Using tailored eHealth programmes to stimulate primary health care professionals' lifestyle counselling guideline adherence - Lessons learned from the STAR project.

BACKGROUND: Although individually tailored eHealth programmes have shown to be effective in changing patient and citizen health behaviours, they have so far not been applied to lifestyle counselling guideline adherence in primary health care professionals beyond our STAR project. The programme aimed to support general practice nurses adhering to national smoking cessation counselling guidelines and showed encouraging positive impacts on both nurse and patient level. OBJECTIVE: To identify lessons learned from our successful application of a tailored eHealth programme in primary health care. METHODS: Triangulation of information from different sources collected throughout the project run time (e.g., project meetings, discussions with experts in the fields of computer tailoring, smoking cessation and professional education and interactions with general practice nurses). RESULTS: We identify four lessons learned which developers and testers of tailored eHealth programmes in primary health care should consider, relating to 1) Choosing outcome measures, 2) Measuring outcomes, 3) Practical feedback application & Programme accessibility, and 4) Programme interaction. PRACTICE IMPLICATIONS: We share this information in the hope that we will see more applications of this promising intervention strategy - that can build on our work - in the future.

Active Ingredients of Interventions Improving Smoking Cessation Support by Dutch Primary Care Providers: A Systematic Review.

The objective was to assess active ingredients, change mechanisms, and fidelity in interventions aiming to increase the quality of smoking cessation care in the Dutch primary healthcare setting. We conducted a systematic review searching five scientific databases on August 2nd, 2019, updated on October 28th, 2021. We included effect data of behavioural interventions aiming at improving the provision of smoking cessation support by Dutch primary care providers to their patients. We excluded studies published before 2000 and those without a behavioural support intervention for primary care providers targeting smoking cessation in their patients. We found 1939 articles and included 15 distinct interventions in the review. We provided an overview of study characteristics, intervention effects, fidelity, active ingredients and change mechanisms using the Behaviour Change Techniques (BCT) Taxonomy and Mechanisms of Action (MoAs) protocols. Interventions seemed more effective when including a face-to-face component, using active learning strategies and providing a tool to help follow the guidelines in practice (e.g., physical cards with information). BCTs, MoAs, and fidelity were overall poorly reported on. To support the application of smoking cessation practices in Dutch primary care, we recommend implementation of face-to-face training programs incorporating active skill training elements combined with practical tools.

Identifying Active Ingredients, Working Mechanisms, and Fidelity Characteristics Reported in Smoking Cessation Interventions in Dutch Primary Care: A Systematic Review.

BACKGROUND: Evidence-based smoking cessation interventions provided by healthcare professionals can be successful in helping citizens to quit smoking. Yet, evidence is needed about the active ingredients of these interventions, how these ingredients work and how they are implemented in practice. Such knowledge is required to effectively support healthcare professionals to optimally put evidence-based smoking cessation interventions to (inter)national practice. OBJECTIVE: To identify active ingredients (including behavior change techniques), mechanisms of action and implementation fidelity reported in smoking cessation interventions in Dutch primary care settings and to relate these to intervention effectiveness. METHODS: A systematic review was conducted by searching nine national intervention or funding databases, five international scientific databases and consulting 17 national smoking cessation experts. Out of 1066 identified manuscripts, 40 interventions were eligible for this review. Based on published protocols, information regarding behavior change techniques and mechanisms of action was systematically abstracted. Additionally, information regarding study characteristics and other active ingredients, effects on smoking behavior and implementation fidelity was abstracted. Comparative effectiveness concerning abstracted intervention characteristics was qualitatively explored. RESULTS: Active ingredients, mechanisms of action and implementation fidelity were moderately to poorly reported. Interventions applying behavior change techniques and interventions with a single behavioral target (i.e. smoking-only versus multiple behaviors) seemed to provide stronger evidence for successfully changing smoking behavior. CONCLUSION: Attention to and reporting on interventions' active ingredients (e.g. behavior change techniques), mechanisms of action and implementation fidelity are prerequisites for developing more effective evidence-based smoking cessation interventions to be successfully implemented in primary healthcare. IMPLICATIONS: This systematic review provides an overview of smoking cessation interventions in Dutch primary care settings, identified since the year 2000. Smoking cessation support is offered in various forms, but our qualitative findings show that interventions including more behavior change techniques and interventions targeting only smoking cessation (compared to multiple behaviors) might be more effective. Results also show that-based on available intervention reports-it is difficult to distinguish patterns of active ingredients (such as behavior change techniques), mechanisms of action and fidelity of implementation in relation to interventions' effectiveness. This means (quality of) reporting on these intervention characteristics should improve.

An economic evaluation of a computer-tailored e-learning program to promote smoking cessation counseling guideline adherence among practice nurses.

OBJECTIVE: 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 €1,586. On patient level, cost-effectiveness was slightly likely after six months (cost per additional quitter: €7,126), but not after twelve months. The cost-utility analysis revealed slight cost-effectiveness (cost per QALY gained: €18,431) 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.

The Effectiveness of a Computer-Tailored E-Learning Program for Practice Nurses to Improve Their Adherence to Smoking Cessation Counseling Guidelines: Randomized Controlled Trial.

