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ORIGINAL ARTICLE |
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Year : 2022 | Volume
: 14
| Issue : 1 | Page : 35-40 |
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Evaluation of Dimensionality and Reliability of the Autonomy over Smoking Scale among South Indian Smokers
Nalini Parimi1, Nalini Bikkina2, Vikramsimha Bommireddy3, Viswa Chaitanya Chandu4, Busi Ruth Anupama5, Madasu Gowthami1
1 Department of Public Health Dentistry, St Joseph Dental College, Eluru, Andhra Pradesh, India 2 School of Gandhian Studies, GITAM University, Visakhapatnam, Andhra Pradesh, India 3 Department of Public Health Dentistry, Sibar Institute of Dental Sciences, Guntur, Andhra Pradesh, India 4 Department of Public Health Dentistry, Government Dental College and Hospital, Vijayawada, Andhra Pradesh, India 5 Johnson’s Dental Clinic, Aganampudi, Andhra Pradesh, India
Date of Submission | 06-Aug-2021 |
Date of Decision | 28-Feb-2022 |
Date of Acceptance | 28-Feb-2022 |
Date of Web Publication | 05-Aug-2022 |
Correspondence Address: Dr. Nalini Parimi Department of Public Health Dentistry, St Joseph Dental College, Eluru, Andhra Pradesh India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jofs.jofs_169_21
Introduction: In spite of the efforts being directed at reducing the tobacco use among public, it remains a significant concern facing India today. In the quest of providing tobacco cessation counseling, documentation of the tobacco dependence of the individuals is quintessential. This study aims to assess the psychometric properties of the autonomy over smoking scale (AUTOS) among patients seeking oral health care at a teaching dental institution in southern India. Materials and Methods: The study sample constituted 199 subjects who satisfied the eligibility criteria of self-reported current smoking and were willing to participate in the study. Participants’ age, gender, and years of smoking were documented along with their nicotine dependence by administration of Fagerstrom test for nicotine dependence (FTND) and AUTOS by a trained interviewer. The dimensionality of AUTOS was verified by confirmatory factor analysis using the Classical and Bayesian Instrument Development software program. Correlation analysis between FTND and AUTOS subscale scores was performed along with multiple linear regression analyses to identify the predictors for AUTOS subscale scores. Results: The symptom type-wise subscales of AUTOS and the overall scale demonstrated good internal consistency reliability (Cronbach alpha ≥0.758). Significant positive correlation was observed between age, years of smoking, FTND score, and all the AUTOS subscale scores. Linear regression analyses showed that the number of years for which the subject had been smoking was a significant predictor of all the three AUTOS subscale scores. Conclusion: AUTOS was observed to be a very useful tool with good internal consistency reliability that measures tobacco dependence in consistence with FTND among South Indian population, and while doing so, it captures the various forms of tobacco dependence in an independent manner.
Keywords: Confirmatory factor analysis, tobacco dependence, withdrawal symptoms
How to cite this article: Parimi N, Bikkina N, Bommireddy V, Chandu VC, Anupama BR, Gowthami M. Evaluation of Dimensionality and Reliability of the Autonomy over Smoking Scale among South Indian Smokers. J Orofac Sci 2022;14:35-40 |
How to cite this URL: Parimi N, Bikkina N, Bommireddy V, Chandu VC, Anupama BR, Gowthami M. Evaluation of Dimensionality and Reliability of the Autonomy over Smoking Scale among South Indian Smokers. J Orofac Sci [serial online] 2022 [cited 2022 Aug 7];14:35-40. Available from: https://www.jofs.in/text.asp?2022/14/1/35/353469 |
Introduction | |  |
The ever-increasing tobacco use is one of the significant problems world is facing today. The habit of tobacco consumption is responsible for over 8 million deaths across the globe.[1] The years of life lost due to tobacco use have been on a consistent rise worldwide, with developing countries contributing around 70% to these premature deaths.[2] In India, it is reported by a study from the World Health Organization that 1% of the nation’s GDP is lost to the disease burden posed by tobacco consumption and the associated mortality.[3] It has been estimated that the revenue obtained from tobacco accounts for only 12% of the costs associated with tobacco use, implying that the nation’s economy loses Rs 8.16 for every rupee of tax obtained from tobacco products.[3]
