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| ORIGINAL ARTICLE |
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| Year : 2021 | Volume
: 37
| Issue : 3 | Page : 319-327 |
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Factor structure of the bengali version of the fagerstrom test for nicotine dependence questionnaire: A cross-sectional study
Abhijit Dutta1, Puja Bhakta2, Anaitulah Ahmed Mir3, Suman Singh1, Athia Sylvia Saprunamei3, Ramkripal Prajapati4, Deepak Kumar Pandey4, Ch Lily Anal5, Nitin Saklani4, Rachna Goenka2, Subhas Singh1, Abhijit Chattopadhyay3, Pralay Sharma6, Satarupa Sadhukhan1, Sk Swaif Ali7, Munmun Koley8, Subhranil Saha9
1 Department of Organon of Medicine, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
2 Department of Homoeopathic Pharmacy, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
3 Department of Materia Medica, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
4 Department of Repertory, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
5 Department of Paediatrics, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
6 Department of Deputy Medical Superintendent, Hospital Section, National Institute of Homoeopathy, Kolkata, Under Ministry of AYUSH, Government of India, Kolkata, India
7 Department of Medicine, Mahesh Bhattacharyya Homoeopathic Medical College and Hospital, Government of West Bengal, India
8 Department of Organon of Medicine and Homoeopathic Philosophy, State National Homoeopathic Medical College and Hospital, Lucknow, Government of Uttar Pradesh, India
9 Department of Repertory, D. N. De Homoeopathic Medical College and Hospital, Kolkata, Government of West Bengal, India
| Date of Submission | 12-Apr-2020 |
| Date of Decision | 25-Jul-2020 |
| Date of Acceptance | 03-Aug-2020 |
| Date of Web Publication | 04-Aug-2021 |
Correspondence Address:
Dr. Abhijit Dutta
Department of Organon of Medicine, National Institute of Homoeopathy, Under Ministry of AYUSH, Government of India, Block GE, Sector III, Salt Lake, Kolkata . 700 106, West Bengal
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijsp.ijsp_71_20
Context: The Fagerstrom test for nicotine dependence (FTND) is a self-administered ordinal measure of nicotine dependence containing six items that evaluate the quantity of tobacco smoking, the compulsion to use, and dependence. Aims: To date, no Bengali version of the questionnaire is available. We aimed to develop its Bengali version and examine its cross-cultural adaptability considering linguistic equivalence. Settings and Design: A cross-sectional study was conducted through consecutive sampling at the outpatients of the National Institute of Homoeopathy, Kolkata. Subjects and Methods: The FTND-Bengali version (FTND-B) was produced by standardized forward-backward translations. The psychometric analysis was run to examine its factor structure, validity, and reliability. Reliability was examined using internal consistency (n = 263). Construct validity was examined by exploratory factor analysis (n = 132) using principal component analysis (varimax rotation). Subsequently, confirmatory factor analysis (CFA; n = 131) was performed to verify the model fit. Results: The internal consistency was acceptable (Cronbach's α = 0.701; 95% confidence interval [CI] 0.641–0.753). The Kaiser–Meyer-Olkin (=0.712) and Bartlett's test of sphericity (Chi-square 109.593, P < 0.001) both suggested adequacy of the sample. In factor analysis using varimax, all the items loaded above the pre-specified value of 0.3 and identified two components – “restraint” (question no. 1, 2, and 6) and “compulsion” (question no. 3, 4, and 5); explaining 56.1% of the variation. The goodness-of-fit in the CFA model was mediocre, but acceptable (Comparative Fit Index = 0.871, Tucker Lewis Index = 0.759, Root Mean Square Error of Approximation = 0.142, Standardized Root Mean Square Residual = 0.026). Conclusions: FTND-B, consisting of 6 items and framed within two components, appeared to be a valid and reliable questionnaire.
