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A Two Dimensional Scale for Oral Discomfort

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19 December 2024

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20 December 2024

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Abstract
Subjective suffering due to oral diseases and disorders has been conceptualized as oral health-related quality of life and is often assessed with a multidimensional version of the Oral Health Impact Profile (OHIP). In the current study, a secondary analysis of a Dutch-language translated version of the original OHIP-14 was performed in different samples of approximately 1000 participants from diverse contexts (i.e., the Netherlands, the Caribbean, and Nepal). The dimensional structure and reliability of the scales resulting from these analyses were also examined. Based on a number of Confirmatory Factor Analyses (CFA) and Simultaneous Components Analysis (SCA) of the OHIP-14 scale, testing various models with different numbers of factors, several models were acceptable, but a two-factor solution, comprising psychological discomfort and physical discomfort was the most satisfactory in all three samples although a one-factor solution, oral discomfort was also acceptable. Instead of using a large number of dimensions with few items each, as often is done, it is most adequate and feasible to use no more than two scales, i.e., psychological discomfort and physical discomfort, comprising 11 items in total. These subscales of 6 and respectively, 5 items are not only statistically, but also theoretically the most adequate. Additionally, all items together, i.e., oral discomfort as a one-dimensional scale are useful and easy to apply for practical use.
Keywords: 
Oral discomfort
;  
Psychological discomfort
;  
Physical discomfort
;  
Psychometrics
;  
Validation study
Subject: 
Public Health and Healthcare  -   Primary Health Care

Introduction

Quality of life (QoL) is a very important concept in healthcare. Particularly for the development and evaluation of health interventions that intend to maintain or improve people’s health. QoL can be considered as the subjective perception of one’s personal position in life related to one´s health [1]. In general, it is a very important aspect of many medical problems and chronical disorders [2], which also applies to oral health conditions, such as tooth decay (caries). Caries can be considered a chronic disease and the most common prevalent disease in both children and adults, and, even though it is largely preventable may affect one´s quality of life [3].
For the development of adequate and tailored oral health interventions, it is a necessary prerequisite to accurately estimate the relative impact of chronic oral diseases on Oral Health Related Quality of Life (OH-QoL), so that healthcare resources can be better planned and allocated to achieve optimal OH-QoL [4]. Quality of life in relation to dental or oral health is a very subjective concept. Therefore, it is important to have a valid and reliable scale to assess OH-QoL. When a scale to measure a psychological attribute, for instance, OH-QoL is developed, the often recommended procedure is to select a representative sample of items from the domain representing the attribute. This approach is called domain sampling theory [5]. In this sample of items, the true dimensionality of the target attribute can be identified. This implies that, if other authors would like to develop another measure of the same attribute, the same dimensions would be found in a different set of items from the domain. It follows that, if a set of items is selected that is not a domain sample and a dimensionality analysis is applied, the real dimensions of the target construct may not be identified.
The present research focuses on the dimensionality of a measure of OH-QoL that is considered here as subjective oral health. Based on the WHO framework for impairment, disability and handicap (1980) a quarter century ago, Kay and Locker [6, p.8] defined oral health as “a standard of health of the mouth and related tissues that enables a person to eat, speak, and socialize without active disease, discomfort or embarrassment and that contributes to general well-being. Building upon this definition, currently oral health is specified and considered a “multifaceted phenomenon, including the ability to speak, smile, smell, taste, touch, chew and swallow, as well as the ability to express a range of emotions through facial expressions, with confidence and without pain, discomfort and disease of the craniofacial complex” [6]. In order to place more focus on the personal and self-experienced, it is assumed that subjective oral health is influenced by an individual’s perceptions, expectations and ability to adapt to different circumstances [7,8]. OH-QoL is an essential aspect of general health throughout life, and essential for the overall quality of life (QoL) [9,10]. Especially psychosocial well-being is an important aspect of patients' OH-QoL [11,12].
The goal of the present research is to develop a single measure, or two measures of OH-QoL that are easy to use and interpret in practice and in research. In 2010, based on previous studies [13,14], Buunk-Werkhoven proposed to interpret the OH-QoL concept as ‘dental satisfaction’ and suggested that the Oral Health Impact Profile-14: OHIP-14 measures a single construct to determine the degree of an individual’s own perceived dental satisfaction. Indeed, in one study an exploratory factor analysis (EFA) showed one appropriate factor for the used dataset [15,16]. Hence, to develop reliable and valid scales for OH-QoL, the present study examined the structure of the items of the widely used OHIP-14 [17,18]. Although the original OHIP-14 is based on the OHIP, a 49-item instrument, that can be considered a domain sample of the construct OH-QoL, it has –from a psychometric perspective– a number of limitations. First, it is not a set of items representative of the domain of OH-QoL. Although in the study by Slade [18], the OHIP-14 accounted for 94% of the variance in the OHIP-49 that does not mean that all dimensions are represented [19]. Second, its dimensional nature consists of seven scales, each of two items. Such scales are not very reliable; according to psychometric insights, reliability depends on the length of the scale and the correlations between the items. Calculating a Cronbach’s alpha, which is commonly used as a measure of a test's reliability [20] for two items, does not make much sense and it in fact not really possible.
A third limitation is that the reported distribution of the items is generally very skewed, due to Cronbach's alpha has been argued as a measure of internal consistency rather than reliability, and any restriction of the range may have had a negative effect on both reliability and validity. A fourth limitation is that with its seven dimensions the OHIP-14 is not very useful in research that wants to predict the OH-QoL from other variables, such as personality, age, dental visits, or attitude towards oral health care. Although review studies recommend a 4-dimensional framework to cover the different domains of OH-QoL, i.e. psychosocial impact (former handicap), oral function, orofacial pain, and orofacial appearance [12,21,22,23], for practical application it is also better to be able to work with one or two scales, for example to evaluate patients' reported OH-QoL. Also in medical research, only a few scales are usually used to measure similar constructs.
Finally, it must be noted that the OHIP-14 does not measure OH-QoL, but rather the opposite, which better can be described as oral discomfort, a term that would fit better the content of the items. In line with the psychological and experiential nature of quality of life, oral discomfort is expected to be only partially determined by the objective dental status, but also by oral hygiene behavior, which may depend considerably on knowledge, lifestyle, gender, occupational status and cultural factors [19,24,25]. Thus, with the goal of developing one or two scales to measure oral discomfort, that are content-valid, structured and easily to apply in practice, the present research examines the psychometric structure of the translated and culturally adapted Dutch version of the short OHIP-14 [26], which has been carefully translated backward-forward, constructed, modified and validated in several population-based studies [27,28,29,30,31,32]. In addition, more specific insight in factors associated with mouth-related e.g., oral discomfort or oral health issues and self-care practices is of great importance for developing of tailored oral health care interventions in the daily practice of oral health professionals [4].

