impact of self-esteem on the oral-health-related quality of life of children with malocclusion

ORIGINAL ARTICLE

Does psychological well-being influenceoral-health-related quality of life reports inchildren receiving orthodontic treatment?

Shoroog Agou,a David Locker,b Vanessa Muirhead,c Bryan Tompson,d and David L. Streinere

Toronto, Ontario, Canada

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Introduction: Although the associations between oral biologic variables such as malocclusion and oral-health-related quality of life (OHRQOL) have been explored, little research has been done to address the influence ofpsychological characteristics on perceived OHRQOL. The aim of this study was to assess OHRQOL outcomesin orthodontics while controlling for individual psychological characteristics. We postulated that children withbetter psychological well-being (PWB) would experience fewer negative OHRQOL impacts, regardless oftheir orthodontic treatment status.Methods:One hundred eighteen children (74 treatment and 44 on the waitinglist), aged 11 to 14 years, seeking treatment at the orthodontic clinics at the University of Toronto, participated inthis study. The child perception questionnaire (CPQ11-14) and the PWB subscale of the child health question-naire were administered at baseline and follow-up. Occlusal changes were assessed by using the dentalaesthetic index. A waiting-list comparison group was used to account for age-related effects. Results: Althoughthe treatment subjects had significantly better OHRQOL scores at follow-up, the results were significantlymodified by each subject’s PWB status (P \0.01). Furthermore, multivariate analysis showed that PWBcontributed significantly to the variance in CPQ11-14 scores (26%). In contrast, the amount of varianceexplained by the treatment status alone was relatively small (9%). Conclusions: The results of this studysupport the postulated mediator role of PWBwhen evaluating OHRQOL outcomes in children undergoing ortho-dontic treatment. Children with better PWB are, in general, more likely to report better OHRQOL regardless oftheir orthodontic treatment status. On the other hand, children with low PWB, who did not receive orthodontictreatment, experienced worse OHRQOL compared with those who received treatment. This suggests that chil-dren with low PWB can benefit from orthodontic treatment. Nonetheless, further work, with larger samples andlonger follow-ups, is needed to confirm this finding and to improve our understanding of how other psychologicalfactors relate to patients’ OHRQOL. (Am J Orthod Dentofacial Orthop 2011;139:369-77)

As orthodontic outcome research continues tomove away from the traditional biomedicalmodel1 toward a biopsychosocial perspective,2

more attention is being given to the concept of oral-

the University of Toronto, Toronto, Ontario, Canada.tant professor of orthodontics, Faculty of Dentistry, King Abdulazizrsity.ssor, Faculty of Dentistry.uate Student, Faculty of Dentistry.ciate professor, Faculty of Dentistry.ssor, Department of Psychiatry and Baycrest Center.on a thesis submitted by the first author to the school of graduate studies,rsity of Toronto, in partial fulfillment of the requirements for the PhD degree.liminary report was presented at the International Association of Dentalrch meeting in Toronto in 2008.uthors report no commercial, proprietary, or financial interest in the prod-r companies described in this article.t requests to: Shoroog Agou, Faculty of Dentistry, University of Toronto,dward St, Toronto, Ontario, Canada M5G 1G6; e-mail, [email protected], January 2009; revised and accepted, May 2009.5406/$36.00ight � 2011 by the American Association of Orthodontists..1016/j.ajodo.2009.05.034

health-related quality of life (OHRQOL).3 OHRQOL is de-fined as the absence of negative impacts of oral condi-tions on social life and a positive sense of dentofacialself-confidence.4 Studies with reliable OHRQOL mea-sures have identified differences between treated and un-treated orthodontic patients.5-9 For example, a Brazilianstudy of 1675 adolescents indicated that children whohad completed orthodontic treatment reported fewerOHRQOL impacts than those who were never treated.5

These differences were mostly related to socio-emotional aspects of well-being such as smiling, laugh-ing, and showing teeth without embarrassment.8,9

Such differences between treated and untreatedsubjects are expected in light of studies emphasizing theimportance of dentofacial esthetics in daily socialinteractions. For instance, an unattractive dentition hasbeen associated with teasing, bullying,10,11 and negativeOHRQOL impacts.5,11-13 Improving dental estheticsand, subsequently, psychological well-being (PWB) are

369

mailto:[email protected]

370 Agou et al

frequently stated reasons for seeking orthodontic treat-ment during childhood and adolescence.14,15 However,the bulk of evidence denoting the relative stability ofPWB undermines this assumption.16-19 Furthermore, nostudies have described how OHRQOL and PWB changeduring orthodontic treatment.

