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In 97 patients with type I diabetes mellitus, 155 patients with type II diabetes mellitus, and two matched control groups, serum concentrations of laminin P1, a non-collagenous component of basement membranes, were determined by radioimmunoassay to see whether laminin P1 might be a valuable indicator of microangiopathic complications in diabetics. Independent of the type of diabetes, serum laminin concentrations in patients without nephropathy or with early renal damage as assessed by microalbuminuria were comparable with those of the control subjects. Patients with macroproteinuria or with renal insufficiency had significantly increased serum laminin P1 concentrations. Diabetic retinopathy was not found to influence serum laminin P1 concentrations. These data indicate that serum laminin P1 concentrations are increased in advanced diabetic nephropathy. [ABSTRACT FROM PUBLISHER]

Background: Frailty is associated with poor outcomes for patients on dialysis; however, dedicated studies among incident peritoneal dialysis (PD) patients are lacking. This study aims to determine the association between frailty and mortality/transfer to hemodialysis (HD) among incident PD patients and identify whether dialysis modality (PD vs. HD) modifies the association of frailty and mortality following dialysis initiation., Methods: A single center retrospective cohort of incident PD and HD patients was analyzed from 2009 to 2020 (last follow-up December 2021). The first version of the clinical frailty scale (CFS) ranging from 1, very fit, to 7, severely frail, was used to characterize patient frailty at dialysis initiation. Time to death/transfer to HD was analyzed using multivariable Cox Survival analyses. Patients were censored at transplant/last follow-up. Dialysis modality was evaluated as a potential effect modifier on the impact of frailty on mortality., Results: Of 253 patients who initiated PD, 182 had completed CFS scores. Mean age at dialysis initiation was 63 ± 13 years and mean CFS score was 3 ± 1. There were 42 deaths and 69 instances of transfer to HD over 379 patient-years at risk. Vulnerable/frail patients (CFS ≥ 4) had a two-fold increase in the adjusted relative hazard for death/transfer to HD (HR 2.04, 95% CI [1.10-3.77]). Incident dialysis modality did not modify the association between frailty and mortality., Conclusions: A higher severity of frailty at PD initiation is associated with both mortality/transfer to HD and mortality alone, and the association between frailty and mortality is not modified by dialysis modality., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare. From 84 potential products, seven fulfilled the inclusion criteria. The products can be categorized into three major areas: diagnosis of autism spectrum disorder (ASD) based on clinical history, behavioral, and eye-tracking data; diagnosis of multiple disorders based on conversational data; and medication selection based on clinical history and genetic data. We found five scientific articles evaluating the devices' performance and external validity. The average completeness of reporting, indicated by 52 % adherence to the Consolidated Standards of Reporting Trials Artificial Intelligence (CONSORT-AI) checklist, was modest, signaling room for improvement in reporting quality. Our findings stress the importance of obtaining regulatory approval, adhering to scientific standards, and staying up-to-date with the latest changes in the regulatory landscape. Refining regulatory guidelines and implementing effective tracking systems for AI-CDSS could enhance transparency and oversight in the field., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Good hand hygiene compliance among healthcare workers is crucial for preventing healthcare-associated infections. While an extensive amount of research has focused on barriers to compliance with hand hygiene guidelines, there remains a critical gap in understanding the factors contributing to consistently excellent compliance among some individuals. Thus, the main aim of this study is to learn from these "champions" of hand hygiene and identify facilitating factors that enable and sustain high compliance using the Theoretical Domains Framework (TDF)., Methods: In this qualitative study, we conducted problem-oriented semi-structured interviews with questions based on the 14 domains of the revised TDF. The N = 25 participants included physicians and nurses from three German hospitals. They were selected based on a reported history of excellent hand hygiene compliance., Results: All topics discussed by the interviewees could be categorised into the 14 TDF domains. Five TDF domains were particularly prominent: environmental context and resources, behavioural regulation, knowledge, social influences, and skills. The single most important facilitator for good hand hygiene compliance among both physicians and nurses was the construct/code goals (i.e., patient protection and self-protection). Additionally, for physicians, developing hand hygiene as a habit was considered particularly advantageous. Conversely, nurses emphasised that learning correct hand hygiene during their vocational training was especially beneficial for good compliance., Conclusions: The results highlight the importance of clear goals, habit development, comprehensive training, adequate resources, and a positive culture of communication in promoting good hand hygiene practices. The TDF has been proven to be a suitable model for identifying facilitating factors for hand hygiene compliance among healthcare workers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 von Auer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Artificial intelligence-enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited., Objective: This meta-analysis identified predictors influencing health care practitioners' intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence., Methods: The literature search using electronic databases, forward searches, conference programs, and personal correspondence yielded 7731 results, of which 17 (0.22%) studies met the inclusion criteria. Random-effects meta-analysis, relative weight analyses, and meta-analytic moderation and mediation analyses were used to examine the relationships between relevant predictor variables and the intention to use AI-CDSSs., Results: The meta-analysis results supported the application of the UTAUT to the context of the intention to use AI-CDSSs. The results showed that performance expectancy (r=0.66), effort expectancy (r=0.55), social influence (r=0.66), and facilitating conditions (r=0.66) were positively associated with the intention to use AI-CDSSs, in line with the predictions of the UTAUT. The meta-analysis further identified positive attitude (r=0.63), trust (r=0.73), anxiety (r=-0.41), perceived risk (r=-0.21), and innovativeness (r=0.54) as additional relevant predictors. Trust emerged as the most influential predictor overall. The results of the moderation analyses show that the relationship between social influence and use intention becomes weaker with increasing age. In addition, the relationship between effort expectancy and use intention was stronger for diagnostic AI-CDSSs than for devices that combined diagnostic and treatment recommendations. Finally, the relationship between facilitating conditions and use intention was mediated through performance and effort expectancy., Conclusions: This meta-analysis contributes to the understanding of the predictors of intention to use AI-CDSSs based on an extended UTAUT model. More research is needed to substantiate the identified relationships and explain the observed variations in effect sizes by identifying relevant moderating factors. The research findings bear important implications for the design and implementation of training programs for health care practitioners to ease the adoption of AI-CDSSs into their practice., (©Julius Dingel, Anne-Kathrin Kleine, Julia Cecil, Anna Leonie Sigl, Eva Lermer, Susanne Gaube. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.08.2024.)

