學齡兒童口腔健康篩檢計劃
Abstract
Background
In school dental screening, a dental health professional visually inspects children’s oral cavities in a school setting and provides information for parents on their child's current oral health status and treatment needs. Screening at school aims to identify potential problems before symptomatic disease presentation, hence prompting preventive and therapeutic oral health care for the children. This review evaluates the effectiveness of school dental screening for improving oral health status. It is the second update of a review originally published in December 2017 and first updated in August 2019.
Objectives
To assess the effectiveness of school dental screening programmes on overall oral health status and use of dental services.
Search methods
An information specialist searched four bibliographic databases up to 15 October 2021 and used additional search methods to identify published, unpublished and ongoing studies.
Selection criteria
We included randomised controlled trials (RCTs; cluster‐ or individually randomised) that evaluated school dental screening compared with no intervention, or that compared two different types of screening.
Data collection and analysis
We used standard methodological procedures expected by Cochrane.
Main results
The previous version of this review included seven RCTs, and our updated search identified one additional trial. Therefore, this update included eight trials (six cluster‐RCTs) with 21,290 children aged 4 to 15 years. Four trials were conducted in the UK, two in India, one in the USA and one in Saudi Arabia. We rated two trials at low risk of bias, three at high risk of bias and three at unclear risk of bias.
No trials had long‐term follow‐up to ascertain the lasting effects of school dental screening. The trials assessed outcomes at 3 to 11 months of follow‐up.
No trials reported the proportion of children with treated or untreated oral diseases other than caries. Neither did they report on cost‐effectiveness or adverse events.
Four trials evaluated traditional screening versus no screening. We performed a meta‐analysis for the outcome 'dental attendance' and found an inconclusive result with high heterogeneity. The heterogeneity was partly due to study design (three cluster‐RCTs and one individually randomised trial). Due to this inconsistency, and unclear risk of bias, we downgraded the evidence to very low certainty, and we are unable to draw conclusions about this comparison.
Two cluster‐RCTs (both four‐arm trials) evaluated criteria‐based screening versus no screening, suggesting a possible small benefit (pooled risk ratio (RR) 1.07, 95% confidence interval (CI) 0.99 to 1.16; low‐certainty evidence). There was no evidence of a difference when comparing criteria‐based screening to traditional screening (RR 1.01, 95% CI 0.94 to 1.08; very low‐certainty evidence).
One trial compared a specific (personalised) referral letter to a non‐specific letter. Results favoured the specific referral letter for increasing attendance at general dentist services (RR 1.39, 95% CI 1.09 to 1.77; very low‐certainty evidence) and attendance at specialist orthodontist services (RR 1.90, 95% CI 1.18 to 3.06; very low‐certainty evidence).
One trial compared screening supplemented with motivation to screening alone. Dental attendance was more likely after screening supplemented with motivation (RR 3.08, 95% CI 2.57 to 3.71; very low‐certainty evidence).
One trial compared referral to a specific dental treatment facility with advice to attend a dentist. There was no evidence of a difference in dental attendance between these two referrals (RR 0.91, 95% CI 0.34 to 2.47; very low‐certainty evidence).
Only one trial reported the proportion of children with treated dental caries. This trial evaluated a post‐screening referral letter based on the common‐sense model of self‐regulation (a theoretical framework that explains how people understand and respond to threats to their health), with or without a dental information guide, compared to a standard referral letter. The findings were inconclusive. Due to high risk of bias, indirectness and imprecision, we assessed the evidence as very low certainty.
Authors' conclusions
The evidence is insufficient to draw conclusions about whether there is a role for school dental screening in improving dental attendance.
We are uncertain whether traditional screening is better than no screening (very low‐certainty evidence). Criteria‐based screening may improve dental attendance when compared to no screening (low‐certainty evidence). However, when compared to traditional screening, there is no evidence of a difference in dental attendance (very low‐certainty evidence).
For children requiring treatment, personalised or specific referral letters may improve dental attendance when compared to non‐specific referral letters (very low‐certainty evidence). Screening supplemented with motivation (oral health education and offer of free treatment) may improve dental attendance in comparison to screening alone (very low‐certainty evidence). We are uncertain whether a referral letter based on the 'common‐sense model of self‐regulation' is better than a standard referral letter (very low‐certainty evidence) or whether specific referral to a dental treatment facility is better than a generic advice letter to visit the dentist (very low‐certainty evidence).
The trials included in this review evaluated effects of school dental screening in the short term. None of them evaluated its effectiveness for improving oral health or addressed possible adverse effects or costs.
PICO
淺顯易懂的口語結論
改善兒童口腔健康的校園牙科篩檢計畫
本文獻回顧之目的為何？
口腔健康是指口腔、喉嚨、牙齒及牙齦的健康狀況。本篇考科藍文獻回顧目的為找出校園牙科篩檢是否可改善兒童口腔健康；如果可改善兒童口腔健康，什麼篩檢方法為最佳。我們發現有八個相關研究可以回答這個問題。此次文獻回顧為第二次更新，於 2017 年 12 月發表；第一次更新為 2019 年 8 月。
關鍵訊息
目前沒有足夠的證據可以得出關於傳統學校牙科篩檢是否能提高牙科就診率（使兒童能更加頻繁去看牙醫）的結論。此外，尚不清楚牙科就診率的提高是否會帶來更好的口腔健康。我們仍需要進行高品質研究用於評估長時間口腔健康篩檢的影響。
本篇文獻回顧的研究內容為何？
口腔疾病，尤其是蛀牙（牙醫稱為 “齲齒”）影響了全世界的兒童。如果不治療，口腔健康會逐漸惡化，對兒童整體健康將產生不良的影響。同時也會給家庭和整個社會帶來經濟成本。
學校牙科篩檢涉及牙科專業人員在學校檢查兒童的口腔及牙齒，並且讓家長了解他們孩子的口腔狀況和治療需求。重點在於能及早確定口腔的健康問題，並促使父母在需要時尋求治療。對於是否能改善兒童口腔健康的問題是此次所要探討的。
本篇文獻回顧的主要結果為何？
自上一版文獻發表以來，一項新的研究納入了此次最新的搜索。總體而言，此次研究結果是針對 21,290 名兒童所做的八項研究。四項研究在英國進行、兩項在印度、一項在美國、一項在沙烏地阿拉伯。其主要針對 4 歲到 15 歲的兒童。研究探討與未接受篩檢的兒童相比，於學校接受篩檢兒童的口腔健康和牙科就診率。有些研究甚至比較了用不同的篩檢方式和不同形式的後續追蹤（例如建議信或轉介）。
我們不知道傳統的學校牙科篩檢是否會提高牙科看診率。基於特定標準（例如：未在牙醫註冊的兒童）進行審查的研究指出，在提高牙科的看診率方面，可能比沒有進行篩檢更有效。在標準的篩檢和普遍在提高牙科就診率的審查方面差別不大，雖然這對結果充滿了不確定。
給家長的客製化或特定轉介信可能比非特定轉介信更能提高牙科就診率，但我們對結果非常不確定。
與單獨篩檢相比，增加誘因（健康教育和提供免費治療）的篩檢或許會提高牙科就診率，但同樣對結果也存在著不確定性。
在一項比較不同轉介信（或多或少有關牙科疾病的資訊）的研究發現，在改善兒童牙科治療方面，兩者都不比另一種更好。
與一般建議去看牙醫的轉介信相比，一封具體的轉介信並不會鼓勵更多的父母帶孩子去看牙醫。
這八項研究皆在兒童接受篩檢後僅追蹤 3~11 個月。因此，我們不知道篩檢在較長時間的影響。
沒有一項研究能夠確認查篩檢計劃是否有負面影響或所需的花費。
本文獻最新的更新日期為何？
我們搜索截至 2021 年 10 月 15 日發表的研究報告。
Authors' conclusions
Summary of findings
| Traditional screening versus no screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| Without screening | With traditional screening | |||||
| Dental attendance | Data not pooled
| 6281 | ⊕⊝⊝⊝ | There was substantial heterogeneity, in part due to study design (3 cluster‐RCTs and 1 individually randomised trial). We are unable to draw conclusions about this comparison. | ||
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| CI: confidence interval; RCT: randomised controlled trial. | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to unclear risk of bias. | ||||||
| Criteria‐based screening versus no screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| No screening | With criteria ‐based screening | |||||
| Dental attendance Follow‐up: 3–4 months | 331 per 1000 | 355 per 1000 | RR 1.07 | 4980 | ⊕⊕⊝⊝ | There may be a 7% relative increase in dental attendance in criteria‐based screening group compared to no screening group, with the 95% CI ranging from 1% decrease to 16% increase. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to imprecision. | ||||||
| Criteria‐based screening versus traditional screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With traditional screening | With criteria‐based screening | |||||
| Dental attendance Follow‐up: 3–4 months | 335 per 1000 | 338 per 1000 | RR 1.01 | 5316 | ⊕⊝⊝⊝ | Criteria‐based screening may have little or no effect on dental attendance compared to traditional screening, with the 95% CI ranging from 6% decrease to 8% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to inconsistency. | ||||||
| Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With criteria‐based screening and non‐specific referral | With criteria‐based screening and specific referral | |||||
| Dental attendance at general dentist Follow‐up: mean 8 months | 490 per 1000 | 687 per 1000 (534 to 867) | RR 1.39 | 201 | ⊕⊝⊝⊝ | There may be a 39% relative increase in attendance at general dentist in the specific referral group compared to non‐specific group, with the 95% CI ranging from 9% to 77% increase in attendance. |
| Dental attendance at orthodontist | 194 per 1000 | 368 per 1000 (229 to 593) | RR 1.90 | 201 | ⊕⊝⊝⊝ | There may be a 90% relative increase in the attendance at orthodontist in the specific referral group compared to the non‐specific group, with the 95% CI ranging from 18% to 206% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded one level due to unclear risk of bias. | ||||||
| Traditional screening with motivation versus traditional screening alone | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With traditional screening | With traditional screening plus motivation | |||||
| Dental attendance | 100 per 1000 | 308 per 1000 | RR 3.08 | 2486 | ⊕⊝⊝⊝ | There may be a 208% relative increase in the attendance of the motivation group compared to control group, with the 95% CI ranging from 157% to 271% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| CSM referral letter versus standard referral letter | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With standard referral letter | With CSM referral letter | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 382 per 1000 | 375 per 1000 | OR 0.97 | 388 | ⊕⊝⊝⊝ | There may be little or no effect in the odds of getting necessary dental care with a standard referral letter compared to one based on the CSM of self‐regulation; the 95% CI ranged from 38% decrease to 50% increase in dental care. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| Referral to specific dental treatment facility versus letter advising parents to take their child to a dentist | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Risk with advice letter to see a dentist | Risk with referral to specific treating facility | |||||
| Dental attendance | 43 per 1000 | 39 per 1000 | RR 0.91 | 362 | ⊕⊝⊝⊝ | There may be little or no effect in dental attendance in the specific referral group compared to the generic advice letter group, with the 95% CI ranging from a 66% decrease to a 147% increase. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
Background
Description of the condition
This is an update of a review first published in December 2017 (Arora 2017a).
