Digital hoarding is a newly emerging phenomenon in academia, with researchers having explored it from multiple disciplinary perspectives in recent years. However, empirical research from the perspective of communication studies is limited. Notably, digital hoarding behaviours are closely linked to individuals’ media usage patterns. Accordingly, our research grounded in theories of Social Cognition and Overconfidence Bias, Technology Acceptance Model, investigates the relationship between new media literacy and digital hoarding behaviours among Chinese youth (N = 399, Mage = 27.5). We also introduce information overload and information anxiety as two mediating variables that may function as explanatory mechanisms. The findings indicate that higher levels of new media literacy are associated with more pronounced digital hoarding behaviour, while greater new media literacy is also linked to lower levels of information overload and information anxiety. Furthermore, higher levels of information overload and information anxiety correspond to more severe digital hoarding behaviours. In addition, a positive relationship exists between information overload and information anxiety. Information overload mediates the relationship between new media literacy and digital hoarding behaviour, reversing the relationship so that increased new media literacy leads to a reduction in perceived information overload, which subsequently results in less digital hoarding behaviour. Our study offers empirical evidence from a new media literacy perspective, contributing to the research on digital hoarding, providing insights into young people’s information management practices.
van BennekomMJBlomRMVulinkN, et al. A case of digital hoarding. Case Reports2015; 2015: bcr2015210814.
4.
SchüllND. Digital containment and its discontents. Hist Anthropol2018; 29(1): 42–48.
5.
LuxonAMHamiltonCEBatesS, et al. Pinning our possessions: associations between digital hoarding and symptoms of hoarding disorder. J Obsessive Compuls Relat Disord2019; 21: 60–68.
6.
HussienMFMahmoudSMohamedHS. Virtual (Digital) hoarding in relation to saving cognition and possession tendency among nursing teaching staff. Assiut Sci Nurs J2023; 11(37): 121–130.
7.
NeaveNBriggsPMcKellarK, et al. Digital hoarding behaviours: measurement and evaluation. Comput Hum Behav2019; 96: 72–77.
8.
VitaleFJanzenIMcGrenereJ. Hoarding and minimalism: tendencies in digital data preservation. In: Proceedings of the 2018 CHI conference on human factors in computing systems, Montreal, QC, Canada, 21–23 Aprils 2018, pp. 1–12. New York: ACM.
9.
WangHMiaoPJiaH, et al. The dark side of upward social comparison for social media users: an investigation of fear of missing out and digital hoarding behavior. Soc Media Soc2023; 9(1): 20563051221150420.
10.
TimpanoKRÇekDFuZF, et al. A consideration of hoarding disorder symptoms in China. Compr Psychiatry2015; 57: 36–45.
11.
KocMBarutE. Development and validation of new media literacy scale (NMLS) for university students. Comput Hum Behav2016; 63: 834–843.
12.
ChenDTWuJWangYM. Unpacking new media literacy. J Syst Cybern Informatics2011; 9: 84–88.
13.
LeeLChenDTLiJY, et al. Understanding new media literacy: the development of a measuring instrument. Comput Educ2015; 85: 84–93.
14.
BozacıaİGökdenizaİ. Development of a digital photo hoarding scale: a research with undergraduate students. Manag Sci Lett2020; 10: 2193–2200.
15.
UğurNGÇalışkanK. Time for De-cluttering: digital clutter scaling for individuals and enterprises. Comput Secur2022; 119: 102751.
16.
LiJGaoTYeY. How college students’ social media information overload affects sleep quality: the mediating effect of social fatigue and irrational procrastination. J Psychol Afr2023; 33(5): 440–447.
17.
BanduraA. Social cognitive theory: an agentic perspective. Annu Rev Psychol2001; 52(1): 1–26.
18.
SchmidtHC. Media literacy education from kindergarten to college: a comparison of how media literacy is addressed across the educational system. J Media Lit Educ2013; 5(1): jmle-5-1-3.
19.
PotterWJ. The state of media literacy. J Broadcast Electron Media2010; 54(4): 675–696.
20.
LivingstoneS. Media literacy and the challenge of new information and communication technologies. Commun Rev2004; 7(1): 3–14.
21.
SongCKimE. The influence of new media literacy on brand engagement: mediating effects of perceived interactivity and openness and the moderating effect of age. Behav Sci2025; 15(4): 458.
22.
Van DeursenAJVan DijkJA. The digital divide shifts to differences in usage. New Media Soc2014; 16(3): 507–526.
23.
NeaveNJacksonRSaxtonT, et al. The influence of anthropomorphic tendencies on human hoarding behaviours. Pers Individ Dif2015; 72: 214–219.
24.
WurmanRS.
Information anxiety. New York: Doubleday, 1989.
25.
BawdenDRobinsonL. The dark side of information: overload, anxiety and other paradoxes and pathologies. J Inf Sci2009; 35(2): 180–191.
26.
EpplerMJ. 11. Information quality and information overload: the promises and perils of the information age. Commun Technol2015; 5: 215.
27.
TandocECKimHK. Avoiding real news, believing in fake news? Investigating pathways from information overload to misbelief. Journalism2023; 24(6): 1174–1192.
