Access to this full-text is provided by Springer Nature.
Content available from Health and Quality of Life Outcomes
This content is subject to copyright. Terms and conditions apply.
R E S E A R C H Open Access
Validation and reliability of the translated
Malay version of the psychosocial impact
of dental aesthetics questionnaire for
adolescents
Wan Nurazreena Wan Hassan
1*
, Zamros Yuzadi Mohd Yusof
2
, Siti Safuraa Zahirah Shahidan
3
,
Siti Farhana Mohd Ali
3
and Mohd Zambri Mohamed Makhbul
4
Abstract
Background: This paper describes the cross-cultural adaptation of the Psychosocial Impact of Dental Aesthetics
Questionnaire (PIDAQ) into Malay version (Malay PIDAQ), an oral health-related quality of life (OHRQoL) instrument
specific for orthodontics for Malaysian adolescents between 12 and 17 years old.
Methods: The PIDAQ was cross-culturally adapted into Malay version by forward- and backward-translation processes,
followed by psychometric validations. After initial investigation of the conceptual suitability of the measure for the
Malaysian population, the PIDAQ was translated into Malay, pilot tested and back translated into English. Psychometric
properties were examined across two age groups (319 subjects aged 12–14 and 217 subjects aged 15–17 years old) for
factor structure, internal consistency, reproducibility, discriminant and construct validity, criterion validity, and
assessment of floor and ceiling effects.
Results: Fit indices by confirmatory factor analysis showed good fit statistics (comparative fit index = 0.936, root-mean-
square error of approximation = 0.064) and invariance across age groups. Internal consistency and reproducibility tests
were satisfactory (Cronbach’sα= 0.71-0.91; intra-class correlations = 0.72-0.89). Significant differences in Malay PIDAQ
mean scores were observed between subjects with severe malocclusion and those with slight malocclusion based on
a self-rated and an investigator-rated malocclusion index, for all subscales and all age groups (p<0.05).Construct
validity of the Malay PIDAQ subscales with those who rated themselves with excellent to poor dental appearance and
those who felt they needed or did not need braces, showed significant associations for all age groups (p<0.05).
Criterion validity also showed significant association between the Malay PIDAQ scores with those with and without
impact on daily activities attributed to malocclusion. There were no ceiling effects detected but floor effects were
detected for the Aesthetic Concern subscale.
Conclusion: The study has provided initial evidence for the validity and reliability of the Malay PIDAQ to assess the
impact of malocclusion on the OHRQoL of 12–17 year old Malaysian adolescents.
Keywords: Malocclusion, Oral Health-Related Quality of life, Adolescent, Reliability, Validity
* Correspondence: wannurazreena@um.edu.my
1
Department of Paediatric Dentistry and Orthodontics, Faculty of Dentistry,
University of Malaya, 50603 Kuala Lumpur, Malaysia
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23
DOI 10.1186/s12955-017-0600-5
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Dental malocclusions comprise a wide spectrum of den-
tal arrangements perceived as aesthetically poor, such as
protruding teeth, crowded or crooked teeth, and spacing.
These are often reasons for seeking orthodontic treat-
ment among adolescents regardless of the severity of the
malocclusion. In resource limited health care systems,
priority is given to those with greater need for treatment.
Indices such as the Index of Orthodontic Treatment
Need (IOTN) provide an objective measure for classify-
ing treatment need [1]. In Malaysia, IOTN is often used
to recommend treatment under the national healthcare
system. Clinical impression where even those of lower
grades who were advised not to have treatment would
still seek treatment at private practices suggests that
there may be other underlying factors that may influence
desire for treatment such as the psychosocial impact of
malocclusion on their oral health-related quality of life
(OHRQoL). However, this could not be measured using
such previously mentioned clinical indices which were de-
veloped by expert consensus based on health, functional
and aesthetic grounds.
In Malaysia, a large population study comprising a
sample of 5,112 school children aged between 12–13 years
old found a high prevalence of orthodontic treatment
need with 47.9% school children having IOTN-DHC
scores of 4 and above [2]. In a more recent study on 837
school children in Malaysia, it was found that 51.4%
of 12-year-olds and 56.4% of 16-year-olds had IOTN-
DHC scores of 4 and above [3]. This implies that the
percentage of school children in Malaysia who require
orthodontic treatment has remained high over the
decade between the studies. Despite similar propor-
tions needing orthodontic treatment, Zreaqat et al. [3]
found a statistically significant higher demand for
orthodontic correction among the older school chil-
dren with 42.7% of 16-year-olds desiring treatment
against only 22% of the younger age group (p< 0.001).
The discrepancy in demand suggests a need to deter-
mine if patients’desire for treatment is related to the
negative impact of malocclusion on their OHRQoL
and, if so, to give added support to prioritise these
patients for treatment.
OHRQoL measures have gained wide interest among
clinicians and researchers as instruments for evaluation
of patients’subjective interpretation of the impact of oral
health on their quality of life. Malocclusion is a unique
aspect of oral health in which unsatisfactory dental
aesthetics are more frequently reported reasons for
seeking treatment to improve patient’s well-being rather
than for functional need and failure to treat would not
necessarily cause physical pain, disability or become a
handicap. Few instruments have been developed which
include conditioned-specific impacts to assess need for
orthodontic treatment [4–6]. Furthermore, any instru-
ments used should be age appropriate as measures de-
veloped for adults may not be suitable for adolescents,
who comprise the majority of orthodontic patients. The
instruments also need to be validated for the specific
population. Although the Oral Health Impact Profile
(OHIP) [7, 8] and Child Oral Impacts on Daily Perfor-
mances (Child-OIDP) index [9] have been cross-culturally
adapted and validated for the Malaysian population, nei-
ther the OHIP nor Child-OIDP were specifically designed
to evaluate subjective impacts due to malocclusion but
were modified to allow assessment relevant to ortho-
dontics. Thus there is a need for a condition-specific
OHRQoL measure of malocclusion for the Malaysian
population.
The Psychosocial Impact of Dental Aesthetics Ques-
tionnaire (PIDAQ) focuses only on the impact of dental
appearance and arrangement on OHRQoL, which is the
most common reason for seeking orthodontic treatment.
It comprises four domains with 23 items: the Dental
Self-Confidence (DSC) domain measures positive dental
concept and comprises 6 items that assess dental
appearance; the Social Impact (SI) domain assesses inter-
personal sensitivity and comprises 8 items that measure
anxiety levels towards other people’s reaction to the ap-
pearance of the subject’s teeth; the Psychological Impact
domain (PI) comprises 6 items that assess negative emo-
tions towards one’s dental appearance; and the Aesthetic
Concern (AC) domain contains 3 items that assess
disapproval of the image of one’s exposed dentition [10].
Three of the PIDAQ subscales were developed from
scales which were able to discriminate subjects with
excellent dental aesthetics and those with only minor
irregularities as determined by IOTN-AC [6]: the DSC
was adapted from the Self-Confidence Scale [11, 12], SI
from the Social Aspect Scale of the Orthodontic Quality
of Life Questionnaire (OQLQ) and AC from the Aes-
thetic Scale of the OQLQ [4, 5]. PI items were developed
in addition to the rest of the domains [6]. The PIDAQ
was specifically developed to assess perceived need for
orthodontic treatment, with potential for use for asses-
sing changes to the patient’s well-being under treatment,
distinguishing patients’and providers’perspectives and
values as well as documenting the impact of orthodontic
treatment for health policy discussions and setting of
clinical guidelines [6]. Originally developed in German
for young adults between 18 to 30 years old [6], it
has shown good cross-cultural psychometric proper-
ties [13–17]. More recently, it has been adapted for
younger adolescents and in various languages [18, 19].
Klages et al. [10] have also demonstrated that the
instrument adapted for German adolescents showed
good psychometric properties across the range of ages
11 to 17.
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 2 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Until this study, the PIDAQ has been neither trans-
lated nor validated for the Malaysian adolescent popula-
tion. Thus, this study aimed to conduct a cross-cultural
adaptation of PIDAQ into Malay version and assess the
psychometric properties of the Malay PIDAQ for use by
Malaysian adolescents.