Method

Sample Description

The Dutch sample included 790 participants/patients (45% female), with a mean age of 28.8 (SD = 18.8). 22% of the Dutch participants had a low level of education, 23% had a medium level, and 54% had a high level of education. In this total sample, 555 participants are students and military recruits of about the same average age [28,31]. The remaining participants can be divided into 112 patients who attended a dental school [13], 80 were forensic psychiatric male patients [27,29] and 43 elderly people [32].
The Caribbean sample included 113 participants/patients (55% female) with a mean (SD) age of 36.5 (13.2) years, who visited a dental practice in Bonaire and in Aruba. Although Dutch is the official language, Papiamento – a mixture of Portuguese, Spanish, English and Dutch words – as the native language is spoken by 73% as its mother tongue. 48% of the participants in the Caribbean sample were married, 5% of the Caribbean participants had a low level of education, 74% had a medium level, and 23% had a high level of education (Buunk-Werkhoven et al., 2011).
The Nepalese sample included 108 participants (54% female); their mean (SD) age was 40.1 (16.5) years, who visited a dental camp of the Netherlands Oral Health Society (NOHS) in the region of Newalparasi. The used Dutch OHIP-14 version was translated in Sanskrit and was filled out by 69 participants, whereas the data for 39 participants were collected through a semi-structured interview by a Nepalese translator. This sample is a multi-ethnic group of people related to Brahmin, Magar, and Newari, Tharu, Chetri, and Gurung background. Nepali as the national language is spoken by 90% as its mother tongue. 74% of the participants in the sample were married, and the level of education varied from no education (28%), low (27%), and medium (32%) to a high level (13%) [33]. Because of the three different nationalities in the sample and to verify that the OHIP-14 was face and content validated for each of these nationalities, the procedure of Geisinger [34] was partially used in the backward forward translation of the items from Dutch into the national mother tongue. Discrepancies were reviewed several times and any differences and concerns were reconciled with the translation until it was agreed that the language was clear and understandable for the sample population and that the OHIP-14 tapped the intended construct in this sample.