Keywords: Bengali language, confirmatory factor analysis, factor analysis, Fagerstrom test for nicotine dependence, principal component analysis
How to cite this article:
Dutta A, Bhakta P, Mir AA, Singh S, Saprunamei AS, Prajapati R, Pandey DK, Anal CL, Saklani N, Goenka R, Singh S, Chattopadhyay A, Sharma P, Sadhukhan S, Ali SS, Koley M, Saha S. Factor structure of the bengali version of the fagerstrom test for nicotine dependence questionnaire: A cross-sectional study. Indian J Soc Psychiatry 2021;37:319-27 |
How to cite this URL:
Dutta A, Bhakta P, Mir AA, Singh S, Saprunamei AS, Prajapati R, Pandey DK, Anal CL, Saklani N, Goenka R, Singh S, Chattopadhyay A, Sharma P, Sadhukhan S, Ali SS, Koley M, Saha S. Factor structure of the bengali version of the fagerstrom test for nicotine dependence questionnaire: A cross-sectional study. Indian J Soc Psychiatry [serial online] 2021 [cited 2022 Jun 28];37:319-27. Available from: https://www.indjsp.org/text.asp?2021/37/3/319/323117 |
| Introduction | |  |
Tobacco consumption is a serious threat to humanity, and a great public health concern both in developed and developing countries, related to numerous health and environmental hazards.[1] It is consumed in many forms according to the culture and geographical location and the most frequent is smoking, followed by different forms of smokeless tobacco as well.[2] In 2015, over 1.1 billion people smoked tobacco globally.[3] According to the Global Adult Tobacco Survey (2016–2017), in India, 99.5 million adults smoke tobacco, and 199.4 million adults use smokeless tobacco. Among them, 42.4% are men and 14.2% are female.[4] Although tobacco use is declining in several countries, including India (dropping from 35% in 2009–2010 to 29% 2016–2017 among adults), it still poses a huge burden on India, as the world's second-largest consumer of tobacco products.[5],[6],[7],[8] Among many, nicotine is the most potent ingredient in any tobacco product, solely responsible for the dependence.[9] Due to the rapid increase of tobacco consumers, screening, and assessment of the severity of nicotine dependence appear to be very necessary for the intervention.
Clinically, Fagerstrom test for nicotine dependence (FTND) is the widely used tool to assess the intensity of addiction to nicotine[10] due to its simplicity and comprehensibility.[11] The Fagerstrom Tolerance Questionnaire (FTQ) was the initial form, developed by Karl Fagerstrom,[12] was further modified to the FTND by Heatherton et al. in 1991.[13] FTND is an ordinal measure of nicotine dependence primarily related to cigarette smoking. It contains six items that evaluate the quantity of cigarette consumption, the compulsion to use, and dependence. In scoring through FTND, Yes/No items are scored 1-0, and multiple-choice items scored from 0 to 3. The six items summed to obtain a result of 0-10. The higher score indicates more dependence on nicotine. This self-administered questionnaire[13] practically takes very few minutes to fill and very much feasible and sensitive to use. The clinical scoring can be used to prescribe medications for nicotine withdrawal or evaluating the clinical status in different visits. A study found that FTQ and FTND both having good test-retest stability, but the internal consistency is somewhat higher in FTND than FTQ.[14] One paper identified 26 studies related to the psychometric properties of the FTND in the indexed literature those confirmed its reliability.[15] Another review substantiated its psychometric properties for smokeless tobacco a well.[16] In the Indian context, the need or validation of translated versions of FTND has already been felt to evaluate the efficacy of nicotine replacement therapy.[17]
Till date, there is no available Bengali version of FTND. We intend to develop the Bengali version of the questionnaire through standardized forward-backward translation, and subsequently evaluating whether the FTND Bengali version (FTND-B) is a psychometrically sound tool to measure the construct and to examine its cross-cultural adaptation considering linguistic equivalence.
| Subjects and Methods | | |
Study design
This non-interventional, cross-sectional, validation study was a mixed-method study; it consisted of standardized translation procedures, face validation by pilot testing, and field testing, and psychometric assessment of the FTND-B.
Study setting
It was conducted at the tobacco cessation center (TCC) outpatient of the National Institute of Homoeopathy (NIH), Kolkata, under the Ministry of AYUSH, Government of India. Institutional Ethics Committee (IEC) approved the protocol before initiation (Ref. No. 5-23/NIH/PG/Ethical Comm. 2009/Vol. 5/2693 (A/S); dated March 28, 2018).
