|
covid-19 |
40 |
|
smoking cessation |
37 |
|
instant messaging |
26 |
|
smoking |
24 |
|
mental health |
23 |
|
chinese |
20 |
|
mhealth |
20 |
|
public health |
18 |
|
tobacco |
18 |
|
health literacy |
17 |
|
depression |
15 |
|
family well-being |
15 |
|
anxiety |
14 |
|
community smoker |
14 |
|
addiction |
13 |
|
cessation |
13 |
|
epidemiology |
13 |
|
face mask |
13 |
|
hong kong |
13 |
|
parenting |
13 |
|
adolescents |
12 |
|
ehealth |
12 |
|
brief intervention |
11 |
|
electronic cigarettes |
11 |
|
family |
11 |
|
family wellbeing |
11 |
|
text messaging |
11 |
|
tobacco use |
11 |
|
women's health |
11 |
|
active referral |
10 |
|
adolescent |
10 |
|
breastfeeding |
10 |
|
coping |
10 |
|
coronavirus |
10 |
|
insomnia |
10 |
|
mobile health |
10 |
|
mobile phone |
10 |
|
nicotine |
10 |
|
randomized controlled trial |
10 |
|
service use |
10 |
|
social media |
10 |
|
surveillance and monitoring |
10 |
|
tobacco control |
10 |
|
well-being |
10 |
|
incentive |
9 |
|
information and communication technologies |
9 |
|
prevention |
9 |
|
relapse prevention |
9 |
|
risk perception |
9 |
|
smartphone |
9 |
|
smoker |
9 |
|
stress |
9 |
|
whatsapp |
9 |
|
adaptive trial |
8 |
|
clinical trial |
8 |
|
family communication |
8 |
|
handgrip |
8 |
|
infodemic |
8 |
|
infodemiology |
8 |
|
lay counsellor |
8 |
|
life satisfaction |
8 |
|
nursing students |
8 |
|
perceived benefit |
8 |
|
perceived harm |
8 |
|
prevalence |
8 |
|
questionnaires |
8 |
|
risk factors |
8 |
|
stepped care |
8 |
|
surveys |
8 |
|
tobacco products |
8 |
|
vaccine hesitancy |
8 |
|
workplace |
8 |
|
advertising and promotion |
7 |
|
attitudes |
7 |
|
chat groups |
7 |
|
chat intervention |
7 |
|
children |
7 |
|
coronavirus disease |
7 |
|
e-cigarettes |
7 |
|
edevice |
7 |
|
electronic cigarette |
7 |
|
family dinner |
7 |
|
family functioning |
7 |
|
hookah |
7 |
|
infection control behaviours |
7 |
|
information sharing |
7 |
|
media |
7 |
|
mental well-being |
7 |
|
meta-analysis |
7 |
|
mindfulness training |
7 |
|
mobile instant messaging |
7 |
|
passive smoking |
7 |
|
policy |
7 |
|
population study |
7 |
|
population-based study |
7 |
|
preventive measures |
7 |
|
problematic smartphone use |
7 |
|
quit attempt |
7 |
|
screen time |
7 |
|
sex education |
7 |
|
sexual health |
7 |
|
sleep problems |
7 |
|
subjective well-being |
7 |
|
systematic review |
7 |
|
unemployment |
7 |
|
waterpipe smoking |
7 |
|
woman smoker |
7 |
|
adult |
6 |
|
ambassadors |
6 |
|
child maltreatment |
6 |
|
community |
6 |
|
compliance |
6 |
|
counselling |
6 |
|
depression symptom |
6 |
|
digital health |
6 |
|
end game |
6 |
|
facebook |
6 |
|
financial incentives |
6 |
|
happiness |
6 |
|
health communication |
6 |
|
heated tobacco product |
6 |
|
heated tobacco products |
6 |
|
income instability |
6 |
|
job loss |
6 |
|
knowledge |
6 |
|
mandatory masking |
6 |
|
misinformation |
6 |
|
nicotine replacement therapy |
6 |
|
observational |
6 |
|
practice |
6 |
|
reliability |
6 |
|
smartphone addiction |
6 |
|
smoking reduction |
6 |
|
social distancing |
6 |
|
socioeconomic status |
6 |
|
stay-at-home |
6 |
|
tobacco dependence treatment |
6 |
|
vaccine acceptance |
6 |
|
validity |
6 |
|
vulnerable group |
6 |
|
women smokers |
6 |
|
youth smoking |
6 |
|
addictive behavior |
5 |
|
addictive symptoms |
5 |
|
adolescent health |
5 |
|
advertising as topic - legislation & jurisprudence |
5 |
|
behaviour |
5 |
|
behaviour and attitudes |
5 |
|
chatting |
5 |
|
child |
5 |
|
child behavioral health |
5 |
|
clinical trials |
5 |
|
cognitive behavioral therapy |
5 |
|
communication contents |
5 |
|
communication method |
5 |
|
community smokers |
5 |
|
community-based network |
5 |
|
company |
5 |
|
computers |
5 |
|
confidence |
5 |
|
cotinine assay |
5 |
|
covid-19 pandemic |
5 |
|
current smokers |
5 |
|
delay in doctor consultation |
5 |
|
depression & mood disorders |