Background and Aim: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screening offer a potential solution to aid self-examinations; however, their uptake is low. Therefore, the aim of this research was to examine provider and user characteristics influencing people's decisions to seek skin cancer screening performed by a mHealth app or a dermatologist., Methods: Two forced-choice conjoint experiments with N main  = 1591 and N replication  = 308 participants from the United States were conducted online to investigate preferences for screening providers. In addition to the provider type (mHealth app vs dermatologist), the following provider attributes were manipulated: costs, expertise, privacy policy, and result details. Subsequently, a questionnaire assessed various user characteristics, including demographics, attitudes toward AI technology and medical mistrust., Results: Outcomes were consistent across the two studies. The provider type was the most influential factor, with the dermatologist being selected more often than the mHealth app. Cost, expertise, and privacy policy also significantly impacted decisions. Demographic subgroup analyses showed rather consistent preference trends across various age, gender, and ethnicity groups. Individuals with greater medical mistrust were more inclined to choose the mHealth app. Trust, accuracy, and quality ratings were higher for the dermatologist, whether selected or not., Conclusion: Our results offer valuable insights for technology developers, healthcare providers, and policymakers, contributing to unlocking the potential of skin cancer screening apps in bridging healthcare gaps in underserved communities., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Despite the rise of decision support systems enabled by artificial intelligence (AI) in personnel selection, their impact on decision-making processes is largely unknown. Consequently, we conducted five experiments (N = 1403 students and Human Resource Management (HRM) employees) investigating how people interact with AI-generated advice in a personnel selection task. In all pre-registered experiments, we presented correct and incorrect advice. In Experiments 1a and 1b, we manipulated the source of the advice (human vs. AI). In Experiments 2a, 2b, and 2c, we further manipulated the type of explainability of AI advice (2a and 2b: heatmaps and 2c: charts). We hypothesized that accurate and explainable advice improves decision-making. The independent variables were regressed on task performance, perceived advice quality and confidence ratings. The results consistently showed that incorrect advice negatively impacted performance, as people failed to dismiss it (i.e., overreliance). Additionally, we found that the effects of source and explainability of advice on the dependent variables were limited. The lack of reduction in participants' overreliance on inaccurate advice when the systems' predictions were made more explainable highlights the complexity of human-AI interaction and the need for regulation and quality standards in HRM., (© 2024. The Author(s).)