Oral health is essential to general health, well‐being and quality of life (WHO 2003). The World Health Organization (WHO) defines it as "a state of being free from mouth and facial pain, oral and throat cancer, oral infection and sores, periodontal (gum) disease, tooth decay, tooth loss, other diseases and disorders that limit an individual's capacity in biting, chewing, smiling, speaking, and psychosocial well being" (WHO 2003).
The importance of children's oral health cannot be overestimated (Manton 2018), as oral diseases, including dental caries, are progressive and cumulative. Availability of services does not always translate to use of services. One national health survey carried out in the USA found that less than half of people aged 21 years or under used dental care in 2009, and only 14.2% used preventive dental services (CDC 2014).
Unrecognised disease and postponed care exacerbate oral and dental problems, leading to pain, discomfort and sometimes irreversible damage. Poor oral health significantly affects children's nutritional intake and consequently their general health, growth and development. The psychosocial impacts can be considerable, and include interference with daily activities, sleeping pattern, quality of life and parental output (AAPD 2008). Poor oral health in children may impede learning, activity and interactions with peers at school (WHO 2003). Such problems are compounded among children from deprived communities (Tickle 1999a; Newacheck 2000; Edelstein 2002; Public Health England 2020). Some of the oral diseases that affect children worldwide are described below.
Dental caries continues to be a common chronic childhood disease. Dental caries prevalence in 5‐year‐old children, as measured by Public Health England with the National Dental Epidemiology Programme survey in 2018 to 2019, was 23.4%, with an average of 3.4 decayed, missing or filled teeth in those who have decay experience (Public Health England 2020). According to data from the Montana Department of Public Health and Human Services, in the 2015 to 2016 school year, 14.2% of children screened in the 3‐ to 5‐year age group had untreated decay (Montana 2016). A recent study in India found that prevalence of caries is higher in the primary dentition than in the permanent dentition in children aged 5 to 12 years (Prabakar 2020). Over 50% of children aged 5 to 9 years in the USA experience tooth decay in primary dentition, and this figure is above 90% in some low‐ and middle‐income countries (Bagramian 2009). These findings demonstrate that dental caries is a present‐day public health crisis (Petersen 2003).
Several gingival diseases also affect children and adolescents with varying rates and severity. The prevalence of gingivitis has been estimated at 73% among school children between 6 and 11 years of age in Iran (Ketabi 2006). Similarly, the prevalence of gingivitis reported in sample of adolescents from Greece was 72.8% (Chrysanthakopoulos 2016). A recent study in India that aimed to measure the association between caries and gingivitis in children aged five to six years reported an 18.3% prevalence of gingivitis (Mahatani 2020).
Developmental defects of enamel have a significant impact on oral health and aesthetics in both primary and permanent dentition. Most epidemiological studies show that the frequency of appearance of these defects is on the rise in almost all populations (Robles 2013). It is of high clinical significance when dentine or pulp involvement ensues due to significant enamel loss or high susceptibility to caries (Pitts 2015).
Dental and facial trauma of varying intensity affects children. One systematic review published in 2015 reported a prevalence of dental trauma in children and adolescents (under 18 years of age) of 17.5%, with variation among different geographic regions (Azami‐Aghdash 2015). Timely intervention may alleviate future complications in children with dental trauma.
A study conducted in Xian (China) found a high prevalence of malocclusion in children with primary dentition (66.3%; Zhou 2016). Identification of modifiable factors that can be addressed through preventive and interceptive orthodontics can save elaborate and expensive treatments later (Pruthi 2013).
Oral diseases impose considerable financial, social and personal burdens. In 2015, the global economic burden of dental diseases for a year amounted to USD 442 billion, including both direct treatment costs and indirect costs in terms of productivity losses owing to absenteeism at school and work (Listl 2015). Advanced disease may necessitate more complex and costly treatments such as root canal therapies, extractions or treatment under general anaesthesia (WHO 2003; Australian Institute of Health 2013). The World Dental Federation (FDI) calls for global action on oral diseases, highlighting the substantial burden on individuals and communities as a result of pain and suffering, impairment of function and reduced quality of life (FDI 2015).
Description of the intervention
School dental screening (or 'oral health/dental examination', 'dental assessment', 'dental certificates', 'dental check‐up') refers to a brief visual examination of the oral cavity of children carried out in a school setting (Tickle 1999b; AAPD 2008; Irish Guideline 2012; Janakiram 2016). Parents then receive information on their child's oral health status and treatment needs. Follow‐up methods can be categorised as:
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conventional methods (i.e. sending a referral card, information letter or consent form (Hebbal 2005; Milsom 2006));
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additional methods, such as phone call reminders and incentives (Reiss 1982), or intensive follow‐up by means of personalised letters (Zarod 1992).
The focus of a school dental screening programme is not merely to identify children with oral health problems, but also to act as a vehicle to bring these children into contact with oral health services (Donaldson 2001; Morgan 2013). It is imperative to follow up screened children to measure the effectiveness of screening in terms of increased uptake of services, for example, registration with a dentist and dental attendance (Zarod 1992; NHS 2000; Milsom 2006; Cunningham 2009; Alayadi 2021).
Hence, the objective of screening is twofold, namely:
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to identify screen‐positive cases; and
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to ensure these cases are followed‐up for appropriate management.
School dental screening is usually a part of school health services and its model, process and objectives vary depending on the individual healthcare delivery policies of each country (Jenner 1986; Milsom 1995; Tickle 1999b; Donaldson 2001; AAPD 2008; Irish Guideline 2012). Programmes can be broadly classified based on the following criteria.
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Personnel involved
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Dentist (Milsom 2006)
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Dentally‐qualified health professionals such as dental hygienists (Locker 2004), or dental nurses (Morgan 2013)
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Health professionals qualified in areas other than dentistry, such as doctors (Bader 2004; Rowan‐Legg 2013)
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Methods used
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Exclusively visual screening (Tantawi 2015)
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Visual screening with tongue blade (Tantawi 2015)
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Mouth mirror and probe (Tantawi 2015)
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Criteria‐based screening (referral of children on the basis of pre‐established checklist of criteria) versus traditional screening (referral based on the screening dentist's opinion) (Milsom 1999; Kearney‐Mitchell 2006)
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Targeted screening (for a specified or high‐risk population; Locker 2004; Chong 2011) versus universal screening (for all children in a population or subpopulation; Milsom 2006)
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Compulsory screening at school entry (AAPD 2008; Irish Guideline 2012) versus optional screening (Hebbal 2005)
The effectiveness of school dental screening depends on adequate follow‐up and treatment. Treatment services may be:
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provided within school premises (screening and treatment services operate as single or linked entity; Irish Guideline 2012); or
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facilitated outside school premises (screening and treatment services function as distinct entities; Milsom 2006).
The literature suggests that children belonging to lower‐income groups and children without dental insurance are less likely to visit the dentist (California HealthCare Foundation 2008). Hence, school dental screening outcomes may depend on whether cost of treatment is:
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charged to parents;
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subsidised; or
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free (Milsom 2006).
