You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


1. Introduction {#s0005}
===============

Quitting smoking at any age affords significant health benefits in secondary care organizations, such as fewer complications and shorter hospital stays ([@bb0015]). People who stop smoking after diagnosis of early stage lung cancer also have better prognostic outcomes than the patient who continues smoking ([@bb0070]). Thus, health professionals working in a hospital setting have the responsibility to promote healthy behavior among patients in their organization. Due to the above reasons, promoting smoking cessation is of paramount importance to secondary care.

Tobacco control is also an important issue in Taiwan. The tobacco health and welfare tax was instituted by the Taiwanese government in 2002. Funds from the tax were used to initiate and maintain several smoking cessation outpatient programs ([@bb0020]). Although doctors had some financial incentives to provide medication (either nicotine replacement therapy or varenicline) and brief cessation consulting during routine outpatient visits, patients attempting to quit smoking had to pay 550--1250 NTD (New Taiwan dollars) (approx. US\$18--42) every week for medication. Due to these out of pocket costs, the smoking cessation rate remained unsatisfactory. In order to encourage more smokers to use the smoking cessation service, the Taiwanese government implemented the New Smoking Cessation Policy in March 2012. In the new policy, (i) all outpatients and inpatients can use the smoking cessation clinic service (ii) patients pay no more than 200 NTD (US\$6.6), per week for two 8 week courses each year. As a result, the number of smokers using the smoking cessation service from March 2012 to February 2013 increased by 39.2% compared to March 2011 to February 2012. The 6-month point abstinence rate during March 2012 to May 2013 was 30.3%, while it was only 23.9% during the decade of February 2002 to February 2012.

In Taiwan, many smokers have health problems, and they have been referred to smoking cessation service during admission or routine clinics by hospital staff, including physicians, nurses and administration staff ([@bb0025], [@bb0060]). However, few studies have elucidated factors that affect the likelihood of referral. This lack of knowledge poses challenges to any health care institution. It is necessary to understand the influential factors. In this study, we aim to explore the barriers and the variables related to hospital staff willingness to provide smoking cessation referrals so that we can contribute to the development of smoking cessation service.

2. Methods {#s0010}
==========

2.1. Design {#s0015}
-----------

This study represents a cross-sectional questionnaire survey of 1500 employees at a 850 beds community hospital in New Taipei City, Taiwan. Paper surveys were given to each department then distributed to the staff during the period of December 2012 to February 2013. The data was analyzed in 2014. Informed consent was implied by the return of the questionnaire. All study procedures were approved by the ethical committee of the hospital.

2.2. Participants {#s0020}
-----------------

The target population was the entire staff of the community hospital. The survey period was from December 2012 to February 2013. The staff included physicians, nurses and administrators.

2.3. Instrument {#s0025}
---------------

A questionnaire with four parts was administered to all participants. Questions on staff demographic characteristics, knowledge of basic cigarette harm and smoking cessation, knowledge of resources and methods about smoking cessation, and willingness to provide smoking cessation referral were included. The questionnaire was designed after careful scrutiny of the literature by a group of experts.

Variable included category of work, smoking status. We also asked about previous participation of smoking awareness activities. These events are usually held in or around the hospital including free exhaled carbon monoxide sampling, free lung function testing, etc. that raise general awareness about the harmful effects of smoking. We also asked whether the staff have interest in receiving more education about smoking cessation. Smoking cessation education for hospital staff included consulting training, review of available medications and pharmacology, and an overview of available resources for patient referral. The other 3 sections are described below.1.Knowledge of basic cigarette harm

Knowledge of basic cigarette harm was measured with six items. All items were based on the clinical experience of investigators and literature review ([@bb0080], [@bb0035], [@bb0005], [@bb0055]). The section contained 6 items, and was scored as true = 1 and false/unknown = 0 for each item with highest potential score of 6.2.Resources and methods about smoking cessation

Seven survey items were included to measure knowledge regarding methods and resources about smoking cessation. These items were decided by journal review ([@bb0085], [@bb0010], [@bb0075]) and experts\' practical experience. The section included 7 items, and was scored as true = 1 and false/unknown = 0 for each item with highest potential score of 7.3.Willingness to provide smoking cessation referral

This section examined staff willingness to provide patients with smoking cessation referral. Willingness was graded using yes = 1 and no = 0.

2.4. Statistical analysis {#s0030}
-------------------------

Data management and statistical analyses were calculated by SPSS 11.0 statistical software. Frequency distributions were used to describe the demographic data and the distribution of each variable. Mean values and standard deviations (SDs) were measured to analyze the association of each variable with occupation, smoking status, interesting in receiving smoking cessation education, knowledge of basic cigarette harm, knowledge of resources and methods regarding smoking cessation, and willingness to provide smoking cessation referral. Logistic regression analysis determined the relative values of the variables related to willingness to provide smoking cessation referral. A value of *p* \< 0.05 was considered statistically significant.

