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系統識別號 U0026-0709201513141300
論文名稱(中文) 五大性格因素、情緒/逃避因應型態及網路使用正向效果預期對大學生網路成癮之影響:一年追蹤研究
論文名稱(英文) The Impacts of Personality, Emotion/Avoidance Coping Style, and Positive Outcome Expectancy of Internet Use on Internet Addiction among College Students : One-Year Follow-up
校院名稱 成功大學
系所名稱(中) 行為醫學研究所
系所名稱(英) Institute of Behavioral Medicine
學年度 103
學期 2
出版年 104
研究生(中文) 趙義揚
研究生(英文) Yi-Yang Chao
電子信箱 unwaveringchao@gmail.com
學號 s86011069
學位類別 碩士
語文別 中文
論文頁數 124頁
口試委員 指導教授-郭乃文
共同指導教授-柯慧貞
口試委員-林以正
口試委員-董旭英
中文關鍵字 大學生  網路成癮  五大性格因素  情緒/逃避因應型態  網路使用正向效果預期  追蹤性研究 
英文關鍵字 Internet addiction  Internet use positive outcome expectancies  emotion/avoidance coping  Five-Factors model of personality  longitudinal study 
學科別分類
中文摘要 研究背景
過去文獻已證實特定性格傾向(高神經質、低親和性與低嚴謹性),以及對網路有特定的正向效果預期,如增進正向或緩解負向情緒,為網路成癮的危險因子,研究亦發現性格會透過正向與逃避預期及失功能因應的中介而影響網路成癮的發展,但正向/逃避預期與失功能因應間的關係仍待釐清。然而,文獻指出性格傾向與特定壓力因應有關;具有高神經質、低親和性與低嚴謹性的個體,較可能採用情緒或逃避性的策略因應生活壓力。研究亦發現逃避因應須透過增進自信/消除壓力的酒精使用預期的中介而預測飲酒行為,指出逃避因應與酒精預期二者間的相關性。但在網路成癮的研究中,仍缺乏縱貫性研究釐清性格傾向、情緒/逃避因應型態、網路使用正向效果預期中的解禁慾望與忘憂增趣,以及網路成癮間的關係。是故,本研究根據文獻推論,情緒/逃避因應型態中介性格傾向與忘憂增趣/解禁慾望的網路使用預期的關係。

研究目的
本研究擬以全國性大學生樣本,以一年追蹤性研究驗證高神經質、低親合性與低嚴謹性之性格傾向、情緒/逃避因應型態、解禁慾望/忘憂增趣的網路使用正向效果預期與大學生網路成癮的發展模式,並假設性格傾向會透過情緒/逃避因應型態的中介而影響次年的忘憂增趣/解禁慾望的網路使用預期,進而預測次年的網路成癮程度。

研究方法
研究設計:本研究採縱貫法,使用柯慧貞教授所主持之國科會研究計畫:「全國大專院校學生網路成癮相關研究」之研究資料庫來進行分析。
研究對象:本研究以台灣大專學生為母群,採叢集機率樣本取樣,第一年有效樣本為2,920份問卷。第二年共追蹤到1,308份,追蹤率為44.79%。
研究工具:陳氏網路成癮量表、五大性格因素量表簡版、柯氏壓力因應量表、網路使用正向效果預期量表。
資料分析:以描述性統計、卡方與 t 檢定、相關分析,以及結構方程模式分析對研究假設進行分析與檢證。

研究結果
第一、二年橫斷模式分析結果均顯示,情緒/逃避因應型態能完全中介性格傾向與解禁慾望/忘憂增趣的網路使用預期之關係,進而預測網路成癮程度;整體模式解釋量部份,第一、二年分別為30%與38%。
縱貫模式分析顯示,在控制第一年網路成癮程度後,第一年性格傾向與情緒/逃避因應型態能顯著正向預測第二年網路成癮;在控制第一年的解禁慾望/忘憂增趣的網路使用預期後,第一年情緒/逃避因應型態能顯著正向預測第二年的解禁慾望/忘憂增趣的網路使用預期;第一年情緒/逃避因應型態能完全中介第一年性格傾向對第二年解禁慾望/忘憂增趣網路使用預期的影響,進而預測第二年網路成癮程度,整體模式解釋量為44%。

