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The psychometric properties of the Chinese version of the Fagerstrom Test for Nicotine Dependence
Addictive Behaviors 31 (2006) 2324 – 2327
Short communication
The psychometric properties of the Chinese version of the Fagerstrom Test for Nicotine Dependence Chih-Ling Huang a,b, Hsi-Hui Lin a, Hsiu-Hung Wang b,* a
b
Department of Nursing, Chang Jung University, Taiwan College of Nursing, Kaohsiung Medical University, No. 100 Shih-Chuan 1st Road, San-Ming District, Kaoshiung 807, Taiwan
Abstract This study examined the psychometric properties of the Chinese version of the Fagerstrom Test for Nicotine Dependence (FTND). Criterion validity, factorial structure, and construct reliability were conducted using PRELIS 2 and LISREL 8.7 software. Two hundred and forty-five adult smokers were recruited from April to August 2005 in Taiwan. Because some items of the FTND are dichotomous and ordinal, biserial and polyserial correlations between the items and saliva cotinine levels were utilized. Confirmatory factor analyses (CFA) were performed to compare the relative fit of three competing models. Computation of the construct reliability was necessitated by a lack of tau-equivalence. The results demonstrated that the Chinese version has satisfactory validity and reliability. One item, bSmoke more in the morning,Q had low correlations with saliva cotinine. CFA found the items of the Chinese version were best modeled as two correlated factors without a cross-loading. These findings differ from the previous research testing the English version. Studies addressing the specific features of cigarette dependence in different socio-cultural contexts are needed. D 2006 Elsevier Ltd. All rights reserved. Keywords: Nicotine dependence; Biomarker; Psychometrics
1. Introduction One measure of cigarette dependence widely used in dependence research is the six-item Fagerstrom Test for Nicotine Dependence (FTND). The FTND was proposed a uni-dimensional structure by using * Corresponding author. Tel.: +886 7 3121101x2621; fax: +886 7 3218364. E-mail address: [email protected] (H.-H. Wang). 0306-4603/$ - see front matter D 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.addbeh.2006.02.024
C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
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an exploratory factor analysis (EFA) (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991). However, an EFA (Radzius et al., 2003) and a confirmatory factor analysis (CFA) (Richardson & Ratner, 2005) proposed one-item (how soon after you wake up do you smoke your first cigarette) loading on two factors (morning smoking and daytime smoking). The FTND has been translated into Chinese and used to assess adult smokers’ nicotine dependence in a nationwide smoking cessation program funded by the Department of Health of Taiwan, which provides financial support for nicotine replacement therapy (NRT). Adult smokers can get financial aid for NRT if their FTND scores are higher than 4 (Bureau of Health Promotion, 2004). But the FTND has yet to be evaluated to expand its use with Taiwanese smokers, who are in a different smoking environment. Because the FTND is scored dichotomously and rankly, biserial correlations were employed to assess the criterion validity, the factorial structure, and the construct reliability of the Chinese version of the FTND. Three nested CFA models of the Chinese version of the FTND were tested using the alternative model testing strategy recommended by Bollen (2000). Model 1 is the single factor model with all six items loading on one factor. Model 2 is the two-correlated factor model (Items 3 and 5 loading on a morning smoking factor; Items 1, 2, 4, and 6 loading on a daytime smoking factor). Model 3 is the twocorrelated factor model with Item 1 loading on both factors.
2. Methods According to Lee, Poon, and Bentler (1995), in order to avoid inadequate convergence or Heywood solutions in which parameters are negative variance estimates the sample size needs to be more than 200. The Chinese version of the FTND was administered to a sample of 245 adult smokers recruited from April to August 2005 from the general community. The FTND was translated into Chinese by the Bureau of Health Promotion of the Department of Health in Taiwan. With Dr. Heatherton’s permission, the Chinese version of the FTND was tested in the Taiwanese socio-cultural context. In order to validate the FTND, saliva cotinine were used. In the tests of criterion validity, biserial and polyserial correlation coefficients were computed between the six items and saliva cotinine levels. CFA was performed to compare three nested models. Instead of Cronbach’s alpha, the construct reliability was necessitated by a lack of tau-equivalence (Raykov, 1997). The coefficient of construct reliability was computed using the
Table 1 Correlation between items and saliva cotinine (N = 245) Item
Cotinine
P value
1. Time to the first cigarette of the day 2. Difficulty refraining from smoking 3. Which cigarette would you most hate to give up 4. Cigarettes per day 5. Smoke more in the morning 6. Smoke when ill Total scores
0.38 0.26 0.31 0.46 0.07 0.41 0.45
0.001*** 0.001*** 0.001*** 0.001*** 0.15 0.001*** 0.001***
*p b 0.05; **p b 0.01; ***p b 0.001.