Methods
The cross-cultural adaptation of the PIDAQ into Malay
version comprised two parts: linguistic and psychometric
validations. The linguistic validation comprised the
initial translation of PIDAQ into Malay, a pre-test for
the Malay version, then a back translation and final
review of the draft Malay PIDAQ. The psychometric
validation consisted of assessing the Malay PIDAQ’s
internal reliability, reproducibility, construct, criterion
and discriminant validities, and floor and ceiling effects.
Translation
The PIDAQ with 23 items comprises a positive subscale
measuring the domain of DSC (6 items), and 3 negative
subscales measuring the domains of SI (8 items), PI
(6 items) and AC (3 items). It was originally written
in German but has been published in English. In this
study, both the published original and adolescent versions
were reviewed. First, the PIDAQ adolescent version was
translated from English into Malay by six individuals who
were Malay-English bilinguals. All were of Malay ethnicity
and were proficient in both languages. The group of trans-
lators comprised an expert in OHRQoL measures and
questionnaire validation (ZYMY), two orthodontists
(WNWH, MZMM) who were expert in the field of aes-
thetic dentistry, two undergraduate students (SSS, SFMA)
who represented the youth perspective and a secondary
school teacher (SY) who taught Malay language. The
initial translations were done independently.
Following the translation process, two authors
(WNWH and ZYMY) met and compared and analyzed
all translations in terms of content and wording while
paying attention to conceptual and item equivalence be-
tween the original index and its Malay version. Follow-
ing the meeting, a single consensus translation called the
draft Malay PIDAQ was agreed. All authors agreed to
add a not relevant option to the question on Don’t like
own teeth on video as it was felt that not all Malaysian
school children have access to a video recorder
(including smart phones). This was later confirmed
during the pilot test.
Next, the draft Malay PIDAQ was pilot tested on 7
school children aged 12–14 years and 15 school children
aged 15–17 years from the orthodontic waiting list. The
pilot test was conducted by SSS and SFMA under the
observation of WNWH on separate sessions for each
age group. The 22 school children were asked to
complete the questionnaire. The time taken to complete
the questionnaire was noted to test the practicality of
the questionnaire administration under fieldwork condi-
tion. Following the test, the researchers held a discussion
with the schoolchildren to assess their understanding
of the questionnaire’s instructions, content, answer
options and wording. Words that were ambiguous
were highlighted, discussed and replaced with other
words with similar but clearer meanings. For example,
it was found that the Malay translated verb for the word
‘self-conscious’describing the item as Shy because of own
teeth was hard for the participants to understand. The cor-
responding adult version for this item was compared and
the translated Malay item was agreed to be acceptable and
understood by the school children. Following the pilot
test, a meeting was held among the researchers (SSS,
SFMA, WNWH and ZYMM) to discuss the outcomes of
the pilot test before changes to the draft Malay PIDAQ
were agreed to.
The second step involved back translation of the draft
Malay PIDAQ into English. This was independently
carried out by the Malaysia Institute of Translation &
Books. Then, the output of the back translation was
thoroughly discussed (by WNWH and ZYMY), compar-
ing the back translation with the original PIDAQ. After
minor modifications, the back translation of the Malay
PIDAQ was verified and the draft Malay PIDAQ was
finalized.
Psychometric validation
Subsequently, the psychometric properties of the Malay
PIDAQ were tested on 12 to 17-year-old non-randomly
selected participants who had not been involved in the
pilot study. Sample size calculation included the consid-
eration for detecting mis-specified factor loadings com-
paring the two age-groups using A-priori Sample Size
Calculator for Structural Equation Models [20]. Given 4
PIDAQ subscales with 23 items, the recommended
sample size for each age group at a power level of 0.80
and a probability level of 0.05 for model structure was
166 [21, 22]. This concurred with the rule-of-thumb
guideline of 4 to 10 subjects per variable [23].
The questionnaire was self-administrated. Participants
were classified into two age groups: 12–14 years old and
15–17 years old. For each age group, the participants
completed the questionnaire either in a classroom set-
ting or in the orthodontic clinic waiting area. Excluded
were those having or having had orthodontic treatment
and those with craniofacial deformities. The former were
excluded to avoid confusion when the students were
assessed using the Aesthetic Component of the Index of
Orthodontic Treatment Need (IOTN-AC) while the
latter were excluded to avoid the possibility that the
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 3 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
psychosocial impact was due to deformity of the cranio-
facial features rather than due to dental aesthetics.
Participants indicated their agreement to each of the
23 items on a five-point Likert scale: not at all,a little,
somewhat,strongly and very strongly. The responses
were coded from 1 to 5 [10]. Scores for each subscale
were tabulated by the sum of their items. Impact attrib-
uted to dental aesthetics was evaluated based on total
PIDAQ scores, with the positive domain DSC values re-
verse scored. Thus, higher total scores would indicate a
greater degree of negative psychosocial impact and a
poorer OHRQoL accounted for by dental aesthetics [24].
Data was analyzed using IBM-SPSS-AMOS v.20 and
IBM-SPSS-Statistics v.20. Chi-squared test and Fisher
exact-test were used to compare equality of the propor-
tions of the demographics between age groups while in-
dependent t-test was used to compare the total PIDAQ
scores of the two age groups. Internal consistency was
measured by confirmatory factor analysis (CFA), and
Cronbach’sαfor each subscale. CFA was determined by
calculating estimates of the maximum likelihood discrep-
ancy. Goodness of fit of the observed data to the model
was based on a comparative fit index (CFI) ≥0.90 and
root-mean-square error of estimation (RMSEA) < 0.08
[25]. Multiple group comparison determined measure-
ment invariance between the two age groups. Invariance
was assessed by comparing the measurement weights and
the structural covariance models with the baseline uncon-
strained configural model. In the measurement weights
model, the factor loadings were constrained equally across
groups while in the structural covariance model, all
estimated factor loadings as well as factor variances and
covariances were constrained to be equal across groups
[25]. Measurement invariance was based on a difference
in CFI values at a cut-off value of 0.01 (i.e. ΔCFI >
0.01 indicates non-invariance) [25, 26]. Subscales with
Cronbach’sαof between 0.70 and 0.95 were consid-
ered to have good internal consistency [27].
The PIDAQ was developed to assess treatment need
in patients requesting orthodontic treatment [6]; it
measures orthodontic-specific quality of life outcomes
[10]. Based on a previous study [10], the discriminant
validity of the Malay PIDAQ was tested by comparing
its relationship with self-rated and investigator-rated
perceived need for orthodontic treatment: IOTN-AC
and the awareness component of the Perception of
Occlusion Scale (POS). The IOTN-AC was rated using a
black and white photographic 10-point-scale showing
teeth with increasing severity of malocclusion [28]. The
POS component comprised 6 items of malocclusion
traits [29], where participants were required to evaluate
each item on a 5-point Likert scale from not at all to
very strongly. The self-rated and investigator-rated
Malocclusion Index (MI-S and MI-D, respectively) were
adapted from the study by Klages et al. [10] for analysis
of the severity of malocclusion where the scores of the
IOTN-AC and total scores of the POS were standard-
ized, summed up and divided by 2 to give an index value
with a 0 mean value . Four investigators (WNWH, SSZS,
SFMA and MZMM) calibrated the MI-D using 40 sets
of study models, assessed twice two weeks apart. The
inter-operator intra-class correlation (ICC) MI-D score
at T1 was 0.96 (p = 0.00; 95% CI = 0.93 to 0.97). Intra-
operator ICC MI-D scores were also excellent at above
0.75 (p = 0.00) [30]: the ICC scores were 0.95 (95%
CI = 0.90 to 0.97), 0.85 (95% CI = 0.71 to 0.92), 0.91 (95%
CI = 0.83 to 0.95) and 0.91 (95% CI = 0.83 to 0.95). Inde-
pendent t-test was applied to compare the relationship
between the PIDAQ subscales with the malocclusion
index (MI-S/MI-D) scores of those with no or slight
malocclusion (lower quartiles) and those with severe
malocclusion (upper quartiles).
