Paths to tobacco abstinence: A repeated-measures latent class analysis

Effects of smoking on sleep architecture and ventilatory parameters including apneas: Results of the Tab-OSA study

Background

The interaction between smoking and sleep seems appears to be bidirectional, but few studies evaluated the impact of smoking and its cessation on objective sleep parameters. In this context, this new study aimed to assess the impact of smoking and its cessation on sleep architecture and on ventilatory sleep parameters, particularly the presence of sleep apnea syndrome (apnea-hypopnea index (AHI)≥15). Methods: Patients hospitalized for polysomnographic sleep exploration were compared according to their smoking status: active smokers (AS), former smokers (FS), non-smokers (NoNi). Psychiatric and non-psychiatric co-morbidities and treatment or substance use were taken into account in the analyses.

Results

A total of 170 participants were included (N = 37 FS, 39 AS, 86 NoNi). A significant decrease in the mean nocturnal O2 saturation was observed for FS and AS compared to NoNi. No differences were found regarding AHI. Regarding sleep architecture, we observed a significant decrease in the slow wave sleep duration for AS compared to NoNi, and interestingly not between FS and NoNi.

Conclusion

This study suggests that current smokers suffer from alterations in both sleep architecture and ventilatory parameters, the later appears to persist even after smoking cessation.

Trajectories of depression symptoms in a therapist-supported digital mental health intervention: a repeated measures latent profile analysis

PURPOSE

Major depression affects 10% of the US adult population annually, contributing to significant burden and impairment. Research indicates treatment response is a non-linear process characterized by combinations of gradual changes and abrupt shifts in depression symptoms, although less is known about differential trajectories of depression symptoms in therapist-supported digital mental health interventions (DMHI).

METHODS

Repeated measures latent profile analysis was used to empirically identify differential trajectories based upon biweekly depression scores on the Patient Health Questionnaire-9 (PHQ-9) among patients engaging in a therapist-supported DMHI from January 2020 to July 2021. Multivariate associations between symptom trajectories with sociodemographics and clinical characteristics were examined with multinomial logistic regression. Minimal clinically important differences (MCID) were defined as a five-point change on the PHQ-9 from baseline to week 12.

RESULTS

The final sample included 2192 patients aged 18 to 82 (mean = 39.1). Four distinct trajectories emerged that differed by symptom severity and trajectory of depression symptoms over 12 weeks. All trajectories demonstrated reductions in symptoms. Despite meeting MCID criteria, evidence of treatment resistance was found among the trajectory with the highest symptom severity. Chronicity of major depressive episodes and lifetime trauma exposures were ubiquitous across the trajectories in a multinomial logistic regression model.

CONCLUSIONS

These data indicate that changes in depression symptoms during DMHI are heterogenous and non-linear, suggesting a need for precision care strategies to address treatment resistance and increase engagement. Future efforts should examine the effectiveness of trauma-informed treatment modules for DMHIs as well as protocols for continuation treatment and relapse prevention.

Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation

BACKGROUND

Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes. This helps to reduce cravings and withdrawal symptoms, and ease the transition from cigarette smoking to complete abstinence. Although there is high-certainty evidence that NRT is effective for achieving long-term smoking abstinence, it is unclear whether different forms, doses, durations of treatment or timing of use impacts its effects.

OBJECTIVES

To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register for papers mentioning NRT in the title, abstract or keywords, most recently in April 2022.

SELECTION CRITERIA

We included randomised trials in people motivated to quit, comparing one type of NRT use with another. We excluded studies that did not assess cessation as an outcome, with follow-up of fewer than six months, and with additional intervention components not matched between arms. Separate reviews cover studies comparing NRT to control, or to other pharmacotherapies.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. We measured smoking abstinence after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs) and study withdrawals due to treatment.  MAIN RESULTS: We identified 68 completed studies with 43,327 participants, five of which are new to this update. Most completed studies recruited adults either from the community or from healthcare clinics. We judged 28 of the 68 studies to be at high risk of bias. Restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results for any comparisons apart from the preloading comparison, which tested the effect of using NRT prior to quit day whilst still smoking.  There is high-certainty evidence that combination NRT (fast-acting form plus patch) results in higher long-term quit rates than single form (risk ratio (RR) 1.27, 95% confidence interval (CI) 1.17 to 1.37; I2 = 12%; 16 studies, 12,169 participants). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg patches are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29; I2 = 38%; 5 studies, 1655 participants), and that 21 mg patches are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08; 1 study, 537 participants). Moderate-certainty evidence, again limited by imprecision, also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41; I2 = 0%; 3 studies, 3446 participants). Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward. There was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44; I2 = 0%; 9 studies, 4395 participants). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05; I2 = 0%; 8 studies, 3319 participants). We found no clear evidence of an effect of duration of nicotine patch use (low-certainty evidence); duration of combination NRT use (low- and very low-certainty evidence); or fast-acting NRT type (very low-certainty evidence). Cardiac AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low- or very low-certainty evidence for all comparisons. Most comparisons found no clear evidence of an effect on these outcomes, and rates were low overall. More withdrawals due to treatment were reported in people using nasal spray compared to patches in one study (RR 3.47, 95% CI 1.15 to 10.46; 1 study, 922 participants; very low-certainty evidence) and in people using 42/44 mg patches in comparison to 21/22 mg patches across two studies (RR 4.99, 95% CI 1.60 to 15.50; I2 = 0%; 2 studies, 544 participants; low-certainty evidence).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that using combination NRT versus single-form NRT and 4 mg versus 2 mg nicotine gum can result in an increase in the chances of successfully stopping smoking. Due to imprecision, evidence was of moderate certainty for patch dose comparisons. There is some indication that the lower-dose nicotine patches and gum may be less effective than higher-dose products. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT before quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is limited. New studies should ensure that AEs, SAEs and withdrawals due to treatment are reported.

Antidepressants for smoking cessation

BACKGROUND

The pharmacological profiles and mechanisms of antidepressants are varied. However, there are common reasons why they might help people to stop smoking tobacco: nicotine withdrawal can produce short-term low mood that antidepressants may relieve; and some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, harms, and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, most recently on 29 April 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in people who smoked, comparing antidepressant medications with placebo or no pharmacological treatment, an alternative pharmacotherapy, or the same medication used differently. We excluded trials with fewer than six months of follow-up from efficacy analyses. We included trials with any follow-up length for our analyses of harms.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. Our primary outcome measure was smoking cessation after at least six months' follow-up. We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Our secondary outcomes were harms and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropouts due to treatment. We carried out meta-analyses where appropriate.

