Abstract
Background
Child dental anxiety is a prevalent issue in the field of pediatric dentistry. At present, several non-pharmacological interventions are employed to mitigate anxiety during dental treatments for children. The objective of this study is to assess the effectiveness of diverse non-pharmacological interventions in reducing dental anxiety, as well as enhancing heart rate during pediatric dental treatments. To achieve this, we conducted a systematic review and a network meta-analysis (NMA) to compare the efficacy of various outcome indicators.
Methods
A thorough search was conducted in the databases of PubMed, Embase, Web of Science, Cochrane Library, Scopus, APA PsycInfo, CINAHL, and AMED to identify all eligible randomized controlled trials (RCTs) from the beginning of the databases up to August 1, 2024. The quality assessment was carried out using the Cochrane Collaboration’s bias risk tool. The two outcome measures under consideration were dental anxiety and heart rate. Network graphs, league tables and SUCRA were constructed using R 4.2.3 software and Stata 16 software. This study is registered in PROSPERO under the registration number CRD42023467610.
Results
The study examined 12 different non-pharmacological approaches, drawing from a pool of 61 research studies involving 6,113 participants aged 4 to 16 years. The results of the network meta-analysis revealed that music (SUCRAs: 93.60%) proved to be the most effective measure in mitigating dental anxiety, followed by aromatherapy (SUCRAs: 78.58%) and game (SUCRAs: 70.99%). Moreover, hypnosis (SUCRAs: 98.80%), music (SUCRAs: 79.58%), and relaxation (SUCRAs: 72.41%) were identified as the top three interventions for decreasing heart rate.
Conclusion
In this NMA, when contemplating dental anxiety outcomes, music is recommended as a priority. For heart rate outcomes, hypnosis may be a preferred measure. However, owing to the limited number of articles, the conclusion of this study still requires additional confirmation or correction through more high-quality primary studies in the future.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12903-024-04919-x.
Keywords: Child, Dentistry, Dental anxiety, Non-pharmacological interventions, Network meta-analysis
Background
Dental anxiety (DA) is characterized by a mental state of fear coupled with a sense of loss of control experienced during dental treatment [1]. Pediatric dental anxiety is a global concern in clinical practice, impacting 13.3–36.5% of children or adolescents across different countries [2]. This anxiety has adverse effects on children’s physiological, mental, and social well-being. Children with dental anxiety often manifest crying, hysteria, resistance, or avoidance behaviors during diagnosis and treatment, and in some cases, it may lead to the abandonment of treatment plans [3]. Missing the opportunity for dental caries treatment in children can exacerbate the condition, resulting in pain, difficulty eating, sleep disturbances, frequent absenteeism, and, in severe cases, impacting nutrition intake and quality of life [4]. This not only places a mental burden on parents but also presents significant challenges and obstacles in pediatric clinical work [3, 5]. Consequently, identifying effective intervention plans to alleviate pediatric dental anxiety holds great importance in promoting pediatric oral health.
In recent years, scholars worldwide have been actively exploring and developing various intervention methods to mitigate pediatric dental anxiety and enhance cooperation. The American Academy of Pediatric Dentistry (AAPD) collectively terms this series of interventions as behavior management techniques (BMT) [6]. The latest guidelines [7] classify BMT into two types: basic behavior guidance and advanced behavior guidance. Basic behavior guidance encompasses communication guidance, positive pre-visit imagery, direct observation, tell-show-do, ask-tell-ask, voice control, non-verbal communication, positive reinforcement and descriptive praise, as well as distraction and desensitization. On the other hand, advanced behavior guidance includes protective stabilization, sedation, and general anesthesia. Drug interventions, such as the inhalation of nitrous oxide, intravenous injections, and oral sedatives, may entail potential unnecessary side effects and risks, such as nausea, vomiting, dizziness, headache, or permanent nerve injury [8, 9]. Therefore, non-pharmacological interventions find more favor among parents of children [10].
In contemporary pediatric dental clinical practice, a variety of non-drug interventions are employed, encompassing pre-visit preparation, communication skills, tell-show-do (TSD), cognitive behavior therapy (CBT), distraction, hypnosis, relaxation, modelling, and more. Numerous systematic reviews have substantiated that these diverse non-pharmacological interventions exhibit varying degrees of effectiveness in mitigating dental anxiety during pediatric dental diagnosis and treatment [11–15]. Hypnosis, recognized as an effective mental intervention, has demonstrated success in reducing anxiety, fear, and pain in pediatric patients. It is capable of modifying behaviors, enhancing cooperation levels, and even overcoming excessive vomiting reflex [16, 17]. Relaxation training involves guiding children through breathing exercises before dental treatment, contributing to the slowing of heart rate, regulation of breathing, and overall relaxation of the body. This, in turn, aids in alleviating anxiety and reducing pain [18]. Distraction, a straightforward, passive, and non-invasive behavioral management technique, encompasses various applications such as music, audiovisual distraction, virtual reality, robots, magic and more. It primarily utilizes audiovisual stimuli generated by aids to divert children’s attention from dental treatment, resulting in reduced pain perception, improved comfort, lowered heart rate, and ultimately achieving the goal of anxiety reduction [19–23]. Studies by Dixit et al. [24] revealed that engaging children in various shaped color puzzle games during the alginate upper impression process can reduce their nausea and vomiting reflex, significantly enhancing the success rate of the impression. In a cross-randomized clinical trial [25], the use of lavender aromatherapy in a dental setting was found to significantly reduce salivary cortisol levels and pulse rate in children, leading to a diminished perception of pain during local anesthesia injection and a decrease in dental anxiety.
Traditional meta-analysis typically assesses the effects of direct comparisons between two non-pharmacological interventions. However, in real-world scenarios, there is often a need to understand the overall effects among multiple intervention measures. Network meta-analysis (NMA) is a valuable tool to address these challenges, enabling the simultaneous comparison of multiple intervention measures using both direct and indirect evidence [26]. Given the absence of comprehensive comparisons regarding the effects of various non-pharmacological interventions in pediatric dental treatment, this network meta-analysis uniquely combines multiple non-pharmacological interventions for the first time. Its aim is to evaluate the effectiveness of all intervention measures, rank them, and provide recommendations for the best non-pharmacological interventions.
