Background Decision aids (DAs) may be used to facilitate an autonomous, informed decision to cease smoking and promote the uptake of evidence-based cessation assistance (ie, behavioral support, nicotine replacement therapy, or prescription medication). However, knowledge is lacking regarding their effective elements and (cost-)effectiveness. Objective We describe the development process of an online DA (called “VISOR”) that helps smokers to choose evidence-based cessation assistance. Additionally, we provide a description of the protocol of an ongoing randomized controlled trial in which the DA containing an explicit value clarification method (VCM) and tailored advice is compared with a DA without an explicit VCM and tailored advice. Methods The development of “VISOR” was based on the International Patient Decision Aid Standards guidelines. Viewpoints of end users (collected through 20 interviews with smokers) and clinical and scientific experts (assessed using 2 Delphi studies with 24 scientists and 38 clinicians) were assessed regarding cessation tool decision making and preferred DA content. These findings, together with principles from the Self-Determination Theory, served as input for the development of the online DA. A first DA prototype was alpha-tested in September 2019 and beta-tested for usability in December 2019; feedback was incorporated and resulted in a final version. The final DA contains (1) an information section, (2) an optional knowledge quiz, (3) a brief smoking assessment, (4) intuitive decision, (5) intermediate advice, (6) an explicit VCM, (7) tailored advice, and (8) access information. A randomized controlled trial is currently being conducted to assess the DA’s (cost-)effectiveness compared to a DA that does not include the explicit VCM and the tailored advice; specifically, the DA’s effect on smoking abstinence, uptake of evidence-based cessation assistance, smoking abstinence mediated through uptake of evidence-based cessation assistance, and decisional conflict are investigated. Participants are randomly allocated to receive access to 1 of the 2 DAs and are asked to complete 5 questionnaires (including the baseline questionnaire) over a period of 12 months. To evaluate the effects of the DA on the outcome measures, logistic and linear regression analyses as well as mediation analyses will be carried out. An economic evaluation will be performed to assess the cost-effectiveness. Results Data regarding the effect of the VISOR DA are currently being collected, and data collection is expected to be concluded in 2021. Conclusions By making use of an iterative process that integrated different stakeholders’ perspectives (including end users), we were able to systematically design an evidence-based DA. The study will contribute to the current knowledge regarding smoking cessation DA application, the added value of explicit VCMs, and the effect of behavioral and informed decision-making outcomes. Trial Registration Netherlands Trial Register NL8270; https://www.trialregister.nl/trial/8270 International Registered Report Identifier (IRRID) DERR1-10.2196/21772

To conduct an economic evaluation of a tailored e-learning program, which successfully improved practice nurses' smoking cessation guideline adherence. Methods: The economic evaluation was embedded in a randomized controlled trial, in which 269 practice nurses recruited 388 smoking patients. Cost-effectiveness was assessed using guideline adherence as effect measure on practice nurse level, and continued smoking abstinence on patient level. Cost-utility was assessed on patient level, using patients' Quality Adjusted Life Years (QALYs) as effect measure. Results: The e-learning program was likely to be cost-effective on practice nurse level, as adherence to an additional guideline step cost s1,586. On patient level, cost-effectiveness was slightly likely after six months (cost per additional quitter: s7,126), but not after twelve months. The cost-utility analysis revealed slight cost-effectiveness (cost per QALY gained: s18,431) on patient level. Conclusion: Providing practice nurses with a tailored e-learning program is cost-effective to improve their smoking cessation counseling. Though, cost-effectiveness on patient level was not found after twelve months, potentially resulting from smoking relapse. Practice implications: Widespread implementation of the e-learning program can improve the quality of smoking cessation care in general practice. Strategies to prevent patients' smoking relapse should be further explored to improve patients' long-term abstinence.

