Older and fearing new technologies? The relationship between older adults’ technophobia and subjective age

心理学 年龄组 老年学 人口学 医学 社会学
作者
Erhong Sun,Xuchun Ye
出处
期刊:Aging & Mental Health [Routledge]
卷期号:28 (4): 569-576 被引量:8
标识
DOI:10.1080/13607863.2023.2241017
摘要

AbstractObjective This article aimed to identify different technophobia subgroups of older adults and examine the associations between these distinct subgroups and the subjective age.Methods A sample of 728 retired older adults over the age of 55 was recruited in China. Latent profile analysis was conducted to identify technophobia subgroups using three indicators: techno-anxiety, techno-paranoia and privacy concerns. Analysis of Variance was applied to determine whether a relationship exists between the identified technophobic subgroups and subjective ages (Feel-age, Look-age, Do-age and Interests-age).Result Four technophobia types were identified: 'low-technophobia' (24.59%), 'high-privacy concerns' (26.48%), 'medium-technophobia' (28.38%), and 'high-technophobia' (20.55%). Privacy concerns play a major role in the profiles of older adults who belong to the profiles of 'high-privacy concerns' and 'high-technophobia' (47.03%). A series of ANOVAs showed that older adults in the 'low-technophobia' were more likely to be younger subjective ages of the feel-age and interest-age.Conclusion The majority of Chinese older adults do not suffer from high levels of technophobia, but do concerns about privacy issues. It also pointed out the younger subjective age might have a protective effect on older adults with technophobia. Future technophobia interventions should better focus on breaking the age stereotype of technology on older adults.Keywords: Technophobiaolder adultslatent profile analysissubjective ageage stereotype Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis work was supported by the National Natural Science Foundation of China (Grant No. 71974196), Naval Medical University Youth Initiation Fund (Grant No.2022QN029).
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