MAIN RESULTS

We included a total of 124 studies (48,832 participants) in this review, with 10 new studies added to this update version. Most studies recruited adults from the community or from smoking cessation clinics; four studies focused on adolescents (with participants between 12 and 21 years old). We judged 34 studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk of bias did not change clinical interpretation of the results.  There was high-certainty evidence that bupropion increased smoking cessation rates when compared to placebo or no pharmacological treatment (RR 1.60, 95% CI 1.49 to 1.72; I2 = 16%; 50 studies, 18,577 participants). There was moderate-certainty evidence that a combination of bupropion and varenicline may have resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). However, there was insufficient evidence to establish whether a combination of bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.17, 95% CI 0.95 to 1.44; I2 = 43%; 15 studies, 4117 participants; low-certainty evidence). There was moderate-certainty evidence that participants taking bupropion were more likely to report SAEs than those taking placebo or no pharmacological treatment. However, results were imprecise and the CI also encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 23 studies, 10,958 participants). Results were also imprecise when comparing SAEs between people randomised to a combination of bupropion and NRT versus NRT alone (RR 1.52, 95% CI 0.26 to 8.89; I2 = 0%; 4 studies, 657 participants) and randomised to bupropion plus varenicline versus varenicline alone (RR 1.23, 95% CI 0.63 to 2.42; I2 = 0%; 5 studies, 1268 participants). In both cases, we judged evidence to be of low certainty. There was high-certainty evidence that bupropion resulted in more trial dropouts due to AEs than placebo or no pharmacological treatment (RR 1.44, 95% CI 1.27 to 1.65; I2 = 2%; 25 studies, 12,346 participants). However, there was insufficient evidence that bupropion combined with NRT versus NRT alone (RR 1.67, 95% CI 0.95 to 2.92; I2 = 0%; 3 studies, 737 participants) or bupropion combined with varenicline versus varenicline alone (RR 0.80, 95% CI 0.45 to 1.45; I2 = 0%; 4 studies, 1230 participants) had an impact on the number of dropouts due to treatment. In both cases, imprecision was substantial (we judged the evidence to be of low certainty for both comparisons). Bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.73, 95% CI 0.67 to 0.80; I2 = 0%; 9 studies, 7564 participants), and to combination NRT (RR 0.74, 95% CI 0.55 to 0.98; I2 = 0%; 2 studies; 720 participants). However, there was no clear evidence of a difference in efficacy between bupropion and single-form NRT (RR 1.03, 95% CI 0.93 to 1.13; I2 = 0%; 10 studies, 7613 participants). We also found evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), and some evidence that bupropion resulted in superior quit rates to nortriptyline (RR 1.30, 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants), although this result was subject to imprecision. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion may increase SAEs (moderate-certainty evidence when compared to placebo/no pharmacological treatment). There is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with people receiving placebo or no pharmacological treatment. Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo, although bupropion may be more effective. Evidence also suggests that bupropion may be as successful as single-form NRT in helping people to quit smoking, but less effective than combination NRT and varenicline. In most cases, a paucity of data made it difficult to draw conclusions regarding harms and tolerability. Further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over other licensed smoking cessation treatments; namely, NRT and varenicline. However, it is important that future studies of antidepressants for smoking cessation measure and report on harms and tolerability.

Tobacco quitline performance: Comparing the impacts of early cessation and proactive re-engagement on callers' smoking status at follow-up at 12 months

INTRODUCTION

While tobacco Quitlines are effective in the promotion of smoking cessation, the majority of callers who wish to quit still fail to do so. The aim of this study was to determine if 12-month tobacco Quitline smoking cessation rates could be improved with re-engagement of callers whose first Quitline treatment failed to establish abstinence.

METHODS

In an adaptive trial, 614 adult smokers, who were active duty, retired, and family of military personnel with TRICARE insurance who called a tobacco Quitline, received a previously evaluated and efficacious four-session tobacco cessation intervention with nicotine replacement therapy (NRT). At the scheduled follow-up at 3 months, callers who had not yet achieved abstinence were offered the opportunity to re-engage. This resulted in three caller groups: 1) those who were abstinent, 2) those who were still smoking but willing to re-engage with an additional Quitline treatment; and 3) individuals who were still smoking but declined re-engagement. A propensity score-adjusted logistic regression model was generated to compare past-7-day point prevalence abstinence at 12 months post Quitline consultation.

RESULTS

Using a propensity score adjusted logistic regression model, comparison of the three groups resulted in higher odds of past-7-day point prevalence abstinence at follow-up at 12 months for those who were abstinent at 3 months compared to those who re-engaged (OR=9.6; 95% CI: 5.2-17.8; Bonferroni adjusted p<0.0001), and relative to those who declined re-engagement (OR=13.4; 95% CI: 6.8-26.3; Bonferroni adjusted p<0.0001). There was no statistically significant difference in smoking abstinence between smokers at 3 months who re-engaged and those who declined re-engagement (OR=1.39; 95% CI: 0.68-2.85).

CONCLUSIONS

Tobacco Quitlines seeking to select a single initiative by which to maximize abstinence at follow-up at 12 months may benefit from diverting additional resources from the re-engagement of callers whose initial quit attempt failed, toward changes which increase callers' probability of success within the first 3 months of treatment.

TRIAL REGISTRATION

This study is registered at clinicaltrials.gov (NCT02201810).

Latent Class Mediation: A Comparison of Six Approaches

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

Antidepressants for smoking cessation

BACKGROUND

Whilst the pharmacological profiles and mechanisms of antidepressants are varied, there are common reasons why they might help people to stop smoking tobacco. Firstly, nicotine withdrawal may produce depressive symptoms and antidepressants may relieve these. Additionally, some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, safety and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Specialized Register, which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO, clinicaltrials.gov, the ICTRP, and other reviews and meeting abstracts, in May 2019.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) that recruited smokers, and compared antidepressant medications with placebo or no treatment, an alternative pharmacotherapy, or the same medication used in a different way. We excluded trials with less than six months follow-up from efficacy analyses. We included trials with any follow-up length in safety analyses.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. We also used GRADE to assess the certainty of the evidence. The primary outcome measure was smoking cessation after at least six months follow-up, expressed as a risk ratio (RR) and 95% confidence intervals (CIs). We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Where appropriate, we performed meta-analysis using a fixed-effect model. Similarly, we presented incidence of safety and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropout due to drug, as RRs (95% CIs).

