Literature DB >> 32484870

Which Method of Assessing Depression and Anxiety Best Predicts Smoking Cessation: Screening Instruments or Self-Reported Conditions?

Noreen L Watson1, Jaimee L Heffner1, Kristin E Mull1, Jennifer B McClure2, Jonathan B Bricker1,3.   

Abstract

INTRODUCTION: Affective disorders and symptoms (ADS) are predictive of lower odds of quitting smoking. However, it is unknown which approach to assessing ADS best predicts cessation. This study compared a battery of ADS screening instruments with a single, self-report question on predicting cessation. Among those who self-reported ADS, we also examined if an additional question regarding whether participants believed the condition(s) might interfere with their ability to quit added predictive utility to the single-item question.
METHODS: Participants (N = 2637) enrolled in a randomized controlled trial of web-based smoking treatments completed a battery of five ADS screening instruments and answered a single-item question about having ADS. Those with a positive self-report on the single-item question were also asked about their interference beliefs. The primary outcome was complete-case, self-reported 30-day point prevalence abstinence at 12 months.
RESULTS: Both assessment approaches significantly predicted cessation. Screening positive for ≥ one ADS in the battery was associated with 23% lower odds of quitting than not screening positive for any (p = .023); those with a positive self-report on the single-item had 39% lower odds of quitting than self-reporting no mental health conditions (p < .001). Area under the receiver operating characteristic curve values for the two assessment approaches were similar (p = .136). Adding the interference belief question to the single-item assessment significantly increased the area under the receiver operating characteristic curve value (p = .042).
CONCLUSIONS: The single-item question assessing ADS had as much predictive validity, and possibly more, than the battery of screening instruments for identifying participants at risk for failing to quit smoking. Adding a question about interference beliefs significantly increased the predictive utility of the single-item question. IMPLICATIONS: This is the first study to demonstrate that a single-item question assessing ADS has at least as much predictive validity, and possibly more, than a battery of validated screening instruments for identifying smokers at highest risk for cessation failure. This study also demonstrates adding a question about interference beliefs significantly adds to the predictive utility of a single, self-report question about mental health conditions. Findings from this study can be used to inform decisions regarding how to assess ADS in the context of tobacco treatment settings.
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Mesh:

Year:  2020        PMID: 32484870      PMCID: PMC7542639          DOI: 10.1093/ntr/ntaa099

Source DB:  PubMed          Journal:  Nicotine Tob Res        ISSN: 1462-2203            Impact factor:   4.244


  41 in total

1.  Biochemical verification of tobacco use and cessation.

Authors: 
Journal:  Nicotine Tob Res       Date:  2002-05       Impact factor: 4.244

2.  Mini-SPIN: A brief screening assessment for generalized social anxiety disorder.

Authors:  K M Connor; K A Kobak; L E Churchill; D Katzelnick; J R Davidson
Journal:  Depress Anxiety       Date:  2001       Impact factor: 6.505

3.  Feasibility and Early Outcomes of a Tailored Quitline Protocol for Smokers With Mental Health Conditions.

Authors:  Kelly M Carpenter; Chelsea M Nash; Robert A Vargas-Belcher; Katrina A Vickerman; Vincent Haufle
Journal:  Nicotine Tob Res       Date:  2019-04-17       Impact factor: 4.244

4.  Smoking cessation behaviors among persons with psychiatric diagnoses: results from a population-level state survey.

Authors:  Chad D Morris; Emily K Burns; Jeanette A Waxmonsky; Arnold H Levinson
Journal:  Drug Alcohol Depend       Date:  2013-12-27       Impact factor: 4.492

5.  A comparison of the content-, construct- and predictive validity of the cigarette dependence scale and the Fagerström test for nicotine dependence.

Authors:  Jean-François Etter
Journal:  Drug Alcohol Depend       Date:  2005-03-07       Impact factor: 4.492

6.  A brief measure for assessing generalized anxiety disorder: the GAD-7.

Authors:  Robert L Spitzer; Kurt Kroenke; Janet B W Williams; Bernd Löwe
Journal:  Arch Intern Med       Date:  2006-05-22

7.  Patterns of tobacco-related mortality among individuals diagnosed with schizophrenia, bipolar disorder, or depression.

Authors:  Russell C Callaghan; Scott Veldhuizen; Trincy Jeysingh; Chloe Orlan; Candida Graham; Gwen Kakouris; Gary Remington; Jodi Gatley
Journal:  J Psychiatr Res       Date:  2013-09-27       Impact factor: 4.791

8.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.

Authors:  Xavier Robin; Natacha Turck; Alexandre Hainard; Natalia Tiberti; Frédérique Lisacek; Jean-Charles Sanchez; Markus Müller
Journal:  BMC Bioinformatics       Date:  2011-03-17       Impact factor: 3.307

9.  Do cravings predict smoking cessation in smokers calling a national quit line: secondary analyses from a randomised trial for the utility of 'urges to smoke' measures.

Authors:  Jaspal S Taggar; Sarah Lewis; Graeme Docherty; Linda Bauld; Andy McEwen; Tim Coleman
Journal:  Subst Abuse Treat Prev Policy       Date:  2015-04-14

Review 10.  Smoking, Mental Illness, and Public Health.

Authors:  Judith J Prochaska; Smita Das; Kelly C Young-Wolff
Journal:  Annu Rev Public Health       Date:  2016-12-16       Impact factor: 21.981

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