Background: Artificial intelligence (AI) is often promoted as a potential solution for many challenges health care systems face worldwide. However, its implementation in clinical practice lags behind its technological development., Objective: This study aims to gain insights into the current state and prospects of AI technology from the stakeholders most directly involved in its adoption in the health care sector whose perspectives have received limited attention in research to date., Methods: For this purpose, the perspectives of AI researchers and health care IT professionals in North America and Western Europe were collected and compared for profession-specific and regional differences. In this preregistered, mixed methods, cross-sectional study, 23 experts were interviewed using a semistructured guide. Data from the interviews were analyzed using deductive and inductive qualitative methods for the thematic analysis along with topic modeling to identify latent topics., Results: Through our thematic analysis, four major categories emerged: (1) the current state of AI systems in health care, (2) the criteria and requirements for implementing AI systems in health care, (3) the challenges in implementing AI systems in health care, and (4) the prospects of the technology. Experts discussed the capabilities and limitations of current AI systems in health care in addition to their prevalence and regional differences. Several criteria and requirements deemed necessary for the successful implementation of AI systems were identified, including the technology's performance and security, smooth system integration and human-AI interaction, costs, stakeholder involvement, and employee training. However, regulatory, logistical, and technical issues were identified as the most critical barriers to an effective technology implementation process. In the future, our experts predicted both various threats and many opportunities related to AI technology in the health care sector., Conclusions: Our work provides new insights into the current state, criteria, challenges, and outlook for implementing AI technology in health care from the perspective of AI researchers and IT professionals in North America and Western Europe. For the full potential of AI-enabled technologies to be exploited and for them to contribute to solving current health care challenges, critical implementation criteria must be met, and all groups involved in the process must work together., (©Pia Hummelsberger, Timo K Koch, Sabrina Rauh, Julia Dorn, Eva Lermer, Martina Raue, Matthias F C Hudecek, Andreas Schicho, Errol Colak, Marzyeh Ghassemi, Susanne Gaube. Originally published in JMIR AI (https://ai.jmir.org), 31.10.2023.)

Background: Despite growing efforts to develop user-friendly artificial intelligence (AI) applications for clinical care, their adoption remains limited because of the barriers at individual, organizational, and system levels. There is limited research on the intention to use AI systems in mental health care., Objective: This study aimed to address this gap by examining the predictors of psychology students' and early practitioners' intention to use 2 specific AI-enabled mental health tools based on the Unified Theory of Acceptance and Use of Technology., Methods: This cross-sectional study included 206 psychology students and psychotherapists in training to examine the predictors of their intention to use 2 AI-enabled mental health care tools. The first tool provides feedback to the psychotherapist on their adherence to motivational interviewing techniques. The second tool uses patient voice samples to derive mood scores that the therapists may use for treatment decisions. Participants were presented with graphic depictions of the tools' functioning mechanisms before measuring the variables of the extended Unified Theory of Acceptance and Use of Technology. In total, 2 structural equation models (1 for each tool) were specified, which included direct and mediated paths for predicting tool use intentions., Results: Perceived usefulness and social influence had a positive effect on the intention to use the feedback tool (P<.001) and the treatment recommendation tool (perceived usefulness, P=.01 and social influence, P<.001). However, trust was unrelated to use intentions for both the tools. Moreover, perceived ease of use was unrelated (feedback tool) and even negatively related (treatment recommendation tool) to use intentions when considering all predictors (P=.004). In addition, a positive relationship between cognitive technology readiness (P=.02) and the intention to use the feedback tool and a negative relationship between AI anxiety and the intention to use the feedback tool (P=.001) and the treatment recommendation tool (P<.001) were observed., Conclusions: The results shed light on the general and tool-dependent drivers of AI technology adoption in mental health care. Future research may explore the technological and user group characteristics that influence the adoption of AI-enabled tools in mental health care., (©Anne-Kathrin Kleine, Eesha Kokje, Eva Lermer, Susanne Gaube. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 12.07.2023.)

