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Multistate Stochastic Process for Quitting Smoking for Taiwanese Males
No full text研究目的
有關台灣地區戒菸行為模式，過去研究雖多有探討，但是鮮少對不同階段之間提出新的解釋模型以及影響因子之探討。本研究目的有二：(1)參考跨理論行為模式，提出適合台灣地區戒菸門診中多階段戒菸模型(持續抽菸、猶豫戒菸及戒菸成功)，(2)探討戒菸族群在菸癮戒除過程中，由抽菸期轉移至心存猶豫以及戒菸成功等階段的影響因子。
材料與方法
本研究所使用的資料主要來自國民健康局自2003年起各縣市所推動的門診戒菸計劃，此計劃透過醫療院所以及社區衛生所辦理門診戒菸來協助民眾戒菸，對於18歲以上之成人，尼古丁成癮度達4分以上或平均一天吸10支菸以上，願意接受簽約之醫療院所所提供之戒菸治療，共收案2,791人。本研究將戒菸過程定義為三個分期，分別為抽菸期(Smoking Phase)、猶豫期(Hesitation Phase)及戒菸成功期(Quitting Smoking)。根據本研究架構所定義的多階段分期可知本研究之依變項包括(1)戒菸猶豫期以及(2)戒菸成功。在自變項部分，我們利用門診戒菸記錄表與電訪所收集之資料，作為本研究各階段相關因子的定義，概分為個案戒菸經驗、個案健康狀況、個案菸癮相關因子、周遭親友疾病經驗，與自覺健康與效益等因素。由於門診戒菸記錄表並未追蹤戒菸成果，本結果設計一問卷進行電話訪談收集民眾戒菸成果、自覺健康、親友疾病經驗、對門診戒菸的記憶以及門診戒菸的效益訊息。
在資料分析方面，本研究利用羅吉斯迴歸模式（Logistic Regression Model）分析影響是否參加第二次以上的戒菸門診及是否戒菸成功兩種二元事件的各別影響因子，並利用比例危險迴歸模式（Proportional Hazards Regression Model）分析在考慮最後一次接受戒菸門診到戒菸成功時所花費時間的影響因子，最後利用多階段模式（Multi-state Model）量化個人在抽菸與意圖戒菸之間行為的轉移及兩種狀態其分別進展至戒菸成功的轉移率。
結果
本研究之研究族群共2,791人，分別來自基隆市(n=125人)、台北縣(n=1,124人)、台南縣(n=1,308人)、連江縣(馬祖)(n=123人)及台東縣(n=111人)等五個縣市在2004年至2006年間參加戒菸門診的民眾，其中主要以台北縣及台南縣為主，各佔40.3%及46.9%。
在影響戒菸猶豫期之相關因子方面包括有個案年齡 (OR=1.01, 95% CI: 1.00-1.01, p=0.0009)、是否罹患過肝病 (OR=1.64, 95% CI: 1.09-2.47, p=0.0189)、在禁菸區會感到難受 (OR=1.21, 95% CI: 1.03-1.41, p=0.0172)，以及戒菸門診提供單位 (OR=1.67, 95% CI: 1.26-2.21, p=0.0004)。
影響戒菸成功相關因子有越年邁者越容易戒菸成功 (OR=1.05, 95% CI=1.03-1.08, P<.0001)，菸齡在15(含)年以下者相對戒菸成功比較高 (OR=6.03, 95% CI=2.27-16.04, P=0.0003)，自覺健康較同年齡者佳者，有較高的相對戒菸成功比 (OR=7.14, 95% CI=3.22-15.83, P<.0001)，自己罹患有糖尿病者，相對戒菸勝算比為3.02 (95% CI=1.08-8.44, P<0.0349)，因自己有健康問題而參加門診戒菸者，相對戒菸成功比為2.23倍，(95% CI=0.99-5.00, P<0.0520)。
以比例危險迴歸模式進行多變項分析，其中菸齡的解釋力最大，菸齡小於15年者其戒菸速率為大於者之4.45倍（95%信賴區間：1.93-10.29）。再者為本身為糖尿病患者，其戒菸速率為非糖尿病患者之2.71倍（95%信賴區間：1.25-5.89）。接著為自覺健康狀態，其中自覺健康比較好者的戒菸速率為自覺健康比較差者的2.34倍（95%信賴區間：1.53-3.58），覺得沒有差者約為自覺健康比較差者的四成（95%信賴區間：0.24-0.57）。當嚴重生病、臥病在床時不會抽菸者為仍會抽菸者之1.89倍（95%信賴區間：1.20-2.97）。年齡每增加一歲其戒菸成功速率增為1.04倍(95%信賴區間：1.02-1.06)。
利用連續時間馬可夫模式估計個案在抽菸期、猶豫期及戒菸期之間，估計結果顯示個案從抽菸期轉變到猶豫期的轉移速率約為每天1.85次（95%信賴區間：0-7.24），由猶豫期返回抽菸期的速率則為每天0.64次（95%信賴區間：0-2.50），由抽菸期和猶豫期分別進展至戒菸期的轉移速率則分別為每天2.69Objectives:
Despite a number of studies addressing smoking cessation outpatient service (SCOS) in Taiwan, very few studies have been conducted to address factors associated with different stages of smoking behaviour change or to propose a new model to accommodate such a multi-state process. The present study aimed (1) to propose a new stage of change model to interpret the behaviour of outpatient smoking cessation in Taiwan and (2) to assess relevant factors associated with different behaviour change states, from smoking phase either to hesitation phase or to quitting smoking.