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C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
Table 2 Results of CFA models Fit indices 2
Model v (df) p-value NFI NNFI GFI CFI RMSEA SRMR
Model 1
Model 2
Model 3
18.47 (9) 0.03 0.97 0.97 0.93 0.98 0.07 0.06
12.87 (8) 0.12 0.98 0.98 0.99 0.95 0.05 0.05
12.43 (7) 0.09 0.98 0.98 0.95 0.99 0.06 0.05
best-fit model. The software PRELIS 2 and LISREL 8.7 were employed to perform the above analyses.
3. Results The 245 smokers smoked an average of 20 cigarettes per day (SD = 10.6), their average age was 47 years (SD = 16.6) with a range from 18 to 88, and 96.7% of them were men. The mean score on the total FTND was 4.6 (SD = 2.5). The mean level of saliva cotinine was 230.4 ng/ml (SD = 127.0). Table 1 shows the relationship between the items and the biomarker. Items 1, 2, 3, 4 and 6 had significantly positive correlation with saliva cotinine levels, with correlation coefficients from 0.26 to 0.46. Item 5 was not significantly correlated with cotinine level. Total FTND scores correlated significantly with cotinine level, with coefficients 0.45. The results of the CFA analyses (Table 2) indicated that Model 1 did not fit the data (v 2Model 1 (9) = 18.47, p = 0.03). Based on cutoff criteria for relatively good fit (normed fit index (NFI) z 0.95, nonnormed fit index (NNFI) z 0.95, goodness-of-fit index (GFI) z 0.95, comparative fit index (CFI) z 0.95, root-mean-square error of approximation (RMSEA) V 0.06, and standardized root-mean-square residual (SRMR) V 0.8) recommended by Hu and Bentler (1999), GFI and RMSEA for Model 1 was less than favorable. Model 2 and Model 3 demonstrated a satisfactory fit with the data. Model 2 appears to have a slightly better fit than Model 3, but the difference is not statistically significant (v 2Model 2 Model 3 (1) = 0.44, p = 0.48). The construct reliability was assessed in Model 2. The coefficient of construct reliability was 0.74.
4. Discussion Overall, this study showed that six items of the Chinese version of the FTND had satisfactory validity. However, item 5 had low correlations with cotinine level. The reasons may be socio-cultural since many participants expressed the desire to smoke after meals instead of bin the morning hours.Q This suggests that smoking behavior in Taiwan has socio-cultural influences, as is reflected in the Chinese saying: bA cigarette after a meal and I am in seventh heaven.Q Regardless of EFA and CFA, previous research found Item 1 cross-loading on two factors (Radzius et al., 2003; Richardson & Ratner, 2005). The structure of the Chinese version of the FTND confirms a two-correlated factor model without a cross-loading.
C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
2327
Richardson and Ratner (2005) reported construct coefficients of 0.82 and 0.70, respectively, for morning smoking factor and daytime smoking factor, instead of an overall value. However, a total score for the Chinese version is used to determine pharmacology treatments in the smoking cessation program in Taiwan. The construct reliability of the best-fit model needs to be reported and indicates that the Chinese version has a satisfactory internal consistency. This study contributes to evaluating the generalizability of using the FTND in different socio-cultural contexts. However, in this study, female smokers comprised 3.3% of the sample due to very difficult recruitment and the low percentage of the female smoking population in Taiwan. Further studies with female smokers and studies that develop the construct of cigarette dependence to address specific features in cultural contexts are needed.
References Bollen, K. A. (2000). Modeling strategies: In search of the Holy Grail. Structure Equation Modeling, 7(1), 74 – 81. Bureau of Health Promotion. (2004). Tobacco control in Taiwan — 2003. Retrieved January 3, 2004, from http:// www.bhp.doh.gov.tw/tobacco/ Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., & Fagerstrom, K. O. (1991). The Fagerstrom Test for Nicotine Dependence: A revision of the Fagerstrom tolerance questionnaire. British Journal of Addiction, 86, 1119 – 1127. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1 – 55. Lee, S. Y., Poon, W. Y., & Bentler, P. M. (1995). A two-stage estimation of structural equation models with continuous and polytomous variables. The British Journal of Mathematical and Statistical Psychology, 48, 339 – 358. Radzius, A., Gallo, J. J., Epstein, D. H., Gorelick, D. A., Cadet, J. L., & Uhl, G. E., et al. (2003). A factor analysis of the Fagerstrom Test for Nicotine Dependence (FTND). Nicotine and Tobacco Research, 5(2), 255 – 260. Raykov, T. (1997). Scale reliability, Cronbach’s coefficient alpha, and violations of essential tau-equivalence with fixed congeneric components. Multivariate Behavioral Research, 32(4), 329 – 353. Richardson, C. G., & Ratner, P. A. (2005). A confirmatory factor analysis of the Fagerstrom Test for Nicotine Dependence. Addictive Behaviors, 30(4), 697 – 709.