Methods
Registration
This network meta-analysis adhered to the Preferred Reporting Items for PRISMA for Network Meta-Analyses (PRISMA-NMA), including their specifications for NMA [27]. The protocol for this study was registered in PROSPERO, an international prospective systematic review database, with the registration number CRD42023467610.
Literature search strategy
We conducted a systematic search for English-language articles in PubMed, Embase, Web of Science, Cochrane Library, Scopus, APA PsycInfo, CINAHL, and AMED. The search encompassed articles from the inception of each database to August 1, 2024. Our search strategy entailed the combination of subject terms with free-text terms. The medical subject terms utilized comprised: child, pediatrics, adolescent, dental health services, dentistry, and anxiety. The specific search strategy is outlined in Appendix 1. Additionally, a secondary search was conducted by manually examining references in published systematic reviews and searching ClinicalTrials.gov for references related to both published and unpublished randomized controlled trials, including ongoing trials. This secondary search was undertaken to enhance the comprehensiveness of the literature search process.
Inclusion and exclusion criteria
The literature that meets the following criteria will be included in this study: (1) Study objects: Children requiring dental treatment. (2) Measures of intervention: Non-pharmacological interventions, such as aromatherapy, audiovisual distraction, enhanced preoperative information (EPI), game, magic, hypnosis, modelling, music, relaxation, robot, and virtual reality, were combined for use. The control group did not undergo any interventions, and the children in this group received only routine dental care without any specific anxiety-reducing measures. (3) Study type: Randomized controlled trials. (4) Outcome indicator: Dental anxiety assessed using the variable self-reported scales and heart rate.
Articles with the following conditions were excluded: (1) Animal or cell experiments, case reports, scientific experimental plans, reviews, letters, editorials, conference papers, etc.; (2) Literature with missing study data or serious errors; (3) Duplicate publications; (4) Full text not found.
Data extraction
Endnote X9.1 literature management software was utilized to organize the records from the literature search. Two researchers independently screened the literature titles and abstracts based on the inclusion and exclusion criteria. Subsequently, a second screening involved reading the full text. Any disagreements in the review process were resolved through discussion or consultation with a third researcher, as needed. For data extraction, two researchers utilized Excel 2016 to independently gather information from the finally included literature. Details such as the first author, publication year, country of origin, intervention and control measures, basic participant information, sample size, outcome indicators, dental anxiety scales, randomization, and additional specifics were included in the information. To maintain consistency, all non-pharmacological interventions and the control group used in the included literature were classified or standardized in this study (see Appendix 2). Two independent reviewers separately defined and categorized the non-pharmacological interventions and the control group in the study, classifying the interventions from the literature. In cases of differing opinions, the study members collectively discussed and resolved them with the assistance of a third reviewer.
Quality assessment
The assessment of included studies was conducted using the Cochrane Bias Risk Assessment Tool (RoB2.0) [28] in five aspects: bias in randomization, bias from defined interventions, bias in missing outcome data, bias in outcome measurement, and bias in selective reporting of results. For each study, two researchers independently assessed the quality of the study, making judgments of “low risk”,“high risk”, and “possible risk” from the above five aspects. Disagreements in the review process, if any, were resolved by discussion or consultation with a third researcher (if necessary). The assessment results were presented as bias risk graph.
Statistical analysis
This study focuses on two main outcome indicators: dental anxiety and heart rate. The effect sizes represent the differences from the baseline (pre-intervention) to the endpoint (post-intervention). The heart rate was quantified as weighted mean differences (MD) with 95% confidence intervals (CIs). In the study, the effect size measure for the continuous outcome was presented using weighted standard mean differences (SMD) with 95% CIs, in accordance with the Cochrane Handbook guideline [29], due to the utilization of various anxiety scales and measurement units for dental anxiety. The SMD was calculated as the difference between the means of two sets of data divided by the standard deviation of the two sets of data, thereby removing the influence of measurement units. Consequently, the transformed data could be amalgamated for further data analysis. In view of the heterogeneity between trials, the Bayesian hierarchical random-effects model was first fitted for multiple comparisons of different treatment options [30, 31]. On the one hand, all the calculations and graphs were obtained using the R 4.2.3 software and Stata 16 software. Based on the theory of likelihood function and some prior assumptions, Markov chain Monte Carlo (MCMC) simulation was performed using Bayesian inference with R 4.2.3 software, 500,000 in iterations and 20,000 in annealing were set, to investigate the posterior distributions of the interrogated nodes [32–34]. The node splitting method was used to evaluate local inconsistencies for outcomes with closed loops. The relationships among the different treatments were presented as a network graph; meanwhile, a comparison-adjusted funnel plot was utilized to test for potential publication bias [35, 36]. Moreover, we adopted surface under the cumulative ranking probabilities (SUCRA) values to rank the examined treatments, and the SUCRA values ranged from 0 to 1. A higher SUCRA value corresponds to a higher ranking compared with other treatments [37, 38]. A league table was generated to present the comparisons between each pair of interventions within each outcome.
Results
Literature search and screening process
Initially, 7,458 articles were retrieved, of which 4,267 articles were subsequently excluded. Upon reviewing the titles and abstracts, an additional 3,012 articles were excluded, and six articles were further excluded due to unavailability of their full texts. The remaining articles underwent a rigorous full-text screening process, strictly adhering to the inclusion and exclusion criteria. Ultimately, 61 pieces of literature were included. The detailed screening process is depicted in Fig. 1.
Fig. 1.