Questionnaire translation stages
The translation method followed standardized forward-backward processes[18] as follows:
- Forward translation: An expert committee was constructed, consisting of trained psychologists experienced in scale development and psychiatrist, linguistic experts, and research methodologists. First, two Bengali speakers, one psychologist, and one linguistic expert, translated the English version of FTND into Bengali (T1 and T2)
- Synthesis of T1, 2: The two translators then agreed on a consensus version of the translation (T1, 2). Then, the expert committee verified the version
- Back translation: Two English language translators (BT1 and BT2; one psychiatrist and one linguistic expert), blinded to the original English version, translated T1, 2 back into English independently
- Committee review: All the translations (T1 and T2, T1, 2, B1, and B2) were reviewed by the committee, and a written report was prepared comparing the back-translations with the forward translations. Based on these, the pre-final version was developed
- Face validation: The pre-final version of the questionnaire was tested on randomly chosen 10 patients visiting the TCC outpatient clinic of the hospital for the purpose of testing contextual clarity, layout, language transparency, ease of understanding the content and use, comprehensibility of the instructions and response scales. Difficulties, if any, were noted. A written report was prepared by the interviewers, including detected insufficiencies and recommended changes and was then submitted back to the committee
- Committee appraisal: The final version of the FTND-B was developed by the committee based on the inputs from face validity (supplementary file). The different translation stages and the complete study flow are presented in [Figure 1]
- Field testing and validation: During development of the original English version, content validity of the FTND-B questionnaire was already evaluated, and we refrained from repeating so [Figure 1].
Inclusion criteria
Age 18–65 years and of both sexes, participants suffering from nicotine dependence exclusively due to smoking; i.e., currently using the substance (ICD-10 F17.24) and continuous use (ICD-10 F17.25),[19] literate patients having ability to read Bengali, and treatment naïve patients willing to participate in the study and giving written informed consent.
Exclusion criteria
Patients having mental and behavior disorder due to psychoactive substance other than tobacco; currently and continuous users of smokeless tobacco or e-cigarette; other forms of substance abuse and/or dependence; patients suffering from mental and behavior disorder due to tobacco, acute intoxication F17.0, harmful uses F17.1, withdrawal state F17.3, withdrawal state with delirium F17.4, psychotic disorder F17.5, amnesic syndrome F17.6, residual and late-onset psychotic disorder F17.7; patient suffering from nicotine dependence who are currently abstinent F17.20, currently abstinent but in a protracted environment F17.21, currently on a clinically supervised maintenance or replacement regime (controlled dependence) F17.22, patients on tobacco-cessation drugs such bupropion, varenicline etc., currently abstinent but receiving treatment with aversive or blocking drugs F17.23, episodic use F17.26; self-reported immune-compromised state; patient is already undergoing nicotine replacement therapy; patient already undergoing any alternative or complementary treatment elsewhere for any chronic diseases; and any symptoms suggestive of any serious medical conditions that may require active intervention within 6 months.
Sample size
Although recommendations for adequate sample size to conduct factor analysis lack clear scientifically sound recommendations and remain controversial,[20] still a sample size between 50 and 250 is usually preferred with most authors recommending at least 100 subjects.[21] Gorsuch's formula of subject to item ratio (5:1 or 10:1) is also used for estimation of sample size for validation studies; thus indicating a requirement of 30–60 samples for our study.[22] However, out of 284 participants approached, we were able to capture 263 responses in total with a response rate of 92.6%, of which first 132 were subjected to principal component analysis (PCA) and the next 131 to confirmatory factor analysis (CFA); thus sample size for our study might be considered as fair to good.[23]
Sampling
Patients suffering from nicotine dependence who attended the outpatients of the hospital on the days of data collection were approached by consecutive sampling and were invited to participate in the study subject to fulfillment of the prespecified eligibility criteria.
