A randomized controlled trial protocol for engaging distress tolerance and working memory to aid smoking cessation in low socioeconomic status (SES) adults

A novel human laboratory alcohol self-administration paradigm for medication screening: Modeling the ability to resist drinking and heavy drinking

Background

Human laboratory analogues of drinking behavior provide an efficient, cost-effective mechanistic evaluation of a medication signal on drinking. We developed a novel alcohol self-administration paradigm which models the ability to resist drinking and heavy drinking.

Methods

We compared a de-escalating schedule of monetary reinforcement (n=16, 50% female) to no schedule (n=16, 50% female) on the ability to resist drinking (i.e., latency to start drinking) and subsequent ad-libitum alcohol consumption of preferred alcoholic beverage in participants with alcohol use disorder (AUD). Participants completed two laboratory sessions designed to model the ability to resist drinking using stress (versus neutral imagery, within-subject factor) as a prime for drinking.

Results

Participants consumed more alcohol with no schedule (74.2%) versus with the de-escalating reinforcement schedule (40.3%,). The de-escalating schedule reduced alcohol consumption by 49%. Eighty-one percent of participants drank heavily with no schedule and this was reduced with the schedule. Use of the de-escalating schedule also increased the latency to pour and sip the first drink. Participants poured and sipped alcohol faster following stress imagery (vs. neutral), had greater craving, and consumed more alcohol in the first 30 minutes.

Conclusions

Our novel alcohol self-administration model generated heavy drinking. Over 80% of participants without reinforcement consumed more than 2/3 of their preferred alcoholic beverage designed to increase blood alcohol levels to 0.12 mg% within a 2-hour window. Our model was sensitive to stress, and the de-escalating schedule highlighted stress effects on drinking. Thus, this model is ideal for a cross-over design to test medications for AUD.

Promotion of Smoking Cessation Using the Transtheoretical Model: Short-Term and Long-Term Effectiveness for Workers in Coastal Central Taiwan

Background

Smoking cessation reduces the risk of severe illnesses in the long run and contributes to improving health. This study evaluated the short-term and long-term effectiveness of workplace smoking cessation intervention implemented using the transtheoretical model.

Methods

Participants were assessed at baseline before the intervention and after 6 months and 4 years of follow-ups. Data on changes in participants' perception of smoking prohibition in the workplace, knowledge of the hazards of smoking, attitude towards quitting smoking, and behavior related to tobacco harm prevention were collected.

Results

Results showed the prevalence of smoking cessation was 31.5% (95% CI: 25.4-38.1%) after 6 months and 10.7% (95% CI: 6.9-15.6%) after 4 years. At the abovementioned time points, the prevalence of second-hand smoke exposure, and the proportion of people who demonstrated correct knowledge of smoke hazards initially decreased and then increased. The proportion of participants who had seen or received information about tobacco harm prevention provided in the workplace increased from 75.6% at baseline to 95.6% (increased by 20.0%) after 6 months and finally to 97.2% (increased by 21.6%) after 4 years (P < .001). However, the percentage of participants who hoped their workplace continued to provide smoking cessation services rose from 80.0% at baseline to 93.6% (increased by 13.6%) after 6 months and then fell to 78.0% (decreased by 2.0%) after 4 years (P < .001).

Conclusion

The short-term effectiveness of the transtheoretical model in promoting workplace smoking cessation is substantial, but in the long-term, effectiveness weakens.

Mindfulness for smoking cessation

BACKGROUND

Mindfulness-based smoking cessation interventions may aid smoking cessation by teaching individuals to pay attention to, and work mindfully with, negative affective states, cravings, and other symptoms of nicotine withdrawal. Types of mindfulness-based interventions include mindfulness training, which involves training in meditation; acceptance and commitment therapy (ACT); distress tolerance training; and yoga.

OBJECTIVES

To assess the efficacy of mindfulness-based interventions for smoking cessation among people who smoke, and whether these interventions have an effect on mental health outcomes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's specialised register, CENTRAL, MEDLINE, Embase, PsycINFO, and trial registries to 15 April 2021. We also employed an automated search strategy, developed as part of the Human Behaviour Change Project, using Microsoft Academic.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs that compared a mindfulness-based intervention for smoking cessation with another smoking cessation programme or no treatment, and assessed smoking cessation at six months or longer. We excluded studies that solely recruited pregnant women.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. We measured smoking cessation at the longest time point, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of intervention and type of comparator. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models. We summarised mental health outcomes narratively.

