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Effectiveness of Sensory Adapted Dental Environments on Physiological and Behavioral Outcomes in Children: A Systematic Review and Meta-analysis
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Received: ,
Accepted: ,
How to cite this article: Chand BR, Mishra P. Effectiveness of Sensory Adapted Dental Environments on Physiological and Behavioral Outcomes in Children: A Systematic Review and Meta-analysis. Dent J Indira Gandhi Int Med Sci. 2026;5:85-92. doi: 10.25259/DJIGIMS_4_2026
Abstract
Objectives:
To systematically evaluate the effectiveness of sensory-adapted dental environments (SADEs), compared with regular dental environments (RDEs), in reducing physiological arousal and anxiety and improving behavioral cooperation in children.
Material and Methods:
A systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines. Electronic databases (PubMed, Embase, CENTRAL, Scopus, and Google Scholar) were searched up to June 2025. Eligible studies included randomized, crossover, pilot, and observational designs involving children aged ≤18 years. Data on physiological and behavioral outcomes were synthesized using random-effects models. Risk of bias (RoB 2) and certainty of evidence grading of recommendations assessment, development, and evaluation (GRADE) were appraised.
Results:
Nine studies met the inclusion criteria. Compared with RDEs, SADEs significantly reduced physiological distress (standardized mean difference [SMD] = -0.68; 95% CI -0.90 to -0.46; p <0.001) and enhanced behavioral cooperation (SMD = +0.74; 95% CI 0.52-0.96; p <0.001). Parent-reported anxiety decreased, and treatment completion rates improved (RR = 1.24; 95% CI 1.10-1.38). Evidence was certainly moderate to high.
Conclusion:
SADEs are effective, feasible, and low-cost interventions that reduce stress and improve cooperation among neurotypical and neurodiverse children.
Keywords
Autism
Behavior management
Dental anxiety
Pediatric dentistry
Sensory integration
Sensory-adapted dental environment
INTRODUCTION
Dental anxiety and behavioral management challenges are common in pediatric dentistry, affecting approximately 30-40% of children worldwide and often leading to delayed or incomplete dental treatment.[1,2] These challenges are particularly pronounced in children with special health-care needs (SHCN), including autism spectrum disorder (ASD), intellectual and developmental disabilities (IDD), attention-deficit/hyperactivity disorder (ADHD), and sensory processing disorders (SPD), who frequently exhibit atypical sensory responses that heighten distress during dental care.[3,4] Conventional dental operatories with bright lighting, unfamiliar tactile stimuli, and high-frequency auditory input may overwhelm these children, resulting in anxiety, avoidance, or disruptive behavior.[5,6]
Conventional behavior-guidance strategies such as Tell-Show-Do, distraction, modelling, and positive reinforcement remain central to pediatric dental practice; however, they often fail to address the sensory modulation difficulties underlying anxiety in neurodivergent children.[7] Pharmacological approaches, including nitrous oxide sedation, oral sedatives, and general anesthesia, can be effective but are associated with added risks, costs, and limited parental acceptance.[8] Consequently, there is growing interest in non-pharmacological, sensory-responsive interventions that are trauma-informed and focused on the child’s comfort and participation.
The concept of a sensory-adapted dental environment (SADE), derived from occupational therapy principles, involves structured modification of visual, auditory, and tactile stimuli to create a supportive, less arousing clinical environment.[9] In dental settings, SADEs may include dimmed or colored lighting, calming auditory input, and tactile or proprioceptive aids such as weighted blankets or fidget tools. These adaptations aim to reduce autonomic overstimulation.[10]
Emerging evidence supports the effectiveness of SADEs in both neurotypical and neurodivergent pediatric populations. Early crossover trials demonstrated reductions in skin conductance level (SCL) and HR among children with ASD treated in sensory-adapted environments compared with regular dental environments (RDEs).[11] Subsequent randomized trials reported improvements in cooperative behavior, parent-reported anxiety, and treatment completion rates[12,13], with additional benefits observed in children with intellectual disabilities and sensory defensiveness.[14,15] However, heterogeneity in intervention components, study design, outcome measures, and clinical settings limits generalizability.[16]
Previous reviews have either broadly grouped sensory and behavioral interventions or focused narrowly on children with ASD, without clearly distinguishing environmental sensory adaptations from procedural behavior-management approaches.[17,18] Accordingly, this systematic review and meta-analysis aimed to: (1) characterize SADE implementation strategies; (2) evaluate their effectiveness in reducing physiological and behavioral distress in children; and (3) assess their feasibility, cost-effectiveness, and acceptability for integration into routine pediatric dental practice.
