TY  - JOUR
AU  - Gültzow, Thomas
AU  - Smit, Eline Suzanne
AU  - Crutzen, Rik
AU  - Jolani, Shahab
AU  - Hoving, Ciska
AU  - Dirksen, Carmen D
PY  - 2022
DA  - 2022/7/15
TI  - Effects of an Explicit Value Clarification Method With Computer-Tailored Advice on the Effectiveness of a Web-Based Smoking Cessation Decision Aid: Findings From a Randomized Controlled Trial
JO  - J Med Internet Res
SP  - e34246
VL  - 24
IS  - 7
KW  - digital health
KW  - decision-making
KW  - decision support technique
KW  - decision aid
KW  - smoking
KW  - smoking cessation
KW  - informed decision-making
KW  - decision support
KW  - decision support tool
KW  - eHealth
KW  - evidence-based medicine
KW  - value clarification method
AB  - Background: Smoking continues to be a driver of mortality. Various forms of evidence-based cessation assistance exist; however, their use is limited. The choice between them may also induce decisional conflict. Offering decision aids (DAs) may be beneficial; however, insights into their effective elements are lacking. Objective: This study tested the added value of an effective element (ie, an “explicit value clarification method” paired with computer-tailored advice indicating the most fitting cessation assistance) of a web-based smoking cessation DA. Methods: A web-based randomized controlled trial was conducted among smokers motivated to stop smoking within 6 months. The intervention group received a DA with the aforementioned elements, and the control group received the same DA without these elements. The primary outcome measure was 7-day point prevalence abstinence 6 months after baseline (time point 3 [t=3]). Secondary outcome measures were 7-day point prevalence of abstinence 1 month after baseline (time point 2 [t=2]), evidence-based cessation assistance use (t=2 and t=3), and decisional conflict (immediately after DA; time point 1). Logistic and linear regression analyses were performed to assess the outcomes. Analyses were conducted following 2 (decisional conflict) and 3 (smoking cessation) outcome scenarios: complete cases, worst-case scenario (assuming that dropouts still smoked), and multiple imputations. A priori sample size calculation indicated that 796 participants were needed. The participants were mainly recruited on the web (eg, social media). All the data were self-reported. Results: Overall, 2375 participants were randomized (intervention n=1164, 49.01%), of whom 599 (25.22%; intervention n=275, 45.91%) completed the DAs, and 276 (11.62%; intervention n=143, 51.81%), 97 (4.08%; intervention n=54, 55.67%), and 103 (4.34%; intervention n=56, 54.37%) completed time point 1, t=2, and t=3, respectively. More participants stopped smoking in the intervention group (23/63, 37%) than in the control group (14/52, 27%) after 6 months; however, this was only statistically significant in the worst-case scenario (crude P=.02; adjusted P=.04). Effects on the secondary outcomes were only observed for smoking abstinence after 1 month (15/55, 27%, compared with 7/46, 15%, in the crude and adjusted models, respectively; P=.02) and for cessation assistance uptake after 1 month (26/56, 46% compared with 18/47, 38% only in the crude model; P=.04) and 6 months (38/61, 62% compared with 26/50, 52%; crude P=.01; adjusted P=.02) but only in the worst-case scenario. Nonuse attrition was 34.19% higher in the intervention group than in the control group (P<.001). Conclusions: Currently, we cannot confidently recommend the inclusion of explicit value clarification methods and computer-tailored advice. However, they might result in higher nonuse attrition rates, thereby limiting their potential. As a lack of statistical power may have influenced the outcomes, we recommend replicating this study with some adaptations based on the lessons learned. Trial Registration: Netherlands Trial Register NL8270; https://www.trialregister.nl/trial/8270 International Registered Report Identifier (IRRID): RR2-10.2196/21772 
SN  - 1438-8871
UR  - https://www.jmir.org/2022/7/e34246
UR  - https://doi.org/10.2196/34246
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35838773
DO  - 10.2196/34246
ID  - info:doi/10.2196/34246
ER  -