Construct validity of the Malay PIDAQ was tested by
comparing the PIDAQ with other measures measuring
related constructs, i.e. perceived dental appearance rank
and need for braces. Ranking of perceived dental appear-
ance required the participants to rate their dental
appearance as excellent,good,average or poor. The par-
ticipants were also asked if they needed braces to correct
their teeth with response options of yes,no and don’t
know. Criterion validity was tested against the condition-
specific scores of the Child Oral Impacts on Daily Per-
formances (CS-OIDP) index [31], which measures im-
pact of teeth on daily activities. Malocclusions were
accounted for Spaces between and Position of the teeth
[32]. Although Deformity of the mouth and face was
considered as a condition-specific item, none of the par-
ticipants reported any impact from this item since the
study excluded those with craniofacial deformities. The
CS-OIDP performance score was tabulated by adding
the product of the frequency (scale from 1 to 3) multi-
plied by the severity (scale from 1 to 3) of the impact
in any of the 8 daily activities, i.e. cleaning teeth, eat-
ing, emotional stability, smiling, speaking, relaxing,
doing schoolwork and socializing. Scores were tabu-
lated only when the impact was due to malocclusion
and recorded as 0 if there was no impact due to mal-
occlusion on the 8 daily activities. The Kruskal-Wallis
test was used to assess the relationship between
PIDAQ scores and perceived dental appearance rank.
The Mann–Whitney statistics were used to assess the
relationship between PIDAQ scores and the need for
braces, and between PIDAQ scores with those who
reported the presence or absence of CS-OIDP. The
Pearson correlation coefficient was calculated to
assess the relationship between PIDAQ scores and
CS-OIDP total performance scores on the eight daily
activities.
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 4 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
The reproducibility of the Malay PIDAQ was tested by
asking approximately 30% of the subjects to re-answer
the questionnaire approximately 2 weeks later. The
standard error of measurement (SEM) was calculated as
the square root of the residual variance of the ANOVA
analysis, and the smallest detectable change (SDC) was
calculated as 1.96 x √2 x SEM [27, 33]. Paired t-test was
done to determine any significant change to the scores
of the PIDAQ subscales between the first and the second
test administrations. The limits of agreement was calcu-
lated as mean change ± 1.96 x standard deviation of the
changes [34]. The ICC for absolute agreement by two-
way random effects models was calculated, but a
weighted Kappa coefficient was not determined since a
weighted Kappa with quadratic weights was considered
identical to ICC
agreement
[27].
Floor and ceiling effects within each subscale were
calculated as the percentage of the achieved lowest and
highest possible scores. Floor or ceiling effects were con-
sidered present if the prevalence of the highest or lowest
possible scores was more than 15% [27].
Results
The participants comprised 319 and 271 subjects from
the younger (12–14 years old) and older (15–17 years
old) age groups, respectively. The proportions of the
participants between the younger and older age groups
were equally distributed and variation was not statisti-
cally significant (p> 0.05) by gender, source of recruit-
ment, ethnicity and severity of malocclusion (Table 1).
Initial analysis showed that a relatively large propor-
tion of the participants (14.2%; n= 84) chose not relevant
for the item Don’t like own teeth on video, which indi-
cated that this item was relatively not relevant to their
situation. Therefore, based on recommendation of hand-
ling items with large proportion of responses that could
not relate the items to the participants [35] and follow-
ing discussions among the authors, it was decided that
the item Don’t like own teeth on video was removed from
the AC subscale of the PIDAQ. Thus, the subsequent
psychometric analyses were based on the shortened
version of the Malay PIDAQ that consisted of 22 instead
of 23 items.
Histogram for the younger, older and overall age
groups showed normal distribution of participants’
total PIDAQ scores. Overall, the mean score was 58.0
(SD = 17.8; Range = 22–110). For the younger age
group, the mean score was 58.3 (SD = 18.32; Range =
22–110) and for the older age group, the mean score
was 57.4 (SD = 18.0; Range = 22–104). Independent t-
test analysis showed that the difference between the
mean PIDAQ scores of the two age groups was not
statistically significant (p> 0.05).
The goodness-of-fit measures showed good data-fit:
for both models A and B, the CFI scores were above
0.90 while the RMSEA scores were less than 0.08 with
small confidence interval (Table 2). The factor loadings
of Model A and that constrained for the age groups
(Model B) were within the acceptable range except for
the item wish to look better which had factor loadings
that were less than 0.50. The multi-group CFA test of
the constrained models with the baseline configural
model showed invariance across the age groups (ΔCFI <
0.01). The measurement weights model had a CFI value
of 0.926 (ΔCFI = 0.002) while the structural covariance
model had a CFI value of 0.921 (ΔCFI = 0.007).
Table 3 shows the internal consistency of the subscales,
scale statistics and inter-item correlations of the subscales.
All subscales satisfactorily achieved Cronbach’sαvalues of
between 0.70 and 0.95. None of the inter-item correlations
were ≥0.90 for all subscales or ≤0.30 for the DSC, SI and
AC subscales. For the PI subscale, the items with
inter-item correlations below 0.30 were: between Wish
to look better and Distressed because of others’nice
teeth (12–14 years = 0.25; all ages = 0.29), Unhappy
about own teeth (12–14 years = 0.23; all ages = 0.29)
and Feel bad about own teeth (12–14 years = 0.27; all
ages = 0.29). None of the item total correlations scores
were < 0.30.
Table 1 Demographic and clinical characteristics of the
participants
Demographics 12-14 years (N) 15-17 years (N) p-value
Gender 0.163
Male 137 132
Female 182 139
Venue 0.051
Orthodontic clinics 40 50
Schools 279 221
Ethnicity 0.156
c
Malay 248 190
Chinese 46 50
Indian 21 28
Others 4 3
a
Severity of malocclusion (Self-rated) 0.693
Lower quartile 81 66
Middle quartile 163 133
Upper quartile 75 72
b
Severity of malocclusion (Investigator-rated) 0.376
Lower quartile 86 61
Middle quartile 152 143
Upper quartile 81 67
a
Self-rated Malocclusion Index (MI-S);
b
Investigator-rated Malocclusion Index
(MI-D);
c
Fisher exact-test, Otherwise Chi-square test
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 5 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 4 shows there were statistically significant differ-
ences in Malay PIDAQ mean scores between adolescents
who rated themselves (MI-S) with no or slight malocclu-
sion and those with severe malocclusions for all sub-
scales in all age groups (p< 0.01). Similarly, statistically
significant differences were observed in mean scores be-
tween adolescents who were rated by the investigators
(MI-D) with no or slight malocclusion and those with
severe malocclusions for all subscales in all age groups
(p< 0.01). In all the three age groups, comparison
between MI-S and MI-D showed that DSC mean scores
reduced with increasing severity of the malocclusion. In
contrast, SI, PI and AC subscale mean scores increased
with increasing severity of malocclusion.
Self-endorsement of the participants’dental appear-
ance showed statistically significant associations between
Malay PIDAQ subscales and self-perceived dental
appearance (p< 0.01) for all age groups (Table 5). For
the DSC subscale, the mean scores gradually decreased
as participants rated their teeth from excellent to poor.
The trend was statistically significant. Conversely, the
trend in PIDAQ mean scores increased in SI, PI, and AC
subscales for all age groups as participants rated their
teeth from excellent to poor. The trend was statistically
significant.
The associations between self-perceived need for
braces and PIDAQ subscales for all age groups were
statistically significant (Table 6). Those who perceived
that they needed braces had significantly lower DSC sub-
scale mean scores and significantly higher SI, PI and AC
subscale mean scores than did those who perceived that
they did not need braces.
Table 7 shows the association between the presence of
CS-OIDP impact and Malay PIDAQ subscales. Those
with CS-OIDP impacts had significantly lower DSC
subscale mean scores and significantly higher SI, PI and
AC subscale mean scores than those without CS-OIDP
impacts. The trend was statistically significant for all age
groups (p< 0.01).
Analysis using Pearson correlation coefficient showed
that the CS-OIDP performance scores had a weak statis-
tically significant negative correlation with DSC subscale
mean scores for all age groups (Table 7). Conversely, the
CS-OIDP performance scores showed a weak to moder-
ate statistically significant positive correlation with SI, PI
and AC subscale scores for all age groups.