MAIN RESULTS

We included 115 studies (33 new to this update) in this review; most recruited adult participants from the community or from smoking cessation clinics. We judged 28 of the studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk did not change clinical interpretation of the results. There was high-certainty evidence that bupropion increased long-term smoking cessation rates (RR 1.64, 95% CI 1.52 to 1.77; I² = 15%; 45 studies, 17,866 participants). There was insufficient evidence to establish whether participants taking bupropion were more likely to report SAEs compared to those taking placebo. Results were imprecise and CIs encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I² = 0%; 21 studies, 10,625 participants; moderate-certainty evidence, downgraded one level due to imprecision). We found high-certainty evidence that use of bupropion resulted in more trial dropouts due to adverse events of the drug than placebo (RR 1.37, 95% CI 1.21 to 1.56; I² = 19%; 25 studies, 12,340 participants). Participants randomized to bupropion were also more likely to report psychiatric AEs compared with those randomized to placebo (RR 1.25, 95% CI 1.15 to 1.37; I² = 15%; 6 studies, 4439 participants). We also looked at the safety and efficacy of bupropion when combined with other non-antidepressant smoking cessation therapies. There was insufficient evidence to establish whether combination bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.19, 95% CI 0.94 to 1.51; I² = 52%; 12 studies, 3487 participants), or whether combination bupropion and varenicline resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I² = 15%; 3 studies, 1057 participants). We judged the certainty of evidence to be low and moderate, respectively; in both cases due to imprecision, and also due to inconsistency in the former. Safety data were sparse for these comparisons, making it difficult to draw clear conclusions. A meta-analysis of six studies provided evidence that bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.71, 95% CI 0.64 to 0.79; I² = 0%; 6 studies, 6286 participants), whilst there was no evidence of a difference in efficacy between bupropion and NRT (RR 0.99, 95% CI 0.91 to 1.09; I² = 18%; 10 studies, 8230 participants). We also found some evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I² = 16%; 6 studies, 975 participants), whilst there was insufficient evidence to determine whether bupropion or nortriptyline were more effective when compared with one another (RR 1.30 (favouring bupropion), 95% CI 0.93 to 1.82; I² = 0%; 3 studies, 417 participants). There was no evidence that any of the other antidepressants tested (including St John's Wort, selective serotonin reuptake inhibitors (SSRIs), monoamine oxidase inhibitors (MAOIs)) had a beneficial effect on smoking cessation. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion also increases the number of adverse events, including psychiatric AEs, and there is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with placebo. However, there is no clear evidence to suggest whether people taking bupropion experience more or fewer SAEs than those taking placebo (moderate certainty). Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo. Evidence suggests that bupropion may be as successful as NRT and nortriptyline in helping people to quit smoking, but that it is less effective than varenicline. There is insufficient evidence to determine whether the other antidepressants tested, such as SSRIs, aid smoking cessation, and when looking at safety and tolerance outcomes, in most cases, paucity of data made it difficult to draw conclusions. Due to the high-certainty evidence, further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over front-line smoking cessation aids already available. However, it is important that where studies of antidepressants for smoking cessation are carried out they measure and report safety and tolerability clearly.

Effects of smoking cessation treatment attendance on abstinence: The moderating role of psychologically based behavioral health conditions

Available smoking cessation treatments have shown only modest quit success. Presence of a psychologically based behavioral health condition (PBHC), such as depression, anxiety, or addiction, can impact smoking cessation treatment engagement and quit success; however, the differential effect of treatment engagement on smoking cessation outcomes across smokers with and without a PBHC is unknown. The current study examined the moderating effect presence (versus absence) of a PBHC on the relation between treatment attendance and early smoking abstinence following a 4-session smoking cessation treatment. Participants included 529 (45.9% male; Mage = 38.23 years, SD = 13.56; 75.4% White) smokers enrolled in a large randomized controlled trial evaluating the efficacy of a transdiagnostic smoking cessation treatment. A repeated-measures latent class analysis (RMLCA) was conducted to examine treatment attendance. The effects of treatment attendance, PBHC (present/absent), and their interaction were modeled on biochemically-verified point prevalence abstinence using a latent growth curve from 1-week to 1-month post-quit. The RMLCA provided evidence for three classes: Drop-outs (n = 197), Titrators (n = 89), and Completers (n = 243). A significant interaction emerged such that Completers without a PBHC were significantly more likely to be abstinent relative to Completers with a PBHC (b = 2.69, SE = 0.67, p < .001) and Titrators without a PBHC (b = 3.36, SE = 0.80, p < .001). These results provide novel data that implicate the clinical importance of treatment attendance and PBHC status on smoking abstinence.

Trait self-control predicts drinking patterns during treatment for alcohol use disorder and recovery up to three years following treatment

To more fully understand recovery from alcohol use disorder, we must consider several ways in which reductions in drinking and improvements in psychosocial functioning may occur. Previous research has demonstrated various patterns of drinking and functioning during and after behavioral treatment for alcohol use disorder, including groups of individuals who consume alcohol at low-risk levels and those that report occasional heavy drinking yet good psychosocial functioning. This study aimed to identify whether trait self-control, which has previously been associated with alcohol treatment outcomes, was a predictor of drinking patterns during treatment as well as three years following treatment. Latent variable mixture modeling was used to identify seven classes of drinking patterns during treatment and four profiles of drinking and psychosocial function after treatment. We found that membership in the low-risk drinking class was predicted by greater trait self-control than several of the other classes, including the consistent abstinence class. Furthermore, we found that greater trait self-control predicted membership in two high-functioning recovery profiles at three years following treatment, including a high functioning occasional heavy drinking profile. These findings suggest that self-control is an important predictor of recovery, particularly for a non-abstinent recovery.