BACKGROUND: Improving practice nurses' (PN) adherence to smoking cessation counseling guidelines will benefit the quality of smoking cessation care and will potentially lead to higher smoking abstinence rates. However, support programs to aid PNs in improving their guideline uptake and adherence do not exist yet. OBJECTIVE: The aim of this study was to assess the effects of a novel computer-tailored electronic learning (e-learning) program on PNs' smoking cessation guideline adherence. METHODS: A Web-based randomized controlled trial (RCT) was conducted in which an intervention group (N=147) with full access to the e-learning program for 6 months was compared with a control group (N=122) without access. Data collection was fully automated at baseline and 6-month follow-up via online questionnaires, assessing PNs' demographics, work-related factors, potential behavioral predictors based on the I-Change model, and guideline adherence. PNs also completed counseling checklists to retrieve self-reported counseling activities for each consultation with a smoker (N=1175). To assess the program's effectiveness in improving PNs' guideline adherence (ie, overall adherence and adherence to individual counseling guideline steps), mixed linear and logistic regression analyses were conducted, thus accommodating for the smokers being nested within PNs. Potential effect moderation by work-related factors and behavioral predictors was also examined. RESULTS: After 6 months, 121 PNs in the intervention group (82.3%, 121/147) and 103 in the control group (84.4%, 103/122) completed the follow-up questionnaire. Mixed linear regression analysis revealed that counseling experience moderated the program's effect on PNs' overall guideline adherence (beta=.589; 95% CI 0.111-1.068; PHolm-Bonferroni =.048), indicating a positive program effect on adherence for PNs with a more than average level of counseling experience. Mixed logistic regression analyses regarding adherence to individual guideline steps revealed a trend toward moderating effects of baseline levels of behavioral predictors and counseling experience. More specifically, for PNs with less favorable scores on behavioral predictors (eg, low baseline self-efficacy) and high levels of counseling experience, the program significantly increased adherence. CONCLUSIONS: Results from our RCT showed that among PNs with more than average counseling experience, the e-learning program resulted in significantly better smoking cessation guideline adherence. Experienced PNs might have been better able to translate the content of our e-learning program into practically applicable counseling strategies compared with less experienced colleagues. Less favorable baseline levels of behavioral predictors among PNs possibly contributed to this effect, as there was more room for improvement by consulting the tailored content of the e-learning program. To further substantiate the effectiveness of e-learning programs on guideline adherence by health care professionals (HCPs), it is important to assess how to support a wider range of HCPs. TRIAL REGISTRATION: Netherlands Trial Register NTR4436; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4436 (Archived by WebCite at http://www.webcitation.org/6zJQuSRq0).

Exploring consensus on how to measure smoking cessation. A Delphi study.

BACKGROUND: Different criteria regarding outcome measures in smoking research are used, which can lead to confusion about study results. Consensus in outcome criteria may enhance the comparability of future studies. This study aims (1) to provide an overview of tobacco researchers' considered preferences regarding outcome criteria in randomized controlled smoking cessation trials, and (2) to identify the extent to which researchers can reach consensus on the importance of these outcome criteria. METHODS: A three-round online Delphi study was conducted among smoking cessation experts. In the first round, the most important smoking cessation outcome measures were collected by means of open-ended questions, which were categorized around self-reported and biochemical validation measures. Experts (n = 17) were asked to name the outcome measures (as well as their assessment method and ideal follow-up period) that they thought were important when assessing smoking-related outcomes. In the second (n = 48) and third rounds (n = 37), a list of outcome measures-identified in the first round-was presented to experts. Asking them to rate the importance of each measure on a seven-point scale. RESULTS: Experts reached consensus on several items. For self-reports, experts agreed that prolonged abstinence (6 or/and 12 months), point prevalence abstinence (7 days), continuous abstinence (6 months), and the number of cigarettes smoked (7 days) are important outcome measures. Experts reached consensus that biochemical validation methods should not always be used. The preferred biochemical validation methods were carbon monoxide (expired air) and cotinine (saliva). Preferred follow-ups included 6 and/or 12 months, with or without intermediate measurements. CONCLUSIONS: Findings suggest only partial compliance with the Russell standard and that more outcome measures may be important (including seven-day point-prevalence abstinence, number of cigarettes smoked, and cotinine when using biochemical validation). This study showed where there is and is not consensus, reflecting the need to develop a more comprehensive standard. For these purposes we provided suggestions for the Russell 2.0 standard.

Dutch practice nurses' adherence to evidence-based smoking cessation treatment guidelines.

Background: Practice nurses in general practice sub-optimally adhere to evidence-based smoking cessation treatment guidelines, but factors explaining their adherence have not yet been investigated. Understanding such factors is important to develop interventions improving practice nurses' smoking cessation guideline adherence and patients' subsequent cessation success. This study explored the association between different socio-cognitive and predisposing factors, and practice nurses' adherence to the Dutch smoking cessation guideline in general (i.e. overall adherence) and to each guideline step individually (i.e. step-based adherence). Methods: A cross-sectional study was conducted among practice nurses (N = 157) in January-March 2015 via web-based questionnaires, assessing constructs from the Integrated Change Model. Spearman's correlations and linear regression analysis were used to identify potential determinants of overall guideline adherence; Mann-Whitney U-tests and logistic regression analyses were used to identify potential determinants of step-based adherence. Results: On average five out of nine steps were completely adhered to by practice nurses; and step-based adherence ranged from 34% to 75%. Overall guideline adherence was associated with high levels of self-efficacy to use a guideline (ß = 0.32, P = 0.00), and step-based adherence was additionally associated with spending more time on counselling. Regression results showed positive associations between self-efficacy (8/9 steps) and perceived advantages (7/9 steps) with step-based adherence. Conclusion: This study quantitatively confirmed practice nurses' sub-optimal guideline adherence and found associations between socio-cognitive (self-efficacy and perceived advantages) and predisposing factors (time spent on counselling), and guideline adherence. Detailed insights in these factors offer preliminary directions for intervention development to improve practice nurses' adherence to evidence-based smoking cessation guidelines.