5 |
|
devices |
5 |
|
empathy |
5 |
|
employers |
5 |
|
expectant father |
5 |
|
face-to-face (f2f) |
5 |
|
facemask |
5 |
|
family communication scale |
5 |
|
family e-chat group |
5 |
|
female smokers |
5 |
|
gad-7 |
5 |
|
gender-specific |
5 |
|
group discussion |
5 |
|
guidelines as topic |
5 |
|
health education |
5 |
|
health promotion |
5 |
|
health risks |
5 |
|
health services |
5 |
|
hospitalized smokers |
5 |
|
humans |
5 |
|
information and communication technology |
5 |
|
instant messaging (im) |
5 |
|
international students |
5 |
|
internet |
5 |
|
intervention |
5 |
|
licensed full-time practicing nurses |
5 |
|
motion pictures as topic |
5 |
|
multiple interventions |
5 |
|
nicotine dependence |
5 |
|
nicotine replacement therapy sampling |
5 |
|
non-cigarette tobacco products |
5 |
|
nurse education |
5 |
|
nurses |
5 |
|
nursing education |
5 |
|
outpatient |
5 |
|
part-time studies in higher education |
5 |
|
patient delay |
5 |
|
patient perceptions |
5 |
|
peer counseling |
5 |
|
perceptions |
5 |
|
phq-2 |
5 |
|
polytobacco product |
5 |
|
population studies |
5 |
|
positive family communication |
5 |
|
pregnancy |
5 |
|
prejudiced attitudes |
5 |
|
preventive medicine |
5 |
|
primary care |
5 |
|
primary prevention |
5 |
|
problematic mobile phone use |
5 |
|
protocols & guidelines |
5 |
|
public opinion |
5 |
|
quality of life |
5 |
|
quitline |
5 |
|
quitting smoking |
5 |
|
quitting trajectory |
5 |
|
salivary cotinine concentration |
5 |
|
screen-based activities |
5 |
|
secondhand smoke (shs) |
5 |
|
self-efficacy |
5 |
|
smartphone dependence |
5 |
|
smartphone ownership |
5 |
|
smokeless tobacco |
5 |
|
smokeless tobacco product |
5 |
|
smoking cessation service |
5 |
|
smoking cessation services |
5 |
|
smoking renormalization |
5 |
|
smoking susceptibility |
5 |
|
social networking |
5 |
|
social networking sites |
5 |
|
tobacco dependence |
5 |
|
tobacco endgame |
5 |
|
tobacco industry |
5 |
|
united kingdom |
5 |
|
university students |
5 |
|
validation |
5 |
|
validation studies |
5 |
|
very brief advice |
5 |
|
voluntary |
5 |
|
waterpipe |
5 |
|
withdrawal symptoms |
5 |
|
workplace smoking cessation |
5 |
|
world health organization |
5 |
|
young smokers |
5 |
|
a chinese general population |
4 |
|
active smoking |
4 |
|
adaptive intervention |
4 |
|
adult smokers |
4 |
|
advertisement |
4 |
|
advocacy |
4 |
|
asian continental ancestry group - statistics and numerical data |
4 |
|
behavioral health |
4 |
|
cancer |
4 |
|
cardiovascular disease |
4 |
|
cardiovascular diseases - ethnology - mortality |
4 |
|
care |
4 |
|
chemicals and cas registry numbers |
4 |
|
chronic disease |
4 |
|
community setting |
4 |
|
community-based |
4 |
|
control |
4 |
|
conventional cigarettes |
4 |
|
cough |
4 |
|
cough - etiology |
4 |
|
daily assessment study |
4 |
|
diet |
4 |
|
displays |
4 |
|
e-health |
4 |
|
ecological momentary assessment (ema) |
4 |
|
educational status |
4 |
|
electronic nicotine delivery devices |
4 |
|
exercise |
4 |
|
fall |
4 |
|
fear |
4 |
|
feedback |
4 |
|
female |
4 |
|
fish |
4 |
|
follow-up |
4 |
|
general health |
4 |
|
harm reduction |
4 |
|
health disparity |
4 |
|
hotspots |
4 |
|
information communication technology |
4 |
|
inhalation exposure - adverse effects |
4 |
|
instant messages |
4 |
|
isometric exercise |
4 |
|
latent profile analysis |
4 |
|
living with smoker(s) |
4 |
|
m-health |
4 |
|
male |
4 |
|
meaning making |
4 |
|
meteorological factors |
4 |
|
mindfulness |
4 |
|
mobile gaming |
4 |
|
mobile health (mhealth) |
4 |
|
mortality |
4 |
|
mortality - trends |
4 |
|
motivational interviewing |
4 |
|
neoplasms |
4 |
|
neoplasms - ethnology - mortality |
4 |
|
never smokers |
4 |
|
nicotine replacement sample |
4 |
|
online support |
4 |
|
outdoor smoking area |
4 |
|
peer support |
4 |
|
perceived benefits |
4 |
|
perceived benefits and harms |
4 |
|
perceived harms |
4 |
|
physical activity |
4 |
|
point-of-sale |
4 |
|
population-based and preventive services |
4 |
|
postpartum health |
4 |
|
postpartum support |
4 |
|
prospective study |
4 |
|
public policy |
4 |
|
randomized trial |
4 |
|
respiration disorders - etiology |
4 |
|
risk communication |
4 |
|
secondhand smoke |
4 |
|
sedentary behavior |
4 |
|
shisha |
4 |
|
sleep |
4 |
|
smart |
4 |
|
smokers |
4 |
|
smoking - adverse effects |
4 |
|
smoking cessatin |
4 |
|
smoking cessation program |
4 |
|
smoking hotpsots |
4 |
|
smoking hotspots |
4 |
|
sociodemographic disparities |
4 |
|
sputum |
4 |
|
sputum - secretion |
4 |
|
stroke |
4 |
|
students |
4 |
|
susceptibility |
4 |
|
telecommunications |
4 |
|
telenursing |
4 |
|
telephone counseling |
4 |
|
temperature |
4 |
|
tobacco craving |
4 |
|
tobacco denormalization |
4 |
|
tobacco smoke pollution - adverse effects |
4 |
|
tv viewing |
4 |
|
unaided quitting |
4 |
|
unassisted quit |
4 |
|
university student |
4 |
|
very brief intervention |
4 |
|
video game playing |
4 |
|
weather |
4 |
|
wellbeing |
4 |
|
withdrawal symptom |
4 |
|
young adult |
4 |
|
young smoker |
4 |
|
youth |
4 |
|
youth health |
4 |
|
adolescent smoking |
3 |
|
advertising |
3 |
|
age of onset |
3 |
|
alcohol drinking |
3 |
|
alcohol drinking - psychology |
3 |
|
apps |
3 |
|
cognitive therapy training |
3 |
|
curriculum |
3 |
|
death certificate |
3 |
|
depressive symptoms |
3 |
|
family happiness |
3 |
|
family health |
3 |
|
health behavior |
3 |
|
health benefit |
3 |
|
health status |
3 |
|
hong kong - epidemiology |
3 |
|
hong kong china |
3 |
|
hong kong chinese |
3 |
|
household smoking |
3 |
|
information seeking behavior |
3 |
|
light drinking |
3 |
|
maternal smoking |
3 |
|
mental health problems |
3 |
|
meta-regression |
3 |
|
multi-unit housing |
3 |
|
nicotine addiction |
3 |
|
openness to smoking |
3 |
|
parents |
3 |
|
passive drinking |
3 |
|
paternal smoking |
3 |
|
perceived health status |
3 |
|
perceived smoking prevalence |
3 |
|
practitioner survey |
3 |
|
proportional mortality study |
3 |
|
psychiatric nursing |
3 |
|
qualitative method |
3 |
|
reactions |
3 |
|
respiratory symptoms |
3 |
|
self-assessment |
3 |
|
single-item scale |
3 |
|
smoking - epidemiology |
3 |
|
smoking - epidemiology - prevention and control - psychology |
3 |
|
smoking - epidemiology - psychology |
3 |
|
smoking prevention |
3 |
|
sns |
3 |
|
social environment |
3 |
|
social networking service |
3 |
|
social norms |
3 |
|
socioeconomic factors |
3 |
|
survey |
3 |
|
thirdhand smoke |
3 |
|
tobacco smoke pollution - prevention and control - statistics and numerical data |
3 |
|
tobacco smoke pollution - statistics and numerical data |
3 |
|
tobacco use disorder - epidemiology |
3 |
|
behavioral treatment |
2 |
|
children - china - hong kong - attitudes. |
2 |
|
children - tobacco use - china - hong kong. |
2 |
|
clinical education |
2 |
|
clinical learning |
2 |
|
denormalization |
2 |
|
economic recession |
2 |
|
fish as food - china - hong kong. |
2 |
|
game |
2 |
|
gamification |
2 |
|
grounded theory |
2 |
|
health brief model |
2 |
|
infection prevention |
2 |
|
mortality - china - hong kong. |
2 |
|
passive smoking - china - hong kong. |
2 |
|
peer-assisted learning |
2 |
|
pregnant women |
2 |
|
school children - china - hong kong. |
2 |
|
shisha smoking |
2 |
|
smoking - law and legislation - china - hong hong. |
2 |
|
smoking engagement dynamics |
2 |
|
socio-economic disparities |
2 |
|
strength recognition |
2 |
|
vaccination |
2 |
|
campus |
1 |
|
chatbot |
1 |
|
china |
1 |
|
gestational diabetes mellitus |
1 |
|
health apps |
1 |
|
hybrid type 2 randomized control design |
1 |
|
implementation |
1 |
|
individualist and collectivist cultures |
1 |
|
physical health |
1 |
|
social determinants of health |
1 |
|
type 2 diabetes mellitus |
1 |
|
wearable technology |
1 |
|
woman |
1 |
