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January 20, 2026Addiction0 citations

Quitting trajectories of Hong Kong Chinese smokers receiving behavioral smoking cessation interventions: A post hoc analysis of eight randomized controlled trials

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YZYingpei ZengYWYongda Socrates WuLTLuk Tzu Tsun

Key Points

  • This research aims to identify distinct quitting trajectories among Hong Kong Chinese smokers participating in behavioral cessation interventions.
  • Analyzed data from eight randomized controlled trials of smoking cessation from 2014 to 2021.
  • Tracked 8300 adult smokers' daily cigarette consumption and follow-ups at 1, 2, 3, and 6 months.
  • Utilized group-based trajectory modeling to identify quitting patterns based on consumption changes.
  • Applied multinomial logistic regression to assess associations with baseline smoking-related characteristics.
  • Identified four quitting trajectories: quitters (4.6%), relapsers (6.8%), reducers (54.8%), and persistent smokers (33.8%).
  • Quitters and relapsers had lower nicotine dependence compared to persistent smokers; reducers had higher dependence.
  • Relapsers exhibited greater intention and perceived importance of quitting than quitters, while reducers showed lower intention and confidence.

Abstract

Abstract Background and aims Characterizing distinct quitting trajectories may inform tailored behavioral smoking cessation interventions. We identified the quitting trajectories and associated characteristics in Hong Kong Chinese smokers. Methods Data were from eight randomized controlled trials nested within the annual Smoking‐free Community Campaign (‘Quit‐to‐Win’ Contest) from 2014 to 2021. The trials were two‐ or three‐arm evaluating the effectiveness of behavioral smoking cessation interventions in 8300 adult daily smokers who were proactively recruited from communities across Hong Kong and followed‐up at 1, 2, 3 and 6 months. Daily cigarette consumption was collected at baseline and follow‐ups for identifying quitting trajectories by group‐based trajectory modeling based on relative changes in cigarette consumption (vs. baseline) over four follow‐up assessment points. Multinomial logistic regressions were used to yield relative risk ratios (RRRs) for the trajectories by baseline smoking‐related characteristics, adjusting for sex, age, economic status and education attainment. Results Four quitting trajectories were identified, including quitters (4.6%), relapsers (6.8%), reducers (54.8%) and persistent smokers (33.8%). Compared with persistent smokers, smokers in the other 3 trajectories were associated with having previous quit attempts, higher intention to quit and perceived higher importance and confidence in quitting (all P < 0.05). Quitters adjusted RRR (aRRR) = 0.59, 95% confidence interval (CI) = 0.62–1.00 and relapsers (aRRR = 0.75, 95% CI = 0.61–0.91) reported lower nicotine dependence vs. persistent smokers, whereas reducers showed higher nicotine dependence (aRRR = 1.39, 95% CI = 1.25–1.55) at baseline. Relapsers and reducers perceived higher difficulty of quitting (all P < 0.05). When compared with quitters, relapsers had higher intention to quit within 7 days (aRRR = 2.32, 95% CI = 1.64–3.28) and perceived higher importance (aRRR = 1.17, 95% CI = 1.09–1.25) and confidence (aRRR = 1.10, 95% CI = 1.04–1.17) in quitting, while reducers showed lower intention to quit within 7 days (aRRR = 0.59, 95% CI = 0.45–0.77) and perceived lower confidence in quitting (aRRR = 0.91, 95% CI = 0.86–0.95). Subgroup analysis of different interventions showed similar trajectory shapes and group probabilities. Conclusions Chinese smokers who joined behavioral smoking cessation trials in Hong Kong appear to have four quitting trajectories, each with associated characteristics, which may help predict the potential quitting trajectories and inform future interventions.

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Cite This Study

Zeng et al. (2026) studied this question.

synapsesocial.com/papers/696f1b189e64f732b51ef199https://doi.org/10.1111/add.70328
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