Defining unmet clinical need across the pathway of brain tumor care: a patient and carer perspective.

OBJECTIVE: The aim of this study was to determine the experience of patients with brain tumors and their carers across distinct parts of their treatment pathway and identify their views on potential service gaps in need of addressing. METHODS: A structured survey was administered at patient workshops across the UK and online through a charity newsletter. Answers to closed questions were analyzed using descriptive statistics, and open questions were examined using techniques of inductive content analysis. RESULTS: A total of 136 survey responses were received, representing patients with a variety of diagnoses and geographical locations (30 counties). There was a wide range of opinions on the provision of current neuro-oncology services. Key themes identified included a perceived lack of information provision, a gap in postdischarge psychological and neuropsychological supports, and an unmet willingness for involvement in research. CONCLUSION: This national survey enhances our knowledge of current patient and carer experience within neuro-oncology services. A number of areas of unmet clinical need are highlighted providing a basis for informing future patient-centered service improvements and research

Scaling up behavioral science interventions in online education

Online education is rapidly expanding in response to rising demand for higher and continuing education, but many online students struggle to achieve their educational goals. Several behavioral science interventions have shown promise in raising student persistence and completion rates in a handful of courses, but evidence of their effectiveness across diverse educational contexts is limited. In this study, we test a set of established interventions over 2.5 y, with one-quarter million students, from nearly every country, across 247 online courses offered by Harvard, the Massachusetts Institute of Technology, and Stanford. We hypothesized that the interventions would produce medium-to-large effects as in prior studies, but this is not supported by our results. Instead, using an iterative scientific process of cyclically preregistering new hypotheses in between waves of data collection, we identified individual, contextual, and temporal conditions under which the interventions benefit students. Self-regulation interventions raised student engagement in the first few weeks but not final completion rates. Value-relevance interventions raised completion rates in developing countries to close the global achievement gap, but only in courses with a global gap. We found minimal evidence that state-of-the-art machine learning methods can forecast the occurrence of a global gap or learn effective individualized intervention policies. Scaling behavioral science interventions across various online learning contexts can reduce their average effectiveness by an order-of-magnitude. However, iterative scientific investigations can uncover what works where for whom.</jats:p