An exponential effect persistence model for intensive longitudinal data

We develop an effect persistence model for intensive longitudinal data under a general assumption of an exponential loss of association between exposure and outcome over time. The working model proposed may be useful for understanding the complexity of phenomena for which subjects can be repeatedly exposed to an intervention or a naturally occurring event, while, the effect of any one exposure is expected to diminish over time. Under the main assumption, we specify a semilinear model with extensions to generalized linear models. These methods are motivated by, and applied to, data from a study of adolescent exposure to prosmoking advertisement in which the impact of prosmoking media exposure on young adults' susceptibility to smoking is assessed along with the decay of the effect over time. We investigate the performance of the proposed method when the model assumptions are correctly specified or not. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A bidirectional path analysis model of smoking cessation self-efficacy and concurrent smoking status: impact on abstinence outcomes

Self-efficacy is routinely associated with abstinence in the addictions literature, and is a major component relapse-prevention models. The magnitude of this relationship has been brought into question following equivocal results in studies controlling for concurrent smoking status. The aim of our study was to clarify the relationship between cessation self-efficacy, smoking status, and cessation outcomes in a cohort of treatment-seeking smokers. Smokers participating in the FLEX trial, a randomized trial investigating the efficacy of three pharmacologic treatments for smoking cessation, completed questionnaires assessing cessation self-efficacy at baseline and at weeks 1, 3, 5 and 10 post-target quit date; smoking status was verified using expired carbon monoxide. Structural models were fit in order to ascertain the relationship between cessation self-efficacy and concurrent smoking at each time-point, and to assess the association between cessation self-efficacy, smoking and seven-day point prevalence smoking status at week 10. A total of 737 treatment-seeking smokers participated. In our path model, self-efficacy and smoking status at all time points were associated with week 10 abstinence (except week 3 self-efficacy), after controlling these values' previous time-points. All direct pathways between cessation self-efficacy and smoking were also significant, supporting a bidirectional relationship. Our results support a bidirectional and reciprocal relationship between cessation self-efficacy and concurrent smoking behavior; participants with higher confidence were more likely to be smoke-free, and concurrent smoking status predicted levels of confidence over the ensuing weeks. Both measures were associated with week 10 abstinence. Our results indicate that while correlated, both cessation self-efficacy and current smoking behavior during a cessation attempt are important independent markers of ultimate cessation success.

Understanding quit patterns from a randomized clinical trial: Latent classes, predictors, and long-term abstinence

OBJECTIVE

Tobacco dependence treatment is recognized as a dynamic, chronic process comprised of several specific phases. Of these phases, the Cessation phase is the most critical as it has demonstrated the strongest relation to quit success. Yet, little is understood about smoking trajectories during this period. The current study aimed to address gaps in the smoking research literature and advance understanding of the dynamic quit process unique to completing an integrated smoking treatment by evaluating quit behavior during the Cessation phase.

METHOD

Two hundred and sixty-seven treatment seeking smokers enrolled in a clinical trial to evaluate the efficacy of a novel, integrated smoking cessation treatment (46.1% male; Mage = 39.25, SD = 13.70) were included in the present study. Repeated-measure latent class analysis was employed to evaluate quit patterns from quit day through day 14 post-quit.

RESULTS

Results supported a four-class solution: Consistent Quitters, Non-Quitters, Relapsers, and Delayed Quitters. Predictors of class membership included age, number of prior quit attempts, motivation to quit smoking, and quit day smoking urges. Moreover, class membership was significantly associated with 6-month abstinence.

CONCLUSION

Results suggest that there are four relevant classes of quit behavior, each with specific predictor variables including age, motivation to quit, smoking urges, and number of quit attempts, and that these classes relate to long-term abstinence. These results have the potential to inform manualized smoking cessation treatment interventions based on relevant subgroups of quit behavior.

Dynamic, data-driven typologies of long-term smoking, cessation, and their correlates: Findings from the International Tobacco Control (ITC) Netherlands Survey

RATIONALE

Efforts towards tobacco control are numerous, but relapse rates for smoking cessations remain high. Behavioral changes necessary for continuous cessation appear complex, variable and subject to social, biological, psychological and environmental determinants. Currently, most cessation studies concentrate on short-to midterm behavioral changes. Besides, they use fixed typologies, thereby failing to capture the temporal changes in smoking/cessation behaviors, and its determinants.

OBJECTIVE

To obtain long-term, data-driven longitudinal patterns or profiles of smoking, cessation, and related determinants in a cohort of adult smokers, and to investigate their dynamic links.

METHODS

The dataset originated from the International Tobacco Control (ITC) Netherlands Project, waves 2008 to 2016. Temporal dynamics of smoking/cessation, psychosocial constructs, and time-varying determinants of smoking were extracted with Group-Based Trajectory Modeling technique. Their associations were investigated via multiple regression models.

RESULTS

Substantial heterogeneity of smoking and cessation behaviors was unveiled. Most respondents were classified as persistent smokers, albeit with distinct levels of consumption. For a minority, cessation could be sustained between 1 and 8 years, while others showed relapsing or fluctuating smoking behavior. Links between smoking/cessation trajectories with those of psychosocial and sociodemographic variables were diverse. Notably, changes in two variables were aligned to behavioral changes towards cessation: decreasing number of smoking peers and attaining a higher self-perceived control.

CONCLUSION

The unveiled heterogeneity of smoking behavior over time and the varied cross-dependencies between smoking data-driven typologies and those of underlying risk factors underscore the need of individually tailored approaches for motivational quitting.

Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation

BACKGROUND

Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes to ease the transition from cigarette smoking to abstinence. It works by reducing the intensity of craving and withdrawal symptoms. Although there is clear evidence that NRT used after smoking cessation is effective, it is unclear whether higher doses, longer durations of treatment, or using NRT before cessation add to its effectiveness.

OBJECTIVES

To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation, compared to one another.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, and trial registries for papers mentioning NRT in the title, abstract or keywords. Date of most recent search: April 2018.

