医疗机器人的伦理风险与治理探析——基于“医−患−机”分析框架

基于“医−患−机”分析框架,医疗机器人的不断发展面临主体资质复杂、责任认定困难等责任伦理风险,医患关系重构、医患信任危机等医患伦理风险,数据质量与数据隐私等数据伦理风险,算法安全与算法偏见等算法伦理风险以及医疗资源分配正义风险。医疗机器人的伦理治理要以医学伦理和机器人伦理准则为依据,建立多元伦理治理体制,推动学术共同体的构建,探索自愿型、调节型与管制型等伦理治理工具的组合运用,加快医疗机器人伦理治理的法治化发展。

     

统计学习的认知神经机制及其与语言的关系

统计学习是指个体在连续刺激流中发现转移概率等统计规律的过程, 在Saffran等(1996)的经典婴儿语音切分研究中首次被提出。大量研究证实了统计学习的普遍存在, 近期学界开始关注统计学习的特异性及其对认知的影响, 尤其是从学习过程及其特异性两个方面阐述统计学习的认知神经机制并揭示其和语言的交互作用。未来应从脑和行为的多模态数据视角, 丰富统计学习结果的行为和神经指标, 考察不同类型统计学习过程的动态神经活动模式, 建立统计学习行为和脑的关联, 深化对统计学习认知神经机制的认识, 在统计学习与语言交互作用的基础上, 从成人二语学习切入结合音乐统计学习训练探讨促进语言学习的统计学习干预手段。     

Approaching Complex Cases With a Crisis Intervention Model and Teamwork

Patients referred for genetic counseling may be in a state of crisis, feeling as though they are incapable of making decisions about the management of their pregnancy, genetic testing options and/or life planning issues. The role of the genetic counselor is to assist a patient through this crisis state by increasing the patient's understanding and by helping to facilitate decision making and adjustment to those decisions. In this paper we present a clinical genetic counseling case that was complicated by numerous medical and psychosocial issues. The wide scope of this case required the involvement of both a prenatal and a medical genetic counselor. Working as a team we utilized a crisis intervention model. Our counseling focused on identifying and isolating the issues, providing factual information, setting a time frame for decisions to be made, and encouraging social support and emotion-focused coping strategies.     

Sensitive Topics,Missing Data,and Refusal in Social Network Studies: An Ethical Examination

We describe our ethics‐driven process of addressing missing data within a social network study about accountability for racism, classism, sexism, heterosexism, cis‐sexism, ableism, and other forms of oppression among social justice union organizers. During data collection, some would‐be participants did not return emails and others explicitly refused to engage in the research. All refusals came from women of color. We faced an ethical dilemma: Should we continue to seek participation from those who had not yet responded, with the hopes of recruiting more women of color from within the network so their perspectives would not be tokenized? Or, should we stop asking those who had been contacted multiple times, which would compromise the social network data and analysis? We delineate ways in which current discussions of the ethics of social network studies fell short, given our framework and our community psychology (CP ) values. We outline literature that was helpful in thinking through this challenge; we looked outside of CP to the decolonization literature on refusal. Lessons learned include listening for the possible meanings of refusals and considering the level of engagement and the labor required of participants when designing research studies.     

Investigating cycling kinematics and braking maneuvers in the real world: e-bikes make cyclists move faster,brake harder,and experience new conflicts