Measures

Oral health-related quality of life. To assess OH-QoL all items of the original OHIP-14 were used. This instrument consists of 14 items organized –the original order was shuffled in the administration of the scale– in seven dimensions of each two items, i.e., function limitation (‘speaking’ + ‘sense of taste’), physical pain (‘painful aching’ + ‘uncomfortable eating’), psychological discomfort (‘self-conscious’ + ‘tension’), physical disability (‘unsatisfactory diet’ + ‘interrupt meals’), psychological disability (‘difficult to relax’ + ‘embarrassed’), social disability (‘irritable’ + ‘occupational’), and handicap (‘unsatisfactory life’ + ‘unable to function’). In the used scale responses were scored on a five-point Likert scale (i.e., 0 = ‘never’, 1 = ‘sometimes’, 2 = ‘regularly’, 3 = ‘often’, 4 = ‘very often’). Please note, hence, that the original answer options in the OHIP-14 were slightly adapted, i.e., 1 = ‘hardly never’ was changed into ‘sometimes’, 2 = ‘occasionally’ was changed into ‘regularly’. From a psychometric perspective, these two original responses wording often showed unequal distance in discrimination, generally causing a skewed distribution. In Dutch psychological research, ‘never’, ‘sometimes’, ‘regularly’, ‘often’, and ‘very often’ are commonly used response options for distance discrimination. Even a possible translation issue such as changing from "occasionally" to "regularly" could potentially affect the variance. However, equal discrimination in response alternatives may better reflect the distribution of the prevalence of impact responses. Moreover, zero was defined as the maximal positive result indicative of total absence of problems and 4 corresponds to a maximal negative answer or always a problem. A total general OHIP-14 score for each respondent was calculated as the sum of all the 14 items.
Noteworthy, Guttman’s lambda 2 coefficient was used here as an alternative measure of reliability. Removing items from OHIP scales may affect the estimate of reliability, and is justified if there is a rationale for it and face validity is still maintained [20].

Statistical Analyses

Analyses were performed using SPSS package for reliability analyses (Lambda-2) and group differences, Lisrel (versoin 8.80; Jöreskog & Sörbom, 2007) for Confirmatory Factor Analyses (CFAs), and Matlab for congruences.

