These data support the performance of the MDAS as a measure of dental anxiety. The internal consistency was very high and the items appeared to describe a uni-dimensional construct which we would understand as providing a dimension of dental anxiety ranging from low to high. More sophisticated methods are available  to tease out discrepancies to this measurement model, however for practical purposes the user will find that the responses they receive from individual participants are easily interpretable.
This is the first report providing normative data of a representative sample of the UK general population. The level of high dental anxiety in the sample was 11% and is comparable to other reports from local or regional community surveys [6, 11]. A large representative UK survey (N = 1800) using Corah's Dental Anxiety Scale has been reported which showed that 11% of their sample showed high dental anxiety (≥15) . Caution should be taken when comparing studies that use different measures and cut-off values. For example, two 'conventional' cut-off values (≥13 and ≥15) are often used for data collected from Corah's scale (see for examples  and ). The cut-off of 19 was selected for the MDAS previously on empirical grounds, and provides greater confidence in the interpretation of the proportion that score at or above this point.
These figures are also reflected in the overall scores presented in the form of percentiles. The percentile at which men reach the 19 cut-off point was 90% in younger men (18 – 39 years) whereas in women this point was reached at the 85th percentile. However, an interesting interaction of gender with age was apparent, reflected in the much higher percentile (97th) in the oldest male age group (60+ years) compared with female counterparts (90th). A male patient aged 60+ years who scored 19 would be part of just 3% of the general population with the same or higher score whereas the comparable female would be associated with as many as 10% of the public. Moreover, a 25 year old male with a score of 9 could be informed by the dentist that about half of the people his age score lower than him, and by implication, half score higher.
The total scores for the MDAS varied by sex and age group but unlike the higher category of dental anxiety (e.g. extremely anxious or above the cut-off value), the interaction of age and sex was not significant. That is, it would appear that at more extreme levels of dental anxiety the effect of age and gender interacted so that in older age groups women were more dentally anxious than men and that these differences were stronger than at the lowest age group. The comparison of results between averages and proportions scoring at a clinically relevant cut-off across the factors of age and gender, was interesting and alerts the researcher and clinician to focus on the purpose and use of scores obtained from an instrument such as the MDAS. Caution is required when considering patients in higher scoring groups as previously mentioned. The validity of the cut-off, although empirically determined, requires additional support. The relatively small error contained in the measure should not be ignored and should indicate to the practitioner that repeated assessment at a later date would be prudent. A discussion with patients about their feelings associated with dental visiting would also assist in the assessment process, especially with those with high scores.
The population norms produced by this survey for the MDAS have merit as they are recently produced and are likely to be more representative. The original norms published in 1995 comprised of four groups of participants obtained in the first 2 years of that decade. They included industrial dental service and general practice service users, members of the community visiting their general medical practitioner (GMP) and mothers attending the community dental service with their child. The closest comparative group was the GMP visitors as they will comprise of participants who do not visit the dentist – a feature not apparent in the other 3 original groups. The mean (SD) levels of the current study (n = 963) and the 1995 'community' group (n = 525) were 10.36 (5.36) and 10.39 (5.46) respectively. These showed remarkable similarity (t = 0.10, df = 1486, p = .54). Another interesting comparison was to inspect the percentages of participants who rated their anxiety as 'extremely anxious'. These data were available for both the total (genders combined) samples in the original (page 146, table four) and current surveys. The level of the rating was identical for the anticipatory items (1 and 2) however the percentage who rated the injection as extremely anxious was 14.6% in 1993 and only 9.5% in 2008. The mean dental anxiety scores for those aged 60 and above were higher in males in the current survey compared to the original community sample (page 147; table five, males: mean = 7.52 (3.81) n = 122 versus 6.52 (2.34) n = 50; t = 2.17, df = 170, p = .016), whereas females showed a smaller increase in the recent survey compared to the original, and the difference was not significant: 10.09 (5.57) n = 122 versus 9.23 (5.25) n = 71; t = 1.07, df = 191, p = .146). There is partial support therefore for Locker's suggestion  that the 50–59 year old cohort 'will carry their relatively high levels of dental anxiety into old age' . This effect appears to be shown in males only. These comparisons are tentative at best however, and await more extensive and organised data collection from longitudinal studies.
The major demographic variables were found to relate strongly with dental anxiety as shown in the multiple logistic regression analysis. Dental anxiety has been reported frequently in previous studies to vary with sex, age, education and social class. Of interest in particular for this study was the relationship of age group with the categorisation of high versus low/moderate dental anxiety. The benefit of conducting the multiple logistic regression was that the effects of education and social class were removed to allow a focus on the relationship of dental anxiety by age. No evidence could be found for a reduction of the proportion of participants with high dental anxiety in the youngest age group. Rather the likelihood of being highly dental anxious compared to those 60 years of age or more was four times greater. This finding supports the view that dental anxiety is relatively stable as a construct regardless of changes to treatment delivery. An interesting possibility may be that to achieve reductions in dental anxiety dental staff may need to engage more with their patients, probably at the young end of the age spectrum to develop resilience. The employment of active and sensitive communication skills may enhance this process .
Potential limitations of this study should be considered. Every effort was made by the market research company to ensure a representative sample. The original spreadsheets of the age, gender and social status breakdown showed that the discrepancy between what the survey aimed to collect to attain representativeness and what was actually collected was found to be similar. Admittedly there was a minor over-representation of ABC respondents. Residential location however was a good fit. The strength of association between social class and dental anxiety was one of the weakest factors entered into the logistic regression (together with education). Hence a weighting procedure to the analysis was not considered to be warranted due to the increased complexity of introducing such a procedure. The response rate of 14% was admittedly low although as argued immediately above we believe the potential bias was minimal. Other authors using telephone survey techniques also experienced similar problems (with an 18.5% response rate) and use identical arguments to our own to support the veracity of the data set . However, a risk of sampling bias exists with telephone survey methods if response rates vary in different groups within a population. For example, some may not have a landline telephone and may only use mobile telephones. Although the impact of such potential bias is unknown, other methods are also prone to response bias for similar reasons. For example, postal surveys can lead to over representation of the views of white participants with higher incomes and educational attainment . Telephone interviews have been used in national dental surveys  and remain an important method for public health and social surveys seeking populations' views, particularly in North America [33–35].