Figure 1 illustrates a schema of post‐screening referral and treatment processes.
A schema of school dental screening process.
How the intervention might work
Regular oral health assessment is imperative for protecting, improving and promoting children's oral health. Early diagnosis of oral conditions is crucial for avoiding short‐term complications and long‐term effects of advanced disease. School dental screening aims to detect and intercept disease before the child would normally present for treatment, and make children and parents aware of the condition and its future complications.
A school dental check‐up programme in Australia demonstrated screening as a less costly and more effective intervention than the standard of care (Nguyen 2017). This reinforces the evidence that reductions in morbidity achieved through screening imply potential cost benefits, both in terms of reduced treatment costs and productivity losses (Listl 2015). Targeting individuals at higher risk may increase cost‐effectiveness (Manton 2018).
The school provides an ideal setting for oral health screening in children. The benefits of early diagnosis and intervention can be reaped for sustainable oral health all through these years and into adulthood. WHO endorses school dental screening as an efficient and effective way to reach over one billion children worldwide; and through them, families and communities (WHO 2003).
Why it is important to do this review
School dental screening is one of the most debated aspects of healthcare systems, public health practices and health policy discussions (Janakiram 2016). The literature presents contrasting and contradictory results.
Some studies suggest that screening is an effective public health measure (Zarod 1992; Donaldson 2001; Hebbal 2005). One 1994 trial reported that personalised referral letters stimulate greater dental attendance than non‐specific referral letters (Burden 1994). A more recent study suggested that vigorous follow‐up of children may lead to improved dental attendance rates, although the acceptability to parents and the cost‐effectiveness of putting significant resources into elaborate follow‐up procedures would need to be scientifically assured (Praveen 2014).
In contrast, large cluster‐randomised trials carried out in the UK did not demonstrate that school dental screening was effective at reducing untreated dental caries (Milsom 2006). Additional analyses of data from these trials suggested that screening also failed to produce worthwhile benefits for the screen‐positive population, as less than half of these children attended the dentist; and of those who did attend, less than a quarter received appropriate treatment. Similarly, a cluster‐randomised trial conducted in Scotland showed that school dental screening did not increase registration at the dentist in a group of 12‐ to 13‐year‐old children (Cunningham 2009). Some authors consider that school dental screening as a public health practice is motivated more by politics than by science, because, despite the strong emphasis of policy‐makers on the importance of this intervention, and despite the heavy expenditure in terms of financial and manpower resources, there is a lack of clear evidence to demonstrate that this process is effective in improving the oral health of the population (Tickle 1999b; Threlfall 2006; Rodgers 2007; Milsom 2008).
This is the second update of a review originally published in December 2017 and first updated in August 2019. It synthesises the evidence regarding the effectiveness of school dental screening programmes for improving oral health. Analysis of the existing literature may help to identify factors that influence the successful provision of school dental screening. We hope that our results can aid government policy‐makers, programme planners at various levels, and administrators in health and education sectors to tailor appropriate school dental health programmes, benefiting the community without unnecessarily burdening fiscal sectors. This review will also be relevant to general dental practitioners, paediatric dentists and oral health promotion teams; and will be of interest to parents, teachers and all those involved in working with children.
Objectives
To assess the effectiveness of school dental screening programmes on overall oral health status and use of dental services.
Methods
Criteria for considering studies for this review
Types of studies
We included randomised controlled trials (RCTs) where the unit of randomisation was a group of children (clustered by school or class, or both) or the individual child.
Types of participants
Eligible studies included children or adolescents (aged 3 to 19 years) attending a school in any country. Participants could have primary, permanent or mixed dentition.
Inclusion was independent of level of dental disease or dental caries at the start of the study, current dental treatment, dentist attendance levels and nationality. We included studies regardless of whether dentists, dental nurses or dental hygienists performed the visual inspection of the child's oral cavity. Given the focus of this review, we excluded studies that were not predominantly carried out in a school setting.
Types of interventions
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School dental screening versus placebo or no screening
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School dental screening A versus B (where A and B refer to different types of screening based on the classification presented above)
Exclusion criteria
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Screening without a specified follow‐up plan or with follow‐up period shorter than three months
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Oral health assessment programmes for children attending special schools
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Dental examination performed by personnel other than those licensed or trained in the process as per state laws (e.g. school teachers, medical practitioners)
Types of outcome measures
We assessed all primary and secondary outcome measures based on duration as follows.
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Short‐term effects (minimum follow‐up of three months up to two years; NICE guideline 2004)
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Long‐term effects (follow‐up of more than two years; Irish Guideline 2012)
Primary outcomes
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Dental attendance (registration and follow‐up dental appointments)
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Proportion of children with treated and untreated caries
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Proportion of children with other treated and untreated oral health needs (e.g. malocclusion, trauma)
Secondary outcomes
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Caries, measured by any validated index (in primary and permanent teeth separately)
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Gingivitis measured by any validated index
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Developmental defects of enamel measured by any validated index
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Malocclusion or orthodontic treatment needs, measured by any validated index
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Trauma to teeth measured by any validated index
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Cost‐effectiveness
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Adverse events
Search methods for identification of studies
Cochrane Oral Health's Information Specialist conducted systematic searches for RCTs and controlled clinical trials (CCTs). Because CENTRAL is updated monthly with newly published RCTs indexed in Embase and other databases, we restricted our search of Embase to the past six years. We applied no other publication date restrictions, and no language restrictions, when searching the electronic databases.
Electronic searches
Cochrane Oral Health's Information Specialist searched the following electronic databases.
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Cochrane Oral Health's Trials Register (searched 15 October 2021; Appendix 1).
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Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Register of Studies (Issue 9, 2021, searched 15 October 2021; Appendix 2).
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MEDLINE Ovid (1946 to 15 October 2021; Appendix 3).
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Embase Ovid (15 September 2016 to 15 October 2021; Appendix 4).
Subject strategies were modelled on the search strategy designed for MEDLINE Ovid. Where appropriate, they were combined with subject strategy adaptations of the highly sensitive search strategies designed by Cochrane for identifying RCTs and CCTs, as described in the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2022).
Searching other resources
We searched the following trial registries.
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US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (clinicaltrials.gov; searched 15 October 2021; Appendix 5)
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World Health Organization International Clinical Trials Registry Platform (apps.who.int/trialsearch; searched 15 October 2021; Appendix 6)
We searched the reference lists of included studies and relevant systematic reviews for further studies.
We checked that none of the included studies in this review were retracted due to error or fraud.
We did not perform a separate search for adverse effects of interventions used, considering only the adverse effects described in included studies.
Data collection and analysis
Selection of studies
Two review authors (AA, SK) independently screened the titles and abstracts recovered by the electronic searches and eliminated obviously ineligible studies. The search was designed to be sensitive and include CCTs; these were filtered out early in the selection process if they were not randomised. We obtained the full‐text copies of all potentially eligible studies, and two review authors (EP, SKN) read through them to identify the studies that met all our inclusion criteria. These two review authors resolved any disagreements by discussion, consulting a third author (NMI), if necessary, to reach consensus. We recorded all studies that reached the full‐text assessment stage but did not meet our inclusion criteria in the Characteristics of excluded studies table, noting the reason for exclusion. We assessed articles in languages other than English by their abstracts, where possible, and translated the full text of articles we considered potentially eligible.
Data extraction and management
Two review authors (AA and SKN) independently extracted the data from each trial. They were not blinded to the authors of the included studies. We resolved any disagreement by discussion or by consulting a third review author (NMI). We extracted the data using a customised data extraction form, which we designed following the guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We entered the study details in the Characteristics of included studies table in Review Manager 5 (RevMan 5; Review Manager 2014).
We recorded the following details for each included trial.
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Publication details such as year of publication, language
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Country of origin
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Details of participants, including demographic characteristics
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Trial characteristics (sample size; method of randomisation; allocation concealment; blinding; method of assessing the outcomes; and dropouts, if any)
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Type of intervention and comparison
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Details of the outcomes reported
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Duration of follow‐up
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Location and costs of follow‐up appointments
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Results of the intervention
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Funding details
We contacted the authors of included studies when we needed clarification of details or any additional data, via email whenever possible.
Assessment of risk of bias in included studies
Two review authors (SKN and AA) independently assessed the risk of bias in the included trials in the following domains.