Data collection
Before obtaining responses on the patients' self-administered FTND-B, all the participants were provided with patient information sheets in local vernacular Bengali and written informed consents were obtained. Patients' privacy was maintained by concealing all the identifiable information. Another section in the questionnaire sought information regarding patients' socio-demographic features. The filled-in FTND-B questionnaires were put inside envelops and sealed at the study site. The same self-administered questionnaire was filled in again by 30 participants selected randomly after 2–3 weeks. A Microsoft Excel spreadsheet was used for extraction of data and finally that was subjected to statistical analysis.
Statistical analysis
It was conducted by using IBM® Statistical Package for Social Sciences (SPSS)® software, version 20.0, and SPSS Amos® version 20.0 (IBM Corp., Armonk, NY, USA). First, adequacy of sample was checked using Kaiser-Meyer-Olkin (KMO) value and data appropriateness for PCA using Bartlett's test of sphericity. The KMO value 0.50 and above[24] with significant Bartlett's test of sphericity (P < 0.05) was considered appropriate for factor analysis. Then, exploratory factor analysis (EFA) using PCA with varimax rotation (Eigenvalue above 1) was conducted to examine the unidimensionality of the construct. The purpose was to test how much the groups of items represent a common underlying (latent) variable. In this, a dataset is simplified by reducing data dimensionality by eliminating the components with small eigenvalues (explained variance per variable) and, therefore, of lesser significance. Only factors with loadings of 0.30 and above were retained. Weak loadings that is, failure to load >0.29 on any component and general loadings of 0.30 on more than one component, would lead to the exclusion of the items from the matrix. Next, FTND-B reliability was evaluated by analyses of internal inconsistency and test-retest reliability. High internal consistencies were denoted by Cronbach's alpha of 0.5–0.7[25] and average item-total correlation in a moderate range of 0.3–0.9. The alpha value of 0.9 and above was considered as excellent, while no meaningful construct was indicated by a correlation near 0.[26] Intra-class correlation coefficient (ICC) values above 0.7 indicated that FTND-B was stable over time, 0.4–0.7 indicated fair reliability, while poor reliability was demonstrated by values <0.4.[27] Paired t-tests were used on randomly chosen 30 patients' responses to evaluate whether the change in scores on the FTND-B between the test-retest evaluations was statistically significant. Correlation statistics was used to assess the inter-item correlations between domains (item discriminant validity) and the overall FTND-B (internal item convergence). The instrument was considered to be internally consistent if the correlation value was found to be 0.4 or higher. Finally, a CFA model was developed to verify the goodness-of-fit of the a priori detected scales as suggested by EFA. Actually, the objective of CFA is to explain as much of the variation as possible with the model specified and to test whether the data fit a hypothesized measurement model. In CFA, the existence of a relationship is hypothesized between a set of experimental variables and their underlying constructs. A multivariate analysis substantiates this factor structure. Causal modeling or path analysis hypothesizes causal relationships among both the manifest (observed directly and endogenous/dependent; presented in rectangular boxes) and latent variables (factors or hypothetical exogenous constructs that are presumed to exist, but not measured or observed directly and are invoked to explain observed covariations; presented in oval shapes) and tests the causal models with a linear equation system. In CFA, specific hypotheses are framed about the structure of factor loadings, and then, the inter-correlations are tested. The goodness-of-fit of the CFA models was evaluated utilizing the following multiple fit indices: Comparative Fit Index (CFI), Normed Fit Index (NFI), Tucker Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), Bayesian Information Criterion (BIC), and Hoelter index. The recommendations for cutoff values indicating a good model fit are CFI or TLI ≥0.95, RMSEA ≤0.6, and SRMR ≤0.8.[28],[29] Statistical tests were two-tailed and were conducted with α fixed at 0.05.
