Predictors of Dental Fear and Anxiety in 9-12-year-old Children in Bosnia and Herzegovina

Abstract

Objectives

Oral health in children is additionally burdened with the presence of dental fear and anxiety (DFA). These clinical psychologic entities in their progressive stages inevitably lead to avoidance of dental appointments, which makes prevention and therapy of oral diseases more difficult. Upon the onset of DFA in general, as one of the emotional outcomes of stress in a dental office, most children patients could define the specific stressors that were most intense for them, which could predict the presence of DFA.

Aim

To examine the predictors of DFA presence in 9-12-year-old children, and investigate how they could explain the DFA occurrence in study participants.

Material and Methods

The sample consisted of 200 children aged from 9 to 12 years. The DFA presence was determined by the modified version of the CFSS-DS scale. The child's behavior in the dental office during the treatment was evaluated by the trained observer using Venham anxiety and behavior rating scales. Socioeconomic status, characteristics of dental office visits, and previous caries experience were also analyzed.

Results

The main DFA predictors were related to invasive dental treatments, where the behavior during dental treatment was the most accurate expression of the DFA appearance.

Conclusions

Invasive dental procedures are the main stressful factor for DFA occurrence. Predisposing factors could strengthen the DFA occurrence.

Introduction

Dental fear and anxiety (DFA) are commonly seen in the general population, especially among children and adolescents. These clinical psychological entities inevitably lead to the avoidance of dental appointments. The presence of DFA is reported in 23.9% of children and adolescents (1-3). The aforementioned cannot be neglected in the context of prevention and therapy of oral diseases. This problem is becoming more complex in children's age questioning the possibilities of modern dentistry to meet its goals. A significant number of child patients are avoiding dental appointments due to DFA until it is too late for preventive treatments, and oral health is consequently impaired (2, 4).

In the beginning of DFA in general, as one of the emotional outcomes of stress in a dental office, most child patients could define the specific stressors that were most intense for them. There were thus two groups of factors for the DFA emergence depending on whether they had a direct or indirect contribution to its onset and development (2, 4). The first ones are the direct factors, related to the situations, content, and course of dental treatment, the dental team, and the dental office itself. The strength of these factors was directly dependent on their invasiveness. The second group is composed of indirect, predisposing (dispositional) factors, that were unrelated to the dentist, dental team, or the office, and with great certainty, it was assumed that they could indirectly contribute to the onset, development, and even deepening of DFA presence (4-8).

There is more than one way to measure the presence of DFA in child patients. The scales of self-reported DFA were most commonly used, due to their simplicity (2, 9). Recently, a modified version of the CFSS-DS scale (CFSS-DS-mod scale) for children aged 9-12 has been introduced to clinical practice. This psychometric instrument showed significant normative values in this age group within the population of child patients (10).

Study objective

This study aimed to determine the predictors of the DFA presence in 9-12-year-old children and how they could explain the DFA occurrence in study participants. Accordingly, the hypothesis of the study was that direct factors have the strongest contribution to the DFA appearance in our study participants.

Materials and methods

Ethical considerations and sample collection

The study was approved by the Ethics Committee of the Faculty of Dentistry with Clinics of the University of Sarajevo and following the Declaration of Helsinki (11). The survey was conducted in a form of prospective, cross-sectional study research.

Study participants were randomly selected patients aged from 9 to 12 years, who visited the Clinic / Department of Pediatric and Preventive Dentistry of the Faculty of Dentistry with Clinics of the University of Sarajevo due to a previously defined dental treatment plan. This specific age of children was selected due to their cognitive, emotional, and psychosocial development, and coping skills (2, 4).

All study participants had prior knowledge and awareness of why they had visited the dental office in the first place, and that all previously established treatment plan actions and interventions related to this study were performed in the same spatial conditions. Exclusion criteria were dental emergencies (odontalgia, oro-mucosal and orofacial swellings of dental and/or other origins, oro-mucosal and orofacial bleedings, dentoalveolar and/or orofacial traumas), and psychological, and/or psychiatric conditions as well. A confirmation of the existence of these conditions as exclusion criteria should be given by trained psychology and psychiatry specialists if needed, according to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (12). Nevertheless, there was not any situation during the study research period where these DSM-5 exclusion criteria should have been implemented.

Prior to survey commencement, the study purpose and content were explained in detail to the child participants and their parents. Parents were asked to fill out and sign informed consent for the participation on behalf of themselves and their minor children as well. Also, children were additionally required to give their consent to participate in the study.