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Random sequence generation (selection bias)
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Allocation concealment (selection bias)
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Blinding of participants and personnel (performance bias)
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Blinding of outcome assessment (detection bias)
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Incomplete outcome data (attrition bias)
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Selective outcome reporting (reporting bias)
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Risk of bias specific to cluster‐randomised trials
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Other biases
For each of these domains, we judged whether each study was at 'high', 'low' or 'unclear', risk of bias, following the guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We contacted the trial authors if details were missing from the publications or were unclear. We resolved disagreements through consensus. We recorded our judgements and justifications in risk of bias tables for each included study and generated a risk of bias summary graph and figure. We used these judgements when grading the overall certainty of evidence for each comparison and outcome in the summary of findings tables. We summarised the risk of bias according to the recommendations in the Cochrane Handbook for Systematic Reviews of Interventions as follows (Higgins 2011b).
| Risk of bias | Interpretation | Within study | Across studies |
|---|---|---|---|
| Low risk of bias | Plausible bias unlikely to seriously alter the results | Low risk of bias for all key domains | Most information is from studies at low risk of bias. |
| Unclear risk of bias | Plausible bias that raises some doubt about the results | Unclear risk of bias for one or more key domains | Most information is from studies at low or unclear risk of bias. |
| High risk of bias | Plausible bias that seriously weakens confidence in the results | High risk of bias for one or more key domains | The proportion of information from studies at high risk of bias is sufficient to affect the interpretation of results. |
Measures of treatment effect
For dichotomous outcomes, such as dental attendance, we used the number of events per arm and calculated risk ratios (RRs) with 95% confidence intervals (CIs). For receipt of dental care, we calculated odds ratios (ORs); however, receipt of dental care is a surrogate measure as it does not directly equate to completion of treatment in the children thereafter.
For continuous outcomes, we intended to use means and standard deviations (SDs) presented in the studies to calculate mean differences (MDs) and CIs. We intended to use standardised mean difference (SMD) if studies used different scales to measure the same outcome. If data were expressed on shorter ordinal scales, we intended to explore the possibility of converting them to dichotomous outcomes. If data were expressed on long ordinal scales, we intended to analyse them as continuous data. If outcomes had been reported both at baseline and at follow‐up or at trial endpoints, we would have used end scores, as they are the most commonly reported. However, we did not find any such data.
Unit of analysis issues
We encountered two types of non‐standard study designs in this review.
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Repeated observations on participants
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Cluster‐randomised trials
In cases of repeated observations on participants for our primary outcomes, we followed the method described in section 9.3.4 of the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2011).
In cluster‐randomised trials, we handled the data following the method described in section 16.3 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011c). In cluster‐randomised trials, the unit of analysis was the cluster.
In trials where adverse effects were described as counts, we intended to follow the method described in Section 9.2.5 of the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2011). However, we did not find any such data.
Dealing with missing data
We intended to use the methods in section 16.1.2 of the Cochrane Handbook for Systematic Reviews of Interventions to estimate missing standard deviations (Higgins 2011c). However, no trials included in our review had missing standard deviations. We contacted trial authors to try to obtain the missing intracluster correlation coefficient (ICC).
Assessment of heterogeneity
In meta‐analyses, we assessed the heterogeneity using a Chi² test, where a P value less than 0.1 indicates statistically significant heterogeneity. We quantified heterogeneity using the I² statistic as follows (Higgins 2003).
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0% to 40% implies slight heterogeneity.
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30% to 60% implies moderate heterogeneity.
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50% to 90% implies substantial heterogeneity.
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75% to 100% implies very substantial ('considerable') heterogeneity.
If we had found very substantial heterogeneity (I² > 75%) that could not be explained by the subgroup analyses, we would not have conducted the meta‐analysis. However, we did not encounter this situation.
Assessment of reporting biases
If we had included more than 10 studies in a meta‐analysis, we would have assessed the possible presence of reporting bias by testing for asymmetry in a funnel plot. If present, we planned to carry out a statistical analysis using the methods described in section 10.4.3.1 of the Cochrane Handbook for Systematic Reviews of Interventions (Sterne 2011).
Data synthesis
We analysed the data using RevMan 5 (Review Manager 2014). We meta‐analysed the data available from studies with similar comparisons and outcomes, using a random‐effects model. With this approach, the confidence intervals for the average intervention effect were wider than those obtained using a fixed‐effect approach, leading to a more conservative interpretation. For data synthesis of dichotomous data, we used RRs for attendance and ORs for receipt of dental care. For continuous data, we used end scores when available.
Subgroup analysis and investigation of heterogeneity
Had there been significant heterogeneity, we would have explored the reasons by performing the following subgroup analyses.
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Age group (age 3 to 5 years, 6 to 12 years, 13 to 19 years; WHO 2013)
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Targeted or universal screening
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Participants offered post‐screening treatment within the school setting or referred for treatment outside the school setting
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Treatment charges borne by parents: full charge; subsidised costs; no cost
However, we did not find enough trials to perform subgroup analysis.
Sensitivity analysis
Had there been sufficient included studies, we would have performed the following sensitivity analyses.
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Including only studies at low risk of bias
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Using the fixed‐effect model for meta‐analysis
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Using different ICC estimates where these values were missing in studies
Summary of findings and assessment of the certainty of the evidence
We used the GRADE approach to interpret findings (Schünemann 2011). We used GRADE Profiler software (GRADEpro GDT), and imported data from RevMan 5 (Review Manager 2014), to create summary of findings tables for the main comparisons and outcomes (receipt of dental care/proportion of children treated for dental caries, dental attendance). We had not planned for prioritisation of the comparisons in our protocol (Arora 2017b). As we had nine comparisons in total, we undertook a prioritisation exercise. The lead review author requested that the other review authors score the comparisons independently (1 to 9, where 1 was most important and 9 was the least important). Based on the combined score, we prioritised seven comparisons for presentation as summary of findings tables. We presented two other comparisons in additional tables.
The summary of findings tables provide information concerning the overall certainty of the evidence from the trials, the magnitude of effect of the interventions examined and the sum of available data on the key outcomes. The GRADE approach considers 'certainty' to be a judgement of the extent to which we can be confident that the estimates of effect are correct (Schünemann 2011). We initially graded each body of evidence from RCTs as high certainty, then downgraded it by one, two or three levels depending on the following five considerations.
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Limitations in the design of the studies
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Indirectness (or applicability) of the evidence
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Inconsistency of results
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Imprecision of the results
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Possibility of publication bias
A certainty level of 'high' means we are very confident that the true effect lies close to that of the estimate of the effect for an outcome. A judgement of 'moderate' certainty indicates that the true effect is likely to be close to the estimate of the effect, but acknowledges the possibility that it could be substantially different. 'Low' and 'very low' certainty evidence limit our confidence in the effect estimate (Balshem 2011).
Results
Description of studies
Results of the search
Our search strategies recovered 3749 records from the electronic databases, and we found another two records by cross‐referencing included trials and other systematic reviews. After deduplication, we had 2709 records, of which we eliminated 2679 through title and abstract screening. We obtained full‐text copies of the 30 remaining records. Two review authors (EP, SKN) independently assessed all of these papers to determine their eligibility, excluding 17 reports from completed studies and one report from an ongoing study. Eight studies (12 reports) met our inclusion criteria (Zarod 1992; Burden 1994; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Nelson 2019; Alayadi 2021). One of these had been included in the previous version of this review as an ongoing study, and had since been published (Alayadi 2021). The Characteristics of included studies and Characteristics of excluded studies tables provide details of the studies we examined and the reasons for inclusion or exclusion. Figure 2 shows the flow of studies.
Study flow diagram.
We contacted authors of six included trials but only received clarifications on Alayadi 2021 (see Characteristics of included studies).
Included studies
See Characteristics of included studies table.
Characteristics of the trial settings and investigators
We included eight trials (12 reports) in the review. All were in the English language. The trials were set in the UK (Zarod 1992; Burden 1994; Milsom 2006; Cunningham 2009), India (Hebbal 2005; Praveen 2014), the USA (Nelson 2019) and Saudi Arabia (Alayadi 2021).
All trials were conducted in a school setting. Six were cluster‐randomised trials (Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Nelson 2019; Alayadi 2021), and two were individually randomised trials (Zarod 1992; Burden 1994).
Of the eight trials, five provided grant information: two had received funding from the UK National Health Service (Milsom 2006; Cunningham 2009), one from the Royal College of Physicians and Surgeons of Glasgow, Scotland (Burden 1994), one from the National Institutes of Health (Nelson 2019) and one from the Saudi Cultural Bureau of London (Alayadi 2021).
Characteristics of the participants
All eight trials included both boys and girls.
The minimum age of participants was four years (Zarod 1992), and the maximum age was 15 years (Hebbal 2005). Two studies included both primary and secondary school children, so the age ranges were wide (6 to 15 years in Hebbal 2005; 6 to 13 years in Praveen 2014). Nelson 2019 recruited elementary school children aged 5 to 10 years, and Alayadi 2021 included primary school children aged 6 to 11 years. The age ranges were more restricted in Zarod 1992 (four to six years), Milsom 2006 (six to eight years), Burden 1994 (11 to 12 years) and Cunningham 2009 (12 to 13 years).
The minimum sample size was 201 children (Burden 1994); and the maximum sample size was 16,864 children in 168 clusters (Milsom 2006).
Characteristics of the interventions
The eight trials evaluated screening versus no screening or compared screening variables (e.g. different criteria for screening, different adjuncts to screening or different types of referral letter after screening).
1. Traditional screening versus no screening
In 'traditional screening', the inspecting dental professional provides a referral card if they consider that the child needs to attend a dentist.
