Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 12  |  Issue : 1  |  Page : 9-12

Aspiring a Paradigm Shift in the Current Understanding of Oral Health Promotion by Testing the Possibility of Deriving Requisite Manpower Using Basic Clinical Data: An Epidemiological Investigation


Department of Public Health Dentistry, Sibar Institute of Dental Sciences, Guntur, Andhra Pradesh, India

Date of Submission18-Feb-2020
Date of Decision05-Mar-2020
Date of Acceptance02-Apr-2020
Date of Web Publication12-Jun-2020

Correspondence Address:
Dr. Viswa Chaitanya Chandu
Public Health Dentistry, III floor, Main block, SIBAR Institute of Dental Sciences, Guntur-522509, Andhra Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jofs.jofs_28_20

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  Abstract 


Introduction: Majority of rural dental outreach programs focus on screening the subjects attending the programs and providing oral health education for them. There has only been limited emphasis on the provision of care as a part of the outreach activities for the geographically disadvantaged rural population. The objective of this study is to check whether the basic clinical data as collected in the form of number of decayed teeth can be a valid and reliable predictor in calculation of requisite time for provision of restorative services by developing a predicting equation from the data obtained on 400 subjects in outreach activities and subsequently testing the predicting general linear equation for predictive accuracy. Materials and Methods: The number of decayed teeth in each of the participants was recorded along with collection of demographic data from the study participants. Data obtained from the 400 participants was used to generate a predicting equation after running a backward stepwise multiple linear regression. The equation was subsequently tested among a subsample of 200 participants from the exploratory sample and an independent validatory sample of 200. SPSS version 20 software, multiple linear regression, Wilcoxon signed rank test, Mann Whitney U test were used in data analysis. Results: Number of decayed teeth was observed to be a single, significant predictor of the man hours required in provision of restorative care. The predicting equation generated had good predictive accuracy and predictive stability as observed from the non-significant differences between the requisite time calculated using the predicting equation and that clinically determined by the calibrated examiner among both the subsample of exploratory sample and the validatory sample. Conclusion: The predicting equation generated in this study accurately and consistently estimated the requisite man hours necessary for provision of restorative oral health care in outreach programs.

Keywords: Community outreach, health workforce, linear models


How to cite this article:
Chandu VC, Mullapudi V, Pachava S, Viswanath V. Aspiring a Paradigm Shift in the Current Understanding of Oral Health Promotion by Testing the Possibility of Deriving Requisite Manpower Using Basic Clinical Data: An Epidemiological Investigation. J Orofac Sci 2020;12:9-12

How to cite this URL:
Chandu VC, Mullapudi V, Pachava S, Viswanath V. Aspiring a Paradigm Shift in the Current Understanding of Oral Health Promotion by Testing the Possibility of Deriving Requisite Manpower Using Basic Clinical Data: An Epidemiological Investigation. J Orofac Sci [serial online] 2020 [cited 2020 Dec 2];12:9-12. Available from: https://www.jofs.in/text.asp?2020/12/1/9/286481




  Introduction Top


Despite the lack of contemporary, comprehensive oral health survey records in India, various oral health surveys in different parts of the country suggest that oral health status continues to be poor over the years. Oral health promotion has long been recognised as the solution for improvement of oral health status. Many authors have proposed various strategies for oral health promotion and discussed in depth on how oral health promotion differs from oral health education in important ways.[1],[2] Provision of oral health services for people is at the heart of oral health promotion. Community outreach programs in the rural and remote areas without access to oral health care services, while being an important prospective way for improvement in oral health, often restrict to oral health screening and bringing awareness among public about the importance of oral health. Though raising awareness on oral health is laudable, national and international experiences suggest that improved knowledge does not necessarily contribute towards better outcomes. Therefore, outreach programs need to focus on provision of care without curtailing the scope of such programs to screening and oral health education. Mere screening programs have been remarked to be one way tickets to disheartenment by letting the people know about their problems without provision of services which is against the cardinal ethical principles.[3] However, provision of services in outreach programs demands thorough preparation on the part of care providers in terms of identification of required manpower, material, and formulation of strategic plans. While few programs have been in existence for quite some time, majority of oral health outreach programs are sporadic in nature without a concrete basis for recruitment of resources.[4]

With the aforementioned background, the objective of this study is to check whether the basic clinical data as collected in the form of number of decayed teeth can be a valid and reliable predictor in calculation of requisite time for provision of restorative services by developing a predicting equation from the data obtained on 400 subjects in outreach activities and subsequently testing the predicting general linear equation for predictive accuracy in two ways: a) on a randomly split sample of 200 from the “exploratory group” b) on a “validatory” sample of 200, independent of the exploratory sample.


