根據財團法人台灣網路資訊中心「2016年台灣寬頻網路使用調查」報告顯示，台灣整體上網率高達84.8%。另一份由全國意向及輔仁大學統計學系暨應用統計研究所在2011年1月到3月的調查顯示“15到19歲上網比率最高，達100%。12歲以下約58%，12到14歲99.9%，20到24歲99.6%，多數上網人口年齡分佈在12到24歲之間”。此訊息的背後隱藏令兒童與青少年精神病學家及教育學家憂心的潛在問題。因為，根據網絡成癮相關研究顯示:“網路成癮者比起非成癮者的親子關係較差，抑鬱程度也較高”[1]。另一份針對5到15歲的研究結果指出“網路成癮者比非成癮者的IQ較低，其中又以兒童抑鬱症量表中的理解能力指標中得分明顯較低”[2]。研究者進一步指出，大腦發育在青春期最為活耀，過度的使用網路，造成所謂的網路成癮可能對青少年的認知能力產生負面影響。

    我們以統合分析(Meta Analysis)中的統合迴歸(Meta Regression)，探討不同的治療方式或其它因素，是否會影響網路成癮之療效。本研究在文獻蒐集方面並不排除其他已發表的統合分析文章，因此，稱之為更新之統合分析(Updated Meta-Analysis)。所收集到的14篇發表文獻中，整理出的變數有:發表年份、介入措施、診斷量表、被治療者國籍、是否有父母參與、是否以團體治療、文獻是否使用隨機分派、效益值計算方式與平均年齡，其中過半(56.3%)的發表文獻未呈現平均年齡，改以教育程度代替。因此，最終結果之呈現分兩部分，包含平均年齡與否。

    研究結果中，我們認為最好的模型為納入介入措施與治療症狀，Adj R-squared = 0.1748，I-squared = 0.8947 (含平均年齡則分別為0.4833與0.8375)。介入措施中療效之效益值前兩高的分別都是心理治療再配合其他療程，說明了以往常使用的心理治療(如:認知行為治療)，可以再配合其他療法或是配合藥物治療，以增加治療效果。不過，本研究之結果顯示“經調整治療症狀效應後，多層次心理治療之效益值最低，但僅達邊際顯著性(p=0.073)”。 經調整介入措施效應後，療效評估所採用之治療症狀的效益值，前兩高的分別為網路成癮嚴重度指標與上網時間。其中，網路成癮量表大多都有衡量上網強迫性、戒斷反應與耐受性。換言之，治療網路成癮必須從如何有效控制上網時間著手。

According to a summary report: “A Survey on Broadband Internet Usage in Taiwan, 2016” by the TWNIC showed that the overall internet rate in Taiwan is as high as 84.8%. Another survey conducted by TrendGo and the Institute of Applied Statistics of Fu Jen Catholic University from January to March 2011 showed that “The age group of the highest rate of Internet access is 15 to 19 years old, up to 100%. It’s about 58% for age below 12. And, it’s 99.9% for age between 12 to 14 year. For age between 20 to 24-year-olds, the Internet access rate is 99.6%. The majority of the Internet usage population is between 12 and 24 years old." There exist some potential problems behind this message that are worrying children and adolescent psychiatrists and educators the most. Because, according to the results of Internet addiction studies, it’s known that "Internet-addicts have poorer parent-child relationships and sever levels of depression than non-addicts." Another study on Internet addiction between the ages of 5 and 15 indicated that: “Internet-addicted group have both lower intelligence test score than non-addicted group and signifiantly lower scores on cognition scale in the Children's Depression Inventory than non-addicted group.” The researchers further pointed out that brain development is most active in adolescence, and excessive use of the Internet may have a negative impact on adolescents' cognitive ability. 

  We used meta regression to explore the impact of different treatments or other potential prognostic factors on the treatment efficacy of Internet addiction. This study didn't exclude other published meta analysis papers. Accordingly, it is named updated meta-analysis. Among the 14 collected papers, the prognostic variables that were sorted out were: year of publication, intervention methods, evaluation scale, nationality of the studied subjects, parent involvement, group therapy, randomized control trial, and the methods of effective size was calculated and mean age. There were more than half (56.3%) of the selected papers did not present the information of mean age (presented by eduction level instead). The final results were presented in two parts: mean age included and excluded. 

  In the study results, we believe that the best fitted model is to include intervention methods and treated symptoms. The corresponging goodness-of-fit indices, named Adj R-squared and I-squared, were 0.1748 and 0.8947, respectively (including the mean age were 0.4833 and 0.8375, respectively). Among the intervention methods, the first two highest effect size were the psychotherapy plus other intervention methods. In other words, to improve the treatment effect of Internet addiction, the commonly used psychotherapy should be used with other methods (such as cognitive behavioral therapy or drugs). However, in this study, we find out that the one with lowest effect size was multi-level psychotherapy, after adjusting for the effect of treated symptoms (although, p=0.073). On the other hand, after adjusting for the effects of interventions, the first two highest effect sizes of treated symptoms were Internet addiction severity indicators and online time. Among them, most of the Internet addiction severity scales were including Internet compulsive, withdraw response and tolerance. In other words, the treatment of internet addiction must begin with how to effectively control online time.