Smartphone use while driving (SUWD) is a major cause of accidents and fatal crashes. This serious problem is still too little understood to be solved. Therefore, the current research aimed to contribute to a better understanding of SUWD by examining factors that have received little or no attention in this context: problematic smartphone use (PSU), fear of missing out (FOMO), and Dark Triad. In the first step, we conducted a systematic literature review to map the current state of research on these factors. In the second step, we conducted a cross-sectional study and collected data from 989 German car drivers. A clear majority (61%) admitted to using the smartphone while driving at least occasionally. Further, the results showed that FOMO is positively linked to PSU and that both are positively associated with SUWD. Additionally, we found that Dark Triad traits are relevant predictors of SUWD and other problematic driving behaviors--in particular, psychopathy is associated with committed traffic offenses. Thus, results indicate that PSU, FOMO, and Dark Triad are relevant factors to explain SUWD. We hope to contribute to a more comprehensive understanding of this dangerous phenomenon with these findings., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Hudecek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Internet trolling is considered a negative form of online interaction that can have detrimental effects on people's well-being. This pre-registered, experimental study had three aims: first, to replicate the association between internet users' online trolling behavior and the Dark Tetrad of personality (Machiavellianism, narcissism, psychopathy, and sadism) established in prior research; second, to investigate the effect of experiencing social exclusion on people's motivation to engage in trolling behavior; and third, to explore the link between humor styles and trolling behavior. In this online study, participants were initially assessed on their personality, humor styles, and global trolling behavior. Next, respondents were randomly assigned to a social inclusion or exclusion condition. Thereafter, we measured participants' immediate trolling motivation. Results drawn from 1,026 German-speaking participants indicate a clear correlation between global trolling and all facets of the Dark Tetrad as well as with aggressive and self-defeating humor styles. However, no significant relationship between experiencing exclusion/inclusion and trolling motivation emerged. Our quantile regression findings suggest that psychopathy and sadism scores have a significant positive effect on immediate trolling motivation after the experimental manipulation, whereas Machiavellianism and narcissism did not explain variation in trolling motivation. Moreover, being socially excluded had generally no effect on immediate trolling motivation, apart from participants with higher immediate trolling motivation, for whom the experience of social exclusion actually reduced trolling motivation. We show that not all facets of the Dark Tetrad are of equal importance for predicting immediate trolling motivation and that research should perhaps focus more on psychopathy and sadism. Moreover, our results emphasize the relevance of quantile regression in personality research and suggest that even psychopathy and sadism may not be suitable predictors for low levels of trolling behavior., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Volkmer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in healthcare. However, the impact of AI-generated advice on physicians' decision-making is underexplored. In this study, physicians received X-rays with correct diagnostic advice and were asked to make a diagnosis, rate the advice's quality, and judge their own confidence. We manipulated whether the advice came with or without a visual annotation on the X-rays, and whether it was labeled as coming from an AI or a human radiologist. Overall, receiving annotated advice from an AI resulted in the highest diagnostic accuracy. Physicians rated the quality of AI advice higher than human advice. We did not find a strong effect of either manipulation on participants' confidence. The magnitude of the effects varied between task experts and non-task experts, with the latter benefiting considerably from correct explainable AI advice. These findings raise important considerations for the deployment of diagnostic advice in healthcare., (© 2023. The Author(s).)