Methods:
The study subjects (n=2,791) were enrolled from the 2004-2006 SCOS in five Taiwan Counties and a telephone interview design. By defining state of change with three phases related to smoking quitting process, including current smoking phase, hesitation phase, and quitting smoking phase were proposed. Independent variables used in our analyses included (1) basic information of smokers with their quitting smoking experiences (2) personal health status (diseases) (3) nicotine dependent factors (4) diseases histories of their friends and relatives (5) perceived health status.
We used logistic regression models to elucidate the effects of relevant factors on whether to have more than two visits of SCOS or whether to quit smoking successfully respectively. The proportional hazards regression model was used to analyze the effects of relevant risk factors on time to smoking cessation. Finally, we applied the multi-state models to quantify the transitions between smoking, hesitation to quit, and quitting from the two states.
Results:
Factors associated with hesitation phase include age, personal diseases with liver diseases, feeling discomfort in the non-smoking area, those who received the smoking cessation outpatient service from the public health centers, were identified as significant predictors. Factors associated with quitting smoking included age, smoking age, perceiving better health than peers, having diabetes mellitus, and attending the smoking cessation clinic due to personal perceived illness. Results of proportional hazards regression model found those who were more likely to quit smoking were elderly, short duration of smoking age, having diabetes mellitus, perceiving better health than peers, or stopping smoking when being ill in bed.
In the continuous-time Markov model, the transition rate from smoking to hesitation phase was estimated as 1.85 per day (95% CI: 0-7.24), and the estimated regression rate from hesitation phase to smoking was 0.64 per day (95% CI: 0-2.50). The daily successful quitting rates from smoking and from hesitation phase in the previous time were estimated as 2.69x10-4 (95% CI: 1.87 x10-4-3.50 x10-4) and 2.44 x10-4 (95% CI: 1.18 x10-4-3.71 x10-4), respectively. In terms of annual quitting rates, the figures were 0.0982 (95% CI: 0.0684-0.1279) and 0.0891 (95% CI: 0.0432-0.1353), respectively. Those perceived healthier has 3.18 times higher quitting rate compared with those perceived worse or equal health. The corresponding figure from hesitation phase was 16.27 (95% CI: 3.74-71.28). Heavy smokers with desire of smoking which having serious diseases had 1.41 (95% CI: 0.98-2.02) times higher transition rate from smoking phase to hesitation phase. The corresponding figure for the regression from hesitation phase back to smoking phase was 1.64 (95% CI: 1.15-2.35).
