	0.150	0.104	0.131	-0.330	0.582
	p	0.027	0.126	0.055	< 0.001	< 0.001
7 Excessiveness	r*	0.120	0.155	0.161	-0.391	0.305	0.683
	p	0.079	0.023	0.018	< 0.001	< 0.001	< 0.001
8 Reassurance	r*	0.119	0.084	0.110	-0.451	0.418	0.600	0.751
	p	0.081	0.221	0.108	< 0.001	< 0.001	< 0.001	< 0.001
9 Mistrust of medical professional	r*	-0.100	0.087	0.014	-0.414	0.233	0.055	0.117	0.086
	p	0.142	0.202	0.834	< 0.001	0.001	0.425	0.085	0.210
10 CSS Total	r*	0.127	0.156	0.161	-0.510	0.626	0.844	0.867	0.825	0.294
	p	0.062	0.022	0.018	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001

^xSpearman’s rho correlation. Note. The CSS total score is calculated from the five dimension scores; therefore, correlations between the CSS total score and its dimensions represent part–whole correlations and were not interpreted as independent associations or used to specify the path model, p < 0.001

Path analysis

Path analysis was conducted to examine the effects of nurse–parent support and fatigue variables on cyberchondria subdimensions using the study dataset. Analyses were performed using IBM SPSS version 23 and SmartPLS version 4 software. In the model, the total score of the Nurse Parent Support Tool, fatigue severity, and the impact of fatigue on daily activities were specified as independent variables, while compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals were included as dependent variables.

Due to the non-normal distribution of the data, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the proposed model. Standardized beta (β) coefficients were used for parameter estimation. Multicollinearity was assessed using variance inflation factor (VIF) values, and all variables demonstrated VIF values within acceptable limits. The VIF values ranged between 1.05 and 1.25, indicating no multicollinearity concerns. These values are well below the commonly recommended threshold of 5, and also below the more conservative threshold of 3, suggesting that multicollinearity was not an issue in the model [35].

According to the path analysis results, higher perceived nurse–parent support was significantly associated with lower scores across all cyberchondria dimensions, including distress (β = −0.351, p < 0.001), excessiveness (β = −0.368, p < 0.001), mistrust of medical professionals (β = −0.382, p < 0.001), reassurance seeking (β = −0.436, p < 0.001), and compulsion (β = −0.335, p < 0.001).

Fatigue severity showed statistically significant effects only on mistrust of medical professionals (β = −0.186, p = 0.006) and reassurance seeking (β = 0.131, p = 0.044). In contrast, the impact of fatigue on daily activities was not a significant predictor of any cyberchondria subdimensions (p > 0.05). The explanatory power of the model was evaluated using R² values. The results indicated that maternal fatigue and nurse–parent support explained 14.7% of the variance in distress (R² = 0.147), 16.4% in excessiveness (R² = 0.164), 18.0% in mistrust of medical professionals (R² = 0.180), 20.6% in reassurance (R² = 0.206), and 11.9% in compulsion (R² = 0.119), indicating a low to moderate level of explanatory power (Table 4, Fig. 2).

Table 4.

Path analysis

	Original sample (O)	Standard deviation (STDEV)	T statistics (|O/STDEV|)	P values	VIF	f2	R2	Adjusted R2
Nurse Parent Support Tool -> Distress	-0.351	0.060	5.844	< 0.001	1.054	0.137	0.147	0.135
Fatigue severity -> Distress	0.134	0.074	1.799	0.072	1.194	0.018
Impact of fatigue on daily life activities -> Distress	0.000	0.073	0.003	0.998	1.253	0.000
Nurse Parent Support Tool -> Excessiveness	-0.368	0.064	5.787	< 0.001	1.054	0.154	0.164	0.152
Fatigue severity -> Excessiveness	0.084	0.073	1.157	0.247	1.194	0.007
Impact of fatigue on daily life activities -> Excessiveness	0.060	0.070	0.848	0.397	1.253	0.003
Nurse Parent Support Tool -> Mistrust of medical professional	-0.382	0.062	6.152	< 0.001	1.054	0.169	0.180	0.169
Fatigue severity -> Mistrust of medical professional	-0.186	0.068	2.754	0.006	1.194	0.035
Impact of fatigue on daily life activities -> Mistrust of medical professional	0.078	0.075	1.051	0.293	1.253	0.006
Nurse Parent Support Tool -> Reassurance	-0.436	0.059	7.384	< 0.001	1.054	0.227	0.206	0.195
Fatigue severity -> Reassurance	0.131	0.065	2.010	0.044	1.194	0.018
Impact of fatigue on daily life activities -> Reassurance	-0.032	0.070	0.451	0.652	1.253	0.001
Nurse Parent Support Tool -> Compulsion	-0.335	0.059	5.676	< 0.001	1.054	0.121	0.119	0.107
Fatigue severity -> Compulsion	0.035	0.070	0.497	0.619	1.194	0.001
Impact of fatigue on daily life activities -> Compulsion	0.022	0.069	0.325	0.745	1.253	0.000