In March 2020, the German government enacted measures on movement restrictions and social distancing due to the COVID-19 pandemic. As this situation was previously unknown, it raised numerous questions about people's perceptions of and behavioral responses to these new policies. In this context, we were specifically interested in people's trust in official information, predictors for self-prepping behavior and health behavior to protect oneself and others, and determinants for adherence to social distancing guidelines. To explore these questions, we conducted three studies in which a total of 1,368 participants were surveyed (Study 1 N =377, March 2020; Study 2 N =461, April 2020; Study 3 N =530, April 2021) across Germany between March 2020 and April 2021. Results showed striking differences in the level of trust in official statistics (depending on the source). Furthermore, all three studies showed congruent findings regarding the influence of different factors on the respective behavioral responses. Trust in official statistics predicted behavioral responses in all three studies. However, it did not influence adherence to social distancing guidelines in 2020, but in 2021. Furthermore, adherence to social distancing guidelines was associated with higher acceptance rates of the measures and being older. Being female and less right-wing orientated were positively associated with guidelines adherence only in the studies from 2020. This year, political orientation moderated the association between acceptance of the measures and guideline adherence. This investigation is one of the first to examine perceptions and reactions during the COVID-19 pandemic in Germany across 1year and provides insights into important dimensions that need to be considered when communicating with the public., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lermer, Hudecek, Gaube, Raue and Batz.)

Health information technologies (HITs) are widely employed in healthcare and are supposed to improve quality of care and patient safety. However, so far, their implementation has shown mixed results, which might be explainable by understudied psychological factors of human-HIT interaction. Therefore, the present study investigates the association between the perception of HIT characteristics and psychological and organizational variables among 445 healthcare workers via a cross-sectional online survey in Germany. The proposed hypotheses were tested using structural equation modeling. The results showed that good HIT usability was associated with lower levels of techno-overload and lower IT-related strain. In turn, experiencing techno-overload and IT-related strain was associated with lower job satisfaction. An effective error management culture at the workplace was linked to higher job satisfaction and a slightly lower frequency of self-reported medical errors. About 69% of surveyed healthcare workers reported making errors less frequently than their colleagues, suggesting a bias in either the perception or reporting of errors. In conclusion, the study's findings indicate that ensuring high perceived usability when implementing HITs is crucial to avoiding frustration among healthcare workers and keeping them satisfied. Additionally healthcare facilities should invest in error management programs since error management culture is linked to other important organizational variables., (© 2021. The Author(s).)

Background: Hand hygiene is essential for infection prevention. This study aimed to find a suitable theoretical model and identify critical facilitators and barriers to explain hospital visitors' hand hygiene practice., Methods: Visitors in 4 hospitals were observed and asked to give explanations for using or not using the hand rub dispenser. The written explanations of N = 838 participants were coded according to three theoretical models: Theory of Planned Behavior, Health Action Process Approach (HAPA), and Theoretical Domains Framework (TDF)., Results: Self-reported hand hygiene behavior differed from observed behavior, with 15.75% wrongly claiming to have cleaned their hands. Critical facilitators for hand hygiene were attitude toward the behavior,subjective norm, outcome expectancies, risk perception, planning, action control, knowledge and skills, motivation and goals, and social influences. Key barriers included perceived behavioral control; barriers and resources; memory, attention, and decision processes; and environmental context and resources., Conclusions: Visitors' self-reported hand hygiene behavior is over-reported. Both HAPA and TDF were identified as suitable theoretical models for explaining visitor's hand hygiene practice. Future behavior change interventions should focus on (1) visibility and accessibility of cleaning products; (2) informing laypeople about their role regarding infection prevention; and (3) leveraging social influence processes., (Copyright © 2021 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.)

Artificial intelligence (AI) models for decision support have been developed for clinical settings such as radiology, but little work evaluates the potential impact of such systems. In this study, physicians received chest X-rays and diagnostic advice, some of which was inaccurate, and were asked to evaluate advice quality and make diagnoses. All advice was generated by human experts, but some was labeled as coming from an AI system. As a group, radiologists rated advice as lower quality when it appeared to come from an AI system; physicians with less task-expertise did not. Diagnostic accuracy was significantly worse when participants received inaccurate advice, regardless of the purported source. This work raises important considerations for how advice, AI and non-AI, should be deployed in clinical environments.

