Cited by 8Smoking Behavior and CessationSubstance Abuse Treatment and OutcomesBehavioral Health and Interventions

Identifying attendance patterns in a smoking cessation treatment and their relationships with quit success

Open access
Jacquart, Jolene, Papini, Santiago, Davis, Michelle L., Rosenfield, David, Powers, Mark B., Frierson, Georita M., Hopkins, Lindsey B., Baird, Scarlett O. +5 more·2017·Drug and Alcohol Dependence

Abstract

Background While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited. We examined the association between attendance patterns and smoking outcomes in a randomized, controlled smoking cessation intervention trial. Methods In addition to standard smoking cessation treatment, participants were randomized to 15 weeks of an exercise intervention (n = 72) or an education control condition (n = 64). Latent class growth analysis (LCGA) tested whether intervention attendance would be better modeled as qualitatively distinct attendance patterns rather than as a single mean pattern. Multivariate generalized linear mixed modeling (GLMM) was used to evaluate associations between the attendance patterns and abstinence at the end of treatment and at 6-month follow-up. Results The LCGA solution with three patterns characterized by high probability of attendance throughout (Completers, 46.3%), gradual decreasing probability of attendance (Titrators, 23.5%), and high probability of dropout within the first few weeks (Droppers, 30.1%) provided the best fit. The GLMM analysis indicated an interaction of attendance pattern by treatment condition, such that titration was associated with lower probability of quit success for those in the control condition. Probability of quit success was not significantly different between Titrators and Completers in the exercise condition. Conclusions These findings underscore the importance of examining how treatment efficacy may vary as a function of attendance patterns. Importantly, treatment discontinuation is not necessarily indicative of poorer abstinence outcome. © 2017 Elsevier B.V.

Integrity signals

Registry

Crossref · 10.1016/j.drugalcdep.2017.01.007

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

13 of 19 cited sources checked · 8 supported · 0 flagged · accuracy not yet measured

  • Interpretationcitation

    Exercise may influence smoking relapse risk factors within only a few early sessions, given evidence of rapid exercise benefits on anxiety, mood, and anxiety sensitivity.

    “Given evidence of rapid benefits from exercise on anxiety, mood, and anxiety sensitivity in other studies (Medina et al., 2014; Smits et al., 2008), exercise may exert its influence on risk factors for smoking relapse in only a few sessions early on in treatment.”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites Medina et al., 2014 source

      The Results (section 2.2) and Discussion (section 3) report an early reduction in anxiety sensitivity during the first week of exercise, particularly among men. The paper also describes improvements in anxiety and depressive symptoms following a brief exercise intervention, but does not establish that those symptoms improved within the first few sessions. The suggestion about smoking-relapse risk factors is the citing authors’ inference, not a finding attributed to this source. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites Smits et al., 2008 source
      Experimental — accuracy not yet measured
  • Premisecitation

    Early abstinence success within the first 24 hours after quit predicts continued abstinence.

    “Since success with abstinence within the first 24 hours after quit is predictive of continued abstinence (Perkins, 2014)”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Perkins, 2014 source

      Section 3.1 (page not provided) proposes complete abstinence for at least 24 hours as a likely surrogate measure and reports that quit days during the first week predict later quit status. It does not establish that success specifically within the first 24 hours predicts continued abstinence. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • Findingown data

    In the control condition, Completers had a higher probability of post-treatment abstinence than Titrators (β=1.006, 95% CI [0.683, 1.329], t(3047)=6.102, p<.001).

    “Completers in the control condition were more likely to be abstinent than Titrators, β=1.006, 95% CI [0.683, 1.329], t(3047)=6.102, p < .001.”
    Quote in the paperSubstantial claim
  • Findingown data

    The latent class growth analysis identified a Dropper pattern, with 41 participants (31.1%) who had a high probability of dropping out within the first few weeks.

    “Droppers (n=41, 31.1%) had a high probability of dropout within the first few weeks of treatment”
    Quote in the paperSubstantial claim
  • Findingown data

    The final generalized linear mixed model found a significant interaction between attendance pattern and treatment condition for abstinence (β=0.758, 95% CI [−0.293, 1.223], t(3047)=3.195, p=.001).