PRISMA flowchart for study selection
Basic characteristics of the included studies
The 61 studies [22, 24, 25, 39–96] included in the analysis were conducted in 15 different countries. India had the highest number of studies, with 34, followed by 4 each from Iran and Turkey, 3 each from Brazil and Saudi Arabia, and 2 each from China, Egypt, and the United Arab Emirates. The remaining studies took place in Sweden, New Zealand, Iraq, Thailand, Pakistan, Korea, and the United Kingdom, each contributing one study. In total, these studies involved 6,113 children, aged between 4 and 16 years old.
There are a total of 9 dental anxiety scales: Modified Child Dental Anxiety Scale(MCDAS), Dental Subscale of the Children’s Fear Survey Schedule(CFSS-DS), the Facial Image scale (FIS), Venhams picture test(VPT), RMS pictorial scale, PJS–Pictorial Scale(PJS-PS), Chotta Bheem-Chutki scale (CBCS), Visual Analogue Scale (VAS), Visual Facial Anxiety Scale (VFAS). The basic characteristic of the included studies are illustrated in Table 1.
Table 1.
Baseline characteristics
| First author(year) | Country | Intervention | Sample(n) | Male(n) | Female(n) | Age(Mean ± SD), y | Outcomes | Dental anxiety scales | Randomization |
|---|---|---|---|---|---|---|---|---|---|
| Shehani(2024) | India | Music | 126 | NA | NA | 7–12 | Dental anxiety/Heart rate | Visual Facial Anxiety Scale (VFAS) | the computer-generated random sequence |
| EPI | 126 | NA | NA | ||||||
| Nikitha(2024) | India | Game | 60 | 25 | 35 | 7.09 ± 1.68 | Dental anxiety | the modified dental anxiety scale (MDAS) | random |
| EPI | 30 | 13 | 17 | ||||||
| Karmarkar(2024) | India | Relaxation | 30 | NA | NA | 8.96 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | the lottery method |
| Control | 15 | NA | NA | ||||||
| Hamdy(2024) | Egypt | EPI | 15 | 7 | 8 | 4–6 | Heart rate | the lottery method | |
| Virtual reality | 15 | 6 | 9 | ||||||
| Game | 15 | 8 | 7 | ||||||
| Bakhaider(2024) | Saudi Arabia | EPI | 20 | NA | NA | 6–12 | Heart rate | random | |
| Virtual reality | 20 | NA | NA | ||||||
| Anchala(2024) | India | Audiovisual distraction | 22 | 10 | 12 | 6.21 ± 1.80 | Dental anxiety/Heart rate | RMS pictorial scale | the computer-generated random sequence |
| Virtual reality | 22 | 10 | 12 | 6.89 ± 1.72 | |||||
| Game | 22 | 10 | 12 | 6.56 ± 1.88 | |||||
| Yucel(2023) | Turkey | EPI | 259 | 120 | 139 | 6–14 | Dental anxiety | Dental Anxiety Scale (DAS) | simple randomisation |
| Control | 252 | 118 | 134 | ||||||
| Yendodu(2023) | India | Relaxation | 35 | 18 | 17 | 8.90 ± 1.40 | Heart rate | random | |
| EPI | 35 | 14 | 21 | 8.90 ± 1.60 | |||||
| Sadeghi (2023) | Iran | Audiovisual distraction | 30 | 13 | 17 | 6.06 ± 1.17 | Heart rate | the random sequence | |
| Music | 30 | 14 | 16 | 5.86 ± 1.07 | |||||
| Pathak(2023) | India | Virtual reality | 15 | 9 | 6 | 9.67 ± 1.80 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | simple randomization |
| Control | 15 | 6 | 9 | 9.87 ± 1.81 | |||||
| Mayer(2023) | Brazil | EPI | 92 | 46 | 46 | 14.60 ± 2.50 | Dental anxiety | VisualAnalogue Scale (VAS) | the random sequence |
| Control | 92 | 46 | 46 | 14.30 ± 2.60 | |||||
| Maru(2023) | India | Game | 78 | 38 | 40 | 5.47 ± 1.12 | Heart rate | ||
| Control | 78 | 19 | 59 | 5.78 ± 4.63 | |||||
| Lekhwani(2023) | India | EPI | 60 | NA | NA | 4–8 | Dental anxiety/Heart rate | the facial image scale (FIS) | the random sequence |
| Game | 90 | NA | NA | ||||||
| Kothari (2023) | India | Magic | 15 | NA | NA | 4–6 | Dental anxiety | Venham’s Picture Test (VPT) | the randomizer software |
| EPI | 15 | NA | NA | ||||||
| Kasimoglu (2023) | Turkey | Robot | 50 | 24 | 26 | 6.71 ± 1.43 | Dental anxiety/Heart rate | the facial image scale (FIS) | the random sequence |
| Control | 52 | 26 | 26 | block randomization | |||||
| Janthasila(2023) | Thailand | Music | 33 | 13 | 20 | 11.00 ± 0.83 | Dental anxiety/Heart rate | the modified child fear survey schedule dental subscale (CFSS-DS) | block randomization |
| Aromatherapy | 31 | 16 | 15 | 10.94 ± 0.89 | |||||
| Control | 32 | 19 | 13 | 11.00 ± 0.88 | |||||
| Bhusari(2023) | India | Control | 15 | NA | NA | 8.60 ± 2.59 | Dental anxiety | Venham’s Picture Test (VPT) | the lottery method |
| Music | 30 | NA | NA | 9.14 ± 2.10 | |||||
| Bagher(2023) | Saudi Arabia | Virtual reality | 18 | 9 | 9 | 9.10 ± 2.60 | Heart rate |
the random sequence block randomization |
|
| Audiovisual distraction | 18 | 9 | 9 | 10.10 ± 2.80 | |||||
| Aziz(2023) | Iraq | EPI | 44 | 24 | 20 | 6–8 | Heart rate | the computer-generated random sequence | |
| Control | 22 | 12 | 10 | ||||||
