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Supplementary Material for: Social factors influencing decision-making in intracerebral haemorrhage: A survey among neurology professionals

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Supplementary_Material_for_Social_factors_influencing_decision-making_in_intracerebral_haemorrhage_A_survey_among_neurology_professionals/31092685
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Objective: Intracerebral haemorrhage (ICH) is the most severe type of stroke characterised by high morbidity and mortality rates. While prognostic scales aim to predict outcomes based solely on medical information, clinicians' assessments may be influenced by patients' social factors potentially resulting in inequitable care. Patients and Methods: A vignette-based survey presenting five pairs of fictitious ICH cases (10 total) was distributed to professionals involved in ICH patient care. Each pair included identical medical data and a comparable computed tomography scan. Social factors - including family status, employment, home status, and medical history - were varied. Respondents assessed prognosis, recommended management, and identified key factors influencing their decisions. Only healthcare professionals involved in the treatment of neuro-intensive care patients were eligible to participate. Results: A total of 172 responses were collected, of which 156 were from physicians. Statistically significant differences were observed across all case pairs with regard to prognosis, initial management and further treatment. Cases with less favourable social backgrounds were more likely to result in delayed treatment or recommendations for palliative care. Notably, when participants were asked which factors influenced their decisions, only an average of 10–11% acknowledged that social factors had played a role in their clinical reasoning Conclusions: Social factors seem to influence clinicians’ prognostic assessments and management decisions in ICH cases, suggesting unconscious bias is present. These findings highlight the need for strategies to ensure equitable treatment, for example, bias-awareness training.
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2026-01-19
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