| Results | | |
Descriptive statistics
Descriptive statistics, namely sociodemographic features, characteristics of tobacco consumption, and obtained response percentages on individual items on FTND-B questionnaires have been presented. FTND-B questionnaire responses were also presented in terms of means, standard deviations, medians, interquartile ranges, skewness, and kurtosis of each individual item [Table 1], [Table 2], [Table 3]. | Table 1: Baseline sociodemographic and features of nicotine dependence (n=263)
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 | Table 2: Descriptive statistics of the Fagerstrom test for nicotine dependence-B responses (n=263)
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 | Table 3: Response percentages on Fagerstrom test for nicotine dependence -B questionnaire (n=263)
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Exploratory factor analysis
The sample size was adequate, as evidenced by the KMO = 0.712, much greater than the minimum Kaiser criterion of 0.5. A significant Bartlett's test of sphericity (Chi-square: 109.593 at df = 15, P < 0.001) also signified that the R-matrix was not an identity matrix. Extraction was performed using the principal component method to verify the number of factors those bet explained the covariation matrix within the experimental sets of data. The first 2 components disclosed high eigenvalues, and subsequently, the curve dropped gradually before the final plateau was reached [Figure 2]. The correlation matrix was searched for values of more than 0.9 to identify multi-co-linearity and singularity. The determinant of the correlation matrix was 0.425 [Table 4]. Thus, multi-collinearity was not a problem for the dataset. All the items correlated well and none of the correlation coefficients were predominantly large; thus contradicting elimination of any item at this stage. The sample size of 132 was adequate for running PCA as the average communalities after extraction was 0.561, above the preferred cutoff of 0.5 [Table 5]. The factor component matrix also supported the screeplot by representing information from initial unrotated solution and extracting two components explaining 56.1% of the total variance [Table 6]. Each of the components with their respective Eigenvalues and percentage of total variances explained are presented in [Table 6]. The values were loads that related the variable to the particular factor. The exhibit of coefficients was arranged by size. Factor loadings were analogous to regression slopes and symbolized the strength of relationship between the factors and the components. The rotated (varimax) component matrix was a matrix of factor loadings for each variable onto each factor. The absolute values <0.3 were suppressed, ensuring that factor loadings within ± 0.3 were not displayed in the output. After conducting factor rotation, those items were eliminated that loaded onto the same factor. Two sub-components of the main construct were identified and named as below [Table 7]: | Table 5: Communalities – initial and after extraction (n=132; principal component analysis)
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 | Table 6: Total variances explained (n=132; principal component analysis)
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 | Table 7: Rotated component matrix – factor loadings revealing 2 component structures (n=132)
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- Items 1, 2 and 6: “Restraint”
- Items 3, 4 and 5: “Compulsion”
Internal consistency
The Cronbach's alpha value for the overall FTND-B was 0.701 and alpha for the 2 subscales were 0.524 and 0.538, respectively, indicating acceptable to good reliability. The intra-class correlation coefficient (ICC), inter-item correlation matrix, and item-total statistics also substantiated FTND-B questionnaire as internally consistent or reliable. Estimated Spearman-Brown coefficient, Guttman's split-half coefficient, and average Guttman's lambda for the six items were 0.741, 0.740, and 0.694 respectively [Table 8], [Table 9], [Table 10]. | Table 8: Internal consistency of the Fagerstrom test for nicotine dependence -B questionnaire (n=263)
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Test-retest reliability
FTND-B individual item scores, subscale scores, and total scores were largely stable with insignificant mean differences, thus indicating acceptable test–retest reliability [Table 11]. | Table 11: Test-retest reliability of the Fagerstrom test for nicotine dependence-B questionnaire items, domains and overall score (n=30)
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Confirmatory factor analysis
The path coefficients of CFA model are not correlation coefficients. Path coefficient θ of 0.93 means that with 1 standard deviation increase of the mean of the domain “restraint,” the domain “compulsion” would be expected to increase by 0.93 its own standard deviations from its own mean while holding all other relevant regional connections constant. The indices of CFA that confirmed model fit (Chi-square = 28.876, degrees of freedom = 8, P < 0.001) were: CFI = 0.871, NFI = 0.837, TLI = 0.759, RMSEA = 0.142, SRMR = 0.026, BIC = 92.253, and Hoelter index (at α 0.05) =70, indicating a mediocre model fit and two distinct components [Figure 3]. We tried to develop a more parsimonious and interpretable model by adding a second-order factor representing the hypothesis that these two seemingly distinct, but highly correlated constructs can be accounted for by one or more common underlying higher-order constructs; however, no such models could be framed successfully because of the absence of other exogenous variables enabling to draw covariances.
