How physiotherapists perceive,interpret, and respond to the ethical dimensions of practice: A qualitative study

The profile and reach of physiotherapy has expanded in areas of extended scope of practice, and broader engagement with population needs beyond the individual treatment encounter. These changes raise increasingly complex ethical challenges evidenced by growth in physiotherapy-based ethics studies and discussions. This paper examines how a broad cross section of Australian physiotherapists perceive, interpret, and respond to ethical challenges in their work contexts and how professional codes of conduct are used in their practice. Using an interpretive qualitative methodology, purposive sampling of 88 members of national clinical special interest groups were recruited for focus group discussions. Narrative-based and thematic data analysis identified ethical challenges as emerging from specific clinical contexts, and influenced by health organizations, funding policies, workplace relationships, and individually held perspectives. Five themes were developed to represent these findings: (1) the working environment, (2) balancing diverse needs and expectation, (3) defining ethics, (4) striving to act ethically, and (5) talking about ethics. The results portray a diverse and complex ethical landscape where therapists encounter and grapple with ethical questions emerging from the impact of funding models and policies affecting clinical work, expanding boundaries and scope of practice and changing professional roles and relationships. Codes of conduct were described as foundational ethical knowledge but not always helpful for “in the moment” ethical decision-making. Based on this research, we suggest how codes of conduct, educators, and professional associations could cultivate and nurture ethics capability in physiotherapy practitioners for these contemporary challenges.     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.