| |
|
|
| Year : 2023 | Volume
: 34
| Issue : 1 | Page : 2-7 |
|
| Development and psychometric validation of the orthodontic health literacy tool |
|
|
Yamuna Marella1, Viswa Chaitanya Chandu2, Abdullah Almalki3, Vikramsimha Bommireddy4, Devikanth Lanka5, Pradeep Kandikatla6
1 Department of Periodontology, SIBAR Institute of Dental Sciences, Guntur, Andhra Pradesh, India
2 Department of Public Health Dentistry, Government Dental College and Hospital, Vijayawada, Andhra Pradesh, India
3 Department of Preventive Dental Sciences (Orthodontics), Faculty of Dentistry College, Majmaah University, Saudi Arabia
4 Department of Public Health Dentistry, SIBAR Institute of Dental Sciences, Guntur, Andhra Pradesh, India
5 Department of Orthodontics, SIBAR Institute of Dental Sciences, Guntur, Andhra Pradesh, India
6 Department of Orthodontics, Vishnu Dental College, Bhimavaram, Andhra Pradesh, India
Click here for correspondence address and email
| Date of Submission | 23-Mar-2021 |
| Date of Decision | 12-Dec-2022 |
| Date of Acceptance | 21-Dec-2022 |
| Date of Web Publication | 05-Jul-2023 |
|
|
 |
|
 Abstract | | |
Introduction: Over the past few years, there has been increasing emphasis on context-specific health literacy. However, no such context-specific psychometric tools are available with regard to oral health literacy. The aim of this study was to develop and validate an Orthodontic Health Literacy Tool (Orth-HLT). Materials and Methods: After development of initial item pool, the items were assessed for content validity. The final tool consisted of 22 items in the four domains of functional, communicative, critical orthodontic health literacy, and orthodontic knowledge. Orth-HLT was administered to a convenience sample of 642 subjects. The data were subjected to exploratory and confirmatory factor analyses using IBM SPSS Version 20.0 software and IBM SPSS Amos 26.0, respectively. Pearson's correlation, independent samples t-test, and one-way analysis of variance were performed. Results: Orth-HLT demonstrated good face and content validity. The domain-specific internal consistency reliability values were optimal. Exploratory factor analysis on the items in all four domains resulted in a single factor solution. Four models were evaluated in the confirmatory factor analysis; the correlated factors model showed best model fit indices. Each domain of Orth-HLT showed moderate to strong positive correlation with Indian Oral Health Literacy Measure in Telugu indicating the convergent validity of the tool. Conclusion: Orth-HLT is the first context-specific oral health literacy tool and demonstrates strong psychometric properties, which could be used to evaluate orthodontic health literacy and articulate orthodontic health education materials in an informed manner.
Keywords: Factor analysis, health literacy, orthodontics, psychometrics
How to cite this article:
Marella Y, Chandu VC, Almalki A, Bommireddy V, Lanka D, Kandikatla P. Development and psychometric validation of the orthodontic health literacy tool. Indian J Dent Res 2023;34:2-7 |
How to cite this URL:
Marella Y, Chandu VC, Almalki A, Bommireddy V, Lanka D, Kandikatla P. Development and psychometric validation of the orthodontic health literacy tool. Indian J Dent Res [serial online] 2023 [cited 2023 Oct 3];34:2-7. Available from: https://www.ijdr.in/text.asp?2023/34/1/2/380514 |
| Introduction | |  |
The increase in the amount of health-related information at the disposal of the public and the increasing complexity of the skills required to access, comprehend, and apply this information has shifted the focus of health education from just disseminating the information to conveying the information in a manner comprehensible to the public.[1] It has been well established that there exists substantial disparities between the assumed health literacy of a population by the creator or disseminator of health information and the actual health literacy levels of that population.[2] The following statement underscores the importance of health literacy: 'A two-year-old is diagnosed with an inner ear infection and prescribed an antibiotic. Her mother understands that her daughter should take the prescribed medicine twice a day. After carefully studying the label on the bottle and deciding that it does not tell how to take the medicine, she fills a teaspoon and pours the antibiotic into her daughter's painful ear'.[3] It is the concerns like these that have resulted in the increasing emphasis on prior establishment of health literacy levels of populations to better articulate health communication and better craft the health education materials and to keep the healthcare providers informed about the desired level of communication with patients. 'Healthy People 2010' identifies oral health literacy (OHL) as “the degree to which individuals have the capacity to obtain, process, and understand basic oral and craniofacial health information and services needed to make appropriate health decisions.”[4] Since the Institute of Medicine's publication entitled 'Health literacy: a prescription to end confusion', a multitude of tools to measure OHL have emerged. Initially, the tools to measure OHL focused on the reading abilities of the subject in the context of oral health information and the focus has later been shifted so as to include comprehension of the read information, skills relating to processing of numerical information, and conceptual oral health knowledge as the important components of the OHL measuring tools.[5]
