JMIR Publications

ABSTRACT

Background:

Feedback is a valuable tool to improve physician-patient interactions. Healthcare professionals receive varied forms of feedback on their practice. At present, physicians receive summative feedback in the form of patient surveys. However, doctors’ skepticism towards patient surveys as quality enhancement tools raises the question of whether real-time feedback might be a better performance improvement tool. On exploring the ambiguities in doctors’ attitudes to patient experience surveys, it was discovered that most physicians undermine the potential for survey-based quality improvement; however, they still find value in receiving patient feedback. Real-time and post-session feedback has proven to be effective in enhancing interpersonal communication. However, the literature on the effect of cognitive load associated with the feedback tool and its impact on physician-patient interactions is sparse. 

Objective:

Our study aims to test the efficacy of 3 feedback tools (haptic feedback, visual feedback, and post-visit summary) to understand which feedback tool helps enhance interpersonal communication. ​​Since burnout rate is one of the main factors influencing physician-patient interaction, the cognitive load will act as a moderator such that a higher cognitive load caused by the feedback modality diminishes the strength of the feedback system's effect on interpersonal communication.

Methods:

An experimental study design was used to test the efficacy of the three feedback tools while measuring the cognitive load associated with these feedback modalities on non-clinical participants in a non-clinical setting. The methods were guided by the best practices in Human Centered Design (HCD) and instructional design processes. The cognitive load associated with using the feedback tool was measured using the Nasa Task Load Index (TLX). A within-subject design method was used to test the feedback tools. Through counterbalancing, a sample size of 18 participants (n = 18) were shortlisted using the participant pool.

Results:

(i) Post-session feedback not only enhances performance but also counters the effect of cognitive load. For comparison between Post session feedback and Real-Time feedback (Haptic + Visual), the difference was significant (p=0.001), indicating that post-feedback modalities had a lower mean than real-time modalities. (ii) Prior experience in conducting interviews results in lower cognitive load . Real-time feedback is most effective on individuals with prior experience, resulting in a low cognitive load . On the contrary, post-session feedback is more effective with novice users. The haptic feedback rating for the group with interview experience is lower (4.84) than for the group without interview experience (7.03). The visual feedback rating is almost similar for both groups (4.38 for those with experience, 4.22 for those without). However, the post-visit feedback rating is higher for the group with experience (3.41) compared to the group without experience (2.42). (iii) Cognitive workload moderates the relationship between the efficacy of the feedback tools and its impact on performance (speaking balance and pace) such that their association gets weaker or stronger depending on how high or low an individual’s cognitive load rating is while using the feedback tool. For the comparison between Post feedback and Haptic feedback, the Z score is -3.245, and the p-value is .001. For the comparison between Post feedback and Visual feedback, the Z score is -2.940, and the p-value is .003. This indicates that there is a significant difference between the means of Post session feedback and Real-time feedback (haptic+visual), where Post session feedback had the lowest mean. As a result, the lower the cognitive load caused by the feedback tool, the better the performance and efficacy of the feedback tool and vice versa. 

Conclusions:

By administering a cognitive workload assessment survey in a high-pressure non-clinical setting, we were able to test our hypothesis and identify key areas that need to be further explored. Our findings suggest that in addition to the mode of feedback, the quality of feedback helps further improve its efficacy. In the study, it was notable that most users found post-session feedback to be descriptive and improvement-focused in comparison to real-time feedback, which according to users, was evaluative and did not aid in long-term performance improvement. Additionally, the preference towards the feedback tool largely depends on the individual's learning style. 78% of users exhibited multimodal learning style preferences. Based on these results, further investigation of the efficacy of bimodal feedback tools to enhance physician-patient interaction is warranted.