Background: Improving hand hygiene in hospitals is the most efficient method to prevent healthcare-associated infections. The hand hygiene behavior of hospital patients and visitors is not well-researched, although they pose a risk for the transmission of pathogens. Therefore, the present study had three aims: (1) Finding a suitable theoretical model to explain patients' and visitors' hand hygiene practice; (2) Identifying important predictors for their hand hygiene behavior; and (3) Comparing the essential determinants of hand hygiene behavior between healthcare professionals from the literature to our non-professional sample., Methods: In total N = 1,605 patients and visitors were surveyed on their hand hygiene practice in hospitals. The employed questionnaires were based on three theoretical models: a) the Theory of Planned Behavior (TPB); b) the Health Action Process Approach (HAPA); and c) the Theoretical Domains Framework (TDF). Structural equation modeling was used to analyze the data. To compare our results to the determinants of healthcare workers' hand hygiene behavior, we searched for studies that used one of the three theoretical models., Results: Among patients, 52% of the variance in the hand hygiene behavior was accounted for by the TDF domains, 44% by a modified HAPA model, and 40% by the TPB factors. Among visitors, these figures were 59%, 37%, and 55%, respectively. Two clusters of variables surfaced as being essential determinants of behavior: self-regulatory processes and social influence processes. The critical determinants for healthcare professionals' hand hygiene reported in the literature were similar to the findings from our non-professional sample., Conclusions: The TDF was identified as the most suitable model to explain patients' and visitors' hand hygiene practices. Patients and visitors should be included in existing behavior change intervention strategies. Newly planned interventions should focus on targeting self-regulatory and social influence processes to improve effectiveness., Competing Interests: The authors have declared that no competing interests exist.

Objective: Hospital visitors pose a risk for transmitting pathogens that can cause health care-associated infections. The present study aimed to test an evidence-based intervention to improve visitors' hand hygiene behavior through persuasive messages., Method: For the 14-week-long field experiment, 7 signs were designed according to the principles of persuasion proposed by Cialdini: reciprocity, consistency, social-proof, unity, liking, authority, and scarcity. Each sign was displayed on a screen for 1 week directly above the hand-rub dispenser in a hospital lobby. After each 1-week posting, the screen was blank for 1 week., Results: An electronic monitoring system counted 246,098 people entering and leaving the hospital's lobby and 17,308 dispenser usages. The signs based on the authority and the social-proof principles significantly increased the hand-rub dispenser usage rate in comparison to the average baseline usage rate., Conclusions: These results indicate that simple and cost-efficient interventions can initiate expedient behavior change in hospitals. However, the findings also highlight the importance of careful planning and rigorous pretesting of material for an intervention to be effective. Theoretical and practical implications of these findings are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Hand hygiene practice in hospitals is unfortunately still widely insufficient, even though it is known that transmitting pathogens via hands is the leading cause of healthcare-associated infections. Previous research has shown that improving knowledge, providing feedback on past behaviour and targeting social norms are promising approaches to improve hand hygiene practices. The present field experiment was designed to direct people on when to perform hand hygiene and prevent forgetfulness. This intervention is the first to examine the effect of inducing injunctive social norms via an emoticon-based feedback system on hand hygiene behaviour. Electronic monitoring and feedback devices were installed in hospital patient rooms on top of hand-rub dispensers, next to the doorway, for a period of 17 weeks. In the emoticon condition, screens at the devices activated whenever a person entered or exited the room. Before using the alcohol-based hand-rub dispenser, a frowny face was displayed, indicating that hand hygiene should be performed. If the dispenser was subsequently used, this picture changed to a smiley face to positively reinforce the correct behaviour. Hand hygiene behaviour in the emoticon rooms significantly outperformed the behaviour in three other tested conditions. The strong effect in this field experiment indicates that activating injunctive norms may be a promising approach to improve hand hygiene behaviour. Theoretical and practical implications of these findings are discussed., Competing Interests: The authors have declared that no competing interests exist.