Context-specific health literacy has been gaining prominence over the last few years.[6],[7],[8] However, OHL remains unexplored in the orthodontic context. There are no validated psychometric tools to estimate orthodontic health literacy (Orth-HL). In light of the fact that malocclusion could have a significant negative influence on the emotional and social wellbeing of a person and vastly undermines the quality of life, it is imperative for populations to derive the ability to identify the need for orthodontic screening and to receive requisite care.[9] In the process of this identification, Orth-HL may become invaluable as the specialty of orthodontics is distinct from other specialties in dentistry, the provision of care relating to which is largely provided by a specialist orthodontist, and most of the available oral health literacy instruments were not inclusive of items relating to orthodontics. With this background, the aim of this study was to develop an orthodontic health literacy tool (Orth-HLT) and to evaluate the psychometric properties of this instrument among adults seeking oral healthcare at teaching dental institutions in the South Indian states of Andhra Pradesh and Telangana.
| Materials and Methods | | |
This cross-sectional study to develop and perform psychometric validation of an orthodontic health literacy tool was conducted among a convenience sample of 642 patients attending four teaching dental institutions in the South Indian states of Andhra Pradesh and Telangana. The study was conducted between January and March, 2021. Ethical approval for the study (Pr: 70/IEC/SIBAR/2021) was obtained from the Institutional Ethics Committee of SIBAR Institute of Dental Sciences. A written informed consent was obtained from all the study participants. The methodology adopted in the development of Orth-HLT is discussed under the following sections:
Defining the construct and development of item pool
The first step in the development of Orth-HLT was to define a theoretical framework of health literacy following which the tool was to be articulated. The development of the conceptual framework was done with a team of six members including four orthodontists and two public health dentists. Functional health literacy, communicative literacy, critical literacy, and health-related knowledge with regard to orthodontics were defined to be the four domains forming the construct of Orth-HL. Functional health literacy relates to the ability to comprehend the written and oral health information provided; communicative health literacy refers to the ability of accessing, obtaining, and understanding health information; critical health literacy pertains to the ability of critically analyzing the obtained information for credibility and searching for alternative strategies in the context of one's own health.[10] Following identification of the framework, item pools were independently generated by four investigators. The item pools were evaluated for similarity and duplicate items were removed. For evaluating functional Orth-HL, two pieces of health information on the need for early orthodontic check-ups and the importance of retainers obtained from the American Association of Orthodontics [11] and Indian Orthodontic Society[12] websites, respectively, were used.
For communicative literacy and critical literacy, investigator-designed items were included. The domain of orthodontic knowledge consisted of items developed basing on previous literature.[13],[14] The initial item pool consisted of 10 items in the domain of functional literacy, three each in the domains of communicative literacy and critical literacy, and 10 items in orthodontic knowledge domain. The initial version of the instrument was developed in English and then translated to the local language Telugu by a bilingual (English and Telugu) dental public health professional. The Telugu version of the instrument was back translated to English by two experts other than the dental public health professional involved in forward translation from English to Telugu. There was substantial agreement between the two back-translated versions and semantic equivalence was observed.
