4.2 Article

SmoCuDa: A Validated Smoking Cue Database to Reliably Induce Craving in Tobacco Use Disorder

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EUROPEAN ADDICTION RESEARCH
卷 27, 期 2, 页码 107-114

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KARGER
DOI: 10.1159/000509758

关键词

Addiction; Cue exposure; Database; Nicotine; Smoking; Tobacco

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This study generated and validated a large set of individually rated smoking-related cues that allow for assessment of different stimulus intensities along the dimensions craving, valence, and arousal. Through volunteer ratings, these cues showed a wide distribution of urge to smoke, valence, and arousal.
Background: Cue-reactivity paradigms provide valuable insights into the underlying mechanisms of nicotine craving in nicotine-dependent subjects. In order to study cue-driven nicotine craving, robust and validated stimulus datasets are essential. Objectives: The aim of this study was to generate and validate a large set of individually rated smoking-related cues that allow for assessment of different stimulus intensities along the dimensions craving, valence, and arousal. Methods: The image database consisted of 330 visual cues. Two hundred fifty smoking-associated pictures (Creative Commons license) were chosen from online databases and showed a widespread variety of smoking-associated content. Eighty pictures from previously published databases were included for cross-validation. Forty volunteers with tobacco use disorder rated urge-to-smoke, valence, and arousal for all images on a 100-point visual analogue scale. Pictures were also labelled according to 18 categories such as lit/unlit cigarettes in mouth, cigarette end, and cigarette in ashtray. Results: Ratings (mean +/- SD) were as follows: urge to smoke, 44.9 +/- 13.2; valence, 51.2 +/- 7.6; and arousal, 54.6 +/- 7.1. All ratings, particularly urge to smoke, were widely distributed along the whole scale spectrum. Conclusions: We present a novel image library of well-described smoking-related cues, which were rated on a continuous scale along the dimensions craving, valence, and arousal that accounts for inter-individual differences. The rating software, image database, and their ratings are publicly available at https://smocuda.github.io.

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