| Umamaheswari(2022) | India | EPI | 30 | 12 | 18 | 7.90 ± 0.40 | Dental anxiety/Heart rate | the facial image scale (FIS) | random |
| Virtual reality | 30 | 19 | 11 | 7.90 ± 0.60 | |||||
| Shekhar(2022) | India | Virtual reality | 41 | 23 | 18 | 10.24 ± 1.65 | Dental anxiety/Heart rate | the modified dental anxiety scale (MDAS) |
the random sequence block randomization |
| EPI | 41 | 20 | 21 | 9.87 ± 1.72 | |||||
| Panchal(2022) | India | Audiovisual distraction | 40 | 20 | 20 | 4–7 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | block randomization |
| EPI | 40 | 20 | 20 | ||||||
| Padminee(2022) | India | Relaxation | 35 | 18 | 17 | 8.86 ± 1.76 | Heart rate | the computer-generated random sequence | |
| Virtual reality | 35 | 19 | 16 | 8.06 ± 1.23 | |||||
| Linthoingambi(2022) | India | Game | 36 | 19 | 17 | 8.33 ± 2.46 | Dental anxiety | Chotta Bheem-Chutki scale (CBCS) | the lottery method |
| Audiovisual distraction | 36 | 20 | 16 | 8.47 ± 2.19 | |||||
| Du(2022) | China | Virtual reality | 60 | NA | NA | 6.30 ± 3.50 | Dental anxiety | the modified child fear survey schedule dental subscale (CFSS-DS) | flipping of a coin |
| EPI | 64 | NA | NA | ||||||
| Sabherwal(2021) | India | Hypnosis | 20 | 13 | 7 | 10.60 | Dental anxiety/Heart rate | Visual Facial Anxiety Scale (VFAS) | the computer-generated random sequence |
| Relaxation | 20 | 11 | 9 | 9.05 | |||||
| EPI | 20 | 12 | 8 | 9.60 | |||||
| Nirmala(2021) | India | Aromatherapy | 120 | NA | NA | 9.56 ± 1.54 | Dental anxiety/Heart rate | the modified dental anxiety scale (MDAS) | block randomization |
| Control | 30 | NA | NA | ||||||
| Kumari(2021) | India | Game | 100 | 51 | 49 | 8.55 ± 1.898 | Dental anxiety | the modified dental anxiety scale (MDAS) | the lottery method |
| Virtual reality | 100 | 50 | 50 | 8.66 ± 1.843 | |||||
| Kaur(2021) | India | EPI | 8 | 5 | 3 | 6–12 | Dental anxiety | PJS–Pictorial Scale (PJS-PS) | the computer-generated random sequence |
| Virtual reality | 8 | 7 | 1 | ||||||
| Audiovisual distraction | 8 | 6 | 2 | ||||||
| Felemban(2021) | Saudi Arabia | Virtual reality | 25 | 14 | 11 | 6–12 | Heart rate | the computer-generated random sequence | |
| Audiovisual distraction | 25 | 15 | 10 | ||||||
| CustÓdio(2021) | Brazil | Virtual reality | 22 | 12 | 10 | 7.73 ± 1.03 | Heart rate | the lottery method | |
| EPI | 22 | 12 | 10 | 7.60 ± 0.91 | |||||
| Abbasi(2021) | Pakistan | EPI | 120 | 57 | 63 | 7.49 ± 2.28 | Dental anxiety/Heart rate | the facial imagescale (FIS) | the lottery method |
| Control | 40 | 22 | 18 | 7.27 ± 1.68 | |||||
| Dixit(2020) | India | Game | 24 | 11 | 13 | 77.9 ± 19.5(months) | Dental anxiety | the facial images cale (FIS) | block randomization |
| Control | 24 | 16 | 8 | 69.2 ± 14.1(months) | |||||
| Zhu(2020) | China | Modelling | 396 | 221 | 175 | 7–8 | Heart rate |
the random sequence block randomization |
|
| EPI | 391 | 226 | 165 | ||||||
| Song(2020) | Korea | Modelling | 24 | 15 | 9 | 5.66 ± 0.92 | Heart rate | the randomizer software | |
| Control | 20 | 10 | 10 | 5.63 ± 1.25 | block randomization | ||||
| Pande(2020) | India | EPI | 15 | NA | NA | 5–8 | Dental anxiety/Heart rate | the facial imagescale (FIS) | the randomizer software |
| Audiovisual distraction | 15 | NA | NA | ||||||
| Virtual reality | 15 | NA | NA | ||||||
| Game | 15 | NA | NA | ||||||
| Obadiah(2020) | India | EPI | 30 | NA | NA | 8.43 ± 1.54 | Dental anxiety | the facial images cale (FIS) | block randomization |
| Relaxation | 30 | NA | NA | ||||||
| Konde(2020) | India | Control | 40 | NA | NA | 7–13 | Dental anxiety | the facial images cale (FIS) | random |
| Magic | 40 | NA | NA | ||||||
| Game | 40 | NA | NA | ||||||
| Kasimoglu(2020) | Turkey | Robot | 100 | 51 | 49 | 6.18 ± 1.69 | Dental anxiety/Heart rate | the facial images cale (FIS) | random |
| EPI | 100 | 51 | 49 | 5.92 ± 1.62 | |||||
| Ghaderi(2020) | Iran | Control | 12 | 7 | 5 | 7.83 ± 0.83 | Heart rate | block randomization | |
| Aromatherapy | 12 | 6 | 6 | 8.00 ± 0.85 | |||||
| Buldur(2020) | Turkey | Virtual reality | 38 | 19 | 19 | 9.07 ± 1.42 | Dental anxiety/Heart rate | the facial images cale (FIS) | the randomizer software |
| Control | 38 | 20 | 18 | 8.97 ± 1.38 | block randomization | ||||
| Sridhar(2019) | India | Relaxation | 33 | NA | NA | 8.57 ± 1.07 | Dental anxiety/Heart rate | the facial images cale (FIS) | block randomization |
| Control | 33 | NA | NA | ||||||
| Shetty(2019) | India | Virtual reality | 60 | NA | NA | 5–8 | Dental anxiety | the modified dental anxiety scale (MDAS) | random |
| EPI | 60 | NA | NA | ||||||
| Nunna(2019) | India | Virtual reality | 23 | 7 | 16 | 8.91 ± 1.44 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | the random sequence |