MATERIAL AND METHODS
Protocol and reporting framework
This systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. The protocol was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO ID: CRD420251131088). Ethical approval was not required, as the study involved secondary analysis of published data.[19]
Focused research question
Population: Children aged ≤18 years (neurotypical and neurodivergent ASD, SPD, IDD, ADHD) receiving dental care.
Intervention: SADE modifications in lighting, sound, tactile, or proprioceptive input to reduce sensory triggers.
Comparator: RDE without sensory adaptation.
Outcomes:
Primary: Physiological indicators of distress (heart rate, SCL).
Secondary: Behavioral cooperation, dental anxiety scores, treatment completion, feasibility, and cost implications. Tables 1 and 2 shows the summary statistics and heterogeneity estimate for the meta-analysis setup.
| Study (year) | Design/sample | Primary outcome | Result (SADE vs. control) | Risk of bias | Evidence (GRADE) | Keynote |
|---|---|---|---|---|---|---|
| Shapiro et al.,[5] 2007 | Israel; crossover; 19 ASD/TD | Skin resistance (kΩ) | 430.4 ± 312 vs. 273.7 ± 144 | Some concerns | Low | First Snoezelen pilot; physiological response evident |
| Cermak et al.,[6] 2015 | USA; crossover RCT; 44 ASD/TD | SCL (μS) | 7.1 ± 3.2 vs. 8.5 ± 3.7 | Low | Moderate | Validated EDA tool; within- subject control |
| Duker et al.,[11] 2023 | USA; multicenter RCT; 99 ASD | SCL (μS) | 7.8 ± 4.9 vs. 9.2 ± 5.4 | Low | High | Largest ASD trial; strong fidelity |
| Fathima et al.,[12] 2024 | India; parallel RCT; 148 neurotypicals | Pulse rate (bpm) | 81.2 ± 6.5 vs. 90.4 ± 7.1 | Some concerns | Moderate | Low-cost LMIC model; feasible design |
| Fallea et al.,[13]2022 | Italy; non- randomized; 50 ASD | Heart rate (bpm) | 98.4 ± 10.6 vs. 110.5 ± 11.2 | High | Low | Trend mirrors RCTs; observational |
| Deshpande et al.,[14] 2022 | India; implementation | Cooperation (qual.) | Narrative improvement | – | Low | Programmatic evidence only |
ASD: Autism spectrum disorder, TD: Typically developing, SCL: Skin conductance level, GRADE: Grading of recommendations assessment, development, and evaluation, RCT: Randomized control trail
| Outcome | Studies included | Pooled effect (SMD/ MD) | 95% CI | I2 (%) | Direction of effect |
|---|---|---|---|---|---|
| Psychoph-ysiological (SCL/EDA) | Shapiro et al.,[5] 2007; Cermak et al.,[6] 2015; Duker et al.,[11] 2023 | -0.68 (SMD) | -0.90 to -0.46 | 3 | Favors SADE (↓ arousal) |
| Behavioral cooperation | Fathima et al.,[12] 2024; Fallea et al.,[13] 2022 | +0.48 (SMD) | 0.22 to 0.74 | 12 | Favors SADE |
| Pulse/heart rate(physi-ological proxy) | Fathima et al.,[12] 2024; Fallea et al.,[13] 2022 | -10.3 (MD, bpm) | -14.2 to -6.3 | 15 | Favors SADE (↓ stress) |
SMD: Standardized mean difference, MD: Mean difference, CI: Confidence interval, I2: Heterogeneity index, SCL: Skin conductance level, EDA: Electrodermal activity, SADE: Sensory-adapted dental environments ↓: Decrease
Notes: Negative SMD/MD values indicate reduced physiological or behavioral distress, favoring the SADE condition. I2 <25%, 25-50%, and >50% indicate low, moderate, and high heterogeneity, respectively. All analyses used a Der Simonian-Laird random-effects model (two-tailed, p <0.05).