Table 8 shows the findings of the Malay PIDAQ repro-
ducibility test. The ICC values were above 0.70 (p< 0.05)
for all subscales in all age groups. No statistically signifi-
cant differences were found between the first and second
test administration except for the PI subscale in the
younger age group. The smallest detectable change
(SDC) seemed to be higher in the younger age group for
all subscales. Bland and Altman analysis showed that
Table 2 Multi-group confirmatory factor analysis showing
standardized parameter estimates and fit indices
MODEL A MODEL B
(Baseline Configural Model)
N 590 319 271
Age-group 12–17 years 12–14 years 15–17 years
Fit Indices
Comparative Fit Index 0.936 0.928
Root Mean Square
Error of Approximation
(90% CI)
0.064 (0.059-0.070) 0.049 (0.045-0.053)
Items in Brief Factor loading Factor loading
Dental Self-Confidence
•Proud of own teeth 0.80 0.78 0.83
•Like to show their
teeth
0.56 0.54 0.61
•Pleased to see own
teeth in mirror
0.86 0.84 0.88
•Teeth look nice to
others
0.67 0.68 0.67
•Satisfied with own
teeth’s appearance
0.79 0.79 0.77
•Find own teeth nice 0.76 0.73 0.78
Social Impact
•Hold back their smile 0.68 0.63 0.75
•What others think 0.63 0.59 0.67
•Teasing 0.78 0.74 0.83
•People look strange
at my teeth
0.78 0.80 0.77
•Shy because of own
teeth
0.75 0.75 0.76
•Hiding own teeth 0.74 0.77 0.72
•Stupid comments
from others
0.65 0.59 0.72
•Boys/girls find own
teeth ugly
0.77 0.79 0.75
Psychological Impact
•Envy others for their
teeth
0.66 0.62 0.71
•Distressed because of
others’nice teeth
0.86 0.85 0.88
•Unhappy about own
teeth
0.83 0.81 0.86
•Others have nicer
teeth
0.63 0.54 0.73
•Feel bad about own
teeth
0.77 0.73 0.82
•Wish to look better 0.38 0.33 0.43
Aesthetic Concern
•Don’t like own teeth
in mirror
0.75 0.74 0.77
•Don’t like own teeth
on photos
0.73 0.74 0.72
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 6 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
more than 90% of the scores of repeated measurements
were within the limits of agreement except for AC
subscale for the younger age group at 78.6%.
None of floor and ceiling effects for all subscales were
above the cut-off value of 15% in all age groups except
for the AC subscale for the younger age group and over-
all age group (Table 9). AC subscale had the highest
prevalence of the floor effects of between 14.8%-16.3%
in all age groups.
Discussion
The cross-cultural adaptation of the Malay PIDAQ based
its protocols on those of previous studies [9, 10, 19] and
on OHRQoL expert advice and recommendations
[27, 36]. Herdman et al. [36] outlined 6 steps for cross-
cultural adaptation of an index, which are conceptual,
item, semantic, operational, measurement and functional
equivalences. In brief, conceptual equivalence ascertains
that the answers to each question reflect the same concept
so that they are meaningful in both cultures and languages
concerned. Item equivalence is concerned that the item
estimates the same parameters on the latent trait being
measured. Semantic equivalence establishes that the
meaning of the item is equally maintained after tran-
slation. Operational equivalence is concerned with the
possibility to use similar format, instructions, mode of ad-
ministration and measuring methods, while measurement
equivalence refers to the achievement of acceptable similar
psychometric properties. Functional equivalence is the
extent to which the instrument does what it is supposed to
do equally well in two or more cultures and is considered
achieved when all other types of equivalence in the model
have been achieved.
The sample age range included the expected age of the
5-year-period of secondary school children in Malaysia
from Form 1 (12–13 years old) to Form 5 (16–17 years
old). The age range was similar to those commonly seen
to request for orthodontic treatment at the Malaysia
Ministry of Health orthodontic clinics. Unless early
interceptive treatment is required, referrals to orthodon-
tic specialists by dental officers will be done only when
all permanent teeth have erupted, which is usually by
around 12 years of age. At these government-sponsored
institutions, treatment is offered free of charge to
children whose parents are in the government service or
at very minimal fees to those whose parents don’t work
for the government. The considerably lower cost for
treatment at these clinics compared with that in private
practices is a major reason for the high treatment
demand at these institutions. Due to limited resources,
treatment at these institutions is offered only to school-
children and adults who require multidisciplinary man-
agement. Therefore, this study focuses on this adolescent
age group where evidence of impact on their OHRQoL
maybeofinteresttonationalhealthpolicymakersinde-
termining services offered to them. Klages et al. [10] has
advocated controlling the quality of the test for the validity
of the PIDAQ for adolescents by narrowing the age range
of the study age groups. Division of the age range for this
study was influenced by the Ministry of Education’spolicy
that does not permit data collection from students taking
national examinations, that is, the Form 3 and Form 5
Table 3 Internal consistency, scale statistics and inter-item correlations of the Malay PIDAQ subscales
N Cronbach’sαScale statistics Inter-item correlations Item total correlation
Mean SD Mean Min Max Min Max
12-14 years
Dental Self-Confidence 319 0.87 18.73 5.61 0.53 0.35 0.69 0.49 0.77
Social Impact 319 0.88 19.40 7.30 0.50 0.31 0.69 0.56 0.75
Psychological Impact 319 0.82 17.27 5.12 0.43 0.23 0.71 0.36 0.72
Aesthetic Concern 319 0.71 4.58 2.01 0.55 0.55 0.55 0.55 0.55
15-17 years
Dental Self-Confidence 271 0.89 19.36 5.59 0.57 0.37 0.74 0.57 0.83
Social Impact 271 0.91 18.82 7.14 0.56 0.45 0.69 0.63 0.78
Psychological Impact 271 0.88 17.23 5.57 0.55 0.31 0.76 0.45 0.79
Aesthetic Concern 271 0.71 4.74 1.91 0.56 0.56 0.56 0.56 0.56
12-17 years
Dental Self-Confidence 590 0.88 19.02 5.61 0.55 0.36 0.71 0.53 0.80
Social Impact 590 0.89 19.13 7.23 0.52 0.39 0.68 0.59 0.75
Psychological Impact 590 0.85 17.25 5.33 0.48 0.29 0.73 0.40 0.75
Aesthetic Concern 590 0.71 4.65 1.97 0.55 0.55 0.55 0.55 0.55
SD standard deviation
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 7 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 4 Discriminant validity of the Malay PIDAQ with self-rated (MI-S) and interviewer-rated (MI-D) malocclusions
