Transtheoretical principles and processes for quitting smoking: A 24-month comparison of a representative sample of quitters, relapsers, and non-quitters

doi:10.1016/j.addbeh.2007.04.005

Addictive Behaviors

Volume 32, Issue 12, December 2007, Pages 2707-2726

https://doi.org/10.1016/j.addbeh.2007.04.005 Get rights and content

Abstract

This longitudinal study compared 14 principles and processes of change applied by successful quitters, relapsers and non-quitters over 24 months in a representative sample of 4144 smokers in intervention and control groups. The successful quitters showed a decrease in the use of experiential processes (cognitive, affective and effective) and an increase in behavioral processes (e.g., counter-conditioning and stimulus control). The non-quitters showed little change in their use of almost all of the processes. The relapsers' use of the processes tended to initially parallel the successful quitters, but over time, their use ended up between the quitters and the non-quitters. In general, the relapsers ended up working harder but not smarter than the successful quitters. The pattern of use of change processes in the treatment and control groups were remarkably similar, suggesting common pathways to change.

Section snippets

Sample

This study began with a representative sample of 4144 smokers proactively recruited in Rhode Island by random digit dialing procedures. Of these smokers 42.1% were in the precontemplation stage and were not intending to quit smoking in the next six months; 40.3% were in the contemplation stage and were intending to quit in the next six months and 17.6% were in the preparation stage and were intending to quit in the next month and had quitted for at least 24 h in the past year. They smoked a

Quit rates and relapse rates

Table 3 shows the 24-hour point prevalence abstinence rates for the expert system intervention group and the assessment only group at 6, 12, 18 and 24 months. These outcome data were reported previously (Prochaska, Velicer, Fava, Rossi et al., 2001). The expert system intervention produced significantly more abstinence at each follow-up than the assessment only group with the differences between the two groups becoming significantly greater over the course of follow-up. The continued increases

Discussion

Graphic analyses of dynamic typologies have in the past served as a foundation for building expert system interventions that have proven to be remarkably robust in population cessation trials. In the past such analyses focused on a population of self-changers and compared the use of principles and processes of change of stable groups that remained in the same stage of change over 24 months, those who regressed one stage or more and those who recycled through the stages of change (Prochaska et