目錄:
第一章 緒論	1
第一節 研究背景	1
第二節 網路成癮	2
第三節 網路成癮診斷與治療	5
第四節 目的	8
第二章 研究方法	8
第一節 統合分析	8
第二節 效益值計算	9
第三節 統計方法	12
第四節 統合迴歸	14
第五節 統合迴歸模型	15
第六節 研究資料	16
第三章 研究結果	31
第一節 單一解釋變數之統合迴歸分析	40
第二節 兩個解釋變數之統合迴歸分析	45
第三節 三個解釋變數之統合迴歸分析	52
第四節 四個解釋變數之統合迴歸分析	61
第五節 五個解釋變數之統合迴歸分析	70
第四章 結論	84
參考文獻	85
附件	89


 
圖目錄:
圖 3.0.1 森林圖……………………………………………………………………38
圖 3.0.2 漏斗圖……………………………………………………………………39
圖 3.0.3 漏斗圖……………………………………………………………………40
圖 3.5.1 治療症狀與介入措施類型對療效之效益值的統合迴歸圖……………79
圖 3.5.2 治療症狀、介入措施與平均年齡對療效之效益值的統合迴歸圖……81
圖 3.5.2 盒型圖……………………………………………………………………83



























表目錄:
表 2.6.1 研究資料 ………………………………………………………………18
表 3.0.1 固定效應 統合效益值…………………………………………………32
表 3.0.2 隨機效應模式 …………………………………………………………32
表 3.0.3 隨機效應 效益值顯著性檢定…………………………………………37
表 3.1.1 發表年分對療效之效益值的統合迴歸表 ……………………………41
表 3.1.2 介入措施對療效之效益值的統合迴歸表 ……………………………41
表 3.1.3 介入措施有無父母參與對療效之效益值的統合迴歸表 ……………42
表 3.1.4 介入措施是否以團體方式治療對療效之效益值的的統合迴歸表 …42
表 3.1.5 治療症狀對療效之效益值的統合迴歸表 ……………………………43
表 3.1.6 被治療者國籍對療效之效益值的統合迴歸表 ………………………44
表 3.1.7 效益值計算方式對療效之效益值的統合迴歸表 ……………………44
表 3.1.8 研究設計(有無隨機分派)對療效之效益值的統合迴歸表 …………45表 3.2.1 治療症狀與發表年分對療效之效益值的統合迴歸表 ………………45
表 3.2.2 治療症狀與介入措施類型對療效之效益值的統合迴歸表 …………46
表 3.2.3 治療症狀與是否以團體治療對療效之效益值的統合迴歸表 ………47
表 3.2.4 治療症狀與有無父母參與對療效之效益值的統合迴歸表 …………48
表 3.2.5 治療症狀與被治療者國籍對療效之效益值的統合迴歸表 …………49
表 3.2.6 治療症狀與效益值計算方式對療效之效益值的統合迴歸表 ………50
表 3.2.7 治療症狀與研究設計(有無隨機分派)對療效之效益值的統合迴歸表………………………………………………………………………51
表 3.3.1 治療症狀、介入措施、發表年分對療效之效益值的統合迴歸表………………………………………………………………………52
表 3.3.2 治療症狀、介入措施、團體治療對療效之效益值的統合迴歸表………………………………………………………………………53
表 3.3.3 治療症狀、介入措施、父母參與對療效之效益值的統合迴歸表………………………………………………………………………55
表 3.3.4 治療症狀、介入措施、被治療者國籍對療效之效益值的統合迴歸表………………………………………………………………………56
表 3.3.5 治療症狀、介入措施、效益值計算方式對療效之效益值的統合迴歸表………………………………………………………………………57
表 3.3.6 治療症狀、介入措施、研究設計(隨機分派)對療效之效益值的統合迴歸表……………………………………………………………………59
表 3.4.1 治療症狀、介入措施、父母參與、發表年分對療效之效益值的統合迴歸表……………………………………………………………………61
表 3.4.2 治療症狀、介入措施、父母參與、團體治療對療效之效益值的統合迴歸表……………………………………………………………………62
表 3.4.3 治療症狀、介入措施、父母參與、被治療者國籍對療效之效益值的統合迴歸表………………………………………………………………64
表 3.4.4 治療症狀、介入措施、父母參與、效益值計算方式對療效之效益值的統合迴歸表……………………………………………………………66
表 3.4.5 治療症狀、介入措施、父母參與、研究設計(隨機分派)對療效之效益值的統合迴歸表………………………………………………………68
表 3.5.1 治療症狀、介入措施、父母參與、研究設計(隨機分派)與發表年分對療效之效益值的統合迴歸表…………………………………………70
表 3.5.2 治療症狀、介入措施、父母參與、研究設計(隨機分派)與團體治療對療效之效益值的統合迴歸表…………………………………………72
表 3.5.3 治療症狀、介入措施、父母參與、研究設計(隨機分派)與被治療者國籍對療效之效益值的統合迴歸表……………………………………74
表 3.5.4 治療症狀、介入措施、父母參與、研究設計(隨機分派)與效益值計算方式對療效之效益值的統合迴歸表…………………………………76
表 3.5.5 最後模型 ………………………………………………………………78
表 3.5.6 最後模型加入平均年齡 ………………………………………………80
表 3.5.7 介入措施 描述性統計量………………………………………………82

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