Two four‐arm cluster‐RCTs (Milsom 2006; Cunningham 2009), and one two‐arm cluster‐RCT (Praveen 2014) compared traditional screening to no screening. Zarod 1992 randomised individual participants to one of two arms: traditional screening or screening without any referral. We consider the control group in this trial to be comparable to a no‐screening control, as the parents received no information on their children's oral health.
2. Criteria‐based screening versus no screening
In criteria‐based screening, the dental professional has pre‐established criteria for referring a child to a dentist. Two four‐arm cluster‐RCTs compared criterial based screening to no screening (Milsom 2006; Cunningham 2009).
3. Criteria‐based screening compared to traditional screening
Milsom 2006 and Cunningham 2009 compared referral based on pre‐established criteria with referral based on the opinion of the dental professional.
4. Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral
One individually randomised trial compared different referral letters for increasing attendance at dental and orthodontic clinics (Burden 1994). The specific referral letter in the intervention group advised parents to seek advice about treatment to straighten their child's teeth, while the control group was given a referral letter with non‐specific advice to attend a dentist.
5. Traditional screening with motivation versus traditional screening alone
Hebbal 2005 compared the effects of screening supplemented with oral health motivation or education sessions versus screening and referral alone. The traditional screening with motivation also included an offer of free treatment.
6. Common‐sense model referral letter plus dental information guide versus standard referral letter
The common‐sense model (CSM) is a self‐regulatory framework that outlines how an individual's cognitive and emotional perception of their chronic illness guides their coping and action planning to self‐manage the disease (key constructs: identity, cause, consequence, timeline, control). The dental information guide (DIG) is a pictographic brochure providing facts and myths about dental caries, information on making dental appointments, Medicaid access, transportation, and a list of dentists in the area. The standard referral letter was based on guidelines for oral health screening in Ohio schools and was consistent with others used across the country.
Nelson 2019 evaluated the CSM referral letter plus dental information guide compared to the standard referral letter. The information provided to parents in the intervention group communicated the importance of primary teeth having no cavities to protect permanent teeth, and explained that caries is a chronic rather than an acute disease.
7. Common‐sense model referral letter versus standard referral letter
Nelson 2019 also evaluated the CSM referral letter alone (without dental information guide) compared to a standard referral letter.
8. Common‐sense model referral letter plus dental information guide versus common‐sense model referral letter alone
Nelson 2019 also evaluated the CSM referral letter plus dental information guide compared to the CSM referral letter alone.
9. Referral to specific treatment facility versus generic advice letter to see a dentist
Alayadi 2021 compared the effects of referral to a specific treatment facility (i.e. parents of screen‐positive children were referred to the dental college hospital) versus an advice letter to see a dentist (i.e. parents of screen‐positive children received a letter informing them of their child's dental status and advising them to take their child to the dentist).
Outcomes
We planned to analyse outcome measures based on the definition of follow‐up duration as short‐term (minimum follow‐up of three months to two years) and long‐term (follow‐up of more than two years). However, the follow‐up period of all included trials was shorter than two years, hence we reported only short‐term effects of school dental screening.
Seven trials used attendance at a dental clinic (general dental practitioner) as a primary outcome (Zarod 1992; Burden 1994; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Alayadi 2021). Burden 1994 measured attendance at a general dental clinic as well as at a specialist orthodontist.
Nelson 2019 measured receipt of dental care as the primary outcome. We considered this a surrogate outcome, as 'receipt of care' does not necessarily equate to completion of required dental treatment. Nelson 2019 referred to secondary outcomes but did not provide results for these.
Milsom 2006 measured change in prevalence of dental caries per child as the primary outcome. Secondary outcomes were sepsis, plaque or calculus and trauma to the permanent incisor teeth. A secondary report further followed up the children who attended the dentist, and measured the treatment these children received.
Alayadi 2021 measured change in decayed primary and permanent teeth (overall dental status) as the primary outcome. Secondary outcomes were change in decayed primary teeth, change in decayed permanent teeth and change in proportion of children who visited the dentist (dental attendance).
Intracluster correlation coefficient and data adjustment to minimise clustering effect
Two studies reported the value of ICC for dental caries (Milsom 2006; Alayadi 2021). Both studies reported the same ICC (0.03), which we used to calculate the effect estimate for dental attendance for other cluster‐randomised trials in this review. We adjusted the data to minimise clustering effect (Adam 2005; see Table 1).
| Data values for total number and events to be divided by effect estimate across all studies Effect estimate: 1 + (M − 1)ICC M = average cluster size ICC = 0.03 (borrowed from Milsom 2006) | Group | Total number of participants (original) | Total number of participants (adjusted) | Events ‒ original (children attending dental clinic) | Events ‒ adjusted (children attending dental clinic) |
| 1 + (15 − 1).03 = 1.42 | Control arm | 819 | 577 | 129 | 91 |
| Traditional arm | 1175 | 827 | 165 | 116 | |
| Criteria‐based arm | 958 | 675 | 151 | 107 | |
| 1 + (42 − 1).03 = 2.23 | Control arm | 4226 | 1895 | 1624 | 728 |
| Traditional arm | 4418 | 1981 | 1838 | 824 | |
| Criteria‐based arm | 4087 | 1833 | 1695 | 760 | |
| 1 + (8 − 1).03 = 1.21 | Contol arm | 300 | 248 | 80 | 67 |
| Intervention arm | 300 | 248 | 54 | 45 | |
| 1 + (69‐1).03 = 3.04 | Control arm | 561 | 185 | 24 | 8 |
| Intervention arm | 537 | 177 | 22 | 7 |
ICC: intracluster correlation coefficient
Excluded studies
We excluded 17 studies (see Characteristics of excluded studies table). Six were not RCTs, and five were oral health promotion trials rather than screening trials.
One trial was in abstract form (Baglee 2000), and another did not explain if participants were divided randomly into intervention or control groups (Binder 1973).
Of the remaining four RCTs, one did not send a communication to parents after screening (Rodgers 2007); two did not investigate use of services or reduction of disease after screening (Locker 2004; Tantawi 2015); and one had a follow‐up period shorter than three months (Donaldson 2001).
Risk of bias in included studies
We documented the risk of bias of included studies based on the full‐text articles. Wherever there was a need for clarification, we tried to contact the study authors. Based on the available data, we assessed the risk of bias as low, high or unclear.
We assessed two trials at low overall risk of bias (Milsom 2006; Cunningham 2009); three at high overall risk (Hebbal 2005; Nelson 2019; Alayadi 2021); and three at unclear overall risk (Zarod 1992; Burden 1994; Praveen 2014).
See the risk of bias tables within the Characteristics of included studies table for further details. For a graphical summary, see Figure 3 and Figure 4.
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Allocation
Only four trials adequately reported the method of sequence generation (Milsom 2006; Cunningham 2009: Nelson 2019; Alayadi 2021); and five adequately reported concealment of allocation (Burden 1994; Milsom 2006; Cunningham 2009; Nelson 2019; Alayadi 2021). Four studies were at unclear risk of selection bias (Zarod 1992; Burden 1994; Hebbal 2005; Praveen 2014).
Blinding
Zarod 1992 and Praveen 2014 did not report blinding of participants and personnel; therefore, we considered them at unclear risk of performance and detection bias. Hebbal 2005 and Alayadi 2021 did not blind participants (high risk of performance bias). Alayadi 2021 measured dental attendance through self‐reported questionnaire (high risk of detection bias); whereas Hebbal 2005 used a computer program to assess the main outcome 'dental attendance' (low risk of detection bias). Four trials blinded participants and assessors (low risk of performance or detection bias; Burden 1994; Milsom 2006; Cunningham 2009; Nelson 2019).
Incomplete outcome data
In this review, not attending or not registering at a dental clinic is an outcome measure rather than attrition. Hence, we redefined attrition bias for this systematic review as 'parents not receiving call letters from school'. Based on this definition, all seven trials reporting dental attendance were at low risk of attrition bias.
Nelson 2019 reported receipt of dental care as the primary outcome. The total number of children randomised was 694, but the number analysed was 597. We categorised the risk of attrition bias as unclear.
Selective reporting
We judged two studies at unclear risk of selection bias: Nelson 2019 did not report the secondary outcomes of change in illness perception and change in behaviour intention of parents as pre‐stated in the trial registry (NCT02395120); and Alayadi 2021 stated that the follow‐up period was 12 months as per the protocol, but the reported mean follow‐up period was 11 months. The other six included trials were at low risk of reporting bias as they reported all outcomes listed in the methods section.
Other potential sources of bias
We identified no other potential sources of bias in seven trials (Zarod 1992; Burden 1994; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Alayadi 2021). We considered Nelson 2019 to be at high risk of other bias, as the participants were initially allocated to five arms, but the trial authors decided to combine the participants who received the CSM letter with those who received a reduced CSM letter; and the participants who received the CSM letter plus dental information guide with the participants who received the reduced CSM letter plus dental information guide.
