| Abstract: | 一、研究背景與目的 各類型網路成癮與智慧型手機成癮在青少年族群中皆具有高盛行率；而不同類網路成癮與智慧型手機成癮的相關、共發、分類法引起當今學者討論。由於不同類型的網路成癮與智慧型手機成癮是否具有不同的相關心理因素，將涉及不同的預防及處遇策略。是故，本研究欲透過群集分析來釐清青少年族群中網路成癮與智慧型手機成癮可能存在的組型，同時檢驗不同組型之間在相關心理因素上的差異。二、研究方法1. 參與者與研究流程：本研究運用柯慧貞教授主持之「107年『青少年健康上網，幸福學習』社會責任計畫調查資料庫」之部分資料進行次級資料分析。該資料庫中之樣本乃是採叢集取樣台灣中部地區三所國、高中之一二年級學生。經過學生家長與學生簽署知情同意書後，對於學生進行網路行為問卷調查，了解學生在網路、手機等使用情形與相關心理社會成因。依國高中男女比例隨機抽樣資料庫中1,292筆資料進行分析，年齡介於10-18歲，平均年齡為14.81歲，標準差±1.59，女性佔比45.28%。2. 研究工具：青少年人口資料表、青少年網路使用行為表、線上遊戲成癮量表、智慧型手機成癮量表、廣泛性網路成癮量表、社交網站成癮量表、壓力因應風格量表、壓力知覺量表、SCL-90-R憂鬱分量表、SCL-90-R人際間敏感分量表、網路正向預期量表、拒用網路自我效能等量表。3. 統計分析：描述性統計、群集分析、Mann–Whitney U test、獨立樣本t檢定、Kruskall–Wallis tests 、ANOVA、卡方檢定。三、研究結果1. 群集分析結果將智慧型手機成癮、廣泛性網路成癮、社交網站成癮、線上遊戲成癮之成癮者區分為四個組型：「智慧型手機成癮且未合併廣泛性網路成癮、線上遊戲成癮、社交網站成癮組」（簡稱：SA without GIA/OGA/SNSA）、「智慧型手機與線上遊戲成癮組」（簡稱：OGA+SA）、「智慧型手機與社交網站成癮組」（簡稱：SNSA+SA）、「智慧型手機成癮合併廣泛性網路成癮、線上遊戲成癮及社交網站成癮組」（簡稱：GIA+OGA+SNSA+SA）。2. 與其他組型相比，OGA+SA與GIA+OGA+SNSA+SA均具有較高男性比例，然而，分別與其他組型相比，SNSA+SA具有較高女性比例。3. 壓力知覺程度上，GIA+OGA+SNSA+SA大於非癮組與SA without GIA/OGA/SNSA；SNSA+SA與OGA+SA均大於非癮組。在非適應性壓力因應風格程度上，非癮組最低，其餘各組之間彼此沒有顯著差異。4. 社交焦慮與憂鬱程度上的組間差異結果一致，非癮組最低；SNSA+SA大於SA without GIA/OGA/SNSA與OGA+SA；GIA+OGA+SNSA+SA大於SA without GIA/OGA/SNSA。5. 線上遊戲正向預期程度上，GIA+OGA+SNSA+SA最高；OGA+SA大於非癮組與SNSA+SA；SA without GIA/OGA/SNSA 大於非癮組與SNSA+SA。社交網站正向預期與智慧型手機正向預期程度上的組間差異結果一致，非癮組最低；GIA+OGA+SNSA+SA大於SA without GIA/OGA/SNSA與OGA+SA。拒用線上遊戲自我效能程度上，GIA+OGA+SNSA+SA最低；SNSA+SA與非癮組均大於SA without GIA+OGA+SNSA與OGA+SA。拒用社交網站自我效能與拒用智慧型手機自我效能程度上的組間差異結果一致，非癮組最高；SA without GIA/OGA/SNSA與OGA+SA大於GIA+OGA+SNSA+SA。四、結論與建議1. (1)本研究發現智慧型手機成癮可單獨成為一個群集，並且涵蓋其他特定性網路成癮與廣泛性網路成癮，再進一步依照特定性網路成癮的內容或是廣泛性網路成癮區分為不同的亞型。特定型智慧型手機成癮取代過去特定性網路成癮的概念，而廣泛性智慧型手機成癮與廣泛性網路成癮的概念彼此相互重疊。(2) GIA+OGA+SNSA+SA與OGA+SA有較高的男性比例；SNSA+SA具有較高的女性比例。(3) 憂鬱、社交焦慮、非適應性壓力因應風格是所有成癮群集共通的心理風險因素，而特定內容的正向預期與拒用自我效能則是各成癮群集的獨特風險因素。2. 研究限制：(1) 本研究採用資料為自陳式問卷與量表所調查蒐集的資料，較缺乏客觀性；(2) 橫斷性設計未能說明因果關係；(3) 樣本未具全國青少年代表性；(4) 未納入當今許多新興網路成癮類型，限制本研究群集分類結果的推論。3. 建議： (1) 憂鬱、社交焦慮、非適應性壓力因應風格是所有成癮群集共通的心理風險因素，建議未來以縱貫研究進一步比較前心理述風險因素對不同成癮群集影響力的強弱，並探究介入成效。 (2)網路與智慧型手機使用的正向預期與拒用自我效能是各成癮群集獨特的風險因素，建議未來以縱貫研究進一步釐清各類網路與智慧型手機成癮、網路與智慧型手機之拒用自我效能及使用正向預期之間的因果關係路徑，亦可探討介入策略及其成效。
BackgroundAdolescents had a high prevalence rate in types of smartphone addiction and internet addiction. Types of internet addiction and smartphone addiction could be stand-alone or have comorbidities. Moreover, types of smartphone addiction and internet addiction might have specific psychological antecedents. Therefore, our research aimed to identify the comorbid types of internet addiction and smartphone addiction, also examine the difference of psychological antecedents among types.Methods Participants and procedure: This was a cross-sectional and secondary data analysis study. The data set was part of the survey of “Promoting University Social Responsibility project (USR project)” in 2018 held by Professor Huei-Chen Ko. The participants were recruited from three junior and senior high schools in middle