| Control | 23 | 16 | 7 | 8.80 ± 1.39 | |||||
| Koticha(2019) | India | Virtual reality | 30 | NA | NA | 6–10 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | random |
| Control | 30 | NA | NA | ||||||
| Elicherla(2019) | India | Game | 25 | 15 | 10 | 7–11 | Dental anxiety/Heart rate | RMS pictorial scale | block randomization |
| EPI | 25 | 15 | 10 | ||||||
| Niharika(2018) | India | Virtual reality | 18 | 8 | 10 | 7.17 ± 0.32 | Heart rate | random | |
| Control | 18 | 10 | 8 | 7.28 ± 0.300 | |||||
| Vishwakarma(2017) | India | Modelling | 49 | NA | NA | 5–7 | Heart rate | block randomization | |
| EPI | 49 | NA | NA | ||||||
| Kamel(2017) | Egypt | Modelling | 30 | NA | NA | 4–6 | Dental anxiety | Venham’s Picture Test (VPT) | random |
| Control | 30 | NA | NA | ||||||
| Oberoi(2016) | India | Hypnosis | 100 | 48 | 52 | 6–16 | Heart rate | the lottery method | |
| Control | 100 | 46 | 54 | ||||||
| Fakhruddin(2016) | United Arab Emirates | Virtual reality | 7 | 3 | 4 | 5.35 ± 0.61 | Heart rate | random | |
| Audiovisual distraction | 8 | 4 | 4 | 5.42 ± 0.52 | |||||
| Al-Khotani(2016) | Sweden | EPI | 28 | 11 | 17 | 8.10 ± 0.90 | Heart rate | the toss of a coin | |
| Virtual reality | 28 | 11 | 17 | 8.30 ± 0.80 | |||||
| Nuvvula(2015) | India | EPI | 30 | 16 | 14 | 8.67 ± 1.60 | Dental anxiety | the modified dental anxiety scale (MDAS) |
the random sequence block randomization |
| Music | 30 | 17 | 13 | 8.40 ± 1.10 | |||||
| Virtual reality | 30 | 16 | 14 | 8.23 ± 1.10 | |||||
| Jones(2015) | New Zealand | EPI | 83 | NA | NA | 10–13 | Dental anxiety | the facial images cale (FIS) | random |
| Control | 85 | NA | NA | ||||||
| Fakhruddin(2015) | United Arab Emirates | Virtual reality | 30 | 14 | 16 | 4.15 ± 0.63 | Heart rate | block randomization | |
| Audiovisual distraction | 30 | 17 | 13 | 6.32 ± 0.31 | |||||
| Singh(2014) | India | Control | 30 | NA | NA | 6–12 | Dental anxiety/Heart rate | Venham’s Picture Test (VPT) | random |
| Music | 30 | NA | NA | ||||||
| Paryab(2014) | Iran | EPI | 23 | NA | NA | 4–6 | Heart rate | block randomization | |
| Modelling | 23 | NA | NA | ||||||
| Gangwal(2014) | India | Modelling | 30 | NA | NA | 7–12 | Dental anxiety | Venham’s Picture Test (VPT) | the lottery method |
| Control | 30 | NA | NA | ||||||
| Jafarzadeh(2013) | Iran | Aromatherapy | 15 | 6 | 9 | 7.80 ± 0.86 | Heart rate | even–odd method | |
| Control | 15 | 4 | 11 | 7.53 ± 0.83 | |||||
| Ramos-Jorge(2011) | Brazil | Modelling | 35 | 19 | 16 | 7.20 ± 2.80 | Dental anxiety | Venham’s Picture Test (VPT) | the computer-generated random sequence |
| Control | 35 | 17 | 18 | 7.40 ± 2.20 | |||||
| Howard(2009) | United Kingdom | Modelling | 27 | 9 | 18 | 7.99 ± 1.33 | Dental anxiety | the modified dental anxiety scale (MDAS) | random |
| Control | 26 | 8 | 18 | 7.62 ± 1.46 |
Results of the methodological quality assessment of the included studies
The results of the bias risk assessment conducted on the 61 included studies are illustrated in Fig. 2. During the randomization process, 25 studies [22, 40, 41, 43, 45, 46, 48, 52, 55, 58–60, 67, 74, 75, 80–82, 84, 86, 89–92, 96] were found to have a potential risk of bias. This was attributed to inadequate description of randomization methods and allocation concealment, or the potential for randomization to result in baseline imbalances. In terms of deviation from established intervention measures, due to the impracticality of implementing blinding for most non-pharmacological interventions, only 4 studies [39, 50, 55, 71] mentioned blinding of healthcare workers or implementers, and 15 studies [39, 42, 50–52, 55, 65, 66, 71, 76, 82–85, 89] mentioned that subjects may be unaware of their group allocation. In all 61 studies, the intervention methods did not differ from conventional measures. Consequently, a low risk assessment was assigned to all the studies. The 61 studies exhibited a low risk of bias in relation to missing outcome data and measurement outcomes. In the assessment of outcome measuring bias, all studies were rated as low risk, and 17 studies [24, 39, 46, 47, 50, 51, 55, 57, 71, 72, 79, 81, 83, 87, 88, 93, 95] mentioned the use of blinding for outcome assessors. For outcome selective reporting bias, one study [80] did not provide a detailed analysis plan, and it was unclear whether it was consistent with the planned study, resulting in a potential risk. The remaining studies had a low bias risk. Overall, 36 studies (59.02%) were rated as having low bias risks, while 25 studies (40.98%) were rated as having moderate bias risks. Despite the identification of some bias risks in the included literature, the overall risk was considered relatively low.
Fig. 2.
