Improving residency training with the help of multisource feedback: Generation of a model of influencing factors

Background: Feedback is considered to be one of the most important drivers of learning. One form of structured feedback used in medical settings is multisource feedback (MSF). This feedback technique provides the opportunity to gain a differentiated view on a doctor’s performance from several perspectives using a questionnaire and a facilitating conversation, in which learning goals are formulated. While many studies have been conducted on the validity, reliability and feasibility of the instrument, little is known about the impact of factors that might influence the effects of MSF on clinical performance. Summary of Work: To study under which circumstances MSF is most effective, we performed a literature review on Google Scholar with focus on MSF and feedback in general. Main key-words were: MSF, multi-source-feedback, multi source feedback, and feedback each combined with influencing/ hindering/ facilitating factors, effective, effectiveness, doctors-intraining, and surgery. Summary of Results: Based on the literature, we developed a preliminary model of facilitating factors. This model includes five main factors influencing MSF: questionnaire, doctor-in-training, group of raters, facilitating supervisor, and facilitating conversation. Discussion and Conclusions: Especially the following points that might influence MSF have not yet been sufficiently studied: facilitating conversation with the supervisor, individual aspects of doctors-in-training, and the causal relations between influencing factors. Overall there are only very few studies focusing on the impact of MSF on actual and long-term performance. We developed a preliminary model of hindering and facilitating factors on MSF. Further studies are needed to better understand under which circumstances MSF is most effective. Take-home messages: The preliminary model might help to guide further studies on how to implement MSF to use it at its full potential.

The unstable CO2 feedback cycle on ocean planets

Ocean planets are volatile-rich planets, not present in our Solar system, which are thought to be dominated by deep, global oceans. This results in the formation of high-pressure water ice, separating the planetary crust from the liquid ocean and, thus, also from the atmosphere. Therefore, instead of a carbonate-silicate cycle like on the Earth, the atmospheric carbon dioxide concentration is governed by the capability of the ocean to dissolve carbon dioxide (CO2). In our study, we focus on the CO2 cycle between the atmosphere and the ocean which determines the atmospheric CO2 content. The atmospheric amount of CO2 is a fundamental quantity for assessing the potential habitability of the planet's surface because of its strong greenhouse effect, which determines the planetary surface temperature to a large degree. In contrast to the stabilizing carbonate-silicate cycle regulating the long-term CO2 inventory of the Earth atmosphere, we find that the CO2 cycle feedback on ocean planets is negative and has strong destabilizing effects on the planetary climate. By using a chemistry model for oceanic CO2 dissolution and an atmospheric model for exoplanets, we show that the CO2 feedback cycle can severely limit the extension of the habitable zone for ocean planets.

Short structured feedback training is equivalent to a mechanical feedback device in two-rescuer BLS: a randomised simulation study.

BACKGROUND Resuscitation guidelines encourage the use of cardiopulmonary resuscitation (CPR) feedback devices implying better outcomes after sudden cardiac arrest. Whether effective continuous feedback could also be given verbally by a second rescuer ("human feedback") has not been investigated yet. We, therefore, compared the effect of human feedback to a CPR feedback device. METHODS In an open, prospective, randomised, controlled trial, we compared CPR performance of three groups of medical students in a two-rescuer scenario. Group "sCPR" was taught standard BLS without continuous feedback, serving as control. Group "mfCPR" was taught BLS with mechanical audio-visual feedback (HeartStart MRx with Q-CPR-Technology™). Group "hfCPR" was taught standard BLS with human feedback. Afterwards, 326 medical students performed two-rescuer BLS on a manikin for 8 min. CPR quality parameters, such as "effective compression ratio" (ECR: compressions with correct hand position, depth and complete decompression multiplied by flow-time fraction), and other compression, ventilation and time-related parameters were assessed for all groups. RESULTS ECR was comparable between the hfCPR and the mfCPR group (0.33 vs. 0.35, p = 0.435). The hfCPR group needed less time until starting chest compressions (2 vs. 8 s, p < 0.001) and showed fewer incorrect decompressions (26 vs. 33 %, p = 0.044). On the other hand, absolute hands-off time was higher in the hfCPR group (67 vs. 60 s, p = 0.021). CONCLUSIONS The quality of CPR with human feedback or by using a mechanical audio-visual feedback device was similar. Further studies should investigate whether extended human feedback training could further increase CPR quality at comparable costs for training.