| Discussion | | |
FTND is a validated questionnaire comprised 6 questions and aimed at assessing nicotine dependence, but, until now, no validated Bengali version of the questionnaire was available and the factor structure was not studied. The English questionnaire underwent standardized forward-backward translation to produce the FTND-B version. EFA using PCA of the FTND-B identified 2 components– “restraint” and “compulsion.” The overall goodness of fit of the two-component model was further confirmed by CFA. FTND-B appeared to be valid and reliable with Cronbach's α, ICC coefficients, and test–retest reliability within acceptable limits.
The rationale for excluding all except F17.2 patients was to ensure responses from a homogeneous sample of tobacco-dependents. One of the major strengths of this study was to apply EFA and CFA on two different samples. The study shows that the overall and individual subscales of FTND-B were similar to other studies.[30],[31],[32],[33],[34] There were satisfactorily high inter-item correlations among the subscales. While running PCA, sample size achieved by us was similar to the original FTND development and validation study and other translations, but we achieved more 131 samples to perform CFA. Fifty percent (3/6) of the items had strong factor loadings of 0.60 and above. The 2 component model had an acceptable model fit in CFA. Thus, further translation and validation of the questionnaire is warranted into other Indian languages and on the larger sample for better and large-scale utilization in a multi-ethnic Indian population.
Unlike other validation studies, there was no control (normal/healthy) group; hence, the assessment of item discriminant validity was not possible. Besides, the responsiveness of the questionnaire was not assessed because the treatment offered by the study site was homeopathy exclusively and that was not an accepted standard treatment for nicotine dependence until now. Our findings revealed that the internal consistency was overall reasonable and comparable to the existing versions; however, two individual components showed a fairly low Cronbach's alpha. It is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. Alpha coefficients that are <0.5 are usually unacceptable, especially for scales purporting to be unidimensional. A low value for alpha may mean that there are not enough questions on the test. Adding more relevant items to the test can increase alpha. The usual practice is to remove few poorly correlated items (coefficients <0.30) to increase the overall consistency or to add more items that constitute the construct. However as the number of items was not too many, and the overall score was higher than 0.30, and retaining all the items revealed a fair fit in the CFA model, we decided not to eliminate any of the items. It should also be kept in mind that alpha has very strict assumptions, including unidimensionality, uncorrelated errors, and identical covariances between the items (tau equivalence). In most of cases, these assumptions are violated and thus over- or underestimates the true reliability. Thus, alpha may not be the best choice for measuring reliability. The probable alternative may be Guttman's lambda or McDonald's omega which are not based on tau-equivalence. There is a relationship between alpha (α), theta (θ), and Omega (Ω) coefficients. If the items take parallel values, three coefficients are equal each other and will be 1.0. Otherwise, the relationship of magnitude for the coefficients will be α < θ < Ω. Another important caveat was that FTND-B was administered to the patients competent in reading and understanding the Bengali language. Therefore, the study findings are generalizable to the Bengalee population only. Another drawback was the consecutive sampling used that might have introduced sampling bias into the study.
In comparison with another factor analysis study of FTND questionnaire by Radzius et al.,[30] two factors were identified– factor 1 comprising items 1, 3 and 5, and factor 2 consisting of items 2, 4 and 6. Item no. 1 loaded substantially on both factors. The difference of results obtained from our study may be due to the reason that Radzius et al. sample has histories of poly-substance abuse, whereas, in ours, we excluded such samples from this study. In similarity with other FTND factor analysis studies,[13],[31],[32] we also used the varimax rotated solutions-the simplest case of orthogonal rotation where the axes are rotated to align with the coordinates keeping the actual coordinate system unaltered. It tends to produce factor loading that are either very high or very low, making it easier to match each item with a single factor. As detected by our study, the Cronbach's alpha was also low in other studies as well, as found in the review by Meneses-Gaya et al.[15] and also in Arabian[33] and Mexican smokers,[34] but significant test–retest reliability.[15]
Thus, the validated FTND-B served as an important patient-administered outcome questionnaire to measure nicotine dependence. Future research should include the utilization of the FTND-B as an outcome measure in clinical trials. Few items may be added to improve the overall consistency of the questionnaire. Hence, the responsiveness and sensitivity to change of the FTND-B to measure symptoms and treatment effects need to be determined in future investigations. Finally, to confirm that FTND-B can measure the impact of clinical treatment, the final step in this development will be to define a minimally important difference of change, reflecting a clinically meaningful difference. The FTND-B assessed two distinct dimensions– “compulsion” and “restraint” that may provide an evaluation of efficacy or effectiveness of any targeted interventions.