Conclusions:
We proposed a new model of multi-state stochastic process for quitting smoking for Taiwanese males who using smoking cessation outpatient service. This multi-state model included smoking phase, hesitation phase and quitting smoking. Using different regression models, the results found those who were more likely to quit smoking were elderly, perceiving better health than peers, having diabetes mellitus, or stopping smoking when being ill in bed. Such a novel multi-state model may be applied to aid men in any phases to quit smoking.誌謝
中文摘要
英文摘要
第一章 緒論……………………………………………………… 1
第一節 研究背景與動…………………………………………… 1
1.1.1 抽菸之盛行率與對健康的危害…………………………. 1
1.1.2 國內門診戒菸實………………………………………… 1
第二節 研究目的………………………………………………….3
第二章 文獻探討………………………………………………… 4
第一節 菸害防制簡史………………………………………… 4
第二節 慢性抽菸成癮與戒除行為……………………………… 5
2.2.1 抽菸成癮…………………………………………………… 5
2.2.2 抽菸行為的定義…………………………………………… 7
2.2.3 抽菸行為狀態的測量……………………………………… 7
2.2.4 戒菸的定義………………………………………………… 8
2.2.5 戒菸之盛行率與戒菸之益處……………………………… 8
第三節 台灣菸害防制計畫……………………………………… 9
2.3.1 菸害防制法………………………………………………… 9
2.3.2 無菸校園……………………………………………………10
2.3.3 創造無菸環境，降低二手菸暴露…………………………10
2.3.4 國民健康局門診戒菸治療計畫………………………… 10
2.3.5 國民健康局門診戒菸治療計畫之成本效益分析…………12
第四節 戒菸方法與成效…………………………………………13
2.4.1 菸害防制的實證方法………………………………………13
2.4.2 戒菸成效之相關因子………………………………………15
2.4.3 尼古丁替代療法順從性……………………………………16
2.4.4 國內戒菸成效相關之研究…………………………………18
第五節 尼古丁替代療法…………………………………………19
2.5.1 尼古丁替代藥物之發明……………………………………19
2.5.2 尼古丁替代療法……………………………………………20
2.5.3 尼古丁替代療法之治療效果………………………………21
第六節 門診戒菸利用之理論架構………………………………23
2.6.1 跨理論模式…………………………………………………23
2.6.2 行為改變模式理論於戒菸上之應用………………………25
第三章 材料與方法………………………………………………26
第一節 戒菸過程模式……………………………………………26
第二節 目標族群…………………………………………………26
3.2.1 戒菸猶豫期研究族群………………………………………27
3.2.2 戒菸成功研究族群…………………………………………27
3.2.3 結合社區整合式篩檢資料庫進行戒菸成功相關因子探討28
第三節 變項定義…………………………………………………30
3.3.1 依變項………………………………………………………30
3.3.2 自變項………………………………………………………30
第四節 資料收集…………………………………………………31
第五節 尼古丁替代療法戒菸成效之統合分析…………………32
3.5.1 統計分析方法………………………………………………32
第六節 戒菸多階段模型建構……………………………………35
第七節 統計方法…………………………………………………36
3.7.1 羅吉斯迴歸模式……………………………………………36
3.7.2 比例危險迴歸模式…………………………………………36
3.7.3 多階段模式…………………………………………………37
第四章 結果………………………………………………………40
第一節 基本資料描述……………………………………………40
第二節 統合分析結果……………………………………………47
第三節 影響戒菸猶豫期之相關因子(羅吉斯回歸分析)………52
第四節 影響戒菸成功相關因子…………………………………59
第五節 影響戒菸成功相關因子之比例危險迴歸模式分析……69
第六節 多階段（抽菸期－猶豫期－戒菸期）模式分析結果…76
第七節 合併整合式篩檢之結果…………………………………81
第五章 討論………………………………………………………83
第一節 主要發現…………………………………………………83
第二節 多階段改變理論的革新…………………………………84
第三節 中西菸癮戒除行為與認知………………………………85
第四節 與國外文獻的比較………………………………………86
第五節 研究方法之新穎…………………………………………88
第六節 研究限制與顧慮…………………………………………89
第六章 結論………………………………………………………91
參考文獻……………………………………………………………92
圖表目錄
圖目錄
圖3-2-3 研究族群…………………………………………………29
圖3-5-1 尼古丁輔助戒菸之隨機效應分析模式…………………33
圖3-5-2 考慮觀察時間因素之NRT之隨機效應羅吉斯迴歸模式 34
圖3-6-1 三階段行為模型…………………………………………35