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A Comparison of Profiles of Transtheoretical Model Constructs of Change among Depressed and Nondepressed Women at Risk for an Alcohol-Exposed Pregnancy
2017, Women's Health Issues
The efficacy of a series of interventions to reduce risk of alcohol-exposed pregnancies is well-established, yet some subsets of women remain at risk. For instance, in CHOICES, a randomized clinical trial of an intervention to prevent alcohol-exposed pregnancy, nondepressed women reduced risk drinking at roughly twice the rate of women with depression (49% vs. 24%). This secondary analysis of CHOICES data examines constructs that can explicate differences between nondepressed and depressed women in the process of changing alcohol behavior.
Profile analysis was used to compare the current status on transtheoretical model constructs of change between groups of depressed (n = 41) and nondepressed (n = 171) women in CHOICES at baseline and at the 9-month follow-up (end of the study). Participants were women aged 18 to 44 years who were at risk for an alcohol-exposed pregnancy at baseline. Measures included the Timeline Followback, Brief Symptom Inventory, and the transtheoretical model measures of decisional balance, self-efficacy, and experiential and behavioral processes of change.
Differences in profiles of the transtheoretical model constructs between groups were found at baseline and 9 months (p < .001). Women with depression had a profile that has historically predicted failure to change. Profiles among depressed women were distinguished by high scores on cons for changing alcohol use and temptation to drink.
Prevention interventions should assess for depression and target interventions to improve success. Results of this study can help practitioners to better tailor interventions to the needs of individuals with depression by strategically targeting decisional balance and self-efficacy.
Predictors of relapse among smokers: Transtheoretical effort variables, demographics, and smoking severity
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Citation Excerpt :
Pros and Cons are most important in preparing individuals to take action but not for maintaining that action. Similar to what has been found in previous studies (Redding et al., 2011; Sun et al., 2007), Self-Reevaluation (SR) was a key process that differentiated relapsers from maintainers. Those studies have indicated that once individuals quit, they benefit from decreasing their reliance on SR and increasing their utilization of Behavioral Processes such as Helping Relationships for potential stress management and support, and Stimulus Control for alteration of environmental cues to maintain the cessation process.
The present longitudinal study investigates baseline assessments of static and dynamic variables, including demographic characteristics, smoking severity, and Transtheoretical Model of Behavior Change (TTM) effort variables (Decisional Balance (i.e. Pros and Cons), Situational Temptations, and Processes of Change) of relapse among individuals who were abstinent at 12 months. The study sample (N = 521) was derived from an integrated dataset of four population-based smoking cessation interventions. Several key findings included: Participants who were aged 25–44 and 45–64 (OR = .43, p = .01 and OR = .40, p = .01, respectively) compared to being aged 18–24 were less likely to relapse at follow-up. Participants in the control group were more than twice as likely to relapse (OR = 2.17, p = .00) at follow-up compared to participants in the treatment group. Participants who reported higher Habit Strength scores were more likely to relapse (OR = 1.05, p = .02). Participants who had higher scores of Reinforcement Management (OR = 1.05, p = .04) and Self-Reevaluation (OR = 1.08, p = .01) were more likely to relapse. Findings add to one assumption that relapsers tend to relapse not solely due to smoking addiction severity, but due to immediate precursor factors such as emotional distress. One approach would be to provide additional expert guidance on how smokers can manage stress effectively when they enroll in treatment at any stage of change.
Hardcore smokers: What do we know?
2014, Addictive Behaviors
Citation Excerpt :
Another population level analysis found that nearly 60% of current smokers in the 1990s had no intention to quit (Wewers, Stillman, Hartman, & Shopland, 2003). A Rhode Island study found that 42% of smokers did not intend to quit and smoked an average of 20 CPD (Sun, Prochaska, Velicer, & Laforge, 2007). If intention to quit alone defines hardcore smoking, 30% of smokers would be so classified based on the 2001–2010 National Health Interview Survey reporting that 70% of smokers want to quit (Centers for Disease Control and Prevention, 2011).
The existence of smokers who are resistant to smoking cessation treatment has long been noted in the literature. There has been ongoing debate as to whether the proportion of these smokers is increasing as smoking prevalence rates stagnate. Studies define hardcore smokers inconsistently and within the context of specific illnesses, addiction, population, and/or theoretical paradigms. This review examines the existing literature related to hardcore smokers to develop a better understanding of what is known and not known about this group to guide smoking cessation treatment.
PubMed MESH search and review of research publications from 1998 to 2012 (N = 61).
Inconsistent definitions of hardcore smoking make it difficult to estimate prevalence rates and to identify specific characteristics of persistent smokers. Generally, persistent smokers have higher levels of nicotine dependence, are disproportionately from lower socioeconomic groups, start smoking at an earlier age, and are more likely to have a psychological co-morbidity.
Defining some smokers as hardcore is limiting. Targeted and tailored interventions for smoking cessation for persistent smoking have demonstrated effectiveness in a small number of studies. Treatment access barriers need to be addressed to improve the reach and effectiveness of cessation with persistent smokers. Efforts to limit early age initiation of tobacco use are a critical element in averting persistent smoking.
Interactions among drinking identity, gender and decisional balance in predicting alcohol use and problems among college students
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Citation Excerpt :
Therefore, we expected that decisional balance would be negatively associated with drinking and positively associated with problems. Although Transtheoretical Model-based drinking studies have not specifically explored drinking identity (e.g., Sun et al., 2007), research generally suggests that drinking identity is positively associated with alcohol consumption (e.g., Neighbors et al., 2010; Reed et al., 2007), which in turn is linked with alcohol-related problems (e.g., Lindgren et al., 2013). Drinking identity is conceptualized as how central or defining alcohol consumption is to one's self-identity (Conner et al., 1999).
The aim of the present study was to test promising constructs (decisional balance and drinking identity) and their interaction with gender as predictors of risky college drinking. We expected that, consistent with previous work, drinking identity would be positively associated with alcohol consumption and problems. We further expected that drinking identity would be more strongly related to outcomes among individuals scoring low in decisional balance. Additionally, we expect the relationship between drinking identity and alcohol behavior to vary as a function of decisional balance.
Participants included 329 undergraduates (M = 23.11; SD = 5.63; 74.47% female) who met heavy drinking criteria (defined as women who consumed 4 or more drinks per occasion and men who consumed 5 or more drinks per occasion) and completed an online survey comprised of self-report measures.
Decisional balance was negatively correlated with both drinking and problems, which partially supported expectations. As expected, drinking identity was positively correlated with drinking and problems. A two-way interaction emerged between drinking identity and decisional balance regarding problems, indicating that drinking identity was associated with more problems, especially among those lower in decisional balance. A three-way interaction between drinking identity, decisional balance, and gender emerged regarding problems such that drinking identity was associated with more problems for those lower in decisional balance and this effect was stronger among men.
Findings lend support to the perspective that decisional balance, drinking identity, and gender are all influential factors that are associated with the experience of alcohol problems.
Baseline transtheoretical and dietary behavioral predictors of dietary fat moderation over 12 and 24months
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Longitudinal predictors of dietary behavior change are important and in need of study. This secondary data analysis combined primary data across three randomized trials to examine transtheoretical model (TTM) and specific dietary predictors of successful dietary change at 12 and 24 months separately in treatment and control groups (N = 4178). The treatment group received three TTM-tailored print interventions over 12 months between 1995 and 2000. Chi-square and MANOVA analyses were used to examine baseline predictors of dietary outcome at 12 and 24 months. Last, a multivariable logistic regression was conducted with all baseline variables included. Across all analyses in both treatment and control groups, the most robust predictors of successful change were for TTM-tailored treatment group, preparation stage of change, and increased use of dietary behavior variables such as moderating fat intake, substitution of lower fat foods, and increasing intake of healthful foods. These results provide strong evidence for treatment, stage and behavioral dietary severity effects predicting dietary behavior change over time, and for targeting these variables with the strongest relationships to outcome in interventions, such as TTM-tailored dietary interventions.
The importance of habits in eating behaviour. An overview and recommendations for future research
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Citation Excerpt :
Therefore, another promising self-regulation technique is counterconditioning, which aims to replace the cued response by another, more healthful response. Research shows that smokers make use of this technique, for instance engaging in physical exercise when having the urge to smoke (Prochaska et al., 1988), and that the use of counterconditioning is significantly associated with successful quitting (Sun et al., 2007). In the domain of eating, it has also been found that, upon being exposed to a food cue, successful dieters spontaneously activate thoughts related to the ultimate goal of weight control, whereas unsuccessful dieters spontaneously activate hedonic food thoughts (Papies, Stroebe, & Aarts, 2007, 2008).
There is ample evidence to suggest that a significant part of daily eating behaviours consists of habits. In line with this, the concept of habit is increasingly incorporated into studies investigating the behavioural and psychosocial determinants of food choice, yielding evidence that habit is one of the most powerful predictors of eating behaviour. Research shows that habitual behaviour is fundamentally different from non-habitual behaviour: when behaviour is habitual, people require little information to make decisions, intentions are poor predictors of behaviour, and behaviour is triggered by situational cues. These insights have vast implications for research in the food domain that are only just beginning to be addressed. Also, theorizing on habits has important implications for behaviour change interventions, yet few interventions that are based on habit theory have been tested in a food context. The present article provides an overview of habit research and discusses possibilities to increase our knowledge of the role of habits in eating behaviour. It is shown that interventions targeting habitual behaviour can try to (i) change the situation that triggers the habitual behaviour, (ii) promote or inhibit the habitual response and (iii) change relevant contingencies. These insights can act as a starting point for future intervention research.