結論與建議
本研究採用縱貫性研究設計,並以代表性大樣本進行研究,結果支持情緒/逃避因應型態中介性格傾向對解禁慾望/忘憂增趣的網路使用預期間的作用模式;並建立性格傾向、壓力因應型態、網路使用正向效果預期與網路成癮的路徑模型。
英文摘要 INTRODUCTION

Internet addiction (IA) has been identified as a pathological use of Internet, which leads to symptoms traditionally associated with behavior addiction and may result in academic, occupational and social function impairments. College students have been indicated as a high-risk population. In Taiwan, the prevalence of IA among college students are relatively high. Approximately 12.9% to 17.9% college students were found to be addicted, highlighting the need for further research and intervention among this age group in Taiwan.

Empirical findings among the college population showed a stable relation between IA and certain personality proneness, which indicated high neuroticism, low agreeableness, and low conscientiousness. On the other hand, Internet Positive Outcome Expectancies (IPOE) have been linked to IA, showing that higher IPOE predicted higher IA scores. Recently, a study found that expectancies of positive/avoidance and dysfunctional coping mediated the relationship between personality and Internet addiction, but the relation of the two mediators remained to be clarified (Brand, Laier, & Young, 2014). In fact, several studies have highlighted the relationship between personality proneness and certain coping strategies, namely emotion and avoidance coping style (E/A Coping). Moreover, it was found that alcohol expectancies of increased confidence and tension reduction could mediated the relationship between avoidant coping and drinking behavior, suggesting the causational relationship between coping and expectancies.

Based on previous research, the hypotheses were as follow: (i) Time 1(T1) personality proneness (high neuroticism, low agreeableness, and low conscientiousness) and T1 E/A Coping predicted time 2 (T2) IA scores, T2 expectancies of desire release/avoidance and emotional enhancement (DR/AEE) predicted T2 IA scores, (ii) T1 E/A Coping predicted T2 expectancies of DR/AEE, (iii) T1 E/A Coping mediated the relationship between T1 personality proneness and T2 expectancies of DR/AEE.

MATERIALS AND METHODS

This study used data set with a two-year longitudinal design through both stratified and random cluster sampling. First, the sample was stratified by technical (2-year vocational school) or non-technical college (university or 4-year technical school), and then stratified according to region (north, middle, and south part of Taiwan). Second, the sample was choose by random cluster sampling according to department. In the first year, a total of 4885 students were invited, and 3996 students actually participated. After exclusion of 380 participants due to incomplete data, the final sample was 3616 (T1), resulting in a response rate of 90.49 percent. In the follow-up, after excluding the seniors in the first year and those with incomplete data, a sample comprising of 1308 students were collected, resulting in a response rate of 44.79 percent.

Internet Use Positive Outcome Expectancies, the Shortened Chinese Version of the Five-Factor Inventory, and the Ko's coping Scale were used. By using SPSS 19.0, relations between two variables were tested using Person correlation. Structural equation modeling (SEM) was performed using Lisrel 8.80 to test the fits of latent variables and structural model, and maximum Likelihood Estimation method was used to test CFA, and SEM analysis. On the other hand, T1 IA and T1 expectancies of DR/AEE were included in the proposed model as controlling confounding variable in order to test the causational relationship.

RESULTS AND DISCUSSION

Both in the cross-sectional and longitudinal design, confirmatory factor analysis (CFA) revealed that the latent dimensions are acceptable by related observed variables with factor loadings achieving significance. By using SEM analysis, the proposed IA models showed a good fit both cross-sectionally and longitudinally. In the longitudinal study (As shown in Figure 1), all the direct effects in the model were positive and significant, and 44 percent of the variance of T2 IA were explained. The direct effect from T2 expectancies of DR/AEE to T2 IA was significant; the direct effect from T1 E/A Coping to T2 expectancies of DR/AEE was significant; and the direct effect from T1 personality proneness to T1 E/A Coping was also significant. Also, The indirect effect from T1 personality proneness through T1 E/A Coping to T2 expectancies of DR/AEE was significant, showing the mediational role of E/A Coping between personality proneness and expectancies of DR/AEE.