SELECTION CRITERIA

Randomized trials in people motivated to quit, comparing one type of NRT use with another. We excluded trials that did not assess cessation as an outcome, with follow-up less than six months, and with additional intervention components not matched between arms. Trials comparing NRT to control, and trials comparing NRT to other pharmacotherapies, are covered elsewhere.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. Smoking abstinence was measured after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs), and study withdrawals due to treatment. We calculated the risk ratio (RR) and the 95% confidence interval (CI) for each outcome for each study, where possible. We grouped eligible studies according to the type of comparison. We carried out meta-analyses where appropriate, using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

We identified 63 trials with 41,509 participants. Most recruited adults either from the community or from healthcare clinics. People enrolled in the studies typically smoked at least 15 cigarettes a day. We judged 24 of the 63 studies to be at high risk of bias, but restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results, apart from in the case of the preloading comparison. There is high-certainty evidence that combination NRT (fast-acting form + patch) results in higher long-term quit rates than single form (RR 1.25, 95% CI 1.15 to 1.36, 14 studies, 11,356 participants; I² = 4%). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29, 5 studies, 1655 participants; I² = 38%), and that 21 mg are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08, 1 study, 537 participants). Moderate-certainty evidence (again limited by imprecision) also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41, 3 studies, 3446 participants; I² = 0%). Five studies comparing 4 mg gum to 2 mg gum found a benefit of the higher dose (RR 1.43, 95% CI 1.12 to 1.83, 5 studies, 856 participants; I² = 63%); however, results of a subgroup analysis suggest that only smokers who are highly dependent may benefit. Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward; there was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44, 9 studies, 4395 participants; I² = 0%). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05, 8 studies, 3319 participants; I² = 0%). We found no evidence of an effect of duration of nicotine patch use (low-certainty evidence); 16-hour versus 24-hour daily patch use; duration of combination NRT use (low- and very low-certainty evidence); tapering of patch dose versus abrupt patch cessation; fast-acting NRT type (very low-certainty evidence); duration of nicotine gum use; ad lib versus fixed dosing of fast-acting NRT; free versus purchased NRT; length of provision of free NRT; ceasing versus continuing patch use on lapse; and participant- versus clinician-selected NRT. However, in most cases these findings are based on very low- or low-certainty evidence, and are the findings from single studies.AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low- or very low-certainty evidence for all comparisons. Most comparisons found no evidence of an effect on cardiac AEs, SAEs or withdrawals. Rates of these were low overall. Significantly more withdrawals due to treatment were reported in participants using nasal spray in comparison to patch in one trial (RR 3.47, 95% CI 1.15 to 10.46, 922 participants; very low certainty) and in participants using 42/44 mg patches in comparison to 21/22 mg patches across two trials (RR 4.99, 95% CI 1.60 to 15.50, 2 studies, 544 participants; I² = 0%; low certainty).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that using combination NRT versus single-form NRT, and 4 mg versus 2 mg nicotine gum, can increase the chances of successfully stopping smoking. For patch dose comparisons, evidence was of moderate certainty, due to imprecision. Twenty-one mg patches resulted in higher quit rates than 14 mg (24-hour) patches, and using 25 mg patches resulted in higher quit rates than using 15 mg (16-hour) patches, although in the latter case the CI included one. There was no clear evidence of superiority for 42/44 mg over 21/22 mg (24-hour) patches. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT prior to quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is of low and very low certainty. New studies should ensure that AEs, SAEs and withdrawals due to treatment are both measured and reported.

Secondary analysis of an RCT on Emergency Department-Initiated Tobacco Control: Repeatedly assessed point-prevalence abstinence up to 12 months and extension of results through a 10-year follow-up

INTRODUCTION

Emergency departments (EDs) are opportune places for tobacco control interventions. The ‘Tobacco Control in an Urban Emergency Department’ (TED) study, ISRCTN41527831, originally evaluated the effect of motivational interviewing on-site plus up to four booster telephone calls on 12-month abstinence. This study’s aim was to evaluate the effect of the intervention on 7-day point-prevalence abstinence at 10 years follow-up (primary outcome) as well as on repeated point-prevalence abstinence at 1, 3, 6, 12 months and at 10 years (continual smoking abstinence, secondary outcome).

METHODS

At the 10 years follow-up and after informed consent, study participants responded to a mailed questionnaire. The primary outcome was analyzed in observed-only and in all-cases analyses. The secondary outcomes were analyzed using a multiple adjusted GLMM for binary outcomes.

RESULTS

Out of 1012 TED-study participants, 986 (97.4%) were alive and 231 (23.4% of 986) responded to the follow-up at 10 years. For observed-only and all-cases analyses, the effect of the baseline intervention on 7-day point-prevalence abstinence at the 10 years follow-up was statistically non-significant. However, when taking into account all repeated measures, the intervention significantly influenced continual abstinence with odds ratio 1.32 (95% CI: 1.01–1.73; p=0.042). Baseline motivation, perceived self-efficacy to stop smoking, and nicotine dependency were independently associated with long-term continual smoking abstinence (all p<0.05).

CONCLUSIONS

A conventional analysis failed to confirm a significant effect of the ED-initiated tobacco control intervention on the point-prevalence abstinence at 10 years. Results from a more integrative analysis nonetheless indicated an enduring intervention effect on continual abstinence among smokers first encountered in the emergency department setting 10 years earlier.

Is There a Spillover Effect of Targeted Dietary Change on Untargeted Health Behaviors? Evidence From a Dietary Modification Trial

Background. The gateway behavior hypothesis posits that change in a health behavior targeted for modification may promote positive changes in other untargeted health behaviors; however, previous studies have shown inconsistent results. Aims. To examine the patterns and predictors of change in untargeted health behaviors in a large health behavior change trial. Method. Using repeated-measures latent class analysis, this study explored patterns of change in untargeted physical activity, alcohol consumption, and smoking behavior during the first year of the Women's Health Initiative dietary modification trial that targeted total fat reduction to 20% kcal and targeted increased fruit and vegetable intake. Participants were healthy postmenopausal women who were randomly assigned to either the low-fat dietary change intervention (n = 8,193) or a control (n = 12,187) arm. Results. Although there were increases in untargeted physical activity and decreases in alcohol consumption and smoking in the first year, these changes were not consistently associated with study arm. Moreover, although the results of the repeated-measures latent class analysis identified three unique subgroups of participants with similar patterns of untargeted health behaviors, none of the subgroups showed substantial change in the probability of engagement in any of the behaviors over 1 year, and the study arms had nearly identical latent class solutions. Discussion and Conclusion. These findings suggest that the dietary intervention did not act as a gateway behavior for change in the untargeted behaviors and that researchers interested in changing multiple health behaviors may need to deliberately target additional behaviors.

What Is the Amount of Visual Field Loss Associated With Disability in Glaucoma?