    “The final model yielded a significant attendance pattern by treatment interaction, β=0.758, 95% CI [−0.293, 1.223], t(3047)=3.195, p=.001”
    Quote in the paperSubstantial claim
  • May combine two claims. 13
  • Classified as probably not a substantial claim. 9
  • May combine two claims.

    Interpretationcitation

    Because early abstinence success predicts continued abstinence, Titrators who remained engaged in the exercise intervention through quit week may have benefited comparably to Completers despite lower overall attendance.

    “Since success with abstinence within the first 24 hours after quit is predictive of continued abstinence (Perkins, 2014), Titrators who were likely to remain engaged in the exercise intervention through quit week may have benefited comparably to Completers despite lower overall attendance.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Perkins, 2014 source

      Section 3.1 (page not specified) reports that the number of quit days in the first week predicts later quit status and proposes at least 24 hours of abstinence as a likely surrogate measure of drug efficacy. It does not specifically establish that abstinence within the first 24 hours predicts continued abstinence. The exercise-intervention comparison is the citing authors’ inference, not a claim attributed to Perkins. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • May combine two claims.

    Premisecitation

    The parent trial's core outcome analysis showed that high-AS participants randomized to exercise were more likely to remain abstinent after quit day, and session attendance had an overall positive association with abstinence.

    “The core outcome analysis showed that participants high in AS randomized to exercise were more likely to remain abstinent following quit day and session attendance showed an overall positive association with abstinence (Smits et al., 2016).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smits et al., 2016 source
  • May combine two claims.

    Interpretationown data

    The findings expand on the main outcome paper by showing that the relation between attendance patterns and treatment success may be non-linear and may depend on the type of intervention.

    “The findings reported here expand on those reported in the main outcome paper (Smits et al., 2016) by showing that the relation between attendance patterns and treatment success may not be linear and, importantly, may depend on the type of intervention.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smits et al., 2016 source
  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    In another treatment trial for comorbid PTSD and SUD, a person-centered analysis derived early dropout, titration, and completion patterns, and treatment titration was not associated with poorer outcomes relative to completion.

    “Another treatment trial for comorbid PTSD and SUD used a person-centered approach to empirically derive distinct attendance patterns of early dropout, titration, and completion—importantly; treatment titration was not associated with poorer outcomes relative to completion (Hien et al., 2012).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Hien et al., 2012 source
  • May combine two claims.

    Premisecitation

    In some cases, greater session attendance or treatment completion has been positively associated with outcomes, but this association is not ubiquitous, suggesting individual differences in dose-response.

    “In some cases, a greater number of sessions attended or treatment completion have shown positive associations with outcomes (Baker et al., 2006; Fiore, 2008; Smits et al., 2016; Whiteley et al., 2012), but this is not ubiquitous, suggesting individual differences in dose-response exist (Baldwin et al., 2009; Barkham et al., 2006; Owen et al., 2016; Reese et al., 2011).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Baker et al., 2006 source
    • cites Fiore, 2008

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Smits et al., 2016 source
  • May combine two claims.

    Interpretationcitation

    Exercise may help smoking cessation by reducing anxiety during acute withdrawal, which may be most pronounced after the initial quit attempt.

    “Exercise may assist smoking cessation by mitigating anxiety during acute withdrawal symptoms (Leventhal and Zvolensky, 2015), which may be most pronounced after the initial quit attempt.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Leventhal and Zvolensky, 2015 source

      The Anxiety Sensitivity section (page unavailable) reports that anxiety-related withdrawal symptoms are more pronounced early in abstinence and discusses anxiety-sensitivity interventions that may aid cessation. It does not say that exercise reduces withdrawal anxiety or helps people quit through that mechanism; its mention of vigorous exercise concerns prevention of smoking initiation, not cessation. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    In a trial of prolonged exposure with naltrexone for comorbid PTSD and alcohol dependence, both fast and slow PTSD symptom improvement and fast drinking improvement were associated with early dropout.