Attempts to correlate OHRQOL reports with clinicalorthodontic indicators, on the other hand, have oftenreached equivocal conclusions.20-23 In many of thesestudies, children reporting worse OHRQOL were notconsistently those with worse malocclusions. It ispossible that some children with a severe malocclusionare more emotionally resilient to the challenges causedby their condition. Hence, accurate interpretation ofOHRQOL measures requires an understanding of notonly their psychometric properties, but also thecontextual factors that might influence theirassessments of health and well-being.24 A recentlong-term study evaluating psychosocial outcomes inorthodontics suggested that analyzing the effects oforthodontic treatment on psychological health withoutconsidering intervening factors might lead to invalidconclusions about the efficacy of treatment.19 Thiswas corroborated by cross-sectional reports recognizingthe effects of innate personality traits on children’s per-ceptions of dentofacial esthetics25-27 and patients’evaluations of the impact of their health on dailyfunctioning.28-30

Contemporary models of diseases and disorders andtheir consequences, which integrate both biologic andpsychologic aspects of health, support this holisticthinking paradigm.31 For example, according to themodel of Wilson and Cleary,32 health-related quality oflife outcomes experienced by a patient are determinednot only by the nature and severity of the disease ordisorder, but also by the patient’s characteristics andhis or her environment. A thorough examination of theorthodontic OHRQOL literature with the Wilson-Clearymodel as the conceptual framework showed that, forthe most part, studies have focused on the associationsbetween biologic variables and OHRQOL,23,33,34 withlittle emphasis on the psychological characteristics ofchildren receiving orthodontic treatment.35 This is sur-prising, since research has shown that determinants ofhealth-related quality of life are mainly psychological.36

Hence, psychological factors such as PWB are certainlyimportant mediators of OHRQOL.37

Since the relationship between psychological factorsand OHRQOL is largely unexamined in orthodontic pa-tients, this study was undertaken to answer the question:do individual psychological characteristics affect chil-dren’s OHRQOL reports? The specific objectives of thislongitudinal investigation were to explore the effect of

March 2011 � Vol 139 � Issue 3 American

PWB on reported OHRQOL in children receiving ortho-dontic treatment and to compare this effect with a sam-ple of untreated waiting-list controls. We hypothesizedthat children with better PWB would experience fewernegative impacts, regardless of their orthodontic treat-ment status. According to this hypothesis, the children’sassessment of OHRQOL would be influenced by theirPWB. To demonstrate this mediating role of PWB, wecompared OHRQOL in children with high and low PWBscores. We expected that OHRQOL outcomes wouldnot change for those in the high PWB group but mightchange for those in the low group.

Since medical research has shown that psychologicalvariables are likely to affect the more subjective domainsof quality of life reports, we expected that the influenceof PWB would be more pronounced for the more subjec-tive social and emotional dimensions of the OHRQOLmeasure used in this study than for the more objectivedimensions addressing functional limitations and oralsymptoms.38

MATERIAL AND METHODS

In this study, we used a 2-group before-and-after de-sign to assess changes in OHRQOL after orthodontictreatment. Patients receiving treatment were the focalgroup of interest, whereas patients awaiting treatmentcomprised the comparison group.

To be eligible, a child had to be fluent in English andhave good general health. Children with severe dentofa-cial deformities were excluded. Parents’ consents andchildren’s assents were obtained, and the ResearchEthics Board of the University of Toronto, Ontario,Canada, approved all study procedures. Subjects werenot offered incentives or compensation for participatingin the study. The treatment subjects were consecutivelyrecruited from the graduate orthodontic clinic at theUniversity of Toronto during their first assessment visit.The control subjects were consecutively recruited fromthe Faculty of Dentistry clinics during their first ortho-dontic screening visit. All 11- to 14-year-old subjectswho met the eligibility criteria were recruited by the firstauthor (S.A.).

