Thomas Gültzow, Eline S. Smit, Raesita Hudales, Carmen D. Dirksen, Ciska Hoving

Informed Decision Making on the Uptake of Evidence-Based Smoking Cessation Assistance by Individuals Motivated to Quit Smoking

Introduction

Informed decision making on the uptake of evidence-based smoking cessation assistance by individuals motivated to quit smoking. Discover research on developing a personalized decision aid for individuals motivated to quit smoking. This study assesses user & expert needs to help choose effective, evidence-based cessation assistance.

Abstract

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.

Review

This study addresses a critical area in public health: enhancing informed decision-making for individuals seeking to quit smoking using evidence-based cessation assistance. Recognizing that current support, while effective, could be improved by better aligning with user preferences, the authors undertake a comprehensive needs assessment. The core aim is to gather perspectives from both potential end-users (motivated individuals) and expert stakeholders (counsellors and scientific experts) to inform the development of a self-administered decision aid (DA). This foundational work is highly relevant as it seeks to leverage individual preferences to potentially improve the uptake and effectiveness of cessation tools, thereby contributing to better public health outcomes. The methodology employed is robust, utilizing a mixed-methods approach to ensure a multi-faceted understanding of the landscape. Data was systematically gathered through twenty semi-structured interviews with potential end-users, complemented by two three-round Delphi studies involving a substantial number of smoking cessation counsellors (61) and scientific experts (44). Qualitative analysis of interview data and initial Delphi rounds, followed by quantitative analysis of subsequent Delphi rounds, provided rich insights. Key findings revealed that end-users acquire information through diverse channels, including personal experiences, and prioritize varied characteristics for cessation tools, though effectiveness and cost were common concerns. Experts, on the other hand, reached consensus on specific tool attributes, such as appropriateness for addiction level. Crucially, the study highlighted significant heterogeneity among stakeholders, leading to the conclusion that a 'one-size-fits-all' approach for a decision aid is undesirable. A significant strength of this research lies in its comprehensive stakeholder engagement and mixed-methods design, which provides a rich and nuanced understanding of the complexities involved in choosing smoking cessation assistance. By synthesizing end-user needs with expert consensus, the study lays a solid groundwork for developing a truly user-centered decision aid. The finding of considerable variation in user preferences and information-seeking behaviours is particularly impactful, underscoring the necessity for a highly flexible and customizable DA. This strongly suggests that future iterations of the DA must enable users to tailor the tool to their specific needs and priorities, moving beyond generic advice. The insights generated from this needs assessment are invaluable for guiding the design and implementation of effective digital health interventions in smoking cessation, potentially increasing engagement and ultimately improving quit rates.

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