Hudak2011
| Hudak2011 | |
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| BibType | ARTICLE |
| Key | Hudak2011 |
| Author(s) | Pamela L. Hudak, Shannon Clark, Geoffrey Raymond |
| Title | How surgeons design treatment recommendations in orthopaedic surgery |
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| Tag(s) | EMCA, Medical EMCA, Doctor-patient interaction, Treatment Recommendation, Orthopaedic Surgery, Surgery |
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| Year | 2011 |
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| Journal | Social Science & Medicine |
| Volume | 73 |
| Number | 7 |
| Pages | 1028–1036 |
| URL | Link |
| DOI | 10.1016/j.socscimed.2011.06.061 |
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Abstract
This paper examines how orthopaedic surgeons skilfully design treatment recommendations to display awareness of what individual patients are anticipating or seeking, and suggests limits to those efforts. It adds leverage to our parallel work by demonstrating that even when surgeons incorporate considerations of recipient design to ‘fit’ recommendations to patients’ displayed orientations, an asymmetry between recommendations for vs. not for surgery remains: recommendations for surgery are generally proposed early, in relatively simple and unmitigated form, and as stand-alone options. In contrast, recommendations not for surgery tend to be significantly more complex: they are likely to be delayed, conveyed indirectly, mitigated and justified, and include other possible treatment options. These findings suggest a tension between surgeons’ efforts to design recommendations for specific recipients and an overarching institutional bias favoring surgery. Surgeons’ efforts to anticipate and respond to resistance to recommendations demonstrate a similar pattern: the methods used to counter patient resistance, and the sequential placement of those efforts, depends on whether the recommendation is for surgery or another treatment option. This work contributes to an understanding of treatment recommendations generally by showing how patients are co-implicated in their accomplishment: because surgeons incorporate considerations of recipient design in response to information provided explicitly or tacitly by patients, patients influence the rendering of recommendations from the beginning.
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