3. Results {#s0035}
==========

3.1. Study participant characteristics {#s0040}
--------------------------------------

Questionnaires were given to all hospital staff a total of 1500 people. And complete information was collected from 848 people for a response rate of 56.5%. There were 249 physicians (29.4%), 402 nursing staff (47.4%), and 197 administration staff (23.2%). Seven hundred and ninety (93.2%) staff members had never smoked, 19 (2.2%) had quit smoking, and 39 (4.6%) still smoked at that time. Of the 848 staff, 114 (13.4%) had ever joined a smoking cessation awareness activity. Seven hundred twenty-nine staff (93.4%) had interest in receiving smoking cessation education in the future. Seven hundred ninety-six (93.9%) staff had a supportive attitude toward creating a smoking free hospital, defined as having an indoor non-smoking policy with smoking cessation clinic available for anyone interested. 699 (82.4%) staff members thought that smoking cessation education was important. The mean total score of basic cigarette harm knowledge was 4.56 (± 1.25) out of 6. The mean total score of resources and methods about smoking cessation was 4.79 (± 1.35) out of 7 ([Table 1](#t0005){ref-type="table"}).

3.2. Basic knowledge of cigarette harm {#s0045}
--------------------------------------

Comparing basic knowledge of cigarette harm in willing to refer staff versus unwilling to refer staff is summarized in [Table 2](#t0010){ref-type="table"}. The correct items in each group are expressed by number and percentage. Stratified analyses were performed on the basic knowledge of cigarette harm in willing to refer and unwilling to refer groups. There was no significant difference between referral willingness in staff who knew about nicotine effect, secondhand smoking harm and risk to infertility and those who did not. However, staff who knew the correct answer regarding dependence mechanism, addictive substances, and associated smoking disease were more willing to refer patients for smoking cessation assistance (*p* \< 0.05).

3.3. Knowledge of resources and methods about smoking cessation {#s0050}
---------------------------------------------------------------

[Table 3](#t0015){ref-type="table"} shows the items surveyed and percentage of accurate responses regarding methods and resources of smoking cessation in willing to refer versus unwilling group. Knowing the correct answer about dependence mechanism, vitamin C decreasing nicotine craving, food choices during smoking cessation, supportive environment factors and exhaled CO detection methods did not affect the willingness to refer. Staff who knew light cigarettes as harmful as regular cigarettes and were more aware of outpatient and inpatient smoking cessation resources were more willing to refer ([Table 3](#t0015){ref-type="table"}).

3.4. Significant variations in knowledge of survey items by type of hospital staff {#s0055}
----------------------------------------------------------------------------------

Different hospital staff had significantly varied knowledge of survey items as shown in [Fig. 1](#f0005){ref-type="fig"}. Physicians and nursing staff had more correct knowledge of cigarette harm and methods about smoking cessation than did administration staff. For example, 190 physician (76.3%) and 310 nursing staff (77.1%) knew the dependence mechanism. However, only 114 administration staff (57.9%) understood the concept of dependence mechanism.

3.5. Important variables correlated with willingness of referral {#s0060}
----------------------------------------------------------------

Logistic regression analysis showed that willingness to refer is not affected by smoking status, occupation, interest in receiving smoking cessation education, and total basic cigarette harm score. The significant variable correlated with willingness of referral was total score of resources and methods about smoking cessation (odds ratio = 1.221, 95% confidence interval = 1.001--1.489) ([Table 4](#t0020){ref-type="table"}).

4. Discussion {#s0065}
=============

This is the first study to understand what factors affect hospital staff to provide smoking cessation referral in Taiwan. According this study, having more knowledge of resources and methods about smoking cessation is the key factor for referral by staff in secondary care. Although smoking cessation is an important issue in Taiwan, not every health care staff member has received education about this topic. In order to improve current smoking cessation strategy, the continued education and training programs for health employees should include resources and methods regarding smoking cessation.

The Taiwanese government began implementing smoking cessation service programs in 2002. Only physicians, nurses and pharmacists who are certified by a smoking cessation training program can be reimbursed for their services. [@bb0040] evaluated the training program as appropriate and effective. However, only health care professionals involved in smoking cessation attend the training program. Many hospital staff still lack correct information regarding smoking harm and smoking cessation. In this study, we emphasize that knowledge of basic smoking harm, and knowledge of methods and resources about smoking cessation does affect willingness to refer patients for smoking cessation. According to our results, staff who knew the correct answer regarding dependence mechanism, addictive substances, and associated smoking disease were more willing to refer. Staff who had correct conceptions about smoking cessation and were more aware of outpatient and inpatient smoking cessation resources were also more willing to refer for smoking cessation.