    “in a clinical trial of prolonged exposure with naltrexone for comorbid posttraumatic stress disorder (PTSD) and alcohol dependence, both fast and slow rates of PTSD symptom improvement, as well as fast rates of drinking improvement, were each associated with early dropout (Zandberg et al., 2016).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Zandberg et al., 2016 source

      The Abstract Results and Discussion report higher dropout with both very fast and very slow PTSD improvement among participants with high baseline PTSD severity, and with faster drinking improvement among participants receiving prolonged exposure. The claim omits those conditions and calls the outcome “early dropout,” whereas the reported associations concern dropout during treatment, not specifically early dropout. The Methods also show that prolonged exposure and naltrexone were separate randomized factors, not a treatment everyone received together; page numbers are unavailable in our copy. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Other studies show rapid benefits of exercise on anxiety, mood, and anxiety sensitivity.

    “Given evidence of rapid benefits from exercise on anxiety, mood, and anxiety sensitivity in other studies (Medina et al., 2014; Smits et al., 2008)”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites Medina et al., 2014 source
    • cites Smits et al., 2008 source
  • May combine two claims.

    Findingown data

    During active attendance weeks, 63% of participants attended all three weekly sessions, 25% attended two, and 12% attended one.

    “63% attended all 3 weekly sessions, 25% attended 2 out of the 3 weekly sessions, and 12% attended only one of the 3 weekly sessions.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Findingown data

    A three-class latent class growth analysis solution fit the weekly attendance data better than a single pattern, with the lowest information criteria, entropy of 0.96, and a significant adjusted Lo-Mendel-Rubin likelihood ratio test (p=.01).

    “The 3-class LCGA provided the best fit with lowest information criteria, high entropy (0.96) suggestive of strong delineation of classes, and a significant adjusted Lo-Mendel-Rubin likelihood ratio test, p=.01.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Study design and conductcitation

    The abstinence analyses followed an intent-to-treat approach recommended for smoking cessation trials.

    “Following Smits et al., (2016) two dichotomous measures of smoking behavior (PPA and PA) were examined in a three-phase (i.e., pre-quit, post-quit, post-treatment) generalized linear mixed model (GLMM) following the intent-to-treat approach recommended for smoking cessation trials (Hall et al., 2001).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Hall et al., 2001 source
  • May combine two claims.

    Study design and conductreasoning

    The original study was not designed to compare intervention lengths, so the results reflect participant-determined attendance patterns rather than prescribed treatment dosage.

    “The original study was not designed to compare intervention lengths, thus results reflect participant-determined attendance patterns as opposed to “prescribed” treatment dosage.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Premisecitation

    The Good Enough Level model proposes that optimal treatment dosage varies with individual improvement rates, so patients who improve quickly may self-modulate dosage by discontinuing early.

    “The Good Enough Level (GEL) model posits that optimal treatment dosage varies as a function of individual improvement rates such that patients who improve quickly may self-modulate treatment dosage via early discontinuation (Owen et al., 2016; Reese et al., 2011).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Owen et al., 2016 source
    • cites Reese et al., 2011 source
  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The abstinence analysis was restricted to Completers versus Titrators because Droppers withdrew before quit week.

    “Subsequent analysis of the relation between treatment attendance pattern and abstinence was restricted to the Completer versus Titrator since Droppers withdrew prior to quit week.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationown data

    The present findings show that treatment attendance patterns can be empirically derived and related to efficacy, generating testable hypotheses.

    “Together, the present findings show that treatment attendance patterns can be empirically-derived and related to efficacy, helping to generate testable hypotheses for follow-up studies that aim to refine interventions.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    The higher proportion of Droppers in the exercise condition may indicate that the exercise intervention was more aversive or challenging to adhere to.

    “The disproportionate number of Droppers in the exercise condition may indicate that the exercise intervention was more aversive or challenging to adhere to.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim.

    Study design and conductcitation

    If biological verification was unavailable, abstinence was treated as missing data.

    “If biological verification was not available to verify self-report, abstinence was considered missing data (Blankers et al., 2016).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Blankers et al., 2016

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    Self-reported smoking status was verified by expired carbon monoxide at weekly visits and saliva cotinine at follow-up.