Evaluation of face and content validity and administration of Orth-HLT
The initial version was given to six experts in the field of orthodontics other than those involved in the study to assess content validity. Content Validity Index was used to assess the content validity. Four items were excluded following this process, two each from the domains of functional literacy and knowledge. The scale level Content Validity Index for the 22-item scale was excellent (0.98). The 22-item scale was then administered to a convenience sample of 642 patients attending the outpatient department of four teaching dental institutions in the south Indian states of Andhra Pradesh and Telangana. Six hundred and forty two subjects with the ability to read and write in Telugu and were willing to participate in the study were included in the final sample. This sample provides an adequate size to perform exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).[15] Together with Orth-HLT, the participants were given a self-administered questionnaire seeking the information relating to age, gender, educational qualification, monthly family income, and the Indian Oral Health Literacy Measure–Telugu (IOHLM-T) which is a tool, validated among an Indian population, to measure oral health literacy in general.[16]
Exploratory and confirmatory factor analysis to extract the factor structure and check the construct validity of the instrument
Factorality of the data was assessed separately for all the individual domains of Orth-HLT using Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett's test of sphericity. EFA was done with principal axis factoring as the extraction method on a subset of data with 300 subjects. The replicability of the factor structure was tested with CFA on another subset of 342 subjects. The unequal split of the dataset was in accordance with the sample size requirements of EFA and CFA, where the latter requires larger size.[15] Goodness-of-fit of the model was assessed using the following model fit indices: goodness of fit index; comparative fit index; and root mean square error of approximation.
The internal consistency reliability of the items in individual domains was determined using Cronbach's alpha and Kuder-Richardson 20 as appropriate. Convergent validity of the scale was assessed by juxtaposing the Orth-HLT score of the participants with their IOHLM-T scores.
Statistical analysis
Data were analyzed using IBM SPSS Version 20.0 software and IBM SPSS Amos 26.0. EFA with principal axis factoring as the extraction method was used for determination of factor structures and CFA was done using goodness-of-fit models to check the construct validity of the instrument. Domain-specific analysis was considered owing to the predetermined distinction between different domains of Orth-HLT and the development of item pools accordingly. Normality of the data was assessed using Kolmogorov-Smirnov test; all the domain scores showed normal distribution of data (P >.05). Independent samples t-test, one-way analysis of variance, and correlation tests were used as necessary to identify the association between Orth-HLT domain-specific scores and dichotomous, multichotomous, continuous independent variables, respectively.
| Results | | |
The mean age of the study participants was 39.14 ± 7.3 years. About 66.8% of the study participants were females. [Table 1] presents the domain-wise corrected item-total correlations and internal consistency reliability statistics of the Orth-HLT. The corrected item-total correlations across the four domains ranged between 0.53 and 0.865; internal consistency reliability statistics ranged between 0.77 and 0.94. Domain-specific Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy and Bartlett's sphericity tests suggested an underlying factor structure for all the four domains. [Table 2] presents the domain-specific factor structures and item communalities. All the domains demonstrated a single-factor solution in EFA. Items in each of the four domains showed factor loadings >0.5. The factor structure was subsequently tested using CFA on the data obtained from an independent subset of 342 subjects. Four models were tested in CFA as follows: unidimensional model [Figure 1]; uncorrelated factors model [Figure 2]; correlated factors model [Figure 3]; and second order model [Figure 4]. Model fit indices for all the models were shown in [Table 3]; correlated factors model showed best model fit indices. Standardized loadings suggest that the items are good indicators for the corresponding latent variables. Since the correlated factors model was retained as the model of best fit, no attempt was made to sum the item scores across factors and only item scores within a factor were summed to obtain the individual domain scores. Moderate to strong positive correlation was found between domain-specific Orth-HLT scores and IOHLM-T scores [Table 4]. While no gender-based differences were observed in the Orth-HLT scores, significant differences were found based on the socioeconomic status of the subjects. Subjects belonging to middle and upper middle socioeconomic strata demonstrated higher Orth-HLT scores compared to those from lower middle and lower socioeconomic strata [Table 5]. | Table 1: Domain-specific corrected item total correlations and internal consistency reliability statistics