β: Standardized beta coefficient, p < 0.001

Fig. 2.

Final model

When the effect sizes (f²) were examined, the Nurse Parent Support Tool was found to have the largest effect size across all dependent variables. Its effect sizes were moderate for reassurance (f² = 0.227), mistrust of medical professionals (f² = 0.169), and excessiveness (f² = 0.154), whereas they were small for distress (f² = 0.137) and compulsion (f² = 0.121). These findings indicate that nurse–parent support made a relatively stronger contribution to explaining the reassurance, mistrust of medical professionals, and excessiveness dimensions.

Accordingly, H1 was not supported, as fatigue severity was not positively associated with all five cyberchondria dimensions. H2 was not supported because the impact of fatigue on daily life activities was not significantly associated with any cyberchondria dimension. H3 was supported, as perceived nurse–parent support was significantly and negatively associated with all five cyberchondria dimensions.

The model was tested separately according to maternal age, educational level, child’s age, and caregiver change status. The structural path coefficients did not differ significantly across most subgroup comparisons.

Subgroup analyses yielded largely consistent findings across maternal education level, maternal age, child age, and caregiver change status. In all subgroup comparisons, nurse–parent support remained significantly and negatively associated with the cyberchondria dimensions, indicating that this association was consistent across different participant characteristics. In contrast, fatigue severity and the impact of fatigue on daily activities showed limited associations with cyberchondria, reaching statistical significance only in selected dimensions or specific subgroups. Overall, no meaningful differences were observed in the direction or magnitude of the main associations across subgroup analyses (Fig. 3).

Fig. 3.

Model evaluation by maternal age, education level, child age, and caregiver change

When the subgroup analyses were evaluated collectively, the Nurse Parent Support Tool showed the largest effect sizes across all groups. The strongest effects were observed for reassurance among mothers who were literate or primary school graduates (f² = 0.437; large effect) (Supplementary File 2) and for mistrust of medical professionals among mothers who experienced caregiver changes during hospitalization (f² = 0.401; large effect) (Supplementary File 3). According to maternal age, the largest effect was observed for excessiveness among mothers aged over 30 years (f² = 0.259) (Supplementary File 4). According to child age, the largest effect was observed for mistrust of medical professionals among mothers of children aged 1–6 years (f² = 0.303) (Supplementary File 5); both effects were moderate. Overall, the Nurse Parent Support Tool demonstrated relatively stronger and more consistent effect sizes, particularly for the reassurance and mistrust of medical professionals dimensions, whereas the effect sizes of fatigue-related variables were negligible or small in most subgroups.

When the explanatory power of the model was evaluated across subgroups, the R² values for the dependent variables ranged from 0.117 to 0.234 among mothers aged under 30 years, with the highest explanatory power observed for reassurance (R² = 0.234) (Supplementary File 4). Among mothers who were literate or primary school graduates, the R² values ranged from 0.223 to 0.336 (Supplementary File 2), and the model again demonstrated the highest explanatory power for reassurance (R² = 0.336). Among mothers of children aged 1–6 years, the R² values ranged from 0.136 to 0.346, with the highest explanatory power observed for mistrust of medical professionals (R² = 0.346) (Supplementary File 5). Among mothers who experienced caregiver changes during hospitalization, the R² values ranged from 0.103 to 0.344 (Supplementary File 3), with the highest explanatory power observed for compulsion (R² = 0.344). Overall, the model explained a low to moderate proportion of the variance in the dependent variables across the examined subgroups.

