2.1 theories and indexes
PRECEDE（Predisposing, Reinforcing, and Enabling Causes in Educational Diagnosis and Evaluation) is the evaluation phase of Green mode, also known as ecological mode of health promotion. Green mode stresses the conduction of ample evaluation of factors which influence behaviors: predisposing factor, enabling factor and reinforcing factor when developing health education plan. ①predisposing factor: the internal basis for behavior occurrence, including knowledge, belief, attitude, self-efficacy, etc. of the individual; ②enabling factor: the premise of the realization of behavior motivation and willingness, that is, the necessary skills, resources and social conditions for the realization or formation of behavior changes; ③reinforcing factor: the factor that provide continuous incentives for long-term maintenance or repetition of behaviors after occurrence. The predisposing factor is the internal motivation, and the enabling factor and reinforcing factor are the external conditions.
(1) predisposing factor
The theory believes "predisposing factor" would influence behaviors. This study, considering its characteristics, defined the core variables: Predisposing factors are students’ knowledge, attitudes, self-efficacy et, al. related to smoking cessation.
Among the questions about the knowledge of smoking cessation: 6 about tobacco epidemic, 10 about tobacco and disease, 5 about the harm of second-smoking on families and 9 about the regulations of smoking cessation.
Attitudes towards the participation in smoking cessation: ①Medical professionals should routinely implement the 5As to help smokers to quit; ② It is the responsibility of medical professional to help smokers to quit. Responses ranked from strongly disagree to strongly agree, scored on a scale of 1-5.
Self-efficacy: It is the proficiency of 5As in helping patients to quit smoking. Responses were from fully unskilled to very skilled, scored on a scale of 1-4.
(2) Enabling factor
The available tobacco cessation instruction and resources include the tobacco cessation education and guidance to students. Resources cover the familiarity with China Clinical Smoking Cessation Guidelines, tobacco cessation websites, smoking control drugs and consulting-phone number. Responses were from completely unknown to well known, scored on a scale of 1-5. The duration of tobacco cessation education for nursing students at school was: 0 minute, 30 minutes, 31-60 minutes, 1-2 hours, 2-3 hours, 3-4 hours, 4-5 hours or more than 5 hours. The number of 5As instructions from clinical tutors was also considered as one of the resources.
(3) Reinforcing factors
They were the factors that reinforce or interfere behaviors, such as the observations of 5As performed by clinical nurses in internship. Responses were scored 1 when never seen 5As performed by tutors in clinic, 2 when twice seen, 3 when 4-9 times seen, 4 when 10-25 times seen and 5 when over 25 times seen. When nursing students implement smoking cessation interventions, if they felt their behaviors were consistent with the setting, as well as the practice and expectation of tutors, they would reinforce and maintain those interventions.
(4) Result variables
The 5As interventions performed by students on patients in the period of internship: asking patients the status of smoking, advising smokers to quit, assessing the tobacco dependence and willingness to quit, assisting patients to quit and arranging following up services for those who were trying to quit. The number of patients helped by students with 5As was taken as result variable: 1= none patients, 2=1-3 patients, 3=4-9 patients, 4=10-25 patients and 5=>25 patients.
2.2 Pathway hypothesis that influences the 5As of nursing students to help patients to quit smoking
Green Mode told whether implementing health behaviors or not would be influenced by predisposing factors (knowledge, attitude and self-efficacy) and enabling factors (objective conditions and resources limitation), as well as reinforcing factors ( self-feeling and evaluation from others). Consequently, the pathway hypothesis was designed:
H1: Knowledge of tobacco cessation directly influences 5As performance
H2: Attitudes towards tobacco cessation directly influences 5As performance
H3: Self-efficacy of tobacco cessation directly influences 5As performance
H4: Education of tobacco cessation directly influences 5As performance
H5: Resources of tobacco cessation directly influences 5As performance
H6: Environment of tobacco cessation directly influences 5As performance
H7: Resources of tobacco cessation indirectly influences 5As performance through self-efficacy
H8: Education of tobacco cessation promotes self-efficacy and indirectly influences 5As performance
H9: Education of tobacco cessation enhances knowledge and indirectly influences 5As performance
H10: Education of tobacco cessation indirectly influences 5As performance through attitudes
H11: Environment of tobacco cessation indirectly influences 5As performance through attitudes
H12: Environment of tobacco cessation indirectly influences 5As performance through self-efficacy
H13: Attitudes towards tobacco cessation change the acquisition of relevant knowledge and indirectly influences 5As performance
H14: Self-efficacy of tobacco cessation indirectly influences 5As performance through attitudes
H15: Knowledge of tobacco cessation facilitate self-efficacy and indirectly influences 5As performance
See pathway in figure 1
2.3 Research objects and data collection
The design and method of this cross-sectional study in Chongqing has been previously reported . To get to know the 5As behaviors and influencing factors of nursing students in helping smokers to quit in clinic work, a web-based survey was conducted among nursing students in 13 teaching hospitals in Chongqing in January 2019. The study was approved by the ethics committee of the First Affiliated Hospital of Chongqing Medical University (2019-157). The participants were nursing students who were taking clinical practicum before graduation. A total of 1522 students participated in the study, with a response rate of 62.4% (1522 / 2400), excluding questionnaires fulfilled less than 180 seconds and addressed with non Chongqing areas. The effective questionnaires were 1358 with an effective rate of 89.2%.
2.4 Statistics and analysis
SPSS 20.0 software （IBM Corporation，Armonk，NY，US）was used to analyze the data. The characteristics of participants were descriptively analyzed by mean and standard deviation or constituent ratio. A structural equation model was developed by the software of Amos24 through path analysis. Firstly, confirmatory factor analysis was used to test the measurement variables whose effectiveness was evaluated by the measurement results of SEM. Factor load indicated how much they contributed to latent variables, and aggregation validity evaluated the internal consistency of the questionnaire through composite reliability (CR) and average variance extracted (AVE). This study described the differential validity through the comparison of the square value of the correlation coefficient between AVE and latent variables. When AVE was higher than the square value of the correlation coefficient among latent variables, the differential validity between latent variables was better. The latent variables included smoking cessation knowledge, attitude, self-efficacy, education, resources, environment and 5As behaviors. Then, a structural equation model was used to test the relationship among target variables. This model made an assessment by generalized least square (GLS) instead of maximum likelihood (ML), because the data went beyond the hypothesis of multivariate normality and the sample size was quite large. The theoretical mode was tested and revised until it was theoretically and statistically acceptable. Generally, the ratio of chi square to degree of freedom was used to assess the model fit, and the relative chi square should be less than 2.0. But it was sensitive to the sample size and a large size might induce a significant chi square. Thus, other variable measures had also been adopted, including Root Mean Square Error of Approximation（RMSEA）< or =0.05，Goodness-of-fit Index（GFI）and Adjusted Goodness-of-fit Index（AGFI）> or = 0.9, Parsimony Normed Fit Index（PNFI）and Parsimony Goodness-of-fit Index（PGFI）and Parsimony Comparative Fit Index（PCFI）>0.5. As a result, the final fit model indicated the correlation and the estimates and levels of regression parameters.