Open AI’s GPT Agent used with the Moriskyscale and Health Beliefs Questionnaire (HBQ) can dramatically improve patient adherence to prescribed medications and successful treatment outcomes. Let's explore how these instruments work in tandem to identify intentional non-adherence and assess treatment-related dimensions for targeted educational counseling.
The MMAS-8, a widely used self-report measure, provides a concise assessment of medication adherence. Its questions delve into key behaviors, unveiling whether patients intentionally skip or alter their medication regimen. By gauging intentional non-adherence, the GPT Agent then can gain insight using the HBQ into the treatment-related dimension of the 5 dimensions of non-adherence.
When a patient scores as intentionally non-adherent on the MMAS8 the GPT agent can utilize the Health Beliefs Questionnaire, another highly validated tool designed to explore patients' perceptions and beliefs regarding their treatment. When focusing on the treatment-related dimension of non-adherence, the HBQ becomes invaluable. By probing into a patient's attitudes, beliefs, and understanding of their prescribed regimen, healthcare professionals can pinpoint areas of concern or misconception.
Suppose the GPT Agent reveals a patient harboring doubts about the necessity of their medication or expressing skepticism about its long-term benefits. Addressing these beliefs head-on allows healthcare providers to provide clarity, reinforce the importance of the treatment plan, and dispel any misconceptions that might contribute to non-adherence. Utilizing a GPT agent with these validated tools not only identifies intentional non-adherence but also delves into the underlying beliefs influencing treatment decisions.
Dr Donald Morisky.