Effects of interventions
See: Summary of findings 1 Traditional screening versus no screening; Summary of findings 2 Criteria‐based screening versus no screening; Summary of findings 3 Criteria‐based screening versus traditional screening; Summary of findings 4 Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral; Summary of findings 5 Traditional screening with motivation versus traditional screening alone; Summary of findings 6 Common‐sense model referral letter versus standard referral letter; Summary of findings 7 Referral to specific treatment facility versus generic advice letter to see a dentist
Seven trials presented dental attendance as the main outcome of a school dental screening intervention (Burden 1994; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Alayadi 2021) and one trial measured receipt of dental care (Nelson 2019). Two trials reported prevalence of dental caries (Milsom 2006; Alayadi 2021) and one measured trauma to the teeth (Milsom 2006).
No studies measured any of our other outcomes (proportion of children with other untreated oral health needs; gingivitis measured by any validated index; developmental defects of enamel measured by any validated index; malocclusion or orthodontic treatment needs measured by any validated index; cost‐effectiveness and adverse events), so we could not evaluate the effect of school dental screening programmes on these outcomes.
1. Traditional screening versus no screening
See summary of findings Table 1.
Four studies (three in the UK and one in India) with 6281 participants evaluated the outcome of dental attendance under the comparison of traditional screening versus no screening (Zarod 1992; Milsom 2006; Cunningham 2009; Praveen 2014). Of these, Zarod 1992 was the only individually randomised trial. The pooled I² measure for heterogeneity was substantial, possibly because we used the ICC value provided by Milsom 2006 for Cunningham 2009 and Praveen 2014, neither of which provided their ICC values. Due to this inconsistency, and unclear risk of bias, we downgraded the evidence to very low certainty, and we are unable to draw conclusions about this comparison (Analysis 1.1; Figure 5).
Forest plot of comparison: 1 Traditional screening versus no screening, outcome: 1.1 Dental attendance
Milsom 2006 measured prevalence of dental caries as mean number of teeth with active caries in primary teeth (dt) and permanent teeth (DT). However, post‐intervention changes of dt and DT from baseline were not significant, and the authors presented the data as binary outcomes of reduction from baseline (yes/no). As a result, we did not have data to conduct a meta‐analysis. Likewise, Milsom 2006 reported the prevalence of trauma to the permanent incisor teeth as a dichotomous outcome (reduction from baseline (yes/no)), and we were unable to include this data in a meta‐analysis.
2. Criteria‐based screening versus no screening
See summary of findings Table 2.
Two UK‐based trials evaluated criteria‐based screening versus no screening (Milsom 2006; Cunningham 2009). They suggested a possible small benefit for criteria‐based screening over no screening in terms of dental attendance (pooled RR 1.07, 95% CI 0.99 to 1.16; 4890 participants; low‐certainty evidence; Analysis 2.1).
For secondary outcomes, see comments on Milsom 2006 in '1. Traditional screening versus no screening' above.
3. Criteria‐based screening versus traditional screening
See summary of findings Table 3.
Two UK‐based trials evaluated criteria‐based screening versus traditional screening (Milsom 2006; Cunningham 2009). Criteria‐based screening resulted in little or no difference in dental attendance compared to traditional screening (pooled RR 1.01, 95% CI 0.94 to 1.08; 5316 participants; very low‐certainty evidence; Analysis 3.1).
For secondary outcomes, see comments on Milsom 2006 in '1. Traditional screening versus no screening' above.
4. Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral
See summary of findings Table 4.
One trial carried out in the UK evaluated criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral (Burden 1994). Criteria‐based screening with a specific referral letter can increase attendance at general dental clinics compared to criteria‐based screening with a non‐specific referral letter (RR 1.39, 95% CI 1.09 to 1.77; 201 participants; very low‐certainty evidence; Analysis 4.1), and increase attendance at orthodontic clinics (RR 1.90, 95% CI 1.18 to 3.06; 201 participants; very low‐certainty evidence; Analysis 4.1).
5. Traditional screening with motivation versus traditional screening alone
See summary of findings Table 5.
One trial carried out in India evaluated traditional screening with motivation versus traditional screening alone (Hebbal 2005). Traditional screening with motivation can increase dental attendance compared to traditional screening alone (RR 3.08, 95% CI 2.57 to 3.71; 2486 participants; very low‐certainty evidence; Analysis 5.1).
6. Common‐sense model referral letter plus dental information guide versus standard referral letter
See Table 2.
| CSM referral letter plus DIG versus standard referral letter | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With standard referral letter | With referral letter based on CSM plus DIG | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 382 per 1000 | 438 per 1000 | OR 1.26 | 395 | ⊕⊝⊝⊝ | There may be little or no difference between the two letter types in terms of their effect on the proportion of children with treated or untreated caries. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
aDowngraded two levels due to high risk of bias.
bDowngraded one level for indirectness.
cDowngraded two levels for imprecision.
One trial carried out in the USA evaluated the CSM referral letter plus dental information guide versus standard referral letter (Nelson 2019). The CSM referral letter plus dental information guide had little to no effect on the proportion of children with treated or untreated caries compared to a standard referral letter (OR 1.26, 95% CI 0.82 to 1.93; 395 participants; very low‐certainty evidence; Analysis 6.1).
7. Common‐sense model referral letter versus standard referral letter
See summary of findings Table 6.
Nelson 2019 evaluated the CSM model referral letter versus standard referral letter. The CSM referral letter had little or no effect on the proportion of children with treated or untreated caries compared to standard referral letter (OR 0.97, 95% CI 0.62 to 1.51; 388 participants; very low‐certainty evidence; Analysis 7.1).
8. Common‐sense model referral letter plus dental information guide versus common‐sense model referral letter alone
See Table 3.
| CSM referral letter plus DIG versus CSM referral letter alone | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With referral letter based on CSM | With CSM referral letter plus DIG | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 376 per 1000 | 439 per 1000 | OR 1.30 | 411 | ⊕⊝⊝⊝ | There may be little or no difference between the two letter types in terms of their effect on the proportion of children with treated or untreated caries. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
1 Downgraded by two levels due to high risk of bias.
2 Downgraded by one level for indirectness.
3 Downgraded by two levels for imprecision.
Nelson 2019 evaluated the CSM referral letter plus dental information guide versus the CSM referral letter alone. The evidence suggests that the CSM referral letter plus dental information guide had little or no effect on the proportion of children with treated or untreated caries compared to the CSM referral letter alone (OR 1.30, 95% CI 0.85 to 1.99; 411 participants; very low‐certainty evidence; Analysis 8.1).
9. Referral to specific dental treatment facility versus generic advice letter to see a dentist
See summary of findings Table 7.
One trial carried out in Saudi Arabia evaluated this comparison (Alayadi 2021). The evidence suggests that there was no difference in dental attendance between those who were referred to a specific dental treatment facility and those who received a generic advice letter (RR 0.91, 95% CI 0.34 to 2.47; very low‐certainty evidence; Analysis 9.1). Moreover, the evidence suggests that, compared to the generic advice letter, referral to a specific facility made little or no difference to number of caries in primary teeth (MD −0.20, 95% CI −0.72 to 0.32; 362 participants; very low‐certainty evidence; Analysis 9.2) or permanent teeth (MD 0.30, 95% CI −0.03 to 0.63; 362 participants; very low‐certainty evidence; Analysis 9.3).
Discussion
Summary of main results
The main objective of this review was to assess the effectiveness of school dental screening programmes on overall oral health status and use of dental services. We included eight RCTs in our review. We assessed two trials at low risk of bias, three trials at high risk of bias, and three trials at unclear risk of bias.
The outcomes reported in the included trials were dental attendance, proportion of children with untreated/treated dental caries, and caries and trauma measured by validated indices. None of the included trials reported the proportion of children with other untreated oral health needs, gingivitis, developmental defects of enamel, malocclusion or orthodontic needs, cost‐effectiveness or adverse events.
Seven included trials reported attendance or registration at the dentist as their main outcome (Zarod 1992; Burden 1994; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014; Alayadi 2021). The methods of screening interventions varied across the trials, and only four trials could be combined in meta‐analysis on the basis of common comparison of traditional screening versus no screening with dental attendance as an outcome. We combined data from these studies for the outcome 'dental attendance' and found an inconclusive result with high heterogeneity. The heterogeneity was, in part, due to study design (three cluster‐randomised trials and one individually randomised trial). Due to the inconsistency, and unclear risk of bias, we downgraded the evidence to very low certainty and were unable to draw conclusions about this comparison (see summary of findings Table 1).
Two trials compared criteria‐based screening to no screening (Milsom 2006; Cunningham 2009). They found a 7% relative increase in the dental attendance in the criteria‐based screening group compared to no screening, with 95% CI ranging from 1% decrease to 16% increase (low‐certainty evidence; see summary of findings Table 2).
The same two trials compared criteria‐based screening to traditional screening (Milsom 2006; Cunningham 2009), finding that neither was superior to the other (very low‐certainty evidence; see summary of findings Table 3).
Milsom 2006 followed up children from two arms of the trial (traditional screening and criteria‐based screening) in a prospective cohort study to describe attendance data on the basis of socioeconomic quintile. The authors also presented data on the number of children who went on to receive appropriate treatment of those who attended the dentist. This study found higher rates of referral among children from deprived quintiles compared to those from affluent quintiles in both screening arms. Moreover, children from affluent quintiles were more likely to attend the dentist when referred compared to children in the most deprived quintiles. The authors highlighted that less than a quarter of children who attend the dentist receive appropriate treatment.