PURPOSE

To propose a new methodology for classifying patient-reported outcomes in glaucoma and for quantifying the amount of visual field damage associated with disability in the disease.

DESIGN

Cross-sectional study.

METHODS

A total of 263 patients with glaucoma were included. Vision-related disability was assessed by the National Eye Institute Visual Function Questionnaire (NEI VFQ-25). A latent class analysis (LCA) model was applied to analyze NEI VFQ-25 data and patients were divided into mutually exclusive classes according to their responses to the questionnaires. Differences in standard automated perimetry (SAP) mean deviation (MD) and integrated binocular mean sensitivity (MS) values between classes were investigated. The optimal number of classes was defined based on goodness-of-fit criteria, interpretability, and clinical utility.

RESULTS

The model with 2 classes, disabled and nondisabled, had the best fit with an entropy of 0.965, indicating excellent separation of classes. The disabled group had 48 (18%) patients, whereas 215 (82%) patients were classified as nondisabled. The average MD of the better eye in the disabled group was -5.98 dB vs -2.51 dB in the nondisabled group (P < .001). For the worse eye, corresponding values were -13.36 dB and -6.05 dB, respectively (P < .001).

CONCLUSION

Application of an LCA model allowed categorization of patient-reported outcomes and quantification of visual field levels associated with disability in glaucoma. A damage of approximately -6 dB for SAP MD, indicating relatively early visual field loss, may already be associated with significant disability if occurring in the better eye.

Patterns of aged care use among older Australian women: A prospective cohort study using linked data

BACKGROUND

Women live longer than men and have an increased need for long-term care. The objective of this study was to identify patterns of aged care use among older Australian women and to examine how these patterns were associated with their demographic and health-related characteristics.

METHODS

The sample consisted of 8768 women from the 1921-1926 birth cohort of the Australian Longitudinal Study on Women's Health (ALSWH), who had survived to age 75-80 years. ALSWH survey and linked administrative aged care and death datasets from 2001 to 2011 were utilized. Patterns of aged care use were identified using a repeated measure latent class analysis.

RESULTS

We identified four patterns of aged care use over time, differentiated by timing of service onset, types of service use and time of death. Approximately 41% of the sample were non-users or using basic home and community care (HACC), while 24% were at high risk of using moderate to high-level HACC/community aged care package (CACP). Only 11% had a greater risk of using residential aged care (RAC) over time. Being widowed, residing in remote/regional areas, having difficulty in managing income, having a chronic condition, reporting poor/fair self-rated health, and lower SF-36 quality of life scores were associated with an increased odds of being a member of the following classes: 1) moderate to high-level HACC/CACP, 2) increasing RAC, and 3) early mortality, compared with the non-user class.

CONCLUSIONS

Distinct patterns of aged care use were identified. These results will facilitate future capacity planning for aged care systems in Australia.

Discontinuous Patterns of Cigarette Smoking From Ages 18 to 50 in the United States: A Repeated-Measures Latent Class Analysis

INTRODUCTION

Effective cigarette smoking prevention and intervention programming is enhanced by accurate understanding of developmental smoking pathways across the life span. This study investigated within-person patterns of cigarette smoking from ages 18 to 50 among a US national sample of high school graduates, focusing on identifying ages of particular importance for smoking involvement change.

AIMS AND METHODS

Using data from approximately 15,000 individuals participating in the longitudinal Monitoring the Future study, trichotomous measures of past 30-day smoking obtained at 11 time points were modeled using repeated-measures latent class analyses. Sex differences in latent class structure and membership were examined.

RESULTS

Twelve latent classes were identified: three characterized by consistent smoking patterns across age (no smoking; smoking < pack per day; smoking pack + per day); three showing uptake to a higher category of smoking across age; four reflecting successful quit behavior by age 50; and two defined by discontinuous shifts between smoking categories. The same latent class structure was found for both males and females, but membership probabilities differed between sexes. Although evidence of increases or decreases in smoking behavior was observed at virtually all ages through 35, 21/22 and 29/30 appeared to be particularly key for smoking category change within class.

CONCLUSIONS

This examination of latent classes of cigarette smoking among a national US longitudinal sample of high school graduates from ages 18 to 50 identified unique patterns and critical ages of susceptibility to change in smoking category within class. Such information may be of particular use in developing effective smoking prevention and intervention programming.

IMPLICATIONS

This study examined cigarette smoking among a national longitudinal US sample of high school graduates from ages 18 to 50 and identified distinct latent classes characterized by patterns of movement between no cigarette use, light-to-moderate smoking, and the conventional definition of heavy smoking at 11 time points via repeated-measures latent class analysis. Membership probabilities for each smoking class were estimated, and critical ages of susceptibility to change in smoking behaviors were identified.

Patterns of youth tobacco and polytobacco usage: The shift to alternative tobacco products

BACKGROUND

Despite significant declines in youth cigarette smoking, overall tobacco usage remains over 20% as non-cigarette tobacco product usage is increasingly common and polytobacco use (using 1+ tobacco product) remains steady.

OBJECTIVES

The present study was designed to identify patterns of youth tobacco use and examine associations with sociodemographic characteristics and tobacco dependence.

METHODS

The current analysis uses Latent Class Analysis (LCA) to examine the 6,958 tobacco users (n = 2,738 female) in the National Youth Tobacco Survey (2012 and 2013). We used as indicators past month use of tobacco products (cigarettes, cigars, smokeless tobacco, e-cigarettes, hookah, snus, pipes, bidis, and kreteks) and regressed resulting classes on sociodemographic characteristics and tobacco dependence.

RESULTS

Nine classes emerged: cigarette smokers (33.4% of sample, also included small probabilities for use of cigars and e-cigarettes), cigar smokers (16.8%, nearly exclusive), smokeless tobacco users (12.3%, also included small probabilities for cigarettes, cigars, snus), hookah smokers (11.8%), tobacco smokers/chewers (10.7%, variety of primarily traditional tobacco products), tobacco/hookah smokers (7.2%), tobacco/snus/e-cig users (3.3%), e-cigarette users (2.9%,), and polytobacco users (1.7%, high probabilities for all products). Compared to cigarette smokers, tobacco/hookah smokers and hookah smokers were more likely to report Hispanic ethnicity. Polytobacco users were more likely to report dependence (AOR:2.77, 95% CI:[1.49-5.18]), whereas e-cigarette users were less likely (AOR:0.49, 95% CI:[0.24-0.97]).