It is noteworthy that in spite of the huge efforts being directed toward reducing the use of tobacco products in India in the form of awareness campaigns and increased taxation on tobacco products, etc., the achievement of desired outcomes remains a distant dream with nearly 29% of the adult Indian population using tobacco in some form according to the Global Adult Tobacco Survey, India (2016–2017).[4] The Government of India in association with the Dental Council of India has taken an initiative and made it mandatory to establish tobacco cessation clinics in teaching dental institutions across the country.[5] Similar efforts have been underway with regard to full integration of tobacco cessation counseling in undergraduate medical curriculum.[6] Though the attitudes of students and faculty at teaching health-care institutions with regard to provision of tobacco cessation counseling at these settings are equivocal, international experiences suggest positive influence of tobacco cessation counseling on bringing down the use of tobacco among subjects seeking care at these facilities.[7],[8],[9],[10] Nevertheless, it has been a common observation that health-care providers belonging to diverse disciplines who take part in tobacco cessation counseling must be equipped with the knowledge on multitude of reasons for nicotine dependence and in various pharmacologic means of tobacco cessation counseling besides the motivational persuasion of potential quitters.[11]
It is to be discerned that nicotine dependence is a complex disorder. People with nicotine addiction consume tobacco products at differing doses and frequencies depending on the demands of the body.[12] Nicotine traverses through the blood–brain barrier and quickly gets distributed into the cerebral tissue. Tobacco users experience a sense of arousal, relief from stress, and improvement in concentration after the intake of the tobacco products.[13] However, cessation of tobacco use among these subjects result in manifestation of withdrawal symptoms such as irritability, anxiety, depression, etc., which need attention from health-care professionals. Understanding the nicotine dependence of an individual is therefore quintessential in the course of provision of tobacco cessation counseling as it also determines the likelihood of quitting the habit of tobacco consumption. Autonomy over smoking scale (AUTOS) is a 12-item psychometric tool developed and previously validated among other populations outside India.[14],[15],[16] With this background, the objective of this study was to assess the psychometric properties of AUTOS among subjects seeking care at a teaching dental institution in the South Indian state of Andhra Pradesh.
Materials and Methods | |  |
This study was conducted among patients seeking oral health care at a teaching dental institution in the South Indian state of Andhra Pradesh. The study was conducted between January and December 2017. AUTOS is a 12-item psychometric tool, to assess the autonomy over smoking, originally developed and validated at the University of Massachusetts Medical School.[14] The scale consisted of items relating to three symptom types as follows: withdrawal symptoms, psychologic dependence, and cue-induced craving. All the items were administered on a 4-point Likert scale ranging from “not at all” to “very well.” Thus, the symptom type-wise scores in AUTOS range from 4 to 16, whereas the overall scale score ranges from 12 to 48. The scale demonstrated excellent internal consistency reliability in previous studies (Cronbach alpha ≤0.91) and showed concurrent validity with the Fagerstrom test for cigarette dependence.[15] The 12-item scale was translated to the local language Telugu by a bilingual expert, which was then back-translated to English by another person proficient in both the languages. Minor modifications in the local language version were made to achieve semantic equivalence. A trained interviewer administered the scale to the participants in a quiet room. Details pertaining to participants’ age, gender, and years of smoking were collected. Fagerstrom test for nicotine dependence (FTND) was also administered along with AUTOS. The average time taken for the conduct of each interview was 8 minutes. All the participants signed a written informed consent before the administration of the scales. Ethical approval for this study {SJDC/CEC/2015-2016} was obtained from the Institutional Ethical Committee of St Joseph Dental College, Eluru, on December 22, 2015. A total of 199 subjects satisfying the eligibility criteria of self-reported current smoking who were willing to participate in the study constituted the final sample. This study aimed to verify the factor structure of AUTOS by performing confirmatory factor analysis (CFA). CFA was performed using Classical and Bayesian Instrument Development software program.[17] The sample size of 199 considered in this study was in accordance with the sample size requirements for structural equation models suggested by Wolf et al. [18] IBM SPSS version 20 software was used to check the internal consistency reliability of the AUTOS subscales. Further, correlation analyses between AUTOS subscale scores, age, years of smoking, and FTND scores were evaluated using Spearman correlation coefficient. Linear regression was performed to check the amount of variance in each of the symptom-wise subscale scores and the overall scale score that could be explained by age of the participant and the number of years for which the participant has been smoking.
