PERSISTENCE OF DISEASE GERMS

致病菌的持续存在

阅读:1

Abstract

Reducing inappropriate prescribing is key to mitigating antibiotic resistance, particularly in acute care settings. Clinicians' prescribing decisions are influenced by their judgments and actual or perceived patient expectations. Fuzzy trace theory predicts that patients and clinicians base such decisions on categorical gist representations that reflect the bottom-line understanding of information about antibiotics. However, due to clinicians' specialized training, the categorical gists driving clinicians' and patients' decisions might differ, which could result in mismatched expectations and inefficiencies in targeting interventions. We surveyed clinicians and patients from 2 large urban academic hospital emergency departments (EDs) and a sample of nonpatient subjects regarding their gist representations of antibiotic decisions, as well as relevant knowledge and expectations. Results were analyzed using exploratory factor analysis (EFA) and multifactor regression. In total, 149 clinicians (47% female; 74% white), 519 online subjects (45% female; 78% white), and 225 ED patients (61% female; 56% black) completed the survey. While clinicians demonstrated greater knowledge of antibiotics and concern about side effects than patients, the predominant categorical gist for both patients and clinicians was "why not take a risk," which compares the status quo of remaining sick to the possibility of benefit from antibiotics. This gist also predicted expectations and prior prescribing in the nonpatient sample. Other representations reflected the gist that "germs are germs" conflating bacteria and viruses, as well as perceptions of side effects and efficacy. Although individually rational, reliance on the "why not take a risk" representation can lead to socially suboptimal results, including antibiotic resistance and individual patient harm due to adverse events. Changing this representation could alter clinicians' and patients' expectations, suggesting opportunities to reduce overprescribing.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。