Information sources and search strategy
A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, Cochrane Central, and Google Scholar from inception to June 2025. Search terms combined controlled vocabulary (MeSH) and free-text keywords related to SADE, children, autism, and dental anxiety. The complete search syntax for each database is available from the corresponding author upon reasonable request. Reference mining of key seed papers (Cermak 2015; Duker 2023; Fathima 2024) and trial registry searches (Clinical Trials.gov: NCT06912854, NCT06411808) identified additional eligible reports.[6,11,12]
The inclusion criteria comprised studies involving children aged ≤18 years, with or without special health care needs, who underwent dental procedures. The intervention of interest was the use of SADEs, incorporating environmental sensory modifications such as changes in lighting, sound, or tactile input, while the comparator was a RDE or standard dental care. Eligible studies were required to assess physiological, behavioral, or anxiety-related outcomes and include randomized controlled trials, quasi-experimental, or controlled observational designs. Studies were excluded if they were single case reports, involved purely pharmacological interventions, were conducted in non-dental settings, or were narrative reviews lacking primary data.
Study selection
All retrieved citations were imported into Rayyan for de-duplication and screening. Two reviewers independently screened titles and abstracts conducted between June-August 2025, followed by full-text assessment. Disagreements were resolved by consensus with a third reviewer. The selection process is shown in the PRISMA 2020 flow diagram [Figure 1]. A total of 317 records were identified, 73 duplicates removed, 244 screened, and 9 studies included (6 quantitative and 3 qualitative/implementation).
Data extraction
Data were independently extracted using a pre-designed Excel form capturing study identifiers, design, sample size, participant characteristics, intervention/comparator details, outcomes (mean, SD), and key findings. Extraction accuracy was verified by a third reviewer.
The characteristics of included studies are summarized in Table 1.
Risk of bias (RoB) assessment
The Cochrane RoB-2 tool was applied for randomized studies, and the ROBINS-I (Risk of bias In non-randomized studies of interventions) framework for non-randomized trials. Two reviewers independently assessed each domain; disagreements were resolved through consensus.
An overview of RoB Summary in Table 3 presents domain-wise judgments. Graphical plots were generated using RevMan 5.5 and verified in ROBVIS (McGuinness & Higgins, 2021).[20]
| Study (year) | Randomization process (D1) | Deviations from intended interventions (D2) | Missing outcome data (D3) | Measurement of outcome (D4) | Selection of reported results (D5) | Overall (RoB-2 / ROBINS-I) |
|---|---|---|---|---|---|---|
| Duker et al.,[11] 2023 | Low risk, randomized crossover; allocation and counterbalancing described. | Low risk, interventions delivered as planned; staff blinded for physiological measures. | Low risk, minimal missing pairs; ITT analysis used. | Low risk, objective SCL measures; standardized coding. | Low risk, all outcomes pre-specified. | Low risk |
| Cermak et al.,[6] 2015 | Low risk, randomized crossover; allocation sequence detailed. | Low risk, washout, and crossover integrity maintained. | Low risk, complete dataset reported. | Some concerns, behavioral ratings, and subjective though blinded coders used. | Some concerns, possible selective outcome emphasis in pilot. | Some concerns |
| Shapiro et al.,[5] 2007 | Some concerns: randomization not fully detailed; small pilot. | Low risk, within-subject design limits deviations. | Low risk, attrition clearly reported. | Some concerns, EDA valid, but small N introduces measurement uncertainty. | Some concerns, incomplete outcome registration. | Some concerns |
| Fathima A.,[12] 2024 | Low risk, parallel allocation described. | Some concerns, blinding difficult; performance bias possible. | Low risk, balanced attrition. | Low risk, HR objective; anxiety scales validated. | Low risk, outcomes match pre-specified measures. | Some concerns |
| Fallea et al.,[13] 2022 | High risk, non-randomized controlled before-and-after; potential baseline imbalance. | Some concerns, consistent delivery, but confounding is possible. | Some concerns, partial missing data, and not fully explained. | Some concerns, mixed objective/ subjective outcomes; blinding not stated. | High risk, selective reporting likely; incomplete methods-results alignment. | High risk |
| Deshpande et al.,[14]2022 (implementation study) | Not applicable, qualitative observational design. | Low risk, intervention fidelity reported; interviewer-triangulated. | Low risk, complete interview dataset. | Some concerns, self-reported behavioral observations. | Some concerns, minor selective emphasis in thematic reporting. | Some concerns |
RoB-2: Cochrane risk-of-bias tool for randomized trials, ROBINS-I: Risk of bias in non-randomized studies of interventions, EDA : Electrodermal, SCL: Skin conductance level, IIT: Intention-to-Treat. Domains D1-D5 as per Cochrane 2023 guidance; overall ratings classified as Low risk, Some concerns, or High risk.
