Parental dental anxiety and children’s dental anxiety: a multicenter cross-sectional study

2.1 Sample size

The sample size for the study was initially estimated using G*Power 3.1.9.7 software (Heinrich Heine University Düsseldorf, Düsseldorf, NRW, Germany) based on an independent-samples t-test. The minimum required sample size was calculated as 226 participants using an effect size of 0.46, α = 0.05, and power of 95% (1 − β = 0.95) [12, 13]. However, since the primary outcome of the study was dichotomous (presence of dental anxiety defined as ACDAS ≥26), an additional sensitivity check was performed using a two-proportion approach. This analysis indicated that the minimum required sample size was approximately 290–300 participants, depending on the expected effect size and the distribution of exposure groups. The final study sample consisted of 296 child–parent pairs, which was considered adequate for the planned statistical analyses.

2.2 Participants

This multicenter study was conducted at three pediatric dentistry departments located in Eskisehir, Nevsehir, and Malatya, Turkey. Children aged 7–14 years and their accompanying parents were recruited consecutively from these centers. All clinics followed the same standardized data collection protocol and used the same validated scale (ACDAS) to ensure methodological consistency.

2.3 Survey content

The survey consisted of four sections:

1. First section: Questions aimed at understanding the participants, including the following:

○ Age of the child and parent,

○ Parental education level,

○ Family socioeconomic status,

○ Number of children and the birth order of the child visiting the clinic,

○ Parents’ recollection of past dental experiences and the emotions associated with them.

2. Second section:

○ Parents completed the questionnaire developed by Corah for adults, which has been validated and deemed reliable in Turkish [14].

3. Third section:

○ Child’s dental examination: Dental caries experience was assessed using the dmft index (decayed, missing, and filled primary teeth). The dmft scores were recorded during the clinical dental examination performed by pediatric dentists during the children’s scheduled treatment visits.

4. Fourth section:

○ The Turkish-validated version of Abeer’s Dental Anxiety Scale for Children (ACDAS), specifically its dental and cognitive sections,

○ Questions assessing whether the parent has shared past dental experiences with the child [15, 16].

2.4 The Abeer children’s dental anxiety scale (ACDAS)

The ACDAS is a 19-item scale comprising three sections: dental, cognitive, and child evaluation sections.

In the present study, children’s dental anxiety was defined using the ACDAS dental section (items 1–13), with scores ranging from 13 to 39 and a cut-off value of ≥26 indicating dental anxiety. The cognitive items (items 14–16) and the child evaluation items (items 17–19) were not included in the calculation of the outcome score. Therefore, when analyzed, these items were treated as separate explanatory variables rather than components of the outcome measure.

● Dental section (13 questions): Children were asked to select the facial expression that best represented how they felt in each situation.

● Scoring: Responses were rated on a 1–3 scale, with total scores ranging from 13 to 39.

● A score of 26 or higher indicated the presence of dental anxiety.

● Child evaluation section (items 17–19): These items were completed by the child’s parent/guardian and the dentist and were used to assess behavioral expectations and observed behavior during the dental visit [15, 16].

2.5 Corah’s dental anxiety scale (CDAS)

Parental dental anxiety was assessed using Corah’s Dental Anxiety Scale (CDAS). The CDAS is a four-item, five-point Likert-type scale designed to measure an individual’s anxiety level regarding dental procedures. CDAS scores were entered into the logistic regression model as a categorical variable with four levels.

● Scoring:

○ Minimum score: 4, Maximum score: 20,

○ Higher scores indicate higher levels of anxiety.

● Anxiety classification:

○ Low anxiety (4–11 points),

▪ 4–7 points: No anxiety,

▪ 8–11 points: Very low anxiety;

○ High anxiety (12–20 points),

▪ 12–14 points: Anxiety,

▪ 15–16 points: Very anxious,

▪ ≥17 points: Extremely anxious [15].

In general, studies classify individuals with a total score of ≥12 as anxious and those with a score of ≥15 as highly anxious [15].

In this study, parental anxiety was classified as follows:

● 4–7 points: No anxiety,

● 8–11 points: Low anxiety,

● 12–14 points: Moderate anxiety,

● ≥15 points: High anxiety.

2.6 Statistical analysis

Data were analyzed using SPSS (version 28.0; IBM Corp., Armonk, NY, USA). Categorical variables were summarized as numbers (n) and percentages (%), and differences between groups were assessed using the chi-square (χ²) test. The normality of continuous variables was tested via the Kolmogorov-Smirnov test. Numerical data were presented as the mean ± standard deviation and median (minimum–maximum). The relationship between dental anxiety and age was analyzed using the Mann-Whitney U test. Differences in parental anxiety scores between children with and without DFA were tested via the Kruskal-Wallis test. The point-biserial correlation was used to measure the strength of the linear relationship between these two variables. The relationships between dental anxiety and sex were analyzed using the chi-square test and Fisher’s exact test. To identify factors influencing dental anxiety, logistic regression analysis was performed, and odds ratios (ORs) with 95% confidence intervals (CIs) were reported. A p-value < 0.05 was considered to indicate statistical significance.

Binary logistic regression analysis was performed to identify independent predictors of children’s dental anxiety (ACDAS ≥26). Variables considered clinically relevant or associated with dental anxiety in previous studies were included in the model. The Enter method was used for variable entry. Multicollinearity among the independent variables was assessed using the variance inflation factor (VIF) values. Model fit was evaluated using the Hosmer-Lemeshow goodness-of-fit test, and the explanatory power of the model was assessed using Nagelkerke’s pseudo-R². Odds ratios (OR) with 95% confidence intervals (CI) were calculated.

