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Diagnostic accuracy of eHealth literacy measurement tools in older adults: a systematic review

BACKGROUND: In Canada, virtual health care rapidly expanded during the COVID-19 pandemic. There is substantial variability between older adults in terms of digital literacy skills, which precludes equitable participation of some older adults in virtual care. Little is known about how to measure olde...

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Detalles Bibliográficos
Autores principales: Huang, Yu Qing, Liu, Laura, Goodarzi, Zahra, Watt, Jennifer A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049781/
https://www.ncbi.nlm.nih.gov/pubmed/36978033
http://dx.doi.org/10.1186/s12877-023-03899-x
Descripción
Sumario:BACKGROUND: In Canada, virtual health care rapidly expanded during the COVID-19 pandemic. There is substantial variability between older adults in terms of digital literacy skills, which precludes equitable participation of some older adults in virtual care. Little is known about how to measure older adults’ electronic health (eHealth) literacy, which could help healthcare providers to support older adults in accessing virtual care. Our study objective was to examine the diagnostic accuracy of eHealth literacy tools in older adults. METHODS: We completed a systematic review examining the validity of eHealth literacy tools compared to a reference standard or another tool. We searched MEDLINE, EMBASE, CENTRAL/CDSR, PsycINFO and grey literature for articles published from inception until January 13, 2021. We included studies where the mean population age was at least 60 years old. Two reviewers independently completed article screening, data abstraction, and risk of bias assessment using the Quality Assessment for Diagnostic Accuracy Studies-2 tool. We implemented the PROGRESS-Plus framework to describe the reporting of social determinants of health. RESULTS: We identified 14,940 citations and included two studies. Included studies described three methods for assessing eHealth literacy: computer simulation, eHealth Literacy Scale (eHEALS), and Transactional Model of eHealth Literacy (TMeHL). eHEALS correlated moderately with participants’ computer simulation performance (r = 0.34) and TMeHL correlated moderately to highly with eHEALS (r = 0.47–0.66). Using the PROGRESS-Plus framework, we identified shortcomings in the reporting of study participants’ social determinants of health, including social capital and time-dependent relationships. CONCLUSIONS: We found two tools to support clinicians in identifying older adults’ eHealth literacy. However, given the shortcomings highlighted in the validation of eHealth literacy tools in older adults, future primary research describing the diagnostic accuracy of tools for measuring eHealth literacy in this population and how social determinants of health impact the assessment of eHealth literacy is needed to strengthen tool implementation in clinical practice. PROTOCOL REGISTRATION: We registered our systematic review of the literature a priori with PROSPERO (CRD42021238365). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-03899-x.