Main Findings
Research Questions: We conducted a meta-analysis of randomized controlled trials to address four questions:
(1) How effective are interventions in promoting intentions to quit smoking?
(2) Does changing quit intentions lead to smoking cessation?
(3) What factors (e.g., quit attempts, pharmacotherapy use) explain the relationship between quit intentions and smoking cessation? and
(4) Which intervention strategies promote quit intentions and the translation of quit intentions into smoking cessation?
Methods: Literature searches identified 13,262 records, and 172 interventions met the inclusion criteria. We contacted trial authors to obtain program materials and used a validated taxonomy to code the behavior change techniques (BCTs) that were deployed.
Results: Interventions had reliable effects on both quit intentions (d = 0.19, 95% CI [0.14, 0.24]) and smoking cessation (OR = 1.34, 95%CI [1.21, 1.48]). There was a linear relationship between changes in quit intention and rates of smoking cessation (B = 0.59, p < .001). On average, interventions that targeted quit intentions increased cessation rates from 10% to 15%.
Quit attempts mediated the relationship between changes in quit intentions and smoking cessation; pharmacotherapy use and engagement with smoking cessation services did not.
We obtained program materials for 83% of treatment and control arms. Using MetaForest, we identified 49 BCTs as predictors of quit intention change (e.g., Additions to environment, Problem-solving) and 27 predictors of smoking cessation. The BCTs that best predicted quit intentions were:
Additions to environment (e.g., wrapping cigarette packs in paper to generate friction), Information on antecedents (i.e., identifying smoking triggers), Body targeted (e.g., deep breathing exercises), Positive reappraisals (e.g., adopt a positive perspective on quitting behavior) and Problem-solving (i.e., prompting strategies to overcome barriers and promote facilitating conditions).
Intention to quit was the most important predictor of smoking cessation. Key BCTs that also predicted smoking cessation were:
Self-monitoring, Assessing feelings about abstinence, and making Changes to [one’s] social environment,
Conclusions: Promoting intentions to quit is vital for successful smoking cessation. Several behavior change techniques are effective in promoting quit intentions.
Other Findings
Two other papers arose from the project: The first concerned authors’ willingness to share data; the second was a conceptual review of the relationship between intention and action.
Research Question: We investigated how often authors provide trial data upon request.
Method: We requested data for 189 studies (167 authors) . Authors were contacted via email up to 4 times. We tracked responses, reasons for not sharing data, and coded 23 features of the author team (eg, number of authors and h-index), the request (eg, amount of information requested), and the study (eg, year of publication and preregistration).
Results: Thirty-five percent of authors provided the requested data, 21% responded but did not provide data, and 44% never responded to our request. Of the 37 reasons offered for not sharing data, the most common were loss of access to data (76%) and lack of time (11%). Morerecent trials, fewer citations, publication in medical (vs. behavioral) journals, and study preregistration were each associated with providing the requested data (Ps < .05).
Conclusions: Contacting authors for unpublished data resulted in a moderate response rate (56%) and modest provision of data (35%). Barriers to data sharing such as access and time constraints highlight challenges faced by behavioral health researchers in promoting transparency. The factors associated with responsiveness underscore the importance of journal policies and Open Science practices in enhancing data sharing.
Abstract: Most of us know the road to hell too well – we intend to do things but fail to do them. For instance, writing this paper has been a goal for far too many years. Drawing upon much self-recrimination, multiple meta-analysis, and a mushrooming empirical literature, this paper offers an overview of research on the intention-behavior gap. We demarcate the chasm between intentions and action using evidence from correlational studies, decompositions, simulations, and experiments. Next, we consider measurement issues and discuss the distinctiveness of the intention construct. Most of the paper is devoted to conceptualizing the wide variety of factors that moderate intention-behavior relations in terms of the Caliber of intention and Feasibility of acting. Caliber of intention embraces multiple features – quality, structure, integrity, and integration – that improve the odds of intention realization. Feasibility becomes an issue as intentions meet reality. Are opportunities available, seen, and seized? Are obstacles recognized and overcome? And what capabilities are needed to get to grips with opportunities and obstacles? We close by offering the Model of Intention REalization (MIRE) as an initial step toward (a) integrating the myriad moderators in a mechanistic account of intention realization, and (b) outlining the scope of work that remains to be done.