This section describes the range of approaches used to assess tobacco dependence, with a focus on commonly used measures such as the Fagerström Test for Nicotine Dependence, Heaviness of Smoking Index and Hooked on Nicotine Checklist.
A person’s degree of tobacco dependence may be assessed in several ways. These include how often and how much tobacco they consume, biochemical markers (such as levels of cotinine, a by-product of nicotine metabolism) (covered in 12.5.6 Biomarkers of tobacco smoke and damage), and self-reported smoking behaviour measured in questionnaires.1
Instruments to assess whether a person who smokes satisfies the criteria for drug dependence include the DSM-5 criteria, derived from the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association3 and the ICD-10 classification from the International statistical classification of diseases of the World Health Organization4 A summary of the diagnostic criteria of Tobacco Use Disorder is described in Section 6.1.
Tests of psychological and physiological dependence, in the form of a questionnaire for people who smoke tobacco products,5 include the Fagerström Test for Nicotine Dependence6 (which evolved from the earlier Fagerström Tolerance Questionnaire7), the Heaviness of Smoking Index,8 the Cigarette Dependence Scales,9 the Nicotine Dependence Syndrome Scale,10 the Wisconsin Inventory of Smoking Dependence Motives,11 Wisconsin Smoking Withdrawal Scale,12 the Autonomy over Tobacco Scale13, and the Glover Nilsson Smoking Behavioral Questionnaire14.
The most commonly used measure15 is the Fagerström Test for Nicotine Dependence.6,16 This instrument asks the person who smokes a set of questions, the answers to which are scored as shown in Table 6.12.1 and added to give a total score: a score of six or more is seen as an indicator of high dependence.
The Heaviness of Smoking Index is a 2-item measure that was derived from the Fagerström Tolerance Questionnaire.8 The items and corresponding response answer options with scoring are shown in Table 6.12.2, and are used to categorise people who smoke into levels of nicotine dependence, although the number of categories and cut-off scores may vary slightly across studies. Due to its brevity, it is also commonly used in population surveys and clinical setting for assessing treatment suitability.17
The ‘time to first cigarette’ included in both the Fagerström Test for Nicotine Dependence and Heaviness of Smoking Index, is considered the best single-item indicator of dependence. Research indicates that earlier time to first cigarette is associated with higher levels of biomarkers of tobacco exposure, and lower likelihood of smoking cessation and maintaining abstinence.18
The Royal Australian College of General Practitioners’ Supporting smoking cessation: A guide for health professionals indicates that health professionals should assess nicotine dependence using time to first cigarette and that smoking within 30 minutes indicates nicotine dependence. The guidance also lists smoking more than 10 cigarettes per day (although some nicotine-dependent people may not smoke daily) and a history of withdrawal symptoms in previous attempts to quit as indicators of nicotine dependence.19
Another measure of addiction levels is the ‘Hooked on Nicotine Checklist’ (HONC), which assesses when the individual loses their control, or autonomy, over their use of tobacco use.20 Loss of autonomy is the point at which ‘the sequelae of tobacco use, either physical or psychological, present a barrier to quitting’ (p399).20 The HONC was originally devised to use with younger people—a group for whom some of the questions in the Fagerström Test were much less relevant. For example, most adolescents would not be able to smoke within minutes of waking in the morning, or if ill in bed, unless they were doing so with parental permission.20 Subsequent research suggests that the HONC is also useful for measuring loss of autonomy over smoking in adults.21,22
The HONC asks 10 questions shown in Table 6.12.3 to assess degree of tobacco dependence.
Research on the HONC in young people has found that dependence may develop rapidly, even at low, sporadic levels of consumption.20 Some of these findings are discussed in Section 6.13.
There is no single ‘ideal’ measure of tobacco dependence. Dependence is a hypothetical construct, and different dependence measures define and operationalise the construct differently. The choice of measure should be guided by its reliability and validity, its suitability for the target population and the purpose of assessment, including whether the aim is to predict outcomes (e.g. cessation), assess severity, or explore underlying mechanisms.23 For example, the Fagerström Test for Nicotine Dependence and Heaviness of Smoking Index are commonly used in population research and clinical settings because they are brief, efficient, and demonstrate strong predictive validity of dependence-related outcomes, such as short- and long-term smoking abstinence.15,18,23 In contrast, the DSM criteria for tobacco use disorder have good face validity as they index clinically meaningful features of dependence and have demonstrated associations with smoking heaviness, smoking-related health and mental health risks, and cessation outcomes, However, they are also more time-consuming to administer and typically require structured clinical interviews, making them better suited to clinical or diagnostic contexts.15,23 Measures such as the Nicotine Dependence Syndrome Scale and the Wisconsin Inventory of Smoking Dependence Motives assess multiple dimensions of dependence and may be better suited for exploring the underlying mechanisms and differences in nicotine dependence.23
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References
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17. Heaviness of Smoking Index (HSI), in Substance Use Screening & Assessment Instruments2025, Addictions, Drug & Alcohol Institute, University of Washington: Seattle. Available from: http://bit.ly/HSI_inst.
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21. DiFranza JR, Savageau JA, Rigotti NA, Fletcher K, Ockene JK, et al. Development of symptoms of tobacco dependence in youths: 30 month follow up data from the DANDY study. Tobacco Control, 2002; 11(3):228–35. Available from: http://tc.bmjjournals.com/cgi/content/abstract/11/3/228
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