Measurement and structural model results (SmartPLS)

The reliability and validity of the measurement model were evaluated using rho_A, composite reliability (CR), average variance extracted (AVE), the Fornell–Larcker criterion, heterotrait–monotrait ratio (HTMT), Q²_predict, and model fit indices. Across all constructs, rho_A values ranged from 0.838 to 0.957, while composite reliability values ranged from 0.848 to 0.958, all exceeding the recommended threshold of 0.70. These findings indicated adequate internal consistency for all constructs. Regarding convergent validity, AVE values exceeded the recommended threshold of 0.50 for most constructs, ranging from 0.505 to 0.861. The only exception was the reassurance dimension, for which the AVE value was 0.491, slightly below the recommended threshold (Table 5). However, because the composite reliability value for this construct was 0.848, its convergent validity was considered acceptable in accordance with the recommendations of Fornell and Larcker.

Table 5.

Measurement model evaluation

Construct	rho_A	CR	AVE	Assessment
Fatigue severity	0.932	0.949	0.861	Acceptable
Impact of fatigue on daily life activities	0.900	0.871	0.535	Acceptable
Nurse Parent Support Tool	0.957	0.958	0.523	Acceptable
Compulsion	0.937	0.937	0.652	Acceptable
Distress	0.924	0.885	0.505	Acceptable
Excessiveness	0.949	0.915	0.576	Acceptable
Reassurance	0.838	0.848	0.491	Borderline AVE
Mistrust of medical professional	0.843	0.901	0.752	Acceptable

AVE ≥ 0.50 indicates convergent validity. The Reassurance Seeking construct showed AVE = 0.491; however, convergent validity was considered acceptable because CR exceeded 0.70

Discriminant validity was assessed using both the Fornell–Larcker criterion and HTMT ratios. In the Fornell–Larcker analysis, the square root of the AVE for each construct was greater than its correlations with the other constructs, indicating that discriminant validity was established. Similarly, all HTMT values were below the recommended threshold of 0.90, ranging from 0.076 to 0.846, further supporting adequate discriminant validity among the constructs (Supplementary File 6 and Supplementary File 7).

The predictive performance of the model was evaluated using Q²_predict values. Positive Q²_predict values for all dependent variables, ranging from 0.111 to 0.230, indicated that the model had predictive relevance. The RMSE and MAE values were also within acceptable ranges for all constructs, further supporting the predictive performance of the model (Table 6).

Table 6.

Predictive relevance

Construct	Q²predict	RMSE	MAE
Compulsion	0.111	0.952	0.720
Distress	0.152	0.925	0.768
Excessiveness	0.157	0.926	0.782
Reassurance	0.230	0.883	0.721
Mistrust of medical professional	0.157	0.924	0.741

Positive Q²predict values indicate predictive relevance

Model fit was evaluated using the SRMR and d_ULS indices. The SRMR values exceeded the recommended threshold (SRMR = 0.210 and 0.220) (Table 7). However, in PLS-SEM, model evaluation is not based solely on global fit indices; the reliability and validity of the measurement model, the explanatory power of the structural model, predictive performance, and the statistical significance of the path coefficients are considered collectively. Therefore, the model was evaluated by taking all of these criteria into account.

Table 7.

Model fit

Index	Saturated model	Estimated model
SRMR	0.210	0.220
d_ULS	7.533	8.298

The SRMR value should be interpreted considering the modelling strategy used

Discussion

The path analysis results demonstrated that perceived nurse–parent support was consistently and negatively associated with all cyberchondria dimensions, whereas the associations of maternal fatigue were limited and varied across dimensions. These findings supported Hypothesis 3, demonstrating that higher levels of perceived nurse–parent support were consistently associated with lower levels of cyberchondria, while Hypothesis 1 and Hypothesis 2 were not supported.