MAIN RESULTS

We included 21 studies, with 8186 participants. Most recruited adults from the community, and the majority (15 studies) were conducted in the USA. We judged four of the studies to be at low risk of bias, nine at unclear risk, and eight at high risk. Mindfulness-based interventions varied considerably in design and content, as did comparators, therefore, we pooled small groups of relatively comparable studies. We did not detect a clear benefit or harm of mindfulness training interventions on quit rates compared with intensity-matched smoking cessation treatment (RR 0.99, 95% CI 0.67 to 1.46; I² = 0%; 3 studies, 542 participants; low-certainty evidence), less intensive smoking cessation treatment (RR 1.19, 95% CI 0.65 to 2.19; I² = 60%; 5 studies, 813 participants; very low-certainty evidence), or no treatment (RR 0.81, 95% CI 0.43 to 1.53; 1 study, 325 participants; low-certainty evidence). In each comparison, the 95% CI encompassed benefit (i.e. higher quit rates), harm (i.e. lower quit rates) and no difference. In one study of mindfulness-based relapse prevention, we did not detect a clear benefit or harm of the intervention over no treatment (RR 1.43, 95% CI 0.56 to 3.67; 86 participants; very low-certainty evidence). We did not detect a clear benefit or harm of ACT on quit rates compared with less intensive behavioural treatments, including nicotine replacement therapy alone (RR 1.27, 95% CI 0.53 to 3.02; 1 study, 102 participants; low-certainty evidence), brief advice (RR 1.27, 95% CI 0.59 to 2.75; 1 study, 144 participants; very low-certainty evidence), or less intensive ACT (RR 1.00, 95% CI 0.50 to 2.01; 1 study, 100 participants; low-certainty evidence). There was a high level of heterogeneity (I² = 82%) across studies comparing ACT with intensity-matched smoking cessation treatments, meaning it was not appropriate to report a pooled result. We did not detect a clear benefit or harm of distress tolerance training on quit rates compared with intensity-matched smoking cessation treatment (RR 0.87, 95% CI 0.26 to 2.98; 1 study, 69 participants; low-certainty evidence) or less intensive smoking cessation treatment (RR 1.63, 95% CI 0.33 to 8.08; 1 study, 49 participants; low-certainty evidence). We did not detect a clear benefit or harm of yoga on quit rates compared with intensity-matched smoking cessation treatment (RR 1.44, 95% CI 0.40 to 5.16; 1 study, 55 participants; very low-certainty evidence). Excluding studies at high risk of bias did not substantially alter the results, nor did using complete case data as opposed to using data from all participants randomised. Nine studies reported on changes in mental health and well-being, including depression, anxiety, perceived stress, and negative and positive affect. Variation in measures and methodological differences between studies meant we could not meta-analyse these data. One study found a greater reduction in perceived stress in participants who received a face-to-face mindfulness training programme versus an intensity-matched programme. However, the remaining eight studies found no clinically meaningful differences in mental health and well-being between participants who received mindfulness-based treatments and participants who received another treatment or no treatment (very low-certainty evidence).

AUTHORS' CONCLUSIONS

We did not detect a clear benefit of mindfulness-based smoking cessation interventions for increasing smoking quit rates or changing mental health and well-being. This was the case when compared with intensity-matched smoking cessation treatment, less intensive smoking cessation treatment, or no treatment. However, the evidence was of low and very low certainty due to risk of bias, inconsistency, and imprecision, meaning future evidence may very likely change our interpretation of the results. Further RCTs of mindfulness-based interventions for smoking cessation compared with active comparators are needed. There is also a need for more consistent reporting of mental health and well-being outcomes in studies of mindfulness-based interventions for smoking cessation.

Anxiety Sensitivity as a Malleable Mechanistic Target for Prevention Interventions: A Meta-Analysis of the Efficacy of Brief Treatment Interventions

Anxiety sensitivity (AS) is a transdiagnostic risk factor and potential treatment target for prevention of associated psychopathology and negative health behaviors. We conducted a meta-analysis evaluating the efficacy of brief interventions in at-risk samples for reducing AS and associated clinical/behavioral outcomes (e.g., depression, alcohol use) across 28 studies (1,998 participants). AS targeted interventions, compared to control conditions, evidenced a significant moderate effect size for alleviating AS from pre- to post-treatment (d = 0.54) and approached a large effect size from pre-treatment to short-term follow-up (d = 0.78). The effect size for long-term follow-up did not reach significance (d = 0.29). For clinical/behavioral outcomes, AS interventions demonstrated significant small-to-moderate effect sizes for the three timepoints examined (d's = 0.20-0.41). Our findings help validate AS as a modifiable mechanistic target for prevention efforts.

Future directions of the National Institutes of Health Science of Behavior Change Program

Background

The National Institutes of Health Science of Behavior Change Common Fund Program has accelerated the investigation of mechanisms of behavior change applicable to multiple health behaviors and outcomes and facilitated the use of the experimental medicine approach to behavior change research.

Purpose

This commentary provides a brief background of the program, plans for its next phase, and thoughts about how the experimental medicine approach to behavior change research can inform future directions in two areas of science—reproductive health and COVID-19 vaccine uptake.

Conclusions

The incorporation of a mechanisms-based approach into behavior intervention research offers new opportunities for improving health.

Working memory moderates the predictive influence of distress intolerance on health-related goal attainment

High distress intolerance (DI: often assessed as anxiety sensitivity) and low working memory capacity (WMC) have each been identified as risk factors for negative health behaviors. To our knowledge, these risk factors have only been studied independently. The current study investigated both the independent and interactive effects of DI and WMC in predicting health-related goal attainment in 118 undergraduates who self-selected a health-related goal. Participants received one of three interventions: values clarification, action planning, or a combination of the two. Across these interventions, we found that DI was at the point of significance (and reflected a small effect size) for predicting goal attainment, whereas WMC was not. Further, we found that when entered into the stepwise regression model together, the interaction of WMC and DI significantly predicted goal success one week later. Specifically, for individuals scoring one standard deviation below the mean in WMC, having worse DI significantly predicted worse goal attainment one week later. We believe this study represents the first published finding of the moderation of the predictive influence of DI by WMC, and underscores the importance of evaluating how risk factors that are typically examined independently operate together.