Risk of bias summary
Network analysis results
Network graph
This meta-analysis includes 61 studies and covers 12 different non-pharmacological interventions: aromatherapy, audiovisual distraction, control, enhanced preoperative information (EPI), game, hypnosis, magic, modelling, music, relaxation, robot, and virtual reality. The network structure graph of different interventions for two outcome indicators (dental anxiety and heart rate) is illustrated in Fig. 3.
Fig. 3.
Network graph of (A) Dental anxiety and (B) Heart rate
In the figure, the thickness of the line is proportional to the number of articles compared pairwise, and the diameter of the circle is proportional to the number of participants included in the intervention. An analysis using the node-splitting method was conducted for outcomes with a closed loop. In terms of outcomes related to dental anxiety, both direct and indirect comparisons between music and aromatherapy (P = 0.03<0.05) demonstrated significant findings. Direct and indirect comparisons of relaxation versus EPI, as well as hypnosis versus EPI (P<0.05), highlighted significant local discrepancies in terms of heart rate outcomes.
Outcome 1: Dental anxiety
A total of 39 research studies have recorded the results linked to dental anxiety, involving 4,002 participants and examining 11 interventions: aromatherapy, audiovisual distraction, control, EPI, game, magic, modelling, music, relaxation, robot, and virtual reality. The results from the comparative analysis revealed that music was significantly more effective than the control group (SMD = 3.26, 95% CI: 1.40, 5.19), the EPI intervention group (SMD = 2.81, 95% CI: 0.85, 4.83), and audiovisual distraction (SMD = 2.57, 95% CI: 0.03, 5.22) in reducing dental anxiety. Furthermore, game intervention was also found to be significantly more effective than the control group (SMD = 1.75, 95% CI: 0.09, 3.42), as outlined in Table 2. The results of the node-splitting method are illustrated in Appendix 3. The cumulative probability results revealed that music, aromatherapy, and game were the top three interventions for alleviating dental anxiety, with SUCRAs of 93.60%, 78.58%, and 70.99%, respectively. Aromatherapy (SUCRAs: 78.58%), audiovisual distraction (SUCRAs: 39.96%), control (SUCRAs: 18.42%), EPI (SUCRAs: 31.98%), game (SUCRAs: 70.99%), magic (SUCRAs: 28.80%), modelling (SUCRAs: 43.35%), music (SUCRAs: 93.60%), relaxation (SUCRAs: 48.94%), robot (SUCRAs: 37.52%), and virtual reality (SUCRAs: 57.87%) were ranked based on their effectiveness in managing dental anxiety (see Table 3; Fig. 4).
Table 2.
League table
| Aromatherapy | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| -1.83 (-5.28, 1.68) | Audiovisual distraction | |||||||||
| -2.5 (-5.34, 0.36) | -0.68 (-2.75, 1.38) | Control | ||||||||
| -2.06 (-5.11, 1.05) | -0.23 (-2.07, 1.62) | 0.45 (-0.83, 1.74) | EPI | |||||||
| -0.76 (-4, 2.53) | 1.06 (-0.84, 2.98) | 1.75 (0.09, 3.42) | 1.29 (-0.18, 2.78) | Game | ||||||
| -2.4 (-6.41, 1.68) | -0.56 (-3.81, 2.69) | 0.11 (-2.75, 3.01) | -0.34 (-3.15, 2.49) | -1.63 (-4.57, 1.31) | Magic | |||||
| -1.73 (-5.23, 1.83) | 0.09 (-2.85, 3.03) | 0.77 (-1.31, 2.86) | 0.32 (-2.14, 2.77) | -0.98 (-3.64, 1.7) | 0.66 (-2.91, 4.19) | Modelling | ||||
| 0.75 (-2.35, 3.99) | 2.57 (0.03, 5.22) | 3.26 (1.4, 5.19) | 2.81 (0.85, 4.83) | 1.51 (-0.76, 3.87) | 3.14 (-0.14, 6.5) | 2.48 (-0.29, 5.34) | Music | |||
| -1.52 (-5.07, 2.09) | 0.31 (-2.49, 3.1) | 0.99 (-1.19, 3.18) | 0.54 (-1.64, 2.72) | -0.75 (-3.29, 1.78) | 0.87 (-2.62, 4.35) | 0.22 (-2.81, 3.24) | -2.27 (-5.07, 0.47) | Relaxation | ||
| -2.02 (-6.1, 2.13) | -0.19 (-3.64, 3.27) | 0.49 (-2.5, 3.49) | 0.04 (-2.96, 3.04) | -1.25 (-4.52, 2.02) | 0.38 (-3.66, 4.43) | -0.28 (-3.93, 3.38) | -2.76 (-6.25, 0.66) | -0.5 (-4.09, 3.11) | Robot | |
| -1.25 (-4.38, 1.93) | 0.57 (-1.34, 2.48) | 1.25 (-0.17, 2.68) | 0.8 (-0.51, 2.11) | -0.49 (-2.11, 1.12) | 1.14 (-1.85, 4.11) | 0.48 (-2.04, 3.01) | -2 (-4.16, 0.08) | 0.26 (-2.14, 2.68) | 0.76 (-2.42, 3.93) | Virtual reality |
Table 3.
Scura ranking table
| Sucra(ranks) | Dental anxiety | Heart rate |
|---|---|---|
| Aromatherapy | 0.785823 | 0.704565 |
| Audiovisual distraction | 0.399602 | 0.3805445 |
| Control | 0.184157 | 0.131841 |
| EPI | 0.3197895 | 0.0723345 |
| Game | 0.70987 | 0.5211545 |
| Magic | 0.2880065 | - |
| Modelling | 0.433489 | 0.289268 |
| Music | 0.9359525 | 0.795819 |
| Relaxation | 0.489358 | 0.724095 |
| Robot | 0.375239 | 0.504296 |
| Virtual reality | 0.5787135 | 0.3880695 |
| Hypnosis | - | 0.988013 |
Fig. 4.