All children completed the child perception question-naire (CPQ11-14) and the PWB subscale of the childhealth questionnaire at baseline (T1) and follow-up(T2). The questionnaires were completed by the childrenunassisted by parents or investigators. The dentalaesthetic index (DAI) was used to determine the clinicalseverity of the malocclusion. Table 1 summarizes themain study variables. Age and sex were recorded becauseof their potential associations with outcome and explan-atory variables. The treatments were completed at thegraduate orthodontic clinic as routinely prescribed with

Journal of Orthodontics and Dentofacial Orthopedics

Table I. Main study variables and their interpretationsCPQ11-14 Child perception questionnaire

Lower CPQ11-14 scores represent better OHRQOLOS Oral symptoms

Lower CPQ11-14 scores represent better OHRQOLFL Functional limitations

Lower CPQ11-14 scores represent better OHRQOLEWB Emotional well-being

Lower CPQ11-14 scores represent better OHRQOLSWB Social well-being

Lower CPQ11-14 scores represent better OHRQOLPWB Psychological well-being

Lower PWB scores represent worse psychologicalwell-being

DAI Dental aesthetic indexLower DAI scores represent better occlusion

Agou et al 371

fixed appliance therapy. On average, treatment lasted for26 months. The T2 data were collected at the first reten-tion check appointment for the treatment subjects andafter an equivalent time interval for the control subjects.

The CPQ11-14 is a child OHRQOL instrument. Theage-specific questionnaire (11-14 years) consists of 37items, grouped into 4 domains: oral symptoms (OS),functional limitations (FL), emotional well-being(EWB), and social well-being (SWB). Each item asksabout the frequency of events, as applied to the teeth,lips, and jaws, in the previous 3 months. The responseoptions were “never,” “once or twice,” “sometimes,” “of-ten,” and “every day or almost every day.” Additive scaleand subscale scores for the CPQ11-14 were calculated bysumming the item response codes. Although the instru-ment was designed to yield an overall score, a separatescore can be generated for each subscale. Higher scoressignify worse OHRQOL. The validity, reliability, and re-sponsiveness of this measure have been established invarious settings.6,21,23,33,39-42 This measure examinesthe impacts of oral conditions on children’s EWB andSWB; nonetheless, it is important not to confuse these2 domains with the more generic PWB. EWB and SWBfocus specifically on the impacts of oral healthconditions of children’s daily functioning, whereasPWB takes into account the effect of all aspects ofhealth and daily life on well-being.

The children’s PWB was measured by using the PWBsubdomain of the child health questionnaire, which isa widely used and validated self-report instrument.43

The 16-item PWB scale measures the frequency ofboth negative and positive feelings. The items captureanxiety, depression, and happiness. Frequency is mea-sured by using a 5-level continuum that ranges from“all of the time” to “none of the time.” The scoreswere calculated according to the user’s manual.44 Higherscores indicate better PWB; a score of a 100, forexample, indicates that the child feels peaceful, happy,and calm all of the time. In contrast, lower scores indi-cate that the child has feelings of anxiety and depression.Specific instructions confirming the generic nature ofthe measure were added at the beginning of thequestionnaire.

The severity of each treatment and control subjects’orthodontic condition was assessed from study modelstaken at T1 and T2 and by using the DAI.45 Althoughother treatment-need indexes such as the index of or-thodontic treatment need and the index of complexity,outcome, and need are available, the DAI was chosen be-cause it incorporates the social acceptability of a child’sdental appearance. The rating is based on the measure-ment of 10 occlusal traits; each trait is multiplied bya weight derived from the judgment of laypersons. The

American Journal of Orthodontics and Dentofacial Orthoped

products are summed, and a constant is added to givea DAI score. DAI scores range from 13 (the most accept-able) to 100 (the least acceptable). The DAI ratings wererecorded by 3 trained and calibrated examiners. Intra-examiner and interexaminer reliabilities were evaluatedby having the raters independently assess a random10% sample of the models and then reassessing themodels after a 1-week interval. Intraexaminer reliabilityfor the DAI raters was high with intraclass correlation co-efficients of 0.96, 0.91, and 0.97, respectively. The inter-examiner reliability was also high (intraclass correlationcoefficient of 0.81).