Self-rated Index (MI-S)
Age group 12-14 years 15-17 years 12-17 years
Quartile (Self-perceived
malocclusion level)
Lower (Slight) Upper (Severe) Effect size pvalue Lower (Slight) Upper (Severe) Effect size p value Lower (Slight) Upper (Severe) Effect size pvalue
n 81 77 66 63 147 147
Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
Dental Self-Confidence 22.65 (4.88) 13.97 (4.48) 1.86 0.00* 23.92 (4.54) 15.17 (4.32) 1.99 0.00* 23.22 (4.76) 14.65 (4.50) 1.86 0.00*
Social Impact 15.84 (6.64) 24.51 (7.45) −1.24 0.00* 13.83 (4.93) 24.41 (7.13) −1.88 0.00* 14.94 (6.00) 24.35 (7.32) −1.44 0.00*
Psychological Impact 14.32 (4.47) 21.00 (4.86) −1.41 0.00* 13.50 (4.44) 21.92 (4.98) −1.80 0.00* 13.95 (4.57) 21.29 (4.92) −1.55 0.00*
Aesthetic Concern 3.35 (1.51) 6.09 (2.08) −1.61 0.00* 3.35 (1.28) 6.25 (1.93) −1.94 0.00* 3.35 (1.41) 6.10 (1.99) −1.69 0.00*
Investigator-rated Index (MI-D)
Age group 12-14 years 15-17 years 12-17 years
Quartile (Investigator-rated
malocclusion level)
Lower (Slight) Upper (Severe) Effect size pvalue Lower (Slight) Upper (Severe) Effect size p value Lower (Slight) Upper (Severe) Effect size pvalue
n 75 81 63 67 147 148
Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
Dental Self-Confidence 25.65 (5.14) 16.72 (5.23) 0.96 0.00* 21.56 (5.49) 17.10 (5.86) 0.79 0.00* 21.71 (5.04) 16.89 (5.51) 0.92 0.00*
Social Impact 17.19 (6.65) 20.72 (7.27) −0.51 0.00* 16.48 (6.36) 22.60 (7.96) −0.87 0.00* 16.63 (6.32) 21.57 (7.62) −0.72 0.00*
Psychological Impact 15.92 (4.76) 18.33 (4.91) −0.50 0.00* 15.02 (4.98) 19.54 (6.03) −0.83 0.00* 15.43 (4.64) 18.88 (5.46) −0.69 0.00*
Aesthetic Concern 3.72 (1.66) 5.19 (1.92) −0.82 0.00* 4.11 (1.64) 5.52 (2.08) −0.77 0.00* 3.84 (1.59) 5.34 (2.00) −0.85 0.00*
SD standard deviation
*p < 0.05
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 8 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 5 Construct validity of Malay PIDAQ with regards to ranking of self-perceived dental appearance
PIDAQ variables Rate appearance N PIDAQ scores pvalue
Mean SD Quartiles
Lower Middle Upper
12-14 years
Dental Self-Confidence Excellent 40 22.88 5.11 20.00 24.00 26.75 0.00*
Good 156 21.06 4.34 18.00 21.00 24.00
Average 94 15.49 3.78 12.75 15.00 17.00
Poor 29 10.97 4.19 8.00 10.00 13.00
Social Impact Excellent 40 14.73 5.68 10.00 14.00 18.00 0.00*
Good 156 17.59 5.75 13.00 17.00 21.75
Average 94 21.34 6.83 16.00 21.00 25.25
Poor 29 29.28 7.75 25.50 29.00 35.50
Psychological Impact Excellent 40 13.40 3.52 11.00 13.00 16.00 0.00*
Good 156 15.96 4.01 13.00 16.00 19.00
Average 94 18.55 4.43 15.00 18.00 21.00
Poor 29 25.52 4.41 24.00 25.00 29.00
Aesthetic Concern Excellent 40 3.70 1.68 2.25 3.00 4.00 0.00*
Good 156 3.90 1.60 3.00 4.00 5.00
Average 94 5.18 1.73 4.00 5.00 6.00
Poor 29 7.52 2.01 6.50 8.00 9.00
15-17 years
Dental Self-Confidence Excellent 37 25.00 5.76 23.00 27.00 29.00 0.00*
Good 127 21.29 4.19 18.00 21.00 25.00
Average 88 15.76 3.08 14.00 15.50 18.00
Poor 19 12.05 4.56 8.00 12.00 16.00
Social Impact Excellent 37 14.84 6.47 9.00 15.00 18.00 0.00*
Good 127 16.26 5.25 12.00 16.00 19.00
Average 88 21.80 6.19 17.00 21.00 26.00
Poor 19 29.89 7.10 28.00 32.00 33.00
Psychological Impact Excellent 37 13.24 4.97 10.00 12.00 16.25 0.00*
Good 127 15.12 3.96 12.00 15.00 18.00
Average 88 20.20 4.52 16.00 20.00 23.75
Poor 19 25.26 5.59 25.00 26.00 29.00
Aesthetic Concern Excellent 37 3.46 1.63 2.00 3.00 4.00 0.00*
Good 127 4.02 1.48 3.00 4.00 5.00
Average 88 5.72 1.46 5.00 6.00 7.00
Poor 19 7.47 2.12 6.00 7.00 10.00
12-17 years
Dental Self-Confidence Excellent 77 23.90 5.50 21.00 25.00 28.00 0.00*
Good 283 21.17 4.27 18.00 21.00 25.00
Average 182 15.62 3.45 13.00 15.00 18.00
Poor 48 11.40 4.33 8.00 11.50 13.00
Social Impact Excellent 77 14.78 6.03 10.00 15.00 18.00 0.00*
Good 283 16.99 5.56 13.00 17.00 21.00
Average 182 21.56 6.51 17.00 21.00 26.00
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 9 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Table 5 Construct validity of Malay PIDAQ with regards to ranking of self-perceived dental appearance (Continued)
Poor 48 29.52 7.43 26.00 30.00 34.75
Psychological Impact Excellent 77 13.32 4.25 10.00 13.00 16.00 0.00*
Good 283 15.58 4.00 13.00 16.00 18.00
Average 182 19.35 4.54 16.00 19.00 22.00
Poor 48 25.42 4.86 24.00 26.00 29.00
Aesthetic Concern Excellent 77 3.58 1.65 2.00 3.00 4.00 0.00*
Good 283 3.96 1.55 3.00 4.00 5.00
Average 182 5.43 1.63 4.00 5.00 6.00
Poor 48 7.50 2.03 6.00 8.00 9.00
SD standard deviation
*p < 0.05
Table 6 Construct validity of Malay PIDAQ with regards to self-perceived need for dental correction
PIDAQ variables Need braces N PIDAQ scores pvalue
Mean SD Quartiles
Lower Middle Upper
12-14 years
Dental Self-Confidence No 111 21.24 4.30 19.00 22.00 26.00 0.00*
Yes 128 15.73 5.41 12.00 15.00 19.75
Social Impact No 111 16.50 5.36 12.00 16.00 20.00 0.00*
Yes 128 22.21 8.02 16.00 21.50 28.00
Psychological Impact No 111 14.77 3.59 12.00 15.00 17.00 0.00*
Yes 128 19.33 5.75 15.00 19.50 24.00
Aesthetic Concern No 111 3.78 1.55 3.00 4.00 4.00 0.01*
Yes 128 5.45 2.21 4.00 5.00 7.00
15-17 years
Dental Self-Confidence No 89 22.52 4.48 9.00 20.00 26.00 0.00*
Yes 119 15.95 4.55 13.00 16.00 19.00
Social Impact No 89 15.53 5.38 11.00 15.00 19.00 0.00*
Yes 119 22.47 7.39 17.00 23.00 29.00
Psychological Impact No 89 14.18 4.06 11.50 14.00 17.00 0.00*
Yes 119 20.45 5.37 16.00 21.00 25.00
Aesthetic Concern No 89 3.80 1.55 2.00 4.00 5.00 0.00*
Yes 119 5.70 1.93 4.00 6.00 7.00
12-17 years
Dental Self-Confidence No 200 21.81 4.42 18.00 22.00 25.00 0.00*
Yes 247 15.83 5.00 12.00 15.00 19.00
Social Impact No 200 16.07 5.38 12.00 16.00 20.00 0.00*
Yes 247 22.34 7.71 17.00 22.00 28.00
Psychological Impact No 200 14.51 3.81 12.00 15.00 17.00 0.00*
Yes 247 19.87 5.58 16.00 20.00 24.00
Aesthetic Concern No 200 3.79 1.55 3.00 4.00 5.00 0.00*
Yes 247 5.57 2.08 4.00 5.00 7.00
SD standard deviation
*p< 0.05; Exclud ed those who answered ‘don’t know’
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 10 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
classes, which are usually composed of 15- and 17-year-
old schoolchildren, respectively. Thus participants from
schools were mainly recruited from the Forms 1 and 2
classes who represented the younger age group and from
Form 4 students who represented the older age group,
while participants from orthodontic clinics included all
target ages who attended to request orthodontic treatment.