SUCRA ranking for dental anxiety
Outcome 2: heart rate
42 studies have reported outcomes related to heart rate, involving 3,988 participants across 11 different interventions, namely: aromatherapy, audiovisual distraction, control, EPI, game, hypnosis, modelling, music, relaxation, robot, and virtual reality. The league table results revealed that, when compared to the control group, aromatherapy (MD = 9.76, 95% CI: 2.36, 17.12), hypnosis (MD = 22.15, 95% CI: 11.78, 32.79), music (MD = 11.73, 95% CI: 4.24, 19.30), and relaxation (MD = 10.02, 95% CI: 2.60, 17.55) demonstrated significantly greater effectiveness in reducing heart rate. Furthermore, music was found to be more effective than EPI (MD = 12.75, 95% CI: 4.94, 20.69). Significant differences were observed when comparing hypnosis with the other seven interventions, including audiovisual distraction, EPI, game, modelling, relaxation, robot, and virtual reality. Hypnosis yielded significantly better results in this comparison. The detailed results are illustrated in Table 4. The outcomes of the node-splitting method are illustrated in Appendix 3.
Table 4.
League table
| Aromatherapy | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| -5.94 (-15.45, 3.63) | Audiovisual distraction | |||||||||
| -9.76 (-17.12, -2.36) | -3.83 (-10.34, 2.63) | Control | ||||||||
| -10.78 (-19.52, -2.06) | -4.84 (-10.74, 0.99) | -1.01 (-6.02, 3.9) | EPI | |||||||
| -3.81 (-13.66, 6.07) | 2.12 (-4.96, 9.19) | 5.96 (-0.77, 12.72) | 6.96 (0.97, 13.03) | Game | ||||||
| 12.38 (-0.22, 25.25) | 18.31 (6.61, 30.29) | 22.15 (11.78, 32.79) | 23.16 (12.44, 34.24) | 16.2 (4.35, 28.35) | Hypnosis | |||||
| -7.56 (-18.69, 3.57) | -1.62 (-11.09, 7.76) | 2.18 (-6.25, 10.64) | 3.19 (-4.34, 10.82) | -3.76 (-13.25, 5.75) | -19.94 (-33.07, -7.14) | Modelling | ||||
| 1.98 (-7.53, 11.56) | 7.9 (-0.4, 16.29) | 11.73 (4.24, 19.3) | 12.75 (4.94, 20.69) | 5.79 (-3.42, 15.02) | -10.41 (-23.12, 2.17) | 9.54 (-1, 20.21) | Music | |||
| 0.26 (-10.16, 10.73) | 6.18 (-2.64, 15.14) | 10.02 (2.6, 17.55) | 11.03 (3.52, 18.76) | 4.07 (-5.02, 13.31) | -12.13 (-23.53, -0.84) | 7.82 (-2.59, 18.38) | -1.73 (-11.87, 8.42) | Relaxation | ||
| -3.72 (-16.78, 9.32) | 2.21 (-9.77, 14.18) | 6.04 (-4.81, 16.86) | 7.04 (-3.76, 17.94) | 0.11 (-12.05, 12.1) | -16.11 (-31.14, -1.38) | 3.84 (-9.14, 16.87) | -5.7 (-18.6, 7.06) | -3.98 (-16.79, 8.69) | Robot | |
| -5.87 (-14.56, 2.82) | 0.07 (-5.22, 5.32) | 3.91 (-0.93, 8.77) | 4.91 (0.55, 9.34) | -2.05 (-8.3, 4.15) | -18.24 (-29.4, -7.34) | 1.71 (-6.76, 10.25) | -7.83 (-15.89, 0.14) | -6.12 (-13.89, 1.52) | -2.13 (-13.39, 9.12) | Virtual reality |
The cumulative probability results suggest that hypnosis, music, and relaxation may be the most optimal interventions for decreasing heart rate, with SUCRAs of 98.80%, 79.58%, and 72.41%, respectively. According to the results, aromatherapy holds a SUCRA of 70.46%, audiovisual distraction 38.05%, control 13.18%, EPI 7.23%, game 52.12%, modelling 28.93%, robot 50.43%, and virtual reality 38.81% (Table 3; Fig. 5).
Fig. 5.
SUCRA ranking for heart rate
Publication bias
Funnel plots were used to evaluate publication bias for all outcome indicators. The funnel plots for dental anxiety and heart rate were even left-right symmetry, suggesting that there may be no publication bias. The details were illustrated in Figs. 6 and 7.
Fig. 6.
Funnel plots for dental anxiety. NoteA: Aromatherapy B: Audiovisual distraction C: Control D: EPI E: Game F: Magic G: Modelling H: Music I: Relaxation J: Robot K: Virtual reality
Fig. 7.
Funnel plots for heart rate. NoteA: Aromatherapy B: Audiovisual distraction C: Control D: EPI E: Game F: Hypnosis G: Modelling H: Music I: Relaxation J: Robot K: Virtual reality
Discussion
To the best of our knowledge, this marks the first network meta-analysis (NMA) aiming to compare the effectiveness of different non-pharmacological interventions in improving pediatric dental anxiety. The NMA systematically analyzed the latest data from 61 eligible randomized controlled trials to gain a comprehensive understanding of which non-pharmacological interventions exhibited superior efficacy in alleviating dental anxiety during pediatric treatment. Our research uncovered that, upon comparing effect sizes across different non-pharmacological interventions, music was identified as the most effective method for alleviating dental anxiety, significantly outperforming the control group, the EPI group, and audiovisual distraction. Meanwhile, hypnosis was established as the most effective approach for reducing heart rate, exhibiting a remarkable decrease superior to audiovisual distraction, EPI, control, game, modelling, relaxation, robot, and virtual reality.
