RESUMEN
Delineating the characteristics of substance-dependent inpatients who are interested in receiving smoking treatment is critical to developing effective recruitment strategies and interventions for this population. Thus, this study comprehensively assessed and compared substance-dependent inpatients who accepted (n = 75) versus refused (n = 25) a stop-smoking treatment. Univariate analyses found treatment acceptors were younger, more addicted to nicotine, had more smoking-related health problems, had more positive attitudes about quitting smoking, and had more positive attitudes about the relationship between smoking cessation and drug/alcohol sobriety (e.g., believed cessation would positively impact sobriety). Logistic regression revealed that believing inpatient treatment was the best time to quit smoking was the primary factor associated with accepting treatment. Aside from their attitudes about the relationship between smoking cessation and sobriety, substance abusers who accepted smoking treatment appeared similar (e.g., in demographics, smoking behaviors) to nonabusers described in previous studies.
Asunto(s)
Aceptación de la Atención de Salud , Cese del Hábito de Fumar , Trastornos Relacionados con Sustancias/rehabilitación , Adulto , Alcoholismo/psicología , Alcoholismo/rehabilitación , Terapia Combinada , Conocimientos, Actitudes y Práctica en Salud , Personas con Mala Vivienda/psicología , Humanos , Masculino , Persona de Mediana Edad , Admisión del Paciente , Cese del Hábito de Fumar/psicología , Centros de Tratamiento de Abuso de Sustancias , Trastornos Relacionados con Sustancias/psicología , Veteranos/psicologíaRESUMEN
This report describes a computer-directed cigarette smoking cessation program that individualizes nicotine fading schedules for smokers based upon their daily smoking behavior. Previous outcome data from minimal intervention and intensive stop-smoking treatment studies are presented. Preliminary urinary cotinine data also are presented to validate the program's underlying assumption that computer-directed nicotine fading results in across-treatment reductions in biological levels of nicotine.