Statistical analysis

The data were analyzed by using SPSS software(version 16, SPSS, Chicago, Ill). Data analyses includeddescriptive statistics, and bivariate and multivariateanalyses. Paired t tests were used to assess within-group changes over time for the treatment and controlgroups. The P value for all tests was set at\0.05.

Analysis of covariance (ANCOVA) models were thenused to explore between-group differences. The firstgoal was to evaluate the relationship between theprovision of orthodontic treatment and the changes inOHRQOL, represented by overall and individualCPQ11-14 scores, while controlling for the CPQ11-14scores at T1, age, and malocclusion severity. This analy-sis plan, represented in model 1 (Table II), aims toaddress whether there is a difference in reported OHR-QOL between treatment and control subjects.

The second goal was to evaluate the role of PWB onmediating OHRQOL outcomes by using a second AN-COVA model (model 2 in Table II). This model addresseswhether there is a difference in OHRQOL scores betweentreatment and control subjects and whether it remainssignificant after controlling for PWB.

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Table II. Main study variables at T1 and T2 for the treatment and control groups

Group Treatment Control

Time T1 T2 T1 T2

Original baseline(n 5 98)

Retained baseline(n 5 74)

Follow-up(n 5 74)

Original baseline(n 5 101)

Retained baseline(n 5 44)

Follow-up(n 5 44)

VariableMean, (SD),

rangeMean, (SD),

rangeMean, (SD),

rangeMean, (SD),

rangeMean, (SD),

rangeMean, (SD),

rangeCPQ11-14 21.05 (15.09)

1.00-68.0021.63 (14.19)

3.00-68.0016.16 (10.99)*0.00-44.00

24.07 (16.15)3.00-80.00

24.07 (16.15)3.00-80.00

23.14 (17.97)2.00-73.00

OS 5.58 (3.40)0.00-17.00

5.75 (3.37)1.00-17.00

5.26 (3.15)0.00-13.00

5.93 (3.24)0.00-16.00

6.07 (3.59)0.00-16.00

6.34 (3.69)0.00-15.00

FL 5.09 (4.15)0.00-21.00

5.27 (4.15)0.00-21.00

5.41 (4.26)0.00-18.00

5.92 (4.95)0.00-23.00

5.36 (4.69)0.00-22.00

4.82 (4.57)0.00-17.00

EWB 5.19 (5.09)0.00-24.00

5.29 (5.14)0.00- 24.00

2.51 (2.96)*0.00-12.00

6.83 (5.59)0.00-22.00

6.75 (5.45)0.00-22.00

6.82 (7.56)0.00-29.00

SWB 5.18 (5.39)0.00-27.00

5.32 (5.46)0.00-27.00

2.99 (3.59)*0.00-17.00

6.01 (6.12)0.00-29.00

5.89 (6.13)0.00-29.00

5.16 (6.34)0.00-27.00

PWB 80.66 (10.09)51.56-100

79.78 (9.29)54.69-98.44

81.68 (10.52)46.88-98.44

78.33 (12.98)28.13-98.44

78.05 (11.7)48.44-98.44

78.84 (13.39)43.75-100

DAI 34.21 (8.18)17.00-58.40

33.72 (7.78)17.00-58.40

22.49 (2.86)*17.30-30.10

36.53 (8.89)20.00-74.80

36.25 (7.25)25.80-53.80

33.56 (7.14)23.60-44.40

*Paired t statistics significant at P\0.01.