Notably, no prior studies have simultaneously examined maternal fatigue, perceived nurse–parent support, and cyberchondria using structural equation modeling or path analysis. Therefore, the present findings were interpreted within a theoretical framework and indirect empirical evidence rather than through direct comparisons. Existing literature has primarily emphasized the role of individual psychological factors, such as health anxiety and intolerance of uncertainty, in the development of cyberchondria [8, 12]. At the same time, studies conducted in pediatric settings have demonstrated that nurse–parent support reduces parental stress, anxiety, and uncertainty during child hospitalization [18, 21]. Taken together, these findings provide indirect support for the observed association between nurse–parent support and lower levels of cyberchondria and are broadly consistent with previous theoretical and empirical work highlighting the importance of caregiver support in contexts characterized by uncertainty and health-related concerns.

Importantly, when the relationships among variables are considered within the structural model, the findings suggest that contextual and relational factors may play a more dominant role than individual-level factors in shaping cyberchondria-related behaviors. From a clinical perspective, the consistently strong negative paths between nurse–parent support and all cyberchondria subdimensions indicate that the findings suggest that professional support may be an important factor to consider alongside individual vulnerabilities such as fatigue. In particular, timely, clear, and consistent communication provided by nurses may reduce caregivers’ uncertainty and limit excessive online health information seeking. Furthermore, the limited and dimension-specific associations of maternal fatigue with cyberchondria suggest that fatigue alone may not be strongly associated with cyberchondria in contexts where higher levels of nurse–parent support are perceived. Accordingly, interventions that prioritize structured communication, emotional reassurance, and trust-building may represent key strategies for reducing maladaptive health-related behaviors among caregivers.

In the present study, the mean total Cyberchondria Severity Scale score among mothers was 73.16 ± 23.31, indicating a moderate level of cyberchondria. This finding is consistent with previous studies conducted in diverse populations. In a study involving mothers and their children, cyberchondria levels were reported to be moderate [43]. Similarly, research conducted among mothers of children with and without food allergies found that Cyberchondria Severity Scale scores were at a moderate level in both groups [4]. Another study involving women of reproductive age (18–49 years) reported moderate cyberchondria levels and identified health anxiety as a significant factor contributing to increased cyberchondria severity. Furthermore, a significant relationship was found between maternal burnout and cyberchondria levels [7]. Moreover, studies including individuals with varying age ranges and sociodemographic characteristics have similarly documented predominantly moderate levels of cyberchondria [8, 12]. Given that cyberchondria reflects a form of negative affect, the absence of excessively high cyberchondria levels among mothers in the present sample may be considered a relatively favorable outcome. However, while the observed levels are broadly consistent with the literature, the moderate level of cyberchondria in the present sample may also reflect context-specific factors related to the hospital environment. Unlike community-based populations, mothers in this study were in direct and continuous contact with healthcare professionals, which may have limited excessive reliance on online health information. Although the study did not aim to test a direct hypothesis regarding the level of cyberchondria, the identification of moderate levels supports the assumption that cyberchondria is a relevant but not extreme phenomenon in this population, thereby allowing for the examination of how maternal fatigue and nurse–parent support contribute to its variability.

In the present study, the mean total Brief Fatigue Inventory score among mothers was 2.86 ± 1.07, indicating a moderate level of fatigue. Previous research has shown that fatigue is a common concern among mothers of hospitalized children; however, its severity may vary depending on caregiving conditions, availability of social support, and duration of hospital stay [13, 44]. Mothers of younger children who provide full-time bedside care are particularly vulnerable to increased fatigue due to fragmented sleep, heightened caregiving demands, and sustained vigilance [13, 44]. Given that the vast majority of mothers in the present study remained with their children on a full-day basis (97.7%), the observation of moderate fatigue levels is noteworthy. However, the limited influence of maternal fatigue on cyberchondria warrants careful consideration. Although fatigue is a common consequence of caregiving burden, it may primarily reflect the physical demands of caregiving rather than directly contribute to maladaptive health information–seeking behaviors. In contrast, cyberchondria is generally regarded as a cognitively and emotionally driven phenomenon, more strongly associated with factors such as health anxiety, intolerance of uncertainty, worry, and reassurance-seeking tendencies. Therefore, maternal fatigue may influence cyberchondria indirectly through its effects on psychological functioning rather than acting as an independent determinant, which may explain why fatigue demonstrated only limited and dimension-specific associations within the structural model.

