重要提醒:2025.12.15 12:00-12:50期间发布的求助,下载出现了问题,现在已经修复完毕,请重新下载即可。如非文件错误,请不要进行驳回。

The metacognitive-motivational links between stress and short-form video addiction

担心 心理学 上瘾 元认知 结构方程建模 应对(心理学) 临床心理学 发展心理学 精神科 认知 焦虑 统计 数学
作者
Ruimei Sun,Meng Xuan Zhang,Chunmin Yeh,Carolina Oi Lam Ung,Anise M. S. Wu
出处
期刊:Technology in Society [Elsevier]
卷期号:77: 102548-102548 被引量:21
标识
DOI:10.1016/j.techsoc.2024.102548
摘要

The recent, sudden growth of short-form video platforms, such as TikTok, has prompted public concern regarding short-form video addiction (SVA), a potential behavioral addiction with adverse health and social consequences. Whereas stress is positively related to SVA, research investigating its underlying psychological mechanism is warranted. Based on the self-regulatory executive function model, this study examined the potential mediating roles of metacognition and motives for short-form video use in a snowball sample of 422 participants, aged 15-66 years (36.3% male; Mage = 26.55, SD = 11.38), via an anonymous online survey. Consistent with the results of structural equation modeling, those of path analysis supported the mediating roles of metacognition (i.e., positive beliefs about worry [POS] and negative beliefs about worry [NEG]) and motives (for escape/coping). To be specific, the significant mediators of the stress-SVA link were POS (β = 0.041, 95% CI [0.006, 0.081]), NEG (β = 0.102, 95% CI [0.026, 0.180]), escape motive (β = 0.052, 95% CI [0.010, 0.103]), as well as NEG and escape motive serially (β = 0.039, 95% CI [0.008, 0.079]). Our findings suggest not only the central role of metacognition, through which stress activates one's motives to use short-form video to escape/cope, contributing to SVA, but also the risk-enhancing roles of NEG and escape motive in explaining the metacognitive-motivational mechanisms underlying the positive association between stress and SVA. Intervention programs for behavioral addictions, including SVA, may consider regulating metacognition of individuals, especially those under high levels of stress.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
飘逸惠完成签到,获得积分10
2秒前
3秒前
zz发布了新的文献求助10
3秒前
lmmorz完成签到,获得积分10
4秒前
rh发布了新的文献求助10
4秒前
flawless完成签到,获得积分10
4秒前
坚定妙旋完成签到,获得积分10
4秒前
6秒前
6秒前
6秒前
7秒前
8秒前
渤大小mn完成签到,获得积分10
8秒前
于鱼发布了新的文献求助10
9秒前
菜花发布了新的文献求助10
9秒前
9秒前
10秒前
蜗牛完成签到,获得积分10
11秒前
寻菡发布了新的文献求助10
11秒前
penghuiye完成签到 ,获得积分10
11秒前
11秒前
无名完成签到,获得积分10
11秒前
李爱国应助Huguizhou采纳,获得10
12秒前
科研通AI6应助rh采纳,获得10
13秒前
13秒前
威武的冷风完成签到,获得积分10
14秒前
14秒前
天下无贼发布了新的文献求助10
14秒前
lovexz完成签到,获得积分10
14秒前
gggkky关注了科研通微信公众号
15秒前
彭于彦祖应助小药童采纳,获得150
15秒前
czq发布了新的文献求助10
16秒前
17秒前
贪玩藏今发布了新的文献求助10
17秒前
丘比特应助nimeng123采纳,获得10
18秒前
张雅露完成签到,获得积分10
18秒前
19秒前
我是老大应助蓓蓓0303采纳,获得10
19秒前
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5468193
求助须知:如何正确求助?哪些是违规求助? 4571644
关于积分的说明 14330855
捐赠科研通 4498131
什么是DOI,文献DOI怎么找? 2464353
邀请新用户注册赠送积分活动 1453088
关于科研通互助平台的介绍 1427739