Introduction: Comparable to second victim phenomenon (SVP), moral injury (MI) affects health professionals (HP) working in stressful environments. Information on how MI and SVP intercorrelate and their part in a psychological trauma complex is limited. We tested and validated a German version of the Moral Injury Symptom and Support Scale for Health Professionals (G-MISS-HP) instrument, screening for MI and correlated it with the recently developed German version of the Second Victim Experience and Support Tool (G-SVESTR) instrument, testing for SVP. Methods: After translating Moral Injury Symptom and Support Scale for Health Professionals (MISS-HP), we conducted a cross-sectional online survey providing G-MISS-HP and G-SVEST-R to HP. Statistics included Pearson’s interitem correlation, reliability analysis, principal axis factoring and principal components analysis with Promax rotation, confirmatory factor and ROC analyses. Results: A total of 244 persons responded, of whom 156 completed the survey (33% nurses, 16% physicians, 9% geriatric nurses, 7.1% speech and language therapists). Interitem and corrected item-scale correlations did not measure for one item sufficiently. It was, therefore, excluded from further analyses. The nine-item score revealed good reliability (Guttman’s lambda 2 = 0.80; Cronbach’s alpha = 0.79). Factor validity was demonstrated, indicating that a three-factor model from the original study might better represent the data compared with our two-factor model. Positive correlations between G-MISS-HP and G-SVESTR subscales demonstrated convergent validity. ROC revealed sensitivity of 89% and specificity of 63% for G-MISS-HP using a nine-item scale with cutoff value of 28.5 points. Positive and negative predictive values were 62% and 69%, respectively. Subgroup analyses did not reveal any differences. Conclusion: G-MISS-HP with nine items is a valid and reliable testing instrument for moral injury. However, strong intercorrelations of MI and SVP indicate the need for further research on the distinction of these phenomena.

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A surgical site infection (SSI) is one of the most common surgical complications. This study analyzed different sources of microorganisms in the air, on reusable surgical instruments, and the outer surface of sterile packaging systems during the use and reprocessing of sterile goods (from the operating room (OR) to the Central Sterile Supply Department (CSSD)). The microbial load in the air was analyzed via active air sampling and settle plates. Furthermore, the airborne particle load was measured by a particle counter. Contact agar plates were used to determine the microbial load on surgical instruments and sterile packaging systems. The highest average microbial and particle load was measured in the air of the OR (active air sampling: max. 56 CFU/m3; settle plates: max. 9 CFU; ≥0.3 μm particles in size: 1,958,403 no./m3). However, no microbial load (0 CFU) was detected on surgical instruments sampled in the OR. The outer surface of stored sterile packaging systems showed a maximal microbial load of 64 CFU. The most common identified pathogen was coagulase-negative staphylococci. Compared to properly reprocessed reusable surgical instruments and sterile packaging systems, the air still seems to be the primary potential source of microbial contamination, especially within the OR.

Background and aimThere are no investigations on hand hygiene during cardiopulmonary resuscitation (CPR), even though these patients are at high risk for healthcare-associated infections. We aimed to evaluate the number of indicated hand hygiene per CPR case in general and the fraction that could be accomplished without delay for other life-saving techniques through standardized observations.Materials and methodsIn 2022, we conducted Advanced Cardiovascular Life Support (ACLS) courses over 4 days, practicing 33 ACLS case vignettes with standard measurements of chest compression fractions and hand hygiene indications. A total of nine healthcare workers (six nurses and three physicians) participated.ResultsA total of 33 training scenarios resulted in 613 indications for hand disinfection. Of these, 150 (24%) occurred before patient contact and 310 (51%) before aseptic activities. In 282 out of 310 (91%) indications, which have the highest impact on patient safety, the medication administrator was responsible; in 28 out of 310 (9%) indications, the airway manager was responsible. Depending on the scenario and assuming 15 s to be sufficient for alcoholic disinfection, 56–100% (mean 84.1%, SD ± 13.1%) of all indications could have been accomplished without delaying patient resuscitation. Percentages were lower for 30-s of exposure time.ConclusionTo the best of our knowledge, this is the first study investigating the feasibility of hand hygiene in a manikin CPR study. Even if the feasibility is overestimated due to the study setup, the fundamental conclusion is that a relevant part of the WHO indications for hand disinfection can be implemented without compromising quality in acute care, thus increasing the overall quality of patient care.

Background: Paediatric emergencies are challenging for healthcare workers, first aiders, and parents waiting for emergency medical services to arrive. With the expected rise of virtual assistants, people will likely seek help from such digital AI tools, especially in regions lacking emergency medical services. Large Language Models like ChatGPT proved effective in providing health-related information and are competent in medical exams but are questioned regarding patient safety. Currently, there is no information on ChatGPT’s performance in supporting parents in paediatric emergencies requiring help from emergency medical services. This study aimed to test 20 paediatric and two basic life support case vignettes for ChatGPT and GPT-4 performance and safety in children. Methods: We provided the cases three times each to two models, ChatGPT and GPT-4, and assessed the diagnostic accuracy, emergency call advice, and the validity of advice given to parents. Results: Both models recognized the emergency in the cases, except for septic shock and pulmonary embolism, and identified the correct diagnosis in 94%. However, ChatGPT/GPT-4reliably advised to call emergency services only in 12 of 22 cases (54%), gave correct first aid instructions in 9 cases (45%) and incorrectly advised advanced life support techniques to parents in 3 of 22 cases (13.6%). Conclusion: Considering these results of the recent ChatGPT versions, the validity, reliability and thus safety of ChatGPT/GPT-4 as an emergency support tool is questionable. However, whether humans would perform better in the same situation is uncertain. Moreover, other studies have shown that human emergency call operators are also inaccurate, partly with worse performance than ChatGPT/GPT-4in our study. However, one of the main limitations of the study is that we used prototypical cases, and the management may differ from urban to rural areas and between different countries, indicating the need for further evaluation of the context sensitivity and adaptability of the model. Nevertheless, ChatGPT and the new versions under development may be promising tools for assisting lay first responders, operators, and professionals in diagnosing a paediatric emergency. Trial registration: not applicable