Biomedicine Hub· 2017
Can Treatment Adherence Be Improved by Using Rubin's Four Tendencies Framework to Understand a Patient's Response to Expectations
- 3,897citations
- 2017year
Short summary
Rubin's Four Tendencies framework, which categorizes patients by their response to expectations, can be used to tailor interventions and improve treatment adherence.
AI-generated from the title and abstract; the full text is not read.
Key points
- Patient adherence to treatment is a complex, two-way process influenced by both patient and healthcare professional expectations.
- Rubin's Four Tendencies model categorizes individuals based on their response to outer and inner expectations.
- This framework can be used to develop patient-specific interventions to improve treatment engagement.
- The model offers an easy, inexpensive, and widely applicable method for clinical practice.
AI-generated from the title and abstract; the full text is not read.
Abstract
Within the context of poorer patient outcomes and rising healthcare costs, we need to better understand why many patients do not engage fully with their treatment plan. Movement away from talking about "compliance" towards "adherence" and "concordance" is evidence of a recognition that this is a two-way process. Whilst healthcare professionals expect patients to engage in treatment, equally, patients have expectations (whether positive or negative) of their treatment and their need for engagement. There is a need for an effective method that can specifically target those interventions that will provide the most benefit to individual patients and which, crucially, is easy and inexpensive to administer in everyday practice and widely applicable. Rubin's Four Tendencies model identifies a patient's "response to outer and inner expectations" as a key factor in adherence. The model therefore provides an opportunity to test such a targeted, patient-specific strategy and we present a call to action for research in this area.
The authors' abstract, as published at the source. Biomedicine Hub, 2017 · DOI ↗
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Field: Infectious Diseases
Infectious DiseasesMedicine