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SCIENTIFIC LITERATURE · MED

A multidimensional gender analysis of health technology self-efficacy among people with Parkinson's disease.

J Neurol · 2024-08-22

DOI: 10.1007/s00415-024-12635-3PMID: 39168866

Open accessresearch-article; Journal ArticleOriginal source ↗

Research overview

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BackgroundDigital health technologies (DHT) enable self-tracking of bio-behavioral states and pharmacotherapy outcomes in various diseases. However, the role of gender, encompassing social roles, expectations, and relations, is often overlooked in their adoption and use. This study addresses this issue for persons with Parkinson's disease (PD), where DHT hold promise for remote evaluations.MethodsWe conducted a cross-sectional survey study in the Netherlands, assessing the impact of gender identity, roles, and relations on health technology self-efficacy (HTSE) and attitude (HTA). An intersectional gender analysis was applied to explore how gender intersects with education, employment, disease duration, and severity in influencing HTSE and HTA.ResultsAmong 313 participants (40% women), no significant correlation was found between gender identity or relations and HTSE or HTA. However, individuals with an androgynous (non-binary) gender role orientation demonstrated better HTSE and HTA. The exploratory intersectional analysis suggested that sociodemographic and clinical factors might affect the influence of gender role orientations on HTSE and HTA, indicating complex and nuanced interactions.ConclusionThis study highlights the importance of investigating gender as a multidimensional variable in PD research on health technology adoption and use. Considering gender as a behavioral construct, such as through gender roles and norms, shows more significant associations with HTSE and HTA, although effect sized were generally small. The impact of gender dimensions on these outcomes can be compounded by intersecting social and disease-specific factors. Future studies should consider multiple gender dimensions and intersecting factors to fully understand their combined effects on technology uptake and use among people with PD.

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