Interim analyses in clinical trials can take on a multitude of forms. They are often used to guide Data and Safety Monitoring Board (DSMB) recommendations to study teams regarding recruitment targets for large, later-phase clinical trials. As collaborative biostatisticians working and teaching in multiple fields of research and across a broad array of trial phases, we note the large heterogeneity and confusion surrounding interim analyses in clinical trials. Thus, in this paper, we aim to provide a general overview and guidance on interim analyses for a nonstatistical audience. We explain each of the following types of interim analyses: efficacy, futility, safety, and sample size re-estimation, and we provide the reader with reasoning, examples, and implications for each. We emphasize that while the types of interim analyses employed may differ depending on the nature of the study, we would always recommend prespecification of the interim analytic plan to the extent possible with risk mitigation and trial integrity remaining a priority. Finally, we posit that interim analyses should be used as tools to help the DSMB make informed decisions in the context of the overarching study. They should generally not be deemed binding, and they should not be reviewed in isolation.

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Advances in the digitization of health systems and expedited regulatory approvals of innovative treatments have led to increased potential for the use of real-world data (RWD) to generate real-world evidence (RWE) to complement evidence from clinical trials. However, health technology assessment (HTA) bodies and payers have concerns about the ability to generate RWE of sufficient quality to be pivotal evidence of relative treatment effectiveness. Consequently, there is a growing need for HTA bodies and payers to develop guidance for the industry and other stakeholders about the use of RWD/RWE to support access, reimbursement, and pricing. We therefore sought to (i) understand barriers to the use of RWD/RWE by HTA bodies and payers; (ii) review potential solutions in the form of published guidance; and (iii) review findings with selected HTA/payer bodies. Four themes considered key to shaping the generation of robust RWE for HTA bodies and payers were identified as: (i) data (availability, governance, and quality); (ii) methodology (design and analytics); (iii) trust (transparency and reproducibility); and (iv) policy and partnerships. A range of guidance documents were found from trusted sources that could address these themes. These were discussed with HTA experts. This commentary summarizes the potential guidance solutions available to help resolve issues faced by HTA decision-makers in the adoption of RWD/RWE. It shows that there is alignment among stakeholders about the areas that need improvement in the development of RWE and that the key priority to move forward is better collaboration to make data usable for multiple purposes.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc.). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer-reviewed journals, as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

As the COVID-19 pandemic escalates worldwide, it is apparent that many patients with more severe illness will also experience delirium. These patients pose a particular challenge in the application of optimal care due to issues with infectious risk, respiratory compromise and potential interactions between medications that can be used to manage delirium with antiviral and other treatments used for COVID-19. We describe a guidance resource adapted from existing guidelines for delirium management that has been tailored to the specific challenge of managing delirium in patients with COVID-19 infection. Issues around the assessment and treatment of these patients are examined and distilled into a simple (one-paged guidance resource that can assist clinicians in managing suspected delirium.

If emotions have a rational role in action, then one challenge for accounting for how we can act rationally when acting emotionally is to show how we can guide our actions by our emotional considerations, seen as reasons. In this paper, I put forward a novel proposal for how this can be so. Drawing on the interconnection between emotions, cares and caring, I argue that, as the emotional agent is a caring agent, she can be aware of the emotional consideration as a pro tanto reason favouring an action choice and, even, as the reason for which she should act.

A non-holonomic robot with a bounded control input travels in a dynamic unknown 3D environment with moving obstacles. We propose a 3D navigation strategy to reach a given final destination point while avoiding collisions with obstacles. A formal analysis of the proposed 3D robot navigation algorithm is given. Computer simulation results and experiments with a real flying autonomous vehicle confirm the applicability and performance of the proposed guidance approach.

Studying worked examples providing problem solutions to learners usually leads to better test performance than solving the equivalent problems without guidance, demonstrating the worked-example effect. The generation effect occurs when learners who generate answers without guidance learn better than those who read answers that provide guidance. The contradiction between these results can be hypothesised to be due to differences in the element interactivity of the learning tasks. Primary school students in Year 6 participated in the experiment, which investigated the hypothesis by using geometry materials. A disordinal interaction was obtained between levels of guidance and levels of element interactivity. Higher levels of guidance facilitated learning using high element interactivity information, while lower levels of guidance facilitated learning for low element interactivity information. Cognitive load theory was used to explain these contrasting results. From an educational perspective, it was suggested that when determining levels of guidance, a consideration of element interactivity is essential.