28.
VragaEKBodeLTullyM. Creating news literacy messages to enhance expert corrections of misinformation on Twitter. Commun Res2022; 49(2): 245–267.
29.
HeissRNanzAMatthesJ. Social media information literacy: conceptualization and associations with information overload, news avoidance and conspiracy mentality. Comput Hum Behav2023; 148: 107908.
30.
ZaremohzzabiehZAbdullahHAhrariS, et al. Exploration of vulnerability factors of digital hoarding behavior among university students and the moderating role of maladaptive perfectionism. Digital Health2024; 10: 20552076241226962.
31.
SchunkDH. Social cognitive theory. In: HarrisKRGrahamSUrdanT, et al. (eds) APA educational psychology handbook. vol. 1. Theories, constructs, and critical issues. Washington, DC: American Psychological Association, 2012, pp. 101–123.
32.
GirardJAllisonM. Information anxiety: fact, fable or fallacy. Electron J Knowl Manag2008; 6(2): 3750.
33.
EpplerMJMengisJ. The concept of information overload-a review of literature from organization science, accounting, marketing, MIS, and related disciplines (2004). Inf Soc: Int J. 2004; 20(5): 325–344.
34.
SwarBHameedTReychavI. Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search. Comput Hum Behav2017; 70: 416–425.
35.
NielsenJ.
Designing web usability: the practice of simplicity. Indianapolis, IN: New Riders Publishing, 1999.
36.
SavolainenR. Information behavior and information practice: reviewing the ‘umbrella concepts’ of information-seeking studies. Libr Q2007; 77(2): 109–132.
37.
BenselinJCRagsdellG. Information overload: the differences that age makes. J Librariansh Inf Sci2016; 48(3): 284–297.
38.
RiehSY. Judgment of information quality and cognitive authority in the web. J Am Soc Inf Sci Tec2002; 53(2): 145–161.
39.
FlanaginAJMetzgerMJ. The role of site features, user attributes, and information verification behaviors on the perceived credibility of web-based information. New Media Soc2007; 9(2): 319–342.
40.
ElsbachKDHargadonAB. Enhancing creativity through ‘mindless’ work: a framework of workday design. Organ Sci2006; 17(4): 470–483.
41.
FuSLiHLiuY, et al. Social media overload, exhaustion, and use discontinuance: examining the effects of information overload, system feature overload, and social overload. Inf Process Manag2020; 57(6): 102307.
42.
SchumackerRELomaxRG.
A beginner’s guide to structural equation modeling. Hove: Psychology Press, 2004.
43.
HuLBentlerPM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling1999; 6(1): 1–55.
44.
DavisFD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q1989; 13: 319–340.
45.
KhanINadeemASaleemM. Digital hoarding as predictor of mental health problems among undergraduate students. Online Media Soc2023; 4(3): 36–44.
46.
Al-QaysiNMohamad-NordinNAl-EmranM. Employing the technology acceptance model in social media: a systematic review. Educ Inf Technol2020; 25: 4961–5002.
47.
TantiponganantPLaksitamasP. An analysis of the technology acceptance model in understanding students’ behavioral intention to use university’s social media. In: 2014 IIAI 3rd international conference on advanced applied informatics, Kokura, Japan, 4 September 2014, pp. 8–12. New York: IEEE.
48.
LoggJMHaranUMooreDA. Is overconfidence a motivated bias? Experimental evidence. J Exp Psychol Gen2018; 147(10): 1445.
49.
JohnsonDDPFowlerJH. The evolution of overconfidence. Nature2011; 477(7364): 317–320.
50.
BernardoAEWelchI. On the evolution of overconfidence and entrepreneurs. J Econ Manage Strat2001; 10(3): 301–330.
51.
AltanlarAAminiSHolmesP, et al. Opportunism, overconfidence and irrationality: a puzzling triad. Int Rev Financ Anal2023; 88: 102643.
52.
XiaoXSuYLeeDKL. Who consumes new media content more wisely? Examining personality factors, SNS use, and new media literacy in the era of misinformation. Soc Media Soc2021; 7(1): 2056305121990635.
53.
GunaratneCBaralNRandW, et al. The effects of information overload on online conversation dynamics. Comput Math Organ Theory2020; 26: 255–276.
54.
BanduraA. Social cognitive theory of self-regulation. Org Behav Hum Decision Process1991; 50: 248–287.
55.
GeorgeAS. Digital hoarding: the rising environmental and personal costs of information overload. Partner Univ Multidiscip Res J2024; 1(2): 51–67.
56.
AdamsGSConverseBAHalesAH, et al. People systematically overlook subtractive changes. Nature2021; 592(7853): 258–261.
57.
HuangQLeiSNiB. Perceived information overload and unverified information sharing on WeChat amid the COVID-19 pandemic: a moderated mediation model of anxiety and perceived herd. Front Psychol2022; 13: 837820.
58.
JiaYWangE. Research on information anxiety of college students under the background of information overloaded based on support vector machine optimization algorithm. In: 2021 2nd international conference on information science and education (ICISE-IE). Chongqing, China, 26–28 November 2021, pp. 484–487. New York: IEEE.
