An algorithm of smoking stages assessment in adolescents: a validation study using the latent class analysis model

Area of Science:

• Adolescent Health
• Behavioral Science
• Psychometrics

Background:

• Accurate measurement of adolescent smoking stages is crucial but lacks appropriate instruments.
• Existing methods are insufficient for evaluating the nuances of smoking progression in youth.

Purpose of the Study:

• To develop and validate a novel algorithm for measuring adolescent smoking stages.
• To assess the algorithm's reliability and validity using established statistical methods.

Main Methods:

• Algorithm development followed by expert and lay expert review for clarity and relevance.
• Reliability was assessed using a test-retest method.
• Latent Class Analysis (LCA) was employed to validate the measured smoking stages in a large adolescent sample.

Main Results:

• The algorithm demonstrated high content validity with excellent relevancy and clarity.
• High reliability was confirmed with an intra-class correlation of 0.929 for the 9-stage smoking model.
• Latent Class Analysis (LCA) supported the validity of the algorithm, revealing nine interpretable classes for smoking stages.

Conclusions:

• The developed algorithm is a clear, valid, and reliable instrument for measuring adolescent smoking stages.
• This tool can aid in better understanding and intervening in adolescent smoking behaviors.