Pedelecs (e-bikes), which facilitate higher speeds with less effort in comparison to traditional bicycles (t-bikes), have grown considerably in popularity in recent years. Despite the large expansion of this new transportation mode, little is known about the behavior of e-cyclists, or whether cycling an e-bike increases crash risk and the likelihood of conflicts with other road users, compared to cycling on t-bikes. In order to support the design of safety measures and to maximize the benefits of e-bike use, it is critical to investigate the real-world behavior of riders as a result of switching from t-bikes to e-bikes.Naturalistic studies provide an unequaled method for investigating rider cycling behavior and bicycle kinematics in the real world in which the cyclist regularly experiences traffic conflicts and may need to perform avoidance maneuvers, such as hard braking, to avoid crashing. In this paper we investigate cycling kinematics and braking events from naturalistic data to determine the extent to which cyclist behavior changes as a result of transferring from t-bikes to e-bikes, and whether such change influences cycling safety.Data from the BikeSAFE and E-bikeSAFE naturalistic studies were used in this investigation to evaluate possible changes in the behavior of six cyclists riding t-bikes in the first study and e-bikes in the second one. Individual cyclists’ kinematics were compared between bicycle types. In addition, a total of 5092 braking events were automatically extracted after identification of dynamic triggers. The 286 harshest braking events (136 cases for t-bike and 150 for e-bike) were then validated and coded via video inspection.Results revealed that each of the cyclists rode faster on the e-bike than on the t-bike, increasing his/her average speed by 2.9–5.0 km/h. Riding an e-bike also increased the probability to unexpectedly have to brake hard (odds ratio = 1.72). In addition, the risk of confronting abrupt braking and sharp deceleration were higher when riding an e-bike than when riding a t-bike.Our findings provide evidence that cyclists’ behavior and the way cyclists interact with other road users change when cyclists switch from t-bikes to e-bikes. Because of the higher velocity, when on e-bikes, cyclists appear to have harder time predicting movements within the traffic environment and, as a result, they need to brake abruptly more often to avoid collisions, compared with cycling on t-bikes. This study provides new insights into the potential impact on safety that a cycling society moving to e-bikes may have, indicating that e-cycling requires more reactive maneuvers than does cycling traditional bicycles and suggesting that any distractive activity may be more critical when riding e-bikes compared to traditional bikes.     

Genetically Engineered Traits versus Virtuous Living

It is fruitless to attempt to genetically engineer virtuous living. Prenatal genome modification could, in principle, establish desired traits and predispose us to certain behaviors. But, traits given at birth are not the same thing as a virtuous character that can be acquired only by self-discipline. The ethicist further fears that free market eugenics—the sale of gene modification—may become one more expression of the social sin our culture inherits.     

Testing autocorrelation and partial autocorrelation: Asymptotic methods versus resampling techniques

Autocorrelation and partial autocorrelation, which provide a mathematical tool to understand repeating patterns in time series data, are often used to facilitate the identification of model orders of time series models (e.g., moving average and autoregressive models). Asymptotic methods for testing autocorrelation and partial autocorrelation such as the 1/T approximation method and the Bartlett's formula method may fail in finite samples and are vulnerable to non-normality. Resampling techniques such as the moving block bootstrap and the surrogate data method are competitive alternatives. In this study, we use a Monte Carlo simulation study and a real data example to compare asymptotic methods with the aforementioned resampling techniques. For each resampling technique, we consider both the percentile method and the bias-corrected and accelerated method for interval construction. Simulation results show that the surrogate data method with percentile intervals yields better performance than the other methods. An R package pautocorr is used to carry out tests evaluated in this study.     

Understanding the prevalence and correlates of implicit theories of weight in the United States: Insights from a nationally representative sample

Objectives: The primary aim of this research is to understand how mindsets about weight controllability in the United States relate to population health. We examined the distribution of people’s implicit theories of weight, from an incremental (controllable) to an entity (not controllable) mindset, in a nationally representative sample, as well as their relation to: sociodemographic factors, beliefs about behaviour and genetics as causes of obesity and engagement in weight management-relevant behaviours.

Methods: We report data from the National Cancer Institute’s Health Information National Trends Survey 4.

Results: A majority of respondents endorsed an incremental mindset of body weight, but endorsement of this mindset was stronger among younger, white respondents, and those with a higher income and more educational attainment. A stronger incremental mindset was related to stronger behaviour and weaker genetic causal beliefs about obesity, as well as a tendency to report increased engagement in weight management-relevant behaviours.

Conclusions: Our research provides evidence that although incremental mindsets are more common overall and associated with engagement in health behaviours that can contribute to or detract from population health, incremental mindsets are less common among individuals from more marginalised groups.     

Collectivizing Rescue Obligations in Bioethics

Bioethicists invoke a duty to rescue in a wide range of cases. Indeed, arguably, there exists an entire medical paradigm whereby vast numbers of medical encounters are treated as rescue cases. The intuitive power of the rescue paradigm is considerable, but much of this power stems from the problematic way that rescue cases are conceptualized—namely, as random, unanticipated, unavoidable, interpersonal events for which context is irrelevant and beneficence is the paramount value. In this article, I critique the basic assumptions of the rescue paradigm, reframe the ethical landscape in which rescue obligations are understood, and defend the necessity and value of a wider social and institutional view. Along the way, I move back and forth between ethical theory and a concrete case where the duty to rescue has been problematically applied: the purported duty to regularly return incidental findings and individual research results in genomic and genetic research.