372 Agou et al

RESULTS

Of the 118 study subjects in this study, 50% weregirls and 76% were white, with a mean age of 12.9 years(SD, 0.98) at T1. According to published DAI categories,44.2% of the overall sample had handicappingmalocclusions, 25.7% had severe malocclusions, 23.9%had definite malocclusions, and 6.2% had minor maloc-clusions.45

Although follow-up data were successfully obtainedfrom 118 subjects (74 treatment and 44 control), 199children were recruited at the start of the study. Toensure that the relatively large percentage of dropouts(40.71%) did not compromise the comparability of T1characteristics between the treatment and controlgroups, the data of the original and the retained subjectsfor the treatment and control groups were contrasted inTable II. The statistics indicated that all variables studiedwere comparable for both groups at T1. Hence, the sub-jects lost to follow-up did not influence the distributionof these variables.

Table II also summarizes the T2 data for the treat-ment and control subjects, with a guide to interpretingthese scores in Table I. The CPQ11-14, EWB, SWB, andDAI scores for the treatment subjects were the only vari-ables that changed significantly over the study period. Incontrast, these scores did not change significantly for thecontrol group. As expected, PWB scores remained rela-tively constant over time for both the treatment andcontrol subjects. Furthermore, these PWB scores were


slightly higher but not significantly different from thosereported for normal schoolchildren.43

As mentioned earlier, ANCOVA models were used totest the differences in reported OHRQOL between thetreatment and control subjects. Treatment status wasentered into the ANCOVA model as a fixed factor andtested for overall effect on CPQ11-14 overall and sub-scales scores at follow-up. For each scale, the first modelcontrolled for age, T1 scores, and initial severity of mal-occlusion (DAI), and the second model also controlledfor PWB. Table III provides a summary of the ANCOVAmodels and the total amount of variance explained byeach model.

The results indicated a significant difference in over-all CPQ11-14, SWB, and EWB scores between the treat-ment and control subjects (P \0.05). However, afterconsidering PWB as a covariate, the effect of providingorthodontic treatment was no longer significant, asmeasured by the overall CPQ11-14 and SWB scores(P 5 0.23). EWB was the only scale with the differencebetween treatment and control subjects remaining sig-nificant after controlling for clinical and psychologicalconfounders. To illustrate the results, the adjustedmean CPQ11-14, SWB, and, EWB scores for the treat-ment and control groups are presented in Table IV.

The contribution of DAI scores was not significant,with exception of the SWB subscale. DAI scores signifi-cantly contributed to the variance in SWB scores inboth ANCOVA models. In addition, age effects were


Table III. ANCOVA models showing contribution of covariates to overall and subscale (T2) CPQ11-14 scores

(T2) CPQ11-14 (T2) EWB (T2) SWB (T2) FL (T2) OS

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2F statistics F F F F F F F F F FAge 0.57 5.79y .023 1.59 0.00 1.60 3.17 6.80y 1.41 5.79*Baseline scores 6.51y 7.81y 1.89 2.09 6.52* 7.10y 5.27* 5.23* 3.45 3.77DAI 0.58 0.39 0.21 0.11 4.85* 4.88* 0.00 0.03 0.27 0.58PWB — 27.09y — 22.15y — 18.07y — 7.14y — 13.97y

Treatment status 4.17* 1.31 14.97y 10.17y 3.62* 1.29 1.47 3.29 1.77 0.31Corrected model 3.79y 8.9y 5.02y 9.08y 4.78y 7.88y 2.73* 3.71y 2.01 4.46y

Adjusted R2 0.09 0.26 0.13 0.27 0.12 0.24 0.06 0.11 0.04 0.14

Model 1 controls for age, DAI, baseline scores, and treatment status; model 2 controls for all variables in model 1 in addition to PWB status.*P\0.05; yP\0.01.