Background: Androgen excess may provoke or aggravate acne by inducing seborrhea. In women, androgen disorders are frequently suspected when acne is accompanied by hirsutism or irregularities of the menstrual cycle. In men, however, acne may be the only sign of androgen excess., Objective: Our aim was to investigate whether male patients with acne display pathologic androgen blood values., Methods: This case-control study at a university dermatology department with referred and unreferred patients investigated male acne patients (n = 82, consecutive sample) in whom the diagnosis of mild to severe acne was made, as well as a control group of men without acne (n = 38). The main outcome measures were androgen parameters including morning values of testosterone, luteinizing hormone, follicle-stimulating hormone, dehydroepiandrosterone sulfate, androstenedione, and 17-hydroxyprogesterone; as well as a corticotropin stimulation test., Results: 17-Hydroxyprogesterone levels were significantly higher (P = .01) in acne patients than in the control group, whereas the other parameters did not differ significantly. In addition, the corticotropin stimulation test revealed abnormal 17-hydroxyprogesterone induction values in 10 of 82 patients., Limitations: The analysis is limited to a selection of androgen parameters., Conclusion: The results suggest that in men irregularities of adrenal steroid metabolism may be a factor contributing to acne.

DNA damage caused by ultraviolet (UV) irradiation is considered the main etiologic factor contributing to the development of skin cancer. Systemic or topical application of antioxidants has been suggested as a protective measure against UV-induced skin damage. We investigated the effect of long-term oral administration of a combination of the antioxidants ascorbic acid (vitamin C) and D-alpha-tocopherol (vitamin E) in human volunteers on UVB-induced epidermal damage. The intake of vitamins C and E for a period of 3 mo significantly reduced the sunburn reaction to UVB irradiation. Detection of thymine dimers in the skin using a specific antibody revealed a significant increase of this type of DNA damage following UVB exposure. After 3 mo of antioxidant administration, significantly less thymine dimers were induced by the UVB challenge, suggesting that antioxidant treatment protected against DNA damage.

Antimicrobials are widely used in topical formulations as preservatives or as therapeutically active agents. Photosensitization by such compounds has not yet been studied systematically. To identify possible phototoxic properties, antimicrobials (benzyl alcohol, bronopol, chloracetamide, clioquinol, diazolidinyl urea, ethylenediamine dihydrochloride, formaldehyde, glutaraldehyde, imidazolidinyl urea, sodium benzoate, propylene glycol) were evaluated in vitro by means of a photohaemolysis test using suspensions of human erythrocytes. Irradiations were performed with UVA- and UVB-rich light sources. In the presence of bronopol or clioquinol, there was photohaemolysis up to 78.1% or 48.5% with UVA and up to 100% or 34.3% with UVB, respectively. The phototoxic effect depended on the concentration of the compounds and the UV doses administered. None of the other substances tested caused significant photohaemolysis. It is concluded that bronopol and clioquinol exert phototoxic effects in vitro and thus might also cause photosensitization when used on the skin. The clinical significance of this has to be established by further work.

A number of findings concerning the pathogenesis of insulin-dependent diabetes mellitus have shown that an autoimmune process is responsible for the destruction of the beta-cell mass, and that a major part of this process has already occurred during the prediabetic phase of the disease. Various immunosuppressive intervention trials have, thus, recently been performed. Remission rates of between 30% and 50% in the Canadian cyclosporin A (CyA) pilot study prompted two placebo-controlled double-blind studies applying this medication. In the French CyA trial 122 patients were followed up for 9 months. 37% of those on high-dose CyA (whole blood levels greater than 300 ng/ml) achieved total remission, compared with 16.7% of those on low-dose CyA (blood level less than 300 ng/ml) and 5% of the placebo group. The Canadian-European trial included 188 patients, of whom 42 were treated in the Viennese centre. Diabetes had been diagnosed in these 42 patients not more than 6 weeks previously, and the duration of their symptoms did not exceed 14 weeks. Whole blood CyA levels ranged from 400 to 800 ng/ml. In relation to short duration of symptoms and early commencement of treatment up to 10 times higher total remission rates were found in the CyA group as compared with the placebo group. In both studies similar side effects were seen. Apart from the cosmetic side effects (hypertrichosis, gingival hyperplasia) a decrease of 20% in creatinine clearance and an increase of 20% in plasma creatinine level seemed to be of clinical importance.(ABSTRACT TRUNCATED AT 250 WORDS)