Technology anxiety in elderly patients with chronic co-morbidities: a latent profile analysis
Abstract Background Technological anxiety has a multidimensional negative effect on the medical process of elderly patients with chronic co-morbidities, which is mainly reflected in the increase of cognitive load and the decrease of doctor-patient interaction efficiency. The challenge of how elderly...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
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| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12889-025-23616-0 |
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| Summary: | Abstract Background Technological anxiety has a multidimensional negative effect on the medical process of elderly patients with chronic co-morbidities, which is mainly reflected in the increase of cognitive load and the decrease of doctor-patient interaction efficiency. The challenge of how elderly patients can more effectively use digital health technologies is a critical issue that both healthcare providers and patients must address. We aimed to explore technology anxiety in elderly patients with chronic co-morbidities by identifying and characterising distinct technology anxiety profiles using latent profile analysis. Methods This study explored the relationship between the Technology Anxiety Scale and the Self-perceived Burden Scale, as well as the different subgroups of medication literacy, using latent profile analysis. The study involved 611 elderly patients with chronic diseases. The research tools used were the Medication Literacy Scale for Elderly Patients with Chronic Diseases, the Self-perceived Burden Scale, and the Technology Anxiety Scale. Results Latent profile analysis revealed four distinct technology anxiety groups of elderly patients with comorbid chronic diseases: low technology anxiety type with 212 cases (34.70%), high technology anxiety type with 81 cases (13.26%), medium technology anxiety low privacy security type with 148 cases (24.22%), and medium technology anxiety high privacy security type with 170 cases (27.82%).The results of multivariate logistic regression analyses indicated that self-Perceived burden, medication literacy, personal monthly income, medical insurance type, daily exercise duration, and times of hospitalizations are significant factors influencing technology anxiety among elderly patients with comorbid chronic diseases. Conclusion The study showed that higher scores in self-perceived burden and medication literacy, lower daily exercise duration, higher hospitalization frequency, lower personal monthly income, and self-funded medical insurance types are associated with more severe technical anxiety.It is recommended that healthcare professionals tailor interventions to address the specific vulnerabilities of each patient type, aiming to reduce technological anxiety and enhance their ability to utilize health information effectively. |
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| ISSN: | 1471-2458 |