Short communication
The psychometric properties of the Chinese version of the Fagerstrom Test for Nicotine Dependence Chih-Ling Huang a,b, Hsi-Hui Lin a, Hsiu-Hung Wang b,* a
b
Department of Nursing, Chang Jung University, Taiwan College of Nursing, Kaohsiung Medical University, No. 100 Shih-Chuan 1st Road, San-Ming District, Kaoshiung 807, Taiwan
Abstract This study examined the psychometric properties of the Chinese version of the Fagerstrom Test for Nicotine Dependence (FTND). Criterion validity, factorial structure, and construct reliability were conducted using PRELIS 2 and LISREL 8.7 software. Two hundred and forty-five adult smokers were recruited from April to August 2005 in Taiwan. Because some items of the FTND are dichotomous and ordinal, biserial and polyserial correlations between the items and saliva cotinine levels were utilized. Confirmatory factor analyses (CFA) were performed to compare the relative fit of three competing models. Computation of the construct reliability was necessitated by a lack of tau-equivalence. The results demonstrated that the Chinese version has satisfactory validity and reliability. One item, bSmoke more in the morning,Q had low correlations with saliva cotinine. CFA found the items of the Chinese version were best modeled as two correlated factors without a cross-loading. These findings differ from the previous research testing the English version. Studies addressing the specific features of cigarette dependence in different socio-cultural contexts are needed. D 2006 Elsevier Ltd. All rights reserved. Keywords: Nicotine dependence; Biomarker; Psychometrics
1. Introduction One measure of cigarette dependence widely used in dependence research is the six-item Fagerstrom Test for Nicotine Dependence (FTND). The FTND was proposed a uni-dimensional structure by using * Corresponding author. Tel.: +886 7 3121101x2621; fax: +886 7 3218364. E-mail address: [email protected] (H.-H. Wang). 0306-4603/$ - see front matter D 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.addbeh.2006.02.024
C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
2325
an exploratory factor analysis (EFA) (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991). However, an EFA (Radzius et al., 2003) and a confirmatory factor analysis (CFA) (Richardson & Ratner, 2005) proposed one-item (how soon after you wake up do you smoke your first cigarette) loading on two factors (morning smoking and daytime smoking). The FTND has been translated into Chinese and used to assess adult smokers’ nicotine dependence in a nationwide smoking cessation program funded by the Department of Health of Taiwan, which provides financial support for nicotine replacement therapy (NRT). Adult smokers can get financial aid for NRT if their FTND scores are higher than 4 (Bureau of Health Promotion, 2004). But the FTND has yet to be evaluated to expand its use with Taiwanese smokers, who are in a different smoking environment. Because the FTND is scored dichotomously and rankly, biserial correlations were employed to assess the criterion validity, the factorial structure, and the construct reliability of the Chinese version of the FTND. Three nested CFA models of the Chinese version of the FTND were tested using the alternative model testing strategy recommended by Bollen (2000). Model 1 is the single factor model with all six items loading on one factor. Model 2 is the two-correlated factor model (Items 3 and 5 loading on a morning smoking factor; Items 1, 2, 4, and 6 loading on a daytime smoking factor). Model 3 is the twocorrelated factor model with Item 1 loading on both factors.
2. Methods According to Lee, Poon, and Bentler (1995), in order to avoid inadequate convergence or Heywood solutions in which parameters are negative variance estimates the sample size needs to be more than 200. The Chinese version of the FTND was administered to a sample of 245 adult smokers recruited from April to August 2005 from the general community. The FTND was translated into Chinese by the Bureau of Health Promotion of the Department of Health in Taiwan. With Dr. Heatherton’s permission, the Chinese version of the FTND was tested in the Taiwanese socio-cultural context. In order to validate the FTND, saliva cotinine were used. In the tests of criterion validity, biserial and polyserial correlation coefficients were computed between the six items and saliva cotinine levels. CFA was performed to compare three nested models. Instead of Cronbach’s alpha, the construct reliability was necessitated by a lack of tau-equivalence (Raykov, 1997). The coefficient of construct reliability was computed using the
Table 1 Correlation between items and saliva cotinine (N = 245) Item
Cotinine
P value
1. Time to the first cigarette of the day 2. Difficulty refraining from smoking 3. Which cigarette would you most hate to give up 4. Cigarettes per day 5. Smoke more in the morning 6. Smoke when ill Total scores
0.38 0.26 0.31 0.46 0.07 0.41 0.45
0.001*** 0.001*** 0.001*** 0.001*** 0.15 0.001*** 0.001***
*p b 0.05; **p b 0.01; ***p b 0.001.
