Over 50% of patients participating in cardiac rehabilitation (CR) experience poor sleep and/or, closely related, psychological stress. Although stress management interventions are generally available, they are typically underutilised in CR, and sleep remains an underaddressed component within CR. This is concerning, as poor sleep and stress not only reinforce each other but are also associated with poorer cardiovascular health and lower quality of life. Therefore, the primary aim of the OPtimising CArdiac REhabilitation by REfining Sleep and STress (RESST) study is to investigate the (cost-)effectiveness of adding a behavioural intervention targeted at improving sleep and managing stress during CR (RESST intervention) on sleep and psychological stress. Furthermore, the study aims to explore the (bidirectional) associations between sleep, stress and lifestyle behaviours.

This parallel-arm multicentre randomised controlled trial will include 200 CR patients across 3 major CR centres in the Netherlands who experience poor sleep and/or stress. Patients will be randomised in a 1:1 ratio to standard CR or standard CR with the RESST intervention. Standard CR is a structured programme combining exercise, lifestyle guidance and risk management. On top of standard CR, the RESST intervention consists of 5 in-person group sessions targeting sleep and stress and is based on Acceptance and Commitment Therapy and Cognitive Behavioural Therapy. Primary outcomes are accelerometer-assessed and self-reported sleep and perceived stress. Secondary outcomes include quality of life, psychosocial well-being, chronic stress biomarkers (hair cortisol and cortisone), momentary fatigue, momentary stress and physical activity. Linear mixed models will be used to assess changes in outcomes at 3-month (after intervention and/or CR completed) and 6-month follow-up. The momentary data collected with ecological momentary assessment and accelerometry will be analysed using multilevel linear mixed models to explore the (bidirectional) relationship between sleep, stress and other lifestyle components such as physical activity.

This study was approved by the ethics committee of Erasmus MC, Erasmus University Medical Centre, Rotterdam, the Netherlands (MEC-2024-0238). The findings will be disseminated through publications in peer-reviewed journals, presentations at academic conferences and professional and patient publications.

NCT06505109.

Systematic literature reviews (SLRs) are essential for synthesising research evidence and guiding informed decision-making. However, SLRs require significant resources and substantial efforts in terms of workload. The introduction of artificial intelligence (AI) tools can reduce this workload. This study aims to investigate the preferences in SLR screening, focusing on trade-offs related to tool attributes.

A discrete choice experiment (DCE) was performed in which participants completed 13 or 14 choice tasks featuring AI tools with varying attributes.

Data were collected via an online survey, where participants provided background on their education and experience.

Professionals who have published SLRs registered on Pubmed, or who were affiliated with a recent Health Economics and Outcomes Research conference were included as participants.

The use of a hypothetical AI tool in SLRs with different attributes was considered by the participants. Key attributes for AI tools were identified through a literature review and expert consultations. These attributes included the AI tool’s role in screening, required user proficiency, sensitivity, workload reduction and the investment needed for training. Primary outcome measures: The participants’ adoption of the AI tool, that is, the likelihood of preferring the AI tool in the choice experiment, considering different configurations of attribute levels, as captured through the DCE choice tasks. Statistical analysis was performed using conditional multinomial logit. An additional analysis was performed by including the demographic characteristics (such as education, experience with SLR publication and familiarity with AI) as interaction variables.

The study received responses from 187 participants with diverse experience in performing SLRs and AI use. The familiarity with AI was generally low, with 55.6% of participants being (very) unfamiliar with AI. In contrast, intermediate proficiency in AI tools is positively associated with adoption (p=0.030). Similarly, workload reduction is also strongly linked to adoption (p

The findings suggest that workload reduction is not the only consideration for SLR reviewers when using AI tools. The key to AI adoption in SLRs is creating reliable, workload-reducing tools that assist rather than replace human reviewers, with moderate proficiency requirements and high sensitivity.