Although the moderate fatigue levels observed are broadly consistent with the literature, they differ from studies reporting higher fatigue in comparable caregiving contexts. One explanation may be the relatively high level of nurse–parent support in the present sample. Consistent with this, Çınar et al. [34] demonstrated that increased nurse and social support significantly reduced fatigue among mothers of hospitalized children. Alternative explanations—including self-report bias, adaptive coping, and variability in hospitalization duration—should also be considered.

Regarding H1 and H2, although maternal fatigue was hypothesized to positively predict five dimensions of cyberchondria, the findings suggest it operates in a dimension-specific rather than uniform manner, underscoring the importance of both individual characteristics and contextual factors—particularly professional support—in interpreting this relationship. Interestingly, the negative association between fatigue severity and mistrust of medical professionals was unexpected. One possible context-specific explanation is that mothers experiencing greater fatigue may rely more strongly on healthcare professionals for information and decision support during hospitalization, which may coincide with lower reported mistrust.

In the present study, perceived nurse–parent support was found to be high (76.56 ± 20.37), indicating that mothers generally experienced strong support from nurses during their child’s hospitalization. This finding is consistent with previous studies demonstrating that nurse–parent support reduces parental fatigue, alleviates uncertainty, and facilitates adaptation to the caregiving process [21, 34]. For example, Bekmaz et al. [45] reported that higher perceived nurse support was associated with significantly lower maternal anxiety during hospitalization (r = − 0.22). Similarly, Loutfy et al. [46] found that nurse support, particularly when integrated with family-centered care, was associated with reduced parental stress, with family-centered care partially mediating this relationship. While these findings support the existing literature, the relatively high levels of perceived nurse–parent support observed in this study may also reflect context-specific factors, such as the organization of pediatric care services, staff–parent communication practices, and the implementation of family-centered care approaches in the study setting. It is also possible that mothers who remained continuously with their children developed stronger interactions with nurses over time, thereby increasing perceived support levels.

In relation to the study hypotheses, the high level of perceived nurse–parent support provides important context for interpreting the structural model results, particularly the consistent negative associations observed between nurse–parent support and all cyberchondria subdimensions (H3). These findings suggest that nurse–parent support may be associated not only with general psychosocial well-being, as reported in previous studies, but also with lower levels of maladaptive health-related information-seeking behaviors. One possible explanation is that mothers who perceive greater support from nurses experience less uncertainty and fewer unmet informational needs, reducing their reliance on online sources for reassurance. Accordingly, the present study extends the literature by identifying nurse–parent support as an important relational factor associated with lower cyberchondria levels, highlighting its relevance beyond traditional outcomes such as stress and anxiety.

When the model was tested across demographic variables, including maternal age, educational level, child’s age, and caregiver change status, the structural path coefficients remained largely stable. The literature reports mixed findings regarding the influence of demographic factors on cyberchondria, fatigue, and parental behaviors. Some studies have indicated that age, educational attainment, and perceived social support may affect parental health anxiety and cyberchondria levels, with higher vulnerability observed particularly among younger individuals, those with higher educational levels, and parents reporting lower perceived social support [8, 12]. In contrast, studies conducted specifically with maternal samples have suggested that the impact of demographic variables on cyberchondria levels may be limited [7]. In the present study, the relative stability of the model across demographic subgroups indicates that the effect of nurse–parent support on cyberchondria was consistently maintained. This finding indicates that the negative association between nurse–parent support and cyberchondria remained stable across diverse maternal subgroups, suggesting that this relationship is not limited to specific demographic characteristics. The absence of substantial subgroup differences may also indicate that the benefits of nurse–parent support are not dependent on demographic characteristics but rather on the quality and consistency of supportive interactions. This finding is particularly relevant for pediatric nursing practice because it suggests that supportive communication strategies may be broadly effective across diverse family profiles.

The relatively low to moderate explanatory power of the model (R² ranging from 11.9% to 20.6%) should also be considered when interpreting the findings. Although these values are acceptable for exploratory behavioral research and indicate meaningful associations, they suggest that cyberchondria is influenced by additional factors not included in the present model. Previous research has identified variables such as health anxiety, intolerance of uncertainty, digital health literacy, personality traits, and prior healthcare experiences as important determinants of cyberchondria. Therefore, the present findings should be interpreted as reflecting only part of a broader and multifactorial phenomenon.

