From Critique to Collaboration: Rethinking Computerized Clinical Alerts

poster abstractThe safe prescribing of medications via computerized physician order entry routinely relies on clinical alerts. Alert compliance, however, remains surprisingly low—with up to 96% of such alerts ignored daily. Prior approaches, such as improving presentational factors in alert design, had limited success, mainly due to physicians’ lack of trust in computerized advice. While designing trustworthy alert is key, actionable design principles to embody elements of trust in alerts remain little explored. To address this issue, we focus on improving the trust between physicians and computerized advice by examining why physicians trust their medical colleagues. To understand trusted advice among physicians, we conducted three contextual inquiries in a hospital setting (n = 22) and corroborated our findings with a survey (n = 37). Drivers that guided physicians in trusting peer advice included: timeliness of the advice, collaborative language, empathy, level of specialization, and medical hierarchy. Based on these findings, we introduced seven design directions for trust-based alerts: endorsement, transparency, team sensing, collaborative, empathic, conflict mitigating, and agency laden. Grounded in these results, we then proposed a model to guide the design of trust-based clinical alerts. Our model constitutes of three key dimensions, using colleagues’ endorsement, foregrounding physicians’ prior actions, and adopting a suitable language. Using this model, we iteratively designed, pruned, and validated a set of novel alert designs. We are currently evaluating eleven alert designs in an online survey with physicians. The ongoing survey evaluates the likelihood of alert compliance and the perceived value of our proposed trust-based alerts. Next, we are planning in-lab studies to evaluate physicians’ cognitive load during decision making and measure attention to different trust cues using gaze duration and trajectories. Our work contributes to the current debate on how to design effective alerts to improve patient safety. Acknowledgements. This research material is based on work supported by the National Science Foundation under Grant #1343973. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the NSF

A study of psychiatrists’ concepts of mental illness

Background: There are multiple models of mental illness that inform professional and lay understanding. Few studies have formally investigated psychiatrists' attitudes. We aimed to measure how a group of trainee psychiatrists understand familiar mental illnesses in terms of propositions drawn from different models. Method: We used a questionnaire study of a sample of trainees from South London and Maudsley National Health Service (NHS) Foundation Trust designed to assess attitudes across eight models of mental illness (e.g. biological, psychodynamic) and four psychiatric disorders. Methods for analysing repeated measures and a principal components analysis (PCA) were used. Results: No one model was endorsed by all respondents. Model endorsement varied with disorder. Attitudes to schizophrenia were expressed with the greatest conviction across models. Overall, the ‘biological’ model was the most strongly endorsed. The first three components of the PCA (interpreted as dimensions around which psychiatrists, as a group, understand mental illness) accounted for 56% of the variance. Each main component was classified in terms of its distinctive combination of statements from different models: PC1 33% biological versus non-biological; PC2 12% ‘eclectic’ (combining biological, behavioural, cognitive and spiritual models); and PC3 10% psychodynamic versus sociological. Conclusions: Trainee psychiatrists are most committed to the biological model for schizophrenia, but in general are not exclusively committed to any one model. As a group, they organize their attitudes towards mental illness in terms of a biological/non-biological contrast, an ‘eclectic’ view and a psychodynamic/sociological contrast. Better understanding of how professional group membership influences attitudes may facilitate better multidisciplinary working

Dynamics, robustness and fragility of trust

Trust is often conveyed through delegation, or through recommendation. This makes the trust authorities, who process and publish trust recommendations, into an attractive target for attacks and spoofing. In some recent empiric studies, this was shown to lead to a remarkable phenomenon of *adverse selection*: a greater percentage of unreliable or malicious web merchants were found among those with certain types of trust certificates, then among those without. While such findings can be attributed to a lack of diligence in trust authorities, or even to conflicts of interest, our analysis of trust dynamics suggests that public trust networks would probably remain vulnerable even if trust authorities were perfectly diligent. The reason is that the process of trust building, if trust is not breached too often, naturally leads to power-law distributions: the rich get richer, the trusted attract more trust. The evolutionary processes with such distributions, ubiquitous in nature, are known to be robust with respect to random failures, but vulnerable to adaptive attacks. We recommend some ways to decrease the vulnerability of trust building, and suggest some ideas for exploration.Comment: 17 pages; simplified the statement and the proof of the main theorem; FAST 200

“Trust me, do not trust anyone”: how epistemic mistrust and credulity are associated with conspiracy mentality

Previous research shows that the propensity to endorse conspiracy theories is associated with disrupted forms of epistemic trust, i.e., the appropriate openness towards interpersonally communicated information. There are associations, first, with an increased mistrust in several actors and institutions responsible for the communication of information in society, and second, with a pronounced credulity in unreliable sources and implausible phenomena (e.g., superstition, astrology). This study aims to investigate whether these phenomena are associated with specific personality-related disruptions of epistemic trust. Based on selfreported data of 417 individuals (mean = 33.28; standard deviation = 11.11) from a UK population sampled online, the potential relationships between disruptions in epistemic trust and the endorsement of a conspiracy mentality are explored. The epistemic stances characterized by mistrust and credulity (independent variables) are measured with the epistemic trust, mistrust, and credulity questionnaire (ETMCQ), and conspiracy mentality (dependent variable) is measured with the conspiracy mentality questionnaire. In a multiple linear regression model, mistrust is associated with the endorsement of a conspiracy mentality, even when accounting for other contributing factors (e.g., individual narcissism, attachment avoidance and anxiety, authoritarianism, loneliness). In a bootstrapped mediation model controlling for other relevant predictors, the association between credulity and conspiracy mentality is fully mediated by mistrust. In future research, the impact of disrupted epistemic trust on conspiracy beliefs should be investigated in terms of the specific epistemic stances of mistrust and credulity. In this respect, the ETMCQ represents a highly promising instrument to assess individual differences in factors underpinning aspects of conspiracy endorsement

Evaluating e-commerce trust using fuzzy logic [article]

Trust is widely recognized as an essential factor for the continual development of business to customer electronic commerce (B2C EC). Many trust models have been developed, however, most are subjective and do not take into account the vagueness and ambiguity of EC trust and the customers’ intuitions and experience when conducting online transactions. In this article, we develop a fuzzy trust model using fuzzy reasoning to evaluate EC trust. This trust model is based on the information customers expect to find on an EC Website and is shown to increase customers trust towards online merchants. We argue that fuzzy logic is suitable for trust evaluation as it takes into account the uncertainties within e-commerce data and like human relationships; it is often expressed by linguistics terms rather then numerical values. The evaluation of the proposed model will be illustrated using two case studies and a comparison with two evaluation models was conducted to emphasise the importance of usin fuzzy logic