To meet the research objectives, the sample consisted of a group of 200 children of both sexes, according to the sample size calculation, with a 95% interval of confidence. Sample size calculation was accomplished according to the study of Pourhoseingholi et al for cross-sectional studies, observing the phenomena of DFA in children and adolescents (estimated prevalence of 23.9%; 95% CI 20.4 to 27.3), with an effect size of 0.84 (13-15).

Study design – direct factors for DFA appearance

The study group was composed of child patients who visited the dental office primarily due to the need for some further dental interventions: regular dental check-ups, preventive dental treatment (dental fluoridation and/or fissure sealing), treatment of a carious dentine lesion of medium depth on a permanent tooth, and/or permanent tooth extractions.

The selection and division of dental procedures, based on their invasiveness, were made because invasive dental procedures were considered the most provoking factors of DFA. Therefore, the procedures were further divided into non-invasive (examination, fluoridation, or sealing) and invasive (drilling or extraction) ones.

The child patients independently answered the questions from the CFSS-DS-mod scale before the scheduled treatment started (10). This psychometric instrument has 17 questions with answers rated on a Likert scale from 1 to 5. The total scale score ranged from 17 to 85, with a cut-off score of 37, which included also a population of latent DFA presence. The scale showed good normative values in an examined population, and this validated version was used in this study research (10).

The evaluation of children's behavior during dental treatment, as the potential expression of DFA presence, was performed by the Venham anxiety and behavior rating scales (Venham scale) (16). This instrument was used in such a way to notify the most negative behaviors during dental treatment. The total score on the Venham scale was 10, and the cut-off score which defined positive versus negative behaviors was 5. Higher scores indicated more negative behaviors in the dental office (16).

Study design – dispositional factors for DFA appearance

During the survey, parents of child participants provided information about the socioeconomic status (SES) of their family, the average number, frequency, and reasons for previous dental visits, as well as about the total number of different dentists previously visited by their children (17, 18). Previous dental caries experience of the child participants was determined by their DMFT index prior to commencement of dental treatment. DMFT index is well known as an indicator of hard dental tissue health status, where the existence of filled and/or missing teeth could be indirectly related to negative experiences in the dental office which could lead to the appearance of DFA in children (19).

Statistical analysis of study results

The data collected in this survey were statistically analyzed and presented as follows:

• − the total number and number of participants within groups were shown descriptively in the tables corresponding to children’s age, average age, and sex;

• − the distribution of obtained results was determined using the Kolmogorov-Smirnov test;

• − the results obtained for the socioeconomic status and dental attendance characteristics were presented in percentages;

• − the existence of statistically significant differences was determined using the nonparametric Kruskal-Wallis test, Mann-Whitney test, and/or Wilcoxon signed-rank test, depending on whether the samples were independent or related ones;

• − the existence of statistically significant correlations between the characteristics of the visit to the dental office was determined by Spearman's correlation coefficient;

• − Identification of the determinants of DFA presence was performed by binary logistic regression analysis.

A significance level of p≤0.05 was set for most statistical analyses, except for logistic regression analysis, where the level was p≤0.25 (20). The analyses were conducted with the SPSS IBM Statistics v. 23 software for the Windows operating system.

Results

Descriptive values of the study sample

The age and the sex distribution of child patients are shown in Table 1.

Table1. Descriptive characteristics of study sample participants.

Table 1 . Descriptive characteristics of study sample participants
study sample
age	9 years		10 years		11 years		12 years		total:
	n (%)		n (%)		n (%)		n (%)		N=200
	49 (24.5)		46 (23.0)		55 (27.5)		50 (25.0)		M=10.53; SD=1.12
sex	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)
	23 (11.5)	26 (13)	27 (13.5)	19 (9.5)	28 (14.0)	27 (13.5)	20 (10.0)	30 (15.0)	98 (49.0)	102 (51.0)
non-invasive treatments
age	9 years		10 years		11 years		12 years		total:
	n (%)		n (%)		n (%)		n (%)		N=100
	21 (21.0)		24 (24.0)		28 (28.0)		27 (27.0)		M=10.61; SD=1.10
sex	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)
	10	11	15	9	17	11	7	20	49	51
	(10.0)	(11.0)	(15.0)	(9.0)	(17.0)	(11.0)	(7.0)	(20.0)	(49.0)	(51.0)
invasive treatments
age	9 years		10 years		11 years		12 years		total:
	n (%)		n (%)		n (%)		n (%)		N=100
	28 (28.0)		22 (22.0)		27 (27.0)		23 (23.0)		M=10.45; SD=1.13
sex	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)	m (%)	f (%)
	13	15	12	10	11	16	13	10	49	51
	(13.0)	(15.0)	(12.0)	(10.0)	(11.0)	(16.0)	(13.0)	(10.0)	(49.0)	(51.0)

n-number of study participants in age group; m-males; f-females; N-total number of study (sub)sample participants; M-mean age of study participants; SD-standard deviation