To promote smoking cessation, WHO and NICE guidelines recommend that all staff be trained to support smokers who seek secondary service to quit smoking ([@bb0090], [@bb0050]). In fact, not all employees in secondary care institution are well trained. For instance, in our study, only 79.5% of physicians knew that cigarettes could cause infertility. Moreover, little more than half of staff members -- only 60.2% of doctors, 65.4% of nurses and 52.3% of administration staff -- knew about inpatient smoking cessation resources. If the hospital staff does not know about a particular service, how can patients be referred to it? Additional on-the-job training should increase likelihood of smoking cessation referral in a health care institution.

Physicians not only serve as role models for patients but also play a significant role as advisers who influence smoking cessation in patients. Despite this, physicians do not routinely discuss smoking cessation, as shown in a German study by [@bb0045]. Previous studies of physician related variables determined that the main barriers include: insufficiency of time to provide consult, limited perceived role, patients\' inability to afford medication, lack of familiarity with a service, lack of education in smoking cessation skills, and the physician\'s smoking status ([@bb0065], [@bb0030]). Their results show that a physician\'s smoking status may influence the offer of smoking cessation treatments to patients. Doctors who currently smoke are less likely to advise and counsel their patients to quit than non-smokers or ex-smokers. However, [@bb0030] also point out that smoking physicians are more likely to refer patients to smoking cessation programs. Our study involved not only physicians, but also other hospital staff including nurse and administration. In contrast to previous literature, our results indicate that smoking status is not a significant factor correlated with willingness of referral. One reason for this may be that only 39 staff members (4.6%) out of 848 total smoke. Occupation, interest in receiving smoking cessation education, and total score of basic smoking harm knowledge were not factors either. The significant variable affecting willingness of referral was the total score of methods and resources smoking cessation. By knowing more about methods and resources of smoking cessation, the hospital staff will be more likely to provide smoking cessation referral for patients. The results of this study might provide a focus for training medical personnel in secondary care and stimulate discussion of smoking cessation knowledge to the effect of promoting quitting.

There are some limitations to this study. First, only one community hospital was included in this study. If several secondary care institutions were included, the result may be more comprehensive and reliable. Second, only 56.5% of the staff surveyed returned the completed questionnaires. Distributing the questionnaire to the staff in daily work setting might have reduced the response rate. Third, because this study was a cross-sectional survey, it is strongly suggested that to devise a future follow-up study which could show the effects of education about smoking cessation.

WHO recommends that all health professionals, including physicians, dentists, pharmacists, nurses and others can be instrumental in helping smokers quit tobacco use ([@bb0090]). Tobacco control should be involved in continued education and training programs for health employees ([@bb0090]). NICE guidelines also mentioned that it is necessary to ensure that staff are trained to support smokers in quitting smoking while seeking secondary care service ([@bb0050]). WHO and NICE both agree that education for health care professionals regarding tobacco control is crucial for smoking cessation success. However, the content of these education programs is not specified in the guidelines. According to our study, staff who are more knowledgeable about the methods of quitting and available smoking cessation programs for inpatients and outpatients are more willing to refer. Thus, guidelines for tobacco control may emphasize the importance of methods and resources about smoking cessation in the continued education and training programs to ensure that all the members of health care organizations are able to give smoker appropriate advice. This kind of survey should be adopted in other countries, and certain results could provide new insights for tobacco control and future focus for research.

5. Conclusion {#s0070}
=============

According to this study, hospital staff who knew more about methods and resources for smoking cessation were more willing to refer patients to the smoking cessation service. This finding could be useful for medical education of hospital staff to promote smoking cessation.

Conflict of interest statement {#s0075}
==============================

The authors declare that there are no conflicts of interest.

All authors had full access to all the data in the study and take responsibility for the integrity of the data analysis. Yin-Yu Chang and Hsien-Liang Huang designed data collection tools, monitored data collection for the whole study, wrote the statistical analysis plan, cleaned and analyzed the data, and drafted and revised the paper. Shu-Man Yu, Yun-Ju Lai, Ping-Lun Wu, and Kuo-Chin Huang designed data collection tools and cleaned and analyzed the data.

![Different hospital staff have significantly varied knowledge of survey items.](gr1){#f0005}

###### 

Variables related to the willingness of referral.