The findings of the present study supported the hypothesized model of IA, indicating that individuals who have certain personality proneness, are more likely to use emotion/avoidance coping to avoid confronting daily stressors, rather than problem solving or social support seeking. Evidences have shown that high neuroticism was more sensitive to threat, punishment, and was associated with poorer emotion regulation, also,
lower agreeableness might suggest poor social information processing, and lower conscientiousness might indicate impairment in executive function. Sequentially, individual who be lacking in adaptive coping and depend on emotion/avoidance coping might in turn have more on certain expectancies of Internet useage, especially for desire release and avoidance/emotional enhancement, rather than information acquirement and social facilitation, which were all initially learned as neutral through daily life. Eventually, individuals as forgoing mentioned are more likely to exhibit symptoms of IA with impaired frontal function gradually.

CONCLUSIONS

The present study used a longitudinal design to test the impact of personality proneness, emotion/avoidance coping style, expectancies of desire release/avoidance and emotional enhancement among college students in Taiwan. Our findings provided empirical evidence to verify the theoretical effectiveness of the cognitive and personality factors to Internet addiction, which could be incorporated when designing prevention programs and strategies for helping Internet addicted college students.
論文目次 第一章、 研究背景
第一節、 大學生網路成癮問題的重要性
壹、 台灣網路使用的普及1
貳、 網路普及後所帶來的問題2
參、 網路成癮的定義與衡鑑
一、 網路成癮的定義3
二、 網路成癮與物質成癮在生理上的相關性5
三、 網路成癮的衡鑑8
肆、 網路成癮的盛行率
一、 國內大學生網路成癮盛行率10
二、 國外大學生網路成癮盛行率10
伍、 大學生是網路成癮的高危險族群11
第二節、 大學生網路成癮可能的心理成因
壹、 從性格來解釋網路成癮可能的心理成因
一、 性格與網路成癮的關係
(一)、五大性格因素的定義12
(二)、五大性格因素與成癮的關係13
(三)、五大性格因素與網路成癮的關係:高神經質、低親和性與嚴謹性15
貳、 從網路使用正向效果預期來解釋網路成癮可能的心理成因
一、 正向效果預期的定義18
二、 解禁慾望/忘憂增趣預期與網路成癮的關係19
參、 從壓力因應型態來解釋網路成癮可能的心理成因
一、 壓力因應型態的定義21
二、 情緒/逃避因應型態與網路成癮的關係22
三、 情緒/逃避因應型態與性格傾向的關係24
四、 情緒/逃避因應型態與解禁慾望/忘憂增趣預期的關係26
第三節、 研究目的與假設
壹、 研究目的28
貳、 研究假設29
第二章、 研究方法
第一節、 研究設計30
第二節、 研究對象31
第三節、 研究工具
壹、 陳氏網路成癮量表32
貳、 五大性格因素量表簡版33
參、 柯氏壓力因應量表34
肆、 網路使用正向效果預期量表35
第四節、 研究程序36
第五節、 統計分析37
第三章、 研究結果
第一節、 參與者人口學變項與各變項之分析
壹、 大學生網路使用之現況40
貳、 有追蹤與未追蹤之基本資料比較41
第二節、 研究模式之驗證
壹、 性格傾向、情緒/逃避因應型態、解禁慾望/忘憂增趣預期與網路成癮程度之相關分析
一、 第一年網路成癮程度與各變項之相關分析42
二、 第二年網路成癮程度與各變項之相關分析42
三、 第一年變項與第二年變項之相關分析42
貳、 研究模式之驗證
一、 第一年橫斷研究模式驗證
(一)第一年情緒/逃避因應型態能中介第一年性格傾向對第一年解禁慾望/忘憂增趣預期的影響44
(二)第一年橫斷研究模式適配度 44
二、 第二年橫斷研究模式驗證
(一)第二年情緒/逃避因應型態能中介第二年傾向性格對第二年解禁慾望/忘憂增趣預期的影響46
(二)第二年橫斷研究模式適配度46
三、 縱貫研究模式驗證
(一)第一年性格傾向能正向預測第二年網路成癮程度48
(二)第一年情緒/逃避因應型態能正向預測第二年網路成癮程度48
(三)第一年情緒/逃避因應型態能正向預測第二年解禁慾望/忘憂增趣預期49
(四)縱貫研究模式驗證
1. 第一年情緒/逃避因應型態中介第一年性格傾向對第二年解禁慾望/忘憂增趣預期的影響49
2. 縱貫研究模式適配度50
第四章、 討論
第一節、 本研究之主要發現與解釋
壹、 整合模式之驗證方面
一、 樣本基本資料分析探討51
二、 性格傾向、情緒/逃避因應型態、解禁慾望/忘憂增趣預期與網路成癮程度之相關性探討
(一)、第一年網路成癮程度與各變項相關性探討51
(二)、第二年網路成癮程度與各變項相關性探討52
(三)、第一年變項與第二年變項相關性探討 52
三、 第一、二年橫斷研究模式
(一)、情緒/逃避因應型態能中介性格傾向對解禁慾望/忘憂增趣預期的影響 54
(二)、橫斷研究模式適配度54
四、 縱貫研究模式
(一)、第一年性格傾向正向預測第二年網路成癮程度56
(二)、第一年情緒/逃避因應型態正向預測第二年網路成癮程度56
(三)、第一年情緒/逃避因應型態正向預測第二年解禁慾望/忘憂增趣預期56
(四)、整體模式解釋式58
(五)、縱貫研究模式59
第二節、 本研究之限制與未來研究方向
壹、 研究設計部份60
貳、 研究參與者部分61
參、 研究工具部分62
第三節、 本研究之學術與應用貢獻
壹、 學術貢獻方面63
貳、 應用貢獻方面64
第五章、 參考文獻66