4.1 Role of parents in children’s DFA

Understanding factors associated with children’s dental anxiety is important for improving clinical management. Previous psychological research indicates that children may be exposed to fear-related responses through observational learning and parental communication [19]. Within this framework, parents may represent contextual factors associated with children’s dental anxiety. Parental attitudes and behaviors toward oral health may therefore be associated with children’s dental anxiety [19]. These findings may be interpreted within the context of observational learning and emotional contagion frameworks, suggesting that children may be exposed to parental fear-related behaviors in the dental context through verbal cues, behavioral modeling, and anticipatory communication before dental visits.

Our findings demonstrated that both parental DFA (p = 0.014) and parental discussion of past negative dental experiences (p = 0.003) were significantly associated with children’s DFA. The present findings are consistent with several previous studies reporting associations between parental and child dental anxiety [3, 8, 10, 20, 21]. However, Wu et al. [1] reported no direct relationship between parental and child DFA, suggesting that intermediary factors—such as family dynamics, parental coping style, and communication patterns—may play a role in shaping this relationship. Overall, parental dental anxiety may represent one of several contextual factors associated with children’s dental anxiety, although its influence may vary depending on family dynamics and communication patterns. Although the association between parental and child dental anxiety was statistically significant, the correlation was relatively small (r = 0.168), indicating a weak association and a modest effect size.

Despite evidence of parental influence, there is no consensus regarding whether mothers or fathers exert a stronger impact on children’s DFA. Some studies have suggested that fathers act as mediators in transmitting DFA-related information [1, 20], whereas others have reported maternal DFA behaviors to be more influential [20]. Still, several studies have identified both maternal and paternal DFA as significant contributors to child DFA [11], while others have found no notable difference between them [1, 22]. In our study, only the parent accompanying the child to the clinic was evaluated, and children accompanied by their mothers exhibited significantly greater DFA than those accompanied by their fathers (p = 0.048). This finding might be explained by the larger proportion of mothers in the sample or by differences in parental roles within Turkish family structures.

4.2 Age, socioeconomic status, and DFA

The literature presents inconsistent findings regarding the effect of age on dental anxiety. Some studies report that DFA decreases with age [10, 23], whereas Boka et al. [24] found no such relationship. Similarly, Lima et al. [25] indicated that children aged 7–9 years experience higher DFA. The present study included children aged 7–14 years, however, no significant association was found between age and DFA. These differences may be due to variations in age grouping, measurement instruments, or cultural context.

The influence of socioeconomic status (SES) on DFA also varies among studies. Yıldırım [9] reported that low SES was associated with increased dental anxiety, whereas Uzel et al. [8] found no such relationship. Muneer et al. [26] reported higher DFA among individuals with low SES. In this study, no significant association was observed between SES and either parental or child DFA. Similarly, maternal education and marital status did not remain significant predictors in the multivariate logistic regression model. This may reflect the availability of free and accessible dental healthcare services in Türkiye, which may minimize financial barriers to treatment and thus may neutralize SES effects.

4.3 Birth order and DFA

Recent research has investigated the association between birth order and DFA. Ghaderi et al. [27] found that only children were more anxious and less cooperative, whereas middle-born children demonstrated better cooperation. Uziel et al. [21] reported that firstborns had an increased risk of DFA. However, in this study, neither the number of siblings (p = 0.86) nor birth order (p = 0.57) showed a significant association with DFA, consistent with findings from Felemban et al. [28]. Some studies, however, have observed that children with siblings exhibiting DFA were more likely to display similar anxiety levels [1, 28]. Wu et al. [1] further suggested that family structure and sibling presence, rather than parental DFA alone, may influence the development of children’s DFA. These findings underscore the importance of considering the broader family environment in understanding children’s anxiety responses.

4.4 Relationship between divorced parents and DFA

In the present study, children of divorced parents exhibited significantly higher DFA levels than those from intact families (p = 0.04). This result is consistent with several prior studies [28, 29], although some studies have reported conflicting findings. These findings may reflect potential psychosocial factors associated with family structure, although the underlying mechanisms remain unclear. Conversely, in certain cases, children from single-parent families may develop greater independence and resilience, which could mitigate fear responses [1]. Hence, the influence of parental divorce on DFA should be interpreted with attention to individual coping mechanisms, family cohesion, and available social support systems.

Taken together, the findings across demographic, familial, and behavioral domains highlight the multifactorial nature of children’s dental anxiety. These findings emphasize the importance of considering family context when assessing and managing dental anxiety in pediatric patients. From a clinical perspective, the findings suggest that parental dental anxiety appears to be one of several factors associated with children’s dental anxiety, even when cognitive and behavioral factors are taken into account. The present study also has several strengths. First, the multicenter design enhances the generalizability of the findings by including participants from different geographic regions. Second, validated instruments (ACDAS and CDAS) were used to assess dental anxiety in both children and parents. Third, the study simultaneously evaluated multiple family-related factors that may influence children’s dental anxiety.

This study has several limitations that should be considered when interpreting the findings. First, due to the cross-sectional design, causal relationships between parental dental anxiety and children’s dental anxiety cannot be established. The observed associations reflect correlations at a single time point rather than directional effects. Another methodological consideration relates to the use of selected ACDAS items in the analysis; however, only the dental section of the scale was used to define the outcome variable in order to minimize conceptual overlap. Nevertheless, cross-sectional studies remain valuable for identifying clinically relevant risk indicators and generating hypotheses for future longitudinal research. Understanding the association between parental and child dental anxiety is particularly important for pediatric dental practice, as it may guide early preventive strategies and parent-focused interventions. Future research should explore longitudinal designs to better understand the temporal relationship between parental and child dental anxiety.