  Materials and Methods Top


This study to develop a predicting equation of requisite man hours and subsequent validation for predictive accuracy and stability was conducted in the outreach programs organized by a teaching dental institution in the neo capital region of Andhra Pradesh between March and May, 2019. Ethical approval for the study was obtained from the institutional ethical committee of SIBAR Institute of Dental Sciences (Pr. 183/IEC/SIBAR/2018) on December 12th, 2018. All the subjects attending the outreach programs for oral examination and treatment were informed about the study and consent was obtained from those willing to participate. The number of decayed teeth was recorded using World Health Organization (WHO) 1997 recommendations.[5]

After recording basic clinical data, the subjects were clinically examined by a single examiner, calibrated for clinical acumen in decision of requisite man hours for rendering restorative care with a gold standard, to document the time required for provision of care. Investigations were advised, wherever felt necessary, by the examiner for which the subjects were not charged and were provided with conveyance facilities to the teaching dental institution. The calibration exercise was done on 25 subjects attending the outpatient department of the teaching dental institution and an Intra class Correlation Coefficient (ICC) of ≥0.95 was deemed as sufficient agreement.

The development of predicting equation was done on a purposive exploratory sample of 400 subjects in outreach activities ensuring representation of people from different age groups, social classes, genders, and smoking habits. The sample size of 400 was arrived at based on the minimum number of events per variable (EPV) rule suggesting EPV of 50 would yield an adequate sample for development of predicting equation.[6] SPSS version 20 software (IBM SPSS statistics for Windows version 20, Armonk, USA) was used to analyze the data. Backward stepwise multiple linear regression method was used to obtain the most appropriate model with highest Coefficient of determination (R2) with requisite time for provision of restorative care as the regressand and number of decayed teeth as the continuous regressor, socioeconomic status[7] as the multichotomous categorical regressor for which dummy variables were created as necessary.

Subsequently, the predictive accuracy and predictive stability of the predicting equation was tested on a subsample of 200 participants of the exploratory sample and on an independent validatory sample of 200 respectively. Lack of significant difference between the requisite man hours calculated using the predicting equation and that documented by the examiner by virtue of clinical acumen signifies the predictive accuracy of the developed model. Wilcoxon signed rank test and Mann Whitney U test were done to assess the predicting model accuracy and stability i.e. to check how well the predicting equation performed in the sub sample of exploratory sample and validatory sample respectively.


  Results Top


Of the 400 study participants, 224 were females and the mean age of the study sample was 41.6±10.25 years. The mean number of decayed teeth among study participants was 2.89±2.1 with no significant differences based on gender. Significant difference in the mean number of decayed teeth was found based on socioeconomic status, while no difference was observed between subjects with and without the habit of smoking [Table 1]. Age was observed to have a strong positive correlation (r=0.78) with the number of decayed teeth, and therefore was not entered in the multiple linear regression model to avoid multicollinearity.
Table 1 Differences in mean number of decayed teeth based on gender, socioeconomic status and tobacco consumption habits

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The predicting equation obtained from stepwise multiple linear regression is given below [Table 2]. Backward stepwise linear regression revealed that the number of decayed teeth is the single, significant predictor of requisite time to provide restorative care (Adjusted R2 = 0.446); Predicted requisite time for provision of restorative care (mins) = 16.38 + 40.13 *number of decayed teeth. There were no significant differences between the requisite time calculated using the predicting equation and that clinically determined by the calibrated examiner among both the subsample of exploratory sample and the validatory sample [Table 3]. These findings highlight the predictive accuracy and the predictive stability of the equation developed.
Table 2 Backward stepwise linear regression with requisite time for restorative care (in minutes) as the dependent variable

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Table 3 Testing the predictive accuracy and predicting stability of the generated equation