Direct factors for DFA appearance

The descriptive values of the average DFA scores by CFSS-DS-mod scale are shown in Table 2. Invasive treatment subgroup obtained statistically significantly higher scale scores compared to non-invasive ones in general (Mann-Whitney test, U = 2972.0, p˂0.0005), and also within 10-year-olds (Wilcoxon signed rank test, Z = -2.307, p = 0.021), 11-year-olds (Z = -4.289, p˂0.0005), boys (Z = -3.506, p˂0.0005) and girls (Z = - 3.818, p˂0.0005). Further analysis showed statistically significant age differences within non-invasive treatment subgroup (Kruskal-Wallis test, χ2 = 12.318, p = 0.006), between 12-year-olds (higher scores) and 9-year-olds (U = 157.00, p = 0.008), and between 12-year-olds (higher scores) and 11-year-olds (U = 176.50, p = 0.001).

Table 2. Descriptive values of average scores obtained in the CFSS-DS-mod scale in study participants concerning treatment invasiveness, age, and sex.

Table 2 Descriptive values of average scores obtained in the CFSS-DS-mod scale in study participants concerning treatment invasiveness, age, and sex
treatment subgroups		N	range	minimum	maximum	M	SD
non-invasive treatments		100	36.00	17.00	53.00	24.98	7.44
invasive treatments		100	63.00	17.00	80.00	31.25	10.91
non-invasive treatments	9 years	21	28.00	17.00	45.00	23.57	6.51
	10 years	24	30.00	17.00	47.00	25.38	8.69
	11 years	28	19.00	17.00	36.00	22.14	4.48
	12 years	27	35.00	18.00	53.00	28.67	8.12
	boys	49	36.00	17.00	53.00	25.39	8.82
	girls	51	25.00	17.00	42.00	24.59	5.87
invasive treatments	9 years	28	40.00	17.00	57.00	28.04	9.37
	10 years	22	37.00	17.00	54.00	30.41	9.11
	11 years	27	59.00	21.00	80.00	33.67	13.17
	12 years	23	35.00	17.00	52.00	33.13	10.89
	boys	49	38.00	17.00	55.00	30.16	9.28
	girls	51	63.00	17.00	80.00	32.29	12.27

N-total number of study (sub)sample and age and gender groups of participants; M-mean CFSS-DS-mod scale score; SD-standard deviation

Scores for the behavior of child patients, determined with the Venham scale, are shown in Table 3.

Table 3. Descriptive values of average scores obtained in the Venham scale in study participants concerning treatment invasiveness, age, and sex.

Table 3 Descriptive values of average scores obtained in the Venham scale in study participants concerning treatment invasiveness, age, and sex
treatment subgroups	N	range	minimum	maximum	M	SD	Wilcoxon test
non-invasive treatments	100	6.00	0.00	6.00	1.5200	1.41049	Z=-8.348
invasive treatments	100	10.00	0.00	10.00	3.9300	2.06586	p≤0.0005
9 years-non-invasive	21	6.00	0.00	6.00	1.5714	1.56753	Z=-2.661
9 years-invasive	28	8.00	0.00	8.00	3.8214	2.05577	p=0.008
10 years-non-invasive	24	5.00	0.00	5.00	1.5000	1.47442	Z=-3.237
10 years-invasive	22	8.00	1.00	9.00	3.9091	2.50541	p=0.001
11 years-non-invasive	28	5.00	0.00	5.00	1.5714	1.19965	Z=-3.426
11 years-invasive	27	9.00	1.00	10.00	4.0000	2.25320	p=0.001
12 years-non invasive	27	4.00	0.00	4.00	1.4444	1.50214	Z=-3.849
12 years-invasive	23	5.00	2.00	7.00	4.0000	1.41421	p≤0.0005
boys-non invasive	49	5.00	0.00	5.00	1.6939	1.37241	Z=-4.916
boys-invasive	49	9.00	0.00	9.00	3.8367	1.98271	p≤0.0005
girls-non-invasive	51	6.00	0.00	6.00	1.3529	1.43977	Z=-4.880
girls-invasive	51	9.00	1.00	10.00	4.0196	2.15861	p≤0.0005

N-total number of study (sub)sample and age and gender groups of participants; M-mean Venham scale score; SD-standard deviation; Z-Z value; p-p value

Statistical analyses (Wilcoxon signed-rank test) showed significant differences between invasive and non-invasive dental procedures according to age and sex of child participants presented with higher scores and more negative dental behavior in invasive treatment subgroup of child patients (Table 3).