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^☆: Grants AG24490 from the National Institute of Aging and CA50087 from the National Cancer Institute supported this research.

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Transtheoretical principles and processes for quitting smoking: A 24-month comparison of a representative sample of quitters, relapsers, and non-quitters☆

Abstract

Section snippets

Sample

Quit rates and relapse rates

Discussion

Addictive Behaviors

Addictive Behaviors

Preventive Medicine

Preventive Medicine

Addictive Behaviors

Preventive Medicine

Patient Education and Counseling

Addictive Behaviors

Biochemical verification of tobacco use and cessation

Nicotine & Tobacco Research

Structural equations with latent variables

The most cited authors and papers in tobacco control

Tobacco Control

Both smoking reduction with nicotine replacement therapy and motivational advice increase future cessation among smokers unmotivated to quit

Journal of Consulting and Clinical Psychology

Community intervention trial for smoking cessation (COMMIT): I. Cohort results from a four-year community intervention

American Journal of Public Health

Self-efficacy and the stages of self change of smoking

Cognitive Therapy and Research

Structural confirmation of short form instruments for the transtheoretical model

Smoking Cessation

Treating tobacco use and dependence: Clinical practice guideline

Biochemical validation of smoking status in public health settings: Pros, cons and data from four low-intensity intervention trials

Addictive Behaviors