Click here to view |
 | Table 2: Domain-specific factor structures with factor loadings and item communalities
Click here to view |
 | Figure 1: Alternative unidimensional factor model of Orthodontic Health Literacy showing standardized estimates
Click here to view |
 | Figure 2: Alternative uncorrelated factors model showing standardized estimates
Click here to view |
 | Figure 3: Alternative correlated factors model showing standardized estimates
Click here to view |
 | Table 4: Correlation between domain specific Orth-HLT scores and IOHLM-T scores
Click here to view |
 | Table 5: Differences in domain-specific Orth-HLT scores based on gender and socioeconomic status
Click here to view |
| Discussion | | |
A number of disease-specific/context-specific health literacy measures have emerged in the recent years. The basis for this phenomenon is the increasing understanding that general health literacy measures may not adequately capture context-specific health literacy skills. Since the theoretical framework of health literacy includes the dimension of critical literacy and health-related knowledge, misconceptions regarding a specific condition or component of health influence the health literacy of the subjects in the context of that condition. Consequently, it becomes imperative to measure context-specific health literacy so that health information materials with regard to that context can be formulated in an informed manner. The present study attempts to develop an Orth-HLT, a psychometric tool that measures health literacy in the context of orthodontics. A validated tool to assess orthodontic health literacy is important in view of the fact that none of the existing tools that assess oral health literacy possess orthodontics as an integral domain.
EFA revealed that all the items of Orth-HLT had acceptable factor loadings (>0.5) as suggested by Truong and McColl.[17] The present study shows that the correlated four-factor model exhibited the best fit in examining Orth-HL. Although a retained correlated factors model suggests a possible higher second-order latent construct, evaluation of higher second-order model in CFA showed poor fit as compared to the correlated four-factor model. Therefore, it is suggested to report Orth-HLT scores in a domain-specific manner and not sum the scores across all the items of the measure. No significant differences were found based on gender in the domain-specific Orth-HLT scores. These results were observed to be consistent with the studies conducted by Sabbahi DA et al.,[18] where no differences in general oral health literacy were found between males and females. However, significant differences were noted based on the socioeconomic status of the participants with subjects belonging to upper middle and middle socioeconomic strata achieving higher scores in each of the four domains of Orth-HLT and particularly so with regard to communicative and critical orthodontic health literacy. This is consistent with the notion that people with higher educational level and socioeconomic status possess abilities to better navigate the healthcare system.[19] The domains in Orth-HLT demonstrated moderate to strong correlation with IOHLM-T scores which is suggestive of the convergent validity of the tool.
The strength of the present study is its larger sample which facilitated the conduct of EFA and CFA to identify and test the factor structure of Orth-HLT. A multitude of fit indices were evaluated for all the models tested in CFA and the correlated factors model showed the best fit indices with great comparative fit index and moderate root mean square error of approximation. These model fit indices were suggested to be better compared to other traditional model fit indices by Lei PW et al.[20] Although two-index fit strategy was deemed to be sufficient in ensuring good model fit, the correlated factors model showed good fit based on all the model fit indices considered. The mean age of the study subjects was nearly 40 years. Although a younger age group could have been considered, this outcome was not a result of stringent exclusion criteria in relation to age. Furthermore, autonomy with regard to orthodontic treatment of children largely rests with parents and orthodontic health literacy of parents is an extremely important construct in the prevention of malocclusion. Future studies need to be conducted to evaluate the ability of Orth-HLT to differentiate between subjects with and without functional limitations as a result of malocclusion by discriminant analysis.