Taiwan. A total of 1,292 students (age: 10-18 y/o; means:14.81 y/o; SD±1.59 female: 45.28%) completed the survey and signed the informed consent. For the study purpose, our study only included the participants who completed all the questionnaires of generalized internet addiction, online gaming addiction, social network sites addiction, and smartphone addiction.Measures: The personal information scale, the internet use habit scale, the Brief COPE, the perceived stress scale, the SCL-90-R interpersonal sensitivity subscales and depression subscales, the questionnaire of positive outcome expectancy of internet and smartphone use, the questionnaire of refusal internet and smartphone use self-efficacy, and the questionnaire of generalized internet addiction, online gaming addiction, social network sites addiction, and smartphone addiction. Statistical analysis: Our study performed descriptive statistics, k-means cluster analysis, Kruskall–Wallis tests, Mann–Whitney U test, ANOVA, chi-square test, and t test.ResultsBased on cluster analysis, our study identified four clusters among the participants with generalized internet addiction (GIA), online gaming addiction (OGA), social network sites addiction (SNSA), and smartphone addiction (SA). These four addicted clusters were named as SA without GIA/OGA/SNSA, OGA+SA, SNSA+SA, and GIA+OGA+SNSA+SA. Compared with non-addicts, all the addicts had a higher level of depression, social anxiety, and maladaptive coping styles. Compared with non-addicts, SA without GIA/OGA/SNSA, OGA+SA, SNSA+SA had more positive outcome expectancies respectively of smartphones, online gaming, and SNS, also, had fewer refusal self-efficacies respectively of smartphones, online gaming, and SNS. DiscussionThe present study findings identified four types of internet addiction and smartphone addiction, with distinct psychological antecedents. SA covered all the addictive clusters, and according to addicted content, SA could be divided into specific or generalized SA. GIA and generalized SA might be synonymous; however, specific internet addiction was replaced by specific SA. Depression, social anxiety, maladaptive coping styles were addicts' common antecedents. Also, Specific addictive clusters owned distinct positive outcome expectancies and specific refusal self-efficacy of addicted content. However, the present finding should be validated by further longitudinal studies to examine causal relationships between psychological antecedents and types of internet addiction and SA. Some limitations should be noted. (1) The raw dataset was obtained from a self-report and might cause response biases. (2) Cross-sectional study design couldn’t explain the causal relationship. (3) The sampling lacked representation for nationwide adolescents. (4) Some types of internet addiction were not included in the cluster analysis and made it limit the exploration of taxonomy. |