Dispositional factors for DFA appearance

Considering the SES, most of the study group participants had married parents (N = 187, 93.5%), and the mothers and fathers of the children had completed high school education (N = 89, 44.5%; N = 84, 42.0%, respectively). The mothers of the study participants were mostly unemployed (N = 93, 46.5%), while their fathers mostly had full-time jobs (N = 145, 72.5%). Household incomes per family member mostly ranged between 150 and 250 Euros (N = 54, 27.0%), and in the total sample, they were below the average level of monthly consumption for the mentioned survey period. Most parents of the study participants thought that dental care was completely available to them (N = 150, 75.0%).

Study group respondents mostly visited dentists between 11 and 30 times (56.5%) in total, with most often visiting the dentist office once in the first three months (81.0%), due to cavity preparation (62.5%). Most participants (54.0%) had previously been to two different dentists. The average caries experience (DMFT) of sample subjects was 8.0. Analyzes showed that the children with a less average number of dental visits showed more negative behaviors in the dental office (Spearman's correlation coefficient, ρ = −0.239, p = 0.001). Also, the children had worse caries experience in cases where their parents considered dental care as less important (ρ = 0.145, p = 0.040), and when the reasons for dental visits were more invasive treatments (ρ = 0.209, p = 0.003).

Predictors of DFA presence

Since the potential predictors of DFA presence were mostly categorical variables (Table 4), binary logistic regression analysis was performed (Table 5). Regression model was good (χ2 = 18.795, p=0.005), with the Hosmer and Lemesh test value χ2 = 4.391 (p = 0.820).

Table 4. Central tendency measures potential predictors for DFA occurrence.

Table 4 Central tendency measures potential predictors for DFA occurrence
predictors	Median	Percentiles
		25	50	75
CFSS-DS-mod scale	1.00	1.00	1.00	1.00
age	3.00	2.00	3.00	3.75
sex	2.00	1.00	2.00	2.00
number of dental visits	3.00	2.00	3.00	4.00
frequency of dental visits	2.00	2.00	2.00	3.00
reasons for dental visits	2.00	2.00	2.00	2.00
number of dentists so far	2.00	2.00	2.00	2.75

Table 5. Variables in the equation of binary logistic regression model.

Table 5 Variables in the equation of binary logistic regression model
	predictors	B	Wald	df	Sig.	Exp (B)	95.0% CI for EXP(B)
							lower bound	upper bound
	age	0.744	4.949	1	0.026	2.103	1.092	4.050
	sex	0.090	0.027	1	0.869	1.094	0.375	3.194
	number of visits	-0.730	6.514	1	0.011	0.482	0.275	0.844
	frequency of visits	-0.329	2.470	1	0.116	0.720	0.478	1.085
	reasons for visits	0.868	7.709	1	0.005	2.381	1.291	4.393
	number of dentists	0.154	0.223	1	0.637	1.167	0.615	2.215

B – B values; S.E. - Wald – Wald test; df – degree of freedom; Sig. – p value; Exp (B) – odds ratio (OR); CI – confidence interval

p value is set to 0.25 (19)

The significant predictors of DFA presence were: the reasons for dental visits, where more uncomfortable reasons brought 2.381 times more chances to develop DFA (Exp /B/ = 2.381, 95% CI = 1.291–4.393; p=0.005); the patient’s age in a way that older children had 2.103 times more chances to develop DFA (Exp /B/ = 2.103, 95% CI = 1.092–4.050; p=0.026); the frequency of dental visits, where rarely visiting brought 0.720 times more chances to develop DFA (Exp /B/ = 0.720, 95% CI = 0.478–1.085; p=0.116); and the number of dental visits, where the higher total number of visiting brought 0.482 times more chances to develop DFA (Exp /B/ = 0.482, 95% CI = 0.275–0.844; p=0.011).

Discussion

The study results confirmed our hypothesis that invasive treatments were among the major direct factors as strongest for DFA onset, through the Rachman mechanism of the development of DFA appearance, by proposing direct experience among three possible ways of DFA development through his conditioning theory of fear acquisition. In brief, classical conditioning is one of the mechanisms through which DFA can develop following previous negative dental encounters. When confronted with a stressful dental stimulus (cavity preparation, tooth extraction, for example), a person (child) could develop a reflexive psychological defensive reaction to it in a form of DFA appearance (21, 22). The reason for the DFA appearance is the fact that these direct invasive stimuli threaten to disturb the integrity of the organism itself. DFA presence in children is most directly expressed through various forms of behavior in the dental office, and negative behaviors in a form of dental behavior problems (DBP) are directly correlated with invasive dental procedures. If this pathway mostly in the child period could not be interrupted by applying the behavior and pain management control techniques in the dental office, DFA could strengthen through time and further develop in a form of odontophobia (2, 4).