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  Discussion Top


Geographical inequalities in the distribution of dentists,[8] lack of concrete policy on proper utilization of available oral health care professionals in public health systems,[4] and lack of comprehensive documentation of oral health status on a regular basis with the national oral health survey conducted in 2002–2003 remaining the solitary comprehensive documentation of the nation’s oral health status[9] are among the primary reasons for the observation of poor oral health status among Indian populace. The Indian context of oral health promotion is paradoxical in the fact that the nation possesses more number of dentists than the estimated requisites, yet the oral health status remains poor.[10] Community outreach programs are considered as a pragmatic solution to address oral health inequalities to some extent. However, the referral services offered at teaching dental institutions through outreach programs are underutilized. Only subjects with oral health needs perceived by themselves tend to utilize the referral services, while those whose needs were disclosed to them after identification by the oral health professionals tend to neglect the oral health problems as most of the oral health care services provided across the globe are curative in nature after the subjective perceive his/her oral health problem. Preventive services and care for problems with negligible impact on quality of life are often untended.[11] It is also for this reason that treatment services at outreach sites are extremely important.The clinical data recorded as part of surveys and outreach programs tend to be too basic that it is challenging to compute the number of man hours required in provision of requisite care for a person and the community as a whole. For instance, recording Decayed, Missing, Filled teeth index (DMFT) gives us valuable insights into the magnitude of caries experience in a community. But the index does not facilitate computation of man hours required in provision of restorative care for the subject as the severity of the carious lesion would not be recorded as a part of the index. This brings up the need for more sensitive clinical examination which bears the drawback of consuming too much time than what is practically possible in outreach scenarios. It is not always possible to spend the same amount of time with a subject in outreach activities, as much as the time spent per patient in a clinical setting. This discrepancy in the amount of time spent per person must be understood in light of reach versus intensity. Therefore it would be worthwhile if the computation of man hours required to provide oral health care can be done based on the fundamental clinical data recorded in surveys and outreach programs. Such computation of man hours from basic clinical data would eliminate unnecessary wastage of time in identification of requisite manpower and aid service providers in preparing for the provision of oral health services by estimating the requisite man hours in advance.

The findings from this study were observed to be coherent with the hypothesis that the severity of carious lesions increases with an increase in the number of decayed teeth in light of the magnitude of increase in requisite man hours with an increase in number of decayed teeth. This study provides an important direction in the estimation of required resources in outreach programs. Outreach activities are usually conducted with major participation from house surgeons of the corresponding institutions. Therefore, it would be extremely beneficial if the accurate estimation of requisite time for provision of care could be derived based on the basic clinical data documented by these dental students. It is to be acknowledged here that lack of insights into the requisite resources, especially manpower, often times is responsible for the idea of provision of care in outreach programs getting aborted even before its conception. Prior estimation of these resources would facilitate provision of care in outreach programs without confining the scope of the programs to mere screening.


  Conclusion Top


The predicting equation generated in this study accurately and consistently estimated the requisite man hours necessary for provision of restorative oral health care in outreach programs. Directions for future research include estimating the resources required for provision of comprehensive oral health care for the communities based on different clinical parameters.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Diaz-Valencia PA. Theoretical conceptions on the theory on health education.Systematic review. Invest Educ Enferm 2012;30:378-89.  Back to cited text no. 1
    
2.
Chandu VC, Pachava S, Viswanath V. Strategies for improving accessibility to oral health care services in rural India: An insight. Int J Oral Health Med Res 2017;4:44-6.  Back to cited text no. 2
    
3.
Janakiram C, Taha F. Ethics of dental health screening. Indian J Med Ethics 2016;1:171-6.  Back to cited text no. 3
    
4.
Kothia NR, Bommireddy VS, Devaki T, Vinnakota NR, Ravoori S, Sanikommu S, Pachava S. Assessment of the status of national oral health policy in India. Int J Health Policy Manag 2015;4:575-81.  Back to cited text no. 4
    
5.
World Health Organization‎. Oral health surveys: basic methods, 4th ed. Geneva: World Health Organization, 1997.  Back to cited text no. 5
    
6.
Bujang MA, Sa’at N, Sidik T, Joo LC. Sample size guidelines for logistic regression from observational studies with large population: emphasis on the accuracy between statistics and parameters based on real life clinical data. The Malaysian Journal of Medical Sciences 2018;25:122-30.  Back to cited text no. 6
    
7.
Mangal A, Kumar V, Panesar S, Talwar R, Raut D, Singh S. Updated BG Prasad socioeconomic classification, 2014: a commentary. Indian Journal of Public Health 2015;59:42-4.  Back to cited text no. 7
    
8.
Suresh S. The great divide. Rural–urban gap in oral health in India. Journal of Dental & Oro-facial Research 2012;8:1-6.  Back to cited text no. 8
    
9.
Bali RK, Mathur VB, Talwar PP, Chanana HB. National Oral Health Survey & Fluoride Mapping, 2002-2003, India. Delhi: Dental Council of India; 2004.  Back to cited text no. 9
    
10.
Vundavalli S. Dental manpower planning in India: current scenario and future projections for the year 2020. Int Dent J 2014;64:62-7.  Back to cited text no. 10
    
11.
Dodd VJ, Logan H, Brown CD, Calderon A, Catalanotto F. Perceptions of oral health, preventive care, and care-seeking behaviors among rural adolescents. J Sch Health 2014;84:802-9.  Back to cited text no. 11
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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