2326
C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
Table 2 Results of CFA models Fit indices 2
Model v (df) p-value NFI NNFI GFI CFI RMSEA SRMR
Model 1
Model 2
Model 3
18.47 (9) 0.03 0.97 0.97 0.93 0.98 0.07 0.06
12.87 (8) 0.12 0.98 0.98 0.99 0.95 0.05 0.05
12.43 (7) 0.09 0.98 0.98 0.95 0.99 0.06 0.05
best-fit model. The software PRELIS 2 and LISREL 8.7 were employed to perform the above analyses.
3. Results The 245 smokers smoked an average of 20 cigarettes per day (SD = 10.6), their average age was 47 years (SD = 16.6) with a range from 18 to 88, and 96.7% of them were men. The mean score on the total FTND was 4.6 (SD = 2.5). The mean level of saliva cotinine was 230.4 ng/ml (SD = 127.0). Table 1 shows the relationship between the items and the biomarker. Items 1, 2, 3, 4 and 6 had significantly positive correlation with saliva cotinine levels, with correlation coefficients from 0.26 to 0.46. Item 5 was not significantly correlated with cotinine level. Total FTND scores correlated significantly with cotinine level, with coefficients 0.45. The results of the CFA analyses (Table 2) indicated that Model 1 did not fit the data (v 2Model 1 (9) = 18.47, p = 0.03). Based on cutoff criteria for relatively good fit (normed fit index (NFI) z 0.95, nonnormed fit index (NNFI) z 0.95, goodness-of-fit index (GFI) z 0.95, comparative fit index (CFI) z 0.95, root-mean-square error of approximation (RMSEA) V 0.06, and standardized root-mean-square residual (SRMR) V 0.8) recommended by Hu and Bentler (1999), GFI and RMSEA for Model 1 was less than favorable. Model 2 and Model 3 demonstrated a satisfactory fit with the data. Model 2 appears to have a slightly better fit than Model 3, but the difference is not statistically significant (v 2Model 2 Model 3 (1) = 0.44, p = 0.48). The construct reliability was assessed in Model 2. The coefficient of construct reliability was 0.74.
4. Discussion Overall, this study showed that six items of the Chinese version of the FTND had satisfactory validity. However, item 5 had low correlations with cotinine level. The reasons may be socio-cultural since many participants expressed the desire to smoke after meals instead of bin the morning hours.Q This suggests that smoking behavior in Taiwan has socio-cultural influences, as is reflected in the Chinese saying: bA cigarette after a meal and I am in seventh heaven.Q Regardless of EFA and CFA, previous research found Item 1 cross-loading on two factors (Radzius et al., 2003; Richardson & Ratner, 2005). The structure of the Chinese version of the FTND confirms a two-correlated factor model without a cross-loading.
C.-L. Huang et al. / Addictive Behaviors 31 (2006) 2324–2327
2327
Richardson and Ratner (2005) reported construct coefficients of 0.82 and 0.70, respectively, for morning smoking factor and daytime smoking factor, instead of an overall value. However, a total score for the Chinese version is used to determine pharmacology treatments in the smoking cessation program in Taiwan. The construct reliability of the best-fit model needs to be reported and indicates that the Chinese version has a satisfactory internal consistency. This study contributes to evaluating the generalizability of using the FTND in different socio-cultural contexts. However, in this study, female smokers comprised 3.3% of the sample due to very difficult recruitment and the low percentage of the female smoking population in Taiwan. Further studies with female smokers and studies that develop the construct of cigarette dependence to address specific features in cultural contexts are needed.
References Bollen, K. A. (2000). Modeling strategies: In search of the Holy Grail. Structure Equation Modeling, 7(1), 74 – 81. Bureau of Health Promotion. (2004). Tobacco control in Taiwan — 2003. Retrieved January 3, 2004, from http:// www.bhp.doh.gov.tw/tobacco/ Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., & Fagerstrom, K. O. (1991). The Fagerstrom Test for Nicotine Dependence: A revision of the Fagerstrom tolerance questionnaire. British Journal of Addiction, 86, 1119 – 1127. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1 – 55. Lee, S. Y., Poon, W. Y., & Bentler, P. M. (1995). A two-stage estimation of structural equation models with continuous and polytomous variables. The British Journal of Mathematical and Statistical Psychology, 48, 339 – 358. Radzius, A., Gallo, J. J., Epstein, D. H., Gorelick, D. A., Cadet, J. L., & Uhl, G. E., et al. (2003). A factor analysis of the Fagerstrom Test for Nicotine Dependence (FTND). Nicotine and Tobacco Research, 5(2), 255 – 260. Raykov, T. (1997). Scale reliability, Cronbach’s coefficient alpha, and violations of essential tau-equivalence with fixed congeneric components. Multivariate Behavioral Research, 32(4), 329 – 353. Richardson, C. G., & Ratner, P. A. (2005). A confirmatory factor analysis of the Fagerstrom Test for Nicotine Dependence. Addictive Behaviors, 30(4), 697 – 709.