The results of the reviewed studies, especially those with longitudinal data, suggest that empathy decline during medical school and residency compromises striving toward professionalism and may threaten health care quality. Theory-based investigations of the factors that contribute to empathy decline among trainees and improvement of the validity of self-assessment methods are necessary for further research.

The results of our study can be used by oncology nurses and physicians to increase their awareness of the complexity and heterogeneity of information needs among CaPts and of clinically significant subgroups of CaPts. Moreover, regression analyses indicate the following association: Nurses and physicians seem to be able to reduce CaPts' unmet information needs by establishing a relationship with the patient, which is trusting, caring and empathic.

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The fluctuations of the cardiac interbeat series contain rich information because they reflect variations of other functions on different time scales (e.g., respiration or blood pressure control). Nonlinear measures such as complexity and fractal scaling properties derived from 24 h heart rate dynamics of healthy subjects vary from childhood to old age. In this study, the age-related variations during childhood and adolescence were addressed. In particular, the cardiac interbeat interval series was quantified with respect to complexity and fractal scaling properties. The R-R interval series of 409 healthy children and adolescents (age range: 1 to 22 years, 220 females) was analyzed with respect to complexity (Approximate Entropy, ApEn) and fractal scaling properties on three time scales: long-term (slope β of the power spectrum, log power vs. log frequency, in the frequency range 10−4 to 10−2 Hz) intermediate-term (DFA, detrended fluctuation analysis, α2) and short-term (DFA α1). Unexpectedly, during age 7 to 13 years β and ApEn were higher compared to the age <7 years and age >13 years (β: −1.06 vs. −1.21; ApEn: 0.88 vs. 0.74). Hence, the heart rate dynamics were closer to a 1/f power law and most complex between 7 and 13 years. However, DFA α1 and α2 increased with progressing age similar to measures reflecting linear properties. In conclusion, the course of long-term fractal scaling properties and complexity of heart rate dynamics during childhood and adolescence indicates that these measures reflect complex changes possibly linked to hormonal changes during pre-puberty and puberty.

Traditional measures of heart rate variability (HRV) in the time or frequency domain (e.g. standard deviation of normal-to-normal intervals, SDNN, or the high frequency component of spectral analysis, HF) may be used to track vagal and sympathetic modulation directed to the sinus node. In this study, we assess the ability of symbolic analysis to monitor cardiac autonomic regulation during two autonomic challenges (phenylephrine and nitroprusside; low and high dose of atropine). To assess the effect of the coarse graining procedure, symbolic series obtained from four different transformations over the original series and the series of successive differences of the original values. The analysis focused on patterns of length 3 and exploited a redundancy reduction strategy to group patterns into a small number of families. It turns out that each symbolic series created by the four transformations still contained sufficient dynamical features to quantify differences of cardiovascular changes during the pharmacological challenges. The symbolic series created by transformations of the beat-to-beat interview, i.e RR interval series, showed that patterns without variations (0V) appear more often during a high dose of atropine compared to rest or to a low dose of atropine. Furthermore, patterns with two unlike variations (2UV) appear more often during a low dose of atropine and less often during a high dose of atropine. Differences of nitroprusside and phenylephrine could also be assessed by patterns with these variations. In conclusion, the changes of cardiovascular regulation during pharmacological challenges can be assessed by the analysis of symbolic dynamics derived from the RR interval series independently of the specific symbolic transformation.