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OBJECTIVES: To examine the associations between tobacco industry denormalisation (TID) beliefs and support for tobacco endgame policies. METHODS: A total of 2810 randomly selected adult respondents of population-based tobacco policy-related surveys (2018-2019) were included. TID beliefs (agree vs disagree/unsure) were measured by seven items: tobacco manufacturers ignore health, induce addiction, hide harm, spread false information, lure smoking, interfere with tobacco control policies and should be responsible for health problems. Score of each item was summed up and dichotomised (median=5, >5 strong beliefs; ≤5 weak beliefs). Support for tobacco endgame policies on total bans of tobacco sales (yes/no) and use (yes/no) was reported. Associations between TID beliefs and tobacco endgame policies support across various smoking status were analysed, adjusting for sociodemographics. RESULTS: Fewer smokers (23.3%) had strong beliefs of TID than ex-smokers (48.4%) and never smokers (48.5%) (p<0.001). Support for total bans on tobacco sales (74.6%) and use (76.9%) was lower in smokers (33.3% and 35.3%) than ex-smokers (74.3% and 77.9%) and never smokers (76.0% and 78.3%) (all p values<0.001). An increase in the number of TID beliefs supported was positively associated with support for a total ban on sales (adjusted risk ratio 1.06, 95% CI 1.05 to 1.08, p<0.001) and use (1.06, 95% CI 1.05 to 1.07, p<0.001). The corresponding associations were stronger in smokers than non-smokers (sales: 1.87 vs 1.25, p value for interaction=0.03; use: 1.78 vs 1.21, p value for interaction=0.03). CONCLUSION: Stronger TID belief was associated with greater support for total bans on tobacco sales and use. TID intervention may increase support for tobacco endgame, especially in current smokers.
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INTRODUCTION: Mobile interventions enable personalized behavioral support that could improve smoking cessation (SC) in smokers ready to quit. Scalable interventions, including unmotivated smokers, are needed. We evaluated the effect of personalized behavioral support through mobile interventions plus nicotine replacement therapy sampling (NRT-S) on SC in Hong Kong community smokers. METHODS: A total of 664 adult daily cigarette smokers (74.4% male, 51.7% not ready to quit in 30 days) were proactively recruited from smoking hotspots and individually randomized (1:1) to the intervention and control groups (each, n=332). Both groups received brief advice and active referral to SC services. The intervention group received 1-week NRT-S at baseline and 12-week personalized behavioral support through SC advisor-delivered Instant Messaging (IM) and a fully automated chatbot. The control group received regular text messages regarding general health at a similar frequency. Primary outcomes were carbon monoxide-validated smoking abstinence at 6 and 12 months post-treatment initiation. Secondary outcomes included self-reported 7-day point-prevalence and 24-week continuous abstinence, quit attempts, smoking reduction, and SC service use at 6 and 12 months. RESULTS: By intention-to-treat, the intervention group did not significantly increase validated abstinence at 6 months (3.9% vs 3.0%, OR=1.31; 95% CI: 0.57-3.04) and 12 months (5.4% vs 4.5%, OR=1.21; 95% CI: 0.60-2.45), as were self-reported 7-day point-prevalence abstinence, smoking reduction, and SC service use at 6 and 12 months. More participants in the intervention than control group made a quit attempt by 6 months (47.0% vs 38.0%, OR=1.45; 95% CI: 1.06-1.97). Intervention engagement rates were low, but engagement in IM alone or combined with chatbot showed higher abstinence at 6 months (adjusted odds ratios, AORs=4.71 and 8.95, both p<0.05). CONCLUSIONS: Personalized behavioral support through mobile interventions plus NRT-S did not significantly improve abstinence in community smokers compared to text only messaging. The suboptimal intervention engagement needs to be addressed in future studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04001972.
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INTRODUCTION: We examined the association of workplace smoking cessation (SC) support from employers, in addition to SC interventions, and smoking abstinence. METHODS: Smoking employees (≥1 cigarette daily, aged ≥18 years) from companies of various industries joined a workplace SC program in Hong Kong. Self-reported past 7-day point prevalence abstinence was measured at follow-up at 6 months. We assessed 14 types of workplace SC support with higher scores (range: 0-14) indicating greater support. Multivariable logistic regression examined the prospective association between workplace SC support and smoking abstinence, adjusting for intention to quit, nicotine dependence, self-efficacy of quitting, and sociodemographic characteristics. Average marginal effects were calculated to test if the association between overall workplace SC support and self-reported past 7-day PPA at follow-up at 6 months was modified by subgroups. We also interviewed employers from different companies to explore their perspectives of providing workplace SC support, and the data were analyzed by thematic analysis. RESULTS: In 383 participants who received a heath talk, a self-help SC booklet, and 15 text messages, greater workplace SC support was associated with smoking abstinence (AOR=1.32; 95% CI: 1.08-1.61), including support for smoke-free environment (AOR=1.51; 95% CI: 1.08-2.11) and for SC attempts/actions (AOR=1.93; 95% CI: 1.21-3.07). The association did not differ by sex, age, intention to quit, nicotine dependence, company size or company type. Qualitative interviews found that employers provided workplace SC support to establish a good company image, cost-benefit considerations were important to the types of workplace SC support provided, and lack of SC knowledge was a barrier to providing workplace SC support. CONCLUSIONS: Greater workplace SC support was associated with more abstinence in a workplace SC program.