| Conclusion | | |
If malocclusion is considered a public health problem, then orthodontic health literacy undeniably becomes a public health priority. Insights into orthodontic health literacy of a community keep us informed in the best possible ways on how to disseminate orthodontic health information and indoctrinate positive care seeking behaviors among the public. Orth-HLT demonstrates adequate psychometric properties and becomes the first instrument that measures health literacy in the context of orthodontics.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Vermeir P, Vandijck D, Degroote S, Peleman R, Verhaeghe R, Mortier E, et al. Communication in healthcare: A narrative review of the literature and practical recommendations. Int J Clin Pract 2015;69:1257-67.  |
| 2. | Lambert M, Luke J, Downey B, Crengle S, Kelaher M, Reid S, et al. Health literacy: Health professionals' understandings and their perceptions of barriers that Indigenous patients encounter. BMC Health Serv Res 2014;14:614. |
| 3. | Parker RM, Ratzan SC, Lurie N. Health literacy: A policy challenge for advancing high-quality health care. Health Aff (Millwood) 2003;22:147-53. |
| 4. | U.S. Department of Health and Human Services. Oral health. In: U.S. Department of Health and Human Services, editor. Healthy People 2010 2 nd Ed. Washington, DC: U.S. Government Printing Office; 2000. |
| 5. | Dickson-Swift V, Kenny A, Farmer J, Gussy M, Larkins S. Measuring oral health literacy: A scoping review of existing tools. BMC Oral Health 2014;14:148. |
| 6. | Leung AY, Lou VW, Cheung MK, Chan SS, Chi I. Development and validation of Chinese health literacy scale for diabetes. J Clin Nurs 2013;22:2090-9. |
| 7. | Wallace LS, Ergen WF, Cassada DC, Freeman MB, Grandas OH, Stevens SL, et al. Development and validation of the rapid estimate of adult literacy in vascular surgery (REAL_VS). Ann Vasc Surg 2009;23:446-52. |
| 8. | Pendlimari R, Holubar SD, Hassinger JP, Cima RR. Assessment of colon cancer literacy in screening colonoscopy patients: A validation study. J Surg Res 2012;175:221-6. |
| 9. | Kragt L, Dhamo B, Wolvius EB, Ongkosuwito EM. The impact of malocclusions on oral health-related quality of life in children-a systematic review and meta-analysis. Clin Oral Investig 2016;20:1881-94. |
| 10. | Nutbeam D. Health literacy as a public health goal: A challenge for contemporary health education and communication strategies into the 21 st century. Health Promot Int 2000;15:259-67. |
| 11. | |
| 12. | |
| 13. | Faizee SH, Veerasankar S, Avanthika K, Aruna Lakshmi MR, Angeline B, Rachel BJ. Awareness survey about the effects of malocclusion among young adults. Indian J Dent Res 2018;29:705-10. [ PUBMED] [Full text] |
| 14. | Pandey M, Singh J, Mangal G, Yadav P. Evaluation of awareness regarding orthodontic procedures among a group of preadolescents in a cross-sectional study. J Int Soc Prev Community Dent 2014;4:44-7. |
| 15. | MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychol Methods 1996;1:130-49. |
| 16. | Chandu VC, Vadapalli V, Pachava S, Marella Y, Bommireddy VS, Ravoori S. Development and evaluation of a new oral health literacy instrument among Telugu speaking population: The Indian Oral Health Literacy Measure. Indian J Dent Res 2020;31:862-71. [ PUBMED] [Full text] |
| 17. | Truong Y, McColl R. Intrinsic motivations, self-esteem, and luxury goods consumption. J Retail Consum Serv 2011;18:555-61. |
| 18. | Sabbahi DA, Lawrence HP, Limeback H, Rootman I. Development and evaluation of an oral health literacy instrument for adults. Community Dent Oral Epidemiol 2009;37:451-62. |
| 19. | Divaris K, Lee JY, Baker AD, Vann WF. Caregivers' oral health literacy and their young children's oral health-related quality-of- life. Acta Odontol Scand 2012;70:390-7. |
| 20. | Lei P-W, Li H. Performance of fit indices in choosing correct cognitive diagnostic models and Q-matrices. Appl Psychol Meas 2016;40:405-17. |
Correspondence Address:
Dr. Viswa Chaitanya Chandu
Department of Public Health Dentistry, Ground Floor, Government Dental College and Hospital, Vijayawada, Andhra Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijdr.ijdr_268_21
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5] |
|
|
|
|
|
|
|
|
|
|
|
|
|
| Article Access Statistics | | | Viewed | 2939 | | | Printed | 130 | | | Emailed | 0 | | | PDF Downloaded | 72 | | | Comments | [Add] | | |
|
|
Users online:
