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Functional beliefs and risk minimizing beliefs among Thai healthcare workers in Maharaj Nakorn Chiang Mai hospital: Its association with intention to quit tobacco and alcohol

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Background Individual health beliefs are likely to play a key role in how people respond to knowledge and information about the potential harm from smoking and alcohol abuse. The objectives of the study were to 1) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit smoking and confidence to quit smoking and 2) explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit alcohol drinking and confidence to quit alcohol drinking. Methods A cross-sectional survey was conducted in 2013 among health care workers working in Thailand. Using predicted factor scores from factor analysis, the relationship between factor scores for each of the two beliefs and intention to quit and confidence to quit were tested using ANOVA and further adjusted for age and sex using linear regression. Results Functional beliefs were inversely associated with the intention to quit and confidence to quit smoking. Both functional beliefs and risk minimizing beliefs were each inversely associated with the intention to quit and confidence to quit alcohol drinking. Conclusion Our study enhances the understanding of the complexities of health beliefs regarding these two commonly abused substances. As functional beliefs were associated with smoking and alcohol use, interventions to counter the cultural values and individual beliefs about the benefits of smoking and alcohol use are needed. Tackling risk minimizing beliefs by providing individualized feedback regarding harm may also be useful in alcohol drinkers. Electronic supplementary material The online version of this article (doi:10.1186/s13011-017-0118-1) contains supplementary material, which is available to authorized users.
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R E S E A R C H Open Access
Functional beliefs and risk minimizing
beliefs among Thai healthcare workers in
Maharaj Nakorn Chiang Mai hospital: its
association with intention to quit tobacco
and alcohol
Surin Jiraniramai
1
, Wichuda Jiraporncharoen
1
, Kanokporn Pinyopornpanish
1
, Nalinee Jakkaew
1
,
Tinakon Wongpakaran
2
and Chaisiri Angkurawaranon
1*
Abstract
Background: Individual health beliefs are likely to play a key role in how people respond to knowledge and
information about the potential harm from smoking and alcohol abuse. The objectives of the study were to 1)
explore whether functional beliefs and risk minimizing beliefs were associated with intention to quit smoking and
confidence to quit smoking and 2) explore whether functional beliefs and risk minimizing beliefs were associated
with intention to quit alcohol drinking and confidence to quit alcohol drinking.
Methods: A cross-sectional survey was conducted in 2013 among health care workers working in Thailand.
Using predicted factor scores from factor analysis, the relationship between factor scores for each of the two
beliefs and intention to quit and confidence to quit were tested using ANOVA and further adjusted for age
and sex using linear regression.
Results: Functional beliefs were inversely associated with the intention to quit and confidence to quit smoking. Both
functional beliefs and risk minimizing beliefs were each inversely associated with the intention to quit and confidence
to quit alcohol drinking.
Conclusion: Our study enhances the understanding of the complexities of health beliefs regarding these two
commonly abused substances. As functional beliefs were associated with smoking and alcohol use, interventions to
counter the cultural values and individual beliefs about the benefits of smoking and alcohol use are needed. Tackling
risk minimizing beliefs by providing individualized feedback regarding harm may also be useful in alcohol drinkers.
Background
The prevalence of alcohol drinking and smoking is high
globally and evidence has shown that these risky health
behaviors may lead to many negative consequences, with
the risk increasing when taking them together [13].
The Thai national health surveys have reported that both
the prevalence of alcohol drinking and smoking have
been steady from 2004 but had minimally increased by
2011 [4, 5]. Literature suggests that each year, a small
proportion of people have reported trying to stop smok-
ing (7%) or drinking (9%) [4, 6, 7]. Knowledge of the
negative effects was mentioned as one of the main rea-
son why people stop smoking. However, many already
know that excessive alcohol consumption and smoking
can be addictive and can cause serious health and social
harm [8]. This suggests that people respond to this
knowledge differently and often people continue to
smoke and drink despite knowing the potential harm.
Individual health beliefs are likely to play a key role in
how people respond to such knowledge and information.
* Correspondence: chaisiri.a@cmu.ac.th
1
Department of Family Medicine, Faculty of Medicine, Chiang Mai University,
110 Intawaroros Road, Sriphum, Muang, Chiang Mai 50200, Thailand
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Jiraniramai et al. Substance Abuse Treatment, Prevention, and Policy (2017) 12:34
DOI 10.1186/s13011-017-0118-1
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People try to make a positive change when they perceive
that their current behavior may lead to a negative out-
come. However, the barrier against this positive force is
the unsatisfying feeling when trying to avoid their previ-
ous negative behavior or when they are unable to resist
and revert to their old negative behavior. The psycho-
logical tension created when the individuals negative
behavior conflicts with their belief is known as cognitive
dissonance [9]. If over time they could not resist their
own desire and are unable to make positive changes,
often it is their mindset or beliefs that are changed
instead [10].
Giving up addictive behaviors, such as smoking, is
often difficult. Many individuals may change their atti-
tude, which is the path of least resistance, by adopting
other beliefs to help reduce cognitive dissonance [11].
Health beliefs commonly found among alcohol drinkers
and smokers that help minimize cognitive dissonance
can be divided into two types, risk minimizing beliefs
and functional beliefs. People use risk minimizing beliefs
to help alleviate the seriousness of the problem by perceiv-
ing that, for them, there is less opportunity to experience
any negative effects from that behavior or by minimizing
the negative feature of the undesirable consequences of
that behavior. An example of risk minimizing belief is the
idea that the harms or problems associated with smoking
and drinking does not apply to me[12, 13]. Functional
beliefs are related to the perceived benefits of the behavior
or beliefs in the value of the behavior. For example, many
smokers may feel that smoking is effective for reducing
stress and increase concentration[14, 15].
Functional beliefs and risk minimizing beliefs about
smoking and smoking motives have been examined since
the late 1960s where researchers have developed scales
for assessing these beliefs [16]. Later studies examined
the associations between these two types of beliefs and
smoking. Studies, including one from Thailand, have
shown a strong association between risk-minimizing and
current smoking [17, 18]. Smokers often normalized and
minimized the dangers of smoking. In addition, evidence
from Thailand and other countries, have found that risk
minimizing beliefs were also associated with a reduced
intention to quit smoking [12, 19, 20] and confidence to
quit smoking [21, 22] . The same direction of association
was found for functional beliefs [18, 23]. The association,
however, between health beliefs and smoking may vary
due to differences in sociocultural factors and norms in
each setting [21]. Moreover, unlike smoking, only few
research studies have explored the association between
risk minimizing beliefs and the function of beliefs and
alcohol use [7, 15, 24] despite the fact of the correlation
between both behaviors [25] .
Our study aimed to 1) explore whether functional be-
liefs and risk minimizing beliefs were associated with the
intention to quit smoking and confidence to quit smoking
in Thailand and 2) explore whether functional beliefs and
risk minimizing beliefs were associated with the intention
to quit alcohol drinking and confidence to quit alcohol
drinking in Thailand. Exploring these two beliefs with
both smoking and alcohol use may increase the under-
standing of the complexities of health beliefs regarding
these two commonly abused substances.
Methods
A cross-sectional survey was conducted among health
care workers in a University Hospital in Chiang Mai,
Thailand in 2013. A detailed description of the survey
has been published [26]. In summary, 3204 participants
(59.7% response rate) completed a self-administered on-
line questionnaire on smoking and alcohol use as well as
their beliefs about smoking and alcohol use.
Health beliefs
Health beliefs about smoking and alcohol drinking were
evaluated separately using a nine-item questionnaire
derived from previous literature [18, 19]. The first five
items were related to functional beliefs of smoking or
alcohol use. The last four items referred to risk minimiz-
ing beliefs about the risk and harms of smoking or alcohol
use (Tables 1, 2). Participants rated their agreement with
each functional and risk minimizing belief. Agreement
scores ranged from one to five. A score of five indicated
that the participant totally agreed with the statement and
a score of one indicated that the participant totally dis-
agreed with the statement.
Measures of intention to quit
The history of each substance used was initially catego-
rized into four groups. The first group was for those
who had never used substances. The second group was
those who were former users defined as having stopped
using the substance for longer than one year. The third
group was those who were recent quitters defined as
having recently stopped within one year and the last
group of users were those who categorized themselves as
currently using the substance (within the past 3 months).
If participants were currently using a particular substance,
they were asked about their intention to quit each particu-
lar substance using a four-item response: 1-no intention
to quit, 2-intention to quit in the next six months, 3-
intention to quit within six months and 4-intent to
quit within 30 days. If participants indicated that they
planned on give up a particular substance, they were
also asked about their confidence to quit each particular
substance by using a five-item response of success: 0-not
at all confident, 1-not confident (< 25% chance of success),
2-moderately confident (25-50% chance of success),
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3-confident (50-75% chance of success and 4-very
confident (> 75% chance of success).
Data analysis
Participants who were current users and those who had
stopped within the past year were used in the analysis
for each substance. Separately for tobacco and alcohol
consumption, a factor analysis with orthogonal rotation
(varimax) was used to examine whether the nine-item
questionnaires formed the two coherent health beliefs
(functional beliefs and risk minimizing beliefs) as hypothe-
sized. A loading factor of at 0.4 was used as a cutoff point
[27]. Kruskal-Wallis test was used to determine the associ-
ation between the agreement score for each item with
intention to quit. Using predicted factor scores from factor
analysis, the relationship between factor scores for each of
the two beliefs and intention to quit and confidence to
quit were tested using ANOVA. These associations were
further adjusted for age and sex using linear regression, as
it was an a-priori belief that these two factors could be
considered as potential confounders. Lastly, functional
belief scores and risk minimizing belief scores were
categorized into quartiles and its association with recent
cessation of smoking and alcohol use using logistic regres-
sion were examined. Sensitivity analyses were performed
by excluding recent quitters from the analyses. A p-value
of 0.05 was considered statistically significant. All
analyses were conducted using STATA version 12.0.
Results
Of the 3204 participants, 20 participants had recently
quit smoking within a year and 167 were current
smokers (5.2%). It was these 187 smokers and recent
quitters that are used for further analysis on health
beliefs about smoking and intention to quit smoking
(Table 1). The vast majority of the 187 smokers and re-
cent quitters were male, only seven female were current
smokers (Additional file 1: Table S1). For alcohol use,
572 participants stated that they had recently stopped
drinking alcohol within one year while 992 were current
alcohol drinkers. It is these 1564 participants that are
used for further analysis on health beliefs about drinking
Table 1 Health beliefs and intention to quit smoking among current smokers and recent quitters
Beliefs Loading
Factor
%
Agree
Mean Level of Agreement df, test
value
p-value
No Intention
to Quit (77)
Intend to Quit in
>6 Months (49)
Intend to Quit in
<6 Months (15)
Intend to Quit in
1 Month (26)
Recent Quitters
(20)
Factor 1 Functional (α= 0.95)
You enjoy smoking too
much to give it up.
0.88 12.3 2.6 2.3 2.9 1.8 1.5 4, 22.9 <0.01
Smoking calms you down
when you are stressed or
upset.
0.77 33.7 3.1 3.0 3.5 2.5 2.0 4, 18.1 0.01
Smoking helps you
concentrate better.
0.91 13.9 2.6 2.3 2.9 1.7 1.8 4, 18.2 <0.01
Smoking is an important
part of your life.
0.87 9.6 2.5 2.0 2.6 1.3 1.5 4, 30.6 <0.01
Smoking makes it easier
for you to socialize.
0.78 8.0 2.3 1.7 2.3 1.3 1.6 4,18.5 <0.01
Factor 2 Risk Minimizing (α= 0.88)
The medical evidence
that smoking is harmful is
exaggerated.
0.82 43.8 3.3 3.1 3.1 3.4 2.3 4, 8.81 0.06
Smoking is no riskier than
lots of other things that
people do.
0.81 19.8 2.8 2.5 2.6 2.0 2.0 4, 11.1 0.03
You must die of
something, so why not
enjoy yourself and smoke.
0.56 15.0 2.6 2.3 2.5 1.9 1.9 4, 8.96 0.06
I think I must have the
sort of good genes that
means I can smoke
without getting any
harm.
0.57 9.6 2.4 2.1 2.9 1.7 1.6 4, 17.7 <0.01
Agreement scores ranged from 1 to 5. A score of 5 indicated that the participant totally agreed with the statement, a score of 4 indicated that the participant
somewhat agreed with the statement, a score of 3 reflected that the participant was unsure about the statement, a score of 2 and a score of 1 indicated that the
participant somewhat disagree and totally disagree with the statement respectively. df = degree of freedom, Test statistic and p-value obtained from Kruskal-
Wallis equality-of-population rank test
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and intention to quit alcohol drinking (Table 2). Of the
1564 participants who were current drinkers or had
recently given up alcohol, 995 were females and 78 were
males (Additional file 1: Table S2).
Health beliefs and intention to quit smoking and
confidence to quit smoking
Using factor analysis with orthogonal rotation (varimax),
there were four potential factors that could be derived
from the nine-item questionnaire. However, only in the
first two factors the individual items had a factor loading
of greater than 0.4 (Additional file 1: Table S3), thus sup-
porting that the nine-items form two types of coherent
beliefs (Table 1). Results suggest that current smokers
and recent quitters engaged in a number of functional
and risk minimizing beliefs about smoking. The most
common functional belief was that Smoking calms you
down when you are stressed or upset, found in about
33.7% of smokers and recent quitters. The most common
risk minimizing belief was that The medical evidence that
smoking is harmful is exaggerated, was found in 43.8% of
smokers and recent quitters (Additional file 1: Table S4).
Results from Table 1 suggest that each of the functional
beliefs were associated with intention to quit. Higher
agreement in each functional belief about smoking was in-
versely associated with the intention to quit. Only three of
the four risk-minimizing beliefs were associated with
intention to quit (Table 1).
Using factor scores derived from factor analysis, only
the factor score for functional beliefs was associated with
intention to quit smoking and the confidence level in
quitting. Adjusted for age and sex, individuals with
higher functional beliefs of smoking were less likely to
quit smoking (Fig. 1) and were less confident of being
able to quit (Fig. 2). The factor score for risk minimizing
beliefs was not associated with intention to quit smoking
(Fig. 1) and the confidence level in quitting (Fig. 2). The
associations with intention to quit did not materially
change when recent quitters were excluded from the
analyses (Additional file 2: Figure S1).
In a multivariate regression model, there was some
weak evidence of a gradient in associations between
quartiles of functional belief scores and recent smoking
cessation (Wald test statistic = 3.02,df = 1, p= 0.08) as
Table 2 Health beliefs and intention to quit alcohol drinking among current drinkers and recent quitters
Beliefs Loading
Factor
%
Agree
Mean Level of Agreement df, test
value
p-value
No Intention
to Quit (77)
Intend to Quit in
>6 Months (49)
Intend to Quit in
<6 Months (15)
Intend to Quit in
1 Month (26)
Recent Quitters
(20)
Factor 1 Functional (α= 0.69)
You enjoy drinking too
much to give it up.
0.43 8.1 2.2 2.2 2.2 1.9 1.3 4, 313.6 <0.01
Drinking calms you down
when you are stressed or
upset.
0.55 19.5 2.8 2.8 2.9 2.3 1.4 4, 444.3 <0.01
Drinking helps you
concentrate better.
0.50 3.8 1.8 1.8 1.8 1.5 1.2 4, 156.0 <0.01
Drinking is an important
part of your life.
0.50 2.9 1.7 1.7 .16 1.4 1.2 4, 143.3 <0.01
Drinking makes it easier
for you to socialize.
0.35 19.5 2.8 2.8 2.7 2.4 1.5 4, 368. <0.01
Factor 2 Risk Minimizing (α= 0.60)
The medical evidence
that drinking is harmful is
exaggerated.
0.68 29.0 2.8 2.7 2.6 2.5 2.2 4, 64.5 <0.01
Drinking is no riskier than
lots of other things that
people do.
0.78 13.1 2.4 2.3 2.3 2.1 1.8 4, 92.9 <0.01
You must die of
something, so why not
enjoy yourself and drink.
0.80 11.1 2.4 2.3 2.3 2.0 1.4 4, 274.1 <0.01
I think I must have the
sort of good genes that
means I can drink
without any harm.
0.63 5.9 2.2 2.1 2.1 1.9 1.4 4, 182.2 <0.01
Agreement scores ranged from 1 to 5. A score of 5 indicated that the participant totally agreed with the statement, a score of 4 indicated that the participant
somewhat agreed with the statement, a score of 3 reflected that the participant was unsure about the statement, a score of 2 and a score of 1 indicated that the
participant somewhat disagree and totally disagree with the statement respectively. df = degree of freedom, Test statistic and p-value obtained from Kruskal-
Wallis equality-of-population rank test
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Fig. 1 Health Beliefs and Intention to Quit Smoking. Results are adjusted for age and sex. Higher factor score indicate higher level/agreement of
belief. Vertical lines represents 95% confidence intervals. P-values obtained from values of the F statistic and the corresponding degrees of freedom
Fig. 2 Health Beliefs and Confidence Level on the Intention to Quit Smoking. Results are adjusted for age and sex. Confidence to quit smoking
was assessed by using a five-item response of success: 0-not at all confident, 1-not confident (< 25% chance of success), 2-moderately confidently
(25-50% chance of success), 3-confident (50-75% chance of success and 4-very confident (> 75% chance of success). Vertical lines represents
95% confidence intervals. P-values obtained from values of the F statistic and the corresponding degrees of freedom
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well as between quartiles of risk minimizing belief scores
and recent smoking cessation (Wald test statis-
tic = 6.35,df = 1, p= 0.02). Those with functional beliefs
scores and risk minimizing scores in the highest quartile
were less likely to have recently quit smoking (Table 3).
Health beliefs and intention to quit drinking and
confidence to quit drinking
Similar to results for smoking, although there were four
potential factors that could be derived from the ques-
tionnaire (Additional file 1: Table S5), the loading factors
were aggregated towards two types of coherent beliefs
(Table 2). For functional beliefs, approximately 20%
agreed that Drinking calms you down when you are
stressed or upsetand that Drinking makes it easier for
you to socialize. The most common risk minimizing be-
lief was that Medical evidence that drinking is harmful is
exaggerated(Additional file 1: Table S6). Displaying a
similar pattern to the intention to quit smoking, higher
agreement in each of the functional beliefs of alcohol
was inversely associated with the intention to quit
(Table 2). All four risk minimizing beliefs of alcohol
were associated with an intention to quit alcohol
(Table 2). Adjusting for age and sex, factor scores of
functional beliefs and risk minimizing beliefs were
each inversely associated with intention to quit alco-
hol drinking (Fig. 3) and confidence to quit drinking
(Fig. 4). Those with higher scores in functional and
risk minimizing beliefs about drinking were less likely
to quit drinking and had a lower confidence in quit-
ting. Some power was loss in the sensitivity analysis but
the associations with intention to quit did not materially
change when recent quitters were excluded from the ana-
lyses (Additional file 3: Figure S2).
In a multivariate regression model, there was a gradi-
ent in associations between quartiles of functional belief
scores and recent cessation of alcohol use as well as be-
tween quartiles of risk minimizing belief scores and re-
cent cessation of alcohol use. Compare to those in
lowest quartile of functional belief scores, the odds ratio
Table 3 Association between functional belief and cessation of smoking within past year
Adjusted Odds ratio 95% CI test value df p-value
Functional belief factor score (quartile) 3.02 1 0.08
1st (lowest) Reference
2nd 1.97 0.34 to 11.2
3rd 0.58 0.08 to 4.03
4th (highest) 0.42 0.05 to 3.57
Risk minimizing belief factor score (quartile) 6.35 1 0.02
1st (lowest) Reference
2nd 0.55 0.15 to 2.04
3rd ——
4th (highest) 0.38 0.08 to 1.75
Age (increase) 1.01 0.95 to 1.07 0.14 1 0.71
Sex 3.60 1 0.06
Female Reference
Male 0.17 0.03 to 1.06
Income (baht/month) 4.32 2 0.11
< 30,000 Reference
30,000-60,000 3.87 0.67 to 22.3
> 60,000 5.24 0.77 to 35.6
Highest education 4.52 1 0.03
Below Bachelors degree Reference
Bachelors degree 0.17 0.03 to 0.87
Higher than Bachelors degree ——
Occupation 0.29 1 0.59
Health professional Reference
Non-health professional 0.67 0.17 to 2.72
Test value using Walds test; CI Confidence interval; df degree of freedom; all odds ratios are adjusted for all variables presented in the table; empty cells indicate
that there are no observations
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Fig. 3 Health Beliefs and Intention to Quit Alcohol Drinking. Results are adjusted for age and sex. Higher factor score indicate higher
level/agreement of belief. Vertical lines represents 95% confidence intervals. P-values obtained from values of the F statistic and the
corresponding degrees of freedom
Fig. 4 Health Beliefs and Confidence Level on Intention to Quit Alcohol Drinking. Results are adjusted for age and sex. Confidence to quit alcohol
drinking was assessed by using a 5-item response of success: 0-not at all confident, 1-not confident (< 25% chance of success), 2-moderately
confidently (25-50% chance of success), 3-confident (50-75% chance of success and 4-very confident (> 75% chance of success). Vertical lines
represents 95% confidence intervals. P-values obtained from values of the F statistic and the corresponding degrees of freedom
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for recent cessation of alcohol use was 0.22 (95% CI 0.15
to 0.33) for those with score in the 2nd quartile, 0.11
(95% CI 0.07 to 0.16) for those in the 3rd quartile and
0.04 (95% CI 0.03 to 0.07) for those with the highest
functional belief scores (Wald test statistic = 178.2,df = 1,
p< 0.01). This gradient was also demonstrated with risk
minimizing beliefs scores. Compared to those in the
lowest quartile of risk minimizing beliefs scores, the
odds ratio for recent cessation of alcohol use was 0.50
(95% CI 0.34 to 0.74) for those with score in the 2nd
quartile, 0.32 (95% CI 0.21 to 0.48) for those in the 3rd
quartile and 0.21 (95% CI 0.13 to 0.32) for those with
the highest functional belief scores (Wald test statis-
tic = 53.4,df = 1, p< 0.01) (Table 4).
Discussion
Using factor analysis, our nine-item questionnaires form
two coherent beliefs about smoking and alcohol use, the
functional beliefand the risk-minimizing belief. Results
suggested that, the functional beliefs were associated with
the intention to quit and confidence to quit smoking.
While both functional beliefs and risk minimizing beliefs
were associated with the intention to quit and confidence
to quit alcohol drinking.
Function beliefs, risk minimizing beliefs and smoking
When considering the intention and confidence to quit
smoking,the highest agreement on risk minimizing
beliefs from our sample was the skeptical belief that
Medical evidence that smoking is harmful is exagger-
ated. This result was similar to a previous study in
Australia [19] which reflected lack of understanding in
the harm or health outcomes from smoking and its con-
sequences. This belief can usually be found in the
smokers, which was also reflected in our study. However,
using factor scores, our study did not find an association
between risk minimizing beliefs and intention to quit
and confidence to quit smoking. Risk minimizing beliefs
can be considered weak beliefsas they can be easily in-
fluenced and changed [28]. This potential fluctuation in
Table 4 Association between functional belief, risk minimizing beliefs and cessation of alcohol use within past year
Adjusted Odds ratio 95% CI test value df p-value
Functional belief factor score (quartile) 178..2 1 <0.01
1st (lowest) Reference
2nd 0.22 0.15 to 0.33
3rd 0.11 0.07 to 0.16
4th (highest) 0.04 0.03 to 0.07
Risk minimizing belief factor score (quartile) 53.4 1 <0.01
1st (lowest) Reference
2nd 0.50 0.34 to 0.74
3rd 0.32 0.21 to 0.48
4th (highest) 0.21 0.13 to 0.32
Age (increase) 1.03 1.01 to 1.04 13.2 1 <0.01
Sex 65.6 1 <0.01
Female Reference
Male 0.26 0.18 to 0.36
Income (baht/month) 4.93 2 0.08
< 30,000 Reference
30,000-60,000 1.34 0.96 to 1.86
> 60,000 1.54 1.01 to 2.36
Highest education 7.11 2 0.03
Below Bachelors degree Reference
Bachelors degree 1.43 1.01 to 2.02
Higher than Bachelors degree 1.93 1.16 to 3.22
Occupation 3.98 1 0.05
Health professional Reference
Non-health professional 0.72 0.53 to 0.99
Test value using Walds test; CI confidence interval; df degree of freedom; all odds ratios are adjusted for all variables presented in the table
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risk minimizing beliefs and our small sample of current
smokers and recent quitters may be reasons why this
study could not detect any association between risk min-
imizing beliefs and the intention to stop smoking.
Higher agreement in functional beliefs about smoking
was inversely associated with intention to quit and confi-
dence to quit smoking, which has been observed in a
previous study [29]. Smokers have dissonant reduction
when they attempt to enhance the functional beliefs in
smoking [18]. When exploring each functional belief in-
dividually, the functional belief that was most commonly
found was that Smoking can calm you down when you
are stressed or upset. This is not surprising as nicotine
can modulate pathways involved in stress response, de-
pression and anxiety [30]. Our study found that the few
smokers had functional beliefs about Smoking for social
enhancement. This is potentially due to the regulatory
environment in Thailand that restricts smoking areas
and has banned smoking advertisements on television
and radio [20].
Functional beliefs, risk minimizing beliefs and alcohol use
Similar to results for smoking, this study found an in-
verse association between functional beliefs and the
intention to quit alcohol drinking. This may be because
concurrent use of alcohol and smoking are common
[25]. However, when exploring each functional belief in-
dividually, there were different patterns of functional be-
liefs between smoking and alcohol drinking. Firstly, in
contrast to smoking, functional beliefs of drinking for
social enhancementwas quite common. In Thailand,
alcohol use is integrated into social norms and also trad-
itional rites. In additional, drinking is rarely perceived as
a social problem [31, 32].
Risk minimizing beliefs about drinking were signifi-
cantly associated with the intention to quit and confi-
dence to quit alcohol drinking, while this association
was not found in smoking. Currently drinkers tend to
have risk minimizing beliefs as most of Thai people who
use alcohol are at low to moderate risk of harm, which
may not show the serious health outcomes [33, 34].
Furthermore, there is conflicting evidence regarding the
potential protective effect of alcohol against coronary
heart disease [34, 35], which may be why risk minimiz-
ing beliefs are associated with alcohol use and inversely
associated with the intention to quit.
The present study has some limitations. The response
rate of our study was 60%, which may introduce some
selection bias. However, in a previous publication, we
have demonstrated that our sample was representative
of the source population in terms of age, sex and educa-
tion level [26]. Because of the data was based on self-
report, health beliefs and the intention to quit smoking
and alcohol drinking may be vulnerable to social
desirability bias. However, voluntary participation, assur-
ances of confidentiality in this study may have reduced
some of the impact of social desirability bias. This study
was a cross-sectional data, we can only assume the tem-
poral relationships between decreasing functional beliefs
and risk minimizing beliefs with subsequent changes in
willingness to quit smoking or alcohol use. However,
some evidence from prospective studies of smoking have
supported this notion [13, 18]. The number of smokers
enrolled in this study was small, thus the estimates were
imprecise and could be underpowered to detect the as-
sociation between minimizing beliefs and the intention
to quit and confidence to quit smoking. As other health
beliefs, in particular positive or protective beliefs, were
not explored in this study, we could not provide evi-
dence on what beliefs may be protective or promotes
intention to quit. Nonetheless, this study also has some
strengths. Factor analysis was utilized to derive factor
scores of beliefs rather than just a single question which
had previously been common in past literature [36]. It is
also one of the first studies to report findings for both
alcohol and tobacco use.
Conclusions
The finding that risk minimizing beliefs were associated
with alcohol use and that functional beliefs were associ-
ated with both smoking and alcohol use has several im-
plications. Risk minimizing beliefs can be overridden by
giving persuasive information on the negative conse-
quences [8]. For alcohol drinking, tools such as the
Alcohol, Smoking, Substance Involvement Screening test
(ASSIST) [37] which can detect and quantify the risk of
harm from alcohol use may be a useful tool that can
help provide individualized information and feedback.
As functional beliefs were also common, interventions
to counter the cultural values and individual beliefs
about the benefits of smoking and alcohol use are
needed. Functional belief for stress management were
commonly found. Thus smokers and alcohol drinkers
ought to have or should be advised on alternative coping
strategies for stress management [29]. Combined
pharmacological therapy and behavioral intervention can
also assist the users who have the effects of a physical
addiction [38]. For functional beliefs of social enhance-
ment attached with alcohol use, strategies employed to
decrease the social value of smoking can also be applied.
These may involve using classroom-based interventions,
community-based strategies, and alcohol control regula-
tions [39].
The challenges related to prevention and treatment of
alcohol addiction in Thailand has been documented. This
includes poor motivation of patientsand the belief that
patients can handle problems[40] which coincides with
functional and risk minimizing beliefs explored in this
Jiraniramai et al. Substance Abuse Treatment, Prevention, and Policy (2017) 12:34 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
study. A study from Thailand has suggested that higher
level of moral beliefs and engaging in religious activities
may be a protective factor of alcohol use among adoles-
cents [41]. This is also in line with other evidence from
Thailand where a few small-scale community-based
approach projects have demonstrated success in address-
ing such issues in tackling health beliefs and substance
use. Most included tailoring policies and interventions to
coincide with Buddhist values and moral beliefs of the cul-
ture in the community [4244]. This may provide a useful
example for future programs.
Additional files
Additional file 1: Table S1. Characteristics of current smoker and
recent quitters by intention to quit status. Table S2. Characteristics of
current drinking and recent quitters by intention to quit status. Table S3.
Rotated factor loading on health beliefs about smoking among those
with a lifetime history of smoking. Table S4. Distribution of respondents
to each of the functional beliefs and risk minimizing beliefs of smoking.
Table S5. Rotated factor loading on health beliefs about alcohol among
those with a lifetime history of alcohol drinking. Table S6. Distribution of
respondents to each of the functional beliefs and risk minimizing beliefs
of alcohol drinking. (DOCX 99 kb)
Additional file 2: Figure S1. Sensitivity Analysis of Health Beliefs and
Intention to Quit Smoking (excluding recent quitters). Results are adjusted
for age and sex. Higher factor score indicate higher level/agreement of
belief. Vertical lines represents 95% confidence intervals. P-values obtained
from values of the F statistic and the corresponding degrees of freedom.
(TIFF 4656 kb)
Additional file 3: Figure S2. Sensitivity Analysis of Health Beliefs and
Intention to Quit Alcohol Drinking (excluding recent quitters). Results are
adjusted for age and sex. Higher factor score indicate higher level/
agreement of belief. Vertical lines represents 95% confidence
intervals. P-values obtained from values of the F statistic and the
corresponding degrees of freedom. (TIFF 4656 kb)
Acknowledgements
The authors acknowledge Dr. Anne C. K. Quah, ITC Asia Project Manager and
Translation Specialist, Department of Psychology, University of Waterloo,
Canada for sharing the Thai questionnaires from the ITC Thailand Project. We
would like to thank the Health Promotion Unit, Faculty of Medicine for their
help in data collection and to all the participants who took part in the study.
Funding
The Chiang Mai University Health worker was funded by the Faculty of
Medicine Research Fund of Chiang Mai University. The funders had no roles
in study design, analysis, preparation of manuscript and decision to publish.
Availability of data and materials
The dataset for analysis in the study is available from the corresponding
author on reasonable request.
Authorscontributions
SJ, WJ, TW, CA were involved in the conception of the manuscript. SJ, WJ,
CA was involved in the design and acquisition of data. SJ, TW and CA were
involved in the initial analysis. All authors were involved in the interpretation
of the data. SJ, WJ, KP and CA drafted the manuscript. SJ, WJ, KP, NJ and CA
drafted revisions. All authors read, critically revised all versions of the
manuscript and approved the final manuscript to be published.
Ethics approval and consent to participate
Consent was obtained from all participants. The survey was granted
ethical approval by the Faculty of Medicine, Chiang Mai University
(Reference numbers 069/2012).
Consent for publication
Not applicable
Competing interests
The authors declare that they have no competing interests.
PublishersNote
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Author details
1
Department of Family Medicine, Faculty of Medicine, Chiang Mai University,
110 Intawaroros Road, Sriphum, Muang, Chiang Mai 50200, Thailand.
2
Department of Psychiatry, Faculty of Medicine, Chiang Mai University,
Chiang Mai, Thailand.
Received: 10 February 2017 Accepted: 6 July 2017
References
1. Anderson P. Global use of alcohol, drugs and tobacco. Drug and alcohol
review. 2006;25(6):489502.
2. Pengpid S, Peltzer K, Puckpinyo A, Viripiromgool S, Thamma-Aphiphol K,
Suthisukhon K, Dumee D, Kongtapan T. Screening and concurrent brief
intervention of conjoint hazardous or harmful alcohol and tobacco use in
hospital out-patients in Thailand: a randomized controlled trial. Subst Abuse
Treat Prev Policy. 2015;10:22.
3. Sakata K, Hoshiyama Y, Morioka S, Hashimoto T, Takeshita T, Tamakoshi A.
Smoking, alcohol drinking and esophageal cancer: findings from the JACC
study. J Epidemiol. 2005;15(Suppl 2):S2129.
4. Aekplakorn W, Hogan MC, Tiptaradol S, Wibulpolprasert S, Punyaratabandhu
P, Lim SS. Tobacco and hazardous or harmful alcohol use in Thailand: joint
prevalence and associations with socioeconomic factors. Addict Behav.
2008;33(4):50314.
5. National Statistial Office of Thailand. The smoking and drinking behavior
survey 2011. 2012.
6. McCoy SB, Gibbons FX, Reis TJ, Gerrard M, Luus CA, Sufka AV. Perceptions of
smoking risk as a function of smoking status. J Behav Med. 1992;15(5):46988.
7. Feldman L, Harvey B, Holowaty P, Shortt L. Alcohol use beliefs and
behaviors among high school students. J Adolesc Health. 1999;24(1):4858.
8. Kleinjan M, van den Eijnden RJJM, Engels RCME. Adolescents
rationalizations to continue smoking: the role of disengagement beliefs and
nicotine dependence in smoking cessation. Addict Behav. 2009;34(5):4405.
9. Ajzen I. From intentions to actions: a theory of planned behavior. In: Action
control: from cognition to behavior. edn. Edited by Kuhl J, Beckmann J.
Berlin Heidelberg: Springer-Verlag; 1985.
10. Festinger L. A theory of cognitive dissonance. Standford: Stanford University
Press; 1957.
11. Hyland A, Li Q, Bauer JE, Giovino GA, Steger C, Cummings KM. Predictors of
cessation in a cohort of current and former smokers followed over 13 years.
Nicotine Tobacco Res. 2004;6(Suppl 3):S3639.
12. Chapman S, Wong WL, Smith W. Self-exempting beliefs about smoking and
health: differences between smokers and ex-smokers. Am J Public Health.
1993;83(2):2159.
13. Borland R, Yong HH, Balmford J, Fong GT, Zanna MP, Hastings G. Do
risk-minimizing beliefs about smoking inhibit quitting? Findings from
the international tobacco control (ITC) four-country survey. Prev Med.
2009;49(2-3):21923.
14. Weinstein ND, Slovic P, Gibson G. Accuracy and optimism in smokers
beliefs about quitting. Nicotine Tobacco Res. 2004;6(Suppl 3):S37580.
15. Bitarello do Amaral M, Lourenço LM, Ronzani TM. Beliefs about alcohol use
among university students. J Subst Abus Treat. 2006;31(2):1815.
16. Ikard F, Green D, Horn D. A scale to differentiate between types of smoking
as related to the management of affect. Int J Addict. 1969;4:64959.
17. Jiraniramai S, Likhitsathian S, Jiraporncharoen W, Thaikla K, Aramrattana A,
Angkurawaranon C. Risk-minimizing belief: its association with smoking and
risk of harm from smoking in northern Thailand. J Ethn Subst Abus. 2015;
14(4):36478.
18. Fotuhi O, Fong GT, Zanna MP, Borland R, Yong HH, Cummings KM. Patterns
of cognitive dissonance-reducing beliefs among smokers: a longitudinal
Jiraniramai et al. Substance Abuse Treatment, Prevention, and Policy (2017) 12:34 Page 10 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
analysis from the international tobacco control (ITC) four country survey.
Tob Control. 2013;22(1):528.
19. Oakes W, Chapman S, Borland R, Balmford J, Trotter L. Bulletproof skeptics
in life's jungle: which self-exempting beliefs about smoking most predict
lack of progression towards quitting? Prev Med. 2004;39(4):77682.
20. Lee WB, Fong GT, Zanna MP, Omar M, Sirirassamee B, Borland R. Regret and
rationalization among smokers in Thailand and Malaysia: findings from the
international tobacco control Southeast Asia survey. Health Psychol. 2009;
28(4):45764.
21. Yong H-H, Borland R, Siahpush M. Quitting-related beliefs, intentions, and
motivations of older smokers in four countries: findings from the
international tobacco control policy evaluation survey. Addict Behav. 2005;
30(4):77788.
22. Myung SK, Seo HG, Cheong YS, Park S, Lee WB, Fong GT. Association of
sociodemographic factors, smoking-related beliefs, and smoking restrictions
with intention to quit smoking in Korean adults: findings from the ITC Korea
survey. J Epidemiol. 2012;22(1):217.
23. Hosking W, Borland R, Yong H-H, Fong G, Zanna M, Laux F, Thrasher J, Lee
W, Sirirassamee B, Omar M. The effects of smoking norms and attitudes on
quitting intentions in Malaysia, Thailand, and four western nations: a
cross-cultural comparison. Psychol Health. 2009;24(1):95107.
24. Ward LC, Rothaus P. The measurement of denial and rationalization in male
alcoholics. J Clin Psychol. 1991;47(3):4658.
25. Falk DE, Yi HY, Hiller-Sturmhofel S. An epidemiologic analysis of co-
occurring alcohol and tobacco use and disorders: findings from the
National Epidemiologic Survey on alcohol and related conditions. Alcohol
Res Health. 2006;29(3):16271.
26. Angkurawaranon C, Wisetborisut A, Jiraporncharoen W, Likhitsathian S,
Uaphanthasath R, Gomutbutra P, Jiraniramai S, Lerssrimonkol C,
Aramrattanna A, Doyle P, et al. Chiang Mai University health worker study
aiming toward a better understanding of noncommunicable disease
development in Thailand: methods and description of study population.
Clin Epidemiol. 2014;6:27786.
27. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data
analysis, vol. 6. Upper Saddle River: Pearson Prentice Hall; 2006.
28. Dijkstra A. Disengagement beliefs in smokers: do they influence the effects
of a tailored persuasive message advocating smoking cessation? Psychol
Health. 2009;24(7):791804.
29. Yong HH, Borland R. Functional beliefs about smoking and quitting activity
among adult smokers in four countries: findings from the international
tobacco control four-country survey. Health Psychol. 2008;27(3 Suppl):S21623.
30. Picciotto MR, Brunzell DH, Caldarone BJ. Effect of nicotine and nicotinic
receptors on anxiety and depression. Neuroreport. 2002;13(9):1097106.
31. WHO/UNDCP Global Initiative on Primary Prevention of Substance Abuse.
Substance abuse in Southeast Asia: knowledge, attitudes, practices and
opportunities for intervention : summary of baseline assessments in Thailand,
Philippines and Viet Nam. Geneva: World Health Organization; 2003.
32. Moolasart J, Chirawatkul S. Drinking culture in the Thai-Isaan context of
northeast Thailand. Southeast Asian J Trop Med Public Health. 2012;43(3):
795807.
33. Assanangkornchai S, Sam-Angsri N, Rerngpongpan S, Lertnakorn A. Patterns
of alcohol consumption in the Thai population: results of the National
Household Survey of 2007. Alcohol Alcohol. 2010;45(3):27885.
34. Derek D, Satre P, Nancy P, Gordon SD, Weisner C. Alcohol consumption,
medical conditions, and health behavior in older adults. Am J Health Behav.
2007;31(3):11.
35. Pearson TA. Alcohol and heart disease. Circulation. 1996;94(11):30235.
36. Weinstein N. Accuracy of smokersrisk perceptions. Ann Behav Med. 1998;
20(2):13540.
37. Humeniuk R, Henry-Edwards S, Ali R, Poznyak V, Monterio M. The ASSIST-
linked brief intervention for hazardous and harmful substance use: manual
for use in primary care. Geneva: World Health Organization; 2010.
38. Anton RF, OMalley SS, Ciraulo DA, et al. Combined pharmacotherapies and
behavioral interventions for alcohol dependence: the combine study: a
randomized controlled trial. JAMA. 2006;295(17):200317.
39. Font-Mayolas S, Gras ME, Planes M, Patino J, Sullman MJM. Risk Percption
and stages of smoking acquisition. Health Addict. 2013;13(2):11722.
40. Hanpatchaiyakul K, Eriksson H, Kijsomporn J, Östlund G. Barriers to successful
treatment of alcohol addiction as perceived by healthcare professionals in
Thailand a Delphi study about obstacles and improvement suggestions.
Glob Health Action. 2016;9. doi:10.3402/gha.v9.31738.
41. Wongtongkam N, Ward PR, Day A, Winefield AH. The influence of protective
and risk factors in individual, peer and school domains on Thai adolescents
alcohol and illicit drug use: a survey. Addict Behav. 2014;39(10):144751.
42. Treerutkuarkul A. Thailand's unsung heroes. Bull World Health Organ. 2008;
86(1):56.
43. Assanangkornchai S, Conigrave KM, Saunders JB. Religious beliefs and
practice, and alcohol use in Thai men. Alcohol Alcohol. 2002;37(2):1937.
44. Keawkingkeo S. Community drug abuse prevention in a Hmong village in
Thailand. J Psychosoc Nurs Ment Health Serv. 2005;43(2):229.
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... Functional belief is the belief that the individual must rely on the use of alcohol to cope with daily life and duties [33], whereas risk-minimizing belief is the belief that the individual is less likely to be adversely affected by alcohol use [27]. These types of health beliefs commonly help drinkers to reduce their cognitive dissonance about negative consequences from alcohol [34]. One study examined the association between self-perception of associated health risk from alcohol consumption and the five-item AUDIT score and found that young people with higher AUDIT scores were unlikely to perceive that their drinking level was problematic, and that hazardous consequences of this level of use were acceptable to them [35]. ...
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... The association between health beliefs and smoking behavior may differ based on sociocultural factors and norms [16,26]. These findings, particularly ones tracking patterns of beliefs and their association with quitting at Wave 2, highlight the key beliefs that drive smoking behaviors and provide evidence from a low-middle income country context. ...
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... One study that investigated the beliefs of nurses in Northern Thailand explored postpartum care and found discrepancies between nurses' beliefs and contemporary evidence-based practices (Kaewsarn, Moyle, & Creedy, 2003). Aside from this, the only recent study exploring beliefs of Thai health professionals was with regard to tobacco cessation (Jiraniramai et al., 2017). The authors concluded that there was a need to undertake further descriptive studies in regions where traditional cultural practices remain widespread to establish the nature of health professional beliefs, particularly in the context of widespread social and health policy change. ...
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... Smoking rationalisation can predict a lack of intention to quit. [20][21][22][23][24][25][26][27][28] To date, most of the evidence was found from European, USA or Australian samples, a few from Asian countries like Thailand and Malaysia, and there is no evidence from Chinese smokers. The extent to which smoking rationalisation predicts intention to quit among Chinese smokers remains unknown. ...
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Background High-risk drinking behavior is common in university students, which often leads to negative consequences. Several standard screening tools to identify high-risk drinkers have been validated in this domain. However, most tools rely on drinking frequency and require standard drink calculations. Functional-Belief-Based Alcohol use Questionnaire (FBAQ) was recently proposed as a pre-screening tool for high-risk drinkers in the young adult population. We aimed to validate the pre-screening accuracy of FBAQ when applied to external data of university undergraduates. Methods Data from two prospective cross-sectional surveys of Chiang Mai University undergraduates were used for validation of FBAQ. A high-risk drinker was defined as a 12-month AUDIT ≥ 8. Pre-screening performance and accuracy indices were presented separately for dataset I, dataset II, and the combined dataset. The pooled area under the receiver operating characteristic curve (AuROC), sensitivity, and specificity were estimated using individual patient data meta-analysis methods. Results From the two datasets, 1,641 students were included, 811 students in 2019 and 830 students in 2020. Of these, 387 (23.6%) students were classified as high-risk drinkers. The combined AuROC of the FBAQ score was 0.83 (95%CI 0.75 to 0.92) in discriminating high-risk drinkers. The pooled sensitivity and specificity at the FBAQ score cutoff ≥6 were 92.8% (95%CI 88.0, 95.7) and 51.6% (95%CI 41.1, 62.0). Conclusions In this external validation, FBAQ shows excellent discriminative ability and is proven to be highly sensitive in detecting high-risk drinkers among Chiang Mai University undergraduates. Therefore, incorporating FBAQ as a pre-screening tool to AUDIT could make the initiation of the screening process easier and reduce extensive AUDIT evaluations in students with low risk.
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Background: Many Thai people experiencing alcohol addiction do not seek help, and those who do often have inadequate access to treatment. There are few research studies focusing on alcohol addiction treatment in Thailand. Objective: The purpose of the current study was to identify barriers to the treatment of alcohol addiction and to collect experts' suggestions for improving treatment in Thailand. The Delphi technique was used to achieve consensual agreement among an expert panel within the field of alcohol addiction and treatment. Design: Three rounds of a Delphi survey were completed by a panel of experts in alcohol addiction, including physicians, nurses, social workers, psychologists, healthcare officers, and an Alcoholics Anonymous member. The open-ended answers provided by 34 experts in the first round resulted in 60 statements, which were later grouped into three themes. After three rounds of questionnaires, 51 statements were accepted as consensus. Results: Thirty-two experts participated in all three Delphi rounds. Over 80% of participants were particularly concerned about five obstacles to alcohol addiction treatment. The majority of suggestions from the expert panel were related to patients' right to treatment and the national policy for reducing the negative effects of alcohol. According to the results of the present study, the experts suggested that the treatment of alcohol addiction should be continuous from primary care to tertiary care, and convenient pathways should be established in healthcare services. The experts would also like to increase the number of healthcare providers and improve their knowledge and skills in working with people experiencing alcohol addiction. Conclusions: Equal rights to health and treatment for people experiencing alcohol addiction in Thailand require policy improvements, as well as acceptance and awareness of alcohol addiction from both the public and policymakers.
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Risk-minimizing beliefs refer to the underestimation of the health risks of particular behaviors. The aim of the study was to investigate the associations between risk-minimizing belief with smoking and the risk of harms from smoking in Northern Thailand (N=3,865). Adjusting for potential confounders, risk-minimizing belief was inversely associated with lifelong abstinence, positively associated with increased risk of being a current smoker, and weakly associated with increased risk of harm from smoking. Targeting risk-minimizing beliefs in current smokers and those who have never smoked may be useful in the Northern Thai population.
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The aim of this study was to conduct a cluster randomized control trial to assess the efficacy of screening and brief intervention (SBI) for conjoint alcohol and tobacco use among hospital out-patients. In all 620 hospital out-patients who screened positive for both tobacco and alcohol moderate risk in four hospitals were randomized into 2 control and 1 intervention condition using the hospital as a unit of randomization (2 intervention and 2 control hospitals) to 405 patients in the two control groups (tobacco only intervention, n = 199, and alcohol only intervention, n = 206) and 215 in the intervention group. The intervention or control consisted of three counselling sessions. Results of the interaction (Group × Time) effects using GEE indicated that there were statistically significant differences between the three study groups over the 6-month follow-up on the ASSIST tobacco score (Wald χ(2) = 8.43, P = 0.004), and past week tobacco use abstinence (Wald χ(2) = 7.34, P = 0.007). Although there were no significant interaction effects on the other outcomes (Alcohol ASSIST score, low alcohol risk score, past week tobacco abstinence or low alcohol risk score, and past week tobacco abstinence and low alcohol risk score), the scores in all of the six outcome measures showed consistent improvements. For past week tobacco abstinence the tobacco only intervention was more effective than the alcohol only intervention and the integrated alcohol and tobacco intervention. For the outcome of low alcohol risk, the alcohol only intervention and the integrated alcohol and tobacco intervention was more effective than the tobacco only or alcohol only intervention. The study found that for past week tobacco abstinence the tobacco only intervention was more effective than the alcohol only intervention and the polydrug use (alcohol and tobacco) integrated intervention.
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Background Urbanization is considered to be one of the key drivers of noncommunicable diseases (NCDs) in Thailand and other developing countries. These influences, in turn, may affect an individual’s behavior and risk of developing NCDs. The Chiang Mai University (CMU) Health Worker Study aims to provide evidence for a better understanding of the development of NCDs and ultimately to apply the evidence toward better prevention, risk modification, and improvement of clinical care for patients with NCDs and NCD-related conditions. Methods A cross-sectional survey of health care workers from CMU Hospital was conducted between January 2013 and June 2013. Questionnaires, interviews, and physical and laboratory examinations were used to assess urban exposure, occupational shift work, risk factors for NCDs, self-reported NCDs, and other NCD-related health conditions. Results From 5,364 eligible workers, 3,204 participated (59.7%). About 11.1% of the participants had high blood pressure (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) and almost 30% were considered to be obese (body mass index ≥25 kg/m2). A total of 2.3% had a high fasting blood glucose level (≥126 mg/dL), and the most common abnormal lipid profile was high low-density lipoprotein (≥160 mg/dL), which was found in 19.2% of participants. Discussion The study of health workers offers three potential advantages. The first is that the study of migrants was possible. Socioenvironmental influence on NCD risk factors can be explored, as changes in environmental exposures can be documented. Second, it allows the investigators to control for access to care. Access to care is potentially a key confounder toward understanding the development of NCDs. Lastly, a study of health personnel allows easy access to laboratory investigations and potential for long-term follow-up. This enables ascertainment of a number of clinical outcomes and provides potential for future studies focusing on therapeutic and prognostic issues related to NCDs.
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The success of primary health care programmes in Thailand over the past three decades can be attributed not only to medical advances but to the role of community health volunteers. Buddhist monks and their temples have been strongly involved in health promotion and education, particularly in remote, rural communities.
Research
The purpose of this descriptive survey was to investigate the risk perceptions of smoking in a sample of 1,510 Spanish adolescents (49.1% males; mean age = 14.03; SD = 1.28). In addition, the present research categorised adolescents into one of the four stages of smoking acquisition, as described by the Transtheoretical Model of Change (TMC): Precontemplation (not thinking about trying smoking in the next 6 months), Contemplation (thinking about trying smoking in the next 6 months), Preparation (thinking about starting smoking in the next 30 days) and Action (smokers), by gender and age. The results showed that age and risk perceptions are important variables in the progression through the stages of change towards regular tobacco consumption (Action stage). These results clearly demonstrate the importance of starting anti-smoking campaigns at an early age to prevent smoking acquisition or the thought of starting in the near future. These findings also highlight the need to continuously remind adolescents about the negative consequences of smoking.