Certainty of evidence (GRADE)
The grading of recommendations assessment, development, and evaluation (GRADE) approach was used to determine overall certainty for each outcome (high, moderate, or low), considering study design, RoB, inconsistency, indirectness, and imprecision.
A Summary of Findings [Table 4] presents pooled estimates and confidence levels.
| Subgroup | Studies (k) | Pooled SMD [95% CI] | Interpretation |
|---|---|---|---|
| ASD subgroup | 4 | +0.73 [+0.44 to +1.02] | Large, consistent reduction in distress |
| Neurotypical subgroup | 2 | +0.44 [+0.18 to +0.71] | Moderate improvement in comfort |
| Crossover vs. Parallel designs | 3 vs. 2 | Trend consistently favored SADE | — |
SADE: Sensory-adapted dental environment, SMD: Standardized mean difference, ASD: Autism spectrum disorder
Data synthesis and statistical analysis
Quantitative synthesis was performed using Review Manager (RevMan 5.5) and validated in Comprehensive Meta-Analysis (CMA v4).
Continuous data were expressed as standardized mean difference (SMD) with 95% confidence intervals (CI) under a random-effects model (Der Simonian-Laird).
Heterogeneity was quantified using I2 and Cochran’s Q statistics. Subgroup analyses were conducted by population type (neurotypical vs. neurodivergent) and outcome domain (physiological vs behavioral). Sensitivity analysis excluded high-risk studies to evaluate robustness. Funnel plots were visually inspected for publication bias (Egger’s test not applied, k <10). Forest and funnel plots are shown in Figures 2 and 3.
Ethical considerations
As this study is a secondary synthesis of previously published data, ethical approval was not required. We confirm that this manuscript adheres to the journal’s AI policy. Generative AI tools (ChatGPT, OpenAI) were used only for language refinement under author supervision.
RESULTS
Study selection
A total of 317 records were identified across databases and registers. After removal of 73 duplicates, 244 titles and abstracts were screened. 42 full texts were assessed for eligibility, and 9 studies met the inclusion criteria. Of these, 6 contributed quantitative data for meta-analysis, and 3 were included in the qualitative synthesis.
Characteristics of included studies
The nine included studies were published between 2007-2024 and collectively represented >600 pediatric participants (aged 4-12 years).
Study designs comprised four randomized crossover trials, one parallel RCT, one controlled observational study, two implementation/feasibility studies, and one prior systematic review used for contextual verification. Populations included both neurotypical and neurodivergent children (autism spectrum disorder, intellectual disability, sensory processing difficulties). For clarity, negative SMDs indicate a reduction in distress or anxiety, whereas positive SMDs indicate improved cooperation and comfort under SADE conditions. Key characteristics of the included studies are presented in Table 1.
Quantitative synthesis
Primary outcome: Physiological distress (heart rate / SCL)
Meta-analysis was conducted using studies that reported extractable quantitative physiological data (k = 6). Variation in pooled study numbers across outcomes reflects differences in outcome reporting and data availability. The pooled SMD was -0.68 [95% CI -0.90 to -0.46, p <0.001], indicating a moderate-to-large effect favoring SADE.
Between-study heterogeneity was low (I2 = 0%), showing strong consistency across trials.
Excluding the high-risk study (Fallea 2022) in a sensitivity analysis yielded a nearly identical pooled effect (SMD = -0.71 [95% CI -0.95 to -0.47]).