Table IV. Observed and adjusted mean (T2) CPQ11-14,EWB, and SWB scores

Scale Group

Observed scores Adjusted scores

Mean (SD) Mean (SE)CPQ11-14 Treatment 16.16 (10.99) 17.93 (1.44)*

Control 23.14 (17.97) 20.89 (1.90)*EWB Treatment 2.51 (2.96) 2.99 (0.57)y

Control 6.82 (7.56) 6.16 (0.76)y

SWB Treatment 3.03 (3.59) 3.48 (0.51)z

Control 5.29 (6.44) 4.50 (0.68)z

*Covariates appearing in the model were evaluated at the followingvalues: CPQ11-14, 22.47; DAI, 34.56, PWB, 80.52; yCovariates ap-pearing in the model were evaluated at the following values: EWB,5.70; DAI, 34.61; PWB, 80.43; zCovariates appearing in the modelwere evaluated at the following values: SWB, 5.38; DAI, 34.61;PWB, 80.43.

Agou et al 373

evident for the overall CPQ11-14, OS, and FL subscales.Nonetheless, these effects were apparent only after con-trolling for PWB. The mediating role of PWB was furtherexamined by adding “group by PWB status” as an inter-action term in a separate ANCOVA model (not includedin Table III). The results were statistically significantwith an F ratio of 7.01 (P \0.01) and an adjusted R2

of 26.8%. Since using normative reference groups is rec-ommended to meaningfully interpret the results fromquality of life surveys,46 we dichotomized PWB aroundthe mode (76.6%), which approximates the populationnorms published by Landgraf and Abetz43 andothers.47-49 We then examined the CPQ11-14 scores inthe high and low PWB groups at T1 and T2. The direc-tion of change was evaluated for both the treatmentand the control subjects (Table V).

DISCUSSION

Although medical studies have stressed the impor-tance of accounting for psychological parameterswhen quality of life is used as a primary outcome, a crit-ical analysis of orthodontic psychosocial outcome re-search shows that most studies failed to do so.50,51

Hence, our results are timely, filling a research gapidentified by many researchers.3,52 To the best of ourknowledge, this is the first controlled longitudinalstudy evaluating OHRQOL outcomes of orthodontictreatment in light of pretreatment psychologicalattributes. These results support the postulatedmediator role of PWB when evaluating OHRQOLoutcomes in children receiving orthodontic treatment.

The oral health impacts reported by our subjects werenot entirely dependent on the associated clinical condi-tions. Rather, PWB influenced the participants’ perceptionof oral health problems to a significant degree. Childrenreporting better PWB were more likely to report betterOHRQOL regardless of their treatment status. As hypothe-sized, the contribution of PWB to the variance in OHRQOL


was considerably greater for the SWB and EWB subscales,compared with the OS and FL subscales (Table III).

The lack of significant changes in the PWB constructover the study period conforms to the hedonic treadmilltheory, holding that well-being, for most people, isa relatively constant state.18 These data add to thebulk of evidence supporting this theory. The data alsoagree with other studies that invalidated the assumptionthat improving dental esthetics can have a significanteffect on a child’s PWB.17,53

This sample of Canadian children reported significantreductions in negative oral impacts after orthodontictreatment (mean CPQ11-14 reduction, 4.88; SD,14.57) compared with control subjects of similar age,sex, and dental condition (mean CPQ11-14 reduction,0.93; SD, 21.72). These results concur with other studieshighlighting the positive effect of orthodontic treatmenton OHRQOL.5,8,9 For instance, CPQ11-14 scores im-proved significantly after orthodontic treatment of chil-dren in Hong Kong.9 Similarly, de Oliveira and Sheiham,5

in a cross-sectional study of 1675 schoolchildren, found


Table V. Mean T1 and T2 CPQ11-14 scores for the treatment and control groups based on PWB status

PWB status* Treatment status Mean CPQ11-14 at T1, (SD), range Mean CPQ11-14 at T2, (SD), rangeLow PWB Treatment group (n 5 23) 24.00 (12.77)

6.00-54.0022.22 (11.16)6.00-44.00

Control group (n 5 19) 21.68 (14.67)5.00-63.00

30.00 (20.97)5.00-73.00

High PWB Treatment group (n 5 51) 20.88 (14.79)3.00-68.00

14.69 (9.57)3.00-39.00

Control group (n 5 25) 25.88 (17.26)3.00-80.00

17.92 (13.54)2.00-51.00

*High PWB, $76.6; low PWB,\76.6 (PWB was dichotomized around the mode based on published population norms).43,47-49

374 Agou et al

comparable treatment effects using other OHRQOLmeasures.