Results

First, the structure of the original OHIP-14 was examined by means of Confirmatory Factor Analyses (CFAs). Based on previous studies on the structure of the OHIP-14, four potential factor models (described as A to D below) were tested in the present study’s three subsamples. For the meaning of the various Q indices, see Table 2.
  • 7-factor solution, that represents the original 7 factors identified by Locker (1988): function limitation (Q4, Q14), physical pain (Q2, Q5), psychological discomfort (Q1, Q9), physical disability (Q12, Q10), psychological disability (Q13, Q8), social disability (Q7, Q3), and handicap (Q11, Q6). These factors were also used in developing the OHIP-14 [16,18].
  • b. 3-factor solution that was found in a Dutch sample using the OHIP-14 [27]: functional limitations (Q2, Q3, Q4, Q5, Q10, Q14), social discomfort (Q7, Q8, Q9, Q11, Q12, Q13), and psychological inhibitions (Q1, Q6).
  • c. 3-factor solution as reported in a Spanish sample [17], and as further examined in Brazilian samples [15]: psychosocial impact (Q1, Q9, Q13, Q8, Q7, Q3, Q11, Q14), pain-discomfort (Q2, Q5, Q12, Q10), and functional limitations (Q4, Q14).
  • d. 1-factor solution: original (14 items ) and final oral discomfort scale (11 items)
Results of the CFAs are summarized in Table 1. In order to assess model fit, the chi-square test, the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the Tucker-Lewis index (TLI) were used, and a cut-off value close to or less than .06 for RMSEA, and a cut-off value close to or greater than .95 for CFI and TLI as indicators of acceptable model fit was recommended [35].
As can be seen from Table 1, there is little difference between the fit indices of the four models in the three samples. Generally speaking, the original 7-factor model (Model A) fits a little bit better than the two three-factor models (Model B and C) and the one-factor model (Model D). The RMSEA values are not satisfactory regardless of model or sample though (all values are 0.087 or higher), and the TLI values are consistently below .95 for the Caribbean and Nepalese samples. Based on these outcomes, there appears not to be a clearly superior model fitting the data in these three samples.
It was therefore decided to exploratively examine the structure of the original OHIP-14. The joint data set was used to find the structure that best fits all three samples. More specifically, Simultaneous Components Analysis (SCA) is used, which is particularly suitable for finding the common structure across different data sets that share the same variables. The differences in variability across the various taxonomies were removed, so that the joint analysis was done on the common correlation structure. There are different variants of SCA [36,37] of which here SCA-ECP version was used (this is a SCA with equal cross-products). Solutions with one, two and three components were examined. It turned out that the three factor solution was uninterpretable. A solution with two factors however was conceptually the best interpretable. The rotated solution (oblimin solution) is reported in Table 2.
Table 2. Rotated SCA-ECP Solution.
Table 2. Rotated SCA-ECP Solution.
Original OHIP-14 with shuffled item order Psychological discomfort Physical discomfort
Q1 = ‘self-conscious’ .465 .122
Q2 = ‘painful aching’ .048 .580
Q3 = ‘occupational ‘ .294 .544
Q4 = ‘speaking’ .397 .234
Q5 = ‘uncomfortable eating’ -.086 .895
Q6 = ‘unable to function’ .377 .247
Q7 = ‘irritable’ .756 -.010
Q8 = ‘embarrassed’ .728 -.013
Q9 = ‘tension’ .739 .087
Q10 = ‘interrupt meals’ .302 .470
Q11 = ‘unsatisfactory life’ .939 -.176
Q12 = ‘unsatisfactory diet’ .390 .453
Q13 = ‘difficult to relax’ .719 .076
Q14 = ‘sense of taste’ .362 .274
Note: selected items per component are printed bold; the not selected items are printed Italic.
The first component can be interpreted as psychological discomfort, and the second component as physical discomfort. To examine the extent to which this SCA-ECP solution fits the factor structure in each of the three samples independently, congruencies between the two SCA-ECP components reported in Table 2 and the explorative two-component solutions (principal axis factoring with oblimin rotation) for each sample were calculated. The congruencies (Tucker’s ɸ) were calculated. A ɸ of .85 to .94 indicates fair similarity, while values of .95 or higher imply that two components can be considered equal [38]. It turned out that in all samples the congruencies were good for the first component, i.e., psychological discomfort, for the Dutch sample ɸ = .99, for the Caribbean sample ɸ = .97, and for the Nepal sample ɸ = .96. The congruency was also good for the second component, i.e., physical discomfort, in the Dutch sample, ɸ = 98, and in the other samples the congruencies indicated only fair similarity, for the Caribbean sample ɸ = 94, and for Nepalese sample ɸ = 87-
Based on these outcomes, it was decided to retain this two component solution, and only retain those items with an absolute factor loading of .40 or higher. This means that items Q4, Q6 and Q14 were dropped from further analyses (see Table 2). To examine the overall model fit of this two factor solution, based on 11 items, CFAs were conducted on the three subsamples (see Table 3). For comparison purposes, two models were tested: one with the two factors as reported in Table 2, and a one factor solution (‘oral discomfort’; model D in Table 1). The two models show a comparable fit in the Dutch and Nepalese samples, with slightly better values of the fit indices for the two factor solution. In the Caribbean sample, the two factors clearly outperform the one factor solution.
Next, in all three samples for the remaining 11 items the reliability of the two components psychological discomfort and physical discomfort was estimated. For this purpose Guttman’s lambda 2 coefficient was calculated, which is preferable over Cronbach’s alpha [20]. The λ2 reliabilities in the Dutch and Caribbean samples were good (for psychological discomfort .98 and .94 respectively, for physical discomfort .87 and .86 respectively). The λ2´s were sufficient in the Nepalese sample (.73 for psychological discomfort and .76 for physical discomfort). On the basis of the factor analyses two scales are proposed for Oral Discomfort, the final versions of these scales are presented in Table 4.
Group differences between the samples were examined by means of a multivariate analysis of variance. There was a significant multivariate effect of sample, F(4, 2014) = 17.07, p < .01, as well as significant univariate effects for both psychological discomfort, F(2, 1008) = 31.07, p < .01, and physical discomfort, F(2, 1008) = 20.37, p < .01. Pairwise comparisons showed that all means differed significantly between the samples (p’s < .01), with the exception of the means for physical discomfort of the Dutch and the Caribbean samples (p = .96). For psychological and physical discomfort the means were for the Netherlands M = .36 (SD = .58) and M = .48 (SD = .61) respectively, for the Caribbean sample M = .58 SD = .74) and .54 (SD = .64) respectively, and for the Nepalese sample, M = .85 SD = .86) and .90 (SD = .87) respectively. These figures show that the Dutch sample reported the lowest discomfort scores, and the Nepalese sample the highest.

