BACKGROUND: Self-monitoring of physical activity (PA) using an accelerometer is a promising intervention to stimulate PA after hospital discharge.OBJECTIVE: This study aimed to evaluate the feasibility of PA self-monitoring after discharge in patients who have undergone gastrointestinal or lung cancer surgery.METHODS: A mixed methods study was conducted in which 41 patients with cancer scheduled for lobectomy, esophageal resection, or hyperthermic intraperitoneal chemotherapy were included. Preoperatively, patients received an ankle-worn accelerometer and the corresponding mobile health app to familiarize themselves with its use. The use was continued for up to 6 weeks after surgery. Feasibility criteria related to the study procedures, the System Usability Scale, and user experiences were established. In addition, 6 patients were selected to participate in semistructured interviews.RESULTS: The percentage of patients willing to participate in the study (68/90, 76%) and the final participation rate (57/90, 63%) were considered good. The retention rate was acceptable (41/57, 72%), whereas the rate of missing accelerometer data was relatively high (31%). The mean System Usability Scale score was good (77.3). Interviewed patients mentioned that the accelerometer and app were easy to use, motivated them to be more physically active, and provided postdischarge support. The technical shortcomings and comfort of the ankle straps should be improved.CONCLUSIONS: Self-monitoring of PA after discharge appears to be feasible based on good system usability and predominantly positive user experiences in patients with cancer after lobectomy, esophageal resection, or hyperthermic intraperitoneal chemotherapy. Solving technical problems and improving the comfort of the ankle strap may reduce the number of dropouts and missing data in clinical use and follow-up studies.
Live programming is a style of development characterized by incremental change and immediate feedback. Instead of long edit-compile cycles, developers modify a running program by changing its source code, receiving immediate feedback as it instantly adapts in response. In this paper, we propose an approach to bridge the gap between running programs and textual domain-specific languages (DSLs). The first step of our approach consists of applying a novel model differencing algorithm, tmdiff, to the textual DSL code. By leveraging ordinary text differencing and origin tracking, tmdiff produces deltas defined in terms of the metamodel of a language. In the second step of our approach, the model deltas are applied at run time to update a running system, without having to restart it. Since the model deltas are derived from the static source code of the program, they are unaware of any run-time state maintained during model execution. We therefore propose a generic, dynamic patch architecture, rmpatch, which can be customized to cater for domain-specific state migration. We illustrate rmpatch in a case study of a live programming environment for a simple DSL implemented in Rascal for simultaneously defining and executing state machines.
In L1 grammar teaching, teachers often struggle with the students’ conceptual understanding of the subject matter. Frequently, students do not acquire an in-depth understanding of grammar, and they seem generally incapable of reasoning about grammatical problems. Some scholars have argued that an in-depth understanding of grammar requires making connections between concepts from traditional grammar and underlying metaconcepts from linguistic theory. In the current study, we evaluate an intervention aiming to do this, following up on a previous study that found a significant effect for such an approach in university students of Dutch Language and Literature (d = 0.62). In the current study, 119 Dutch secondary school students’ grammatical reasonings (N=684) were evaluated by language teachers, teacher educators and linguists pre and post intervention using comparative judgement. Results indicate that the intervention significantly boosted the students’ ability to reason grammatically (d = 0.46), and that many students can reason based on linguistic metaconcepts. The study also shows that reasoning based on explicit underlying linguistic metaconcepts and on explicit concepts from traditional grammar is more favored by teachers and (educational) linguists than reasoning without explicit (meta)concepts. However, some students show signs of incomplete acquisition of the metaconcepts. The paper discusses explanations for this incomplete acquisition.