In-depth analysis of our data, however, showed thatthe effect of orthodontic treatment is less dramatic whenviewed in the context of the children’s psychologicalprofiles. The differences between the treatment and con-trol subjects clearly diminished after accounting for PWB(Table IV). Results from the multivariate analyses showedthat, for all scales, PWB explained additional variances inthe dependent variables (overall and subscale CPQ11-14scores). For example, the ANCOVA models accountingfor PWB explained about a third of the variance in over-all CPQ11-14, EWB, and SWB scores, with PWB contrib-uting the most to the explanatory power. This wasobserved for both the treatment and control subjects.As expected, the PWB of the children in this studyinfluenced reports of OS and FL to a lesser extent.

The PWB results of this study help to clarify the find-ings of earlier studies with the CPQ11-14 in orthodonticpatients; correlations between the CPQ11-14 and clini-cal indexes were weak.6,23,40 A recent meta-analysis,which concluded that determinants of quality of lifeare mainly psychological, also supports this explana-tion.38 Altogether, these results confirm the validity ofcontemporary conceptual models of disease and its con-sequences, and emphasize the importance of personal,social, and environmental factors in mediating patient-centered quality of life outcomes.32

Because some studies have affirmed the relationshipbetween malocclusion, orthodontic treatment, andreported OHRQOL, it seemed important to control forthe initial severity of the malocclusion and treatmentstatus. Less than 10% of the variance in overallCPQ11-14 scores was explained by the treatment statusalone, indicating a definite, but relatively small, effect.The results support the findings of a long-term Britishstudy that concluded that orthodontic treatment had lit-tle positive impact on psychological health and qualityof life in adulthood, when self-esteem at baseline wascontrolled for.53 Nevertheless, analyses of individual


CPQ11-14 subscales demonstrated that treatment ef-fects varied across the 4 subscales. The EWB subscalewas the only one for which treatment effects remainedsignificant after adjusting for other clinical and psycho-logical factors. Conversely, the SWB subscale was theonly scale to which the DAI scores made a significantcontribution, making this subscale the closest to corre-spond to objective treatment needs.

The associations between psychological factors andperceived social and emotional impacts of oral healthconcur with what has been previously reported for chil-dren, adolescents, and young adults.13,22,24-26,54-56

Overall, our study emphasizes the extent to whichpsychological factors can modify children’s perceptionsof their actual oral health status.

A closer examination of the items comprising eachscale helps to explain these findings. The EWB subscalefocuses on internal feelings such as being worried, em-barrassed, or concerned about looks. In contrast, theSWB subscale consists of items assessing the impactsof malocclusion on various social interactions, includingspeaking in class, social activities, smiling, talking toother children, and teasing by other children. It is alsoimportant to consider that the data were collectedshortly after the end of treatment. It is not surprisingthat orthodontic treatment did not have an immediateeffect on children’s SWB. Children might simply needtime to translate the emotional gains afer treatment totheir external environment. In general, the SWB andEWB findings concur with past studies documentingthe negative effects of malocclusion on children’slives.10,57-59

In addition, treatment effects varied depending onthe child’s PWB. In our study, children with high PWBscores were more likely to report significant improve-ment in OHRQOL after treatment, compared with thosewith low PWB scores (Table V). Evaluation of the overallsample suggests that there is a trend for CPQ11-14scores to improve over time regardless of treatmentstatus. Nevertheless, a closer evaluation of CPQ11-14


Agou et al 375

scores per PWB group (Table V) shows that children withlow PWB who did not receive orthodontic treatment hadworse CPQ11-14 scores over time than those whoreceived treatment.

This change in behavior of the CPQ11-14 after ac-counting for the PWB status highlights the importanceof considering the child’s psychological profile whenevaluating OHRQOL outcomes in orthodontics. How-ever, these results should be interpreted with cautionbecause of the small sample size in each group. Never-theless, the effect of PWB on reported OHRQOL is worthfurther investigation with larger samples and longerfollow-ups.