Table 1

  Variables                                                      n               \%
  -------------------------------------------------------------- --------------- -------
  Occupation                                                                     
   Physician                                                     249             29.4
   Nursing staff                                                 402             47.4
   Administration staff                                          197             23.2
  Smoking status                                                                 
   Yes                                                           39              4.6
   Quit                                                          19              2.2
   Never                                                         790             93.2
  Ever joined smoking cessation awareness activity                               
   Yes                                                           114             13.4
   No                                                            734             86.6
  Interest in receiving smoking cessation education                              
   Yes                                                           792             93.4
   No                                                            56              6.6
  Attitude toward smoking free hospital                                          
   Supportive                                                    796             93.9
   Not at all or fairly supportive                               52              6.1
  Attitude toward smoking cessation education                                    
   Important                                                     699             82.4
   Not at all or fairly important                                149             17.6
  Variables                                                      Mean (± SD)     Range
  Total score of basic cigarette harm knowledge                  4.56 (± 1.25)   0--6
  Total score of resources and methods about smoking cessation   4.79 (± 1.35)   0--7

###### 

Comparing basic knowledge of cigarette harm in willing to refer versus unwilling group of hospital staff.

Table 2

  Knowledge survey item                                       Correct answers among willing to refer group[a](#tf0015){ref-type="table-fn"}   Correct answers among unwilling group[b](#tf0020){ref-type="table-fn"}   *p*-Value[⁎](#tf0005){ref-type="table-fn"}          
  ----------------------------------------------------------- ------------------------------------------------------------------------------- ------------------------------------------------------------------------ -------------------------------------------- ------ -------
  1\. Dependence mechanism[†](#tf0010){ref-type="table-fn"}   568                                                                             73.5                                                                     56                                           61.3   0.025
  2\. Nicotine effect                                         653                                                                             84.5                                                                     60                                           80     0.312
  3\. Associated disease[†](#tf0010){ref-type="table-fn"}     534                                                                             69.1                                                                     40                                           53.3   0.005
  4\. Addiction substances[†](#tf0010){ref-type="table-fn"}   744                                                                             96.2                                                                     66                                           88     0.001
  5\. Secondhand smoke harm                                   595                                                                             77                                                                       51                                           68     0.082
  6\. Risk to infertility                                     619                                                                             80.1                                                                     56                                           74.7   0.267

The *p*-value was calculated using the chi-square test for the analysis between willing to refer and unwilling to refer group.

Item with *p*-value \< 0.05.

Willing to refer number = 773.

Unwilling to refer number = 75.

###### 

Comparing knowledge of resources and methods about smoking cessation in willing to refer versus unwilling group of hospital staff.

Table 3

  Knowledge survey item                                                                             Correct answers among willing to refer group[a](#tf0035){ref-type="table-fn"}   Correct answers among unwilling group[b](#tf0040){ref-type="table-fn"}   *p*-Value[⁎](#tf0025){ref-type="table-fn"}          
  ------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------- ------------------------------------------------------------------------ -------------------------------------------- ------ ----------
  1\. Vitamin C decreases craving                                                                   457                                                                             59.1                                                                     38                                           50.7   0.156
  2\. Food choices during smoking cessation                                                         309                                                                             40                                                                       28                                           37.3   0.655
  3\. Light cigarettes are equally harmful as regular cigarettes[†](#tf0030){ref-type="table-fn"}   732                                                                             94.7                                                                     63                                           84     \< 0.001
  4\. Supporting environment factors                                                                370                                                                             47.9                                                                     38                                           50.7   0.643
  5\. Exhaled CO detection methods                                                                  466                                                                             60.3                                                                     50                                           66.7   0.280
  6\. Outpatient clinics smoking cessation resources[†](#tf0030){ref-type="table-fn"}               750                                                                             97.0                                                                     59                                           78.7   \< 0.001
  7\. Inpatient smoking cessation resources[†](#tf0030){ref-type="table-fn"}                        447                                                                             57.8                                                                     19                                           25.3   \< 0.001

The *p*-value was calculated using the chi-square test for the analysis between willing to refer and unwilling to refer group.

Item with *p*-value \< 0.05.

Willing to refer number = 773.

Unwilling to refer number = 75.

###### 

The significant variables influencing the willingness of referral for smoking cessation.

Table 4

  Variables                                                      OR      95% CI
  -------------------------------------------------------------- ------- --------------
  Smoking status                                                 1.424   0.523--3.877
  Occupation                                                     1.054   0.527--2.110
  Wiling to receive smoking cessation education                  0.546   0.252--1.185
  Total score of basic cigarette harm knowledge                  1.181   0.961--1.452
  Total score of resources and methods about smoking cessation   1.221   1.001--1.489

OR, odds ratio; CI, confidence interval.