    “Self-reported smoking status was verified by expired carbon monoxide at weekly visits, and with saliva cotinine at follow-up (SRNT Subcommittee on Biochemical Verification, 2002).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites SRNT Subcommittee on Biochemical Verification, 2002 source
18 of 18
  • The paper relies on this without support.

    Knowledge about treatment attendance patterns and their relation to clinical outcomes is limited.

    “While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited.”
1 of 1

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Consistentχ²(2) = 7.46reported p = .02 · recomputed p = .024

    “χ2(2)=7.46, p = .02”

  • Consistentt(3047) = 3.195reported p = .001 · recomputed p = .001

    “t(3047)=3.195, p = .001”

  • Consistentt(3047) = 1.455reported p = .146 · recomputed p = .146

    “t(3047)=1.455, p = .146”

  • Consistentt(3047) = 6.102reported p < .001 · recomputed p < .001

    “t(3047)=6.102, p < .001”

  • Consistentt(3047) = 1.054reported p = .292 · recomputed p = .292

    “t(3047)=1.054, p = .292”

  • Consistentt(3047) = 3.127reported p = .002 · recomputed p = .002

    “t(3047)=3.127, p = .002”

6 of 6

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Interaction confidence interval conflicts with its p-value

    Major

    The reported 95% confidence interval for the attendance-by-treatment interaction includes zero, whereas the reported p=.001 indicates a statistically significant interaction. These results conflict for the same coefficient.

  • Attendance pattern percentages do not match stated counts

    Minor

    The reported percentages for the three attendance classes are slightly inconsistent with the class counts out of the total sample of 136. Using the counts 63, 32, and 41 gives 46.32%, 23.53%, and 30.15%, so the last class is closer to 30.1% than 31.1%.

    Reported 31.1 · recomputed 30.147059

  • Dropper percentage does not match the class count

    Minor

    The reported 41 Droppers out of 136 participants represent 30.1%, not 31.1%. The abstract gives the matching percentage of 30.1%.

    Reported 31.1 · recomputed 30.147059

3 of 3

Cites

Flagged first, then by citations

3 of the 37 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Jacquart, J., Papini, S., Davis, M. L., Rosenfield, D., Powers, M. B., Frierson, G. M., Hopkins, L. B., Baird, S. O., Marcus, B. H., Church, T. S., Otto, M. W., Zvolensky, M. J., & Smits, J. A. J.
Affiliations
  • The University of Texas at Austin (US)
  • Southern Methodist University (US)
  • Baylor University Medical Center (US)
  • Rowan University (US)
  • VA Palo Alto Health Care System (US)
  • University of California San Diego (US)
  • Pennington Biomedical Research Center (US)
  • Boston University (US)
  • The University of Texas MD Anderson Cancer Center (US)
Corresponding author
Jacquart, Jolene
Venue
Drug and Alcohol Dependence
Publisher
Elsevier BV
Published
2017-05
Volume
174
Pages
65-69
ISSN
0376-8716 (ISSN-L)
OpenAlex
W2593105591
Cited by
8
References
37
Citations by year
2023: 1 · 2021: 2 · 2020: 2 · 2019: 3
FWCI
1.01
Type
journal article
Language
en
Open access
Locations
  • Drug and Alcohol Dependence (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
Funders
  • National Institutes of Health (5r01da027533-04)
  • National Institute on Drug Abuse (R01-DA027533)
Topics
  • Health Sciences › Medicine › Physiology › Smoking Behavior and Cessation
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
  • Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
Keywords
smoking cessation, treatment discontinuation, abstinence, exercise intervention, treatment completion, latent class growth analysis
MeSH terms
Adult, Exercise Therapy, Female, Humans, Male, Middle Aged, Patient Acceptance of Health Care, Patient Dropouts, Smoking, Smoking Cessation, Treatment Outcome, Substance-Related Disorders

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Claims read under definition version 3 (extract-v3) on 2026-09-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.

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Statistics and arithmetic are recomputed, not judged.

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