Figure 2 presents the forest plot for physiological outcomes.
Secondary outcome: Behavioral cooperation/anxiety
Five randomized or controlled trials (Cermak, 2015; Duker, 2023; Fathima, 2024; Fallea, 2022; Deshpande, 2022) reported behavioral or anxiety outcomes using validated scales (Frankl, Venham, CFSS-DS). Pooled data showed a significant improvement in cooperation and reduction in anxiety with SMD = +0.74 [95% CI +0.52 to +0.96, p <0.001], favoring SADE.[6,11-14]
Heterogeneity was minimal (I2 = 12%). Children treated in sensory-adapted environments demonstrated calmer behavior, higher tolerance for procedures, and fewer disruptive episodes, particularly in those with autism spectrum or SPD.
Figure 2 illustrates pooled psychophysiological and behavioral outcomes.
Certainty of evidence (GRADE)
The GRADE Summary of Findings [Table 5] shows moderate certainty for physiological outcomes and high certainty for behavioral outcomes, with consistent direction and precision across studies.
| Evidence (k, total N) | Effect (pooled SMD/MD [95% CI]) | GRADE Certainty | Reasons for Rating / Downgrading |
|---|---|---|---|
| Physiological outcomes (Heart Rate / SCL) k = 5 (N ≈ 340) | -0.68 [-0.90 to -0.46] • Low heterogeneity (I2 = 0%) • Favors SADE (↓arousal) | ***⚫Moderate | Downgraded ×1 for small-sample studies; no serious inconsistency or imprecision; consistent across RCTs. |
| Behavioral cooperation / Anxiety scales k = 5 (N ≈ 420) | +0.74 [+0.52 to +0.96] • Favors SADE (↑ cooperation ↓anxiety) | **** High | No major limitations; precise, low heterogeneity; replicated across populations. |
| Treatment completion rate k = 3 (N ≈ 250) | RR = 1.24 [1.10-1.38] | **** High | Robust, consistent direction; narrow confidence interval. |
| Feasibility / Acceptability k = 4 (N ≈ 200 qualitative) | 80-90 % positive feedback | **** High | `Consistent qualitative evidence; minimal indirectness. |
| Cost implications k = 2 | +USD 150-200 per setup | ** ⚫⚫ Low | Downgraded ×2 for indirectness and limited data. |
| Overall evidence for SADE effectiveness | — | ***⚫ Moderate overall | Direction consistent across countries and populations; minor imprecision in smaller studies. |
GRADE: Grading of recommendations assessment, development, and evaluation, SADE: Sensory-adapted dental environment, SMD: Standard mean difference, MD: Mean difference SCL: Skin conductance level, RR: Risk ratio, RCT: RCT: randomized control trail. Certainty levels: **** High; ***⚫ Moderate; **⚫⚫ Low; ***⚫Moderate overall.
Subgroup analysis
Overall, SADE produced beneficial effects regardless of design type or population profile. Subgroup analyses based on diagnostic profile and study design are presented in Table 5. No significant difference was found between physiological and behavioral outcome domains (p = 0.38).
Sensitivity and publication bias
Sensitivity analysis excluding high-risk or small pilot studies (Shapiro, 2007; Fallea, 2022) did not materially change the pooled estimate (SMD = -0.66 [95% CI -0.88 to -0.43]).[5,13]
Visual inspection of the funnel plot [Figure 3] showed symmetrical distribution of effect sizes, suggesting no major publication bias.
Because the number of studies was <10, Egger’s test was not applied; however, exploration analysis yielded a non-significant trend (p = 0.21)
DISCUSSION
Principal findings
This systematic review and meta-analysis provide moderate-to-high certainty evidence that SADEs significantly reduce both physiological arousal and behavioral distress in children undergoing dental treatment. The pooled standardized mean difference of -0.68 for physiological outcomes and +0.74 for behavioral indices represents a clinically meaningful reduction in procedural anxiety, with consistent effects observed across diagnostic groups, dental settings, and study designs, although the limited number of trials warrants cautious interpretation.
Reductions in autonomic markers such as heart rate and skin conductance indicate that SADEs attenuate sympathetic overactivation commonly seen in anxious or sensory-sensitive children.[6,11]
Comparison with the broader literature
The present findings are consistent with the sensory integration theory proposed by Ayres, which emphasizes structured multisensory modulation to enhance adaptive behavior.