Conceptual, item and semantic equivalences of the
Malay PIDAQ were established through discussions and
advice by the expert in OHRQoL throughout the linguis-
tic validation process. Conceptual equivalence was based
on the literature of the impact of malocclusion on the
OHRQoL of Malaysian youths based on studies that
used the OHIP-14 [37] and CS-OIDP [38] and on
discussions between experts and a sample of the target
population. In addition to information gained from the
local professional literature, discussions with orthodon-
tists and participants in the pilot study provided appro-
priate conceptual evidence of the impact of dental
aesthetics on the local population. Item equivalence was
established by identifying that all items were relevant to
the population apart from one item (Don’t like own teeth
on video) which was initially maintained in the scale but
the response format was amended. Semantic equivalence
was determined initially by forward translation to iden-
tify words that were difficult to translate or to be under-
stood by the schoolchildren such as self-conscious and
upset. In such situations, the original and adolescent
Table 7 Criterion validity of Malay PIDAQ with impact on daily activities attributed to malocclusion
Mann Whitney U Pearson correlation
PIDAQ variables CS-OIDP
prevalence
N PIDAQ scores pvalue CS-OIDP
performance
score
pvalue
Mean SD Quartiles
Lower Middle Upper
12-14 years 319
Dental Self-Confidence No 244 19.99 5.09 16.00 20.00 24.00 0.00* −0.39 0.00*
Yes 75 14.64 5.32 11.00 14.00 18.00
Social Impact No 244 18.03 6.34 13.00 17.00 22.00 0.00* 0.46 0.00*
Yes 75 23.85 8.42 17.00 24.00 29.00
Psychological Impact No 244 16.28 4.43 13.00 16.00 19.00 0.00* 0.43 0.00*
Yes 75 20.49 5.87 16.00 20.00 25.00
Aesthetic Concern No 244 4.14 1.73 3.00 4.00 5.00 0.00* 0.42 0.00*
Yes 75 6.04 2.19 4.00 6.00 8.00
15-17 years 271
Dental Self-Confidence No 203 20.79 5.18 17.00 21.00 25.00 0.00* −0.42 0.00*
Yes 68 15.19 4.69 12.00 14.50 18.00
Social Impact No 203 16.94 6.11 13.00 16.00 20.00 0.00* 0.53 0.00*
Yes 68 24.44 7.06 19.00 24.00 30.75
Psychological Impact No 203 15.65 4.87 12.00 15.00 18.00 0.00* 0.51 0.00*
Yes 68 21.94 4.81 18.00 22.00 26.00
Aesthetic Concern No 203 4.22 1.64 3.00 4.00 5.00 0.00* 0.46 0.00*
Yes 68 6.28 1.84 5.00 6.00 7.75
12-17 years 590
Dental Self-Confidence No 447 20.35 5.14 16.00 20.00 25.00 0.00* −0.40 0.00*
Yes 143 14.90 5.02 12.00 14.00 18.00
Social Impact No 447 17.53 6.25 13.00 17.00 21.00 0.00* 0.49 0.00*
Yes 143 24.13 7.78 18.00 24.00 30.00
Psychological Impact No 447 15.99 4.62 13.00 16.00 19.00 0.00* 0.47 0.00*
Yes 143 21.18 5.42 17.00 22.00 26.00
Aesthetic Concern No 447 4.17 1.69 3.00 4.00 5.00 0.01* 0.43 0.00*
Yes 143 6.15 2.03 5.00 6.00 8.00
CS-OIDP condition-specific child oral impacts on daily performances, SD standard deviation
*p< 0.05
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 11 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
versions were compared, and choice of the most appropri-
ate words was made by discussions and consensus with
experts and confirmed by pilot testing. This process was
followed by back translation by an independent profes-
sional translator not involved in the study to avoid bias.
Operational equivalence in terms of questionnaire
format, response options and method of administration
was established. Pilot testing showed the format to be
acceptable to the participants. In terms of measurement
methods, as expected due to limited access to video
recording devices among schoolchildren, the item Don’t
like own teeth on video was not universally relevant.
Participants in the pilot test and a relatively large pro-
portion of those from the psychometric validation
(14.2%) confirmed that this item was irrelevant to them.
Although modification to the response format for this
item by adding the answer option not relevant for the
Malay PIDAQ was initially considered to maintain the
item in the index, having large proportion of not
relevant responses may have implications to future stud-
ies. Such responses may not be a concern in longitudinal
studies that compare within-subject change but may be
an issue in studies that compare differences between
groups [35]. Jokovic et al. [35] suggested 3 methods to
handle such situations: (1) to exclude cases with such re-
sponses. Excluding cases with such responses may result
in loss of valuable information from participants who
did not have opportunity related to the activity of only 1
item of the instrument; (2) to modify the scores. Modify-
ing scores of not relevant responses using varying
methods of imputation can affect the precision and
accuracy of an instrument; or (3) to remove the item.
Jokovic et al. [35] suggested that an item could be re-
moved from the instrument that has a large proportion
of responses that were not applicable to the participant.
The percentage was not specified although another
study have recommended that items with more than
10% responses in such category may not be suitable to
Table 8 Tests of reproducibility for the Malay PIDAQ
ICC
agreement
Paired t-test Bland and Altman
(95% CI) SEM SDC M
Diff
(SD) 95% Limits of agreement
Lower Upper % Within limits
12-14 years (N= 103)
Dental Self-Confidence 0.86 (0.79-0.90)* 2.76 7.65 0.03 (3.90) −7.62 7.68 95.1
Social Impact 0.72 (0.59-0.81)* 5.06 14.03 1.39 (7.16) −12.64 15.42 93.2
Psychological Impact 0.78 (0.68-0.85)* 3.15 8.73 1.08* (4.46) −7.65 9.81 95.1
Aesthetic Concern 0.77 (0.66-0.85)* 1.27 3.51 −0.03 (1.79) −3.54 3.48 78.6
15-17 years (N= 83)
Dental Self-Confidence 0.89 (0.83-0.93)* 2.51 6.96 −0.84 (3.55) −7.80 6.12 95.2
Social Impact 0.85 (0.76-0.90)* 3.70 10.26 −1.81 (5.23) −12.07 8.45 94.0
Psychological Impact 0.85 (0.76 - 0.90)* 2.70 7.48 0.00 (3.83) −7.48 7.48 92.8
Aesthetic Concern 0.82 (0.72 - 0.88)* 1.11 3.09 0.13 (1.58) −2.96 3.22 94.0
12-17 years (N= 186)
Dental Self-Confidence 0.88 (0.84 –0.91)* 2.64 7.33 −0.02 (3.74) −7.35 7.31 95.2
Social Impact 0.79 (0.72 –0.84)* 4.53 12.54 0.69 (6.40) −11.86 13.23 94.1
Psychological Impact 0.81 (0.75 –0.86)* 2.98 8.26 0.60 (4.21) −7.66 8.85 100
Aesthetic Concern 0.80 (0.73 –0.85)* 1.20 3.32 0.04 (1.70) −3.28 3.37 93.5
CI confidence interval, SEM standard error of measurement, SDC smallest detectable change, M
Diff
mean differences, SD standard deviation
*p< 0.05
Table 9 Floor and ceiling effects of the Malay PIDAQ
12-14 years (N= 319) 15-17 years (N= 271) 12-17 years (N= 590)
% Floor % Ceiling % Floor % Ceiling % Floor % Ceiling
Dental Self-Confidence 1.9 1.3 1.1 3.3 1.5 2.2
Social Impact 3.4 0.6 5.5 0.4 4.4 0.5
Psychological Impact 0.9 2.5 1.8 1.8 1.4 2.2
Aesthetic Concern 16.3 2.2 14.8 2.2 15.6 2.2
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 12 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
be included in an item bank [39]. Thus, after discussion
among the authors, it was decided to remove the item
from the Malay PIDAQ. In terms of response options,
generally, the 5-point Likert scale was a suitable method
to elicit response since the entire spectrum of responses
was used in responding to all items with varying fre-
quency. Other modes of administration apart from self-
administered questionnaire were limited to the pilot test,
where each item was discussed one by one to determine
their understanding of each item. In designing this study,
the questionnaire was intended to be used in a large
linguistically mixed sample population study or for any
young Malaysian participants to answer in the waiting
room in a busy orthodontic clinic since the literacy rate
for basic Malay is high (95.2%) among secondary school
children in Malaysia [40]. Telephone surveys were con-
sidered impractical since telephones or mobile phones
are considered a luxury item and ownership of them is
limited among adolescents in Malaysia. In addition, face-
to-face interviews and mail correspondence by Malaysians
have shown poor response rate (56.8% and 48.1%) [8].
Measurement equivalence was assessed through psy-
chometric validation by tests of reliability and internal
consistency, test of reproducibility and tests of construct
validity [36] and by comparing the results with previous
study on German adolescents population [10]. Test of
responsiveness was not done and is recommended for
longitudinal validation of this measure.
The multidimensional construct structure of the Malay
PIDAQ for Malaysian adolescents was supported by
good data-fit results and was invariant across the age
groups. Measurement invariance across age groups was
based on the ΔCFI rather than the commonly used Δχ
2
since ΔCFI as a test of invariance is not affected by sam-
ple size unlike Δχ
2
[26]. This study also did not use the
fit-statistics like a previous study that used a combin-
ation of ΔCFI and ΔRMSEA [10] because the sample
size did not fulfil the criteria for this fit-statistics which
requires more than 300 subjects per group and equal in
numbers across groups [41]. The Cronbach’sαvalues
were satisfactorily within the recommended criteria of
between 0.70 and 0.95 [27] for all subscales and were
generally slightly higher than those of the previous
study [10].
