Background: According to the principles of Reablement, home care services are meant to be goal-oriented, holistic and person-centred taking into account the capabilities and opportunities of older adults. However, home care services traditionally focus on doing things for older adults rather than with them. To implement Reablement in practice, the ‘Stay Active at Home’ programme was developed. It is assumed that the programme leads to a reduction in sedentary behaviour in older adults and consequently more cost-effective outcomes in terms of their health and wellbeing. However, this has yet to be proven. Methods/ design: A two-group cluster randomised controlled trial with 12 months follow-up will be conducted. Ten nursing teams will be selected, pre-stratified on working area and randomised into an intervention group (‘Stay Active at Home’) or control group (no training). All nurses of the participating teams are eligible to participate in the study. Older adults and, if applicable, their domestic support workers (DSWs) will be allocated to the intervention or control group as well, based on the allocation of the nursing team. Older adults are eligible to participate, if they: 1) receive homecare services by the selected teams; and 2) are 65 years or older. Older adults will be excluded if they: 1) are terminally ill or bedbound; 2) have serious cognitive or psychological problems; or 3) are unable to communicate in Dutch. DSWs are eligible to participate if they provide services to clients who fulfil the eligibility criteria for older adults. The study consists of an effect evaluation (primary outcome: sedentary behaviour in older adults), an economic evaluation and a process evaluation. Data for the effect and economic evaluation will be collected at baseline and 6 and/or 12 months after baseline using performance-based and self-reported measures. In addition, data from client records will be extracted. A mixed-methods design will be applied for the process evaluation, collecting data of older adults and professionals throughout the study period. Discussion: This study will result in evidence about the effectiveness, cost-effectiveness and feasibility of the ‘Stay Active at Home’ programme.
Background Running-related injuries (RRIs) can be considered the primary enemy of runners. Most literature on injury prediction and prevention overlooks the mental aspects of overtraining and under-recovery, despite their potential role in injury prediction and prevention. Consequently, knowledge on the role of mental aspects in RRIs is lacking. Objective To investigate mental aspects of overtraining and under-recovery by means of an online injury prevention programme. Methods and analysis The ‘Take a Mental Break!’ study is a randomised controlled trial with a 12 month follow-up. After completing a web-based baseline survey, half and full marathon runners were randomly assigned to the intervention group or the control group. Participants of the intervention group obtained access to an online injury prevention programme, consisting of a running-related smartphone application. This app provided the participants of the intervention group with information on how to prevent overtraining and RRIs with special attention to mental aspects. The primary outcome measure is any self-reported RRI over the past 12 months. Secondary outcome measures include vigour, fatigue, sleep and perceived running performance. Regression analysis will be conducted to investigate whether the injury prevention programme has led to a lower prevalence of RRIs, better health and improved perceived running performance. Ethics and dissemination The Medical Ethics Committee of the University Medical Center Utrecht, the Netherlands, has exempted the current study from ethical approval (reference number: NL64342.041.17). Results of the study will be communicated through scientific articles in peer-reviewed journals, scientific reports and presentations on scientific conferences.
We use a randomised experiment to study the effect of offering half of 556 freshman students a learning analytics dashboard and a weekly email with a link to their dashboard, on student behaviour in the online environment and final exam performance. The dashboard shows their online progress in the learning management systems, their predicted chance of passing, their predicted grade and their online intermediate performance compared with the total cohort. The email with dashboard access, as well as dashboard use, has positive effects on student behaviour in the online environment, but no effects are found on student performance in the final exam of the programming course. However, we do find differential effects by specialisation and student characteristics.
MULTIFILE