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BACKGROUND: eHealth literacy can potentially facilitate web-based information seeking and taking informed measures. OBJECTIVE: This study aimed to evaluate socioeconomic disparities in eHealth literacy and seeking of web-based information on COVID-19, and their associations with COVID-19 preventive behaviors. METHODS: The COVID-19 Health Information Survey (CoVHIns), using telephonic (n=500) and web-based surveys (n=1001), was conducted among adults in Hong Kong in April 2020. The Chinese eHealth literacy scale (eHEALS; score range 8-40) was used to measure eHealth literacy. COVID-19 preventive behaviors included wearing surgical masks, wearing fabric masks, washing hands, social distancing, and adding water or bleach to the household drainage system. Adjusted beta coefficients and the slope indices of inequality for the eHEALS score by socioeconomic status, adjusted odds ratios (aORs) for seeking of web-based information on COVID-19 by socioeconomic status, and aORs for the high adherence to preventive behaviors by the eHEALS score and seeking of web-based information on COVID-19 were calculated. RESULTS: The mean eHEALS score was 26.10 (SD 7.70). Age was inversely associated with the eHEALS score, but education and personal income were positively associated with the eHEALS score and seeking of web-based information on COVID-19 (for all, P for trend<.05). Participants who sought web-based information on COVID-19 showed high adherence to the practice of wearing surgical masks (aOR 1.56, 95% CI 1.15-2.13), washing hands (aOR 1.33, 95% CI 1.05-1.71), social distancing (aOR 1.48, 95% CI 1.14-1.93), and adding water or bleach to the household drainage system (aOR 1.67, 95% CI 1.28-2.18). Those with the highest eHEALS score displayed high adherence to the practice of wearing surgical masks (aOR 3.84, 95% CI 1.63-9.05), washing hands (aOR 4.14, 95% CI 2.46-6.96), social distancing (aOR 2.25, 95% CI 1.39-3.65), and adding water or bleach to the household drainage system (aOR 1.94, 95% CI 1.19-3.16), compared to those with the lowest eHEALS score. CONCLUSIONS: Chinese adults with a higher socioeconomic status had higher eHealth literacy and sought more web-based information on COVID-19; both these factors were associated with a high adherence to the guidelines for preventive behaviors during the COVID-19 pandemic.
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COVID-19/epidemiologia , Letramento em Saúde/métodos , SARS-CoV-2/isolamento & purificação , Telemedicina/métodos , Adulto , Estudos Transversais , Feminino , Inquéritos Epidemiológicos/métodos , Hong Kong/epidemiologia , Humanos , Masculino , Pandemias , Fatores SocioeconômicosRESUMO
BACKGROUND: Inequalities in health information seeking behaviors (HISBs) using mass media and internet websites (web 1.0) are well documented. Little is known about web 2.0 such as social networking sites (SNS) and instant messaging (IM) and experiences of HISBs. METHODS: We surveyed representative Hong Kong Chinese adults (N = 10143, 54.9% female; 72.3% aged 25-64 years) on frequency of HISBs using traditional sources, internet websites, SNS (e.g., Facebook, Twitter), and IM (e.g., WhatsApp, WeChat) and experiences measured using Information Seeking Experience Scale. Adjusted prevalence ratios (aPRs) for HISBs and experiences by sociodemographic and health-related characteristics were yielded using multivariable Poisson regression with robust variance estimators. aPRs for experiences by HISBs using internet websites, SNS, and IM adjusting for sociodemographic and health-related characteristics were also yielded. RESULTS: Being female, higher educational attainment, not smoking, and being physically active were associated with HISBs using any source (all P<0.05). Older age had decreased aPRs for HISBs using traditional sources (P for trend = 0.03), internet websites (P for trend<0.001), and SNS (P for trend<0.001) but not for IM (aged 45-64 years: aPR = 1.48, 95% CI 1.07, 2.03). Lower educational attainment and income were associated with negative experiences including feelings of effort and difficulties in understanding the information (all P for trend<0.05). Older age had increased aPRs for difficulties in understanding the information (P for trend = 0.003). Compared with internet websites, HISBs using IM was associated with feelings of frustration (aPR = 1.39, 95% CI 1.08, 1.79), difficulties in understanding the information (aPR = 1.36, 95% CI 1.12, 1.65), and quality concern (aPR = 1.20, 95% CI 1.08, 1.32). CONCLUSIONS: We identified correlates of web-based health information seeking and experiences in Hong Kong Chinese adults. Providing greater access to and improved information environment of web 2.0 to the target groups may help address digital inequalities.