Educational Intervention for the Development of Professionals Skills in Family Medicine and Community Nursing Residents

BACKGROUND The burnout syndrome among health care workers frequently rises to prevalence above 50%. One of the consequences most supported by the literature is the impoverishment of the therapeutic alliance, triggered by a loss of empathy of the clinician towards the patient due to the emotional exhaustion he or she suffers. The main factors that influence the presence of this pathology are stressors related to the organization of work. However, this equation is also influenced by individual factors that can be acted upon and which are often the only tools available for professionals. Due to the widely supported relationship of empathy, burnout and therapeutic alliance, the investigators decided to carry out a complex training plan focused on personal development in teaching units of Family and Community Care in Spain. RESEARCH QUESTION Is effective an intervention aimed to promoting the development of personal skills throughout the training of family and community care doctors and nurses? METHOD Pre-post study, comparing two educational interventions, one face-to-face (N=90) and other online (N=70), with a control group (N=170). Participants: All physicians and nurse trainees on Primary Health Care in three Spanish Health Regions who wish to participate in the study. The face-to-face intervention consists of 3 annual workshops, while the online one will be carried out by adapting the theoretical contents of the face-to-face intervention for online use and will pursue the same objectives and be fed by the same contents. The variation in the level of empathy will be quantified by means of the Interpersonal Reactivity Index (IRI) questionnaire, adjusted by burnout (Copenhagen questionnaire) and other variables such as resilience (Connor-Davidson), locus of control, social support (Oslo-3), sense of coherence (OLQ-13), age, sex, personality (Ten Item Personality Inventory, TIPI-SP) and other organisational factors. Statistical analysis with generalized lineal models and generalized additive models.