CONCLUSION

Findings are consistent with other research demonstrating shifts in adolescent tobacco product usage towards non-cigarette tobacco products. Continuous monitoring of these patterns is needed to help predict if this shift will ultimately result in improved public health.

Patterns of high-intensity drinking among young adults in the United States: A repeated measures latent class analysis

OBJECTIVE

Using a national sample of young adults, this study identified latent classes of alcohol use including high-intensity drinking (10+ drinks) from ages 18 to 25/26, and explored associations between time-invariant covariates measured at age 18 and class membership.

METHOD

Longitudinal data from the national Monitoring the Future study were available for 1078 individuals (51% female) first surveyed as 12th grade students in 2005-2008, and followed through modal age 25/26. Repeated measures latent class analysis was used to identify latent classes based on self-reported alcohol use: no past 30-day drinking, 1-9 drinks per occasion in the past 2weeks, and 10+ drinks per occasion.

RESULTS

Four latent classes of alcohol use from ages 18 to 25/26 were identified: (1) Non-Drinkers (21%); (2) Legal Non-High-Intensity Drinkers (23%); (3) Persistent Non-High-Intensity Drinkers (40%); and (4) High-Intensity Drinkers (16%). Membership in the High-Intensity Drinkers class was characterized by higher than average probabilities of high-intensity drinking at all ages, with the probability of high-intensity drinking increasing between ages 18 and 21/22. Both gender and race/ethnicity significantly differentiated class membership, whereas neither parental education (a proxy for socioeconomic status) nor college plans at 12th grade showed significant associations.

CONCLUSIONS

More than one in seven individuals who were seniors in high school experienced a long-term pattern of high-intensity drinking lasting into middle young adulthood. Young adult high-intensity drinking is often preceded by high-intensity drinking in high school, suggesting the importance of screening and prevention for high-intensity drinking during adolescence.

Emergency Department-Initiated Tobacco Control: Update of a Systematic Review and Meta-Analysis of Randomized Controlled Trials

INTRODUCTION

A 2012 systematic review and meta-analysis of randomized controlled trials on emergency department-initiated tobacco control (ETC) showed only short-term efficacy. The aim of this study was to update data through May 2015.

METHODS

After registering the study protocol on the international prospective register of systematic reviews (PROSPERO) in May 2015, we searched 7 databases and the gray literature. Our outcome of interest was the point prevalence of tobacco-use abstinence at 1-month, 3-month, 6-month, or 12-month follow-up. We calculated the relative risk (RR) of tobacco-use abstinence after ETC at each follow-up time separately for each study and then pooled Mantel-Haenszel RRs by follow-up time. These results were pooled with results of the 7 studies included in the previous review. We calculated the effect of ETC on the combined point prevalence of tobacco-use abstinence across all follow-up times by using generalized linear mixed models.

RESULTS

We retrieved 4 additional studies, one published as an abstract, comprising 1,392 participants overall. The 1-month follow-up point prevalence of tobacco-use abstinence after ETC resulted in an RR of 1.49 (95% confidence interval [CI], 1.08-2.05) across 3 studies; 3-month follow-up, an RR of 1.38 (95% CI, 1.12-1.71) across 9 studies; 6-month follow-up, an RR of 1.09 (95% CI, 0.84-1.41) across 6 studies; and 12-month follow-up, an RR of 1.26 (95% CI, 1.00-1.59) across 3 studies. The effect on the combined point prevalence of abstinence was an RR of 1.40 (95% CI, 1.06-1.86) (P = .02).

CONCLUSION

ETC is effective in promoting continual tobacco-use abstinence up to 12 months after intervention. ETC may be a critically important public health strategy for engaging hard-to-reach smokers in tobacco-use cessation.

How Much Is Too Much? Patterns of Drinking During Alcohol Treatment and Associations With Post-Treatment Outcomes Across Three Alcohol Clinical Trials

OBJECTIVE

This secondary data analysis examined patterns of drinking during alcohol treatment and associated drinking outcomes during the first year following treatment. The goal was to provide clinicians with guidance on which patients may be most at risk for negative long-term outcomes based on drinking patterns during treatment.

METHOD

This study was an analysis of existing data (N = 3,851) from three randomized clinical trials for alcohol use disorder: the COMBINE Study (n = 1,383), Project MATCH (n = 1,726), and the United Kingdom Alcohol Treatment Trial (n = 742). Indicators of abstinence, non-heavy drinking, and heavy drinking (defined as 4/5 or more drinks per day for women/men) were examined during each week of treatment using repeated-measures latent class analysis. Associations between drinking patterns during treatment and drinking intensity, drinking consequences, and physical and mental health 12 months following intake were examined.

RESULTS

Seven drinking patterns were identified. Patients who engaged in persistent heavy drinking throughout treatment and those who returned to persistent heavy drinking during treatment had the worst long-term outcomes. Patients who engaged in some heavy drinking during treatment had better long-term outcomes than persistent heavy drinkers. Patients who reported low-risk drinking or abstinence had the best long-term outcomes. There were no differences in outcomes between low-risk drinkers and abstainers.

CONCLUSIONS

Abstinence, low-risk drinking, or even some heavy drinking during treatment are associated with the best long-term outcomes. Patients who are engaging in persistent heavy drinking are likely to have the worst outcomes and may require a higher level of care.

Postdischarge smoking cessation in subgroups of hospitalized smokers: A latent class analysis

BACKGROUND

Hospitalization presents a window of opportunity to treat smoking, and hospital-initiated smoking treatment has demonstrated effectiveness. Despite effective interventions, not all smokers will discontinue use, highlighting the need to better understand which patients achieve cessation. Traditional regression methods may not capture the complexity of inpatient smoker subgroups.

METHODS

Latent class analysis (LCA) was conducted with data from 397 hospitalized adult cigarette smokers enrolled in a randomized trial. Six categorical indicator variables known to impact cessation were selected to estimate subgroups: health conditions (smoking-related disease [SRD], depressive symptoms, positive screen for alcohol problems) and smoking-related variables (time to first cigarette, cigarettes/day, smoking indoors). The probability of achieving biologically verified 7-day tobacco cessation 6 months after discharged was estimated.