Conclusion

In conclusion, this study demonstrated that perceived nurse–parent support was consistently associated with lower levels of cyberchondria among mothers of hospitalized children, whereas the effects of maternal fatigue were limited and varied across subdimensions. By examining maternal fatigue, nurse–parent support, and cyberchondria within a single structural model, this study contributes to the nursing literature by characterizing their concurrent relationships in the context of pediatric hospitalization. From a family-centered care perspective, the findings suggest that supportive nurse–parent interactions may represent an important factor associated with lower caregiver uncertainty and maladaptive health information-seeking behaviors. Clinically, these results underscore the importance of strengthening nurse–parent communication and support through structured information provision, individualized counseling, and emotional support. In addition, incorporating brief screening for fatigue and cyberchondria-related behaviors into routine care may facilitate the early identification of at-risk mothers and support targeted nursing interventions aimed at improving family adaptation during hospitalization.

Future research should address the limitations of the present study by employing longitudinal designs to better understand causal relationships, as the cross-sectional nature of this study limits causal inference. In addition, multi-center studies including more diverse caregiver populations are needed to improve the generalizability of the findings beyond a single hospital setting and mothers only. Furthermore, integrating potential confounding variables directly into structural models may provide a more comprehensive understanding of the relationships among the variables. Finally, intervention-based studies evaluating the effectiveness of nurse-led strategies in reducing cyberchondria are recommended.

Limitations and strengths of the study

This study has several limitations that should be considered when interpreting the findings. First, the cross-sectional design limits causal inferences; therefore, the observed associations between maternal fatigue, nurse–parent support, and cyberchondria should be interpreted as correlational rather than causal. Second, the use of self-report measures may have introduced reporting bias, potentially affecting the accuracy of fatigue and cyberchondria assessments. Third, the study was conducted in a single hospital setting and included only mothers, which may limit the generalizability of the findings to other settings and caregiver groups.

Importantly, these limitations may have influenced the magnitude and variability of the observed relationships. For instance, contextual factors specific to the hospital environment and the relatively homogeneous sample may have contributed to the stability of the association between nurse–parent support and cyberchondria. Therefore, the findings should be interpreted within these contextual boundaries, and future studies using longitudinal and multi-center designs are recommended to validate and extend these results.

One of the key strengths of this study is that it is among the first to simultaneously examine maternal fatigue, nurse–parent support, and cyberchondria within a single analytical model—variables that have been rarely addressed together in the existing literature. In particular, evaluating these constructs using structural equation modeling (path analysis) adds methodological rigor and originality to the study. Furthermore, testing the model across multiple demographic variables and observing largely consistent structural path coefficients supports the robustness of the model and strengthens confidence in the stability of the findings.

Implications for nursing practice

The findings of this study suggest that nurse–parent support may be relevant to addressing cyberchondria-related behaviors in pediatric care. Structured nurse-led communication strategies, including regular information updates, individualized counseling, and emotional support, may be incorporated into family-centered care practices.

In addition, assessing maternal fatigue and cyberchondria-related behaviors may help identify mothers who may benefit from additional support. Educational approaches focusing on reliable health information sources and digital health literacy may also support more balanced online health information–seeking behaviors among caregivers.

Authors’ contributions

Zeliha Yılmaz: Conceptualization, data curation, writing, reviewing, and editing. Özge Karakaya Suzan: Data curation, analysis, writing, reviewing, and editing. Selin Tan: Conceptualization, analysis, supervision, reviewing, and editing. Ayşe Çetintaş: Data curation, supervision, reviewing, and editing. All authors critically reviewed and approved the final version of the manuscript submitted for publication.

Funding

This study was funded by the TUBITAK 2209-A University Student Research Projects Support Program. Türkiye Bilimsel ve Teknolojik Araştırma Kurumu.

Data availability

Data or information needed to re-produce the findings presented are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Prior to the study, ethical approval was obtained from the Ethics Committee on Sakarya University (Decision No: E-61923333-050.99-478135). Participants were informed that the data collected would be used solely for scientific purposes and that they could withdraw at any time. Written informed consent was obtained from all parents who voluntarily agreed to participate by signing the informed consent form. The study was conducted in accordance with scientific publication ethics and the principles of the Declaration of Helsinki.

Consent for publication

None.

Competing interests

The authors declare no competing interests.