圖4-2-3 尼古丁輔助戒菸隨機分派試驗統合分析………………51
表目錄
表2-2-1 Fagerström尼古丁依賴測試表…………………………6
表2-3-4 目前台灣已引進或常用戒菸治療藥物…………………12
表2-4-1 戒菸之實證方法…………………………………………14
表4-1-1 研究族群來源地區(縣市)及使用門診時間(年份)……40
表4-1-2 研究族群戒菸經驗分佈…………………………………42
表4-1-3 研究族群疾病經驗分佈…………………………………44
表4-1-4 研究族群菸癮相關因子分佈……………………………46
表4-2-1 戒菸尼古丁輔助介入隨機分派結果之文獻整理………48
表4-2-2 統合分析危險對比值……………………………………49
表4-2-3 考慮觀察時間對於尼古丁輔助戒菸隨機分派試驗統合分析…… 50
表4-3-1 羅吉斯回歸分析猶豫期相關因子單變項分析(戒菸經驗)………. 53
表4-3-2 羅吉斯回歸分析猶豫期相關因子單變項分析(個人疾病經驗)… 55
表4-3-3 羅吉斯回歸分析猶豫期相關因子單變項分析(菸癮相關因子)… 57
表4-3-4 羅吉斯回歸分析菸猶豫期相關因子多變項分析………58
表4-4-1 北縣南縣戒菸成功相關因子單變項分析(戒菸經驗)………… 60
表4-4-2 北縣南縣戒菸成功相關因子單變項分析(個人疾病經驗)……… 62
表4-4-3 北縣南縣戒菸成功相關因子單變項分析(個人菸癮相關因子)… 64
表4-4-4 北縣南縣戒菸成功相關因子單變項分析(親友得病經驗)………. 66
表4-4-5 北縣南縣戒菸成功相關因子單變項分析(自覺健康效益)……… 67
表4-4-6 北縣南縣戒菸成功相關因子多變項分析………………68
表4-5-1 比例危險迴歸模式進行兩縣族群戒菸成功速率之
單變項分析 (戒菸經驗)……………………………………………69
表4-5-2 比例危險迴歸模式進行兩縣族群戒菸成功速率之
單變項分析 (個人疾病經驗)………………………………………70
表4-5-3 比例危險迴歸模式進行兩縣族群戒菸成功速率之
單變項分析 (個人菸癮相關因子)…………………………………71
表4-5-4 比例危險迴歸模式進行兩縣族群戒菸成功速率之
單變項分析 (親友健康經驗/健康信念模型(意感威脅)因子)… 72
表4-5-5 比例危險迴歸模式進行兩縣族群戒菸成功速率之
單變項分析 (自覺健康效益)………………………………………73
表4-5-6 比例危險迴歸模式進行兩縣族群戒菸成功速率之多變項分析… 75
表4-6-1 應用多階段連續時間馬可夫模式於
戒菸研究階段間轉移速率估計結果……………………………… 76
表4-6-2 應用多階段間斷時間馬可夫模式於
戒菸研究階段間轉移機率估計結果……………………………… 78
表4-6-3 影響多階段間斷時間馬可夫模式於
戒菸機率之相關因子分析………………………………………… 79
表4-6-4 影響多階段間斷時間馬可夫模式於
抽菸期及猶豫期間轉移機率之相關因子分析…………………… 80
表4-7-1 結合整篩後戒菸成功相關因素多變項羅吉斯廻歸分析結果…… 8
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sophisticated methods
The Solid-State Neck Growth Mechanisms in Low Energy Laser Sintering of Gold Nanoparticles: A Molecular Dynamics Simulation Study
No full textMolecular dynamics (MD) simulations were employed to investigate the mechanism and kinetics of the solid-state sintering of two crystalline gold nanoparticles (4.4-10.0 nm) induced by low energy laser heating. At low temperature (300 K), sintering can occur between two bare nanoparticles by elastic and plastic deformation driven by strong local potential gradients. This initial neck growth occurs very fast (< 150 ps), and is therefore essentially insensitive to laser irradiation. This paper focuses on the subsequent longer time scale intermediate neck growth process induced by laser heating. The classical diffusion based neck growth model is modified to predict the time resolved neck growth during continuous heating with the diffusion coefficients and surface tension extracted from MD simulation. The diffusion model underestimates the neck growth rate for smaller particles (5.4 nm) while satisfactory agreement is obtained for larger particles (10 nm). The deviation is due to the ultrafine size effect for particles below 10 nm. Various possible mechanisms were identified and discussed.N
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