Several studies reported that DFA prevalence is decreasing over time. The main reasons for this occurrence were related to the cognitive development from the child to adolescent period, where successful coping mechanisms to possible previously stressful dental stimuli were developed. Hence, a successful coping in the dental office with not expressing the DBP in now older adolescents was followed by the consequent decrease of DFA prevalence over time (2, 4). Nevertheless, our study results partially showed the opposite findings, where some older children had more chance of DFA presence. The reason for this could be the fact that possible oral health problems and invasive treatment factors in this period of life could be the reason for the DFA onset (23). Accordingly, an increase in the prevalence of DFA presence in adolescents has also been reported earlier, where it was stated that changing of psychological states during significant life transitions could be also the reason for the DFA appearance (23).

So far, several previous studies have investigated possible effects of SES components on DFA occurrence, where SES was considered a dispositional factor that possibly exacerbated DFA in children (24-26). These associations and differences in the DFA presence were not confirmed in our study. Moreover, our findings were confirmed by some more recent studies, where SES components do not have such an impact on the DFA onset as before (27-29). The reasons for this concordance could be various, including different methodologies and assessing tools, but it seems that the prevalence of DFA appearance does not vary significantly anymore to great extent between the children from different socioeconomic family groups to predict DFA appearance (27-29).

Furthermore, the non-visiting of dental offices is a global problem of modern dentistry in the context of mechanisms for avoiding stressors within them. The formation and development of a vicious circle, associated with previously experienced or assumed stressful situations within the dental office, lead to the onset of DFA, DBP, and avoidance of dental visits from an early age. This has been confirmed in our study, and also was the focus of research by others (30-33). This is the core problem of already impaired oral health in childhood, where the parents have to take more responsibilities and play more important roles, not only in managing better oral health in their children (proper oral hygiene, anti-cariogenic diet, fluoride usage) but also in cooperation for conducting of better cooperative behaviors of their children in the dental office. Thus, the avoidance of visiting the dental office would be significantly decreased over time (34, 35).

Predictors of the DFA presence in pediatric subjects were determined and analyzed in several previous studies, where direct and dispositional factors for the DFA appearance were mostly combined, such as invasive dental stimuli that could cause pain during dental treatment, age and sex of child participants, presence of DFA in parents, uncooperative behavior in the dental office (7, 30, 36-38). In our study, the most prominent were more stressful reasons for visiting the dental office and the children’s age, as well as the frequency and number of dental visits to smaller extent.

Finally, according to the hypothesis of the study and the results of conducted analyses that were discussed, the hypothesis itself was accepted, in a way that direct factors had the strongest contribution to the DFA appearance in our study participants.

Past medical experiences represent a major part in the possible acquisition of medical fear and anxiety, in a similar way as dental experiences could cause DFA. Medically compromised child patients are usually dental patients as well, and mostly with the need for extensive invasive dental treatments (39, 40). When medical fear and anxiety are once established in a child patient, there is great certainty for the DFA to develop. The reasons are obvious and related to the similar content of medical and dental offices (content, smells, noises, stuff) and/or invasiveness of procedures. Also, DFA could be consequently intensified especially in medically compromised patients, and the time to correct the presence of DBP in children could be much longer (41, 42).

It is also well known that the parents are role models for their children. Their dental behaviors and attitudes (about oral health maintenance, attendance to the dental office, etc.) play a major role in the transfer of habits from generation to generation. If the parents develop the presence of DFA over time, there is great certainty that their children consequently could behave in the same way (43, 44).

These two important dispositional factors for the DFA appearance in children (in a form of past medical experiences in children and the presence of DFA in their parents) were not considered in the study, although they could widen the perspective and understanding of the prediction of DFA appearance. Our reasons were to avoid possible biases in study research, with a research proposal for their consideration in further research on predictors of DFA appearance in children.

Along with the strengths of our study which were presented by explaining and confirming the most significant determinants and predictors of the DFA appearance in children regarding the direct and dispositional dental stimuli, the limitations of the present study could be correlated with the fact that other previously mentioned related conditions important for DFA appearance in children were not considered.

Conclusions

The most powerful predictors of dental fear and anxiety presence were invasive dental treatments. Behavior during dental treatment is clinically the most accurate expression of the DFA presence in child patients.

Indirect factors for the onset of dental fear and anxiety could contribute to its strengthening through the creation of a vicious circle that could lead to avoiding dental office visits.