In terms of dental anxiety, music has been identified as the most effective in reducing dental anxiety, a conclusion consistent with findings from two traditional systematic reviews and meta-analyses [97, 98]. Both studies reached concordant results, highlighting that playing music during dental treatments has the potential to reduce anxiety in children, adolescents, and adult patients. Music impacts anxiety on both physiological and mental levels. On one hand, it stimulates the brain to produce alpha waves, inducing relaxation by lowering blood pressure, pulse, and respiration rate, fostering a state of calmness [54]. On the other hand, music directly influences the senses, regulating cognition and emotions. By diverting attention from unpleasant thoughts and feelings, the use of gentle and pleasant music creates a relaxed mood, diminishes unpleasant feelings, and enhances overall comfort and relaxation [99]. Additionally, playing music can help mask the noise generated by high-speed dental handpieces during procedures, mitigating anxiety induced by auditory stimulation [100]. Consequently, music is considered an effective complementary approach to alleviate anxiety in a clinical setting. Gowdham et al. [100] applied music intervention to special children and observed a significant reduction in anxiety levels among children with mild intellectual disabilities during dental treatment. For children with intellectual disabilities experiencing cognitive disorders and communication difficulties, who often lean toward drug intervention methods, music intervention provides a non-invasive, non-drug alternative, offering a new approach for these special children.
Physiological indicators undergo changes that can reflect alterations in anxiety levels to a certain extent. Consequently, in addition to employing anxiety scales in the study, heart rate was conducted to capture physiological changes in response to stress and anxiety. According to the outcomes of this network meta-analysis, hypnosis appears to be among the most effective non-pharmacological interventions for improving heart rate, aligning with previous studies [64, 79]. The American Psychological Association (APA) Division 30 defines hypnosis as “a state of consciousness involving focused attention and reduced peripheral awareness, characterized by enhanced responsiveness to suggestion“ [101]. The temporal dynamics of the cardiac cycle are primarily governed by the activity of the sympathetic and parasympathetic nervous systems regulating the heart. Hypnosis achieves a relaxed physiological state by regulating cerebral blood flow and reducing tension in the sympathetic nervous system while enhancing parasympathetic nervous system activity [102]. Oberoi et al. [79] applied hypnosis during the induction of local anesthesia in children requiring dental treatment. A pediatric dentist, certified in clinical hypnosis, employed a series of hypnotic induction techniques, guiding children to relax and focus on their inner experiences, including sensations, thoughts, and imagery. The study observed a significant reduction in heart rate in pediatric patients through hypnosis, coupled with increased treatment compliance. Consequently, hypnosis is frequently employed in pediatric dentistry to assist children in relaxation, thereby reducing anxiety and fear [17].
In this study, network meta-analysis was employed to quantify the rankings of non-pharmacological interventions on dental anxiety, and heart rate changes in children requiring dental treatment. However, the study has several limitations. Firstly, The findings of this study may be subject to bias due to the limited coverage of countries and geographical distribution in the included article. It is important to note that the results may be more applicable to countries and populations that are involved in a larger number of the included studies. The results should be interpreted with caution for other countries, due to regional and cultural differences. The cultural differences in different regions should be considered comprehensively when other countries refer to it. Secondly, the quality of the included literature exhibited variability. Despite all studies being randomized controlled trials, the impracticality of blinding in most non-pharmacological interventions led to a lack of information on allocation concealment and blinding in the majority of studies, making it challenging to assess potential bias. Unlike traditional meta-analyses, network meta-analysis used rankings to represent results, introducing variability influenced by the definition of intervention categories, data extraction, and statistical method selection. Additionally, the impact of dental anxiety on children receiving dental treatment can vary significantly across different age groups, including preschoolers, schoolchildren, and adolescents [2]. It’s important to note that the effectiveness of various interventions may also vary based on the children’s age. When non-pharmacological interventions are being implemented, dentists and dental teams should consider the differences in comprehension and concentration abilities influenced by cognitive and intellectual development at different stages. For instance, young preschoolers often struggle with focus due to their developmental stage and are typically drawn to engaging stimuli, such as audiovisual materials and games, which can effectively capture their attention [103]. Therefore, it is hypothesized that such interventions may be particularly effective for younger children. However, due to limitations in the extracted data, a detailed subgroup analysis of dental anxiety levels across different age groups was not possible. Conclusions on the impact of different intervention measures on children of different age groups cannot be temporarily drawn. Further research will be carried out in the future to confirm and refine the conclusions through more follow-up studies on children of different age groups.
With the rapid development of non-pharmacological interventions in pediatric dentistry and mental health, certain interventions may only be suitable for children with low or moderate dental anxiety. However, the applicability of these measures for children with high dental anxiety or dental phobia remains to be verified [11]. Consequently, no definitive conclusions can be drawn regarding recommended non-pharmacological interventions for children with different levels of dental anxiety. Further analysis and confirmation necessitate additional primary study evidence.
Conclusion
In conclusion, this study aimed to compare the effectiveness of various non-pharmacological interventions in alleviating dental anxiety and reducing heart rate in children undergoing dental treatment, offering guidance for the selection of non-pharmacological interventions in pediatric dental care. The results of our study suggest that music could be given priority in reducing dental anxiety, whereas hypnosis might be more effective in lowering heart rate. However, due to the limitations of the quantity of articles, further confirmation and refinement of the conclusions are needed through high-quality, multicenter, large-sample double-blind RCTs in the future.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to thank the researchers and study participants for their contributions.
Author contributions
Xiangrong Kong: Conceptualization, Methodology, Software, Formal analysis, Investigation, Data Curation, Writing - Original Draft. Ning Song: Conceptualization, Formal analysis, Investigation, Data Curation, Writing - Review & Editing. Lulu Chen: Conceptualization, Investigation, Data Curation, Visualization, Writing - Review & Editing. Yuemei Li: Conceptualization, Investigation, Supervision, Writing - Review & Editing, Funding acquisition. All authors read and approved the final manuscript.
Funding
This work was supported by Guangdong High-level Hospital Construction Fund Clinical Research Project of Shenzhen Children’s Hospital(HLLCYJ2022028).
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.