Discussion

The purpose of the present study was to examine the dimensional structure and the reliability of a Dutch version of the Oral Health Impact Profile-14, with the aim of developing one or two scales to measure oral discomfort, that are valid in terms of content, structured and easy to apply in practice. Initially, like previous studies [15,39], this research focused on confirmatory factor analysis of the structure of the Dutch OHIP-14 using three different samples. Simultaneous Components Analysis (SCA) was used, which is particularly suitable for finding the common structure across different data sets that share the same variables. The results of this study provide evidence of how this OHIP-14 instrument works in different samples.
Based on this, a two-dimensional scale, with dimensions labeled as psychological discomfort and physical discomfort seems to best fit the data, and seems moreover an adequate measurement tool for clinical and research purposes. In this two-factor solution, it was found that three items of the original OHIP-14 did not correlate consistently with the remaining items and were dropped. Two deleted items in the used OHIP-14, i.e., ‘speaking’ and ‘sense of taste’, formed in the original OHIP-14 [40] one of the seven dimensions, namely function limitation. Item ‘unable to function’ was also removed from the scale presented here, while, though in the original OHIP scale this particular item OHIP-14 combined with OHIP-13 (‘unsatisfactory life’) formed the dimension handicap. It may be noted that also in previous studies item ‘unable to function’ correlated inconsistently with the other items. However, in this study there is overlap and only some shifts of items compared to the three subscales described in a previous study of Buunk and Buunk-Werkhoven [27], for example, here, psychological discomfort is interpreted as compared to ‘social discomfort', and physical discomfort as compared to ‘functional limitations’ respectively.
To summarize, the present research suggests that what is often referred to as oral health-related quality of life can be best be conceptualized as consisting of two dimensions measured by two brief scales that are easy to administer. The psychological discomfort subscale encompasses the affective aspects of oral discomfort, including tension, dissatisfaction and embarrassment related to oral health conditions or treatments. The physical discomfort subscale evaluates sensory experiences such as pain and eating problems directly associated with teeth, mouth, or dentures. In addition, there is also psychometric support for a one-factor solution of overall oral discomfort, that can be measured with the final 11-item scale including the i.e., two subscales together, which can be useful and easy to apply for practical use (see Table 4). If the length of the questionnaire (i.e. the time needed for its completion by participants or patients) and interpretation or for instance the number of dimensions are an issue [16,21,41,42], the scales presented here may be optimal, and practitioners as well as researchers can choose to look only at the scores of the total 11-item version, or to examine the scores of the two subscales. Especially in various situations, for example, when one wants to evaluate the effect of a treatment or when one is interested in examining the level of oral discomfort in a specific patients or population [41,43,44], the final 11-item scale can be a useful tool that does not require too much time of patients, and will therefore result in low non-response levels.
The present research has a number of limitations. A first limitation of this study is that most data came from quite specific populations, and thus in the future the scales should be administered to samples representative of the population, also to obtain norm scores for the scales, so that users can assess to what extent a score of a patient or group is high or low. A second limitation is that there were no data on the validity of the scales, that could be assessed, for example, by relating the scales so similar instruments. A third potential limitation is that it yet not been demonstrated how useful the scales are in practice. Nevertheless, the scales included only items from the original OHIP-14 that have been widely used.
Overall, quantitative research on the outcomes of oral disorders, as perceived and reported by patients and individuals, is required needed to further innovate dental and oral care. Therefore, a universally applicable Oral Discomfort measure to ensure consistency of assessing and measuring outcomes that more explicitly address the issues and discomfort related to the mouth should be adopted [17,18,19,26,27,31]. The scales proposed in the present research might play a role in future applied research to further study its characteristics, for example, the convergent and discriminant validity of this Oral Discomfort scale.
In practice, the scale might be used to develop interventions aimed at improving oral quality of life and its related oral health behavior. This means appropriately applying the Problem-Analysis-Test-Help-Success (PATHS) model, i.e., different phases must be distinguished for designing effective interventions [4]. This means that in the P-phase, the potential target population should be defined. In this phase, the present Oral Discomfort scales might help to identify groups, subgroups and individuals with the most urgent needs. In the following A- and T-phase, a broad set of determinants of oral discomfort should be assessed and analysed. For example, the Oral Discomfort scale score might be related to dental care organization, treatment practices and individual behaviors. In the H-phase, the actual intervention package is developed to improve oral comfort by targeting target the population-specific determinants [30]. The Oral Discomfort might be integral part of the intervention procedure as a screening instrument.
Lastly, in the S-phase, the effectiveness of the intervention must be assessed, for example, with the present Oral Discomfort scale. When the intervention is effective, the intervention may be widely implemented in practice.