Two trials used screening interventions of different designs (Burden 1994; Hebbal 2005). Burden 1994 evaluated criteria‐based screening with specific referral compared to criteria‐based screening with non‐specific referral for the outcome of attendance at dental and orthodontic clinics. It reported a 39% relative increase in attendance at dental clinics in the specific referral group compared to the non‐specific group, with a 95% CI ranging from 9% to 77% increase in attendance (very low‐certainty evidence; see summary of findings Table 4). They found a 90% relative increase in attendance at orthodontic clinics in the specific referral group compared to the non‐specific group, with a 95% CI ranging from 18% to 206% increase in attendance (very low‐certainty evidence; see summary of findings Table 4). This trial shows that specific information through a referral letter prompts more parents to take their child to visit the dentist compared to a non‐specific referral.
One cluster‐randomised trial of 4500 school children supplemented traditional screening with motivation (oral health education, offer of free treatment and motivation to parents through school authorities) and compared it with traditional screening alone (Hebbal 2005). There was a 208% relative increase in dental attendance among the motivation group compared to the control group, with 95% CI ranging from 157% to 271% increase in attendance (very low‐certainty evidence; see summary of findings Table 5). We can assume that the improved response rate in the group given oral health motivation along with screening is attributable to the motivation activities rather than to the screening process itself.
One multi‐centre trial reported proportion of children with treated or untreated caries (receipt of dental care) as the main outcome based on changes in International Caries Detection and Assessment System (ICDAS) scores during follow‐up (Nelson 2019). The trial compared different referral approaches: referral letter based on the CSM, referral letter based on the CSM plus a dental information guide, and the standard referral letter at three sites. The results show that there was no reliable evidence of one approach being superior, though the available evidence is very low certainty due to imprecision, indirectness and high risk of bias for all three comparisons (summary of findings Table 6; Table 2; Table 3).
One cluster‐randomised trial compared the effectiveness of referral to a specific treatment facility versus a generic advice letter to see a dentist (Alayadi 2021). It evaluated dental attendance, dental caries in primary teeth measured using the dt index and dental caries in permanent teeth measured using the DT index. Neither group showed superiority in terms of the proportion of children visiting a dentist. However, both groups reported a 4% increase in dental visits compared to baseline. It is not specified whether the 4% increase in dental visits related solely to children visiting the dentist who had not done so before. The study authors did not take this into consideration when calculating the results. Therefore, we analysed the data on incidence of dentist visits only. The available evidence in this trial was very low certainty due to high risk of bias, inconsistency, indirectness and imprecision (summary of findings Table 7).
As none of the studies reported cost‐effectiveness, we could not assess the cost‐benefit aspect of school dental screening. It is an important area of concern for governments and administration at various levels, as the process requires considerable investment in terms of finances and manpower, with co‐ordination of activities from healthcare and education sectors.
Overall completeness and applicability of evidence
We systematically searched for trials according to the methodology specified in our protocol. We included all RCTs that met the inclusion criteria for our review. The methods of screening and strength of referral varied considerably within and across the trials. Translators helped us with studies written in languages we do not know.
We proposed to measure short‐term and long‐term effects of screening on the primary outcomes of proportion of children with untreated dental caries, proportion of children with untreated other oral diseases and dental attendance. However, we did not find any trials with long‐term follow‐up. Seven included trials measured dental attendance and one reported the proportion of children with untreated or treated dental caries in terms of receipt of dental care. No trial reported the proportion of children with other treated or untreated oral health needs.
Amongst the secondary outcomes proposed in our review, only two trials measured prevalence of dental caries and one trial measured the prevalence of trauma to incisor teeth. One of these trials evaluated dental caries in primary teeth measured using the dt index and dental caries in permanent teeth measured using the DT index. No included trials evaluated prevalence of gingivitis, developmental defects of enamel, malocclusion or orthodontic needs, cost of screening or adverse effects.
We included in the meta‐analysis all trials with comparable methodology of screening and referral, and conducted separate analyses for arms of trials with atypical screening and referral procedures. We did not exclude any trial due to missing data. This review does not include trial arms where parents received letters or leaflets but their child did not have an oral examination, as this constitutes an oral health promotion activity rather than screening.
This review provides limited evidence on improvements in oral health or dental attendance following school dental screening. However, our findings highlight the need for further high‐quality RCTs with primary outcomes of proportion of children with active or untreated caries and other diseases, and long‐term follow‐up (more than two years) to derive definitive conclusions and recommendations.
Quality of the evidence
We assessed the body of evidence for a single commonly reported outcome (dental attendance) using the GRADE approach (GRADEpro GDT), which incorporates study limitations (risk of bias), indirectness of evidence, inconsistency of results, imprecision of the estimates, and risk of publication bias.
Four RCTs with 6281 participants compared traditional screening to no screening. We downgraded the certainty of the evidence to very low because of inconsistency, imprecision and risk of bias (summary of findings Table 1). The results do not allow us to draw a robust conclusion regarding improvement in dental attendance.
When analysing the pooled data of two trials comparing criteria‐based screening to no screening, we downgraded the certainty of evidence by two levels to low because one trial demonstrated inconsistency and the ICC for this trial was borrowed from another (summary of findings Table 2).
We assessed the certainty of evidence as very low for the comparison of criteria‐based screening versus traditional screening (summary of findings Table 3). We downgraded the level of evidence by two levels because of inconsistency in both trials and two level due to imprecision.
For the comparison of specific and non‐specific referral letters, we downgraded the certainty of the evidence to very low: two levels owing to unclear risk of selection bias and two levels due to imprecision (summary of findings Table 4).
Similarly, we downgraded the certainty of evidence for the comparison of traditional screening supplemented with motivation versus traditional screening alone (described by a single study) to very low owing to high risk of bias and imprecision (summary of findings Table 5).
We downgraded the certainty of evidence by three levels to very low for the comparisons between the CSM referral letter, with or without a dental information guide, versus a standard referral letter, owing to high risk of bias, indirectness and imprecision (summary of findings Table 6; Table 2; Table 3).
For the trial that compared groups referred to a specific dental treatment facility with groups who received a generic letter advising a visit to the dentist, we downgraded the certainty of evidence to very low because of high risk of bias, inconsistency, indirectness and imprecision (summary of findings Table 7).
Potential biases in the review process
We have taken steps to minimise bias at every stage of the review. We searched the above‐mentioned databases, conference proceedings and trial registries to include all relevant reports. We tried to contact trial authors by email for missing data. If the reports were very old, we tried to get the contact details of the authors through peer contacts, Google search, Facebook search and websites of universities or hospitals where they were previously affiliated. Nevertheless, there may be unpublished data that we were unable to trace with the described methods. We made every effort to follow the methodology stated in the protocol.
Agreements and disagreements with other studies or reviews
We found two systematic reviews that described the effectiveness of screening on improving oral health in children, based on reports from five trials each (Joury 2017; Sanjeevan 2019). These reviews found 2369 records and 875 records, respectively, based on searches to 2016, whereas we found 2709 records through our database searches to 2021. Both Joury 2017 and Sanjeevan 2019 included five similar trials (Donaldson 2001; Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014). Our review includes four of the same trials (Hebbal 2005; Milsom 2006; Cunningham 2009; Praveen 2014), but we also included Zarod 1992, Burden 1994 and the recently published trials Nelson 2019 and Alayadi 2021. We excluded Donaldson 2001 as the follow‐up period was shorter than three months.
The results of our meta‐analysis are consistent with Joury 2017, which found no evidence of improvement in dental attendance or reduction in dental caries or other diseases between 'screening' and 'no screening' groups. Sanjeevan 2019 concluded that school‐based dental screening marginally increases dental attendance (by 16%) compared to no screening (RR 1.16, 95% CI 1.11 to 1.21). They assessed the quality of the evidence as low. Sanjeevan 2019 performed subgroup analysis for Indian and Caucasian populations to investigate heterogeneity, and found more favourable results in the Indian population (RR 2.60, 95% CI 2.21 to 3.05) compared to the Caucasian population (RR 1.09, 95% CI 1.05 to 1.14). We did not conduct subgroup analyses on this criterion, and our results comparing effects of screening to those of no screening are inconsistent with Sanjeevan 2019.
A schema of school dental screening process.
Study flow diagram.
