Heart-rate recovery (HRR) can be defined as the rate at which heart rate declines, usually within minutes after the cessation of physical exercise. [1][2][3] The autonomic nervous system (ANS) regulates both the initial increase in heart rate after the start of physical activity and the decrease in heart rate immediately after physical activity ends. The ANS is composed of a parasympathetic and a sympathetic branch that operate in a reciprocal and inverse manner: An increase in heart rate is caused by an increase in sympathetic activity combined with decreased parasympathetic drive, whereas HRR is characterized by parasympathetic reactivation and sympathetic withdrawal. [3][4][5][6][7] Cardiac output is adjusted during exercise based on the metabolic demand. The regulation occurs by intrinsic autoregulation of cardiac pumping (the so-called Frank-Starling law of the heart) and by sympathetic activation and parasympathetic deactivation, which increases heart rate and the contraction force of mainly the left ventricle. 8 Increased sympathetic activity combined with parasympathetic withdrawal (eg, during exercise) leads to reduced skin blood flow and increased blood flow to the muscles. 9 When the exercise stops, cardiac output is reduced by intrinsic autoregulation (by the ANS), more specifically by parasympathetic nervous system reactivation and inhibition of sympathetic impulses.Although it is well documented that changes in HRR coincide well with changes in training status in patient populations, 10 to our knowledge a systematic review on the use of HRR in athletes is missing. HRR may be an indicator of fitness, which is currently generally expressed in terms of VO 2max or VO 2peak , the maximum oxygen uptake during exhaustive exercise. Although VO 2max has a strong relationship with training status in a general population, it loses its predictive value for aerobic performance in already well-trained and elite athletes. 2 In addition, the typical error of measurement of VO 2max is relatively high, which makes VO 2max unreliable to monitor training changes over time. 2 In contrast, parameters such as HRR, peak power output, and/or peak treadmill running speed have lower typical errors of measurements, which makes them more sensitive to detect changes in training status.Therefore, the aim of this study was to conduct a systematic review on the use of HRR in athletes to track long-term changes in training status. Methods Data SourcesAn electronic literature search was performed in the digital databases of Scopus, EMBASE, and PubMed. The search terms used were a combination of heart/pulse rate(s), recovery/deceleration, (physical) exercise, and health(y) subjects/population. This search yielded 90 scientific articles (see Figure 1). Heart-rate recovery (HRR) has been proposed as a marker of autonomic function and training status in athletes. The authors performed a systematic review of studies that examined HRR after training. Five cross-sectional studies and 8 studies investigating changes over time (longitudinal)...

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BACKGROUND Although prehabilitation programmes for patients undergoing major intra-abdominal cancer surgery have been shown to improve pre-operative physical fitness, the conclusions regarding any postoperative benefits are inconsistent. OBJECTIVES The aim of this study was to evaluate the content of and the outcome measures used in studies of prehabilitation programmes for these patients. It was hypothesised that the content of prehabilitation programmes is often therapeutically invalid, and that the postoperative outcomes assessed are inadequate to evaluate the impact of complications. DESIGN A systematic review of randomised controlled trials.

How we perceive our environment affects the way we feel and behave. The impressions of our ambient environment are influenced by its entire spectrum of physical characteristics (e.g., luminosity, sound, scents, temperature) in a dynamic and interactive way. The ability to manipulate the sensory aspects of an environment such that people feel comfortable or exhibit a desired behavior is gaining interest and social relevance. Although much is known about the sensory effects of individual environmental characteristics, their combined effects are not a priori evident due to a wide range of non-linear interactions in the processing of sensory cues. As a result, it is currently not known how different environmental characteristics should be combined to effectively induce desired emotional and behavioral effects. To gain more insight into this matter, we performed a literature review on the emotional effects of multisensory stimulation. Although we found some interesting mechanisms, the outcome also reveals that empirical evidence is still scarce and haphazard. To stimulate further discussion and research, we propose a conceptual framework that describes how environmental interventions are likely to affect human emotional responses. This framework leads to some critical research questions that suggest opportunities for further investigation.

Research on food experience is typically challenged by the way questions are worded. We therefore developed the EmojiGrid: a graphical (language-independent) intuitive self-report tool to measure food-related valence and arousal. In a first experiment participants rated the valence and the arousing quality of 60 food images, using either the EmojiGrid or two independent visual analog scales (VAS). The valence ratings obtained with both tools strongly agree. However, the arousal ratings only agree for pleasant food items, but not for unpleasant ones. Furthermore, the results obtained with the EmojiGrid show the typical universal U-shaped relation between the mean valence and arousal that is commonly observed for a wide range of (visual, auditory, tactile, olfactory) affective stimuli, while the VAS tool yields a positive linear association between valence and arousal. We hypothesized that this disagreement reflects a lack of proper understanding of the arousal concept in the VAS condition. In a second experiment we attempted to clarify the arousal concept by asking participants to rate the valence and intensity of the taste associated with the perceived food items. After this adjustment the VAS and EmojiGrid yielded similar valence and arousal ratings (both showing the universal U-shaped relation between the valence and arousal). A comparison with the results from the first experiment showed that VAS arousal ratings strongly depended on the actual wording used, while EmojiGrid ratings were not affected by the framing of the associated question. This suggests that the EmojiGrid is largely self-explaining and intuitive. To test this hypothesis, we performed a third experiment in which participants rated food images using the EmojiGrid without an associated question, and we compared the results to those of the first two experiments. The EmojiGrid ratings obtained in all three experiments closely agree. We conclude that the EmojiGrid appears to be a valid and intuitive affective self-report tool that does not rely on written instructions and that can efficiently be used to measure food-related emotions.