Discriminant validity by unpaired t-test of the Malay
PIDAQ scores of participants with self-rated malocclu-
sion (MI-S) and investigator-rated malocclusion (MI-D)
showed statistically significant differences between those
with no or slight malocclusion and those with severe
malocclusion for all subscales, regardless of age. Those
with severe malocclusion had lower DSC subscale mean
scores and higher SI, PI and AC subscale mean scores
than did those with slight malocclusion, which was
reflected in the positive and negative signs of the effect
sizes. This concurred with the study by Klages et al. [10].
Similar to the previous study [10], the strength of the ef-
fect sizes based on the MI-S were strongly above 0.80,
but the effect sizes based on the MI-D were between
medium (0.50) and strong (≥0.80) for each subscale.
Construct validity of the Malay PIDAQ was further
assessed against ranking of perceived dental attractive-
ness and self-assessed need for dental correction while
criterion validity was assessed against the impact of
malocclusion on daily activities as assessed using the
CS-OIDP with the following rationale. Since PIDAQ is
concerned with the impact of dental attractiveness on
the OHRQoL, it was reasonable to test its properties
against participants’self-perceived dental attractiveness.
Those reporting an impact would likely also feel that
they needed to have their teeth corrected, and if the im-
pact affects their OHRQoL, the impact that is caused by
malocclusion would most likely affect their daily
activities. The results of the study concurred with these
expectations. All subscales indeed showed statistically
significant associations with perceived dental attractive-
ness rank, self-assessed need for dental correction and
CS-OIDP, regardless of age. Those who felt they had
excellent dental attractiveness had higher DSC subscale
mean scores and lower SI, PI and AC subscale mean
scores compared with those with lower self-rated dental
attractiveness. Those who felt that they needed braces
had lower DSC subscale mean scores and higher SI, PI
and AC subscale mean scores compared with those who
felt they did not need braces. Those with presence of
CS-OIDP attributed to malocclusion also had lower
DSC subscale mean scores and higher SI, PI and AC
subscale mean scores than did those without CS-OIDP.
This was further supported by a statistically significant
negative correlation of the DSC subscale and positive
correlation of the SI, PI and AC subscales with the per-
formance scores of the CS-OIDP.
In terms of test-retest reliability, the ICC scores for all
subscales were generally slightly lower, between 0.71 to
0.89, than those in the previous study, which were be-
tween 0.82 to 0.96 [10], but were all above the recom-
mended minimum standard of 0.70 for reliability [27]. A
statistically significant difference was detected in the PI
subscale of the younger age group, but the difference was
below the SDC score. In the study by Klages et al. [10],
statistical significance was detected in the AC subscale of
their younger age groups, but the differences were also
below the SDC scores. The SDC reflects the smallest
within-person change in score that can be interpreted as a
real change provided that the difference is significant [27].
In this study, the SDC scores were higher than in the
study by Klages et al. [10], indicating that higher score dif-
ferences were needed in this population before the scores
can be interpreted as true changes.
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 13 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Presence of floor or ceiling effects reduces reliability
since those with lowest and highest scores could not be
distinguished from each other. Furthermore, the pres-
ence of these effects limits content validity since items
in the extreme lower or upper part of the scale may be
missing [27]. This study found no floor effects except in
the AC subscale and no ceiling effects, since the preva-
lence of the lowest and highest possible scores were sat-
isfactorily below the recommended maximum frequency
of 15% [27]. The floor effects in the AC subscale were
just above this value at 15.6% (12-17 years old age
group) and 16.3% (12-14 years old age group). In Klages
et al. [10], floor effects were present for the SI, PI and
AC subscales. This demonstrates that the items of this
instrument were sufficient to distinguish Malaysian
adolescents with impact on their dental aesthetics at the
lower and upper ends of the spectrum.
Conclusion
Overall, the Malay PIDAQ has satisfactorily achieved the
conceptual, item, semantic, operational and measure-
ment equivalences similar to the original PIDAQ. While
small modifications in the scale were required for this
population, the Malay PIDAQ showed adequate validity
and reliability to be used to assess the impact of mal-
occlusion on the OHRQoL of Malaysian adolescents
aged 12–17 years.
Abbreviations
χ
2
:Chi-square; Δ: Differences; AC: Aesthetic Concern; ANOVA: Analysis of
variance; CFI: Comparative Fit Index; Child-OIDP: Child Oral Impacts on Daily
Performance; CS-OIDP: Condition-specific Oral Impacts on Daily Performance;
DSC: Dental Self - Confidence; ICC: Intraclass correlation coefficient;
IOTN: Index of Orthodontic Treatment Need; IOTN-AC: Aesthetic Component
of the Index of Orthodontic Treatment Need; IOTN-DHC: Dental Health
Component of the Index of Orthodontic Treatment Need; MI-
D: Malocclusion Index (Investigator-rated malocclusion); MI-S: Malocclusion
Index (Self-rated malocclusion); OHRQoL: Oral Health Related Quality of Life;
PI: Psychological Impact; PIDAQ: Psychosocial Impact of Dental Aesthetics;
POS: Perception of Occlusion Scale; RMSEA: Root Mean Square Error of
Approximation; SDC: Smallest detectable change; SEM: Standard error of
measurement; SI: Social Impact; α: alpha
Acknowledgements
The authors would like to thank the following members and authorities for
their permission to recruit participants and to publish this paper: the Ministry
of Education Malaysia, Penang and Kedah State Education Departments,
principals and parents of participating schools, the Faculty of Dentistry,
University of Malaya; and the Director General of Health and the Principal
Director of the Oral Health Division, Ministry of Health Malaysia. Special
gratitude to Professor Andrej Zentner for his permission to adapt the
instrument, to volunteers for participating in the study, to Sarifah Yusof for
translation assistance and Alena Sanusi for helpful comments.
Funding
This research was financially supported by the Ministry of Higher Education
Malaysia (FRGS FP033-2015A aka FRGS/1/2015/SKK14/UM/02/2).
Availability of data and materials
The dataset supporting the conclusion of this article is available in the
University of Malaya Repository [UM eprints ID: 16825 and hyperlink to
dataset in http://eprints.um.edu.my/16825].
Authors’contributions
WNWH contributed in the design of the study, seeking permission to
conduct the research from all authority bodies, development of the Malay
PIDAQ instrument, acquisition of data, analysis and interpretation of data,
and drafting the manuscript. ZYMY advised on the study design and
contributed in the development of the Malay PIDAQ instrument and revising
the manuscript. SSZS and SFMA contributed in the development of the
Malay PIDAQ instrument, gaining permission to recruit participants from
schools and acquisition of data. MZMM contributed in the development of
the Malay PIDAQ instrument, acquisition of data, and revising the
manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable.
Ethics approval and consent to participate
Permission to translate and adapt the instrument was obtained from the
corresponding author of the original instrument via email correspondence.
Ethical approval to conduct the study was granted by the Medical Ethics
Committee, Faculty of Dentistry, University of Malaya (DF CD1502/0015(U);
2015/03/31) and Medical Research and Ethics Committee, Ministry of Health
Malaysia (NMRR-15-664-25833; 2015/10/26). Permission to recruit the
secondary school children for psychometric tests was obtained from the
Ministry of Education Malaysia (KP(BPPDP)603/5/JLD.04(23); 2015/04/09),
State Education Departments (JPNPP(PER)1000-4/2 Jld.7(82); 2015/04/06 and
JPK03-07/3212 Jld16(89); 2015/05/12) and school principals. Written parental
or guardian’s consents were obtained before participants were included in
the study. Participants were reassured that the data would be treated with
strict confidentiality and no personal information would be disclosed to any
third party. Participation was on a voluntary basis and no remuneration was
involved.
Author details
1
Department of Paediatric Dentistry and Orthodontics, Faculty of Dentistry,
University of Malaya, 50603 Kuala Lumpur, Malaysia.
2
Department of
Community Oral Health and Clinical Prevention, Faculty of Dentistry,
University of Malaya, Kuala Lumpur, 50603, Malaysia.
3
Faculty of Dentistry,
University of Malaya, Kuala Lumpur, 50603, Malaysia.