Results | |  |
The mean age of the study participants was 43.92 ± 16.48 years and the mean duration for which the participants have been smokers was 19.16 ± 14.77 years. All the study subjects were males. The symptom type-wise subscales of AUTOS demonstrated good internal consistency reliability (Cronbach alpha ≥0.758). [Table 1] presents the corrected item total correlations, Cronbach alpha values for the AUTOS subscales along with Cronbach alpha values with deletion of individual items. Both the unidimensional factor structure and the symptom type-wise tridimensional factor structure of AUTOS were verified in CFA. [Table 2] presents the factor loadings of items in both the unidimensional and tridimensional models obtained using CFA. [Table 3] summarizes the model fit indices of both the CFA models evaluated. It was observed that the symptom type-wise tridimensional model showed good model fit indices compared to the unidimensional model. Significant positive correlation was observed between age, years of smoking, FTND score, and all the symptom type-wise subscale scores of AUTOS [Table 4]. Linear regression analyses showed that the number of years for which the subject had been smoking was a significant predictor of all the three AUTOS subscale scores [Table 5]. | Table 1 Internal consistency reliability statistics and the corrected item total correlations of the symptom type wise subscales of autonomy over smoking scale
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 | Table 2 Standardized estimates from the unidimensional and tridimensional models of AUTOS using confirmatory factor analysis
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 | Table 3 Comparison of model fit indices of both the unidimensional and tridimensional models tested in CFA
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 | Table 4 Correlation between age, years of smoking, autonomy over smoking scale, and its symptom-wise subscale scores
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 | Table 5 Multiple linear regression models with autonomy over smoking scale score and its subscale scores as outcome variables
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Discussion | |  |
This study tested the dimensionality of AUTOS among subjects seeking oral health care at a teaching dental institution in southern India by the conduct of confirmatory factor analysis. The study results support the symptom type-wise factor structure of AUTOS unlike the unidimensional factor structure observed in previous studies.[14],[19] It is important at this juncture to underscore the fact that AUTOS was originally developed with a notion that the manifestation of tobacco dependence can be manifold and three domains of withdrawal, psychologic dependence, and cue-induced craving were identified as different forms of tobacco dependence.[14] Such explicit distinction of items in the scale to be belonging to different domains holds an assumption that the factors responsible for each of these forms of tobacco dependence, the underlying mechanism of development of dependence, and the influence of each of these forms of dependence on the ability of the subject to quit tobacco are different.[19] Thus AUTOS possess an intrinsic tridimensional factor structure which was also established among the validation studies performed among adolescent smokers. Nevertheless, confirmatory factor analysis demonstrated a unidimensional factor structure of AUTOS among adult smokers of the United States America, the reason for which was identified to be the diminishing boundaries between the AUTOS subscales with increasing age.[19] However, in the present study performed among a sample of South Indian adult population, the mean age of whom was 43.92 ± 16.48 years, the tridimensional factor structure of AUTOS showed better model fit indices compared to the unidimensional factor structure. Each of the three subscales of AUTOS demonstrated good internal consistency reliability (Cronbach alpha ≥0.758). Similar observations were reported by Wellman et al.[16] The reasons cited for diminishing boundaries between AUTOS subscales with increasing age were the evolution of physical dependence early in the process of habituating tobacco consumption and the increasing association between physical dependence and psychologic dependence, cue-induced cravings with increasing durations of smoking.[20],[21] Though higher AUTOS subscale scores were observed in this study with increasing age, the explanations surrounding the fading distinction between subscales with age did not hold well among the population considered in the present study. Prospective studies that follow subjects from adolescence to late into their adulthoods may be necessary to acquire concrete insights into the differential inter item relations of AUTOS for participants from different age groups. It was observed in this study that the subscales of psychologic dependence and cue-induced cravings were the most correlated of the three subscales. All the three subscales of AUTOS showed good concurrent validity with the FTND score. Of the three subscales, withdrawal symptoms demonstrated strongest positive correlation with FTND score which could be understood in light of the nature of FTND items that attempt to document the compelling feelings of smokers to smoke. These findings were consistent with the results reported by DiFranza et al.[22],[23] The AUTOS subscale scores showed weak to moderate positive correlations with the years for which the subjects have been smoking. Contrary to these findings, strong positive correlation between AUTOS scores and duration, frequency of smoking were found in the studies conducted among the US and German populations.[14],[15] One of the limitations of this study is its reliance on a convenience sample of subjects seeking care at an oral health-care facility which limits the ability of the investigators to define the population from which the sample was drawn. Another potential limitation in this study is the social desirability bias inherent in all self-reported data, particularly with regard to a deleterious habit which is known to be harmful both for the individual and the society in a broader context.
Conclusion | |  |
Within the limitations of this study, AUTOS was observed to be a very useful tool that measures tobacco dependence in consistence with FTND among South Indian population, and while doing so, it captures the various forms of tobacco dependence in an independent manner. Future directions for research include the conduct of longitudinal studies that document the transformations in the factor structures of AUTOS with time and the reasons for such dynamic nature of association between items belonging to different symptom domains.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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