Conclusions

The present research suggests that an adapted version of the original OHIP-14, consisting of two scales, i.e. psychological discomfort and physical discomfort may be the most adequate approach to measuring what is usually labeled as oral health-related quality of life, but that maybe better can referred to as oral discomfort. The two subscales together can be easily used in practice and research to assess patients’ oral discomfort in terms of psychological and physical discomfort at the intake, as well at the end of a treatment to examine the effect of a treatment on subjective oral health.

Compliance with Ethical Standards

Ethical clearance and permission was granted for the current study with human participants from the ethical committee for all previous published studies conducted according to universal ethical principles (included informed consent) of the Declaration of Helsinki.

Conflicts of Interest

none.

Data Availability Statement

The dataset for this study is in a repository and is available at the Open Science Framework (OSF; https://osf.io/wuyfr/). The DOI is as follows: DOI 10.17605/OSF.IO/WUYFR.

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Table 1. Results from the CFAs in Three Samples.
Table 1. Results from the CFAs in Three Samples.
The Netherlands
X2 RMSEA (90% CI) CFI TLI
Model A 415.92 .087 (.079-.095) .98 .97
Model B 619.18 .098 (.091-.11) .97 .96
Model C 610.88 .097 (.090-.10) .97 .96
Model D 730.21 .11 (.10-.11) .96 .96
Caribbean
X2 RMSEA (90% CI) CFI TLI
Model A 140.18 .11 (.088-.14) .96 .94
Model B 193.53 .12 (.095-.14) .95 .93
Model C 186.48 .12 (.095-.14) .95 .94
Model D 269.88 .18 (.16-.20) .91 .90
Nepal
X2 RMSEA (90% CI) CFI TLI
Model A 121.85 .098 (.071-.12) .93 .89
Model B 149.65 .093 (.070-.12) .92 .90
Model C 155.63 .094 (.071-.12) .91 .89
Model D 157.61 .092 (.069-.11) .91 .90
Table 3. Results from the CFAs in Three Samples based on 11 items.
Table 3. Results from the CFAs in Three Samples based on 11 items.
The Netherlands
X2 RMSEA (90% CI) CFI TLI
Two factors 398.63 .11 (.096-.11) .97 .96
One factor 586.84 .13 (.13-.14) .96 .94
Caribbean
X2 RMSEA (90% CI) CFI TLI
Two factors 70.35 .073 (.039-.10) .98 .98
One factor 183.59 .20 (.18-.25) .91 .89
Nepal
X2 RMSEA (90% CI) CFI TLI
Two factors 92.22 .091 (.060-.12) .92 .90
One factor 95.18 .094 (.064-.12) .92 .90
Table 4. The final oral discomfort measure as a two dimensional scale (11 items) [psychological discomfort (1, 2, 3, 4, 5, 6) and physical discomfort (7, 8, 9, 10, 11)].
Table 4. The final oral discomfort measure as a two dimensional scale (11 items) [psychological discomfort (1, 2, 3, 4, 5, 6) and physical discomfort (7, 8, 9, 10, 11)].
Oral Discomfort 0 1 2 3 4
1. Have you been self-conscious because of your teeth, mouth, or dentures? never sometimes regularly often very often
2. Have you been a bit irritable with other people because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
3. Have you been a bit embarrassed because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
4. Have you felt tense because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
5. Have you felt that life in general was less satisfying because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
6. Have you found it difficult to relax because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
7. Have you had painful aching in your mouth? never sometimes regularly often very often
8. Have you had difficulty doing your usual jobs because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
9. Have you found it uncomfortable to eat any foods because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
10. Have you had to interrupt meals because of problems with your teeth, mouth, or dentures? never sometimes regularly often very often
11. Has your diet been unsatisfactory because of problems with your teeth, mouth or dentures? never sometimes regularly often very often
Note: The Dutch, Nepalese and Indonesian versions of the final Oral Discomfort scale can be obtained from the first author.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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