高齡族群網路成癮狀況

Abstract

科技的進步，使得手機與行動網路快速進展，隨著這樣的快速發展與普及，也引發過度的使用導致成癮問題，影響身心健康，成為全球關注的議題。「網路成癮失調症」，是由Goldberg（1995）提出，並輔以Young（1996）與Griffiths（1998）、陳淑惠(1998)等國內外學者的評估標準，其核心概念涵蓋耐受性、戒斷性、強迫性、人際與健康問題與時間管理問題等五面向。本研究以60歲以上已退休且未在職的高齡族群為樣本，透過問卷調查其網路使用行為與成癮狀況，並以陳淑惠等人（2003）發展「中文網路成癮量表（CIAS）」進行改編、調查，透過Google表單與紙本問卷收集數據，最終收回共計442份有效問卷，並以SPSS統計軟體進行分析處理。研究結果顯示，20.8%之高齡族群達到網路成癮切分點。其中年齡、教育程度、每天平均上網時間與網路成癮在相關分析中達到顯著相關；而年齡、每天出門多久、每天平均上網時間與網路成癮則在迴歸分析中達到顯著性；最後每天出門多久、週末平均上網時間與網路成癮在二元羅吉斯迴歸分析達到顯著性。另外，高齡者網路成癮在耐受性構面高於全體平均分數，表示需要逐漸增加上網時間以獲得相同滿足感，也更進一步提高成癮風險。整體高齡者雖有79.2%未達到成癮切分點，但卻有較過往更加成癮之趨勢，而上網最常使用之類型則以社群媒體為首要。不同性別之高齡男性與高齡女性在網路成癮上則是未有顯著不同。The advancement of technology has led to the rapid development and widespread use of mobile phones and mobile internet. However, this convenience has also resulted in excessive use, leading to internet addiction issues that affect both physical and mental health, and have become a global concern. “Internet Addiction Disorder” (IAD) was first proposed by Goldberg (1995), with further diagnostic criteria developed by Young (1996), Griffiths (1998), and Chen Shu-Hui (1998). The core dimensions include tolerance, withdrawal symptoms, compulsive use, interpersonal and health issues, and time management problems.This study targeted retired individuals aged 60 and above who are not currently employed. Using a questionnaire survey to examine their internet usage behaviors and addiction tendencies, data were collected through both Google Forms and paper-based questionnaires. The revised version of the Chen Internet Addiction Scale (CIAS; Chen et al., 2003) was used for measurement, resulting in a total of 442 valid responses. The data were analyzed by using SPSS statistical software.The findings revealed that 20.8% of the elderly participants reached the cutoff score for internet addiction. Correlation analysis showed that age, educational level, and average daily internet usage were significantly related to internet addiction. Regression analysis further indicated that age, daily time spent outside, and average daily internet usage were significant predictors of addiction. In addition, binary logistic regression revealed that daily time spent outside and average weekend internet usage significantly predicted the risk of addiction.Among the five addiction dimensions, tolerance scored higher than the overall average, suggesting that elderly individuals increasingly require more time online to achieve the same level of satisfaction, thereby heightening the risk of addiction. Although 79.2% of the elderly participants did not meet the clinical threshold for addiction, the overall trend suggests an increasing level of immersion. Social media emerged as the most frequently used type of online activity. No significant differences were found between elderly males and females in terms of addiction levels.