RESULTS

A 3-class model best fit the trial data: a Light Smokers subgroup had lower probability for most indicators; a High Health Burden subgroup had high smoking behavior probabilities and similar health problems to the Light Smokers subgroup; and a Heavy Smoking Drinking Depressed subgroup had high nicotine dependence, depressive symptoms, and alcohol misuse probabilities. Probability of biologically verified cessation conditional on class membership was significantly higher (P < .001) for the High Health Burden and the Light Smokers subgroups compared with the Heavy Smoking Drinking Depressed subgroup.

CONCLUSION

Results suggest that subgroups with lower probabilities of alcohol misuse and depression and higher probability of SRD had higher probability of successful cessation after hospital discharge. Hospitalized patients with nicotine dependence combined with behavioral and mental health problems have additional cessation barriers that may require intervention focus.

Quitting smoking during substance use disorders treatment: Patient and treatment-related variables

Although individuals in substance use disorders (SUD) treatment continue to smoke at high rates, regulatory, policy and programming changes promoting tobacco cessation are being implemented and some patients quit successfully. We examined associations of smoking patterns, tobacco advertising receptivity, anti-tobacco message awareness, health risk perception, attitudes towards addressing smoking and availability of smoking cessation services with quitting smoking during SUD treatment. Surveys were completed by 1127 patients in 24 programs chosen randomly, stratified by program type (residential, methadone maintenance, outpatient), from among publicly funded, adult treatment programs within the National Drug Abuse Treatment Clinical Trials Network. Among respondents who had been in SUD treatment for at least one month, there were 631 current smokers and 52 former smokers who reported quitting smoking during treatment for at least one month prior to survey completion; these respondents comprised our sample (N=683). Results showed that participants who reported health concerns as a reason for quitting were 1.27 times more likely to have quit during treatment (p=0.015) than those reporting health concerns affected quitting a little or not at all. Additionally, participants who reported that smoking cessation was part of their personal treatment plan during SUD treatment were 1.08 times more likely to have quit during treatment (p<0.001). Participants in methadone treatment were 49% less likely to report successfully quitting during treatment than those in outpatient treatment (95%CI: 0. 35-0.75, p<0.001). Leveraging health concerns about smoking and including smoking cessation in an individualized treatment plan may help increase smoking cessation during SUD treatment.

Patterns of Change in Weekend Drinking Cognitions Among Non-Treatment-Seeking Young Adults During Exposure to a 12-Week Text Message Intervention

OBJECTIVE

We sought to identify patterns of response (latent classes) to a text-message (short message service) intervention based on weekend drinking cognitions (e.g., drinking plans, commitment to a low consumption goal), and to examine how the latent classes differed in baseline characteristics and alcohol consumption outcomes.

METHOD

We conducted a secondary analysis of 384 non-treatment seeking young adults with hazardous alcohol use randomly assigned to a 12-week short message service intervention. Responses to weekly short message service queries related to weekend drinking cognitions were categorized as (a) planned not to drink, (b) planned to drink but did not plan a heavy drinking episode (HDE), (c) planned to have an HDE but willing to limit alcohol consumption, (d) planned to have an HDE and not willing to limit alcohol consumption We used repeated-measures latent class analysis to identify distinct classes based on these categories and examined associations of the classes with baseline covariates and alcohol consumption outcomes through 6 months.

RESULTS

We identified the following three latent classes: planned not to drink (62%), willing to limit drinks (27%), and not willing to limit drinks (12%). The "not willing to limit drinks" class exhibited the least reductions in alcohol consumption and was more likely to include White individuals and those with higher baseline drinking severity. The "planned not to drink" class had the greatest reductions in alcohol consumption.

CONCLUSIONS

Young adults who exhibited low likelihood of committing to goals to limit weekend drinking were less responsive to short message service intervention, suggesting the need for alternative interventions.

Repeated measures latent class analysis of daily smoking in three smoking cessation studies

BACKGROUND

Person-centered approaches to the study of behavior change, such as repeated measures latent class analysis (RMLCA), can be used to identify patterns of change and link these to later behavior change outcomes.

METHODS

Daily smoking status data from three smoking cessation studies (N=287, N=334, and N=403) were submitted to RMLCA to identify latent classes of smokers based on patterns of abstinence across the first 27days of a quit attempt. Three-month biochemically verified abstinence rates were compared among latent classes with particular patterns of smoking across days. Pharmacotherapy variables and baseline individual differences were added as covariates of latent class membership.

RESULTS

Results of separate and pooled analyses supported a five-class solution that replicated across studies. Latent classes included a large class that achieved immediate stable abstinence, a smaller class of cessation failures, and three classes with partial abstinence that increased, decreased, or remained stable over time. Three-month point-prevalence abstinence rates varied among the latent classes, with 38-55% abstinent among early quitters, 3-20% abstinent among those who smoked intermittently throughout the first 27days, and fewer than 5% abstinent in the classes marked by little or delayed change in smoking. High-dose nicotine patch and bupropion promoted membership in abstinent classes. Demographics, nicotine dependence, and craving were related to latent class in multiple studies and pooled analyses.

CONCLUSIONS

We identified five patterns of smoking behavior in the first weeks of a smoking cessation attempt. These patterns are robust across multiple studies and are related to later point-prevalence abstinence rates.

Insomnia symptoms as a risk factor for cessation failure following smoking treatment

Insomnia symptoms are associated with smoking, and may interfere with smoking cessation. Specifically, studies have shown that smoking-related sleep problems are associated with long-term smoking relapse, and longer sleep duration is associated with successful smoking cessation. However, it is currently unclear whether pre- or post-quit insomnia symptoms are associated with smoking cessation outcomes. As such, the current study aimed to extend previous findings by using a measure of insomnia symptoms as a predictor of smoking cessation failure by month 3 following smoking cessation treatment. Additionally, we examined whether post-quit insomnia symptoms predicted cessation outcomes. Results indicated that pre-, but not post-quit insomnia, predicted smoking cessation failure by 3 months post-cessation, after covarying for depressive symptoms, anxiety sensitivity, alcohol use disorder severity, treatment condition, and number of cigarettes per day. These findings add to the literature on insomnia symptoms as a risk factor for difficulties with smoking cessation, and suggest it may be a worthy clinical target for smoking populations who are interested in quitting smoking.