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Forest plot of comparison: 1 Traditional screening versus no screening, outcome: 1.1 Dental attendance
Comparison 1: Traditional screening versus no screening, Outcome 1: Dental attendance
Comparison 2: Criteria‐based screening versus no screening, Outcome 1: Dental attendance
Comparison 3: Criteria‐based screening versus traditional screening, Outcome 1: Dental attendance
Comparison 4: Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral, Outcome 1: Dental attendance
Comparison 5: Traditional screening with motivation versus traditional screening alone, Outcome 1: Dental attendance
Comparison 6: Common‐sense model (CSM) referral letter plus dental information guide (DIG) versus standard referral letter, Outcome 1: Receipt of dental care
Comparison 7: Common‐sense model (CSM) referral letter versus standard referral letter, Outcome 1: Receipt of dental care
Comparison 8: Common‐sense model (CSM) referral letter plus dental information guide (DIG) versus common‐sense model referral letter, Outcome 1: Receipt of dental care
Comparison 9: Referral to specific treatment facility versus advice letter to see a dentist, Outcome 1: Dental attendance
Comparison 9: Referral to specific treatment facility versus advice letter to see a dentist, Outcome 2: Caries in primary dentition
Comparison 9: Referral to specific treatment facility versus advice letter to see a dentist, Outcome 3: Caries in permanent dentition
| Traditional screening versus no screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| Without screening | With traditional screening | |||||
| Dental attendance | Data not pooled
| 6281 | ⊕⊝⊝⊝ | There was substantial heterogeneity, in part due to study design (3 cluster‐RCTs and 1 individually randomised trial). We are unable to draw conclusions about this comparison. | ||
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| CI: confidence interval; RCT: randomised controlled trial. | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to unclear risk of bias. | ||||||
| Criteria‐based screening versus no screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| No screening | With criteria ‐based screening | |||||
| Dental attendance Follow‐up: 3–4 months | 331 per 1000 | 355 per 1000 | RR 1.07 | 4980 | ⊕⊕⊝⊝ | There may be a 7% relative increase in dental attendance in criteria‐based screening group compared to no screening group, with the 95% CI ranging from 1% decrease to 16% increase. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to imprecision. | ||||||
| Criteria‐based screening versus traditional screening | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With traditional screening | With criteria‐based screening | |||||
| Dental attendance Follow‐up: 3–4 months | 335 per 1000 | 338 per 1000 | RR 1.01 | 5316 | ⊕⊝⊝⊝ | Criteria‐based screening may have little or no effect on dental attendance compared to traditional screening, with the 95% CI ranging from 6% decrease to 8% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to inconsistency. | ||||||
| Criteria‐based screening with specific referral versus criteria‐based screening with non‐specific referral | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With criteria‐based screening and non‐specific referral | With criteria‐based screening and specific referral | |||||
| Dental attendance at general dentist Follow‐up: mean 8 months | 490 per 1000 | 687 per 1000 (534 to 867) | RR 1.39 | 201 | ⊕⊝⊝⊝ | There may be a 39% relative increase in attendance at general dentist in the specific referral group compared to non‐specific group, with the 95% CI ranging from 9% to 77% increase in attendance. |
| Dental attendance at orthodontist | 194 per 1000 | 368 per 1000 (229 to 593) | RR 1.90 | 201 | ⊕⊝⊝⊝ | There may be a 90% relative increase in the attendance at orthodontist in the specific referral group compared to the non‐specific group, with the 95% CI ranging from 18% to 206% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded one level due to unclear risk of bias. | ||||||
| Traditional screening with motivation versus traditional screening alone | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants (studies) | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With traditional screening | With traditional screening plus motivation | |||||
| Dental attendance | 100 per 1000 | 308 per 1000 | RR 3.08 | 2486 | ⊕⊝⊝⊝ | There may be a 208% relative increase in the attendance of the motivation group compared to control group, with the 95% CI ranging from 157% to 271% increase in attendance. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| CSM referral letter versus standard referral letter | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With standard referral letter | With CSM referral letter | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 382 per 1000 | 375 per 1000 | OR 0.97 | 388 | ⊕⊝⊝⊝ | There may be little or no effect in the odds of getting necessary dental care with a standard referral letter compared to one based on the CSM of self‐regulation; the 95% CI ranged from 38% decrease to 50% increase in dental care. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| Referral to specific dental treatment facility versus letter advising parents to take their child to a dentist | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Risk with advice letter to see a dentist | Risk with referral to specific treating facility | |||||
| Dental attendance | 43 per 1000 | 39 per 1000 | RR 0.91 | 362 | ⊕⊝⊝⊝ | There may be little or no effect in dental attendance in the specific referral group compared to the generic advice letter group, with the 95% CI ranging from a 66% decrease to a 147% increase. |
| Proportion of children with treated/untreated caries | Not reported | |||||
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| Data values for total number and events to be divided by effect estimate across all studies Effect estimate: 1 + (M − 1)ICC M = average cluster size ICC = 0.03 (borrowed from Milsom 2006) | Group | Total number of participants (original) | Total number of participants (adjusted) | Events ‒ original (children attending dental clinic) | Events ‒ adjusted (children attending dental clinic) |
| 1 + (15 − 1).03 = 1.42 | Control arm | 819 | 577 | 129 | 91 |
| Traditional arm | 1175 | 827 | 165 | 116 | |
| Criteria‐based arm | 958 | 675 | 151 | 107 | |
| 1 + (42 − 1).03 = 2.23 | Control arm | 4226 | 1895 | 1624 | 728 |
| Traditional arm | 4418 | 1981 | 1838 | 824 | |
| Criteria‐based arm | 4087 | 1833 | 1695 | 760 | |
| 1 + (8 − 1).03 = 1.21 | Contol arm | 300 | 248 | 80 | 67 |
| Intervention arm | 300 | 248 | 54 | 45 | |
| 1 + (69‐1).03 = 3.04 | Control arm | 561 | 185 | 24 | 8 |
| Intervention arm | 537 | 177 | 22 | 7 | |
| ICC: intracluster correlation coefficient | |||||
| CSM referral letter plus DIG versus standard referral letter | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With standard referral letter | With referral letter based on CSM plus DIG | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 382 per 1000 | 438 per 1000 | OR 1.26 | 395 | ⊕⊝⊝⊝ | There may be little or no difference between the two letter types in terms of their effect on the proportion of children with treated or untreated caries. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| aDowngraded two levels due to high risk of bias. | ||||||
| CSM referral letter plus DIG versus CSM referral letter alone | ||||||
| Population: school children | ||||||
| Outcomes | Anticipated absolute effects* (95% CI) | Relative effect | Number of participants | Certainty of the evidence | Comment | |
|---|---|---|---|---|---|---|
| With referral letter based on CSM | With CSM referral letter plus DIG | |||||
| Dental attendance | Not reported | |||||
| Proportion of children with treated/untreated caries | 376 per 1000 | 439 per 1000 | OR 1.30 | 411 | ⊕⊝⊝⊝ | There may be little or no difference between the two letter types in terms of their effect on the proportion of children with treated or untreated caries. |
| Proportion of children with other treated/untreated oral health need | Not reported | |||||
| Adverse events | Not reported | |||||
| *The risk in the intervention group (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| 1 Downgraded by two levels due to high risk of bias. | ||||||
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 1.1 Dental attendance Show forest plot | 4 | Risk Ratio (IV, Random, 95% CI) | Totals not selected | |
| 1.1.1 Cluster‐RCT with ICC 0.03 | 3 | Risk Ratio (IV, Random, 95% CI) | Totals not selected | |
| 1.1.2 Individually randomised trial | 1 | Risk Ratio (IV, Random, 95% CI) | Totals not selected | |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 2.1 Dental attendance Show forest plot | 2 | 4980 | Risk Ratio (IV, Random, 95% CI) | 1.07 [0.99, 1.16] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 3.1 Dental attendance Show forest plot | 2 | 5316 | Risk Ratio (IV, Random, 95% CI) | 1.01 [0.94, 1.08] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 4.1 Dental attendance Show forest plot | 1 | 402 | Risk Ratio (IV, Random, 95% CI) | 1.52 [1.15, 2.00] |
| 4.1.1 Attending general dentist | 1 | 201 | Risk Ratio (IV, Random, 95% CI) | 1.39 [1.09, 1.77] |
| 4.1.2 Attending orthodontist | 1 | 201 | Risk Ratio (IV, Random, 95% CI) | 1.90 [1.18, 3.06] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 5.1 Dental attendance Show forest plot | 1 | 2486 | Risk Ratio (IV, Random, 95% CI) | 3.08 [2.57, 3.71] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 6.1 Receipt of dental care Show forest plot | 1 | 395 | Odds Ratio (IV, Random, 95% CI) | 1.26 [0.82, 1.93] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 7.1 Receipt of dental care Show forest plot | 1 | 388 | Odds Ratio (IV, Random, 95% CI) | 0.97 [0.62, 1.51] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 8.1 Receipt of dental care Show forest plot | 1 | 411 | Odds Ratio (IV, Random, 95% CI) | 1.30 [0.85, 1.99] |
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
| 9.1 Dental attendance Show forest plot | 1 | 362 | Risk Ratio (M‐H, Random, 95% CI) | 0.91 [0.34, 2.47] |
| 9.2 Caries in primary dentition Show forest plot | 1 | 362 | Mean Difference (IV, Random, 95% CI) | ‐0.20 [‐0.72, 0.32] |
| 9.3 Caries in permanent dentition Show forest plot | 1 | 362 | Mean Difference (IV, Random, 95% CI) | 0.30 [‐0.03, 0.63] |