| Conclusion | | |
The developed FTND-B contains 6 items which are constructed within 2-component model. It is a reasonably valid and reliable tool, enabled to measure nicotine dependence in Bengalee patients. However, to strengthen the validity of the FTND-B, further independent replications are recommended.
Acknowledgment
The authors appreciate the kind help received from Dr. Malay Mundle, Research Methodologist, Dr. Atanu Dogra, Psychologist, Dr. Arabinda Brahma, Psychiatrist, Mr. Kohinoor Chakraborty and Mr. Indrajit Mitra, Linguistic Experts for their services as expert panelist in the review committee. We are also grateful to the patients for their sincere participation.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | |
| 2. | Chun J. Public health threat of tobacco and substance use in Asia: An introduction to the theme issue. J Psychoactive Drugs 2020;52:1-4.  |
| 3. | |
| 4. | Singh PK, Yadav A, Singh L, Singh S, Mehrotra R. Social determinants of dual tobacco use in India: An analysis based on the two rounds of global adult tobacco survey. Prev Med Rep 2020;18:101073. |
| 5. | Nagler EM, Aghi M, Rathore A, Lando H, Pednekar MS, Gupta PC, et al. Factors associated with successful tobacco use cessation among teachers in Bihar state, India: A mixed-method study. Health Educ Res 2020;35:60-73. |
| 6. | Yuvaraj BY, Mane VP, Anilkumar L, Biradar M, Nayaka V, Sreenivasamurthy R. Prevalence of consumption of smokeless tobacco products and exposure to second-hand smoke among women in the reproductive age group in a rural area of Koppal, Karnataka. Indian J Community Med 2020;45:92-5. [ PUBMED] [Full text] |
| 7. | Singh PK, Yadav A, Lal P, Sinha DN, Prakash CG, Swasthicharan L, et al. Dual burden of smoked and smokeless tobacco use in India, 2009-17: A repeated cross-sectional analysis based on global adult tobacco survey. Nicotine Tob Res 2020;ntaa033. |
| 8. | Rupani MP, Parikh KD, Kakadia MJ, Pathak MM, Patel MR, Shah MA. Cross-sectional study on smokeless tobacco use, awareness and expenditure in an urban slum of Bhavnagar, western India. Natl Med J India 2019;32:137-40. [ PUBMED] [Full text] |
| 9. | How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease: A Report of the Surgeon General. Centers for Disease Control and Prevention (US); National Center for Chronic Disease Prevention and Health Promotion (US); Office on Smoking and Health (US). Atlanta (GA): Centers for Disease Control and Prevention (US); 2010. Available from: https://www.ncbi.nlm.nih.gov/books/NBK53018/. [Last accessed on 2020 Mar 17]. |
| 10. | Fagerström K, Helena Furberg H. A comparison of the Fagerström test for nicotine dependence and smoking prevalence across countries. Addiction 2008;103:841-5. |
| 11. | Etter JF, Duc TV, Perneger TV. Validity of the Fagerström test for nicotine dependence and of the Heaviness of Smoking Index among relatively light smokers. Addiction 1999;94:269-81. |
| 12. | Pomerleau CS, Majchrzak MJ, Pomerleau OF. Nicotine dependence and the Fagerström Tolerance Questionnaire: A brief review. J Subst Abuse 1989;1:471-7. |
| 13. | Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The fagerström test for nicotine dependence: A revision of the fagerström tolerance questionnaire. Br J Addict 1991;86:1119-27. |
| 14. | Pomerleau CS, Carton SM, Lutzke ML, Flessland KA, Pomerleau OF. Reliability of the Fagerstrom Tolerance Questionnaire and the Fagerstrom test for nicotine dependence. Addict Behav 1994;19:33-9. |
