Probability analysis of compassion: Enhancing compassionate care in psychiatry through mirror neurons

Abstract

Introduction

The probability that psychiatric care becomes compassionate is higher when individual subjects, groups or organizations utilize mirror neurons to attune with the emotional world of their clients.

Objectives

To create an algorithm for compassionate care in mental health by attunement of mirror neurons.

Aims

To predict the probability of the occurrence of sympathetic care in mental health.

Methods

Naturalistic observation of health care organizations identified the major nodes-agents of the organizational-neural network leading to a compassionate care (events A): individual, group, organization and society. Negative influences on compassionate care are (events B) subjective and collective acts.

Results

The probability that compassionate care occurs as a result of a single mediator's action was only 0.167 (16%). The probability that compassion results from training mirror neurons were as follows:.Multiple event probability formula:

– probability of event A that occurs P(A) = 0.667 (66%) [positive subject + group + organization + society)];

– probability of event B that occurs P(B) = 0.333 [negative individual and group];

– probability that both the events occur P(A∩B) = P(A) × P(B) = 0.222 [inhibitory influence];

– probability that either of event occurs P(A∪B) = P(A) + P(B) − P(A∩B) = 0.778.

Conclusions

The probability of organizational compassion (PA) is high when all the agents interact. As compassion is reinforced by mirror neurons, a reduction in the number of people involved in compassionate care also means the final outcome is less likely to appear.

Disclosure of interest

The authors have not supplied their declaration of competing interest.