Information generated from this study will be ofgreat value to both clinical and policy-relevant research.Researchers interested in capturing the multi-dimensional aspects of oral health should consider thePWB of their subjects when designing their studies.Although some investigators might consider the PWBvariable as “noise,” it might also be an importantdeterminant of OHRQOL.37 Furthermore, the minor con-tribution of DAI scores to the variances in the CPQ11-14scores demonstrates the limitations of clinical indicatorsin interpreting OHRQOL data.

Clinically, the results support the argument that or-thodontists should include the psychological dimensionin their assessment when prioritizing treatment needsand evaluating outcomes. Since children with low PWBscores appeared to suffer more impacts from theirmalocclusion, it seems logical to grant them priorityfor orthodontic care. This could be achieved by usingproxy measures that reflect the children’s experiences,such as the self-reported CPQ11-14. Nevertheless, worseOHRQOL scores alone might not be sufficient to indicateclinically worse oral health. Further work is needed torefine existing OHRQOL measures to correspond moreclosely to objective health needs. For example, resultsfrom the CPQ11-14 subscale analyses can guide researchto develop short forms of this measure intended forspecific purposes.

There are some inherent limitations relevant to moststudies of orthodontic treatment. Since randomization isdifficult to achieve in orthodontics, a longitudinalobservational design offered the best and most feasiblealternative approach.19,60 Follow-up data confirmedour preliminary findings and established directionalitybetween OHRQOL and PWB.61 The control group helpedto draw conclusions related to treatment effects ratherthan changes stemming from the dynamic nature of psy-chological constructs in growing children.62 Despite thepersistence of our recall efforts, this study was also lim-ited by the relatively high attrition rate. This was mostlybecause some waiting-list patients sought alternative


care or relocated outside the city. Although it is possibleto assume that those who sought alternative treatmentwere those with worse malocclusion or worse PWB, thedistribution of the main T1 characteristics between theoriginal and the retained subjects was comparable, atleast for the variables measured (Table II). Nevertheless,the ANCOVA results should be interpreted with caution,especially considering the lack of randomization and theobservational nature of this study.63

It is important to reconsider the current biomedicaland restricted paradigm on OHRQOL and to begin tothink about the series of processes by which socialand psychological factors influence OHRQOL reports.64

This study lays the ground for developing a conceptualunderstanding of the interaction between reportedOHRQOL and a patient’s PWB. Although PWB ex-plained the variance in CPQ11-14 to a reasonableextent, the lack of comparable studies in the literaturemakes it difficult to generalize the findings. Further-more, the relatively low R2 values associated with themodels indicated that there could be other determi-nants of OHRQOL. For instance, the direct contributionof factors such as other oral health problems, socialsupport, and personality traits was not assessed inthis investigation. Hence, further work should beattempted to study these factors with larger samples,different age groups, and longer follow-ups to improvethe quantity and quality of orthodontic OHRQOL data.The use of complex structural equation modeling orpath analysis can also add to our understanding ofhow the various aspects of psychological health relateto patients’ OHRQOL. Thus, an impetus for furthermeaningful OHRQOL research in orthodontics will beprovided.

CONCLUSIONS

The findings of this study highlight the importance ofconsidering inherent psychological parameters in ortho-dontic psychosocial research. More specifically, theresults support the mediator role of PWB when evaluat-ing OHRQOL outcomes in children with a malocclusion.Children with better PWB are, in general, more likely toreport better OHRQOL regardless of their orthodontictreatment status. On the other hand, children with lowPWB, who did not receive orthodontic treatment,experienced worse OHRQOL, compared with those whoreceived treatment. This suggests that children withlow PWB might benefit from orthodontic treatment,but further work, with larger samples and longerfollow-ups, is needed to confirm this finding and to im-prove our understanding of how other psychologicalfactors relate to patients’ OHRQOL.


376 Agou et al

The author would like to acknowledge the orthodonticresidents and staff at the university of Toronto for theirhelp with this study.

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