Objectives Evidence-based smoking cessation support tools (EBSTs) can double the quitting chances, but uptake among smokers is low. A digital decision aid (DA) could help smokers choose an EBST in concordance with their values and preferences, but it is unclear which type of smokers are interested in a digital DA. We hypothesized that smokers’ general decision-making style (GDMS) could be used to identify early adopters. This study therefore aimed to identify smoker profiles based on smokers’ GDMS and investigate these profiles’ association with intention to use a digital DA. Design A cross-sectional dataset (N = 200 smokers intending to quit) was used to perform a hierarchical cluster analysis based on smokers’ GDMS scores. Methods Clusters were compared on demographic and socio-cognitive variables. Mediation analyses were conducted to see if the relationship between cluster membership and intention was mediated through socio-cognitive variables (e.g., attitude). Results Two clusters were identified; “ Avoidant Regretters ” (n = 134) were more avoidant, more regretful and tended to depend more on others in their decision making, while “ Intuitive Non-regretters ” (n = 66) were more spontaneous and intuitive in their decision making. Cluster membership was significantly related to intention to use a DA, with “ Avoidant Regretters ” being more interested. Yet, this association ceased to be significant when corrected for socio-cognitive variables (e.g., attitude). This indicates that cluster membership affected intention via socio-cognitive variables. Conclusions The GDMS can be used to identify smokers who are interested in a digital DA early on. As such, the GDMS can be used to tailor recruitment and DA content.

Evidence-based cessation assistance increases cessation rates. Activating preferences during decision making could improve effectiveness further. Decision aids (DAs) facilitate deciding by taking preferences into account. To develop effective DAs, potential end users' (i.e., individuals motivated to quit) needs and experts' viewpoints should be considered. Therefore, the aim of this needs assessment was: (1) To explore end users' needs and (2) to obtain consensus among smoking cessation counsellors and scientific experts to develop a self-administered DA to support end users in choosing cessation assistance. Data was gathered via two approaches: (1) twenty semi-structured interviews with potential end users and (2) two three-round Delphi studies with 61 counsellors and 44 scientific experts. Interview data and the first Delphi rounds were analysed qualitatively, the other Delphi rounds were analysed quantitatively. Potential end users acquired information in different ways, e.g., via own experiences. Important characteristics to decide between tools varied, however effectiveness and costs were commonly reported. Experts reached consensus on 38 and 40 statements, e.g., tools should be appropriate for users' addiction level. Although some trends emerged, due to the variation among stakeholders, a 'one size fits all'-approach is undesirable. This heterogeneity should be considered, e.g., by enabling users to customise the DA.

Introduction: Evidence-based cessation assistance is known to increase cessation rates. Activating personal preferences as part of the decision for smoking cessation assistance tools could further improve tools' effectiveness. Decision aids (DAs) help individuals to choose amongst the various options by taking these preferences into account and, therefore, could have a positive effect on cessation rates. To develop attractive and effective DAs, potential end users' needs, and experts' viewpoints should be considered during development processes. Therefore, the aim of this study was: (1) To explore smokers' needs and viewpoints regarding a smoking cessation assistance DA, and (2) to obtain consensus among smoking cessation counsellors and scientific experts about the content and format of such a DA. Materials and methods: Data was gathered via two approaches applied across three studies: (1) 20 semi-structured interviews with potential end users, (2) two three-round Delphi studies with 61 smoking cessation counsellors and 44 scientific experts. Data from the interviews and the first round of the Delphi studies were analysed qualitatively using the Framework method, while data from the second and third round of the Delphi studies were analysed quantitatively using medians and interquartile ranges. Results: Potential end users reported to acquire information in different ways: Via own experiences, their social environment, and the media. Important characteristics to decide between tools also varied, however effectiveness and costs were commonly reported as the most important characteristics. The experts reached consensus on 38 and 40 statements (respectively) regarding important cessation assistance tools' characteristics and their viewpoints on a smoking cessation assistance DA, e.g., that a tool should be appropriate for users' level of addiction. Discussion and conclusion: Some clear trends emerged among the potential end users (especially regarding important characteristics). Experts also reached consensus among a number of statements. However, there was some variation in the needs and wishes among the (different) stakeholders. The combination of these studies highlights that a 'one size fits all' approach is not desirable. In the development of DAs, this heterogeneity should be taken into account, e.g., by enabling users to customize a DA based on their personal preferences while safeguarding essential elements.