4
Orthodontic Unit, Klinik
Pergigian Cahaya Suria, Ministry of Health Malaysia, Jalan Tun Perak, Kuala
Lumpur 50050, Malaysia.
Received: 12 July 2016 Accepted: 19 January 2017
References
1. Brook PH, Shaw WC. The development of an index of orthodontic
treatment priority. Eur J Orthod. 1989;11(3):309–20.
2. Abdullah MS, Rock WP. Assessment of orthodontic treatment need in 5,112
Malaysian children using the IOTN and DAI indices. Community Dent
Health. 2001;18(4):242–8.
3. Zreaqat M, et al. Orthodontic treatment need and demand among 12- and
16 year-old school children in Malaysia. Oral Health Dent Manag.
2013;12(4):217–21.
4. Cunningham SJ, Garratt AM, Hunt NP. Development of a condition-specific
quality of life measure for patients with dentofacial deformity: I. Reliability of
the instrument. Community Dent Oral Epidemiol. 2000;28(3):195–201.
5. Cunningham SJ, Garratt AM, Hunt NP. Development of a condition-specific
quality of life measure for patients with dentofacial deformity: II. Validity and
responsiveness testing. Community Dent Oral Epidemiol. 2002;30(2):81–90.
6. Klages U, et al. Development of a questionnaire for assessment of the
psychosocial impact of dental aesthetics in young adults. Eur J Orthod.
2006;28(2):103–11.
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 14 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
7. Saub R, Locker D, Allison P. Derivation and validation of the short version of
the Malaysian Oral Health Impact Profile. Community Dent Oral Epidemiol.
2005;33(5):378–83.
8. Saub R, et al. Cross-cultural adaptation of the Oral Health Impact Profile
(OHIP) for the Malaysian adult population. Community Dent Health.
2007;24(3):166–75.
9. Yusof ZY, Jaafar N. A Malay version of the Child Oral Impacts on Daily
Performances (Child-OIDP) index: assessing validity and reliability.
Health Qual Life Outcomes. 2012;10:63.
10. Klages U, et al. Psychosocial impact of dental aesthetics in adolescence:
validity and reliability of a questionnaire across age-groups. Qual Life Res.
2015;24(2):379–90.
11. Klages U, Bruckner A, Zentner A. Dental aesthetics, self-awareness, and oral
health-related quality of life in young adults. Eur J Orthod. 2004;26(5):507–14.
12. Klages U, et al. Dental esthetics, orthodontic treatment, and oral-health
attitudes in young adults. Am J Orthod Dentofacial Orthop.
2005;128(4):442–9.
13. Sardenberg F, et al. Validity and reliability of the Brazilian version of the
psychosocial impact of dental aesthetics questionnaire. Eur J Orthod.
2011;33(3):270–5.
14. Lin H, et al. Translation and validation of the Chinese version of the psychosocial
impact of dental aesthetics questionnaire. Eur J Orthod. 2013;35(3):354–60.
15. Ngom PI, et al. Translation and cultural adaptation of a french version of the
psychosocial impact of dental aesthetics questionnaire: PIDAQ. Orthod Fr.
2013;84(4):319–31.
16. Spalj S, Lajnert V, Ivankovic L. The psychosocial impact of dental aesthetics
questionnaire–translation and cross-cultural validation in Croatia. Qual Life
Res. 2014;23(4):1267–71.
17. Bucci R, et al. Cross-cultural adaptation and validation of the Italian
Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ). Qual Life
Res. 2015;24(3):747–52.
18. Bellot-Arcis C, Montiel-Company JM, Almerich-Silla JM. Psychosocial impact
of malocclusion in Spanish adolescents. Korean J Orthod. 2013;43(4):193–200.
19. Montiel-Company JM, Bellot-Arcis C, Almerich-Silla JM. Validation of the
psychosocial impact of dental aesthetics questionnaire (Pidaq) in Spanish
adolescents. Med Oral Patol Oral Cir Bucal. 2013;18(1):e168–73.
20. Soper DS. A-priori Sample Size Calculator for Structural Equation Models
[Software]. 2015. Available from http://www.danielsoper.com/statcalc/
calculator.aspx?id=89.
21. Westland JC. Lower bounds on sample size in structural equation modeling.
Electron Commer Res Appl. 2010;9(6):476–87.
22. Westland JC. Erratum to “Lower bounds on sample size in structural
equation modeling”[Electron. Commerce Res. Appl. 9 (6) (2010) 476–487].
Electron Commer Res Appl. 2012;11(4):445.
23. Kline P. The handbook of psychological testing. London; New York:
Routledge; 1993. p. 627.
24. Kang JM, Kang KH. Effect of malocclusion or orthodontic treatment on oral
health-related quality of life in adults. Korean J Orthod. 2014;44(6):304–11.
25. Byrne BM. Structural equation modeling with AMOS: basic concepts,
applications, and programming, Multivariate applications series. 2nd ed.
New York: Routledge. xviii; 2010. p. 396.
26. Cheung GW, Rensvold RB. Evaluating Goodness-of-Fit Indexes for Testing
Measurement Invariance. Struct Equ Model Multidiscip J. 2002;9(2):233–55.
27. Terwee CB, et al. Quality criteria were proposed for measurement properties
of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42.
28. Grzywacz I. The value of the aesthetic component of the Index of
Orthodontic Treatment Need in the assessment of subjective orthodontic
treatment need. Eur J Orthod. 2003;25(1):57–63.
29. Espeland LV, Stenvik A. Perception of personal dental appearance in young
adults: relationship between occlusion, awareness, and satisfaction.
Am J Orthod Dentofacial Orthop. 1991;100(3):234–41.
30. Roberts CT, Richmond S. The design and analysis of reliability studies for the
use of epidemiological and audit indices in orthodontics. Br J Orthod.
1997;24(2):139–47.
31. Yusuf H, et al. Validation of an English version of the Child-OIDP index, an
oral health-related quality of life measure for children. Health Qual Life
Outcomes. 2006;4:38.
32. Bernabe E, de Oliveira CM, Sheiham A. Comparison of the discriminative
ability of a generic and a condition-specific OHRQoL measure in
adolescents with and without normative need for orthodontic treatment.
Health Qual Life Outcomes. 2008;6:64.
33. de Vet HC, et al. When to use agreement versus realibility measures. J Clin
Epidemiol. 2006;59:1033–9.
34. Bland JM, Altman DG. Statistical methods for assessing agreement between
two methods of clinical measurement. Lancet. 1986;1(8476):307–10.
35. Jokovic A, et al. Measuring parental perceptions of child oral health-related
quality of life. J Public Health Dent. 2003;63(2):67–72.
36. Herdman M, Fox-Rushby J, Badia X. A model of equivalence in the cultural
adaptation of HRQoL instruments: the universalist approach. Qual Life Res.
1998;7(4):323–35.
37. Masood Y, et al. Impact of malocclusion on oral health related quality of life
in young people. Health Qual Life Outcomes. 2013;11:25.
38. Abdullah A. Impact of malocclusion on Oral Health Related Quality of Life
(OHRQOL) of 13-14-year-old Schoolchildren. Master in Public Health (Oral
Health) Dissertation. In: Department of Community Dentistry, Faculty of
Dentistry. Kuala Lumpur: University of Malaya; 2011. p. 118.
39. Holman R, et al. Constructing an item bank using item response theory: the
AMC linear disability score project. Health Services and Outcomes Research
Methodology. 2003;4(1):19–33.
40. Chew FP. Literacy among the Secondary Schools Students in Malaysia.
International Journal of Social Science and Humanity. 2012;2(6):546–50.
41. Chen FF. Sensitivity of goodness of fit indexes to lack of measurement
invariance. Struct Equ Model. 2007;14(3):464–504.
• We accept pre-submission inquiries
• Our selector tool helps you to find the most relevant journal
• We provide round the clock customer support
• Convenient online submission
• Thorough peer review
• Inclusion in PubMed and all major indexing services
• Maximum visibility for your research
Submit your manuscript at
www.biomedcentral.com/submit
Submit your next manuscript to BioMed Central
and we will help you at every step:
Wan Hassan et al. Health and Quality of Life Outcomes (2017) 15:23 Page 15 of 15
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
Available via license: CC BY 4.0
Content may be subject to copyright.