| 15. | Meneses-Gaya IC, Zuardi AW, Loureiro SR, Crippa JA. Psychometric properties of the Fagerström Test for Nicotine Dependence. J Bras Pneumol 2009;35:73-82. |
| 16. | Mushtaq N, Beebe LA. Psychometric properties of fagerström test for nicotine dependence for smokeless tobacco users (FTND-ST). Nicotine Tob Res 2017;19:1095-101. |
| 17. | Sharma MK, Sharma P. Need for validation of Fagerstrom test for nicotine dependence in indian context: Implications for nicotine replacement therapy. Indian J Psychol Med 2016;38:105-8. [Full text] |
| 18. | Koller M, Aaronson NK, Blazeby J, Bottomley A, Dewolf L, Fayers P, et al. Translation procedures for standardised quality of life questionnaires: The European organisation for research and treatment of cancer (EORTC) approach. Eur J Cancer 2007;43:1810-20. |
| 19. | World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization; 1992. |
| 20. | Anthoine E, Moret L, Regnault A, Sébille V, Hardouin JB. Sample size used to validate a scale: A review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes 2014;12:176. |
| 21. | Preacher KJ, MacCallum RC. Exploratory factor analysis in behavior genetics research: Factor recovery with small sample sizes. Behav Genet 2002;32:153-61. |
| 22. | Gorsuch RL. Factor Analysis. 2 nd ed.. Hillsdale: Lawrence Erlbaum Associates; 1983. |
| 23. | Comrey AL, Lee HB. A First Course in Factor Analysis. 2 nd ed.. Hillsdale, NJ: Lawrence Erlbaum Associates; 1992. p. 488. |
| 24. | Sitzia J. How valid and reliable are patient satisfaction data? An analysis of 195 studies. Int J Qual Health Care 1999;11:319-28. |
| 25. | Streiner DL, Norman GR. Health Measurement Scales: A Practical Guide to Their Development and Use. Oxford: Oxford University Press; 2008. |
| 26. | Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess 1994;6:284-90. |
| 27. | Maccallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling of fit involving a particular measure of model. Psychol Methods 1996;13:130-49. |
| 28. | Hu L, Bentler P. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling 1999;6:1-55. |
| 29. | 2Brown TA. Confirmatory Factor Analysis for Applied Research. New York, NY: Guilford Press; 2006. |
| 30. | Radzius A, Gallo JJ, Epstein DH, Gorelick DA, Cadet JL, Uhl GE, et al. A factor analysis of the Fagerström Test for Nicotine Dependence (FTND). Nicotine Tob Res 2003;5:255-40. |
| 31. | Haddock CK, Lando H, Klesges RC, Talcott GW, Renaud EA. A study of the psychometric and predictive properties of the Fagerström Test for Nicotine Dependence in a population of young smokers. Nicotine Tob Res 1999;1:59-66. |
| 32. | Payne TJ, Smith PO, McCracken LM, McSherry WC, Antony MM. Assessing nicotine dependence: A comparison of the Fagerström Tolerance Questionnaire (FTQ) with the Fagerstrom Test for Nicotine Dependence (FTND) in a clinical sample. Addict Behav 1994;19:307-17. |
| 33. | Kassim S, Salam M, Croucher R. Validity and reliability of the Fagerstrom Test for Cigarette Dependence in a sample of Arabic speaking UK-resident Yemeni khat chewers. Asian Pac J Cancer Prev 2012;13:1285-8. |
| 34. | Moreno-Coutiño A, Villalobos-Gallegos L. Psychometric properties of the fagerström test for nicotine dependence in a sample of Mexican smokers. J Addict Nurs 2017;28:27-33. |
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9], [Table 10], [Table 11]
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