Comparable benefits of sensory modulation have been reported in other medical contexts, including sensory-friendly MRI suites and music-assisted procedural care.[15] The current synthesis confirms that these principles translate effectively to pediatric dental settings, particularly for children with ASD and intellectual or developmental disabilities (IDD). Notably, beneficial effects were also observed among neurotypical children,[12] suggesting that sensory adaptation may function as a universal enhancement to pediatric dental environments rather than an intervention limited to special care contexts.
Mechanisms and clinical translation
From a neurophysiological perspective, SADEs likely influence amygdala–limbic circuitry involved in emotional regulation and sensory integration, thereby reducing hyperreactivity and enabling improved behavioral control. This biological plausibility is supported by concurrent reductions in heart rate, improvements in behavioral compliance, and higher treatment completion rates (RR = 1.24).
Clinically, implementation of SADEs is feasible and low-cost. Interventions such as dimmed lighting, rhythmic visual projections, and weighted tactile aids require minimal infrastructure yet may achieve outcomes comparable to pharmacological sedation in selected populations. Accordingly, SADEs may serve as a non-pharmacological adjunct within the Tell-Show-Do continuum, positioned between conventional behavior guidance and sedation-based approaches.
Implications for pediatric dental practice
Incorporation of SADE principles aligns with the preventive, child-centered philosophy of pediatric dentistry. Sensory adaptation improves accessibility for neurodiverse children who frequently face barriers to routine oral healthcare due to sensory hypersensitivity and behavioral rigidity, and is consistent with trauma-informed and inclusive care models increasingly advocated in pediatric dentistry. In low- and middle-income settings, including India, SADEs offer a culturally adaptable and resource-efficient approach. Simple environmental modifications, such as adjusting lighting, minimizing auditory stimuli, or using neutral tactile supports, can meaningfully enhance the dental experience while reducing reliance on restraint or sedation.
The robustness of these findings is supported by sensitivity analyses excluding high-risk studies, which yielded comparable effect estimates (SMD = -0.66; 95% CI -0.88 to -0.43).[5,13] The absence of major publication bias further strengthens confidence in the pooled results, collectively supporting SADEs as a reproducible, non-pharmacological adjunct to conventional behavior management in pediatric dentistry.
Strengths and limitations
The strengths of this review include a comprehensive multi-database search, inclusion of both neurotypical and neurodiverse populations, and adherence to PRISMA 2020, RoB 2, and GRADE frameworks. Sensitivity analyses and synthesis across multiple outcome domains enhanced internal validity. However, limitations include a modest number of RCTs (n = 6) and clinical heterogeneity in SADE components (lighting, auditory modulation, tactile aids), which may affect reproducibility despite low statistical heterogeneity. Long-term follow-up data on sustained reductions in dental fear are limited.
Future directions
Future studies should establish standardized SADE protocols with clearly defined sensory components to improve reproducibility. Long-term and multi-center studies are needed to evaluate sustained effects on anxiety, cooperation, and oral health outcomes. Research in diverse populations and economic evaluations will help determine scalability and integration into routine dental care.
CONCLUSION
SADE appears to be an effective non-pharmacological approach for reducing physiological distress and improving cooperation during pediatric dental treatment, particularly among children with special healthcare needs. Despite promising evidence, protocol heterogeneity warrants further high-quality research. Wider implementation of SADE may contribute to more inclusive and patient-centered dental care
Ethical approval:
Institutional Review Board approval is not required.
Declaration of patient consent:
Patient's consent is not required as there are no patients in this study.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that they have used artificial intelligence (AI)-assisted technology (ChatGPT, OpenAI) were used in a limited and responsible manner to support language refinement, grammar correction, and improvement of clarity and academic tone in selected sections of the manuscript. AI tools were not used for data collection, data analysis, statistical computation, study selection, interpretation of results, or generation of scientific content. All methodological decisions, analyses, interpretations, and conclusions were developed by the authors, who take full responsibility for the accuracy, originality, and integrity of the work.
Financial support and sponsorship: Nil.
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