表目錄
表1. Internet Gaming Disorder77
表2. Internet Addiction Test78
表3. Pathological Internet Use Scale79
表4. Online Cognition Scale80
表5. Generealizrd Problematic Internet Use Scale82
表6. Compulsive Interent Use Scale83
表7. 性格與因應的相關係數-取自Connor-Smith與Flachsbart,200784
表8. 有追蹤組與未追蹤組在基本人口學變項及各量表得分85
表9. 性格、情緒/逃避因應型態、解禁慾望/忘憂增趣預期與網路成癮程度之相關矩陣88
表10. 第一年橫斷模式估計參數之顯著性考驗與標準化效果值94
表11. 第一年橫斷模式之個別信度指標、潛在變項的組成信度以及平均變異抽取量95
表12. 第一年橫斷模式之潛在變項的直接、間接及整體效果之標準化效果值96
表13. 第二年橫斷模式估計參數之顯著性考驗與標準化效果值97
表14. 第二年橫斷模式之個別信度指標、潛在變項的組成信度以及平均變異抽取量98
表15. 第二年橫斷模式之潛在變項的直接、間接及整體效果之標準化效果值99
表16. 縱貫模式估計參數之顯著性考驗與標準化效果值100
表17. 縱貫模式之個別信度指標、潛在變項的組成信度以及平均變異抽取量101
表18. 縱貫模式之潛在變項的直接、間接及整體效果之標準化效果值102

圖目錄
圖1.Brand等人(2014)所提出的網路成癮整合模式圖103
圖2.Hasking(2011)所提出的酒精預期中介因應策略而影響飲酒行為模式圖104
圖3.本研究假設之網路成癮整合模式圖105
圖4.第一年橫斷模式圖106
圖5.第二年橫斷模式圖107
圖6.縱貫模式圖108

附錄目錄
附錄一.同意書109
附錄二.個人基本資料表110
附錄三.網路使用行為與網路使用程度(網路成癮量表)114
附錄四.網路使用效果預期量表117
附錄五.五因素性格問卷119
附錄六.壓力因應量表 121
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