Good communication between the doctor or a nurse and patient is of vital importance. And, in a medical context, good team performance can save lives. Therefore, researchers study teamwork behavior in hospitals, communication patterns in medical conversations, and caregiver - patient interaction at nursing homes.
Simulating events adds to our understanding and helps us improve processes and protocols. An operating room (simulator) can provide a secure environment for training and evaluation: new protocols or high-tech tools can be tested and different scenarios can be simulated.
Because it is a very broad research area, we’ve highlighted 4 exciting blog posts. They are about doctor patient interaction, medical encounters, and setting up a coding scheme for communication in healthcare. See what others are working on and benefit from new insights!
- Doctor-patient interaction during medical consultations - It is all about trust - Smets et al. (2012) gained insight into the relationship between patient and radiation oncologists. The researchers investigated whether the content of information provided by the doctor and the way the doctor delivered the information increased the amount of trust patients placed in them.
- Nurse patient interaction - two coding schemes - Cultural differences - Kim and Woods (2012) looked into social interactions between direct-care staff and Korean Americans with dementia.
- What's new in healthcare communication? - How to develop a coding scheme -Zhou et al. (2012) were primarily searching for a coding scheme that reflects focus on the dental staff’s encouragement- centered interaction approach.
- Clinical interviews – analyzing verbal and non-verbal behavior - Eye gaze orientation - Montague et al. presented a study in which they analyzed non-verbal behavior in clinical interactions, specifically, looking into eye gaze behavior patterns (eye gaze behavior is considered an important aspect of doctor-patient interaction). They introduced a new method to evaluate gaze behavior patterns in doctor-patient interaction based on a lag sequential analysis for the description of eye gaze orientation between clinicians and patients.